Datasets:

jon-tow

/

starcoderdata-python-edu

like 8

tests/test_preempt_return.py

vpv11110000/pyss

300

<reponame>vpv11110000/pyss<gh_stars>0 # #!/usr/bin/python # -*- coding: utf-8 -*- # test_preempt_return.py # pylint: disable=line-too-long,missing-docstring,bad-whitespace, unused-argument, too-many-locals import sys import os import random import unittest DIRNAME_MODULE = os.path.dirname(os.path.dirname(os.path.dirname(os.path.realpath(sys.argv[0])))) + os.sep sys.path.append(DIRNAME_MODULE) sys.path.append(DIRNAME_MODULE + "pyss" + os.sep) from pyss import pyssobject from pyss.pyss_model import PyssModel from pyss.segment import Segment from pyss.generate import Generate from pyss.terminate import Terminate from pyss import logger from pyss.table import Table from pyss.handle import Handle from pyss.enter import Enter from pyss.leave import Leave from pyss.storage import Storage from pyss.advance import Advance from pyss.preempt import Preempt from pyss.g_return import GReturn from pyss.facility import Facility from pyss.seize import Seize from pyss.release import Release from pyss.transfer import Transfer from pyss.test import Test from pyss.pyss_const import * class TestPreemptReturn(unittest.TestCase): def setUp(self): pass def tearDown(self): pass # @unittest.skip("testing skipping test_preempt_return_001") def test_preempt_return_001(self): """Тест Preempt - Return Формируется один транзакт в момент времени 1. Прерывает работу устройства F_1 на 5 единиц времени. Выходит из модели в момент времени 6. """ logger.info("--- test_preempt_return_001 ----------------------------------") ### MODEL ---------------------------------- m = PyssModel() sgm = Segment(m) # m[OPTIONS].setAllFalse() MAX_TIME = 20 # list_all_transact = [] # MAX_TIME = 20 # F_1 = "F_1" # ОКУ Facility(m, facilityName=F_1) # def funcTransactTo_list_all_transact(owner, transact): # складируем транзакты в список list_all_transact.append(transact) ### SEGMENT ---------------------------- # формируется одна заявка в момент времени 1 Generate(sgm, med_value=None, modificatorFunc=None, first_tx=1, max_amount=1) Handle(sgm, handlerFunc=funcTransactTo_list_all_transact) # test Handle(sgm, handlerFunc=lambda o, t:self.assertNotIn(F_1, t[FACILITY])) # Preempt(sgm, facilityName=F_1) # test Handle(sgm, handlerFunc=lambda o, t:self.assertIn(F_1, t[FACILITY])) # Advance(sgm, meanTime=5, modificatorFunc=None) GReturn(sgm, facilityName=F_1) # test Handle(sgm, handlerFunc=lambda o, t:not self.assertNotIn(F_1, t[FACILITY])) # Terminate(sgm, deltaTerminate=0) # ЗАПУСК ---------------------- m.start(terminationCount=MAX_TIME, maxTime=MAX_TIME) # ТЕСТЫ ---------------------- for t in list_all_transact: self.assertEqual(t[TIME_CREATED], 1) self.assertEqual(t[TERMINATED_TIME], 6) print str(["%s:%s" % (k, t[k]) for k in t.keys() if k in [TIME_CREATED, TERMINATED_TIME]]) # @unittest.skip("testing skipping test_preempt_return_002") def test_preempt_return_002(self): """Тест Preempt - Return Формируется транзакт A в момент времени 1. Идёт на обработку устройством F_1 в течение 3 единиц времени. Формируется транзакт B в момент времени 2. Прерывает работу устройства на 5 единиц времени. Транзакт B выходит из модели в момент времени 7. Транзакт А выходит из модели в момент времени 9. Обработка транзакта А была прервана с 2 по 7. """ logger.info("--- test_preempt_return_002 ----------------------------------") ### MODEL ---------------------------------- m = PyssModel() sgm = Segment(m) # m[OPTIONS].setAllFalse() MAX_TIME = 20 # CONSTS TRANSACT_A = "A" TRANSACT_B = "B" # list_all_transact = [] tA = [] tB = [] # F_1 = "F_1" # ОКУ facility_1 = Facility(m, facilityName=F_1) # def funcTransactTo_list_all_transact(owner, transact): # складируем транзакты в список list_all_transact.append(transact) def setTransactLabel(owner, transact): if transact[NUM] == 1: transact[LABEL] = TRANSACT_A tA.append(transact) elif transact[NUM] == 2: transact[LABEL] = TRANSACT_B tB.append(transact) # функция проверки условия def checkTest(o): t=m.getCurrentTransact() if t[LABEL] == TRANSACT_B: return False return True def printAllTransact(owner, transact): print "Time=%s" % str(m.getCurTime()) print "\n".join([str(t) for t in list_all_transact]) print "tA=%s" % str(tA[0]) print "tB=%s" % str(tB[0]) ### SEGMENT ---------------------------- # формируется одна заявка в момент времени 1 Generate(sgm, med_value=1, modificatorFunc=None, first_tx=1, max_amount=2) # вспомогательные операции Handle(sgm, handlerFunc=funcTransactTo_list_all_transact) Handle(sgm, handlerFunc=setTransactLabel) # test Handle(sgm, handlerFunc=lambda o, t:self.assertNotIn(F_1, t[FACILITY])) # # первый транзакт проходит, второй направляется к метке "to_preempt" Test(sgm, funcCondition=checkTest, move2block="to_preempt") # только первый транзакт Seize(sgm, facilityName=F_1) # test Handle(sgm, handlerFunc=lambda o, t:self.assertIn(F_1, t[FACILITY])) # Advance(sgm, meanTime=3, modificatorFunc=None) Release(sgm, facilityName=F_1) # test Handle(sgm, handlerFunc=lambda o, t:self.assertNotIn(F_1, t[FACILITY])) # Transfer(sgm, funcTransfer=lambda o, t: o.findBlockByLabel("to_term")) #--- # только второй транзакт Preempt(sgm, facilityName=F_1, label="to_preempt") # test # .addBlock(handle.Handle(handlerFunc=lambda o,t:self.assertEqual(tA[0][REMAIND_TIME], None))) Handle(sgm, handlerFunc=printAllTransact) Handle(sgm, handlerFunc=lambda o, t:self.assertIn(F_1, t[FACILITY])) # Handle(sgm, handlerFunc=printAllTransact) Advance(sgm, meanTime=5, modificatorFunc=None) GReturn(sgm, facilityName=F_1) # test Handle(sgm, handlerFunc=lambda o, t:self.assertEqual(tA[0][REMAIND_TIME], 2)) Handle(sgm, handlerFunc=lambda o, t:self.assertEqual(tA[0][SCHEDULED_TIME], 9)) Handle(sgm, handlerFunc=lambda o, t:self.assertNotIn(F_1, t[FACILITY])) # Handle(sgm, handlerFunc=printAllTransact) # все транзакты Terminate(sgm, label="to_term", deltaTerminate=0) # ЗАПУСК ---------------------- m.start(terminationCount=MAX_TIME, maxTime=MAX_TIME) # ТЕСТЫ ---------------------- for t in list_all_transact: # Формируется транзакт A в момент времени 1. # Идёт на обработку устройством F_1 в течение 3 единиц времени. # Формируется транзакт B в момент времени 2. # Прерывает работу устройства на 5 единиц времени. # Транзакт B выходит из модели в момент времени 7. # Транзакт А выходит из модели в момент времени 9. # Обработка транзакта А была прервана с 2 по 7. print str(["%s:%s" % (k, t[k]) for k in t.keys() if k in [TIME_CREATED, TERMINATED_TIME, LIFE_TIME_LIST]]) if t[LABEL] == TRANSACT_A: self.assertEqual(t[TIME_CREATED], 1) self.assertEqual(t[REMAIND_TIME], 2) self.assertEqual(t[TERMINATED_TIME], 9) self.assertListEqual(t[LIFE_TIME_LIST], [ {'start': 1, 'state': 'actived'}, {'start': 2, 'state': 'preempted'}, {'start': 7, 'state': 'actived'}, {'start': 9, 'state': 'deleted'}]) elif t[LABEL] == TRANSACT_B: self.assertEqual(t[TIME_CREATED], 2) self.assertEqual(t[TERMINATED_TIME], 7) self.assertListEqual(t[LIFE_TIME_LIST], [ {'start': 2, 'state': 'actived'}, {'start': 7, 'state': 'deleted'}]) if __name__ == '__main__': unittest.main(module="test_preempt_return")

python/ray/rllib/ddpg2/ddpg_evaluator.py

songqing/ray

301

from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import ray from ray.rllib.ddpg2.models import DDPGModel from ray.rllib.models.catalog import ModelCatalog from ray.rllib.optimizers import PolicyEvaluator from ray.rllib.utils.filter import NoFilter from ray.rllib.utils.process_rollout import process_rollout from ray.rllib.utils.sampler import SyncSampler class DDPGEvaluator(PolicyEvaluator): def __init__(self, registry, env_creator, config): self.env = ModelCatalog.get_preprocessor_as_wrapper( registry, env_creator(config["env_config"])) # contains model, target_model self.model = DDPGModel(registry, self.env, config) self.sampler = SyncSampler( self.env, self.model.model, NoFilter(), config["num_local_steps"], horizon=config["horizon"]) def sample(self): """Returns a batch of samples.""" rollout = self.sampler.get_data() rollout.data["weights"] = np.ones_like(rollout.data["rewards"]) # since each sample is one step, no discounting needs to be applied; # this does not involve config["gamma"] samples = process_rollout( rollout, NoFilter(), gamma=1.0, use_gae=False) return samples def update_target(self): """Updates target critic and target actor.""" self.model.update_target() def compute_gradients(self, samples): """Returns critic, actor gradients.""" return self.model.compute_gradients(samples) def apply_gradients(self, grads): """Applies gradients to evaluator weights.""" self.model.apply_gradients(grads) def compute_apply(self, samples): grads, _ = self.compute_gradients(samples) self.apply_gradients(grads) def get_weights(self): """Returns model weights.""" return self.model.get_weights() def set_weights(self, weights): """Sets model weights.""" self.model.set_weights(weights) def get_completed_rollout_metrics(self): """Returns metrics on previously completed rollouts. Calling this clears the queue of completed rollout metrics. """ return self.sampler.get_metrics() RemoteDDPGEvaluator = ray.remote(DDPGEvaluator)

python/sysmap/graph.py

harryherold/sysmap

302

<reponame>harryherold/sysmap from graphviz import Digraph from collections import namedtuple class NetworkGraph: ''' Representation of the network connections. This class contains the entities in the network e.g. hosts or switches. And the connections between them. ''' Vertex = namedtuple('Vertexes', ['hosts', 'switches']) _edges = [] def _sanitize_edge_connection(self, edge): ''' Update '_to' and '_form' field of a edge. :param edge: One edge connection. :type edge: dict :returns: Updated edge with _to and _from key. :rtype: dict ''' if edge['to_guid'].startswith('S'): to_collection = 'switches/' elif edge['to_guid'].startswith('H'): to_collection = 'hosts/' if edge['from_guid'].startswith('S'): from_collection = 'switches/' elif edge['from_guid'].startswith('H'): from_collection = 'hosts/' edge.update({ '_to': to_collection + edge['to_guid'], '_from': from_collection + edge['from_guid'] }) return edge def _sanitize_vertexes(self, vertex): ''' Update '_key' field of vertex to appropriate guid. :param vertex: Vertex :type vertex: dict :returns: An updated dict, '_key' field with 'guid' value. :rtype: dict ''' vertex.update({'_key': vertex['guid']}) return vertex def __init__(self, hsts=None, switches=None, connections=None): self._vertexes = self.Vertex(hosts=[self._sanitize_vertexes(h) for h in hsts], switches=[self._sanitize_vertexes(s) for s in switches]) self._edges = [self._sanitize_edge_connection(c) for c in connections] @property def vertexes(self): ''' Returns a concatenated list of all vertexes. :returns: List of vertexes, contains of hosts and switches. :rtype: List[dict] ''' return self._vertexes.hosts + self._vertexes.switches @property def switches(self): ''' Returns a list of all 'switch' vertexes. :returns: List of all switches. :rtype: List[dict] ''' return self._vertexes.switches @property def hosts(self): ''' Returns a list of all 'host' vertexes. :returns: List of all hosts. :rtype: List[dict] ''' return self._vertexes.hosts @property def edges(self): ''' Return a list of all 'connection' edges. :returns: List of all connections. :rtype: List[dict] ''' return self._edges def to_graph(self, graphargs): ''' Draw a dot graph of the network graph. :params graphargs: Arguments to graphviz.Digraph. :type graphargs: dict ''' graph = Digraph(**graphargs) for v in self._vertexes: graph.node(v['guid'], v['description']) for c in self._edges: graph.edge(c['from_guid'], c['to_guid']) graph.render()

png/imageRecognition_Simple.py

tanthanadon/senior

303

from math import sqrt from skimage import data from skimage.feature import blob_dog, blob_log, blob_doh from skimage.color import rgb2gray from skimage import io import matplotlib.pyplot as plt image = io.imread("star.jpg") image_gray = rgb2gray(image) blobs_log = blob_log(image_gray, max_sigma=30, num_sigma=10, threshold=.1) # Compute radii in the 3rd column. blobs_log[:, 2] = blobs_log[:, 2] * sqrt(2) blobs_dog = blob_dog(image_gray, max_sigma=30, threshold=.1) blobs_dog[:, 2] = blobs_dog[:, 2] * sqrt(2) blobs_doh = blob_doh(image_gray, max_sigma=30, threshold=.01) blobs_list = [blobs_log, blobs_dog, blobs_doh] colors = ['yellow', 'lime', 'red'] titles = ['Laplacian of Gaussian', 'Difference of Gaussian', 'Determinant of Hessian'] sequence = zip(blobs_list, colors, titles) fig, axes = plt.subplots(1, 3, figsize=(9, 3), sharex=True, sharey=True) ax = axes.ravel() for idx, (blobs, color, title) in enumerate(sequence): ax[idx].set_title(title) ax[idx].imshow(image) for blob in blobs: y, x, r = blob c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False) ax[idx].add_patch(c) ax[idx].set_axis_off() plt.tight_layout() plt.show()

indexof.py

gnuchev/homework

304

def indexof(listofnames, value): if value in listofnames: value_index = listofnames.index(value) return(listofnames, value_index) else: return(-1)

Day22_Pong/ball.py

syt1209/PythonProjects

305

from turtle import Turtle SPEED = 10 class Ball(Turtle): def __init__(self): super().__init__() self.penup() self.color("white") self.shape("circle") self.move_speed = 0.1 self.y_bounce = 1 self.x_bounce = 1 def move(self): new_x = self.xcor() + SPEED*self.x_bounce new_y = self.ycor() + SPEED*self.y_bounce self.goto(new_x, new_y) def reset(self): self.goto(0, 0) self.move_speed = 0.1 self.x_bounce *= -1

programs/combine/jry2/treedef.py

lsrcz/SyGuS

306

from jry2.semantics import Expr class TreeNode: pass class TreeLeaf(TreeNode): def __init__(self, term): self.term = term def getExpr(self): return self.term class TreeInnerNode(TreeNode): def __init__(self, pred, left, right): self.pred = pred self.left = left self.right = right def getExpr(self): return Expr('ite', self.pred, self.left.getExpr(), self.right.getExpr())

src/sage/modular/dirichlet.py

hsm207/sage

307

# -*- coding: utf-8 -*- r""" Dirichlet characters A :class:`DirichletCharacter` is the extension of a homomorphism .. MATH:: (\ZZ/N\ZZ)^* \to R^*, for some ring `R`, to the map `\ZZ/N\ZZ \to R` obtained by sending those `x\in\ZZ/N\ZZ` with `\gcd(N,x)>1` to `0`. EXAMPLES:: sage: G = DirichletGroup(35) sage: x = G.gens() sage: e = x[0]*x[1]^2; e Dirichlet character modulo 35 of conductor 35 mapping 22 |--> zeta12^3, 31 |--> zeta12^2 - 1 sage: e.order() 12 This illustrates a canonical coercion:: sage: e = DirichletGroup(5, QQ).0 sage: f = DirichletGroup(5,CyclotomicField(4)).0 sage: e*f Dirichlet character modulo 5 of conductor 5 mapping 2 |--> -zeta4 AUTHORS: - <NAME> (2005-09-02): Fixed bug in comparison of Dirichlet characters. It was checking that their values were the same, but not checking that they had the same level! - <NAME> (2006-01-07): added more examples - <NAME> (2006-05-21): added examples of everything; fix a *lot* of tiny bugs and design problem that became clear when creating examples. - <NAME> (2008-02-16): speed up __call__ method for Dirichlet characters, miscellaneous fixes - <NAME> (2014-03-06): use UniqueFactory to cache DirichletGroups """ # **************************************************************************** # Copyright (C) 2004-2006 <NAME> <<EMAIL>> # Copyright (C) 2014 <NAME> <<EMAIL>> # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 2 of the License, or # (at your option) any later version. # https://www.gnu.org/licenses/ # **************************************************************************** from __future__ import print_function import sage.categories.all as cat from sage.misc.all import prod import sage.misc.prandom as random import sage.modules.free_module as free_module import sage.modules.free_module_element as free_module_element import sage.rings.all as rings import sage.rings.number_field.number_field as number_field from sage.libs.pari import pari from sage.categories.map import Map from sage.rings.rational_field import is_RationalField from sage.rings.complex_mpfr import is_ComplexField from sage.rings.qqbar import is_AlgebraicField from sage.rings.ring import is_Ring from sage.misc.functional import round from sage.misc.cachefunc import cached_method from sage.misc.fast_methods import WithEqualityById from sage.structure.element import MultiplicativeGroupElement from sage.structure.gens_py import multiplicative_iterator from sage.structure.parent import Parent from sage.structure.sequence import Sequence from sage.structure.factory import UniqueFactory from sage.structure.richcmp import richcmp from sage.arith.all import (binomial, bernoulli, kronecker, factor, gcd, lcm, fundamental_discriminant, euler_phi, factorial, valuation) def trivial_character(N, base_ring=rings.RationalField()): r""" Return the trivial character of the given modulus, with values in the given base ring. EXAMPLES:: sage: t = trivial_character(7) sage: [t(x) for x in [0..20]] [0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1] sage: t(1).parent() Rational Field sage: trivial_character(7, Integers(3))(1).parent() Ring of integers modulo 3 """ return DirichletGroup(N, base_ring)(1) TrivialCharacter = trivial_character def kronecker_character(d): """ Return the quadratic Dirichlet character (d/.) of minimal conductor. EXAMPLES:: sage: kronecker_character(97*389*997^2) Dirichlet character modulo 37733 of conductor 37733 mapping 1557 |--> -1, 37346 |--> -1 :: sage: a = kronecker_character(1) sage: b = DirichletGroup(2401,QQ)(a) # NOTE -- over QQ! sage: b.modulus() 2401 AUTHORS: - <NAME> (2006-08-06) """ d = rings.Integer(d) if d == 0: raise ValueError("d must be nonzero") D = fundamental_discriminant(d) G = DirichletGroup(abs(D), rings.RationalField()) return G([kronecker(D,u) for u in G.unit_gens()]) def kronecker_character_upside_down(d): """ Return the quadratic Dirichlet character (./d) of conductor d, for d0. EXAMPLES:: sage: kronecker_character_upside_down(97*389*997^2) Dirichlet character modulo 37506941597 of conductor 37733 mapping 13533432536 |--> -1, 22369178537 |--> -1, 14266017175 |--> 1 AUTHORS: - <NAME> (2006-08-06) """ d = rings.Integer(d) if d <= 0: raise ValueError("d must be positive") G = DirichletGroup(d, rings.RationalField()) return G([kronecker(u.lift(),d) for u in G.unit_gens()]) def is_DirichletCharacter(x): r""" Return True if x is of type DirichletCharacter. EXAMPLES:: sage: from sage.modular.dirichlet import is_DirichletCharacter sage: is_DirichletCharacter(trivial_character(3)) True sage: is_DirichletCharacter([1]) False """ return isinstance(x, DirichletCharacter) class DirichletCharacter(MultiplicativeGroupElement): """ A Dirichlet character. """ def __init__(self, parent, x, check=True): r""" Create a Dirichlet character with specified values on generators of `(\ZZ/n\ZZ)^*`. INPUT: - ``parent`` -- :class:`DirichletGroup`, a group of Dirichlet characters - ``x`` -- one of the following: - tuple or list of ring elements: the values of the Dirichlet character on the standard generators of `(\ZZ/N\ZZ)^*` as returned by :meth:`sage.rings.finite_rings.integer_mod_ring.IntegerModRing_generic.unit_gens`. - vector over `\ZZ/e\ZZ`, where `e` is the order of the standard root of unity for ``parent``. In both cases, the orders of the elements must divide the orders of the respective generators of `(\ZZ/N\ZZ)^*`. OUTPUT: The Dirichlet character defined by `x` (type :class:`DirichletCharacter`). EXAMPLES:: sage: G.<e> = DirichletGroup(13) sage: G Group of Dirichlet characters modulo 13 with values in Cyclotomic Field of order 12 and degree 4 sage: e Dirichlet character modulo 13 of conductor 13 mapping 2 |--> zeta12 sage: loads(e.dumps()) == e True :: sage: G, x = DirichletGroup(35).objgens() sage: e = x[0]*x[1]; e Dirichlet character modulo 35 of conductor 35 mapping 22 |--> zeta12^3, 31 |--> zeta12^2 sage: e.order() 12 sage: loads(e.dumps()) == e True TESTS:: sage: G = DirichletGroup(10) sage: TestSuite(G[1]).run() It is checked that the orders of the elements in `x` are admissible (see :trac:`17283`):: sage: k.<i> = CyclotomicField(4) sage: G = DirichletGroup(192) sage: G([i, -1, -1]) Traceback (most recent call last): ... ValueError: values (= (zeta16^4, -1, -1)) must have multiplicative orders dividing (2, 16, 2), respectively sage: from sage.modular.dirichlet import DirichletCharacter sage: M = FreeModule(Zmod(16), 3) sage: DirichletCharacter(G, M([4, 8, 8])) Traceback (most recent call last): ... ValueError: values (= (4, 8, 8) modulo 16) must have additive orders dividing (2, 16, 2), respectively """ MultiplicativeGroupElement.__init__(self, parent) if check: orders = parent.integers_mod().unit_group().gens_orders() if len(x) != len(orders): raise ValueError("wrong number of values (= {}) on generators (want {})".format(x, len(orders))) if free_module_element.is_FreeModuleElement(x): x = parent._module(x) if any(u * v for u, v in zip(x, orders)): raise ValueError("values (= {} modulo {}) must have additive orders dividing {}, respectively" .format(x, parent.zeta_order(), orders)) self.element.set_cache(x) else: R = parent.base_ring() x = tuple(map(R, x)) if R.is_exact() and any(u**v != 1 for u, v in zip(x, orders)): raise ValueError("values (= {}) must have multiplicative orders dividing {}, respectively" .format(x, orders)) self.values_on_gens.set_cache(x) else: if free_module_element.is_FreeModuleElement(x): self.element.set_cache(x) else: self.values_on_gens.set_cache(x) @cached_method def __eval_at_minus_one(self): r""" Efficiently evaluate the character at -1 using knowledge of its order. This is potentially much more efficient than computing the value of -1 directly using dlog and a large power of the image root of unity. We use the following. Proposition: Suppose eps is a character mod `p^n`, where `p` is a prime. Then `\varepsilon(-1) = -1` if and only if `p = 2` and the factor of eps at 4 is nontrivial or `p > 2` and 2 does not divide `\phi(p^n)/\mbox{\rm ord}(\varepsilon)`. EXAMPLES:: sage: chi = DirichletGroup(20).0; chi._DirichletCharacter__eval_at_minus_one() -1 """ D = self.decomposition() val = self.base_ring()(1) for e in D: if e.modulus() % 2 == 0: if e.modulus() % 4 == 0: val *= e.values_on_gens()[0] # first gen is -1 for 2-power modulus elif (euler_phi(e.parent().modulus()) / e.order()) % 2: val *= -1 return val def __call__(self, m): """ Return the value of this character at the integer `m`. .. warning:: A table of values of the character is made the first time you call this (unless `m` equals -1) EXAMPLES:: sage: G = DirichletGroup(60) sage: e = prod(G.gens(), G(1)) sage: e Dirichlet character modulo 60 of conductor 60 mapping 31 |--> -1, 41 |--> -1, 37 |--> zeta4 sage: e(-1) -1 sage: e(2) 0 sage: e(7) -zeta4 sage: Integers(60).unit_gens() (31, 41, 37) sage: e(31) -1 sage: e(41) -1 sage: e(37) zeta4 sage: e(31*37) -zeta4 sage: parent(e(31*37)) Cyclotomic Field of order 4 and degree 2 """ N = self.modulus() m = m % N if self.values.is_in_cache() or m != N - 1: return self.values()[m] else: return self.__eval_at_minus_one() def change_ring(self, R): """ Return the base extension of ``self`` to ``R``. INPUT: - ``R`` -- either a ring admitting a conversion map from the base ring of ``self``, or a ring homomorphism with the base ring of ``self`` as its domain EXAMPLES:: sage: e = DirichletGroup(7, QQ).0 sage: f = e.change_ring(QuadraticField(3, 'a')) sage: f.parent() Group of Dirichlet characters modulo 7 with values in Number Field in a with defining polynomial x^2 - 3 with a = 1.732050807568878? :: sage: e = DirichletGroup(13).0 sage: e.change_ring(QQ) Traceback (most recent call last): ... TypeError: Unable to coerce zeta12 to a rational We test the case where `R` is a map (:trac:`18072`):: sage: K.<i> = QuadraticField(-1) sage: chi = DirichletGroup(5, K)[1] sage: chi(2) i sage: f = K.complex_embeddings()[0] sage: psi = chi.change_ring(f) sage: psi(2) -1.83697019872103e-16 - 1.00000000000000*I """ if self.base_ring() is R: return self G = self.parent().change_ring(R) return G.element_class(G, [R(x) for x in self.values_on_gens()]) def _richcmp_(self, other, op): """ Compare ``self`` to ``other``. .. NOTE:: Since there is no coercion between Dirichlet groups of different moduli, characters of different moduli compare as unequal, even if they define identical functions on ``ZZ``. EXAMPLES:: sage: e = DirichletGroup(16)([-1, 1]) sage: f = e.restrict(8) sage: e == e True sage: f == f True sage: e == f False sage: k = DirichletGroup(7)([-1]) sage: k == e False """ return richcmp(self.values_on_gens(), other.values_on_gens(), op) def __hash__(self): """ Return the hash of ``self``. EXAMPLES:: sage: e = DirichletGroup(16)([-1, 1]) sage: hash(e) == hash((-1,1)) True """ return hash(self.values_on_gens()) def __invert__(self): """ Return the multiplicative inverse of self. EXAMPLES:: sage: e = DirichletGroup(13).0 sage: f = ~e sage: f*e Dirichlet character modulo 13 of conductor 1 mapping 2 |--> 1 """ G = self.parent() if G.zeta.is_in_cache(): x = -self.element() else: x = tuple(~z for z in self.values_on_gens()) return G.element_class(G, x, check=False) def _mul_(self, other): """ Return the product of self and other. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: a Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1 sage: b Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> zeta4 sage: a*b # indirect doctest Dirichlet character modulo 20 of conductor 20 mapping 11 |--> -1, 17 |--> zeta4 Multiplying elements whose parents have different zeta orders works:: sage: a = DirichletGroup(3, QQ, zeta=1, zeta_order=1)(1) sage: b = DirichletGroup(3, QQ, zeta=-1, zeta_order=2)([-1]) sage: a * b # indirect doctest Dirichlet character modulo 3 of conductor 3 mapping 2 |--> -1 """ G = self.parent() if G.zeta.is_in_cache(): x = self.element() + other.element() else: x = tuple(y * z for y, z in zip(self.values_on_gens(), other.values_on_gens())) return G.element_class(G, x, check=False) def __copy__(self): """ Return a (shallow) copy of this Dirichlet character. EXAMPLES:: sage: G.<a> = DirichletGroup(11) sage: b = copy(a) sage: a is b False sage: a.element() is b.element() False sage: a.values_on_gens() is b.values_on_gens() True """ # This method exists solely because of a bug in the cPickle module -- # see modsym/manin_symbols.py. G = self.parent() return G.element_class(G, self.values_on_gens(), check=False) def __pow__(self, n): """ Return self raised to the power of n EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: a^2 Dirichlet character modulo 20 of conductor 1 mapping 11 |--> 1, 17 |--> 1 sage: b^2 Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> -1 """ G = self.parent() if G.zeta.is_in_cache(): x = n * self.element() else: x = tuple(z**n for z in self.values_on_gens()) return G.element_class(G, x, check=False) def _repr_short_(self): r""" A short string representation of self, often used in string representations of modular forms EXAMPLES:: sage: chi = DirichletGroup(24).0 sage: chi._repr_short_() '[-1, 1, 1]' """ return str(list(self.values_on_gens())) def _repr_(self): """ String representation of self. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: repr(a) # indirect doctest 'Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1' TESTS: Dirichlet characters modulo 1 and 2 are printed correctly (see :trac:`17338`):: sage: DirichletGroup(1)[0] Dirichlet character modulo 1 of conductor 1 sage: DirichletGroup(2)[0] Dirichlet character modulo 2 of conductor 1 """ s = 'Dirichlet character modulo %s of conductor %s' % (self.modulus(), self.conductor()) r = len(self.values_on_gens()) if r != 0: s += ' mapping ' for i in range(r): if i != 0: s += ', ' s += str(self.parent().unit_gens()[i]) + ' |--> ' + str(self.values_on_gens()[i]) return s def _latex_(self): r""" LaTeX representation of self. EXAMPLES:: sage: G.<a,b> = DirichletGroup(16) sage: latex(b) # indirect doctest \hbox{Dirichlet character modulo } 16 \hbox{ of conductor } 16 \hbox{ mapping } 15 \mapsto 1,\ 5 \mapsto \zeta_{4} TESTS: Dirichlet characters modulo 1 and 2 are printed correctly (see :trac:`17338`):: sage: latex(DirichletGroup(1)[0]) \hbox{Dirichlet character modulo } 1 \hbox{ of conductor } 1 sage: latex(DirichletGroup(2)[0]) \hbox{Dirichlet character modulo } 2 \hbox{ of conductor } 1 """ s = r'\hbox{Dirichlet character modulo } %s \hbox{ of conductor } %s' % (self.modulus(), self.conductor()) r = len(self.values_on_gens()) if r != 0: s += r' \hbox{ mapping } ' for i in range(r): if i != 0: s += r',\ ' s += self.parent().unit_gens()[i]._latex_() + r' \mapsto ' + self.values_on_gens()[i]._latex_() return s def base_ring(self): """ Returns the base ring of this Dirichlet character. EXAMPLES:: sage: G = DirichletGroup(11) sage: G.gen(0).base_ring() Cyclotomic Field of order 10 and degree 4 sage: G = DirichletGroup(11, RationalField()) sage: G.gen(0).base_ring() Rational Field """ return self.parent().base_ring() def bar(self): """ Return the complex conjugate of this Dirichlet character. EXAMPLES:: sage: e = DirichletGroup(5).0 sage: e Dirichlet character modulo 5 of conductor 5 mapping 2 |--> zeta4 sage: e.bar() Dirichlet character modulo 5 of conductor 5 mapping 2 |--> -zeta4 """ return ~self def bernoulli(self, k, algorithm='recurrence', cache=True, **opts): r""" Returns the generalized Bernoulli number `B_{k,eps}`. INPUT: - ``k`` -- a non-negative integer - ``algorithm`` -- either ``'recurrence'`` (default) or ``'definition'`` - ``cache`` -- if True, cache answers - ``**opts`` -- optional arguments; not used directly, but passed to the :func:`bernoulli` function if this is called OUTPUT: Let `\varepsilon` be a (not necessarily primitive) character of modulus `N`. This function returns the generalized Bernoulli number `B_{k,\varepsilon}`, as defined by the following identity of power series (see for example [DI1995]_, Section 2.2): .. MATH:: \sum_{a=1}^N \frac{\varepsilon(a) t e^{at}}{e^{Nt}-1} = sum_{k=0}^{\infty} \frac{B_{k,\varepsilon}}{k!} t^k. ALGORITHM: The ``'recurrence'`` algorithm computes generalized Bernoulli numbers via classical Bernoulli numbers using the formula in [Coh2007]_, Proposition 9.4.5; this is usually optimal. The ``definition`` algorithm uses the definition directly. .. WARNING:: In the case of the trivial Dirichlet character modulo 1, this function returns `B_{1,\varepsilon} = 1/2`, in accordance with the above definition, but in contrast to the value `B_1 = -1/2` for the classical Bernoulli number. Some authors use an alternative definition giving `B_{1,\varepsilon} = -1/2`; see the discussion in [Coh2007]_, Section 9.4.1. EXAMPLES:: sage: G = DirichletGroup(13) sage: e = G.0 sage: e.bernoulli(5) 7430/13*zeta12^3 - 34750/13*zeta12^2 - 11380/13*zeta12 + 9110/13 sage: eps = DirichletGroup(9).0 sage: eps.bernoulli(3) 10*zeta6 + 4 sage: eps.bernoulli(3, algorithm="definition") 10*zeta6 + 4 TESTS: Check that :trac:`17586` is fixed:: sage: DirichletGroup(1)[0].bernoulli(1) 1/2 """ if cache: try: self.__bernoulli except AttributeError: self.__bernoulli = {} if k in self.__bernoulli: return self.__bernoulli[k] N = self.modulus() K = self.base_ring() if N == 1: # By definition, the first Bernoulli number of the trivial # character is 1/2, in contrast to the value B_1 = -1/2. ber = K.one()/2 if k == 1 else K(bernoulli(k)) elif self(-1) != K((-1)**k): ber = K.zero() elif algorithm == "recurrence": # The following code is pretty fast, at least compared to # the other algorithm below. That said, I'm sure it could # be sped up by a factor of 10 or more in many cases, # especially since we end up computing all the Bernoulli # numbers up to k, which should be done with power series # instead of calls to the Bernoulli function. Likewise # computing all binomial coefficients can be done much # more efficiently. v = self.values() S = lambda n: sum(v[r] * r**n for r in range(1, N)) ber = K(sum(binomial(k,j) * bernoulli(j, **opts) * N**(j-1) * S(k-j) for j in range(k+1))) elif algorithm == "definition": # This is better since it computes the same thing, but requires # no arith in a poly ring over a number field. prec = k+2 R = rings.PowerSeriesRing(rings.QQ, 't') t = R.gen() # g(t) = t/(e^{Nt}-1) g = t/((N*t).exp(prec) - 1) # h(n) = g(t)*e^{nt} h = [0] + [g * ((n*t).exp(prec)) for n in range(1,N+1)] ber = sum([self(a)*h[a][k] for a in range(1,N+1)]) * factorial(k) else: raise ValueError("algorithm = '%s' unknown"%algorithm) if cache: self.__bernoulli[k] = ber return ber def lfunction(self, prec=53, algorithm='pari'): """ Return the L-function of ``self``. The result is a wrapper around a PARI L-function or around the ``lcalc`` program. INPUT: - ``prec`` -- precision (default 53) - ``algorithm`` -- 'pari' (default) or 'lcalc' EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: L = a.lfunction(); L PARI L-function associated to Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1 sage: L(4) 0.988944551741105 With the algorithm "lcalc":: sage: a = a.primitive_character() sage: L = a.lfunction(algorithm='lcalc'); L L-function with complex Dirichlet coefficients sage: L.value(4) # abs tol 1e-14 0.988944551741105 - 5.16608739123418e-18*I """ if algorithm is None: algorithm = 'pari' if algorithm == 'pari': from sage.lfunctions.pari import lfun_character, LFunction Z = LFunction(lfun_character(self), prec=prec) Z.rename('PARI L-function associated to %s' % self) return Z elif algorithm == 'lcalc': from sage.libs.lcalc.lcalc_Lfunction import Lfunction_from_character return Lfunction_from_character(self) raise ValueError('algorithm must be "pari" or "lcalc"') @cached_method def conductor(self): """ Computes and returns the conductor of this character. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: a.conductor() 4 sage: b.conductor() 5 sage: (a*b).conductor() 20 TESTS:: sage: G.<a, b> = DirichletGroup(20) sage: type(G(1).conductor()) <type 'sage.rings.integer.Integer'> """ if self.modulus() == 1 or self.is_trivial(): return rings.Integer(1) F = factor(self.modulus()) if len(F) > 1: return prod([d.conductor() for d in self.decomposition()]) p = F[0][0] # When p is odd, and x =/= 1, the conductor is the smallest p**r such that # Order(x) divides EulerPhi(p**r) = p**(r-1)*(p-1). # For a given r, whether or not the above divisibility holds # depends only on the factor of p**(r-1) on the right hand side. # Since p-1 is coprime to p, this smallest r such that the # divisibility holds equals Valuation(Order(x),p)+1. cond = p**(valuation(self.order(),p) + 1) if p == 2 and F[0][1] > 2 and self.values_on_gens()[1].multiplicative_order() != 1: cond *= 2 return rings.Integer(cond) @cached_method def decomposition(self): r""" Return the decomposition of self as a product of Dirichlet characters of prime power modulus, where the prime powers exactly divide the modulus of this character. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: c = a*b sage: d = c.decomposition(); d [Dirichlet character modulo 4 of conductor 4 mapping 3 |--> -1, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> zeta4] sage: d[0].parent() Group of Dirichlet characters modulo 4 with values in Cyclotomic Field of order 4 and degree 2 sage: d[1].parent() Group of Dirichlet characters modulo 5 with values in Cyclotomic Field of order 4 and degree 2 We can't multiply directly, since coercion of one element into the other parent fails in both cases:: sage: d[0]*d[1] == c Traceback (most recent call last): ... TypeError: unsupported operand parent(s) for *: 'Group of Dirichlet characters modulo 4 with values in Cyclotomic Field of order 4 and degree 2' and 'Group of Dirichlet characters modulo 5 with values in Cyclotomic Field of order 4 and degree 2' We can multiply if we're explicit about where we want the multiplication to take place. :: sage: G(d[0])*G(d[1]) == c True Conductors that are divisible by various powers of 2 present some problems as the multiplicative group modulo `2^k` is trivial for `k = 1` and non-cyclic for `k \ge 3`:: sage: (DirichletGroup(18).0).decomposition() [Dirichlet character modulo 2 of conductor 1, Dirichlet character modulo 9 of conductor 9 mapping 2 |--> zeta6] sage: (DirichletGroup(36).0).decomposition() [Dirichlet character modulo 4 of conductor 4 mapping 3 |--> -1, Dirichlet character modulo 9 of conductor 1 mapping 2 |--> 1] sage: (DirichletGroup(72).0).decomposition() [Dirichlet character modulo 8 of conductor 4 mapping 7 |--> -1, 5 |--> 1, Dirichlet character modulo 9 of conductor 1 mapping 2 |--> 1] """ D = self.parent().decomposition() vals = [[z] for z in self.values_on_gens()] if self.modulus() % 8 == 0: # 2 factors at 2. vals[0].append(vals[1][0]) del vals[1] elif self.modulus() % 4 == 2: # 0 factors at 2. vals = [1] + vals return [D[i](vals[i]) for i in range(len(D))] def extend(self, M): """ Returns the extension of this character to a Dirichlet character modulo the multiple M of the modulus. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: H.<c> = DirichletGroup(4) sage: c.extend(20) Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1 sage: a Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1 sage: c.extend(20) == a True """ if M % self.modulus() != 0: raise ArithmeticError("M(=%s) must be a multiple of the modulus(=%s)"%(M,self.modulus())) H = DirichletGroup(M, self.base_ring()) return H(self) def _pari_conversion(self): r""" Prepare data for the conversion of the character to Pari. OUTPUT: pair (G, v) where G is `(\ZZ / N \ZZ)^*` where `N` is the modulus EXAMPLES:: sage: chi4 = DirichletGroup(4).gen() sage: chi4._pari_conversion() ([[4, [0]], [2, [2], [3]], [[2]~, Vecsmall([2])], [[4], [[1, matrix(0,2)]], Mat(1), [3], [2], [0]], Mat(1)], [1]) sage: chi = DirichletGroup(24)([1,-1,-1]); chi Dirichlet character modulo 24 of conductor 24 mapping 7 |--> 1, 13 |--> -1, 17 |--> -1 sage: chi._pari_conversion() ([[24, [0]], [8, [2, 2, 2], [7, 13, 17]], [[2, 2, 3]~, Vecsmall([3, 3, 1])], [[8, 8, 3], [[1, matrix(0,2)], [1, matrix(0,2)], [2, Mat([2, 1])]], [1, 0, 0; 0, 1, 0; 0, 0, 1], [7, 13, 17], [2, 2, 2], [0, 0, 0]], [1, 0, 0; 0, 1, 0; 0, 0, 1]], [0, 1, 1]) """ G = pari.znstar(self.modulus(), 1) pari_orders = G[1][1] pari_gens = G[1][2] # one should use the following, but this does not work # pari_orders = G.cyc() # pari_gens = G.gen() values_on_gens = (self(x) for x in pari_gens) # now compute the input for pari (list of exponents) P = self.parent() if is_ComplexField(P.base_ring()): zeta = P.zeta() zeta_argument = zeta.argument() v = [int(x.argument() / zeta_argument) for x in values_on_gens] else: dlog = P._zeta_dlog v = [dlog[x] for x in values_on_gens] m = P.zeta_order() v = [(vi * oi) // m for vi, oi in zip(v, pari_orders)] return (G, v) def conrey_number(self): r""" Return the Conrey number for this character. This is a positive integer coprime to q that identifies a Dirichlet character of modulus q. See https://www.lmfdb.org/knowledge/show/character.dirichlet.conrey EXAMPLES:: sage: chi4 = DirichletGroup(4).gen() sage: chi4.conrey_number() 3 sage: chi = DirichletGroup(24)([1,-1,-1]); chi Dirichlet character modulo 24 of conductor 24 mapping 7 |--> 1, 13 |--> -1, 17 |--> -1 sage: chi.conrey_number() 5 sage: chi = DirichletGroup(60)([1,-1,I]) sage: chi.conrey_number() 17 sage: chi = DirichletGroup(420)([1,-1,-I,1]) sage: chi.conrey_number() 113 TESTS:: sage: eps1 = DirichletGroup(5)([-1]) sage: eps2 = DirichletGroup(5,QQ)([-1]) sage: eps1.conrey_number() == eps2.conrey_number() True """ G, v = self._pari_conversion() return pari.znconreyexp(G, v).sage() def lmfdb_page(self): r""" Open the LMFDB web page of the character in a browser. See https://www.lmfdb.org EXAMPLES:: sage: E = DirichletGroup(4).gen() sage: E.lmfdb_page() # optional -- webbrowser """ import webbrowser lmfdb_url = 'https://www.lmfdb.org/Character/Dirichlet/{}/{}' url = lmfdb_url.format(self.modulus(), self.conrey_number()) webbrowser.open(url) def galois_orbit(self, sort=True): r""" Return the orbit of this character under the action of the absolute Galois group of the prime subfield of the base ring. EXAMPLES:: sage: G = DirichletGroup(30); e = G.1 sage: e.galois_orbit() [Dirichlet character modulo 30 of conductor 5 mapping 11 |--> 1, 7 |--> -zeta4, Dirichlet character modulo 30 of conductor 5 mapping 11 |--> 1, 7 |--> zeta4] Another example:: sage: G = DirichletGroup(13) sage: G.galois_orbits() [ [Dirichlet character modulo 13 of conductor 1 mapping 2 |--> 1], ..., [Dirichlet character modulo 13 of conductor 13 mapping 2 |--> -1] ] sage: e = G.0 sage: e Dirichlet character modulo 13 of conductor 13 mapping 2 |--> zeta12 sage: e.galois_orbit() [Dirichlet character modulo 13 of conductor 13 mapping 2 |--> zeta12, Dirichlet character modulo 13 of conductor 13 mapping 2 |--> -zeta12^3 + zeta12, Dirichlet character modulo 13 of conductor 13 mapping 2 |--> zeta12^3 - zeta12, Dirichlet character modulo 13 of conductor 13 mapping 2 |--> -zeta12] sage: e = G.0^2; e Dirichlet character modulo 13 of conductor 13 mapping 2 |--> zeta12^2 sage: e.galois_orbit() [Dirichlet character modulo 13 of conductor 13 mapping 2 |--> zeta12^2, Dirichlet character modulo 13 of conductor 13 mapping 2 |--> -zeta12^2 + 1] A non-example:: sage: chi = DirichletGroup(7, Integers(9), zeta = Integers(9)(2)).0 sage: chi.galois_orbit() Traceback (most recent call last): ... TypeError: Galois orbits only defined if base ring is an integral domain """ if not self.base_ring().is_integral_domain(): raise TypeError("Galois orbits only defined if base ring is an integral domain") k = self.order() if k <= 2: return [self] P = self.parent() z = self.element() o = int(z.additive_order()) Auts = set([m % o for m in P._automorphisms()]) v = [P.element_class(P, m * z, check=False) for m in Auts] if sort: v.sort() return v def gauss_sum(self, a=1): r""" Return a Gauss sum associated to this Dirichlet character. The Gauss sum associated to `\chi` is .. MATH:: g_a(\chi) = \sum_{r \in \ZZ/m\ZZ} \chi(r)\,\zeta^{ar}, where `m` is the modulus of `\chi` and `\zeta` is a primitive `m^{th}` root of unity. FACTS: If the modulus is a prime `p` and the character is nontrivial, then the Gauss sum has absolute value `\sqrt{p}`. CACHING: Computed Gauss sums are *not* cached with this character. EXAMPLES:: sage: G = DirichletGroup(3) sage: e = G([-1]) sage: e.gauss_sum(1) 2*zeta6 - 1 sage: e.gauss_sum(2) -2*zeta6 + 1 sage: norm(e.gauss_sum()) 3 :: sage: G = DirichletGroup(13) sage: e = G.0 sage: e.gauss_sum() -zeta156^46 + zeta156^45 + zeta156^42 + zeta156^41 + 2*zeta156^40 + zeta156^37 - zeta156^36 - zeta156^34 - zeta156^33 - zeta156^31 + 2*zeta156^30 + zeta156^28 - zeta156^24 - zeta156^22 + zeta156^21 + zeta156^20 - zeta156^19 + zeta156^18 - zeta156^16 - zeta156^15 - 2*zeta156^14 - zeta156^10 + zeta156^8 + zeta156^7 + zeta156^6 + zeta156^5 - zeta156^4 - zeta156^2 - 1 sage: factor(norm(e.gauss_sum())) 13^24 TESTS: The field of algebraic numbers is supported (:trac:`19056`):: sage: G = DirichletGroup(7, QQbar) sage: G[1].gauss_sum() -2.440133358345538? + 1.022618791871794?*I Check that :trac:`19060` is fixed:: sage: K.<z> = CyclotomicField(8) sage: G = DirichletGroup(13, K) sage: chi = G([z^2]) sage: chi.gauss_sum() zeta52^22 + zeta52^21 + zeta52^19 - zeta52^16 + zeta52^15 + zeta52^14 + zeta52^12 - zeta52^11 - zeta52^10 - zeta52^7 - zeta52^5 + zeta52^4 Check that :trac:`25127` is fixed:: sage: G = DirichletGroup(1) sage: chi = G.one() sage: chi.gauss_sum() 1 .. SEEALSO:: - :func:`sage.arith.misc.gauss_sum` for general finite fields - :func:`sage.rings.padics.misc.gauss_sum` for a `p`-adic version """ G = self.parent() K = G.base_ring() chi = self m = G.modulus() if is_ComplexField(K): return self.gauss_sum_numerical(a=a) elif is_AlgebraicField(K): L = K zeta = L.zeta(m) elif number_field.is_CyclotomicField(K) or is_RationalField(K): chi = chi.minimize_base_ring() n = lcm(m, G.zeta_order()) L = rings.CyclotomicField(n) zeta = L.gen(0) ** (n // m) else: raise NotImplementedError("Gauss sums only currently implemented when the base ring is a cyclotomic field, QQ, QQbar, or a complex field") zeta = zeta ** a g = L(chi(0)) z = L.one() for c in chi.values()[1:]: z *= zeta g += L(c)*z return g def gauss_sum_numerical(self, prec=53, a=1): r""" Return a Gauss sum associated to this Dirichlet character as an approximate complex number with prec bits of precision. INPUT: - ``prec`` -- integer (default: 53), *bits* of precision - ``a`` -- integer, as for :meth:`gauss_sum`. The Gauss sum associated to `\chi` is .. MATH:: g_a(\chi) = \sum_{r \in \ZZ/m\ZZ} \chi(r)\,\zeta^{ar}, where `m` is the modulus of `\chi` and `\zeta` is a primitive `m^{th}` root of unity. EXAMPLES:: sage: G = DirichletGroup(3) sage: e = G.0 sage: abs(e.gauss_sum_numerical()) 1.7320508075... sage: sqrt(3.0) 1.73205080756888 sage: e.gauss_sum_numerical(a=2) -...e-15 - 1.7320508075...*I sage: e.gauss_sum_numerical(a=2, prec=100) 4.7331654313260708324703713917e-30 - 1.7320508075688772935274463415*I sage: G = DirichletGroup(13) sage: H = DirichletGroup(13, CC) sage: e = G.0 sage: f = H.0 sage: e.gauss_sum_numerical() -3.07497205... + 1.8826966926...*I sage: f.gauss_sum_numerical() -3.07497205... + 1.8826966926...*I sage: abs(e.gauss_sum_numerical()) 3.60555127546... sage: abs(f.gauss_sum_numerical()) 3.60555127546... sage: sqrt(13.0) 3.60555127546399 TESTS: The field of algebraic numbers is supported (:trac:`19056`):: sage: G = DirichletGroup(7, QQbar) sage: G[1].gauss_sum_numerical() -2.44013335834554 + 1.02261879187179*I """ G = self.parent() K = G.base_ring() if is_ComplexField(K): phi = lambda t : t CC = K elif is_AlgebraicField(K): from sage.rings.complex_mpfr import ComplexField CC = ComplexField(prec) phi = CC.coerce_map_from(K) elif number_field.is_CyclotomicField(K) or is_RationalField(K): phi = K.complex_embedding(prec) CC = phi.codomain() else: raise NotImplementedError("Gauss sums only currently implemented when the base ring is a cyclotomic field, QQ, QQbar, or a complex field") zeta = CC.zeta(G.modulus()) ** a g = phi(self(0)) z = CC.one() for c in self.values()[1:]: z *= zeta g += phi(c)*z return g def jacobi_sum(self, char, check=True): r""" Return the Jacobi sum associated to these Dirichlet characters (i.e., J(self,char)). This is defined as .. MATH:: J(\chi, \psi) = \sum_{a \in \ZZ / N\ZZ} \chi(a) \psi(1-a) where `\chi` and `\psi` are both characters modulo `N`. EXAMPLES:: sage: D = DirichletGroup(13) sage: e = D.0 sage: f = D[-2] sage: e.jacobi_sum(f) 3*zeta12^2 + 2*zeta12 - 3 sage: f.jacobi_sum(e) 3*zeta12^2 + 2*zeta12 - 3 sage: p = 7 sage: DP = DirichletGroup(p) sage: f = DP.0 sage: e.jacobi_sum(f) Traceback (most recent call last): ... NotImplementedError: Characters must be from the same Dirichlet Group. sage: all_jacobi_sums = [(DP[i].values_on_gens(),DP[j].values_on_gens(),DP[i].jacobi_sum(DP[j])) ....: for i in range(p-1) for j in range(i, p-1)] sage: for s in all_jacobi_sums: ....: print(s) ((1,), (1,), 5) ((1,), (zeta6,), -1) ((1,), (zeta6 - 1,), -1) ((1,), (-1,), -1) ((1,), (-zeta6,), -1) ((1,), (-zeta6 + 1,), -1) ((zeta6,), (zeta6,), -zeta6 + 3) ((zeta6,), (zeta6 - 1,), 2*zeta6 + 1) ((zeta6,), (-1,), -2*zeta6 - 1) ((zeta6,), (-zeta6,), zeta6 - 3) ((zeta6,), (-zeta6 + 1,), 1) ((zeta6 - 1,), (zeta6 - 1,), -3*zeta6 + 2) ((zeta6 - 1,), (-1,), 2*zeta6 + 1) ((zeta6 - 1,), (-zeta6,), -1) ((zeta6 - 1,), (-zeta6 + 1,), -zeta6 - 2) ((-1,), (-1,), 1) ((-1,), (-zeta6,), -2*zeta6 + 3) ((-1,), (-zeta6 + 1,), 2*zeta6 - 3) ((-zeta6,), (-zeta6,), 3*zeta6 - 1) ((-zeta6,), (-zeta6 + 1,), -2*zeta6 + 3) ((-zeta6 + 1,), (-zeta6 + 1,), zeta6 + 2) Let's check that trivial sums are being calculated correctly:: sage: N = 13 sage: D = DirichletGroup(N) sage: g = D(1) sage: g.jacobi_sum(g) 11 sage: sum([g(x)*g(1-x) for x in IntegerModRing(N)]) 11 And sums where exactly one character is nontrivial (see :trac:`6393`):: sage: G = DirichletGroup(5); X=G.list(); Y=X[0]; Z=X[1] sage: Y.jacobi_sum(Z) -1 sage: Z.jacobi_sum(Y) -1 Now let's take a look at a non-prime modulus:: sage: N = 9 sage: D = DirichletGroup(N) sage: g = D(1) sage: g.jacobi_sum(g) 3 We consider a sum with values in a finite field:: sage: g = DirichletGroup(17, GF(9,'a')).0 sage: g.jacobi_sum(g**2) 2*a TESTS: This shows that :trac:`6393` has been fixed:: sage: G = DirichletGroup(5); X = G.list(); Y = X[0]; Z = X[1] sage: # Y is trivial and Z is quartic sage: sum([Y(x)*Z(1-x) for x in IntegerModRing(5)]) -1 sage: # The value -1 above is the correct value of the Jacobi sum J(Y, Z). sage: Y.jacobi_sum(Z); Z.jacobi_sum(Y) -1 -1 """ if check: if self.parent() != char.parent(): raise NotImplementedError("Characters must be from the same Dirichlet Group.") return sum([self(x) * char(1-x) for x in rings.IntegerModRing(self.modulus())]) def kloosterman_sum(self, a=1, b=0): r""" Return the "twisted" Kloosterman sum associated to this Dirichlet character. This includes Gauss sums, classical Kloosterman sums, Salié sums, etc. The Kloosterman sum associated to `\chi` and the integers a,b is .. MATH:: K(a,b,\chi) = \sum_{r \in (\ZZ/m\ZZ)^\times} \chi(r)\,\zeta^{ar+br^{-1}}, where `m` is the modulus of `\chi` and `\zeta` is a primitive `m` th root of unity. This reduces to the Gauss sum if `b=0`. This method performs an exact calculation and returns an element of a suitable cyclotomic field; see also :meth:`.kloosterman_sum_numerical`, which gives an inexact answer (but is generally much quicker). CACHING: Computed Kloosterman sums are *not* cached with this character. EXAMPLES:: sage: G = DirichletGroup(3) sage: e = G([-1]) sage: e.kloosterman_sum(3,5) -2*zeta6 + 1 sage: G = DirichletGroup(20) sage: e = G([1 for u in G.unit_gens()]) sage: e.kloosterman_sum(7,17) -2*zeta20^6 + 2*zeta20^4 + 4 TESTS:: sage: G = DirichletGroup(20, UniversalCyclotomicField()) sage: e = G([1 for u in G.unit_gens()]) sage: e.kloosterman_sum(7,17) -2*E(5) - 4*E(5)^2 - 4*E(5)^3 - 2*E(5)^4 sage: G = DirichletGroup(12, QQbar) sage: e = G.gens()[0] sage: e.kloosterman_sum(5,11) Traceback (most recent call last): ... NotImplementedError: Kloosterman sums not implemented over this ring """ G = self.parent() zo = G.zeta_order() m = G.modulus() g = 0 L = rings.CyclotomicField(m.lcm(zo)) zeta = L.gen(0) try: self(1) * zeta**(a+b) except TypeError: raise NotImplementedError('Kloosterman sums not implemented ' 'over this ring') n = zeta.multiplicative_order() zeta = zeta**(n // m) for c in m.coprime_integers(m): e = rings.Mod(c, m) g += self(c) * zeta**int(a*e + b*e**(-1)) return g def kloosterman_sum_numerical(self, prec=53, a=1, b=0): r""" Return the Kloosterman sum associated to this Dirichlet character as an approximate complex number with prec bits of precision. See also :meth:`.kloosterman_sum`, which calculates the sum exactly (which is generally slower). INPUT: - ``prec`` -- integer (default: 53), *bits* of precision - ``a`` -- integer, as for :meth:`.kloosterman_sum` - ``b`` -- integer, as for :meth:`.kloosterman_sum`. EXAMPLES:: sage: G = DirichletGroup(3) sage: e = G.0 The real component of the numerical value of e is near zero:: sage: v=e.kloosterman_sum_numerical() sage: v.real() < 1.0e15 True sage: v.imag() 1.73205080756888 sage: G = DirichletGroup(20) sage: e = G.1 sage: e.kloosterman_sum_numerical(53,3,11) 3.80422606518061 - 3.80422606518061*I """ G = self.parent() K = G.base_ring() if not (number_field.is_CyclotomicField(K) or is_RationalField(K)): raise NotImplementedError("Kloosterman sums only currently implemented when the base ring is a cyclotomic field or QQ.") phi = K.complex_embedding(prec) CC = phi.codomain() g = 0 m = G.modulus() zeta = CC.zeta(m) for c in m.coprime_integers(m): e = rings.Mod(c, m) z = zeta ** int(a*e + b*(e**(-1))) g += phi(self(c))*z return g @cached_method def is_even(self): r""" Return ``True`` if and only if `\varepsilon(-1) = 1`. EXAMPLES:: sage: G = DirichletGroup(13) sage: e = G.0 sage: e.is_even() False sage: e(-1) -1 sage: [e.is_even() for e in G] [True, False, True, False, True, False, True, False, True, False, True, False] sage: G = DirichletGroup(13, CC) sage: e = G.0 sage: e.is_even() False sage: e(-1) -1.000000... sage: [e.is_even() for e in G] [True, False, True, False, True, False, True, False, True, False, True, False] sage: G = DirichletGroup(100000, CC) sage: G.1.is_even() True Note that ``is_even`` need not be the negation of is_odd, e.g., in characteristic 2:: sage: G.<e> = DirichletGroup(13, GF(4,'a')) sage: e.is_even() True sage: e.is_odd() True """ R = self.base_ring() # self(-1) is either +1 or -1 if not R.is_exact(): return abs(self(-1) - R(1)) < 0.5 return self(-1) == R(1) @cached_method def is_odd(self): r""" Return ``True`` if and only if `\varepsilon(-1) = -1`. EXAMPLES:: sage: G = DirichletGroup(13) sage: e = G.0 sage: e.is_odd() True sage: [e.is_odd() for e in G] [False, True, False, True, False, True, False, True, False, True, False, True] sage: G = DirichletGroup(13) sage: e = G.0 sage: e.is_odd() True sage: [e.is_odd() for e in G] [False, True, False, True, False, True, False, True, False, True, False, True] sage: G = DirichletGroup(100000, CC) sage: G.0.is_odd() True Note that ``is_even`` need not be the negation of is_odd, e.g., in characteristic 2:: sage: G.<e> = DirichletGroup(13, GF(4,'a')) sage: e.is_even() True sage: e.is_odd() True """ R = self.base_ring() # self(-1) is either +1 or -1 if not R.is_exact(): return abs(self(-1) - R(-1)) < 0.5 return self(-1) == R(-1) @cached_method def is_primitive(self): """ Return ``True`` if and only if this character is primitive, i.e., its conductor equals its modulus. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: a.is_primitive() False sage: b.is_primitive() False sage: (a*b).is_primitive() True sage: G.<a,b> = DirichletGroup(20, CC) sage: a.is_primitive() False sage: b.is_primitive() False sage: (a*b).is_primitive() True """ return (self.conductor() == self.modulus()) @cached_method def is_trivial(self): r""" Returns ``True`` if this is the trivial character, i.e., has order 1. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: a.is_trivial() False sage: (a^2).is_trivial() True """ if self.element.is_in_cache(): return not self.element() one = self.base_ring().one() return all(x == one for x in self.values_on_gens()) def kernel(self): r""" Return the kernel of this character. OUTPUT: Currently the kernel is returned as a list. This may change. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: a.kernel() [1, 9, 13, 17] sage: b.kernel() [1, 11] """ one = self.base_ring().one() return [x for x in range(self.modulus()) if self(x) == one] def maximize_base_ring(self): r""" Let .. MATH:: \varepsilon : (\ZZ/N\ZZ)^* \to \QQ(\zeta_n) be a Dirichlet character. This function returns an equal Dirichlet character .. MATH:: \chi : (\ZZ/N\ZZ)^* \to \QQ(\zeta_m) where `m` is the least common multiple of `n` and the exponent of `(\ZZ/N\ZZ)^*`. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20,QQ) sage: b.maximize_base_ring() Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> -1 sage: b.maximize_base_ring().base_ring() Cyclotomic Field of order 4 and degree 2 sage: DirichletGroup(20).base_ring() Cyclotomic Field of order 4 and degree 2 """ g = rings.IntegerModRing(self.modulus()).unit_group_exponent() if g == 1: g = 2 z = self.base_ring().zeta() n = z.multiplicative_order() m = lcm(g,n) if n == m: return self K = rings.CyclotomicField(m) return self.change_ring(K) def minimize_base_ring(self): r""" Return a Dirichlet character that equals this one, but over as small a subfield (or subring) of the base ring as possible. .. note:: This function is currently only implemented when the base ring is a number field. It's the identity function in characteristic p. EXAMPLES:: sage: G = DirichletGroup(13) sage: e = DirichletGroup(13).0 sage: e.base_ring() Cyclotomic Field of order 12 and degree 4 sage: e.minimize_base_ring().base_ring() Cyclotomic Field of order 12 and degree 4 sage: (e^2).minimize_base_ring().base_ring() Cyclotomic Field of order 6 and degree 2 sage: (e^3).minimize_base_ring().base_ring() Cyclotomic Field of order 4 and degree 2 sage: (e^12).minimize_base_ring().base_ring() Rational Field TESTS: Check that :trac:`18479` is fixed:: sage: f = Newforms(Gamma1(25), names='a')[1] sage: eps = f.character() sage: eps.minimize_base_ring() == eps True A related bug (see :trac:`18086`):: sage: K.<a,b>=NumberField([x^2 + 1, x^2 - 3]) sage: chi = DirichletGroup(7, K).0 sage: chi.minimize_base_ring() Dirichlet character modulo 7 of conductor 7 mapping 3 |--> -1/2*b*a + 1/2 """ R = self.base_ring() if R.is_prime_field(): return self p = R.characteristic() if p: K = rings.IntegerModRing(p) elif self.order() <= 2: K = rings.QQ elif (isinstance(R, number_field.NumberField_generic) and euler_phi(self.order()) < R.absolute_degree()): K = rings.CyclotomicField(self.order()) else: return self try: return self.change_ring(K) except (TypeError, ValueError, ArithmeticError): return self def modulus(self): """ The modulus of this character. EXAMPLES:: sage: e = DirichletGroup(100, QQ).0 sage: e.modulus() 100 sage: e.conductor() 4 """ return self.parent().modulus() def level(self): """ Synonym for modulus. EXAMPLES:: sage: e = DirichletGroup(100, QQ).0 sage: e.level() 100 """ return self.modulus() @cached_method def multiplicative_order(self): """ The order of this character. EXAMPLES:: sage: e = DirichletGroup(100).1 sage: e.order() # same as multiplicative_order, since group is multiplicative 20 sage: e.multiplicative_order() 20 sage: e = DirichletGroup(100).0 sage: e.multiplicative_order() 2 """ if self.parent().zeta.is_in_cache(): return self.element().additive_order() return lcm([z.multiplicative_order() for z in self.values_on_gens()]) def primitive_character(self): """ Returns the primitive character associated to self. EXAMPLES:: sage: e = DirichletGroup(100).0; e Dirichlet character modulo 100 of conductor 4 mapping 51 |--> -1, 77 |--> 1 sage: e.conductor() 4 sage: f = e.primitive_character(); f Dirichlet character modulo 4 of conductor 4 mapping 3 |--> -1 sage: f.modulus() 4 """ return self.restrict(self.conductor()) def restrict(self, M): """ Returns the restriction of this character to a Dirichlet character modulo the divisor M of the modulus, which must also be a multiple of the conductor of this character. EXAMPLES:: sage: e = DirichletGroup(100).0 sage: e.modulus() 100 sage: e.conductor() 4 sage: e.restrict(20) Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1 sage: e.restrict(4) Dirichlet character modulo 4 of conductor 4 mapping 3 |--> -1 sage: e.restrict(50) Traceback (most recent call last): ... ValueError: conductor(=4) must divide M(=50) """ M = int(M) if self.modulus()%M != 0: raise ValueError("M(=%s) must divide the modulus(=%s)"%(M,self.modulus())) if M%self.conductor() != 0: raise ValueError("conductor(=%s) must divide M(=%s)"%(self.conductor(),M)) H = DirichletGroup(M, self.base_ring()) return H(self) @cached_method def values(self): """ Return a list of the values of this character on each integer between 0 and the modulus. EXAMPLES:: sage: e = DirichletGroup(20)(1) sage: e.values() [0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1] sage: e = DirichletGroup(20).gen(0) sage: e.values() [0, 1, 0, -1, 0, 0, 0, -1, 0, 1, 0, -1, 0, 1, 0, 0, 0, 1, 0, -1] sage: e = DirichletGroup(20).gen(1) sage: e.values() [0, 1, 0, -zeta4, 0, 0, 0, zeta4, 0, -1, 0, 1, 0, -zeta4, 0, 0, 0, zeta4, 0, -1] sage: e = DirichletGroup(21).gen(0) ; e.values() [0, 1, -1, 0, 1, -1, 0, 0, -1, 0, 1, -1, 0, 1, 0, 0, 1, -1, 0, 1, -1] sage: e = DirichletGroup(21, base_ring=GF(37)).gen(0) ; e.values() [0, 1, 36, 0, 1, 36, 0, 0, 36, 0, 1, 36, 0, 1, 0, 0, 1, 36, 0, 1, 36] sage: e = DirichletGroup(21, base_ring=GF(3)).gen(0) ; e.values() [0, 1, 2, 0, 1, 2, 0, 0, 2, 0, 1, 2, 0, 1, 0, 0, 1, 2, 0, 1, 2] :: sage: chi = DirichletGroup(100151, CyclotomicField(10)).0 sage: ls = chi.values() ; ls[0:10] [0, 1, -zeta10^3, -zeta10, -zeta10, 1, zeta10^3 - zeta10^2 + zeta10 - 1, zeta10, zeta10^3 - zeta10^2 + zeta10 - 1, zeta10^2] TESTS: Test that :trac:`11783` and :trac:`14368` are fixed:: sage: chi = DirichletGroup(1).list()[0] sage: chi.values() [1] sage: chi(1) 1 """ G = self.parent() R = G.base_ring() mod = self.parent().modulus() if mod == 1: return [R.one()] elif mod == 2: return [R.zero(), R.one()] result_list = [R.zero()] * mod gens = G.unit_gens() orders = G.integers_mod().unit_group().gens_orders() R_values = G._zeta_powers val_on_gen = self.element() exponents = [0] * len(orders) n = G.integers_mod().one() value = val_on_gen.base_ring().zero() while True: # record character value on n result_list[n] = R_values[value] # iterate: # increase the exponent vector by 1, # increase n accordingly, and increase value i = 0 while True: try: exponents[i] += 1 except IndexError: # Done! return result_list value += val_on_gen[i] n *= gens[i] if exponents[i] < orders[i]: break exponents[i] = 0 i += 1 @cached_method(do_pickle=True) def values_on_gens(self): r""" Return a tuple of the values of ``self`` on the standard generators of `(\ZZ/N\ZZ)^*`, where `N` is the modulus. EXAMPLES:: sage: e = DirichletGroup(16)([-1, 1]) sage: e.values_on_gens () (-1, 1) .. NOTE:: The constructor of :class:`DirichletCharacter` sets the cache of :meth:`element` or of :meth:`values_on_gens`. The cache of one of these methods needs to be set for the other method to work properly, these caches have to be stored when pickling an instance of :class:`DirichletCharacter`. """ pows = self.parent()._zeta_powers return tuple([pows[i] for i in self.element()]) @cached_method(do_pickle=True) def element(self): r""" Return the underlying `\ZZ/n\ZZ`-module vector of exponents. .. warning:: Please do not change the entries of the returned vector; this vector is mutable *only* because immutable vectors are not implemented yet. EXAMPLES:: sage: G.<a,b> = DirichletGroup(20) sage: a.element() (2, 0) sage: b.element() (0, 1) .. NOTE:: The constructor of :class:`DirichletCharacter` sets the cache of :meth:`element` or of :meth:`values_on_gens`. The cache of one of these methods needs to be set for the other method to work properly, these caches have to be stored when pickling an instance of :class:`DirichletCharacter`. """ P = self.parent() M = P._module if is_ComplexField(P.base_ring()): zeta = P.zeta() zeta_argument = zeta.argument() v = M([int(round(x.argument() / zeta_argument)) for x in self.values_on_gens()]) else: dlog = P._zeta_dlog v = M([dlog[x] for x in self.values_on_gens()]) v.set_immutable() return v def __setstate__(self, state): r""" Restore a pickled element from ``state``. TESTS:: sage: e = DirichletGroup(16)([-1, 1]) sage: loads(dumps(e)) == e True """ # values_on_gens() used an explicit cache __values_on_gens in the past # we need to set the cache of values_on_gens() from that if we encounter it in a pickle values_on_gens_key = '_DirichletCharacter__values_on_gens' values_on_gens = None state_dict = state[1] if values_on_gens_key in state_dict: values_on_gens = state_dict[values_on_gens_key] del state_dict[values_on_gens_key] # element() used an explicit cache __element in the past # we need to set the cache of element() from that if we encounter it in a pickle element_key = '_DirichletCharacter__element' element = None if element_key in state_dict: element = state_dict[element_key] del state_dict[element_key] super(DirichletCharacter, self).__setstate__(state) if values_on_gens is not None: self.values_on_gens.set_cache(values_on_gens) if element is not None: self.element.set_cache(element) class DirichletGroupFactory(UniqueFactory): r""" Construct a group of Dirichlet characters modulo `N`. INPUT: - ``N`` -- positive integer - ``base_ring`` -- commutative ring; the value ring for the characters in this group (default: the cyclotomic field `\QQ(\zeta_n)`, where `n` is the exponent of `(\ZZ/N\ZZ)^*`) - ``zeta`` -- (optional) root of unity in ``base_ring`` - ``zeta_order`` -- (optional) positive integer; this must be the order of ``zeta`` if both are specified - ``names`` -- ignored (needed so ``G.<...> = DirichletGroup(...)`` notation works) - ``integral`` -- boolean (default: ``False``); whether to replace the default cyclotomic field by its rings of integers as the base ring. This is ignored if ``base_ring`` is not ``None``. OUTPUT: The group of Dirichlet characters modulo `N` with values in a subgroup `V` of the multiplicative group `R^*` of ``base_ring``. This is the group of homomorphisms `(\ZZ/N\ZZ)^* \to V` with pointwise multiplication. The group `V` is determined as follows: - If both ``zeta`` and ``zeta_order`` are omitted, then `V` is taken to be `R^*`, or equivalently its `n`-torsion subgroup, where `n` is the exponent of `(\ZZ/N\ZZ)^*`. Many operations, such as finding a set of generators for the group, are only implemented if `V` is cyclic and a generator for `V` can be found. - If ``zeta`` is specified, then `V` is taken to be the cyclic subgroup of `R^*` generated by ``zeta``. If ``zeta_order`` is also given, it must be the multiplicative order of ``zeta``; this is useful if the base ring is not exact or if the order of ``zeta`` is very large. - If ``zeta`` is not specified but ``zeta_order`` is, then `V` is taken to be the group of roots of unity of order dividing ``zeta_order`` in `R`. In this case, `R` must be a domain (so `V` is cyclic), and `V` must have order ``zeta_order``. Furthermore, a generator ``zeta`` of `V` is computed, and an error is raised if such ``zeta`` cannot be found. EXAMPLES: The default base ring is a cyclotomic field of order the exponent of `(\ZZ/N\ZZ)^*`:: sage: DirichletGroup(20) Group of Dirichlet characters modulo 20 with values in Cyclotomic Field of order 4 and degree 2 We create the group of Dirichlet character mod 20 with values in the rational numbers:: sage: G = DirichletGroup(20, QQ); G Group of Dirichlet characters modulo 20 with values in Rational Field sage: G.order() 4 sage: G.base_ring() Rational Field The elements of G print as lists giving the values of the character on the generators of `(Z/NZ)^*`:: sage: list(G) [Dirichlet character modulo 20 of conductor 1 mapping 11 |--> 1, 17 |--> 1, Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1, Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> -1, Dirichlet character modulo 20 of conductor 20 mapping 11 |--> -1, 17 |--> -1] Next we construct the group of Dirichlet character mod 20, but with values in `\QQ(\zeta_n)`:: sage: G = DirichletGroup(20) sage: G.1 Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> zeta4 We next compute several invariants of ``G``:: sage: G.gens() (Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1, Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> zeta4) sage: G.unit_gens() (11, 17) sage: G.zeta() zeta4 sage: G.zeta_order() 4 In this example we create a Dirichlet group with values in a number field:: sage: R.<x> = PolynomialRing(QQ) sage: K.<a> = NumberField(x^4 + 1) sage: DirichletGroup(5, K) Group of Dirichlet characters modulo 5 with values in Number Field in a with defining polynomial x^4 + 1 An example where we give ``zeta``, but not its order:: sage: G = DirichletGroup(5, K, a); G Group of Dirichlet characters modulo 5 with values in the group of order 8 generated by a in Number Field in a with defining polynomial x^4 + 1 sage: G.list() [Dirichlet character modulo 5 of conductor 1 mapping 2 |--> 1, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> a^2, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> -1, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> -a^2] We can also restrict the order of the characters, either with or without specifying a root of unity:: sage: DirichletGroup(5, K, zeta=-1, zeta_order=2) Group of Dirichlet characters modulo 5 with values in the group of order 2 generated by -1 in Number Field in a with defining polynomial x^4 + 1 sage: DirichletGroup(5, K, zeta_order=2) Group of Dirichlet characters modulo 5 with values in the group of order 2 generated by -1 in Number Field in a with defining polynomial x^4 + 1 :: sage: G.<e> = DirichletGroup(13) sage: loads(G.dumps()) == G True :: sage: G = DirichletGroup(19, GF(5)) sage: loads(G.dumps()) == G True We compute a Dirichlet group over a large prime field:: sage: p = next_prime(10^40) sage: g = DirichletGroup(19, GF(p)); g Group of Dirichlet characters modulo 19 with values in Finite Field of size 10000000000000000000000000000000000000121 Note that the root of unity has small order, i.e., it is not the largest order root of unity in the field:: sage: g.zeta_order() 2 :: sage: r4 = CyclotomicField(4).ring_of_integers() sage: G = DirichletGroup(60, r4) sage: G.gens() (Dirichlet character modulo 60 of conductor 4 mapping 31 |--> -1, 41 |--> 1, 37 |--> 1, Dirichlet character modulo 60 of conductor 3 mapping 31 |--> 1, 41 |--> -1, 37 |--> 1, Dirichlet character modulo 60 of conductor 5 mapping 31 |--> 1, 41 |--> 1, 37 |--> zeta4) sage: val = G.gens()[2].values_on_gens()[2] ; val zeta4 sage: parent(val) Gaussian Integers in Cyclotomic Field of order 4 and degree 2 sage: r4.residue_field(r4.ideal(29).factor()[0][0])(val) 17 sage: r4.residue_field(r4.ideal(29).factor()[0][0])(val) * GF(29)(3) 22 sage: r4.residue_field(r4.ideal(29).factor()[0][0])(G.gens()[2].values_on_gens()[2]) * 3 22 sage: parent(r4.residue_field(r4.ideal(29).factor()[0][0])(G.gens()[2].values_on_gens()[2]) * 3) Residue field of Fractional ideal (-2*zeta4 + 5) :: sage: DirichletGroup(60, integral=True) Group of Dirichlet characters modulo 60 with values in Gaussian Integers in Cyclotomic Field of order 4 and degree 2 sage: parent(DirichletGroup(60, integral=True).gens()[2].values_on_gens()[2]) Gaussian Integers in Cyclotomic Field of order 4 and degree 2 If the order of ``zeta`` cannot be determined automatically, we can specify it using ``zeta_order``:: sage: DirichletGroup(7, CC, zeta=exp(2*pi*I/6)) Traceback (most recent call last): ... NotImplementedError: order of element not known sage: DirichletGroup(7, CC, zeta=exp(2*pi*I/6), zeta_order=6) Group of Dirichlet characters modulo 7 with values in the group of order 6 generated by 0.500000000000000 + 0.866025403784439*I in Complex Field with 53 bits of precision If the base ring is not a domain (in which case the group of roots of unity is not necessarily cyclic), some operations still work, such as creation of elements:: sage: G = DirichletGroup(5, Zmod(15)); G Group of Dirichlet characters modulo 5 with values in Ring of integers modulo 15 sage: chi = G([13]); chi Dirichlet character modulo 5 of conductor 5 mapping 2 |--> 13 sage: chi^2 Dirichlet character modulo 5 of conductor 5 mapping 2 |--> 4 sage: chi.multiplicative_order() 4 Other operations only work if ``zeta`` is specified:: sage: G.gens() Traceback (most recent call last): ... NotImplementedError: factorization of polynomials over rings with composite characteristic is not implemented sage: G = DirichletGroup(5, Zmod(15), zeta=2); G Group of Dirichlet characters modulo 5 with values in the group of order 4 generated by 2 in Ring of integers modulo 15 sage: G.gens() (Dirichlet character modulo 5 of conductor 5 mapping 2 |--> 2,) TESTS: Dirichlet groups are cached, creating two groups with the same parameters yields the same object:: sage: DirichletGroup(60) is DirichletGroup(60) True """ def create_key(self, N, base_ring=None, zeta=None, zeta_order=None, names=None, integral=False): """ Create a key that uniquely determines a Dirichlet group. TESTS:: sage: DirichletGroup.create_key(60) (Cyclotomic Field of order 4 and degree 2, 60, None, None) An example to illustrate that ``base_ring`` is a part of the key:: sage: k = DirichletGroup.create_key(2, base_ring=QQ); k (Rational Field, 2, None, None) sage: l = DirichletGroup.create_key(2, base_ring=CC); l (Complex Field with 53 bits of precision, 2, None, None) sage: k == l False sage: G = DirichletGroup.create_object(None, k); G Group of Dirichlet characters modulo 2 with values in Rational Field sage: H = DirichletGroup.create_object(None, l); H Group of Dirichlet characters modulo 2 with values in Complex Field with 53 bits of precision sage: G == H False If ``base_ring`` was not be a part of the key, the keys would compare equal and the caching would be broken:: sage: k = k[1:]; k (2, None, None) sage: l = l[1:]; l (2, None, None) sage: k == l True sage: DirichletGroup(2, base_ring=QQ) is DirichletGroup(2, base_ring=CC) False If the base ring is not an integral domain, an error will be raised if only ``zeta_order`` is specified:: sage: DirichletGroup(17, Integers(15)) Group of Dirichlet characters modulo 17 with values in Ring of integers modulo 15 sage: DirichletGroup(17, Integers(15), zeta_order=4) Traceback (most recent call last): ... ValueError: base ring (= Ring of integers modulo 15) must be an integral domain if only zeta_order is specified sage: G = DirichletGroup(17, Integers(15), zeta=7); G Group of Dirichlet characters modulo 17 with values in the group of order 4 generated by 7 in Ring of integers modulo 15 sage: G.order() 4 sage: DirichletGroup(-33) Traceback (most recent call last): ... ValueError: modulus should be positive """ modulus = rings.Integer(N) if modulus <= 0: raise ValueError('modulus should be positive') if base_ring is None: if not (zeta is None and zeta_order is None): raise ValueError("zeta and zeta_order must be None if base_ring not specified") e = rings.IntegerModRing(modulus).unit_group_exponent() base_ring = rings.CyclotomicField(e) if integral: base_ring = base_ring.ring_of_integers() if not is_Ring(base_ring): raise TypeError("base_ring (= %s) must be a ring" % base_ring) # If either zeta or zeta_order is given, compute the other. if zeta is not None: zeta = base_ring(zeta) if zeta_order is None: zeta_order = zeta.multiplicative_order() elif zeta_order is not None: if not base_ring.is_integral_domain(): raise ValueError("base ring (= %s) must be an integral domain if only zeta_order is specified" % base_ring) zeta_order = rings.Integer(zeta_order) zeta = base_ring.zeta(zeta_order) return (base_ring, modulus, zeta, zeta_order) def create_object(self, version, key, **extra_args): """ Create the object from the key (extra arguments are ignored). This is only called if the object was not found in the cache. TESTS:: sage: K = CyclotomicField(4) sage: DirichletGroup.create_object(None, (K, 60, K.gen(), 4)) Group of Dirichlet characters modulo 60 with values in the group of order 4 generated by zeta4 in Cyclotomic Field of order 4 and degree 2 """ base_ring, modulus, zeta, zeta_order = key return DirichletGroup_class(base_ring, modulus, zeta, zeta_order) DirichletGroup = DirichletGroupFactory("DirichletGroup") def is_DirichletGroup(x): """ Returns True if x is a Dirichlet group. EXAMPLES:: sage: from sage.modular.dirichlet import is_DirichletGroup sage: is_DirichletGroup(DirichletGroup(11)) True sage: is_DirichletGroup(11) False sage: is_DirichletGroup(DirichletGroup(11).0) False """ return isinstance(x, DirichletGroup_class) class DirichletGroup_class(WithEqualityById, Parent): """ Group of Dirichlet characters modulo `N` with values in a ring `R`. """ Element = DirichletCharacter def __init__(self, base_ring, modulus, zeta, zeta_order): """ Create a Dirichlet group. Not to be called directly (use the factory function ``DirichletGroup``). The ``DirichletGroup`` factory ensures that either both ``zeta`` and ``zeta_order`` are specified, or that both are ``None``. In the former case, it also ensures that ``zeta`` is an element of ``base_ring`` and that ``zeta_order`` is an element of ``ZZ``. TESTS:: sage: G = DirichletGroup(7, base_ring=Integers(9), zeta=2) # indirect doctest sage: TestSuite(G).run() sage: G.base() # check that Parent.__init__ has been called Ring of integers modulo 9 sage: DirichletGroup(13) == DirichletGroup(13) True sage: DirichletGroup(13) == DirichletGroup(13, QQ) False """ from sage.categories.groups import Groups category = Groups().Commutative() if base_ring.is_integral_domain() or base_ring.is_finite(): # The group of n-th roots of unity in the base ring is # finite, and hence this Dirichlet group is finite too. # In particular, it is finitely generated; the added # FinitelyGenerated() here means that the group has a # distinguished set of generators. category = category.Finite().FinitelyGenerated() Parent.__init__(self, base_ring, category=category) self._zeta = zeta self._zeta_order = zeta_order self._modulus = modulus self._integers = rings.IntegerModRing(modulus) def __setstate__(self, state): """ Used for unpickling old instances. TESTS:: sage: G = DirichletGroup(9) sage: loads(dumps(G)) is G True """ self._set_element_constructor() if '_zeta_order' in state: state['_zeta_order'] = rings.Integer(state['_zeta_order']) super(DirichletGroup_class, self).__setstate__(state) @property def _module(self): """ Return the free module used to represent Dirichlet characters. TESTS:: sage: DirichletGroup(12)._module Vector space of dimension 2 over Ring of integers modulo 2 """ return free_module.FreeModule(rings.IntegerModRing(self.zeta_order()), len(self.unit_gens())) @property def _zeta_powers(self): """ Return a list of powers of the distinguished root of unity. TESTS:: sage: DirichletGroup(5)._zeta_powers [1, zeta4, -1, -zeta4] """ R = self.base_ring() a = R.one() w = [a] zeta = self.zeta() zeta_order = self.zeta_order() if is_ComplexField(R): for i in range(1, zeta_order): a = a * zeta a._set_multiplicative_order(zeta_order/gcd(zeta_order, i)) w.append(a) else: for i in range(1, zeta_order): a = a * zeta w.append(a) return w @property def _zeta_dlog(self): """ Return a dictionary that can be used to compute discrete logarithms in the value group of this Dirichlet group. TESTS:: sage: DirichletGroup(5)._zeta_dlog {-1: 2, -zeta4: 3, zeta4: 1, 1: 0} """ return {z: i for i, z in enumerate(self._zeta_powers)} def change_ring(self, R, zeta=None, zeta_order=None): """ Return the base extension of ``self`` to ``R``. INPUT: - ``R`` -- either a ring admitting a conversion map from the base ring of ``self``, or a ring homomorphism with the base ring of ``self`` as its domain - ``zeta`` -- (optional) root of unity in ``R`` - ``zeta_order`` -- (optional) order of ``zeta`` EXAMPLES:: sage: G = DirichletGroup(7,QQ); G Group of Dirichlet characters modulo 7 with values in Rational Field sage: G.change_ring(CyclotomicField(6)) Group of Dirichlet characters modulo 7 with values in Cyclotomic Field of order 6 and degree 2 TESTS: We test the case where `R` is a map (:trac:`18072`):: sage: K.<i> = QuadraticField(-1) sage: f = K.complex_embeddings()[0] sage: D = DirichletGroup(5, K) sage: D.change_ring(f) Group of Dirichlet characters modulo 5 with values in Complex Field with 53 bits of precision """ if zeta is None and self._zeta is not None: # A root of unity was explicitly given; we use it over the # new base ring as well. zeta = self._zeta if zeta_order is None: # We reuse _zeta_order if we know that it stays the # same; otherwise it will be recomputed as the order # of R(zeta) by the DirichletGroup factory. p = R.characteristic() if p == 0 or p.gcd(self._zeta_order) == 1: zeta_order = self._zeta_order else: # No root of unity specified; use the same zeta_order # (which may still be None). zeta_order = self._zeta_order # Map zeta to the new parent if zeta is not None: zeta = R(zeta) if isinstance(R, Map): R = R.codomain() return DirichletGroup(self.modulus(), R, zeta=zeta, zeta_order=zeta_order) def base_extend(self, R): """ Return the base extension of ``self`` to ``R``. INPUT: - ``R`` -- either a ring admitting a *coercion* map from the base ring of ``self``, or a ring homomorphism with the base ring of ``self`` as its domain EXAMPLES:: sage: G = DirichletGroup(7,QQ); G Group of Dirichlet characters modulo 7 with values in Rational Field sage: H = G.base_extend(CyclotomicField(6)); H Group of Dirichlet characters modulo 7 with values in Cyclotomic Field of order 6 and degree 2 Note that the root of unity can change:: sage: H.zeta() zeta6 This method (in contrast to :meth:`change_ring`) requires a coercion map to exist:: sage: G.base_extend(ZZ) Traceback (most recent call last): ... TypeError: no coercion map from Rational Field to Integer Ring is defined Base-extended Dirichlet groups do not silently get roots of unity with smaller order than expected (:trac:`6018`):: sage: G = DirichletGroup(10, QQ).base_extend(CyclotomicField(4)) sage: H = DirichletGroup(10, CyclotomicField(4)) sage: G is H True sage: G3 = DirichletGroup(31, CyclotomicField(3)) sage: G5 = DirichletGroup(31, CyclotomicField(5)) sage: K30 = CyclotomicField(30) sage: G3.gen(0).base_extend(K30) * G5.gen(0).base_extend(K30) Dirichlet character modulo 31 of conductor 31 mapping 3 |--> -zeta30^7 + zeta30^5 + zeta30^4 + zeta30^3 - zeta30 - 1 When a root of unity is specified, base extension still works if the new base ring is not an integral domain:: sage: f = DirichletGroup(17, ZZ, zeta=-1).0 sage: g = f.base_extend(Integers(15)) sage: g(3) 14 sage: g.parent().zeta() 14 """ if not (isinstance(R, Map) or R.has_coerce_map_from(self.base_ring())): raise TypeError("no coercion map from %s to %s is defined" % (self.base_ring(), R)) return self.change_ring(R) def _element_constructor_(self, x): """ Construct a Dirichlet character from `x`. EXAMPLES:: sage: G = DirichletGroup(13) sage: K = G.base_ring() sage: G(1) Dirichlet character modulo 13 of conductor 1 mapping 2 |--> 1 sage: G([-1]) Dirichlet character modulo 13 of conductor 13 mapping 2 |--> -1 sage: G([K.0]) Dirichlet character modulo 13 of conductor 13 mapping 2 |--> zeta12 sage: G(0) Traceback (most recent call last): ... TypeError: cannot convert 0 to an element of Group of Dirichlet characters modulo 13 with values in Cyclotomic Field of order 12 and degree 4 sage: G = DirichletGroup(6) sage: G(DirichletGroup(3).0) Dirichlet character modulo 6 of conductor 3 mapping 5 |--> -1 sage: G(DirichletGroup(15).0) Dirichlet character modulo 6 of conductor 3 mapping 5 |--> -1 sage: G(DirichletGroup(15).1) Traceback (most recent call last): ... TypeError: conductor must divide modulus sage: H = DirichletGroup(16, QQ); H(DirichletGroup(16).1) Traceback (most recent call last): ... TypeError: Unable to coerce zeta4 to a rational """ R = self.base_ring() try: if x == R.one(): x = [R.one()] * len(self.unit_gens()) except (TypeError, ValueError, ArithmeticError): pass if isinstance(x, list): # list of values on each unit generator return self.element_class(self, x) elif not isinstance(x, DirichletCharacter): raise TypeError("cannot convert %s to an element of %s" % (x, self)) elif not x.conductor().divides(self.modulus()): raise TypeError("conductor must divide modulus") a = [] for u in self.unit_gens(): v = u.lift() # have to do this, since e.g., unit gens mod 11 are not units mod 22. while x.modulus().gcd(v) != 1: v += self.modulus() a.append(R(x(v))) return self.element_class(self, a) def _coerce_map_from_(self, X): """ Decide whether there is a coercion map from `X`. There is conversion between Dirichlet groups of different moduli, but no coercion. This implies that Dirichlet characters of different moduli do not compare as equal. TESTS:: sage: trivial_character(6) == trivial_character(3) # indirect doctest False sage: trivial_character(3) == trivial_character(9) False sage: trivial_character(3) == DirichletGroup(3, QQ).0^2 True """ return (isinstance(X, DirichletGroup_class) and self.modulus() == X.modulus() and self.base_ring().has_coerce_map_from(X.base_ring()) and (self._zeta is None or (X._zeta is not None and self.base_ring()(X._zeta) in self._zeta_powers))) def __len__(self): """ Return the number of elements of this Dirichlet group. This is the same as self.order(). EXAMPLES:: sage: len(DirichletGroup(20)) 8 sage: len(DirichletGroup(20, QQ)) 4 sage: len(DirichletGroup(20, GF(5))) 8 sage: len(DirichletGroup(20, GF(2))) 1 sage: len(DirichletGroup(20, GF(3))) 4 """ return self.order() def _repr_(self): """ Return a print representation of this group, which can be renamed. EXAMPLES:: sage: G = DirichletGroup(11) sage: repr(G) # indirect doctest 'Group of Dirichlet characters modulo 11 with values in Cyclotomic Field of order 10 and degree 4' sage: G.rename('Dir(11)') sage: G Dir(11) """ s = "Group of Dirichlet characters modulo %s with values in " % self.modulus() if self._zeta is not None: s += "the group of order %s generated by %s in " % (self._zeta_order, self._zeta) s += str(self.base_ring()) return s @cached_method def decomposition(self): r""" Returns the Dirichlet groups of prime power modulus corresponding to primes dividing modulus. (Note that if the modulus is 2 mod 4, there will be a "factor" of `(\ZZ/2\ZZ)^*`, which is the trivial group.) EXAMPLES:: sage: DirichletGroup(20).decomposition() [ Group of Dirichlet characters modulo 4 with values in Cyclotomic Field of order 4 and degree 2, Group of Dirichlet characters modulo 5 with values in Cyclotomic Field of order 4 and degree 2 ] sage: DirichletGroup(20,GF(5)).decomposition() [ Group of Dirichlet characters modulo 4 with values in Finite Field of size 5, Group of Dirichlet characters modulo 5 with values in Finite Field of size 5 ] """ R = self.base_ring() return Sequence([DirichletGroup(p**r,R) for p, r \ in factor(self.modulus())], cr=True, universe = cat.Objects()) def exponent(self): """ Return the exponent of this group. EXAMPLES:: sage: DirichletGroup(20).exponent() 4 sage: DirichletGroup(20,GF(3)).exponent() 2 sage: DirichletGroup(20,GF(2)).exponent() 1 sage: DirichletGroup(37).exponent() 36 """ return self.zeta_order() @cached_method def _automorphisms(self): """ Compute the automorphisms of self. These are always given by raising to a power, so the return value is a list of integers. At present this is only implemented if the base ring has characteristic 0 or a prime. EXAMPLES:: sage: DirichletGroup(17)._automorphisms() [1, 3, 5, 7, 9, 11, 13, 15] sage: DirichletGroup(17, GF(11^4, 'a'))._automorphisms() [1, 11, 121, 1331] sage: DirichletGroup(17, Integers(6), zeta=Integers(6)(5))._automorphisms() Traceback (most recent call last): ... NotImplementedError: Automorphisms for finite non-field base rings not implemented sage: DirichletGroup(17, Integers(9), zeta=Integers(9)(2))._automorphisms() Traceback (most recent call last): ... NotImplementedError: Automorphisms for finite non-field base rings not implemented """ n = self.zeta_order() R = self.base_ring() p = R.characteristic() if p == 0: Auts = [e for e in range(1,n) if gcd(e,n) == 1] else: if not rings.ZZ(p).is_prime(): raise NotImplementedError("Automorphisms for finite non-field base rings not implemented") # The automorphisms in characteristic p are # k-th powering for # k = 1, p, p^2, ..., p^(r-1), # where p^r = 1 (mod n), so r is the mult order of p modulo n. r = rings.IntegerModRing(n)(p).multiplicative_order() Auts = [p**m for m in range(0,r)] return Auts def galois_orbits(self, v=None, reps_only=False, sort=True, check=True): """ Return a list of the Galois orbits of Dirichlet characters in self, or in v if v is not None. INPUT: - ``v`` - (optional) list of elements of self - ``reps_only`` - (optional: default False) if True only returns representatives for the orbits. - ``sort`` - (optional: default True) whether to sort the list of orbits and the orbits themselves (slightly faster if False). - ``check`` - (optional, default: True) whether or not to explicitly coerce each element of v into self. The Galois group is the absolute Galois group of the prime subfield of Frac(R). If R is not a domain, an error will be raised. EXAMPLES:: sage: DirichletGroup(20).galois_orbits() [ [Dirichlet character modulo 20 of conductor 20 mapping 11 |--> -1, 17 |--> -1], ..., [Dirichlet character modulo 20 of conductor 1 mapping 11 |--> 1, 17 |--> 1] ] sage: DirichletGroup(17, Integers(6), zeta=Integers(6)(5)).galois_orbits() Traceback (most recent call last): ... TypeError: Galois orbits only defined if base ring is an integral domain sage: DirichletGroup(17, Integers(9), zeta=Integers(9)(2)).galois_orbits() Traceback (most recent call last): ... TypeError: Galois orbits only defined if base ring is an integral domain """ if v is None: v = self.list() else: if check: v = [self(x) for x in v] G = [] seen_so_far = set([]) for x in v: z = x.element() e = tuple(z) # change when there are immutable vectors (and below) if e in seen_so_far: continue orbit = x.galois_orbit(sort=sort) if reps_only: G.append(x) else: G.append(orbit) for z in orbit: seen_so_far.add(tuple(z.element())) G = Sequence(G, cr=True) if sort: G.sort() return G def gen(self, n=0): """ Return the n-th generator of self. EXAMPLES:: sage: G = DirichletGroup(20) sage: G.gen(0) Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1 sage: G.gen(1) Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> zeta4 sage: G.gen(2) Traceback (most recent call last): ... IndexError: n(=2) must be between 0 and 1 :: sage: G.gen(-1) Traceback (most recent call last): ... IndexError: n(=-1) must be between 0 and 1 """ n = int(n) g = self.gens() if n<0 or n>=len(g): raise IndexError("n(=%s) must be between 0 and %s"%(n,len(g)-1)) return g[n] @cached_method def gens(self): """ Returns generators of self. EXAMPLES:: sage: G = DirichletGroup(20) sage: G.gens() (Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1, Dirichlet character modulo 20 of conductor 5 mapping 11 |--> 1, 17 |--> zeta4) """ g = [] ord = self.zeta_order() M = self._module zero = M(0) orders = self.integers_mod().unit_group().gens_orders() for i in range(len(self.unit_gens())): z = zero.__copy__() z[i] = ord//gcd(ord, orders[i]) g.append(self.element_class(self, z, check=False)) return tuple(g) def integers_mod(self): r""" Returns the group of integers `\ZZ/N\ZZ` where `N` is the modulus of self. EXAMPLES:: sage: G = DirichletGroup(20) sage: G.integers_mod() Ring of integers modulo 20 """ return self._integers __iter__ = multiplicative_iterator def list(self): """ Return a list of the Dirichlet characters in this group. EXAMPLES:: sage: DirichletGroup(5).list() [Dirichlet character modulo 5 of conductor 1 mapping 2 |--> 1, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> zeta4, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> -1, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> -zeta4] """ return self._list_from_iterator() def modulus(self): """ Returns the modulus of self. EXAMPLES:: sage: G = DirichletGroup(20) sage: G.modulus() 20 """ return self._modulus def ngens(self): """ Returns the number of generators of self. EXAMPLES:: sage: G = DirichletGroup(20) sage: G.ngens() 2 """ return len(self.gens()) @cached_method def order(self): """ Return the number of elements of self. This is the same as len(self). EXAMPLES:: sage: DirichletGroup(20).order() 8 sage: DirichletGroup(37).order() 36 """ ord = rings.Integer(1) for g in self.gens(): ord *= int(g.order()) return ord def random_element(self): """ Return a random element of self. The element is computed by multiplying a random power of each generator together, where the power is between 0 and the order of the generator minus 1, inclusive. EXAMPLES:: sage: DirichletGroup(37).random_element() Dirichlet character modulo 37 of conductor 37 mapping 2 |--> zeta36^4 sage: DirichletGroup(20).random_element() Dirichlet character modulo 20 of conductor 4 mapping 11 |--> -1, 17 |--> 1 sage: DirichletGroup(60).random_element() Dirichlet character modulo 60 of conductor 3 mapping 31 |--> 1, 41 |--> -1, 37 |--> 1 """ e = self(1) for i in range(self.ngens()): g = self.gen(i) n = random.randrange(g.order()) e *= g**n return e def unit_gens(self): r""" Returns the minimal generators for the units of `(\ZZ/N\ZZ)^*`, where `N` is the modulus of self. EXAMPLES:: sage: DirichletGroup(37).unit_gens() (2,) sage: DirichletGroup(20).unit_gens() (11, 17) sage: DirichletGroup(60).unit_gens() (31, 41, 37) sage: DirichletGroup(20,QQ).unit_gens() (11, 17) """ return self._integers.unit_gens() @cached_method def zeta(self): """ Return the chosen root of unity in the base ring. EXAMPLES:: sage: DirichletGroup(37).zeta() zeta36 sage: DirichletGroup(20).zeta() zeta4 sage: DirichletGroup(60).zeta() zeta4 sage: DirichletGroup(60,QQ).zeta() -1 sage: DirichletGroup(60, GF(25,'a')).zeta() 2 """ zeta = self._zeta if zeta is None: R = self.base_ring() e = self._integers.unit_group_exponent() for d in reversed(e.divisors()): try: zeta = R.zeta(d) break except ValueError: pass self.zeta_order.set_cache(d) return zeta @cached_method def zeta_order(self): """ Return the order of the chosen root of unity in the base ring. EXAMPLES:: sage: DirichletGroup(20).zeta_order() 4 sage: DirichletGroup(60).zeta_order() 4 sage: DirichletGroup(60, GF(25,'a')).zeta_order() 4 sage: DirichletGroup(19).zeta_order() 18 """ order = self._zeta_order if order is None: order = self.zeta().multiplicative_order() return order

src/biotite/file.py

danijoo/biotite

308

<reponame>danijoo/biotite # This source code is part of the Biotite package and is distributed # under the 3-Clause BSD License. Please see 'LICENSE.rst' for further # information. __name__ = "biotite" __author__ = "<NAME>" __all__ = ["File", "TextFile", "InvalidFileError"] import abc import io import warnings from .copyable import Copyable import copy class File(Copyable, metaclass=abc.ABCMeta): """ Base class for all file classes. The constructor creates an empty file, that can be filled with data using the class specific setter methods. Conversely, the class method :func:`read()` reads a file from disk (or a file-like object from other sources). In order to write the instance content into a file the :func:`write()` method is used. """ def __init__(self): # Support for deprecated instance method 'read()': # When creating an instance, the 'read()' class method is # replaced by the instance method, so that subsequent # 'read()' calls are delegated to the instance method self.read = self._deprecated_read @classmethod @abc.abstractmethod def read(cls, file): """ Parse a file (or file-like object). Parameters ---------- file : file-like object or str The file to be read. Alternatively a file path can be supplied. Returns ------- file_object : File An instance from the respective :class:`File` subclass representing the parsed file. """ pass def _deprecated_read(self, file, *args, **kwargs): """ Support for deprecated instance method :func:`read()`. Internally this calls the :func:`read()` class method and replaces the data in `self` with the data from the newly created :class:`File` object """ warnings.warn( "Instance method 'read()' is deprecated, " "use class method instead", DeprecationWarning ) cls = type(self) new_file = cls.read(file, *args, **kwargs) self.__dict__.update(new_file.__dict__) @abc.abstractmethod def write(self, file): """ Write the contents of this :class:`File` object into a file. Parameters ---------- file_name : file-like object or str The file to be written to. Alternatively a file path can be supplied. """ pass class TextFile(File, metaclass=abc.ABCMeta): """ Base class for all line based text files. When reading a file, the text content is saved as list of strings, one for each line. When writing a file, this list is written into the file. Attributes ---------- lines : list List of string representing the lines in the text file. PROTECTED: Do not modify from outside. """ def __init__(self): super().__init__() self.lines = [] @classmethod def read(cls, file, *args, **kwargs): # File name if isinstance(file, str): with open(file, "r") as f: lines = f.read().splitlines() # File object else: if not is_text(file): raise TypeError("A file opened in 'text' mode is required") lines = file.read().splitlines() file_object = cls(*args, **kwargs) file_object.lines = lines return file_object @staticmethod def read_iter(file): """ Create an iterator over each line of the given text file. Parameters ---------- file : file-like object or str The file to be read. Alternatively a file path can be supplied. Yields ------ line : str The current line in the file. """ # File name if isinstance(file, str): with open(file, "r") as f: while True: line = f.readline() if not line: break yield line # File object else: if not is_text(file): raise TypeError("A file opened in 'text' mode is required") while True: line = file.readline() if not line: break yield line def write(self, file): """ Write the contents of this object into a file (or file-like object). Parameters ---------- file_name : file-like object or str The file to be written to. Alternatively a file path can be supplied. """ if isinstance(file, str): with open(file, "w") as f: f.write("\n".join(self.lines) + "\n") else: if not is_text(file): raise TypeError("A file opened in 'text' mode is required") file.write("\n".join(self.lines) + "\n") def __copy_fill__(self, clone): super().__copy_fill__(clone) clone.lines = copy.copy(self.lines) def __str__(self): return("\n".join(self.lines)) class InvalidFileError(Exception): """ Indicates that the file is not suitable for the requested action, either because the file does not contain the required data or because the file is malformed. """ pass def wrap_string(text, width): """ A much simpler and hence much more efficient version of `textwrap.wrap()`. This function simply wraps the given `text` after `width` characters, ignoring sentences, whitespaces, etc. """ lines = [] for i in range(0, len(text), width): lines.append(text[i : i+width]) return lines def is_binary(file): if isinstance(file, io.BufferedIOBase): return True # for file wrappers, e.g. 'TemporaryFile' elif hasattr(file, "file") and isinstance(file.file, io.BufferedIOBase): return True else: return False def is_text(file): if isinstance(file, io.TextIOBase): return True # for file wrappers, e.g. 'TemporaryFile' elif hasattr(file, "file") and isinstance(file.file, io.TextIOBase): return True else: return False

src/cms/views/push_notifications/push_notification_sender.py

mckinly/cms-django

309

""" Module for sending Push Notifications """ import logging import requests from django.conf import settings from ...models import PushNotificationTranslation from ...models import Region from ...constants import push_notifications as pnt_const logger = logging.getLogger(__name__) # pylint: disable=too-few-public-methods class PushNotificationSender: """ Sends push notifications via FCM HTTP API. Definition: https://firebase.google.com/docs/cloud-messaging/http-server-ref#downstream-http-messages-json """ fcm_url = "https://fcm.googleapis.com/fcm/send" def __init__(self, push_notification): """ Load relevant push notification translations and prepare content for sending :param push_notification: the push notification that should be sent :type push_notification: ~cms.models.push_notifications.push_notification.PushNotification """ self.push_notification = push_notification self.prepared_pnts = [] self.primary_pnt = PushNotificationTranslation.objects.get( push_notification=push_notification, language=push_notification.region.default_language, ) if len(self.primary_pnt.title) > 0: self.prepared_pnts.append(self.primary_pnt) self.load_secondary_pnts() self.auth_key = self.get_auth_key() def load_secondary_pnts(self): """ Load push notification translations in other languages """ secondary_pnts = PushNotificationTranslation.objects.filter( push_notification=self.push_notification ).exclude(id=self.primary_pnt.id) for secondary_pnt in secondary_pnts: if ( secondary_pnt.title == "" and pnt_const.USE_MAIN_LANGUAGE == self.push_notification.mode ): secondary_pnt.title = self.primary_pnt.title secondary_pnt.text = self.primary_pnt.text self.prepared_pnts.append(secondary_pnt) if len(secondary_pnt.title) > 0: self.prepared_pnts.append(secondary_pnt) def is_valid(self): """ Check if all data for sending push notifications is available :return: all prepared push notification translations are valid :rtype: bool """ if self.auth_key is None: return False for pnt in self.prepared_pnts: if not pnt.title: logger.debug("%r has no title", pnt) return False return True @staticmethod def get_auth_key(): """ Get FCM API auth key :return: FCM API auth key :rtype: str """ fcm_auth_config_key = "fcm_auth_key" auth_key = settings.FCM_KEY if auth_key.exists(): logger.debug("Got fcm_auth_key from database") return auth_key.first().value logger.warning( "Could not get %r from configuration database", fcm_auth_config_key ) return None def send_pn(self, pnt): """ Send single push notification translation :param pnt: the prepared push notification translation to be sent :type pnt: ~cms.models.push_notifications.push_notification_translation.PushNotificationTranslation :return: Response of the :mod:`requests` library :rtype: ~requests.Response """ if settings.DEBUG: region_slug = Region.objects.get( id=settings.TEST_BLOG_ID ).slug # Testumgebung - prevent sending PNs to actual users in development else: region_slug = self.push_notification.region.slug payload = { "to": f"/topics/{region_slug}-{pnt.language.slug}-{self.push_notification.channel}", "notification": {"title": pnt.title, "body": pnt.text}, "data": { "lanCode": pnt.language.slug, "city": self.push_notification.region.slug, }, } headers = {"Authorization": f"key={self.auth_key}"} return requests.post(self.fcm_url, json=payload, headers=headers) # pylint: disable=too-many-arguments def send_all(self): """ Send all prepared push notification translations :return: Success status :rtype: bool """ status = True for pnt in self.prepared_pnts: res = self.send_pn(pnt) if res.status_code == 200: logger.info("%r sent, FCM id: %r", pnt, res.json()["message_id"]) else: status = False logger.warning( "Received invalid response from FCM for %r, status: %r, body: %r", pnt, res.status_code, res.text, ) return status

tests/functional/index/create/test_03.py

reevespaul/firebird-qa

310

#coding:utf-8 # # id: functional.index.create.03 # title: CREATE ASC INDEX # decription: CREATE ASC INDEX # # Dependencies: # CREATE DATABASE # CREATE TABLE # SHOW INDEX # tracker_id: # min_versions: [] # versions: 1.0 # qmid: functional.index.create.create_index_03 import pytest from firebird.qa import db_factory, isql_act, Action # version: 1.0 # resources: None substitutions_1 = [] init_script_1 = """CREATE TABLE t( a INTEGER); commit;""" db_1 = db_factory(sql_dialect=3, init=init_script_1) test_script_1 = """CREATE ASC INDEX test ON t(a); SHOW INDEX test;""" act_1 = isql_act('db_1', test_script_1, substitutions=substitutions_1) expected_stdout_1 = """TEST INDEX ON T(A)""" @pytest.mark.version('>=1.0') def test_1(act_1: Action): act_1.expected_stdout = expected_stdout_1 act_1.execute() assert act_1.clean_expected_stdout == act_1.clean_stdout

app/logic/httpcommon/Page.py

imvu/bluesteel

311

<filename>app/logic/httpcommon/Page.py<gh_stars>1-10 """ Page object file """ class Page(): """ Page object, it contains information about the pare we are refering, index, items per page, etc. """ page_index = 0 items_per_page = 0 def __init__(self, items_per_page, page_index): """ Creates the page """ self.page_index = int(page_index) self.items_per_page = int(items_per_page)

models/AI-Model-Zoo/VAI-1.3-Model-Zoo-Code/PyTorch/pt_personreid-res18_market1501_176_80_1.1G_1.3/code/core/data_manager.py

guochunhe/Vitis-AI

312

# Copyright 2019 Xilinx Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function, absolute_import import glob import re from os import path as osp from .market1501 import Market1501 __factory = { 'market1501': Market1501 } def get_names(): return list(__factory.keys()) def init_dataset(name, *args, **kwargs): if name not in __factory.keys(): raise KeyError("Unknown datasets: {}".format(name)) return __factory[name](*args, **kwargs)

PyBank/.ipynb_checkpoints/Pymain-checkpoint.py

yash5OG/PythonChallengeW3-Y5

313

{ "cells": [ { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": [ "# Import libraries\n", "import os, csv" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": [ "#variables for the script\n", "months = [] #list of months\n", "pl =[] #list of monthly PL\n", "pl_changes = [] #list of P&L Changes\n", "n_months = 0 #count of months\n", "pl_total = 0 #total of P&L\n", "plc = 0 #variable to track PL changes\n", "avg_pl_change = 0 #average of changes in PL\n", "maxpl = 0 #maximum increase in profits\n", "minpl = 0 #maximum decrease in losses\n", "max_i = 0 #index for max pl\n", "min_i = 0 #index for min pl\n", "\n", "#read the resource file\n", "bankcsv = os.path.join(\".\", \"Resources\", \"budget_data.csv\") #set path\n", "\n", "\n", "#read file\n", "with open(bankcsv, 'r') as csv_file:\n", " csv_reader = csv.reader(csv_file,delimiter=\",\")\n", " header = next(csv_reader)\n", " \n", " #for loop to update the counters and lists\n", " for row in csv_reader:\n", " n_months += 1\n", " pl_total += int(row[1])\n", " pl.append(row[1])\n", " months.append(row[0])" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "# loop to track the PL change values\n", "pl_changes = [] \n", "plc = int(pl[0])\n", "for i in range(1, len(pl)):\n", " pl_changes.append(int(pl[i]) - plc)\n", " plc = int(pl[i])\n", " i += 1\n", "#print(pl_changes)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "#calculate the average PL Changes, max and min\n", "avg_pl_change = sum(pl_changes) / len(pl_changes)\n", "maxpl = max(pl_changes)\n", "minpl = min(pl_changes)\n", "#print(avg_pl_change, maxpl, minpl)\n", "#print(pl_changes.index(maxpl))\n", "#print(len(pl_changes))" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Financial Analysis\n", "---------------------------------------------------------------------\n", "Total Months: 86\n", "Total: $38382578\n", "Average Change: $-2315.12\n", "Greatest Increase in Profits: Feb-2012 ($1926159)\n", "Greatest Decrease in Profits: Sep-2013 ($-2196167)\n" ] } ], "source": [ "#find dates for max and min PL changes\n", "max_i = pl_changes.index(maxpl) +1 #adding +1 since the changes are calculated one row above\n", "min_i = pl_changes.index(minpl) +1\n", "\n", "maxmonth = months[max_i]\n", "minmonth = months[min_i]\n", "\n", "#print output to the terminal\n", "\n", "print(\"Financial Analysis\")\n", "print(\"-\"*69)\n", "print(f\"Total Months: {n_months}\")\n", "print(f\"Total: ${round(pl_total,2)}\")\n", "print(f\"Average Change: ${round(avg_pl_change,2)}\")\n", "print(f\"Greatest Increase in Profits: {maxmonth} (${maxpl})\")\n", "print(f\"Greatest Decrease in Profits: {minmonth} (${minpl})\")\n" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [], "source": [ "# write summary to txt file\n", "output = os.path.join(\".\",\"Analysis\", \"summary.txt\")\n", "\n", "# use \"\\n\" to create a new line\n", "with open(output, 'w') as output:\n", " output.write(\"Financial Analysis\\n\")\n", " output.write(\"-\"*69 + \"\\n\")\n", " output.write(f\"Total Months: {n_months}\\n\")\n", " output.write(f\"Total: ${round(pl_total,2)}\\n\")\n", " output.write(f\"Average Change: ${round(avg_pl_change,2)}\\n\")\n", " output.write(f\"Greatest Increase in Profits: {maxmonth} (${maxpl})\\n\")\n", " output.write(f\"Greatest Decrease in Profits: {minmonth} (${minpl})\\n\")" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }

xlib/api/win32/oleaut32/oleaut32.py

jkennedyvz/DeepFaceLive

314

<reponame>jkennedyvz/DeepFaceLive<gh_stars>0 from ctypes import POINTER, Structure from ..wintypes import VARIANT, dll_import @dll_import('OleAut32') def VariantInit( pvarg : POINTER(VARIANT) ) -> None: ...

azure-devops/azext_devops/vstsCompressed/service_hooks/v4_0/models/__init__.py

vijayraavi/azure-devops-cli-extension

315

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- # Generated file, DO NOT EDIT # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------------------------- from .models import Consumer from .models import ConsumerAction from .models import Event from .models import EventTypeDescriptor from .models import ExternalConfigurationDescriptor from .models import FormattedEventMessage from .models import IdentityRef from .models import InputDescriptor from .models import InputFilter from .models import InputFilterCondition from .models import InputValidation from .models import InputValue from .models import InputValues from .models import InputValuesError from .models import InputValuesQuery from .models import Notification from .models import NotificationDetails from .models import NotificationResultsSummaryDetail from .models import NotificationsQuery from .models import NotificationSummary from .models import Publisher from .models import PublisherEvent from .models import PublishersQuery from .models import ReferenceLinks from .models import ResourceContainer from .models import SessionToken from .models import Subscription from .models import SubscriptionsQuery from .models import VersionedResource __all__ = [ 'Consumer', 'ConsumerAction', 'Event', 'EventTypeDescriptor', 'ExternalConfigurationDescriptor', 'FormattedEventMessage', 'IdentityRef', 'InputDescriptor', 'InputFilter', 'InputFilterCondition', 'InputValidation', 'InputValue', 'InputValues', 'InputValuesError', 'InputValuesQuery', 'Notification', 'NotificationDetails', 'NotificationResultsSummaryDetail', 'NotificationsQuery', 'NotificationSummary', 'Publisher', 'PublisherEvent', 'PublishersQuery', 'ReferenceLinks', 'ResourceContainer', 'SessionToken', 'Subscription', 'SubscriptionsQuery', 'VersionedResource', ]

pizdyuk/pzd_logging.py

DeathAdder1999/Pizdyuk

316

<filename>pizdyuk/pzd_logging.py<gh_stars>1-10 import datetime as date from pzd_utils import datetime_to_str class PizdyukLogger: __logger = None def __init__(self): global __logger if self.__logger: raise RuntimeError("Logger instance already exists") @staticmethod def get_logger(): global __logger if not PizdyukLogger._PizdyukLogger__logger: PizdyukLogger._PizdyukLogger__logger = PizdyukLogger() return PizdyukLogger._PizdyukLogger__logger def log_info(self, msg): self.__log(msg, "INFO") def log_warning(self, warning): self.__log(warning, "WARNING") def log_error(self, error): self.__log(error, "ERROR") def log_fatal(self, fatal): self.__log(fatal, "FATAL") def __log(self, msg, lvl): date_str = datetime_to_str(date.datetime.now()) log = "[{0}] [{1}] {2}".format(lvl, date_str, msg) print(log)

beta_reconstruction/crystal_relations.py

LightForm-group/beta-reconstruction

317

import numpy as np from defdap.quat import Quat hex_syms = Quat.symEqv("hexagonal") # subset of hexagonal symmetries that give unique orientations when the # Burgers transformation is applied unq_hex_syms = [ hex_syms[0], hex_syms[5], hex_syms[4], hex_syms[2], hex_syms[10], hex_syms[11] ] cubic_syms = Quat.symEqv("cubic") # subset of cubic symmetries that give unique orientations when the # Burgers transformation is applied unq_cub_syms = [ cubic_syms[0], cubic_syms[7], cubic_syms[9], cubic_syms[1], cubic_syms[22], cubic_syms[16], cubic_syms[12], cubic_syms[15], cubic_syms[4], cubic_syms[8], cubic_syms[21], cubic_syms[20] ] # HCP -> BCC burg_eulers = np.array([135, 90, 354.74]) * np.pi / 180 burg_trans = Quat.fromEulerAngles(*burg_eulers).conjugate

a2.py

Changhong-Jiang/test

318

print('222')

app/api/v1/views/auth_views.py

emdeechege/Questionaire-API

319

<filename>app/api/v1/views/auth_views.py from flask import jsonify, Blueprint, request, json, make_response from werkzeug.security import generate_password_hash, check_password_hash from datetime import datetime from ..utils.validators import Validation from ..models.auth_models import Users v1_auth_blueprint = Blueprint('auth', __name__, url_prefix='/api/v1') USER = Users() VALIDATOR = Validation() @v1_auth_blueprint.route('/signup', methods=['POST']) def signup(): """View that controls creation of new users""" try: data = request.get_json() except: return jsonify({ "status": 400, "message": "Invalid input" }), 400 firstname = data.get('firstname') lastname = data.get('lastname') othername = data.get('othername') email = data.get('email') phone_number = data.get('phone_number') username = data.get('username') is_admin = data.get('is_admin') password = data.get('password') if not firstname or not firstname.split(): return make_response(jsonify({ "status": 400, "message": "Firstname is required" })), 400 if not lastname or not lastname.split(): return make_response(jsonify({ "status": 400, "message": "Lastname is required" })), 400 if not email or not email.split(): return make_response(jsonify({ "status": 400, "message": "Email is required" })), 400 if not phone_number: return make_response(jsonify({ "status": 400, "message": "Phone number is required" })), 400 if not username or not username.split(): return make_response(jsonify({ "status": 400, "message": "Username is required" })), 400 if not password or not password.split(): return make_response(jsonify({ "status": 400, "message": "Password is required" })), 400 if not VALIDATOR.validate_phone_number(phone_number): return jsonify({ "status": 400, "message": "Please input valid phone number" }), 400 if VALIDATOR.validate_password(password): return jsonify({ "status": 400, "message": "Password not valid" }), 400 if not VALIDATOR.validate_email(email): return jsonify({ "status": 400, "message": "Invalid email" }), 400 if VALIDATOR.username_exists(username): return jsonify({ "status": 400, "message": "Username exists" }), 400 if VALIDATOR.email_exists(email): return jsonify({ "status": 400, "message": "Email exists" }), 400 password = generate_password_hash( password, method='pbkdf2:sha256', salt_length=8) res = USER.signup( firstname, lastname, othername, email, phone_number, username, is_admin, password) return jsonify({ "status": 201, "data": [{ "firstname": firstname, "lastname": lastname, "othername": othername, "email": email, "phone_number": phone_number, "username": username, "is_admin": is_admin }] }), 201 @v1_auth_blueprint.route('/login', methods=['POST']) def login(): """ A view to control users login """ try: data = request.get_json() except: return make_response(jsonify({ "status": 400, "message": "Wrong input" })), 400 username = data.get('username') password = data.get('password') if not username: return make_response(jsonify({ "status": 400, "message": "Username is required" })), 400 if not password: return make_response(jsonify({ "status": 400, "message": "Password is required" })), 400 if not VALIDATOR.username_exists(username): return jsonify({ "status": 404, "message": "User does not exist" }), 404 auth_token = user.generate_auth_token(username) return make_response(jsonify({ "status": 200, "message": 'Logged in successfuly', "token": auth_token })), 200

pint/testsuite/test_definitions.py

s-avni/pint

320

# -*- coding: utf-8 -*- from __future__ import division, unicode_literals, print_function, absolute_import from pint.util import (UnitsContainer) from pint.converters import (ScaleConverter, OffsetConverter) from pint.definitions import (Definition, PrefixDefinition, UnitDefinition, DimensionDefinition, AliasDefinition) from pint.testsuite import BaseTestCase class TestDefinition(BaseTestCase): def test_invalid(self): self.assertRaises(ValueError, Definition.from_string, 'x = [time] * meter') self.assertRaises(ValueError, Definition.from_string, '[x] = [time] * meter') def test_prefix_definition(self): for definition in ('m- = 1e-3', 'm- = 10**-3', 'm- = 0.001'): x = Definition.from_string(definition) self.assertIsInstance(x, PrefixDefinition) self.assertEqual(x.name, 'm') self.assertEqual(x.aliases, ()) self.assertEqual(x.converter.to_reference(1000), 1) self.assertEqual(x.converter.from_reference(0.001), 1) self.assertEqual(str(x), 'm') x = Definition.from_string('kilo- = 1e-3 = k-') self.assertIsInstance(x, PrefixDefinition) self.assertEqual(x.name, 'kilo') self.assertEqual(x.aliases, ()) self.assertEqual(x.symbol, 'k') self.assertEqual(x.converter.to_reference(1000), 1) self.assertEqual(x.converter.from_reference(.001), 1) x = Definition.from_string('kilo- = 1e-3 = k- = anotherk-') self.assertIsInstance(x, PrefixDefinition) self.assertEqual(x.name, 'kilo') self.assertEqual(x.aliases, ('anotherk', )) self.assertEqual(x.symbol, 'k') self.assertEqual(x.converter.to_reference(1000), 1) self.assertEqual(x.converter.from_reference(.001), 1) def test_baseunit_definition(self): x = Definition.from_string('meter = [length]') self.assertIsInstance(x, UnitDefinition) self.assertTrue(x.is_base) self.assertEqual(x.reference, UnitsContainer({'[length]': 1})) def test_unit_definition(self): x = Definition.from_string('coulomb = ampere * second') self.assertIsInstance(x, UnitDefinition) self.assertFalse(x.is_base) self.assertIsInstance(x.converter, ScaleConverter) self.assertEqual(x.converter.scale, 1) self.assertEqual(x.reference, UnitsContainer(ampere=1, second=1)) x = Definition.from_string('faraday = 96485.3399 * coulomb') self.assertIsInstance(x, UnitDefinition) self.assertFalse(x.is_base) self.assertIsInstance(x.converter, ScaleConverter) self.assertEqual(x.converter.scale, 96485.3399) self.assertEqual(x.reference, UnitsContainer(coulomb=1)) x = Definition.from_string('degF = 9 / 5 * kelvin; offset: 255.372222') self.assertIsInstance(x, UnitDefinition) self.assertFalse(x.is_base) self.assertIsInstance(x.converter, OffsetConverter) self.assertEqual(x.converter.scale, 9/5) self.assertEqual(x.converter.offset, 255.372222) self.assertEqual(x.reference, UnitsContainer(kelvin=1)) x = Definition.from_string('turn = 6.28 * radian = _ = revolution = = cycle = _') self.assertIsInstance(x, UnitDefinition) self.assertEqual(x.name, 'turn') self.assertEqual(x.aliases, ('revolution', 'cycle')) self.assertEqual(x.symbol, 'turn') self.assertFalse(x.is_base) self.assertIsInstance(x.converter, ScaleConverter) self.assertEqual(x.converter.scale, 6.28) self.assertEqual(x.reference, UnitsContainer(radian=1)) def test_dimension_definition(self): x = DimensionDefinition('[time]', '', (), converter='') self.assertTrue(x.is_base) self.assertEqual(x.name, '[time]') x = Definition.from_string('[speed] = [length]/[time]') self.assertIsInstance(x, DimensionDefinition) self.assertEqual(x.reference, UnitsContainer({'[length]': 1, '[time]': -1})) def test_alias_definition(self): x = Definition.from_string("@alias meter = metro = metr") self.assertIsInstance(x, AliasDefinition) self.assertEqual(x.name, "meter") self.assertEqual(x.aliases, ("metro", "metr"))

electrum/dnssec.py

Jesusown/electrum

321

#!/usr/bin/env python # # Electrum - lightweight Bitcoin client # Copyright (C) 2015 <NAME> # # Permission is hereby granted, free of charge, to any person # obtaining a copy of this software and associated documentation files # (the "Software"), to deal in the Software without restriction, # including without limitation the rights to use, copy, modify, merge, # publish, distribute, sublicense, and/or sell copies of the Software, # and to permit persons to whom the Software is furnished to do so, # subject to the following conditions: # # The above copyright notice and this permission notice shall be # included in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, # EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND # NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS # BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN # ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN # CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # Check DNSSEC trust chain. # Todo: verify expiration dates # # Based on # http://backreference.org/2010/11/17/dnssec-verification-with-dig/ # https://github.com/rthalley/dnspython/blob/master/tests/test_dnssec.py import dns import dns.name import dns.query import dns.dnssec import dns.message import dns.resolver import dns.rdatatype import dns.rdtypes.ANY.NS import dns.rdtypes.ANY.CNAME import dns.rdtypes.ANY.DLV import dns.rdtypes.ANY.DNSKEY import dns.rdtypes.ANY.DS import dns.rdtypes.ANY.NSEC import dns.rdtypes.ANY.NSEC3 import dns.rdtypes.ANY.NSEC3PARAM import dns.rdtypes.ANY.RRSIG import dns.rdtypes.ANY.SOA import dns.rdtypes.ANY.TXT import dns.rdtypes.IN.A import dns.rdtypes.IN.AAAA from .logging import get_logger _logger = get_logger(__name__) # hard-coded trust anchors (root KSKs) trust_anchors = [ # KSK-2017: dns.rrset.from_text('.', 1 , 'IN', 'DNSKEY', '<KEY>), # KSK-2010: dns.rrset.from_text('.', 15202, 'IN', 'DNSKEY', '257 3 8 AwEAAagAIKlVZrpC6Ia7gEzahOR+9W29euxhJhVVLOyQbSEW0O8gcCjF FVQUTf6v58fLjwBd0YI0EzrAcQqBGCzh/RStIoO8g0NfnfL2MTJRkxoX bfDaUeVPQuYEhg37NZWAJQ9VnMVDxP/VHL496M/QZxkjf5/Efucp2gaD X6RS6CXpoY68LsvPVjR0ZSwzz1apAzvN9dlzEheX7ICJBBtuA6G3LQpz W<KEY>S Qageu+ipAdTTJ25AsRTAoub8ONGcLmqrAmRLKBP1dfwhYB4N7knNnulq QxA+Uk1ihz0='), ] def _check_query(ns, sub, _type, keys): q = dns.message.make_query(sub, _type, want_dnssec=True) response = dns.query.tcp(q, ns, timeout=5) assert response.rcode() == 0, 'No answer' answer = response.answer assert len(answer) != 0, ('No DNS record found', sub, _type) assert len(answer) != 1, ('No DNSSEC record found', sub, _type) if answer[0].rdtype == dns.rdatatype.RRSIG: rrsig, rrset = answer elif answer[1].rdtype == dns.rdatatype.RRSIG: rrset, rrsig = answer else: raise Exception('No signature set in record') if keys is None: keys = {dns.name.from_text(sub):rrset} dns.dnssec.validate(rrset, rrsig, keys) return rrset def _get_and_validate(ns, url, _type): # get trusted root key root_rrset = None for dnskey_rr in trust_anchors: try: # Check if there is a valid signature for the root dnskey root_rrset = _check_query(ns, '', dns.rdatatype.DNSKEY, {dns.name.root: dnskey_rr}) break except dns.dnssec.ValidationFailure: # It's OK as long as one key validates continue if not root_rrset: raise dns.dnssec.ValidationFailure('None of the trust anchors found in DNS') keys = {dns.name.root: root_rrset} # top-down verification parts = url.split('.') for i in range(len(parts), 0, -1): sub = '.'.join(parts[i-1:]) name = dns.name.from_text(sub) # If server is authoritative, don't fetch DNSKEY query = dns.message.make_query(sub, dns.rdatatype.NS) response = dns.query.udp(query, ns, 3) assert response.rcode() == dns.rcode.NOERROR, "query error" rrset = response.authority[0] if len(response.authority) > 0 else response.answer[0] rr = rrset[0] if rr.rdtype == dns.rdatatype.SOA: continue # get DNSKEY (self-signed) rrset = _check_query(ns, sub, dns.rdatatype.DNSKEY, None) # get DS (signed by parent) ds_rrset = _check_query(ns, sub, dns.rdatatype.DS, keys) # verify that a signed DS validates DNSKEY for ds in ds_rrset: for dnskey in rrset: htype = 'SHA256' if ds.digest_type == 2 else 'SHA1' good_ds = dns.dnssec.make_ds(name, dnskey, htype) if ds == good_ds: break else: continue break else: raise Exception("DS does not match DNSKEY") # set key for next iteration keys = {name: rrset} # get TXT record (signed by zone) rrset = _check_query(ns, url, _type, keys) return rrset def query(url, rtype): # 8.8.8.8 is Google's public DNS server nameservers = ['8.8.8.8'] ns = nameservers[0] try: out = _get_and_validate(ns, url, rtype) validated = True except Exception as e: _logger.info(f"DNSSEC error: {repr(e)}") out = dns.resolver.resolve(url, rtype) validated = False return out, validated

specs/d3d11.py

ds-hwang/apitrace

322

########################################################################## # # Copyright 2012 <NAME> # All Rights Reserved. # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. # ##########################################################################/ from dxgi import * from d3dcommon import * from d3d11sdklayers import * HRESULT = MAKE_HRESULT([ "D3D11_ERROR_FILE_NOT_FOUND", "D3D11_ERROR_TOO_MANY_UNIQUE_STATE_OBJECTS", "D3D11_ERROR_TOO_MANY_UNIQUE_VIEW_OBJECTS", "D3D11_ERROR_DEFERRED_CONTEXT_MAP_WITHOUT_INITIAL_DISCARD", "D3DERR_INVALIDCALL", "D3DERR_WASSTILLDRAWING", ]) ID3D11DepthStencilState = Interface("ID3D11DepthStencilState", ID3D11DeviceChild) ID3D11BlendState = Interface("ID3D11BlendState", ID3D11DeviceChild) ID3D11RasterizerState = Interface("ID3D11RasterizerState", ID3D11DeviceChild) ID3D11Resource = Interface("ID3D11Resource", ID3D11DeviceChild) ID3D11Buffer = Interface("ID3D11Buffer", ID3D11Resource) ID3D11Texture1D = Interface("ID3D11Texture1D", ID3D11Resource) ID3D11Texture2D = Interface("ID3D11Texture2D", ID3D11Resource) ID3D11Texture3D = Interface("ID3D11Texture3D", ID3D11Resource) ID3D11View = Interface("ID3D11View", ID3D11DeviceChild) ID3D11ShaderResourceView = Interface("ID3D11ShaderResourceView", ID3D11View) ID3D11RenderTargetView = Interface("ID3D11RenderTargetView", ID3D11View) ID3D11DepthStencilView = Interface("ID3D11DepthStencilView", ID3D11View) ID3D11UnorderedAccessView = Interface("ID3D11UnorderedAccessView", ID3D11View) ID3D11VertexShader = Interface("ID3D11VertexShader", ID3D11DeviceChild) ID3D11HullShader = Interface("ID3D11HullShader", ID3D11DeviceChild) ID3D11DomainShader = Interface("ID3D11DomainShader", ID3D11DeviceChild) ID3D11GeometryShader = Interface("ID3D11GeometryShader", ID3D11DeviceChild) ID3D11PixelShader = Interface("ID3D11PixelShader", ID3D11DeviceChild) ID3D11ComputeShader = Interface("ID3D11ComputeShader", ID3D11DeviceChild) ID3D11InputLayout = Interface("ID3D11InputLayout", ID3D11DeviceChild) ID3D11SamplerState = Interface("ID3D11SamplerState", ID3D11DeviceChild) ID3D11Asynchronous = Interface("ID3D11Asynchronous", ID3D11DeviceChild) ID3D11Query = Interface("ID3D11Query", ID3D11Asynchronous) ID3D11Predicate = Interface("ID3D11Predicate", ID3D11Query) ID3D11Counter = Interface("ID3D11Counter", ID3D11Asynchronous) ID3D11ClassInstance = Interface("ID3D11ClassInstance", ID3D11DeviceChild) ID3D11ClassLinkage = Interface("ID3D11ClassLinkage", ID3D11DeviceChild) ID3D11CommandList = Interface("ID3D11CommandList", ID3D11DeviceChild) ID3D11Device = Interface("ID3D11Device", IUnknown) D3D11_INPUT_CLASSIFICATION = Enum("D3D11_INPUT_CLASSIFICATION", [ "D3D11_INPUT_PER_VERTEX_DATA", "D3D11_INPUT_PER_INSTANCE_DATA", ]) D3D11_INPUT_ELEMENT_ALIGNED_BYTE_OFFSET = FakeEnum(UINT, [ "D3D11_APPEND_ALIGNED_ELEMENT", ]) D3D11_INPUT_ELEMENT_DESC = Struct("D3D11_INPUT_ELEMENT_DESC", [ (LPCSTR, "SemanticName"), (UINT, "SemanticIndex"), (DXGI_FORMAT, "Format"), (UINT, "InputSlot"), (D3D11_INPUT_ELEMENT_ALIGNED_BYTE_OFFSET, "AlignedByteOffset"), (D3D11_INPUT_CLASSIFICATION, "InputSlotClass"), (UINT, "InstanceDataStepRate"), ]) D3D11_FILL_MODE = Enum("D3D11_FILL_MODE", [ "D3D11_FILL_WIREFRAME", "D3D11_FILL_SOLID", ]) D3D11_PRIMITIVE_TOPOLOGY = Enum("D3D11_PRIMITIVE_TOPOLOGY", [ "D3D11_PRIMITIVE_TOPOLOGY_UNDEFINED", "D3D11_PRIMITIVE_TOPOLOGY_POINTLIST", "D3D11_PRIMITIVE_TOPOLOGY_LINELIST", "D3D11_PRIMITIVE_TOPOLOGY_LINESTRIP", "D3D11_PRIMITIVE_TOPOLOGY_TRIANGLELIST", "D3D11_PRIMITIVE_TOPOLOGY_TRIANGLESTRIP", "D3D11_PRIMITIVE_TOPOLOGY_LINELIST_ADJ", "D3D11_PRIMITIVE_TOPOLOGY_LINESTRIP_ADJ", "D3D11_PRIMITIVE_TOPOLOGY_TRIANGLELIST_ADJ", "D3D11_PRIMITIVE_TOPOLOGY_TRIANGLESTRIP_ADJ", "D3D11_PRIMITIVE_TOPOLOGY_1_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_2_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_3_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_4_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_5_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_6_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_7_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_8_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_9_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_10_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_11_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_12_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_13_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_14_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_15_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_16_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_17_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_18_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_19_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_20_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_21_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_22_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_23_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_24_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_25_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_26_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_27_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_28_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_29_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_30_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_31_CONTROL_POINT_PATCHLIST", "D3D11_PRIMITIVE_TOPOLOGY_32_CONTROL_POINT_PATCHLIST", ]) D3D11_PRIMITIVE = Enum("D3D11_PRIMITIVE", [ "D3D11_PRIMITIVE_UNDEFINED", "D3D11_PRIMITIVE_POINT", "D3D11_PRIMITIVE_LINE", "D3D11_PRIMITIVE_TRIANGLE", "D3D11_PRIMITIVE_LINE_ADJ", "D3D11_PRIMITIVE_TRIANGLE_ADJ", "D3D11_PRIMITIVE_1_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_2_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_3_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_4_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_5_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_6_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_7_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_8_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_9_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_10_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_11_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_12_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_13_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_14_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_15_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_16_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_17_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_18_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_19_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_20_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_21_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_22_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_23_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_24_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_25_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_26_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_27_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_28_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_29_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_30_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_31_CONTROL_POINT_PATCH", "D3D11_PRIMITIVE_32_CONTROL_POINT_PATCH", ]) D3D11_CULL_MODE = Enum("D3D11_CULL_MODE", [ "D3D11_CULL_NONE", "D3D11_CULL_FRONT", "D3D11_CULL_BACK", ]) D3D11_SO_DECLARATION_ENTRY = Struct("D3D11_SO_DECLARATION_ENTRY", [ (UINT, "Stream"), (LPCSTR, "SemanticName"), (UINT, "SemanticIndex"), (BYTE, "StartComponent"), (BYTE, "ComponentCount"), (BYTE, "OutputSlot"), ]) D3D11_VIEWPORT = Struct("D3D11_VIEWPORT", [ (FLOAT, "TopLeftX"), (FLOAT, "TopLeftY"), (FLOAT, "Width"), (FLOAT, "Height"), (FLOAT, "MinDepth"), (FLOAT, "MaxDepth"), ]) D3D11_RESOURCE_DIMENSION = Enum("D3D11_RESOURCE_DIMENSION", [ "D3D11_RESOURCE_DIMENSION_UNKNOWN", "D3D11_RESOURCE_DIMENSION_BUFFER", "D3D11_RESOURCE_DIMENSION_TEXTURE1D", "D3D11_RESOURCE_DIMENSION_TEXTURE2D", "D3D11_RESOURCE_DIMENSION_TEXTURE3D", ]) D3D11_SRV_DIMENSION = Enum("D3D11_SRV_DIMENSION", [ "D3D11_SRV_DIMENSION_UNKNOWN", "D3D11_SRV_DIMENSION_BUFFER", "D3D11_SRV_DIMENSION_TEXTURE1D", "D3D11_SRV_DIMENSION_TEXTURE1DARRAY", "D3D11_SRV_DIMENSION_TEXTURE2D", "D3D11_SRV_DIMENSION_TEXTURE2DARRAY", "D3D11_SRV_DIMENSION_TEXTURE2DMS", "D3D11_SRV_DIMENSION_TEXTURE2DMSARRAY", "D3D11_SRV_DIMENSION_TEXTURE3D", "D3D11_SRV_DIMENSION_TEXTURECUBE", "D3D11_SRV_DIMENSION_TEXTURECUBEARRAY", "D3D11_SRV_DIMENSION_BUFFEREX", ]) D3D11_DSV_DIMENSION = Enum("D3D11_DSV_DIMENSION", [ "D3D11_DSV_DIMENSION_UNKNOWN", "D3D11_DSV_DIMENSION_TEXTURE1D", "D3D11_DSV_DIMENSION_TEXTURE1DARRAY", "D3D11_DSV_DIMENSION_TEXTURE2D", "D3D11_DSV_DIMENSION_TEXTURE2DARRAY", "D3D11_DSV_DIMENSION_TEXTURE2DMS", "D3D11_DSV_DIMENSION_TEXTURE2DMSARRAY", ]) D3D11_RTV_DIMENSION = Enum("D3D11_RTV_DIMENSION", [ "D3D11_RTV_DIMENSION_UNKNOWN", "D3D11_RTV_DIMENSION_BUFFER", "D3D11_RTV_DIMENSION_TEXTURE1D", "D3D11_RTV_DIMENSION_TEXTURE1DARRAY", "D3D11_RTV_DIMENSION_TEXTURE2D", "D3D11_RTV_DIMENSION_TEXTURE2DARRAY", "D3D11_RTV_DIMENSION_TEXTURE2DMS", "D3D11_RTV_DIMENSION_TEXTURE2DMSARRAY", "D3D11_RTV_DIMENSION_TEXTURE3D", ]) D3D11_UAV_DIMENSION = Enum("D3D11_UAV_DIMENSION", [ "D3D11_UAV_DIMENSION_UNKNOWN", "D3D11_UAV_DIMENSION_BUFFER", "D3D11_UAV_DIMENSION_TEXTURE1D", "D3D11_UAV_DIMENSION_TEXTURE1DARRAY", "D3D11_UAV_DIMENSION_TEXTURE2D", "D3D11_UAV_DIMENSION_TEXTURE2DARRAY", "D3D11_UAV_DIMENSION_TEXTURE3D", ]) D3D11_USAGE = Enum("D3D11_USAGE", [ "D3D11_USAGE_DEFAULT", "D3D11_USAGE_IMMUTABLE", "D3D11_USAGE_DYNAMIC", "D3D11_USAGE_STAGING", ]) D3D11_BIND_FLAG = Flags(UINT, [ "D3D11_BIND_VERTEX_BUFFER", "D3D11_BIND_INDEX_BUFFER", "D3D11_BIND_CONSTANT_BUFFER", "D3D11_BIND_SHADER_RESOURCE", "D3D11_BIND_STREAM_OUTPUT", "D3D11_BIND_RENDER_TARGET", "D3D11_BIND_DEPTH_STENCIL", "D3D11_BIND_UNORDERED_ACCESS", ]) D3D11_CPU_ACCESS_FLAG = Flags(UINT, [ "D3D11_CPU_ACCESS_WRITE", "D3D11_CPU_ACCESS_READ", ]) D3D11_RESOURCE_MISC_FLAG = Flags(UINT, [ "D3D11_RESOURCE_MISC_GENERATE_MIPS", "D3D11_RESOURCE_MISC_SHARED", "D3D11_RESOURCE_MISC_TEXTURECUBE", "D3D11_RESOURCE_MISC_DRAWINDIRECT_ARGS", "D3D11_RESOURCE_MISC_BUFFER_ALLOW_RAW_VIEWS", "D3D11_RESOURCE_MISC_BUFFER_STRUCTURED", "D3D11_RESOURCE_MISC_RESOURCE_CLAMP", "D3D11_RESOURCE_MISC_SHARED_KEYEDMUTEX", "D3D11_RESOURCE_MISC_GDI_COMPATIBLE", ]) D3D11_MAP = Enum("D3D11_MAP", [ "D3D11_MAP_READ", "D3D11_MAP_WRITE", "D3D11_MAP_READ_WRITE", "D3D11_MAP_WRITE_DISCARD", "D3D11_MAP_WRITE_NO_OVERWRITE", ]) D3D11_MAP_FLAG = Flags(UINT, [ "D3D11_MAP_FLAG_DO_NOT_WAIT", ]) D3D11_RAISE_FLAG = Flags(UINT, [ "D3D11_RAISE_FLAG_DRIVER_INTERNAL_ERROR", ]) D3D11_CLEAR_FLAG = Flags(UINT, [ "D3D11_CLEAR_DEPTH", "D3D11_CLEAR_STENCIL", ]) D3D11_RECT = Alias("D3D11_RECT", RECT) D3D11_BOX = Struct("D3D11_BOX", [ (UINT, "left"), (UINT, "top"), (UINT, "front"), (UINT, "right"), (UINT, "bottom"), (UINT, "back"), ]) ID3D11DeviceChild.methods += [ StdMethod(Void, "GetDevice", [Out(Pointer(ObjPointer(ID3D11Device)), "ppDevice")]), StdMethod(HRESULT, "GetPrivateData", [(REFGUID, "guid"), Out(Pointer(UINT), "pDataSize"), Out(OpaquePointer(Void), "pData")]), StdMethod(HRESULT, "SetPrivateData", [(REFGUID, "guid"), (UINT, "DataSize"), (OpaqueBlob(Const(Void), "DataSize"), "pData")]), StdMethod(HRESULT, "SetPrivateDataInterface", [(REFGUID, "guid"), (OpaquePointer(Const(IUnknown)), "pData")]), ] D3D11_COMPARISON_FUNC = Enum("D3D11_COMPARISON_FUNC", [ "D3D11_COMPARISON_NEVER", "D3D11_COMPARISON_LESS", "D3D11_COMPARISON_EQUAL", "D3D11_COMPARISON_LESS_EQUAL", "D3D11_COMPARISON_GREATER", "D3D11_COMPARISON_NOT_EQUAL", "D3D11_COMPARISON_GREATER_EQUAL", "D3D11_COMPARISON_ALWAYS", ]) D3D11_DEPTH_WRITE_MASK = Enum("D3D11_DEPTH_WRITE_MASK", [ "D3D11_DEPTH_WRITE_MASK_ZERO", "D3D11_DEPTH_WRITE_MASK_ALL", ]) D3D11_STENCIL_OP = Enum("D3D11_STENCIL_OP", [ "D3D11_STENCIL_OP_KEEP", "D3D11_STENCIL_OP_ZERO", "D3D11_STENCIL_OP_REPLACE", "D3D11_STENCIL_OP_INCR_SAT", "D3D11_STENCIL_OP_DECR_SAT", "D3D11_STENCIL_OP_INVERT", "D3D11_STENCIL_OP_INCR", "D3D11_STENCIL_OP_DECR", ]) D3D11_DEPTH_STENCILOP_DESC = Struct("D3D11_DEPTH_STENCILOP_DESC", [ (D3D11_STENCIL_OP, "StencilFailOp"), (D3D11_STENCIL_OP, "StencilDepthFailOp"), (D3D11_STENCIL_OP, "StencilPassOp"), (D3D11_COMPARISON_FUNC, "StencilFunc"), ]) D3D11_DEPTH_STENCIL_DESC = Struct("D3D11_DEPTH_STENCIL_DESC", [ (BOOL, "DepthEnable"), (D3D11_DEPTH_WRITE_MASK, "DepthWriteMask"), (D3D11_COMPARISON_FUNC, "DepthFunc"), (BOOL, "StencilEnable"), (UINT8, "StencilReadMask"), (UINT8, "StencilWriteMask"), (D3D11_DEPTH_STENCILOP_DESC, "FrontFace"), (D3D11_DEPTH_STENCILOP_DESC, "BackFace"), ]) ID3D11DepthStencilState.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_DEPTH_STENCIL_DESC), "pDesc")]), ] D3D11_BLEND = Enum("D3D11_BLEND", [ "D3D11_BLEND_ZERO", "D3D11_BLEND_ONE", "D3D11_BLEND_SRC_COLOR", "D3D11_BLEND_INV_SRC_COLOR", "D3D11_BLEND_SRC_ALPHA", "D3D11_BLEND_INV_SRC_ALPHA", "D3D11_BLEND_DEST_ALPHA", "D3D11_BLEND_INV_DEST_ALPHA", "D3D11_BLEND_DEST_COLOR", "D3D11_BLEND_INV_DEST_COLOR", "D3D11_BLEND_SRC_ALPHA_SAT", "D3D11_BLEND_BLEND_FACTOR", "D3D11_BLEND_INV_BLEND_FACTOR", "D3D11_BLEND_SRC1_COLOR", "D3D11_BLEND_INV_SRC1_COLOR", "D3D11_BLEND_SRC1_ALPHA", "D3D11_BLEND_INV_SRC1_ALPHA", ]) D3D11_BLEND_OP = Enum("D3D11_BLEND_OP", [ "D3D11_BLEND_OP_ADD", "D3D11_BLEND_OP_SUBTRACT", "D3D11_BLEND_OP_REV_SUBTRACT", "D3D11_BLEND_OP_MIN", "D3D11_BLEND_OP_MAX", ]) D3D11_COLOR_WRITE_ENABLE = Enum("D3D11_COLOR_WRITE_ENABLE", [ "D3D11_COLOR_WRITE_ENABLE_ALL", "D3D11_COLOR_WRITE_ENABLE_RED", "D3D11_COLOR_WRITE_ENABLE_GREEN", "D3D11_COLOR_WRITE_ENABLE_BLUE", "D3D11_COLOR_WRITE_ENABLE_ALPHA", ]) D3D11_RENDER_TARGET_BLEND_DESC = Struct("D3D11_RENDER_TARGET_BLEND_DESC", [ (BOOL, "BlendEnable"), (D3D11_BLEND, "SrcBlend"), (D3D11_BLEND, "DestBlend"), (D3D11_BLEND_OP, "BlendOp"), (D3D11_BLEND, "SrcBlendAlpha"), (D3D11_BLEND, "DestBlendAlpha"), (D3D11_BLEND_OP, "BlendOpAlpha"), (UINT8, "RenderTargetWriteMask"), ]) D3D11_BLEND_DESC = Struct("D3D11_BLEND_DESC", [ (BOOL, "AlphaToCoverageEnable"), (BOOL, "IndependentBlendEnable"), (Array(D3D11_RENDER_TARGET_BLEND_DESC, 8), "RenderTarget"), ]) ID3D11BlendState.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_BLEND_DESC), "pDesc")]), ] D3D11_RASTERIZER_DESC = Struct("D3D11_RASTERIZER_DESC", [ (D3D11_FILL_MODE, "FillMode"), (D3D11_CULL_MODE, "CullMode"), (BOOL, "FrontCounterClockwise"), (INT, "DepthBias"), (FLOAT, "DepthBiasClamp"), (FLOAT, "SlopeScaledDepthBias"), (BOOL, "DepthClipEnable"), (BOOL, "ScissorEnable"), (BOOL, "MultisampleEnable"), (BOOL, "AntialiasedLineEnable"), ]) ID3D11RasterizerState.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_RASTERIZER_DESC), "pDesc")]), ] D3D11_SUBRESOURCE_DATA = Struct("D3D11_SUBRESOURCE_DATA", [ (OpaquePointer(Const(Void)), "pSysMem"), (UINT, "SysMemPitch"), (UINT, "SysMemSlicePitch"), ]) D3D11_MAPPED_SUBRESOURCE = Struct("D3D11_MAPPED_SUBRESOURCE", [ (OpaquePointer(Void), "pData"), (UINT, "RowPitch"), (UINT, "DepthPitch"), ]) ID3D11Resource.methods += [ StdMethod(Void, "GetType", [Out(Pointer(D3D11_RESOURCE_DIMENSION), "pResourceDimension")]), StdMethod(Void, "SetEvictionPriority", [(UINT, "EvictionPriority")]), StdMethod(UINT, "GetEvictionPriority", []), ] D3D11_BUFFER_DESC = Struct("D3D11_BUFFER_DESC", [ (UINT, "ByteWidth"), (D3D11_USAGE, "Usage"), (D3D11_BIND_FLAG, "BindFlags"), (D3D11_CPU_ACCESS_FLAG, "CPUAccessFlags"), (D3D11_RESOURCE_MISC_FLAG, "MiscFlags"), (UINT, "StructureByteStride"), ]) ID3D11Buffer.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_BUFFER_DESC), "pDesc")]), ] D3D11_TEXTURE1D_DESC = Struct("D3D11_TEXTURE1D_DESC", [ (UINT, "Width"), (UINT, "MipLevels"), (UINT, "ArraySize"), (DXGI_FORMAT, "Format"), (D3D11_USAGE, "Usage"), (D3D11_BIND_FLAG, "BindFlags"), (D3D11_CPU_ACCESS_FLAG, "CPUAccessFlags"), (D3D11_RESOURCE_MISC_FLAG, "MiscFlags"), ]) ID3D11Texture1D.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_TEXTURE1D_DESC), "pDesc")]), ] D3D11_TEXTURE2D_DESC = Struct("D3D11_TEXTURE2D_DESC", [ (UINT, "Width"), (UINT, "Height"), (UINT, "MipLevels"), (UINT, "ArraySize"), (DXGI_FORMAT, "Format"), (DXGI_SAMPLE_DESC, "SampleDesc"), (D3D11_USAGE, "Usage"), (D3D11_BIND_FLAG, "BindFlags"), (D3D11_CPU_ACCESS_FLAG, "CPUAccessFlags"), (D3D11_RESOURCE_MISC_FLAG, "MiscFlags"), ]) ID3D11Texture2D.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_TEXTURE2D_DESC), "pDesc")]), ] D3D11_TEXTURE3D_DESC = Struct("D3D11_TEXTURE3D_DESC", [ (UINT, "Width"), (UINT, "Height"), (UINT, "Depth"), (UINT, "MipLevels"), (DXGI_FORMAT, "Format"), (D3D11_USAGE, "Usage"), (D3D11_BIND_FLAG, "BindFlags"), (D3D11_CPU_ACCESS_FLAG, "CPUAccessFlags"), (D3D11_RESOURCE_MISC_FLAG, "MiscFlags"), ]) ID3D11Texture3D.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_TEXTURE3D_DESC), "pDesc")]), ] D3D11_TEXTURECUBE_FACE = Enum("D3D11_TEXTURECUBE_FACE", [ "D3D11_TEXTURECUBE_FACE_POSITIVE_X", "D3D11_TEXTURECUBE_FACE_NEGATIVE_X", "D3D11_TEXTURECUBE_FACE_POSITIVE_Y", "D3D11_TEXTURECUBE_FACE_NEGATIVE_Y", "D3D11_TEXTURECUBE_FACE_POSITIVE_Z", "D3D11_TEXTURECUBE_FACE_NEGATIVE_Z", ]) ID3D11View.methods += [ StdMethod(Void, "GetResource", [Out(Pointer(ObjPointer(ID3D11Resource)), "ppResource")]), ] D3D11_BUFFER_SRV = Struct("D3D11_BUFFER_SRV", [ (Union(None, [(UINT, "FirstElement"), (UINT, "ElementOffset")]), None), (Union(None, [(UINT, "NumElements"), (UINT, "ElementWidth")]), None), ]) D3D11_BUFFEREX_SRV_FLAG = Flags(UINT, [ "D3D11_BUFFEREX_SRV_FLAG_RAW", ]) D3D11_BUFFEREX_SRV = Struct("D3D11_BUFFEREX_SRV", [ (UINT, "FirstElement"), (UINT, "NumElements"), (D3D11_BUFFEREX_SRV_FLAG, "Flags"), ]) D3D11_TEX1D_SRV = Struct("D3D11_TEX1D_SRV", [ (UINT, "MostDetailedMip"), (UINT, "MipLevels"), ]) D3D11_TEX1D_ARRAY_SRV = Struct("D3D11_TEX1D_ARRAY_SRV", [ (UINT, "MostDetailedMip"), (UINT, "MipLevels"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX2D_SRV = Struct("D3D11_TEX2D_SRV", [ (UINT, "MostDetailedMip"), (UINT, "MipLevels"), ]) D3D11_TEX2D_ARRAY_SRV = Struct("D3D11_TEX2D_ARRAY_SRV", [ (UINT, "MostDetailedMip"), (UINT, "MipLevels"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX3D_SRV = Struct("D3D11_TEX3D_SRV", [ (UINT, "MostDetailedMip"), (UINT, "MipLevels"), ]) D3D11_TEXCUBE_SRV = Struct("D3D11_TEXCUBE_SRV", [ (UINT, "MostDetailedMip"), (UINT, "MipLevels"), ]) D3D11_TEXCUBE_ARRAY_SRV = Struct("D3D11_TEXCUBE_ARRAY_SRV", [ (UINT, "MostDetailedMip"), (UINT, "MipLevels"), (UINT, "First2DArrayFace"), (UINT, "NumCubes"), ]) D3D11_TEX2DMS_SRV = Struct("D3D11_TEX2DMS_SRV", [ (UINT, "UnusedField_NothingToDefine"), ]) D3D11_TEX2DMS_ARRAY_SRV = Struct("D3D11_TEX2DMS_ARRAY_SRV", [ (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_SHADER_RESOURCE_VIEW_DESC = Struct("D3D11_SHADER_RESOURCE_VIEW_DESC", [ (DXGI_FORMAT, "Format"), (D3D11_SRV_DIMENSION, "ViewDimension"), (Union(None, [ (D3D11_BUFFER_SRV, "Buffer"), (D3D11_TEX1D_SRV, "Texture1D"), (D3D11_TEX1D_ARRAY_SRV, "Texture1DArray"), (D3D11_TEX2D_SRV, "Texture2D"), (D3D11_TEX2D_ARRAY_SRV, "Texture2DArray"), (D3D11_TEX2DMS_SRV, "Texture2DMS"), (D3D11_TEX2DMS_ARRAY_SRV, "Texture2DMSArray"), (D3D11_TEX3D_SRV, "Texture3D"), (D3D11_TEXCUBE_SRV, "TextureCube"), (D3D11_TEXCUBE_ARRAY_SRV, "TextureCubeArray"), (D3D11_BUFFEREX_SRV, "BufferEx"), ]), None), ]) ID3D11ShaderResourceView.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_SHADER_RESOURCE_VIEW_DESC), "pDesc")]), ] D3D11_BUFFER_RTV = Struct("D3D11_BUFFER_RTV", [ (Union(None, [(UINT, "FirstElement"), (UINT, "ElementOffset")]), None), (Union(None, [(UINT, "NumElements"), (UINT, "ElementWidth")]), None), ]) D3D11_TEX1D_RTV = Struct("D3D11_TEX1D_RTV", [ (UINT, "MipSlice"), ]) D3D11_TEX1D_ARRAY_RTV = Struct("D3D11_TEX1D_ARRAY_RTV", [ (UINT, "MipSlice"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX2D_RTV = Struct("D3D11_TEX2D_RTV", [ (UINT, "MipSlice"), ]) D3D11_TEX2DMS_RTV = Struct("D3D11_TEX2DMS_RTV", [ (UINT, "UnusedField_NothingToDefine"), ]) D3D11_TEX2D_ARRAY_RTV = Struct("D3D11_TEX2D_ARRAY_RTV", [ (UINT, "MipSlice"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX2DMS_ARRAY_RTV = Struct("D3D11_TEX2DMS_ARRAY_RTV", [ (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX3D_RTV = Struct("D3D11_TEX3D_RTV", [ (UINT, "MipSlice"), (UINT, "FirstWSlice"), (UINT, "WSize"), ]) D3D11_RENDER_TARGET_VIEW_DESC = Struct("D3D11_RENDER_TARGET_VIEW_DESC", [ (DXGI_FORMAT, "Format"), (D3D11_RTV_DIMENSION, "ViewDimension"), (Union(None, [ (D3D11_BUFFER_RTV, "Buffer"), (D3D11_TEX1D_RTV, "Texture1D"), (D3D11_TEX1D_ARRAY_RTV, "Texture1DArray"), (D3D11_TEX2D_RTV, "Texture2D"), (D3D11_TEX2D_ARRAY_RTV, "Texture2DArray"), (D3D11_TEX2DMS_RTV, "Texture2DMS"), (D3D11_TEX2DMS_ARRAY_RTV, "Texture2DMSArray"), (D3D11_TEX3D_RTV, "Texture3D"), ]), None), ]) ID3D11RenderTargetView.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_RENDER_TARGET_VIEW_DESC), "pDesc")]), ] D3D11_TEX1D_DSV = Struct("D3D11_TEX1D_DSV", [ (UINT, "MipSlice"), ]) D3D11_TEX1D_ARRAY_DSV = Struct("D3D11_TEX1D_ARRAY_DSV", [ (UINT, "MipSlice"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX2D_DSV = Struct("D3D11_TEX2D_DSV", [ (UINT, "MipSlice"), ]) D3D11_TEX2D_ARRAY_DSV = Struct("D3D11_TEX2D_ARRAY_DSV", [ (UINT, "MipSlice"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX2DMS_DSV = Struct("D3D11_TEX2DMS_DSV", [ (UINT, "UnusedField_NothingToDefine"), ]) D3D11_TEX2DMS_ARRAY_DSV = Struct("D3D11_TEX2DMS_ARRAY_DSV", [ (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_DSV_FLAG = Flags(UINT, [ "D3D11_DSV_READ_ONLY_DEPTH", "D3D11_DSV_READ_ONLY_STENCIL", ]) D3D11_DEPTH_STENCIL_VIEW_DESC = Struct("D3D11_DEPTH_STENCIL_VIEW_DESC", [ (DXGI_FORMAT, "Format"), (D3D11_DSV_DIMENSION, "ViewDimension"), (D3D11_DSV_FLAG, "Flags"), (Union(None, [ (D3D11_TEX1D_DSV, "Texture1D"), (D3D11_TEX1D_ARRAY_DSV, "Texture1DArray"), (D3D11_TEX2D_DSV, "Texture2D"), (D3D11_TEX2D_ARRAY_DSV, "Texture2DArray"), (D3D11_TEX2DMS_DSV, "Texture2DMS"), (D3D11_TEX2DMS_ARRAY_DSV, "Texture2DMSArray"), ]), None), ]) ID3D11DepthStencilView.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_DEPTH_STENCIL_VIEW_DESC), "pDesc")]), ] D3D11_BUFFER_UAV_FLAG = Flags(UINT, [ "D3D11_BUFFER_UAV_FLAG_RAW", "D3D11_BUFFER_UAV_FLAG_APPEND", "D3D11_BUFFER_UAV_FLAG_COUNTER", ]) D3D11_BUFFER_UAV = Struct("D3D11_BUFFER_UAV", [ (UINT, "FirstElement"), (UINT, "NumElements"), (D3D11_BUFFER_UAV_FLAG, "Flags"), ]) D3D11_TEX1D_UAV = Struct("D3D11_TEX1D_UAV", [ (UINT, "MipSlice"), ]) D3D11_TEX1D_ARRAY_UAV = Struct("D3D11_TEX1D_ARRAY_UAV", [ (UINT, "MipSlice"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX2D_UAV = Struct("D3D11_TEX2D_UAV", [ (UINT, "MipSlice"), ]) D3D11_TEX2D_ARRAY_UAV = Struct("D3D11_TEX2D_ARRAY_UAV", [ (UINT, "MipSlice"), (UINT, "FirstArraySlice"), (UINT, "ArraySize"), ]) D3D11_TEX3D_UAV = Struct("D3D11_TEX3D_UAV", [ (UINT, "MipSlice"), (UINT, "FirstWSlice"), (UINT, "WSize"), ]) D3D11_UNORDERED_ACCESS_VIEW_DESC = Struct("D3D11_UNORDERED_ACCESS_VIEW_DESC", [ (DXGI_FORMAT, "Format"), (D3D11_UAV_DIMENSION, "ViewDimension"), (Union(None, [ (D3D11_BUFFER_UAV, "Buffer"), (D3D11_TEX1D_UAV, "Texture1D"), (D3D11_TEX1D_ARRAY_UAV, "Texture1DArray"), (D3D11_TEX2D_UAV, "Texture2D"), (D3D11_TEX2D_ARRAY_UAV, "Texture2DArray"), (D3D11_TEX3D_UAV, "Texture3D"), ]), None), ]) ID3D11UnorderedAccessView.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_UNORDERED_ACCESS_VIEW_DESC), "pDesc")]), ] D3D11_FILTER = Enum("D3D11_FILTER", [ "D3D11_FILTER_MIN_MAG_MIP_POINT", "D3D11_FILTER_MIN_MAG_POINT_MIP_LINEAR", "D3D11_FILTER_MIN_POINT_MAG_LINEAR_MIP_POINT", "D3D11_FILTER_MIN_POINT_MAG_MIP_LINEAR", "D3D11_FILTER_MIN_LINEAR_MAG_MIP_POINT", "D3D11_FILTER_MIN_LINEAR_MAG_POINT_MIP_LINEAR", "D3D11_FILTER_MIN_MAG_LINEAR_MIP_POINT", "D3D11_FILTER_MIN_MAG_MIP_LINEAR", "D3D11_FILTER_ANISOTROPIC", "D3D11_FILTER_COMPARISON_MIN_MAG_MIP_POINT", "D3D11_FILTER_COMPARISON_MIN_MAG_POINT_MIP_LINEAR", "D3D11_FILTER_COMPARISON_MIN_POINT_MAG_LINEAR_MIP_POINT", "D3D11_FILTER_COMPARISON_MIN_POINT_MAG_MIP_LINEAR", "D3D11_FILTER_COMPARISON_MIN_LINEAR_MAG_MIP_POINT", "D3D11_FILTER_COMPARISON_MIN_LINEAR_MAG_POINT_MIP_LINEAR", "D3D11_FILTER_COMPARISON_MIN_MAG_LINEAR_MIP_POINT", "D3D11_FILTER_COMPARISON_MIN_MAG_MIP_LINEAR", "D3D11_FILTER_COMPARISON_ANISOTROPIC", ]) D3D11_FILTER_TYPE = Enum("D3D11_FILTER_TYPE", [ "D3D11_FILTER_TYPE_POINT", "D3D11_FILTER_TYPE_LINEAR", ]) D3D11_TEXTURE_ADDRESS_MODE = Enum("D3D11_TEXTURE_ADDRESS_MODE", [ "D3D11_TEXTURE_ADDRESS_WRAP", "D3D11_TEXTURE_ADDRESS_MIRROR", "D3D11_TEXTURE_ADDRESS_CLAMP", "D3D11_TEXTURE_ADDRESS_BORDER", "D3D11_TEXTURE_ADDRESS_MIRROR_ONCE", ]) D3D11_SAMPLER_DESC = Struct("D3D11_SAMPLER_DESC", [ (D3D11_FILTER, "Filter"), (D3D11_TEXTURE_ADDRESS_MODE, "AddressU"), (D3D11_TEXTURE_ADDRESS_MODE, "AddressV"), (D3D11_TEXTURE_ADDRESS_MODE, "AddressW"), (FLOAT, "MipLODBias"), (UINT, "MaxAnisotropy"), (D3D11_COMPARISON_FUNC, "ComparisonFunc"), (Array(FLOAT, 4), "BorderColor"), (FLOAT, "MinLOD"), (FLOAT, "MaxLOD"), ]) ID3D11SamplerState.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_SAMPLER_DESC), "pDesc")]), ] D3D11_FORMAT_SUPPORT = Flags(UINT, [ "D3D11_FORMAT_SUPPORT_BUFFER", "D3D11_FORMAT_SUPPORT_IA_VERTEX_BUFFER", "D3D11_FORMAT_SUPPORT_IA_INDEX_BUFFER", "D3D11_FORMAT_SUPPORT_SO_BUFFER", "D3D11_FORMAT_SUPPORT_TEXTURE1D", "D3D11_FORMAT_SUPPORT_TEXTURE2D", "D3D11_FORMAT_SUPPORT_TEXTURE3D", "D3D11_FORMAT_SUPPORT_TEXTURECUBE", "D3D11_FORMAT_SUPPORT_SHADER_LOAD", "D3D11_FORMAT_SUPPORT_SHADER_SAMPLE", "D3D11_FORMAT_SUPPORT_SHADER_SAMPLE_COMPARISON", "D3D11_FORMAT_SUPPORT_SHADER_SAMPLE_MONO_TEXT", "D3D11_FORMAT_SUPPORT_MIP", "D3D11_FORMAT_SUPPORT_MIP_AUTOGEN", "D3D11_FORMAT_SUPPORT_RENDER_TARGET", "D3D11_FORMAT_SUPPORT_BLENDABLE", "D3D11_FORMAT_SUPPORT_DEPTH_STENCIL", "D3D11_FORMAT_SUPPORT_CPU_LOCKABLE", "D3D11_FORMAT_SUPPORT_MULTISAMPLE_RESOLVE", "D3D11_FORMAT_SUPPORT_DISPLAY", "D3D11_FORMAT_SUPPORT_CAST_WITHIN_BIT_LAYOUT", "D3D11_FORMAT_SUPPORT_MULTISAMPLE_RENDERTARGET", "D3D11_FORMAT_SUPPORT_MULTISAMPLE_LOAD", "D3D11_FORMAT_SUPPORT_SHADER_GATHER", "D3D11_FORMAT_SUPPORT_BACK_BUFFER_CAST", "D3D11_FORMAT_SUPPORT_TYPED_UNORDERED_ACCESS_VIEW", "D3D11_FORMAT_SUPPORT_SHADER_GATHER_COMPARISON", ]) D3D11_FORMAT_SUPPORT2 = Enum("D3D11_FORMAT_SUPPORT2", [ "D3D11_FORMAT_SUPPORT2_UAV_ATOMIC_ADD", "D3D11_FORMAT_SUPPORT2_UAV_ATOMIC_BITWISE_OPS", "D3D11_FORMAT_SUPPORT2_UAV_ATOMIC_COMPARE_STORE_OR_COMPARE_EXCHANGE", "D3D11_FORMAT_SUPPORT2_UAV_ATOMIC_EXCHANGE", "D3D11_FORMAT_SUPPORT2_UAV_ATOMIC_SIGNED_MIN_OR_MAX", "D3D11_FORMAT_SUPPORT2_UAV_ATOMIC_UNSIGNED_MIN_OR_MAX", "D3D11_FORMAT_SUPPORT2_UAV_TYPED_LOAD", "D3D11_FORMAT_SUPPORT2_UAV_TYPED_STORE", ]) ID3D11Asynchronous.methods += [ StdMethod(UINT, "GetDataSize", []), ] D3D11_ASYNC_GETDATA_FLAG = Flags(UINT, [ "D3D11_ASYNC_GETDATA_DONOTFLUSH", ]) D3D11_QUERY = Enum("D3D11_QUERY", [ "D3D11_QUERY_EVENT", "D3D11_QUERY_OCCLUSION", "D3D11_QUERY_TIMESTAMP", "D3D11_QUERY_TIMESTAMP_DISJOINT", "D3D11_QUERY_PIPELINE_STATISTICS", "D3D11_QUERY_OCCLUSION_PREDICATE", "D3D11_QUERY_SO_STATISTICS", "D3D11_QUERY_SO_OVERFLOW_PREDICATE", "D3D11_QUERY_SO_STATISTICS_STREAM0", "D3D11_QUERY_SO_OVERFLOW_PREDICATE_STREAM0", "D3D11_QUERY_SO_STATISTICS_STREAM1", "D3D11_QUERY_SO_OVERFLOW_PREDICATE_STREAM1", "D3D11_QUERY_SO_STATISTICS_STREAM2", "D3D11_QUERY_SO_OVERFLOW_PREDICATE_STREAM2", "D3D11_QUERY_SO_STATISTICS_STREAM3", "D3D11_QUERY_SO_OVERFLOW_PREDICATE_STREAM3", ]) D3D11_QUERY_MISC_FLAG = Flags(UINT, [ "D3D11_QUERY_MISC_PREDICATEHINT", ]) D3D11_QUERY_DESC = Struct("D3D11_QUERY_DESC", [ (D3D11_QUERY, "Query"), (D3D11_QUERY_MISC_FLAG, "MiscFlags"), ]) ID3D11Query.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_QUERY_DESC), "pDesc")]), ] D3D11_QUERY_DATA_TIMESTAMP_DISJOINT = Struct("D3D11_QUERY_DATA_TIMESTAMP_DISJOINT", [ (UINT64, "Frequency"), (BOOL, "Disjoint"), ]) D3D11_QUERY_DATA_PIPELINE_STATISTICS = Struct("D3D11_QUERY_DATA_PIPELINE_STATISTICS", [ (UINT64, "IAVertices"), (UINT64, "IAPrimitives"), (UINT64, "VSInvocations"), (UINT64, "GSInvocations"), (UINT64, "GSPrimitives"), (UINT64, "CInvocations"), (UINT64, "CPrimitives"), (UINT64, "PSInvocations"), (UINT64, "HSInvocations"), (UINT64, "DSInvocations"), (UINT64, "CSInvocations"), ]) D3D11_QUERY_DATA_SO_STATISTICS = Struct("D3D11_QUERY_DATA_SO_STATISTICS", [ (UINT64, "NumPrimitivesWritten"), (UINT64, "PrimitivesStorageNeeded"), ]) D3D11_COUNTER = Enum("D3D11_COUNTER", [ "D3D11_COUNTER_DEVICE_DEPENDENT_0", ]) D3D11_COUNTER_TYPE = Enum("D3D11_COUNTER_TYPE", [ "D3D11_COUNTER_TYPE_FLOAT32", "D3D11_COUNTER_TYPE_UINT16", "D3D11_COUNTER_TYPE_UINT32", "D3D11_COUNTER_TYPE_UINT64", ]) D3D11_COUNTER_DESC = Struct("D3D11_COUNTER_DESC", [ (D3D11_COUNTER, "Counter"), (UINT, "MiscFlags"), ]) D3D11_COUNTER_INFO = Struct("D3D11_COUNTER_INFO", [ (D3D11_COUNTER, "LastDeviceDependentCounter"), (UINT, "NumSimultaneousCounters"), (UINT8, "NumDetectableParallelUnits"), ]) ID3D11Counter.methods += [ StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_COUNTER_DESC), "pDesc")]), ] D3D11_STANDARD_MULTISAMPLE_QUALITY_LEVELS = Enum("D3D11_STANDARD_MULTISAMPLE_QUALITY_LEVELS", [ "D3D11_STANDARD_MULTISAMPLE_PATTERN", "D3D11_CENTER_MULTISAMPLE_PATTERN", ]) D3D11_DEVICE_CONTEXT_TYPE = Enum("D3D11_DEVICE_CONTEXT_TYPE", [ "D3D11_DEVICE_CONTEXT_IMMEDIATE", "D3D11_DEVICE_CONTEXT_DEFERRED", ]) D3D11_CLASS_INSTANCE_DESC = Struct("D3D11_CLASS_INSTANCE_DESC", [ (UINT, "InstanceId"), (UINT, "InstanceIndex"), (UINT, "TypeId"), (UINT, "ConstantBuffer"), (UINT, "BaseConstantBufferOffset"), (UINT, "BaseTexture"), (UINT, "BaseSampler"), (BOOL, "Created"), ]) ID3D11ClassInstance.methods += [ StdMethod(Void, "GetClassLinkage", [Out(Pointer(ObjPointer(ID3D11ClassLinkage)), "ppLinkage")]), StdMethod(Void, "GetDesc", [Out(Pointer(D3D11_CLASS_INSTANCE_DESC), "pDesc")]), StdMethod(Void, "GetInstanceName", [Out(LPSTR, "pInstanceName"), Out(Pointer(SIZE_T), "pBufferLength")]), StdMethod(Void, "GetTypeName", [Out(LPSTR, "pTypeName"), Out(Pointer(SIZE_T), "pBufferLength")]), ] ID3D11ClassLinkage.methods += [ StdMethod(HRESULT, "GetClassInstance", [(LPCSTR, "pClassInstanceName"), (UINT, "InstanceIndex"), Out(Pointer(ObjPointer(ID3D11ClassInstance)), "ppInstance")]), StdMethod(HRESULT, "CreateClassInstance", [(LPCSTR, "pClassTypeName"), (UINT, "ConstantBufferOffset"), (UINT, "ConstantVectorOffset"), (UINT, "TextureOffset"), (UINT, "SamplerOffset"), Out(Pointer(ObjPointer(ID3D11ClassInstance)), "ppInstance")]), ] ID3D11CommandList.methods += [ StdMethod(UINT, "GetContextFlags", []), ] D3D11_FEATURE_DATA_THREADING = Struct("D3D11_FEATURE_DATA_THREADING", [ (BOOL, "DriverConcurrentCreates"), (BOOL, "DriverCommandLists"), ]) D3D11_FEATURE_DATA_DOUBLES = Struct("D3D11_FEATURE_DATA_DOUBLES", [ (BOOL, "DoublePrecisionFloatShaderOps"), ]) D3D11_FEATURE_DATA_FORMAT_SUPPORT = Struct("D3D11_FEATURE_DATA_FORMAT_SUPPORT", [ (DXGI_FORMAT, "InFormat"), (D3D11_FORMAT_SUPPORT, "OutFormatSupport"), ]) D3D11_FEATURE_DATA_FORMAT_SUPPORT2 = Struct("D3D11_FEATURE_DATA_FORMAT_SUPPORT2", [ (DXGI_FORMAT, "InFormat"), (D3D11_FORMAT_SUPPORT2, "OutFormatSupport2"), ]) D3D11_FEATURE_DATA_D3D10_X_HARDWARE_OPTIONS = Struct("D3D11_FEATURE_DATA_D3D10_X_HARDWARE_OPTIONS", [ (BOOL, "ComputeShaders_Plus_RawAndStructuredBuffers_Via_Shader_4_x"), ]) D3D11_FEATURE, D3D11_FEATURE_DATA = EnumPolymorphic("D3D11_FEATURE", "Feature", [ ("D3D11_FEATURE_THREADING", Pointer(D3D11_FEATURE_DATA_THREADING)), ("D3D11_FEATURE_DOUBLES", Pointer(D3D11_FEATURE_DATA_DOUBLES)), ("D3D11_FEATURE_FORMAT_SUPPORT", Pointer(D3D11_FEATURE_DATA_FORMAT_SUPPORT)), ("D3D11_FEATURE_FORMAT_SUPPORT2", Pointer(D3D11_FEATURE_DATA_FORMAT_SUPPORT2)), ("D3D11_FEATURE_D3D10_X_HARDWARE_OPTIONS", Pointer(D3D11_FEATURE_DATA_D3D10_X_HARDWARE_OPTIONS)), ], Blob(Void, "FeatureSupportDataSize"), False) ID3D11DeviceContext.methods += [ StdMethod(Void, "VSSetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "PSSetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(Const(ObjPointer(ID3D11ShaderResourceView)), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "PSSetShader", [(ObjPointer(ID3D11PixelShader), "pPixelShader"), (Array(Const(ObjPointer(ID3D11ClassInstance)), "NumClassInstances"), "ppClassInstances"), (UINT, "NumClassInstances")]), StdMethod(Void, "PSSetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(Const(ObjPointer(ID3D11SamplerState)), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "VSSetShader", [(ObjPointer(ID3D11VertexShader), "pVertexShader"), (Array(Const(ObjPointer(ID3D11ClassInstance)), "NumClassInstances"), "ppClassInstances"), (UINT, "NumClassInstances")]), StdMethod(Void, "DrawIndexed", [(UINT, "IndexCount"), (UINT, "StartIndexLocation"), (INT, "BaseVertexLocation")]), StdMethod(Void, "Draw", [(UINT, "VertexCount"), (UINT, "StartVertexLocation")]), StdMethod(HRESULT, "Map", [(ObjPointer(ID3D11Resource), "pResource"), (UINT, "Subresource"), (D3D11_MAP, "MapType"), (D3D11_MAP_FLAG, "MapFlags"), Out(Pointer(D3D11_MAPPED_SUBRESOURCE), "pMappedResource")]), StdMethod(Void, "Unmap", [(ObjPointer(ID3D11Resource), "pResource"), (UINT, "Subresource")]), StdMethod(Void, "PSSetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "IASetInputLayout", [(ObjPointer(ID3D11InputLayout), "pInputLayout")]), StdMethod(Void, "IASetVertexBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppVertexBuffers"), (Pointer(Const(UINT)), "pStrides"), (Pointer(Const(UINT)), "pOffsets")]), StdMethod(Void, "IASetIndexBuffer", [(ObjPointer(ID3D11Buffer), "pIndexBuffer"), (DXGI_FORMAT, "Format"), (UINT, "Offset")]), StdMethod(Void, "DrawIndexedInstanced", [(UINT, "IndexCountPerInstance"), (UINT, "InstanceCount"), (UINT, "StartIndexLocation"), (INT, "BaseVertexLocation"), (UINT, "StartInstanceLocation")]), StdMethod(Void, "DrawInstanced", [(UINT, "VertexCountPerInstance"), (UINT, "InstanceCount"), (UINT, "StartVertexLocation"), (UINT, "StartInstanceLocation")]), StdMethod(Void, "GSSetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "GSSetShader", [(ObjPointer(ID3D11GeometryShader), "pShader"), (Array(Const(ObjPointer(ID3D11ClassInstance)), "NumClassInstances"), "ppClassInstances"), (UINT, "NumClassInstances")]), StdMethod(Void, "IASetPrimitiveTopology", [(D3D11_PRIMITIVE_TOPOLOGY, "Topology")]), StdMethod(Void, "VSSetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(Const(ObjPointer(ID3D11ShaderResourceView)), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "VSSetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(Const(ObjPointer(ID3D11SamplerState)), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "Begin", [(ObjPointer(ID3D11Asynchronous), "pAsync")]), StdMethod(Void, "End", [(ObjPointer(ID3D11Asynchronous), "pAsync")]), StdMethod(HRESULT, "GetData", [(ObjPointer(ID3D11Asynchronous), "pAsync"), Out(OpaqueBlob(Void, "DataSize"), "pData"), (UINT, "DataSize"), (D3D11_ASYNC_GETDATA_FLAG, "GetDataFlags")]), StdMethod(Void, "SetPredication", [(ObjPointer(ID3D11Predicate), "pPredicate"), (BOOL, "PredicateValue")]), StdMethod(Void, "GSSetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(Const(ObjPointer(ID3D11ShaderResourceView)), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "GSSetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(Const(ObjPointer(ID3D11SamplerState)), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "OMSetRenderTargets", [(UINT, "NumViews"), (Array(Const(ObjPointer(ID3D11RenderTargetView)), "NumViews"), "ppRenderTargetViews"), (ObjPointer(ID3D11DepthStencilView), "pDepthStencilView")]), StdMethod(Void, "OMSetRenderTargetsAndUnorderedAccessViews", [(UINT, "NumRTVs"), (Array(Const(ObjPointer(ID3D11RenderTargetView)), "NumRTVs"), "ppRenderTargetViews"), (ObjPointer(ID3D11DepthStencilView), "pDepthStencilView"), (UINT, "UAVStartSlot"), (UINT, "NumUAVs"), (Array(Const(ObjPointer(ID3D11UnorderedAccessView)), "NumUAVs"), "ppUnorderedAccessViews"), (Pointer(Const(UINT)), "pUAVInitialCounts")]), StdMethod(Void, "OMSetBlendState", [(ObjPointer(ID3D11BlendState), "pBlendState"), (Array(Const(FLOAT), 4), "BlendFactor"), (UINT, "SampleMask")]), StdMethod(Void, "OMSetDepthStencilState", [(ObjPointer(ID3D11DepthStencilState), "pDepthStencilState"), (UINT, "StencilRef")]), StdMethod(Void, "SOSetTargets", [(UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppSOTargets"), (Pointer(Const(UINT)), "pOffsets")]), StdMethod(Void, "DrawAuto", []), StdMethod(Void, "DrawIndexedInstancedIndirect", [(ObjPointer(ID3D11Buffer), "pBufferForArgs"), (UINT, "AlignedByteOffsetForArgs")]), StdMethod(Void, "DrawInstancedIndirect", [(ObjPointer(ID3D11Buffer), "pBufferForArgs"), (UINT, "AlignedByteOffsetForArgs")]), StdMethod(Void, "Dispatch", [(UINT, "ThreadGroupCountX"), (UINT, "ThreadGroupCountY"), (UINT, "ThreadGroupCountZ")]), StdMethod(Void, "DispatchIndirect", [(ObjPointer(ID3D11Buffer), "pBufferForArgs"), (UINT, "AlignedByteOffsetForArgs")]), StdMethod(Void, "RSSetState", [(ObjPointer(ID3D11RasterizerState), "pRasterizerState")]), StdMethod(Void, "RSSetViewports", [(UINT, "NumViewports"), (Array(Const(D3D11_VIEWPORT), "NumViewports"), "pViewports")]), StdMethod(Void, "RSSetScissorRects", [(UINT, "NumRects"), (Array(Const(D3D11_RECT), "NumRects"), "pRects")]), StdMethod(Void, "CopySubresourceRegion", [(ObjPointer(ID3D11Resource), "pDstResource"), (UINT, "DstSubresource"), (UINT, "DstX"), (UINT, "DstY"), (UINT, "DstZ"), (ObjPointer(ID3D11Resource), "pSrcResource"), (UINT, "SrcSubresource"), (Pointer(Const(D3D11_BOX)), "pSrcBox")]), StdMethod(Void, "CopyResource", [(ObjPointer(ID3D11Resource), "pDstResource"), (ObjPointer(ID3D11Resource), "pSrcResource")]), StdMethod(Void, "UpdateSubresource", [(ObjPointer(ID3D11Resource), "pDstResource"), (UINT, "DstSubresource"), (Pointer(Const(D3D11_BOX)), "pDstBox"), (OpaquePointer(Const(Void)), "pSrcData"), (UINT, "SrcRowPitch"), (UINT, "SrcDepthPitch")]), StdMethod(Void, "CopyStructureCount", [(ObjPointer(ID3D11Buffer), "pDstBuffer"), (UINT, "DstAlignedByteOffset"), (ObjPointer(ID3D11UnorderedAccessView), "pSrcView")]), StdMethod(Void, "ClearRenderTargetView", [(ObjPointer(ID3D11RenderTargetView), "pRenderTargetView"), (Array(Const(FLOAT), 4), "ColorRGBA")]), StdMethod(Void, "ClearUnorderedAccessViewUint", [(ObjPointer(ID3D11UnorderedAccessView), "pUnorderedAccessView"), (Array(Const(UINT), 4), "Values")]), StdMethod(Void, "ClearUnorderedAccessViewFloat", [(ObjPointer(ID3D11UnorderedAccessView), "pUnorderedAccessView"), (Array(Const(FLOAT), 4), "Values")]), StdMethod(Void, "ClearDepthStencilView", [(ObjPointer(ID3D11DepthStencilView), "pDepthStencilView"), (D3D11_CLEAR_FLAG, "ClearFlags"), (FLOAT, "Depth"), (UINT8, "Stencil")]), StdMethod(Void, "GenerateMips", [(ObjPointer(ID3D11ShaderResourceView), "pShaderResourceView")]), StdMethod(Void, "SetResourceMinLOD", [(ObjPointer(ID3D11Resource), "pResource"), (FLOAT, "MinLOD")]), StdMethod(FLOAT, "GetResourceMinLOD", [(ObjPointer(ID3D11Resource), "pResource")]), StdMethod(Void, "ResolveSubresource", [(ObjPointer(ID3D11Resource), "pDstResource"), (UINT, "DstSubresource"), (ObjPointer(ID3D11Resource), "pSrcResource"), (UINT, "SrcSubresource"), (DXGI_FORMAT, "Format")]), StdMethod(Void, "ExecuteCommandList", [(ObjPointer(ID3D11CommandList), "pCommandList"), (BOOL, "RestoreContextState")]), StdMethod(Void, "HSSetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(Const(ObjPointer(ID3D11ShaderResourceView)), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "HSSetShader", [(ObjPointer(ID3D11HullShader), "pHullShader"), (Array(Const(ObjPointer(ID3D11ClassInstance)), "NumClassInstances"), "ppClassInstances"), (UINT, "NumClassInstances")]), StdMethod(Void, "HSSetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(Const(ObjPointer(ID3D11SamplerState)), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "HSSetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "DSSetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(Const(ObjPointer(ID3D11ShaderResourceView)), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "DSSetShader", [(ObjPointer(ID3D11DomainShader), "pDomainShader"), (Array(Const(ObjPointer(ID3D11ClassInstance)), "NumClassInstances"), "ppClassInstances"), (UINT, "NumClassInstances")]), StdMethod(Void, "DSSetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(Const(ObjPointer(ID3D11SamplerState)), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "DSSetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "CSSetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(Const(ObjPointer(ID3D11ShaderResourceView)), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "CSSetUnorderedAccessViews", [(UINT, "StartSlot"), (UINT, "NumUAVs"), (Array(Const(ObjPointer(ID3D11UnorderedAccessView)), "NumUAVs"), "ppUnorderedAccessViews"), (Pointer(Const(UINT)), "pUAVInitialCounts")]), StdMethod(Void, "CSSetShader", [(ObjPointer(ID3D11ComputeShader), "pComputeShader"), (Array(Const(ObjPointer(ID3D11ClassInstance)), "NumClassInstances"), "ppClassInstances"), (UINT, "NumClassInstances")]), StdMethod(Void, "CSSetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(Const(ObjPointer(ID3D11SamplerState)), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "CSSetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(Const(ObjPointer(ID3D11Buffer)), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "VSGetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "PSGetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(ObjPointer(ID3D11ShaderResourceView), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "PSGetShader", [Out(Pointer(ObjPointer(ID3D11PixelShader)), "ppPixelShader"), Out(Array(ObjPointer(ID3D11ClassInstance), "*pNumClassInstances"), "ppClassInstances"), Out(Pointer(UINT), "pNumClassInstances")]), StdMethod(Void, "PSGetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(ObjPointer(ID3D11SamplerState), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "VSGetShader", [Out(Pointer(ObjPointer(ID3D11VertexShader)), "ppVertexShader"), Out(Array(ObjPointer(ID3D11ClassInstance), "*pNumClassInstances"), "ppClassInstances"), Out(Pointer(UINT), "pNumClassInstances")]), StdMethod(Void, "PSGetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "IAGetInputLayout", [Out(Pointer(ObjPointer(ID3D11InputLayout)), "ppInputLayout")]), StdMethod(Void, "IAGetVertexBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppVertexBuffers"), Out(Pointer(UINT), "pStrides"), Out(Pointer(UINT), "pOffsets")]), StdMethod(Void, "IAGetIndexBuffer", [Out(Pointer(ObjPointer(ID3D11Buffer)), "pIndexBuffer"), Out(Pointer(DXGI_FORMAT), "Format"), Out(Pointer(UINT), "Offset")]), StdMethod(Void, "GSGetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "GSGetShader", [Out(Pointer(ObjPointer(ID3D11GeometryShader)), "ppGeometryShader"), Out(Array(ObjPointer(ID3D11ClassInstance), "*pNumClassInstances"), "ppClassInstances"), Out(Pointer(UINT), "pNumClassInstances")]), StdMethod(Void, "IAGetPrimitiveTopology", [Out(Pointer(D3D11_PRIMITIVE_TOPOLOGY), "pTopology")]), StdMethod(Void, "VSGetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(ObjPointer(ID3D11ShaderResourceView), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "VSGetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(ObjPointer(ID3D11SamplerState), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "GetPredication", [Out(Pointer(ObjPointer(ID3D11Predicate)), "ppPredicate"), Out(Pointer(BOOL), "pPredicateValue")]), StdMethod(Void, "GSGetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(ObjPointer(ID3D11ShaderResourceView), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "GSGetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(ObjPointer(ID3D11SamplerState), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "OMGetRenderTargets", [(UINT, "NumViews"), (Array(ObjPointer(ID3D11RenderTargetView), "NumViews"), "ppRenderTargetViews"), Out(Pointer(ObjPointer(ID3D11DepthStencilView)), "ppDepthStencilView")]), StdMethod(Void, "OMGetRenderTargetsAndUnorderedAccessViews", [(UINT, "NumRTVs"), (Array(ObjPointer(ID3D11RenderTargetView), "NumRTVs"), "ppRenderTargetViews"), Out(Pointer(ObjPointer(ID3D11DepthStencilView)), "ppDepthStencilView"), (UINT, "UAVStartSlot"), (UINT, "NumUAVs"), (Array(ObjPointer(ID3D11UnorderedAccessView), "NumUAVs"), "ppUnorderedAccessViews")]), StdMethod(Void, "OMGetBlendState", [Out(Pointer(ObjPointer(ID3D11BlendState)), "ppBlendState"), Out(Array(FLOAT, 4), "BlendFactor"), Out(Pointer(UINT), "pSampleMask")]), StdMethod(Void, "OMGetDepthStencilState", [Out(Pointer(ObjPointer(ID3D11DepthStencilState)), "ppDepthStencilState"), Out(Pointer(UINT), "pStencilRef")]), StdMethod(Void, "SOGetTargets", [(UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppSOTargets")]), StdMethod(Void, "RSGetState", [Out(Pointer(ObjPointer(ID3D11RasterizerState)), "ppRasterizerState")]), StdMethod(Void, "RSGetViewports", [Out(Pointer(UINT), "pNumViewports"), Out(Array(D3D11_VIEWPORT, "*pNumViewports"), "pViewports")]), StdMethod(Void, "RSGetScissorRects", [Out(Pointer(UINT), "pNumRects"), Out(Array(D3D11_RECT, "*pNumRects"), "pRects")]), StdMethod(Void, "HSGetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(ObjPointer(ID3D11ShaderResourceView), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "HSGetShader", [Out(Pointer(ObjPointer(ID3D11HullShader)), "ppHullShader"), Out(Array(ObjPointer(ID3D11ClassInstance), "*pNumClassInstances"), "ppClassInstances"), Out(Pointer(UINT), "pNumClassInstances")]), StdMethod(Void, "HSGetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(ObjPointer(ID3D11SamplerState), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "HSGetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "DSGetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(ObjPointer(ID3D11ShaderResourceView), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "DSGetShader", [Out(Pointer(ObjPointer(ID3D11DomainShader)), "ppDomainShader"), Out(Array(ObjPointer(ID3D11ClassInstance), "*pNumClassInstances"), "ppClassInstances"), Out(Pointer(UINT), "pNumClassInstances")]), StdMethod(Void, "DSGetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(ObjPointer(ID3D11SamplerState), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "DSGetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "CSGetShaderResources", [(UINT, "StartSlot"), (UINT, "NumViews"), (Array(ObjPointer(ID3D11ShaderResourceView), "NumViews"), "ppShaderResourceViews")]), StdMethod(Void, "CSGetUnorderedAccessViews", [(UINT, "StartSlot"), (UINT, "NumUAVs"), (Array(ObjPointer(ID3D11UnorderedAccessView), "NumUAVs"), "ppUnorderedAccessViews")]), StdMethod(Void, "CSGetShader", [Out(Pointer(ObjPointer(ID3D11ComputeShader)), "ppComputeShader"), Out(Array(ObjPointer(ID3D11ClassInstance), "*pNumClassInstances"), "ppClassInstances"), Out(Pointer(UINT), "pNumClassInstances")]), StdMethod(Void, "CSGetSamplers", [(UINT, "StartSlot"), (UINT, "NumSamplers"), (Array(ObjPointer(ID3D11SamplerState), "NumSamplers"), "ppSamplers")]), StdMethod(Void, "CSGetConstantBuffers", [(UINT, "StartSlot"), (UINT, "NumBuffers"), (Array(ObjPointer(ID3D11Buffer), "NumBuffers"), "ppConstantBuffers")]), StdMethod(Void, "ClearState", []), StdMethod(Void, "Flush", []), StdMethod(D3D11_DEVICE_CONTEXT_TYPE, "GetType", []), StdMethod(UINT, "GetContextFlags", []), StdMethod(HRESULT, "FinishCommandList", [(BOOL, "RestoreDeferredContextState"), Out(Pointer(ObjPointer(ID3D11CommandList)), "ppCommandList")]), ] D3D11_CREATE_DEVICE_FLAG = Flags(UINT, [ "D3D11_CREATE_DEVICE_SINGLETHREADED", "D3D11_CREATE_DEVICE_DEBUG", "D3D11_CREATE_DEVICE_SWITCH_TO_REF", "D3D11_CREATE_DEVICE_PREVENT_INTERNAL_THREADING_OPTIMIZATIONS", "D3D11_CREATE_DEVICE_BGRA_SUPPORT", ]) ID3D11Device.methods += [ StdMethod(HRESULT, "CreateBuffer", [(Pointer(Const(D3D11_BUFFER_DESC)), "pDesc"), (Pointer(Const(D3D11_SUBRESOURCE_DATA)), "pInitialData"), Out(Pointer(ObjPointer(ID3D11Buffer)), "ppBuffer")]), StdMethod(HRESULT, "CreateTexture1D", [(Pointer(Const(D3D11_TEXTURE1D_DESC)), "pDesc"), (Pointer(Const(D3D11_SUBRESOURCE_DATA)), "pInitialData"), Out(Pointer(ObjPointer(ID3D11Texture1D)), "ppTexture1D")]), StdMethod(HRESULT, "CreateTexture2D", [(Pointer(Const(D3D11_TEXTURE2D_DESC)), "pDesc"), (Pointer(Const(D3D11_SUBRESOURCE_DATA)), "pInitialData"), Out(Pointer(ObjPointer(ID3D11Texture2D)), "ppTexture2D")]), StdMethod(HRESULT, "CreateTexture3D", [(Pointer(Const(D3D11_TEXTURE3D_DESC)), "pDesc"), (Pointer(Const(D3D11_SUBRESOURCE_DATA)), "pInitialData"), Out(Pointer(ObjPointer(ID3D11Texture3D)), "ppTexture3D")]), StdMethod(HRESULT, "CreateShaderResourceView", [(ObjPointer(ID3D11Resource), "pResource"), (Pointer(Const(D3D11_SHADER_RESOURCE_VIEW_DESC)), "pDesc"), Out(Pointer(ObjPointer(ID3D11ShaderResourceView)), "ppSRView")]), StdMethod(HRESULT, "CreateUnorderedAccessView", [(ObjPointer(ID3D11Resource), "pResource"), (Pointer(Const(D3D11_UNORDERED_ACCESS_VIEW_DESC)), "pDesc"), Out(Pointer(ObjPointer(ID3D11UnorderedAccessView)), "ppUAView")]), StdMethod(HRESULT, "CreateRenderTargetView", [(ObjPointer(ID3D11Resource), "pResource"), (Pointer(Const(D3D11_RENDER_TARGET_VIEW_DESC)), "pDesc"), Out(Pointer(ObjPointer(ID3D11RenderTargetView)), "ppRTView")]), StdMethod(HRESULT, "CreateDepthStencilView", [(ObjPointer(ID3D11Resource), "pResource"), (Pointer(Const(D3D11_DEPTH_STENCIL_VIEW_DESC)), "pDesc"), Out(Pointer(ObjPointer(ID3D11DepthStencilView)), "ppDepthStencilView")]), StdMethod(HRESULT, "CreateInputLayout", [(Array(Const(D3D11_INPUT_ELEMENT_DESC), "NumElements"), "pInputElementDescs"), (UINT, "NumElements"), (Blob(Const(Void), "BytecodeLength"), "pShaderBytecodeWithInputSignature"), (SIZE_T, "BytecodeLength"), Out(Pointer(ObjPointer(ID3D11InputLayout)), "ppInputLayout")]), StdMethod(HRESULT, "CreateVertexShader", [(Blob(Const(Void), "BytecodeLength"), "pShaderBytecode"), (SIZE_T, "BytecodeLength"), (ObjPointer(ID3D11ClassLinkage), "pClassLinkage"), Out(Pointer(ObjPointer(ID3D11VertexShader)), "ppVertexShader")]), StdMethod(HRESULT, "CreateGeometryShader", [(Blob(Const(Void), "BytecodeLength"), "pShaderBytecode"), (SIZE_T, "BytecodeLength"), (ObjPointer(ID3D11ClassLinkage), "pClassLinkage"), Out(Pointer(ObjPointer(ID3D11GeometryShader)), "ppGeometryShader")]), StdMethod(HRESULT, "CreateGeometryShaderWithStreamOutput", [(Blob(Const(Void), "BytecodeLength"), "pShaderBytecode"), (SIZE_T, "BytecodeLength"), (Array(Const(D3D11_SO_DECLARATION_ENTRY), "NumEntries"), "pSODeclaration"), (UINT, "NumEntries"), (Array(Const(UINT), "NumStrides"), "pBufferStrides"), (UINT, "NumStrides"), (UINT, "RasterizedStream"), (ObjPointer(ID3D11ClassLinkage), "pClassLinkage"), Out(Pointer(ObjPointer(ID3D11GeometryShader)), "ppGeometryShader")]), StdMethod(HRESULT, "CreatePixelShader", [(Blob(Const(Void), "BytecodeLength"), "pShaderBytecode"), (SIZE_T, "BytecodeLength"), (ObjPointer(ID3D11ClassLinkage), "pClassLinkage"), Out(Pointer(ObjPointer(ID3D11PixelShader)), "ppPixelShader")]), StdMethod(HRESULT, "CreateHullShader", [(Blob(Const(Void), "BytecodeLength"), "pShaderBytecode"), (SIZE_T, "BytecodeLength"), (ObjPointer(ID3D11ClassLinkage), "pClassLinkage"), Out(Pointer(ObjPointer(ID3D11HullShader)), "ppHullShader")]), StdMethod(HRESULT, "CreateDomainShader", [(Blob(Const(Void), "BytecodeLength"), "pShaderBytecode"), (SIZE_T, "BytecodeLength"), (ObjPointer(ID3D11ClassLinkage), "pClassLinkage"), Out(Pointer(ObjPointer(ID3D11DomainShader)), "ppDomainShader")]), StdMethod(HRESULT, "CreateComputeShader", [(Blob(Const(Void), "BytecodeLength"), "pShaderBytecode"), (SIZE_T, "BytecodeLength"), (ObjPointer(ID3D11ClassLinkage), "pClassLinkage"), Out(Pointer(ObjPointer(ID3D11ComputeShader)), "ppComputeShader")]), StdMethod(HRESULT, "CreateClassLinkage", [Out(Pointer(ObjPointer(ID3D11ClassLinkage)), "ppLinkage")]), StdMethod(HRESULT, "CreateBlendState", [(Pointer(Const(D3D11_BLEND_DESC)), "pBlendStateDesc"), Out(Pointer(ObjPointer(ID3D11BlendState)), "ppBlendState")]), StdMethod(HRESULT, "CreateDepthStencilState", [(Pointer(Const(D3D11_DEPTH_STENCIL_DESC)), "pDepthStencilDesc"), Out(Pointer(ObjPointer(ID3D11DepthStencilState)), "ppDepthStencilState")]), StdMethod(HRESULT, "CreateRasterizerState", [(Pointer(Const(D3D11_RASTERIZER_DESC)), "pRasterizerDesc"), Out(Pointer(ObjPointer(ID3D11RasterizerState)), "ppRasterizerState")]), StdMethod(HRESULT, "CreateSamplerState", [(Pointer(Const(D3D11_SAMPLER_DESC)), "pSamplerDesc"), Out(Pointer(ObjPointer(ID3D11SamplerState)), "ppSamplerState")]), StdMethod(HRESULT, "CreateQuery", [(Pointer(Const(D3D11_QUERY_DESC)), "pQueryDesc"), Out(Pointer(ObjPointer(ID3D11Query)), "ppQuery")]), StdMethod(HRESULT, "CreatePredicate", [(Pointer(Const(D3D11_QUERY_DESC)), "pPredicateDesc"), Out(Pointer(ObjPointer(ID3D11Predicate)), "ppPredicate")]), StdMethod(HRESULT, "CreateCounter", [(Pointer(Const(D3D11_COUNTER_DESC)), "pCounterDesc"), Out(Pointer(ObjPointer(ID3D11Counter)), "ppCounter")]), StdMethod(HRESULT, "CreateDeferredContext", [(UINT, "ContextFlags"), Out(Pointer(ObjPointer(ID3D11DeviceContext)), "ppDeferredContext")]), StdMethod(HRESULT, "OpenSharedResource", [(HANDLE, "hResource"), (REFIID, "ReturnedInterface"), Out(Pointer(ObjPointer(Void)), "ppResource")]), StdMethod(HRESULT, "CheckFormatSupport", [(DXGI_FORMAT, "Format"), Out(Pointer(D3D11_FORMAT_SUPPORT), "pFormatSupport")]), StdMethod(HRESULT, "CheckMultisampleQualityLevels", [(DXGI_FORMAT, "Format"), (UINT, "SampleCount"), Out(Pointer(UINT), "pNumQualityLevels")]), StdMethod(Void, "CheckCounterInfo", [Out(Pointer(D3D11_COUNTER_INFO), "pCounterInfo")]), StdMethod(HRESULT, "CheckCounter", [(Pointer(Const(D3D11_COUNTER_DESC)), "pDesc"), Out(Pointer(D3D11_COUNTER_TYPE), "pType"), Out(Pointer(UINT), "pActiveCounters"), Out(LPSTR, "szName"), Out(Pointer(UINT), "pNameLength"), Out(LPSTR, "szUnits"), Out(Pointer(UINT), "pUnitsLength"), Out(LPSTR, "szDescription"), Out(Pointer(UINT), "pDescriptionLength")]), StdMethod(HRESULT, "CheckFeatureSupport", [(D3D11_FEATURE, "Feature"), Out(D3D11_FEATURE_DATA, "pFeatureSupportData"), (UINT, "FeatureSupportDataSize")]), StdMethod(HRESULT, "GetPrivateData", [(REFGUID, "guid"), Out(Pointer(UINT), "pDataSize"), Out(OpaquePointer(Void), "pData")]), StdMethod(HRESULT, "SetPrivateData", [(REFGUID, "guid"), (UINT, "DataSize"), (OpaqueBlob(Const(Void), "DataSize"), "pData")]), StdMethod(HRESULT, "SetPrivateDataInterface", [(REFGUID, "guid"), (OpaquePointer(Const(IUnknown)), "pData")]), StdMethod(D3D_FEATURE_LEVEL, "GetFeatureLevel", []), StdMethod(D3D11_CREATE_DEVICE_FLAG, "GetCreationFlags", []), StdMethod(HRESULT, "GetDeviceRemovedReason", []), StdMethod(Void, "GetImmediateContext", [Out(Pointer(ObjPointer(ID3D11DeviceContext)), "ppImmediateContext")]), StdMethod(HRESULT, "SetExceptionMode", [(D3D11_RAISE_FLAG, "RaiseFlags")]), StdMethod(UINT, "GetExceptionMode", []), ] d3d11 = API("d3d11") d3d11.addFunctions([ StdFunction(HRESULT, "D3D11CreateDevice", [(ObjPointer(IDXGIAdapter), "pAdapter"), (D3D_DRIVER_TYPE, "DriverType"), (HMODULE, "Software"), (D3D11_CREATE_DEVICE_FLAG, "Flags"), (Array(Const(D3D_FEATURE_LEVEL), "FeatureLevels"), "pFeatureLevels"), (UINT, "FeatureLevels"), (UINT, "SDKVersion"), Out(Pointer(ObjPointer(ID3D11Device)), "ppDevice"), Out(Pointer(D3D_FEATURE_LEVEL), "pFeatureLevel"), Out(Pointer(ObjPointer(ID3D11DeviceContext)), "ppImmediateContext")]), StdFunction(HRESULT, "D3D11CreateDeviceAndSwapChain", [(ObjPointer(IDXGIAdapter), "pAdapter"), (D3D_DRIVER_TYPE, "DriverType"), (HMODULE, "Software"), (D3D11_CREATE_DEVICE_FLAG, "Flags"), (Array(Const(D3D_FEATURE_LEVEL), "FeatureLevels"), "pFeatureLevels"), (UINT, "FeatureLevels"), (UINT, "SDKVersion"), (Pointer(Const(DXGI_SWAP_CHAIN_DESC)), "pSwapChainDesc"), Out(Pointer(ObjPointer(IDXGISwapChain)), "ppSwapChain"), Out(Pointer(ObjPointer(ID3D11Device)), "ppDevice"), Out(Pointer(D3D_FEATURE_LEVEL), "pFeatureLevel"), Out(Pointer(ObjPointer(ID3D11DeviceContext)), "ppImmediateContext")]), # XXX: Undocumented functions, called by d3d11sdklayers.dll when D3D11_CREATE_DEVICE_DEBUG is set StdFunction(HRESULT, "D3D11CoreRegisterLayers", [LPCVOID, DWORD], internal=True), StdFunction(SIZE_T, "D3D11CoreGetLayeredDeviceSize", [LPCVOID, DWORD], internal=True), StdFunction(HRESULT, "D3D11CoreCreateLayeredDevice", [LPCVOID, DWORD, LPCVOID, (REFIID, "riid"), Out(Pointer(ObjPointer(Void)), "ppvObj")], internal=True), StdFunction(HRESULT, "D3D11CoreCreateDevice", [DWORD, DWORD, DWORD, DWORD, DWORD, DWORD, DWORD, DWORD, DWORD], internal=True), ]) d3d11.addInterfaces([ IDXGIAdapter1, IDXGIDevice1, IDXGIResource, ID3D11Debug, ID3D11InfoQueue, ID3D11SwitchToRef, ])

day08.py

Pil0u/adventofcode2020

323

<filename>day08.py from copy import deepcopy def boot(seq): index = 0 played_indices = set() acc = 0 while True: if index == len(seq): return True, acc if index in played_indices: return False, acc played_indices.add(index) line = seq[index].split() op = line[0] value = int(line[1]) if op == 'nop': index += 1 if op == 'acc': acc += value index += 1 if op == 'jmp': index += value def generate_sequences(list_): all_seqs = [] for idx, value in enumerate(list_): if value[:3] == 'nop': seq = deepcopy(list_) seq[idx] = 'jmp' + value[3:] all_seqs.append(seq) if value[:3] == 'jmp': seq = deepcopy(list_) seq[idx] = 'nop' + value[3:] all_seqs.append(seq) return all_seqs def result(input_): # Part 1 part_one = boot(input_)[1] # Part 2 all_sequences = generate_sequences(input_) for sequence in all_sequences: result = boot(sequence) if result[0] is not False: part_two = result[1] break return part_one, part_two

train_fcn.py

onlyNata/segModel

324

# -*- coding: utf-8 -*- """ Created on Tue Jun 26 16:34:21 2018 @author: LiHongWang """ import os import tensorflow as tf from model import fcn_vgg from model import fcn_mobile from model import fcn_resnet_v2 from data import input_data slim = tf.contrib.slim def main(): num_classes=2 tfRecorf_dir= 'D:/dataSet/kitti/road/sub_um_lane_tra66.tfrecord' train_dir = './fm2/' if not os.path.exists(train_dir): os.makedirs(train_dir) with tf.Graph().as_default(): global_step = tf.contrib.framework.get_or_create_global_step() tf.logging.set_verbosity(tf.logging.INFO) with tf.device("/cpu:0"): samples=input_data.get_images_labels(tfRecorf_dir,num_classes,66, crop_size=[224,224], batch_size=4) batch_queue = slim.prefetch_queue.prefetch_queue(samples, capacity=128 ) tra_batch = batch_queue.dequeue() logit,prediction=fcn_mobile.fcn_mobv1(tra_batch['image'],num_classes) # logit,prediction=fcn_vgg.fcn_vgg16(tra_batch['image'],num_classes) # logit,prediction=fcn_resnet_v2.fcn_res101(tra_batch['image'],num_classes) cross_entropy=tf.nn.sparse_softmax_cross_entropy_with_logits(logits=logit, labels=tf.squeeze(tra_batch['label'], squeeze_dims=[3]),name="entropy") loss = tf.reduce_mean(cross_entropy,name='loss') slim.losses.add_loss(loss) total_loss = slim.losses.get_total_loss() # print("image", tra_batch['image']) # print("label", tf.cast(tra_batch['label']*255, tf.uint8)) # print("prediction", tf.cast(prediction*255, tf.uint8)) # Create some summaries to visualize the training process: tf.summary.scalar('losses/Total_Loss', total_loss) tf.summary.image("image", tra_batch['image'], max_outputs=4) tf.summary.image("label", tf.cast(tra_batch['label']*255, tf.uint8), max_outputs=4) tf.summary.image("prediction", tf.cast(prediction*255, tf.uint8), max_outputs=4) lr = tf.train.exponential_decay(0.001, global_step, 10000, 0.8, staircase=True) #lr = tf.constant(0.001, tf.float32) tf.summary.scalar('learning_rate', lr) for variable in slim.get_model_variables(): tf.summary.histogram(variable.op.name, variable) # Specify the optimizer and create the train op: optimizer = tf.train.RMSPropOptimizer(lr,0.9) train_op = slim.learning.create_train_op(total_loss, optimizer) # Run the training: gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.7) config=tf.ConfigProto(gpu_options=gpu_options) final_loss = slim.learning.train(train_op, logdir=train_dir, log_every_n_steps=100, save_summaries_secs=20, save_interval_secs=1800, init_fn=None,#fcn_mobile.get_init_fn(), session_config=config, number_of_steps=65000) print('Finished training. Last batch loss %f' % final_loss) if __name__=='__main__': main()

setup.py

xbabka01/filetype.py

325

#!/usr/bin/env python # -*- coding: utf-8 -*- import codecs from setuptools import find_packages, setup setup( name='filetype', version='1.0.7', description='Infer file type and MIME type of any file/buffer. ' 'No external dependencies.', long_description=codecs.open('README.rst', 'r', encoding='utf-8', errors='ignore').read(), keywords='file libmagic magic infer numbers magicnumbers discovery mime ' 'type kind', url='https://github.com/h2non/filetype.py', download_url='https://github.com/h2non/filetype.py/tarball/master', author='<NAME>', author_email='<EMAIL>', license='MIT', license_files=['LICENSE'], classifiers=[ 'Development Status :: 5 - Production/Stable', 'Environment :: Console', 'Environment :: Web Environment', 'Intended Audience :: Developers', 'Intended Audience :: System Administrators', 'License :: OSI Approved :: MIT License', 'Operating System :: OS Independent', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Topic :: System', 'Topic :: System :: Filesystems', 'Topic :: Utilities'], platforms=['any'], packages=find_packages(exclude=['dist', 'build', 'docs', 'tests', 'examples']), package_data={'filetype': ['LICENSE', '*.md']}, zip_safe=True)

demos/netmiko_textfsm.py

ryanaa08/NPA

326

# make sure templates are present and netmiko knows about them # git clone https://github.com/networktocode/ntc-templates # export NET_TEXTFSM=/home/ntc/ntc-templates/templates/ # see https://github.com/networktocode/ntc-templates/tree/master/templates # for list of templates from netmiko import ConnectHandler import json user = 'ntc' pwd = '<PASSWORD>' d_type = 'cisco_ios' csr1 = ConnectHandler(ip='csr1', username=user, password=pwd, device_type=d_type) sh_ip_int_br = csr1.send_command("show ip int brief", use_textfsm=True) # [{'status': 'up', 'intf': 'GigabitEthernet1', 'ipaddr': '10.0.0.51', 'proto': 'up'}, {'status': 'up', 'intf': 'GigabitEthernet2', 'ipaddr': 'unassigned', 'proto': 'up'}, {'status': 'up', 'intf': 'GigabitEthernet3', 'ipaddr': 'unassigned', 'proto': 'up'}, {'status': 'up', 'intf': 'GigabitEthernet4', 'ipaddr': '172.16.17.32', 'proto': 'up'}, {'status': 'up', 'intf': 'Loopback100', 'ipaddr': '10.200.1.20', 'proto': 'up'}] # is type list print (type(sh_ip_int_br)) # list of dicts print (type(sh_ip_int_br[0])) for each_dict in sh_ip_int_br: print "\n" for key in each_dict.keys(): print key for each_dict in sh_ip_int_br: print "\n" for key, value in each_dict.items(): print key + " is " + value sh_ver_ios = csr1.send_command("show version", use_textfsm=True) # [{'running_image': 'packages.conf', 'hostname': 'csr1', 'uptime': '6 hours, 59 minutes', 'config_register': '0x2102', 'hardware': ['CSR1000V'], 'version': '16.6.2', 'serial': ['9KIBQAQ3OPE'], 'rommon': 'IOS-XE'}] # print the json nicely print (json.dumps(sh_ver_ios, indent=4)) print sh_ver_ios # list print type(sh_ver_ios) # each item is a dict print type(sh_ver_ios[0]) # list of dicts with some nested lists with the dicts for each_dict in sh_ver_ios: print "\n" for key, value in each_dict.items(): if type(value) is list: print key + " is " for list_entry in value: print list_entry if type(value) is str: print key + " is " + value

iap/validate_jwt.py

spitfire55/python-docs-samples

327

<gh_stars>1-10 # Copyright 2016 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Sample showing how to validate the Identity-Aware Proxy (IAP) JWT. This code should be used by applications in Google Compute Engine-based environments (such as Google App Engine flexible environment, Google Compute Engine, or Google Container Engine) to provide an extra layer of assurance that a request was authorized by IAP. For applications running in the App Engine standard environment, use App Engine's Users API instead. """ # [START iap_validate_jwt] import jwt import requests def validate_iap_jwt_from_app_engine(iap_jwt, cloud_project_number, cloud_project_id): """Validate a JWT passed to your App Engine app by Identity-Aware Proxy. Args: iap_jwt: The contents of the X-Goog-IAP-JWT-Assertion header. cloud_project_number: The project *number* for your Google Cloud project. This is returned by 'gcloud projects describe $PROJECT_ID', or in the Project Info card in Cloud Console. cloud_project_id: The project *ID* for your Google Cloud project. Returns: (user_id, user_email, error_str). """ expected_audience = '/projects/{}/apps/{}'.format( cloud_project_number, cloud_project_id) return _validate_iap_jwt(iap_jwt, expected_audience) def validate_iap_jwt_from_compute_engine(iap_jwt, cloud_project_number, backend_service_id): """Validate an IAP JWT for your (Compute|Container) Engine service. Args: iap_jwt: The contents of the X-Goog-IAP-JWT-Assertion header. cloud_project_number: The project *number* for your Google Cloud project. This is returned by 'gcloud projects describe $PROJECT_ID', or in the Project Info card in Cloud Console. backend_service_id: The ID of the backend service used to access the application. See https://cloud.google.com/iap/docs/signed-headers-howto for details on how to get this value. Returns: (user_id, user_email, error_str). """ expected_audience = '/projects/{}/global/backendServices/{}'.format( cloud_project_number, backend_service_id) return _validate_iap_jwt(iap_jwt, expected_audience) def _validate_iap_jwt(iap_jwt, expected_audience): try: key_id = jwt.get_unverified_header(iap_jwt).get('kid') if not key_id: return (None, None, '**ERROR: no key ID**') key = get_iap_key(key_id) decoded_jwt = jwt.decode( iap_jwt, key, algorithms=['ES256'], audience=expected_audience) return (decoded_jwt['sub'], decoded_jwt['email'], '') except (jwt.exceptions.InvalidTokenError, requests.exceptions.RequestException) as e: return (None, None, '**ERROR: JWT validation error {}**'.format(e)) def get_iap_key(key_id): """Retrieves a public key from the list published by Identity-Aware Proxy, re-fetching the key file if necessary. """ key_cache = get_iap_key.key_cache key = key_cache.get(key_id) if not key: # Re-fetch the key file. resp = requests.get( 'https://www.gstatic.com/iap/verify/public_key') if resp.status_code != 200: raise Exception( 'Unable to fetch IAP keys: {} / {} / {}'.format( resp.status_code, resp.headers, resp.text)) key_cache = resp.json() get_iap_key.key_cache = key_cache key = key_cache.get(key_id) if not key: raise Exception('Key {!r} not found'.format(key_id)) return key # Used to cache the Identity-Aware Proxy public keys. This code only # refetches the file when a JWT is signed with a key not present in # this cache. get_iap_key.key_cache = {} # [END iap_validate_jwt]

examples/calc.py

manatlan/htag

328

<filename>examples/calc.py<gh_stars>1-10 import os,sys; sys.path.insert(0,os.path.dirname(os.path.dirname(__file__))) from htag import Tag """ This example show you how to make a "Calc App" (with physical buttons + keyboard events) There is no work for rendering the layout ;-) Can't be simpler ! """ class Calc(Tag.div): statics=[Tag.H.style(""" .mycalc *,button {font-size:2em;font-family: monospace} """)] def init(self): self.txt="" self.aff = Tag.Div("&nbsp;",_style="border:1px solid black") self["class"]="mycalc" self <= self.aff self <= Tag.button("C", _onclick=self.bind( self.clean) ) self <= [Tag.button(i, _onclick=self.bind( self.press, i) ) for i in "0123456789+-x/."] self <= Tag.button("=", _onclick=self.bind( self.compute ) ) #-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/ with real keyboard self["onkeyup"] = self.bind( self.presskey, b"event.key" ) def presskey(self,key): if key in "0123456789+-*/.": self.press(key) elif key=="Enter": self.compute() elif key in ["Delete","Backspace"]: self.clean() #-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/ def press(self,val): self.txt += val self.aff.set( self.txt ) def compute(self): try: self.txt = str(eval(self.txt.replace("x","*"))) self.aff.set( self.txt ) except: self.txt = "" self.aff.set( "Error" ) def clean(self): self.txt="" self.aff.set("&nbsp;") if __name__=="__main__": # import logging # logging.basicConfig(format='[%(levelname)-5s] %(name)s: %(message)s',level=logging.DEBUG) # logging.getLogger("htag.tag").setLevel( logging.INFO ) # and execute it in a pywebview instance from htag.runners import * # here is another runner, in a simple browser (thru ajax calls) BrowserHTTP( Calc ).run() # PyWebWiew( Calc ).run()

res/example1.py

tghira16/Giraphics

329

<filename>res/example1.py from giraphics.graphing.graph import Graph def func(x): return (x-3)*(x+2)*x*0.2 g = Graph(800,600,8,6, 'example1.svg') g.bg() g.grid() g.axes() g.graph(func) g.save() g.display()

tools/data.py

seanys/2D-Irregular-Packing-Algorithm

330

from tools.geofunc import GeoFunc import pandas as pd import json def getData(index): '''报错数据集有（空心）：han,jakobs1,jakobs2 ''' '''形状过多暂时未处理：shapes、shirt、swim、trousers''' name=["ga","albano","blaz1","blaz2","dighe1","dighe2","fu","han","jakobs1","jakobs2","mao","marques","shapes","shirts","swim","trousers"] print("开始处理",name[index],"数据集") '''暂时没有考虑宽度，全部缩放来表示''' scale=[100,0.5,100,100,20,20,20,10,20,20,0.5,20,50] print("缩放",scale[index],"倍") df = pd.read_csv("data/"+name[index]+".csv") polygons=[] for i in range(0,df.shape[0]): for j in range(0,df['num'][i]): poly=json.loads(df['polygon'][i]) GeoFunc.normData(poly,scale[index]) polygons.append(poly) return polygons

src/trw/reporting/__init__.py

civodlu/trw

331

<reponame>civodlu/trw #from trw.utils import collect_hierarchical_module_name, collect_hierarchical_parameter_name, get_batch_n, to_value, \ # safe_lookup, len_batch from .export import as_image_ui8, as_rgb_image, export_image, export_sample, export_as_image from .table_sqlite import TableStream, SQLITE_TYPE_PATTERN, get_table_number_of_rows from .reporting_bokeh import report, create_default_reporting_options from .reporting_bokeh_samples import PanelDataSamplesTabular

vframe_cli/commands/templates/image-mp.py

julescarbon/vframe

332

############################################################################# # # VFRAME # MIT License # Copyright (c) 2020 <NAME> and VFRAME # https://vframe.io # ############################################################################# import click @click.command('') @click.option('-i', '--input', 'opt_dir_in', required=True) @click.option('-r', '--recursive', 'opt_recursive', is_flag=True) @click.option('-e', '--ext', 'opt_exts', default=['jpg', 'png'], multiple=True, help='Glob extension') @click.option('--slice', 'opt_slice', type=(int, int), default=(None, None), help='Slice list of files') @click.option('-t', '--threads', 'opt_threads', default=None) @click.pass_context def cli(ctx, opt_dir_in, opt_recursive, opt_exts, opt_slice, opt_threads): """Multiprocessor image template""" # ------------------------------------------------ # imports from os.path import join from pathlib import Path from dataclasses import asdict import numpy as np import cv2 as cv from tqdm import tqdm from pathos.multiprocessing import ProcessingPool as Pool from pathos.multiprocessing import cpu_count from vframe.settings import app_cfg from vframe.settings.modelzoo_cfg import modelzoo from vframe.models.dnn import DNN from vframe.image.dnn_factory import DNNFactory from vframe.utils import file_utils from vframe.utils.video_utils import FileVideoStream, mediainfo log = app_cfg.LOG # set N threads if not opt_threads: opt_threads = cpu_count() # maximum # glob items fp_items = file_utils.glob_multi(opt_dir_in, opt_exts, recursive=opt_recursive) if any(opt_slice): fp_items = fp_items[opt_slice[0]:opt_slice[1]] log.info(f'Processing: {len(fp_items):,} files') # ----------------------------------------------------------- # start pool worker def pool_worker(pool_item): # init threaded video reader fp = pool_item['fp'] result = {'fp': fp} # add media metadata im = cv.imread(fp) for i in range(20): im = cv.blur(im, (35,35)) return result # end pool worker # ----------------------------------------------------------- # convert file list into object with pool_items = [{'fp': fp} for fp in fp_items] # init processing pool iterator # use imap instead of map via @hkyi Stack Overflow 41920124 desc = f'image-mp x{opt_threads}' with Pool(opt_threads) as p: pool_results = list(tqdm(p.imap(pool_worker, pool_items), total=len(fp_items), desc=desc))

src/learndash/api_resources/user.py

MarkMacDon/learndash-python

333

<filename>src/learndash/api_resources/user.py import learndash from learndash.api_resources.abstract import ListableAPIResource from learndash.api_resources.abstract import RetrievableAPIResource from learndash.api_resources.abstract import UpdateableAPIResource from learndash.api_resources.abstract import NestedAPIResource from learndash.api_resources.typing import UserDict from learndash.api_resources.typing import UserCourseProgressDict from learndash.api_resources.typing import UserCourseDict from learndash.api_resources.typing import UserGroupDict from learndash.api_resources.typing import UserQuizProgressDict class User(RetrievableAPIResource[UserDict], ListableAPIResource[UserDict]): api_path = learndash.path_users def course_progress(self, id=None): return UserCourseProgress(id, parent=self) def courses(self, id=None): return UserCourse(id, parent=self) def groups(self, id=None): return UserGroup(id, parent=self) def quiz_progress(self, id=None): return UserQuizProgress(id, parent=self) class UserCourseProgress(ListableAPIResource[UserCourseProgressDict], NestedAPIResource): api_path = learndash.path_user_course_progress # class UserCourseProgressSteps(ListableAPIResource, NestedAPIResource): class UserCourse(ListableAPIResource[UserCourseDict], UpdateableAPIResource, NestedAPIResource): # also deletable api_path = learndash.path_user_courses def instance_url(self): # This endpoint accepts updates and deletions at it's base endpoint return self.class_url() class UserGroup(ListableAPIResource[UserGroupDict], UpdateableAPIResource, NestedAPIResource): # also deleteable api_path = learndash.path_user_groups def instance_url(self): # This endpoint accepts updates and deletions at it's base endpoint return self.class_url() class UserQuizProgress(ListableAPIResource[UserQuizProgressDict], NestedAPIResource): api_path = learndash.path_user_quiz_progress

lib/galaxy/tool_util/deps/container_resolvers/__init__.py

sneumann/galaxy

334

<filename>lib/galaxy/tool_util/deps/container_resolvers/__init__.py<gh_stars>1-10 """The module defines the abstract interface for resolving container images for tool execution.""" from abc import ( ABCMeta, abstractmethod, abstractproperty, ) import six from galaxy.util.dictifiable import Dictifiable @six.python_2_unicode_compatible @six.add_metaclass(ABCMeta) class ContainerResolver(Dictifiable): """Description of a technique for resolving container images for tool execution.""" # Keys for dictification. dict_collection_visible_keys = ['resolver_type', 'can_uninstall_dependencies'] can_uninstall_dependencies = False def __init__(self, app_info=None, **kwds): """Default initializer for ``ContainerResolver`` subclasses.""" self.app_info = app_info self.resolver_kwds = kwds def _get_config_option(self, key, default=None): """Look in resolver-specific settings for option and then fallback to global settings. """ if self.app_info and hasattr(self.app_info, key): return getattr(self.app_info, key) else: return default @abstractmethod def resolve(self, enabled_container_types, tool_info, **kwds): """Find a container matching all supplied requirements for tool. The supplied argument is a :class:`galaxy.tool_util.deps.containers.ToolInfo` description of the tool and its requirements. """ @abstractproperty def resolver_type(self): """Short label for the type of container resolution.""" def _container_type_enabled(self, container_description, enabled_container_types): """Return a boolean indicating if the specified container type is enabled.""" return container_description.type in enabled_container_types def __str__(self): return "%s[]" % self.__class__.__name__

projects/eyetracking/gen_adhd_sin.py

nirdslab/streaminghub

335

<reponame>nirdslab/streaminghub #!/usr/bin/env python3 import glob import os import pandas as pd import dfs SRC_DIR = f"{dfs.get_data_dir()}/adhd_sin_orig" OUT_DIR = f"{dfs.get_data_dir()}/adhd_sin" if __name__ == '__main__': files = glob.glob(f"{SRC_DIR}/*.csv") file_names = list(map(os.path.basename, files)) for file_name in file_names: df: pd.DataFrame = pd.read_csv(f'{SRC_DIR}/{file_name}').set_index('EyeTrackerTimestamp').sort_index()[ ['GazePointX (ADCSpx)', 'GazePointY (ADCSpx)', 'PupilLeft', 'PupilRight']].reset_index() df.columns = ['t', 'x', 'y', 'dl', 'dr'] # fill blanks (order=interpolate(inter)->bfill+ffill(edges))->zerofill df = df.apply(lambda x: x.interpolate().fillna(method="bfill").fillna(method="ffill")).fillna(0) df['x'] = df['x'] / 1920 df['y'] = df['y'] / 1080 df['d'] = (df['dl'] + df['dr']) / 2 # start with t=0, and set unit to ms df['t'] = (df['t'] - df['t'].min()) / 1000 df = df[['t', 'x', 'y', 'd']].round(6).set_index('t') df.to_csv(f'{OUT_DIR}/{file_name}') print(f'Processed: {file_name}')

dataProcessing.py

TauferLab/PENGUIN

336

import pandas as pd import numpy as np import matplotlib.pyplot as plt import os import matplotlib.pyplot as plt import CurveFit import shutil #find all DIRECTORIES containing non-hidden files ending in FILENAME def getDataDirectories(DIRECTORY, FILENAME="valLoss.txt"): directories=[] for directory in os.scandir(DIRECTORY): for item in os.scandir(directory): if item.name.endswith(FILENAME) and not item.name.startswith("."): directories.append(directory.path) return directories #get all non-hidden data files in DIRECTORY with extension EXT def getDataFiles(DIRECTORY, EXT='txt'): datafiles=[] for item in os.scandir(DIRECTORY): if item.name.endswith("."+EXT) and not item.name.startswith("."): datafiles.append(item.path) return datafiles #checking if loss ever doesn't decrease for numEpochs epochs in a row. def stopsDecreasing(loss, epoch, numEpochs): minLoss=np.inf epochMin=0 for i in range(0,loss.size): if loss[i] < minLoss: minLoss=loss[i] epochMin=epoch[i] elif (epoch[i]-epochMin) >= numEpochs: return i, minLoss return i, minLoss #dirpath is where the accuracy and loss files are stored. want to move the files into the same format expected by grabNNData. def createFolders(SEARCHDIR, SAVEDIR): for item in os.scandir(SEARCHDIR): name=str(item.name) files=name.split('-') SAVEFULLDIR=SAVEDIR+str(files[0]) if not os.path.exists(SAVEFULLDIR): try: os.makedirs(SAVEFULLDIR) except FileExistsError: #directory already exists--must have been created between the if statement & our attempt at making directory pass shutil.move(item.path, SAVEFULLDIR+"/"+str(files[1])) #a function to read in information (e.g. accuracy, loss) stored at FILENAME def grabNNData(FILENAME, header='infer', sep=' '): data = pd.read_csv(FILENAME, sep, header=header) if ('epochs' in data.columns) and ('trainLoss' in data.columns) and ('valLoss' in data.columns) and ('valAcc' in data.columns) and ('batch_size' in data.columns) and ('learning_rate' in data.columns): sortedData=data.sort_values(by="epochs", axis=0, ascending=True) epoch=np.array(sortedData['epochs']) trainLoss=np.array(sortedData['trainLoss']) valLoss=np.array(sortedData['valLoss']) valAcc=np.array(sortedData['valAcc']) batch_size=np.array(sortedData['batch_size']) learning_rate=np.array(sortedData['learning_rate']) convKers=np.array(sortedData['convKernels']) return(epoch, trainLoss, valLoss, valAcc, batch_size, learning_rate, convKers) elif ('epochs' in data.columns) and ('trainLoss' in data.columns) and ('valLoss' in data.columns) and ('valAcc' in data.columns): sortedData=data.sort_values(by="epochs", axis=0, ascending=True) epoch=np.array(sortedData['epochs']) trainLoss=np.array(sortedData['trainLoss']) valLoss=np.array(sortedData['valLoss']) valAcc=np.array(sortedData['valAcc']) else: print("Missing a column in NN datafile") raise Exception('NN datafile is missing one of the expected columns: epochs trainLoss valLoss valAcc [optional extra columns: batch_size, learning_rate]') #slice data could be used to test values of E other than E=0.5, which we use by default def sliceData(xsize, x, y, z=None, w=None): #we can slice the data to sample less often, but not more often. We verify that we're not being asked for a granularity that is smaller than the frequency of datapoints in the vectors. if x[0] > xsize: return x,y,z,w else: result=(1.0/x[0])*xsize #result is how often we should take datapoints if we wish to consider values every xsize x=x[int(result-1)::int(result)] y=y[int(result-1)::int(result)] if z is not None: z=z[int(result-1)::int(result)] if w is None: return x,y,z else: return x,y #if we get to this point in function, it means z and w are both not None. w=w[int(result-1)::int(result)] return x,y,z,w

algo_probs/newcoder/classic/nc52.py

Jackthebighead/recruiment-2022

337

<filename>algo_probs/newcoder/classic/nc52.py # 题意：给出一个仅包含字符'(',')','{','}','['和']',的字符串，判断给出的字符串是否是合法的括号序列。括号必须以正确的顺序关闭，"()"和"()[]{}"都是合法的括号序列，但"(]"和"([)]"不合法。 # @param s string字符串 # @return bool布尔型 # class Solution: def isValid(self , s ): # write code here if not s: return True stack = [] dic = {'{':'}','[':']','(':')'} for char in s: if not stack or char in dic: stack.append(char) elif stack and dic.get(stack[-1])!=char: return False else: stack.pop() continue return True

piecrust/processing/util.py

airbornemint/PieCrust2

338

import os.path import time import logging import yaml from piecrust.processing.base import Processor logger = logging.getLogger(__name__) class _ConcatInfo(object): timestamp = 0 files = None delim = "\n" class ConcatProcessor(Processor): PROCESSOR_NAME = 'concat' def __init__(self): super(ConcatProcessor, self).__init__() self._cache = {} def matches(self, path): return path.endswith('.concat') def getDependencies(self, path): info = self._load(path) return info.files def getOutputFilenames(self, filename): return [filename[:-7]] def process(self, path, out_dir): dirname, filename = os.path.split(path) out_path = os.path.join(out_dir, filename[:-7]) info = self._load(path) if not info.files: raise Exception("No files specified in: %s" % os.path.relpath(path, self.app.root_dir)) logger.debug("Concatenating %d files to: %s" % (len(info.files), out_path)) encoded_delim = info.delim.encode('utf8') with open(out_path, 'wb') as ofp: for p in info.files: with open(p, 'rb') as ifp: ofp.write(ifp.read()) if info.delim: ofp.write(encoded_delim) return True def _load(self, path): cur_time = time.time() info = self._cache.get(path) if (info is not None and (cur_time - info.timestamp <= 1 or os.path.getmtime(path) < info.timestamp)): return info if info is None: info = _ConcatInfo() self._cache[path] = info with open(path, 'r') as fp: config = yaml.load(fp) info.files = config.get('files', []) info.delim = config.get('delim', "\n") info.timestamp = cur_time path_mode = config.get('path_mode', 'relative') if path_mode == 'relative': dirname, _ = os.path.split(path) info.files = [os.path.join(dirname, f) for f in info.files] elif path_mode == 'absolute': info.files = [os.path.join(self.app.root_dir, f) for f in info.files] else: raise Exception("Unknown path mode: %s" % path_mode) return info

src/events/cell_pressed.py

ArcosJuan/Get-out-of-my-fucking-maze

339

from src.events import Event class CellPressed(Event): def __init__(self, position): self.position = position def get_position(self): return self.position

TopQuarkAnalysis/TopJetCombination/python/TtSemiLepJetCombMaxSumPtWMass_cfi.py

ckamtsikis/cmssw

340

import FWCore.ParameterSet.Config as cms # # module to make the MaxSumPtWMass jet combination # findTtSemiLepJetCombMaxSumPtWMass = cms.EDProducer("TtSemiLepJetCombMaxSumPtWMass", ## jet input jets = cms.InputTag("selectedPatJets"), ## lepton input leps = cms.InputTag("selectedPatMuons"), ## maximum number of jets to be considered maxNJets = cms.int32(4), ## nominal WMass parameter (in GeV) wMass = cms.double(80.4), ## use b-tagging two distinguish between light and b jets useBTagging = cms.bool(False), ## choose algorithm for b-tagging bTagAlgorithm = cms.string("trackCountingHighEffBJetTags"), ## minimum b discriminator value required for b jets and ## maximum b discriminator value allowed for non-b jets minBDiscBJets = cms.double(1.0), maxBDiscLightJets = cms.double(3.0) )

xortool/__init__.py

runapp/xortool

341

<reponame>runapp/xortool<filename>xortool/__init__.py #!/usr/bin/env python #-*- coding:utf-8 -*- __all__ = ["args", "colors", "libcolors", "routine"] __version__ = "0.96"

baopig/ressources/ressources.py

ChreSyr/baopig

342

<gh_stars>0 from baopig.pybao.objectutilities import Object from baopig.pybao.issomething import * class RessourcePack: def config(self, **kwargs): for name, value in kwargs.items(): self.__setattr__('_'+name, value) class FontsRessourcePack(RessourcePack): def __init__(self, file=None, height=15, color=(0, 0, 0), ): assert is_color(color) self._file = file self._height = height self._color = color file = property(lambda self: self._file) color = property(lambda self: self._color) height = property(lambda self: self._height) class ScenesRessourcePack(RessourcePack): def __init__(self, background_color=(170, 170, 170), ): assert is_color(background_color) self._background_color = background_color background_color = property(lambda self: self._background_color) # TODO : ButtonRessourcePack.style.create_surface(size) class _RessourcePack: def __init__(self): self.font = FontsRessourcePack() self.scene = ScenesRessourcePack() ressources = _RessourcePack()

bufr_extract_unique_stations.py

glamod/glamod-misc

343

#!/usr/bin/python2.7 """ Extract unique set of station locations (and names) along with number of obs RJHD - Exeter - October 2017 """ # ECMWF import defaults import traceback import sys from eccodes import * # RJHD imports import cartopy import numpy as np import matplotlib as mpl mpl.use('Agg') import matplotlib.pyplot as plt import gc VERBOSE = 1 # verbose error reporting. ATTRS = [ 'code', 'units', 'scale', 'reference', 'width' ] INTMDI = 2147483647 #*************************************************** def process_file(infilename, station_names, fixed_station, latitudes, longitudes, observations, start_year, end_year): infile = open(infilename) year = int(infilename.split(".")[0].split("_")[-1]) cmatch = 0 counter = 0 # loop all messages (with stop statement) while 1: """OPEN MESSAGE""" # get handle for message bufr = codes_bufr_new_from_file(infile) if bufr is None: break if counter%100000 == 0: print "message: {:d}".format(counter) # we need to instruct ecCodes to expand all the descriptors # i.e. unpack the data values codes_set(bufr, 'unpack', 1) """ITERATOR TO EXTRACT KEYS""" these_keys = [] # get BUFR key iterator iterid = codes_bufr_keys_iterator_new(bufr) # loop over the keys while codes_bufr_keys_iterator_next(iterid): # print key name keyname = codes_bufr_keys_iterator_get_name(iterid) # print(" %s" % keyname) these_keys += [keyname] # delete the key iterator codes_bufr_keys_iterator_delete(iterid) # Use these to select obs from land/marine surface name_keys = ["#1#shipOrMobileLandStationIdentifier", "#1#stationNumber"] processed = False for nk in name_keys: if nk in these_keys: try: name = codes_get(bufr, nk) lat = codes_get(bufr, "#1#latitude") lon = codes_get(bufr, "#1#longitude") sloc = tloc = nloc = [-1] if name in station_names: sloc, = np.where(station_names == name) if lat in latitudes: tloc, = np.where(latitudes == lat) if lon in longitudes: nloc, = np.where(longitudes == lon) if tloc[0] == -1 and nloc[0] == -1: # if not in list, then add station_names = np.append(station_names, name) latitudes = np.append(latitudes, lat) longitudes = np.append(longitudes, lon) observations = np.append(observations, 1) start_year = np.append(start_year, year) end_year = np.append(end_year, year) # allow splitting of land and marine/mobile if nk == "#1#stationNumber": fixed_station = np.append(fixed_station, True) else: fixed_station = np.append(fixed_station, False) elif (tloc[0] != -1 or nloc[0] != -1) and tloc[0] != nloc[0]: # add if one element of position is unique station_names = np.append(station_names, name) latitudes = np.append(latitudes, lat) longitudes = np.append(longitudes, lon) observations = np.append(observations, 1) start_year = np.append(start_year, year) end_year = np.append(end_year, year) # allow splitting of land and marine/mobile if nk == "#1#stationNumber": fixed_station = np.append(fixed_station, True) else: fixed_station = np.append(fixed_station, False) elif tloc[0] != -1 and tloc[0] == nloc[0]: # if position matches exactly, up observation counter observations[tloc[0]] += 1 end_year[tloc[0]] = year # allow splitting of land and marine/mobile if nk == "#1#stationNumber": if fixed_station[tloc[0]] != True: # if listed as land and now marine, take marine fixed_station[tloc[0]] = False else: if fixed_station[tloc[0]] != False: # easier to leave as mobile/marine than to move # hopefully will stand out later pass else: cmatch += 1 processed = True except CodesInternalError: raw_input("key error?") # check for new keys which give station ID information if not processed: other_keys = ["#1#carrierBalloonOrAircraftIdentifier", "#1#aircraftFlightNumber"] new_key = True for ok in other_keys: if ok in these_keys: new_key = False if new_key: raw_input(these_keys) # if counter > 10000: break counter += 1 codes_release(bufr) # print "Number of unique locations in this year: {}".format(len(latitudes)) return station_names, fixed_station, latitudes, longitudes, observations, start_year, end_year # process_file #*************************************************** def scatter_map(outname, data, lons, lats, cmap, bounds, cb_label, title = "", figtext = "", doText = False): ''' Standard scatter map :param str outname: output filename root :param array data: data to plot :param array lons: longitudes :param array lats: latitudes :param obj cmap: colourmap to use :param array bounds: bounds for discrete colormap :param str cb_label: colorbar label ''' norm=mpl.cm.colors.BoundaryNorm(bounds,cmap.N) fig = plt.figure(figsize =(10,6.5)) plt.clf() ax = plt.axes([0.05, 0.10, 0.90, 0.90], projection=cartopy.crs.Robinson()) ax.gridlines() #draw_labels=True) ax.add_feature(cartopy.feature.LAND, zorder = 0, facecolor = "0.9", edgecolor = "k") ax.coastlines() ext = ax.get_extent() # save the original extent scatter = plt.scatter(lons, lats, c = data, cmap = cmap, norm = norm, s=10, \ transform = cartopy.crs.Geodetic(), edgecolor = "r", linewidth = 0.1) cb=plt.colorbar(scatter, orientation = 'horizontal', pad = 0.05, fraction = 0.05, \ aspect = 30, ticks = bounds[1:-1], label = cb_label, drawedges=True) # thicken border of colorbar and the dividers # http://stackoverflow.com/questions/14477696/customizing-colorbar-border-color-on-matplotlib # cb.set_ticklabels(["{:g}".format(b) for b in bounds[1:-1]]) # cb.outline.set_color('k') # cb.outline.set_linewidth(2) cb.dividers.set_color('k') cb.dividers.set_linewidth(2) ax.set_extent(ext, ax.projection) # fix the extent change from colormesh plt.title(title) if doText: plt.text(0.01, 0.98, "#stations: {}".format(data.shape[0]), transform = ax.transAxes, fontsize = 10) plt.savefig(outname) plt.close() return # scatter_map #*************************************************** def main(ms = "era40_", year = 1980): LOCS = "/group_workspaces/jasmin2/c3s311a_lot2/data/incoming/mars/v20170628/data/" print year station_names = np.array([]) fixed_station = np.array([]) latitudes = np.array([]) longitudes = np.array([]) observations = np.array([]) start_year = np.array([]) end_year = np.array([]) if ms == "erai_" and year < 1979: return else: INFILE = "{}mars_{}{}.bufr".format(LOCS, ms, year) try: station_names, fixed_station, latitudes, longitudes, observations, start_year, end_year = \ process_file(INFILE, station_names, fixed_station, latitudes, longitudes, observations, start_year, end_year) except CodesInternalError as err: if VERBOSE: traceback.print_exc(file=sys.stderr) else: sys.stderr.write(err.msg + '\n') land = np.where(np.array(fixed_station) == True) marine = np.where(np.array(fixed_station) == False) bounds = np.linspace(0,max(observations),10).astype(int) cmap = plt.cm.YlOrRd_r if ms == "erai_": title = "MARS - SYNOP - {}".format(year) else: title = "MARS - ERA40 - {}".format(year) scatter_map("mars_{}{}_land_observations.png".format(ms, year), observations[land], longitudes[land], latitudes[land], cmap, bounds, "Number of Observations", title, doText = True) scatter_map("mars_{}{}_marine_observations.png".format(ms, year), observations[marine], longitudes[marine], latitudes[marine], cmap, bounds, "Number of Observations", title) station_names = 0 fixed_station = 0 latitudes = 0 longitudes = 0 observations = 0 start_year = 0 end_year = 0 land = 0 marine = 0 gc.collect() return # main #*************************************************** if __name__ == "__main__": import argparse # set up keyword arguments parser = argparse.ArgumentParser() parser.add_argument('--ms', dest='ms', action='store', default = "era40_", help='Run on ERA40 ["era40_"] (default) or ERA-I ["erai_"] data') parser.add_argument('--year', dest='year', action='store', default = 1980, help='Which year to process - default 1980') args = parser.parse_args() main(ms = args.ms, year = args.year) sys.exit() #*************************************************** # END #***************************************************

libsaas/services/twilio/applications.py

MidtownFellowship/libsaas

344

<gh_stars>100-1000 from libsaas import http, parsers from libsaas.services import base from libsaas.services.twilio import resource class ApplicationsBase(resource.TwilioResource): path = 'Applications' class Application(ApplicationsBase): def create(self, *args, **kwargs): raise base.MethodNotSupported() class Applications(ApplicationsBase): @base.apimethod def get(self, FriendlyName=None, Page=None, PageSize=None, AfterSid=None): """ Fetch the Applications belonging to an account. :var FriendlyName: Only return the Account resources with friendly names that exactly match this name. :vartype FriendlyName: str :var Page: The current page number. Zero-indexed, so the first page is 0. :vartype Page: int :var PageSize: How many resources to return in each list page. The default is 50, and the maximum is 1000. :vartype PageSize: int :var AfterSid: The last Sid returned in the previous page, used to avoid listing duplicated resources if new ones are created while paging. :vartype AfterSid: str """ params = resource.get_params(None, locals()) request = http.Request('GET', self.get_url(), params) return request, parsers.parse_json def update(self, *args, **kwargs): raise base.MethodNotSupported() def delete(self, *args, **kwargs): raise base.MethodNotSupported() class ConnectAppsBase(resource.TwilioResource): path = 'ConnectApps' def create(self, *args, **kwargs): raise base.MethodNotSupported() def delete(self, *args, **kwargs): raise base.MethodNotSupported() class ConnectApp(ConnectAppsBase): pass class ConnectApps(ConnectAppsBase): @base.apimethod def get(self, Page=None, PageSize=None, AfterSid=None): """ Fetch the Connect Apps belonging to an account. :var Page: The current page number. Zero-indexed, so the first page is 0. :vartype Page: int :var PageSize: How many resources to return in each list page. The default is 50, and the maximum is 1000. :vartype PageSize: int :var AfterSid: The last Sid returned in the previous page, used to avoid listing duplicated resources if new ones are created while paging. :vartype AfterSid: str """ params = resource.get_params(None, locals()) request = http.Request('GET', self.get_url(), params) return request, parsers.parse_json def update(self, *args, **kwargs): raise base.MethodNotSupported() class AuthorizedConnectAppsBase(resource.TwilioResource): path = 'AuthorizedConnectApps' def create(self, *args, **kwargs): raise base.MethodNotSupported() def update(self, *args, **kwargs): raise base.MethodNotSupported() def delete(self, *args, **kwargs): raise base.MethodNotSupported() class AuthorizedConnectApp(AuthorizedConnectAppsBase): pass class AuthorizedConnectApps(AuthorizedConnectAppsBase): @base.apimethod def get(self, Page=None, PageSize=None, AfterSid=None): """ Fetch the Authorized Connect Apps belonging to an account. :var Page: The current page number. Zero-indexed, so the first page is 0. :vartype Page: int :var PageSize: How many resources to return in each list page. The default is 50, and the maximum is 1000. :vartype PageSize: int :var AfterSid: The last Sid returned in the previous page, used to avoid listing duplicated resources if new ones are created while paging. :vartype AfterSid: str """ params = resource.get_params(None, locals()) request = http.Request('GET', self.get_url(), params) return request, parsers.parse_json

research/gnn/sgcn/postprocess.py

leelige/mindspore

345

# Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """ postprocess. """ import os import argparse import numpy as np from src.ms_utils import calculate_auc from mindspore import context, load_checkpoint def softmax(x): t_max = np.max(x, axis=1, keepdims=True) # returns max of each row and keeps same dims e_x = np.exp(x - t_max) # subtracts each row with its max value t_sum = np.sum(e_x, axis=1, keepdims=True) # returns sum of each row and keeps same dims f_x = e_x / t_sum return f_x def score_model(preds, test_pos, test_neg, weight, bias): """ Score the model on the test set edges in each epoch. Args: epoch (LongTensor): Training epochs. Returns: auc(Float32): AUC result. f1(Float32): F1-Score result. """ score_positive_edges = np.array(test_pos, dtype=np.int32).T score_negative_edges = np.array(test_neg, dtype=np.int32).T test_positive_z = np.concatenate((preds[score_positive_edges[0, :], :], preds[score_positive_edges[1, :], :]), axis=1) test_negative_z = np.concatenate((preds[score_negative_edges[0, :], :], preds[score_negative_edges[1, :], :]), axis=1) # operands could not be broadcast together with shapes (4288,128) (128,3) scores = np.dot(np.concatenate((test_positive_z, test_negative_z), axis=0), weight) + bias probability_scores = np.exp(softmax(scores)) predictions = probability_scores[:, 0]/probability_scores[:, 0:2].sum(1) # predictions = predictions.asnumpy() targets = [0]*len(test_pos) + [1]*len(test_neg) auc, f1 = calculate_auc(targets, predictions) return auc, f1 def get_acc(): """get infer Accuracy.""" parser = argparse.ArgumentParser(description='postprocess') parser.add_argument('--dataset_name', type=str, default='bitcoin-otc', choices=['bitcoin-otc', 'bitcoin-alpha'], help='dataset name') parser.add_argument('--result_path', type=str, default='./ascend310_infer/input/', help='result Files') parser.add_argument('--label_path', type=str, default='', help='y_test npy Files') parser.add_argument('--mask_path', type=str, default='', help='test_mask npy Files') parser.add_argument("--checkpoint_file", type=str, default='sgcn_alpha_f1.ckpt', help="Checkpoint file path.") parser.add_argument("--edge_path", nargs="?", default="./input/bitcoin_alpha.csv", help="Edge list csv.") parser.add_argument("--features-path", nargs="?", default="./input/bitcoin_alpha.csv", help="Edge list csv.") parser.add_argument("--test-size", type=float, default=0.2, help="Test dataset size. Default is 0.2.") parser.add_argument("--seed", type=int, default=42, help="Random seed for sklearn pre-training. Default is 42.") parser.add_argument("--spectral-features", default=True, dest="spectral_features", action="store_true") parser.add_argument("--reduction-iterations", type=int, default=30, help="Number of SVD iterations. Default is 30.") parser.add_argument("--reduction-dimensions", type=int, default=64, help="Number of SVD feature extraction dimensions. Default is 64.") args_opt = parser.parse_args() # Runtime context.set_context(mode=context.GRAPH_MODE, device_target='Ascend', device_id=0) # Create network test_pos = np.load(os.path.join(args_opt.result_path, 'pos_test.npy')) test_neg = np.load(os.path.join(args_opt.result_path, 'neg_test.npy')) # Load parameters from checkpoint into network param_dict = load_checkpoint(args_opt.checkpoint_file) print(type(param_dict)) print(param_dict) print(type(param_dict['regression_weights'])) print(param_dict['regression_weights']) # load_param_into_net(net, param_dict) pred = np.fromfile('./result_Files/repos_0.bin', np.float32) if args_opt.dataset_name == 'bitcoin-otc': pred = pred.reshape(5881, 64) else: pred = pred.reshape(3783, 64) auc, f1 = score_model(pred, test_pos, test_neg, param_dict['regression_weights'].asnumpy(), param_dict['regression_bias'].asnumpy()) print("Test set results:", "auc=", "{:.5f}".format(auc), "f1=", "{:.5f}".format(f1)) if __name__ == '__main__': get_acc()

pykeops/common/get_options.py

dvolgyes/keops

346

import re import numpy as np from collections import OrderedDict import pykeops import pykeops.config ############################################################ # define backend ############################################################ class SetBackend(): """ This class is used to centralized the options used in PyKeops. """ dev = OrderedDict([('CPU',0),('GPU',1)]) grid = OrderedDict([('1D',0),('2D',1)]) memtype = OrderedDict([('host',0), ('device',1)]) possible_options_list = ['auto', 'CPU', 'GPU', 'GPU_1D', 'GPU_1D_device', 'GPU_1D_host', 'GPU_2D', 'GPU_2D_device', 'GPU_2D_host' ] def define_tag_backend(self, backend, variables): """ Try to make a good guess for the backend... available methods are: (host means Cpu, device means Gpu) CPU : computations performed with the host from host arrays GPU_1D_device : computations performed on the device from device arrays, using the 1D scheme GPU_2D_device : computations performed on the device from device arrays, using the 2D scheme GPU_1D_host : computations performed on the device from host arrays, using the 1D scheme GPU_2D_host : computations performed on the device from host data, using the 2D scheme :param backend (str), variables (tuple) :return (tagCPUGPU, tag1D2D, tagHostDevice) """ # check that the option is valid if (backend not in self.possible_options_list): raise ValueError('Invalid backend. Should be one of ', self.possible_options_list) # auto : infer everything if backend == 'auto': return int(pykeops.config.gpu_available), self._find_grid(), self._find_mem(variables) split_backend = re.split('_',backend) if len(split_backend) == 1: # CPU or GPU return self.dev[split_backend[0]], self._find_grid(), self._find_mem(variables) elif len(split_backend) == 2: # GPU_1D or GPU_2D return self.dev[split_backend[0]], self.grid[split_backend[1]], self._find_mem(variables) elif len(split_backend) == 3: # the option is known return self.dev[split_backend[0]], self.grid[split_backend[1]], self.memtype[split_backend[2]] def define_backend(self, backend, variables): tagCPUGPU, tag1D2D, tagHostDevice = self.define_tag_backend(backend, variables) return self.dev[tagCPUGPU], self.grid[tag1D2D], self.memtype[tagHostDevice] @staticmethod def _find_dev(): return int(pykeops.config.gpu_available) @staticmethod def _find_mem(variables): if all([type(var) is np.ndarray for var in variables ]): # Infer if we're working with numpy arrays or torch tensors: MemType = 0 elif pykeops.config.torch_found: import torch if all([type(var) in [torch.Tensor, torch.nn.parameter.Parameter] for var in variables]): from pykeops.torch.utils import is_on_device VarsAreOnGpu = tuple(map(is_on_device, tuple(variables))) if all(VarsAreOnGpu): MemType = 1 elif not any(VarsAreOnGpu): MemType = 0 else: raise ValueError('At least two input variables have different memory locations (Cpu/Gpu).') else: raise TypeError('All variables should either be numpy arrays or torch tensors.') return MemType @staticmethod def _find_grid(): return 0 def get_tag_backend(backend, variables, str = False): """ entry point to get the correct backend """ res = SetBackend() if not str: return res.define_tag_backend(backend, variables) else: return res.define_backend(backend, variables)

prepare_features_vc.py

tkm2261/dnn-voice-changer

347

<filename>prepare_features_vc.py """Prepare acoustic features for one-to-one voice conversion. usage: prepare_features_vc.py [options] <DATA_ROOT> <source_speaker> <target_speaker> options: --max_files=<N> Max num files to be collected. [default: 100] --dst_dir=<d> Destination directory [default: data/cmu_arctic_vc]. --overwrite Overwrite files. -h, --help show this help message and exit """ from __future__ import division, print_function, absolute_import from docopt import docopt import numpy as np from nnmnkwii.datasets import FileSourceDataset from nnmnkwii import preprocessing as P from nnmnkwii.preprocessing.alignment import DTWAligner from nnmnkwii.datasets import cmu_arctic, voice_statistics, vcc2016 import pysptk import pyworld from scipy.io import wavfile from tqdm import tqdm from os.path import basename, splitext, exists, expanduser, join, dirname import os import sys from hparams import vc as hp from hparams import hparams_debug_string # vcc2016.WavFileDataSource and voice_statistics.WavFileDataSource can be # drop-in replacement. See below for details: # https://r9y9.github.io/nnmnkwii/latest/references/datasets.html#builtin-data-sources class MGCSource(cmu_arctic.WavFileDataSource): def __init__(self, data_root, speakers, max_files=None): super(MGCSource, self).__init__(data_root, speakers, max_files=max_files) self.alpha = None def collect_features(self, wav_path): fs, x = wavfile.read(wav_path) x = x.astype(np.float64) f0, timeaxis = pyworld.dio(x, fs, frame_period=hp.frame_period) f0 = pyworld.stonemask(x, f0, timeaxis, fs) spectrogram = pyworld.cheaptrick(x, f0, timeaxis, fs) spectrogram = P.trim_zeros_frames(spectrogram) if self.alpha is None: self.alpha = pysptk.util.mcepalpha(fs) mgc = pysptk.sp2mc(spectrogram, order=hp.order, alpha=self.alpha) # Drop 0-th coefficient mgc = mgc[:, 1:] # 50Hz cut-off MS smoothing hop_length = int(fs * (hp.frame_period * 0.001)) modfs = fs / hop_length mgc = P.modspec_smoothing(mgc, modfs, cutoff=50) # Add delta mgc = P.delta_features(mgc, hp.windows) return mgc.astype(np.float32) if __name__ == "__main__": args = docopt(__doc__) print("Command line args:\n", args) DATA_ROOT = args["<DATA_ROOT>"] source_speaker = args["<source_speaker>"] target_speaker = args["<target_speaker>"] max_files = int(args["--max_files"]) dst_dir = args["--dst_dir"] overwrite = args["--overwrite"] print(hparams_debug_string(hp)) X_dataset = FileSourceDataset(MGCSource(DATA_ROOT, [source_speaker], max_files=max_files)) Y_dataset = FileSourceDataset(MGCSource(DATA_ROOT, [target_speaker], max_files=max_files)) skip_feature_extraction = exists(join(dst_dir, "X")) \ and exists(join(dst_dir, "Y")) if overwrite: skip_feature_extraction = False if skip_feature_extraction: print("Features seems to be prepared, skipping feature extraction.") sys.exit(0) # Create dirs for speaker, name in [(source_speaker, "X"), (target_speaker, "Y")]: d = join(dst_dir, name) print("Destination dir for {}: {}".format(speaker, d)) if not exists(d): os.makedirs(d) # Convert to arrays print("Convert datasets to arrays") X, Y = X_dataset.asarray(verbose=1), Y_dataset.asarray(verbose=1) # Alignment print("Perform alignment") X, Y = DTWAligner().transform((X, Y)) print("Save features to disk") for idx, (x, y) in tqdm(enumerate(zip(X, Y))): # paths src_name = splitext(basename(X_dataset.collected_files[idx][0]))[0] tgt_name = splitext(basename(Y_dataset.collected_files[idx][0]))[0] src_path = join(dst_dir, "X", src_name) tgt_path = join(dst_dir, "Y", tgt_name) # Trim and ajast frames x = P.trim_zeros_frames(x) y = P.trim_zeros_frames(y) x, y = P.adjust_frame_lengths(x, y, pad=True, divisible_by=2) # Save np.save(src_path, x) np.save(tgt_path, y)

lib/tests/streamlit/pydeck_test.py

zgtz/streamlit

348

<filename>lib/tests/streamlit/pydeck_test.py # Copyright 2018-2021 Streamlit Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import json import pandas as pd import pydeck as pdk from tests import testutil import streamlit as st import streamlit.elements.deck_gl_json_chart as deck_gl_json_chart df1 = pd.DataFrame({"lat": [1, 2, 3, 4], "lon": [10, 20, 30, 40]}) class PyDeckTest(testutil.DeltaGeneratorTestCase): def test_basic(self): """Test that pydeck object orks.""" st.pydeck_chart( pdk.Deck( layers=[ pdk.Layer("ScatterplotLayer", data=df1), ] ) ) el = self.get_delta_from_queue().new_element actual = json.loads(el.deck_gl_json_chart.json) self.assertEqual(actual["layers"][0]["@@type"], "ScatterplotLayer") self.assertEqual( actual["layers"][0]["data"], [ {"lat": 1, "lon": 10}, {"lat": 2, "lon": 20}, {"lat": 3, "lon": 30}, {"lat": 4, "lon": 40}, ], ) def test_no_args(self): """Test that it can be called with no args.""" st.pydeck_chart() el = self.get_delta_from_queue().new_element actual = json.loads(el.deck_gl_json_chart.json) self.assertEqual(actual, deck_gl_json_chart.EMPTY_MAP)

sdks/python/apache_beam/io/gcp/bigquery_tools.py

Doctusoft/beam

349

<filename>sdks/python/apache_beam/io/gcp/bigquery_tools.py # # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # """Tools used by BigQuery sources and sinks. Classes, constants and functions in this file are experimental and have no backwards compatibility guarantees. These tools include wrappers and clients to interact with BigQuery APIs. NOTHING IN THIS FILE HAS BACKWARDS COMPATIBILITY GUARANTEES. """ from __future__ import absolute_import import datetime import decimal import json import logging import re import sys import time import uuid from builtins import object from future.utils import iteritems from apache_beam import coders from apache_beam.internal.gcp import auth from apache_beam.internal.gcp.json_value import from_json_value from apache_beam.internal.gcp.json_value import to_json_value from apache_beam.internal.http_client import get_new_http from apache_beam.io.gcp.internal.clients import bigquery from apache_beam.options import value_provider from apache_beam.options.pipeline_options import GoogleCloudOptions from apache_beam.runners.dataflow.native_io import iobase as dataflow_io from apache_beam.transforms import DoFn from apache_beam.utils import retry # Protect against environments where bigquery library is not available. # pylint: disable=wrong-import-order, wrong-import-position try: from apitools.base.py.exceptions import HttpError except ImportError: pass # pylint: enable=wrong-import-order, wrong-import-position MAX_RETRIES = 3 JSON_COMPLIANCE_ERROR = 'NAN, INF and -INF values are not JSON compliant.' def default_encoder(obj): if isinstance(obj, decimal.Decimal): return str(obj) raise TypeError( "Object of type '%s' is not JSON serializable" % type(obj).__name__) def get_hashable_destination(destination): """Parses a table reference into a (project, dataset, table) tuple. Args: destination: Either a TableReference object from the bigquery API. The object has the following attributes: projectId, datasetId, and tableId. Or a string representing the destination containing 'PROJECT:DATASET.TABLE'. Returns: A string representing the destination containing 'PROJECT:DATASET.TABLE'. """ if isinstance(destination, bigquery.TableReference): return '%s:%s.%s' % ( destination.projectId, destination.datasetId, destination.tableId) else: return destination def parse_table_schema_from_json(schema_string): """Parse the Table Schema provided as string. Args: schema_string: String serialized table schema, should be a valid JSON. Returns: A TableSchema of the BigQuery export from either the Query or the Table. """ json_schema = json.loads(schema_string) def _parse_schema_field(field): """Parse a single schema field from dictionary. Args: field: Dictionary object containing serialized schema. Returns: A TableFieldSchema for a single column in BigQuery. """ schema = bigquery.TableFieldSchema() schema.name = field['name'] schema.type = field['type'] if 'mode' in field: schema.mode = field['mode'] else: schema.mode = 'NULLABLE' if 'description' in field: schema.description = field['description'] if 'fields' in field: schema.fields = [_parse_schema_field(x) for x in field['fields']] return schema fields = [_parse_schema_field(f) for f in json_schema['fields']] return bigquery.TableSchema(fields=fields) def parse_table_reference(table, dataset=None, project=None): """Parses a table reference into a (project, dataset, table) tuple. Args: table: The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). If dataset argument is None then the table argument must contain the entire table reference: 'DATASET.TABLE' or 'PROJECT:DATASET.TABLE'. This argument can be a bigquery.TableReference instance in which case dataset and project are ignored and the reference is returned as a result. Additionally, for date partitioned tables, appending '$YYYYmmdd' to the table name is supported, e.g. 'DATASET.TABLE$YYYYmmdd'. dataset: The ID of the dataset containing this table or null if the table reference is specified entirely by the table argument. project: The ID of the project containing this table or null if the table reference is specified entirely by the table (and possibly dataset) argument. Returns: A TableReference object from the bigquery API. The object has the following attributes: projectId, datasetId, and tableId. Raises: ValueError: if the table reference as a string does not match the expected format. """ if isinstance(table, bigquery.TableReference): return table elif callable(table): return table elif isinstance(table, value_provider.ValueProvider): return table table_reference = bigquery.TableReference() # If dataset argument is not specified, the expectation is that the # table argument will contain a full table reference instead of just a # table name. if dataset is None: match = re.match( r'^((?P<project>.+):)?(?P<dataset>\w+)\.(?P<table>[\w\$]+)$', table) if not match: raise ValueError( 'Expected a table reference (PROJECT:DATASET.TABLE or ' 'DATASET.TABLE) instead of %s.' % table) table_reference.projectId = match.group('project') table_reference.datasetId = match.group('dataset') table_reference.tableId = match.group('table') else: table_reference.projectId = project table_reference.datasetId = dataset table_reference.tableId = table return table_reference # ----------------------------------------------------------------------------- # BigQueryWrapper. class BigQueryWrapper(object): """BigQuery client wrapper with utilities for querying. The wrapper is used to organize all the BigQuery integration points and offer a common place where retry logic for failures can be controlled. In addition it offers various functions used both in sources and sinks (e.g., find and create tables, query a table, etc.). """ TEMP_TABLE = 'temp_table_' TEMP_DATASET = 'temp_dataset_' def __init__(self, client=None): self.client = client or bigquery.BigqueryV2( http=get_new_http(), credentials=auth.get_service_credentials(), response_encoding=None if sys.version_info[0] < 3 else 'utf8') self._unique_row_id = 0 # For testing scenarios where we pass in a client we do not want a # randomized prefix for row IDs. self._row_id_prefix = '' if client else uuid.uuid4() self._temporary_table_suffix = uuid.uuid4().hex @property def unique_row_id(self): """Returns a unique row ID (str) used to avoid multiple insertions. If the row ID is provided, BigQuery will make a best effort to not insert the same row multiple times for fail and retry scenarios in which the insert request may be issued several times. This comes into play for sinks executed in a local runner. Returns: a unique row ID string """ self._unique_row_id += 1 return '%s_%d' % (self._row_id_prefix, self._unique_row_id) def _get_temp_table(self, project_id): return parse_table_reference( table=BigQueryWrapper.TEMP_TABLE + self._temporary_table_suffix, dataset=BigQueryWrapper.TEMP_DATASET + self._temporary_table_suffix, project=project_id) @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def get_query_location(self, project_id, query, use_legacy_sql): """ Get the location of tables referenced in a query. This method returns the location of the first referenced table in the query and depends on the BigQuery service to provide error handling for queries that reference tables in multiple locations. """ reference = bigquery.JobReference(jobId=uuid.uuid4().hex, projectId=project_id) request = bigquery.BigqueryJobsInsertRequest( projectId=project_id, job=bigquery.Job( configuration=bigquery.JobConfiguration( dryRun=True, query=bigquery.JobConfigurationQuery( query=query, useLegacySql=use_legacy_sql, )), jobReference=reference)) response = self.client.jobs.Insert(request) if response.statistics is None: # This behavior is only expected in tests logging.warning( "Unable to get location, missing response.statistics. Query: %s", query) return None referenced_tables = response.statistics.query.referencedTables if referenced_tables: # Guards against both non-empty and non-None table = referenced_tables[0] location = self.get_table_location( table.projectId, table.datasetId, table.tableId) logging.info("Using location %r from table %r referenced by query %s", location, table, query) return location logging.debug("Query %s does not reference any tables.", query) return None @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def _insert_copy_job(self, project_id, job_id, from_table_reference, to_table_reference, create_disposition=None, write_disposition=None): reference = bigquery.JobReference() reference.jobId = job_id reference.projectId = project_id request = bigquery.BigqueryJobsInsertRequest( projectId=project_id, job=bigquery.Job( configuration=bigquery.JobConfiguration( copy=bigquery.JobConfigurationTableCopy( destinationTable=to_table_reference, sourceTable=from_table_reference, createDisposition=create_disposition, writeDisposition=write_disposition, ) ), jobReference=reference, ) ) logging.info("Inserting job request: %s", request) response = self.client.jobs.Insert(request) logging.info("Response was %s", response) return response.jobReference @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def _insert_load_job(self, project_id, job_id, table_reference, source_uris, schema=None, write_disposition=None, create_disposition=None): reference = bigquery.JobReference(jobId=job_id, projectId=project_id) request = bigquery.BigqueryJobsInsertRequest( projectId=project_id, job=bigquery.Job( configuration=bigquery.JobConfiguration( load=bigquery.JobConfigurationLoad( sourceUris=source_uris, destinationTable=table_reference, schema=schema, writeDisposition=write_disposition, createDisposition=create_disposition, sourceFormat='NEWLINE_DELIMITED_JSON', autodetect=schema is None, ) ), jobReference=reference, ) ) response = self.client.jobs.Insert(request) return response.jobReference @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def _start_query_job(self, project_id, query, use_legacy_sql, flatten_results, job_id, dry_run=False): reference = bigquery.JobReference(jobId=job_id, projectId=project_id) request = bigquery.BigqueryJobsInsertRequest( projectId=project_id, job=bigquery.Job( configuration=bigquery.JobConfiguration( dryRun=dry_run, query=bigquery.JobConfigurationQuery( query=query, useLegacySql=use_legacy_sql, allowLargeResults=True, destinationTable=self._get_temp_table(project_id), flattenResults=flatten_results)), jobReference=reference)) response = self.client.jobs.Insert(request) return response.jobReference.jobId @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def _get_query_results(self, project_id, job_id, page_token=None, max_results=10000): request = bigquery.BigqueryJobsGetQueryResultsRequest( jobId=job_id, pageToken=page_token, projectId=project_id, maxResults=max_results) response = self.client.jobs.GetQueryResults(request) return response @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_timeout_or_quota_issues_filter) def _insert_all_rows(self, project_id, dataset_id, table_id, rows, skip_invalid_rows=False): """Calls the insertAll BigQuery API endpoint. Docs for this BQ call: https://cloud.google.com/bigquery/docs/reference\ /rest/v2/tabledata/insertAll.""" # The rows argument is a list of # bigquery.TableDataInsertAllRequest.RowsValueListEntry instances as # required by the InsertAll() method. request = bigquery.BigqueryTabledataInsertAllRequest( projectId=project_id, datasetId=dataset_id, tableId=table_id, tableDataInsertAllRequest=bigquery.TableDataInsertAllRequest( skipInvalidRows=skip_invalid_rows, # TODO(silviuc): Should have an option for ignoreUnknownValues? rows=rows)) response = self.client.tabledata.InsertAll(request) # response.insertErrors is not [] if errors encountered. return not response.insertErrors, response.insertErrors @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def get_table(self, project_id, dataset_id, table_id): """Lookup a table's metadata object. Args: client: bigquery.BigqueryV2 instance project_id, dataset_id, table_id: table lookup parameters Returns: bigquery.Table instance Raises: HttpError if lookup failed. """ request = bigquery.BigqueryTablesGetRequest( projectId=project_id, datasetId=dataset_id, tableId=table_id) response = self.client.tables.Get(request) return response def _create_table(self, project_id, dataset_id, table_id, schema): table = bigquery.Table( tableReference=bigquery.TableReference( projectId=project_id, datasetId=dataset_id, tableId=table_id), schema=schema) request = bigquery.BigqueryTablesInsertRequest( projectId=project_id, datasetId=dataset_id, table=table) response = self.client.tables.Insert(request) logging.debug("Created the table with id %s", table_id) # The response is a bigquery.Table instance. return response @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def get_or_create_dataset(self, project_id, dataset_id, location=None): # Check if dataset already exists otherwise create it try: dataset = self.client.datasets.Get(bigquery.BigqueryDatasetsGetRequest( projectId=project_id, datasetId=dataset_id)) return dataset except HttpError as exn: if exn.status_code == 404: dataset_reference = bigquery.DatasetReference( projectId=project_id, datasetId=dataset_id) dataset = bigquery.Dataset(datasetReference=dataset_reference) if location is not None: dataset.location = location request = bigquery.BigqueryDatasetsInsertRequest( projectId=project_id, dataset=dataset) response = self.client.datasets.Insert(request) # The response is a bigquery.Dataset instance. return response else: raise @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def _is_table_empty(self, project_id, dataset_id, table_id): request = bigquery.BigqueryTabledataListRequest( projectId=project_id, datasetId=dataset_id, tableId=table_id, maxResults=1) response = self.client.tabledata.List(request) # The response is a bigquery.TableDataList instance. return response.totalRows == 0 @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def _delete_table(self, project_id, dataset_id, table_id): request = bigquery.BigqueryTablesDeleteRequest( projectId=project_id, datasetId=dataset_id, tableId=table_id) try: self.client.tables.Delete(request) except HttpError as exn: if exn.status_code == 404: logging.warning('Table %s:%s.%s does not exist', project_id, dataset_id, table_id) return else: raise @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def _delete_dataset(self, project_id, dataset_id, delete_contents=True): request = bigquery.BigqueryDatasetsDeleteRequest( projectId=project_id, datasetId=dataset_id, deleteContents=delete_contents) try: self.client.datasets.Delete(request) except HttpError as exn: if exn.status_code == 404: logging.warning('Dataset %s:%s does not exist', project_id, dataset_id) return else: raise @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def get_table_location(self, project_id, dataset_id, table_id): table = self.get_table(project_id, dataset_id, table_id) return table.location @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def create_temporary_dataset(self, project_id, location): dataset_id = BigQueryWrapper.TEMP_DATASET + self._temporary_table_suffix # Check if dataset exists to make sure that the temporary id is unique try: self.client.datasets.Get(bigquery.BigqueryDatasetsGetRequest( projectId=project_id, datasetId=dataset_id)) if project_id is not None: # Unittests don't pass projectIds so they can be run without error raise RuntimeError( 'Dataset %s:%s already exists so cannot be used as temporary.' % (project_id, dataset_id)) except HttpError as exn: if exn.status_code == 404: logging.warning( 'Dataset %s:%s does not exist so we will create it as temporary ' 'with location=%s', project_id, dataset_id, location) self.get_or_create_dataset(project_id, dataset_id, location=location) else: raise @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def clean_up_temporary_dataset(self, project_id): temp_table = self._get_temp_table(project_id) try: self.client.datasets.Get(bigquery.BigqueryDatasetsGetRequest( projectId=project_id, datasetId=temp_table.datasetId)) except HttpError as exn: if exn.status_code == 404: logging.warning('Dataset %s:%s does not exist', project_id, temp_table.datasetId) return else: raise self._delete_dataset(temp_table.projectId, temp_table.datasetId, True) @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def get_job(self, project, job_id, location=None): request = bigquery.BigqueryJobsGetRequest() request.jobId = job_id request.projectId = project request.location = location return self.client.jobs.Get(request) def perform_load_job(self, destination, files, job_id, schema=None, write_disposition=None, create_disposition=None): """Starts a job to load data into BigQuery. Returns: bigquery.JobReference with the information about the job that was started. """ return self._insert_load_job( destination.projectId, job_id, destination, files, schema=schema, create_disposition=create_disposition, write_disposition=write_disposition) @retry.with_exponential_backoff( num_retries=MAX_RETRIES, retry_filter=retry.retry_on_server_errors_and_timeout_filter) def get_or_create_table( self, project_id, dataset_id, table_id, schema, create_disposition, write_disposition): """Gets or creates a table based on create and write dispositions. The function mimics the behavior of BigQuery import jobs when using the same create and write dispositions. Args: project_id: The project id owning the table. dataset_id: The dataset id owning the table. table_id: The table id. schema: A bigquery.TableSchema instance or None. create_disposition: CREATE_NEVER or CREATE_IF_NEEDED. write_disposition: WRITE_APPEND, WRITE_EMPTY or WRITE_TRUNCATE. Returns: A bigquery.Table instance if table was found or created. Raises: RuntimeError: For various mismatches between the state of the table and the create/write dispositions passed in. For example if the table is not empty and WRITE_EMPTY was specified then an error will be raised since the table was expected to be empty. """ from apache_beam.io.gcp.bigquery import BigQueryDisposition found_table = None try: found_table = self.get_table(project_id, dataset_id, table_id) except HttpError as exn: if exn.status_code == 404: if create_disposition == BigQueryDisposition.CREATE_NEVER: raise RuntimeError( 'Table %s:%s.%s not found but create disposition is CREATE_NEVER.' % (project_id, dataset_id, table_id)) else: raise # If table exists already then handle the semantics for WRITE_EMPTY and # WRITE_TRUNCATE write dispositions. if found_table: table_empty = self._is_table_empty(project_id, dataset_id, table_id) if (not table_empty and write_disposition == BigQueryDisposition.WRITE_EMPTY): raise RuntimeError( 'Table %s:%s.%s is not empty but write disposition is WRITE_EMPTY.' % (project_id, dataset_id, table_id)) # Delete the table and recreate it (later) if WRITE_TRUNCATE was # specified. if write_disposition == BigQueryDisposition.WRITE_TRUNCATE: self._delete_table(project_id, dataset_id, table_id) # Create a new table potentially reusing the schema from a previously # found table in case the schema was not specified. if schema is None and found_table is None: raise RuntimeError( 'Table %s:%s.%s requires a schema. None can be inferred because the ' 'table does not exist.' % (project_id, dataset_id, table_id)) if found_table and write_disposition != BigQueryDisposition.WRITE_TRUNCATE: return found_table else: created_table = self._create_table(project_id=project_id, dataset_id=dataset_id, table_id=table_id, schema=schema or found_table.schema) logging.info('Created table %s.%s.%s with schema %s. Result: %s.', project_id, dataset_id, table_id, schema or found_table.schema, created_table) # if write_disposition == BigQueryDisposition.WRITE_TRUNCATE we delete # the table before this point. if write_disposition == BigQueryDisposition.WRITE_TRUNCATE: # BigQuery can route data to the old table for 2 mins max so wait # that much time before creating the table and writing it logging.warning('Sleeping for 150 seconds before the write as ' + 'BigQuery inserts can be routed to deleted table ' + 'for 2 mins after the delete and create.') # TODO(BEAM-2673): Remove this sleep by migrating to load api time.sleep(150) return created_table else: return created_table def run_query(self, project_id, query, use_legacy_sql, flatten_results, dry_run=False): job_id = self._start_query_job(project_id, query, use_legacy_sql, flatten_results, job_id=uuid.uuid4().hex, dry_run=dry_run) if dry_run: # If this was a dry run then the fact that we get here means the # query has no errors. The start_query_job would raise an error otherwise. return page_token = None while True: response = self._get_query_results(project_id, job_id, page_token) if not response.jobComplete: # The jobComplete field can be False if the query request times out # (default is 10 seconds). Note that this is a timeout for the query # request not for the actual execution of the query in the service. If # the request times out we keep trying. This situation is quite possible # if the query will return a large number of rows. logging.info('Waiting on response from query: %s ...', query) time.sleep(1.0) continue # We got some results. The last page is signalled by a missing pageToken. yield response.rows, response.schema if not response.pageToken: break page_token = response.pageToken def insert_rows(self, project_id, dataset_id, table_id, rows, skip_invalid_rows=False): """Inserts rows into the specified table. Args: project_id: The project id owning the table. dataset_id: The dataset id owning the table. table_id: The table id. rows: A list of plain Python dictionaries. Each dictionary is a row and each key in it is the name of a field. skip_invalid_rows: If there are rows with insertion errors, whether they should be skipped, and all others should be inserted successfully. Returns: A tuple (bool, errors). If first element is False then the second element will be a bigquery.InserttErrorsValueListEntry instance containing specific errors. """ # Prepare rows for insertion. Of special note is the row ID that we add to # each row in order to help BigQuery avoid inserting a row multiple times. # BigQuery will do a best-effort if unique IDs are provided. This situation # can happen during retries on failures. # TODO(silviuc): Must add support to writing TableRow's instead of dicts. final_rows = [] for row in rows: json_object = bigquery.JsonObject() for k, v in iteritems(row): if isinstance(v, decimal.Decimal): # decimal values are converted into string because JSON does not # support the precision that decimal supports. BQ is able to handle # inserts into NUMERIC columns by receiving JSON with string attrs. v = str(v) json_object.additionalProperties.append( bigquery.JsonObject.AdditionalProperty( key=k, value=to_json_value(v))) final_rows.append( bigquery.TableDataInsertAllRequest.RowsValueListEntry( insertId=str(self.unique_row_id), json=json_object)) result, errors = self._insert_all_rows( project_id, dataset_id, table_id, final_rows, skip_invalid_rows) return result, errors def _convert_cell_value_to_dict(self, value, field): if field.type == 'STRING': # Input: "XYZ" --> Output: "XYZ" return value elif field.type == 'BOOLEAN': # Input: "true" --> Output: True return value == 'true' elif field.type == 'INTEGER': # Input: "123" --> Output: 123 return int(value) elif field.type == 'FLOAT': # Input: "1.23" --> Output: 1.23 return float(value) elif field.type == 'TIMESTAMP': # The UTC should come from the timezone library but this is a known # issue in python 2.7 so we'll just hardcode it as we're reading using # utcfromtimestamp. # Input: 1478134176.985864 --> Output: "2016-11-03 00:49:36.985864 UTC" dt = datetime.datetime.utcfromtimestamp(float(value)) return dt.strftime('%Y-%m-%d %H:%M:%S.%f UTC') elif field.type == 'BYTES': # Input: "YmJi" --> Output: "YmJi" return value elif field.type == 'DATE': # Input: "2016-11-03" --> Output: "2016-11-03" return value elif field.type == 'DATETIME': # Input: "2016-11-03T00:49:36" --> Output: "2016-11-03T00:49:36" return value elif field.type == 'TIME': # Input: "00:49:36" --> Output: "00:49:36" return value elif field.type == 'RECORD': # Note that a schema field object supports also a RECORD type. However # when querying, the repeated and/or record fields are flattened # unless we pass the flatten_results flag as False to the source return self.convert_row_to_dict(value, field) elif field.type == 'NUMERIC': return decimal.Decimal(value) elif field.type == 'GEOGRAPHY': return value else: raise RuntimeError('Unexpected field type: %s' % field.type) def convert_row_to_dict(self, row, schema): """Converts a TableRow instance using the schema to a Python dict.""" result = {} for index, field in enumerate(schema.fields): value = None if isinstance(schema, bigquery.TableSchema): cell = row.f[index] value = from_json_value(cell.v) if cell.v is not None else None elif isinstance(schema, bigquery.TableFieldSchema): cell = row['f'][index] value = cell['v'] if 'v' in cell else None if field.mode == 'REPEATED': if value is None: # Ideally this should never happen as repeated fields default to # returning an empty list result[field.name] = [] else: result[field.name] = [self._convert_cell_value_to_dict(x['v'], field) for x in value] elif value is None: if not field.mode == 'NULLABLE': raise ValueError('Received \'None\' as the value for the field %s ' 'but the field is not NULLABLE.' % field.name) result[field.name] = None else: result[field.name] = self._convert_cell_value_to_dict(value, field) return result # ----------------------------------------------------------------------------- # BigQueryReader, BigQueryWriter. class BigQueryReader(dataflow_io.NativeSourceReader): """A reader for a BigQuery source.""" def __init__(self, source, test_bigquery_client=None, use_legacy_sql=True, flatten_results=True, kms_key=None): self.source = source self.test_bigquery_client = test_bigquery_client if auth.is_running_in_gce: self.executing_project = auth.executing_project elif hasattr(source, 'pipeline_options'): self.executing_project = ( source.pipeline_options.view_as(GoogleCloudOptions).project) else: self.executing_project = None # TODO(silviuc): Try to automatically get it from gcloud config info. if not self.executing_project and test_bigquery_client is None: raise RuntimeError( 'Missing executing project information. Please use the --project ' 'command line option to specify it.') self.row_as_dict = isinstance(self.source.coder, RowAsDictJsonCoder) # Schema for the rows being read by the reader. It is initialized the # first time something gets read from the table. It is not required # for reading the field values in each row but could be useful for # getting additional details. self.schema = None self.use_legacy_sql = use_legacy_sql self.flatten_results = flatten_results self.kms_key = kms_key if self.source.table_reference is not None: # If table schema did not define a project we default to executing # project. project_id = self.source.table_reference.projectId if not project_id: project_id = self.executing_project self.query = 'SELECT * FROM [%s:%s.%s];' % ( project_id, self.source.table_reference.datasetId, self.source.table_reference.tableId) elif self.source.query is not None: self.query = self.source.query else: # Enforce the "modes" enforced by BigQuerySource.__init__. # If this exception has been raised, the BigQuerySource "modes" have # changed and this method will need to be updated as well. raise ValueError("BigQuerySource must have either a table or query") def _get_source_location(self): """ Get the source location (e.g. ``"EU"`` or ``"US"``) from either - :data:`source.table_reference` or - The first referenced table in :data:`source.query` See Also: - :meth:`BigQueryWrapper.get_query_location` - :meth:`BigQueryWrapper.get_table_location` Returns: Optional[str]: The source location, if any. """ if self.source.table_reference is not None: tr = self.source.table_reference return self.client.get_table_location( tr.projectId if tr.projectId is not None else self.executing_project, tr.datasetId, tr.tableId) else: # It's a query source return self.client.get_query_location( self.executing_project, self.source.query, self.source.use_legacy_sql) def __enter__(self): self.client = BigQueryWrapper(client=self.test_bigquery_client) self.client.create_temporary_dataset( self.executing_project, location=self._get_source_location()) return self def __exit__(self, exception_type, exception_value, traceback): self.client.clean_up_temporary_dataset(self.executing_project) def __iter__(self): for rows, schema in self.client.run_query( project_id=self.executing_project, query=self.query, use_legacy_sql=self.use_legacy_sql, flatten_results=self.flatten_results): if self.schema is None: self.schema = schema for row in rows: if self.row_as_dict: yield self.client.convert_row_to_dict(row, schema) else: yield row class BigQueryWriter(dataflow_io.NativeSinkWriter): """The sink writer for a BigQuerySink.""" def __init__(self, sink, test_bigquery_client=None, buffer_size=None): self.sink = sink self.test_bigquery_client = test_bigquery_client self.row_as_dict = isinstance(self.sink.coder, RowAsDictJsonCoder) # Buffer used to batch written rows so we reduce communication with the # BigQuery service. self.rows_buffer = [] self.rows_buffer_flush_threshold = buffer_size or 1000 # Figure out the project, dataset, and table used for the sink. self.project_id = self.sink.table_reference.projectId # If table schema did not define a project we default to executing project. if self.project_id is None and hasattr(sink, 'pipeline_options'): self.project_id = ( sink.pipeline_options.view_as(GoogleCloudOptions).project) assert self.project_id is not None self.dataset_id = self.sink.table_reference.datasetId self.table_id = self.sink.table_reference.tableId def _flush_rows_buffer(self): if self.rows_buffer: logging.info('Writing %d rows to %s:%s.%s table.', len(self.rows_buffer), self.project_id, self.dataset_id, self.table_id) passed, errors = self.client.insert_rows( project_id=self.project_id, dataset_id=self.dataset_id, table_id=self.table_id, rows=self.rows_buffer) self.rows_buffer = [] if not passed: raise RuntimeError('Could not successfully insert rows to BigQuery' ' table [%s:%s.%s]. Errors: %s' % (self.project_id, self.dataset_id, self.table_id, errors)) def __enter__(self): self.client = BigQueryWrapper(client=self.test_bigquery_client) self.client.get_or_create_table( self.project_id, self.dataset_id, self.table_id, self.sink.table_schema, self.sink.create_disposition, self.sink.write_disposition) return self def __exit__(self, exception_type, exception_value, traceback): self._flush_rows_buffer() def Write(self, row): self.rows_buffer.append(row) if len(self.rows_buffer) > self.rows_buffer_flush_threshold: self._flush_rows_buffer() class RowAsDictJsonCoder(coders.Coder): """A coder for a table row (represented as a dict) to/from a JSON string. This is the default coder for sources and sinks if the coder argument is not specified. """ def encode(self, table_row): # The normal error when dumping NAN/INF values is: # ValueError: Out of range float values are not JSON compliant # This code will catch this error to emit an error that explains # to the programmer that they have used NAN/INF values. try: return json.dumps( table_row, allow_nan=False, default=default_encoder).encode('utf-8') except ValueError as e: raise ValueError('%s. %s' % (e, JSON_COMPLIANCE_ERROR)) def decode(self, encoded_table_row): return json.loads(encoded_table_row.decode('utf-8')) class RetryStrategy(object): RETRY_ALWAYS = 'RETRY_ALWAYS' RETRY_NEVER = 'RETRY_NEVER' RETRY_ON_TRANSIENT_ERROR = 'RETRY_ON_TRANSIENT_ERROR' _NON_TRANSIENT_ERRORS = {'invalid', 'invalidQuery', 'notImplemented'} @staticmethod def should_retry(strategy, error_message): if strategy == RetryStrategy.RETRY_ALWAYS: return True elif strategy == RetryStrategy.RETRY_NEVER: return False elif (strategy == RetryStrategy.RETRY_ON_TRANSIENT_ERROR and error_message not in RetryStrategy._NON_TRANSIENT_ERRORS): return True else: return False class AppendDestinationsFn(DoFn): """Adds the destination to an element, making it a KV pair. Outputs a PCollection of KV-pairs where the key is a TableReference for the destination, and the value is the record itself. Experimental; no backwards compatibility guarantees. """ def __init__(self, destination): self.destination = AppendDestinationsFn._get_table_fn(destination) @staticmethod def _value_provider_or_static_val(elm): if isinstance(elm, value_provider.ValueProvider): return elm else: # The type argument is a NoOp, because we assume the argument already has # the proper formatting. return value_provider.StaticValueProvider(lambda x: x, value=elm) @staticmethod def _get_table_fn(destination): if callable(destination): return destination else: return lambda x: AppendDestinationsFn._value_provider_or_static_val( destination).get() def process(self, element): yield (self.destination(element), element)

VENV/lib/python3.6/site-packages/PyInstaller/hooks/hook-PyQt5.py

workingyifei/display-pattern-generator

350

#----------------------------------------------------------------------------- # Copyright (c) 2005-2017, PyInstaller Development Team. # # Distributed under the terms of the GNU General Public License with exception # for distributing bootloader. # # The full license is in the file COPYING.txt, distributed with this software. #----------------------------------------------------------------------------- import os from PyInstaller.utils.hooks import ( get_module_attribute, is_module_satisfies, qt_menu_nib_dir, get_module_file_attribute, collect_data_files) from PyInstaller.compat import getsitepackages, is_darwin, is_win # On Windows system PATH has to be extended to point to the PyQt5 directory. # The PySide directory contains Qt dlls. We need to avoid including different # version of Qt libraries when there is installed another application (e.g. QtCreator) if is_win: from PyInstaller.utils.win32.winutils import extend_system_path extend_system_path([os.path.join(x, 'PyQt5') for x in getsitepackages()]) extend_system_path([os.path.join(os.path.dirname(get_module_file_attribute('PyQt5')), 'Qt', 'bin')]) # In the new consolidated mode any PyQt depends on _qt hiddenimports = ['sip', 'PyQt5.Qt'] # Collect just the qt.conf file. datas = [x for x in collect_data_files('PyQt5', False, os.path.join('Qt', 'bin')) if x[0].endswith('qt.conf')] # For Qt<5.4 to work on Mac OS X it is necessary to include `qt_menu.nib`. # This directory contains some resource files necessary to run PyQt or PySide # app. if is_darwin: # Version of the currently installed Qt 5.x shared library. qt_version = get_module_attribute('PyQt5.QtCore', 'QT_VERSION_STR') if is_module_satisfies('Qt < 5.4', qt_version): datas = [(qt_menu_nib_dir('PyQt5'), '')]

tests/ast/nodes/test_from_node.py

upgradvisor/vyper

351

from vyper import ast as vy_ast def test_output_class(): old_node = vy_ast.parse_to_ast("foo = 42") new_node = vy_ast.Int.from_node(old_node, value=666) assert isinstance(new_node, vy_ast.Int) def test_source(): old_node = vy_ast.parse_to_ast("foo = 42") new_node = vy_ast.Int.from_node(old_node, value=666) assert old_node.src == new_node.src assert old_node.node_source_code == new_node.node_source_code def test_kwargs(): old_node = vy_ast.parse_to_ast("42").body[0].value new_node = vy_ast.Int.from_node(old_node, value=666) assert old_node.value == 42 assert new_node.value == 666 def test_compare_nodes(): old_node = vy_ast.parse_to_ast("foo = 42") new_node = vy_ast.Int.from_node(old_node, value=666) assert not vy_ast.compare_nodes(old_node, new_node) def test_new_node_has_no_parent(): old_node = vy_ast.parse_to_ast("foo = 42") new_node = vy_ast.Int.from_node(old_node, value=666) assert new_node._parent is None assert new_node._depth == 0

generator/modules/opencv.py

dayta-ai/deepo

352

# -*- coding: utf-8 -*- from .__module__ import Module, dependency, source, version from .tools import Tools from .boost import Boost from .python import Python @dependency(Tools, Python, Boost) @source('git') @version('4.0.1') class Opencv(Module): def build(self): return r''' RUN ln -fs /usr/share/zoneinfo/Asia/Hong_Kong /etc/localtime && \ DEBIAN_FRONTEND=noninteractive \ add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main" && \ apt update && \ $APT_INSTALL \ libatlas-base-dev \ libgflags-dev \ libgoogle-glog-dev \ libhdf5-serial-dev \ libleveldb-dev \ liblmdb-dev \ libprotobuf-dev \ libsnappy-dev \ protobuf-compiler \ libopencv-dev \ yasm \ libjpeg-dev \ libjasper-dev \ libavcodec-dev \ libavformat-dev \ libswscale-dev \ libdc1394-22-dev \ libv4l-dev \ libtbb-dev \ libqt4-dev \ libgtk2.0-dev \ libfaac-dev \ libmp3lame-dev \ libopencore-amrnb-dev \ libopencore-amrwb-dev \ libtheora-dev \ libvorbis-dev \ libxvidcore-dev \ x264 \ v4l-utils \ ffmpeg \ && \ $GIT_CLONE --branch {0} https://github.com/opencv/opencv opencv && \ $GIT_CLONE --branch {0} https://github.com/opencv/opencv_contrib.git opencv_contrib && \ mkdir -p opencv/build && cd opencv/build && \ cmake -D CMAKE_BUILD_TYPE=RELEASE \ -D CMAKE_INSTALL_PREFIX=/usr/local \ -D WITH_IPP=OFF \ -D WITH_CUDA=OFF \ -D WITH_TBB=ON \ -D WITH_V4L=ON \ -D WITH_QT=ON \ -D WITH_OPENCL=ON \ -D WITH_GTK=ON \ -D WITH_LIBV4L=ON \ -D BUILD_TESTS=OFF \ -D BUILD_PERF_TESTS=OFF \ -D WITH_FFMPEG=ON \ -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules \ .. && \ make -j"$(nproc)" install && \ ln -s /usr/local/include/opencv4/opencv2 /usr/local/include/opencv2 '''.format(self.version)

day16/solve16.py

jmacarthur/aoc2017

353

#!/usr/bin/python import sys import copy stage_length = 16 stage = map(chr, range(ord('a'),ord('a')+stage_length)) def spin(amount): """To save time, this function isn't used except at the end. Normally, a counter marks the start of the stage and this changes instead. """ global stage stage = stage[amount:] + stage[:amount] def swap(pos1, pos2): global stage (stage[pos1], stage[pos2]) = (stage[pos2], stage[pos1]) with open(sys.argv[1], 'rt') as f: program = ",".join(f.readlines()).split(",") n = 0 pos = 0 arguments_list = [x[1:].strip().split("/") for x in program] action_list = [x[0] for x in program] history = [] # Change this to 1 for the solution to part 1. iterations = 1000000000 while n<iterations: for s in range(0,len(program)): arguments = arguments_list[s] if action_list[s] == 's': pos += stage_length-int(arguments[0]) elif action_list[s] == 'x': swap((int(arguments[0])+pos)%stage_length, (int(arguments[1])+pos)%stage_length) elif action_list[s] == 'p': pos1 = stage.index(arguments[0]) pos2 = stage.index(arguments[1]) swap(pos1, pos2) if stage in history: print("Duplicate found: %r at index %d matches at stage %d"%(stage, history.index(stage), n)) loop_length = n - history.index(stage) complete_cycles = (iterations - n) / loop_length n += complete_cycles * loop_length history.append(copy.copy(stage)) n += 1 spin(pos % stage_length) print "".join(stage)

skimage/segmentation/tests/test_felzenszwalb.py

jaberg/scikits-image

354

<reponame>jaberg/scikits-image import numpy as np from numpy.testing import assert_equal, assert_array_equal from nose.tools import assert_greater from skimage.segmentation import felzenszwalb def test_grey(): # very weak tests. This algorithm is pretty unstable. img = np.zeros((20, 21)) img[:10, 10:] = 0.2 img[10:, :10] = 0.4 img[10:, 10:] = 0.6 seg = felzenszwalb(img, sigma=0) # we expect 4 segments: assert_equal(len(np.unique(seg)), 4) # that mostly respect the 4 regions: for i in range(4): hist = np.histogram(img[seg == i], bins=[0, 0.1, 0.3, 0.5, 1])[0] assert_greater(hist[i], 40) def test_color(): # very weak tests. This algorithm is pretty unstable. img = np.zeros((20, 21, 3)) img[:10, :10, 0] = 1 img[10:, :10, 1] = 1 img[10:, 10:, 2] = 1 seg = felzenszwalb(img, sigma=0) # we expect 4 segments: assert_equal(len(np.unique(seg)), 4) assert_array_equal(seg[:10, :10], 0) assert_array_equal(seg[10:, :10], 2) assert_array_equal(seg[:10, 10:], 1) assert_array_equal(seg[10:, 10:], 3) if __name__ == '__main__': from numpy import testing testing.run_module_suite()

tests/middleware/test_csrf_middleware.py

w3x10e8/core

355

<filename>tests/middleware/test_csrf_middleware.py from masonite.request import Request from masonite.view import View from masonite.auth.Csrf import Csrf from masonite.app import App from masonite.middleware import CsrfMiddleware from masonite.testsuite.TestSuite import generate_wsgi import pytest from masonite.exceptions import InvalidCSRFToken class TestCSRFMiddleware: def setup_method(self): self.app = App() self.request = Request(generate_wsgi()) self.view = View(self.app) self.app.bind('Request', self.request) self.request = self.app.make('Request') self.middleware = CsrfMiddleware(self.request, Csrf(self.request), self.view) def test_middleware_shares_correct_input(self): self.middleware.before() assert 'csrf_field' in self.view.dictionary assert self.view.dictionary['csrf_field'].startswith("<input type='hidden' name='__token' value='") def test_middleware_throws_exception_on_post(self): self.request.environ['REQUEST_METHOD'] = 'POST' self.middleware.exempt = [] with pytest.raises(InvalidCSRFToken): self.middleware.before() def test_incoming_token_does_not_throw_exception_with_token(self): self.request.environ['REQUEST_METHOD'] = 'POST' self.request.request_variables.update({'__token': self.request.get_cookie('csrf_token')}) self.middleware.exempt = [] self.middleware.before()

phoible/views.py

ltxom/phoible

356

<reponame>ltxom/phoible from pyramid.view import view_config import os @view_config(route_name='faq', renderer='faq.mako') def faq_view(request): dir_path = os.path.dirname(__file__) faq_file = os.path.join(dir_path, 'static/faq_with_indexes.html') with open(faq_file, 'r') as f: faq_page = f.read() return {'content': faq_page} @view_config(route_name='conventions', renderer='conventions.mako') def conventions_view(request): dir_path = os.path.dirname(__file__) conventions_file = os.path.join(dir_path, 'static/conventions.html') with open(conventions_file, 'r') as file: conventions_page = file.read().replace('\n', '') return {'content': conventions_page}

tests/restapi/test_routes.py

aiace9/aiida-core

357

# -*- coding: utf-8 -*- ########################################################################### # Copyright (c), The AiiDA team. All rights reserved. # # This file is part of the AiiDA code. # # # # The code is hosted on GitHub at https://github.com/aiidateam/aiida-core # # For further information on the license, see the LICENSE.txt file # # For further information please visit http://www.aiida.net # ########################################################################### # pylint: disable=too-many-lines """Unittests for REST API.""" import tempfile from flask_cors.core import ACL_ORIGIN from aiida import orm from aiida.backends.testbase import AiidaTestCase from aiida.common import json from aiida.common.links import LinkType from aiida.restapi.run_api import configure_api class RESTApiTestCase(AiidaTestCase): """ Setup of the tests for the AiiDA RESTful-api """ _url_prefix = '/api/v4' _dummy_data = {} _PERPAGE_DEFAULT = 20 _LIMIT_DEFAULT = 400 @classmethod def setUpClass(cls, *args, **kwargs): # pylint: disable=too-many-locals, too-many-statements """ Add objects to the database for different requests/filters/orderings etc. """ super().setUpClass() api = configure_api(catch_internal_server=True) cls.app = api.app cls.app.config['TESTING'] = True # create test inputs cell = ((2., 0., 0.), (0., 2., 0.), (0., 0., 2.)) structure = orm.StructureData(cell=cell) structure.append_atom(position=(0., 0., 0.), symbols=['Ba']) structure.store() structure.add_comment('This is test comment.') structure.add_comment('Add another comment.') cif = orm.CifData(ase=structure.get_ase()) cif.store() parameter1 = orm.Dict(dict={'a': 1, 'b': 2}) parameter1.store() parameter2 = orm.Dict(dict={'c': 3, 'd': 4}) parameter2.store() kpoint = orm.KpointsData() kpoint.set_kpoints_mesh([4, 4, 4]) kpoint.store() resources = {'num_machines': 1, 'num_mpiprocs_per_machine': 1} calcfunc = orm.CalcFunctionNode(computer=cls.computer) calcfunc.store() calc = orm.CalcJobNode(computer=cls.computer) calc.set_option('resources', resources) calc.set_attribute('attr1', 'OK') calc.set_attribute('attr2', 'OK') calc.set_extra('extra1', False) calc.set_extra('extra2', 'extra_info') calc.add_incoming(structure, link_type=LinkType.INPUT_CALC, link_label='link_structure') calc.add_incoming(parameter1, link_type=LinkType.INPUT_CALC, link_label='link_parameter') aiida_in = 'The input file\nof the CalcJob node' # Add the calcjob_inputs folder with the aiida.in file to the CalcJobNode repository with tempfile.NamedTemporaryFile(mode='w+') as handle: handle.write(aiida_in) handle.flush() handle.seek(0) calc.put_object_from_filelike(handle, 'calcjob_inputs/aiida.in', force=True) calc.store() # create log message for calcjob import logging from aiida.common.log import LOG_LEVEL_REPORT from aiida.common.timezone import now from aiida.orm import Log log_record = { 'time': now(), 'loggername': 'loggername', 'levelname': logging.getLevelName(LOG_LEVEL_REPORT), 'dbnode_id': calc.id, 'message': 'This is a template record message', 'metadata': { 'content': 'test' }, } Log(**log_record) aiida_out = 'The output file\nof the CalcJob node' retrieved_outputs = orm.FolderData() # Add the calcjob_outputs folder with the aiida.out file to the FolderData node with tempfile.NamedTemporaryFile(mode='w+') as handle: handle.write(aiida_out) handle.flush() handle.seek(0) retrieved_outputs.put_object_from_filelike(handle, 'calcjob_outputs/aiida.out', force=True) retrieved_outputs.store() retrieved_outputs.add_incoming(calc, link_type=LinkType.CREATE, link_label='retrieved') kpoint.add_incoming(calc, link_type=LinkType.CREATE, link_label='create') calc1 = orm.CalcJobNode(computer=cls.computer) calc1.set_option('resources', resources) calc1.store() dummy_computers = [{ 'label': 'test1', 'hostname': 'test1.epfl.ch', 'transport_type': 'ssh', 'scheduler_type': 'pbspro', }, { 'label': 'test2', 'hostname': 'test2.epfl.ch', 'transport_type': 'ssh', 'scheduler_type': 'torque', }, { 'label': 'test3', 'hostname': 'test3.epfl.ch', 'transport_type': 'local', 'scheduler_type': 'slurm', }, { 'label': 'test4', 'hostname': 'test4.epfl.ch', 'transport_type': 'ssh', 'scheduler_type': 'slurm', }] for dummy_computer in dummy_computers: computer = orm.Computer(**dummy_computer) computer.store() # Prepare typical REST responses cls.process_dummy_data() def get_dummy_data(self): return self._dummy_data def get_url_prefix(self): return self._url_prefix @classmethod def process_dummy_data(cls): # pylint: disable=fixme """ This functions prepare atomic chunks of typical responses from the RESTapi and puts them into class attributes """ # TODO: Storing the different nodes as lists and accessing them # by their list index is very fragile and a pain to debug. # Please change this! computer_projections = ['id', 'uuid', 'name', 'hostname', 'transport_type', 'scheduler_type'] computers = orm.QueryBuilder().append(orm.Computer, tag='comp', project=computer_projections).order_by({ 'comp': [{ 'id': { 'order': 'asc' } }] }).dict() # Cast UUID into a string (e.g. in sqlalchemy it comes as a UUID object) computers = [_['comp'] for _ in computers] for comp in computers: if comp['uuid'] is not None: comp['uuid'] = str(comp['uuid']) cls._dummy_data['computers'] = computers calculation_projections = ['id', 'uuid', 'user_id', 'node_type'] calculations = orm.QueryBuilder().append(orm.CalculationNode, tag='calc', project=calculation_projections).order_by({ 'calc': [{ 'id': { 'order': 'desc' } }] }).dict() calculations = [_['calc'] for _ in calculations] for calc in calculations: if calc['uuid'] is not None: calc['uuid'] = str(calc['uuid']) cls._dummy_data['calculations'] = calculations data_projections = ['id', 'uuid', 'user_id', 'node_type'] data_types = { 'cifdata': orm.CifData, 'parameterdata': orm.Dict, 'structuredata': orm.StructureData, 'data': orm.Data, } for label, dataclass in data_types.items(): data = orm.QueryBuilder().append(dataclass, tag='data', project=data_projections).order_by({ 'data': [{ 'id': { 'order': 'desc' } }] }).dict() data = [_['data'] for _ in data] for datum in data: if datum['uuid'] is not None: datum['uuid'] = str(datum['uuid']) cls._dummy_data[label] = data def split_path(self, url): # pylint: disable=no-self-use """ Split the url with "?" to get url path and it's parameters :param url: Web url :return: url path and url parameters """ parts = url.split('?') path = '' query_string = '' if parts: path = parts[0] if len(parts) > 1: query_string = parts[1] return path, query_string def compare_extra_response_data(self, node_type, url, response, uuid=None): """ In url response, we pass some extra information/data along with the node results. e.g. url method, node_type, path, pk, query_string, url, url_root, etc. :param node_type: url requested fot the type of the node :param url: web url :param response: url response :param uuid: url requested for the node pk """ path, query_string = self.split_path(url) self.assertEqual(response['method'], 'GET') self.assertEqual(response['resource_type'], node_type) self.assertEqual(response['path'], path) self.assertEqual(response['id'], uuid) self.assertEqual(response['query_string'], query_string) self.assertEqual(response['url'], f'http://localhost{url}') self.assertEqual(response['url_root'], 'http://localhost/') # node details and list with limit, offset, page, perpage def process_test( self, entity_type, url, full_list=False, empty_list=False, expected_list_ids=None, expected_range=None, expected_errormsg=None, uuid=None, result_node_type=None, result_name=None ): # pylint: disable=too-many-arguments """ Check whether response matches expected values. :param entity_type: url requested for the type of the node :param url: web url :param full_list: if url is requested to get full list :param empty_list: if the response list is empty :param expected_list_ids: list of expected ids from data :param expected_range: [start, stop] range of expected ids from data :param expected_errormsg: expected error message in response :param uuid: url requested for the node pk :param result_node_type: node type in response data :param result_name: result name in response e.g. incoming, outgoing """ if expected_list_ids is None: expected_list_ids = [] if expected_range is None: expected_range = [] if result_node_type is None and result_name is None: result_node_type = entity_type result_name = entity_type url = self._url_prefix + url with self.app.test_client() as client: rv_response = client.get(url) response = json.loads(rv_response.data) if expected_errormsg: self.assertEqual(response['message'], expected_errormsg) else: if full_list: expected_data = self._dummy_data[result_node_type] elif empty_list: expected_data = [] elif expected_list_ids: expected_data = [self._dummy_data[result_node_type][i] for i in expected_list_ids] elif expected_range != []: expected_data = self._dummy_data[result_node_type][expected_range[0]:expected_range[1]] else: from aiida.common.exceptions import InputValidationError raise InputValidationError('Pass the expected range of the dummydata') expected_node_uuids = [node['uuid'] for node in expected_data] result_node_uuids = [node['uuid'] for node in response['data'][result_name]] self.assertEqual(expected_node_uuids, result_node_uuids) self.compare_extra_response_data(entity_type, url, response, uuid) class RESTApiTestSuite(RESTApiTestCase): # pylint: disable=too-many-public-methods """ Define unittests for rest api """ ############### generic endpoints ######################## def test_server(self): """ Test that /server endpoint returns AiiDA version """ url = f'{self.get_url_prefix()}/server' from aiida import __version__ with self.app.test_client() as client: response = client.get(url) data = json.loads(response.data)['data'] self.assertEqual(__version__, data['AiiDA_version']) self.assertEqual(self.get_url_prefix(), data['API_prefix']) def test_base_url(self): """ Test that / returns list of endpoints """ with self.app.test_client() as client: data_base = json.loads(client.get(self.get_url_prefix() + '/').data)['data'] data_server = json.loads(client.get(self.get_url_prefix() + '/server/endpoints').data)['data'] self.assertTrue(len(data_base['available_endpoints']) > 0) self.assertDictEqual(data_base, data_server) def test_cors_headers(self): """ Test that REST API sets cross-origin resource sharing headers """ url = f'{self.get_url_prefix()}/server' with self.app.test_client() as client: response = client.get(url) headers = response.headers self.assertEqual(headers.get(ACL_ORIGIN), '*') ############### computers endpoint ######################## def test_computers_details(self): """ Requests the details of single computer """ node_uuid = self.get_dummy_data()['computers'][1]['uuid'] RESTApiTestCase.process_test( self, 'computers', f'/computers/{str(node_uuid)}', expected_list_ids=[1], uuid=node_uuid ) def test_computers_list(self): """ Get the full list of computers from database """ RESTApiTestCase.process_test(self, 'computers', '/computers?orderby=+id', full_list=True) def test_computers_list_limit_offset(self): """ Get the list of computers from database using limit and offset parameter. It should return the no of rows specified in limit from database starting from the no. specified in offset """ RESTApiTestCase.process_test( self, 'computers', '/computers?limit=2&offset=2&orderby=+id', expected_range=[2, 4] ) def test_computers_list_limit_only(self): """ Get the list of computers from database using limit parameter. It should return the no of rows specified in limit from database. """ RESTApiTestCase.process_test(self, 'computers', '/computers?limit=2&orderby=+id', expected_range=[None, 2]) def test_computers_list_offset_only(self): """ Get the list of computers from database using offset parameter It should return all the rows from database starting from the no. specified in offset """ RESTApiTestCase.process_test(self, 'computers', '/computers?offset=2&orderby=+id', expected_range=[2, None]) def test_computers_list_limit_offset_perpage(self): """ If we pass the limit, offset and perpage at same time, it would return the error message. """ expected_error = 'perpage key is incompatible with limit and offset' RESTApiTestCase.process_test( self, 'computers', '/computers?offset=2&limit=1&perpage=2&orderby=+id', expected_errormsg=expected_error ) def test_computers_list_page_limit_offset(self): """ If we use the page, limit and offset at same time, it would return the error message. """ expected_error = 'requesting a specific page is incompatible with ' \ 'limit and offset' RESTApiTestCase.process_test( self, 'computers', '/computers/page/2?offset=2&limit=1&orderby=+id', expected_errormsg=expected_error ) def test_complist_pagelimitoffset_perpage(self): """ If we use the page, limit, offset and perpage at same time, it would return the error message. """ expected_error = 'perpage key is incompatible with limit and offset' RESTApiTestCase.process_test( self, 'computers', '/computers/page/2?offset=2&limit=1&perpage=2&orderby=+id', expected_errormsg=expected_error ) def test_computers_list_page_default(self): """ it returns the no. of rows defined as default perpage option from database. no.of pages = total no. of computers in database / perpage "/page" acts as "/page/1?perpage=default_value" """ RESTApiTestCase.process_test(self, 'computers', '/computers/page?orderby=+id', full_list=True) def test_computers_list_page_perpage(self): """ no.of pages = total no. of computers in database / perpage Using this formula it returns the no. of rows for requested page """ RESTApiTestCase.process_test( self, 'computers', '/computers/page/1?perpage=2&orderby=+id', expected_range=[None, 2] ) def test_computers_list_page_perpage_exceed(self): """ no.of pages = total no. of computers in database / perpage If we request the page which exceeds the total no. of pages then it would return the error message. """ expected_error = 'Non existent page requested. The page range is [1 : ' \ '3]' RESTApiTestCase.process_test( self, 'computers', '/computers/page/4?perpage=2&orderby=+id', expected_errormsg=expected_error ) ############### list filters ######################## def test_computers_filter_id1(self): """ Add filter on the id of computer and get the filtered computer list (e.g. id=1) """ node_pk = self.get_dummy_data()['computers'][1]['id'] RESTApiTestCase.process_test(self, 'computers', f'/computers?id={str(node_pk)}', expected_list_ids=[1]) def test_computers_filter_id2(self): """ Add filter on the id of computer and get the filtered computer list (e.g. id > 2) """ node_pk = self.get_dummy_data()['computers'][1]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers?id>{str(node_pk)}&orderby=+id', expected_range=[2, None] ) def test_computers_filter_pk(self): """ Add filter on the id of computer and get the filtered computer list (e.g. id=1) """ node_pk = self.get_dummy_data()['computers'][1]['id'] RESTApiTestCase.process_test(self, 'computers', f'/computers?pk={str(node_pk)}', expected_list_ids=[1]) def test_computers_filter_name(self): """ Add filter for the name of computer and get the filtered computer list """ RESTApiTestCase.process_test(self, 'computers', '/computers?name="test1"', expected_list_ids=[1]) def test_computers_filter_hostname(self): """ Add filter for the hostname of computer and get the filtered computer list """ RESTApiTestCase.process_test(self, 'computers', '/computers?hostname="test1.epfl.ch"', expected_list_ids=[1]) def test_computers_filter_transport_type(self): """ Add filter for the transport_type of computer and get the filtered computer list """ RESTApiTestCase.process_test( self, 'computers', '/computers?transport_type="local"&name="test3"&orderby=+id', expected_list_ids=[3] ) ############### list orderby ######################## def test_computers_orderby_id_asc(self): """ Returns the computers list ordered by "id" in ascending order """ RESTApiTestCase.process_test(self, 'computers', '/computers?orderby=id', full_list=True) def test_computers_orderby_id_asc_sign(self): """ Returns the computers list ordered by "+id" in ascending order """ RESTApiTestCase.process_test(self, 'computers', '/computers?orderby=+id', full_list=True) def test_computers_orderby_id_desc(self): """ Returns the computers list ordered by "id" in descending order """ RESTApiTestCase.process_test(self, 'computers', '/computers?orderby=-id', expected_list_ids=[4, 3, 2, 1, 0]) def test_computers_orderby_name_asc(self): """ Returns the computers list ordered by "name" in ascending order """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers?pk>{str(node_pk)}&orderby=name', expected_list_ids=[1, 2, 3, 4] ) def test_computers_orderby_name_asc_sign(self): """ Returns the computers list ordered by "+name" in ascending order """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers?pk>{str(node_pk)}&orderby=+name', expected_list_ids=[1, 2, 3, 4] ) def test_computers_orderby_name_desc(self): """ Returns the computers list ordered by "name" in descending order """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers?pk>{str(node_pk)}&orderby=-name', expected_list_ids=[4, 3, 2, 1] ) def test_computers_orderby_scheduler_type_asc(self): """ Returns the computers list ordered by "scheduler_type" in ascending order """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f"/computers?transport_type=\"ssh\"&pk>{str(node_pk)}&orderby=scheduler_type", expected_list_ids=[1, 4, 2] ) def test_comp_orderby_scheduler_ascsign(self): """ Returns the computers list ordered by "+scheduler_type" in ascending order """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f"/computers?transport_type=\"ssh\"&pk>{str(node_pk)}&orderby=+scheduler_type", expected_list_ids=[1, 4, 2] ) def test_computers_orderby_schedulertype_desc(self): """ Returns the computers list ordered by "scheduler_type" in descending order """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f"/computers?pk>{str(node_pk)}&transport_type=\"ssh\"&orderby=-scheduler_type", expected_list_ids=[2, 4, 1] ) ############### list orderby combinations ####################### def test_computers_orderby_mixed1(self): """ Returns the computers list first order by "transport_type" in ascending order and if it is having same transport_type, order it by "id" """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers?pk>{str(node_pk)}&orderby=transport_type,id', expected_list_ids=[3, 1, 2, 4] ) def test_computers_orderby_mixed2(self): """ Returns the computers list first order by "scheduler_type" in descending order and if it is having same scheduler_type, order it by "name" """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers?pk>{str(node_pk)}&orderby=-scheduler_type,name', expected_list_ids=[2, 3, 4, 1] ) def test_computers_orderby_mixed3(self): """ Returns the computers list first order by "scheduler_type" in ascending order and if it is having same scheduler_type, order it by "hostname" descending order Response:: test4 slurm test3 slurm test2 torque test1 pbspro localhost pbspro ========== Expected:: test1 pbspro localhost pbspro test4 slurm test3 slurm test2 torque test1 test4 RESTApiTestCase.process_test(self, "computers", "/computers?orderby=+scheduler_type, -hostname", expected_list_ids=[1,0,4,3,2]) """ ############### list filter combinations ####################### def test_computers_filter_mixed1(self): """ Add filter for the hostname and id of computer and get the filtered computer list """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f"/computers?id>{str(node_pk)}&hostname=\"test1.epfl.ch\"", expected_list_ids=[1] ) def test_computers_filter_mixed2(self): """ Add filter for the id, hostname and transport_type of the computer and get the filtered computer list """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f"/computers?id>{str(node_pk)}&hostname=\"test3.epfl.ch\"&transport_type=\"ssh\"", empty_list=True ) ############### list all parameter combinations ####################### def test_computers_mixed1(self): """ url parameters: id, limit and offset """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers?id>{str(node_pk)}&limit=2&offset=3&orderby=+id', expected_list_ids=[4] ) def test_computers_mixed2(self): """ url parameters: id, page, perpage """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f'/computers/page/2?id>{str(node_pk)}&perpage=2&orderby=+id', expected_list_ids=[3, 4] ) def test_computers_mixed3(self): """ url parameters: id, transport_type, orderby """ node_pk = self.get_dummy_data()['computers'][0]['id'] RESTApiTestCase.process_test( self, 'computers', f"/computers?id>={str(node_pk)}&transport_type=\"ssh\"&orderby=-id&limit=2", expected_list_ids=[4, 2] ) ########## pass unknown url parameter ########### def test_computers_unknown_param(self): """ url parameters: id, limit and offset from aiida.common.exceptions import InputValidationError RESTApiTestCase.node_exception(self, "/computers?aa=bb&id=2", InputValidationError) """ ############### calculation retrieved_inputs and retrieved_outputs ############# def test_calculation_retrieved_inputs(self): """ Get the list of given calculation retrieved_inputs """ node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f'{self.get_url_prefix()}/calcjobs/{str(node_uuid)}/input_files' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertEqual(response['data'], [{'name': 'calcjob_inputs', 'type': 'DIRECTORY'}]) def test_calculation_retrieved_outputs(self): """ Get the list of given calculation retrieved_outputs """ node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f'{self.get_url_prefix()}/calcjobs/{str(node_uuid)}/output_files' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertEqual(response['data'], [{'name': 'calcjob_outputs', 'type': 'DIRECTORY'}]) ############### calculation incoming ############# def test_calculation_inputs(self): """ Get the list of give calculation incoming """ node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] self.process_test( 'nodes', f'/nodes/{str(node_uuid)}/links/incoming?orderby=id', expected_list_ids=[5, 3], uuid=node_uuid, result_node_type='data', result_name='incoming' ) def test_calculation_input_filters(self): """ Get filtered incoming list for given calculations """ node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] self.process_test( 'nodes', f"/nodes/{str(node_uuid)}/links/incoming?node_type=\"data.dict.Dict.\"", expected_list_ids=[3], uuid=node_uuid, result_node_type='data', result_name='incoming' ) def test_calculation_iotree(self): """ Get filtered incoming list for given calculations """ node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f'{self.get_url_prefix()}/nodes/{str(node_uuid)}/links/tree?in_limit=1&out_limit=1' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertEqual(len(response['data']['nodes']), 1) self.assertEqual(len(response['data']['nodes'][0]['incoming']), 1) self.assertEqual(len(response['data']['nodes'][0]['outgoing']), 1) self.assertEqual(len(response['data']['metadata']), 1) expected_attr = [ 'ctime', 'mtime', 'id', 'node_label', 'node_type', 'uuid', 'description', 'incoming', 'outgoing' ] received_attr = response['data']['nodes'][0].keys() for attr in expected_attr: self.assertIn(attr, received_attr) RESTApiTestCase.compare_extra_response_data(self, 'nodes', url, response, uuid=node_uuid) ############### calculation attributes ############# def test_calculation_attributes(self): """ Get list of calculation attributes """ attributes = { 'attr1': 'OK', 'attr2': 'OK', 'resources': { 'num_machines': 1, 'num_mpiprocs_per_machine': 1 }, } node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f'{self.get_url_prefix()}/nodes/{str(node_uuid)}/contents/attributes' with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data) self.assertNotIn('message', response) self.assertEqual(response['data']['attributes'], attributes) RESTApiTestCase.compare_extra_response_data(self, 'nodes', url, response, uuid=node_uuid) def test_contents_attributes_filter(self): """ Get list of calculation attributes with filter attributes_filter """ node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f"{self.get_url_prefix()}/nodes/{str(node_uuid)}/contents/attributes?attributes_filter=\"attr1\"" with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data) self.assertNotIn('message', response) self.assertEqual(response['data']['attributes'], {'attr1': 'OK'}) RESTApiTestCase.compare_extra_response_data(self, 'nodes', url, response, uuid=node_uuid) ############### calculation node attributes filter ############# def test_calculation_attributes_filter(self): """ Get the list of given calculation attributes filtered """ attributes = { 'attr1': 'OK', 'attr2': 'OK', 'resources': { 'num_machines': 1, 'num_mpiprocs_per_machine': 1 }, } node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f'{self.get_url_prefix()}/nodes/{str(node_uuid)}?attributes=true' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertEqual(response['data']['nodes'][0]['attributes'], attributes) ############### calculation node extras_filter ############# def test_calculation_extras_filter(self): """ Get the list of given calculation extras filtered """ extras = {'extra1': False, 'extra2': 'extra_info'} node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f'{self.get_url_prefix()}/nodes/{str(node_uuid)}?extras=true&extras_filter=extra1,extra2' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertEqual(response['data']['nodes'][0]['extras']['extra1'], extras['extra1']) self.assertEqual(response['data']['nodes'][0]['extras']['extra2'], extras['extra2']) ############### structure node attributes filter ############# def test_structure_attributes_filter(self): """ Get the list of given calculation attributes filtered """ cell = [[2., 0., 0.], [0., 2., 0.], [0., 0., 2.]] node_uuid = self.get_dummy_data()['structuredata'][0]['uuid'] url = f'{self.get_url_prefix()}/nodes/{str(node_uuid)}?attributes=true&attributes_filter=cell' with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data) self.assertEqual(response['data']['nodes'][0]['attributes']['cell'], cell) ############### node attributes_filter with pagination ############# def test_node_attributes_filter_pagination(self): """ Check that node attributes specified in attributes_filter are returned as a dictionary when pagination is set """ expected_attributes = ['resources', 'cell'] url = f'{self.get_url_prefix()}/nodes/page/1?perpage=10&attributes=true&attributes_filter=resources,cell' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertNotEqual(len(response['data']['nodes']), 0) for node in response['data']['nodes']: self.assertIn('attributes', node) self.assertNotIn('attributes.resources', node) self.assertNotIn('attributes.cell', node) self.assertEqual(len(node['attributes']), len(expected_attributes)) for attr in expected_attributes: self.assertIn(attr, node['attributes']) ############### node get one attributes_filter with pagination ############# def test_node_single_attributes_filter(self): """ Check that when only one node attribute is specified in attributes_filter only this attribute is returned as a dictionary when pagination is set """ expected_attribute = ['resources'] url = f'{self.get_url_prefix()}/nodes/page/1?perpage=10&attributes=true&attributes_filter=resources' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertNotEqual(len(response['data']['nodes']), 0) for node in response['data']['nodes']: self.assertEqual(list(node['attributes'].keys()), expected_attribute) ############### node extras_filter with pagination ############# def test_node_extras_filter_pagination(self): """ Check that node extras specified in extras_filter are returned as a dictionary when pagination is set """ expected_extras = ['extra1', 'extra2'] url = f'{self.get_url_prefix()}/nodes/page/1?perpage=10&extras=true&extras_filter=extra1,extra2' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertNotEqual(len(response['data']['nodes']), 0) for node in response['data']['nodes']: self.assertIn('extras', node) self.assertNotIn('extras.extra1', node) self.assertNotIn('extras.extra2', node) self.assertEqual(len(node['extras']), len(expected_extras)) for extra in expected_extras: self.assertIn(extra, node['extras']) ############### node get one extras_filter with pagination ############# def test_node_single_extras_filter(self): """ Check that when only one node extra is specified in extras_filter only this extra is returned as a dictionary when pagination is set """ expected_extra = ['extra2'] url = f'{self.get_url_prefix()}/nodes/page/1?perpage=10&extras=true&extras_filter=extra2' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertNotEqual(len(response['data']['nodes']), 0) for node in response['data']['nodes']: self.assertEqual(list(node['extras'].keys()), expected_extra) ############### node full_type filter ############# def test_nodes_full_type_filter(self): """ Get the list of nodes filtered by full_type """ expected_node_uuids = [] for calc in self.get_dummy_data()['calculations']: if calc['node_type'] == 'process.calculation.calcjob.CalcJobNode.': expected_node_uuids.append(calc['uuid']) url = f"{self.get_url_prefix()}/nodes/?full_type=\"process.calculation.calcjob.CalcJobNode.|\"" with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data) for node in response['data']['nodes']: self.assertIn(node['uuid'], expected_node_uuids) ############### Structure visualization and download ############# def test_structure_derived_properties(self): """ Get the list of give calculation incoming """ node_uuid = self.get_dummy_data()['structuredata'][0]['uuid'] url = f'{self.get_url_prefix()}/nodes/{str(node_uuid)}/contents/derived_properties' with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data) self.assertNotIn('message', response) self.assertEqual( response['data']['derived_properties']['dimensionality'], { 'dim': 3, 'value': 8.0, 'label': 'volume' } ) self.assertEqual(response['data']['derived_properties']['formula'], 'Ba') RESTApiTestCase.compare_extra_response_data(self, 'nodes', url, response, uuid=node_uuid) def test_structure_download(self): """ Test download of structure file """ from aiida.orm import load_node node_uuid = self.get_dummy_data()['structuredata'][0]['uuid'] url = f'{self.get_url_prefix()}/nodes/{node_uuid}/download?download_format=xsf' with self.app.test_client() as client: rv_obj = client.get(url) structure_data = load_node(node_uuid)._exportcontent('xsf')[0] # pylint: disable=protected-access self.assertEqual(rv_obj.data, structure_data) def test_cif(self): """ Test download of cif file """ from aiida.orm import load_node node_uuid = self.get_dummy_data()['cifdata'][0]['uuid'] url = f'{self.get_url_prefix()}/nodes/{node_uuid}/download?download_format=cif' with self.app.test_client() as client: rv_obj = client.get(url) cif = load_node(node_uuid)._prepare_cif()[0] # pylint: disable=protected-access self.assertEqual(rv_obj.data, cif) ############### projectable_properties ############# def test_projectable_properties(self): """ test projectable_properties endpoint """ for nodetype in ['nodes', 'processes', 'computers', 'users', 'groups']: url = f'{self.get_url_prefix()}/{nodetype}/projectable_properties' with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data) self.assertNotIn('message', response) expected_keys = ['display_name', 'help_text', 'is_display', 'is_foreign_key', 'type'] # check fields for _, pinfo in response['data']['fields'].items(): available_keys = pinfo.keys() for prop in expected_keys: self.assertIn(prop, available_keys) # check order available_properties = response['data']['fields'].keys() for prop in response['data']['ordering']: self.assertIn(prop, available_properties) def test_node_namespace(self): """ Test the rest api call to get list of available node namespace """ url = f'{self.get_url_prefix()}/nodes/full_types' with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data) expected_data_keys = ['path', 'namespace', 'subspaces', 'label', 'full_type'] response_keys = response['data'].keys() for dkay in expected_data_keys: self.assertIn(dkay, response_keys) RESTApiTestCase.compare_extra_response_data(self, 'nodes', url, response) def test_comments(self): """ Get the node comments """ node_uuid = self.get_dummy_data()['structuredata'][0]['uuid'] url = f'{self.get_url_prefix()}/nodes/{str(node_uuid)}/contents/comments' with self.app.test_client() as client: rv_obj = client.get(url) response = json.loads(rv_obj.data)['data']['comments'] all_comments = [] for comment in response: all_comments.append(comment['message']) self.assertEqual(sorted(all_comments), sorted(['This is test comment.', 'Add another comment.'])) def test_repo(self): """ Test to get repo list or repo file contents for given node """ from aiida.orm import load_node node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f"{self.get_url_prefix()}/nodes/{str(node_uuid)}/repo/list?filename=\"calcjob_inputs\"" with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) self.assertEqual(response['data']['repo_list'], [{'type': 'FILE', 'name': 'aiida.in'}]) url = f"{self.get_url_prefix()}/nodes/{str(node_uuid)}/repo/contents?filename=\"calcjob_inputs/aiida.in\"" with self.app.test_client() as client: response_obj = client.get(url) input_file = load_node(node_uuid).get_object_content('calcjob_inputs/aiida.in', mode='rb') self.assertEqual(response_obj.data, input_file) def test_process_report(self): """ Test process report """ node_uuid = self.get_dummy_data()['calculations'][1]['uuid'] url = f'{self.get_url_prefix()}/processes/{str(node_uuid)}/report' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) expected_keys = response['data'].keys() for key in ['logs']: self.assertIn(key, expected_keys) expected_log_keys = response['data']['logs'][0].keys() for key in ['time', 'loggername', 'levelname', 'dbnode_id', 'message']: self.assertIn(key, expected_log_keys) def test_download_formats(self): """ test for download format endpoint """ url = f'{self.get_url_prefix()}/nodes/download_formats' with self.app.test_client() as client: response_value = client.get(url) response = json.loads(response_value.data) for key in ['data.structure.StructureData.|', 'data.cif.CifData.|']: self.assertIn(key, response['data'].keys()) for key in ['cif', 'xsf', 'xyz']: self.assertIn(key, response['data']['data.structure.StructureData.|']) self.assertIn('cif', response['data']['data.cif.CifData.|'])

processmonitor.py

yletallec/processmonitor

358

<gh_stars>0 """Process Monitor Usage: processmonitor.py <process_name> <overall_duration> [<sampling_interval>] processmonitor.py -h|--help processmonitor.py -v|--version Options: <process_name> Process name argument. <overall_duration> Overall duration of the monitoring in seconds. <sampling_interval> Sampling interval in seconds (optional, default 5). -h --help Show this screen. -v --version Show version. """ from docopt import docopt from utils import string_to_integer from process import Process from threading import Event, Thread from datetime import datetime import os import sys import csv import time from enum import IntEnum class ExitStatus(IntEnum): OK = 0 BAD_DURATION = 1 BAD_INTERVAL = 2 INTERVAL_GT_DURATION = 3 def call_repeatedly(interval, func, *args): stopped = Event() def loop(): iteration = 1 while not stopped.wait(interval - time.time() % interval): func(*args, iteration) iteration = iteration + 1 Thread(target=loop).start() return stopped.set def print_average(): cpu_avg, mem_avg, files_avg = Process.metrics_average() if cpu_avg != None and mem_avg != None and files_avg != None: print(f"Metrics Avg.: %CPU: {cpu_avg}, MEMORY(B): {mem_avg}, OPEN FILES: {files_avg}") return True return False def generate_report(name, duration, interval): if len(Process.metrics) == 0: return False ts = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") filename = f"{ts}_process-metrics-report_{name}_{duration}_{interval}.csv" with open(f"{filename}", mode='w') as report: writer = csv.writer(report, delimiter=',') writer.writerow(['ITERATION', '%CPU', 'MEMORY(B)', 'OPEN FILES']) iteration = 1 for metric in Process.metrics: writer.writerow([ iteration, metric.cpu, metric.mem, metric.files]) iteration = iteration + 1 reportpath = f"./{filename}" print(f"Metrics report: {reportpath}") return True def raise_memory_leak_warning(name): if (Process.has_memory_leaks(name)): print(f"WARNING: possible memory leaks detected for process \'{name}\'") return True return False def main(): args = docopt(__doc__, version='Process Monitor 1.0') if not args['<sampling_interval>']: args['<sampling_interval>'] = 5 name = args['<process_name>'] try: duration = string_to_integer(args['<overall_duration>']) except: print("duration parameter is not an integer") return ExitStatus.BAD_DURATION try: interval = string_to_integer(args['<sampling_interval>']) except: print("interval parameter is not an integer") return ExitStatus.BAD_INTERVAL if interval > duration: print("interval parameter is greater than duration parameter") return ExitStatus.INTERVAL_GT_DURATION print("---------------------------------------------") print(" Process Monitor") print("---------------------------------------------") print(f"Monitoring process \'{name}\' every {interval} sec for {duration} sec") cancel_future_calls = call_repeatedly(interval, Process.monitor, name) time.sleep(duration) cancel_future_calls() print_average() generate_report(name, duration, interval) raise_memory_leak_warning(name) return ExitStatus.OK def init(): if __name__ == '__main__': if len(sys.argv) == 1: sys.argv.append('-h') sys.exit(main()) init()

Projects/DeepLearningTechniques/MobileNet_v2/tiny_imagenet/data_loader.py

Tim232/Python-Things

359

<gh_stars>1-10 import os import re import numpy as np from Projects.DeepLearningTechniques.MobileNet_v2.tiny_imagenet.constants import * class DataLoader: # todo train/test/validation => (클래스 당 500/50/50) def __init__(self): self.image_width = flags.FLAGS.image_width self.image_height = flags.FLAGS.image_height self.batch_size = flags.FLAGS.batch_size self.data_path = flags.FLAGS.data_path self.img_reg = re.compile('.*\\.jpeg', re.IGNORECASE) self.init_class() self.init_annotation() def init_class(self): self.cls = {} for idx, dir in enumerate(os.listdir(os.path.join(self.data_path, 'train'))): self.cls[dir] = idx def init_annotation(self): self.anno = {} for line in open(os.path.join(self.data_path, 'val', 'val_annotations.txt')): filename, label, *_ = line.split('\t') self.anno[filename] = label def init_train(self): train_x, train_y = [], [] for (path, dirs, files) in os.walk(os.path.join(self.data_path, 'train')): for file in files: if self.img_reg.match(file): train_x.append(os.path.join(path, file)) train_y.append(self.cls[re.match('(.+)\\_\d+\\.jpeg', file, re.IGNORECASE).group(1)]) self.train_len = len(train_y) #todo train data random sort random_sort = np.random.permutation(self.train_len) train_x, train_y = np.asarray(train_x, dtype=np.string_)[random_sort], np.asarray(train_y, dtype=np.int64)[random_sort] #todo (Numpy / List) => Tensor 로 변환 with tf.variable_scope(name_or_scope='data_tensor'): self.train_x = tf.convert_to_tensor(value=train_x, dtype=tf.string, name='train_x') self.train_y = tf.convert_to_tensor(value=train_y, dtype=tf.int64, name='train_y') def init_validation(self): valid_x, valid_y = [], [] for (path, dirs, files) in os.walk(os.path.join(self.data_path, 'val')): for file in files: if self.img_reg.match(file): valid_x.append(os.path.join(path, file)) valid_y.append(self.cls[self.anno[file]]) self.valid_len = len(valid_y) #todo validataion data random sort random_sort = np.random.permutation(self.valid_len) valid_x, valid_y = np.asarray(valid_x, dtype=np.string_)[random_sort], np.asarray(valid_y, dtype=np.int64)[random_sort] #todo (Numpy / List) -> Tensor 로 변환 with tf.variable_scope(name_or_scope='data_tensor'): self.valid_x = tf.convert_to_tensor(value=valid_x, dtype=tf.string, name='valid_x') self.valid_y = tf.convert_to_tensor(value=valid_y, dtype=tf.int64, name='valid_y') def init_test(self): test_x = [] for (path, dirs, files) in os.walk(os.path.join(self.data_path, 'test')): for file in files: test_x.append(os.path.join(path, file)) self.test_len = len(test_x) #todo (Numpy / List) -> Tensor 로 변환 with tf.variable_scope(name_or_scope='data_tensor'): self.test_x = tf.convert_to_tensor(value=test_x, dtype=tf.string, name='test_x') def train_normal(self, x, y): with tf.variable_scope(name_or_scope='train_normal'): x = tf.read_file(filename=x) x = tf.image.decode_png(contents=x, channels=3, name='decode_png') x = tf.divide(tf.cast(x, tf.float32), 255.) x = tf.subtract(x, [0.4921, 0.4833, 0.4484]) x = tf.divide(x, [0.2465, 0.2431, 0.2610]) return x, y def train_random_crop(self, x, y): with tf.variable_scope(name_or_scope='train_random_crop'): x = tf.read_file(filename=x) x = tf.image.decode_png(contents=x, channels=3, name='decode_png') x = tf.pad(x, [[0, 0], [4, 4], [4, 4], [0, 0]], name='padding') # x = tf.image.resize_images(images=x, size=(self.image_height+8, self.image_width+8), method=tf.image.ResizeMethod.NEAREST_NEIGHBOR) x = tf.random_crop(value=x, size=(self.image_height, self.image_width, 3)) x = tf.divide(tf.cast(x, tf.float32), 255.) x = tf.subtract(x, [0.4921, 0.4833, 0.4484]) x = tf.divide(x, [0.2465, 0.2431, 0.2610]) return x, y def valid_normal(self, x, y): with tf.variable_scope(name_or_scope='valid_normal'): x = tf.read_file(filename=x) x = tf.image.decode_png(contents=x, channels=3, name='decode_png') x = tf.divide(tf.cast(x, tf.float32), 255.) x = tf.subtract(x, [0.4921, 0.4833, 0.4484]) x = tf.divide(x, [0.2465, 0.2431, 0.2610]) return x, y def test_normal(self, x): with tf.variable_scope(name_or_scope='test_normal'): x = tf.read_file(filename=x) x = tf.image.decode_png(contents=x, channels=3, name='decode_png') x = tf.divide(tf.cast(x, tf.float32), 255.) x = tf.subtract(x, [0.4921, 0.4833, 0.4484]) x = tf.divide(x, [0.2465, 0.2431, 0.2610]) return x def dataset_batch_loader(self, dataset, ref_func, name): with tf.variable_scope(name_or_scope=name): dataset_map = dataset.map(ref_func).batch(self.batch_size) iterator = dataset_map.make_one_shot_iterator() batch_input = iterator.get_next() return batch_input def train_loader(self): with tf.variable_scope('train_loader'): ''' repeat(): 데이터셋이 끝에 도달했을 때 다시 처음부터 수행하게 하는 함수 shuffle(): 데이터셋에 대해 random sort 기능을 수행하는 함수 (괄호안에 값이 전체 데이터 수보다 크면 전체 데이터에 대한 random sort) ''' dataset = tf.data.Dataset.from_tensor_slices((self.train_x, self.train_y)).repeat() normal_batch = self.dataset_batch_loader(dataset, self.train_normal, name='normal_batch') random_crop_batch = self.dataset_batch_loader(dataset, self.train_random_crop, name='random_crop_batch') return normal_batch, random_crop_batch def valid_loader(self): with tf.variable_scope('valid_loader'): dataset = tf.data.Dataset.from_tensor_slices((self.valid_x, self.valid_y)).repeat() normal_batch = self.dataset_batch_loader(dataset, self.valid_normal, name='normal_batch') return normal_batch def test_loader(self): with tf.variable_scope('test_loader'): dataset = tf.data.Dataset.from_tensor_slices(self.test_x).repeat() normal_batch = self.dataset_batch_loader(dataset, self.test_normal, name='normal_batch') return normal_batch

MarkReport/MarkReport.py

dedukun/MarkReport

360

<filename>MarkReport/MarkReport.py #!/usr/bin/env python3 # Command line flags import os import glob import re import pyinotify import subprocess from sys import stdout, stderr from time import time, sleep from tempfile import gettempdir from distutils.dir_util import copy_tree from shutil import copyfile from weasyprint import HTML import argparse parser = argparse.ArgumentParser( description='Converts Markdown to elegant PDF reports') parser.add_argument('--basic', dest='basic', action='store_true', help='Do not enrich HTML with LaTeX and syntax highlighting (faster builds)') parser.add_argument('--watch', dest='watch', action='store_true', help='Watch the current folder for changes and rebuild automatically') parser.add_argument('--quiet', dest='quiet', action='store_true', help='Do not output any information') parser.add_argument("--timeout", type=int, default=2, help='Page generation timeout') parser.add_argument("--base-html", type=str, default="", help='The path to the base HTML file') parser.set_defaults(watch=False) args = parser.parse_args() # Check directory ok = False for file in os.listdir("."): if file.endswith(".md"): ok = True break if not ok: stderr.write("No markdown file found in the current folder") exit(1) if args.base_html != "": if not os.path.isfile(args.base_html): stderr.write("The given base HTML file doesn't exist") exit(1) script_path = os.path.dirname(os.path.realpath(__file__)) # Temp dir timestamp = str(int(time())) tmp_dir = gettempdir() + "/" + timestamp + "_md-report/" os.makedirs(tmp_dir, exist_ok=True) # Headless browser if not args.basic: from selenium import webdriver from selenium.webdriver.firefox.options import Options from selenium.webdriver.common.desired_capabilities import DesiredCapabilities options = Options() options.headless = True options.log.level = "trace" d = DesiredCapabilities.FIREFOX d['loggingPrefs'] = {'browser': 'ALL'} driver = webdriver.Firefox(options=options, capabilities=d) driver.set_page_load_timeout(args.timeout) prev_compile_time = 0 def recompile(notifier): if notifier is not None and (notifier.maskname != "IN_MODIFY" or notifier.pathname.endswith(".pdf")): return global prev_compile_time if time() - prev_compile_time < 1: return prev_compile_time = time() if not args.quiet: stdout.write("\rBuilding the PDF file...") stdout.flush() files = glob.glob(tmp_dir + '/*.md') for f in files: os.remove(f) if args.base_html == "": copyfile(script_path + "/base.html", tmp_dir + "/base.html") else: copyfile(args.base_html, tmp_dir + "/base.html") if not os.path.islink(tmp_dir + "/src"): os.symlink(script_path + "/src", tmp_dir + "/src") copy_tree(".", tmp_dir) # Markdown parsing subprocess.check_output(script_path + "/md-parsing " + tmp_dir, shell=True).decode('utf-8') html_file_name = tmp_dir + "output.html" # Interpret JS code if not args.basic: driver.get("file:///" + html_file_name) sleep(2) elem = driver.find_element_by_xpath("//*") interpreted_html = elem.get_attribute("outerHTML") with open(html_file_name, "w") as html_out_file: html_out_file.write(interpreted_html) # Create final PDF file pdf = HTML(html_file_name).write_pdf() f = open("output.pdf", 'wb') f.write(pdf) if not args.quiet: stdout.write("\rDone. ") stdout.flush() recompile(None) if not args.watch: if not args.basic: driver.quit() exit(0) watch_manager = pyinotify.WatchManager() event_notifier = pyinotify.Notifier(watch_manager, recompile) watch_manager.add_watch(os.path.abspath("."), pyinotify.ALL_EVENTS, rec=True) event_notifier.loop() if not args.basic: driver.quit()

DFS/13023.py

kjh9267/BOJ_Python

361

# https://www.acmicpc.net/problem/13023 import sys sys.setrecursionlimit(999999999) def dfs_all(): is_possible = [False] for node in range(N): visited = [False for _ in range(N)] dfs(node, 0, visited, is_possible) if is_possible[0]: return 1 return 0 def dfs(cur, depth, visited, is_possible): if visited[cur]: return if depth == target_depth: is_possible[0] = True return visited[cur] = True for nxt in graph[cur]: dfs(nxt, depth + 1, visited, is_possible) visited[cur] = False if __name__ == '__main__': input = __import__('sys').stdin.readline target_depth = 4 N, M = map(int, input().split()) graph = [list() for _ in range(N)] for _ in range(M): a, b = map(int, input().split()) graph[a].append(b) graph[b].append(a) print(dfs_all())

experiments/bst/setup.py

bigchaindb/privacy-protocols

362

<reponame>bigchaindb/privacy-protocols """bst: BigchainDB Sharing Tools""" from setuptools import setup, find_packages install_requires = [ 'base58~=0.2.2', 'PyNaCl~=1.1.0', 'bigchaindb-driver', 'click==6.7', 'colorama', ] setup( name='bst', version='0.1.0', description='bst: BigchainDB Sharing Tools', long_description=( 'A collection of scripts with different patterns to share' 'private data on BigchainDB.'), url='https://github.com/vrde/bst/', author='<NAME>', author_email='<EMAIL>', license='AGPLv3', zip_safe=False, classifiers=[ 'Development Status :: 3 - Alpha', 'Intended Audience :: Developers', 'Topic :: Database', 'Topic :: Database :: Database Engines/Servers', 'Topic :: Software Development', 'Natural Language :: English', 'License :: OSI Approved :: GNU Affero General Public License v3', 'Programming Language :: Python :: 3 :: Only', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Operating System :: MacOS :: MacOS X', 'Operating System :: POSIX :: Linux', ], packages=find_packages(), entry_points={ 'console_scripts': [ 'bst=bst.cli:main' ], }, install_requires=install_requires )

polyaxon/db/admin/job_resources.py

elyase/polyaxon

363

<gh_stars>0 from django.contrib import admin from db.models.job_resources import JobResources admin.site.register(JobResources)

voting_ml/main.py

tommy-waltmann/voting-ml

364

<reponame>tommy-waltmann/voting-ml<filename>voting_ml/main.py import numpy as np import sklearn import subprocess from sklearn import model_selection, tree import data import feature_selection import model_sel import os import matplotlib.pyplot as plt import seaborn as sns def main(): #parameter space list_test_size = [0.1,0.15,0.2] # decide this list_ftsel_method = ['chi2','mutlinfo','pca','dt'] list_num_features = [10,15,20] # decide this list_Kfold = [3,5] list_corr_threshold = [1,0.5,0.6,0.7] # decide this param_space = { 'criterion': ['gini', 'entropy'], 'max_depth': [2, 3, 4, 5, 7], 'min_samples_split': [2, 5, 10], 'min_samples_leaf': [2, 5, 10], 'max_leaf_nodes': [2, 4, 6, 8, 10, 12, 15], } repeat = 1 #output dictrionary list list_output_dict = [] # output directory path outdir = "../results/run1/" if(not os.path.isdir(outdir)): os.mkdir(outdir) o_models_file = open(outdir+"models.csv","w") o_models_file.write("test size,run num,ftsel method,Kfold,number of features,correlation threshold,best features,criterion,max_depth,max_leaf_nodes,min_samples_leaf,min_samples_split,training accuracy,test accuracy\n") #splitting data and weights into train, test (refer to optimal_params.py) poll_data = data.PollDataProxy(remove_nan=False, convert_to_float=False) acc = [] '''refer to optimal_params.py. Functions from this python scripts are transferred here. (get_bad_questions() and separate_weights().)''' for ts in list_test_size: for run_num in range(repeat): all_data, all_data_questions = poll_data.all_data_except(get_bad_questions()) X = all_data[:, :-1] y = all_data[:, -1] X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, test_size=ts, shuffle=True) X_train, weights_train, questions = separate_weights(X_train, all_data_questions[:-1]) X_test, weights_test, _ = separate_weights(X_test, all_data_questions[:-1]) print("Number of Training Samples:", len(X_train)) print("Number of Testing Samples:", len(X_test)) data_dict = { 'X_train': X_train, 'X_test': X_test, 'y_train': y_train, 'y_test': y_test } weights_dict = { 'weights_train': weights_train, 'weights_test': weights_test} for meth in list_ftsel_method: '''Create class objects of the current selection method''' for thres in list_corr_threshold: data_ranked_dict, ranked_questions = {}, [] ftsel_obj =None if(meth=='chi2'): ftsel_obj = feature_selection.FeatureSelection( necess_que_file="../extern/manage_data/list_all_questions.txt", unnecess_que_file="../extern/manage_data/list_unnecessary_columns.txt", bool_necess_que=False, run_name="test_chi2" ) data_ranked_dict, ranked_questions = ftsel_obj.ftsel_chi2(data_dict, thres) elif(meth=='mutlinfo'): ftsel_obj = feature_selection.FeatureSelection( necess_que_file="../extern/manage_data/list_all_questions.txt", unnecess_que_file="../extern/manage_data/list_unnecessary_columns.txt", bool_necess_que=False, run_name="test_mutlinfo" ) data_ranked_dict, ranked_questions = ftsel_obj.ftsel_mutlinfo(data_dict, thres) elif(meth=='pca'): ftsel_obj = feature_selection.FeatureSelection( necess_que_file="../extern/manage_data/list_all_questions.txt", unnecess_que_file="../extern/manage_data/list_unnecessary_columns.txt", bool_necess_que=False, run_name="test_pca" ) data_ranked_dict,_ = ftsel_obj.ftsel_pca(data_dict) fts = data_sel_dict['X_train'].shape[1] questions_int = list(map(str, list(range(1,fts+1,1)))) ranked_questions = ["ft_"+x for x in questions_int] elif(meth=='dt'): ftsel_obj = feature_selection.FeatureSelection( necess_que_file="../extern/manage_data/list_all_questions.txt", unnecess_que_file="../extern/manage_data/list_unnecessary_columns.txt", bool_necess_que=False, run_name="test_dt" ) data_ranked_dict, ranked_questions = ftsel_obj.ftsel_decision_tree_method(data_dict, thres) for num in list_num_features: data_sel_dict, sel_questions = ftsel_obj.select_num_features(data_ranked_dict, num, ranked_questions) ftsel_obj.plot_heatmap(data_sel_dict['X_train'], sel_questions) for K in list_Kfold: '''Here create a class onject of "model_sel" and output all the best parameters and values into "list_output_dict". Then, can create a .csv file to list all the models and accuracies.''' model_obj = model_sel.model_sel(ts, run_num, meth, param_space, K, num, thres, data_sel_dict ,weights_dict, sel_questions, outdir).select_model() # intermediate = model_obj.select_model() acc.append(model_obj['test_acc']) o_models_file.write(str(ts)+",") o_models_file.write(str(run_num)+",") o_models_file.write(meth+",") o_models_file.write(str(K)+",") o_models_file.write(str(num)+",") o_models_file.write(str(thres)+",") for ii in range(len(model_obj['best_features'])): o_models_file.write(model_obj['best_features'][ii]+" ") o_models_file.write(",") o_models_file.write(model_obj['best_params']['criterion']+",") o_models_file.write(str(model_obj['best_params']['max_depth'])+",") o_models_file.write(str(model_obj['best_params']['max_leaf_nodes'])+",") o_models_file.write(str(model_obj['best_params']['min_samples_leaf'])+",") o_models_file.write(str(model_obj['best_params']['min_samples_split'])+",") o_models_file.write(str(model_obj['train_acc'])+",") o_models_file.write(str(model_obj['test_acc'])+",") o_models_file.write("\n") list_output_dict.append(model_obj) '''Once all the models are run, select the model with best test accuracy and return the output dict for that model.''' o_models_file.close() best_index = np.argmax(acc) best_model_dict = list_output_dict[best_index] print("The best model parameters:") print(best_model_dict) def get_bad_questions(): f = open("../extern/manage_data/list_unnecessary_columns.txt", 'r') bad_questions = f.readline().split(',') bad_questions[-1] = bad_questions[-1][:-1] # chop the \n off the end bad_questions.remove('weight') # need weight for training return bad_questions def separate_weights(X_train, column_names): """ Removes the column containing weights from X_train, and returns it as a separate array. """ weight_column_idx = column_names.index('weight') weights = X_train[:, weight_column_idx] new_X_train = np.delete(X_train, weight_column_idx, axis=1) new_questions = column_names new_questions.remove('weight') return new_X_train, weights, new_questions if __name__ == "__main__": main()

src/the_tale/the_tale/game/heroes/tests/test_logic.py

al-arz/the-tale

365

<reponame>al-arz/the-tale import smart_imports smart_imports.all() class HeroDescriptionTests(utils_testcase.TestCase): def setUp(self): super().setUp() game_logic.create_test_map() account = self.accounts_factory.create_account(is_fast=True) self.storage = game_logic_storage.LogicStorage() self.storage.load_account_data(account) self.hero = self.storage.accounts_to_heroes[account.id] def test_no_description(self): self.assertEqual(logic.get_hero_description(self.hero.id), '') def test_has_description(self): logic.set_hero_description(self.hero.id, 'bla-bla') self.assertEqual(logic.get_hero_description(self.hero.id), 'bla-bla') def test_update_description(self): logic.set_hero_description(self.hero.id, 'bla-bla') logic.set_hero_description(self.hero.id, 'new description') self.assertEqual(logic.get_hero_description(self.hero.id), 'new description') class CreateHero(utils_testcase.TestCase): def setUp(self): super().setUp() game_logic.create_test_map() self.account = accounts_prototypes.AccountPrototype.create(nick='nick-xxx', email='<EMAIL>', is_fast=False) self.attributes = {'is_fast': False, 'is_bot': False, 'might': 0, 'active_state_end_at': datetime.datetime.now() + datetime.timedelta(days=3), 'premium_state_end_at': datetime.datetime.fromtimestamp(0), 'ban_state_end_at': datetime.datetime.fromtimestamp(0)} def test_default(self): logic.create_hero(account_id=self.account.id, attributes=self.attributes) hero = logic.load_hero(self.account.id) self.assertEqual(hero.id, self.account.id) self.assertEqual(hero.account_id, self.account.id) self.assertIn(hero.gender, (game_relations.GENDER.MALE, game_relations.GENDER.FEMALE)) self.assertEqual(hero.preferences.energy_regeneration_type, hero.race.energy_regeneration) self.assertEqual(hero.habit_honor.raw_value, 0) self.assertEqual(hero.habit_peacefulness.raw_value, 0) self.assertTrue(hero.preferences.archetype.is_NEUTRAL) self.assertTrue(hero.upbringing.is_PHILISTINE) self.assertTrue(hero.first_death.is_FROM_THE_MONSTER_FANGS) self.assertTrue(hero.death_age.is_MATURE) def test_account_attributes_required(self): for attribute in self.attributes.keys(): with self.assertRaises(exceptions.HeroAttributeRequiredError): logic.create_hero(account_id=self.account.id, attributes={key: value for key, value in self.attributes.items() if key != attribute }) def test_account_attributes(self): attributes = {'is_fast': random.choice((True, False)), 'is_bot': random.choice((True, False)), 'might': random.randint(1, 1000), 'active_state_end_at': datetime.datetime.fromtimestamp(1), 'premium_state_end_at': datetime.datetime.fromtimestamp(2), 'ban_state_end_at': datetime.datetime.fromtimestamp(3)} logic.create_hero(account_id=self.account.id, attributes=attributes) hero = logic.load_hero(self.account.id) self.assertEqual(hero.is_fast, attributes['is_fast']) self.assertEqual(hero.is_bot, attributes['is_bot']) self.assertEqual(hero.might, attributes['might']) self.assertEqual(hero.active_state_end_at, attributes['active_state_end_at']) self.assertEqual(hero.premium_state_end_at, attributes['premium_state_end_at']) self.assertEqual(hero.ban_state_end_at, attributes['ban_state_end_at']) def test_attributes(self): self.attributes.update({'race': game_relations.RACE.random(), 'gender': game_relations.GENDER.random(), 'name': game_names.generator().get_name(game_relations.RACE.random(), game_relations.GENDER.random()), 'peacefulness': random.randint(-c.HABITS_BORDER, c.HABITS_BORDER), 'honor': random.randint(-c.HABITS_BORDER, c.HABITS_BORDER), 'archetype': game_relations.ARCHETYPE.random(), 'upbringing': tt_beings_relations.UPBRINGING.random(), 'first_death': tt_beings_relations.FIRST_DEATH.random(), 'death_age': tt_beings_relations.AGE.random()}) logic.create_hero(account_id=self.account.id, attributes=self.attributes) hero = logic.load_hero(self.account.id) self.assertEqual(hero.race, self.attributes['race']) self.assertEqual(hero.gender, self.attributes['gender']) self.assertEqual(hero.utg_name, self.attributes['name']) self.assertEqual(hero.habit_peacefulness.raw_value, self.attributes['peacefulness']) self.assertEqual(hero.habit_honor.raw_value, self.attributes['honor']) self.assertEqual(hero.preferences.archetype, self.attributes['archetype']) self.assertEqual(hero.upbringing, self.attributes['upbringing']) self.assertEqual(hero.first_death, self.attributes['first_death']) self.assertEqual(hero.death_age, self.attributes['death_age']) class RegisterSpendingTests(utils_testcase.TestCase): def setUp(self): super().setUp() self.places = game_logic.create_test_map() account = self.accounts_factory.create_account() self.storage = game_logic_storage.LogicStorage() self.storage.load_account_data(account) self.hero = self.storage.accounts_to_heroes[account.id] self.hero.premium_state_end_at game_tt_services.debug_clear_service() @mock.patch('the_tale.game.heroes.objects.Hero.can_change_place_power', lambda hero, place: True) def test_not_in_place(self): self.hero.position.set_position(0, 0) self.assertEqual(self.hero.position.place_id, None) logic.register_spending(self.hero, 100) impacts = game_tt_services.money_impacts.cmd_get_targets_impacts(targets=[(tt_api_impacts.OBJECT_TYPE.PLACE, self.places[0].id)]) self.assertEqual(impacts, []) @mock.patch('the_tale.game.heroes.objects.Hero.can_change_place_power', lambda hero, place: False) def test_can_not_change_place_power(self): self.hero.position.set_place(self.places[0]) logic.register_spending(self.hero, 100) impacts = game_tt_services.money_impacts.cmd_get_targets_impacts(targets=[(tt_api_impacts.OBJECT_TYPE.PLACE, self.places[0].id)]) self.assertEqual(impacts, []) @mock.patch('the_tale.game.heroes.objects.Hero.can_change_place_power', lambda hero, place: True) def test_can_change_place_power(self): self.hero.position.set_place(self.places[0]) logic.register_spending(self.hero, 100) impacts = game_tt_services.money_impacts.cmd_get_targets_impacts(targets=[(tt_api_impacts.OBJECT_TYPE.PLACE, self.places[0].id)]) self.assertEqual(len(impacts), 1) self.assertEqual(impacts[0].amount, 100) self.assertTrue(impacts[0].target_type.is_PLACE) self.assertEqual(impacts[0].target_id, self.places[0].id) @mock.patch('the_tale.game.heroes.objects.Hero.can_change_place_power', lambda hero, place: True) def test_can_change_place_power__below_zero(self): self.hero.position.set_place(self.places[0]) logic.register_spending(self.hero, 100) logic.register_spending(self.hero, -50) impacts = game_tt_services.money_impacts.cmd_get_targets_impacts(targets=[(tt_api_impacts.OBJECT_TYPE.PLACE, self.places[0].id)]) self.assertEqual(len(impacts), 1) self.assertEqual(impacts[0].amount, 150) class GetPlacesPathModifiersTests(places_helpers.PlacesTestsMixin, utils_testcase.TestCase): def setUp(self): super().setUp() self.places = game_logic.create_test_map() account = self.accounts_factory.create_account(is_fast=True) self.storage = game_logic_storage.LogicStorage() self.storage.load_account_data(account) self.hero = self.storage.accounts_to_heroes[account.id] def place_0_cost(self): return logic.get_places_path_modifiers(self.hero)[self.places[0].id] def test_every_place_has_modifier(self): modifiers = logic.get_places_path_modifiers(self.hero) self.assertEqual(set(modifiers.keys()), {place.id for place in self.places}) def test_race_bonus(self): self.places[0].race = game_relations.RACE.random(exclude=(self.hero.race,)) with self.check_almost_delta(self.place_0_cost, -c.PATH_MODIFIER_MINOR_DELTA): self.places[0].race = self.hero.race def test_modifier_bonus(self): self.assertFalse(self.places[0].is_modifier_active()) with self.check_almost_delta(self.place_0_cost, -c.PATH_MODIFIER_MINOR_DELTA): self.places[0].set_modifier(places_modifiers.CITY_MODIFIERS.FORT) self.create_effect(self.places[0].id, value=100500, attribute=places_relations.ATTRIBUTE.MODIFIER_FORT, delta=0) self.places[0].refresh_attributes() self.assertTrue(self.places[0].is_modifier_active()) def test_home_place(self): with self.check_almost_delta(self.place_0_cost, -c.PATH_MODIFIER_NORMAL_DELTA): self.hero.preferences.set(relations.PREFERENCE_TYPE.PLACE, self.places[0]) def test_friend(self): with self.check_almost_delta(self.place_0_cost, -c.PATH_MODIFIER_NORMAL_DELTA): self.hero.preferences.set(relations.PREFERENCE_TYPE.FRIEND, self.places[0].persons[0]) def test_enemy(self): with self.check_almost_delta(self.place_0_cost, c.PATH_MODIFIER_NORMAL_DELTA): self.hero.preferences.set(relations.PREFERENCE_TYPE.ENEMY, self.places[0].persons[0]) def test_tax(self): self.places[0].attrs.size = 10 self.places[0].refresh_attributes() self.assertEqual(self.places[0].attrs.tax, 0) with self.check_almost_delta(self.place_0_cost, c.PATH_MODIFIER_NORMAL_DELTA): self.create_effect(self.places[0].id, value=100, attribute=places_relations.ATTRIBUTE.TAX, delta=0) self.places[0].refresh_attributes() HABITS_DELTAS = [(-1, -1, -c.PATH_MODIFIER_MINOR_DELTA), (-1, 0, 0), (-1, +1, +c.PATH_MODIFIER_MINOR_DELTA), ( 0, -1, 0), ( 0, 0, 0), ( 0, +1, 0), (+1, -1, +c.PATH_MODIFIER_MINOR_DELTA), (+1, 0, 0), (+1, +1, -c.PATH_MODIFIER_MINOR_DELTA)] def test_habits__honor(self): for place_direction, hero_direction, expected_delta in self.HABITS_DELTAS: self.places[0].habit_honor.set_habit(0) self.hero.habit_honor.set_habit(0) with self.check_almost_delta(self.place_0_cost, expected_delta): self.places[0].habit_honor.set_habit(place_direction * c.HABITS_BORDER) self.hero.habit_honor.set_habit(hero_direction * c.HABITS_BORDER) def test_habits__peacefulness(self): for place_direction, hero_direction, expected_delta in self.HABITS_DELTAS: self.places[0].habit_peacefulness.set_habit(0) self.hero.habit_peacefulness.set_habit(0) with self.check_almost_delta(self.place_0_cost, expected_delta): self.places[0].habit_peacefulness.set_habit(place_direction * c.HABITS_BORDER) self.hero.habit_peacefulness.set_habit(hero_direction * c.HABITS_BORDER)

tinylinks/tests/test_app/models.py

brad/django-tinylinks

366

<filename>tinylinks/tests/test_app/models.py<gh_stars>10-100 """Dummy model needed for tests.""" pass

postcipes/hydraulic_jump.py

timofeymukha/postcipes

367

# This file is part of postcipes # (c) <NAME> # The code is released under the MIT Licence. # See LICENCE.txt and the Legal section in the README for more information from __future__ import absolute_import from __future__ import division from __future__ import print_function from .postcipe import Postcipe import turbulucid as tbl from scipy.interpolate import interp1d import numpy as np import h5py __all__ = ["HydraulicJump"] class HydraulicJump(Postcipe): def __init__(self, path): Postcipe.__init__(self) self.case = tbl.Case(path) self.case['alphag'] = 1 - self.case['alpha.waterMean'] self.U = self.case.boundary_data("inlet", sort="y")[1]['UMean'][0, 0] y_inlet = self.case.boundary_data("inlet", sort="y")[0][:, 1] inlet_edge_length = tbl.edge_lengths(self.case, "inlet") self.d = y_inlet[-1] + 0.5*inlet_edge_length[-1] self.Fr1 = self.U/np.sqrt(9.81*self.d) self.d2 = self.d*(np.sqrt(1 + 8*self.Fr1**2) - 1)/2 self.Fr2 = self.U/np.sqrt(9.81*self.d2) iso05 = tbl.isoline(self.case, "alpha.waterMean", 0.5) idx = iso05[:, 0].argsort() self.xfs = iso05[idx, 0] self.yfs = iso05[idx, 1] idx_toe = np.argmin(np.abs(self.d*1.1 - self.yfs[:int(self.yfs.size/2)])) self.xtoe = self.xfs[idx_toe]

main/SimulationSettings/ScreenshotsSteppable/Simulation/screenshots_steppables.py

JulianoGianlupi/nh-cc3d-4x-base-tool

368

from cc3d.core.PySteppables import * from cc3d import CompuCellSetup from random import random class ScreenshotSteppable(SteppableBasePy): def __init__(self, frequency=10): SteppableBasePy.__init__(self, frequency) def step(self, mcs): if mcs in [3, 5, 19,20, 23, 29, 31]: self.request_screenshot(mcs=mcs, screenshot_label='Cell_Field_CellField_2D_XY_0')

aesara/gpuarray/optdb.py

anirudhacharya/aesara

369

<filename>aesara/gpuarray/optdb.py from aesara.compile import optdb from aesara.graph.opt import GraphToGPULocalOptGroup, TopoOptimizer, local_optimizer from aesara.graph.optdb import ( EquilibriumDB, LocalGroupDB, OptimizationDatabase, SequenceDB, ) gpu_optimizer = EquilibriumDB() gpu_cut_copies = EquilibriumDB() # Not used for an EquilibriumOptimizer. It has the "tracks" that we need for GraphToGPUDB. gpu_optimizer2 = EquilibriumDB() gpu_seqopt = SequenceDB() # do not add 'fast_run' to these two as this would always enable gpuarray mode optdb.register( "gpuarray_opt", gpu_seqopt, optdb.__position__.get("add_destroy_handler", 49.5) - 1, "gpuarray", ) pool_db = LocalGroupDB() pool_db2 = LocalGroupDB(local_opt=GraphToGPULocalOptGroup) pool_db2.__name__ = "pool_db2" matrix_ops_db = LocalGroupDB() matrix_ops_db2 = LocalGroupDB(local_opt=GraphToGPULocalOptGroup) matrix_ops_db2.__name__ = "matrix_ops_db2" abstract_batch_norm_db = LocalGroupDB() abstract_batch_norm_db2 = LocalGroupDB(local_opt=GraphToGPULocalOptGroup) abstract_batch_norm_db2.__name__ = "abstract_batch_norm_db2" abstract_batch_norm_groupopt = LocalGroupDB() abstract_batch_norm_groupopt.__name__ = "gpuarray_batchnorm_opts" def register_opt(*tags, **kwargs): def f(local_opt): name = (kwargs and kwargs.pop("name")) or local_opt.__name__ gpu_optimizer.register(name, local_opt, "fast_run", "gpuarray", *tags) return local_opt return f def register_opt2(tracks, *tags, **kwargs): """ Decorator for the new GraphToGPU optimizer. Takes an extra parameter(Op) compared to register_opt decorator. Parameters ---------- tracks : List of Op class Or Op instance or None The Node's Op to which optimization is being applied. tags : String The optimization tag to which the optimizer will be registered. """ def f(local_opt): name = (kwargs and kwargs.pop("name")) or local_opt.__name__ if isinstance(local_opt, OptimizationDatabase): opt = local_opt else: opt = local_optimizer(tracks)(local_opt) gpu_optimizer2.register(name, opt, "fast_run", "gpuarray", *tags) return local_opt return f def register_inplace(*tags, **kwargs): def f(local_opt): name = (kwargs and kwargs.pop("name")) or local_opt.__name__ optdb.register( name, TopoOptimizer(local_opt, failure_callback=TopoOptimizer.warn_inplace), 60, "fast_run", "inplace", "gpuarray", *tags, ) return local_opt return f # Register GPU convolution implementation # They are tried in a specific order so we can control # which ones take precedence over others. abstractconv_groupopt = LocalGroupDB() abstractconv_groupopt.__name__ = "gpuarray_abstractconv_opts" register_opt("fast_compile")(abstractconv_groupopt) class GraphToGPUDB(OptimizationDatabase): """ Retrieves the list local optimizers based on the optimizer flag's value from EquilibriumOptimizer by calling the method query. """ def query(self, *tags, **kwtags): from aesara.gpuarray.opt import GraphToGPU opt = gpu_optimizer2.query(*tags, **kwtags) return GraphToGPU(opt.local_optimizers_all, opt.local_optimizers_map)

jenkinsapi/node.py

imsardine/jenkinsapi

370

<reponame>imsardine/jenkinsapi<gh_stars>0 """ Module for jenkinsapi Node class """ from jenkinsapi.jenkinsbase import JenkinsBase from jenkinsapi.custom_exceptions import PostRequired import logging try: from urllib import quote as urlquote except ImportError: # Python3 from urllib.parse import quote as urlquote log = logging.getLogger(__name__) class Node(JenkinsBase): """ Class to hold information on nodes that are attached as slaves to the master jenkins instance """ def __init__(self, baseurl, nodename, jenkins_obj): """ Init a node object by providing all relevant pointers to it :param baseurl: basic url for querying information on a node :param nodename: hostname of the node :param jenkins_obj: ref to the jenkins obj :return: Node obj """ self.name = nodename self.jenkins = jenkins_obj JenkinsBase.__init__(self, baseurl) def get_jenkins_obj(self): return self.jenkins def __str__(self): return self.name def is_online(self): return not self.poll(tree='offline')['offline'] def is_temporarily_offline(self): return self.poll(tree='temporarilyOffline')['temporarilyOffline'] def is_jnlpagent(self): return self._data['jnlpAgent'] def is_idle(self): return self._data['idle'] def set_online(self): """ Set node online. Before change state verify client state: if node set 'offline' but 'temporarilyOffline' is not set - client has connection problems and AssertionError raised. If after run node state has not been changed raise AssertionError. """ self.poll() # Before change state check if client is connected if self._data['offline'] and not self._data['temporarilyOffline']: raise AssertionError("Node is offline and not marked as " "temporarilyOffline, check client " "connection: offline = %s, " "temporarilyOffline = %s" % (self._data['offline'], self._data['temporarilyOffline'])) elif self._data['offline'] and self._data['temporarilyOffline']: self.toggle_temporarily_offline() if self._data['offline']: raise AssertionError("The node state is still offline, " "check client connection:" " offline = %s, " "temporarilyOffline = %s" % (self._data['offline'], self._data['temporarilyOffline'])) def set_offline(self, message="requested from jenkinsapi"): """ Set node offline. If after run node state has not been changed raise AssertionError. : param message: optional string explain why you are taking this node offline """ if not self._data['offline']: self.toggle_temporarily_offline(message) data = self.poll(tree='offline,temporarilyOffline') if not data['offline']: raise AssertionError("The node state is still online:" + "offline = %s , temporarilyOffline = %s" % (data['offline'], data['temporarilyOffline'])) def toggle_temporarily_offline(self, message="requested from jenkinsapi"): """ Switches state of connected node (online/offline) and set 'temporarilyOffline' property (True/False) Calling the same method again will bring node status back. :param message: optional string can be used to explain why you are taking this node offline """ initial_state = self.is_temporarily_offline() url = self.baseurl + \ "/toggleOffline?offlineMessage=" + urlquote(message) try: html_result = self.jenkins.requester.get_and_confirm_status(url) except PostRequired: html_result = self.jenkins.requester.post_and_confirm_status( url, data={}) self.poll() log.debug(html_result) state = self.is_temporarily_offline() if initial_state == state: raise AssertionError( "The node state has not changed: temporarilyOffline = %s" % state)

edexOsgi/com.raytheon.edex.plugin.gfe/utility/common_static/base/gfe/textproducts/templates/product/GenericHazards.py

srcarter3/awips2

371

## # This software was developed and / or modified by Raytheon Company, # pursuant to Contract DG133W-05-CQ-1067 with the US Government. # # U.S. EXPORT CONTROLLED TECHNICAL DATA # This software product contains export-restricted data whose # export/transfer/disclosure is restricted by U.S. law. Dissemination # to non-U.S. persons whether in the United States or abroad requires # an export license or other authorization. # # Contractor Name: <NAME> # Contractor Address: 6825 Pine Street, Suite 340 # Mail Stop B8 # Omaha, NE 68106 # 402.291.0100 # # See the AWIPS II Master Rights File ("Master Rights File.pdf") for # further licensing information. ## # ---------------------------------------------------------------------------- # # SOFTWARE HISTORY # # Date Ticket# Engineer Description # ------------ ---------- ----------- -------------------------- # 05/07/2015 4027 randerso Migrated A1 OB9.16 code to A2 # 06/17/2015 4027 dgilling Perform case-insensitive # comparisons in foundCTAs. # 07/13/2015 4648 randerso Fix bullets in follow up products # 02/24/2016 5411 randerso Make bullet headers upper case # 07/15/2016 5749 randerso Replaced ellipses with commas in hazardBodyText # ## # This is a base file that is not intended to be overridden. ## #------------------------------------------------------------------------- # Description: This product is a template for creating Hazard Products. #------------------------------------------------------------------------- # Copying: # This software is in the public domain, furnished "as is", without technical # support, and with no warranty, express or implied, as to its usefulness for # any purpose. #------------------------------------------------------------------------- # Standard and Local file names and Locations: # GenericHazards #------------------------------------------------------------------------- # Customization Points: # # DEFINITION SECTION # # Required Configuration Items: # # displayName If not None, defines how product appears in GFE GUI # # You must set the following: # # productName defines name of product e.g. "Zone Forecast Product" # fullStationID Full station identifier, 4 letter, such as "KSLC". # wmoID WMO ID code for product header, such as "FOUS45" # pil Product pil, such as "SFTBOS" # areaName (opt.) Area name for product header, such as "Western New York" # wfoCityState City,state that the WFO is located in, such as "Buffalo NY" # # Optional Configuration Items # # mapNameForCombinations Name of the map background that is used for # creating/editing the combinations file. This must # be defined or the GFE zone combiner # database Source database for product. Can be "Official", # "Fcst" or "ISC" # outputFile Defines the output location of the finished product. # Product is saved if autoWrite is 1. # debug If on, debug_print statements will appear. # textdbPil Defines the awips product identifier # (e.g., DENCCFDEN) that is used to store the product # in the AWIPS text database. The product is not # automatically stored unless autoStore is 1. This # value is also used for the default GUI entry for # storage. # awipsWANPil Defines the awips product identifier # (e.g., KBOUCCFDEN) that is used to transmit the # product to the AWIPS WAN. The product is not # automatically transmitted unless autoSend is 1. # This value is also used for the default GUI # entry for storage. # autoSend If set to 1, then the product will be automatically # sent on the AWIPS WAN to the "autoSendAddress" with # the "awipsWANPil after product creation. # autoStore If set to 1, then the product will be automatically # stored into the text database using the "textdbPil" # after product creation. # autoWrite If set to 1, then the product will be automatically # written to the "output" named disk file after # product creation. # # lineLength max length of each line # # defaultEditAreas defines edit areas, default is Combinations # # purgeTime Maximum number of hours past issuance time for the # expire time. # includeCities If 1, cities will be included in the area header # accurateCities If 1, cities are determined from grids # citiesPhrase "Including the cities of" phrase used when including # cities # includeZoneNames If 1, zone names will be included in the area header # easPhrase Optional EAS phrase to be include in product header # # hazardSamplingThreshold Defines the percentage coverage or number of # grid points in a zone that must contain the hazard # in order for it to be considered. Tuple (percent, points) # includeOverviewHeadline If 1, the overview header is templated # includeOverview If 1, the overview section is templated # bulletProd If 1, the product will use a bullet format #------------------------------------------------------------------------- # Weather Elements Needed: # Hazards #------------------------------------------------------------------------- # Edit Areas Needed: None #------------------------------------------------------------------------- # Associated Utilities Files e.g. Combinations file: # Combinations file #------------------------------------------------------------------------- # Component Products: # Hazards #------------------------------------------------------------------------- # Development tasks that are identified and in progress: # # To look up tasks and their status, see the Text Product User Guide # Section on "Tkgnats: Task Reporting System". #------------------------------------------------------------------------- # Additional Information: #------------------------------------------------------------------------- # Example Output: #------------------------------------------------------------------------- import LogStream import TextRules import SampleAnalysis import time, string, types, copy, re import CallToActions import AbsTime class TextProduct(TextRules.TextRules, SampleAnalysis.SampleAnalysis, CallToActions.CallToActions): Definition = { "type": "smart", "displayName": None, # Source database for product. Can be "Official", "Fcst" or "ISC" "database": "Official", # Defines output location of finished product. "outputFile": "{prddir}/TEXT/genHaz.txt", "debug": 0, # Name of map background for creating Combinations # Can be: # Zones_BOU # FireWxZones_BOU # Counties # Marine_Zones_BOU "mapNameForCombinations": "Zones_<site>", ## Edit Areas: Create Combinations file with edit area combinations. ## Can be: ## EditAreas_PublicZones_BOU ## EditAreas_FireWx_BOU ## EditAreas_FIPS_BOU ## EditAreas_MarineZones_BOU "defaultEditAreas" : "EditAreas_PublicZones_<site>_<MultiPil>", # product identifiers "productName": "Generic Hazard Product", # product name "fullStationID": "<fullStationID>", # full station identifier (4letter) "wmoID": "<wmoID>", # WMO ID "pil": "<pil>", # Product pil "areaName": "", # Name of state, such as "Georgia" -- optional "wfoCityState": "<wfoCityState>", # Location of WFO - city,state "textdbPil": "<textdbPil>", # Product ID for storing to AWIPS text database. "awipsWANPil": "<awipsWANPil>", # Product ID for transmitting to AWIPS WAN. "periodCombining" : 0, # If 1, combine periods, if possible # automatic functions "autoSend": 0, #set to 1 to automatically transmit product "autoSendAddress": "000", #transmission address "autoStore": 0, #set to 1 to automatically store product in textDB "autoWrite": 0, #set to 1 to automatically write product to file # Area Dictionary -- Descriptive information about zones "areaDictionary": "AreaDictionary", # Language "language": "english", "lineLength": 66, #Maximum line length "purgeTime": 8, # Maximum hours for expireTime "includeCities": 1 , # Cities included in area header "accurateCities": 0, # Include all cities in area header "cityLocation": "CityLocation", # City lat/lon dictionary to use "cityDescriptor":"Including the cities of", "includeZoneNames":1, # Zone names will be included in the area header "easPhrase" :"", # Optional EAS phrase to be include in product header "includeOverviewHeadline": 1, #include overview header "includeOverview": 1, #include overview section "bulletProd": 0, # do not default to bullets "hazardSamplingThreshold": (10, None), #(%cov, #points) "callToAction": 1, } def __init__(self): TextRules.TextRules.__init__(self) SampleAnalysis.SampleAnalysis.__init__(self) self.__overviewText = "" self.__procCTA = None def generateForecast(self, argDict): # Generate Text Phrases for a list of edit areas # Get variables error = self._getVariables(argDict) if error is not None: return error # Get the segments hazardsC = argDict['hazards'] segmentList = self.organizeHazards(hazardsC.rawAnalyzedTable()) if len(segmentList) == 0: return "No hazards to report" # Determine time ranges error = self._determineTimeRanges(argDict) if error is not None: return error # Initialize the output string fcst = "" fcst = self._preProcessProduct(fcst, argDict) # Generate the product for each segment in the segmentList fraction = 0 fractionOne = 1.0/float(len(segmentList)) percent = 50.0 self.setProgressPercentage(50) for segmentAreas in segmentList: self.progressMessage(fraction, percent, "Making Product for Segment") fcst = self._preProcessArea(fcst, segmentAreas, self._expireTime, argDict) fcst = self._makeProduct(fcst, segmentAreas, argDict) fcst = self._postProcessArea(fcst, segmentAreas, argDict) fraction = fractionOne fcst = self._postProcessProduct(fcst, argDict) return fcst def _getVariables(self, argDict): # Make argDict accessible self.__argDict = argDict # Get Definition variables self._definition = argDict["forecastDef"] for key in self._definition.keys(): exec "self._" + key + "= self._definition[key]" # Get VariableList varDict = argDict["varDict"] for key in varDict.keys(): if type(key) is types.TupleType: label, variable = key exec "self._" + variable + "= varDict[key]" self._language = argDict["language"] # Set up information for Hazards product self._hazards = argDict['hazards'] self._combinations = argDict["combinations"] return None def _determineTimeRanges(self, argDict): # Set up the time range for 0-240 hours self._timeRange = self.createTimeRange(0, 240) self._ddhhmmTime = self.getCurrentTime( argDict, "%d%H%M", shiftToLocal=0, stripLeading=0) self._issueTime = AbsTime.AbsTime(argDict['creationTime']) self._currentTime = argDict['creationTime'] self._expireTime = self._issueTime + self._purgeTime*3600 self._timeLabel = self.getCurrentTime( argDict, "%l%M %p %Z %a %b %e %Y", stripLeading=1) return None def _preProcessProduct(self, fcst, argDict): # Product header if self._areaName != "": self._areaName = " for " + self._areaName issuedByString = self.getIssuedByString() productName = self.checkTestMode(argDict, self._productName + self._areaName) if len(self._easPhrase) != 0: eas = self._easPhrase + '\n' else: eas = '' s = self._wmoID + " " + self._fullStationID + " " + \ self._ddhhmmTime + "\n" + self._pil + "\n\n" fcst = fcst + s.upper() s = eas + productName + "\n" +\ "National Weather Service " + self._wfoCityState + \ "\n" + issuedByString + self._timeLabel + "\n\n" fcst = fcst + s fcst = fcst + "Default overview section\n" return fcst def _preProcessArea(self, fcst, segmentAreas, expireTime, argDict): # This is the header for an edit area combination areaHeader = self.makeAreaHeader( argDict, "", self._issueTime, expireTime, self._areaDictionary, None, cityDescriptor=self._cityDescriptor, areaList=segmentAreas, includeCities=self._includeCities, includeZoneNames = self._includeZoneNames, accurateCities = self._accurateCities) fcst = fcst + areaHeader return fcst def _makeProduct(self, fcst, segmentAreas, argDict): argDict["language"] = self._language # Generate Narrative Forecast for Edit Area # get the hazards text # We only need to get headlines for the first edit area # in the segment since all areas in the segment have # the same headlines editArea = segmentAreas[0] areaLabel = editArea headlines = self.generateProduct("Hazards", argDict, area = editArea, areaLabel=areaLabel, timeRange = self._timeRange) fcst = fcst + headlines return fcst def _postProcessArea(self, fcst, segmentAreas, argDict): return fcst + "\n\n$$\n\n" def _postProcessProduct(self, fcst, argDict): # # If an overview exists for this product, insert it # overview = self.finalOverviewText() overviewSearch = re.compile(r'Default overview section', re.DOTALL) fcst = overviewSearch.sub(overview, fcst) # # Added to place line feeds in the CAP tags to keep separate from CTAs fcst = string.replace(fcst, \ r"PRECAUTIONARY/PREPAREDNESS ACTIONS\.\.\.", \ r"\nPRECAUTIONARY/PREPAREDNESS ACTIONS\.\.\.\n") fcst = string.replace(fcst, "\n ","\n") fcst = string.replace(fcst, "&&", "\n&&\n") # Prevent empty Call to Action Tags fcst = re.sub(r'\nPRECAUTIONARY/PREPAREDNESS ACTIONS\.\.\.\s*&&\n', \ "", fcst) fcst = self._indentBulletText(fcst) # # Clean up multiple line feeds # fixMultiLF = re.compile(r'(\n\n)\n*', re.DOTALL) fcst = fixMultiLF.sub(r'\1', fcst) # finish progress meter self.setProgressPercentage(100) self.progressMessage(0, 100, self._displayName + " Complete") return fcst def allowedHazards(self): return [] # Added for DR 21194 def _bulletDict(self): return [] # Added for DR 21309 def _bulletOrder(self): return [] ## Replaced by 21309 code ## def _getBullets(self, newBulletList, argDict): ## ## ### get the bullet dictionary and split the bullets ## bDict = self._bulletDict() ## bLine = bDict.get(eachHazard['phen']) ## print 20* "*" + (eachHazard['phen']) ## bList = newBulletList.split(",") ## ## ### initialize the bullet output ## bullets = "" ## ## ### loop through the bullets and format the output ## for b in bList: ## bullets = bullets + "* " + b + "...|* Enter bullet text *|\n\n" ## # bullets = bullets + "\n" ## return bullets def _indentBulletText(self, prevText): print prevText ### if previous text is empty, return nothing if prevText is None: return prevText ### ### split the text ### bullets = [] bullets = string.split(prevText, '\n\n') if len(bullets) <= 1: return prevText ### ### process the text ### outText = "" for b in bullets: ### if first character is a * we found a bullet if re.match("\*", b): ### remove line feeds removeLF = re.compile(r'(s*[^\n])\n([^\n])', re.DOTALL) bullet = removeLF.sub(r'\1 \2',b) ### indent code bullet = self.indentText(bullet, indentFirstString = '', indentNextString = ' ', maxWidth=self._lineLength, breakStrings=[" ", "..."]) ### ### the "-" in the breakStrings line above is causing issues with ### offices that use "-20 degrees" in the text. ### outText = outText + bullet + "\n\n" else: ### not a bullet, CTA text outText = outText + b + "\n\n" ### that's it print outText return outText # The _hazardTimePhrases method is passed a hazard key, and returns # time phrase wording consistent with that generated by the headline # algorithms in DiscretePhrases. # def hazardTimePhrases(self, hazard, argDict, prefixSpace=True): timeWords = self.getTimingPhrase(hazard, argDict['creationTime']) if prefixSpace and len(timeWords): timeWords = " " + timeWords #add a leading space return timeWords # # The method hazardBodyText creates an attribution phrase # def hazardBodyText(self, hazardList, argDict): bulletProd = self._bulletProd hazardBodyPhrase = '' # # First, sort the hazards for this segment by importance # sortedHazardList = [] for each in ['W', 'Y', 'A', 'O', 'S']: for eachHazard in hazardList: if eachHazard['sig'] == each: if eachHazard not in sortedHazardList: sortedHazardList.append(eachHazard) # # Next, break them into individual lists based on action # newList = [] canList = [] expList = [] extList = [] conList = [] upgList = [] statementList = [] for eachHazard in sortedHazardList: if eachHazard['sig'] in ['S']and eachHazard['phen'] in ['CF', 'LS']: statementList.append(eachHazard) elif eachHazard['act'] in ['NEW', 'EXA', 'EXB']: newList.append(eachHazard) elif eachHazard['act'] in ['CAN']: canList.append(eachHazard) elif eachHazard['act'] in ['EXP']: expList.append(eachHazard) elif eachHazard['act'] in ['EXT']: extList.append(eachHazard) elif eachHazard['act'] in ['UPG']: upgList.append(eachHazard) else: conList.append(eachHazard) # # Now, go through each list and build the phrases # nwsIntroUsed = 0 # # This is for the new hazards # phraseCount = 0 lastHdln = None for eachHazard in newList: hdln = eachHazard['hdln'] if len(eachHazard['hdln']) == 0: continue #no defined headline, skip phrase endTimePhrase = self.hazardTimePhrases(eachHazard, argDict) hazNameA = self.hazardName(eachHazard['hdln'], argDict, True) hazNameACap = self.sentence(hazNameA, addPeriod=False) hazName = self.hazardName(eachHazard['hdln'], argDict, False) if hazName in ["Winter Weather Advisory", "Winter Storm Warning", "Beach Hazards Statement"]: forPhrase = " for |* Enter hazard type *|" else: forPhrase ="" if nwsIntroUsed == 0: hazardBodyPhrase = "The National Weather Service in " + self._wfoCity nwsIntroUsed = 1 if phraseCount == 0: phraseCount = 1 if eachHazard['phen'] in ['HU', 'TR', 'TY']: hazardBodyPhrase = hazardBodyPhrase + " has issued " + \ hazNameA + ". " else: hazardBodyPhrase += " has issued " + hazNameA + forPhrase + \ ", which is in effect" + endTimePhrase + ". " elif phraseCount == 1: phraseCount = 2 if hdln != lastHdln: if eachHazard['phen'] in ['HU', 'TR', 'TY']: hazardBodyPhrase = hazardBodyPhrase + hazNameACap + \ " has also been issued." else: hazardBodyPhrase = hazardBodyPhrase + hazNameACap + \ " has also been issued. This " + hazName + forPhrase + \ " is in effect" + endTimePhrase + ". " else: if eachHazard['phen'] in ['HU', 'TR', 'TY']: hazardBodyPhrase = hazardBodyPhrase + hazNameACap + \ " has also been issued." else: hazardBodyPhrase = hazardBodyPhrase + hazNameACap + forPhrase + \ " has also been issued" + endTimePhrase + ". " else: if eachHazard['phen'] in ['HU', 'TR', 'TY']: hazardBodyPhrase += "In addition, " + \ hazNameA + " has been issued." else: hazardBodyPhrase += "In addition, " + \ hazNameA + forPhrase + " has been issued. This " + hazName + \ " is in effect" + endTimePhrase + ". " lastHdln = hdln # # This is for the can hazards # for eachHazard in canList: if len(eachHazard['hdln']) == 0: continue #no defined headline, skip phrase hazName = self.hazardName(eachHazard['hdln'], argDict, False) if nwsIntroUsed == 0: hazardBodyPhrase = "The National Weather Service in " +\ self._wfoCity nwsIntroUsed = 1 hazardBodyPhrase = hazardBodyPhrase + \ " has cancelled the " + hazName + ". " else: hazardBodyPhrase = hazardBodyPhrase + "The " + hazName + \ " has been cancelled. " # # This is for the exp hazards # phraseCount = 0 for eachHazard in expList: if len(eachHazard['hdln']) == 0: continue #no defined headline, skip phrase if self._bulletProd: continue # No attribution for this case if it is a bullet product hazName = self.hazardName(eachHazard['hdln'], argDict, False) if eachHazard['endTime'] <= argDict['creationTime']: hazardBodyPhrase = hazardBodyPhrase + "The " + hazName + \ " is no longer in effect. " else: expTimeCurrent = argDict['creationTime'] timeWords = self.getTimingPhrase(eachHazard, expTimeCurrent) hazardBodyPhrase = hazardBodyPhrase + "The " + hazName + \ " will expire " + timeWords + ". " # # This is for ext hazards # for eachHazard in extList: if len(eachHazard['hdln']) == 0: continue #no defined headline, skip phrase if self._bulletProd: continue # No attribution for this case if it is a bullet product endTimePhrase = self.hazardTimePhrases(eachHazard, argDict) hazName = self.hazardName(eachHazard['hdln'], argDict, False) hazardBodyPhrase = hazardBodyPhrase + "The " + hazName + \ " is now in effect" + endTimePhrase + ". " # # This is for upgrade hazards # for eachHazard in upgList: if len(eachHazard['hdln']) == 0: continue #no defined headline, skip phrase hazName = self.hazardName(eachHazard['hdln'], argDict, False) hazardBodyPhrase = hazardBodyPhrase + "The " + hazName + \ " is no longer in effect. " # # This is for con hazards # for eachHazard in conList: if len(eachHazard['hdln']) == 0: continue #no defined headline, skip phrase if self._bulletProd: continue # No attribution for this case if it is a bullet product endTimePhrase = self.hazardTimePhrases(eachHazard, argDict) hazNameA = self.hazardName(eachHazard['hdln'], argDict, True) hazardBodyPhrase = hazardBodyPhrase + hazNameA + \ " remains in effect" + endTimePhrase + ". " # # This is for statement hazards # for eachHazard in statementList: hazardBodyPhrase = "...|* Add statement headline *|...\n\n" # # This adds segment text # segmentText = '' # # Check that this segment codes to determine capture or not, # and frame captured text or not # incTextFlag, incFramingCodes, skipCTAs, forceCTAList = \ self.useCaptureText(sortedHazardList) # # # Check that the previous text exists # foundCTAs = [] for eachHazard in sortedHazardList: if eachHazard.has_key('prevText'): prevText = eachHazard['prevText'] if eachHazard['pil'] == 'MWS': startPara = 0 else: startPara = 1 segmentText, foundCTAs = self.cleanCapturedText(prevText, startPara, addFramingCodes = False, skipCTAs = skipCTAs) tester = segmentText[0] if tester == '*': startPara = 1 else: startPara = 2 segmentText, foundCTAs = self.cleanCapturedText(prevText, startPara, addFramingCodes = False, skipCTAs = skipCTAs) # # Check that the segment text isn't very short or blank # if len(segmentText) < 6: incTextFlag = 0 # DR 21309 code addition from Middendorf (BYZ) # # Now if there is a new hazard and previous segment Text, then # we may have to add bullets. # if incTextFlag and bulletProd: for eachHazard in sortedHazardList: if not eachHazard.has_key('prevText'): newBullets = string.split(self._bulletDict().get(eachHazard['phen']),",") print "newBullets = ", newBullets print "segment text is: ", segmentText for bullet in newBullets: if re.search("\* " + bullet + "\.\.\.", segmentText, flags=re.IGNORECASE) is None: print bullet + " not in segmentText" start = self._bulletOrder().index(bullet) + 1 end = len(self._bulletOrder()) bulletFlag = 1 for i in range(start,end): if (re.search("\* " + self._bulletOrder()[i] + "\.\.\.", segmentText, flags=re.IGNORECASE) is not None) and bulletFlag: print "* " + self._bulletOrder()[i] + "... found!" segmentTextSplit = re.split("\* " + self._bulletOrder()[i] + "\.\.\.", segmentText, flags=re.IGNORECASE) segmentText = string.join(segmentTextSplit,"* " + bullet.upper() + \ "...|* Enter bullet text *|\n\n* " + self._bulletOrder()[i] + "...") bulletFlag = 0 if bulletFlag: print "appending to bottom list of bullets!" segmentTextSplit = re.split("PRECAUTIONARY/PREPAREDNESS ACTIONS\.\.\.", segmentText, flags=re.IGNORECASE) segmentText = "\n" + string.join(segmentTextSplit,"* " + bullet.upper() + \ "...|* Enter bullet text *|\n\nPRECAUTIONARY/PREPAREDNESS ACTIONS...") bulletFlag = 0 # # Now if there is a can/exp hazard and previous segment Text, then # we may have to remove bullets. # if incTextFlag and bulletProd: # First make list of bullets that we need to keep. keepBulletList = [] for eachHazard in sortedHazardList: if eachHazard['act'] not in ["CAN","EXP"]: saveBullets = string.split(self._bulletDict().get(eachHazard['phen']),",") for saveBullet in saveBullets: if saveBullet not in keepBulletList: keepBulletList.append(saveBullet) # Now determine which bullets we have to remove. removeBulletList = [] for eachHazard in sortedHazardList: if eachHazard['act'] in ["CAN","EXP"]: canBullets = string.split(self._bulletDict().get(eachHazard['phen']),",") for canBullet in canBullets: if canBullet not in keepBulletList and canBullet not in removeBulletList: removeBulletList.append(canBullet) print "hazardBodyText info: keepBulletList: ",keepBulletList print "hazardBodyText info: removeBulletList: ",removeBulletList # Finally remove the bullets no longer needed. for bullet in removeBulletList: if re.search("\* "+ bullet + "\.\.\.", segmentText, flags=re.IGNORECASE) is not None: segmentTextSplit = re.split("\* " + bullet + "\.\.\.", segmentText, flags=re.IGNORECASE) print "segmentTextSplit is ", segmentTextSplit segmentTextSplit2 = string.split(segmentTextSplit[1],"*",1) if len(segmentTextSplit2) == 2: segmentTextSplit[1] = "*" + segmentTextSplit2[1] else: segmentTextSplit2 = re.split("PRECAUTIONARY/PREPAREDNESS ACTIONS\.\.\.", segmentTextSplit[1], 1, flags=re.IGNORECASE) if len(segmentTextSplit2) == 2: segmentTextSplit[1] = "PRECAUTIONARY/PREPAREDNESS ACTIONS..." + segmentTextSplit2[1] segmentText = string.join(segmentTextSplit,"") if removeBulletList != []: segmentText = "|*\n" + segmentText + "*|" else: segmentText = segmentText # # If segment passes the above checks, add the text # print "hazardBodyText info: incTextFlag: ",incTextFlag if incTextFlag: print "hazardBodyText info: segmentText: ",segmentText hazardBodyPhrase = hazardBodyPhrase + "\n\n" + \ segmentText + '\n\n' elif bulletProd: bulletFlag = 0 if eachHazard['act'] == 'CAN': hazardBodyPhrase = hazardBodyPhrase + \ "\n\n|* Wrap-up text goes here *|.\n" elif eachHazard['act'] == 'EXP': hazardBodyPhrase = hazardBodyPhrase + \ "\n\n|* Wrap-up text goes here *|.\n" else: bulletFlag = 1 ## print "bulletFlag is: ",bulletFlag if bulletFlag: newBulletList = [] bullets = "" for eachHazard in sortedHazardList: ### get the default bullets for all hazards from the bullet diction newBullets = string.split(self._bulletDict().get(eachHazard['phen']),",") for newBullet in newBullets: if newBullet not in newBulletList: newBulletList.append(newBullet) print "my bullets are: ", newBulletList ### Determine the correct order for all bullets bulletOrder = self._bulletOrder() staticBulletOrder = self._bulletOrder() for bullet in staticBulletOrder: print "correct bullet order should be: ", bulletOrder if bullet not in newBulletList: bulletOrder.remove(bullet) print "reordered bullets are: ", bulletOrder for b in bulletOrder: bullets = bullets + "* " + b.upper() + "...|* Enter bullet text *|\n\n" hazardBodyPhrase = hazardBodyPhrase + "\n\n" + bullets # If segment doesn't pass the checks, put in framing codes else: hazardBodyPhrase = hazardBodyPhrase + \ "\n\n|* Statement text goes here *|.\n\n" # End code for DR 21310 # # This adds the call to action statements. This is only performed # if the segment is 'NEW' or if the previous text has been discarded # due to a CAN/EXP/UPG segment # # remove items from forceCTAList if they exist in foundCTAs. Note # that the formats of these lists are different, thus this code # is more complicated for ent in foundCTAs: #only process CTAs that are vtec phen/sig based if ent.find('.') == 2: phensig = (ent[0:2], ent[3]) #phen.sig if phensig in forceCTAList: del forceCTAList[forceCTAList.index(phensig)] hazardBodyPhrase = hazardBodyPhrase + '\n\n' ctas = [] for (phen,sig) in forceCTAList: hazardPhenSig = phen + "." + sig cta = self.defaultCTA(hazardPhenSig) if cta not in ctas: ctas.append(cta) if len(ctas) > 0: hazardBodyPhrase = hazardBodyPhrase + \ 'PRECAUTIONARY/PREPAREDNESS ACTIONS...\n\n' for c in ctas: hazardBodyPhrase = hazardBodyPhrase + c + '\n\n' hazardBodyPhrase = hazardBodyPhrase + '&&\n\n' # Make sure there is only one CAP tag pairs hazardBodyPhrase = re.sub(r'&&\s*PRECAUTIONARY/PREPAREDNESS ACTIONS\.\.\.\n', \ "", hazardBodyPhrase) return hazardBodyPhrase def finalOverviewText(self): #if didn't calculate any, use the default if len(self.__overviewText) == 0: if self._includeOverviewHeadline: overviewHeadline = "...|*Overview headline (must edit)*|...\n\n" else: overviewHeadline = "" if self._includeOverview: overviewBody = ".|*Overview (must edit)*|.\n\n" else: overviewBody = "" #assemble the lines overview = overviewHeadline + overviewBody return overview else: return self.__overviewText def overviewText(self, hazardList, pil): # # This method finds an overview in the previous product # overview = "" for each in hazardList: if (each.has_key('prevOverviewText') and each.has_key('pil') and each.has_key('endTime') and each.has_key('act')): if (each['pil'] == pil and each['endTime'] > self._currentTime and each['act'] not in ['CAN', 'EXP']): overview = each['prevOverviewText'] self.__overviewText, dummy = self.cleanCapturedText( overview, 0) break def useCaptureText(self, hazardList): #Based on the hazardlist, returns a tuple indicating: # (inc capture text, inc framing codes, skip CTAs, forceCTAList) # # For the values to be considered, the 'hdln' value must be # present in the list, or it needs to be a Statement (sig="S") cans = ['CAN','UPG','EXP'] acts = ['NEW','EXT','EXA','EXB','CON'] foundACTS = 0 foundCANS = 0 foundSig = [] for eh in hazardList: if eh['act'] in acts and (len(eh['hdln']) or eh['sig'] == 'S'): foundACTS = 1 if eh['act'] in cans and (len(eh['hdln']) or eh['sig'] == 'S'): foundCANS = 1 if eh['sig'] not in foundSig: foundSig.append(eh['sig']) includeFrameCodes = 0 includeText = 1 skipCTAs = 0 forceCTAList = [] # all actions are in CAN, UPG, EXP only (don't include text) if foundCANS and not foundACTS: if 'S' in foundSig and len(foundSig) == 1: #only S includeFrameCodes = 1 #capture text, but frame it else: includeText = 0 #end of non statement # something in CANS and something in acts (frame it, include text) elif foundCANS and foundACTS: includeFrameCodes = 1 skipCTAs = 1 for eh in hazardList: if eh['act'] in acts and \ (eh['phen'], eh['sig']) not in forceCTAList and \ len(eh['hdln']): forceCTAList.append((eh['phen'], eh['sig'])) #everything in active entries, captured text is used, but still # need to handle the "NEW" entries. else: for eh in hazardList: if eh['act'] in ['NEW'] and len(eh['hdln']): forceCTAList.append((eh['phen'], eh['sig'])) return (includeText, includeFrameCodes, skipCTAs, forceCTAList) def cleanCapturedText(self, text, paragraphs, addFramingCodes = False, skipCTAs = False): # # This method takes a block of text, wraps it preserving blank lines, # then returns the part after 'paragraphs'. So, if paragraphs is 0, it # returns the whole thing, if it's 2, it returns paragraphs 2 -> end, etc. # Headlines are always removed. # Framing codes are added if specified. # paras = self.convertSingleParas(text) #single paragraphs # keep track of any call to actions found foundCTAs = [] # Process the paragraphs, keep only the interested ones paraCount = 0 processedText = '' for eachPara in paras: if paraCount >= paragraphs: found = self.ctasFound(eachPara) #get list of ctas found if skipCTAs and len(found): pass else: processedText = processedText + eachPara + '\n\n' #keep track of remaining CTAs in processed text for f in found: if f not in foundCTAs: foundCTAs.append(f) if eachPara.find('...') == 0: pass #ignore headlines paraCount = paraCount + 1 # Add framing codes if addFramingCodes: processedText = processedText.rstrip() processedText = "|*\n" + processedText + "*|\n" # Wrap processedText = self.endline(processedText, linelength=self._lineLength, breakStr=[" ", "-", "..."]) return processedText, foundCTAs def decodeBulletedText(self, prevText): # returns the bullet paragraph text or None, returns the # regular text after the bullets. The afterText is text up to # the next bullet or up to "The National Weather Service". Note # that this only correctly handles the 1st set of entries in # a segment, thus double events will only decode the first set # of bullets and text. The multipleRecords is set to 1 in the # event that there are multiple sets of bullets. In this case # only the 1st set was captured/decoded. # (hazard, time, basis, impact, afterText, multipleRecords) if prevText is None: return (None, None, None, None, None, None) # find the bullets bullets = [] buf = prevText.split('\n\n* ') if len(buf) <= 1: return (None, None, None, None, None, None) multRecords = 0 #indicator of multiple sets of bullets for x in xrange(len(buf)): if x == 0: continue #headlines and text before the bullets bullets.append(buf[x]) # find only the bulleted text, defined by the double line feed term. # of the text regText = "" #regular text after bullets for x in xrange(1, len(bullets)): index = bullets[x].find('\n\n') if index != -1: regText = bullets[x][index+2:] bullets[x] = bullets[x][0:index] #eliminate after bullet text if len(bullets) > x+2: #more bullets are present multRecords = 1 bullets = bullets[0:x+1] #only interested in these bullets break # regular text is the remainder of the text. However we only # want text from the last in the series of bullets to the # beginning of any next NWS phrase. lines = regText.split('\n') for x in xrange(len(lines)): if lines[x].find('The National Weather Service') == 0: lines = lines[0:x] #eliminate following lines break regText = ("\n").join(lines) # now clean up the text for x in xrange(len(bullets)): bullets[x] = string.replace(bullets[x],'\n',' ') removeLF = re.compile(r'(s*[^\n])\n([^\n])', re.DOTALL) regText = removeLF.sub(r'\1 \2',regText) # extract out each section for returning the values if len(bullets) >= 1: hazard = bullets[0] else: hazard = None if len(bullets) >= 2: time = bullets[1] else: time = None if len(bullets) >= 3: basis = bullets[2] else: basis = None if len(bullets) >= 4: impact = bullets[3] else: impact = None if len(regText) == 0: regText = None #no regular text after bullets return (hazard, time, basis, impact, regText, multRecords) def substituteBulletedText(self, capText, defaultText, frameit="Never"): #returns a properly formatted bulleted text based on #the capText variable. If capText is None or 0 length, then #the default text is used. frameit can be "Never", in which #nothing is wrapped in framing codes, "Always" in which the #text (default or cap) is wrapped in framing codes, or #DefaultOnly" in which just the default text is wrapped. if capText is not None and len(capText): textToUse = capText[0].upper()+capText[1:] if frameit == "Always": textToUse = "|* " + textToUse + " *|" else: textToUse = defaultText if frameit == "Always" or frameit == "DefaultOnly": textToUse = "|* " + textToUse + " *|" # add bullet codes textToUse = "* " + textToUse # format it return self.indentText(textToUse, indentFirstString = '', indentNextString = ' ', maxWidth=self._lineLength, breakStrings=[" ", "-", "..."]) def convertSingleParas(self, text): #returns a list of paragraphs based on the input text. lf = re.compile(r'(s*[^\n])\n([^\n])', re.DOTALL) ptext = lf.sub(r'\1 \2', text) ptext = ptext.replace('\n\n', '\n') paragraphs = ptext.split('\n') return paragraphs def ctasFound(self, text): #returns types of ctas found. The identifier is the pil (e.g., ZFP), #phen/sig (e.g., DU.Y), or GENERIC. Uses the CallToAction definitions. #convert text to single paragraphs paragraphs = self.convertSingleParas(text) for x in xrange(len(paragraphs)): paragraphs[x] = string.replace(paragraphs[x],' ','') #make list of call to actions (type, cta text) if self.__procCTA is None: self.__procCTA = [] ctao = CallToActions.CallToActions() d = ctao.ctaDict() for k in d.keys(): func = d[k] items = func() for it in items: if type(it) == types.TupleType: it = it[1] #get second string which is the CTA ctaParas = self.convertSingleParas(it) for cta in ctaParas: self.__procCTA.append((k,string.replace(cta,' ',''))) d = ctao.ctaPilDict() for k in d.keys(): func = d[k] items = func() for it in items: if type(it) == types.TupleType: it = it[1] #get second string which is the CTA ctaParas = self.convertSingleParas(it) for cta in ctaParas: self.__procCTA.append((k,string.replace(cta,' ',''))) ctas = ctao.genericCTAs() for it in ctas: if type(it) == types.TupleType: it = it[1] #get second string which is the CTA ctaParas = self.convertSingleParas(it) for cta in ctaParas: self.__procCTA.append(("GENERIC", string.replace(cta,' ',''))) #compare found = [] for para in paragraphs: for (ctaType, cta) in self.__procCTA: ## Added following line to account for framing code issues in CTA cta = re.sub("\|\*.*\*\|","",cta) # We want this comparison to be case-insensitive just in case # the site is not transmitting in mixed case yet. if para.upper() == cta.upper() and ctaType not in found: found.append(ctaType) return found

virtualscreening/vina/spark/buried_areas.py

rodrigofaccioli/drugdesign

372

<filename>virtualscreening/vina/spark/buried_areas.py from pyspark import SparkContext, SparkConf, SparkFiles from pyspark.sql import SQLContext, Row import ConfigParser as configparser from subprocess import Popen, PIPE from datetime import datetime from vina_utils import get_directory_complex_pdb_analysis, get_files_pdb, get_name_model_pdb, get_ligand_from_receptor_ligand_model, get_separator_filename_mode, get_directory_pdb_analysis, loading_pdb_2_list, get_name_receptor_pdb, get_files_pdb_filter import os, sys from os_utils import preparing_path from gromacs_utils import get_value_from_xvg_sasa from pdb_io import replace_chain_atom_line from database_io import load_database def sorting_buried_area(sc, buried_areaRDD): sqlCtx = SQLContext(sc) buried_areaRDD = sc.parallelize(buried_areaRDD) #buried_areaRDD = buried_areaRDD.map(lambda p: Row(receptor=str(p[0]), ligand=str(p[1]), model=int(p[2]), buried_lig_rec=float(p[3]), buried_lig_rec_perc=float(p[4]), buried_lig_lig_perc=float(p[5]) ) ) buried_areaRDD = buried_areaRDD.map(lambda p: Row(pose=str(p[0]), buried_total=float(p[1]) ) ) buried_area_table = sqlCtx.createDataFrame(buried_areaRDD) buried_area_table.registerTempTable("buried_area") buried_area_sorted_by_buried_total = sqlCtx.sql("SELECT * FROM buried_area ORDER BY buried_total DESC") #buried_lig_lig_perc return buried_area_sorted_by_buried_total def save_receptor_buried_area(path_file_buried_area, buried_area_sorted_by_lig_rec_perc): f_buried_area = open(path_file_buried_area,"w") for area in buried_area_sorted_by_lig_rec_perc: #splited_line = area[0].split("_-_") #aux_recep = splited_line[0] #aux_lig = str(splited_line[1]) #preparing receptor #receptor = str(str(aux_recep).replace("compl_", " ")).strip() #preparing ligand #splited_aux_lig = str(aux_lig).split(get_separator_filename_mode()) #ligand = splited_aux_lig[0] #model = splited_aux_lig[1] pose = area[0] buried_total = "{:.4f}".format(area[1]) #line = receptor+"\t"+ligand+"\t"+model+"\t"+str(buried_lig_rec)+"\t"+str(buried_lig_rec_perc)+"\t"+str(buried_lig_lig_perc)+"\n" line = pose+"\t"+str(buried_total)+"\n" f_buried_area.write(line) f_buried_area.close() def save_buried_area(path_file_buried_area, buried_area_sorted_by_lig_rec_perc): f_buried_area = open(path_file_buried_area,"w") line = "# buried_area_total[nm2]\tpose"+"\n" f_buried_area.write(line) for area in buried_area_sorted_by_lig_rec_perc: #receptor = area[0] #ligand = area[1] #model = area[2] pose = str(str(area[0]).replace("compl_", " ")).strip() buried_total = "{:.4f}".format(area[1]) #buried_lig_rec_perc = "{:.4f}".format(area[4]) #buried_lig_lig_perc = "{:.4f}".format(area[5]) #line = receptor+"\t"+ligand+"\t"+str(model)+"\t"+str(buried_lig_rec)+"\t"+str(buried_lig_rec_perc)+"\t"+str(buried_lig_lig_perc)+"\n" line = str(buried_total)+"\t"+str(pose)+"\n" f_buried_area.write(line) f_buried_area.close() def save_normalized_buried_area(path_file_buried_area, full_dataRDD): f_buried_area = open(path_file_buried_area,"w") line = "# normalized_buried_area_total[nm2]\tpose"+"\n" f_buried_area.write(line) for area in full_dataRDD.collect(): pose = str(str(area[0]).replace("compl_", " ")).strip() normalized_buried_total = "{:.4f}".format(area[1]) line = str(normalized_buried_total)+"\t"+str(pose)+"\n" f_buried_area.write(line) f_buried_area.close() def loading_lines_from_area_files(line): line_splited = str(line).split() #line_ret = ( str(line_splited[0]), str(line_splited[1]), int(line_splited[2]), float(line_splited[3]), float(line_splited[4]), float(line_splited[5]) ) line_ret = ( str(line_splited[0]), float(line_splited[1]) ) return line_ret def get_files_area(mypath): only_mol2_file = [] for root, dirs, files in os.walk(mypath): for file in files: if file.endswith(".area"): f_path = os.path.join(root,file) only_mol2_file.append(f_path) return only_mol2_file def save_log(finish_time, start_time): log_file_name = 'vs_buried_areas.log' current_path = os.getcwd() path_file = os.path.join(current_path, log_file_name) log_file = open(path_file, 'w') diff_time = finish_time - start_time msg = 'Starting ' + str(start_time) +'\n' log_file.write(msg) msg = 'Finishing ' + str(finish_time) +'\n' log_file.write(msg) msg = 'Time Execution (seconds): ' + str(diff_time.total_seconds()) +'\n' log_file.write(msg) def main(): config = configparser.ConfigParser() config.read('config.ini') #Path for Gromacs project gromacs_path = preparing_path(config.get('DRUGDESIGN', 'gromacs_path')) #Path where PDB ligand are - They are NOT participated in docking pdb_ligand_path = config.get('DEFAULT', 'pdb_ligand_path') #Path that contains all files for analysis path_analysis = config.get('DEFAULT', 'path_analysis') #Ligand Database file ligand_database = config.get('DEFAULT', 'ligand_database_path_file') #Path where all pdb receptor are path_receptor_pdb = config.get('DEFAULT', 'pdb_path') #Path for saving pdb files of models generated by VS path_analysis_pdb = get_directory_pdb_analysis(path_analysis) # Create SPARK config maxResultSize = str(config.get('SPARK', 'maxResultSize')) conf = (SparkConf().set("spark.driver.maxResultSize", maxResultSize)) # Create context sc = SparkContext(conf=conf) sqlCtx = SQLContext(sc) #Adding Python Source file #Path for drugdesign project path_spark_drugdesign = config.get('DRUGDESIGN', 'path_spark_drugdesign') sc.addPyFile(os.path.join(path_spark_drugdesign,"vina_utils.py")) sc.addPyFile(os.path.join(path_spark_drugdesign,"os_utils.py")) sc.addPyFile(os.path.join(path_spark_drugdesign,"gromacs_utils.py")) sc.addPyFile(os.path.join(path_spark_drugdesign,"pdb_io.py")) sc.addPyFile(os.path.join(path_spark_drugdesign,"database_io.py")) sc.addPyFile(os.path.join(path_spark_drugdesign,"json_utils.py")) #Adding bash scripts sc.addFile(os.path.join(path_spark_drugdesign,"make_ndx_buried_area_total.sh")) sc.addFile(os.path.join(path_spark_drugdesign,"make_sasa_rec_buried_area_total.sh")) #Parameters form command line #Indicates probe. Example: 0.14 probe = float(sys.argv[1]) #Indicates ndots. Example: 24 ndots = int(sys.argv[2]) #Broadcast path_analysis_pdb_complex_b = sc.broadcast(path_analysis_pdb) gromacs_path = sc.broadcast(gromacs_path) pdb_ligand_path = sc.broadcast(pdb_ligand_path) probe = sc.broadcast(probe) ndots = sc.broadcast(ndots) start_time = datetime.now() os.environ["GMX_MAXBACKUP"]="-1" #Loading all PDB receptor files into memory list_all_pdb_receptor_files_path = [] all_receptor_for_complex = get_files_pdb(path_receptor_pdb) for receptor in all_receptor_for_complex: list_all_pdb_receptor_files_path.append(loading_pdb_2_list(receptor)) #Computing Buried areas for pdb_receptor_files in list_all_pdb_receptor_files_path: #Getting receptor name by fully path base_file_name_receptor = get_name_receptor_pdb(str(pdb_receptor_files[0])) #PDB file loaded into memory is sent by broadcast pdb_file_receptor = pdb_receptor_files[1] pdb_file_receptor = sc.broadcast(pdb_file_receptor) #Loading PDB model files based on receptor into memory base_file_name_receptor_for_filter = base_file_name_receptor+"_-_" all_model_for_complex = get_files_pdb_filter(path_analysis_pdb,base_file_name_receptor_for_filter) all_model_for_complexRDD = sc.parallelize(all_model_for_complex) all_model_filesRDD = all_model_for_complexRDD.map(loading_pdb_2_list).collect() # ********** Starting function ********************************************************** def compute_buried_area(pdb_complex): chZ = "chZ" sasa_complex = -1.0 sasa_rec = -1.0 sasa_lig = -1.0 buried_total = -1.0 returned_list = [] try: base_name = get_name_model_pdb(pdb_complex) ligand_name = get_ligand_from_receptor_ligand_model(base_name) f_pdb_ligand_no_docking = os.path.join(pdb_ligand_path.value,ligand_name+".pdb") f_ndx = os.path.join(path_analysis_pdb_complex_b.value,base_name+".ndx") f_temp_sasa_complex = os.path.join(path_analysis_pdb_complex_b.value,base_name+"_sasa_complex.xvg") f_temp_sasa_rec = os.path.join(path_analysis_pdb_complex_b.value,base_name+"_sasa_rec.xvg") f_temp_sasa_lig = os.path.join(path_analysis_pdb_complex_b.value,base_name+"_sasa_lig.xvg") # Makes the index file with the ligand (chain z) and the rest (non chain z) script_make_ndx = SparkFiles.get("make_ndx_buried_area_total.sh") #Getting bash script that was copied by addFile command command = script_make_ndx + " " + gromacs_path.value + " "+ pdb_complex + " "+ f_ndx process = Popen(command,shell=True, stdout=PIPE, stderr=PIPE) stdout, stderr = process.communicate() command = gromacs_path.value +"gmx sasa -f " + pdb_complex + " -s " + pdb_complex + " -nopbc " + " -n " + f_ndx + " -surface System " + " -output System "+ " -xvg none " + " -o " + f_temp_sasa_complex process = Popen(command,shell=True, stdout=PIPE, stderr=PIPE) stdout, stderr = process.communicate() # Makes f_temp_sasa_rec file script_make_sasa_rec = SparkFiles.get("make_sasa_rec_buried_area_total.sh") #Getting bash script that was copied by addFile command command = script_make_sasa_rec + " " + gromacs_path.value + " "+ pdb_complex + " "+ f_ndx + " " + f_temp_sasa_rec process = Popen(command,shell=True, stdout=PIPE, stderr=PIPE) stdout, stderr = process.communicate() command = gromacs_path.value +"gmx sasa -f " + pdb_complex + " -s " + pdb_complex + " -nopbc " + " -n " + f_ndx + " -surface chZ " + " -output chZ "+ " -xvg none " + " -o " + f_temp_sasa_lig process = Popen(command,shell=True, stdout=PIPE, stderr=PIPE) stdout, stderr = process.communicate() sasa_complex = get_value_from_xvg_sasa(f_temp_sasa_complex) sasa_rec = get_value_from_xvg_sasa(f_temp_sasa_rec) sasa_lig = get_value_from_xvg_sasa(f_temp_sasa_lig) buried_total = sasa_rec + sasa_lig - sasa_complex #Generating result - See column sorting because resultaed file will be created based on this sorting returned_list = (base_name, buried_total) except: returned_list = (base_name, float(0)) #Deleting files if os.path.exists(f_ndx): os.remove(f_ndx) if os.path.exists(f_temp_sasa_complex): os.remove(f_temp_sasa_complex) if os.path.exists(f_temp_sasa_rec): os.remove(f_temp_sasa_rec) if os.path.exists(f_temp_sasa_lig): os.remove(f_temp_sasa_lig) return returned_list # ********** Finish function ********************************************************** # ********** Starting function ********************************************************** def save_model_receptor(list_receptor_model_file): receptor_file = pdb_file_receptor.value #Obtained from broadcast model_file = list_receptor_model_file[0] full_path_for_save_complex = list_receptor_model_file[1] #Open file for writting the complex f_compl = open(full_path_for_save_complex, "w") #Insert lines of receptor for item in receptor_file: f_compl.write(item) #Insert lines of model and insert Z chain for item in model_file: item = replace_chain_atom_line(item,"d","z") f_compl.write(item) f_compl.close() # ********** Finish function ********************************************************** # ********** Starting function ********************************************************** def build_list_model_for_complex(model): full_path_model = model[0] model_file = model[1] path_pdb_complex = path_analysis_pdb_complex_b.value #Obtained from broadcast #Building complex file based on model file name base_name_model = get_name_model_pdb(full_path_model) complex_name = "compl_"+base_name_model+".pdb" full_path_for_save_complex = os.path.join(path_pdb_complex,complex_name) list_receptor_model_file = (model_file, full_path_for_save_complex) save_model_receptor(list_receptor_model_file) list_ret = compute_buried_area(full_path_for_save_complex) os.remove(full_path_for_save_complex) return list_ret # ********** Finish function ********************************************************** all_model_filesRDD = sc.parallelize(all_model_filesRDD) all_model_filesRDD = all_model_filesRDD.map(build_list_model_for_complex).collect() #Saving buried area of receptor full_area_file = os.path.join(path_analysis,base_file_name_receptor+".area") save_receptor_buried_area(full_area_file, all_model_filesRDD) #Loading all area file all_area_file = os.path.join(path_analysis,"*.area") buried_areaRDD = sc.textFile(all_area_file).map(loading_lines_from_area_files).collect() #Sorting by buried_total column buried_area_sorted_by_buried_total = sorting_buried_area(sc, buried_areaRDD) buried_area_sorted_by_buried_total.cache() buried_area_sorted_by_buried_total_LIST = buried_area_sorted_by_buried_total.map(lambda p: (p.pose, p.buried_total) ).collect() #Saving buried area file path_file_buried_area = os.path.join(path_analysis, "summary_buried_areas_total.dat") save_buried_area(path_file_buried_area, buried_area_sorted_by_buried_total_LIST) #Calculating normalized buried area #Loading database rdd_database = load_database(sc, ligand_database) #Creating Dataframe database_table = sqlCtx.createDataFrame(rdd_database) database_table.registerTempTable("database") number_pose_ligandRDD = buried_area_sorted_by_buried_total.map(lambda p: Row(buried_total=int(p.buried_total), ligand=get_ligand_from_receptor_ligand_model(p.pose), pose=str(p.pose) ) ).collect() number_pose_ligand_table = sqlCtx.createDataFrame(number_pose_ligandRDD) number_pose_ligand_table.registerTempTable("buried_area_total_sort") sql = """ SELECT pose, (b.buried_total / a.heavyAtom) as normalized_buried_area FROM database a JOIN buried_area_total_sort b ON b.ligand = a.ligand ORDER BY normalized_buried_area DESC """ #Getting all data full_dataRDD = sqlCtx.sql(sql) #Saving normalized buried area file path_file_buried_area = os.path.join(path_analysis, "summary_normalized_buried_areas.dat") save_normalized_buried_area(path_file_buried_area, full_dataRDD) #Removing all area files all_area_files = get_files_area(path_analysis) for area_file in all_area_files: os.remove(area_file) finish_time = datetime.now() save_log(finish_time, start_time) main()

oase-root/web_app/views/system/mail/action_mail.py

Masa-Yasuno/oase

373

<gh_stars>1-10 # Copyright 2019 NEC Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # """ [概要] MAILアクション用画面表示補助クラス """ import pytz import datetime import json import socket import traceback from django.http import HttpResponse from django.http import HttpResponseServerError from django.db import transaction from django.conf import settings from libs.commonlibs import define as defs from libs.commonlibs.oase_logger import OaseLogger from libs.commonlibs.aes_cipher import AESCipher from web_app.models.models import ActionType from web_app.models.mail_models import MailDriver from web_app.templatetags.common import get_message from web_app.serializers.unicode_check import UnicodeCheck logger = OaseLogger.get_instance() # ロガー初期化 class mailDriverInfo(): def __init__(self, drv_id, act_id, name, ver, icon_name): self.drv_id = drv_id self.act_id = act_id self.name = name self.ver = ver self.icon_name = icon_name def __str__(self): return '%s(ver%s)' % (self.name, self.ver) def get_driver_name(self): return '%s Driver ver%s' % (self.name, self.ver) def get_driver_id(self): return self.drv_id def get_icon_name(self): return self.icon_name @classmethod def get_template_file(cls): return 'system/mail/action_mail.html' @classmethod def get_info_list(cls, user_groups): try: mail_driver_obj_list = MailDriver.objects.all() except Exception as e: # ここでの例外は大外で拾う raise protocol_dict = cls.get_define()['dict'] mail_driver_dto_list = [] cipher = AESCipher(settings.AES_KEY) for mail_obj in mail_driver_obj_list: mail_info = mail_obj.__dict__ if mail_obj.password: mail_info['password'] = <PASSWORD>.decrypt(mail_obj.password) mail_info['protocol_str'] = protocol_dict[mail_obj.protocol] mail_driver_dto_list.append(mail_info) return mail_driver_dto_list @classmethod def get_group_list(cls, user_groups): """ [概要] グループ一覧を取得する(システム管理グループを除く) """ return [] @classmethod def get_define(cls): protocol_dict = {key_value['v']: key_value['k'] for key_value in defs.SMTP_PROTOCOL.LIST_ALL} defines = { 'list_all': defs.SMTP_PROTOCOL.LIST_ALL, 'dict': protocol_dict, } return defines def record_lock(self, json_str, request): logger.logic_log('LOSI00001', 'None', request=request) driver_id = self.get_driver_id() # 更新前にレコードロック if json_str['json_str']['ope'] in (defs.DABASE_OPECODE.OPE_UPDATE, defs.DABASE_OPECODE.OPE_DELETE): drvinfo_modify = int(json_str['json_str']['mail_driver_id']) MailDriver.objects.select_for_update().filter(pk=drvinfo_modify) logger.logic_log('LOSI00002', 'Record locked.(driver_id=%s)' % driver_id, request=request) def modify(self, json_str, request): """ [メソッド概要] グループのDB更新処理 """ logger.logic_log('LOSI00001', 'None', request=request) error_flag = False error_msg = { 'mail_disp_name' : '', 'protocol' : '', 'smtp_server' : '', 'port' : '', 'user' : '', 'password' : '', } now = datetime.datetime.now(pytz.timezone('UTC')) emo_chk = UnicodeCheck() # 成功時データ response = {"status": "success",} try: rq = json_str['json_str'] ope = int(rq['ope']) #削除以外の場合の入力チェック if ope != defs.DABASE_OPECODE.OPE_DELETE: error_flag = self._validate(rq, error_msg, request) if error_flag: raise UserWarning('validation error.') # パスワードを暗号化 空なら空文字 cipher = AESCipher(settings.AES_KEY) if ope == defs.DABASE_OPECODE.OPE_UPDATE: encrypted_password = <PASSWORD>.encrypt(rq['password']) if rq['password'] else '' driver_info_mod = MailDriver.objects.get(mail_driver_id=rq['mail_driver_id']) driver_info_mod.mail_disp_name = rq['mail_disp_name'] driver_info_mod.protocol = rq['protocol'] driver_info_mod.smtp_server = rq['smtp_server'] driver_info_mod.port = rq['port'] driver_info_mod.user = rq['user'] driver_info_mod.password = <PASSWORD> driver_info_mod.last_update_user = request.user.user_name driver_info_mod.last_update_timestamp = now driver_info_mod.save(force_update=True) elif ope == defs.DABASE_OPECODE.OPE_DELETE: MailDriver.objects.filter(pk=rq['mail_driver_id']).delete() elif ope == defs.DABASE_OPECODE.OPE_INSERT: encrypted_password = <PASSWORD>.encrypt(rq['password']) if rq['password'] else '' driver_info_reg = MailDriver( mail_disp_name = rq['mail_disp_name'], protocol = rq['protocol'], smtp_server = rq['smtp_server'], port = rq['port'], user = rq['user'], password = <PASSWORD>, last_update_user = request.user.user_name, last_update_timestamp = now ).save(force_insert=True) except MailDriver.DoesNotExist: logger.logic_log('LOSM07006', "mail_driver_id", mail_driver_id, request=request) except Exception as e: logger.logic_log('LOSI00005', traceback.format_exc(), request=request) response = { 'status': 'failure', 'error_msg': error_msg, # エラー詳細(エラーアイコンで出す) } logger.logic_log('LOSI00002', 'response=%s' % response, request=request) return response def _validate(self, rq, error_msg, request): """ [概要] 入力チェック [引数] rq: dict リクエストされた入力データ error_msg: dict [戻り値] """ logger.logic_log('LOSI00001', 'data: %s, error_msg:%s'%(rq, error_msg)) error_flag = False emo_chk = UnicodeCheck() emo_flag = False emo_flag_ita_disp_name = False emo_flag_hostname = False if len(rq['mail_disp_name']) == 0: error_flag = True error_msg['mail_disp_name'] += get_message('MOSJA27201', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07001', 'mail_disp_name', request=request) if len(rq['mail_disp_name']) > 64: error_flag = True error_msg['mail_disp_name'] += get_message('MOSJA27202', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07002', 'mail_disp_name', 64, rq['mail_disp_name'], request=request) # 絵文字チェック value_list = emo_chk.is_emotion(rq['mail_disp_name']) if len(value_list) > 0: error_flag = True emo_flag = True error_msg['mail_disp_name'] += get_message('MOSJA27216', request.user.get_lang_mode(), showMsgId=False) + '\n' if len(rq['protocol']) == 0: error_flag = True error_msg['protocol'] += get_message('MOSJA27212', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07001', 'protocol', request=request) if len(rq['protocol']) > 64: error_flag = True error_msg['protocol'] += get_message('MOSJA27213', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07002', 'protocol', 64, rq['protocol'], request=request) if len(rq['smtp_server']) == 0: error_flag = True error_msg['smtp_server'] += get_message('MOSJA27203', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07001', 'smtp_server', request=request) if len(rq['smtp_server']) > 128: error_flag = True error_msg['smtp_server'] += get_message('MOSJA27204', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07002', 'smtp_server', 64, rq['smtp_server'], request=request) # 絵文字チェック value_list = emo_chk.is_emotion(rq['smtp_server']) if len(value_list) > 0: error_flag = True error_msg['smtp_server'] += get_message('MOSJA27217', request.user.get_lang_mode(), showMsgId=False) + '\n' if len(rq['port']) == 0: error_flag = True error_msg['port'] += get_message('MOSJA27205', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07001', 'port', request=request) try: tmp_port = int(rq['port']) if 0 > tmp_port or tmp_port > 65535: error_flag = True error_msg['port'] += get_message('MOSJA27206', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07003', 'port', rq['port'], request=request) except ValueError: error_flag = True error_msg['port'] += get_message('MOSJA27206', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07003', 'port', rq['port'], request=request) if len(rq['user']) > 64: error_flag = True error_msg['user'] += get_message('MOSJA27207', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07002', 'user', 64, rq['user'], request=request) # 絵文字チェック value_list = emo_chk.is_emotion(rq['user']) if len(value_list) > 0: error_flag = True error_msg['user'] += get_message('MOSJA27218', request.user.get_lang_mode(), showMsgId=False) + '\n' if len(rq['password']) > 64: error_flag = True error_msg['password'] += get_message('<PASSWORD>', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07002', 'password', 64, rq['password'], request=request) # 絵文字チェック value_list = emo_chk.is_emotion(rq['password']) if len(value_list) > 0: error_flag = True error_msg['password'] += get_message('<PASSWORD>', request.user.get_lang_mode(), showMsgId=False) + '\n' if not emo_flag: duplication = MailDriver.objects.filter(mail_disp_name=rq['mail_disp_name']) if len(duplication) == 1 and int(rq['mail_driver_id']) != duplication[0].mail_driver_id: error_flag = True error_msg['mail_disp_name'] += get_message('MOSJA27209', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07004', 'mail_disp_name', rq['mail_disp_name'], request=request) if error_flag == False: # 疎通確認 resp_code = -1 try: with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock: resp_code = sock.connect_ex((rq['smtp_server'], int(rq['port']))) # host名名前解決が必要/etc/hostsとか sock.close() except Exception as e: pass if resp_code != 0: error_flag = True #todo 仮でこのエラーは名前に入れている error_msg['mail_disp_name'] += get_message('MOSJA27215', request.user.get_lang_mode()) + '\n' logger.user_log('LOSM07005', rq['smtp_server'], rq['port'], request=request) return error_flag

queue/animal_queue.py

cozek/code-practice

374

#!/usr/bin/env python3 from typing import Any, Union class Animal: def __init__(self, name: str) -> None: self.name = name def set_order(self, order: int) -> None: self.order = order def peek_order(self) -> int: return self.order def __str__(self) -> str: return f"{self.name}" class Node: def __init__(self, data: Any): self.data = data self.next_node = None class LinkedList: def __init__(self) -> None: self.head = None self.tail = None def __str__(self) -> str: current = self.head string = f"" while current.next_node is not None: string += f"{current.data} -> " current = current.next_node return string + "END" def is_empty(self) -> bool: if self.head is None: return True else: return False def insert(self, item: Any) -> None: if self.is_empty(): self.head = Node(item) self.tail = self.head else: new_node = Node(item) self.tail.next_node = new_node self.tail = self.tail.next_node def remove(self) -> Any: if self.head is None: raise ("Empty LinkedList!") else: data = self.head.data self.head = self.head.next_node return data def peak(self): return self.head.data class Dog(Animal): def __init__(self, name: str): super().__init__(name) class Cat(Animal): def __init__(self, name: str): super().__init__(name) class AnimalQueue: def __init__(self) -> None: self.dogs = LinkedList() self.cats = LinkedList() self.order = 0 def enqueue(self, animal: Union[Dog, Cat]) -> None: if not isinstance(animal, (Dog, Cat)): raise Exception("Expected Dog or Cat!") else: animal.set_order(self.order) self.order += 1 if isinstance(animal, Dog): self.dogs.insert(animal) elif isinstance(animal, Cat): self.cats.insert(animal) def dequeAny(self) -> Union[Dog, Cat]: if self.dogs.is_empty(): return self.dequeCat() elif self.cats.is_empty(): return self.dequeDog() if self.dogs.head.data.peek_order() > self.cats.head.data.peek_order(): return self.dequeCat() else: return self.dequeDog() def print_cats(self) -> str: string = "" cat = self.cats.head while cat is not None: string += f"{cat.data.name} {cat.data.peek_order()} | " cat = cat.next_node return string def dequeDog(self) -> Dog: return self.dogs.remove() def dequeCat(self) -> Cat: return self.cats.remove() def main(): q = AnimalQueue() dogs = [Dog("d1"), Dog("d2"), Dog("d3")] cats = [Cat("c1"), Cat("c2"), Cat("c3")] both = [] while cats != []: both.append(cats.pop()) both.append(dogs.pop()) [q.enqueue(animal) for animal in both] string = "" for anim in both: string += f"{anim.name} {anim.order} | " print(string) # print(q.print_cats()) get = q.dequeDog() print(get.order,get.name) get = q.dequeAny() print(get.order,get.name) if __name__ == "__main__": main()

ophyd/areadetector/detectors.py

NSLS-II/ophyd

375

# vi: ts=4 sw=4 '''AreaDetector Devices `areaDetector`_ detector abstractions .. _areaDetector: https://areadetector.github.io/master/index.html ''' import warnings from .base import (ADBase, ADComponent as C) from . import cam __all__ = ['DetectorBase', 'AreaDetector', 'AdscDetector', 'Andor3Detector', 'AndorDetector', 'BrukerDetector', 'DexelaDetector', 'EmergentVisionDetector', 'EigerDetector', 'FirewireLinDetector', 'FirewireWinDetector', 'GreatEyesDetector', 'LightFieldDetector', 'Mar345Detector', 'MarCCDDetector', 'PSLDetector', 'PerkinElmerDetector', 'PICamDetector', 'PilatusDetector', 'PixiradDetector', 'PointGreyDetector', 'ProsilicaDetector', 'PvcamDetector', 'RoperDetector', 'SimDetector', 'URLDetector', 'UVCDetector', 'Xspress3Detector' ] class DetectorBase(ADBase): """ The base class for the hardware-specific classes that follow. Note that Plugin also inherits from ADBase. This adds some AD-specific methods that are not shared by the plugins. """ _default_configuration_attrs = (ADBase._default_configuration_attrs + ('cam', )) def generate_datum(self, key, timestamp, datum_kwargs=None): """ Notify plugins of acquisition being complete. When a new acquisition is started, this method is called with a key which is a label like 'light', 'dark', or 'gain8'. It in turn calls ``generate_datum`` on all of the plugins that have that method. File plugins are identified by searching for a :meth:`~ophyd.areadetector.filestore_mixins.FileStoreBase.generate_datum` method that must have the signature :: def generate_datum(key: str, timestamp: float, datum_kwargs: dict): ... Parameters ---------- key : str The label for the datum that should be generated timestamp : float The time of the trigger datum_kwargs : Dict[str, Any], optional Any datum kwargs that should go to all children. """ if datum_kwargs is None: datum_kwargs = {} file_plugins = [s for s in self._signals.values() if hasattr(s, 'generate_datum')] for p in file_plugins: if p.enable.get(): p.generate_datum(key, timestamp, datum_kwargs) def dispatch(self, key, timestamp): warnings.warn( ".dispatch is deprecated, use .generate_datum instead", stacklevel=2 ) return self.generate_datum(key, timestamp, {}) dispatch.__doc__ = generate_datum.__doc__ def make_data_key(self): source = 'PV:{}'.format(self.prefix) # This shape is expected to match arr.shape for the array. shape = (self.cam.num_images.get(), self.cam.array_size.array_size_y.get(), self.cam.array_size.array_size_x.get()) return dict(shape=shape, source=source, dtype='array', external='FILESTORE:') def collect_asset_docs(self): file_plugins = [s for s in self._signals.values() if hasattr(s, 'collect_asset_docs')] for p in file_plugins: yield from p.collect_asset_docs() class AreaDetector(DetectorBase): cam = C(cam.AreaDetectorCam, 'cam1:') class SimDetector(DetectorBase): _html_docs = ['simDetectorDoc.html'] cam = C(cam.SimDetectorCam, 'cam1:') class AdscDetector(DetectorBase): _html_docs = ['adscDoc.html'] cam = C(cam.AdscDetectorCam, 'cam1:') class AndorDetector(DetectorBase): _html_docs = ['andorDoc.html'] cam = C(cam.AndorDetectorCam, 'cam1:') class Andor3Detector(DetectorBase): _html_docs = ['andor3Doc.html'] cam = C(cam.Andor3DetectorCam, 'cam1:') class BrukerDetector(DetectorBase): _html_docs = ['BrukerDoc.html'] cam = C(cam.BrukerDetectorCam, 'cam1:') class DexelaDetector(DetectorBase): _html_docs = ['DexelaDoc.html'] cam = C(cam.DexelaDetectorCam, 'cam1:') class EmergentVisionDetector(DetectorBase): _html_docs = ['EVTDoc.html'] cam = C(cam.EmergentVisionDetectorCam, 'cam1:') class EigerDetector(DetectorBase): _html_docs = ['EigerDoc.html'] cam = C(cam.EigerDetectorCam, 'cam1:') class FirewireLinDetector(DetectorBase): _html_docs = ['FirewireWinDoc.html'] cam = C(cam.FirewireLinDetectorCam, 'cam1:') class FirewireWinDetector(DetectorBase): _html_docs = ['FirewireWinDoc.html'] cam = C(cam.FirewireWinDetectorCam, 'cam1:') class GreatEyesDetector(DetectorBase): _html_docs = [] # the documentation is not public cam = C(cam.GreatEyesDetectorCam, 'cam1:') class LightFieldDetector(DetectorBase): _html_docs = ['LightFieldDoc.html'] cam = C(cam.LightFieldDetectorCam, 'cam1:') class Mar345Detector(DetectorBase): _html_docs = ['Mar345Doc.html'] cam = C(cam.Mar345DetectorCam, 'cam1:') class MarCCDDetector(DetectorBase): _html_docs = ['MarCCDDoc.html'] cam = C(cam.MarCCDDetectorCam, 'cam1:') class PerkinElmerDetector(DetectorBase): _html_docs = ['PerkinElmerDoc.html'] cam = C(cam.PerkinElmerDetectorCam, 'cam1:') class PSLDetector(DetectorBase): _html_docs = ['PSLDoc.html'] cam = C(cam.PSLDetectorCam, 'cam1:') class PICamDetector(DetectorBase): _html_docs = ['PICamDoc.html'] cam = C(cam.PICamDetectorCam, 'cam1:') class PilatusDetector(DetectorBase): _html_docs = ['pilatusDoc.html'] cam = C(cam.PilatusDetectorCam, 'cam1:') class PixiradDetector(DetectorBase): _html_docs = ['PixiradDoc.html'] cam = C(cam.PixiradDetectorCam, 'cam1:') class PointGreyDetector(DetectorBase): _html_docs = ['PointGreyDoc.html'] cam = C(cam.PointGreyDetectorCam, 'cam1:') class ProsilicaDetector(DetectorBase): _html_docs = ['prosilicaDoc.html'] cam = C(cam.ProsilicaDetectorCam, 'cam1:') class PvcamDetector(DetectorBase): _html_docs = ['pvcamDoc.html'] cam = C(cam.PvcamDetectorCam, 'cam1:') class RoperDetector(DetectorBase): _html_docs = ['RoperDoc.html'] cam = C(cam.RoperDetectorCam, 'cam1:') class URLDetector(DetectorBase): _html_docs = ['URLDoc.html'] cam = C(cam.URLDetectorCam, 'cam1:') class UVCDetector(DetectorBase): _html_docs = ['UVCDoc.html'] cam = C(cam.UVCDetectorCam, 'cam1:') class Xspress3Detector(DetectorBase): _html_docs = ['Xspress3Doc.html'] cam = C(cam.Xspress3DetectorCam, 'det1:')

python/EXERCICIO 96 - FUNCAO QUE CALCULA A AREA.py

debor4h/exerciciosPython

376

def area(msg):#declaracao da funcao com o parametro msg print(msg)#aqui msg e a area print('Controle de Terrenos') print('-' * 20) l = float(input('Largura (m): ')) c = float(input('Comprimento (m): ')) area(f'A área do seu terreno {l}X{c} é de {l*c}m².')

auth_iam/dashboard/auth/routes.py

santiher/dash-auth-example

377

import os from functools import wraps from os.path import join as join_path from dash import Dash from flask import make_response, render_template_string, redirect excluded_resources_endpoints = ( 'static', '_dash_assets.static', '/_favicon.ico', '/login', '/logout', '/_user', '/auth') def add_routes(app, authorizer): """Adds authentication endpoints to a flask app. Decorates other endpoints to grant access. The endpoints are: * /login * Method: GET * /logout * Method: GET * Erases cookies * /auth * Method: GET * Validates cookies if present or header authentication * Header: 'Authorization: DASHBOARD-AUTH username=([^/]*)/password=([^/]*)' * Sets cookies on login * Rejects unauthorized users Parameters ---------- app: flask.Flask or dash.Dash The flask or dash application excluded_resources_endpoints: tuple(str) Tuple with endpoints where access must not be checked. """ def login(): ok, _ = authorizer.validate() if ok: return make_response(redirect('/'), 307) return render_template_string(login_template) def logout(): _, response = authorizer.clean_cookie() return response def auth(): _, response = authorizer.validate() return response def authorize_endpoint(function): @wraps(function) def authorized_function(*args, **kwargs): ok, response = authorizer.validate() if ok: return function(*args, **kwargs) return response return authorized_function if isinstance(app, Dash): app = app.server login_template = load_template('login.html') app.add_url_rule('/auth', '/auth', auth) app.add_url_rule('/login', '/login', login) app.add_url_rule('/logout', '/logout', logout) for endpoint, function in app.view_functions.items(): if endpoint not in excluded_resources_endpoints: app.view_functions[endpoint] = authorize_endpoint(function) def load_template(filename): """Loads the login html template.""" pyfile_path = os.path.dirname(os.path.abspath(__file__)) path = join_path(pyfile_path, 'templates', filename) with open(path, 'r') as f: return f.read().strip()

amazon/model_api/migrations/0005_remove_order_datetimecreated_alter_order__id_and_more.py

gabrielkarras/SOEN341

378

# Generated by Django 4.0.1 on 2022-04-07 01:20 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('model_api', '0004_remove_order_created_remove_order_id_and_more'), ] operations = [ migrations.RemoveField( model_name='order', name='dateTimeCreated', ), migrations.AlterField( model_name='order', name='_id', field=models.AutoField(editable=False, primary_key=True, serialize=False), ), migrations.AlterField( model_name='orderedproduct', name='_id', field=models.AutoField(editable=False, primary_key=True, serialize=False), ), migrations.AlterField( model_name='orderedproduct', name='price', field=models.CharField(blank=True, max_length=20, null=True), ), ]

items/migrations/0001_initial.py

tony-joseph/livre

379

# -*- coding: utf-8 -*- # Generated by Django 1.9 on 2015-12-21 12:22 from __future__ import unicode_literals from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='BookCopy', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('book_status', models.IntegerField(choices=[(1, 'Available'), (2, 'In Circulation'), (3, 'Temporarily Unavailable'), (4, 'Unavailable'), (5, 'Protected'), (6, 'Damaged')])), ('remarks', models.TextField(blank=True, default='')), ('created_on', models.DateTimeField(auto_now_add=True)), ('updated_on', models.DateTimeField(auto_now=True)), ], ), migrations.CreateModel( name='BookDetail', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=1024)), ('author', models.CharField(default='Unknown', max_length=1024)), ('description', models.TextField(blank=True, default='')), ('publisher', models.CharField(blank=True, default='', max_length=512)), ('published_on', models.DateField(blank=True, null=True)), ('pages', models.PositiveIntegerField(blank=True, default=0, null=True)), ('ddc', models.CharField(blank=True, default='', max_length=1024)), ('llcc', models.CharField(blank=True, default='', max_length=1024)), ('isbn', models.CharField(blank=True, default='', max_length=1024)), ('tags', models.CharField(blank=True, max_length=1024, null=True)), ('created_on', models.DateTimeField(auto_now_add=True)), ('updated_on', models.DateTimeField(auto_now=True)), ], ), migrations.CreateModel( name='Category', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=512)), ('slug', models.SlugField(max_length=128, unique=True)), ('description', models.TextField(blank=True, default='')), ('created_on', models.DateTimeField(auto_now_add=True)), ('updated_on', models.DateTimeField(auto_now=True)), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ('updated_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='category_updated_by', to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='Language', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=512)), ('short_code', models.CharField(db_index=True, max_length=8, unique=True)), ('description', models.TextField(blank=True, default='')), ('created_on', models.DateTimeField(auto_now_add=True)), ('updated_on', models.DateTimeField(auto_now=True)), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ('updated_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='language_updated_by', to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='Periodical', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=1024)), ('description', models.TextField(blank=True, default='')), ('publisher', models.CharField(blank=True, default='', max_length=512)), ('tags', models.CharField(blank=True, max_length=1024, null=True)), ('created_on', models.DateTimeField(auto_now_add=True)), ('updated_on', models.DateTimeField(auto_now=True)), ('category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='items.Category')), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ('language', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='items.Language')), ('updated_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='periodical_updated_by', to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='PeriodicalIssue', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('issue_status', models.IntegerField(choices=[(1, 'Available'), (2, 'In Circulation'), (3, 'Temporarily Unavailable'), (4, 'Unavailable'), (5, 'Protected'), (6, 'Damaged')])), ('published_on', models.DateField(blank=True, null=True)), ('volume', models.PositiveIntegerField(blank=True, null=True)), ('issue', models.PositiveIntegerField(blank=True, null=True)), ('remarks', models.TextField(blank=True, default='')), ('tags', models.CharField(blank=True, max_length=1024, null=True)), ('created_on', models.DateTimeField(auto_now_add=True)), ('updated_on', models.DateTimeField(auto_now=True)), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ('periodical', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='items.Periodical')), ('updated_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='periodical_issue_updated_by', to=settings.AUTH_USER_MODEL)), ], ), migrations.AddField( model_name='bookdetail', name='category', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='items.Category'), ), migrations.AddField( model_name='bookdetail', name='created_by', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='bookdetail', name='language', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='items.Language'), ), migrations.AddField( model_name='bookdetail', name='updated_by', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='book_detail_updated_by', to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='bookcopy', name='book_detail', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='items.BookDetail'), ), migrations.AddField( model_name='bookcopy', name='created_by', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='bookcopy', name='updated_by', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='book_copy_updated_by', to=settings.AUTH_USER_MODEL), ), ]

compliance_suite/exceptions/user_config_exception.py

alextsaihi/rnaget-compliance-suite

380

<filename>compliance_suite/exceptions/user_config_exception.py<gh_stars>1-10 # -*- coding: utf-8 -*- """Module compliance_suite.exceptions.user_config_exception.py This module contains class definition for user config file exceptions. """ class UserConfigException(Exception): """Exception for user config file-related errors""" pass

2021/day15/aoc-2021-d15.py

bbornstein/aoc

381

<reponame>bbornstein/aoc #!/usr/bin/env python3 # Advent of Code 2021, Day 15 (https://adventofcode.com/2021/day/15) # Author: <NAME> import collections import heapq Point = collections.namedtuple('Point', ['x', 'y']) Point.__add__ = lambda self, q: Point(self[0] + q[0], self[1] + q[1]) class RiskMap: def __init__ (self): """Creates a new (empty) risk-level map. Individual risk-levels as specific positions are accessible via `RiskMap[Point]`. See also `RiskMap.load()` """ self._factor = 1 self._levels = [ ] self._nrows = 0 self._ncols = 0 def __getitem__ (self, pos): """Returns the risk-level at position `pos`, i.e. `RiskMap[pos]`.""" if self._factor > 1: risk = self._levels[pos.y % self._nrows][pos.x % self._ncols] risk += pos.y // self._nrows risk += pos.x // self._ncols if risk > 9: risk = risk % 9 else: risk = self._levels[pos.y][pos.x] return risk @staticmethod def load (filename): """Creates a new risk-level map from `filename`.""" rmap = RiskMap() with open(filename) as stream: for line in stream.readlines(): rmap.append([ int(c) for c in line.strip() ]) return rmap @property def ncols (self): """The number of columns in this `RiskMap`.""" return self._factor * self._ncols @property def nrows (self): """The number of rows in this `RiskMap`.""" return self._factor * self._nrows def append (self, row): """Appends `row` to this `RiskMap`.""" if len(self._levels) == 0: self._ncols = len(row) self._levels.append(row) self._nrows += 1 def neighbors (self, pos): """Iterable 4-neighbors (up, down, left, right) for `pos`ition.""" deltas = (0, -1), (0, 1), (-1, 0), (1, 0) adjacent = ( pos + Point(*delta) for delta in deltas ) yield from ( p for p in adjacent if self.valid(p) ) def resize (self, factor): """Resizes this `RiskMap` by setting its expansion factor to `factor` copies both horizontally and vertically. """ self._factor = factor def valid (self, pos): """Indicates whether or not `pos` is valid (inside this `RiskMap`).""" return pos.y in range(0, self.nrows) and pos.x in range(0, self.ncols) def search (rmap, start, end): """Searches `RiskMap` `rmap` (breadth-first) to find the least risky path from `start` to `end`. Returns the total risk of that path. """ risk = 0 queue = [ (rmap[p], p) for p in rmap.neighbors(start) ] visited = { start } heapq.heapify(queue) while len(queue) > 0: risk, current = heapq.heappop(queue) if current == end: break for pos in rmap.neighbors(current): if pos not in visited: heapq.heappush( queue, ((rmap[pos] + risk), pos) ) visited.add(pos) return risk filename = 'aoc-2021-d15.txt' rmap = RiskMap.load(filename) start = Point(0, 0) end = Point(rmap.ncols - 1, rmap.nrows - 1) # Part 1 # # Q: Lowest total risk of any path from the top left to the bottom right? # A: Total Risk = 755 print(f'Part 1: Total Risk = {search(rmap, start, end):4}') # Part 2 # # Q: Lowest total risk of any path from the top left to the bottom right? # A: Total Risk = 3016 rmap.resize(factor=5) end = Point(rmap.ncols - 1, rmap.nrows - 1) print(f'Part 2: Total Risk = {search(rmap, start, end)}')

indico/modules/events/abstracts/compat.py

aiforrural/Digital-Events-Example

382

# This file is part of Indico. # Copyright (C) 2002 - 2020 CERN # # Indico is free software; you can redistribute it and/or # modify it under the terms of the MIT License; see the # LICENSE file for more details. from flask import redirect from indico.modules.events.abstracts.models.abstracts import Abstract from indico.web.flask.util import url_for from indico.web.rh import RHSimple @RHSimple.wrap_function def compat_abstract(endpoint, confId, friendly_id, track_id=None, management=False): abstract = Abstract.find(event_id=confId, friendly_id=friendly_id).first_or_404() return redirect(url_for('abstracts.' + endpoint, abstract, management=management))

src/cosmosdb-preview/azext_cosmosdb_preview/vendored_sdks/azure_mgmt_cosmosdb/models/database_account_list_keys_result_py3.py

limingu/azure-cli-extensions

383

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from .database_account_list_read_only_keys_result_py3 import DatabaseAccountListReadOnlyKeysResult class DatabaseAccountListKeysResult(DatabaseAccountListReadOnlyKeysResult): """The access keys for the given database account. Variables are only populated by the server, and will be ignored when sending a request. :ivar primary_readonly_master_key: Base 64 encoded value of the primary read-only key. :vartype primary_readonly_master_key: str :ivar secondary_readonly_master_key: Base 64 encoded value of the secondary read-only key. :vartype secondary_readonly_master_key: str :ivar primary_master_key: Base 64 encoded value of the primary read-write key. :vartype primary_master_key: str :ivar secondary_master_key: Base 64 encoded value of the secondary read-write key. :vartype secondary_master_key: str """ _validation = { 'primary_readonly_master_key': {'readonly': True}, 'secondary_readonly_master_key': {'readonly': True}, 'primary_master_key': {'readonly': True}, 'secondary_master_key': {'readonly': True}, } _attribute_map = { 'primary_readonly_master_key': {'key': 'primaryReadonlyMasterKey', 'type': 'str'}, 'secondary_readonly_master_key': {'key': 'secondaryReadonlyMasterKey', 'type': 'str'}, 'primary_master_key': {'key': 'primaryMasterKey', 'type': 'str'}, 'secondary_master_key': {'key': 'secondaryMasterKey', 'type': 'str'}, } def __init__(self, **kwargs) -> None: super(DatabaseAccountListKeysResult, self).__init__(**kwargs) self.primary_master_key = None self.secondary_master_key = None

Google/google_books/scrape_google_books.py

dimitryzub/blog-posts-archive

384

from parsel import Selector import requests, json, re params = { "q": "<NAME>", "tbm": "bks", "gl": "us", "hl": "en" } headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.87 Safari/537.36", } html = requests.get("https://www.google.com/search", params=params, headers=headers, timeout=30) selector = Selector(text=html.text) books_results = [] # https://regex101.com/r/mapBs4/1 book_thumbnails = re.findall(r"s=\\'data:image/jpg;base64,(.*?)\\'", str(selector.css("script").getall()), re.DOTALL) for book_thumbnail, book_result in zip(book_thumbnails, selector.css(".Yr5TG")): title = book_result.css(".DKV0Md::text").get() link = book_result.css(".bHexk a::attr(href)").get() displayed_link = book_result.css(".tjvcx::text").get() snippet = book_result.css(".cmlJmd span::text").get() author = book_result.css(".fl span::text").get() author_link = f'https://www.google.com/search{book_result.css(".N96wpd .fl::attr(href)").get()}' date_published = book_result.css(".fl+ span::text").get() preview_link = book_result.css(".R1n8Q a.yKioRe:nth-child(1)::attr(href)").get() more_editions_link = book_result.css(".R1n8Q a.yKioRe:nth-child(2)::attr(href)").get() books_results.append({ "title": title, "link": link, "displayed_link": displayed_link, "snippet": snippet, "author": author, "author_link": author_link, "date_published": date_published, "preview_link": preview_link, "more_editions_link": f"https://www.google.com{more_editions_link}" if more_editions_link is not None else None, "thumbnail": bytes(bytes(book_thumbnail, "ascii").decode("unicode-escape"), "ascii").decode("unicode-escape") })

Python/Higher-Or-Lower/hol/__init__.py

AustinTSchaffer/DailyProgrammer

385

<reponame>AustinTSchaffer/DailyProgrammer<filename>Python/Higher-Or-Lower/hol/__init__.py r""" Contains classes and methods that can be used when simulating the game Higher-or-Lower and performing statistical analysis on different games. """ from hol import ( cards, constants, ) from hol._hol import ( generate_all_games, should_pick_higher, is_a_winning_game, generate_win_statistics, )

Lib/hTools2/dialogs/glyphs/slide.py

gferreira/hTools2

386

# [h] slide selected glyphs from mojo.roboFont import CurrentFont, CurrentGlyph, version from vanilla import * from hTools2 import hDialog from hTools2.modules.fontutils import get_full_name, get_glyphs from hTools2.modules.messages import no_font_open, no_glyph_selected class slideGlyphsDialog(hDialog): '''A dialog to slide the selected glyphs vertically and/or horizontally. .. image:: imgs/glyphs/slide.png ''' _moveX = 0 _moveY = 0 _xMax = 1000 _xMin = -1000 _yMax = 500 _yMin = -500 font = None font_name = '(no font selected)' def __init__(self): # window self.title = "slide" self.button_width = 70 self.column_1 = 20 self.column_2 = 240 self.width = self.column_1 + self.column_2 + self.button_width + self.padding_x*3 self.height = self.text_height*3 + self.padding_y*4 self.w = HUDFloatingWindow((self.width, self.height), self.title) x = self.padding_x y = self.padding_y # current font name self.w.box = Box( (x, y, self.column_1 + self.column_2, self.text_height)) self.w.box.text = TextBox( (5, 0, self.column_1 + self.column_2, self.text_height), self.font_name, sizeStyle=self.size_style) x += (self.column_2 + self.column_1 + self.padding_x) self.w.button_update_font = SquareButton( (x, y, self.button_width, self.text_height), "update", callback=self.update_font_callback, sizeStyle=self.size_style) # x slider x = self.padding_x y += self.text_height + self.padding_y self.w.x_label = TextBox( (x, y + 5, self.column_1, self.text_height), "x", sizeStyle=self.size_style) x += self.column_1 self.w.x_slider = Slider( (x, y, self.column_2, self.text_height), value=0, maxValue=self._xMax, minValue=self._xMin, callback=self.slide_callback, sizeStyle=self.size_style) x += (self.column_2 + self.padding_x) self.w.button_restore_x = SquareButton( (x, y, self.button_width, self.text_height), "reset x", callback=self.restore_x_callback, sizeStyle=self.size_style) # y slider x = self.padding_x y += (self.text_height + self.padding_y) self.w.y_label = TextBox( (x, y + 5, self.column_1, self.text_height), "y", sizeStyle=self.size_style) x += self.column_1 self.w.y_slider = Slider( (x, y, self.column_2, self.text_height), value=0, maxValue=self._yMax, minValue=self._yMin, callback=self.slide_callback, sizeStyle=self.size_style) x += (self.column_2 + self.padding_x) self.w.button_restore_y = SquareButton( (x, y, self.button_width, self.text_height), "reset y", callback=self.restore_y_callback, sizeStyle=self.size_style) # open self.w.open() self.update_font() # callbacks def restore_x(self): self._moveX = 0 self.w.x_slider.set(self._moveX) def restore_y(self): self._moveY = 0 self.w.y_slider.set(self._moveY) def restore_x_callback(self, sender): self.restore_x() def restore_y_callback(self, sender): self.restore_y() def update_font(self): self.font = CurrentFont() if self.font is not None: self.w.box.text.set(get_full_name(self.font)) self.set_defaults() self.restore_x() self.restore_y() else: print no_font_open def set_defaults(self): self._xMax = self.font.info.unitsPerEm self._yMax = self.font.info.unitsPerEm / 2 self._xMin = -self._xMax self._yMin = -self._yMax def update_font_callback(self, sender): self.update_font() def slide_callback(self, sender): xValue = self.w.x_slider.get() yValue = self.w.y_slider.get() x = self._moveX - xValue y = self._moveY - yValue self._moveX = xValue self._moveY = yValue glyph_names = get_glyphs(self.font) if len(glyph_names) > 0: for glyph_name in glyph_names: # RF 2.0 if version[0] == '2': self.font[glyph_name].moveBy((-x, -y)) # RF 1.8.X else: self.font[glyph_name].move((-x, -y)) else: print no_glyph_selected

werobot/utils.py

lilac/WeRobot

387

# -*- coding: utf-8 -*- from __future__ import absolute_import, unicode_literals import io import json import os import random import re import string import time from functools import wraps from hashlib import sha1 import six try: from secrets import choice except ImportError: from random import choice string_types = (six.string_types, six.text_type, six.binary_type) re_type = type(re.compile("regex_test")) def get_signature(token, timestamp, nonce, *args): sign = [token, timestamp, nonce] + list(args) sign.sort() sign = to_binary(''.join(sign)) return sha1(sign).hexdigest() def check_signature(token, timestamp, nonce, signature): if not (token and timestamp and nonce and signature): return False sign = get_signature(token, timestamp, nonce) return sign == signature def check_token(token): return re.match('^[A-Za-z0-9]{3,32}$', token) def cached_property(method): prop_name = '_{}'.format(method.__name__) @wraps(method) def wrapped_func(self, *args, **kwargs): if not hasattr(self, prop_name): setattr(self, prop_name, method(self, *args, **kwargs)) return getattr(self, prop_name) return property(wrapped_func) def to_text(value, encoding="utf-8"): if isinstance(value, six.text_type): return value if isinstance(value, six.binary_type): return value.decode(encoding) return six.text_type(value) def to_binary(value, encoding="utf-8"): if isinstance(value, six.binary_type): return value if isinstance(value, six.text_type): return value.encode(encoding) return six.binary_type(value) def is_string(value): return isinstance(value, string_types) def byte2int(s, index=0): """Get the ASCII int value of a character in a string. :param s: a string :param index: the position of desired character :return: ASCII int value """ if six.PY2: return ord(s[index]) return s[index] def generate_token(length=''): if not length: length = random.randint(3, 32) length = int(length) assert 3 <= length <= 32 letters = string.ascii_letters + string.digits return ''.join(choice(letters) for _ in range(length)) def json_loads(s): s = to_text(s) return json.loads(s) def json_dumps(d): return json.dumps(d) def pay_sign_dict( appid, pay_sign_key, add_noncestr=True, add_timestamp=True, add_appid=True, **kwargs ): """ 支付参数签名 """ assert pay_sign_key, "PAY SIGN KEY IS EMPTY" if add_appid: kwargs.update({'appid': appid}) if add_noncestr: kwargs.update({'noncestr': generate_token()}) if add_timestamp: kwargs.update({'timestamp': int(time.time())}) params = kwargs.items() _params = [ (k.lower(), v) for k, v in kwargs.items() if k.lower() != "appid" ] _params += [('appid', appid), ('appkey', pay_sign_key)] _params.sort() sign = '&'.join(["%s=%s" % (str(p[0]), str(p[1])) for p in _params]).encode("utf-8") sign = sha1(sign).hexdigest() sign_type = 'SHA1' return dict(params), sign, sign_type def make_error_page(url): with io.open( os.path.join(os.path.dirname(__file__), 'contrib/error.html'), 'r', encoding='utf-8' ) as error_page: return error_page.read().replace('{url}', url) def is_regex(value): return isinstance(value, re_type)

tensorflow/python/ops/standard_ops.py

ashutom/tensorflow-upstream

388

# Copyright 2015 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== # pylint: disable=unused-import """Import names of Tensor Flow standard Ops.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import platform as _platform import sys as _sys from tensorflow.python import autograph from tensorflow.python.training.experimental import loss_scaling_gradient_tape # pylint: disable=g-bad-import-order # Imports the following modules so that @RegisterGradient get executed. from tensorflow.python.ops import array_grad from tensorflow.python.ops import cudnn_rnn_grad from tensorflow.python.ops import data_flow_grad from tensorflow.python.ops import manip_grad from tensorflow.python.ops import math_grad from tensorflow.python.ops import random_grad from tensorflow.python.ops import rnn_grad from tensorflow.python.ops import sparse_grad from tensorflow.python.ops import state_grad from tensorflow.python.ops import tensor_array_grad # go/tf-wildcard-import # pylint: disable=wildcard-import from tensorflow.python.ops.array_ops import * # pylint: disable=redefined-builtin from tensorflow.python.ops.check_ops import * from tensorflow.python.ops.clip_ops import * from tensorflow.python.ops.special_math_ops import * # TODO(vrv): Switch to import * once we're okay with exposing the module. from tensorflow.python.ops.confusion_matrix import confusion_matrix from tensorflow.python.ops.control_flow_ops import Assert from tensorflow.python.ops.control_flow_ops import case from tensorflow.python.ops.control_flow_ops import cond from tensorflow.python.ops.control_flow_ops import group from tensorflow.python.ops.control_flow_ops import no_op from tensorflow.python.ops.control_flow_ops import tuple # pylint: disable=redefined-builtin # pylint: enable=redefined-builtin from tensorflow.python.eager import wrap_function from tensorflow.python.ops.control_flow_ops import while_loop from tensorflow.python.ops.batch_ops import * from tensorflow.python.ops.critical_section_ops import * from tensorflow.python.ops.data_flow_ops import * from tensorflow.python.ops.functional_ops import * from tensorflow.python.ops.gradients import * from tensorflow.python.ops.histogram_ops import * from tensorflow.python.ops.init_ops import * from tensorflow.python.ops.io_ops import * from tensorflow.python.ops.linalg_ops import * from tensorflow.python.ops.logging_ops import Print from tensorflow.python.ops.logging_ops import get_summary_op from tensorflow.python.ops.logging_ops import timestamp from tensorflow.python.ops.lookup_ops import initialize_all_tables from tensorflow.python.ops.lookup_ops import tables_initializer from tensorflow.python.ops.manip_ops import * from tensorflow.python.ops.math_ops import * # pylint: disable=redefined-builtin from tensorflow.python.ops.numerics import * from tensorflow.python.ops.parsing_ops import * from tensorflow.python.ops.partitioned_variables import * from tensorflow.python.ops.proto_ops import * from tensorflow.python.ops.ragged import ragged_dispatch as _ragged_dispatch from tensorflow.python.ops.ragged import ragged_operators as _ragged_operators from tensorflow.python.ops.random_ops import * from tensorflow.python.ops.script_ops import py_func from tensorflow.python.ops.session_ops import * from tensorflow.python.ops.sort_ops import * from tensorflow.python.ops.sparse_ops import * from tensorflow.python.ops.state_ops import assign from tensorflow.python.ops.state_ops import assign_add from tensorflow.python.ops.state_ops import assign_sub from tensorflow.python.ops.state_ops import count_up_to from tensorflow.python.ops.state_ops import scatter_add from tensorflow.python.ops.state_ops import scatter_div from tensorflow.python.ops.state_ops import scatter_mul from tensorflow.python.ops.state_ops import scatter_sub from tensorflow.python.ops.state_ops import scatter_min from tensorflow.python.ops.state_ops import scatter_max from tensorflow.python.ops.state_ops import scatter_update from tensorflow.python.ops.state_ops import scatter_nd_add from tensorflow.python.ops.state_ops import scatter_nd_sub # TODO(simister): Re-enable once binary size increase due to scatter_nd # ops is under control. # from tensorflow.python.ops.state_ops import scatter_nd_mul # from tensorflow.python.ops.state_ops import scatter_nd_div from tensorflow.python.ops.state_ops import scatter_nd_update from tensorflow.python.ops.stateless_random_ops import * from tensorflow.python.ops.string_ops import * from tensorflow.python.ops.template import * from tensorflow.python.ops.tensor_array_ops import * from tensorflow.python.ops.variable_scope import * # pylint: disable=redefined-builtin from tensorflow.python.ops.variables import * from tensorflow.python.ops.parallel_for.control_flow_ops import vectorized_map # pylint: disable=g-import-not-at-top if _platform.system() == "Windows": from tensorflow.python.compiler.tensorrt import trt_convert_windows as trt else: from tensorflow.python.compiler.tensorrt import trt_convert as trt # pylint: enable=g-import-not-at-top # pylint: enable=wildcard-import # pylint: enable=g-bad-import-order # These modules were imported to set up RaggedTensor operators and dispatchers: del _ragged_dispatch, _ragged_operators

src/tango_scaling_test/TestDeviceServer/__main__.py

rtobar/sdp-prototype

389

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """Test Tango device server for use with scaling tests.""" import sys import time import argparse import tango from tango.server import run from TestDevice import TestDevice def init_callback(): """Report server start up times. This callback is executed post server initialisation. """ # pylint: disable=global-statement global START_TIME db = tango.Database() elapsed = time.time() - START_TIME list_devices() exported_devices = list(db.get_device_exported('test/*')) num_devices = len(exported_devices) file = open('results.txt', 'a') file.write(',{},{}\n'.format(elapsed, elapsed / num_devices)) print('>> Time taken to start devices: {:.4f} s ({:.4f} s/dev)' .format(elapsed, elapsed / num_devices)) def delete_server(): """Delete the TestDeviceServer from the tango db.""" db = tango.Database() db.set_timeout_millis(50000) server = 'TestDeviceServer/1' server_list = list(db.get_server_list(server)) if server in server_list: start_time = time.time() db.delete_server('TestDeviceServer/1') print('- Delete server: {:.4f} s'.format(time.time() - start_time)) def register(num_devices): """Register devices in the tango db.""" db = tango.Database() device_info = tango.DbDevInfo() device_info.server = 'TestDeviceServer/1' # pylint: disable=protected-access device_info._class = 'TestDevice' start_time = time.time() for device_id in range(num_devices): device_info.name = 'test/test_device/{:05d}'.format(device_id) db.add_device(device_info) elapsed = time.time() - start_time file = open('results.txt', 'a') file.write('{},{},{}'.format(num_devices, elapsed, elapsed/num_devices)) print('- Register devices: {:.4f} s ({:.4f} s/device)' .format(elapsed, elapsed / num_devices)) def list_devices(): """List tango devices associated with the TestDeviceServer.""" db = tango.Database() server_instance = 'TestDeviceServer/1' device_class = 'TestDevice' devices = list(db.get_device_name(server_instance, device_class)) print('- No. registered devices: {}'.format(len(devices))) exported_devices = list(db.get_device_exported('test/*')) print('- No. running devices: {}'.format(len(exported_devices))) def main(args=None, **kwargs): """Run (start) the device server.""" run([TestDevice], verbose=True, msg_stream=sys.stdout, post_init_callback=init_callback, raises=False, args=args, **kwargs) if __name__ == '__main__': PARSER = argparse.ArgumentParser(description='Device registration time.') PARSER.add_argument('num_devices', metavar='N', type=int, default=1, nargs='?', help='Number of devices to start.') ARGS = PARSER.parse_args() delete_server() time.sleep(0.5) list_devices() print('* Registering {} devices'.format(ARGS.num_devices)) register(ARGS.num_devices) list_devices() print('* Starting server ...') sys.argv = ['TestDeviceServer', '1', '-v4'] START_TIME = time.time() main()

test/test_pipeline.py

ParikhKadam/haystack

390

from pathlib import Path import pytest from haystack.document_store.elasticsearch import ElasticsearchDocumentStore from haystack.pipeline import TranslationWrapperPipeline, JoinDocuments, ExtractiveQAPipeline, Pipeline, FAQPipeline, \ DocumentSearchPipeline, RootNode from haystack.retriever.dense import DensePassageRetriever from haystack.retriever.sparse import ElasticsearchRetriever @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True) def test_load_yaml(document_store_with_docs): # test correct load of indexing pipeline from yaml pipeline = Pipeline.load_from_yaml(Path("samples/pipeline/test_pipeline.yaml"), pipeline_name="indexing_pipeline") pipeline.run(file_path=Path("samples/pdf/sample_pdf_1.pdf"), top_k_retriever=10, top_k_reader=3) # test correct load of query pipeline from yaml pipeline = Pipeline.load_from_yaml(Path("samples/pipeline/test_pipeline.yaml"), pipeline_name="query_pipeline") prediction = pipeline.run(query="Who made the PDF specification?", top_k_retriever=10, top_k_reader=3) assert prediction["query"] == "Who made the PDF specification?" assert prediction["answers"][0]["answer"] == "Adobe Systems" # test invalid pipeline name with pytest.raises(Exception): Pipeline.load_from_yaml(path=Path("samples/pipeline/test_pipeline.yaml"), pipeline_name="invalid") @pytest.mark.slow @pytest.mark.elasticsearch @pytest.mark.parametrize( "retriever_with_docs, document_store_with_docs", [("elasticsearch", "elasticsearch")], indirect=True ) def test_graph_creation(reader, retriever_with_docs, document_store_with_docs): pipeline = Pipeline() pipeline.add_node(name="ES", component=retriever_with_docs, inputs=["Query"]) with pytest.raises(AssertionError): pipeline.add_node(name="Reader", component=retriever_with_docs, inputs=["ES.output_2"]) with pytest.raises(AssertionError): pipeline.add_node(name="Reader", component=retriever_with_docs, inputs=["ES.wrong_edge_label"]) with pytest.raises(Exception): pipeline.add_node(name="Reader", component=retriever_with_docs, inputs=["InvalidNode"]) with pytest.raises(Exception): pipeline = Pipeline() pipeline.add_node(name="ES", component=retriever_with_docs, inputs=["InvalidNode"]) @pytest.mark.slow @pytest.mark.elasticsearch @pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True) def test_extractive_qa_answers(reader, retriever_with_docs): pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs) prediction = pipeline.run(query="Who lives in Berlin?", top_k_retriever=10, top_k_reader=3) assert prediction is not None assert prediction["query"] == "Who lives in Berlin?" assert prediction["answers"][0]["answer"] == "Carla" assert prediction["answers"][0]["probability"] <= 1 assert prediction["answers"][0]["probability"] >= 0 assert prediction["answers"][0]["meta"]["meta_field"] == "test1" assert prediction["answers"][0]["context"] == "My name is Carla and I live in Berlin" assert len(prediction["answers"]) == 3 @pytest.mark.elasticsearch @pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True) def test_extractive_qa_offsets(reader, retriever_with_docs): pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs) prediction = pipeline.run(query="Who lives in Berlin?", top_k_retriever=10, top_k_reader=5) assert prediction["answers"][0]["offset_start"] == 11 assert prediction["answers"][0]["offset_end"] == 16 start = prediction["answers"][0]["offset_start"] end = prediction["answers"][0]["offset_end"] assert prediction["answers"][0]["context"][start:end] == prediction["answers"][0]["answer"] @pytest.mark.slow @pytest.mark.elasticsearch @pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True) def test_extractive_qa_answers_single_result(reader, retriever_with_docs): pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs) query = "testing finder" prediction = pipeline.run(query=query, top_k_retriever=1, top_k_reader=1) assert prediction is not None assert len(prediction["answers"]) == 1 @pytest.mark.elasticsearch @pytest.mark.parametrize( "retriever,document_store", [("embedding", "memory"), ("embedding", "faiss"), ("embedding", "milvus"), ("embedding", "elasticsearch")], indirect=True, ) def test_faq_pipeline(retriever, document_store): documents = [ {"text": "How to test module-1?", 'meta': {"source": "wiki1", "answer": "Using tests for module-1"}}, {"text": "How to test module-2?", 'meta': {"source": "wiki2", "answer": "Using tests for module-2"}}, {"text": "How to test module-3?", 'meta': {"source": "wiki3", "answer": "Using tests for module-3"}}, {"text": "How to test module-4?", 'meta': {"source": "wiki4", "answer": "Using tests for module-4"}}, {"text": "How to test module-5?", 'meta': {"source": "wiki5", "answer": "Using tests for module-5"}}, ] document_store.write_documents(documents) document_store.update_embeddings(retriever) pipeline = FAQPipeline(retriever=retriever) output = pipeline.run(query="How to test this?", top_k_retriever=3) assert len(output["answers"]) == 3 assert output["answers"][0]["query"].startswith("How to") assert output["answers"][0]["answer"].startswith("Using tests") if isinstance(document_store, ElasticsearchDocumentStore): output = pipeline.run(query="How to test this?", filters={"source": ["wiki2"]}, top_k_retriever=5) assert len(output["answers"]) == 1 @pytest.mark.elasticsearch @pytest.mark.parametrize( "retriever,document_store", [("embedding", "memory"), ("embedding", "faiss"), ("embedding", "milvus"), ("embedding", "elasticsearch")], indirect=True, ) def test_document_search_pipeline(retriever, document_store): documents = [ {"text": "Sample text for document-1", 'meta': {"source": "wiki1"}}, {"text": "Sample text for document-2", 'meta': {"source": "wiki2"}}, {"text": "Sample text for document-3", 'meta': {"source": "wiki3"}}, {"text": "Sample text for document-4", 'meta': {"source": "wiki4"}}, {"text": "Sample text for document-5", 'meta': {"source": "wiki5"}}, ] document_store.write_documents(documents) document_store.update_embeddings(retriever) pipeline = DocumentSearchPipeline(retriever=retriever) output = pipeline.run(query="How to test this?", top_k_retriever=4) assert len(output.get('documents', [])) == 4 if isinstance(document_store, ElasticsearchDocumentStore): output = pipeline.run(query="How to test this?", filters={"source": ["wiki2"]}, top_k_retriever=5) assert len(output["documents"]) == 1 @pytest.mark.slow @pytest.mark.elasticsearch @pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True) def test_extractive_qa_answers_with_translator(reader, retriever_with_docs, en_to_de_translator, de_to_en_translator): base_pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs) pipeline = TranslationWrapperPipeline( input_translator=de_to_en_translator, output_translator=en_to_de_translator, pipeline=base_pipeline ) prediction = pipeline.run(query="Wer lebt in Berlin?", top_k_retriever=10, top_k_reader=3) assert prediction is not None assert prediction["query"] == "Wer lebt in Berlin?" assert "Carla" in prediction["answers"][0]["answer"] assert prediction["answers"][0]["probability"] <= 1 assert prediction["answers"][0]["probability"] >= 0 assert prediction["answers"][0]["meta"]["meta_field"] == "test1" assert prediction["answers"][0]["context"] == "My name is Carla and I live in Berlin" @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True) @pytest.mark.parametrize("reader", ["farm"], indirect=True) def test_join_document_pipeline(document_store_with_docs, reader): es = ElasticsearchRetriever(document_store=document_store_with_docs) dpr = DensePassageRetriever( document_store=document_store_with_docs, query_embedding_model="facebook/dpr-question_encoder-single-nq-base", passage_embedding_model="facebook/dpr-ctx_encoder-single-nq-base", use_gpu=False, ) document_store_with_docs.update_embeddings(dpr) query = "Where does Carla lives?" # test merge without weights join_node = JoinDocuments(join_mode="merge") p = Pipeline() p.add_node(component=es, name="R1", inputs=["Query"]) p.add_node(component=dpr, name="R2", inputs=["Query"]) p.add_node(component=join_node, name="Join", inputs=["R1", "R2"]) results = p.run(query=query) assert len(results["documents"]) == 3 # test merge with weights join_node = JoinDocuments(join_mode="merge", weights=[1000, 1], top_k_join=2) p = Pipeline() p.add_node(component=es, name="R1", inputs=["Query"]) p.add_node(component=dpr, name="R2", inputs=["Query"]) p.add_node(component=join_node, name="Join", inputs=["R1", "R2"]) results = p.run(query=query) assert results["documents"][0].score > 1000 assert len(results["documents"]) == 2 # test concatenate join_node = JoinDocuments(join_mode="concatenate") p = Pipeline() p.add_node(component=es, name="R1", inputs=["Query"]) p.add_node(component=dpr, name="R2", inputs=["Query"]) p.add_node(component=join_node, name="Join", inputs=["R1", "R2"]) results = p.run(query=query) assert len(results["documents"]) == 3 # test join_node with reader join_node = JoinDocuments() p = Pipeline() p.add_node(component=es, name="R1", inputs=["Query"]) p.add_node(component=dpr, name="R2", inputs=["Query"]) p.add_node(component=join_node, name="Join", inputs=["R1", "R2"]) p.add_node(component=reader, name="Reader", inputs=["Join"]) results = p.run(query=query) assert results["answers"][0]["answer"] == "Berlin" def test_parallel_paths_in_pipeline_graph(): class A(RootNode): def run(self, **kwargs): kwargs["output"] = "A" return kwargs, "output_1" class B(RootNode): def run(self, **kwargs): kwargs["output"] += "B" return kwargs, "output_1" class C(RootNode): def run(self, **kwargs): kwargs["output"] += "C" return kwargs, "output_1" class D(RootNode): def run(self, **kwargs): kwargs["output"] += "D" return kwargs, "output_1" class E(RootNode): def run(self, **kwargs): kwargs["output"] += "E" return kwargs, "output_1" class JoinNode(RootNode): def run(self, **kwargs): kwargs["output"] = kwargs["inputs"][0]["output"] + kwargs["inputs"][1]["output"] return kwargs, "output_1" pipeline = Pipeline() pipeline.add_node(name="A", component=A(), inputs=["Query"]) pipeline.add_node(name="B", component=B(), inputs=["A"]) pipeline.add_node(name="C", component=C(), inputs=["B"]) pipeline.add_node(name="E", component=E(), inputs=["C"]) pipeline.add_node(name="D", component=D(), inputs=["B"]) pipeline.add_node(name="F", component=JoinNode(), inputs=["D", "E"]) output = pipeline.run(query="test") assert output["output"] == "ABDABCE" pipeline = Pipeline() pipeline.add_node(name="A", component=A(), inputs=["Query"]) pipeline.add_node(name="B", component=B(), inputs=["A"]) pipeline.add_node(name="C", component=C(), inputs=["B"]) pipeline.add_node(name="D", component=D(), inputs=["B"]) pipeline.add_node(name="E", component=JoinNode(), inputs=["C", "D"]) output = pipeline.run(query="test") assert output["output"] == "ABCABD" def test_parallel_paths_in_pipeline_graph_with_branching(): class AWithOutput1(RootNode): outgoing_edges = 2 def run(self, **kwargs): kwargs["output"] = "A" return kwargs, "output_1" class AWithOutput2(RootNode): outgoing_edges = 2 def run(self, **kwargs): kwargs["output"] = "A" return kwargs, "output_2" class AWithOutputAll(RootNode): outgoing_edges = 2 def run(self, **kwargs): kwargs["output"] = "A" return kwargs, "output_all" class B(RootNode): def run(self, **kwargs): kwargs["output"] += "B" return kwargs, "output_1" class C(RootNode): def run(self, **kwargs): kwargs["output"] += "C" return kwargs, "output_1" class D(RootNode): def run(self, **kwargs): kwargs["output"] += "D" return kwargs, "output_1" class E(RootNode): def run(self, **kwargs): kwargs["output"] += "E" return kwargs, "output_1" class JoinNode(RootNode): def run(self, **kwargs): if kwargs.get("inputs"): kwargs["output"] = "" for input_dict in kwargs["inputs"]: kwargs["output"] += (input_dict["output"]) return kwargs, "output_1" pipeline = Pipeline() pipeline.add_node(name="A", component=AWithOutput1(), inputs=["Query"]) pipeline.add_node(name="B", component=B(), inputs=["A.output_1"]) pipeline.add_node(name="C", component=C(), inputs=["A.output_2"]) pipeline.add_node(name="D", component=E(), inputs=["B"]) pipeline.add_node(name="E", component=D(), inputs=["B"]) pipeline.add_node(name="F", component=JoinNode(), inputs=["D", "E", "C"]) output = pipeline.run(query="test") assert output["output"] == "ABEABD" pipeline = Pipeline() pipeline.add_node(name="A", component=AWithOutput2(), inputs=["Query"]) pipeline.add_node(name="B", component=B(), inputs=["A.output_1"]) pipeline.add_node(name="C", component=C(), inputs=["A.output_2"]) pipeline.add_node(name="D", component=E(), inputs=["B"]) pipeline.add_node(name="E", component=D(), inputs=["B"]) pipeline.add_node(name="F", component=JoinNode(), inputs=["D", "E", "C"]) output = pipeline.run(query="test") assert output["output"] == "AC" pipeline = Pipeline() pipeline.add_node(name="A", component=AWithOutputAll(), inputs=["Query"]) pipeline.add_node(name="B", component=B(), inputs=["A.output_1"]) pipeline.add_node(name="C", component=C(), inputs=["A.output_2"]) pipeline.add_node(name="D", component=E(), inputs=["B"]) pipeline.add_node(name="E", component=D(), inputs=["B"]) pipeline.add_node(name="F", component=JoinNode(), inputs=["D", "E", "C"]) output = pipeline.run(query="test") assert output["output"] == "ACABEABD"

src/telr/TELR_assembly.py

dominik-handler/TELR

391

<gh_stars>10-100 import sys import os import subprocess import shutil import time import logging from Bio import SeqIO from multiprocessing import Pool import pysam from telr.TELR_utility import mkdir, check_exist, format_time def get_local_contigs( assembler, polisher, contig_dir, vcf_parsed, out, sample_name, bam, raw_reads, thread, presets, polish_iterations, ): """Perform local assembly using reads from parsed VCF file in parallel""" # Prepare reads used for local assembly and polishing sv_reads_dir = os.path.join(out, "sv_reads") try: prep_assembly_inputs( vcf_parsed, out, sample_name, bam, raw_reads, sv_reads_dir, read_type="sv" ) except Exception as e: print(e) print("Prepare local assembly input data failed, exiting...") sys.exit(1) mkdir(contig_dir) k = 0 asm_pa_list = [] with open(vcf_parsed, "r") as input: for line in input: entry = line.replace("\n", "").split("\t") contig_name = "_".join([entry[0], entry[1], entry[2]]) # rename variant reads sv_reads = sv_reads_dir + "/contig" + str(k) sv_reads_rename = sv_reads_dir + "/" + contig_name + ".reads.fa" os.rename(sv_reads, sv_reads_rename) thread_asm = 1 asm_pa = [ sv_reads_rename, contig_dir, contig_name, thread_asm, presets, assembler, polisher, polish_iterations, ] asm_pa_list.append(asm_pa) k = k + 1 # run assembly in parallel logging.info("Perform local assembly of non-reference TE loci...") start_time = time.time() try: pool = Pool(processes=thread) contig_list = pool.map(run_assembly_polishing, asm_pa_list) pool.close() pool.join() except Exception as e: print(e) print("Local assembly failed, exiting...") sys.exit(1) proc_time = time.time() - start_time # merge all contigs assembly_passed_loci = set() merged_contigs = os.path.join(out, sample_name + ".contigs.fa") with open(merged_contigs, "w") as merged_output_handle: for contig in contig_list: if check_exist(contig): contig_name = os.path.basename(contig).replace(".cns.fa", "") assembly_passed_loci.add(contig_name) parsed_contig = os.path.join(contig_dir, contig_name + ".cns.ctg1.fa") with open(contig, "r") as input: records = SeqIO.parse(input, "fasta") for record in records: if record.id == "ctg1" or record.id == "contig_1": record.id = contig_name record.description = "len=" + str(len(record.seq)) SeqIO.write(record, merged_output_handle, "fasta") with open(parsed_contig, "w") as parsed_output_handle: SeqIO.write(record, parsed_output_handle, "fasta") logging.info("Local assembly finished in " + format_time(proc_time)) return merged_contigs, assembly_passed_loci def run_assembly_polishing(args): reads = args[0] asm_dir = args[1] contig_name = args[2] thread = args[3] presets = args[4] assembler = args[5] polisher = args[6] polish_iterations = args[7] # run assembly if assembler == "wtdbg2": asm_cns = run_wtdbg2_assembly(reads, asm_dir, contig_name, thread, presets) else: asm_cns = run_flye_assembly(reads, asm_dir, contig_name, thread, presets) if not check_exist(asm_cns): print("assembly failed") return None # run polishing if polish_iterations > 0: if polisher == "wtdbg2": asm_cns = run_wtdbg2_polishing( asm_cns, reads, thread, polish_iterations, presets ) else: asm_cns = run_flye_polishing( asm_cns, reads, asm_dir, contig_name, thread, polish_iterations, presets ) if check_exist(asm_cns): return asm_cns else: return None def run_flye_polishing( asm_cns, reads, asm_dir, contig_name, thread, polish_iterations, presets ): """Run Flye polishing""" if presets == "pacbio": presets_flye = "--pacbio-raw" else: presets_flye = "--nano-raw" tmp_out_dir = os.path.join(asm_dir, contig_name) mkdir(tmp_out_dir) try: subprocess.call( [ "flye", "--polish-target", asm_cns, presets_flye, reads, "--out-dir", tmp_out_dir, "--thread", str(thread), "--iterations", str(polish_iterations), ] ) except Exception as e: print(e) print("Polishing failed, exiting...") return None # rename contig file polished_contig = os.path.join( tmp_out_dir, "polished_" + str(polish_iterations) + ".fasta" ) if check_exist(polished_contig): os.rename(polished_contig, asm_cns) shutil.rmtree(tmp_out_dir) return asm_cns else: return None def run_wtdbg2_polishing(asm_cns, reads, threads, polish_iterations, presets): """Run wtdbg2 polishing""" if presets == "pacbio": presets_minimap2 = "map-pb" else: presets_minimap2 = "map-ont" # polish consensus threads = str(min(threads, 4)) bam = asm_cns + ".bam" k = 0 while True: # align reads to contigs command = ( "minimap2 -t " + threads + " -ax " + presets_minimap2 + " -r2k " + asm_cns + " " + reads + " | samtools sort -@" + threads + " > " + bam ) try: subprocess.run( command, shell=True, timeout=300, stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT, ) except subprocess.TimeoutExpired: print("fail to map reads to contig: " + asm_cns) return # run wtpoa-cns to get polished contig cns_tmp = asm_cns + ".tmp" command = ( "samtools view -F0x900 " + bam + " | wtpoa-cns -t " + threads + " -d " + asm_cns + " -i - -fo " + cns_tmp ) try: subprocess.run( command, shell=True, timeout=300, stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT, ) except subprocess.TimeoutExpired: print("fail to polish contig: " + asm_cns) return if check_exist(cns_tmp): os.rename(cns_tmp, asm_cns) os.remove(bam) else: break k = k + 1 if k >= polish_iterations: break if check_exist(asm_cns): return asm_cns else: print("polishing failed for " + asm_cns + "\n") return None def run_flye_assembly(sv_reads, asm_dir, contig_name, thread, presets): """Run Flye assembly""" if presets == "pacbio": presets_flye = "--pacbio-raw" else: presets_flye = "--nano-raw" tmp_out_dir = os.path.join(asm_dir, contig_name) mkdir(tmp_out_dir) try: subprocess.call( [ "flye", presets_flye, sv_reads, "--out-dir", tmp_out_dir, "--thread", str(thread), "--iterations", "0", ] ) except Exception as e: print(e) print("Assembly failed, exiting...") return # rename contigs contig_path = os.path.join(tmp_out_dir, "assembly.fasta") contig_path_new = os.path.join(asm_dir, contig_name + ".cns.fa") if check_exist(contig_path): os.rename(contig_path, contig_path_new) # remove tmp files shutil.rmtree(tmp_out_dir) return contig_path_new else: print("assembly failed") return None def run_wtdbg2_assembly(sv_reads, asm_dir, contig_name, thread, presets): """Run wtdbg2 assembly""" if presets == "pacbio": presets_wtdbg2 = "rs" else: presets_wtdbg2 = "ont" prefix = sv_reads.replace(".reads.fa", "") try: subprocess.run( [ "wtdbg2", "-x", presets_wtdbg2, "-q", "-AS", "1", "-g", "30k", "-t", str(thread), "-i", sv_reads, "-fo", prefix, ], timeout=300, ) except subprocess.TimeoutExpired: print("fail to build contig layout for contig: " + contig_name) return except Exception as e: print(e) print("wtdbg2 failed, exiting...") return None # derive consensus contig_layout = prefix + ".ctg.lay.gz" if check_exist(contig_layout): cns_thread = str(min(thread, 4)) consensus = prefix + ".cns.fa" try: subprocess.run( [ "wtpoa-cns", "-q", "-t", cns_thread, "-i", contig_layout, "-fo", consensus, ], timeout=300, ) except subprocess.TimeoutExpired: print("fail to assemble contig: " + contig_name) return None if check_exist(consensus): consensus_rename = os.path.join(asm_dir, contig_name + ".cns.fa") os.rename(consensus, consensus_rename) return consensus_rename else: return None def prep_assembly_inputs( vcf_parsed, out, sample_name, bam, raw_reads, reads_dir, read_type="sv" ): """Prepare reads for local assembly""" # logging.info("Prepare reads for local assembly") if read_type == "sv": # TODO: figure out what this does # extract read IDs read_ids = os.path.join(out, sample_name + ".id") with open(vcf_parsed, "r") as input, open(read_ids, "w") as output: for line in input: entry = line.replace("\n", "").split("\t") read_list = entry[8].split(",") for read in read_list: output.write(read + "\n") else: # TODO: think about using this for assembly, filter for cigar reads window = 1000 samfile = pysam.AlignmentFile(bam, "rb") read_ids = os.path.join(out, sample_name + ".id") vcf_parsed_new = vcf_parsed + ".new" with open(vcf_parsed, "r") as input, open(read_ids, "w") as output, open( vcf_parsed_new, "w" ) as VCF: for line in input: entry = line.replace("\n", "").split("\t") # get sniffles read list read_list = entry[8].split(",") reads_sniffles = set(read_list) ins_chr = entry[0] ins_breakpoint = round((int(entry[1]) + int(entry[2])) / 2) start = ins_breakpoint - window end = ins_breakpoint + window reads = set() # coverage = 0 for read in samfile.fetch(ins_chr, start, end): reads.add(read.query_name) for read in reads: output.write(read + "\n") # write out_line = line.replace("\n", "") + "\t" + str(len(reads)) VCF.write(out_line + "\n") vcf_parsed = vcf_parsed_new # generate unique ID list read_ids_unique = read_ids + ".unique" command = "cat " + read_ids + " | sort | uniq" with open(read_ids_unique, "w") as output: subprocess.call(command, stdout=output, shell=True) # filter raw reads using read list subset_fa = os.path.join(out, sample_name + ".subset.fa") command = "seqtk subseq " + raw_reads + " " + read_ids_unique + " | seqtk seq -a" with open(subset_fa, "w") as output: subprocess.call(command, stdout=output, shell=True) # reorder reads subset_fa_reorder = out + "/" + sample_name + ".subset.reorder.fa" extract_reads(subset_fa, read_ids, subset_fa_reorder) # separate reads into multiple files, using csplit mkdir(reads_dir) csplit_prefix = reads_dir + "/contig" m = [] k = 1 with open(vcf_parsed, "r") as input: for line in input: entry = line.replace("\n", "").split("\t") if read_type == "sv": k = k + 2 * (len(entry[8].split(","))) else: k = k + 2 * int(entry[14]) m.append(k) if len(m) == 1: subprocess.call(["cp", subset_fa_reorder, reads_dir + "/contig0"]) elif len(m) == 0: print("No insertion detected, exiting...") else: m = m[:-1] index = " ".join(str(i) for i in m) command = ( "csplit -s -f " + csplit_prefix + " -n 1 " + subset_fa_reorder + " " + index ) subprocess.call(command, shell=True) # remove tmp files os.remove(read_ids) os.remove(read_ids_unique) os.remove(subset_fa) os.remove(subset_fa_reorder) def extract_reads(reads, list, out): """Extract reads from fasta using read ID list""" record_dict = SeqIO.index(reads, "fasta") with open(out, "wb") as output_handle, open(list, "r") as ID: for entry in ID: entry = entry.replace("\n", "") output_handle.write(record_dict.get_raw(entry))

pygmt/tests/test_clib.py

aliciaha1997/pygmt

392

# pylint: disable=protected-access """ Test the wrappers for the C API. """ import os from contextlib import contextmanager import numpy as np import numpy.testing as npt import pandas as pd import pytest import xarray as xr from packaging.version import Version from pygmt import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), "data") with clib.Session() as _lib: gmt_version = Version(_lib.info["version"]) @contextmanager def mock(session, func, returns=None, mock_func=None): """ Mock a GMT C API function to make it always return a given value. Used to test that exceptions are raised when API functions fail by producing a NULL pointer as output or non-zero status codes. Needed because it's not easy to get some API functions to fail without inducing a Segmentation Fault (which is a good thing because libgmt usually only fails with errors). """ if mock_func is None: def mock_api_function(*args): # pylint: disable=unused-argument """ A mock GMT API function that always returns a given value. """ return returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): """ Return our mock function. """ if name == func: return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, "get_libgmt_func", mock_get_libgmt_func) yield setattr(session, "get_libgmt_func", get_libgmt_func) def test_getitem(): """ Test that I can get correct constants from the C lib. """ ses = clib.Session() assert ses["GMT_SESSION_EXTERNAL"] != -99999 assert ses["GMT_MODULE_CMD"] != -99999 assert ses["GMT_PAD_DEFAULT"] != -99999 assert ses["GMT_DOUBLE"] != -99999 with pytest.raises(GMTCLibError): ses["A_WHOLE_LOT_OF_JUNK"] # pylint: disable=pointless-statement def test_create_destroy_session(): """ Test that create and destroy session are called without errors. """ # Create two session and make sure they are not pointing to the same memory session1 = clib.Session() session1.create(name="test_session1") assert session1.session_pointer is not None session2 = clib.Session() session2.create(name="test_session2") assert session2.session_pointer is not None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create and destroy a session twice ses = clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create("session1") assert ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): """ Check that an exception is raised when failing to create a session. """ ses = clib.Session() with mock(ses, "GMT_Create_Session", returns=None): with pytest.raises(GMTCLibError): ses.create("test-session-name") # Should fail if trying to create a session before destroying the old one. ses.create("test1") with pytest.raises(GMTCLibError): ses.create("test2") def test_destroy_session_fails(): """ Fail to destroy session when given bad input. """ ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create("test-session") with mock(ses, "GMT_Destroy_Session", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): """ Run a command to see if call_module works. """ data_fname = os.path.join(TEST_DATA_DIR, "points.txt") out_fname = "test_call_module.txt" with clib.Session() as lib: with GMTTempFile() as out_fname: lib.call_module("info", "{} -C ->{}".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output == "11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338" def test_call_module_invalid_arguments(): """ Fails for invalid module arguments. """ with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module("info", "bogus-data.bla") def test_call_module_invalid_name(): """ Fails when given bad input. """ with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module("meh", "") def test_call_module_error_message(): """ Check is the GMT error message was captured. """ with clib.Session() as lib: try: lib.call_module("info", "bogus-data.bla") except GMTCLibError as error: assert "Module 'info' failed with status code" in str(error) assert "gmtinfo [ERROR]: Cannot find file bogus-data.bla" in str(error) def test_method_no_session(): """ Fails when not in a session. """ # Create an instance of Session without "with" so no session is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module("gmtdefaults", "") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): """ Parsing a single family argument correctly. """ lib = clib.Session() for family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite(): """ Parsing a composite constant argument (separated by |) correctly. """ lib = clib.Session() test_cases = ((family, via) for family in FAMILIES for via in VIAS) for family, via in test_cases: composite = "|".join([family, via]) expected = lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails(): """ Check if the function fails when given bad input. """ lib = clib.Session() test_cases = [ "SOME_random_STRING", "GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR", "GMT_IS_DATASET|NOT_A_PROPER_VIA", "NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX", "NOT_A_PROPER_FAMILY|ALSO_INVALID", ] for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if not given valid modifiers but is using them anyway. # This should work... lib._parse_constant( "GMT_IS_DATASET|GMT_VIA_MATRIX", valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( "GMT_IS_DATASET|GMT_VIA_MATRIX", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): """ Run the function to make sure it doesn't fail badly. """ with clib.Session() as lib: # Dataset from vectors data_vector = lib.create_data( family="GMT_IS_DATASET|GMT_VIA_VECTOR", geometry="GMT_IS_POINT", mode="GMT_CONTAINER_ONLY", dim=[10, 20, 1, 0], # columns, rows, layers, dtype ) # Dataset from matrices data_matrix = lib.create_data( family="GMT_IS_DATASET|GMT_VIA_MATRIX", geometry="GMT_IS_POINT", mode="GMT_CONTAINER_ONLY", dim=[10, 20, 1, 0], ) assert data_vector != data_matrix def test_create_data_grid_dim(): """ Create a grid ignoring range and inc. """ with clib.Session() as lib: # Grids from matrices using dim lib.create_data( family="GMT_IS_GRID|GMT_VIA_MATRIX", geometry="GMT_IS_SURFACE", mode="GMT_CONTAINER_ONLY", dim=[10, 20, 1, 0], ) def test_create_data_grid_range(): """ Create a grid specifying range and inc instead of dim. """ with clib.Session() as lib: # Grids from matrices using range and int lib.create_data( family="GMT_IS_GRID|GMT_VIA_MATRIX", geometry="GMT_IS_SURFACE", mode="GMT_CONTAINER_ONLY", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): """ Check that create_data raises exceptions for invalid input and output. """ # Passing in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family="GMT_IS_DATASET", geometry="GMT_IS_SURFACE", mode="Not_a_valid_mode", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # Passing in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family="GMT_IS_GRID", geometry="Not_a_valid_geometry", mode="GMT_CONTAINER_ONLY", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # If the data pointer returned is None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib, "GMT_Create_Data", returns=None): lib.create_data( family="GMT_IS_DATASET", geometry="GMT_IS_SURFACE", mode="GMT_CONTAINER_ONLY", dim=[11, 10, 2, 0], ) def test_virtual_file(): """ Test passing in data via a virtual file with a Dataset. """ dtypes = "float32 float64 int32 int64 uint32 uint64".split() shape = (5, 3) for dtype in dtypes: with clib.Session() as lib: family = "GMT_IS_DATASET|GMT_VIA_MATRIX" geometry = "GMT_IS_POINT" dataset = lib.create_data( family=family, geometry=geometry, mode="GMT_CONTAINER_ONLY", dim=[shape[1], shape[0], 1, 0], # columns, rows, layers, dtype ) data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset to a virtual file and pass it along to gmt info vfargs = (family, geometry, "GMT_IN|GMT_IS_REFERENCE", dataset) with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile: lib.call_module("info", "{} ->{}".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = "\t".join( ["<{:.0f}/{:.0f}>".format(col.min(), col.max()) for col in data.T] ) expected = "<matrix memory>: N = {}\t{}\n".format(shape[0], bounds) assert output == expected def test_virtual_file_fails(): """ Check that opening and closing virtual files raises an exception for non- zero return codes. """ vfargs = ( "GMT_IS_DATASET|GMT_VIA_MATRIX", "GMT_IS_POINT", "GMT_IN|GMT_IS_REFERENCE", None, ) # Mock Open_VirtualFile to test the status check when entering the context. # If the exception is raised, the code won't get to the closing of the # virtual file. with clib.Session() as lib, mock(lib, "GMT_Open_VirtualFile", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print("Should not get to this code") # Test the status check when closing the virtual file # Mock the opening to return 0 (success) so that we don't open a file that # we won't close later. with clib.Session() as lib, mock(lib, "GMT_Open_VirtualFile", returns=0), mock( lib, "GMT_Close_VirtualFile", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print("Shouldn't get to this code either") def test_virtual_file_bad_direction(): """ Test passing an invalid direction argument. """ with clib.Session() as lib: vfargs = ( "GMT_IS_DATASET|GMT_VIA_MATRIX", "GMT_IS_POINT", "GMT_IS_GRID", # The invalid direction argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print("This should have failed") def test_virtualfile_from_vectors(): """ Test the automation for transforming vectors to virtual file dataset. """ dtypes = "float32 float64 int32 int64 uint32 uint64".split() size = 10 for dtype in dtypes: x = np.arange(size, dtype=dtype) y = np.arange(size, size * 2, 1, dtype=dtype) z = np.arange(size * 2, size * 3, 1, dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as outfile: lib.call_module("info", "{} ->{}".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = "\t".join( ["<{:.0f}/{:.0f}>".format(i.min(), i.max()) for i in (x, y, z)] ) expected = "<vector memory>: N = {}\t{}\n".format(size, bounds) assert output == expected @pytest.mark.parametrize("dtype", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): """ Test passing in one column with string or object dtype into virtual file dataset. """ size = 5 x = np.arange(size, dtype=np.int32) y = np.arange(size, size * 2, 1, dtype=np.int32) strings = np.array(["a", "bc", "defg", "hijklmn", "opqrst"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile() as outfile: lib.call_module("convert", f"{vfile} ->{outfile.name}") output = outfile.read(keep_tabs=True) expected = "".join(f"{i}\t{j}\t{k}\n" for i, j, k in zip(x, y, strings)) assert output == expected @pytest.mark.parametrize("dtype", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): """ Test passing in two columns of string or object dtype into virtual file dataset. """ size = 5 x = np.arange(size, dtype=np.int32) y = np.arange(size, size * 2, 1, dtype=np.int32) strings1 = np.array(["a", "bc", "def", "ghij", "klmno"], dtype=dtype) strings2 = np.array(["pqrst", "uvwx", "yz!", "@#", "$"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with GMTTempFile() as outfile: lib.call_module("convert", f"{vfile} ->{outfile.name}") output = outfile.read(keep_tabs=True) expected = "".join( f"{h}\t{i}\t{j} {k}\n" for h, i, j, k in zip(x, y, strings1, strings2) ) assert output == expected def test_virtualfile_from_vectors_transpose(): """ Test transforming matrix columns to virtual file dataset. """ dtypes = "float32 float64 int32 int64 uint32 uint64".split() shape = (7, 5) for dtype in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile: lib.call_module("info", "{} -C ->{}".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = "\t".join( ["{:.0f}\t{:.0f}".format(col.min(), col.max()) for col in data.T] ) expected = "{}\n".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size(): """ Test the function fails for arrays of different sizes. """ x = np.arange(5) y = np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print("This should have failed") def test_virtualfile_from_matrix(): """ Test transforming a matrix to virtual file dataset. """ dtypes = "float32 float64 int32 int64 uint32 uint64".split() shape = (7, 5) for dtype in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module("info", "{} ->{}".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = "\t".join( ["<{:.0f}/{:.0f}>".format(col.min(), col.max()) for col in data.T] ) expected = "<matrix memory>: N = {}\t{}\n".format(shape[0], bounds) assert output == expected def test_virtualfile_from_matrix_slice(): """ Test transforming a slice of a larger array to virtual file dataset. """ dtypes = "float32 float64 int32 int64 uint32 uint64".split() shape = (10, 6) for dtype in dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5 cols = 3 data = full_data[:rows, :cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module("info", "{} ->{}".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = "\t".join( ["<{:.0f}/{:.0f}>".format(col.min(), col.max()) for col in data.T] ) expected = "<matrix memory>: N = {}\t{}\n".format(rows, bounds) assert output == expected def test_virtualfile_from_vectors_pandas(): """ Pass vectors to a dataset using pandas Series. """ dtypes = "float32 float64 int32 int64 uint32 uint64".split() size = 13 for dtype in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size * 2, size * 3, 1, dtype=dtype), ) ) with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile() as outfile: lib.call_module("info", "{} ->{}".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = "\t".join( [ "<{:.0f}/{:.0f}>".format(i.min(), i.max()) for i in (data.x, data.y, data.z) ] ) expected = "<vector memory>: N = {}\t{}\n".format(size, bounds) assert output == expected def test_virtualfile_from_vectors_arraylike(): """ Pass array-like vectors to a dataset. """ size = 13 x = list(range(0, size, 1)) y = tuple(range(size, size * 2, 1)) z = range(size * 2, size * 3, 1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as outfile: lib.call_module("info", "{} ->{}".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = "\t".join( ["<{:.0f}/{:.0f}>".format(min(i), max(i)) for i in (x, y, z)] ) expected = "<vector memory>: N = {}\t{}\n".format(size, bounds) assert output == expected def test_extract_region_fails(): """ Check that extract region fails if nothing has been plotted. """ Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): """ Extract region should handle multiple figures existing at the same time. """ # Make two figures before calling extract_region to make sure that it's # getting from the current figure, not the last figure. fig1 = Figure() region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection="M6i", frame=True, land="black") fig2 = Figure() fig2.basemap(region="US.HI+r5", projection="M6i", frame=True) # Activate the first figure and extract the region from it # Use in a different session to avoid any memory problems. with clib.Session() as lib: lib.call_module("figure", "{} -".format(fig1._name)) with clib.Session() as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it with the second one with clib.Session() as lib: lib.call_module("figure", "{} -".format(fig2._name)) with clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): """ Check that write data raises an exception for non-zero return codes. """ # It's hard to make the C API function fail without causing a Segmentation # Fault. Can't test this if by giving a bad file name because if # output=='', GMT will just write to stdout and spaces are valid file # names. Use a mock instead just to exercise this part of the code. with clib.Session() as lib: with mock(lib, "GMT_Write_Data", returns=1): with pytest.raises(GMTCLibError): lib.write_data( "GMT_IS_VECTOR", "GMT_IS_POINT", "GMT_WRITE_SET", [1] * 6, "some-file-name", None, ) def test_dataarray_to_matrix_works(): """ Check that dataarray_to_matrix returns correct output. """ data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[("y", y), ("x", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): """ Check if dataarray_to_matrix returns correct output with flipped x. """ data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[("y", y), ("x", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): """ Check that dataarray_to_matrix returns correct output with flipped y. """ data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[("y", y), ("x", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): """ Check that dataarray_to_matrix returns correct output with flipped x/y. """ data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[("y", y), ("x", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): """ Check that it fails for > 2 dims. """ # Make a 3D regular grid data = np.ones((10, 12, 11), dtype="float32") x = np.arange(11) y = np.arange(12) z = np.arange(10) grid = xr.DataArray(data, coords=[("z", z), ("y", y), ("x", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): """ Check that it fails for variable increments. """ data = np.ones((4, 5), dtype="float64") x = np.linspace(0, 1, 5) y = np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[("y", y), ("x", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): """ Make sure get_default works without crashing and gives reasonable results. """ with clib.Session() as lib: assert lib.get_default("API_GRID_LAYOUT") in ["rows", "columns"] assert int(lib.get_default("API_CORES")) >= 1 assert Version(lib.get_default("API_VERSION")) >= Version("6.2.0") def test_get_default_fails(): """ Make sure get_default raises an exception for invalid names. """ with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default("NOT_A_VALID_NAME") def test_info_dict(): """ Make sure the clib.Session.info dict is working. """ # Check if there are no errors or segfaults from getting all of the # properties. with clib.Session() as lib: assert lib.info # Mock GMT_Get_Default to return always the same string def mock_defaults(api, name, value): # pylint: disable=unused-argument """ Put 'bla' in the value buffer. """ value.value = b"bla" return 0 ses = clib.Session() ses.create("test-session") with mock(ses, "GMT_Get_Default", mock_func=mock_defaults): # Check for an empty dictionary assert ses.info for key in ses.info: assert ses.info[key] == "bla" ses.destroy() def test_fails_for_wrong_version(): """ Make sure the clib.Session raises an exception if GMT is too old. """ # Mock GMT_Get_Default to return an old version def mock_defaults(api, name, value): # pylint: disable=unused-argument """ Return an old version. """ if name == b"API_VERSION": value.value = b"5.4.3" else: value.value = b"bla" return 0 lib = clib.Session() with mock(lib, "GMT_Get_Default", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info["version"] != "5.4.3" # Make sure the session is closed when the exception is raised. with pytest.raises(GMTCLibNoSessionError): assert lib.session_pointer

stubs/_pytest/_code.py

questioneer-ltd/scrut

393

<reponame>questioneer-ltd/scrut """Type stubs for _pytest._code.""" # This class actually has more functions than are specified here. # We don't use these features, so I don't think its worth including # them in our type stub. We can always change it later. class ExceptionInfo: @property def value(self) -> Exception: ...

Prime Factorization/prime_factorization_II.py

rayvantsahni/Let-us-Math

394

def get_primes(n): primes = [] # stores the prime numbers within the reange of the number sieve = [False] * (n + 1) # stores boolean values indicating whether a number is prime or not sieve[0] = sieve[1] = True # marking 0 and 1 as not prime for i in range(2, n + 1): # loops over all the numbers to check for prime numbers if sieve[i]: # checks whether a number is not prime continue # skips the loop if the number is not a prime number primes.append(i) # adds a number into list if it is a prime number for j in range(i ** 2, n + 1, i): # loops over all multiples of the prime number starting from the sqaure of the prime number sieve[j] = True # marks the multiple of the prime number as not prime return primes # returns the list containing prime numbers def get_factorization(n): prime_factors = [] # stores the prime factorization of the number for prime in get_primes(n): # looping over all the prime numbers while n != 1: # keeps diving the number by a certain prime number until the number is 1 if n % prime == 0: # checks if the number is divisible by a particular prime number prime_factors.append(prime) # add the prime factor in the list if it divides the number n /= prime # reducing the number after dividing it by the prime number else: break # if the number is not divisible by the paricular prime number then the inner loop breaks and the number is further divided by the next prime number until the number becomes 1 return prime_factors # returns the list containing the prime factorization of the number if __name__ == "__main__": n = int(input("Enter a number: ")) print(get_factorization(n))

pandas/core/indexes/range.py

mujtahidalam/pandas

395

from __future__ import annotations from datetime import timedelta import operator from sys import getsizeof from typing import ( TYPE_CHECKING, Any, Callable, Hashable, List, cast, ) import warnings import numpy as np from pandas._libs import index as libindex from pandas._libs.lib import no_default from pandas._typing import Dtype from pandas.compat.numpy import function as nv from pandas.util._decorators import ( cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops import pandas.core.common as com from pandas.core.construction import extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index _empty_range = range(0) class RangeIndex(NumericIndex): """ Immutable Index implementing a monotonic integer range. RangeIndex is a memory-saving special case of Int64Index limited to representing monotonic ranges. Using RangeIndex may in some instances improve computing speed. This is the default index type used by DataFrame and Series when no explicit index is provided by the user. Parameters ---------- start : int (default: 0), range, or other RangeIndex instance If int and "stop" is not given, interpreted as "stop" instead. stop : int (default: 0) step : int (default: 1) dtype : np.int64 Unused, accepted for homogeneity with other index types. copy : bool, default False Unused, accepted for homogeneity with other index types. name : object, optional Name to be stored in the index. Attributes ---------- start stop step Methods ------- from_range See Also -------- Index : The base pandas Index type. Int64Index : Index of int64 data. """ _typ = "rangeindex" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, "signed integer") _can_hold_na = False _range: range # -------------------------------------------------------------------- # Constructors def __new__( cls, start=None, stop=None, step=None, dtype: Dtype | None = None, copy: bool = False, name: Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name) # validate the arguments if com.all_none(start, stop, step): raise TypeError("RangeIndex(...) must be called with integers") start = ensure_python_int(start) if start is not None else 0 if stop is None: start, stop = 0, start else: stop = ensure_python_int(stop) step = ensure_python_int(step) if step is not None else 1 if step == 0: raise ValueError("Step must not be zero") rng = range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod def from_range( cls, data: range, name=None, dtype: Dtype | None = None ) -> RangeIndex: """ Create RangeIndex from a range object. Returns ------- RangeIndex """ if not isinstance(data, range): raise TypeError( f"{cls.__name__}(...) must be called with object coercible to a " f"range, {repr(data)} was passed" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range, name: Hashable = None) -> RangeIndex: result = object.__new__(cls) assert isinstance(values, range) result._range = values result._name = name result._cache = {} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: """ return the class to use for construction """ return Int64Index @cache_readonly def _data(self) -> np.ndarray: """ An int array that for performance reasons is created only when needed. The constructed array is saved in ``_cache``. """ return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index: # wrap _cached_int64index so we can be sure its name matches self.name res = self._cached_int64index res._name = self._name return res def _get_data_as_items(self): """ return a list of tuples of start, stop, step """ rng = self._range return [("start", rng.start), ("stop", rng.stop), ("step", rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): """ Return a list of tuples of the (attr, formatted_value) """ attrs = self._get_data_as_items() if self.name is not None: attrs.append(("name", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): # we are formatting thru the attributes return None def _format_with_header(self, header: list[str], na_rep: str = "NaN") -> list[str]: if not len(self._range): return header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header + [f"{x:<{max_length}}" for x in self._range] # -------------------------------------------------------------------- _deprecation_message = ( "RangeIndex.{} is deprecated and will be " "removed in a future version. Use RangeIndex.{} " "instead" ) @property def start(self) -> int: """ The value of the `start` parameter (``0`` if this was not supplied). """ # GH 25710 return self._range.start @property def _start(self) -> int: """ The value of the `start` parameter (``0`` if this was not supplied). .. deprecated:: 0.25.0 Use ``start`` instead. """ warnings.warn( self._deprecation_message.format("_start", "start"), FutureWarning, stacklevel=2, ) return self.start @property def stop(self) -> int: """ The value of the `stop` parameter. """ return self._range.stop @property def _stop(self) -> int: """ The value of the `stop` parameter. .. deprecated:: 0.25.0 Use ``stop`` instead. """ # GH 25710 warnings.warn( self._deprecation_message.format("_stop", "stop"), FutureWarning, stacklevel=2, ) return self.stop @property def step(self) -> int: """ The value of the `step` parameter (``1`` if this was not supplied). """ # GH 25710 return self._range.step @property def _step(self) -> int: """ The value of the `step` parameter (``1`` if this was not supplied). .. deprecated:: 0.25.0 Use ``step`` instead. """ # GH 25710 warnings.warn( self._deprecation_message.format("_step", "step"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly def nbytes(self) -> int: """ Return the number of bytes in the underlying data. """ rng = self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name in ["start", "stop", "step"] ) def memory_usage(self, deep: bool = False) -> int: """ Memory usage of my values Parameters ---------- deep : bool Introspect the data deeply, interrogate `object` dtypes for system-level memory consumption Returns ------- bytes used Notes ----- Memory usage does not include memory consumed by elements that are not components of the array if deep=False See Also -------- numpy.ndarray.nbytes """ return self.nbytes @property def dtype(self) -> np.dtype: return np.dtype(np.int64) @property def is_unique(self) -> bool: """ return if the index has unique values """ return True @cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step > 0 or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step < 0 or len(self) <= 1 def __contains__(self, key: Any) -> bool: hash(key) try: key = ensure_python_int(key) except TypeError: return False return key in self._range @property def inferred_type(self) -> str: return "integer" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if method is None and tolerance is None: if is_integer(key) or (is_float(key) and key.is_integer()): new_key = int(key) try: return self._range.index(new_key) except ValueError as err: raise KeyError(key) from err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target: Index, method: str | None = None, limit: int | None = None, tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if self.step > 0: start, stop, step = self.start, self.stop, self.step else: # GH 28678: work on reversed range for simplicity reverse = self._range[::-1] start, stop, step = reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs = target_array - start valid = (locs % step == 0) & (locs >= 0) & (target_array < stop) locs[~valid] = -1 locs[valid] = locs[valid] / step if step != self.step: # We reversed this range: transform to original locs locs[valid] = len(self) - 1 - locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index: # type: ignore[override] return self._int64index.delete(loc) def take( self, indices, axis: int = 0, allow_fill: bool = True, fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception("Int64Index", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable = no_default): name = self.name if name is no_default else name if values.dtype.kind == "f": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result @doc(Int64Index.copy) def copy( self, name: Hashable = None, deep: bool = False, dtype: Dtype | None = None, names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn( "parameter dtype is deprecated and will be removed in a future " "version. Use the astype method instead.", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return new_index def _minmax(self, meth: str): no_steps = len(self) - 1 if no_steps == -1: return np.nan elif (meth == "min" and self.step > 0) or (meth == "max" and self.step < 0): return self.start return self.start + self.step * no_steps def min(self, axis=None, skipna: bool = True, *args, **kwargs) -> int: """The minimum value of the RangeIndex""" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax("min") def max(self, axis=None, skipna: bool = True, *args, **kwargs) -> int: """The maximum value of the RangeIndex""" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax("max") def argsort(self, *args, **kwargs) -> np.ndarray: """ Returns the indices that would sort the index and its underlying data. Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort """ ascending = kwargs.pop("ascending", True) # EA compat nv.validate_argsort(args, kwargs) if self._range.step > 0: result = np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) - 1, -1, -1, dtype=np.intp) if not ascending: result = result[::-1] return result def factorize( self, sort: bool = False, na_sentinel: int | None = -1 ) -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques = self if sort and self.step < 0: codes = codes[::-1] uniques = uniques[::-1] return codes, uniques def equals(self, other: object) -> bool: """ Determines if two Index objects contain the same elements. """ if isinstance(other, RangeIndex): return self._range == other._range return super().equals(other) # -------------------------------------------------------------------- # Set Operations def _intersection(self, other: Index, sort=False): if not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if not len(self) or not len(other): return self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0 else self._range second = other._range[::-1] if other.step < 0 else other._range # check whether intervals intersect # deals with in- and decreasing ranges int_low = max(first.start, second.start) int_high = min(first.stop, second.stop) if int_high <= int_low: return self._simple_new(_empty_range) # Method hint: linear Diophantine equation # solve intersection problem # performance hint: for identical step sizes, could use # cheaper alternative gcd, s, _ = self._extended_gcd(first.step, second.step) # check whether element sets intersect if (first.start - second.start) % gcd: return self._simple_new(_empty_range) # calculate parameters for the RangeIndex describing the # intersection disregarding the lower bounds tmp_start = first.start + (second.start - first.start) * first.step // gcd * s new_step = first.step * second.step // gcd new_range = range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) # adjust index to limiting interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step < 0 and other.step < 0) is not (new_index.step < 0): new_index = new_index[::-1] if sort is None: new_index = new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int) -> int: """Returns the smallest element greater than or equal to the limit""" no_steps = -(-(lower_limit - self.start) // abs(self.step)) return self.start + abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int) -> int: """Returns the largest element smaller than or equal to the limit""" no_steps = (upper_limit - self.start) // abs(self.step) return self.start + abs(self.step) * no_steps def _extended_gcd(self, a: int, b: int) -> tuple[int, int, int]: """ Extended Euclidean algorithms to solve Bezout's identity: a*x + b*y = gcd(x, y) Finds one particular solution for x, y: s, t Returns: gcd, s, t """ s, old_s = 0, 1 t, old_t = 1, 0 r, old_r = b, a while r: quotient = old_r // r old_r, r = r, old_r - quotient * r old_s, s = s, old_s - quotient * s old_t, t = t, old_t - quotient * t return old_r, old_s, old_t def _union(self, other: Index, sort): """ Form the union of two Index objects and sorts if possible Parameters ---------- other : Index or array-like sort : False or None, default None Whether to sort resulting index. ``sort=None`` returns a monotonically increasing ``RangeIndex`` if possible or a sorted ``Int64Index`` if not. ``sort=False`` always returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union : Index """ if isinstance(other, RangeIndex) and sort is None: start_s, step_s = self.start, self.step end_s = self.start + self.step * (len(self) - 1) start_o, step_o = other.start, other.step end_o = other.start + other.step * (len(other) - 1) if self.step < 0: start_s, step_s, end_s = end_s, -step_s, start_s if other.step < 0: start_o, step_o, end_o = end_o, -step_o, start_o if len(self) == 1 and len(other) == 1: step_s = step_o = abs(self.start - other.start) elif len(self) == 1: step_s = step_o elif len(other) == 1: step_o = step_s start_r = min(start_s, start_o) end_r = max(end_s, end_o) if step_o == step_s: if ( (start_s - start_o) % step_s == 0 and (start_s - end_o) <= step_s and (start_o - end_s) <= step_s ): return type(self)(start_r, end_r + step_s, step_s) if ( (step_s % 2 == 0) and (abs(start_s - start_o) <= step_s / 2) and (abs(end_s - end_o) <= step_s / 2) ): return type(self)(start_r, end_r + step_s / 2, step_s / 2) elif step_o % step_s == 0: if ( (start_o - start_s) % step_s == 0 and (start_o + step_s >= start_s) and (end_o - step_s <= end_s) ): return type(self)(start_r, end_r + step_s, step_s) elif step_s % step_o == 0: if ( (start_s - start_o) % step_o == 0 and (start_s + step_o >= start_o) and (end_s - step_o <= end_o) ): return type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): # optimized set operation if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first = self._range[::-1] if self.step < 0 else self._range overlap = self.intersection(other) if overlap.step < 0: overlap = overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We won't end up with RangeIndex, so fall back return super()._difference(other, sort=sort) if overlap.step != first.step: # In some cases we might be able to get a RangeIndex back, # but not worth the effort. return super()._difference(other, sort=sort) if overlap[0] == first.start: # The difference is everything after the intersection new_rng = range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1] == first[-1]: # The difference is everything before the intersection new_rng = range(first.start, overlap[0], first.step) else: # The difference is not range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first is not self._range: new_index = new_index[::-1] return new_index def symmetric_difference(self, other, result_name: Hashable = None, sort=None): if not isinstance(other, RangeIndex) or sort is not None: return super().symmetric_difference(other, result_name, sort) left = self.difference(other) right = other.difference(self) result = left.union(right) if result_name is not None: result = result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable) -> Index: """ Overriding parent method for the case of all RangeIndex instances. When all members of "indexes" are of type RangeIndex: result will be RangeIndex if possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) """ if not all(isinstance(x, RangeIndex) for x in indexes): return super()._concat(indexes, name) elif len(indexes) == 1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start = step = next_ = None # Filter the empty indexes non_empty_indexes = [obj for obj in rng_indexes if len(obj)] for obj in non_empty_indexes: rng = obj._range if start is None: # This is set by the first non-empty index start = rng.start if step is None and len(rng) > 1: step = rng.step elif step is None: # First non-empty index had only one element if rng.start == start: values = np.concatenate([x._values for x in rng_indexes]) result = Int64Index(values) return result.rename(name) step = rng.start - start non_consecutive = (step != rng.step and len(rng) > 1) or ( next_ is not None and rng.start != next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name) if step is not None: next_ = rng[-1] + step if non_empty_indexes: # Get the stop value from "next" or alternatively # from the last non-empty index stop = non_empty_indexes[-1].stop if next_ is None else next_ return RangeIndex(start, stop, step).rename(name) # Here all "indexes" had 0 length, i.e. were empty. # In this case return an empty range index. return RangeIndex(0, 0).rename(name) def __len__(self) -> int: """ return the length of the RangeIndex """ return len(self._range) @property def size(self) -> int: return len(self) def __getitem__(self, key): """ Conserve RangeIndex type for scalar and slice keys. """ if isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key) try: return self._range[new_key] except IndexError as err: raise IndexError( f"index {key} is out of bounds for axis 0 with size {len(self)}" ) from err elif is_scalar(key): raise IndexError( "only integers, slices (`:`), " "ellipsis (`...`), numpy.newaxis (`None`) " "and integer or boolean " "arrays are valid indices" ) # fall back to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: """ Fastpath for __getitem__ when we know we have a slice. """ res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer("__floordiv__") def __floordiv__(self, other): if is_integer(other) and other != 0: if len(self) == 0 or self.start % other == 0 and self.step % other == 0: start = self.start // other step = self.step // other stop = start + len(self) * step new_range = range(start, stop, step or 1) return self._simple_new(new_range, name=self.name) if len(self) == 1: start = self.start // other new_range = range(start, start + 1, 1) return self._simple_new(new_range, name=self.name) return self._int64index // other # -------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs) -> bool: return 0 not in self._range def any(self, *args, **kwargs) -> bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other, RangeIndex) and self._range == other._range: # Both are immutable so if ._range attr. are equal, shortcut is possible return super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self, other, op): """ Parameters ---------- other : Any op : callable that accepts 2 params perform the binary op """ if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True on timedelta64, # so we need to catch these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390 return op(self._int64index, other) if op in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other) step: Callable | None = None if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op # TODO: if other is a RangeIndex we may have more efficient options other = extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right = self, other try: # apply if we have an override if step: with np.errstate(all="ignore"): rstep = step(left.step, right) # we don't have a representable op # so return a base index if not is_integer(rstep) or not rstep: raise ValueError else: rstep = left.step with np.errstate(all="ignore"): rstart = op(left.start, right) rstop = op(left.stop, right) result = type(self)(rstart, rstop, rstep, **attrs) # for compat with numpy / Int64Index # even if we can represent as a RangeIndex, return # as a Float64Index if we have float-like descriptors if not all(is_integer(x) for x in [rstart, rstop, rstep]): result = result.astype("float64") return result except (ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index implementation return op(self._int64index, other) # TODO: Do attrs get handled reliably?

model.py

Hasanweight/pytorch-chatbot-master

396

import torch import torch.nn as nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self, x): out = self.l1(x) out = self.relu(out) out = self.l2(out) out = self.relu(out) out = self.l3(out) out = self.relu(out) out = self.l4(out) # no activation and no softmax at the end return out

jwql/utils/logging_functions.py

hover2pi/jwql

397

""" Logging functions for the ``jwql`` automation platform. This module provides decorators to log the execution of modules. Log files are written to the ``logs/`` directory in the ``jwql`` central storage area, named by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 - <NAME>, 2013 (WFC3 QL Version) Use --- To log the execution of a module, use: :: import os import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function(): pass if __name__ == '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The user must have a configuration file named ``config.json`` placed in the ``utils`` directory. References ---------- This code is adopted and updated from python routine ``logging_functions.py`` written by Alex Viana, 2013 for the WFC3 Quicklook automation platform. """ import datetime import getpass import importlib import logging import os import pwd import socket import sys import time import traceback from functools import wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'): """Configure the log file with a standard logging format. Parameters ---------- module : str The name of the module being logged. production_mode : bool Whether or not the output should be written to the production environement. path : str Where to write the log if user-supplied path; default to working dir. """ # Determine log file location if production_mode: log_file = make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode # Create the log file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): """Create the log file name based on the module name. The name of the ``log_file`` is a combination of the name of the module being logged and the current datetime. Parameters ---------- module : str The name of the module being logged. production_mode : bool Whether or not the output should be written to the production environment. path : str Where to write the log if user-supplied path; default to working dir. Returns ------- log_file : str The full path to where the log file will be written to. """ timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules = [] if user != admin_account and module not in exempt_modules and production_mode: module = os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path, module, filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): """Decorator to log useful system information. This function can be used as a decorator to log user environment and system information. Future packages we want to track can be added or removed as necessary. Parameters ---------- func : func The function to decorate. Returns ------- wrapped : func The wrapped function. """ @wraps(func) def wrapped(*a, **kw): # Log environment information logging.info('User: ' + getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\n', '')) logging.info('Python Executable Path: ' + sys.executable) # Read in setup.py file to build list of required modules settings = get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as setup: for line in setup: if line[0:8] == "REQUIRES": module_required = line[12:-2] module_list = module_required.split(',') # Clean up the module list module_list = [module.replace('"', '').replace("'", '').replace(' ', '') for module in module_list] module_list = [module.split('=')[0] for module in module_list] # Log common module version information for module in module_list: try: mod = importlib.import_module(module) logging.info(module + ' Version: ' + mod.__version__) logging.info(module + ' Path: ' + mod.__path__[0]) except ImportError as err: logging.warning(err) # Call the function and time it t1_cpu = time.clock() t1_time = time.time() func(*a, **kw) t2_cpu = time.clock() t2_time = time.time() # Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time - t1_time, 60 * 60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): """Decorator to log crashes in the decorated code. Parameters ---------- func : func The function to decorate. Returns ------- wrapped : func The wrapped function. """ @wraps(func) def wrapped(*a, **kw): try: # Run the function func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc()) logging.critical('CRASHED') return wrapped

api/services/http.py

takos22/API-1

398

from aiohttp import ClientSession from typing import Optional session: Optional[ClientSession] = None __all__ = (session,)

bcloud-snap/bcloud-3.9.1/bcloud/hasher.py

jiaxiaolei/my_snap_demo

399

<gh_stars>0 # Copyright (C) 2014-2015 LiuLang <<EMAIL>> # Use of this source code is governed by GPLv3 license that can be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib CHUNK = 2 ** 20 def crc(path): _crc = 0 fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk: break _crc = zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh = open(path, 'rb') if start > 0: fh.seek(start) if stop == -1: stop = os.path.getsize(path) pos = start while pos < stop: size = min(CHUNK, stop - pos) chunk = fh.read(size) if not chunk: break pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk: break _sha512.update(chunk) fh.close() return _sha512.hexdigest()