xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

85d84988da11a476dce7c74f79d147f461a965d2

98

py

Python

tests/fractions_tok/addition.py

aroberge/importhooks

57483ce24d265d391587f6321954f2ed60f04afd

[ "MIT" ]

36

2020-02-23T19:06:24.000Z

2022-02-20T22:53:02.000Z

tests/fractions_tok/addition.py

aroberge/importhooks

57483ce24d265d391587f6321954f2ed60f04afd

[ "MIT" ]

13

2020-02-21T15:25:40.000Z

2021-07-01T09:56:35.000Z

tests/fractions_tok/addition.py

aroberge/importhooks

57483ce24d265d391587f6321954f2ed60f04afd

[ "MIT" ]

1

2020-11-05T13:12:07.000Z

print("1 / 10 + 2 / 10 = ", 1 / 10 + 2 / 10) assert 1 / 10 + 2 / 10 == 3 / 10, "simple addition"

24.5

51

0.469388

18

98

2.555556

0.444444

0.195652

0.26087

0.391304

0

0.313433

0.316327

98

3

52

32.666667

0.373134

0

0.336735

0

0.5

1

0

true

0

0.5

1

0

null

0

1

0

1

0

1

0

1

0

null

0

1

0

1

0

1

0

9

85de7d1934df09fd14efcf602409f4521903938e

5,674

py

Python

Message encoder.py

cjw0621/Growing-Python

50d754ab0a9d32f2284b3732df046f1ce849eca4

[ "Unlicense" ]

1

2021-11-21T01:51:30.000Z

Message encoder.py

cjw0621/Growing-Python

50d754ab0a9d32f2284b3732df046f1ce849eca4

[ "Unlicense" ]

null

Message encoder.py

cjw0621/Growing-Python

50d754ab0a9d32f2284b3732df046f1ce849eca4

[ "Unlicense" ]

null

def make_encoded(user_input): user_input = user_input.replace("a", "~") user_input = user_input.replace("A", "~") user_input = user_input.replace("b", "@") user_input = user_input.replace("B", "@") user_input = user_input.replace("c", "#") user_input = user_input.replace("C", "#") user_input = user_input.replace("d", "$") user_input = user_input.replace("D", "$") user_input = user_input.replace("e", "%") user_input = user_input.replace("E", "%") user_input = user_input.replace("f", "^") user_input = user_input.replace("F", "^") user_input = user_input.replace("g", "&") user_input = user_input.replace("G", "&") user_input = user_input.replace("h", "*") user_input = user_input.replace("H", "*") user_input = user_input.replace("i", "(") user_input = user_input.replace("I", "(") user_input = user_input.replace("j", ")") user_input = user_input.replace("J", ")") user_input = user_input.replace("k", "-") user_input = user_input.replace("K", "-") user_input = user_input.replace("l", "=") user_input = user_input.replace("L", "=") user_input = user_input.replace("m", "+") user_input = user_input.replace("M", "+") user_input = user_input.replace("n", "`") user_input = user_input.replace("N", "`") user_input = user_input.replace("o", ",") user_input = user_input.replace("O", ",") user_input = user_input.replace("p", "<") user_input = user_input.replace("P", "<") user_input = user_input.replace("q", ".") user_input = user_input.replace("Q", ".") user_input = user_input.replace("r", ">") user_input = user_input.replace("R", ">") user_input = user_input.replace("s", "/") user_input = user_input.replace("S", "/") user_input = user_input.replace("t", "?") user_input = user_input.replace("T", "?") user_input = user_input.replace("u", "[") user_input = user_input.replace("U", "[") user_input = user_input.replace("v", "]") user_input = user_input.replace("V", "]") user_input = user_input.replace("w", "|") user_input = user_input.replace("W", "|") user_input = user_input.replace("x", "}") user_input = user_input.replace("X", "}") user_input = user_input.replace("y", "{") user_input = user_input.replace("Y", "{") user_input = user_input.replace("z", ";") user_input = user_input.replace("Z", ";") return user_input def make_decoded(user_input): user_input = user_input.replace("~", "a") user_input = user_input.replace("~", "A") user_input = user_input.replace("@", "b") user_input = user_input.replace("@", "B") user_input = user_input.replace("#", "c") user_input = user_input.replace("#", "C") user_input = user_input.replace("$", "d") user_input = user_input.replace("$", "D") user_input = user_input.replace("%", "e") user_input = user_input.replace("%", "E") user_input = user_input.replace("^", "f") user_input = user_input.replace("^", "F") user_input = user_input.replace("&", "g") user_input = user_input.replace("&", "G") user_input = user_input.replace("*", "h") user_input = user_input.replace("*", "H") user_input = user_input.replace("(", "i") user_input = user_input.replace("(", "I") user_input = user_input.replace(")", "j") user_input = user_input.replace(")", "J") user_input = user_input.replace("-", "k") user_input = user_input.replace("-", "K") user_input = user_input.replace("=", "l") user_input = user_input.replace("=", "L") user_input = user_input.replace("+", "m") user_input = user_input.replace("+", "M") user_input = user_input.replace("`", "n") user_input = user_input.replace("`", "N") user_input = user_input.replace(",", "o") user_input = user_input.replace(",", "O") user_input = user_input.replace("<", "p") user_input = user_input.replace("<", "P") user_input = user_input.replace(".", "q") user_input = user_input.replace(".", "Q") user_input = user_input.replace(">", "r") user_input = user_input.replace(">", "R") user_input = user_input.replace("/", "s") user_input = user_input.replace("/", "S") user_input = user_input.replace("?", "t") user_input = user_input.replace("?", "T") user_input = user_input.replace("[", "u") user_input = user_input.replace("[", "U") user_input = user_input.replace("]", "v") user_input = user_input.replace("]", "V") user_input = user_input.replace("|", "w") user_input = user_input.replace("|", "W") user_input = user_input.replace("}", "x") user_input = user_input.replace("}", "X") user_input = user_input.replace("{", "y") user_input = user_input.replace("{", "Y") user_input = user_input.replace(";", "z") user_input = user_input.replace(";", "Z") return user_input loop = False while loop == False: y_n = input("Do you have a message you would like to decode? -> ") print(y_n) if y_n == "y" or y_n == "Y" or y_n == "yes" or y_n == "Yes" or y_n == "YES": user_input = input("Whats your encoded message? -> ") print(make_decoded(user_input)) elif y_n == "n" or y_n == "N" or y_n == "no" or y_n == "No" or y_n == "NO": user_input = input("What would you like encoded? -> ") print(make_encoded(user_input)) else: print("Your response is invalid, please to ensure youre only using letters.") user_input = y_n print(user_input) loop == False

42.984848

86

0.594466

748

5,674

4.195187

0.085562

0.625239

0.439133

0.608031

0.894519

0.88942

0.876992

0

0.20497

5,674

132

87

42.984848

0.695633

0

0.01626

0

0.073773

0

1

0.01626

false

0

0.03252

0.04065

0

null

1

0

null

0

9

c0ac50180aac8a7c789ac715647fd3941ab60825

3,122

py

Python

content_interactions_stats/tasks.py

aaboffill/django-content-interactions

8ea881e46cc6d5c375542939bb69d2980efdec23

[ "BSD-3-Clause" ]

null

content_interactions_stats/tasks.py

aaboffill/django-content-interactions

8ea881e46cc6d5c375542939bb69d2980efdec23

[ "BSD-3-Clause" ]

null

content_interactions_stats/tasks.py

aaboffill/django-content-interactions

8ea881e46cc6d5c375542939bb69d2980efdec23

[ "BSD-3-Clause" ]

null

# coding=utf-8 from celery import shared_task @shared_task(name='content_interactions.like_process') def item_like_process(item_id, item_content_type): from content_interactions_stats.utils import item_like_process item_like_process(item_id, item_content_type) @shared_task(name='content_interactions.dislike_process') def item_dislike_process(item_id, item_content_type): from content_interactions_stats.utils import item_dislike_process item_dislike_process(item_id, item_content_type) @shared_task(name='content_interactions.new_rating_process') def item_new_rating_process(item_id, item_content_type, rating): from content_interactions_stats.utils import item_new_rating_process item_new_rating_process(item_id, item_content_type, rating) @shared_task(name='content_interactions.update_rating_process') def item_updated_rating_process(item_id, item_content_type, old_rating, rating): from content_interactions_stats.utils import item_updated_rating_process item_updated_rating_process(item_id, item_content_type, old_rating, rating) @shared_task(name='content_interactions.mark_favorite_process') def item_marked_favorite_process(item_id, item_content_type): from content_interactions_stats.utils import item_marked_favorite_process item_marked_favorite_process(item_id, item_content_type) @shared_task(name='content_interactions.unmark_favorite_process') def item_unmarked_favorite_process(item_id, item_content_type): from content_interactions_stats.utils import item_unmarked_favorite_process item_unmarked_favorite_process(item_id, item_content_type) @shared_task(name='content_interactions.share_process') def item_shared_process(item_id, item_content_type): from content_interactions_stats.utils import item_shared_process item_shared_process(item_id, item_content_type) @shared_task(name='content_interactions.denounce_process') def item_denounced_process(item_id, item_content_type): from content_interactions_stats.utils import item_denounced_process item_denounced_process(item_id, item_content_type) @shared_task(name='content_interactions.denounce_removed_process') def item_denounce_removed_process(item_id, item_content_type): from content_interactions_stats.utils import item_denounce_removed_process item_denounce_removed_process(item_id, item_content_type) @shared_task(name='content_interactions.comment_process') def item_got_comment_process(item_id, item_content_type): from content_interactions_stats.utils import item_got_comment_process item_got_comment_process(item_id, item_content_type) @shared_task(name='content_interactions.comment_deleted_process') def item_comment_deleted_process(item_id, item_content_type): from content_interactions_stats.utils import item_comment_deleted_process item_comment_deleted_process(item_id, item_content_type) @shared_task(name='content_interactions.visit_process') def item_visited_process(item_id, item_content_type): from content_interactions_stats.utils import item_visited_process item_visited_process(item_id, item_content_type)

41.078947

80

0.858424

439

3,122

5.571754

0.088838

0.161897

0.127555

0.166803

0.874898

0.80417

0.777187

0.687244

0.627555

0

0.000349

0.081038

3,122

75

81

41.626667

0.852213

0.003844

0

0.149984

0

1

0.244898

false

0

0.265306

0

0.510204

0

null

0

1

0

1

0

null

0

1

0

1

0

8

c0b529e628f3a72c09629012a1f2718796b37dee

39

py

Python

SAKIR/ilk.py

vektorelpython24proje/temelbilgiler

bced2723d247dbb8b10cf86e25ee209635f82921

[ "MIT" ]

null

SAKIR/ilk.py

vektorelpython24proje/temelbilgiler

bced2723d247dbb8b10cf86e25ee209635f82921

[ "MIT" ]

null

SAKIR/ilk.py

vektorelpython24proje/temelbilgiler

bced2723d247dbb8b10cf86e25ee209635f82921

[ "MIT" ]

3

2020-10-24T14:36:14.000Z

2020-10-24T14:41:13.000Z

print("ŞAKİR KAYADAN 25.10.2020 Pazar")

39

0.769231

9

39

3.444444

1

0

0.222222

0.076923

39

1

39

0.611111

0

0.75

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

7

c0df6898fa90babf8a53f67c3f1bbcf7e7683899

9,452

py

Python

database/ohca-api/ohca/models.py

SterArcher/OHCA-registry-Slovenia

ad8278a28039503ab6a75d48ffea314de9a759ba

[ "MIT" ]

1

2022-02-28T13:02:14.000Z

database/ohca-api/ohca/models.py

SterArcher/dispatch

ad8278a28039503ab6a75d48ffea314de9a759ba

[ "MIT" ]

1

2022-03-20T10:51:17.000Z

2022-03-21T07:52:57.000Z

database/ohca-api/ohca/models.py

SterArcher/OHCA-registry-Slovenia

ad8278a28039503ab6a75d48ffea314de9a759ba

[ "MIT" ]

null

from django.db import models from django.core.validators import MinValueValidator, MaxValueValidator class Locale(models.Model): localID = models.BigAutoField(primary_key=True) friendlyName = models.TextField() population = models.IntegerField(default = 0) attendedCAs = models.IntegerField(default = 0) attemptedResusc = models.IntegerField(default = 0) casesDNR = models.IntegerField(default = 0) casesFutile = models.IntegerField(default = 0) casesCirculation = models.IntegerField(default = 0) casesUnknown = models.IntegerField(default = 0) description = models.JSONField(default = dict) descriptionSupplemental = models.TextField(null = True, blank = True) def update(self, *args, **kwargs): for name,values in kwargs.items(): if not(name == 'localID'): try: setattr(self,name,values) except KeyError: pass self.save() return True def __str__(self): return self.friendlyName class Meta: db_table = 'locales' class System(models.Model): systemID = models.BigAutoField(primary_key=True) friendlyName = models.TextField() population = models.IntegerField(default = 0) attendedCAs = models.IntegerField(default = 0) attemptedResusc = models.IntegerField(default = 0) casesDNR = models.IntegerField(default = 0) casesFutile = models.IntegerField(default = 0) casesCirculation = models.IntegerField(default = 0) casesUnknown = models.IntegerField(default = 0) description = models.JSONField(default = dict) descriptionSupplemental = models.TextField(null = True, blank = True) def update(self, *args, **kwargs): for name,values in kwargs.items(): if not(name == 'systemID'): try: setattr(self,name,values) except KeyError: pass self.save() return True def __str__(self): return self.friendlyName class Meta: db_table = 'systems' class CaseReport(models.Model): caseID = models.CharField(max_length = 32, primary_key = True) dispatchID = models.CharField(max_length = 32, blank = True, null = True, unique = True) systemID = models.ForeignKey(System, on_delete = models.DO_NOTHING) localID = models.ForeignKey(Locale, on_delete = models.DO_NOTHING) dispIdentifiedCA = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) dispProvidedCPRinst = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) age = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(200)]) gender = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) witnesses = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(3)]) location = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(8)]) bystanderResponse = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(2)]) bystanderResponseTime = models.BigIntegerField(null = True, blank = True, validators=[MaxValueValidator(-1)]) bystanderAED = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(2)]) bystanderAEDTime = models.BigIntegerField(null = True, blank = True, validators=[MaxValueValidator(-1)]) deadOnArrival = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) firstMonitoredRhy = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) pathogenesis = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(1), MaxValueValidator(6)]) independentLiving = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) comorbidities = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) vad = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) cardioverterDefib = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(2)]) stemiPresent = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) responseTime = models.BigIntegerField(null = True, blank = True, validators=[MinValueValidator(-1)]) defibTime = models.BigIntegerField(null = True, blank = True, validators=[MinValueValidator(-1)]) ttm = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(5)]) ttmTemp =models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(400)]) drugs = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(7)]) airwayControl = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(15)]) cprQuality = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) shocks = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1)]) drugTimings = models.JSONField(default = dict) vascularAccess = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(4)]) mechanicalCPR = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(3)]) targetVent = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(3)]) reperfusionAttempt = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(8)]) reperfusionTime = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1)]) ecls = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(2)]) iabp = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) ph = models.DecimalField(max_digits = 5, decimal_places = 3, null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(14)]) lactate = models.DecimalField(max_digits = 10, decimal_places = 5, null = True, blank = True, validators=[MinValueValidator(-1)]) glucose = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) neuroprognosticTests = models.JSONField(default = dict) specialistHospital = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) hospitalVolume = models.IntegerField(null = True, blank = True, validators=[MinValueValidator(-1)]) ecg = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) ecgBLOB = models.FileField(null = True, blank = True) targetBP = models.DecimalField(max_digits = 10, decimal_places = 5, null = True, blank = True, validators=[MinValueValidator(-1)]) survived = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) rosc = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) roscTime = models.BigIntegerField(null = True, blank = True, validators=[MinValueValidator(-1)]) SurvivalDischarge30d = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) cpcDischarge = models.SmallIntegerField( null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(5)]) mrsDischarge = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(6)]) survivalStatus = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) transportToHospital = models.SmallIntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) treatmentWithdrawn = models.IntegerField(null = True, blank = True, validators=[MinValueValidator(-1)]) cod = models.CharField(max_length = 6, null = True, blank = True) organDonation = models.IntegerField(null = True, blank = True, validators=[MinValueValidator(-1), MaxValueValidator(1)]) patientReportedOutcome = models.SmallIntegerField(null = True, blank = True) qualityOfLife = models.JSONField(default = dict) def update(self, *args, **kwargs): for name,values in kwargs.items(): if not(name == 'caseID'): try: setattr(self,name,values) except KeyError: pass self.save() return True def __str__(self): return self.caseID class Meta: db_table = 'cases'

68.492754

150

0.714452

924

9,452

7.274892

0.16342

0.066647

0.106367

0.139096

0.822374

0.807795

0.801845

0.792621

0.692502

0

0.015716

0.165256

9,452

138

151

68.492754

0.836248

0

0.412698

0

0.004231

0

1

0.047619

false

0.02381

0.015873

0.02381

0.809524

0

null

0

1

0

null

0

1

0

7

c0eb62f3c132cacd12369f13e8b5129d606db945

166,643

py

Python

pymatflow/qe/opt.py

DeqiTang/pymatflow

bd8776feb40ecef0e6704ee898d9f42ded3b0186

[ "MIT" ]

6

2020-03-06T16:13:08.000Z

2022-03-09T07:53:34.000Z

pymatflow/qe/opt.py

DeqiTang/pymatflow

bd8776feb40ecef0e6704ee898d9f42ded3b0186

[ "MIT" ]

1

2021-10-02T02:23:08.000Z

2021-11-08T13:29:37.000Z

pymatflow/qe/opt.py

DeqiTang/pymatflow

bd8776feb40ecef0e6704ee898d9f42ded3b0186

[ "MIT" ]

1

2021-07-10T16:28:14.000Z

""" Geometric Optimization calc """ import os import re import shutil import numpy as np import pymatflow.base as base from pymatflow.remote.server import server_handle from pymatflow.qe.pwscf import PwScf class OptRun(PwScf): """ structural optimization uses both energies and forces to locate the minima along serach directions. usually insufficient scf convergence will lead to bad convergence of BFGS algorithm or even to errors. so when doing geometric optimization, we better set parameters to get a good scf convergece. when you structure is small, use a large kpoint set, or the optimization will not be reliable. if you structure is big enough, a small kpoint set will usually suffice the requirement. """ def __init__(self): super().__init__() self.arts.ifstatic = False def relax(self, directory="tmp-qe-relax", inpname="relax.in", output="relax.out", runopt="gen", auto=0): """ :param directory: a place for all the generated files """ #self.set_relax() if runopt == "gen" or runopt == "genrun": if os.path.exists(directory): shutil.rmtree(directory) os.mkdir(directory) #os.system("cp *.UPF %s/" % directory) #os.system("cp %s %s/" % (self.arts.xyz.file, directory)) # do not copy too many files at the same time or it will be slow # so we do not copy all UPF files in the directory but just copy # those used in the calculation. shutil.copyfile(self.arts.xyz.file, os.path.join(directory, os.path.basename(self.arts.xyz.file))) #all_upfs = [s for s in os.listdir() if s.split(".")[-1] == "UPF"] all_file = os.listdir() for element in self.arts.xyz.specie_labels: for item in all_file: #if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE): #if item.split(".")[0].lower() == element.lower() or item.split("_")[0].lower() == element.lower(): if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE) or re.match("(%s)(_*)(upf)" % element, item, re.IGNORECASE): shutil.copyfile(item, os.path.join(directory, item)) break self.arts.pseudo.dir = os.path.abspath(directory) self.control.set_params({"pseudo_dir": os.path.abspath(directory)}) # with open(os.path.join(directory, inpname), 'w') as fout: self.control.to_in(fout) self.system.to_in(fout) self.electrons.to_in(fout) self.ions.to_in(fout) self.arts.to_in(fout) # gen yhbatch script self.gen_llhpc(directory=directory, inpname=inpname, output=output, cmd="$PMF_PWX") # gen pbs script self.gen_pbs(directory=directory, inpname=inpname, output=output, cmd="$PMF_PWX", jobname=self.run_params["jobname"], nodes=self.run_params["nodes"], ppn=self.run_params["ppn"], queue=self.run_params["queue"]) # gen cdcloud script self.gen_cdcloud(directory=directory, inpname=inpname, output=output, cmd="$PMF_PWX") if runopt == "run" or runopt == "genrun": os.chdir(directory) os.system("%s $PMF_PWX < %s | tee %s" % (self.run_params["mpi"], inpname, output)) os.chdir("../") server_handle(auto=auto, directory=directory, jobfilebase="relax", server=self.run_params["server"]) def vc_relax(self, directory="tmp-qe-vc-relax", inpname="vc-relax.in", output="vc-relax.out", runopt="gen", auto=0): """ :param directory: a place for all the generated files """ #self.set_vc_relax() if runopt == "gen" or runopt == "genrun": if os.path.exists(directory): shutil.rmtree(directory) os.mkdir(directory) #os.system("cp *.UPF %s/" % directory) #os.system("cp %s %s/" % (self.arts.xyz.file, directory)) # do not copy too many files at the same time or it will be slow # so we do not copy all UPF files in the directory but just copy # those used in the calculation. shutil.copyfile(self.arts.xyz.file, os.path.join(directory, os.path.basename(self.arts.xyz.file))) #all_upfs = [s for s in os.listdir() if s.split(".")[-1] == "UPF"] all_file = os.listdir() for element in self.arts.xyz.specie_labels: for item in all_file: #if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE): #if item.split(".")[0].lower() == element.lower() or item.split("_")[0].lower() == element.lower(): if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE) or re.match("(%s)(_*)(upf)" % element, item, re.IGNORECASE): shutil.copyfile(item, os.path.join(directory, item)) break # self.arts.pseudo.dir = os.path.abspath(directory) self.control.set_params({"pseudo_dir": os.path.abspath(directory)}) with open(os.path.join(directory, inpname), 'w') as fout: self.control.to_in(fout) self.system.to_in(fout) self.electrons.to_in(fout) self.ions.to_in(fout) self.cell.to_in(fout) self.arts.to_in(fout) # gen yhbatch script self.gen_yh(directory=directory, inpname=inpname, output=output, cmd="$PMF_PWX") # gen pbs script self.gen_pbs(directory=directory, inpname=inpname, cmd="$PMF_PWX", output=output, jobname=self.run_params["jobname"], nodes=self.run_params["nodes"], ppn=self.run_params["ppn"], queue=self.run_params["queue"]) # gen cdcloud script self.gen_cdcloud(directory=directory, inpname=inpname, output=output, cmd="$PMF_PWX") if runopt == "run" or runopt == "genrun": os.chdir(directory) os.system("%s $PMF_PWX < %s | tee %s" % (self.run_params["mpi"], inpname, output)) os.chdir("../") server_handle(auto=auto, directory=directory, jobfilebase="vc-relax", server=self.run_params["server"]) def set_relax(self): self.control.calculation("relax") self.control.basic_setting("relax") self.system.basic_setting(self.arts) self.electrons.basic_setting() self.ions.basic_setting() def set_vc_relax(self): self.control.calculation("vc-relax") self.control.basic_setting("vc-relax") self.system.basic_setting(self.arts) self.electrons.basic_setting() self.ions.basic_setting() def cubic(self, directory="tmp-qe-relax-cubic", runopt="gen", auto=0, range_a=[-0.1, 0.101, 0.01]): """ """ na = len(np.arange(range_a[0], range_a[1], range_a[2])) if self.batch_a == None: # namely all in one batch self.batch_a = na else: pass if na % self.batch_a == 0: n_batch_a = int(na / self.batch_a) else: n_batch_a = int(na / self.batch_a) + 1 # # if os.path.exists(directory): shutil.rmtree(directory) os.mkdir(directory) shutil.copyfile(self.arts.xyz.file, os.path.join(directory, os.path.basename(self.arts.xyz.file))) #all_upfs = [s for s in os.listdir() if s.split(".")[-1] == "UPF"] all_file = os.listdir() for element in self.arts.xyz.specie_labels: for item in all_file: #if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE): #if item.split(".")[0].lower() == element.lower() or item.split("_")[0].lower() == element.lower(): if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE) or re.match("(%s)(_*)(upf)" % element, item, re.IGNORECASE): shutil.copyfile(item, os.path.join(directory, item)) break self.arts.pseudo.dir = os.path.abspath(directory) self.control.set_params({"pseudo_dir": os.path.abspath(directory)}) # os.chdir(directory) with open("relax.in.template", 'w') as fout: self.control.to_in(fout) self.system.to_in(fout) self.electrons.to_in(fout) self.ions.to_in(fout) coordtype = "crystal" # use crystal here so we could only change cell when opt cell fout.write("ATOMIC_SPECIES\n") all_file = os.listdir(self.arts.pseudo.dir) for element in self.arts.xyz.specie_labels: for item in all_file: if re.match("(%s)(.*)(upf)" % (element), item, re.IGNORECASE): fout.write("%s %f %s\n" % (element, base.element[element].mass, item)) break fout.write("\n") if coordtype == "angstrom": fout.write("ATOMIC_POSITIONS angstrom\n") if self.arts.ifstatic == True: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (atom.name, atom.x, atom.y, atom.z)) elif self.arts.ifstatic == False: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f" % (atom.name, atom.x, atom.y, atom.z)) for fix in atom.fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") elif coordtype == "crystal": # crystal namely fractional coordinate can be convert from cartesian coordinates # the conversion process is like transformation of presentation in quantum mechanics # the convmat is bulid to do the conversion #latcell = np.array(self.xyz.cell) #latcell = latcell.reshape(3, 3) latcell = np.array(self.arts.xyz.cell) convmat = np.linalg.inv(latcell.T) crystal_coord = np.zeros([self.arts.xyz.natom, 3]) for i in range(self.arts.xyz.natom): crystal_coord[i] = convmat.dot(np.array([self.arts.xyz.atoms[i].x, self.arts.xyz.atoms[i].y, self.arts.xyz.atoms[i].z])) # fout.write("ATOMIC_POSITIONS crystal\n") if self.arts.ifstatic == True: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) elif self.arts.ifstatic == False: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) for fix in self.arts.xyz.atoms[k].fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") # end crystal type ATOMIC_POSITIONS # writing KPOINTS to the fout self.arts.write_kpoints(fout) # ========================= # # writing forces act on atoms if self.arts.atomic_forces_status == True: self.arts.write_atomic_forces(fout) # ========================= for i_batch_a in range(n_batch_a): # gen llhpc script with open("relax-cubic-%d.slurm" % (i_batch_a), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d\n" % (self.run_params["jobname"], i_batch_a)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") # gen pbs script with open("relax-cubic-%d.pbs" % (i_batch_a), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#PBS -N %s-%d\n" % (self.run_params["jobname"], i_batch_a)) fout.write("#PBS -l nodes=%d:ppn=%d\n" % (self.run_params["nodes"], self.run_params["ppn"])) if "queue" in self.run_params and self.run_params["queue"] != None: fout.write("#PBS -q %s\n" %self.run_params["queue"]) fout.write("\n") fout.write("cd $PBS_O_WORKDIR\n") fout.write("NP=`cat $PBS_NODEFILE | wc -l`\n") #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") # gen local bash script with open("relax-cubic-%d.sh" % (i_batch_a), 'w') as fout: fout.write("#!/bin/bash\n") a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${a}.in | tee relax-${a}.out\n" % self.run_params["mpi"]) fout.write("done\n") # gen cdcloud script with open("relax-cubic-%d.slurm_cd" % (i_batch_a), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d\n" % (self.run_params["jobname"], i_batch_a)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) fout.write("#\n") fout.write("export I_MPI_PMI_LIBRARY=/opt/gridview/slurm/lib/libpmi.so\n") #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${a} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") # generate result analysis script os.system("mkdir -p post-processing") with open("post-processing/get_energy.sh", 'w') as fout: fout.write("#!/bin/bash\n") fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: a energy(Ry)\n") fout.write("EOF\n") fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a[0], range_a[2], a+range_a[1])) fout.write("do\n") fout.write(" energy=`cat ../relax-${a}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${a} ${energy:32:-2}\n") fout.write("EOF\n") fout.write("done\n") fout.write("cat > energy-latconst.gp<<EOF\n") fout.write("set term gif\n") fout.write("set output 'energy-latconst.gif'\n") fout.write("set title 'Energy Latconst'\n") fout.write("set xlabel 'latconst(a)'\n") fout.write("set ylabel 'Energy'\n") fout.write("plot 'energy-latconst.data' w l\n") fout.write("EOF\n") fout.write("gnuplot energy-latconst.gp\n") #os.system("cd post-processing; bash get_energy.sh; cd ../") os.chdir("../") if runopt == "run" or runopt == "genrun": os.chdir(directory) for i_batch_a in range(n_batch_a): os.system("bash relax-cubic-%d.sh" % i_batch_a) os.chdir("../") for i_batch_a in range(n_batch_a): server_handle(auto=auto, directory=directory, jobfilebase="relax-cubic-%d" % i_batch_a, server=self.run_params["server"]) def hexagonal(self, directory="tmp-qe-hexagonal", runopt="gen", auto=0, range_a=[-0.1, 0.101, 0.01], range_c=[-0.1, 0.101, 0.01]): """ """ na = len(np.arange(range_a[0], range_a[1], range_a[2])) nc = len(np.arange(range_c[0], range_c[1], range_c[2])) if self.batch_a == None: # namely all in one batch self.batch_a = na else: pass if self.batch_c == None: # namely all in one batch self.batch_c = nc else: pass if na % self.batch_a == 0: n_batch_a = int(na / self.batch_a) else: n_batch_a = int(na / self.batch_a) + 1 if nc % self.batch_c == 0: n_batch_c = int(nc / self.batch_c) else: n_batch_c = int(nc / self.batch_c) + 1 # if os.path.exists(directory): shutil.rmtree(directory) os.mkdir(directory) shutil.copyfile(self.arts.xyz.file, os.path.join(directory, os.path.basename(self.arts.xyz.file))) #all_upfs = [s for s in os.listdir() if s.split(".")[-1] == "UPF"] all_file = os.listdir() for element in self.arts.xyz.specie_labels: for item in all_file: #if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE): #if item.split(".")[0].lower() == element.lower() or item.split("_")[0].lower() == element.lower(): if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE) or re.match("(%s)(_*)(upf)" % element, item, re.IGNORECASE): shutil.copyfile(item, os.path.join(directory, item)) break self.arts.pseudo.dir = os.path.abspath(directory) self.control.set_params({"pseudo_dir": os.path.abspath(directory)}) # os.chdir(directory) with open("relax.in.template", 'w') as fout: self.control.to_in(fout) self.system.to_in(fout) self.electrons.to_in(fout) self.ions.to_in(fout) coordtype = "crystal" # use crystal here so we could only change cell when opt cell fout.write("ATOMIC_SPECIES\n") all_file = os.listdir(self.arts.pseudo.dir) for element in self.arts.xyz.specie_labels: for item in all_file: if re.match("(%s)(.*)(upf)" % (element), item, re.IGNORECASE): fout.write("%s %f %s\n" % (element, base.element[element].mass, item)) break fout.write("\n") if coordtype == "angstrom": fout.write("ATOMIC_POSITIONS angstrom\n") if self.arts.ifstatic == True: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (atom.name, atom.x, atom.y, atom.z)) elif self.arts.ifstatic == False: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f" % (atom.name, atom.x, atom.y, atom.z)) for fix in atom.fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") elif coordtype == "crystal": # crystal namely fractional coordinate can be convert from cartesian coordinates # the conversion process is like transformation of presentation in quantum mechanics # the convmat is bulid to do the conversion #latcell = np.array(self.xyz.cell) #latcell = latcell.reshape(3, 3) latcell = np.array(self.arts.xyz.cell) convmat = np.linalg.inv(latcell.T) crystal_coord = np.zeros([self.arts.xyz.natom, 3]) for i in range(self.arts.xyz.natom): crystal_coord[i] = convmat.dot(np.array([self.arts.xyz.atoms[i].x, self.arts.xyz.atoms[i].y, self.arts.xyz.atoms[i].z])) # fout.write("ATOMIC_POSITIONS crystal\n") if self.arts.ifstatic == True: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) elif self.arts.ifstatic == False: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) for fix in self.arts.xyz.atoms[k].fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") # end crystal type ATOMIC_POSITIONS # writing KPOINTS to the fout self.arts.write_kpoints(fout) # ========================= # # writing forces act on atoms if self.arts.atomic_forces_status == True: self.arts.write_atomic_forces(fout) # ========================= for i_batch_a in range(n_batch_a): for i_batch_c in range(n_batch_c): # gen llhpc script with open("relax-hexagonal-%d-%d.slurm" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_c)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") # here with the usage of length and scale in bs processing, we can make sure that number like '.123' will be correctly # set as '0.123', namely the ommited 0 by bs by default is not ommited now! fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${a}-${c}.in > relax-${a}-${c}.out\n") fout.write("done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${c}.in > relax-${c}.out\n") fout.write("done\n") else: # neither a or c is optimized pass # gen pbs script with open("relax-hexagonal-%d-%d.pbs" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#PBS -N %s-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_c)) fout.write("#PBS -l nodes=%d:ppn=%d\n" % (self.run_params["nodes"], self.run_params["ppn"])) if "queue" in self.run_params and self.run_params["queue"] != None: fout.write("#PBS -q %s\n" %self.run_params["queue"]) fout.write("\n") fout.write("cd $PBS_O_WORKDIR\n") fout.write("NP=`cat $PBS_NODEFILE | wc -l`\n") #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") # here with the usage of length and scale in bs processing, we can make sure that number like '.123' will be correctly # set as '0.123', namely the ommited 0 by bs by default is not ommited now! fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${a}-${c}.in > relax-${a}-${c}.out\n") fout.write("done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${c}.in > relax-${c}.out\n") fout.write("done\n") else: # neither a or c is optimized pass # gen local bash script with open("relax-hexagonal-%d-%d.sh" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") # here with the usage of length and scale in bs processing, we can make sure that number like '.123' will be correctly # set as '0.123', namely the ommited 0 by bs by default is not ommited now! fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${a}-${c}.in | tee relax-${a}-${c}.out\n" % self.run_params["mpi"]) fout.write("done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${a}.in | tee relax-${a}.out\n" % self.run_params["mpi"]) fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${c}.in | tee relax-${c}.out\n" % self.run_params["mpi"]) fout.write("done\n") else: # neither a or c is optimized pass # gen cdcloud script with open("relax-hexagonal-%d-%d.slurm_cd" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_c)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) fout.write("#\n") fout.write("export I_MPI_PMI_LIBRARY=/opt/gridview/slurm/lib/libpmi.so\n") #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") # here with the usage of length and scale in bs processing, we can make sure that number like '.123' will be correctly # set as '0.123', namely the ommited 0 by bs by default is not ommited now! fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${a}-${c}.in > relax-${a}-${c}.out\n") fout.write("done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${c}.in > relax-${c}.out\n") fout.write("done\n") else: # neither a or c is optimized pass # generate result analysis script os.system("mkdir -p post-processing") with open("post-processing/get_energy.sh", 'w') as fout: fout.write("#!/bin/bash\n") # the comment if na >= 2 and nc >= 2: fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: a c energy(Ry)\n") fout.write("EOF\n") if na >= 2 and nc < 2: fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: a energy(Ry)\n") fout.write("EOF\n") if na < 2 and nc >= 2: fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: c energy(Ry)\n") fout.write("EOF\n") # end if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a[0], range_a[2], a+range_a[1])) fout.write("do\n") if nc >= 2: # both a and c are optimized fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c[0], range_c[2], c+range_c[1])) fout.write("do\n") fout.write(" energy=`cat ../relax-${a}-${c}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${a} ${c} ${energy:32:-2}\n") fout.write("EOF\n") fout.write("done\n") fout.write("doen\n") fout.write("cat > energy-latconst.gp<<EOF\n") fout.write("set term gif\n") fout.write("set output 'energy-latconst.gif'\n") fout.write("set title 'Energy Latconst'\n") fout.write("set xlabel 'latconst(a)'\n") fout.write("set ylabel 'latconst(c)'\n") fout.write("set zlabel 'Energy'\n") fout.write("splot 'energy-latconst.data'\n") fout.write("EOF\n") else: fout.write(" energy=`cat ../relax-${a}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${a} ${energy:32:-2}\n") fout.write("EOF\n") fout.write("done\n") fout.write("cat > energy-latconst.gp<<EOF\n") fout.write("set term gif\n") fout.write("set output 'energy-latconst.gif'\n") fout.write("set title 'Energy Latconst'\n") fout.write("set xlabel 'latconst(a)'\n") fout.write("set ylabel 'Energy'\n") fout.write("plot 'energy-latconst.data' w l\n") fout.write("EOF\n") else: # a is not optimized if nc >= 2: # only c is optimized fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c[0], range_c[2], c+range_c[1])) fout.write("do\n") fout.write(" energy=`cat ../relax-${c}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${c} ${energy:32:-2}\n") fout.write("EOF\n") fout.write("done\n") fout.write("cat > energy-latconst.gp<<EOF\n") fout.write("set term gif\n") fout.write("set output 'energy-latconst.gif'\n") fout.write("set title 'Energy Latconst'\n") fout.write("set xlabel 'latconst(c)'\n") fout.write("set ylabel 'Energy'\n") fout.write("plot 'energy-latconst.data' w l\n") fout.write("EOF\n") else: # neither a nor c is optimized pass fout.write("gnuplot energy-latconst.gp\n") #os.system("cd post-processing; bash get_energy.sh; cd ../") os.chdir("../") if runopt == "run" or runopt == "genrun": os.chdir(directory) for i_batch_a in range(n_batch_a): for i_batch_c in range(n_batch_c): os.system("bash relax-hexagonal-%d-%d.sh" % (i_batch_a, i_batch_c)) os.chdir("../") for i_batch_a in range(n_batch_a): for i_batch_c in range(n_batch_c): server_handle(auto=auto, directory=directory, jobfilebase="relax-hexagonal-%d-%d" % (i_batch_a, i_batch_c), server=self.run_params["server"]) def tetragonal(self, directory="tmp-qe-relax-tetragonal", runopt="gen", auto=0, range_a=[-0.1, 0.101, 0.01], range_c=[-0.1, 0.101, 0.01]): """ """ na = len(np.arange(range_a[0], range_a[1], range_a[2])) nc = len(np.arange(range_c[0], range_c[1], range_c[2])) if self.batch_a == None: # namely all in one batch self.batch_a = na else: pass if self.batch_c == None: # namely all in one batch self.batch_c = nc else: pass if na % self.batch_a == 0: n_batch_a = int(na / self.batch_a) else: n_batch_a = int(na / self.batch_a) + 1 if nc % self.batch_c == 0: n_batch_c = int(nc / self.batch_c) else: n_batch_c = int(nc / self.batch_c) + 1 # if os.path.exists(directory): shutil.rmtree(directory) os.mkdir(directory) shutil.copyfile(self.arts.xyz.file, os.path.join(directory, os.path.basename(self.arts.xyz.file))) #all_upfs = [s for s in os.listdir() if s.split(".")[-1] == "UPF"] all_file = os.listdir() for element in self.arts.xyz.specie_labels: for item in all_file: #if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE): #if item.split(".")[0].lower() == element.lower() or item.split("_")[0].lower() == element.lower(): if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE) or re.match("(%s)(_*)(upf)" % element, item, re.IGNORECASE): shutil.copyfile(item, os.path.join(directory, item)) break self.arts.pseudo.dir = os.path.abspath(directory) self.control.set_params({"pseudo_dir": os.path.abspath(directory)}) # os.chdir(directory) with open("relax.in.template", 'w') as fout: self.control.to_in(fout) self.system.to_in(fout) self.electrons.to_in(fout) self.ions.to_in(fout) coordtype = "crystal" # use crystal here so we could only change cell when opt cell fout.write("ATOMIC_SPECIES\n") all_file = os.listdir(self.arts.pseudo.dir) for element in self.arts.xyz.specie_labels: for item in all_file: if re.match("(%s)(.*)(upf)" % (element), item, re.IGNORECASE): fout.write("%s %f %s\n" % (element, base.element[element].mass, item)) break fout.write("\n") if coordtype == "angstrom": fout.write("ATOMIC_POSITIONS angstrom\n") if self.arts.ifstatic == True: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (atom.name, atom.x, atom.y, atom.z)) elif self.arts.ifstatic == False: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f" % (atom.name, atom.x, atom.y, atom.z)) for fix in atom.fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") elif coordtype == "crystal": # crystal namely fractional coordinate can be convert from cartesian coordinates # the conversion process is like transformation of presentation in quantum mechanics # the convmat is bulid to do the conversion #latcell = np.array(self.xyz.cell) #latcell = latcell.reshape(3, 3) latcell = np.array(self.arts.xyz.cell) convmat = np.linalg.inv(latcell.T) crystal_coord = np.zeros([self.arts.xyz.natom, 3]) for i in range(self.arts.xyz.natom): crystal_coord[i] = convmat.dot(np.array([self.arts.xyz.atoms[i].x, self.arts.xyz.atoms[i].y, self.arts.xyz.atoms[i].z])) # fout.write("ATOMIC_POSITIONS crystal\n") if self.arts.ifstatic == True: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) elif self.arts.ifstatic == False: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) for fix in self.arts.xyz.atoms[k].fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") # end crystal type ATOMIC_POSITIONS # writing KPOINTS to the fout self.arts.write_kpoints(fout) # ========================= # # writing forces act on atoms if self.arts.atomic_forces_status == True: self.arts.write_atomic_forces(fout) # ========================= for i_batch_a in range(n_batch_a): for i_batch_c in range(n_batch_c): # gen llhpc script with open("relax-tetragonal-%d-%d.slurm" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_c)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${a}-${c}.in > relax-${a}-${c}.out\n") fout.write(" done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${c}.in > relax-${c}.out\n") fout.write("done\n") else: # neither a or c is optimized pass # gen pbs script with open("relax-tetragonal-%d-%d.pbs" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#PBS -N %s-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_c)) fout.write("#PBS -l nodes=%d:ppn=%d\n" % (self.run_params["nodes"], self.run_params["ppn"])) if "queue" in self.run_params and self.run_params["queue"] != None: fout.write("#PBS -q %s\n" %self.run_params["queue"]) fout.write("\n") fout.write("cd $PBS_O_WORKDIR\n") fout.write("NP=`cat $PBS_NODEFILE | wc -l`\n") #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${a}-${c}.in > relax-${a}-${c}.out\n") fout.write(" done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${c}.in > relax-${c}.out\n") fout.write("done\n") else: # neither a or c is optimized pass # gen local bash script with open("relax-tetragonal-%d-%d.bash" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${a}-${c}.in | tee relax-${a}-${c}.out\n" % self.run_params["mpi"]) fout.write(" done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${a}.in | tee relax-${a}.out\n" % self.run_params["mpi"]) fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${c}.in | tee relax-${c}.out\n" % self.run_params["mpi"]) fout.write("done\n") else: # neither a or c is optimized pass # gen cdcloud script with open("relax-tetragonal-%d-%d.slurm_cd" % (i_batch_a, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_c)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) fout.write("#\n") fout.write("export I_MPI_PMI_LIBRARY=/opt/gridview/slurm/lib/libpmi.so\n") #fout.write("mpirun -np $NP -machinefile $PBS_NODEFILE %s < %s > %s\n" % (cmd, inpname, output)) a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") if nc >= 2: # optimize both a and c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${a}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${a}-${c}.in > relax-${a}-${c}.out\n") fout.write(" done\n") else: # only optimize a fout.write(" cp relax.in.template relax-${a}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c_in} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${a}.in > relax-${a}.out\n") fout.write("done\n") else: # a is not optimized if nc >= 2: # only optimize c fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") fout.write(" cp relax.in.template relax-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${a_in} / ${a_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${c}.in<<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${c}.in > relax-${c}.out\n") fout.write("done\n") else: # neither a or c is optimized pass # generate result analysis script os.system("mkdir -p post-processing") with open("post-processing/get_energy.sh", 'w') as fout: fout.write("#!/bin/bash\n") # the comment if na >= 2 and nc >= 2: fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: a c energy(Ry)\n") fout.write("EOF\n") if na >= 2 and nc < 2: fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: a energy(Ry)\n") fout.write("EOF\n") if na < 2 and nc >= 2: fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: c energy(Ry)\n") fout.write("EOF\n") # end if na >= 2: # a is optimized fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a[0], range_a[2], a+range_a[1])) fout.write("do\n") if nc >= 2: # both a and c are optimized fout.write(" for c in `seq -w %f %f %f`\n" % (c+range_c[0], range_c[2], c+range_c[1])) fout.write(" do\n") fout.write(" energy=`cat ../relax-${a}-${c}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${a} ${c} ${energy:32:-2}\n") fout.write("EOF\n") fout.write(" done\n") fout.write("done\n") fout.write("cat > energy-latconst.gp<<EOF\n") fout.write("set term gif\n") fout.write("set output 'energy-latconst.gif'\n") fout.write("set title 'Energy Latconst'\n") fout.write("set xlabel 'latconst(a)'\n") fout.write("set ylabel 'latconst(c)'\n") fout.write("set zlabel 'Energy'\n") fout.write("splot 'energy-latconst.data'\n") fout.write("EOF\n") else: fout.write(" energy=`cat ../relax-${a}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${a} ${energy:32:-2}\n") fout.write("EOF\n") fout.write("done\n") fout.write("cat > energy-latconst.gp<<EOF\n") fout.write("set term gif\n") fout.write("set output 'energy-latconst.gif'\n") fout.write("set title 'Energy Latconst'\n") fout.write("set xlabel 'latconst(a)'\n") fout.write("set ylabel 'Energy'\n") fout.write("plot 'energy-latconst.data' w l\n") fout.write("EOF\n") else: # a is not optimized if nc >= 2: # only c is optimized fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c[0], range_c[2], c+range_c[1])) fout.write("do\n") fout.write(" energy=`cat ../relax-${c}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${c} ${energy:32:-2}\n") fout.write("EOF\n") fout.write("done\n") fout.write("cat > energy-latconst.gp<<EOF\n") fout.write("set term gif\n") fout.write("set output 'energy-latconst.gif'\n") fout.write("set title 'Energy Latconst'\n") fout.write("set xlabel 'latconst(c)'\n") fout.write("set ylabel 'Energy'\n") fout.write("plot 'energy-latconst.data' w l\n") fout.write("EOF\n") else: # neither a nor c is optimized pass fout.write("gnuplot energy-latconst.gp\n") #os.system("cd post-processing; bash get_energy.sh; cd ../") os.chdir("../") if runopt == "run" or runopt == "genrun": os.chdir(directory) for i_batch_a in range(n_batch_a): for i_batch_c in range(n_batch_c): os.system("bash relax-tetragonal-%d-%d.sh" % (i_batch_a, i_batch_c)) os.chdir("../") for i_batch_a in range(n_batch_a): for i_batch_c in range(n_batch_c): server_handle(auto=auto, directory=directory, jobfilebase="relax-tetragonal-%d-%d" % (i_batch_a, i_batch_c), server=self.run_params["server"]) def abc(self, directory="tmp-qe-opt-abc", runopt="gen", auto=0, range_a=[-0.1, 0.1, 0.01], range_b=[-0.1, 0.1, 0.01], range_c=[-0.1, 0.1, 0.01]): """ """ na = len(np.arange(range_a[0], range_a[1], range_a[2])) nb = len(np.arange(range_b[0], range_b[1], range_b[2])) nc = len(np.arange(range_c[0], range_c[1], range_c[2])) if self.batch_a == None: # namely all in one batch self.batch_a = na else: pass if self.batch_b == None: # namely all in one batch self.batch_b = nb else: pass if self.batch_c == None: # namely all in one batch self.batch_c = nc else: pass if na % self.batch_a == 0: n_batch_a = int(na / self.batch_a) else: n_batch_a = int(na / self.batch_a) + 1 if nb % self.batch_b == 0: n_batch_b = int(nb / self.batch_b) else: n_batch_b = int(nb / self.batch_b) + 1 if nc % self.batch_c == 0: n_batch_c = int(nc / self.batch_c) else: n_batch_c = int(nc / self.batch_c) + 1 # if os.path.exists(directory): shutil.rmtree(directory) os.mkdir(directory) shutil.copyfile(self.arts.xyz.file, os.path.join(directory, os.path.basename(self.arts.xyz.file))) #all_upfs = [s for s in os.listdir() if s.split(".")[-1] == "UPF"] all_file = os.listdir() for element in self.arts.xyz.specie_labels: for item in all_file: #if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE): #if item.split(".")[0].lower() == element.lower() or item.split("_")[0].lower() == element.lower(): if re.match("(%s)(.*)(upf)" % element, item, re.IGNORECASE) or re.match("(%s)(_*)(upf)" % element, item, re.IGNORECASE): shutil.copyfile(item, os.path.join(directory, item)) break self.arts.pseudo.dir = os.path.abspath(directory) self.control.set_params({"pseudo_dir": os.path.abspath(directory)}) # os.chdir(directory) with open("relax.in.template", 'w') as fout: self.control.to_in(fout) self.system.to_in(fout) self.electrons.to_in(fout) self.ions.to_in(fout) coordtype = "crystal" # use crystal here so we could only change cell when opt cell fout.write("ATOMIC_SPECIES\n") all_file = os.listdir(self.arts.pseudo.dir) for element in self.arts.xyz.specie_labels: for item in all_file: #if re.match("(%s)(.*)(upf)" % (element), item, re.IGNORECASE): if item.split(".")[0].lower() == element.lower() or item.split("_")[0].lower() == element.lower(): fout.write("%s %f %s\n" % (element, base.element[element].mass, item)) break fout.write("\n") if coordtype == "angstrom": fout.write("ATOMIC_POSITIONS angstrom\n") if self.arts.ifstatic == True: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (atom.name, atom.x, atom.y, atom.z)) elif self.arts.ifstatic == False: for atom in self.arts.xyz.atoms: fout.write("%s\t%.9f\t%.9f\t%.9f" % (atom.name, atom.x, atom.y, atom.z)) for fix in atom.fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") elif coordtype == "crystal": # crystal namely fractional coordinate can be convert from cartesian coordinates # the conversion process is like transformation of presentation in quantum mechanics # the convmat is bulid to do the conversion #latcell = np.array(self.xyz.cell) #latcell = latcell.reshape(3, 3) latcell = np.array(self.arts.xyz.cell) convmat = np.linalg.inv(latcell.T) crystal_coord = np.zeros([self.arts.xyz.natom, 3]) for i in range(self.arts.xyz.natom): crystal_coord[i] = convmat.dot(np.array([self.arts.xyz.atoms[i].x, self.arts.xyz.atoms[i].y, self.arts.xyz.atoms[i].z])) # fout.write("ATOMIC_POSITIONS crystal\n") if self.arts.ifstatic == True: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f\n" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) elif self.arts.ifstatic == False: for k in range(self.arts.xyz.natom): fout.write("%s\t%.9f\t%.9f\t%.9f" % (self.arts.xyz.atoms[k].name, crystal_coord[k, 0], crystal_coord[k, 1], crystal_coord[k, 2])) for fix in self.arts.xyz.atoms[k].fix: if fix == True: fout.write("\t0") elif fix == False: fout.write("\t1") fout.write("\n") else: print("===============================================\n") print("warning: qe.base.arts.to_in():\n") print("arts.ifstatic could only be True or False\n") sys.exit(1) fout.write("\n") # end crystal type ATOMIC_POSITIONS # writing KPOINTS to the fout self.arts.write_kpoints(fout) # ========================= # # writing forces act on atoms if self.arts.atomic_forces_status == True: self.arts.write_atomic_forces(fout) # ========================= for i_batch_a in range(n_batch_a): for i_batch_b in range(n_batch_b): for i_batch_c in range(n_batch_c): range_a_start = range_a[0] + i_batch_a * self.batch_a * range_a[2] range_a_end = range_a[0] + (i_batch_a+1) * self.batch_a * range_a[2] - range_a[2] / 2 # - range_a[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_a_end > range_a[1]: range_a_end = range_a[1] range_b_start = range_b[0] + i_batch_b * self.batch_b * range_b[2] range_b_end = range_b[0] + (i_batch_b+1) * self.batch_b * range_b[2] - range_b[2] / 2 # - range_b[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_b_end > range_b[1]: range_b_end = range_b[1] range_c_start = range_c[0] + i_batch_c * self.batch_c * range_c[2] range_c_end = range_c[0] + (i_batch_c+1) * self.batch_c * range_c[2] - range_c[2] / 2 # - range_c[2] / 2, so that the last value is ignored which is actually the begining of next batch if range_c_end > range_c[1]: range_c_end = range_c[1] a = np.sqrt(self.arts.xyz.cell[0][0]**2+self.arts.xyz.cell[0][1]**2+self.arts.xyz.cell[0][2]**2) b = np.sqrt(self.arts.xyz.cell[1][0]**2+self.arts.xyz.cell[1][1]**2+self.arts.xyz.cell[1][2]**2) c = np.sqrt(self.arts.xyz.cell[2][0]**2+self.arts.xyz.cell[2][1]**2+self.arts.xyz.cell[2][2]**2) # gen llhpc script with open("opt-abc-%d-%d-%d.slurm" % (i_batch_a, i_batch_b, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_b, i_batch_c)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write("for b in `seq -w %f %f %f`\n" % (b+range_b_start, range_b[2], b+range_b_end)) fout.write("do\n") fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") #fout.write(" mkdir relax-${a}-${b}-${c}\n") fout.write(" cp relax.in.template relax-${a}-${b}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${b}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" yhrun $PMF_PWX < relax-${a}-${b}-${c}.in > relax-${a}-${b}-${c}.out\n") fout.write("done\n") fout.write("done\n") fout.write("done\n") # gen pbs script with open("opt-abc-%d-%d-%d.pbs" % (i_batch_a, i_batch_b, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#PBS -N %s-%d-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_b, i_batch_c)) fout.write("#PBS -l nodes=%d:ppn=%d\n" % (self.run_params["nodes"], self.run_params["ppn"])) if "queue" in self.run_params and self.run_params["queue"] != None: fout.write("#PBS -q %s\n" %self.run_params["queue"]) fout.write("\n") fout.write("cd $PBS_O_WORKDIR\n") fout.write("NP=`cat $PBS_NODEFILE | wc -l`\n") fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write("for b in `seq -w %f %f %f`\n" % (b+range_b_start, range_b[2], b+range_b_end)) fout.write("do\n") fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") #fout.write(" mkdir relax-${a}-${b}-${c}\n") fout.write(" cp relax.in.template relax-${a}-${b}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${b}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" mpirun -np $NP -machinefile $PBS_NODEFILE $PMF_PWX < relax-${a}-${b}-${c}.in > relax-${a}-${b}-${c}.out\n") fout.write("done\n") fout.write("done\n") fout.write("done\n") # gen local bash script with open("opt-abc-%d-%d-%d.sh" % (i_batch_a, i_batch_b, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write("for b in `seq -w %f %f %f`\n" % (b+range_b_start, range_b[2], b+range_b_end)) fout.write("do\n") fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") #fout.write(" mkdir relax-${a}-${b}-${c}\n") fout.write(" cp relax.in.template relax-${a}-${b}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${b}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${a}-${b}-${c}.in | tee relax-${a}-${b}-${c}.out\n" % self.run_params["mpi"]) fout.write("done\n") fout.write("done\n") fout.write("done\n") # gen lsf_sz script with open("opt-abc-%d-%d-%d.lsf_sz" % (i_batch_a,i_batch_b, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("APP_NAME=%s\n" % self.run_params["queue"]) fout.write("NP=%d\n" % (self.run_params["nodes"]*self.run_params["ppn"])) fout.write("NP_PER_NODE=%d\n" % self.run_params["ppn"]) fout.write("RUN=\"RAW\"\n") fout.write("CURDIR=$PWD\n") fout.write("#VASP=/home-yg/Soft/Vasp5.4/vasp_std\n") fout.write("source /home-yg/env/intel-12.1.sh\n") fout.write("source /home-yg/env/openmpi-1.6.5-intel.sh\n") fout.write("cd $CURDIR\n") fout.write("# starting creating ./nodelist\n") fout.write("rm -rf $CURDIR/nodelist >& /dev/null\n") fout.write("for i in `echo $LSB_HOSTS`\n") fout.write("do\n") fout.write(" echo \"$i\" >> $CURDIR/nodelist \n") fout.write("done\n") fout.write("ndoelist=$(cat $CURDIR/nodelist | uniq | awk \'{print $1}\' | tr \'\n\' \',\')\n") fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write("for b in `seq -w %f %f %f`\n" % (b+range_b_start, range_b[2], b+range_b_end)) fout.write("do\n") fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") #fout.write(" mkdir relax-${a}-${b}-${c}\n") fout.write(" cp relax.in.template relax-${a}-${b}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${b}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" %s $PMF_PWX < relax-${a}-${b}-${c}.in | tee relax-${a}-${b}-${c}.out\n" % self.run_params["mpi"]) fout.write("done\n") fout.write("done\n") fout.write("done\n") # gen cdcloud script with open("opt-abc-%d-%d-%d.slurm_cd" % (i_batch_a, i_batch_b, i_batch_c), 'w') as fout: fout.write("#!/bin/bash\n") fout.write("#SBATCH -p %s\n" % self.run_params["partition"]) fout.write("#SBATCH -N %d\n" % self.run_params["nodes"]) fout.write("#SBATCH -n %d\n" % self.run_params["ntask"]) fout.write("#SBATCH -J %s-%d-%d-%d\n" % (self.run_params["jobname"], i_batch_a, i_batch_b, i_batch_c)) fout.write("#SBATCH -o %s\n" % self.run_params["stdout"]) fout.write("#SBATCH -e %s\n" % self.run_params["stderr"]) fout.write("#\n") fout.write("export I_MPI_PMI_LIBRARY=/opt/gridview/slurm/lib/libpmi.so\n") fout.write("a_in=%f\n" % a) fout.write("b_in=%f\n" % b) fout.write("c_in=%f\n" % c) fout.write("a1=%f\n" % self.arts.xyz.cell[0][0]) fout.write("a2=%f\n" % self.arts.xyz.cell[0][1]) fout.write("a3=%f\n" % self.arts.xyz.cell[0][2]) fout.write("b1=%f\n" % self.arts.xyz.cell[1][0]) fout.write("b2=%f\n" % self.arts.xyz.cell[1][1]) fout.write("b3=%f\n" % self.arts.xyz.cell[1][2]) fout.write("c1=%f\n" % self.arts.xyz.cell[2][0]) fout.write("c2=%f\n" % self.arts.xyz.cell[2][1]) fout.write("c3=%f\n" % self.arts.xyz.cell[2][2]) fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a_start, range_a[2], a+range_a_end)) fout.write("do\n") fout.write("for b in `seq -w %f %f %f`\n" % (b+range_b_start, range_b[2], b+range_b_end)) fout.write("do\n") fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c_start, range_c[2], c+range_c_end)) fout.write("do\n") #fout.write(" mkdir relax-${a}-${b}-${c}\n") fout.write(" cp relax.in.template relax-${a}-${b}-${c}.in\n") fout.write(" vec11=$(printf \"%-.6f\" `echo \"scale=6; result=${a1} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec12=$(printf \"%-.6f\" `echo \"scale=6; result=${a2} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec13=$(printf \"%-.6f\" `echo \"scale=6; result=${a3} * ${a} / ${a_in}; print result\" | bc`)\n") fout.write(" vec21=$(printf \"%-.6f\" `echo \"scale=6; result=${b1} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec22=$(printf \"%-.6f\" `echo \"scale=6; result=${b2} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec23=$(printf \"%-.6f\" `echo \"scale=6; result=${b3} * ${b} / ${b_in}; print result\" | bc`)\n") fout.write(" vec31=$(printf \"%-.6f\" `echo \"scale=6; result=${c1} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec32=$(printf \"%-.6f\" `echo \"scale=6; result=${c2} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" vec33=$(printf \"%-.6f\" `echo \"scale=6; result=${c3} * ${c} / ${c_in}; print result\" | bc`)\n") fout.write(" cat >> relax-${a}-${b}-${c}.in <<EOF\n") fout.write("\n") fout.write("CELL_PARAMETERS angstrom\n") fout.write("${vec11} ${vec12} ${vec13}\n") fout.write("${vec21} ${vec22} ${vec23}\n") fout.write("${vec31} ${vec32} ${vec33}\n") fout.write("EOF\n") fout.write(" srun --mpi=pmix_v3 $PMF_PWX < relax-${a}-${b}-${c}.in > relax-${a}-${b}-${c}.out\n") fout.write("done\n") fout.write("done\n") fout.write("done\n") # generate result analysis script os.system("mkdir -p post-processing") with open("post-processing/get_energy.sh", 'w') as fout: fout.write("#!/bin/bash\n") # the comment fout.write("cat > energy-latconst.data <<EOF\n") fout.write("# format: a b c energy(Ry)\n") fout.write("EOF\n") # end fout.write("for a in `seq -w %f %f %f`\n" % (a+range_a[0], range_a[2], a+range_a[1])) fout.write("do\n") fout.write("for b in `seq -w %f %f %f`\n" % (b+range_b[0], range_b[2], b+range_b[1])) fout.write("do\n") fout.write("for c in `seq -w %f %f %f`\n" % (c+range_c[0], range_c[2], c+range_c[1])) fout.write("do\n") fout.write(" energy=`cat ../relax-${a}-${b}-${c}.out | grep '! total energy' | tail -1`\n") fout.write(" cat >> energy-latconst.data <<EOF\n") fout.write("${a} ${b} ${c} ${energy:32:-2}\n") fout.write("EOF\n") fout.write("done\n") fout.write("done\n") fout.write("done\n") #fout.write("cat > energy-latconst.gp<<EOF\n") #fout.write("set term gif\n") #fout.write("set output 'energy-latconst.gif'\n") #fout.write("set title 'Energy Latconst'\n") #fout.write("set xlabel 'latconst(a)'\n") #fout.write("set ylabel 'latconst(c)'\n") #fout.write("set zlabel 'Energy'\n") #fout.write("splot 'energy-latconst.data'\n") #fout.write("EOF\n") #fout.write("\n") #fout.write("gnuplot energy-latconst.gp") os.chdir("../") if runopt == "run" or runopt == "genrun": os.chdir(directory) for i_batch_a in range(n_batch_a): for i_batch_b in range(n_batch_b): for i_batch_c in range(n_batch_c): os.system("bash opt-abc-%d-%d-%d.sh" % (i_batch_a, i_batch_b, i_batch_c)) os.chdir("../") for i_batch_a in range(n_batch_a): for i_batch_b in range(n_batch_b): for i_batch_c in range(n_batch_c): server_handle(auto=auto, directory=directory, jobfilebase="opt-abc-%d-%d-%d" % (i_batch_a, i_batch_b, i_batch_c), server=self.run_params["server"])

69.376769

222

0.431575

20,959

166,643

3.337755

0.019371

0.165704

0.116073

0.072174

0.982732

0.978815

0.976714

0.971854

0.967437

0.964864

0

0.03457

0.378906

166,643

2,401

223

69.405664

0.641327

0.066741

0

0.952972

0

0.017054

0.207873

0.018507

0

1

0.004651

false

0.009302

0.003618

0

0.008786

0.166408

0

null

0

1

0

1

0

null

0

7

c0f4098fa2c91e2b004cf73197cfbcc5d427a223

4,064

py

Python

programm/ball.py

team172011/ps_cagebot

ab6f7bdbc74ad3baee3feebc4b7b0fa4f726b179

[ "MIT" ]

null

programm/ball.py

team172011/ps_cagebot

ab6f7bdbc74ad3baee3feebc4b7b0fa4f726b179

[ "MIT" ]

null

programm/ball.py

team172011/ps_cagebot

ab6f7bdbc74ad3baee3feebc4b7b0fa4f726b179

[ "MIT" ]

null

#!/usr/bin/env python # coding: utf8 import general def calculatemotorspeedsball(horact, actradius): # global leftspeedvalue # global rightspeedvalue # global speedvalue # global horact # global actradius steermultiplier = 0 # unter diesem Wert keine Beschleunigung minradius = 70 # ab diesem Wert verfolgt er das Objekt defaultradius = 45 # ab diesem Wert Vollgas maxradius = 25 # Maximalgeschwindigkeit des Motors maxspeed = 100 #ltrttempspeed = maxspeed/maxltrtval*(rtact-ltact) #ltrttempspeed = int(float((rtact-ltact))/(minradius-maxradius)*maxspeed) #speedvalue = ltrttempspeed = maxspeed/maxltrtval*(rtact-ltact) # Geschwindigkeit anhand des Radius ermitteln # tempspeed = (1-((actradius-maxradius)/minradius))*maxspeed tempspeed = int((1-((float(actradius)-maxradius)/minradius))*maxspeed) if tempspeed<0: tempspeed=0 elif tempspeed>100: tempspeed=100 minval = -1000 maxval = 1000 # Ab wann reagiert er steernull = 50 # Möglichkeit den Nullpunkt zu verschieben. nullmin = 0 - steernull nullmax = 0 + steernull if horact < nullmin: steermultiplier = float(horact)/minval for_left = tempspeed - (steermultiplier * maxspeed)*2 # limit left and right speed -100 >= speed <= +100 if for_left >= 0: for_left = min(100, for_left) else: for_left = max(-100, for_left) for_right = tempspeed + (steermultiplier * maxspeed)*2 if for_right >= 0: for_right = min(100, for_right) else: for_right = max(-100, for_right) general.leftspeedvalue = for_left general.rightspeedvalue = for_right elif horact > nullmax: steermultiplier = float(horact)/maxval for_left = tempspeed + (steermultiplier * maxspeed)*2 if for_left >= 0: for_left = min(100, for_left) else: for_left = max(-100, for_left) for_right = tempspeed - (steermultiplier * maxspeed)*2 if for_right > 0: for_right = min(100, for_right) else: for_right = max(-100, for_right) general.leftspeedvalue = for_left general.rightspeedvalue = for_right else: general.leftspeedvalue = general.rightspeedvalue = tempspeed print('sm: ' + str(steermultiplier) + ' actradius: ' + str(actradius) + ' tempspeed ' + str(tempspeed) + ' lsv: ' + str(general.leftspeedvalue) + ' rsv: ' + str(general.rightspeedvalue)) def calculatemotorspeedsline(horact, actradius): # global leftspeedvalue # global rightspeedvalue # global speedvalue # global horact # global actradius steermultiplier = 0 # unter diesem Wert keine Beschleunigung minradius = 70 # ab diesem Wert verfolgt er das Objekt defaultradius = 45 # ab diesem Wert Vollgas maxradius = 25 # Maximalgeschwindigkeit des Motors maxspeed = 100 #ltrttempspeed = maxspeed/maxltrtval*(rtact-ltact) #ltrttempspeed = int(float((rtact-ltact))/(minradius-maxradius)*maxspeed) #speedvalue = ltrttempspeed = maxspeed/maxltrtval*(rtact-ltact) # Geschwindigkeit anhand des Radius ermitteln # tempspeed = (1-((actradius-maxradius)/minradius))*maxspeed tempspeed = min(20, actradius) # line following always same speed minval = -1000 maxval = 1000 # Ab wann reagiert er steernull = 75 # -1000 bis 1000 # Möglichkeit den Nullpunkt zu verschieben. nullmin = 0 - steernull nullmax = 0 + steernull if horact < nullmin: steermultiplier = float(horact)/minval general.leftspeedvalue = tempspeed - (steermultiplier * maxspeed)*2 general.rightspeedvalue = tempspeed + (steermultiplier * maxspeed)*2 elif horact > nullmax: steermultiplier = float(horact)/maxval general.leftspeedvalue = tempspeed + (steermultiplier * maxspeed)*2 general.rightspeedvalue = tempspeed - (steermultiplier * maxspeed)*2 else: general.leftspeedvalue = general.rightspeedvalue = tempspeed print('sm: ' + str(steermultiplier) + ' actradius: ' + str(actradius) + ' tempspeed ' + str(tempspeed) + ' lsv: ' + str(general.leftspeedvalue) + ' rsv: ' + str(general.rightspeedvalue))

26.562092

188

0.699803

442

4,064

6.371041

0.205882

0.034801

0.090909

0.09375

0.901989

0.87358

0.838778

0.806818

0

0.033261

0.201033

4,064

152

189

26.736842

0.834001

0.317913

0

0.704225

0

0.028519

0

1

0.028169

false

0

0.014085

0

0.042254

0.028169

0

null

0

1

0

1

0

null

0

7

23ec92ade8f4d15447de64bf45ffa8730430f2b2

5,262

py

Python

jlib.py

jskDr/jamespy

729c496732d8ec2d6ba25d6b97ef2aa02065c18c

[ "MIT" ]

null

jlib.py

jskDr/jamespy

729c496732d8ec2d6ba25d6b97ef2aa02065c18c

[ "MIT" ]

null

jlib.py

jskDr/jamespy

729c496732d8ec2d6ba25d6b97ef2aa02065c18c

[ "MIT" ]

null

import numpy as np def hello(name = 'no name'): """ name is welcome by saying hello input: name - the welcome name """ print('Hello {name}!'.format(**locals())) print('2015-3-2, 2:45pm') def check_mol_similarity(): from rdkit import Chem from rdkit import DataStructs from rdkit.Chem.Fingerprints import FingerprintMols ms = [Chem.MolFromSmiles('CCOC'), Chem.MolFromSmiles('CCO'), Chem.MolFromSmiles('COC')] fps = [FingerprintMols.FingerprintMol(x) for x in ms] print fps[0] print DataStructs.FingerprintSimilarity( fps[0], fps[1]) print DataStructs.FingerprintSimilarity( fps[0], fps[2]) print DataStructs.FingerprintSimilarity( fps[1], fps[2]) print DataStructs.FingerprintSimilarity( fps[0], fps[0]) def mols_similarity( ms_smiles = ['CCOC', 'CCO', 'COC']): from rdkit import Chem from rdkit import DataStructs from rdkit.Chem.Fingerprints import FingerprintMols ms = [Chem.MolFromSmiles( m_sm) for m_sm in ms_smiles] # [Chem.MolFromSmiles('CCOC'), Chem.MolFromSmiles('CCO'), Chem.MolFromSmiles('COC')] fps = [FingerprintMols.FingerprintMol(x) for x in ms] print fps[0] print DataStructs.FingerprintSimilarity( fps[0], fps[1]) print DataStructs.FingerprintSimilarity( fps[0], fps[2]) print DataStructs.FingerprintSimilarity( fps[1], fps[2]) print DataStructs.FingerprintSimilarity( fps[0], fps[0]) def _mols_similarity_base_r0( ms_smiles_mid, ms_smiles_base): """ Input: dictionary type required such as {nick name: smiles code, ...} """ from rdkit import Chem from rdkit import DataStructs from rdkit.Chem.Fingerprints import FingerprintMols #processing for mid print( "Target: " + ms_smiles_mid.keys()) ms_mid = [Chem.MolFromSmiles( m_sm) for m_sm in ms_smiles_mid.values()] # [Chem.MolFromSmiles('CCOC'), Chem.MolFromSmiles('CCO'), Chem.MolFromSmiles('COC')] fps_mid = [FingerprintMols.FingerprintMol(x) for x in ms_mid] #processing for base print( "Base: " + ms_smiles_base.keys()) ms_base = [Chem.MolFromSmiles( m_sm) for m_sm in ms_smiles_base.values()] # [Chem.MolFromSmiles('CCOC'), Chem.MolFromSmiles('CCO'), Chem.MolFromSmiles('COC')] fps_base = [FingerprintMols.FingerprintMol(x) for x in ms_base] for (bx, f_b) in enumerate(fps_base): for (dx, f_d) in enumerate(fps_mid): print( "Base:{0}, Target:{1}".format( ms_smiles_base.keys()[bx], ms_smiles_mid.keys()[dx])) print( DataStructs.FingerprintSimilarity( f_b, f_d)) """ core part is generated while addition is changed for both """ def mols_similarity_base_core( ms_smiles_mid, ms_smiles_base): """ Input: dictionary type required such as {nick name: smiles code, ...} """ from rdkit import Chem from rdkit import DataStructs from rdkit.Chem.Fingerprints import FingerprintMols # Processing for mid print( "Target: ", ms_smiles_mid.keys()) ms_mid = [Chem.MolFromSmiles( m_sm) for m_sm in ms_smiles_mid.values()] # [Chem.MolFromSmiles('CCOC'), Chem.MolFromSmiles('CCO'), Chem.MolFromSmiles('COC')] fps_mid = [FingerprintMols.FingerprintMol(x) for x in ms_mid] #processing for base print( "Base: ", ms_smiles_base.keys()) ms_base = [Chem.MolFromSmiles( m_sm) for m_sm in ms_smiles_base.values()] # [Chem.MolFromSmiles('CCOC'), Chem.MolFromSmiles('CCO'), Chem.MolFromSmiles('COC')] fps_base = [FingerprintMols.FingerprintMol(x) for x in ms_base] return fps_base, fps_mid def mols_similarity_base( ms_smiles_mid, ms_smiles_base): """ Input: dictionary type required such as {nick name: smiles code, ...} """ from rdkit import DataStructs [fps_base, fps_mid] = mols_similarity_base_core( ms_smiles_mid, ms_smiles_base) for (bx, f_b) in enumerate(fps_base): for (dx, f_d) in enumerate(fps_mid): print( "Base:{0}, Target:{1}".format( ms_smiles_base.keys()[bx], ms_smiles_mid.keys()[dx])) print( DataStructs.FingerprintSimilarity( f_b, f_d)) def mols_similarity_base_return( ms_smiles_mid, ms_smiles_base, property_of_base = None): """ The results will be returned. A * w = b, A and b will be returned. return A, b, w """ from rdkit import DataStructs [fps_base, fps_mid] = mols_similarity_base_core( ms_smiles_mid, ms_smiles_base) Nb, Nm = len(fps_base), len(fps_mid) A = np.zeros( (Nm, Nb)) b = np.zeros( Nb) for (bx, f_b) in enumerate(fps_base): for (mx, f_m) in enumerate(fps_mid): print( "Base:{0}, Target:{1}".format( ms_smiles_base.keys()[bx], ms_smiles_mid.keys()[mx])) A[mx, bx] = DataStructs.FingerprintSimilarity( f_b, f_m) print( A[mx, bx]) if property_of_base: b[ bx] = property_of_base[ bx] print( b[ bx]) if property_of_base: print "b is obtained." return A, b else: return A def mols_similarity_base_get_w( ms_smiles_mid, ms_smiles_base, property_of_base): """ property_of_base, which is b, must be entered """ [A, b] = mols_similarity_base_return( ms_smiles_mid, ms_smiles_base, property_of_base) w = np.dot( np.linalg.pinv(A), b) return w

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null

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f1c888ed796a55c5a9008e90b18c27ce4153e92f

160

py

Python

lovef/io.py

lovef/.lovef

a0ede4844ce349f28bc6cfddaa94922234c16262

[ "Apache-2.0" ]

2

2018-03-17T20:17:17.000Z

2018-03-19T08:46:49.000Z

lovef/io.py

lovef/.lovef

a0ede4844ce349f28bc6cfddaa94922234c16262

[ "Apache-2.0" ]

null

lovef/io.py

lovef/.lovef

a0ede4844ce349f28bc6cfddaa94922234c16262

[ "Apache-2.0" ]

1

2020-02-09T06:00:20.000Z

import sys def readFromClipboard(): import tkinter return tkinter.Tk().clipboard_get() def readFromStdin(): return "".join(sys.stdin.readlines())

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9e80dd92e1a09b4ba8d93c520461b8e666cf8cde

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py

Python

tests/test_provider_poseidon_matchbox.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

507

2017-07-26T02:58:38.000Z

2022-01-21T12:35:13.000Z

tests/test_provider_poseidon_matchbox.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

135

2017-07-20T12:01:59.000Z

2021-10-04T22:25:40.000Z

tests/test_provider_poseidon_matchbox.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

81

2018-02-20T17:55:28.000Z

2022-01-31T07:08:40.000Z

# tests/test_provider_poseidon_matchbox.py # Automatically generated by tools/makecode.py (24-Sep-2021 15:21:35 UTC) def test_provider_import(): import terrascript.provider.poseidon.matchbox def test_resource_import(): from terrascript.resource.poseidon.matchbox import matchbox_group from terrascript.resource.poseidon.matchbox import matchbox_profile # TODO: Shortcut imports without namespace for official and supported providers. # TODO: This has to be moved into a required_providers block. # def test_version_source(): # # import terrascript.provider.poseidon.matchbox # # t = terrascript.provider.poseidon.matchbox.matchbox() # s = str(t) # # assert 'https://github.com/poseidon/terraform-provider-matchbox' in s # assert '0.4.1' in s

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0.149936

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1

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1

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7

9e8657a5e570b72f526c6b889657da67dbaa305f

85,750

py

Python

tests/test_symmetry.py

neutronpy/neutronpy

44ca74a0bef25c03397a77aafb359bb257de1fe6

[ "MIT" ]

14

2015-05-08T02:43:46.000Z

2019-05-28T03:47:32.000Z

tests/test_symmetry.py

neutronpy/neutronpy

44ca74a0bef25c03397a77aafb359bb257de1fe6

[ "MIT" ]

96

2015-02-09T01:04:33.000Z

2020-12-08T22:57:37.000Z

tests/test_symmetry.py

neutronpy/neutronpy

44ca74a0bef25c03397a77aafb359bb257de1fe6

[ "MIT" ]

5

2016-02-26T22:53:13.000Z

2018-07-16T07:13:04.000Z

# -*- coding: utf-8 -*- r"""Tests of space group symmetry operations """ import pytest from neutronpy import symmetry poses = {1: ['x,y,z'], 2: ['x,y,z', '-x,-y,-z'], 3: ['x,y,z', '-x,y,-z'], 4: ['x,y,z', '-x,y+1/2,-z'], 5: ['x,y,z', '-x,y,-z', 'x+1/2,y+1/2,z', '-x+1/2,y+1/2,-z'], 6: ['x,y,z', 'x,-y,z'], 7: ['x,y,z', 'x,-y,z+1/2'], 8: ['x,y,z', 'x,-y,z', 'x+1/2,y+1/2,z', 'x+1/2,-y+1/2,z'], 9: ['x,y,z', 'x,-y,z+1/2', 'x+1/2,y+1/2,z', 'x+1/2,-y+1/2,z+1/2'], 10: ['x,y,z', '-x,y,-z', '-x,-y,-z', 'x,-y,z'], 11: ['x,y,z', '-x,y+1/2,-z', '-x,-y,-z', 'x,-y+1/2,z'], 12: ['x,y,z', '-x,y,-z', '-x,-y,-z', 'x,-y,z', 'x+1/2,y+1/2,z', '-x+1/2,y+1/2,-z', '-x+1/2,-y+1/2,-z', 'x+1/2,-y+1/2,z'], 13: ['x,y,z', '-x,y,-z+1/2', '-x,-y,-z', 'x,-y,z+1/2'], 14: ['x,y,z', '-x,y+1/2,-z+1/2', '-x,-y,-z', 'x,-y+1/2,z+1/2'], 15: ['x,y,z', '-x,y,-z+1/2', '-x,-y,-z', 'x,-y,z+1/2', 'x+1/2,y+1/2,z', '-x+1/2,y+1/2,-z+1/2', '-x+1/2,-y+1/2,-z', 'x+1/2,-y+1/2,z+1/2'], 16: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z'], 17: ['x,y,z', '-x,-y,z+1/2', '-x,y,-z+1/2', 'x,-y,-z'], 18: ['x,y,z', '-x,-y,z', '-x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,-z'], 19: ['x,y,z', '-x+1/2,-y,z+1/2', '-x,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z'], 20: ['x,y,z', '-x,-y,z+1/2', '-x,y,-z+1/2', 'x,-y,-z', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z'], 21: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', '-x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,-z'], 22: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', '-x,y+1/2,-z+1/2', 'x,-y+1/2,-z+1/2', 'x+1/2,y,z+1/2', '-x+1/2,-y,z+1/2', '-x+1/2,y,-z+1/2', 'x+1/2,-y,-z+1/2', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', '-x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,-z'], 23: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'x+1/2,y+1/2,z+1/2', '-x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z+1/2'], 24: ['x,y,z', '-x+1/2,-y,z+1/2', '-x,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z', 'x+1/2,y+1/2,z+1/2', '-x,-y+1/2,z', '-x+1/2,y,-z', 'x,-y,-z+1/2'], 25: ['x,y,z', '-x,-y,z', 'x,-y,z', '-x,y,z'], 26: ['x,y,z', '-x,-y,z+1/2', 'x,-y,z+1/2', '-x,y,z'], 27: ['x,y,z', '-x,-y,z', 'x,-y,z+1/2', '-x,y,z+1/2'], 28: ['x,y,z', '-x,-y,z', 'x+1/2,-y,z', '-x+1/2,y,z'], 29: ['x,y,z', '-x,-y,z+1/2', 'x+1/2,-y,z', '-x+1/2,y,z+1/2'], 30: ['x,y,z', '-x,-y,z', 'x,-y+1/2,z+1/2', '-x,y+1/2,z+1/2'], 31: ['x,y,z', '-x+1/2,-y,z+1/2', 'x+1/2,-y,z+1/2', '-x,y,z'], 32: ['x,y,z', '-x,-y,z', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z'], 33: ['x,y,z', '-x,-y,z+1/2', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z+1/2'], 34: ['x,y,z', '-x,-y,z', 'x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,z+1/2'], 35: ['x,y,z', '-x,-y,z', 'x,-y,z', '-x,y,z', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z'], 36: ['x,y,z', '-x,-y,z+1/2', 'x,-y,z+1/2', '-x,y,z', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z+1/2', 'x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,z'], 37: ['x,y,z', '-x,-y,z', 'x,-y,z+1/2', '-x,y,z+1/2', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', 'x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,z+1/2'], 38: ['x,y,z', '-x,-y,z', 'x,-y,z', '-x,y,z', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', 'x,-y+1/2,z+1/2', '-x,y+1/2,z+1/2'], 39: ['x,y,z', '-x,-y,z', 'x,-y+1/2,z', '-x,y+1/2,z', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', 'x,-y,z+1/2', '-x,y,z+1/2'], 40: ['x,y,z', '-x,-y,z', 'x+1/2,-y,z', '-x+1/2,y,z', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', 'x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,z+1/2'], 41: ['x,y,z', '-x,-y,z', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', 'x+1/2,-y,z+1/2', '-x+1/2,y,z+1/2'], 42: ['x,y,z', '-x,-y,z', 'x,-y,z', '-x,y,z', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', 'x,-y+1/2,z+1/2', '-x,y+1/2,z+1/2', 'x+1/2,y,z+1/2', '-x+1/2,-y,z+1/2', 'x+1/2,-y,z+1/2', '-x+1/2,y,z+1/2', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z'], 43: ['x,y,z', '-x,-y,z', 'x+1/4,-y+1/4,z+1/4', '-x+1/4,y+1/4,z+1/4', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', 'x+1/4,-y+3/4,z+3/4', '-x+1/4,y+3/4,z+3/4', 'x+1/2,y,z+1/2', '-x+1/2,-y,z+1/2', 'x+3/4,-y+1/4,z+3/4', '-x+3/4,y+1/4,z+3/4', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', 'x+3/4,-y+3/4,z+1/4', '-x+3/4,y+3/4,z+1/4'], 44: ['x,y,z', '-x,-y,z', 'x,-y,z', '-x,y,z', 'x+1/2,y+1/2,z+1/2', '-x+1/2,-y+1/2,z+1/2', 'x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,z+1/2'], 45: ['x,y,z', '-x,-y,z', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z', 'x+1/2,y+1/2,z+1/2', '-x+1/2,-y+1/2,z+1/2', 'x,-y,z+1/2', '-x,y,z+1/2'], 46: ['x,y,z', '-x,-y,z', 'x+1/2,-y,z', '-x+1/2,y,z', 'x+1/2,y+1/2,z+1/2', '-x+1/2,-y+1/2,z+1/2', 'x,-y+1/2,z+1/2', '-x,y+1/2,z+1/2'], 47: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', '-x,-y,-z', 'x,y,-z', 'x,-y,z', '-x,y,z'], 48: ['x,y,z', '-x+1/2,-y+1/2,z', '-x+1/2,y,-z+1/2', 'x,-y+1/2,-z+1/2', '-x,-y,-z', 'x+1/2,y+1/2,-z', 'x+1/2,-y,z+1/2', '-x,y+1/2,z+1/2'], 49: ['x,y,z', '-x,-y,z', '-x,y,-z+1/2', 'x,-y,-z+1/2', '-x,-y,-z', 'x,y,-z', 'x,-y,z+1/2', '-x,y,z+1/2'], 50: ['x,y,z', '-x+1/2,-y+1/2,z', '-x+1/2,y,-z', 'x,-y+1/2,-z', '-x,-y,-z', 'x+1/2,y+1/2,-z', 'x+1/2,-y,z', '-x,y+1/2,z'], 51: ['x,y,z', '-x+1/2,-y,z', '-x,y,-z', 'x+1/2,-y,-z', '-x,-y,-z', 'x+1/2,y,-z', 'x,-y,z', '-x+1/2,y,z'], 52: ['x,y,z', '-x+1/2,-y,z', '-x+1/2,y+1/2,-z+1/2', 'x,-y+1/2,-z+1/2', '-x,-y,-z', 'x+1/2,y,-z', 'x+1/2,-y+1/2,z+1/2', '-x,y+1/2,z+1/2'], 53: ['x,y,z', '-x+1/2,-y,z+1/2', '-x+1/2,y,-z+1/2', 'x,-y,-z', '-x,-y,-z', 'x+1/2,y,-z+1/2', 'x+1/2,-y,z+1/2', '-x,y,z'], 54: ['x,y,z', '-x+1/2,-y,z', '-x,y,-z+1/2', 'x+1/2,-y,-z+1/2', '-x,-y,-z', 'x+1/2,y,-z', 'x,-y,z+1/2', '-x+1/2,y,z+1/2'], 55: ['x,y,z', '-x,-y,z', '-x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,-z', '-x,-y,-z', 'x,y,-z', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z'], 56: ['x,y,z', '-x+1/2,-y+1/2,z', '-x,y+1/2,-z+1/2', 'x+1/2,-y,-z+1/2', '-x,-y,-z', 'x+1/2,y+1/2,-z', 'x,-y+1/2,z+1/2', '-x+1/2,y,z+1/2'], 57: ['x,y,z', '-x,-y,z+1/2', '-x,y+1/2,-z+1/2', 'x,-y+1/2,-z', '-x,-y,-z', 'x,y,-z+1/2', 'x,-y+1/2,z+1/2', '-x,y+1/2,z'], 58: ['x,y,z', '-x,-y,z', '-x+1/2,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z+1/2', '-x,-y,-z', 'x,y,-z', 'x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,z+1/2'], 59: ['x,y,z', '-x+1/2,-y+1/2,z', '-x,y+1/2,-z', 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152: ['x,y,z', '-y,x-y,z+1/3', '-x+y,-x,z+2/3', 'y,x,-z', 'x-y,-y,-z+2/3', '-x,-x+y,-z+1/3'], 153: ['x,y,z', '-y,x-y,z+2/3', '-x+y,-x,z+1/3', '-y,-x,-z+1/3', '-x+y,y,-z+2/3', 'x,x-y,-z'], 154: ['x,y,z', '-y,x-y,z+2/3', '-x+y,-x,z+1/3', 'y,x,-z', 'x-y,-y,-z+1/3', '-x,-x+y,-z+2/3'], 155: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'y,x,-z', 'x-y,-y,-z', '-x,-x+y,-z', 'x+2/3,y+1/3,z+1/3', '-y+2/3,x-y+1/3,z+1/3', '-x+y+2/3,-x+1/3,z+1/3', 'y+2/3,x+1/3,-z+1/3', 'x-y+2/3,-y+1/3,-z+1/3', '-x+2/3,-x+y+1/3,-z+1/3', 'x+1/3,y+2/3,z+2/3', '-y+1/3,x-y+2/3,z+2/3', '-x+y+1/3,-x+2/3,z+2/3', 'y+1/3,x+2/3,-z+2/3', 'x-y+1/3,-y+2/3,-z+2/3', '-x+1/3,-x+y+2/3,-z+2/3'], 156: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-y,-x,z', '-x+y,y,z', 'x,x-y,z'], 157: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'y,x,z', 'x-y,-y,z', '-x,-x+y,z'], 158: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-y,-x,z+1/2', '-x+y,y,z+1/2', 'x,x-y,z+1/2'], 159: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'y,x,z+1/2', 'x-y,-y,z+1/2', '-x,-x+y,z+1/2'], 160: ['x,y,z', '-y,x-y,z', 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'-y+1/3,-x+2/3,z+2/3', '-x+y+1/3,y+2/3,z+2/3', 'x+1/3,x-y+2/3,z+2/3'], 167: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'y,x,-z+1/2', 'x-y,-y,-z+1/2', '-x,-x+y,-z+1/2', '-x,-y,-z', 'y,-x+y,-z', 'x-y,x,-z', '-y,-x,z+1/2', '-x+y,y,z+1/2', 'x,x-y,z+1/2', 'x+2/3,y+1/3,z+1/3', '-y+2/3,x-y+1/3,z+1/3', '-x+y+2/3,-x+1/3,z+1/3', 'y+2/3,x+1/3,-z+5/6', 'x-y+2/3,-y+1/3,-z+5/6', '-x+2/3,-x+y+1/3,-z+5/6', '-x+2/3,-y+1/3,-z+1/3', 'y+2/3,-x+y+1/3,-z+1/3', 'x-y+2/3,x+1/3,-z+1/3', '-y+2/3,-x+1/3,z+5/6', '-x+y+2/3,y+1/3,z+5/6', 'x+2/3,x-y+1/3,z+5/6', 'x+1/3,y+2/3,z+2/3', '-y+1/3,x-y+2/3,z+2/3', '-x+y+1/3,-x+2/3,z+2/3', 'y+1/3,x+2/3,-z+1/6', 'x-y+1/3,-y+2/3,-z+1/6', '-x+1/3,-x+y+2/3,-z+1/6', '-x+1/3,-y+2/3,-z+2/3', 'y+1/3,-x+y+2/3,-z+2/3', 'x-y+1/3,x+2/3,-z+2/3', '-y+1/3,-x+2/3,z+1/6', '-x+y+1/3,y+2/3,z+1/6', 'x+1/3,x-y+2/3,z+1/6'], 168: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z', 'y,-x+y,z', 'x-y,x,z'], 169: ['x,y,z', '-y,x-y,z+1/3', '-x+y,-x,z+2/3', '-x,-y,z+1/2', 'y,-x+y,z+5/6', 'x-y,x,z+1/6'], 170: ['x,y,z', 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'y,x,-z+1/3', 'x-y,-y,-z', '-x,-x+y,-z+2/3', '-y,-x,-z+5/6', '-x+y,y,-z+1/2', 'x,x-y,-z+1/6'], 179: ['x,y,z', '-y,x-y,z+2/3', '-x+y,-x,z+1/3', '-x,-y,z+1/2', 'y,-x+y,z+1/6', 'x-y,x,z+5/6', 'y,x,-z+2/3', 'x-y,-y,-z', '-x,-x+y,-z+1/3', '-y,-x,-z+1/6', '-x+y,y,-z+1/2', 'x,x-y,-z+5/6'], 180: ['x,y,z', '-y,x-y,z+2/3', '-x+y,-x,z+1/3', '-x,-y,z', 'y,-x+y,z+2/3', 'x-y,x,z+1/3', 'y,x,-z+2/3', 'x-y,-y,-z', '-x,-x+y,-z+1/3', '-y,-x,-z+2/3', '-x+y,y,-z', 'x,x-y,-z+1/3'], 181: ['x,y,z', '-y,x-y,z+1/3', '-x+y,-x,z+2/3', '-x,-y,z', 'y,-x+y,z+1/3', 'x-y,x,z+2/3', 'y,x,-z+1/3', 'x-y,-y,-z', '-x,-x+y,-z+2/3', '-y,-x,-z+1/3', '-x+y,y,-z', 'x,x-y,-z+2/3'], 182: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z+1/2', 'y,-x+y,z+1/2', 'x-y,x,z+1/2', 'y,x,-z', 'x-y,-y,-z', '-x,-x+y,-z', '-y,-x,-z+1/2', '-x+y,y,-z+1/2', 'x,x-y,-z+1/2'], 183: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z', 'y,-x+y,z', 'x-y,x,z', '-y,-x,z', '-x+y,y,z', 'x,x-y,z', 'y,x,z', 'x-y,-y,z', '-x,-x+y,z'], 184: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z', 'y,-x+y,z', 'x-y,x,z', '-y,-x,z+1/2', '-x+y,y,z+1/2', 'x,x-y,z+1/2', 'y,x,z+1/2', 'x-y,-y,z+1/2', '-x,-x+y,z+1/2'], 185: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z+1/2', 'y,-x+y,z+1/2', 'x-y,x,z+1/2', '-y,-x,z+1/2', '-x+y,y,z+1/2', 'x,x-y,z+1/2', 'y,x,z', 'x-y,-y,z', '-x,-x+y,z'], 186: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z+1/2', 'y,-x+y,z+1/2', 'x-y,x,z+1/2', '-y,-x,z', '-x+y,y,z', 'x,x-y,z', 'y,x,z+1/2', 'x-y,-y,z+1/2', '-x,-x+y,z+1/2'], 187: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'x,y,-z', '-y,x-y,-z', '-x+y,-x,-z', '-y,-x,z', '-x+y,y,z', 'x,x-y,z', '-y,-x,-z', '-x+y,y,-z', 'x,x-y,-z'], 188: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'x,y,-z+1/2', '-y,x-y,-z+1/2', '-x+y,-x,-z+1/2', '-y,-x,z+1/2', '-x+y,y,z+1/2', 'x,x-y,z+1/2', '-y,-x,-z', '-x+y,y,-z', 'x,x-y,-z'], 189: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'x,y,-z', '-y,x-y,-z', '-x+y,-x,-z', 'y,x,-z', 'x-y,-y,-z', '-x,-x+y,-z', 'y,x,z', 'x-y,-y,z', '-x,-x+y,z'], 190: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', 'x,y,-z+1/2', '-y,x-y,-z+1/2', '-x+y,-x,-z+1/2', 'y,x,-z', 'x-y,-y,-z', '-x,-x+y,-z', 'y,x,z+1/2', 'x-y,-y,z+1/2', '-x,-x+y,z+1/2'], 191: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z', 'y,-x+y,z', 'x-y,x,z', 'y,x,-z', 'x-y,-y,-z', '-x,-x+y,-z', '-y,-x,-z', '-x+y,y,-z', 'x,x-y,-z', '-x,-y,-z', 'y,-x+y,-z', 'x-y,x,-z', 'x,y,-z', '-y,x-y,-z', '-x+y,-x,-z', '-y,-x,z', '-x+y,y,z', 'x,x-y,z', 'y,x,z', 'x-y,-y,z', '-x,-x+y,z'], 192: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z', 'y,-x+y,z', 'x-y,x,z', 'y,x,-z+1/2', 'x-y,-y,-z+1/2', '-x,-x+y,-z+1/2', '-y,-x,-z+1/2', '-x+y,y,-z+1/2', 'x,x-y,-z+1/2', '-x,-y,-z', 'y,-x+y,-z', 'x-y,x,-z', 'x,y,-z', '-y,x-y,-z', '-x+y,-x,-z', '-y,-x,z+1/2', '-x+y,y,z+1/2', 'x,x-y,z+1/2', 'y,x,z+1/2', 'x-y,-y,z+1/2', '-x,-x+y,z+1/2'], 193: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z+1/2', 'y,-x+y,z+1/2', 'x-y,x,z+1/2', 'y,x,-z+1/2', 'x-y,-y,-z+1/2', '-x,-x+y,-z+1/2', '-y,-x,-z', '-x+y,y,-z', 'x,x-y,-z', '-x,-y,-z', 'y,-x+y,-z', 'x-y,x,-z', 'x,y,-z+1/2', '-y,x-y,-z+1/2', '-x+y,-x,-z+1/2', '-y,-x,z+1/2', '-x+y,y,z+1/2', 'x,x-y,z+1/2', 'y,x,z', 'x-y,-y,z', '-x,-x+y,z'], 194: ['x,y,z', '-y,x-y,z', '-x+y,-x,z', '-x,-y,z+1/2', 'y,-x+y,z+1/2', 'x-y,x,z+1/2', 'y,x,-z', 'x-y,-y,-z', '-x,-x+y,-z', '-y,-x,-z+1/2', '-x+y,y,-z+1/2', 'x,x-y,-z+1/2', '-x,-y,-z', 'y,-x+y,-z', 'x-y,x,-z', 'x,y,-z+1/2', '-y,x-y,-z+1/2', '-x+y,-x,-z+1/2', '-y,-x,z', '-x+y,y,z', 'x,x-y,z', 'y,x,z+1/2', 'x-y,-y,z+1/2', '-x,-x+y,z+1/2'], 195: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x'], 196: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', '-x,y+1/2,-z+1/2', 'x,-y+1/2,-z+1/2', 'z,x+1/2,y+1/2', 'z,-x+1/2,-y+1/2', '-z,-x+1/2,y+1/2', '-z,x+1/2,-y+1/2', 'y,z+1/2,x+1/2', '-y,z+1/2,-x+1/2', 'y,-z+1/2,-x+1/2', '-y,-z+1/2,x+1/2', 'x+1/2,y,z+1/2', '-x+1/2,-y,z+1/2', '-x+1/2,y,-z+1/2', 'x+1/2,-y,-z+1/2', 'z+1/2,x,y+1/2', 'z+1/2,-x,-y+1/2', '-z+1/2,-x,y+1/2', '-z+1/2,x,-y+1/2', 'y+1/2,z,x+1/2', '-y+1/2,z,-x+1/2', 'y+1/2,-z,-x+1/2', '-y+1/2,-z,x+1/2', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', '-x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,-z', 'z+1/2,x+1/2,y', 'z+1/2,-x+1/2,-y', '-z+1/2,-x+1/2,y', '-z+1/2,x+1/2,-y', 'y+1/2,z+1/2,x', '-y+1/2,z+1/2,-x', 'y+1/2,-z+1/2,-x', '-y+1/2,-z+1/2,x'], 197: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'x+1/2,y+1/2,z+1/2', '-x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z+1/2', 'z+1/2,x+1/2,y+1/2', 'z+1/2,-x+1/2,-y+1/2', '-z+1/2,-x+1/2,y+1/2', '-z+1/2,x+1/2,-y+1/2', 'y+1/2,z+1/2,x+1/2', '-y+1/2,z+1/2,-x+1/2', 'y+1/2,-z+1/2,-x+1/2', '-y+1/2,-z+1/2,x+1/2'], 198: ['x,y,z', '-x+1/2,-y,z+1/2', '-x,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z', 'z,x,y', 'z+1/2,-x+1/2,-y', '-z+1/2,-x,y+1/2', '-z,x+1/2,-y+1/2', 'y,z,x', '-y,z+1/2,-x+1/2', 'y+1/2,-z+1/2,-x', '-y+1/2,-z,x+1/2'], 199: ['x,y,z', '-x+1/2,-y,z+1/2', '-x,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z', 'z,x,y', 'z+1/2,-x+1/2,-y', '-z+1/2,-x,y+1/2', '-z,x+1/2,-y+1/2', 'y,z,x', '-y,z+1/2,-x+1/2', 'y+1/2,-z+1/2,-x', '-y+1/2,-z,x+1/2', 'x+1/2,y+1/2,z+1/2', '-x,-y+1/2,z', '-x+1/2,y,-z', 'x,-y,-z+1/2', 'z+1/2,x+1/2,y+1/2', 'z,-x,-y+1/2', '-z,-x+1/2,y', '-z+1/2,x,-y', 'y+1/2,z+1/2,x+1/2', '-y+1/2,z,-x', 'y,-z,-x+1/2', '-y,-z+1/2,x'], 200: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', '-x,-y,-z', 'x,y,-z', 'x,-y,z', '-x,y,z', '-z,-x,-y', '-z,x,y', 'z,x,-y', 'z,-x,y', '-y,-z,-x', 'y,-z,x', '-y,z,x', 'y,z,-x'], 201: ['x,y,z', '-x+1/2,-y+1/2,z', '-x+1/2,y,-z+1/2', 'x,-y+1/2,-z+1/2', 'z,x,y', 'z,-x+1/2,-y+1/2', '-z+1/2,-x+1/2,y', '-z+1/2,x,-y+1/2', 'y,z,x', '-y+1/2,z,-x+1/2', 'y,-z+1/2,-x+1/2', '-y+1/2,-z+1/2,x', '-x,-y,-z', 'x+1/2,y+1/2,-z', 'x+1/2,-y,z+1/2', '-x,y+1/2,z+1/2', '-z,-x,-y', '-z,x+1/2,y+1/2', 'z+1/2,x+1/2,-y', 'z+1/2,-x,y+1/2', '-y,-z,-x', 'y+1/2,-z,x+1/2', '-y,z+1/2,x+1/2', 'y+1/2,z+1/2,-x'], 202: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', '-x,-y,-z', 'x,y,-z', 'x,-y,z', '-x,y,z', '-z,-x,-y', '-z,x,y', 'z,x,-y', 'z,-x,y', '-y,-z,-x', 'y,-z,x', '-y,z,x', 'y,z,-x', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', '-x,y+1/2,-z+1/2', 'x,-y+1/2,-z+1/2', 'z,x+1/2,y+1/2', 'z,-x+1/2,-y+1/2', '-z,-x+1/2,y+1/2', '-z,x+1/2,-y+1/2', 'y,z+1/2,x+1/2', '-y,z+1/2,-x+1/2', 'y,-z+1/2,-x+1/2', '-y,-z+1/2,x+1/2', '-x,-y+1/2,-z+1/2', 'x,y+1/2,-z+1/2', 'x,-y+1/2,z+1/2', '-x,y+1/2,z+1/2', '-z,-x+1/2,-y+1/2', '-z,x+1/2,y+1/2', 'z,x+1/2,-y+1/2', 'z,-x+1/2,y+1/2', '-y,-z+1/2,-x+1/2', 'y,-z+1/2,x+1/2', '-y,z+1/2,x+1/2', 'y,z+1/2,-x+1/2', 'x+1/2,y,z+1/2', '-x+1/2,-y,z+1/2', '-x+1/2,y,-z+1/2', 'x+1/2,-y,-z+1/2', 'z+1/2,x,y+1/2', 'z+1/2,-x,-y+1/2', '-z+1/2,-x,y+1/2', '-z+1/2,x,-y+1/2', 'y+1/2,z,x+1/2', '-y+1/2,z,-x+1/2', 'y+1/2,-z,-x+1/2', '-y+1/2,-z,x+1/2', '-x+1/2,-y,-z+1/2', 'x+1/2,y,-z+1/2', 'x+1/2,-y,z+1/2', '-x+1/2,y,z+1/2', '-z+1/2,-x,-y+1/2', '-z+1/2,x,y+1/2', 'z+1/2,x,-y+1/2', 'z+1/2,-x,y+1/2', '-y+1/2,-z,-x+1/2', 'y+1/2,-z,x+1/2', '-y+1/2,z,x+1/2', 'y+1/2,z,-x+1/2', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', '-x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,-z', 'z+1/2,x+1/2,y', 'z+1/2,-x+1/2,-y', '-z+1/2,-x+1/2,y', '-z+1/2,x+1/2,-y', 'y+1/2,z+1/2,x', '-y+1/2,z+1/2,-x', 'y+1/2,-z+1/2,-x', '-y+1/2,-z+1/2,x', '-x+1/2,-y+1/2,-z', 'x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,z', '-x+1/2,y+1/2,z', '-z+1/2,-x+1/2,-y', '-z+1/2,x+1/2,y', 'z+1/2,x+1/2,-y', 'z+1/2,-x+1/2,y', '-y+1/2,-z+1/2,-x', 'y+1/2,-z+1/2,x', '-y+1/2,z+1/2,x', 'y+1/2,z+1/2,-x'], 203: ['x,y,z', '-x+3/4,-y+3/4,z', '-x+3/4,y,-z+3/4', 'x,-y+3/4,-z+3/4', 'z,x,y', 'z,-x+3/4,-y+3/4', '-z+3/4,-x+3/4,y', '-z+3/4,x,-y+3/4', 'y,z,x', '-y+3/4,z,-x+3/4', 'y,-z+3/4,-x+3/4', '-y+3/4,-z+3/4,x', '-x,-y,-z', 'x+1/4,y+1/4,-z', 'x+1/4,-y,z+1/4', '-x,y+1/4,z+1/4', '-z,-x,-y', '-z,x+1/4,y+1/4', 'z+1/4,x+1/4,-y', 'z+1/4,-x,y+1/4', '-y,-z,-x', 'y+1/4,-z,x+1/4', '-y,z+1/4,x+1/4', 'y+1/4,z+1/4,-x', 'x,y+1/2,z+1/2', '-x+3/4,-y+1/4,z+1/2', '-x+3/4,y+1/2,-z+1/4', 'x,-y+1/4,-z+1/4', 'z,x+1/2,y+1/2', 'z,-x+1/4,-y+1/4', '-z+3/4,-x+1/4,y+1/2', '-z+3/4,x+1/2,-y+1/4', 'y,z+1/2,x+1/2', '-y+3/4,z+1/2,-x+1/4', 'y,-z+1/4,-x+1/4', '-y+3/4,-z+1/4,x+1/2', '-x,-y+1/2,-z+1/2', 'x+1/4,y+3/4,-z+1/2', 'x+1/4,-y+1/2,z+3/4', '-x,y+3/4,z+3/4', '-z,-x+1/2,-y+1/2', '-z,x+3/4,y+3/4', 'z+1/4,x+3/4,-y+1/2', 'z+1/4,-x+1/2,y+3/4', '-y,-z+1/2,-x+1/2', 'y+1/4,-z+1/2,x+3/4', '-y,z+3/4,x+3/4', 'y+1/4,z+3/4,-x+1/2', 'x+1/2,y,z+1/2', '-x+1/4,-y+3/4,z+1/2', '-x+1/4,y,-z+1/4', 'x+1/2,-y+3/4,-z+1/4', 'z+1/2,x,y+1/2', 'z+1/2,-x+3/4,-y+1/4', '-z+1/4,-x+3/4,y+1/2', '-z+1/4,x,-y+1/4', 'y+1/2,z,x+1/2', '-y+1/4,z,-x+1/4', 'y+1/2,-z+3/4,-x+1/4', '-y+1/4,-z+3/4,x+1/2', '-x+1/2,-y,-z+1/2', 'x+3/4,y+1/4,-z+1/2', 'x+3/4,-y,z+3/4', '-x+1/2,y+1/4,z+3/4', '-z+1/2,-x,-y+1/2', '-z+1/2,x+1/4,y+3/4', 'z+3/4,x+1/4,-y+1/2', 'z+3/4,-x,y+3/4', '-y+1/2,-z,-x+1/2', 'y+3/4,-z,x+3/4', '-y+1/2,z+1/4,x+3/4', 'y+3/4,z+1/4,-x+1/2', 'x+1/2,y+1/2,z', '-x+1/4,-y+1/4,z', '-x+1/4,y+1/2,-z+3/4', 'x+1/2,-y+1/4,-z+3/4', 'z+1/2,x+1/2,y', 'z+1/2,-x+1/4,-y+3/4', '-z+1/4,-x+1/4,y', '-z+1/4,x+1/2,-y+3/4', 'y+1/2,z+1/2,x', '-y+1/4,z+1/2,-x+3/4', 'y+1/2,-z+1/4,-x+3/4', '-y+1/4,-z+1/4,x', '-x+1/2,-y+1/2,-z', 'x+3/4,y+3/4,-z', 'x+3/4,-y+1/2,z+1/4', '-x+1/2,y+3/4,z+1/4', '-z+1/2,-x+1/2,-y', '-z+1/2,x+3/4,y+1/4', 'z+3/4,x+3/4,-y', 'z+3/4,-x+1/2,y+1/4', '-y+1/2,-z+1/2,-x', 'y+3/4,-z+1/2,x+1/4', '-y+1/2,z+3/4,x+1/4', 'y+3/4,z+3/4,-x'], 204: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', '-x,-y,-z', 'x,y,-z', 'x,-y,z', '-x,y,z', '-z,-x,-y', '-z,x,y', 'z,x,-y', 'z,-x,y', '-y,-z,-x', 'y,-z,x', '-y,z,x', 'y,z,-x', 'x+1/2,y+1/2,z+1/2', '-x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z+1/2', 'z+1/2,x+1/2,y+1/2', 'z+1/2,-x+1/2,-y+1/2', '-z+1/2,-x+1/2,y+1/2', '-z+1/2,x+1/2,-y+1/2', 'y+1/2,z+1/2,x+1/2', '-y+1/2,z+1/2,-x+1/2', 'y+1/2,-z+1/2,-x+1/2', '-y+1/2,-z+1/2,x+1/2', '-x+1/2,-y+1/2,-z+1/2', 'x+1/2,y+1/2,-z+1/2', 'x+1/2,-y+1/2,z+1/2', '-x+1/2,y+1/2,z+1/2', '-z+1/2,-x+1/2,-y+1/2', '-z+1/2,x+1/2,y+1/2', 'z+1/2,x+1/2,-y+1/2', 'z+1/2,-x+1/2,y+1/2', '-y+1/2,-z+1/2,-x+1/2', 'y+1/2,-z+1/2,x+1/2', '-y+1/2,z+1/2,x+1/2', 'y+1/2,z+1/2,-x+1/2'], 205: ['x,y,z', '-x+1/2,-y,z+1/2', '-x,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z', 'z,x,y', 'z+1/2,-x+1/2,-y', '-z+1/2,-x,y+1/2', '-z,x+1/2,-y+1/2', 'y,z,x', '-y,z+1/2,-x+1/2', 'y+1/2,-z+1/2,-x', '-y+1/2,-z,x+1/2', '-x,-y,-z', 'x+1/2,y,-z+1/2', 'x,-y+1/2,z+1/2', '-x+1/2,y+1/2,z', '-z,-x,-y', '-z+1/2,x+1/2,y', 'z+1/2,x,-y+1/2', 'z,-x+1/2,y+1/2', '-y,-z,-x', 'y,-z+1/2,x+1/2', '-y+1/2,z+1/2,x', 'y+1/2,z,-x+1/2'], 206: ['x,y,z', '-x+1/2,-y,z+1/2', '-x,y+1/2,-z+1/2', 'x+1/2,-y+1/2,-z', 'z,x,y', 'z+1/2,-x+1/2,-y', '-z+1/2,-x,y+1/2', '-z,x+1/2,-y+1/2', 'y,z,x', '-y,z+1/2,-x+1/2', 'y+1/2,-z+1/2,-x', '-y+1/2,-z,x+1/2', '-x,-y,-z', 'x+1/2,y,-z+1/2', 'x,-y+1/2,z+1/2', '-x+1/2,y+1/2,z', '-z,-x,-y', '-z+1/2,x+1/2,y', 'z+1/2,x,-y+1/2', 'z,-x+1/2,y+1/2', '-y,-z,-x', 'y,-z+1/2,x+1/2', '-y+1/2,z+1/2,x', 'y+1/2,z,-x+1/2', 'x+1/2,y+1/2,z+1/2', '-x,-y+1/2,z', '-x+1/2,y,-z', 'x,-y,-z+1/2', 'z+1/2,x+1/2,y+1/2', 'z,-x,-y+1/2', '-z,-x+1/2,y', '-z+1/2,x,-y', 'y+1/2,z+1/2,x+1/2', '-y+1/2,z,-x', 'y,-z,-x+1/2', '-y,-z+1/2,x', '-x+1/2,-y+1/2,-z+1/2', 'x,y+1/2,-z', 'x+1/2,-y,z', '-x,y,z+1/2', '-z+1/2,-x+1/2,-y+1/2', '-z,x,y+1/2', 'z,x+1/2,-y', 'z+1/2,-x,y', '-y+1/2,-z+1/2,-x+1/2', 'y+1/2,-z,x', '-y,z,x+1/2', 'y,z+1/2,-x'], 207: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'y,x,-z', '-y,-x,-z', 'y,-x,z', '-y,x,z', 'x,z,-y', '-x,z,y', '-x,-z,-y', 'x,-z,y', 'z,y,-x', 'z,-y,x', '-z,y,x', '-z,-y,-x'], 208: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'y+1/2,x+1/2,-z+1/2', '-y+1/2,-x+1/2,-z+1/2', 'y+1/2,-x+1/2,z+1/2', '-y+1/2,x+1/2,z+1/2', 'x+1/2,z+1/2,-y+1/2', '-x+1/2,z+1/2,y+1/2', '-x+1/2,-z+1/2,-y+1/2', 'x+1/2,-z+1/2,y+1/2', 'z+1/2,y+1/2,-x+1/2', 'z+1/2,-y+1/2,x+1/2', '-z+1/2,y+1/2,x+1/2', '-z+1/2,-y+1/2,-x+1/2'], 209: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'y,x,-z', '-y,-x,-z', 'y,-x,z', '-y,x,z', 'x,z,-y', '-x,z,y', '-x,-z,-y', 'x,-z,y', 'z,y,-x', 'z,-y,x', '-z,y,x', '-z,-y,-x', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', '-x,y+1/2,-z+1/2', 'x,-y+1/2,-z+1/2', 'z,x+1/2,y+1/2', 'z,-x+1/2,-y+1/2', '-z,-x+1/2,y+1/2', '-z,x+1/2,-y+1/2', 'y,z+1/2,x+1/2', '-y,z+1/2,-x+1/2', 'y,-z+1/2,-x+1/2', '-y,-z+1/2,x+1/2', 'y,x+1/2,-z+1/2', '-y,-x+1/2,-z+1/2', 'y,-x+1/2,z+1/2', '-y,x+1/2,z+1/2', 'x,z+1/2,-y+1/2', '-x,z+1/2,y+1/2', '-x,-z+1/2,-y+1/2', 'x,-z+1/2,y+1/2', 'z,y+1/2,-x+1/2', 'z,-y+1/2,x+1/2', '-z,y+1/2,x+1/2', '-z,-y+1/2,-x+1/2', 'x+1/2,y,z+1/2', '-x+1/2,-y,z+1/2', '-x+1/2,y,-z+1/2', 'x+1/2,-y,-z+1/2', 'z+1/2,x,y+1/2', 'z+1/2,-x,-y+1/2', '-z+1/2,-x,y+1/2', '-z+1/2,x,-y+1/2', 'y+1/2,z,x+1/2', '-y+1/2,z,-x+1/2', 'y+1/2,-z,-x+1/2', '-y+1/2,-z,x+1/2', 'y+1/2,x,-z+1/2', '-y+1/2,-x,-z+1/2', 'y+1/2,-x,z+1/2', '-y+1/2,x,z+1/2', 'x+1/2,z,-y+1/2', '-x+1/2,z,y+1/2', '-x+1/2,-z,-y+1/2', 'x+1/2,-z,y+1/2', 'z+1/2,y,-x+1/2', 'z+1/2,-y,x+1/2', '-z+1/2,y,x+1/2', '-z+1/2,-y,-x+1/2', 'x+1/2,y+1/2,z', '-x+1/2,-y+1/2,z', '-x+1/2,y+1/2,-z', 'x+1/2,-y+1/2,-z', 'z+1/2,x+1/2,y', 'z+1/2,-x+1/2,-y', '-z+1/2,-x+1/2,y', '-z+1/2,x+1/2,-y', 'y+1/2,z+1/2,x', '-y+1/2,z+1/2,-x', 'y+1/2,-z+1/2,-x', '-y+1/2,-z+1/2,x', 'y+1/2,x+1/2,-z', '-y+1/2,-x+1/2,-z', 'y+1/2,-x+1/2,z', '-y+1/2,x+1/2,z', 'x+1/2,z+1/2,-y', '-x+1/2,z+1/2,y', '-x+1/2,-z+1/2,-y', 'x+1/2,-z+1/2,y', 'z+1/2,y+1/2,-x', 'z+1/2,-y+1/2,x', '-z+1/2,y+1/2,x', '-z+1/2,-y+1/2,-x'], 210: ['x,y,z', '-x,-y+1/2,z+1/2', '-x+1/2,y+1/2,-z', 'x+1/2,-y,-z+1/2', 'z,x,y', 'z+1/2,-x,-y+1/2', '-z,-x+1/2,y+1/2', '-z+1/2,x+1/2,-y', 'y,z,x', '-y+1/2,z+1/2,-x', 'y+1/2,-z,-x+1/2', 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'y+3/4,-x+3/4,z+1/4', '-y+1/4,x+3/4,z+3/4', 'x+1/4,z+1/4,-y+1/4', '-x+1/4,z+3/4,y+3/4', '-x+3/4,-z+1/4,-y+3/4', 'x+3/4,-z+3/4,y+1/4', 'z+1/4,y+1/4,-x+1/4', 'z+3/4,-y+3/4,x+1/4', '-z+1/4,y+3/4,x+3/4', '-z+3/4,-y+1/4,-x+3/4', 'x+1/2,y+1/2,z', '-x+1/2,-y,z+1/2', '-x,y,-z', 'x,-y+1/2,-z+1/2', 'z+1/2,x+1/2,y', 'z,-x+1/2,-y+1/2', '-z+1/2,-x,y+1/2', '-z,x,-y', 'y+1/2,z+1/2,x', '-y,z,-x', 'y,-z+1/2,-x+1/2', '-y+1/2,-z,x+1/2', 'y+1/4,x+3/4,-z+3/4', '-y+3/4,-x+3/4,-z+1/4', 'y+3/4,-x+1/4,z+3/4', '-y+1/4,x+1/4,z+1/4', 'x+1/4,z+3/4,-y+3/4', '-x+1/4,z+1/4,y+1/4', '-x+3/4,-z+3/4,-y+1/4', 'x+3/4,-z+1/4,y+3/4', 'z+1/4,y+3/4,-x+3/4', 'z+3/4,-y+1/4,x+3/4', '-z+1/4,y+1/4,x+1/4', '-z+3/4,-y+3/4,-x+1/4'], 211: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'y,x,-z', '-y,-x,-z', 'y,-x,z', '-y,x,z', 'x,z,-y', '-x,z,y', '-x,-z,-y', 'x,-z,y', 'z,y,-x', 'z,-y,x', '-z,y,x', '-z,-y,-x', 'x+1/2,y+1/2,z+1/2', '-x+1/2,-y+1/2,z+1/2', 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'z+1/2,-y+1/2,-x+1/2', '-z+1/2,y+1/2,-x+1/2', '-z+1/2,-y+1/2,x+1/2'], 218: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'y+1/2,x+1/2,z+1/2', '-y+1/2,-x+1/2,z+1/2', 'y+1/2,-x+1/2,-z+1/2', '-y+1/2,x+1/2,-z+1/2', 'x+1/2,z+1/2,y+1/2', '-x+1/2,z+1/2,-y+1/2', '-x+1/2,-z+1/2,y+1/2', 'x+1/2,-z+1/2,-y+1/2', 'z+1/2,y+1/2,x+1/2', 'z+1/2,-y+1/2,-x+1/2', '-z+1/2,y+1/2,-x+1/2', '-z+1/2,-y+1/2,x+1/2'], 219: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'y+1/2,x+1/2,z+1/2', '-y+1/2,-x+1/2,z+1/2', 'y+1/2,-x+1/2,-z+1/2', '-y+1/2,x+1/2,-z+1/2', 'x+1/2,z+1/2,y+1/2', '-x+1/2,z+1/2,-y+1/2', '-x+1/2,-z+1/2,y+1/2', 'x+1/2,-z+1/2,-y+1/2', 'z+1/2,y+1/2,x+1/2', 'z+1/2,-y+1/2,-x+1/2', '-z+1/2,y+1/2,-x+1/2', '-z+1/2,-y+1/2,x+1/2', 'x,y+1/2,z+1/2', '-x,-y+1/2,z+1/2', '-x,y+1/2,-z+1/2', 'x,-y+1/2,-z+1/2', 'z,x+1/2,y+1/2', 'z,-x+1/2,-y+1/2', 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'-z+1/4,y+1/4,-x+3/4', '-z+3/4,-y+1/4,x+1/4'], 221: ['x,y,z', '-x,-y,z', '-x,y,-z', 'x,-y,-z', 'z,x,y', 'z,-x,-y', '-z,-x,y', '-z,x,-y', 'y,z,x', '-y,z,-x', 'y,-z,-x', '-y,-z,x', 'y,x,-z', '-y,-x,-z', 'y,-x,z', '-y,x,z', 'x,z,-y', '-x,z,y', '-x,-z,-y', 'x,-z,y', 'z,y,-x', 'z,-y,x', '-z,y,x', '-z,-y,-x', '-x,-y,-z', 'x,y,-z', 'x,-y,z', '-x,y,z', '-z,-x,-y', '-z,x,y', 'z,x,-y', 'z,-x,y', '-y,-z,-x', 'y,-z,x', '-y,z,x', 'y,z,-x', '-y,-x,z', 'y,x,z', '-y,x,-z', 'y,-x,-z', '-x,-z,y', 'x,-z,-y', 'x,z,y', '-x,z,-y', '-z,-y,x', '-z,y,-x', 'z,-y,-x', 'z,y,x'], 222: ['x,y,z', '-x+1/2,-y+1/2,z', '-x+1/2,y,-z+1/2', 'x,-y+1/2,-z+1/2', 'z,x,y', 'z,-x+1/2,-y+1/2', '-z+1/2,-x+1/2,y', '-z+1/2,x,-y+1/2', 'y,z,x', '-y+1/2,z,-x+1/2', 'y,-z+1/2,-x+1/2', '-y+1/2,-z+1/2,x', 'y,x,-z+1/2', '-y+1/2,-x+1/2,-z+1/2', 'y,-x+1/2,z', '-y+1/2,x,z', 'x,z,-y+1/2', '-x+1/2,z,y', '-x+1/2,-z+1/2,-y+1/2', 'x,-z+1/2,y', 'z,y,-x+1/2', 'z,-y+1/2,x', '-z+1/2,y,x', '-z+1/2,-y+1/2,-x+1/2', '-x,-y,-z', 'x+1/2,y+1/2,-z', 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'x+1/2,-y,z', '-x,y,z+1/2', '-z+1/2,-x+1/2,-y+1/2', '-z,x,y+1/2', 'z,x+1/2,-y', 'z+1/2,-x,y', '-y+1/2,-z+1/2,-x+1/2', 'y+1/2,-z,x', '-y,z,x+1/2', 'y,z+1/2,-x', '-y+3/4,-x+1/4,z+1/4', 'y+3/4,x+3/4,z+3/4', '-y+1/4,x+1/4,-z+3/4', 'y+1/4,-x+3/4,-z+1/4', '-x+3/4,-z+1/4,y+1/4', 'x+1/4,-z+3/4,-y+1/4', 'x+3/4,z+3/4,y+3/4', '-x+1/4,z+1/4,-y+3/4', '-z+3/4,-y+1/4,x+1/4', '-z+1/4,y+1/4,-x+3/4', 'z+1/4,-y+3/4,-x+1/4', 'z+3/4,y+3/4,x+3/4']} def test_generators(): for i in range(1, 231): sg = symmetry.SpaceGroup(i) string_generators = sg.string_generators gens_str = symmetry.get_str_from_generator(sg.generators) for op in gens_str: assert (op in string_generators) def test_operators(): for i in range(1, 231): sg = symmetry.SpaceGroup(i) symops = sg.symmetry_operations symops_str = symmetry.get_str_from_generator(symops) assert (len(symops_str) == len(poses[i])) for op in poses[i]: assert (op in symops_str) if __name__ == "__main__": pytest.main()

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9e973901bc2c7503d62d3b183d01693c93100c31

27

py

Python

project3_absolute/package3/module3.py

munich-ml/Python-imports

da41467507a7edf1d12c1a78d9aff812a6b553ed

[ "MIT" ]

null

project3_absolute/package3/module3.py

munich-ml/Python-imports

da41467507a7edf1d12c1a78d9aff812a6b553ed

[ "MIT" ]

null

project3_absolute/package3/module3.py

munich-ml/Python-imports

da41467507a7edf1d12c1a78d9aff812a6b553ed

[ "MIT" ]

null

def func3(): return 42

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9eaf68c1a15945ec2e29748770691f2ea107d806

13,431

py

Python

PubMedScraperFunctions.py

alexcwsmith/scNLP

1691316f1dc13774fa05b0e6ea075941667fa6b0

[ "MIT" ]

1

2021-06-23T13:07:29.000Z

PubMedScraperFunctions.py

alexcwsmith/scNLP

1691316f1dc13774fa05b0e6ea075941667fa6b0

[ "MIT" ]

null

PubMedScraperFunctions.py

alexcwsmith/scNLP

1691316f1dc13774fa05b0e6ea075941667fa6b0

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sun Apr 26 03:06:01 2020 @author: smith """ from Bio import Entrez import pandas as pd from bs4 import BeautifulSoup from multiprocessing import Pool import os import glob import nltk import requests import re from nltk.corpus import stopwords from nltk.tokenize import word_tokenize from nltk.tokenize import sent_tokenize import matplotlib.pyplot as plt from config.PubMedScraperSettings import * def info(title): print(title, 'processID:', os.getpid()) def countPMCResults(term1): page = requests.get('https://www.ncbi.nlm.nih.gov/pmc/?term=' + term1) soup = BeautifulSoup(page.content, 'html.parser') res = soup.find(id='maincontent') res = soup.find(class_='result_count left').get_text() numRes = int(res.rsplit()[-1]) return(numRes) def findPMCIDs(searchTerm, term2=None, results=20, start=0, sort='relevance'): search = Entrez.esearch(db='pmc', retmax=results, term=searchTerm, retstart=start, sort=sort) record = Entrez.read(search) recDf = pd.DataFrame.from_dict(record, orient='index').T IDs = recDf.IdList.apply(pd.Series).T IDs.columns=['PMCID'] # IDs.to_excel(os.path.join(paperDirectory, searchTerm + '_PMCIDS.xlsx')) IDlist= IDs['PMCID'].tolist() if len(IDlist) < 5: print("WARNING: Low number of results detected for " + str(searchTerm.split(' ')[0])) if term2 is not None: search = Entrez.esearch(db='pmc', retmax=results, term=term2, retstart=start, sort=sort) record = Entrez.read(search) recDf = pd.DataFrame.from_dict(record, orient='index').T IDs_term2 = recDf.IdList.apply(pd.Series).T IDs_term2.columns=['PMCID'] IDlist2 = IDs_term2['PMCID'].tolist() IDlist.extend(IDlist2) return(IDlist) def getFullText(PMCID): if not os.path.exists(paperDirectory): os.mkdir(paperDirectory) os.mkdir(os.path.join(paperDirectory, 'null/')) if not os.path.exists(abstractDirectory): os.mkdir(abstractDirectory) if not os.path.exists(titleDirectory): os.mkdir(titleDirectory) article = Entrez.efetch(db='pmc', id=PMCID, rettype='full', retmode='xml') art = article.read() soup = BeautifulSoup(art, 'html.parser') title = soup.find('article-title').get_text() journal = soup.find('journal-title') if hasattr(journal, 'get_text'): journal = soup.find('journal-title').get_text() else: journal = None tables = soup.find_all('tr') tab = list(tables) for t in tab: try: t.decompose() except AttributeError: pass try: doi = soup.find_all('article-id')[2].get_text() except IndexError: doi = 'No DOI available' info = 'TITLE: ' + str(title) + '\n' + 'JOURNAL: ' + str(journal) + '\n' + 'DOI: ' + str(doi) with open(os.path.join(titleDirectory, str(PMCID) + '_info.txt'), 'w+') as f: f.write(info) f.close() abstract = soup.find('abstract') if hasattr(abstract, 'get_text') == True: abstract_text = abstract.get_text() with open(os.path.join(abstractDirectory, str(PMCID) + '_abstract.txt'), 'w+') as fa: fa.write(abstract_text) fa.close() elif hasattr(abstract, 'get_text') == False: with open(os.path.join(abstractDirectory, str(PMCID) + '_abstract_null.txt'), 'w+') as fa: fa.write('No abstract available') fa.close() body = soup.find('body') if hasattr(body, 'get_text') == True: body_text = body.get_text() body_text = re.sub(r'[\ \n]{2,}', '', body_text) with open(os.path.join(paperDirectory, str(PMCID) + '_fulltext.txt'), 'w') as fb: fb.write(body_text) fb.close() elif hasattr(body, 'get_text') == False: with open(os.path.join(paperDirectory, 'null/' + str(PMCID) + '_fulltext_null.txt'), 'w+') as fb: fb.write('No full text available') fb.close() def getFullTexts(IDs, results=50, start=0, end=None, sort='relevance'): if not os.path.exists(paperDirectory): os.mkdir(paperDirectory) os.mkdir(os.path.join(paperDirectory, 'null/')) if not os.path.exists(abstractDirectory): os.mkdir(abstractDirectory) if not os.path.exists(titleDirectory): os.mkdir(titleDirectory) for ID in IDs[start:end]: dirs = os.listdir(paperDirectory) if len(dirs)-2 < results: getFullText(ID) else: pass def getFullTextGene(PMCID, directory, gene=None): paperDirectory = os.path.join(directory, 'papers/' + str(gene) + '/') if not os.path.exists(paperDirectory): os.mkdir(paperDirectory) os.mkdir(os.path.join(paperDirectory, 'null/')) if not os.path.exists(abstractDirectory): os.mkdir(abstractDirectory) os.mkdir(abstractDirectory, 'null/') if not os.path.exists(titleDirectory): os.mkdir(titleDirectory) article = Entrez.efetch(db='pmc', id=PMCID, rettype='full', retmode='xml') art = article.read() soup = BeautifulSoup(art, 'html.parser') if hasattr(soup.find('article-title'), 'get_text') ==True: title = soup.find('article-title').get_text() elif hasattr(soup.find('article-title'), 'get_text') == False: title = 'No title available' journal = soup.find('journal-title').get_text() tables = soup.find_all('tr') tab = list(tables) for t in tab: try: t.decompose() except AttributeError: pass try: doi = soup.find_all('article-id')[2].get_text() except IndexError: doi = 'No DOI available' info = 'TITLE: ' + str(title) + '\n' + 'JOURNAL: ' + str(journal) + '\n' + 'DOI: ' + str(doi) with open(os.path.join(titleDirectory, str(PMCID) + '_info.txt'), 'w+') as f: f.write(info) f.close() abstract = soup.find('abstract') if hasattr(abstract, 'get_text') == True: abstract_text = abstract.get_text() with open(os.path.join(abstractDirectory, gene + '/' + str(PMCID) + '_abstract.txt'), 'w+') as fa: fa.write(abstract_text) fa.close() elif hasattr(abstract, 'get_text') == False: with open(os.path.join(abstractDirectory, gene + '/null/' + str(PMCID) + '_abstract_null.txt'), 'w+') as fa: fa.write('No abstract available') fa.close() body = soup.find('body') if hasattr(body, 'get_text') == True: body_text = body.get_text() body_text = re.sub(r'[\ \n]{2,}', '', body_text) with open(os.path.join(paperDirectory, str(PMCID) + '_fulltext.txt'), 'w') as fb: fb.write(body_text) fb.close() elif hasattr(body, 'get_text') == False: with open(os.path.join(paperDirectory, 'null/' + str(PMCID) + '_fulltext_null.txt'), 'w+') as fb: fb.write('No full text available') fb.close() def getFullTextsGene(IDs, directory, gene=None, results=50, start=0, end=None, sort='relevance'): complete = False paperDirectory = os.path.join(directory, 'papers/', str(gene) + '/') if not os.path.exists(paperDirectory): os.mkdir(paperDirectory) os.mkdir(os.path.join(paperDirectory, 'null/')) if not os.path.exists(abstractDirectory): os.mkdir(abstractDirectory) if not os.path.exists(titleDirectory): os.mkdir(titleDirectory) for ID in IDs[start:end]: dirs = os.listdir(paperDirectory) if len(dirs)-2 < results: getFullTextGene(ID, directory=directory, gene=gene) elif len(dirs)-2 == results: pass dirs = os.listdir(paperDirectory) print("Retrieved " + str(len(dirs)-1) + " literature results for " + gene) if len(dirs)-1 == 0: print("WARNING: NO RESULTS RETRIEVED FOR " + gene) print("WARNING: NO RESULTS RETRIEVED FOR " + gene) def getAbstracts(PMCID): if not os.path.exists(paperDirectory): os.mkdir(paperDirectory) os.mkdir(os.path.join(paperDirectory, 'null/')) if not os.path.exists(abstractDirectory): os.mkdir(abstractDirectory) if not os.path.exists(titleDirectory): os.mkdir(titleDirectory) article = Entrez.efetch(db='pmc', id=PMCID, rettype='abstract', retmode='xml') art = article.read() soup = BeautifulSoup(art, 'html.parser') title = soup.find('article-title').get_text() journal = soup.find('journal-title') if hasattr(journal, 'get_text'): journal = soup.find('journal-title').get_text() else: journal = None tables = soup.find_all('tr') tab = list(tables) for t in tab: try: t.decompose() except AttributeError: pass try: doi = soup.find_all('article-id')[2].get_text() except IndexError: doi = 'No DOI available' info = 'TITLE: ' + str(title) + '\n' + 'JOURNAL: ' + str(journal) + '\n' + 'DOI: ' + str(doi) with open(os.path.join(titleDirectory, str(PMCID) + '_info.txt'), 'w+') as f: f.write(info) f.close() abstract = soup.find('abstract') if hasattr(abstract, 'get_text') == True: abstract_text = abstract.get_text() with open(os.path.join(abstractDirectory, str(PMCID) + '_abstract.txt'), 'w+') as fa: fa.write(abstract_text) fa.close() elif hasattr(abstract, 'get_text') == False: with open(os.path.join(abstractDirectory, str(PMCID) + '_abstract_null.txt'), 'w+') as fa: fa.write('No abstract available') fa.close() def getAbstractGene(PMCID, directory, gene=None): paperDirectory = os.path.join(directory, 'papers/' + str(gene) + '/') if not os.path.exists(paperDirectory): os.mkdir(paperDirectory) os.mkdir(os.path.join(paperDirectory, 'null/')) if not os.path.exists(abstractDirectory): os.mkdir(abstractDirectory) if not os.path.exists(titleDirectory): os.mkdir(titleDirectory) article = Entrez.efetch(db='pmc', id=PMCID, rettype='abstract', retmode='xml') art = article.read() soup = BeautifulSoup(art, 'html.parser') if hasattr(soup.find('article-title'), 'get_text') ==True: title = soup.find('article-title').get_text() elif hasattr(soup.find('article-title'), 'get_text') == False: title = 'No title available' journal = soup.find('journal-title').get_text() tables = soup.find_all('tr') tab = list(tables) for t in tab: try: t.decompose() except AttributeError: pass try: doi = soup.find_all('article-id')[2].get_text() except IndexError: doi = 'No DOI available' info = 'TITLE: ' + str(title) + '\n' + 'JOURNAL: ' + str(journal) + '\n' + 'DOI: ' + str(doi) with open(os.path.join(titleDirectory, str(PMCID) + '_info.txt'), 'w+') as f: f.write(info) f.close() abstract = soup.find('abstract') if hasattr(abstract, 'get_text') == True: abstract_text = abstract.get_text() with open(os.path.join(abstractDirectory, str(gene) + '/' + str(PMCID) + '_abstract.txt'), 'w+') as fa: fa.write(abstract_text) fa.close() elif hasattr(abstract, 'get_text') == False: with open(os.path.join(abstractDirectory, str(gene) + '/' + str(PMCID) + '_abstract_null.txt'), 'w+') as fa: fa.write('No abstract available') fa.close() def getAbstractsGene(IDs, directory, gene=None, results=500, start=0, end=None, sort='relevance'): complete = False abstractDirectory = os.path.join(directory, 'abstracts/', str(gene) + '/') if not os.path.exists(paperDirectory): os.mkdir(paperDirectory) os.mkdir(os.path.join(paperDirectory, 'null/')) if not os.path.exists(abstractDirectory): os.mkdir(abstractDirectory) if not os.path.exists(titleDirectory): os.mkdir(titleDirectory) for ID in IDs[start:end]: dirs = os.listdir(abstractDirectory) if len(dirs) < results: getAbstractGene(ID, directory=directory, gene=gene) elif len(dirs) == results: pass dirs = os.listdir(abstractDirectory) print("Retrieved " + str(len(dirs)-1) + " literature results for " + gene) if len(dirs)-1 == 0: print("WARNING: NO RESULTS RETRIEVED FOR " + gene) print("WARNING: NO RESULTS RETRIEVED FOR " + gene) def combineTextFiles(directory, rettype='full', sizeLimit=1e6): if rettype == 'full': read_files = glob.glob(os.path.join(directory, '*fulltext.txt')) elif rettype=='abstract': read_files = glob.glob(os.path.join(directory, '*abstract.txt')) skipList = [] with open(os.path.join(directory, 'CombinedFullTexts.txt'), 'w+') as outfile: for file in read_files: if os.stat(file).st_size < sizeLimit: with open(file, 'r+') as infile: outfile.write(infile.read()) else: skipList.append(file) with open(os.path.join(directory, 'skippedFullTexts.txt'), 'w+') as f: f.write('\n'.join(skipList)) f.close() with open(os.path.join(directory, 'CombinedFullTexts.txt'), 'r+') as r: text = r.read() r.close() # return(text)

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7

7b77bdadff5b3e43456a956fcb7c22043ca7548e

4,219

py

Python

tests/test_provider_hashicorp_azurestack.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

507

2017-07-26T02:58:38.000Z

2022-01-21T12:35:13.000Z

tests/test_provider_hashicorp_azurestack.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

135

2017-07-20T12:01:59.000Z

2021-10-04T22:25:40.000Z

tests/test_provider_hashicorp_azurestack.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

81

2018-02-20T17:55:28.000Z

2022-01-31T07:08:40.000Z

# tests/test_provider_hashicorp_azurestack.py # Automatically generated by tools/makecode.py (24-Sep-2021 15:13:15 UTC) def test_provider_import(): import terrascript.provider.hashicorp.azurestack def test_resource_import(): from terrascript.resource.hashicorp.azurestack import azurestack_availability_set from terrascript.resource.hashicorp.azurestack import azurestack_dns_a_record from terrascript.resource.hashicorp.azurestack import azurestack_dns_zone from terrascript.resource.hashicorp.azurestack import azurestack_lb from terrascript.resource.hashicorp.azurestack import ( azurestack_lb_backend_address_pool, ) from terrascript.resource.hashicorp.azurestack import azurestack_lb_nat_pool from terrascript.resource.hashicorp.azurestack import azurestack_lb_nat_rule from terrascript.resource.hashicorp.azurestack import azurestack_lb_probe from terrascript.resource.hashicorp.azurestack import azurestack_lb_rule from terrascript.resource.hashicorp.azurestack import ( azurestack_local_network_gateway, ) from terrascript.resource.hashicorp.azurestack import azurestack_managed_disk from terrascript.resource.hashicorp.azurestack import azurestack_network_interface from terrascript.resource.hashicorp.azurestack import ( azurestack_network_security_group, ) from terrascript.resource.hashicorp.azurestack import ( azurestack_network_security_rule, ) from terrascript.resource.hashicorp.azurestack import azurestack_public_ip from terrascript.resource.hashicorp.azurestack import azurestack_resource_group from terrascript.resource.hashicorp.azurestack import azurestack_route from terrascript.resource.hashicorp.azurestack import azurestack_route_table from terrascript.resource.hashicorp.azurestack import azurestack_storage_account from terrascript.resource.hashicorp.azurestack import azurestack_storage_blob from terrascript.resource.hashicorp.azurestack import azurestack_storage_container from terrascript.resource.hashicorp.azurestack import azurestack_subnet from terrascript.resource.hashicorp.azurestack import azurestack_template_deployment from terrascript.resource.hashicorp.azurestack import azurestack_virtual_machine from terrascript.resource.hashicorp.azurestack import ( azurestack_virtual_machine_extension, ) from terrascript.resource.hashicorp.azurestack import ( azurestack_virtual_machine_scale_set, ) from terrascript.resource.hashicorp.azurestack import azurestack_virtual_network from terrascript.resource.hashicorp.azurestack import ( azurestack_virtual_network_gateway, ) from terrascript.resource.hashicorp.azurestack import ( azurestack_virtual_network_gateway_connection, ) def test_datasource_import(): from terrascript.data.hashicorp.azurestack import azurestack_client_config from terrascript.data.hashicorp.azurestack import azurestack_network_interface from terrascript.data.hashicorp.azurestack import azurestack_network_security_group from terrascript.data.hashicorp.azurestack import azurestack_platform_image from terrascript.data.hashicorp.azurestack import azurestack_public_ip from terrascript.data.hashicorp.azurestack import azurestack_resource_group from terrascript.data.hashicorp.azurestack import azurestack_route_table from terrascript.data.hashicorp.azurestack import azurestack_storage_account from terrascript.data.hashicorp.azurestack import azurestack_subnet from terrascript.data.hashicorp.azurestack import azurestack_virtual_network from terrascript.data.hashicorp.azurestack import azurestack_virtual_network_gateway # TODO: Shortcut imports without namespace for official and supported providers. # TODO: This has to be moved into a required_providers block. # def test_version_source(): # # import terrascript.provider.hashicorp.azurestack # # t = terrascript.provider.hashicorp.azurestack.azurestack() # s = str(t) # # assert 'https://github.com/hashicorp/terraform-provider-azurestack' in s # assert '0.10.0' in s

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11

cdc0b01dda5906444aca85708d437f40024752ad

6,517

py

Python

streams/ckan_pages/migrations/0003_auto_20200928_0605.py

Engerrs/ckan.org

a5a9b63b0ca16cb5aa4f709f7a264b8f6c265158

[ "BSD-3-Clause" ]

1

2022-03-18T03:20:00.000Z

streams/ckan_pages/migrations/0003_auto_20200928_0605.py

Engerrs/ckan.org

a5a9b63b0ca16cb5aa4f709f7a264b8f6c265158

[ "BSD-3-Clause" ]

26

2021-07-07T08:42:42.000Z

2022-03-29T14:34:59.000Z

streams/ckan_pages/migrations/0003_auto_20200928_0605.py

Engerrs/ckan.org

a5a9b63b0ca16cb5aa4f709f7a264b8f6c265158

[ "BSD-3-Clause" ]

3

2021-07-07T22:11:03.000Z

2021-09-15T18:19:10.000Z

# Generated by Django 3.1.1 on 2020-09-28 06:05 from django.db import migrations, models import django.db.models.deletion import modelcluster.fields class Migration(migrations.Migration): dependencies = [ ('ckan_pages', '0002_auto_20200928_0605'), ('wagtailimages', '0022_uploadedimage'), ('streams', '0002_auto_20200928_0605'), ] operations = [ migrations.AddField( model_name='workinggroups', name='working_group', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.workinggroup'), ), migrations.AddField( model_name='stewards', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='stewards', to='ckan_pages.communitypage'), ), migrations.AddField( model_name='stewards', name='steward', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.steward'), ), migrations.AddField( model_name='softwareengineers', name='developer', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.softwareengineer'), ), migrations.AddField( model_name='softwareengineers', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='developers', to='ckan_pages.communitypage'), ), migrations.AddField( model_name='showcasesection3', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='showcase_section_3', to='ckan_pages.showcasepage'), ), migrations.AddField( model_name='showcasesection3', name='showcase', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.poweredcard'), ), migrations.AddField( model_name='showcasesection2', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='showcase_section_2', to='ckan_pages.showcasepage'), ), migrations.AddField( model_name='showcasesection2', name='showcase', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.poweredcard'), ), migrations.AddField( model_name='showcasesection1', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='showcase_section_1', to='ckan_pages.showcasepage'), ), migrations.AddField( model_name='showcasesection1', name='showcase', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.poweredcard'), ), migrations.AddField( model_name='generalfeatures', name='feature', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.generalfeature'), ), migrations.AddField( model_name='generalfeatures', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='general_features', to='ckan_pages.featurespage'), ), migrations.AddField( model_name='feedbacksection2', name='feedback', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.feedback'), ), migrations.AddField( model_name='feedbacksection2', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='feedback_section_2', to='ckan_pages.showcasepage'), ), migrations.AddField( model_name='feedbacksection1', name='feedback', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.feedback'), ), migrations.AddField( model_name='feedbacksection1', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='feedback_section_1', to='ckan_pages.showcasepage'), ), migrations.AddField( model_name='features', name='feature', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.feature'), ), migrations.AddField( model_name='features', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='features', to='ckan_pages.featurespage'), ), migrations.AddField( model_name='extensions', name='extension', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.extension'), ), migrations.AddField( model_name='extensions', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='extensions', to='ckan_pages.featurespage'), ), migrations.AddField( model_name='communitypage', name='contributors_image', field=models.ForeignKey(help_text="Contributors' photos", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.image'), ), migrations.AddField( model_name='communitypage', name='open_knowledge_foundation_image', field=models.ForeignKey(help_text='Open Knowledge Foundation block image', null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.image'), ), migrations.AddField( model_name='ckanforfeatures', name='ckan_for_card', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='streams.ckanforcard'), ), migrations.AddField( model_name='ckanforfeatures', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='ckan_for_cards', to='ckan_pages.featurespage'), ), ]

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7

cdef5d8dcc7fc8e0f97dd96c748ea6b02b5ff4d0

18,160

py

Python

server/TimeSeriesJoiner/LocalStreamBuffer/tester.py

iot-salzburg/panta-rhei

3249fdbb199df59bf400f0f6d0497438afcec443

[ "Apache-2.0" ]

6

2019-07-15T22:41:58.000Z

2020-10-04T11:34:35.000Z

server/TimeSeriesJoiner/LocalStreamBuffer/tester.py

iot-salzburg/panta-rhei

3249fdbb199df59bf400f0f6d0497438afcec443

[ "Apache-2.0" ]

null

server/TimeSeriesJoiner/LocalStreamBuffer/tester.py

iot-salzburg/panta-rhei

3249fdbb199df59bf400f0f6d0497438afcec443

[ "Apache-2.0" ]

3

2019-01-11T11:02:00.000Z

2021-09-30T12:58:50.000Z

#!/usr/bin/env python3 # Tester for the join-algorithm in local_stream_buffer. import sys import time import random try: from .local_stream_buffer import Record, StreamBuffer except ImportError: from local_stream_buffer import Record, StreamBuffer def join_fct(record_left, record_right): """ Blueprint for the join function, takes two records and merges them using the defined routine. :param record_left: Record Record that is joined as left join partner :param record_right: Record Record that is joined as right join partner :return: Record the resulting record from the join of both partners """ record = Record(quantity="t", result=record_left.get_result() * record_right.get_result(), timestamp=(record_left.get_time() + record_right.get_time()) / 2) # here, the resulting record can be produced to e.g. Apache Kafka or a pipeline return record def test_one_one(): ts = time.time() # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=sys.maxsize, left="r", buffer_results=True, verbose=True) # create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized Records N = 100 random.seed(0) event_order = ["r", "s"] * int(N / 2) start_time = 1600000000 for i in range(len(event_order)): if event_order[i] == "r": events_r.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) elif event_order[i] == "s": events_s.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) ingestion_order = ["r", "s"] * int(N/2) # works n_r = n_s = 0 for i in range(N): # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if ingestion_order[i] == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif ingestion_order[i] == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 # print("\nRecords in buffer r:") # for rec in stream_buffer.buffer_left: # print(rec) # print("Records in buffer s:") # for rec in stream_buffer.buffer_right: # print(rec) # print("Merged records in buffer t:") events_t = stream_buffer.fetch_results() # for rec in events_t: # print(rec) print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") assert len(events_t) == 99 def test_five_five(): # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=sys.maxsize, left="r", buffer_results=True, verbose=True) # Test Settings: # Create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized N = 20 random.seed(0) event_order = (["r"] * 5 + ["s"] * 5) * int(N / 10) start_time = 1600000000 for i in range(len(event_order)): if event_order[i] == "r": events_r.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) elif event_order[i] == "s": events_s.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) ingestion_order = (["r"] * 5 + ["s"] * 5) * N n_r = n_s = 0 ts = time.time() for i in range(N): # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if ingestion_order[i] == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif ingestion_order[i] == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 events_t = stream_buffer.fetch_results() print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") assert len(events_t) == 23 def test_five_five_many(): # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=sys.maxsize, left="r", buffer_results=True, verbose=False) # Test Settings: # Create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized N = 100_000 random.seed(0) event_order = (["r"] * 5 + ["s"] * 5) * int(N / 10) start_time = 1600000000 for i in range(len(event_order)): if event_order[i] == "r": events_r.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) elif event_order[i] == "s": events_s.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) ingestion_order = (["r"] * 5 + ["s"] * 5) * int(N/10) n_r = 0 n_s = 0 ts = time.time() for i in range(N): # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if ingestion_order[i] == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif ingestion_order[i] == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 events_t = stream_buffer.fetch_results() stop_time = time.time() print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") print(f"that are {int(len(events_t)/(time.time() - ts))} joins per second.") assert len(events_t) == 179987 assert stop_time - ts < 12 def test_unordered(): # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=sys.maxsize, left="r", buffer_results=True, verbose=True) # Fill the input_stream with randomized random.seed(0) start_time = 1600000000 # Test Settings: # Create Queues to store the input records events_r = list() for i in range(10): events_r.append(Record(timestamp=i + start_time, quantity="r", result=random.random())) ts = time.time() # first ingest all Records into R, then all into s for event in events_r: stream_buffer.ingest_left(event) # instant emit print("Ingest Records into s.") stream_buffer.ingest_right(Record(timestamp=start_time - 0.5, quantity="s", result=random.random())) stream_buffer.ingest_right(Record(timestamp=start_time + 0.5, quantity="s", result=random.random())) stream_buffer.ingest_right(Record(timestamp=start_time + 5.5, quantity="s", result=random.random())) stream_buffer.ingest_right(Record(timestamp=start_time + 9.5, quantity="s", result=random.random())) events_t = stream_buffer.fetch_results() print(f"Join time-series with |r| = {len(events_r)}, |s| = {4}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") if time.time() - ts > 1e-3: print(f"that are {int(len(events_t)/(time.time() - ts))} joins per second.") assert len(events_t) == 20 d = {'r.quantity': 'r', 'r.phenomenonTime': 1600000006, 'r.result': 0.7837985890347726, 's.quantity': 's', 's.phenomenonTime': 1600000005.5, 's.result': 0.28183784439970383} assert d in events_t def test_randomized(): # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=sys.maxsize, left="r", buffer_results=True, verbose=True) # Test Settings: # Create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized n_r = n_s = 10 random.seed(0) start_time = 1600000000 phenomenon_time = start_time for i in range(n_r): phenomenon_time += random.random() events_r.append(Record(timestamp=phenomenon_time, quantity="r", result=random.random())) phenomenon_time = start_time for i in range(n_s): phenomenon_time += random.random() events_s.append(Record(timestamp=phenomenon_time, quantity="s", result=random.random())) ingestion_order = ["r"] * n_r + ["s"] * n_s random.shuffle(ingestion_order) n_r = n_s = 0 ts = time.time() for quantity in ingestion_order: # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if quantity == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif quantity == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 events_t = stream_buffer.fetch_results() print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") assert len(events_t) == 20 def test_randomized_many(): # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=sys.maxsize, left="r", buffer_results=True, verbose=False) # Test Settings: # Create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized n_r = n_s = 10_000 random.seed(0) start_time = 1600000000 phenomenon_time = start_time for i in range(n_r): phenomenon_time += random.random() events_r.append(Record(timestamp=phenomenon_time, quantity="r", result=random.random())) phenomenon_time = start_time for i in range(n_s): phenomenon_time += random.random() events_s.append(Record(timestamp=phenomenon_time, quantity="s", result=random.random())) ingestion_order = ["r"] * n_r + ["s"] * n_s random.shuffle(ingestion_order) n_r = n_s = 0 ts = time.time() for quantity in ingestion_order: # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if quantity == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif quantity == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 events_t = stream_buffer.fetch_results() stop_time = time.time() print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") print(f"that are {int(len(events_t)/(time.time() - ts))} joins per second.") assert len(events_t) == 23041 assert stop_time - ts < 2 # we got around 0.4 s def test_delayed_many(): imbalance = 100 # additional latency of stream s # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=sys.maxsize, left="r", buffer_results=True, verbose=False) # Test Settings: # Create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized N = 10_000 random.seed(0) event_order = (["r"] * 5 + ["s"] * 5) * int(N/10) start_time = 1600000000 for i in range(len(event_order)): if event_order[i] == "r": events_r.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) elif event_order[i] == "s": events_s.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) ingestion_order = ["r"] * imbalance + (["r"] * 5 + ["s"] * 5) * int(N/10) n_r = 0 n_s = 0 ts = time.time() while n_r < len(events_r) and n_s < len(events_s): # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if ingestion_order[n_r+n_s] == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif ingestion_order[n_r+n_s] == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 events_t = stream_buffer.fetch_results() print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") print(f"that are {int(len(events_t)/(time.time() - ts))} joins per second.") assert len(events_t) == 13702 assert time.time() - ts < 1 # we got around 0.2 s def test_timeout_five_five(): # create an instance of the StreamBuffer class stream_buffer = StreamBuffer(instant_emit=True, delta_time=3, left="r", buffer_results=True, verbose=True) # Test Settings: # Create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized N = 20 random.seed(0) event_order = (["r"] * 5 + ["s"] * 5) * int(N / 10) start_time = 1600000000 for i in range(len(event_order)): if event_order[i] == "r": events_r.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) elif event_order[i] == "s": events_s.append(Record(timestamp=i + start_time, quantity=event_order[i], result=random.random())) ingestion_order = (["r"] * 5 + ["s"] * 5) * N n_r = n_s = 0 ts = time.time() for i in range(N): # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if ingestion_order[i] == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif ingestion_order[i] == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 events_t = stream_buffer.fetch_results() print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") assert len(events_t) == 13 def test_timeout_randomized(): # create an instance of the StreamBuffer class with a delta_time of 0.5 seconds. stream_buffer = StreamBuffer(instant_emit=True, delta_time=0.5, left="r", buffer_results=True, verbose=True) # Test Settings: # Create Queues to store the input streams events_r = list() events_s = list() # Fill the input_stream with randomized n_r = n_s = 10 random.seed(0) start_time = 1600000000 phenomenon_time = start_time for i in range(n_r): phenomenon_time += random.random() events_r.append(Record(timestamp=phenomenon_time, quantity="r", result=random.random())) phenomenon_time = start_time for i in range(n_s): phenomenon_time += random.random() events_s.append(Record(timestamp=phenomenon_time, quantity="s", result=random.random())) ingestion_order = ["r"] * n_r + ["s"] * n_s random.shuffle(ingestion_order) n_r = n_s = 0 ts = time.time() for quantity in ingestion_order: # decide based on the ingestion order which stream record is forwarded # store as dict of KafkaRecords and a flag whether it was already joined as older sibling if quantity == "r": # receive the first record from the event stream stream_buffer.ingest_left(events_r[n_r]) # instant emit n_r += 1 elif quantity == "s": # receive the first record from the event stream stream_buffer.ingest_right(events_s[n_s]) n_s += 1 events_t = stream_buffer.fetch_results() print(f"Join time-series with |r| = {n_r}, |s| = {n_s}.") print(f"joined {len(events_t)} tuples in {time.time() - ts} s.") assert len(events_t) == 16 # to profile via cProfile, run it normally with a python interpreter if __name__ == "__main__": import cProfile pr = cProfile.Profile() pr.enable() # test ordered ingestion test_one_one() test_five_five() print("\n #############################\n") print("Testing unordered ingestion:") test_unordered() test_randomized() # test unordered ingestion print("\n #############################\n") print("Performance tests") test_five_five_many() test_randomized_many() test_delayed_many() print("\n #############################\n") print("Timeout tests") test_timeout_five_five() test_timeout_randomized() pr.disable() # after your program ends pr.print_stats(sort="tottime") # Back in outer section of code # pr.dump_stats('tester_profile.pstat')

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0.082012

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1

0

null

0

7

b56a95803496f05bea0423e4dd78cdd3b91796d8

1,745

py

Python

08/8.py

cjm00/project-euler

10f186aafda2ed13bf93cf3e3ba6cff63c85fbd0

[ "CC-BY-3.0" ]

1

2015-08-16T20:30:40.000Z

08/8.py

cjm00/project-euler

10f186aafda2ed13bf93cf3e3ba6cff63c85fbd0

[ "CC-BY-3.0" ]

1

2016-08-11T13:06:12.000Z

08/8.py

cjm00/project-euler

10f186aafda2ed13bf93cf3e3ba6cff63c85fbd0

[ "CC-BY-3.0" ]

null

window = 13 #Problem asks for 13 adjacent digits #whitespace kept to preserve readability problem_string = """73167176531330624919225119674426574742355349194934 96983520312774506326239578318016984801869478851843 85861560789112949495459501737958331952853208805511 12540698747158523863050715693290963295227443043557 66896648950445244523161731856403098711121722383113 62229893423380308135336276614282806444486645238749 30358907296290491560440772390713810515859307960866 70172427121883998797908792274921901699720888093776 65727333001053367881220235421809751254540594752243 52584907711670556013604839586446706324415722155397 53697817977846174064955149290862569321978468622482 83972241375657056057490261407972968652414535100474 82166370484403199890008895243450658541227588666881 16427171479924442928230863465674813919123162824586 17866458359124566529476545682848912883142607690042 24219022671055626321111109370544217506941658960408 07198403850962455444362981230987879927244284909188 84580156166097919133875499200524063689912560717606 05886116467109405077541002256983155200055935729725 71636269561882670428252483600823257530420752963450""" #strip newlines problem_string = problem_string.replace('\n', '') def StringProduct(input): #Takes the product of the individual digits in the input string total = 1 for k in range(len(input)): total *= int(input[k]) return total output = 0 window_product = 0 index = 0 for k in range(len(problem_string)-window): window_product = StringProduct(problem_string[k:k+window]) if output < window_product: output = window_product index = k print "The string with the greatest product is " + problem_string[index:index+window] + ", at position " + str(index) print "The product is " + str(output)

37.12766

117

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126

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12.063492

0.507937

0.051316

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0.018421

0

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null

1

0

1

0

7

b57f5f198ffbb8d88c16ba9b6c566b3a8bb98f0e

205

py

Python

app/blueprints/__init__.py

sarahmk125/flask-model

4347b2d7fd065c10c150acc7376f21d2cbce6dbc

[ "Apache-2.0" ]

null

app/blueprints/__init__.py

sarahmk125/flask-model

4347b2d7fd065c10c150acc7376f21d2cbce6dbc

[ "Apache-2.0" ]

null

app/blueprints/__init__.py

sarahmk125/flask-model

4347b2d7fd065c10c150acc7376f21d2cbce6dbc

[ "Apache-2.0" ]

null

from app.blueprints import home from app.blueprints import model from app.blueprints import auth def init_app(app, blueprints): for blueprint in blueprints: app.register_blueprint(blueprint)

22.777778

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205

5.642857

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0.329114

0.322785

0.436709

0

0.165854

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false

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null

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0

1

0

null

0

1

0

1

0

8

a9348c6facb7d21dbbec1ee7d15dc38fd78f9d94

8,099

py

Python

uq4k/models/loss.py

JPLMLIA/UQ4K

7884200992b9bf5b4d8782e243eb4ff2470cea3f

[ "MIT" ]

1

2022-03-18T14:40:23.000Z

uq4k/models/loss.py

JPLMLIA/UQ4K

7884200992b9bf5b4d8782e243eb4ff2470cea3f

[ "MIT" ]

null

uq4k/models/loss.py

JPLMLIA/UQ4K

7884200992b9bf5b4d8782e243eb4ff2470cea3f

[ "MIT" ]

null

# Implements objective function class for UQ4K. Provides a general objective # function framework, which can take an arbitrary forward model. # # Author : Mike Stanley # Written : August 26, 2021 # Last Mod : November 20, 2021 from abc import ABC, abstractmethod import jax.numpy as jnp import numpy as np class AbstractLoss(ABC): # TODO: should these abstract methods be defined here? def __init__(self): super().__init__() @abstractmethod def sum_sq_norms(self): """ Finds the squared 2-norm of the difference between model and data """ pass @abstractmethod def center_dist(self): """ Finds the squared 2-norm between a new proposed parameter value and the current center """ pass class MeritFunc(AbstractLoss): def __init__(self, forward_model, mu, data, qoi_func): """ Dimension key: n : number of data points d : dimension of each data point m : dimension of the qoi Parameters: ----------- forward_model (BaseModel) : see base_model.py mu (float) : merit function parameter data (np arr) : array of observed data - n x d qoi_func (function) : maps theta |-> qoi, R^n -> R^m """ self.forward_model = forward_model self.mu = mu self.data = data self.qoi_func = qoi_func def sum_sq_norms(self, params): """ Finds the squared 2-norm of the difference between model and data Dimension key: p : dimension of model parameters Parameters: ----------- params (np arr) : p Returns: -------- 2-norm of residuals """ diffs = self.data - self.forward_model(params) return np.square(diffs).sum() def center_dist(self, new_point, center): """ Finds the squared 2-norm between a new proposed parameter value and the current center Dimension key: p : dimension of model parameters Parameters: ----------- new_point (np arr) : p center (np arr) : m Returns: -------- squared 2-norm of distance between two points """ return np.linalg.norm(self.qoi_func(new_point) - center) ** 2 def __call__(self, new_point, center, M_alpha): """ Evaluates the objective function at some new point. Dimension key: p : dimension of model parameters m : dimension of the QoI Parameters: ----------- new_point (np arr) : p center (np arr) : m M_alpha (float) : bound on the error Returns: -------- Objective function """ # find the distance from center center_dist_term = self.center_dist(new_point=new_point, center=center) # compute the penalty term error = self.sum_sq_norms(params=new_point) merit_term = self.mu * np.max(np.array([0, error - M_alpha])) return -center_dist_term + merit_term class DifferentaibleMeritFunc(AbstractLoss): def __init__(self, forward_model, mu, data, qoi_func): """ Dimension key: n : number of data points d : dimension of each data point m : dimension of the qoi Parameters: ----------- forward_model (BaseModel) : see base_model.py mu (float) : merit function parameter data (np arr) : array of observed data - n x d qoi_func (function) : maps theta |-> qoi, R^n -> R^m """ self.forward_model = forward_model self.mu = mu self.data = data self.qoi_func = qoi_func def sum_sq_norms(self, params): """ Finds the squared 2-norm of the difference between model and data Dimension key: p : dimension of model parameters Parameters: ----------- params (jax DeviceArray) : p Returns: -------- 2-norm of residuals """ diffs_squared = jnp.square(self.data - self.forward_model(params)) return jnp.sum(diffs_squared) def center_dist(self, new_point, center): """ Finds the squared 2-norm between a new proposed parameter value and the current center Dimension key: p : dimension of model parameters Parameters: ----------- new_point (jax DeviceArray) : p center (jax DeviceArray) : m Returns: -------- squared 2-norm of distance between two points """ diffs_squared = jnp.square(self.qoi_func(new_point) - center) return jnp.sum(diffs_squared) def __call__(self, new_point, center, M_alpha): """ Evaluates the objective function at some new point. Dimension key: p : dimension of model parameters m : dimension of the QoI Parameters: ----------- new_point (jax.numpy.DeviceArray) : p center (np arr) : m M_alpha (float) : bound on the error Returns: -------- Objective function """ center_dist_term = self.center_dist(new_point, center) error = self.sum_sq_norms(params=new_point) constraint = self.mu * jnp.max(jnp.array([error - M_alpha, 0])) return -center_dist_term + constraint class MeritFunc_NEW(AbstractLoss): def __init__(self, forward_model, mu, data_y, data_x): """ Dimension key: n : number of data points dx : dimension of each input dy : dimension of each output Parameters: ----------- forward_model (BaseModel) : see base_model.py mu (float) : merit function parameter data_y (np arr) : array of observed output - n x dy data_x (np arr) : array of observed input - n x dx """ self.forward_model = forward_model self.mu = mu self.data_y = data_y self.data_x = data_x def sum_sq_norms(self): """ Finds the squared 2-norm of the difference between model and data Dimension key: p : dimension of model parameters Parameters: ----------- params (np arr) : p Returns: -------- 2-norm of residuals """ diffs = self.data_y - self.forward_model(self.data_x) return np.square(diffs).sum() def center_dist(self, new_point, center): """ Finds the squared 2-norm between a new proposed parameter value and the current center Dimension key: p : dimension of model parameters Parameters: ----------- new_point (np arr) : p center (np arr) : p Returns: -------- squared 2-norm of distance between two points """ return np.linalg.norm(new_point - center) ** 2 def __call__(self, new_point, center, M_alpha): """ Evaluates the objective function at some new point. Dimension key: p : dimension of model parameters Parameters: ----------- new_point (np arr) : p center (np arr) : p M_alpha (float) : bound on the error Returns: -------- Objective function """ # find the distance from center center_dist_term = self.center_dist(new_point=new_point, center=center) # compute the penalty term error = self.sum_sq_norms(params=new_point) merit_term = self.mu * np.max(np.array([0, error - M_alpha])) return -center_dist_term + merit_term

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py

Python

dxm/lib/masking_api/api/mount_filesystem_api.py

experiortec/dxm-toolkit

b2ab6189e163c62fa8d7251cd533d2a36430d44a

[ "Apache-2.0" ]

5

2018-08-23T15:47:05.000Z

2022-01-19T23:38:18.000Z

dxm/lib/masking_api/api/mount_filesystem_api.py

experiortec/dxm-toolkit

b2ab6189e163c62fa8d7251cd533d2a36430d44a

[ "Apache-2.0" ]

59

2018-10-15T10:37:00.000Z

2022-03-22T20:49:25.000Z

dxm/lib/masking_api/api/mount_filesystem_api.py

experiortec/dxm-toolkit

b2ab6189e163c62fa8d7251cd533d2a36430d44a

[ "Apache-2.0" ]

12

2019-03-08T19:59:13.000Z

2021-12-16T03:28:04.000Z

# coding: utf-8 """ Masking API Schema for the Masking Engine API # noqa: E501 OpenAPI spec version: 5.1.8 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from dxm.lib.masking_api.api_client import ApiClient class MountFilesystemApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def connect_mount_filesystem(self, mount_id, **kwargs): # noqa: E501 """Connect filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.connect_mount_filesystem(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to connect (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.connect_mount_filesystem_with_http_info(mount_id, **kwargs) # noqa: E501 else: (data) = self.connect_mount_filesystem_with_http_info(mount_id, **kwargs) # noqa: E501 return data def connect_mount_filesystem_with_http_info(self, mount_id, **kwargs): # noqa: E501 """Connect filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.connect_mount_filesystem_with_http_info(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to connect (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ all_params = ['mount_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method connect_mount_filesystem" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'mount_id' is set if self.api_client.client_side_validation and ('mount_id' not in params or params['mount_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `mount_id` when calling `connect_mount_filesystem`") # noqa: E501 collection_formats = {} path_params = {} if 'mount_id' in params: path_params['mountID'] = params['mount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem/{mountID}/connect', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='MountInformation', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def create_mount_filesystem(self, body, **kwargs): # noqa: E501 """Create filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_mount_filesystem(body, async_req=True) >>> result = thread.get() :param async_req bool :param MountInformation body: The filesystem to mount (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_mount_filesystem_with_http_info(body, **kwargs) # noqa: E501 else: (data) = self.create_mount_filesystem_with_http_info(body, **kwargs) # noqa: E501 return data def create_mount_filesystem_with_http_info(self, body, **kwargs): # noqa: E501 """Create filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_mount_filesystem_with_http_info(body, async_req=True) >>> result = thread.get() :param async_req bool :param MountInformation body: The filesystem to mount (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ all_params = ['body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_mount_filesystem" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'body' is set if self.api_client.client_side_validation and ('body' not in params or params['body'] is None): # noqa: E501 raise ValueError("Missing the required parameter `body` when calling `create_mount_filesystem`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='MountInformation', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_mount_filesystem(self, mount_id, **kwargs): # noqa: E501 """Delete filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_mount_filesystem(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to delete (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_mount_filesystem_with_http_info(mount_id, **kwargs) # noqa: E501 else: (data) = self.delete_mount_filesystem_with_http_info(mount_id, **kwargs) # noqa: E501 return data def delete_mount_filesystem_with_http_info(self, mount_id, **kwargs): # noqa: E501 """Delete filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_mount_filesystem_with_http_info(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to delete (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['mount_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_mount_filesystem" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'mount_id' is set if self.api_client.client_side_validation and ('mount_id' not in params or params['mount_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `mount_id` when calling `delete_mount_filesystem`") # noqa: E501 collection_formats = {} path_params = {} if 'mount_id' in params: path_params['mountID'] = params['mount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem/{mountID}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def disconnect_mount_filesystem(self, mount_id, **kwargs): # noqa: E501 """Disconnect filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.disconnect_mount_filesystem(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to disconnect (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.disconnect_mount_filesystem_with_http_info(mount_id, **kwargs) # noqa: E501 else: (data) = self.disconnect_mount_filesystem_with_http_info(mount_id, **kwargs) # noqa: E501 return data def disconnect_mount_filesystem_with_http_info(self, mount_id, **kwargs): # noqa: E501 """Disconnect filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.disconnect_mount_filesystem_with_http_info(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to disconnect (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ all_params = ['mount_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method disconnect_mount_filesystem" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'mount_id' is set if self.api_client.client_side_validation and ('mount_id' not in params or params['mount_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `mount_id` when calling `disconnect_mount_filesystem`") # noqa: E501 collection_formats = {} path_params = {} if 'mount_id' in params: path_params['mountID'] = params['mount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem/{mountID}/disconnect', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='MountInformation', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_all_mounts(self, **kwargs): # noqa: E501 """Get all mounts # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_all_mounts(async_req=True) >>> result = thread.get() :param async_req bool :param int page_number: The page number for which to get mount information. This will default to the first page if excluded :param int page_size: The maximum number of objects to return. This will default to the DEFAULT_API_PAGE_SIZE property if not provided :return: MountInformationList If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_all_mounts_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_all_mounts_with_http_info(**kwargs) # noqa: E501 return data def get_all_mounts_with_http_info(self, **kwargs): # noqa: E501 """Get all mounts # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_all_mounts_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param int page_number: The page number for which to get mount information. This will default to the first page if excluded :param int page_size: The maximum number of objects to return. This will default to the DEFAULT_API_PAGE_SIZE property if not provided :return: MountInformationList If the method is called asynchronously, returns the request thread. """ all_params = ['page_number', 'page_size'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_all_mounts" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'page_number' in params: query_params.append(('page_number', params['page_number'])) # noqa: E501 if 'page_size' in params: query_params.append(('page_size', params['page_size'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='MountInformationList', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_mount_by_id(self, mount_id, **kwargs): # noqa: E501 """Get mount by ID # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_mount_by_id(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to get (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_mount_by_id_with_http_info(mount_id, **kwargs) # noqa: E501 else: (data) = self.get_mount_by_id_with_http_info(mount_id, **kwargs) # noqa: E501 return data def get_mount_by_id_with_http_info(self, mount_id, **kwargs): # noqa: E501 """Get mount by ID # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_mount_by_id_with_http_info(mount_id, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to get (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ all_params = ['mount_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_mount_by_id" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'mount_id' is set if self.api_client.client_side_validation and ('mount_id' not in params or params['mount_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `mount_id` when calling `get_mount_by_id`") # noqa: E501 collection_formats = {} path_params = {} if 'mount_id' in params: path_params['mountID'] = params['mount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem/{mountID}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='MountInformation', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def remount_mount_filesystem(self, mount_id, body, **kwargs): # noqa: E501 """Remount filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.remount_mount_filesystem(mount_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to update (required) :param MountInformation body: The updated filesystem (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.remount_mount_filesystem_with_http_info(mount_id, body, **kwargs) # noqa: E501 else: (data) = self.remount_mount_filesystem_with_http_info(mount_id, body, **kwargs) # noqa: E501 return data def remount_mount_filesystem_with_http_info(self, mount_id, body, **kwargs): # noqa: E501 """Remount filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.remount_mount_filesystem_with_http_info(mount_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to update (required) :param MountInformation body: The updated filesystem (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ all_params = ['mount_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method remount_mount_filesystem" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'mount_id' is set if self.api_client.client_side_validation and ('mount_id' not in params or params['mount_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `mount_id` when calling `remount_mount_filesystem`") # noqa: E501 # verify the required parameter 'body' is set if self.api_client.client_side_validation and ('body' not in params or params['body'] is None): # noqa: E501 raise ValueError("Missing the required parameter `body` when calling `remount_mount_filesystem`") # noqa: E501 collection_formats = {} path_params = {} if 'mount_id' in params: path_params['mountID'] = params['mount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem/{mountID}/remount', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='MountInformation', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_mount_filesystem(self, mount_id, body, **kwargs): # noqa: E501 """Update filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_mount_filesystem(mount_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to update (required) :param MountInformation body: The updated filesystem (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.update_mount_filesystem_with_http_info(mount_id, body, **kwargs) # noqa: E501 else: (data) = self.update_mount_filesystem_with_http_info(mount_id, body, **kwargs) # noqa: E501 return data def update_mount_filesystem_with_http_info(self, mount_id, body, **kwargs): # noqa: E501 """Update filesystem mount # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_mount_filesystem_with_http_info(mount_id, body, async_req=True) >>> result = thread.get() :param async_req bool :param int mount_id: The ID of the mount to update (required) :param MountInformation body: The updated filesystem (required) :return: MountInformation If the method is called asynchronously, returns the request thread. """ all_params = ['mount_id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_mount_filesystem" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'mount_id' is set if self.api_client.client_side_validation and ('mount_id' not in params or params['mount_id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `mount_id` when calling `update_mount_filesystem`") # noqa: E501 # verify the required parameter 'body' is set if self.api_client.client_side_validation and ('body' not in params or params['body'] is None): # noqa: E501 raise ValueError("Missing the required parameter `body` when calling `update_mount_filesystem`") # noqa: E501 collection_formats = {} path_params = {} if 'mount_id' in params: path_params['mountID'] = params['mount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/mount-filesystem/{mountID}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='MountInformation', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

40.142138

142

0.609062

3,684

31,913

5.010043

0.04696

0.046378

0.024273

0.031208

0.960069

0.959582

0.948204

0.937314

0.932167

0.929891

0

0.01487

0.304578

31,913

794

143

40.192695

0.816789

0.315796

0

0.81106

1

0

0.180413

0.052746

0

1

0.039171

false

0

0.009217

0

0.105991

0

null

0

1

0

1

0

null

0

8

8d5783e3a968024ee1976594fb9c6cbdc718ffd5

662

py

Python

dll/bener.py

syahricogan/spam

037b1a497f313e75502ea091058cbd8a6d44f4f2

[ "Apache-2.0" ]

2

2021-01-17T03:52:35.000Z

2021-03-02T18:51:12.000Z

dll/bener.py

syahricogan/spam

037b1a497f313e75502ea091058cbd8a6d44f4f2

[ "Apache-2.0" ]

null

dll/bener.py

syahricogan/spam

037b1a497f313e75502ea091058cbd8a6d44f4f2

[ "Apache-2.0" ]

5

2021-01-18T16:31:59.000Z

2021-07-12T06:08:53.000Z

import marshal,zlib,base64 exec(zlib.decompress(base64.b64decode("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")))

331

635

0.953172

26

662

24.269231

0.923077

0

0.127273

0.003021

662

2

635

331

0.828788

0

0.5

0.892911

0

1

0

1

0

true

0

0.5

0

0.5

0

1

0

1

null

0

1

0

1

0

1

null

1

0

1

0

1

0

10

8d68c5b57b8d32eecf44653744baf367dbfb01d8

14,387

py

Python

poloniex_orderbook_error.py

nateGeorge/crypto_predict

5058af6d389cc06d40e21a663eff3901511198c0

[ "Apache-2.0" ]

null

poloniex_orderbook_error.py

nateGeorge/crypto_predict

5058af6d389cc06d40e21a663eff3901511198c0

[ "Apache-2.0" ]

null

poloniex_orderbook_error.py

nateGeorge/crypto_predict

5058af6d389cc06d40e21a663eff3901511198c0

[ "Apache-2.0" ]

null

saving BTC_RADS retrieving orderbooks... HTTPSConnectionPool(host='poloniex.com', port=443): Max retries excee) Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n (self.host, self.port), self.timeout, **extra_kw) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/connection for res in socket.getaddrinfo(host, port, family, socket.SOCK_STR: File "/usr/lib/python3.5/socket.py", line 732, in getaddrinfo for res in _socket.getaddrinfo(host, port, family, type, proto, f: socket.gaierror: [Errno -3] Temporary failure in name resolution During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln chunked=chunked) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpoolt self._validate_conn(conn) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln conn.connect() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"t conn = self._new_conn() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n self, "Failed to establish a new connection: %s" % e) urllib3.exceptions.NewConnectionError: <urllib3.connection.VerifiedHTn During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d timeout=timeout File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln _stacktrace=sys.exc_info()[2]) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/retry.py"t raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='poloniex.) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",g return func(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",_ ret = _get(**payload) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return request('get', url, params=params, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return session.request(method=method, url=url, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",t resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",d r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPSConnectionPool(host='poloni) HTTPSConnectionPool(host='poloniex.com', port=443): Max retries excee) Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n (self.host, self.port), self.timeout, **extra_kw) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/connection for res in socket.getaddrinfo(host, port, family, socket.SOCK_STR: File "/usr/lib/python3.5/socket.py", line 732, in getaddrinfo for res in _socket.getaddrinfo(host, port, family, type, proto, f: socket.gaierror: [Errno -3] Temporary failure in name resolution During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln chunked=chunked) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpoolt self._validate_conn(conn) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln conn.connect() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"t conn = self._new_conn() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n self, "Failed to establish a new connection: %s" % e) urllib3.exceptions.NewConnectionError: <urllib3.connection.VerifiedHTn During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d timeout=timeout File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln _stacktrace=sys.exc_info()[2]) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/retry.py"t raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='poloniex.) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",g return func(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",_ ret = _get(**payload) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return request('get', url, params=params, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return session.request(method=method, url=url, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",t resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",d r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPSConnectionPool(host='poloni) HTTPSConnectionPool(host='poloniex.com', port=443): Max retries excee) Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n (self.host, self.port), self.timeout, **extra_kw) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/connection for res in socket.getaddrinfo(host, port, family, socket.SOCK_STR: File "/usr/lib/python3.5/socket.py", line 732, in getaddrinfo for res in _socket.getaddrinfo(host, port, family, type, proto, f: socket.gaierror: [Errno -3] Temporary failure in name resolution During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln chunked=chunked) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpoolt self._validate_conn(conn) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln conn.connect() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"t conn = self._new_conn() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n self, "Failed to establish a new connection: %s" % e) urllib3.exceptions.NewConnectionError: <urllib3.connection.VerifiedHTn During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d timeout=timeout File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln _stacktrace=sys.exc_info()[2]) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/retry.py"t raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='poloniex.) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",g return func(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",_ ret = _get(**payload) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return request('get', url, params=params, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return session.request(method=method, url=url, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",t resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",d r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPSConnectionPool(host='poloni) HTTPSConnectionPool(host='poloniex.com', port=443): Max retries excee) Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n (self.host, self.port), self.timeout, **extra_kw) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/connection for res in socket.getaddrinfo(host, port, family, socket.SOCK_STR: File "/usr/lib/python3.5/socket.py", line 732, in getaddrinfo for res in _socket.getaddrinfo(host, port, family, type, proto, f: socket.gaierror: [Errno -3] Temporary failure in name resolution During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln chunked=chunked) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpoolt self._validate_conn(conn) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln conn.connect() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"t conn = self._new_conn() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n self, "Failed to establish a new connection: %s" % e) urllib3.exceptions.NewConnectionError: <urllib3.connection.VerifiedHTn During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d timeout=timeout File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln _stacktrace=sys.exc_info()[2]) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/retry.py"t raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='poloniex.) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",g return func(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",_ ret = _get(**payload) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return request('get', url, params=params, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return session.request(method=method, url=url, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",t resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",d r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPSConnectionPool(host='poloni) [ConnectionError(MaxRetryError("HTTPSConnectionPool(host='poloniex.co] Exception in thread Thread-14: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n (self.host, self.port), self.timeout, **extra_kw) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/connection for res in socket.getaddrinfo(host, port, family, socket.SOCK_STR: File "/usr/lib/python3.5/socket.py", line 732, in getaddrinfo for res in _socket.getaddrinfo(host, port, family, type, proto, f: socket.gaierror: [Errno -3] Temporary failure in name resolution During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln chunked=chunked) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpoolt self._validate_conn(conn) File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln conn.connect() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"t conn = self._new_conn() File "/usr/local/lib/python3.5/dist-packages/urllib3/connection.py"n self, "Failed to establish a new connection: %s" % e) urllib3.exceptions.NewConnectionError: <urllib3.connection.VerifiedHTn During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d timeout=timeout File "/usr/local/lib/python3.5/dist-packages/urllib3/connectionpooln _stacktrace=sys.exc_info()[2]) File "/usr/local/lib/python3.5/dist-packages/urllib3/util/retry.py"t raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='poloniex.) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/lib/python3.5/threading.py", line 914, in _bootstrap_innr self.run() File "/usr/lib/python3.5/threading.py", line 862, in run self._target(*self._args, **self._kwargs) File "/home/nate/github/crypto_predict_latest/crypto_predict/code/pg Poloniex allows 6 calls/second before your IP is banned. File "/home/nate/github/crypto_predict_latest/crypto_predict/code/ps File "/home/nate/github/crypto_predict_latest/crypto_predict/code/ps full depth File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",k 'depth': str(depth) File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",g return func(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/poloniex/__init__.py",_ ret = _get(**payload) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return request('get', url, params=params, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/api.py", linet return session.request(method=method, url=url, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",t resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/sessions.py",d r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.5/dist-packages/requests/adapters.py",d raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPSConnectionPool(host='poloni)

50.480702

70

0.757628

2,063

14,387

5.223461

0.073679

0.060412

0.094933

0.11971

0.977635

0.97216

0

0.022715

0.106485

14,387

284

71

50.658451

0.815558

0

0.948819

0

0.098425

0.28074

0.262112

0

null

0

null

0

null

0

1

0

1

0

null

0

1

0

8

8d88e514dc4c25069bc8af6e7e8423a588c68861

693

py

Python

domains/gym_taxi/tests/reproducability.py

AndrewPaulChester/sage-code

9fe676bfbcbc6f642eca29b30a1027fba2a426a0

[ "MIT" ]

null

domains/gym_taxi/tests/reproducability.py

AndrewPaulChester/sage-code

9fe676bfbcbc6f642eca29b30a1027fba2a426a0

[ "MIT" ]

null

domains/gym_taxi/tests/reproducability.py

AndrewPaulChester/sage-code

9fe676bfbcbc6f642eca29b30a1027fba2a426a0

[ "MIT" ]

null

from domains.gym_taxi.envs import taxi_env import time import numpy as np # np.random.seed(1) # print(np.random.randint(6)) # print(np.random.randint(6)) # print(np.random.randint(6)) # print(np.random.randint(6)) # np.random.seed(1) # print(np.random.randint(6)) # print(np.random.randint(6)) # print(np.random.randint(6)) # print(np.random.randint(6)) # np.random.seed(2) # print(np.random.randint(6)) # print(np.random.randint(6)) # print(np.random.randint(6)) # print(np.random.randint(6)) env = taxi_env.JsonTaxiEnv("mixed", "predictable") # env.reset() # env.render() # env.render() # time.sleep(2) # env.reset() env.seed(1) env.reset() env.render() env.render() time.sleep(20)

17.769231

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null

0

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8

570015042da1184e500abb62c5004cc6d759cd0b

199

py

Python

whatistheplan/models/__init__.py

Cookie150CC/whatistheplan.com

bcee8f769a0e820b4bc8f619b3fb118fd6f1e68c

[ "MIT" ]

5

2015-04-06T16:56:20.000Z

2017-03-27T15:34:12.000Z

whatistheplan/models/__init__.py

Cookie150CC/whatistheplan.com

bcee8f769a0e820b4bc8f619b3fb118fd6f1e68c

[ "MIT" ]

48

2015-04-03T23:15:42.000Z

2018-10-05T19:08:50.000Z

whatistheplan/models/__init__.py

Cookie150CC/whatistheplan.com

bcee8f769a0e820b4bc8f619b3fb118fd6f1e68c

[ "MIT" ]

7

2015-04-10T20:50:17.000Z

2018-09-07T18:28:09.000Z

"""Aggregate all database classes for easy importing""" from whatistheplan.models.userprofile import UserProfile from whatistheplan.models.game import Game from whatistheplan.models.team import Team

39.8

56

0.844221

25

199

6.72

0.56

0.303571

0.410714

0

0.095477

199

4

57

49.75

0.933333

0.246231

0

1

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true

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1

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1

0

1

0

null

0

1

0

1

0

1

0

7

f509d5a1463b80de35df698cdc839503206f0623

66

py

Python

tests/t5.py

jplevyak/pyc

9f4bc49be78ba29427841460945ce63826fcd857

[ "BSD-3-Clause" ]

3

2019-08-21T22:01:35.000Z

2021-07-25T00:21:28.000Z

tests/t5.py

jplevyak/pyc

9f4bc49be78ba29427841460945ce63826fcd857

[ "BSD-3-Clause" ]

null

tests/t5.py

jplevyak/pyc

9f4bc49be78ba29427841460945ce63826fcd857

[ "BSD-3-Clause" ]

null

print 1 + 2 print 2 - 1 print 2 * 2 print -1 print -(-1) print ~1

9.428571

11

0.590909

15

66

2.6

0.2

0.615385

0.564103

0.615385

0

0.1875

0.272727

66

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11

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null

0

null

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null

1

0

1

0

null

0

1

0

1

0

7

f56943657c33c5e8316add28848cfbd4fddae1e4

111

py

Python

boa3_test/test_sc/interop_test/runtime/InvocationCounter.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

25

2020-07-22T19:37:43.000Z

2022-03-08T03:23:55.000Z

boa3_test/test_sc/interop_test/runtime/InvocationCounter.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

419

2020-04-23T17:48:14.000Z

2022-03-31T13:17:45.000Z

boa3_test/test_sc/interop_test/runtime/InvocationCounter.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

15

2020-05-21T21:54:24.000Z

2021-11-18T06:17:24.000Z

from boa3.builtin.interop.runtime import invocation_counter def Main() -> int: return invocation_counter

18.5

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111

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0.4

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null

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8

f58794cf9bf98e493a3a35302bab8601d4799839

190

py

Python

iotbx/command_line/reflection_file_editor.py

dperl-sol/cctbx_project

b9e390221a2bc4fd00b9122e97c3b79c632c6664

[ "BSD-3-Clause-LBNL" ]

155

2016-11-23T12:52:16.000Z

2022-03-31T15:35:44.000Z

iotbx/command_line/reflection_file_editor.py

dperl-sol/cctbx_project

b9e390221a2bc4fd00b9122e97c3b79c632c6664

[ "BSD-3-Clause-LBNL" ]

590

2016-12-10T11:31:18.000Z

2022-03-30T23:10:09.000Z

iotbx/command_line/reflection_file_editor.py

dperl-sol/cctbx_project

b9e390221a2bc4fd00b9122e97c3b79c632c6664

[ "BSD-3-Clause-LBNL" ]

115

2016-11-15T08:17:28.000Z

2022-02-09T15:30:14.000Z

from __future__ import absolute_import, division, print_function import sys from iotbx import reflection_file_editor if __name__ == "__main__" : reflection_file_editor.run(sys.argv[1:])

23.75

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0.810526

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190

5.230769

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0.294118

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7

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null

0

1

0

1

0

1

0

7

1961f9b770d13814d3cde43fc000846f59887ef3

102

py

Python

execute_517/__init__.py

Cadair/execute-517

f57b05ceda3caf5f34b0790260b14604b60f583a

[ "BSD-3-Clause" ]

null

execute_517/__init__.py

Cadair/execute-517

f57b05ceda3caf5f34b0790260b14604b60f583a

[ "BSD-3-Clause" ]

2

2020-11-10T13:31:09.000Z

2020-11-10T14:54:11.000Z

execute_517/__init__.py

Cadair/execute-517

f57b05ceda3caf5f34b0790260b14604b60f583a

[ "BSD-3-Clause" ]

null

from .version import __version__ from .run import run_python_in_env __all__ = ['run_python_in_env']

17

34

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102

4.25

0.5

0.264706

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0.411765

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7

198779f7a1fa7bbbc94dfcd521af04b52b5f0a53

6,109

py

Python

2020/Day17/Cubes.py

dh256/adventofcode

428eec13f4cbf153333a0e359bcff23070ef6d27

[ "MIT" ]

null

2020/Day17/Cubes.py

dh256/adventofcode

428eec13f4cbf153333a0e359bcff23070ef6d27

[ "MIT" ]

null

2020/Day17/Cubes.py

dh256/adventofcode

428eec13f4cbf153333a0e359bcff23070ef6d27

[ "MIT" ]

null

class Cubes: # get active cubes # range is the min-1 to nax-1 for each dimension def ranges(self): active_cubes = [item[0] for item in list(filter(lambda i:i[1],self.grid.items()))] min_x = min(active_cubes,key=lambda i:i[0])[0] max_x = max(active_cubes,key=lambda i:i[0])[0] min_y = min(active_cubes,key=lambda i:i[1])[1] max_y = max(active_cubes,key=lambda i:i[1])[1] min_z = min(active_cubes,key=lambda i:i[2])[2] max_z = max(active_cubes,key=lambda i:i[2])[2] return (min_x-1,max_x+1,min_y-1,max_y+1,min_z-1,max_z+1) def __init__(self,filename) -> None: self.grid = {} # grid - key is coord of cube, value is state (False, inactive; True, active) with open(filename,"r") as input_file: initial_grid_points = [line.strip('\n') for line in input_file] x = 0 y = 0 z = 0 for row in initial_grid_points: x = 0 for c in row: self.grid[(x,y,z)] = c == '#' x += 1 y += 1 def get_neighbours(self,coord): neighbours = [(x,y,z) for x in range(coord[0]-1,coord[0]+2) for y in range(coord[1]-1,coord[1]+2) for z in range(coord[2]-1,coord[2]+2)] # make sure they are all in the grid for neighbour in neighbours: if neighbour not in self.grid.keys(): self.grid[neighbour] = False # remove actual coord neighbours.remove(coord) return neighbours def cycle(self,cycles): # Go through neighbours, if active count; if inactive get all its neighbours and count active, if 3 active add to switch_list (for active cubes if active count is 2 or 3 add to switch_list) # Repeat cycle number of times for cycle in range(0,cycles): # get all active cubes switch_list = [] # contains the co-ords of all cubes to switch ranges = self.ranges() # for each cube - get neighbours for x in range(ranges[0],ranges[1]+1): for y in range(ranges[2],ranges[3]+1): for z in range(ranges[4],ranges[5]+1): neighbours = self.get_neighbours((x,y,z)) active_neighbours = len([n for n in neighbours if self.grid[n]]) if (self.grid[(x,y,z)] and active_neighbours not in (2,3)) or (not self.grid[(x,y,z)] and active_neighbours == 3): switch_list.append((x,y,z)) for cube in switch_list: if not cube in self.grid.keys(): self.grid[cube] = False self.grid[cube] = not self.grid[cube] # return number of active cubes return len(list(filter(lambda v:v,self.grid.values()))) class Cubes2: # get active cubes # range is the min-1 to nax-1 for each dimension def ranges(self): active_cubes = [item[0] for item in list(filter(lambda i:i[1],self.grid.items()))] min_x = min(active_cubes,key=lambda i:i[0])[0] max_x = max(active_cubes,key=lambda i:i[0])[0] min_y = min(active_cubes,key=lambda i:i[1])[1] max_y = max(active_cubes,key=lambda i:i[1])[1] min_z = min(active_cubes,key=lambda i:i[2])[2] max_z = max(active_cubes,key=lambda i:i[2])[2] min_w = min(active_cubes,key=lambda i:i[3])[3] max_w = max(active_cubes,key=lambda i:i[3])[3] return (min_x-1,max_x+1,min_y-1,max_y+1,min_z-1,max_z+1,min_w-1,max_w+1) def __init__(self,filename) -> None: self.grid = {} # grid - key is coord of cube, value is state (False, inactive; True, active) with open(filename,"r") as input_file: initial_grid_points = [line.strip('\n') for line in input_file] x = 0 y = 0 z = 0 w = 0 for row in initial_grid_points: x = 0 for c in row: self.grid[(x,y,z,w)] = c == '#' x += 1 y += 1 def get_neighbours(self,coord): neighbours = [(x,y,z,w) for x in range(coord[0]-1,coord[0]+2) for y in range(coord[1]-1,coord[1]+2) for z in range(coord[2]-1,coord[2]+2) for w in range(coord[3]-1,coord[3]+2)] # make sure they are all in the grid for neighbour in neighbours: if neighbour not in self.grid.keys(): self.grid[neighbour] = False # remove actual coord neighbours.remove(coord) return neighbours def cycle(self,cycles): # Go through neighbours, if active count; if inactive get all its neighbours and count active, if 3 active add to switch_list (for active cubes if active count is 2 or 3 add to switch_list) # Repeat cycle number of times for cycle in range(0,cycles): # get all active cubes switch_list = [] # contains the co-ords of all cubes to switch ranges = self.ranges() # for each cube - get neighbours for x in range(ranges[0],ranges[1]+1): for y in range(ranges[2],ranges[3]+1): for z in range(ranges[4],ranges[5]+1): for w in range(ranges[6],ranges[7]+1): neighbours = self.get_neighbours((x,y,z,w)) active_neighbours = len([n for n in neighbours if self.grid[n]]) if (self.grid[(x,y,z,w)] and active_neighbours not in (2,3)) or (not self.grid[(x,y,z,w)] and active_neighbours == 3): switch_list.append((x,y,z,w)) for cube in switch_list: if not cube in self.grid.keys(): self.grid[cube] = False self.grid[cube] = not self.grid[cube] # return number of active cubes return len(list(filter(lambda v:v,self.grid.values())))

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5ff85b78082b4439aba47027801b0952f89e55f9

33,068

py

Python

2018/Day08.py

hrmorley34/AdventofCode

74590422717fb5c6b80ef3fca226359d354c4aec

[ "MIT" ]

null

2018/Day08.py

hrmorley34/AdventofCode

74590422717fb5c6b80ef3fca226359d354c4aec

[ "MIT" ]

null

2018/Day08.py

hrmorley34/AdventofCode

74590422717fb5c6b80ef3fca226359d354c4aec

[ "MIT" ]

null

numbers = "8 11 6 2 4 3 3 6 1 5 0 7 1 8 5 2 4 1 1 1 1 3 2 1 1 9 0 7 6 6 1 4 1 2 2 1 1 3 3 2 2 1 1 1 1 6 0 10 4 7 5 5 3 3 8 4 4 1 1 3 1 2 1 1 4 5 3 2 3 5 3 4 1 9 0 9 8 7 1 2 3 1 9 1 3 1 3 1 2 3 2 1 3 2 1 9 0 10 5 2 7 8 7 9 6 3 8 1 1 3 3 3 3 1 2 1 2 1 5 0 8 4 4 8 2 2 7 4 1 2 1 2 3 1 3 3 2 3 3 7 1 9 0 10 9 3 1 4 8 9 2 6 7 4 1 3 1 1 3 3 3 1 3 1 7 0 6 8 7 6 3 4 1 1 1 1 1 1 2 1 1 7 0 8 1 9 5 2 2 1 1 5 3 3 1 3 3 2 2 5 2 4 1 5 4 2 3 5 1 6 0 6 1 5 2 1 8 5 1 3 1 1 1 3 1 8 0 10 4 3 1 7 1 8 6 9 9 9 1 1 1 1 2 3 1 2 1 7 0 11 2 3 1 2 3 5 2 5 1 2 4 2 2 1 1 2 1 2 1 4 1 1 1 4 2 1 4 5 3 5 1 8 0 6 3 6 6 8 1 9 1 1 2 1 3 1 2 3 1 8 0 6 4 9 5 1 6 1 2 2 1 2 2 3 2 2 1 5 0 10 7 5 3 1 9 8 1 5 6 4 3 1 3 1 3 3 2 3 2 1 3 5 1 8 0 9 7 6 1 3 3 1 1 8 7 1 1 1 3 2 1 3 1 1 5 0 11 4 3 1 4 1 7 7 7 9 6 6 3 1 1 1 1 1 5 0 6 1 2 3 1 4 9 3 1 2 3 2 4 4 2 4 5 3 5 1 6 0 10 1 2 5 1 8 1 1 7 6 7 1 2 2 1 1 1 1 7 0 10 8 9 7 8 1 2 1 5 3 5 1 3 1 1 1 3 1 1 6 0 7 7 8 7 1 9 7 1 3 1 3 3 3 1 4 4 4 3 2 3 4 1 5 0 6 7 7 1 6 4 2 1 1 2 1 3 1 6 0 7 4 3 4 1 2 4 6 3 2 3 1 1 3 1 8 0 6 8 8 4 1 1 1 3 1 3 3 3 3 1 1 1 5 5 3 3 6 1 2 1 5 3 3 7 1 6 0 8 3 1 2 9 1 6 8 1 1 3 2 2 3 1 1 5 0 11 1 2 3 4 1 4 9 8 4 6 9 1 3 2 2 1 1 9 0 8 1 6 6 5 4 9 1 2 1 2 1 3 1 2 1 1 3 3 3 3 1 3 1 3 3 4 1 7 0 6 9 1 1 4 1 3 1 2 1 3 3 1 1 1 7 0 10 8 5 5 1 2 3 6 9 9 1 3 1 3 2 3 2 3 1 5 0 9 9 4 1 1 8 3 8 5 3 1 1 2 1 1 1 1 2 5 3 6 1 7 0 9 8 4 1 9 1 9 2 2 1 3 2 1 2 3 3 3 1 6 0 8 9 2 8 7 9 5 1 1 1 3 2 2 1 2 1 6 0 9 5 5 9 5 6 9 3 1 7 3 1 3 1 3 3 4 1 1 1 5 3 3 7 1 6 0 7 4 6 1 1 2 2 7 1 1 3 2 3 1 1 5 0 9 6 9 2 7 3 3 1 5 7 3 1 2 1 3 1 5 0 9 5 6 5 8 6 1 8 2 8 1 1 2 3 3 2 2 4 5 5 3 4 3 5 1 8 0 10 1 3 2 3 1 1 3 8 8 4 1 1 2 2 3 3 2 2 1 5 0 8 3 6 7 8 1 4 5 3 2 1 2 1 1 1 9 0 8 3 2 3 7 9 1 1 1 2 3 2 2 2 1 3 1 3 4 2 2 3 3 2 6 4 5 4 3 5 1 5 0 11 7 9 3 1 3 8 5 9 9 2 6 2 1 3 2 3 1 9 0 9 1 4 1 1 4 8 8 1 1 2 1 2 1 3 3 1 3 3 1 5 0 10 7 8 7 5 6 3 5 2 3 1 1 1 1 3 3 5 2 4 1 5 3 7 1 7 0 9 7 7 2 6 1 5 6 6 6 3 3 1 3 2 1 3 1 9 0 11 1 5 7 4 2 8 3 2 8 9 7 1 2 3 2 2 3 3 1 2 1 9 0 10 6 3 3 8 2 1 7 3 9 8 1 3 3 1 2 1 2 1 1 3 1 2 4 3 5 2 3 6 1 7 0 8 9 2 8 4 9 1 8 4 2 2 3 2 2 1 1 1 5 0 7 7 7 1 9 8 8 9 2 2 1 1 3 1 5 0 8 9 4 4 4 2 8 4 1 1 3 1 1 2 2 1 5 2 5 3 3 5 1 8 0 6 7 9 1 6 3 4 2 1 3 1 2 1 1 2 1 7 0 6 9 1 3 8 1 2 3 1 2 2 3 2 2 1 7 0 6 5 7 1 1 3 1 1 2 1 1 2 3 1 1 3 1 3 4 3 7 1 8 0 8 6 2 7 7 9 1 2 4 2 2 3 2 1 2 1 3 1 8 0 7 6 8 4 7 1 1 1 2 2 1 2 1 1 1 3 1 6 0 11 1 8 9 8 3 6 7 6 5 8 2 2 1 2 1 1 3 2 5 1 1 3 3 1 4 6 1 2 4 5 3 5 1 5 0 6 1 6 2 9 4 1 1 1 1 3 2 1 7 0 11 7 9 8 5 1 8 1 2 8 6 1 1 2 3 1 1 3 1 1 8 0 6 5 7 7 8 1 2 3 2 2 1 2 1 2 3 3 4 4 1 5 3 5 1 5 0 11 1 7 6 1 3 7 8 3 6 5 1 2 1 2 3 1 1 7 0 10 4 4 1 4 7 7 7 8 7 7 3 1 3 2 2 1 3 1 7 0 6 7 9 4 7 1 4 2 1 1 1 1 2 1 1 1 3 4 3 3 4 1 5 0 11 6 4 3 3 1 1 3 8 1 5 2 1 3 1 3 2 1 8 0 7 6 9 8 7 1 1 5 1 3 1 1 3 1 3 2 1 5 0 8 8 6 7 8 9 1 5 6 2 2 2 1 1 3 5 2 3 3 5 1 9 0 9 1 5 1 7 7 6 1 1 2 3 1 2 3 2 1 3 3 1 1 6 0 9 1 3 5 4 1 1 6 5 7 1 2 3 2 1 2 1 9 0 8 3 5 1 8 2 1 1 1 2 3 1 3 2 2 2 3 2 4 1 1 2 3 4 2 4 4 5 5 5 3 7 1 8 0 6 3 6 4 5 2 1 2 1 3 1 2 2 1 1 1 9 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8 5 1 9 7 3 4 9 4 1 3 3 1 3 2 1 5 0 9 9 5 1 6 3 7 3 1 4 1 1 2 2 1 1 2 4 5 2 4 4 3 4 1 8 0 9 6 7 8 1 4 3 7 4 5 1 1 1 1 3 3 2 1 1 5 0 11 4 8 1 1 1 2 4 4 1 5 1 2 1 1 1 1 1 9 0 9 5 3 4 5 4 1 2 5 8 3 2 2 1 1 2 2 1 2 3 2 3 2 3 7 1 7 0 11 6 7 1 9 9 8 3 4 7 9 8 1 2 3 1 2 1 1 1 5 0 7 9 1 8 5 1 1 8 1 3 1 2 1 1 9 0 11 3 9 1 4 3 8 2 1 4 9 5 2 1 1 3 2 3 3 3 1 3 5 3 5 2 4 2 3 5 1 6 0 9 1 2 8 3 3 1 5 9 8 2 1 3 2 2 1 1 6 0 11 7 5 2 7 1 2 4 4 1 1 4 2 2 2 2 1 1 1 6 0 8 3 2 4 1 8 6 4 6 1 1 2 2 1 3 2 4 3 4 5 5 6 3 4 3 3 4 1 5 0 10 2 3 8 5 6 1 1 5 2 8 2 2 1 2 1 1 9 0 11 9 1 7 4 9 8 1 8 4 3 1 2 3 2 2 3 2 1 1 3 1 7 0 7 9 5 5 9 1 5 1 1 2 3 3 2 1 1 1 4 5 1 3 7 1 5 0 7 2 6 1 4 1 1 6 2 1 2 3 1 1 6 0 6 1 1 5 2 6 4 2 2 3 1 1 1 1 7 0 9 1 7 1 1 8 4 7 7 8 1 2 2 2 2 1 2 1 2 1 3 1 4 5 3 4 1 8 0 10 1 1 5 6 7 6 6 6 9 5 1 1 1 1 1 2 1 2 1 5 0 6 5 1 4 1 3 9 2 2 1 2 3 1 9 0 10 4 8 6 3 1 8 5 9 5 1 2 2 3 2 1 1 2 1 1 3 1 5 3 3 4 1 6 0 10 6 9 9 1 5 1 8 6 5 5 3 3 2 3 1 1 1 6 0 9 1 1 2 8 8 7 5 1 9 1 3 1 1 2 1 1 5 0 9 1 1 9 7 7 9 5 1 8 3 1 1 3 3 1 1 5 1 3 2 3 3 6 3 8 2 6 7 5 1 6 4 3 9 4" #numbers = "2 3 0 3 10 11 12 1 1 0 1 99 2 1 1 2" def ids_gen(): x = 1 while True: yield x x += 1 ids = ids_gen() def parse_node(numbers): numbers = iter(numbers) c_id = next(ids) children_n = next(numbers) children = [] metadata_n = next(numbers) metadata = [] for x in range(0, children_n): children.append(parse_node(numbers)) for x in range(0, metadata_n): metadata.append(next(numbers)) return([c_id, children, metadata]) def total_sum(nodemap): return(sum(map(lambda c: total_sum(c), nodemap[1]))+sum(nodemap[2])) def special_sum(nodemap): if len(nodemap[1]) == 0: return(sum(nodemap[2])) else: total = 0 for r in nodemap[2]: if r in range(1, len(nodemap[1])+1): total += special_sum(nodemap[1][r-1]) return(total) numbers = list(map(int, numbers.split(" "))) root = parse_node(numbers) print(total_sum(root)) print(special_sum(root))

769.023256

32,072

0.506532

16,063

33,068

1.041711

0.003175

0.157174

0.076555

0.032033

0.851192

0.693779

0.522261

0.288651

0.101596

0.029702

0

0.958212

0.489083

33,068

42

32,073

787.333333

0.032199

0.001421

0

0.029412

0.970957

0

1

0.117647

false

0

0.029412

0.117647

0.058824

0

1

null

0

1

0

1

0

1

0

1

0

null

0

7

27157d35ef7dbf12c8c7abc7071b48ae43b32fce

2,989

py

Python

easistrain/EDD/EDD_Test_fund_method.py

woutdenolf/easistrain

0484168e33e548af01a5cc649abf815c45b182f1

[ "MIT" ]

null

easistrain/EDD/EDD_Test_fund_method.py

woutdenolf/easistrain

0484168e33e548af01a5cc649abf815c45b182f1

[ "MIT" ]

null

easistrain/EDD/EDD_Test_fund_method.py

woutdenolf/easistrain

0484168e33e548af01a5cc649abf815c45b182f1

[ "MIT" ]

1

2021-08-04T14:02:16.000Z

import numpy as np import scipy.optimize def diffVector(angles, e11, e22, e33, e23, e13, e12): phi = np.radians(angles[:, 0]) chi = np.radians(angles[:, 1]) omega = np.radians(angles[:, 2]) theta = np.radians(angles[:, 3]) delta = np.radians(angles[:, 4]) q1 = ( (np.cos(theta) * np.cos(chi) * np.sin(delta) * np.sin(phi)) + ( np.cos(delta) * np.cos(theta) * ( (np.cos(phi) * np.sin(omega)) - (np.cos(omega) * np.sin(phi) * np.sin(chi)) ) ) - np.sin(theta) * ((np.cos(phi) * np.cos(omega)) + (np.sin(phi) * np.sin(chi) * np.sin(omega))) ) q2 = ( np.cos(delta) * np.cos(theta) * ((np.cos(phi) * np.cos(omega) * np.sin(chi)) + (np.sin(phi) * np.sin(omega))) - (np.cos(theta) * np.cos(phi) * np.cos(chi) * np.sin(delta)) - ( np.sin(theta) * ( (np.cos(omega) * np.sin(phi)) - (np.cos(phi) * np.sin(chi) * np.sin(omega)) ) ) ) q3 = ( (np.cos(delta) * np.cos(theta) * np.cos(chi) * np.cos(omega)) + (np.cos(theta) * np.sin(delta) * np.sin(chi)) + (np.cos(chi) * np.sin(theta) * np.sin(omega)) ) defDirMeas = ( (e11 * q1 ** 2) + (e22 * q2 ** 2) + (e33 * q3 ** 2) + (2 * e12 * q1 * q2) + (2 * e13 * q1 * q3) + (2 * e23 * q2 * q3) ) return q1, q2, q3, defDirMeas def deforDirMeas(angles, e11, e22, e33, e23, e13, e12): phi = np.radians(angles[:, 0]) chi = np.radians(angles[:, 1]) omega = np.radians(angles[:, 2]) theta = np.radians(angles[:, 3]) delta = np.radians(angles[:, 4]) q1 = ( (np.cos(theta) * np.cos(chi) * np.sin(delta) * np.sin(phi)) + ( np.cos(delta) * np.cos(theta) * ( (np.cos(phi) * np.sin(omega)) - (np.cos(omega) * np.sin(phi) * np.sin(chi)) ) ) - np.sin(theta) * ((np.cos(phi) * np.cos(omega)) + (np.sin(phi) * np.sin(chi) * np.sin(omega))) ) q2 = ( np.cos(delta) * np.cos(theta) * ((np.cos(phi) * np.cos(omega) * np.sin(chi)) + (np.sin(phi) * np.sin(omega))) - (np.cos(theta) * np.cos(phi) * np.cos(chi) * np.sin(delta)) - ( np.sin(theta) * ( (np.cos(omega) * np.sin(phi)) - (np.cos(phi) * np.sin(chi) * np.sin(omega)) ) ) ) q3 = ( (np.cos(delta) * np.cos(theta) * np.cos(chi) * np.cos(omega)) + (np.cos(theta) * np.sin(delta) * np.sin(chi)) + (np.cos(chi) * np.sin(theta) * np.sin(omega)) ) defDirMeas = ( (e11 * q1 ** 2) + (e22 * q2 ** 2) + (e33 * q3 ** 2) + (2 * e12 * q1 * q2) + (2 * e13 * q1 * q3) + (2 * e23 * q2 * q3) ) return defDirMeas

30.191919

87

0.424891

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2,989

3.207071

0.085859

0.181102

0.110236

0.113386

0.930709

0

0.051377

0.368351

2,989

98

88

30.5

0.621292

0

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false

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0

null

0

1

0

1

0

null

0

7

27adf2119869e9c68d0a3c070336f9f551af44d9

12,320

py

Python

directoalartista/apps/myaccount/forms.py

mpampols/directoalartista.com

833eea7f4db5a2343dba4314793d593cd66cf1fb

[ "MIT" ]

null

directoalartista/apps/myaccount/forms.py

mpampols/directoalartista.com

833eea7f4db5a2343dba4314793d593cd66cf1fb

[ "MIT" ]

null

directoalartista/apps/myaccount/forms.py

mpampols/directoalartista.com

833eea7f4db5a2343dba4314793d593cd66cf1fb

[ "MIT" ]

1

2018-03-29T02:16:18.000Z

# -*- coding: utf-8 -*- from django.forms import ModelForm from django.db import models from django import forms from django.contrib.admin.widgets import * from localflavor.es.forms import ESProvinceSelect, ESIdentityCardNumberField, ESPostalCodeField, ESPhoneNumberField from directoalartista.apps.genericuser.models import GenericUser from django.contrib.auth import get_user_model User = get_user_model() class GenericUserEditProfileFormArtist(ModelForm): user = models.ForeignKey(User, unique=True) email = forms.CharField(max_length=75, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', 'type': 'email', }), label='Email' ) phone = ESPhoneNumberField(max_length=15, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', 'type': 'tel', }), label='Teléfono' ) first_name = forms.CharField(max_length=30, widget=forms.TextInput( attrs={ 'class': 'form-control', 'placeholder': 'El de verdad, no el artístico', 'required': 'true' }), label='Nombre' ) last_name = forms.CharField(max_length=60, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='Apellidos' ) dni = forms.CharField(max_length=10, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='DNI' ) address = forms.CharField(max_length=255, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control' }), label='Dirección' ) postal_code = ESPostalCodeField(max_length=10, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='Código postal' ) city = forms.CharField(max_length=80, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='Ciudad' ) province = forms.CharField(max_length=80, widget=ESProvinceSelect( attrs={ 'class': 'form-control', }), label='Provincia' ) actual_password = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Contraseña' ) new_password = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Nueva contraseña' ) new_password_repeat = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Repite la nueva contraseña' ) newsletter_subscription = forms.BooleanField(required=False) class Meta: model = GenericUser fields = {"email", "phone", "first_name", "last_name", "dni", "address", "postal_code", "city", "province", "actual_password", "new_password", "new_password_repeat", "newsletter_subscription"} def __unicode__(self): return unicode(self.user) class GenericUserEditProfileFormAgency(ModelForm): user = models.ForeignKey(User, unique=True) email = forms.CharField(max_length=75, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', 'type': 'email', }), label='Email' ) phone = ESPhoneNumberField(max_length=15, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', 'type': 'tel', }), label='Teléfono' ) first_name = forms.CharField(max_length=30, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='Nombre' ) last_name = forms.CharField(max_length=60, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='Apellidos' ) dni = forms.CharField(max_length=10, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='DNI' ) address = forms.CharField(max_length=255, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control' }), label='Dirección' ) postal_code = ESPostalCodeField(max_length=10, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='Código postal' ) city = forms.CharField(max_length=80, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='Ciudad' ) province = forms.CharField(max_length=80, widget=ESProvinceSelect( attrs={ 'class': 'form-control', }), label='Provincia' ) agency_name = forms.CharField(max_length=255, required=True, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', }), label='Nombre de la agencia' ) agency_company_name = forms.CharField(max_length=255, required=True, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', }), label='Razón social' ) agency_cif = forms.CharField(max_length=15, required=True, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', }), label='CIF' ) agency_additional_info = forms.CharField(max_length=1000, required=False, widget=forms.Textarea( attrs={ 'class': 'form-control', 'required': 'false' }), label='Información adicional' ) actual_password = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Contraseña' ) new_password = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Nueva contraseña' ) new_password_repeat = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Repite la nueva contraseña' ) newsletter_subscription = forms.BooleanField(required=False) class Meta: model = GenericUser fields = {"email", "phone", "first_name", "last_name", "dni", "address", "postal_code", "city", "province", "agency_additional_info", "agency_cif", "agency_company_name", "agency_name", "actual_password", "new_password", "new_password_repeat", "newsletter_subscription"} def __unicode__(self): return unicode(self.user) class GenericUserEditProfileFormPromoter(ModelForm): user = models.ForeignKey(User, unique=True) email = forms.CharField(max_length=75, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', 'type': 'email', }), label='Email' ) phone = ESPhoneNumberField(max_length=15, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true', 'type': 'tel', }), label='Teléfono' ) first_name = forms.CharField(max_length=30, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='Nombre' ) last_name = forms.CharField(max_length=60, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='Apellidos' ) dni = forms.CharField(max_length=10, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='DNI' ) address = forms.CharField(max_length=255, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control' }), label='Dirección' ) postal_code = ESPostalCodeField(max_length=10, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='Código postal' ) city = forms.CharField(max_length=80, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='Ciudad' ) province = forms.CharField(max_length=80, widget=ESProvinceSelect( attrs={ 'class': 'form-control', }), label='Provincia' ) promoter_room_or_event_name = forms.CharField(max_length=255, widget=forms.TextInput( attrs={ 'class': 'form-control', 'required': 'true' }), label='Nombre de la sala o evento*' ) promoter_company_name = forms.CharField(max_length=255, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='Razón social' ) promoter_cif = forms.CharField(max_length=15, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', }), label='CIF' ) promoter_additional_info = forms.CharField(max_length=1000, required=False, widget=forms.Textarea( attrs={ 'class': 'form-control', }), label='Provincia' ) actual_password = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Contraseña' ) new_password = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Nueva contraseña' ) new_password_repeat = forms.CharField(max_length=60, required=False, widget=forms.TextInput( attrs={ 'class': 'form-control', 'type': 'password', }), label='Repite la nueva contraseña' ) newsletter_subscription = forms.BooleanField(required=False) class Meta: model = GenericUser fields = {"email", "phone", "first_name", "last_name", "dni", "address", "postal_code", "city", "province", "promoter_room_or_event_name", "promoter_company_name", "promoter_cif", "promoter_additional_info", "actual_password", "new_password", "new_password_repeat", "newsletter_subscription"} def __unicode__(self): return unicode(self.user)

30.723192

117

0.516071

1,058

12,320

5.879017

0.106805

0.063666

0.099035

0.148553

0.886495

0.878457

0.873633

0.86463

0.861736

0

0.012658

0.358766

12,320

400

118

30.8

0.774684

0.001705

0

0.789318

0

0.178174

0.013255

0

1

0.008902

false

0.065282

0.020772

0.008902

0.204748

0

null

0

1

0

1

0

null

0

1

0

8

fda12589643014bae8ffbc22525fe1b15f309d40

118

py

Python

ou_Axion_limit/__init__.py

OuYangMinOa/ou_Axion_limit

7f68dd906579b3cd255fa3098f9b1d6d44e412b3

[ "MIT" ]

1

2021-09-29T20:01:41.000Z

ou_Axion_limit/__init__.py

OuYangMinOa/ou_Axion_limit

7f68dd906579b3cd255fa3098f9b1d6d44e412b3

[ "MIT" ]

null

ou_Axion_limit/__init__.py

OuYangMinOa/ou_Axion_limit

7f68dd906579b3cd255fa3098f9b1d6d44e412b3

[ "MIT" ]

null

from ou_Axion_limit.Glimit import Glimit from ou_Axion_limit.Analy import analyse if __name__ == "__main__": pass

16.857143

41

0.79661

18

118

4.555556

0.666667

0.146341

0.268293

0.390244

0

0.144068

118

6

42

19.666667

0.811881

0

0.067797

0

1

0

true

0.25

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

7

fdb6e1ad7ec60624db0ae18c5509acf5fa8bd887

141

py

Python

bot/text_src/__init__.py

JakubKoralewski/idiotduo-biblia-twitter

6aa65378f0964fee7d0cc305e755962acdee9b37

[ "MIT" ]

2

2019-05-12T18:48:38.000Z

2019-09-25T22:21:09.000Z

bot/text_src/__init__.py

JakubKoralewski/idiotduo-biblia-twitter

6aa65378f0964fee7d0cc305e755962acdee9b37

[ "MIT" ]

7

2019-04-05T14:20:46.000Z

2022-03-11T23:32:14.000Z

bot/text_src/__init__.py

JakubKoralewski/idiotduo-biblia-twitter

6aa65378f0964fee7d0cc305e755962acdee9b37

[ "MIT" ]

3

2019-05-12T18:51:26.000Z

2020-08-25T22:11:08.000Z

from .bible.zdobadz_cytat import zdobadz_cytat from .lexical.slowo_na_dzis import slowo_na_dzis from .rnm.get_rnm_quote import get_rnm_quote

35.25

48

0.87234

25

141

4.52

0.48

0.212389

0.19469

0

0.085106

141

3

49

47

0.875969

0

1

0

true

0

1

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1

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null

1

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1

0

null

0

1

0

1

0

1

0

7

fdd13fbba46b87a629b5978ff051acac390c6e15

15,568

py

Python

test/test_swarm.py

JouleCai/GeoSpaceLab

6cc498d3c32501e946931de596a840c73e83edb3

[ "BSD-3-Clause" ]

19

2021-08-07T08:49:22.000Z

2022-03-02T18:26:30.000Z

test/test_swarm.py

JouleCai/GeoSpaceLab

6cc498d3c32501e946931de596a840c73e83edb3

[ "BSD-3-Clause" ]

4

2021-11-09T05:53:42.000Z

2022-03-25T11:49:37.000Z

test/test_swarm.py

JouleCai/GeoSpaceLab

6cc498d3c32501e946931de596a840c73e83edb3

[ "BSD-3-Clause" ]

3

2021-11-07T11:41:20.000Z

2022-02-14T13:43:11.000Z

import cartopy.crs as ccrs import matplotlib.pyplot as plt import matplotlib.colors as colors from loaders.load_uta_gitm_201602_newrun import * import utilities.datetime_utilities as du import visualization.time_series as ts from geospacelab.visualization.mpl.geomap.geopanels import PolarMapPanel as PolarMap import geospacelab.visualization.mpl.colormaps as cm def get_swarm_data(dt_fr, dt_to, satID="C"): dt_range = [dt_fr, dt_to] instr_info1 = {'name': 'SWARM-' + satID, 'assign_key': 'SWARM_ACC'} database = 'uta' paralist = [ {'database': database, 'instrument': instr_info1, 'paraname': 'N_n_SC'}, {'database': database, 'instrument': instr_info1, 'paraname': 'N_n_s450'}, {'database': database, 'instrument': instr_info1, 'paraname': 'N_n_s500'}, ] paras_layout = [[1, 2]] tsObj = ts.TimeSeries(dt_range=dt_range, paralist=paralist, paras_layout=paras_layout, timeline='multiple') sc_lat = tsObj.dataObjs['uta_swarm_c_acc'].paras['SC_GEO_LAT'] sc_lon = tsObj.dataObjs['uta_swarm_c_acc'].paras['SC_GEO_LON'] sc_lst = tsObj.dataObjs['uta_swarm_c_acc'].paras['SC_GEO_ST'] sc_datetime = tsObj.dataObjs['uta_swarm_c_acc'].paras['SC_DATETIME'] rho_n_sc = tsObj.dataObjs['uta_swarm_c_acc'].paras['N_n_SC'] swarm_data = { 'sc_lat': sc_lat, 'sc_lon': sc_lon, 'sc_lst': sc_lst, 'sc_datetime': sc_datetime, 'rho_n_sc': rho_n_sc } return swarm_data def show_rho_n(dt_fr, dt_to): swarm_data = get_swarm_data(dt_fr, dt_to) sc_lon = swarm_data['sc_lon'].flatten() sc_lat = swarm_data['sc_lat'].flatten() sc_dt = swarm_data['sc_datetime'].flatten() rho_n_sc = swarm_data['rho_n_sc'].flatten() plt.figure(figsize=(8,8)) # cs = 'GEO' # panel = PolarView(cs='GEO', sytle='lst-fixed', pole='N', lon_c=None, lst_c=0, mlt_c=None, ut=dt_fr, boundary_lat=30., proj_style='Stereographic') cs = 'AACGM' panel = PolarMap(cs=cs, style='mlt-fixed', pole='N', lon_c=None, lst_c=None, mlt_c=0, ut=dt_fr, boundary_lat=30., proj_style='Stereographic') panel.add_subplot(major=True) panel.set_extent(boundary_style='circle') data = panel.projection.transform_points(ccrs.PlateCarree(), sc_lon, sc_lat) x = data[:, 0] y = data[:, 1] from scipy.stats import linregress coef = linregress(x, y) a = coef.slope b = coef.intercept # x1 = np.linspace(np.nanmin(x), np.nanmax(x), num=500) # y1 = np.linspace(np.nanmin(y), np.nanmax(y), num=500) # x2d, y2d = np.meshgrid(x, y) # z2d = griddata(data[:, 0:2], rho_n_sc.flatten(), (x2d, y2d), method='nearest') # z2d_dist = np.abs(a*x2d - y2d + b) / np.sqrt(a**2 + 1) # z2d = np.where(z2d_dist>1000, np.nan, z2d) # # im = panel.major_ax.pcolormesh(x2d, y2d, z2d, vmin=2e-14, vmax=20e-13, cmap='gist_ncar') # panel.major_ax.plot(sc_lon, sc_lat, transform=ccrs.Geodetic(), linewidth=0.5, color='k') # plt.colorbar(im) # xx = np.tile(x, [3, 1]) # # yy = np.concatenate((y[np.newaxis, :]-150000, y[np.newaxis, :], y[np.newaxis, :]+150000), axis=0) # zz = np.concatenate((rho_n_sc.T, rho_n_sc.T, rho_n_sc.T), axis=0) # # zz = griddata(data[:, 0:2], rho_n_sc.flatten(), (xx, yy), method='nearest') # im = panel.major_ax.pcolormesh(xx, yy, zz, vmin=2e-14, vmax=20e-13, cmap='gist_ncar') # # # panel.major_ax.plot(sc_lon, sc_lat, transform=ccrs.Geodetic(), linewidth=0.5, color='k') # plt.colorbar(im) #panel.major_ax.plot(data[:,0], data[:,1], linewidth=3) from matplotlib.collections import LineCollection coords = {'lat': sc_lat, 'lon': sc_lon, 'height': 250.} cs_new = panel.cs_transform(cs_fr='GEO', cs_to=cs, coords=coords) data = panel.projection.transform_points(ccrs.PlateCarree(), cs_new['lon'], cs_new['lat']) x = data[:, 0] y = data[:, 1] z = rho_n_sc.flatten() points = np.array([x, y]).T.reshape(-1, 1, 2) segments = np.concatenate([points[:-1], points[1:]], axis=1) norm = plt.Normalize(2e-14, 18e-13) lc = LineCollection(segments, cmap='gist_ncar', norm=norm) lc.set_array(z) lc.set_linewidth(6) line = panel.major_ax.add_collection(lc) cbar = plt.gcf().colorbar(line, ax=panel.major_ax, pad=0.1, fraction=0.03) cbar.set_label('Neutral mass density\n' + r'(kg/m$^{3}$)', rotation=270, labelpad=25) #cbaxes = plt.gcf().add_axes([0.8, 0.1, 0.03, 0.8]) #cb = plt.colorbar(panel.major_ax, cax = cbaxes) sectime, dt0 = du.convert_datetime_to_sectime(sc_dt, datetime.datetime(dt_fr.year, dt_fr.month, dt_fr.day)) sectime_res = 10 * 60 time_ticks = np.arange(np.floor(sectime[0]/sectime_res)*sectime_res, np.ceil(sectime[-1]/sectime_res)*sectime_res, sectime_res) from scipy.interpolate import interp1d f = interp1d(sectime, x, fill_value='extrapolate') x_time_ticks = f(time_ticks) f = interp1d(sectime, y, fill_value='extrapolate') y_time_ticks = f(time_ticks) panel.major_ax.plot(x_time_ticks, y_time_ticks, '.', markersize=4, color='k') for ind, time_tick in enumerate(time_ticks): time = dt0 + datetime.timedelta(seconds=time_tick) x_time_tick = x_time_ticks[ind] y_time_tick = y_time_ticks[ind] if x_time_tick < panel._extent[0] or x_time_tick > panel._extent[1]: continue if y_time_tick < panel._extent[2] or y_time_tick > panel._extent[3]: continue panel.major_ax.text( x_time_tick, y_time_tick, time.strftime("%d %H:%M"), fontsize=6) panel.add_coastlines() panel.add_grids() plt.gcf().suptitle('Swarm-C neutral mass density\n 2016-02-03T07:00 - 2016-02-03T07:50') plt.savefig('test_pho_n_aacgm.png', dpi=300) # plt.show() def show_n_e(dt_fr, dt_to): import cdflib filepath = "~/tmp/SW_OPER_EFIC_LP_1B_20160203T000000_20160203T235959_0501_MDR_EFI_LP.cdf" cf = cdflib.CDF(filepath) cf_info = cf.cdf_info() n_e = cf.varget(variable='Ne') T_e = cf.varget(variable='Te') sc_lat = cf.varget(variable='Latitude') sc_lon = cf.varget(variable='Longitude') timestamp = cf.varget(variable='Timestamp') dtstrs = cdflib.cdfepoch.encode(timestamp) dts = np.empty_like(timestamp, dtype=datetime.datetime) for ind, dtstr in enumerate(dtstrs): dts[ind] = datetime.datetime.strptime(dtstr+'000', '%Y-%m-%dT%H:%M:%S.%f') ind_dt = np.where((dts >= dt_fr) & (dts <= dt_to))[0] # times = cdflib.cdfepoch.unixtime(timestamp, to_np=True) sc_lon = sc_lon[ind_dt] sc_lat = sc_lat[ind_dt] sc_dt = dts[ind_dt] rho_n_sc = n_e[ind_dt] plt.figure(figsize=(8,8)) cs = 'GEO' panel = PolarMap( cs='GEO', style='lst-fixed', pole='N', lon_c=None, lst_c=0, mlt_c=None, ut=dt_fr, boundary_lat=0., proj_type='Stereographic') # cs = 'AACGM' #panel = PolarMap(cs=cs, style='mlt-fixed', pole='N', lon_c=None, lst_c=None, mlt_c=0, ut=dt_fr, boundary_lat=30., # proj_type='Stereographic') panel.set_extent(boundary_style='circle') data = panel.projection.transform_points(ccrs.PlateCarree(), sc_lon, sc_lat) x = data[:, 0] y = data[:, 1] from scipy.stats import linregress coef = linregress(x, y) a = coef.slope b = coef.intercept # x1 = np.linspace(np.nanmin(x), np.nanmax(x), num=500) # y1 = np.linspace(np.nanmin(y), np.nanmax(y), num=500) # x2d, y2d = np.meshgrid(x, y) # z2d = griddata(data[:, 0:2], rho_n_sc.flatten(), (x2d, y2d), method='nearest') # z2d_dist = np.abs(a*x2d - y2d + b) / np.sqrt(a**2 + 1) # z2d = np.where(z2d_dist>1000, np.nan, z2d) # # im = panel.major_ax.pcolormesh(x2d, y2d, z2d, vmin=2e-14, vmax=20e-13, cmap='gist_ncar') # panel.major_ax.plot(sc_lon, sc_lat, transform=ccrs.Geodetic(), linewidth=0.5, color='k') # plt.colorbar(im) # xx = np.tile(x, [3, 1]) # # yy = np.concatenate((y[np.newaxis, :]-150000, y[np.newaxis, :], y[np.newaxis, :]+150000), axis=0) # zz = np.concatenate((rho_n_sc.T, rho_n_sc.T, rho_n_sc.T), axis=0) # # zz = griddata(data[:, 0:2], rho_n_sc.flatten(), (xx, yy), method='nearest') # im = panel.major_ax.pcolormesh(xx, yy, zz, vmin=2e-14, vmax=20e-13, cmap='gist_ncar') # # # panel.major_ax.plot(sc_lon, sc_lat, transform=ccrs.Geodetic(), linewidth=0.5, color='k') # plt.colorbar(im) #panel.major_ax.plot(data[:,0], data[:,1], linewidth=3) from matplotlib.collections import LineCollection coords = {'lat': sc_lat, 'lon': sc_lon, 'height': 250.} cs_new = panel.cs_transform(cs_fr='GEO', cs_to=cs, coords=coords) data = panel.projection.transform_points(ccrs.PlateCarree(), cs_new['lon'], cs_new['lat']) x = data[:, 0] y = data[:, 1] z = rho_n_sc.flatten() points = np.array([x, y]).T.reshape(-1, 1, 2) segments = np.concatenate([points[:-1], points[1:]], axis=1) norm = colors.LogNorm(vmin=8e3, vmax=1e6) lc = LineCollection(segments, cmap=cm.cmap_gist_ncar_modified(), norm=norm) lc.set_array(z) lc.set_linewidth(6) line = panel.major_ax.add_collection(lc) cbar = plt.gcf().colorbar(line, ax=panel.major_ax, pad=0.1, fraction=0.03) cbar.set_label(r'$n_e$' + '\n' + r'(cm$^{-3}$)', rotation=270, labelpad=25) #cbaxes = plt.gcf().add_axes([0.8, 0.1, 0.03, 0.8]) #cb = plt.colorbar(panel.major_ax, cax = cbaxes) sectime, dt0 = du.convert_datetime_to_sectime(sc_dt, datetime.datetime(dt_fr.year, dt_fr.month, dt_fr.day)) sectime_res = 10 * 60 time_ticks = np.arange(np.floor(sectime[0]/sectime_res)*sectime_res, np.ceil(sectime[-1]/sectime_res)*sectime_res, sectime_res) from scipy.interpolate import interp1d f = interp1d(sectime, x, fill_value='extrapolate') x_time_ticks = f(time_ticks) f = interp1d(sectime, y, fill_value='extrapolate') y_time_ticks = f(time_ticks) panel.major_ax.plot(x_time_ticks, y_time_ticks, '.', markersize=4, color='k') for ind, time_tick in enumerate(time_ticks): time = dt0 + datetime.timedelta(seconds=time_tick) x_time_tick = x_time_ticks[ind] y_time_tick = y_time_ticks[ind] if x_time_tick < panel._extent[0] or x_time_tick > panel._extent[1]: continue if y_time_tick < panel._extent[2] or y_time_tick > panel._extent[3]: continue panel.major_ax.text( x_time_tick, y_time_tick, time.strftime("%d %H:%M"), fontsize=6) panel.add_coastlines() panel.add_gridlines() plt.gcf().suptitle('Swarm-C electron density\n' + dt_fr.strftime("%Y%m%dT%H%M") + ' - ' + dt_to.strftime("%Y%m%dT%H%M")) plt.savefig('swarm_ne_' + cs + '_' + dt_fr.strftime("%Y%m%d_%H%M") + '-' + dt_to.strftime('%H%M'), dpi=300) plt.show() def show_T_e(dt_fr, dt_to): import cdflib filepath = "~/tmp/SW_OPER_EFIC_LP_1B_20160203T000000_20160203T235959_0501_MDR_EFI_LP.cdf" cf = cdflib.CDF(filepath) cf_info = cf.cdf_info() n_e = cf.varget(variable='Ne') T_e = cf.varget(variable='Te') sc_lat = cf.varget(variable='Latitude') sc_lon = cf.varget(variable='Longitude') timestamp = cf.varget(variable='Timestamp') dtstrs = cdflib.cdfepoch.encode(timestamp) dts = np.empty_like(timestamp, dtype=datetime.datetime) for ind, dtstr in enumerate(dtstrs): dts[ind] = datetime.datetime.strptime(dtstr+'000', '%Y-%m-%dT%H:%M:%S.%f') ind_dt = np.where((dts >= dt_fr) & (dts <= dt_to))[0] # times = cdflib.cdfepoch.unixtime(timestamp, to_np=True) sc_lon = sc_lon[ind_dt] sc_lat = sc_lat[ind_dt] sc_dt = dts[ind_dt] rho_n_sc = T_e[ind_dt] plt.figure(figsize=(8,8)) panel = PolarView(cs='GEO', pole='N', lon_c=None, lst_c=0, ut=dt_fr, boundary_lat=0., proj_style='Stereographic') panel.add_subplot(major=True) panel.set_extent(boundary_style='circle') data = panel.projection.transform_points(ccrs.PlateCarree(), sc_lon, sc_lat) x = data[:, 0] y = data[:, 1] from scipy.stats import linregress coef = linregress(x, y) a = coef.slope b = coef.intercept # x1 = np.linspace(np.nanmin(x), np.nanmax(x), num=500) # y1 = np.linspace(np.nanmin(y), np.nanmax(y), num=500) # x2d, y2d = np.meshgrid(x, y) # z2d = griddata(data[:, 0:2], rho_n_sc.flatten(), (x2d, y2d), method='nearest') # z2d_dist = np.abs(a*x2d - y2d + b) / np.sqrt(a**2 + 1) # z2d = np.where(z2d_dist>1000, np.nan, z2d) # # im = panel.major_ax.pcolormesh(x2d, y2d, z2d, vmin=2e-14, vmax=20e-13, cmap='gist_ncar') # panel.major_ax.plot(sc_lon, sc_lat, transform=ccrs.Geodetic(), linewidth=0.5, color='k') # plt.colorbar(im) # xx = np.tile(x, [3, 1]) # # yy = np.concatenate((y[np.newaxis, :]-150000, y[np.newaxis, :], y[np.newaxis, :]+150000), axis=0) # zz = np.concatenate((rho_n_sc.T, rho_n_sc.T, rho_n_sc.T), axis=0) # # zz = griddata(data[:, 0:2], rho_n_sc.flatten(), (xx, yy), method='nearest') # im = panel.major_ax.pcolormesh(xx, yy, zz, vmin=2e-14, vmax=20e-13, cmap='gist_ncar') # # # panel.major_ax.plot(sc_lon, sc_lat, transform=ccrs.Geodetic(), linewidth=0.5, color='k') # plt.colorbar(im) #panel.major_ax.plot(data[:,0], data[:,1], linewidth=3) from matplotlib.collections import LineCollection data = panel.projection.transform_points(ccrs.PlateCarree(), sc_lon, sc_lat) x = data[:, 0] y = data[:, 1] z = rho_n_sc.flatten() points = np.array([x, y]).T.reshape(-1, 1, 2) segments = np.concatenate([points[:-1], points[1:]], axis=1) norm = plt.Normalize(500, 4000) # norm = colors.LogNorm(vmin=5e2, vmax=1e6) lc = LineCollection(segments, cmap='gist_ncar', norm=norm) lc.set_array(z) lc.set_linewidth(6) line = panel.major_ax.add_collection(lc) cbar = plt.gcf().colorbar(line, ax=panel.major_ax, pad=0.1, fraction=0.03) cbar.set_label(r'$T_e$' + '\n' + r'(K)', rotation=270, labelpad=25) #cbaxes = plt.gcf().add_axes([0.8, 0.1, 0.03, 0.8]) #cb = plt.colorbar(panel.major_ax, cax = cbaxes) sectime, dt0 = du.convert_datetime_to_sectime(sc_dt, datetime.datetime(dt_fr.year, dt_fr.month, dt_fr.day)) sectime_res = 10 * 60 time_ticks = np.arange(np.floor(sectime[0]/sectime_res)*sectime_res, np.ceil(sectime[-1]/sectime_res)*sectime_res, sectime_res) from scipy.interpolate import interp1d f = interp1d(sectime, x, fill_value='extrapolate') x_time_ticks = f(time_ticks) f = interp1d(sectime, y, fill_value='extrapolate') y_time_ticks = f(time_ticks) panel.major_ax.plot(x_time_ticks, y_time_ticks, '.', markersize=4, color='k') for ind, time_tick in enumerate(time_ticks): time = dt0 + datetime.timedelta(seconds=time_tick) x_time_tick = x_time_ticks[ind] y_time_tick = y_time_ticks[ind] if x_time_tick < panel._extent[0] or x_time_tick > panel._extent[1]: continue if y_time_tick < panel._extent[2] or y_time_tick > panel._extent[3]: continue panel.major_ax.text( x_time_tick, y_time_tick, time.strftime("%d %H:%M"), fontsize=6) panel.add_coastlines() panel.add_grids() plt.gcf().suptitle('Swarm-C electron temperature\n 2016-02-03T07:00 - 2016-02-03T07:50') plt.savefig('test_T_e.png', dpi=300) plt.show() if __name__ == "__main__": dt_fr = datetime.datetime(2016, 2, 3, 0, 40) dt_to = datetime.datetime(2016, 2, 3, 1, 40) # show_rho_n(dt_fr, dt_to) show_n_e(dt_fr, dt_to) # show_T_e(dt_fr, dt_to)

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fddda20cbaf80350828fa414f762768a4f2b2d51

16,037

py

Python

tests/test_controllers.py

mark-koren/flow

f3f6d7e9c64f6b641a464a716c7f38ca00388805

[ "MIT" ]

null

tests/test_controllers.py

mark-koren/flow

f3f6d7e9c64f6b641a464a716c7f38ca00388805

[ "MIT" ]

null

tests/test_controllers.py

mark-koren/flow

f3f6d7e9c64f6b641a464a716c7f38ca00388805

[ "MIT" ]

null

import unittest from flow.core.experiment import SumoExperiment from flow.core.params import SumoParams, EnvParams, InitialConfig, NetParams from flow.core.vehicles import Vehicles from flow.controllers.routing_controllers import ContinuousRouter from flow.controllers.car_following_models import * from setup_scripts import ring_road_exp_setup class TestCFMController(unittest.TestCase): """ Tests that the CFM Controller returning mathematically accurate values. """ def setUp(self): # add a few vehicles to the network using the requested model # also make sure that the input params are what is expected contr_params = \ {"k_d": 1, "k_v": 1, "k_c": 1, "d_des": 1, "v_des": 8, "accel_max": 20, "decel_max": -5, "tau": 0, "dt": 0.1, "noise": 0} vehicles = Vehicles() vehicles.add_vehicles( veh_id="test", acceleration_controller=(CFMController, contr_params), routing_controller=(ContinuousRouter, {}), num_vehicles=5 ) # create the environment and scenario classes for a ring road self.env, scenario = ring_road_exp_setup(vehicles=vehicles) def tearDown(self): # terminate the traci instance self.env.terminate() # free data used by the class self.env = None def test_get_action(self): self.env.reset() ids = self.env.vehicles.get_ids() test_headways = [5, 10, 15, 20, 25] test_speeds = [5, 10, 5, 10, 5] for i, veh_id in enumerate(ids): self.env.vehicles.set_headway(veh_id, test_headways[i]) self.env.vehicles.set_speed(veh_id, test_speeds[i]) requested_accel = [self.env.vehicles.get_acc_controller( veh_id).get_action(self.env) for veh_id in ids] expected_accel = [12, 2, 20, 12, 20] np.testing.assert_array_almost_equal(requested_accel, expected_accel) class TestBCMController(unittest.TestCase): """ Tests that the BCM Controller returning mathematically accurate values. """ def setUp(self): # add a few vehicles to the network using the requested model # also make sure that the input params are what is expected contr_params = \ {"k_d": 1, "k_v": 1, "k_c": 1, "d_des": 1, "v_des": 8, "accel_max": 15, "decel_max": -5, "tau": 0, "dt": 0.1, "noise": 0} vehicles = Vehicles() vehicles.add_vehicles( veh_id="test", acceleration_controller=(BCMController, contr_params), routing_controller=(ContinuousRouter, {}), num_vehicles=5 ) # create the environment and scenario classes for a ring road self.env, scenario = ring_road_exp_setup(vehicles=vehicles) def tearDown(self): # terminate the traci instance self.env.terminate() # free data used by the class self.env = None def test_get_action(self): self.env.reset() ids = self.env.vehicles.get_ids() test_headways = [5, 10, 15, 20, 25] test_speeds = [5, 10, 5, 10, 5] for i, veh_id in enumerate(ids): self.env.vehicles.set_headway(veh_id, test_headways[i]) self.env.vehicles.set_speed(veh_id, test_speeds[i]) requested_accel = [self.env.vehicles.get_acc_controller( veh_id).get_action(self.env) for veh_id in ids] expected_accel = [-12, -7, 15, -7, 13] np.testing.assert_array_almost_equal(requested_accel, expected_accel) class TestOVMController(unittest.TestCase): """ Tests that the OVM Controller returning mathematically accurate values. """ def setUp(self): # add a few vehicles to the network using the requested model # also make sure that the input params are what is expected contr_params = \ {"alpha": 1, "beta": 1, "h_st": 2, "h_go": 15, "v_max": 30, "accel_max": 15, "decel_max": -5, "tau": 0, "dt": 0.1, "noise": 0} vehicles = Vehicles() vehicles.add_vehicles( veh_id="test", acceleration_controller=(OVMController, contr_params), routing_controller=(ContinuousRouter, {}), num_vehicles=5 ) # create the environment and scenario classes for a ring road self.env, scenario = ring_road_exp_setup(vehicles=vehicles) def tearDown(self): # terminate the traci instance self.env.terminate() # free data used by the class self.env = None def test_get_action(self): self.env.reset() ids = self.env.vehicles.get_ids() test_headways = [0, 10, 5, 5, 5] test_speeds = [5, 10, 5, 10, 5] for i, veh_id in enumerate(ids): self.env.vehicles.set_headway(veh_id, test_headways[i]) self.env.vehicles.set_speed(veh_id, test_speeds[i]) requested_accel = [self.env.vehicles.get_acc_controller( veh_id).get_action(self.env) for veh_id in ids] expected_accel = [0, 5.319073, 3.772339, -5., -1.227661] np.testing.assert_array_almost_equal(requested_accel, expected_accel) class TestLinearOVM(unittest.TestCase): """ Tests that the Linear OVM Controller returning mathematically accurate values. """ def setUp(self): # add a few vehicles to the network using the requested model # also make sure that the input params are what is expected contr_params = \ {"v_max": 30, "accel_max": 15, "decel_max": -5, "adaptation": 0.65, "h_st": 5, "tau": 0, "dt": 0.1, "noise": 0} vehicles = Vehicles() vehicles.add_vehicles( veh_id="test", acceleration_controller=(LinearOVM, contr_params), routing_controller=(ContinuousRouter, {}), num_vehicles=5 ) # create the environment and scenario classes for a ring road self.env, scenario = ring_road_exp_setup(vehicles=vehicles) def tearDown(self): # terminate the traci instance self.env.terminate() # free data used by the class self.env = None def test_get_action(self): self.env.reset() ids = self.env.vehicles.get_ids() test_headways = [5, 10, 10, 15, 0] test_speeds = [5, 10, 5, 10, 5] for i, veh_id in enumerate(ids): self.env.vehicles.set_headway(veh_id, test_headways[i]) self.env.vehicles.set_speed(veh_id, test_speeds[i]) requested_accel = [self.env.vehicles.get_acc_controller( veh_id).get_action(self.env) for veh_id in ids] expected_accel = [-5., -2.392308, 5.3, 10.6, -5.] np.testing.assert_array_almost_equal(requested_accel, expected_accel) class TestIDMController(unittest.TestCase): """ Tests that the IDM Controller returning mathematically accurate values. """ def setUp(self): # add a few vehicles to the network using the requested model # also make sure that the input params are what is expected contr_params = {"v0": 30, "T": 1, "a": 1, "b": 1.5, "delta": 4, "s0": 2, "s1": 0, "decel_max": -5, "dt": 0.1, "noise": 0} vehicles = Vehicles() vehicles.add_vehicles( veh_id="test", acceleration_controller=(IDMController, contr_params), routing_controller=(ContinuousRouter, {}), num_vehicles=5 ) # create the environment and scenario classes for a ring road self.env, scenario = ring_road_exp_setup(vehicles=vehicles) def tearDown(self): # terminate the traci instance self.env.terminate() # free data used by the class self.env = None def test_get_action(self): self.env.reset() ids = self.env.vehicles.get_ids() test_headways = [10, 20, 30, 40, 50] test_speeds = [5, 10, 5, 10, 5] for i, veh_id in enumerate(ids): self.env.vehicles.set_headway(veh_id, test_headways[i]) self.env.vehicles.set_speed(veh_id, test_speeds[i]) requested_accel = [self.env.vehicles.get_acc_controller( veh_id).get_action(self.env) for veh_id in ids] expected_accel = \ [0.959228, -1.638757, 0.994784, 0.331051, 0.979628] np.testing.assert_array_almost_equal(requested_accel, expected_accel) # set the perceived headway to zero test_headways = [0, 0, 0, 0, 0] for i, veh_id in enumerate(ids): self.env.vehicles.set_headway(veh_id, test_headways[i]) # make sure the controller doesn't return a ZeroDivisionError when the # headway is zero [self.env.vehicles.get_acc_controller(veh_id).get_action(self.env) for veh_id in ids] class TestInstantaneousFailsafe(unittest.TestCase): """ Tests that the instantaneous failsafe of the base acceleration controller does not allow vehicles to crash under situations where they otherwise would. This is tested on two crash-prone controllers: OVM and LinearOVM """ def setUp_failsafe(self, vehicles): additional_env_params = {"target_velocity": 8, "max-deacc": 3, "max-acc": 3} env_params = EnvParams(additional_params=additional_env_params, longitudinal_fail_safe="instantaneous") additional_net_params = {"length": 100, "lanes": 1, "speed_limit": 30, "resolution": 40} net_params = NetParams(additional_params=additional_net_params) initial_config = InitialConfig(bunching=10) # create the environment and scenario classes for a ring road env, scenario = ring_road_exp_setup(vehicles=vehicles, env_params=env_params, net_params=net_params, initial_config=initial_config) # instantiate an experiment class self.exp = SumoExperiment(env, scenario) def tearDown_failsafe(self): # free data used by the class self.exp = None def test_no_crash_OVM(self): vehicles = Vehicles() vehicles.add_vehicles( veh_id="test", acceleration_controller=(OVMController, {}), routing_controller=(ContinuousRouter, {}), num_vehicles=10 ) self.setUp_failsafe(vehicles=vehicles) # run the experiment, see if it fails self.exp.run(1, 200) self.tearDown_failsafe() def test_no_crash_LinearOVM(self): vehicles = Vehicles() vehicles.add_vehicles( veh_id="test", acceleration_controller=(LinearOVM, {}), routing_controller=(ContinuousRouter, {}), num_vehicles=10 ) self.setUp_failsafe(vehicles=vehicles) # run the experiment, see if it fails self.exp.run(1, 200) self.tearDown_failsafe() class TestSafeVelocityFailsafe(TestInstantaneousFailsafe): """ Tests that the safe velocity failsafe of the base acceleration controller does not fail under extreme conditions. """ def setUp_failsafe(self, vehicles): additional_env_params = {"target_velocity": 8, "max-deacc": 3, "max-acc": 3} env_params = EnvParams(additional_params=additional_env_params, longitudinal_fail_safe="safe_velocity") additional_net_params = {"length": 100, "lanes": 1, "speed_limit": 30, "resolution": 40} net_params = NetParams(additional_params=additional_net_params) initial_config = InitialConfig(bunching=10) # create the environment and scenario classes for a ring road env, scenario = ring_road_exp_setup(vehicles=vehicles, env_params=env_params, net_params=net_params, initial_config=initial_config) # instantiate an experiment class self.exp = SumoExperiment(env, scenario) class TestStaticLaneChanger(unittest.TestCase): """ Makes sure that vehicles with a static lane-changing controller do not change lanes. """ def setUp(self): # add an extra lane to the ring road network additional_net_params = {"length": 230, "lanes": 2, "speed_limit": 30, "resolution": 40} net_params = NetParams(additional_params=additional_net_params) # create the environment and scenario classes for a ring road self.env, scenario = ring_road_exp_setup(net_params=net_params) def tearDown(self): # terminate the traci instance self.env.terminate() # free data used by the class self.env = None def runTest(self): ids = self.env.vehicles.get_ids() # run the experiment for a few iterations and collect the lane index # for vehicles lanes = [self.env.vehicles.get_lane(veh_id) for veh_id in ids] for i in range(5): self.env._step(rl_actions=[]) lanes += [self.env.vehicles.get_lane(veh_id) for veh_id in ids] # set the timer as very high and reset (the timer used to cause bugs at # the beginning of a new run for this controller) self.env.timer = 10000 self.env.reset() # run the experiment for a few more iterations and collect the lane # index for vehicles lanes = [self.env.vehicles.get_lane(veh_id) for veh_id in ids] for i in range(5): self.env._step(rl_actions=[]) lanes += [self.env.vehicles.get_lane(veh_id) for veh_id in ids] # assert that all lane indices are zero self.assertEqual(sum(np.array(lanes)), 0) class TestContinuousRouter(unittest.TestCase): """ Tests that the continuous router operates properly if there is no need to reroute, and if there is a need to do so. """ def setUp(self): # create the environment and scenario classes for a ring road self.env, scenario = ring_road_exp_setup() def tearDown(self): # terminate the traci instance self.env.terminate() # free data used by the class self.env = None def runTest(self): veh_id = self.env.vehicles.get_ids()[0] # set the perceived route of the vehicle self.env.vehicles.set_route(veh_id, ["bottom", "right", "top", "left"]) # set the perceived edge of the vehicle at the beginning of its route self.env.vehicles.set_edge(veh_id, "bottom") # assert that the controller is returning a None value requested_route = self.env.vehicles.get_routing_controller( veh_id).choose_route(self.env) self.assertIsNone(requested_route) # set the perceived edge of the vehicle at the middle of its route self.env.vehicles.set_edge(veh_id, "right") # assert that the controller is returning a None value requested_route = self.env.vehicles.get_routing_controller( veh_id).choose_route(self.env) self.assertIsNone(requested_route) # set the perceived edge of the vehicle at the end of its route self.env.vehicles.set_edge(veh_id, "left") # assert that the controller is returning a list of edges starting at # this link and then containing the route of the link ahead of it requested_route = self.env.vehicles.get_routing_controller( veh_id).choose_route(self.env) expected_route = ["left", "bottom", "right", "top"] self.assertSequenceEqual(requested_route, expected_route) if __name__ == '__main__': unittest.main()

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e310b1c11b7b561bcd3ace50103b82d456e470ea

247

py

Python

timemachines/skaters/nproph/allnprophetskaters.py

iklasky/timemachines

1820fa9453d31d4daaeff75274a935c7455febe3

[ "MIT" ]

253

2021-01-08T17:33:30.000Z

2022-03-21T17:32:36.000Z

timemachines/skaters/nproph/allnprophetskaters.py

iklasky/timemachines

1820fa9453d31d4daaeff75274a935c7455febe3

[ "MIT" ]

65

2021-01-20T16:43:35.000Z

2022-03-30T19:07:22.000Z

timemachines/skaters/nproph/allnprophetskaters.py

iklasky/timemachines

1820fa9453d31d4daaeff75274a935c7455febe3

[ "MIT" ]

28

2021-02-04T14:58:30.000Z

2022-01-17T04:35:17.000Z

from timemachines.skaters.nproph.nprophetskaters import NPROPHET_UNIVARIATE_SKATERS from timemachines.skaters.nproph.nprophskaterscomposed import NPROPHET_SKATERS_COMPOSED NPROPHET_SKATERS = NPROPHET_UNIVARIATE_SKATERS + NPROPHET_SKATERS_COMPOSED

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7

477403a44ff39f469ed37fdb99910aa01763e27a

2,649

py

Python

channels/migrations/0018_add_post_and_comment_fields.py

mitodl/open-discussions

ab6e9fac70b8a1222a84e78ba778a7a065c20541

[ "BSD-3-Clause" ]

12

2017-09-27T21:23:27.000Z

2020-12-25T04:31:30.000Z

channels/migrations/0018_add_post_and_comment_fields.py

mitodl/open-discussions

ab6e9fac70b8a1222a84e78ba778a7a065c20541

[ "BSD-3-Clause" ]

3,293

2017-06-30T18:16:01.000Z

2022-03-31T18:01:34.000Z

channels/migrations/0018_add_post_and_comment_fields.py

mitodl/open-discussions

ab6e9fac70b8a1222a84e78ba778a7a065c20541

[ "BSD-3-Clause" ]

1

2020-04-13T12:19:57.000Z

# Generated by Django 2.1.5 on 2019-01-18 19:04 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("channels", "0017_remove_unique"), ] operations = [ migrations.AddField( model_name="comment", name="author", field=models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL, ), ), migrations.AddField( model_name="comment", name="deleted", field=models.BooleanField(null=True) ), migrations.AddField( model_name="comment", name="edited", field=models.BooleanField(null=True) ), migrations.AddField( model_name="comment", name="removed", field=models.BooleanField(null=True) ), migrations.AddField( model_name="comment", name="score", field=models.BigIntegerField(null=True) ), migrations.AddField( model_name="comment", name="text", field=models.TextField(null=True) ), migrations.AddField( model_name="post", name="author", field=models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL, ), ), migrations.AddField( model_name="post", name="deleted", field=models.BooleanField(null=True) ), migrations.AddField( model_name="post", name="edited", field=models.BooleanField(null=True) ), migrations.AddField( model_name="post", name="num_comments", field=models.BigIntegerField(null=True), ), migrations.AddField( model_name="post", name="removed", field=models.BooleanField(null=True) ), migrations.AddField( model_name="post", name="score", field=models.BigIntegerField(null=True) ), migrations.AddField( model_name="post", name="text", field=models.TextField(null=True) ), migrations.AddField( model_name="post", name="title", field=models.CharField(max_length=300, null=True), ), migrations.AddField( model_name="post", name="url", field=models.URLField(max_length=2048, null=True), ), ]

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47ff264ac5ccd9a71d40e31f962a80ca71a13c27

2,229

py

Python

web/transiq/restapi/migrations/0023_auto_20181029_1058.py

manibhushan05/transiq

763fafb271ce07d13ac8ce575f2fee653cf39343

[ "Apache-2.0" ]

null

web/transiq/restapi/migrations/0023_auto_20181029_1058.py

manibhushan05/transiq

763fafb271ce07d13ac8ce575f2fee653cf39343

[ "Apache-2.0" ]

14

2020-06-05T23:06:45.000Z

2022-03-12T00:00:18.000Z

web/transiq/restapi/migrations/0023_auto_20181029_1058.py

manibhushan05/transiq

763fafb271ce07d13ac8ce575f2fee653cf39343

[ "Apache-2.0" ]

null

# Generated by Django 2.0.5 on 2018-10-29 10:58 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('restapi', '0022_auto_20181003_1919'), ] operations = [ migrations.AlterField( model_name='bookingstatuses', name='status', field=models.CharField(choices=[('confirmed', 'Confirmed'), ('loaded', 'Loaded'), ('lr_generated', 'Lr Generated'), ('advance_paid', 'Advance Paid'), ('unloaded', 'Unloaded'), ('pod_uploaded', 'PoD Uploaded'), ('pod_verified', 'PoD Verified'), ('invoice_raised', 'Invoice Raised'), ('invoice_confirmed', 'Invoice Confirmed'), ('balance_paid', 'Balance Paid'), ('party_invoice_sent', 'Party Invoice Sent'), ('inward_followup_completed', 'Inward Followup Completed'), ('complete', 'Complete')], default='confirmed', max_length=35, null=True), ), migrations.AlterField( model_name='bookingstatusesmapping', name='booking_stage', field=models.CharField(choices=[('in_progress', 'In Progress'), ('done', 'Done'), ('reverted', 'Reverted'), ('escalated', 'Escalated')], default='in_progress', max_length=15, null=True), ), migrations.AlterField( model_name='historicalbookingstatuses', name='status', field=models.CharField(choices=[('confirmed', 'Confirmed'), ('loaded', 'Loaded'), ('lr_generated', 'Lr Generated'), ('advance_paid', 'Advance Paid'), ('unloaded', 'Unloaded'), ('pod_uploaded', 'PoD Uploaded'), ('pod_verified', 'PoD Verified'), ('invoice_raised', 'Invoice Raised'), ('invoice_confirmed', 'Invoice Confirmed'), ('balance_paid', 'Balance Paid'), ('party_invoice_sent', 'Party Invoice Sent'), ('inward_followup_completed', 'Inward Followup Completed'), ('complete', 'Complete')], default='confirmed', max_length=35, null=True), ), migrations.AlterField( model_name='historicalbookingstatusesmapping', name='booking_stage', field=models.CharField(choices=[('in_progress', 'In Progress'), ('done', 'Done'), ('reverted', 'Reverted'), ('escalated', 'Escalated')], default='in_progress', max_length=15, null=True), ), ]

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9a1a5c24cda44b9419993cc8a494ca2ca3d040ee

2,193

py

Python

pesis/pesis_old/engine/create_players.py

paulamh/pesis

c5ab10a96fc78c761c8c642f316c68acfb8a6892

[ "BSD-2-Clause" ]

null

pesis/pesis_old/engine/create_players.py

paulamh/pesis

c5ab10a96fc78c761c8c642f316c68acfb8a6892

[ "BSD-2-Clause" ]

null

pesis/pesis_old/engine/create_players.py

paulamh/pesis

c5ab10a96fc78c761c8c642f316c68acfb8a6892

[ "BSD-2-Clause" ]

null

from ..objects import Player from ..utils import dgv, prc_choice, rand_pick def create_players(level_multiplier=1.): ps = []; lm = level_multiplier; nu = 2. gens = ('perusvarma','tulokas','konkari') ins = ('lyöjä','etenijä','yleispelaaja') outs = ('koppari','sieppari','polttaja','lukkari') ps.append(Player('Player A', dgv(14,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player B', dgv(14,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player C', dgv(13,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player D', dgv(12,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player E', dgv(12,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player F', dgv(10,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player G', dgv(10,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player H', dgv(10,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player I', dgv(10,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player J', dgv(8,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player K', dgv(8,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player L', dgv(6,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player M', dgv(6,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player N', dgv(4,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) ps.append(Player('Player O', dgv(4,1)*lm, nu, rand_pick(gens), rand_pick(ins), rand_pick(outs)) return ps

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null

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8

7beb2c91b457cb0c558c1a7c46443d99172775ce

140

py

Python

zvt/domain/misc/__init__.py

Evergreen2020/zvt

446a2512d716a38a12164b6d4468a6c9de01b986

[ "MIT" ]

6

2020-09-03T10:02:00.000Z

2021-02-04T02:51:47.000Z

zvt/domain/misc/__init__.py

Evergreen2020/zvt

446a2512d716a38a12164b6d4468a6c9de01b986

[ "MIT" ]

2

2019-12-20T13:12:30.000Z

2020-01-03T06:24:30.000Z

zvt/domain/misc/__init__.py

Evergreen2020/zvt

446a2512d716a38a12164b6d4468a6c9de01b986

[ "MIT" ]

2

2020-07-08T04:15:40.000Z

2021-06-08T08:51:31.000Z

# -*- coding: utf-8 -*- from zvt.domain.misc.holder import * from zvt.domain.misc.money_flow import * from zvt.domain.misc.overall import *

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7

d0385067e14cd963a9ed6c7d8d1474cf6d868a11

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py

Python

tests/test_cut_point.py

zStupan/NiaARM

3ade6c5f89a22da7f1e7309cb4fec227bb913e6b

[ "MIT" ]

null

tests/test_cut_point.py

zStupan/NiaARM

3ade6c5f89a22da7f1e7309cb4fec227bb913e6b

[ "MIT" ]

14

2022-03-02T07:38:34.000Z

2022-03-15T11:18:50.000Z

tests/test_cut_point.py

zStupan/NiaARM

3ade6c5f89a22da7f1e7309cb4fec227bb913e6b

[ "MIT" ]

1

2022-03-01T14:41:07.000Z

from unittest import TestCase from niaarm.niaarm import NiaARM, _cut_point from niaarm.feature import Feature from niaarm.dataset import Dataset import os # The basic test for checking the identification of the appropriate cut point of association rule. class TestCutPoint(TestCase): # let's borrow a test case from Wikipedia: # https://en.wikipedia.org/wiki/Lift_(data_mining) def setUp(self): data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'wiki_test_case.csv')) self.features = data.features self.oper = NiaARM(data.dimension, data.features, data.transactions, ('support',)) def test_cut_pointA(self): sol = [0.98328107, 0.93655004, 0.6860223, 0.78527931, 0.96291945, 0.18117294, 0.50567635, 0.33333333] cut_value = sol[len(sol) - 1] new_sol = sol[:-1] cut = _cut_point(cut_value, len(self.features)) rule = self.oper.build_rule(new_sol) # get antecedent and consequent of rule antecedent = rule[:cut] consequent = rule[cut:] self.assertEqual(cut_value, 0.33333333) self.assertEqual(new_sol, [0.98328107, 0.93655004, 0.6860223, 0.78527931, 0.96291945, 0.18117294, 0.50567635]) self.assertEqual(cut, 1) self.assertEqual(antecedent, [Feature('Feat1', 'cat', categories=['B'])]) self.assertEqual(consequent, [None]) class TestCutPointB(TestCase): def setUp(self): data = Dataset(os.path.join(os.path.dirname(__file__), 'test_data', 'Abalone.csv')) self.features = data.features self.oper = NiaARM(data.dimension, data.features, data.transactions, ('support',)) def test_cut_pointB(self): sol = [ 0.35841534, 0.15056955, 0.57296633, 0.25275099, 0.1311689, 0.48081366, 0.86191609, 0.0, 0.4988256, 1.0, 0.23, 0.15337635, 0.91438008, 0.24168367, 0.1185402, 0.81325209, 0.67415024, 0.59137232, 0.1794402, 0.48980977, 0.13287764, 0.63728572, 0.3163273, 0.37061311, 0.52579599, 0.7206465, 0.72623934, 0.0, 0.57660376, 0.0694041, 0.35173438, 0.09158622, 0.74415574, 0.56159659, 0.49068101, 0.33333333] new_sol_a = [ 0.35841534, 0.15056955, 0.57296633, 0.25275099, 0.1311689, 0.48081366, 0.86191609, 0.0, 0.4988256, 1.0, 0.23, 0.15337635, 0.91438008, 0.24168367, 0.1185402, 0.81325209, 0.67415024, 0.59137232, 0.1794402, 0.48980977, 0.13287764, 0.63728572, 0.3163273, 0.37061311, 0.52579599, 0.7206465, 0.72623934, 0.0, 0.57660376, 0.0694041, 0.35173438, 0.09158622, 0.74415574, 0.56159659, 0.49068101] cut_value = sol[len(sol) - 1] new_sol = sol[:-1] cut = _cut_point(cut_value, len(self.features)) rule = self.oper.build_rule(new_sol) # get antecedent and consequent of rule antecedent = rule[:cut] consequent = rule[cut:] self.assertEqual(cut_value, 0.33333333) self.assertEqual(new_sol, new_sol_a) self.assertEqual(cut, 2) self.assertEqual(antecedent, [Feature('Length', 'float', min_val=0.2620357326, max_val=0.4989950842), Feature('Height', 'float', min_val=0.5636729279999999, max_val=1.13)]) self.assertEqual(consequent, [None, None, None, None, Feature('Diameter', 'float', 0.34108412769999996, 0.56784007355), Feature('Sex', 'cat', categories=['I']), Feature('Viscera weight', 'float', 0.13678483190000001, 0.44964727704)]) def test_cut_pointC(self): sol = [ 0.35841534, 0.15056955, 0.57296633, 0.25275099, 0.1311689, 0.48081366, 0.86191609, 0.0, 0.4988256, 1.0, 0.23, 0.15337635, 0.91438008, 0.24168367, 0.1185402, 0.81325209, 0.67415024, 0.59137232, 0.1794402, 0.48980977, 0.13287764, 0.63728572, 0.3163273, 0.37061311, 0.52579599, 0.7206465, 0.72623934, 0.0, 0.57660376, 0.0694041, 0.35173438, 0.09158622, 0.74415574, 0.56159659, 0.49068101, 0.53333333] new_sol_a = [ 0.35841534, 0.15056955, 0.57296633, 0.25275099, 0.1311689, 0.48081366, 0.86191609, 0.0, 0.4988256, 1.0, 0.23, 0.15337635, 0.91438008, 0.24168367, 0.1185402, 0.81325209, 0.67415024, 0.59137232, 0.1794402, 0.48980977, 0.13287764, 0.63728572, 0.3163273, 0.37061311, 0.52579599, 0.7206465, 0.72623934, 0.0, 0.57660376, 0.0694041, 0.35173438, 0.09158622, 0.74415574, 0.56159659, 0.49068101] cut_value = sol[len(sol) - 1] new_sol = sol[:-1] cut = _cut_point(cut_value, len(self.features)) rule = self.oper.build_rule(new_sol) # get antecedent and consequent of rule antecedent = rule[:cut] consequent = rule[cut:] self.assertEqual(cut_value, 0.53333333) self.assertEqual(new_sol, new_sol_a) self.assertEqual(cut, 4) self.assertEqual(antecedent, [Feature('Length', 'float', 0.2620357326, 0.4989950842), Feature('Height', 'float', 0.5636729279999999, 1.13), None, None]) self.assertEqual(consequent, [None, None, Feature('Diameter', 'float', 0.34108412769999996, 0.56784007355), Feature('Sex', 'cat', categories=['I']), Feature('Viscera weight', 'float', 0.13678483190000001, 0.44964727704)])

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118

0.482925

727

7,057

4.603851

0.181568

0.011951

0.007171

0.021512

0.817747

0.783089

0.757395

0

0.364336

0.410373

7,057

242

119

29.161157

0.440038

0.042511

0

0.859903

0

0.028444

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0.072464

1

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0

1

0

1

0

1

0

null

0

9

d0cdc5142df4d73d6b955678e3582948448ab33b

236

py

Python

resources/util/toolbox/__init__.py

marrcio/relate-kanji

1f21892e546194c65f87b42ee45bee706b21ec92

[ "MIT" ]

null

resources/util/toolbox/__init__.py

marrcio/relate-kanji

1f21892e546194c65f87b42ee45bee706b21ec92

[ "MIT" ]

null

resources/util/toolbox/__init__.py

marrcio/relate-kanji

1f21892e546194c65f87b42ee45bee706b21ec92

[ "MIT" ]

null

from toolbox.filetools import * from toolbox.graphictools import * from toolbox.misctools import * from toolbox.objecttools import * from toolbox.webtools import * from toolbox.kanjitools import * from toolbox.dataqualitytools import *

29.5

38

0.822034

28

236

6.928571

0.357143

0.396907

0.525773

0

0.118644

236

7

39

33.714286

0.932692

0

1

0

true

0

1

0

1

0

1

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null

1

0

1

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null

0

1

0

1

0

1

0

7

ef6e3b2a58ff7ab71c78722515f32e47818c61c4

8,352

py

Python

tests/unit/story/story_service_data.py

hmajid2301/banter-bus-management-api

d51a40c2d5254d4197cbe5bb84aa576df2c24893

[ "Apache-2.0" ]

null

tests/unit/story/story_service_data.py

hmajid2301/banter-bus-management-api

d51a40c2d5254d4197cbe5bb84aa576df2c24893

[ "Apache-2.0" ]

null

tests/unit/story/story_service_data.py

hmajid2301/banter-bus-management-api

d51a40c2d5254d4197cbe5bb84aa576df2c24893

[ "Apache-2.0" ]

null

from typing import List from app.game.game_exceptions import GameNotFound add_story_data = [ ( { "game_name": "quibly", "question": "how many fish are there?", "round": "pair", "answers": [ { "nickname": "funnyMan420", "answer": "one", "votes": 12341, }, { "nickname": "lima_Bean", "answer": "many", "votes": 0, }, ], } ), ( { "game_name": "drawlosseum", "question": "fish", "nickname": "i_cannotDraw", "round": "drawing", "answers": [ { "start": { "x": 100, "y": -100, }, "end": { "x": 90, "y": -100, }, "color": "#000000", }, ], } ), ( { "game_name": "fibbing_it", "question": "What do you think about horses?", "round": "opinion", "answers": [ { "answer": "tasty", "nickname": "!sus", }, { "answer": "lame", "nickname": "!normal_guy", }, { "answer": "lame", "nickname": "normal_guy1", }, ], } ), ] add_story_fail_data = [ ( { "question": "how many fish are there?", "round": "pair", "answers": [ { "nickname": "funnyMan420", "answer": "one", "votes": 12341, }, { "nickname": "lima_Bean", "answer": "many", "votes": 0, }, ], }, ValueError, ), ( { "game_name": "invalid", "question": "how many fish are there?", "round": "pair", "answers": [ { "nickname": "funnyMan420", "answer": "one", "votes": 12341, }, { "nickname": "lima_Bean", "answer": "many", "votes": 0, }, ], }, GameNotFound, ), ( { "question": "how many fish are there?", "game_name": "quibly", "round": "invalid", "answers": [ { "nickname": "funnyMan420", "answer": "one", "votes": 12341, }, { "nickname": "lima_Bean", "answer": "many", "votes": 0, }, ], }, ValueError, ), ( { "game_name": "quibly", "question": "how many fish are there?", "answers": [ { "nickname": "funnyMan420", "answer": "one", "votes": 12341, }, { "nickname": "lima_Bean", "answer": "many", "votes": 0, }, ], }, ValueError, ), ( { "round": "pair", "answers": [ { "nickname": "funnyMan420", "answer": "one", "votes": 12341, }, { "nickname": "lima_Bean", "answer": "many", "votes": 0, }, ], }, ValueError, ), ( { "round": "pair", "question": "how many fish are there?", }, ValueError, ), ( { "game_name": "quibly", "question": "how many fish are there?", "round": "pair", "nickname": "hello", "answers": [ { "nickname": "funnyMan420", "answer": "one", "votes": 12341, }, { "nickname": "lima_Bean", "answer": "many", "votes": 0, }, ], }, ValueError, ), ( { "game_name": "drawlosseum", "question": "fish", "answers": [ { "start": { "x": 100, "y": -100, }, "end": { "x": 90, "y": -100, }, "color": "#000000", }, ], }, ValueError, ), ( { "nickname": "i_cannotDraw", "round": "opinion", "answers": [ { "answer": "tasty", "nickname": "!sus", }, { "answer": "lame", "nickname": "!normal_guy", }, { "answer": "lame", "nickname": "normal_guy1", }, ], }, ValueError, ), ( { "game_name": "fibbing_it", "nickname": "i_cannotDraw", "round": "invalid", "answers": [ { "answer": "tasty", "nickname": "!sus", }, { "answer": "lame", "nickname": "!normal_guy", }, { "answer": "lame", "nickname": "normal_guy1", }, ], }, ValueError, ), ( { "game_name": "fibbing_it", "question": "What do you think about horses?", "round": "opinion", "nickname": "!sus", "answers": [ { "answer": "tasty", "nickname": "!sus", }, { "answer": "lame", "nickname": "!normal_guy", }, { "answer": "lame", "nickname": "normal_guy1", }, ], }, ValueError, ), ( { "game_name": "fibbing_it", "question": "What do you think about horses?", "answers": [ { "answer": "tasty", "nickname": "!sus", }, { "answer": "lame", "nickname": "!normal_guy", }, { "answer": "lame", "nickname": "normal_guy1", }, ], }, ValueError, ), ] all_games_enabled: List[dict] = [ { "name": "quibly", "rules_url": "https://gitlab.com/banter-bus/banter-bus-server/-/wikis/docs/rules/quibly", "enabled": True, "description": "A game about quibbing.", "display_name": "Quibly", }, { "name": "fibbing_it", "rules_url": "https://gitlab.com/banter-bus/banter-bus-server/-/wikis/docs/rules/fibbing_it", "enabled": True, "description": "A game about lying.", "display_name": "Fibbing IT!", }, { "name": "drawlosseum", "rules_url": "https://google.com/drawlosseum", "enabled": True, "description": "A game about drawing.", "display_name": "Drawlosseum", }, ]

25.619632

101

0.287955

448

8,352

5.254464

0.185268

0.037383

0.076466

0.101954

0.813509

0.790569

0.726848

0

0.028603

0.573036

8,352

325

102

25.698462

0.63152

0

0.560748

0

0.006231

0.26341

0

1

0

false

0

0.006231

0

0.006231

0

null

0

1

0

1

0

null

0

7

ef93c1668ff4f9b514a4b9b32e1482a91a8df8f7

3,490

py

Python

Aulas de JS/exercicios_fora_de_aula/sorteador.py

BEp0/Estudos_Web

06cdabd482034533c080dc0c7978ba190844edf7

[ "MIT" ]

null

Aulas de JS/exercicios_fora_de_aula/sorteador.py

BEp0/Estudos_Web

06cdabd482034533c080dc0c7978ba190844edf7

[ "MIT" ]

null

Aulas de JS/exercicios_fora_de_aula/sorteador.py

BEp0/Estudos_Web

06cdabd482034533c080dc0c7978ba190844edf7

[ "MIT" ]

null

from random import shuffle print('Sorteador (somente até 8 grupos/pessoas)...') numero_de_alunos = int(input('Qual a quantidade de grupos para se sortear?')) #vairáveis para cada estudante/grupo #se for 2 if numero_de_alunos == 2: al1 = str(input('Primeiro grupo/estudante: '))# pede o 1° aluno al2 = str(input('Segundo grupo/estudante: '))# pede o 2° aluno lista = [al1, al2] # lista os dois shuffle(lista) # embaralha a lista print('A ordem dos grupos/estudantes é: {}'.format(lista)) # mostra a lista embaralhada #se for 3 if numero_de_alunos == 3: al1 = str(input('Primeiro grupo/estudante: '))# pede o 1° aluno al2 = str(input('Segundo grupo/estudante: '))# pede o 2° aluno al3 = str(input('Terceiro grupo/estudante: ')) lista = [al1, al2, al3] # lista os dois shuffle(lista) # embaralha a lista print('A ordem dos grupos/estudantes é: {}'.format(lista)) # mostra a lista embaralhada #se for 4 if numero_de_alunos == 4: al1 = str(input('Primeiro grupo/estudante: '))# pede o 1° aluno al2 = str(input('Segundo grupo/estudante: '))# pede o 2° aluno al3 = str(input('Terceiro grupo/estudante: ')) al4 = str(input('Quarto grupo/estudante: ')) lista = [al1, al2, al3, al4] # lista os dois shuffle(lista) # embaralha a lista print('A ordem dos grupos/estudantes é: {}'.format(lista)) # mostra a lista embaralhada #se for 5 if numero_de_alunos == 5: al1 = str(input('Primeiro grupo/estudante: '))# pede o 1° aluno al2 = str(input('Segundo grupo/estudante: '))# pede o 2° aluno al3 = str(input('Terceiro grupo/estudante: ')) al4 = str(input('Quarto grupo/estudante: ')) al5 = str(input('Quinto grupo/estudante: ')) lista = [al1, al2, al3, al4, al5] shuffle(lista) print('A ordem dos grupos/estudantes é: {}'.format(lista)) #se for 6 if numero_de_alunos == 6: al1 = str(input('Primeiro grupo/estudante: '))# pede o 1° aluno al2 = str(input('Segundo grupo/estudante: '))# pede o 2° aluno al3 = str(input('Terceiro grupo/estudante: ')) al4 = str(input('Quarto grupo/estudante: ')) al5 = str(input('Quinto grupo/estudante: ')) al6 = str(input('Sexto grupo/estudante: ')) lista = [al1, al2, al3, al4, al5, al6] shuffle(lista) print('A ordem dos grupos/estudantes é: {}'.format(lista)) #se for 7 if numero_de_alunos == 7: al1 = str(input('Primeiro grupo/estudante: '))# pede o 1° aluno al2 = str(input('Segundo grupo/estudante: '))# pede o 2° aluno al3 = str(input('Terceiro grupo/estudante: ')) al4 = str(input('Quarto grupo/estudante: ')) al5 = str(input('Quinto grupo/estudante: ')) al6 = str(input('Sexto grupo/estudante: ')) al7 = str(input('Sétimo grupo/estudante: ')) lista = [al1, al2, al3, al4, al5, al6, al7] shuffle(lista) print('A ordem dos grupos/estudantes é: {}'.format(lista)) #se for 8 (último) if numero_de_alunos == 8: al1 = str(input('Primeiro grupo/estudante: '))# pede o 1° aluno al2 = str(input('Segundo grupo/estudante: '))# pede o 2° aluno al3 = str(input('Terceiro grupo/estudante: ')) al4 = str(input('Quarto grupo/estudante: ')) al5 = str(input('Quinto grupo/estudante: ')) al6 = str(input('Sexto grupo/estudante: ')) al7 = str(input('Sétimo grupo/estudante: ')) al8 = str(input('Oitavo grupo/estudante: ')) lista = [al1, al2, al3, al4, al5, al6, al7, al8] shuffle(lista) print('A ordem dos grupos/estudantes é: {}'.format(lista)) print('_FIM_')

46.533333

91

0.652436

517

3,490

4.396518

0.133462

0.123185

0.110867

0.117026

0.856577

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0

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3,490

75

92

46.533333

0.765143

0.144126

0

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0

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0

null

0

1

0

1

0

null

0

7

efb659417142ed3ebe31414ca5982bd58e77e72a

62,899

py

Python

multicurrency/euro.py

fscm/multicurrency

5eabdcbfbf427dcafe08d4d05cfce8c9348aeb91

[ "MIT" ]

2

2021-03-26T18:19:57.000Z

2021-07-27T01:15:50.000Z

multicurrency/euro.py

fscm/multicurrency

5eabdcbfbf427dcafe08d4d05cfce8c9348aeb91

[ "MIT" ]

null

multicurrency/euro.py

fscm/multicurrency

5eabdcbfbf427dcafe08d4d05cfce8c9348aeb91

[ "MIT" ]

null

# -*- coding: UTF-8 -*- # # copyright: 2020-2022, Frederico Martins # author: Frederico Martins <http://github.com/fscm> # license: SPDX-License-Identifier: MIT """Euro currency representation(s).""" from decimal import Decimal from typing import Optional, Union from .currency import Currency class Euro(Currency): """Euro currency representation. Simple usage example: >>> from multicurrency import Euro >>> euro = Euro( ... amount=123456.789) >>> print(euro) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'Euro': """Class creator. Returns: Euro: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroSBA(Currency): """EuroSBA currency representation. Simple usage example: >>> from multicurrency import EuroSBA >>> eurosba = EuroSBA( ... amount=123456.789) >>> print(eurosba) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroSBA': """Class creator. Returns: EuroSBA: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroAD(Currency): """EuroAD currency representation. Simple usage example: >>> from multicurrency import EuroAD >>> euroad = EuroAD( ... amount=123456.789) >>> print(euroad) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroAD': """Class creator. Returns: EuroAD: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='AD€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroAT(Currency): """EuroAT currency representation. Simple usage example: >>> from multicurrency import EuroAT >>> euroat = EuroAT( ... amount=123456.789) >>> print(euroat) € 123.456,79 For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to True. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = True, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroAT': """Class creator. Returns: EuroAT: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='AT€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroBE(Currency): """EuroBE currency representation. Simple usage example: >>> from multicurrency import EuroBE >>> eurobe = EuroBE( ... amount=123456.789) >>> print(eurobe) € 123.456,79 For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to True. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = True, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroBE': """Class creator. Returns: EuroBE: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='BE€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroCY(Currency): """EuroCY currency representation. Simple usage example: >>> from multicurrency import EuroCY >>> eurocy = EuroCY( ... amount=123456.789) >>> print(eurocy) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroCY': """Class creator. Returns: EuroCY: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='CY€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroEE(Currency): """EuroEE currency representation. Simple usage example: >>> from multicurrency import EuroEE >>> euroee = EuroEE( ... amount=123456.789) >>> print(euroee) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroEE': """Class creator. Returns: EuroEE: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='EE€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroFI(Currency): """EuroFI currency representation. Simple usage example: >>> from multicurrency import EuroFI >>> eurofi = EuroFI( ... amount=123456.789) >>> print(eurofi) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroFI': """Class creator. Returns: EuroFI: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='FI€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroFR(Currency): """EuroFR currency representation. Simple usage example: >>> from multicurrency import EuroFR >>> eurofr = EuroFR( ... amount=123456.789) >>> print(eurofr) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroFR': """Class creator. Returns: EuroFR: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='FR€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroDE(Currency): """EuroDE currency representation. Simple usage example: >>> from multicurrency import EuroDE >>> eurode = EuroDE( ... amount=123456.789) >>> print(eurode) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroDE': """Class creator. Returns: EuroDE: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='DE€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroGR(Currency): """EuroGR currency representation. Simple usage example: >>> from multicurrency import EuroGR >>> eurogr = EuroGR( ... amount=123456.789) >>> print(eurogr) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroGR': """Class creator. Returns: EuroGR: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='GR€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroIE(Currency): """EuroIE currency representation. Simple usage example: >>> from multicurrency import EuroIE >>> euroie = EuroIE( ... amount=123456.789) >>> print(euroie) €123,456.79 For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to '.'. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ','. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ''. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to True. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = '.', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = ',', international: Optional[bool] = False, symbol_ahead: Optional[bool] = True, symbol_separator: Optional[str] = '', **other) -> 'EuroIE': """Class creator. Returns: EuroIE: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='IR€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroIT(Currency): """EuroIT currency representation. Simple usage example: >>> from multicurrency import EuroIT >>> euroit = EuroIT( ... amount=123456.789) >>> print(euroit) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroIT': """Class creator. Returns: EuroIT: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='IT€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroXK(Currency): """EuroXK currency representation. Simple usage example: >>> from multicurrency import EuroXK >>> euroxk = EuroXK( ... amount=123456.789) >>> print(euroxk) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroXK': """Class creator. Returns: EuroXK: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='XK€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroLV(Currency): """EuroLV currency representation. Simple usage example: >>> from multicurrency import EuroLV >>> eurolv = EuroLV( ... amount=123456.789) >>> print(eurolv) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroLV': """Class creator. Returns: EuroLV: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='LV€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroLT(Currency): """EuroLT currency representation. Simple usage example: >>> from multicurrency import EuroLT >>> eurolt = EuroLT( ... amount=123456.789) >>> print(eurolt) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroLT': """Class creator. Returns: EuroLT: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='LT€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroLU(Currency): """EuroLU currency representation. Simple usage example: >>> from multicurrency import EuroLU >>> eurolu = EuroLU( ... amount=123456.789) >>> print(eurolu) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroLU': """Class creator. Returns: EuroLU: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='LU€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroMT(Currency): """EuroMT currency representation. Simple usage example: >>> from multicurrency import EuroMT >>> euromt = EuroMT( ... amount=123456.789) >>> print(euromt) €123,456.79 For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to '.'. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ','. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ''. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to True. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = '.', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = ',', international: Optional[bool] = False, symbol_ahead: Optional[bool] = True, symbol_separator: Optional[str] = '', **other) -> 'EuroMT': """Class creator. Returns: EuroMT: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='MT€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroMC(Currency): """EuroMC currency representation. Simple usage example: >>> from multicurrency import EuroMC >>> euromc = EuroMC( ... amount=123456.789) >>> print(euromc) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroMC': """Class creator. Returns: EuroMC: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='MC€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroME(Currency): """EuroME currency representation. Simple usage example: >>> from multicurrency import EuroME >>> eurome = EuroME( ... amount=123456.789) >>> print(eurome) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroME': """Class creator. Returns: EuroME: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='ME€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroNL(Currency): """EuroNL currency representation. Simple usage example: >>> from multicurrency import EuroNL >>> euronl = EuroNL( ... amount=123456.789) >>> print(euronl) € 123.456,79 For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to True. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = True, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroNL': """Class creator. Returns: EuroNL: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='NL€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroPT(Currency): """EuroPT currency representation. Simple usage example: >>> from multicurrency import EuroPT >>> europt = EuroPT( ... amount=123456.789) >>> print(europt) € 123.456,79 For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to True. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = True, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroPT': """Class creator. Returns: EuroPT: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='PT€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroSM(Currency): """EuroSM currency representation. Simple usage example: >>> from multicurrency import EuroSM >>> eurosm = EuroSM( ... amount=123456.789) >>> print(eurosm) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroSM': """Class creator. Returns: EuroSM: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='SM€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroSK(Currency): """EuroSK currency representation. Simple usage example: >>> from multicurrency import EuroSK >>> eurosk = EuroSK( ... amount=123456.789) >>> print(eurosk) 123 456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ' '. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '\u202F', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroSK': """Class creator. Returns: EuroSK: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='SK€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroSI(Currency): """EuroSI currency representation. Simple usage example: >>> from multicurrency import EuroSI >>> eurosi = EuroSI( ... amount=123456.789) >>> print(eurosi) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroSI': """Class creator. Returns: EuroSI: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='SI€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroES(Currency): """EuroES currency representation. Simple usage example: >>> from multicurrency import EuroES >>> euroes = EuroES( ... amount=123456.789) >>> print(euroes) 123.456,79 € For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to ','. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to '.'. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ' '. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to False. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = ',', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = '.', international: Optional[bool] = False, symbol_ahead: Optional[bool] = False, symbol_separator: Optional[str] = '\u00A0', **other) -> 'EuroES': """Class creator. Returns: EuroES: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='ES€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international) class EuroVA(Currency): """EuroVA currency representation. Simple usage example: >>> from multicurrency import EuroVA >>> eurova = EuroVA( ... amount=123456.789) >>> print(eurova) €123,456.79 For more details see `multicurrency.currency.Currency` . Args: amount (Union[int, float, Decimal]): Represented value. decimal_places (int, optional): Number of decimal places for the currency representation. Defaults to 2, decimal_sign (str, optional): Decimal symbol. Defaults to '.'. grouping_places (int, optional): Number of digits for grouping. Defaults to 3, grouping_sign (str, optional): Grouping symbol. Defaults to ','. international (bool, optional): Identifies the currency using the 'currency' value instead of the 'symbol'. Defaults to False. symbol_separator (str, optional): Separation between the symbol and the value. Defaults to ''. symbol_ahead (bool, optional): True if symbol goes ahead of the value. False otherwise. Defaults to True. """ __slots__ = [] def __new__( # pylint: disable=signature-differs,disable=unused-argument cls, amount: Union[int, float, Decimal], decimal_places: Optional[int] = 2, decimal_sign: Optional[str] = '.', grouping_places: Optional[int] = 3, grouping_sign: Optional[str] = ',', international: Optional[bool] = False, symbol_ahead: Optional[bool] = True, symbol_separator: Optional[str] = '', **other) -> 'EuroVA': """Class creator. Returns: EuroVA: new opbject. """ return Currency.__new__( cls, amount=amount, alpha_code='EUR', numeric_code='978', symbol='€', symbol_separator=symbol_separator, symbol_ahead=symbol_ahead, localized_symbol='VA€', decimal_places=decimal_places, decimal_sign=decimal_sign, grouping_places=grouping_places, grouping_sign=grouping_sign, convertion='', international=international)

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ef0625d83f22172d5b716a32bc66935b3664efbd

60,934

py

Python

clarifai/rest/grpc/proto/clarifai/api/endpoint_pb2_grpc.py

Taik/clarifai-python

c3b66b84cb348d3cb1edff958f561a4734b78650

[ "Apache-2.0" ]

322

2015-08-25T03:16:11.000Z

2021-11-08T09:36:50.000Z

clarifai/rest/grpc/proto/clarifai/api/endpoint_pb2_grpc.py

Taik/clarifai-python

c3b66b84cb348d3cb1edff958f561a4734b78650

[ "Apache-2.0" ]

76

2015-10-25T13:03:47.000Z

2022-02-19T09:36:10.000Z

clarifai/rest/grpc/proto/clarifai/api/endpoint_pb2_grpc.py

Taik/clarifai-python

c3b66b84cb348d3cb1edff958f561a4734b78650

[ "Apache-2.0" ]

136

2015-09-04T13:48:27.000Z

2021-06-12T16:48:36.000Z

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! import grpc from clarifai.rest.grpc.proto.clarifai.api import code_pb2 as proto_dot_clarifai_dot_api_dot_code__pb2 from clarifai.rest.grpc.proto.clarifai.api import concept_graph_pb2 as proto_dot_clarifai_dot_api_dot_concept__graph__pb2 from clarifai.rest.grpc.proto.clarifai.api import concept_language_pb2 as proto_dot_clarifai_dot_api_dot_concept__language__pb2 from clarifai.rest.grpc.proto.clarifai.api import concept_pb2 as proto_dot_clarifai_dot_api_dot_concept__pb2 from clarifai.rest.grpc.proto.clarifai.api import concept_reference_pb2 as proto_dot_clarifai_dot_api_dot_concept__reference__pb2 from clarifai.rest.grpc.proto.clarifai.api import input_pb2 as proto_dot_clarifai_dot_api_dot_input__pb2 from clarifai.rest.grpc.proto.clarifai.api import model_pb2 as proto_dot_clarifai_dot_api_dot_model__pb2 from clarifai.rest.grpc.proto.clarifai.api import model_version_pb2 as proto_dot_clarifai_dot_api_dot_model__version__pb2 from clarifai.rest.grpc.proto.clarifai.api import output_pb2 as proto_dot_clarifai_dot_api_dot_output__pb2 from clarifai.rest.grpc.proto.clarifai.api import search_pb2 as proto_dot_clarifai_dot_api_dot_search__pb2 from clarifai.rest.grpc.proto.clarifai.api.status import status_pb2 as proto_dot_clarifai_dot_api_dot_status_dot_status__pb2 from clarifai.rest.grpc.proto.clarifai.api import subscription_pb2 as proto_dot_clarifai_dot_api_dot_subscription__pb2 from clarifai.rest.grpc.proto.clarifai.api import visualization_pb2 as proto_dot_clarifai_dot_api_dot_visualization__pb2 from clarifai.rest.grpc.proto.clarifai.api import vocab_pb2 as proto_dot_clarifai_dot_api_dot_vocab__pb2 from clarifai.rest.grpc.proto.clarifai.api import workflow_pb2 as proto_dot_clarifai_dot_api_dot_workflow__pb2 class V2Stub(object): # missing associated documentation comment in .proto file pass def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.GetConceptCounts = channel.unary_unary( '/clarifai.api.V2/GetConceptCounts', request_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.GetConceptCountsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptCountResponse, ) self.GetConcept = channel.unary_unary( '/clarifai.api.V2/GetConcept', request_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.GetConceptRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.SingleConceptResponse, ) self.ListConcepts = channel.unary_unary( '/clarifai.api.V2/ListConcepts', request_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.ListConceptsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse, ) self.PostConceptsSearches = channel.unary_unary( '/clarifai.api.V2/PostConceptsSearches', request_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.PostConceptsSearchesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse, ) self.PostConcepts = channel.unary_unary( '/clarifai.api.V2/PostConcepts', request_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.PostConceptsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse, ) self.PatchConcepts = channel.unary_unary( '/clarifai.api.V2/PatchConcepts', request_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.PatchConceptsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse, ) self.GetVocab = channel.unary_unary( '/clarifai.api.V2/GetVocab', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.GetVocabRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.SingleVocabResponse, ) self.ListVocabs = channel.unary_unary( '/clarifai.api.V2/ListVocabs', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.ListVocabsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.MultiVocabResponse, ) self.PostVocabs = channel.unary_unary( '/clarifai.api.V2/PostVocabs', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.PostVocabsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.MultiVocabResponse, ) self.PatchVocabs = channel.unary_unary( '/clarifai.api.V2/PatchVocabs', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.PatchVocabsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.MultiVocabResponse, ) self.DeleteVocab = channel.unary_unary( '/clarifai.api.V2/DeleteVocab', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.DeleteVocabs = channel.unary_unary( '/clarifai.api.V2/DeleteVocabs', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.ListVocabConcepts = channel.unary_unary( '/clarifai.api.V2/ListVocabConcepts', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.ListVocabConceptsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse, ) self.PostVocabConcepts = channel.unary_unary( '/clarifai.api.V2/PostVocabConcepts', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.PostVocabConceptsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse, ) self.DeleteVocabConcept = channel.unary_unary( '/clarifai.api.V2/DeleteVocabConcept', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabConceptRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.DeleteVocabConcepts = channel.unary_unary( '/clarifai.api.V2/DeleteVocabConcepts', request_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabConceptsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.GetConceptLanguage = channel.unary_unary( '/clarifai.api.V2/GetConceptLanguage', request_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.GetConceptLanguageRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.SingleConceptLanguageResponse, ) self.ListConceptLanguages = channel.unary_unary( '/clarifai.api.V2/ListConceptLanguages', request_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.ListConceptLanguagesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.MultiConceptLanguageResponse, ) self.PostConceptLanguages = channel.unary_unary( '/clarifai.api.V2/PostConceptLanguages', request_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.PostConceptLanguagesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.MultiConceptLanguageResponse, ) self.PatchConceptLanguages = channel.unary_unary( '/clarifai.api.V2/PatchConceptLanguages', request_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.PatchConceptLanguagesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.MultiConceptLanguageResponse, ) self.ListConceptReferences = channel.unary_unary( '/clarifai.api.V2/ListConceptReferences', request_serializer=proto_dot_clarifai_dot_api_dot_concept__reference__pb2.ListConceptReferencesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__reference__pb2.MultiConceptReferenceResponse, ) self.ListConceptRelations = channel.unary_unary( '/clarifai.api.V2/ListConceptRelations', request_serializer=proto_dot_clarifai_dot_api_dot_concept__graph__pb2.ListConceptRelationsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse, ) self.GetInputCount = channel.unary_unary( '/clarifai.api.V2/GetInputCount', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.GetInputCountRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.SingleInputCountResponse, ) self.StreamInputs = channel.unary_unary( '/clarifai.api.V2/StreamInputs', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.StreamInputsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse, ) self.GetInput = channel.unary_unary( '/clarifai.api.V2/GetInput', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.GetInputRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.SingleInputResponse, ) self.ListInputs = channel.unary_unary( '/clarifai.api.V2/ListInputs', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.ListInputsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse, ) self.PostInputs = channel.unary_unary( '/clarifai.api.V2/PostInputs', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.PostInputsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse, ) self.PatchInputs = channel.unary_unary( '/clarifai.api.V2/PatchInputs', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.PatchInputsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse, ) self.DeleteInput = channel.unary_unary( '/clarifai.api.V2/DeleteInput', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.DeleteInputRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.DeleteInputs = channel.unary_unary( '/clarifai.api.V2/DeleteInputs', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.DeleteInputsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.PostModelOutputs = channel.unary_unary( '/clarifai.api.V2/PostModelOutputs', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.PostModelOutputsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_output__pb2.MultiOutputResponse, ) self.PostModelFeedback = channel.unary_unary( '/clarifai.api.V2/PostModelFeedback', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.PostModelFeedbackRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.GetModel = channel.unary_unary( '/clarifai.api.V2/GetModel', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.GetModelRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse, ) self.GetModelOutputInfo = channel.unary_unary( '/clarifai.api.V2/GetModelOutputInfo', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.GetModelRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse, ) self.ListModels = channel.unary_unary( '/clarifai.api.V2/ListModels', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.ListModelsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.MultiModelResponse, ) self.PostModelsSearches = channel.unary_unary( '/clarifai.api.V2/PostModelsSearches', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.PostModelsSearchesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.MultiModelResponse, ) self.PostModels = channel.unary_unary( '/clarifai.api.V2/PostModels', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.PostModelsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse, ) self.PatchModels = channel.unary_unary( '/clarifai.api.V2/PatchModels', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.PatchModelsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.MultiModelResponse, ) self.DeleteModel = channel.unary_unary( '/clarifai.api.V2/DeleteModel', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.DeleteModelRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.DeleteModels = channel.unary_unary( '/clarifai.api.V2/DeleteModels', request_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.DeleteModelsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.ListModelInputs = channel.unary_unary( '/clarifai.api.V2/ListModelInputs', request_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.ListModelInputsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse, ) self.GetModelVersion = channel.unary_unary( '/clarifai.api.V2/GetModelVersion', request_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.GetModelVersionRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.SingleModelVersionResponse, ) self.ListModelVersions = channel.unary_unary( '/clarifai.api.V2/ListModelVersions', request_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.ListModelVersionsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.MultiModelVersionResponse, ) self.PostModelVersions = channel.unary_unary( '/clarifai.api.V2/PostModelVersions', request_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.PostModelVersionsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse, ) self.DeleteModelVersion = channel.unary_unary( '/clarifai.api.V2/DeleteModelVersion', request_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.DeleteModelVersionRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.GetModelVersionMetrics = channel.unary_unary( '/clarifai.api.V2/GetModelVersionMetrics', request_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.GetModelVersionMetricsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.SingleModelVersionResponse, ) self.PostModelVersionMetrics = channel.unary_unary( '/clarifai.api.V2/PostModelVersionMetrics', request_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.PostModelVersionMetricsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.SingleModelVersionResponse, ) self.GetWorkflow = channel.unary_unary( '/clarifai.api.V2/GetWorkflow', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.GetWorkflowRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.SingleWorkflowResponse, ) self.ListWorkflows = channel.unary_unary( '/clarifai.api.V2/ListWorkflows', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.ListWorkflowsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse, ) self.ListPublicWorkflows = channel.unary_unary( '/clarifai.api.V2/ListPublicWorkflows', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.ListPublicWorkflowsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse, ) self.PostWorkflows = channel.unary_unary( '/clarifai.api.V2/PostWorkflows', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PostWorkflowsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse, ) self.PatchWorkflows = channel.unary_unary( '/clarifai.api.V2/PatchWorkflows', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PatchWorkflowsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse, ) self.DeleteWorkflow = channel.unary_unary( '/clarifai.api.V2/DeleteWorkflow', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.DeleteWorkflowRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.DeleteWorkflows = channel.unary_unary( '/clarifai.api.V2/DeleteWorkflows', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.DeleteWorkflowsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.PostWorkflowResults = channel.unary_unary( '/clarifai.api.V2/PostWorkflowResults', request_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PostWorkflowResultsRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PostWorkflowResultsResponse, ) self.PostSearches = channel.unary_unary( '/clarifai.api.V2/PostSearches', request_serializer=proto_dot_clarifai_dot_api_dot_search__pb2.PostSearchesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_search__pb2.MultiSearchResponse, ) self.PostSearchFeedback = channel.unary_unary( '/clarifai.api.V2/PostSearchFeedback', request_serializer=proto_dot_clarifai_dot_api_dot_search__pb2.PostSearchFeedbackRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse, ) self.GetSubscription = channel.unary_unary( '/clarifai.api.V2/GetSubscription', request_serializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.GetSubscriptionRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.SingleSubscriptionResponse, ) self.PostSubscription = channel.unary_unary( '/clarifai.api.V2/PostSubscription', request_serializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.PostSubscriptionRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.SingleSubscriptionResponse, ) self.GetAppVisualization = channel.unary_unary( '/clarifai.api.V2/GetAppVisualization', request_serializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.GetAppVisualizationRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.SingleVisualizationResponse, ) self.GetVisualization = channel.unary_unary( '/clarifai.api.V2/GetVisualization', request_serializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.GetVisualizationRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.SingleVisualizationResponse, ) self.PostVisualization = channel.unary_unary( '/clarifai.api.V2/PostVisualization', request_serializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.PostVisualizationRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.SingleVisualizationResponse, ) self.ListStatusCodes = channel.unary_unary( '/clarifai.api.V2/ListStatusCodes', request_serializer=proto_dot_clarifai_dot_api_dot_code__pb2.ListStatusCodesRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_code__pb2.MultiStatusCodeResponse, ) self.GetStatusCode = channel.unary_unary( '/clarifai.api.V2/GetStatusCode', request_serializer=proto_dot_clarifai_dot_api_dot_code__pb2.GetStatusCodeRequest.SerializeToString, response_deserializer=proto_dot_clarifai_dot_api_dot_code__pb2.SingleStatusCodeResponse, ) class V2Servicer(object): # missing associated documentation comment in .proto file pass def GetConceptCounts(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetConcept(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListConcepts(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostConceptsSearches(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostConcepts(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PatchConcepts(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetVocab(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListVocabs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostVocabs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PatchVocabs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteVocab(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteVocabs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListVocabConcepts(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostVocabConcepts(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteVocabConcept(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteVocabConcepts(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetConceptLanguage(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListConceptLanguages(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostConceptLanguages(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PatchConceptLanguages(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListConceptReferences(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListConceptRelations(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetInputCount(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def StreamInputs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetInput(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListInputs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostInputs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PatchInputs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteInput(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteInputs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostModelOutputs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostModelFeedback(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetModel(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetModelOutputInfo(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListModels(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostModelsSearches(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostModels(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PatchModels(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteModel(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteModels(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListModelInputs(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetModelVersion(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListModelVersions(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostModelVersions(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteModelVersion(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetModelVersionMetrics(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostModelVersionMetrics(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetWorkflow(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListWorkflows(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListPublicWorkflows(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostWorkflows(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PatchWorkflows(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteWorkflow(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteWorkflows(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostWorkflowResults(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostSearches(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostSearchFeedback(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetSubscription(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostSubscription(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetAppVisualization(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetVisualization(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PostVisualization(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListStatusCodes(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetStatusCode(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_V2Servicer_to_server(servicer, server): rpc_method_handlers = { 'GetConceptCounts': grpc.unary_unary_rpc_method_handler( servicer.GetConceptCounts, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.GetConceptCountsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptCountResponse.SerializeToString, ), 'GetConcept': grpc.unary_unary_rpc_method_handler( servicer.GetConcept, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.GetConceptRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.SingleConceptResponse.SerializeToString, ), 'ListConcepts': grpc.unary_unary_rpc_method_handler( servicer.ListConcepts, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.ListConceptsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse.SerializeToString, ), 'PostConceptsSearches': grpc.unary_unary_rpc_method_handler( servicer.PostConceptsSearches, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.PostConceptsSearchesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse.SerializeToString, ), 'PostConcepts': grpc.unary_unary_rpc_method_handler( servicer.PostConcepts, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.PostConceptsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse.SerializeToString, ), 'PatchConcepts': grpc.unary_unary_rpc_method_handler( servicer.PatchConcepts, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__pb2.PatchConceptsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse.SerializeToString, ), 'GetVocab': grpc.unary_unary_rpc_method_handler( servicer.GetVocab, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.GetVocabRequest, response_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.SingleVocabResponse.SerializeToString, ), 'ListVocabs': grpc.unary_unary_rpc_method_handler( servicer.ListVocabs, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.ListVocabsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.MultiVocabResponse.SerializeToString, ), 'PostVocabs': grpc.unary_unary_rpc_method_handler( servicer.PostVocabs, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.PostVocabsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.MultiVocabResponse.SerializeToString, ), 'PatchVocabs': grpc.unary_unary_rpc_method_handler( servicer.PatchVocabs, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.PatchVocabsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.MultiVocabResponse.SerializeToString, ), 'DeleteVocab': grpc.unary_unary_rpc_method_handler( servicer.DeleteVocab, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'DeleteVocabs': grpc.unary_unary_rpc_method_handler( servicer.DeleteVocabs, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'ListVocabConcepts': grpc.unary_unary_rpc_method_handler( servicer.ListVocabConcepts, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.ListVocabConceptsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse.SerializeToString, ), 'PostVocabConcepts': grpc.unary_unary_rpc_method_handler( servicer.PostVocabConcepts, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.PostVocabConceptsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse.SerializeToString, ), 'DeleteVocabConcept': grpc.unary_unary_rpc_method_handler( servicer.DeleteVocabConcept, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabConceptRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'DeleteVocabConcepts': grpc.unary_unary_rpc_method_handler( servicer.DeleteVocabConcepts, request_deserializer=proto_dot_clarifai_dot_api_dot_vocab__pb2.DeleteVocabConceptsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'GetConceptLanguage': grpc.unary_unary_rpc_method_handler( servicer.GetConceptLanguage, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.GetConceptLanguageRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.SingleConceptLanguageResponse.SerializeToString, ), 'ListConceptLanguages': grpc.unary_unary_rpc_method_handler( servicer.ListConceptLanguages, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.ListConceptLanguagesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.MultiConceptLanguageResponse.SerializeToString, ), 'PostConceptLanguages': grpc.unary_unary_rpc_method_handler( servicer.PostConceptLanguages, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.PostConceptLanguagesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.MultiConceptLanguageResponse.SerializeToString, ), 'PatchConceptLanguages': grpc.unary_unary_rpc_method_handler( servicer.PatchConceptLanguages, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.PatchConceptLanguagesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__language__pb2.MultiConceptLanguageResponse.SerializeToString, ), 'ListConceptReferences': grpc.unary_unary_rpc_method_handler( servicer.ListConceptReferences, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__reference__pb2.ListConceptReferencesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__reference__pb2.MultiConceptReferenceResponse.SerializeToString, ), 'ListConceptRelations': grpc.unary_unary_rpc_method_handler( servicer.ListConceptRelations, request_deserializer=proto_dot_clarifai_dot_api_dot_concept__graph__pb2.ListConceptRelationsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_concept__pb2.MultiConceptResponse.SerializeToString, ), 'GetInputCount': grpc.unary_unary_rpc_method_handler( servicer.GetInputCount, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.GetInputCountRequest, response_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.SingleInputCountResponse.SerializeToString, ), 'StreamInputs': grpc.unary_unary_rpc_method_handler( servicer.StreamInputs, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.StreamInputsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse.SerializeToString, ), 'GetInput': grpc.unary_unary_rpc_method_handler( servicer.GetInput, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.GetInputRequest, response_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.SingleInputResponse.SerializeToString, ), 'ListInputs': grpc.unary_unary_rpc_method_handler( servicer.ListInputs, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.ListInputsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse.SerializeToString, ), 'PostInputs': grpc.unary_unary_rpc_method_handler( servicer.PostInputs, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.PostInputsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse.SerializeToString, ), 'PatchInputs': grpc.unary_unary_rpc_method_handler( servicer.PatchInputs, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.PatchInputsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse.SerializeToString, ), 'DeleteInput': grpc.unary_unary_rpc_method_handler( servicer.DeleteInput, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.DeleteInputRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'DeleteInputs': grpc.unary_unary_rpc_method_handler( servicer.DeleteInputs, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.DeleteInputsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'PostModelOutputs': grpc.unary_unary_rpc_method_handler( servicer.PostModelOutputs, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.PostModelOutputsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_output__pb2.MultiOutputResponse.SerializeToString, ), 'PostModelFeedback': grpc.unary_unary_rpc_method_handler( servicer.PostModelFeedback, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.PostModelFeedbackRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'GetModel': grpc.unary_unary_rpc_method_handler( servicer.GetModel, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.GetModelRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse.SerializeToString, ), 'GetModelOutputInfo': grpc.unary_unary_rpc_method_handler( servicer.GetModelOutputInfo, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.GetModelRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse.SerializeToString, ), 'ListModels': grpc.unary_unary_rpc_method_handler( servicer.ListModels, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.ListModelsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.MultiModelResponse.SerializeToString, ), 'PostModelsSearches': grpc.unary_unary_rpc_method_handler( servicer.PostModelsSearches, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.PostModelsSearchesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.MultiModelResponse.SerializeToString, ), 'PostModels': grpc.unary_unary_rpc_method_handler( servicer.PostModels, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.PostModelsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse.SerializeToString, ), 'PatchModels': grpc.unary_unary_rpc_method_handler( servicer.PatchModels, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.PatchModelsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.MultiModelResponse.SerializeToString, ), 'DeleteModel': grpc.unary_unary_rpc_method_handler( servicer.DeleteModel, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.DeleteModelRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'DeleteModels': grpc.unary_unary_rpc_method_handler( servicer.DeleteModels, request_deserializer=proto_dot_clarifai_dot_api_dot_model__pb2.DeleteModelsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'ListModelInputs': grpc.unary_unary_rpc_method_handler( servicer.ListModelInputs, request_deserializer=proto_dot_clarifai_dot_api_dot_input__pb2.ListModelInputsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_input__pb2.MultiInputResponse.SerializeToString, ), 'GetModelVersion': grpc.unary_unary_rpc_method_handler( servicer.GetModelVersion, request_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.GetModelVersionRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.SingleModelVersionResponse.SerializeToString, ), 'ListModelVersions': grpc.unary_unary_rpc_method_handler( servicer.ListModelVersions, request_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.ListModelVersionsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.MultiModelVersionResponse.SerializeToString, ), 'PostModelVersions': grpc.unary_unary_rpc_method_handler( servicer.PostModelVersions, request_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.PostModelVersionsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__pb2.SingleModelResponse.SerializeToString, ), 'DeleteModelVersion': grpc.unary_unary_rpc_method_handler( servicer.DeleteModelVersion, request_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.DeleteModelVersionRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'GetModelVersionMetrics': grpc.unary_unary_rpc_method_handler( servicer.GetModelVersionMetrics, request_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.GetModelVersionMetricsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.SingleModelVersionResponse.SerializeToString, ), 'PostModelVersionMetrics': grpc.unary_unary_rpc_method_handler( servicer.PostModelVersionMetrics, request_deserializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.PostModelVersionMetricsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_model__version__pb2.SingleModelVersionResponse.SerializeToString, ), 'GetWorkflow': grpc.unary_unary_rpc_method_handler( servicer.GetWorkflow, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.GetWorkflowRequest, response_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.SingleWorkflowResponse.SerializeToString, ), 'ListWorkflows': grpc.unary_unary_rpc_method_handler( servicer.ListWorkflows, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.ListWorkflowsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse.SerializeToString, ), 'ListPublicWorkflows': grpc.unary_unary_rpc_method_handler( servicer.ListPublicWorkflows, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.ListPublicWorkflowsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse.SerializeToString, ), 'PostWorkflows': grpc.unary_unary_rpc_method_handler( servicer.PostWorkflows, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PostWorkflowsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse.SerializeToString, ), 'PatchWorkflows': grpc.unary_unary_rpc_method_handler( servicer.PatchWorkflows, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PatchWorkflowsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.MultiWorkflowResponse.SerializeToString, ), 'DeleteWorkflow': grpc.unary_unary_rpc_method_handler( servicer.DeleteWorkflow, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.DeleteWorkflowRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'DeleteWorkflows': grpc.unary_unary_rpc_method_handler( servicer.DeleteWorkflows, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.DeleteWorkflowsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'PostWorkflowResults': grpc.unary_unary_rpc_method_handler( servicer.PostWorkflowResults, request_deserializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PostWorkflowResultsRequest, response_serializer=proto_dot_clarifai_dot_api_dot_workflow__pb2.PostWorkflowResultsResponse.SerializeToString, ), 'PostSearches': grpc.unary_unary_rpc_method_handler( servicer.PostSearches, request_deserializer=proto_dot_clarifai_dot_api_dot_search__pb2.PostSearchesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_search__pb2.MultiSearchResponse.SerializeToString, ), 'PostSearchFeedback': grpc.unary_unary_rpc_method_handler( servicer.PostSearchFeedback, request_deserializer=proto_dot_clarifai_dot_api_dot_search__pb2.PostSearchFeedbackRequest, response_serializer=proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.BaseResponse.SerializeToString, ), 'GetSubscription': grpc.unary_unary_rpc_method_handler( servicer.GetSubscription, request_deserializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.GetSubscriptionRequest, response_serializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.SingleSubscriptionResponse.SerializeToString, ), 'PostSubscription': grpc.unary_unary_rpc_method_handler( servicer.PostSubscription, request_deserializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.PostSubscriptionRequest, response_serializer=proto_dot_clarifai_dot_api_dot_subscription__pb2.SingleSubscriptionResponse.SerializeToString, ), 'GetAppVisualization': grpc.unary_unary_rpc_method_handler( servicer.GetAppVisualization, request_deserializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.GetAppVisualizationRequest, response_serializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.SingleVisualizationResponse.SerializeToString, ), 'GetVisualization': grpc.unary_unary_rpc_method_handler( servicer.GetVisualization, request_deserializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.GetVisualizationRequest, response_serializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.SingleVisualizationResponse.SerializeToString, ), 'PostVisualization': grpc.unary_unary_rpc_method_handler( servicer.PostVisualization, request_deserializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.PostVisualizationRequest, response_serializer=proto_dot_clarifai_dot_api_dot_visualization__pb2.SingleVisualizationResponse.SerializeToString, ), 'ListStatusCodes': grpc.unary_unary_rpc_method_handler( servicer.ListStatusCodes, request_deserializer=proto_dot_clarifai_dot_api_dot_code__pb2.ListStatusCodesRequest, response_serializer=proto_dot_clarifai_dot_api_dot_code__pb2.MultiStatusCodeResponse.SerializeToString, ), 'GetStatusCode': grpc.unary_unary_rpc_method_handler( servicer.GetStatusCode, request_deserializer=proto_dot_clarifai_dot_api_dot_code__pb2.GetStatusCodeRequest, response_serializer=proto_dot_clarifai_dot_api_dot_code__pb2.SingleStatusCodeResponse.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'clarifai.api.V2', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,))

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ef674643de8371e3507eff6315561c7f636cd873

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py

Python

2015/day_06.py

nabiirah/advent-of-code

9c7e7cae437c024aa05d9cb7f9211fd47f5226a2

[ "MIT" ]

24

2020-12-08T20:07:52.000Z

2022-01-18T20:08:06.000Z

2015/day_06.py

nestorhf/advent-of-code

1bb827e9ea85e03e0720e339d10b3ed8c44d8f27

[ "MIT" ]

null

2015/day_06.py

nestorhf/advent-of-code

1bb827e9ea85e03e0720e339d10b3ed8c44d8f27

[ "MIT" ]

10

2020-12-04T10:04:15.000Z

2022-02-21T22:22:26.000Z

"""Advent of Code Day 6 - Probably a Fire Hazard""" import re # Generate Lights (x, y, 0/1) lights = [] for x in range(1000): for y in range(1000): lights.append([x, y, 0]) with open('inputs/day_06.txt') as f: instructions = f.readlines() for instruction in instructions: # Parse instruction if 'on' in instruction: action = 'on' elif 'off' in instruction: action = 'off' if 'toggle' in instruction: action = 'toggle' # Isolate coord pairs/coords coords_regex = re.compile(r'([0-9,]*) through ([0-9,]*)') first_coords = coords_regex.search(instruction).group(1) last_coords = coords_regex.search(instruction).group(2) first_x = int(first_coords.split(',')[0]) last_x = int(last_coords.split(',')[0]) first_y = int(first_coords.split(',')[1]) last_y = int(last_coords.split(',')[1]) # Select specified rectangle x_offset = last_x - first_x y_offset = last_y - first_y for x in range(first_x, first_x + x_offset + 1): for y in range(first_y, first_y + y_offset + 1): # Calculate list position position = x * 1000 + y if action == 'on': lights[position] = [x, y, 1] elif action == 'off': lights[position] = [x, y, 0] elif action == 'toggle': if lights[position][2] == 0: lights[position] = [x, y, 1] elif lights[position][2] == 1: lights[position] = [x, y, 0] on = 0 for light in lights: if light[2] == 1: on += 1 print("Answer One =", on) lights = [] for x in range(1000): for y in range(1000): lights.append([x, y, 0]) for instruction in instructions: # Parse instruction if 'on' in instruction: action = 'on' elif 'off' in instruction: action = 'off' if 'toggle' in instruction: action = 'toggle' # Isolate coord pairs/coords coords_regex = re.compile(r'([0-9,]*) through ([0-9,]*)') first_coords = coords_regex.search(instruction).group(1) last_coords = coords_regex.search(instruction).group(2) first_x = int(first_coords.split(',')[0]) last_x = int(last_coords.split(',')[0]) first_y = int(first_coords.split(',')[1]) last_y = int(last_coords.split(',')[1]) # Select specified rectangle x_offset = int(last_x) - int(first_x) y_offset = int(last_y) - int(first_y) for x in range(first_x, first_x + x_offset + 1): for y in range(first_y, first_y + y_offset + 1): # Calculate list position position = x * 1000 + y if action == 'on': brightness = lights[position][2] lights[position] = [x, y, brightness + 1] elif action == 'off': brightness = lights[position][2] if brightness != 0: lights[position] = [x, y, brightness - 1] elif action == 'toggle': brightness = lights[position][2] lights[position] = [x, y, brightness + 2] overall_brightness = 0 for light in lights: overall_brightness += light[2] print("Answer Two =", overall_brightness)

28.955357

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0.642616

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0.298489

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29.216216

0.746374

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32306d781dab4fc19d472d73eb4fc4a02c41835e

26,205

py

Python

nipy/labs/utils/random_threshold.py

neurospin/nipy

cc54600a0dca1e003ad393bc05c46f91eef30a68

[ "BSD-3-Clause" ]

1

2016-03-08T15:01:06.000Z

nipy/labs/utils/random_threshold.py

neurospin/nipy

cc54600a0dca1e003ad393bc05c46f91eef30a68

[ "BSD-3-Clause" ]

null

nipy/labs/utils/random_threshold.py

neurospin/nipy

cc54600a0dca1e003ad393bc05c46f91eef30a68

[ "BSD-3-Clause" ]

null

# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vi: set ft=python sts=4 ts=4 sw=4 et: ############################################################################## # Random Thresholding Procedure (after M. Lavielle and C. Ludena) import numpy as np import scipy.stats as st from nipy.algorithms.graph import wgraph_from_3d_grid from ..group.routines import add_lines tol = 1e-10 ############################################################################## # Wrappers def randthresh_main(Y, K, XYZ=None, p=np.inf, varwind=False, knownull=True, stop=False, verbose=False): """ Wrapper for random threshold functions Parameters ========== Y: array of shape (n,),Observations K: int, Some positive integer (lower bound on the number of null hypotheses) XYZ: array of shape (3, n) voxel coordinates. If not empty, connexity constraints are used on the non-null set p: float, optional, lp norm varwind: bool, Varying window variant (vs. fixed window, with width K) knownull: bool, optional, Known null distribution (observations assumed Exp(1) under H0) versus unknown (observations assumed Gaussian under H0) stop: bool, optional Stop when minimum is attained (save computation time) verbose: bool, 'Chatty' mode Returns ======= A dictionary D containing the following fields: "C" (n-K) array Lp norm of partial sums fluctuation about their conditional expectation "thresh" <float> Detection threshold "detect" (k,) Index of detected activations Note ==== Random thresholding is performed only if null hypothesis of no activations is rejected at level 5% """ if XYZ == None: return randthresh(Y, K, p, stop, verbose, varwind, knownull) else: return randthresh_connex(Y, K, XYZ, p, stop, verbose, varwind, knownull) def randthresh(Y, K, p=np.inf, stop=False, verbose=False, varwind=False, knownull=True): """ Wrapper for random threshold functions (without connexity constraints) Parameters ========== Y: array of shape (n,) Observations K: int, Some positive integer (lower bound on the number of null hypotheses) p: float, lp norm stop <bool> Stop when minimum is attained (save computation time) verbose <bool> 'Chatty' mode varwind <bool> Varying window variant (vs. fixed window, with width K) knownull <bool> Known null distribution (observations assumed Exp(1) under H0) versus unknown (observations assumed Gaussian under H0) Returns ======= A dictionary D containing the following fields: "C" (n-K) Lp norm of partial sums fluctuation about their conditional expectation "thresh" <float> Detection threshold "detect" (k,) Index of detected activations "v" <float> Estimated null variance (if knownull is False) Note ==== Random thresholding is performed only if null hypothesis of no activations is rejected at level 5% """ D = {} # Test presence of activity if knownull: X = Y else: v = np.square(Y).mean() X = np.clip( - np.log(1 - st.chi2.cdf(Y ** 2, 1, 0, scale=v)), 0, 1 / tol) D["v"] = v T = test_stat(X, p=np.inf) if T <= 0.65: print "No activity detected at 5% level" D["detect"] = np.array([]) D["thresh"] = np.inf else: # Find optimal threshold if varwind: if knownull: C = randthresh_varwind_knownull(Y, K, p, stop, verbose) else: C, V = randthresh_varwind_gaussnull( Y, K, p, stop, one_sided=False, verbose=verbose) else: if knownull: C = randthresh_fixwind_knownull(Y, K, p, stop, verbose) else: C, V = randthresh_fixwind_gaussnull( Y, K, p, stop, one_sided=False, verbose=verbose) n = len(X) if stop: I = np.where(C > 0)[0] if len(I) > 0: ncoeffs = I[-1] else: ncoeffs = n - K else: I = np.where((C[2:] > C[1:-1]) * (C[1:-1] < C[:-2]))[0] if len(I) > 0: ncoeffs = I[np.argmin(C[1: -1][I])] + 1 else: ncoeffs = n - K thresh = np.sort(np.abs(Y))[ - ncoeffs] # Detected activations detect = np.where(np.abs(Y) > thresh)[0] D["C"] = C[2:] D["thresh"] = thresh D["detect"] = detect if not knownull: D["v"] = V[2:] return D def randthresh_connex(Y, K, XYZ, p=np.inf, stop=False, verbose=False, varwind=False, knownull=True): """ Wrapper for random threshold functions under connexity constraints Parameters ========== Y (n,) Observations K <int> Some positive integer (lower bound on the number of null hypotheses) XYZ (3,n) voxel coordinates p <float> lp norm stop <bool> Stop when minimum is attained (save computation time) verbose <bool> 'Chatty' mode varwind <bool> Varying window variant (vs. fixed window, with width K) knownull <bool> Known null distribution (observations assumed Exp(1) under H0) versus unknown (observations assumed Gaussian under H0) Returns ======= A dictionary D containing the following fields: "C" (n-K) Lp norm of partial sums fluctuation about their conditional expectation "thresh" <float> Detection threshold "detect" (ncoeffs,) Index of detected voxels Note ==== Random thresholding is performed only if null hypothesis of no activations is rejected at level 5% """ # Test presence of activity D = {} if knownull: X = Y else: v = np.square(Y).mean() X = np.clip( - np.log(1 - st.chi2.cdf(Y ** 2, 1, 0, scale=v)), 0, 1 / tol) D["v"] = v T = test_stat(X, p=np.inf) if T <= 0.65: print "No activity detected at 5% level" D["detect"] = np.array([]) D["thresh"] = np.inf else: # Find optimal threshold if varwind: if knownull: C = randthresh_varwind_knownull_connex( Y, K, XYZ, p, stop, verbose) else: C, V = randthresh_varwind_gaussnull_connex( Y, K, XYZ, p, stop, verbose=verbose) else: if knownull: C = randthresh_fixwind_knownull_connex( Y, K, XYZ, p, stop, verbose) else: C, V = randthresh_fixwind_gaussnull_connex( Y, K, XYZ, p, stop, verbose=verbose) n = len(X) if stop: I = np.where(C > 0)[0] if len(I) > 0: ncoeffs = I[-1] else: ncoeffs = n - K else: I = np.where((C[2:] > C[1:-1]) * (C[1:-1] < C[:-2]))[0] if len(I) > 0: ncoeffs = I[np.argmin(C[1:-1][I])] + 1 else: ncoeffs = n - K thresh = np.sort(np.abs(Y))[ - ncoeffs] detect = np.where(np.abs(Y) > thresh)[0] # Remove isolated voxels iso = isolated(XYZ[:, detect]) detect[iso] = -1 detect = detect[detect != -1] D["C"] = C[2:] D["thresh"] = thresh D["detect"] = detect if knownull == False: Ynull = np.square(Y).copy() Ynull[detect] = np.nan Ynull = Ynull[np.isnan(Ynull) == False] D["v"] = V[2:] return D ######################################################################### # random threshold functions without connexity constraints def randthresh_fixwind_knownull(X, K, p=np.inf, stop=False, verbose=False): """Random threshold with fixed-window and known null distribution Parameters ========== X (n,): Observations (must be Exp(1) under H0) K <int>: Some positive integer (lower bound on the number of null hypotheses) p <float>: Lp norm stop <bool>: Stop when minimum is attained (save computation time) Returns ======= C (n-K): Lp norm of partial sums fluctuation about their conditional expectation """ n = len(X) I = 1.0 / np.arange(1, n + 1) # Sort data sortX = np.sort(X)[:: - 1] C = np.zeros(n - K, float) T = np.cumsum(sortX) for k in xrange(2, n - K): #Ratio of expectations B = np.arange(1, K + 1) * (1 + I[:n - 1 - k].sum() - I[:K].cumsum()) B /= float(K) * ( 1 + I[K: n - 1 - k].sum() ) #Partial sums Tk = T[k + 1: k + K + 1] - T[k] #Conditional expectations Q = B * Tk[-1] if p == np.inf: C[k] = np.abs(Tk - Q).max() / np.sqrt(n) else: C[k] = ( np.abs(Tk - Q) ** p ).sum() / n ** (p / 2.0 + 1) if verbose: print "k :", k, "C[k]:", C[k] if C[k] > C[k - 1] and C[k - 1] < C[k - 2] and stop: break return C def randthresh_varwind_knownull(X, K, p=np.inf, stop=False, verbose=False): """Random threshold with varying window and known null distribution Parameters ========== X (n,): Observations (Exp(1) under H0) K <int>: Some positive integer (lower bound on the number of null hypotheses) p <float>: lp norm stop <bool>: Stop when minimum is attained (save computation time) Returns ======= C (n-K) Lp norm of partial sums fluctuation about their conditional expectation """ n = len(X) I = 1.0 / np.arange(1, n + 1) #Sort data sortX = np.sort(X)[:: - 1] T = np.cumsum(sortX) C = np.zeros(n - K, float) for k in xrange(2, n - K): #Ratio of expectations B = np.arange(1, n - k) * ( 1 + I[:n - 1 - k].sum() - I[:n - k - 1].cumsum()) B /= float(n - k - 1) #Partial sums Tk = T[k + 1:] - T[k] #Conditional expectations Q = B * Tk[ - 1] if p == np.inf: C[k] = np.abs(Tk - Q).max() / np.sqrt(n - k - 1) else: C[k] = ( np.abs(Tk - Q) ** p).sum() / (n - k - 1) ** (p / 2.0 + 1) if verbose: print "k:", k, "C[k]:", C[k] if C[k] > C[k - 1] and C[k - 1] < C[k - 2] and stop: break return C def randthresh_fixwind_gaussnull(Y, K, p=np.inf, stop=False, one_sided=False, verbose=False): """ Random threshold with fixed window and null gaussian distribution Parameters ========== Y array of shape (n,) Observations (assumed Gaussian under H0, with unknown variance) K, int, Some positive integer (lower bound on the number of null hypotheses) p, float, lp norm stop: bool, Stop when minimum is attained (save computation time) one_sided: bool, If nonzero means are positive only (vs. positive or negative) Returns ======= C array of shape (n-K) Lp norm of partial sums fluctuation about their conditional expectation """ n = len(Y) I = 1.0 / np.arange(1, n + 1) if one_sided: sortY = np.sort(Y) std = np.sqrt((np.sum(sortY[1:K] ** 2) + np.cumsum(sortY[K: n] ** 2))\ * 1.0 / np.arange(K, n)) std = std[:: - 1] else: sortY = np.sort(np.square(Y)) V = (np.sum(sortY[1: K]) + np.cumsum(sortY[K: n])) * \ 1.0 / np.arange(K, n) V = V[:: - 1] C = np.zeros(n - K, float) sortY = sortY[:: - 1] for k in xrange(2, n - K): if one_sided: X = np.clip( - np.log(1 - st.norm.cdf(sortY[k + 1: k + K + 1], scale=std[k])), 0, 1 / tol) else: X = np.clip( - np.log(1 - st.chi2.cdf(sortY[k + 1: k + K + 1], 1, 0, scale=V[k])), 0, 1 / tol) # Ratio of expectations B = np.arange(1, K + 1) * (1 + I[:n - 1 - k].sum() - I[: K].cumsum()) B /= float(K) * (1 + I[K: n - 1 - k].sum()) # Partial sums T = X.cumsum() # Conditional expectations Q = B * T[-1] if p == np.inf: C[k] = np.abs(T - Q).max() / np.sqrt(n) else: C[k] = ( np.abs(T - Q) ** p ).sum() / n ** ( p / 2.0 + 1) if verbose: print "k:", k, "C[k]:", C[k] if C[k] > C[k-1] and C[k-1] < C[k-2] and stop: break return C, V def randthresh_varwind_gaussnull(Y, K, p=np.inf, stop=False, one_sided=False, verbose=False): """Random threshold with fixed window and gaussian null distribution Parameters ========== Y (n,) Observations (assumed Gaussian under H0, with unknown variance) K <int> Some positive integer (lower bound on the number of null hypotheses) p <float> lp norm stop <bool> Stop when minimum is attained (save computation time) one_sided <bool> If nonzero means are positive only (vs. positive or negative) Returns ======= C (n-K) Lp norm of partial sums fluctuation about their conditional expectation """ n = len(Y) I = 1.0 / np.arange(1, n + 1) if one_sided: sortY = np.sort(Y) std = np.sqrt((np.sum(sortY[1: K] ** 2) + np.cumsum(sortY[K: n] ** 2)) * 1.0 / np.arange(K, n)) std = std[:: - 1] else: sortY = np.sort(np.square(Y)) V = (np.sum(sortY[1: K]) + np.cumsum(sortY[K: n]))\ * 1.0 / np.arange(K, n) V = V[:: - 1] C = np.zeros(n - K, float) sortY = sortY[:: - 1] for k in xrange(2, n - K): if one_sided: X = np.clip( - np.log(1 - st.norm.cdf(sortY[k + 1:], scale=std[k])), 0, 1 / tol) else: X = np.clip( - np.log(1 - st.chi2.cdf(sortY[k + 1:], 1, 0, scale=V[k])), 0, 1 / tol) # Ratio of expectations B = np.arange(1, n - k) * ( 1 + I[: n - 1 - k].sum() - \ I[: n - k - 1].cumsum() ) B /= float(n - k - 1) # Partial sums T = X.cumsum() # Conditional expectations Q = B * T[ - 1] if p == np.inf: C[k] = np.abs(T - Q).max() / np.sqrt(n) else: C[k] = ( np.abs(T - Q) ** p ).sum() / n ** (p / 2.0 + 1) if verbose: print "k:", k, "C[k]:", C[k] if C[k] > C[k - 1] and C[k - 1] < C[k - 2] and stop: break return C, V ############################################################################### # random threshold functions with connexity constraints def randthresh_fixwind_knownull_connex(X, K, XYZ, p=np.inf, stop=False, verbose=False): """Random threshold with fixed-window and known null distribution, using connexity constraint on non-null set. Parameters ========== X (n,): Observations (must be Exp(1) under H0) XYZ (3,n): voxel coordinates K <int>: Some positive integer (lower bound on the number of null hypotheses) p <float>: Lp norm stop <bool>: Stop when minimum is attained (save computation time) Returns ======= C (n-K): Lp norm of partial sums fluctuation about their conditional expectation """ n = len(X) I = 1.0 / np.arange(1, n + 1) #Sort data J = np.argsort(X)[:: - 1] sortX = X[J] C = np.zeros(n - K, float) T = np.zeros(K, float) L = np.zeros(n, int) L[J[0]] = 1 for k in xrange(2, n - K): #Ratio of expectations B = np.arange(1, K + 1) * (1 + I[: n - 1 - k].sum() - I[: K].cumsum()) B /= float(K) * ( 1 + I[K: n - 1 - k].sum() ) Jk = J[:k] #Suprathreshold voxels connected to new voxel XYZk = np.abs(XYZ[:, Jk] - XYZ[:, J[k - 1]].reshape(3, 1)) Lk = np.where((XYZk.sum(axis=0) <= 2) * (XYZk.max(axis=0) <= 1))[0]\ [: - 1] if len(Lk) == 0: L[J[k - 1]] = 1 else: L[J[Lk]] = 0 Ik = np.where(L[Jk] == 1)[0] nk = len(Ik) #Partial sums if nk >= K: T = sortX[Ik[:K]].cumsum() elif nk == 0: T = sortX[k + 1: k + K + 1].cumsum() else: T[:nk] = sortX[Ik].cumsum() T[nk:] = T[nk - 1] + sortX[k + 1:k + K - nk + 1].cumsum() # Conditional expectations Q = B * T[-1] if p == np.inf: C[k] = np.abs(T - Q).max() / np.sqrt(n) else: C[k] = (np.abs(T - Q) ** p).sum() / n ** (p / 2.0 + 1) if verbose: print "k:", k, "nk:", nk, "C[k]:", C[k] if C[k] > C[k - 1] and C[k - 1] < C[k - 2] and stop: break return C def randthresh_varwind_knownull_connex(X, K, XYZ, p=np.inf, stop=False, verbose=False): """Random threshold with varying window and known null distribution Parameters ========== X (n,): Observations (Exp(1) under H0) K <int>: Some positive integer (lower bound on the number of null hypotheses) XYZ (3,n): voxel coordinates p <float>: lp norm stop <bool>: Stop when minimum is attained (save computation time) Returns ======= C (n-K) Lp norm of partial sums fluctuation about their conditional expectation """ n = len(X) I = 1.0 / np.arange(1, n + 1) #Sort data J = np.argsort(X)[:: - 1] sortX = X[J] C = np.zeros(n - K, float) L = np.zeros(n, int) L[J[0]] = 1 for k in xrange(2, n - K): Jk = J[:k] #Suprathreshold voxels connected to new voxel XYZk = np.abs(XYZ[:, Jk] - XYZ[:, J[k-1]].reshape(3, 1)) Lk = np.where((XYZk.sum(axis=0) <= 2) * (XYZk.max(axis=0) <= 1))\ [0][:-1] if len(Lk) == 0: L[J[k - 1]] = 1 else: L[J[Lk]] = 0 Ik = np.where(L[Jk] == 1)[0] #Ik = isolated(XYZ[:, Jk]) nk = len(Ik) #Ratio of expectations B = np.arange(1, n - k + nk) * ( 1 + I[:n - 1 - k + nk].sum() - I[:n - k - 1 + nk].cumsum()) B /= float(n - k - 1 + nk) #Partial sums if nk == 0: T = sortX[k + 1:].cumsum() else: T = np.zeros(n - k + nk - 1, float) T[:nk] = sortX[Ik].cumsum() T[nk:] = T[nk - 1] + sortX[k + 1:].cumsum() #Conditional expectations Q = B * T[-1] if p == np.inf: C[k] = np.abs(T - Q).max() / np.sqrt(n - k - 1 + nk) else: C[k] = ( np.abs(T - Q) ** p ).sum() / (n - k - 1 + nk) **\ (p / 2.0 + 1) if C[k] > C[k - 1] and C[k - 1] < C[k - 2] and stop: break if verbose: print "k:", k, "nk:", nk, "C[k]:", C[k] return C def randthresh_fixwind_gaussnull_connex(X, K, XYZ, p=np.inf, stop=False, verbose=False): """Random threshold with fixed-window and gaussian null distribution, using connexity constraint on non-null set. Parameters ========== X (n,): Observations (assumed Gaussian under H0) XYZ (3,n): voxel coordinates K <int>: Some positive integer (lower bound on the number of null hypotheses) p <float>: Lp norm stop <bool>: Stop when minimum is attained (save computation time) Returns ======= C (n-K): Lp norm of partial sums fluctuation about their conditional expectation """ n = len(X) I = 1.0 / np.arange(1, n + 1) #Sort data J = np.argsort(X ** 2)[:: - 1] sortX = np.square(X)[J] C = np.zeros(n - K, float) V = np.zeros(n - K, float) T = np.zeros(K, float) L = np.zeros(n, int) L[J[0]] = 1 for k in xrange(2, n - K): #Ratio of expectations B = np.arange(1, K + 1) * ( 1 + I[:n - 1 - k].sum() - I[:K].cumsum()) B /= float(K) * ( 1 + I[K:n - 1 - k].sum()) Jk = J[:k] #Suprathreshold voxels connected to new voxel XYZk = np.abs(XYZ[:, Jk] - XYZ[:, J[k - 1]].reshape(3, 1)) Lk = np.where((XYZk.sum(axis=0) <= 2) * (XYZk.max(axis=0) <= 1))[0][: - 1] if len(Lk) == 0: L[J[k - 1]] = 1 else: L[J[Lk]] = 0 Ik = np.where(L[Jk] == 1)[0] nk = len(Ik) #Null variance V[k] = (sortX[Ik].sum() + sortX[k + 1:].sum()) / float(nk + n - k - 1) #Partial sums if nk >= K: T = np.clip( - np.log(1 - st.chi2.cdf( sortX[Ik[:K]], 1, 0, scale=V[k])), 0, 1 / tol).cumsum() elif nk == 0: T = np.clip( - np.log(1 - st.chi2.cdf(sortX[k + 1:k + K + 1], 1, 0, scale=V[k])), 0, 1 / tol).cumsum() else: T[:nk] = np.clip( - np.log(1 - st.chi2.cdf(sortX[Ik], 1, 0, scale=V[k])), 0, 1 / tol).cumsum() T[nk:] = T[nk - 1] + np.clip( - np.log(1 - st.chi2.cdf(sortX[k + 1:k + K - nk + 1], 1, 0, scale=V[k])), 0, 1 / tol).cumsum() # Conditional expectations Q = B * T[ - 1] if p == np.inf: C[k] = np.abs(T - Q).max() / np.sqrt(n) else: C[k] = (np.abs(T - Q) ** p).sum() / n ** (p / 2.0 + 1) if verbose: print "k:", k, "nk:", nk, "C[k]:", C[k] if C[k] > C[k - 1] and C[k - 1] < C[k - 2] and stop: break return C, V def randthresh_varwind_gaussnull_connex(X, K, XYZ, p=np.inf, stop=False, verbose=False): """Random threshold with fixed-window and gaussian null distribution, using connexity constraint on non-null set. Parameters ========== X (n,): Observations (assumed Gaussian under H0) XYZ (3,n): voxel coordinates K <int>: Some positive integer (lower bound on the number of null hypotheses) p <float>: Lp norm stop <bool>: Stop when minimum is attained (save computation time) Returns ======= C (n-K): Lp norm of partial sums fluctuation about their conditional expectation """ n = len(X) I = 1.0 / np.arange(1, n + 1) #Sort data J = np.argsort(X ** 2)[:: - 1] sortX = np.square(X)[J] C = np.zeros(n - K, float) V = np.zeros(n - K, float) T = np.zeros(K, float) L = np.zeros(n, int) L[J[0]] = 1 for k in xrange(2, n - K): Jk = J[:k] #Suprathreshold voxels connected to new voxel XYZk = np.abs(XYZ[:, Jk] - XYZ[:, J[k - 1]].reshape(3, 1)) Lk = np.where((XYZk.sum(axis=0) <= 2) * (XYZk.max(axis=0) <= 1))[0][: - 1] if len(Lk) == 0: L[J[k - 1]] = 1 else: L[J[Lk]] = 0 Ik = np.where(L[Jk] == 1)[0] #Ik = isolated(XYZ[:, Jk]) nk = len(Ik) #Ratio of expectations B = np.arange(1, n - k + nk) * ( 1 + I[:n - 1 - k + nk].sum() - I[:n - k - 1 + nk].cumsum()) B /= float(n - k - 1 + nk) #Null variance V[k] = (sortX[Ik].sum() + sortX[k + 1:].sum()) / float(nk + n - k - 1) #Partial sums if nk == 0: T = np.clip( - np.log(1 - st.chi2.cdf(sortX[k + 1:], 1, 0, scale=V[k])), 0, 1 / tol).cumsum() else: T = np.zeros(n - k + nk - 1, float) T[:nk] = np.clip( - np.log(1 - st.chi2.cdf(sortX[Ik], 1, 0, scale=V[k])), 0, 1 / tol).cumsum() T[nk:] = T[nk-1] + np.clip( - np.log(1 - st.chi2.cdf(sortX[k + 1:], 1, 0, scale=V[k])), 0, 1 / tol).cumsum() #Conditional expectations Q = B * T[-1] if p == np.inf: C[k] = np.abs(T - Q).max() / np.sqrt(n - k - 1 + nk) else: C[k] = ( np.abs(T - Q) ** p).sum() / \ (n - k - 1 + nk) ** (p / 2.0 + 1) if verbose: print "k:", k, "nk:", nk, "C[k]:", C[k] if C[k] > C[k - 1] and C[k - 1] < C[k - 2] and stop: break return C, V ############################################################################# # Miscellanous functions def test_stat(X, p=np.inf): """Test statistic of global null hypothesis that all observations have zero-mean Parameters ========== X (n,) : X[j] = -log(1-F(|Y[j]|)) where F: cdf of |Y[j]| under null hypothesis (must be computed beforehand) p : Lp norm (<= inf) to use for computing test statistic Returns ======= D <float> : test statistic """ n = len(X) I = 1.0 / np.arange(1, n + 1) #Partial sums T = np.cumsum(np.sort(X)[:: - 1]) #Expectation of partial sums E = np.arange(1, n + 1) * (1 + I.sum() - I.cumsum()) #Conditional expectation of partial sums Q = E / n * T[ - 1] #Test statistic if p == np.inf: return np.max( ( np.abs(T - Q) ) / np.sqrt(n) ) else: return sum(np.abs(T - Q) ** p) / (n ** (0.5 * p + 1)) def isolated(XYZ, k=18): """ Outputs an index I of isolated points from their integer coordinates, XYZ (3, n), and under k-connectivity, k = 6, 18 or 26. """ label = wgraph_from_3d_grid(XYZ.T, k).cc() # Isolated points ncc = label.max() + 1 p = XYZ.shape[1] size = np.zeros(ncc, float) ones = np.ones((p, 1), float) add_lines(ones, size.reshape(ncc, 1), label) return np.where(size[label] == 1)[0]

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08a017627f1c4ab78548d13a934be4d8775581c9

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py

Python

generate_presentation_figures.py

youngmp/park_and_ermentrout_2017

1b3b6af46ddbba16f850438571d0103e8eda177c

[ "MIT" ]

8

2018-01-19T02:40:21.000Z

2019-05-24T09:44:30.000Z

generate_presentation_figures.py

youngmp/park_and_ermentrout_2017

1b3b6af46ddbba16f850438571d0103e8eda177c

[ "MIT" ]

null

generate_presentation_figures.py

youngmp/park_and_ermentrout_2017

1b3b6af46ddbba16f850438571d0103e8eda177c

[ "MIT" ]

null

""" Run to generate figures for presentation. Requires TeX; may need to install texlive-extra-utils on linux Requires xppy and Py_XPPCall the main() function at the end calls the preceding individual figure functions. figures are saved as both png and pdf. Copyright (c) 2016, Youngmin Park, Bard Ermentrout All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ # last compiled using python 2.7.6 # numpy version 1.8.2 # scipy version 0.13.3 # matplotlib version 1.3.1 import os from sys import stdout import numpy as np import scipy as sp import matplotlib import copy #from matplotlib.ticker import MultipleLocator #import matplotlib.ticker as mticker import matplotlib.colors as colors from matplotlib import pyplot as plt import matplotlib.pylab as mp #import matplotlib.gridspec as gridspec from mpl_toolkits.mplot3d import proj3d import matplotlib.gridspec as gridspec import matplotlib.patches as patches from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar from mpl_toolkits.axes_grid1.inset_locator import mark_inset from mpl_toolkits.mplot3d.art3d import Line3DCollection from matplotlib.collections import LineCollection from mpl_toolkits.mplot3d import axes3d # 3d plotting is generated in twod_full_square.py, then beautified in this file. from matplotlib import rc rc('text', usetex=True) rc('font', family='serif', serif=['Computer Modern Roman']) matplotlib.rcParams['text.latex.preamble'] = [r'\boldmath \usepackage{bm} \usepackage{xcolor} \setlength{\parindent}{0pt}'] matplotlib.rcParams.update({'figure.autolayout': True}) sizeOfFont = 20 fontProperties = {'weight' : 'bold', 'size' : sizeOfFont} from scipy.interpolate import interp1d import oned_simple import fourier_2d as f2d import twod_full as twod import twod_phase as twodp from xppy.utils import diagram from xppcall import xpprun from generate_figures import beautify_phase cos = np.cos sin = np.sin pi = np.pi;Pi=pi sqrt = np.sqrt Sqrt = np.sqrt exp = np.exp erfc = sp.special.erfc;Erfc=erfc erf = sp.special.erf;Erf=erf E = np.exp(1)#2.7182818284590452353602874713527 cosh = np.cosh;Cosh=cosh class MyAxes3D(axes3d.Axes3D): def __init__(self, baseObject, sides_to_draw): self.__class__ = type(baseObject.__class__.__name__, (self.__class__, baseObject.__class__), {}) self.__dict__ = baseObject.__dict__ self.sides_to_draw = list(sides_to_draw) self.mouse_init() def set_some_features_visibility(self, visible): for t in self.w_zaxis.get_ticklines() + self.w_zaxis.get_ticklabels(): t.set_visible(visible) self.w_zaxis.line.set_visible(visible) self.w_zaxis.pane.set_visible(visible) self.w_zaxis.label.set_visible(visible) def draw(self, renderer): # set visibility of some features False self.set_some_features_visibility(False) # draw the axes super(MyAxes3D, self).draw(renderer) # set visibility of some features True. # This could be adapted to set your features to desired visibility, # e.g. storing the previous values and restoring the values self.set_some_features_visibility(True) zaxis = self.zaxis draw_grid_old = zaxis.axes._draw_grid # disable draw grid zaxis.axes._draw_grid = False tmp_planes = zaxis._PLANES if 'l' in self.sides_to_draw : # draw zaxis on the left side zaxis._PLANES = (tmp_planes[2], tmp_planes[3], tmp_planes[0], tmp_planes[1], tmp_planes[4], tmp_planes[5]) zaxis.draw(renderer) if 'r' in self.sides_to_draw : # draw zaxis on the right side zaxis._PLANES = (tmp_planes[3], tmp_planes[2], tmp_planes[1], tmp_planes[0], tmp_planes[4], tmp_planes[5]) zaxis.draw(renderer) zaxis._PLANES = tmp_planes # disable draw grid zaxis.axes._draw_grid = draw_grid_old def collect_disjoint_branches(diagram,all_sv=True,return_eval=False,sv_tol=.1,remove_isolated=True,isolated_number=2,remove_redundant=True,redundant_threshold=.01,N=20,fix_reverse=True): """ collect all disjoint branches into disjoint arrays in a dict. diagram.dat: all_info.dat from xppauto version 8. currently not compatible with info.dat. recall org for xpp version 8: type, branch, 0, par1, par2, period, uhigh[1..n], ulow[1..n], evr[1] evm[1] ... evr[n] evm[n] yes there is a zero there as of xpp version 8. I don't know why. for more information on how diagram is organized, see tree.pdf in the xpp source home directory. all_sv: True or False. in each branch, return all state variables (to be implemented) return_eval: return eigenvalues (to be implemented) sv_tol: difference in consecutive state variables. If above this value, break branch. remove_isolated: True/False. If a branch has fewer than isolated_number of points, do not include. remove_redundant: if branches overlap, remove. we require the max diff to be above redundant_threshold by default, we keep branches with a longer arc length. N: number of points to check for redundancy fix_reverse: True/False. some branches are computed backwards as a function of the parameter. If so, reverse. """ # get number of state variables (both hi and lo values, hence the 2*) varnum = 2*len(diagram[0,6:])/4 # numer of preceding entries (tbparper stands for xpp type xpp branch parameter period) # diagram[:,6] is the first state variable over all parameter values # diagram[:,:6] are all the xpp types, xpp branches, parameters, periods for all parameter values tbparper = 6 # column index of xpp branch type typeidx = 0 # column index of xpp branch number bridx = 1 # column index of 0 guy zeroidx = 2 # column index of bifurcation parameters par1idx = 3 par2idx = 4 # set up array values for retreival c1 = [] c2 = [] c1.append(typeidx) c1.append(bridx) c2.append(par1idx) c2.append(par2idx) for i in range(varnum): c2.append(tbparper+i) c1 = np.array(c1,dtype=int) c2 = np.array(c2,dtype=int) # store various branches to dictionary # this dict is for actual plotting values val_dict = {} # this dict is for type and xpp branch values type_dict = {} # loop over each coordinate. begin new branch if type, branch change values # or if parval, period, sv1, sv2, .. svn change discontinuously. # first set of comparisons is called c1 # second set of comparisons is called c2 brnum = 0 val_dict['br'+str(brnum)] = np.zeros((1,2+varnum)) # branches are named in order they are created type_dict['br'+str(brnum)] = np.zeros((1,2)) # initialize c1v_prev = np.array([list(diagram[0,c1])]) c1v = np.array([list(diagram[1,c1])]) c2v_prev = np.array([list(diagram[0,c2])]) c2v = np.array([list(diagram[1,c2])]) # val_dict has entries [par1, par2, sv1hi, sv1lo, ..., svnhi, svnlo] # type_dict has entries [type, br] # for a given xpp branch, consecutive terms are appended as a new row val_dict['br'+str(brnum)] = c2v_prev type_dict['br'+str(brnum)] = c1v_prev for i in range(2,len(diagram[:,0])): # get values for type and branch c1v_prev = np.array([list(diagram[i-1,c1])]) c1v = np.array([list(diagram[i,c1])]) # get values for svs and parameters c2v_prev = np.array([list(diagram[i-1,c2])]) c2v = np.array([list(diagram[i,c2])]) # append above values to current branch val_dict['br'+str(brnum)] = np.append(val_dict['br'+str(brnum)],c2v_prev,axis=0) type_dict['br'+str(brnum)] = np.append(type_dict['br'+str(brnum)],c1v_prev,axis=0) # if either above threshold, start new key. if np.any( np.abs((c1v - c1v_prev))>=1): brnum += 1 val_dict['br'+str(brnum)] = c2v type_dict['br'+str(brnum)] = c1v elif np.any( np.abs((c2v - c2v_prev))>=sv_tol): brnum += 1 val_dict['br'+str(brnum)] = c2v type_dict['br'+str(brnum)] = c1v # remove isolated points if remove_isolated: keyvals = val_dict.keys() for i in range(len(keyvals)): if len(val_dict[keyvals[i]]) <= isolated_number: val_dict.pop(keyvals[i]) type_dict.pop(keyvals[i]) # remove redundant branches # a python branch is removed if it shares multiple points (N) with another xpp branch. if remove_redundant: val_dict_final = {} type_dict_final = {} # get all xpp branch numbers brlist = np.unique(diagram[:,1]) # collect all branches for each xpp branch number keyvals = val_dict.keys() keyignorelist = [] keysavelist = [] # loop over keys of python branches for i in range(len(keyvals)): key = keyvals[i] if not(key in keyignorelist): # get xpp branch xppbrnum = type_dict[key][0,1] for j in range(i+1,len(keyvals)): key2 = keyvals[j] if not(key2 in keyignorelist) and (key2 != key): # make sure xpp branches are different if xppbrnum != type_dict[key2][0,1]: # loop over N different values N = 20 belowthresholdcount = 0 dN = len(val_dict[key][:,0])/N for i in range(N): # check if 2 points in val_dict[key] are in val_dict[key2] # first point par1diff = np.amin(np.abs(val_dict[key][dN*i,0]-val_dict[key2][:,0])) par2diff = np.amin(np.abs(val_dict[key][dN*i,1]-val_dict[key2][:,1])) sv1diff = np.amin(np.abs(val_dict[key][dN*i,2]-val_dict[key2][:,2])) sv2diff = np.amin(np.abs(val_dict[key][dN*i,3]-val_dict[key2][:,3])) diff1 = par1diff + par2diff + sv1diff + sv2diff if diff1 <= redundant_threshold: #print 'delete', key2 belowthresholdcount += 1 if belowthresholdcount >= 4: keyignorelist.append(key2) #print 'del', key2 else: if not(key2 in keysavelist): #print 'keep', key2 val_dict_final[key2] = val_dict[key2] type_dict_final[key2] = type_dict[key2] keysavelist.append(key2) for key in keyignorelist: if key in keysavelist: val_dict_final.pop(key) type_dict_final.pop(key) else: val_dict_final = val_dict type_dict_final = type_dict if fix_reverse: for key in val_dict_final.keys(): if val_dict_final[key][2,0] - val_dict_final[key][1,0] < 0: for i in range(varnum): val_dict_final[key][:,i] = val_dict_final[key][:,i][::-1] return val_dict_final, type_dict_final def collect(x,y,use_nonan=True,lwstart=1.,lwend=5.,zorder=1.,cmapmax=1.,cmapmin=0.): """ add desired line properties """ x = np.real(x) y = np.real(y) x_nonan = x[(~np.isnan(x))*(~np.isnan(y))] y_nonan = y[(~np.isnan(x))*(~np.isnan(y))] if use_nonan: points = np.array([x_nonan, y_nonan]).T.reshape(-1, 1, 2) else: points = np.array([x, y]).T.reshape(-1, 1, 2) lwidths = np.linspace(lwstart,lwend,len(x_nonan)) cmap = plt.get_cmap('copper') #my_cmap = truncate_colormap(cmap,gshift/ga[-1],cmapmax) my_cmap = truncate_colormap(cmap,cmapmin,cmapmax) segments = np.concatenate([points[:-1], points[1:]], axis=1) lc = LineCollection(segments, linewidths=lwidths,cmap=my_cmap, norm=plt.Normalize(0.0, 1.0),zorder=zorder) #points = np.array([x, y]).T.reshape(-1, 1, 2) #segments = np.concatenate([points[:-1], points[1:]], axis=1) #lc = LineCollection(segments, cmap=plt.get_cmap('copper'), # linewidths=1+np.linspace(0,1,len(x)-1) # #norm=plt.Normalize(0, 1) #) lc.set_array(np.sqrt(x**2+y**2)) #lc.set_array(y) return lc def collect3d(v1a,ga,v2a,use_nonan=True): """ set desired line properties """ v1a = np.real(v1a) ga = np.real(ga) v2a = np.real(v2a) # remove nans for linewidth stuff later. ga_nonan = ga[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] v1a_nonan = v1a[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] v2a_nonan = v2a[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] if use_nonan: sol = np.zeros((len(ga_nonan),3)) sol[:,0] = v1a_nonan sol[:,1] = ga_nonan sol[:,2] = v2a_nonan else: sol = np.zeros((len(ga),3)) sol[:,0] = v1a sol[:,1] = ga sol[:,2] = v2a sol = np.transpose(sol) points = np.array([sol[0,:],sol[1,:],sol[2,:]]).T.reshape(-1,1,3) segs = np.concatenate([points[:-1],points[1:]],axis = 1) line3d = Line3DCollection(segs,linewidths=(1.+(v1a_nonan)/(.001+np.amax(v1a_nonan))*6.),colors='k',norm=plt.Normalize(0.0, 1.0)) return line3d def collect3d_colorgrad(v1a,ga,v2a,use_nonan=True,lwstart=1.,lwend=5.,zorder=1.,cmapmin=0.,cmapmax=1.): """ set desired line properties. with color gradient. and width denotes g value """ v1a = np.real(v1a) ga = np.real(ga) v2a = np.real(v2a) # remove nans for linewidth stuff later. ga_nonan = ga[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] v1a_nonan = v1a[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] v2a_nonan = v2a[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] if use_nonan: sol = np.zeros((len(ga_nonan),3)) sol[:,0] = v1a_nonan sol[:,1] = ga_nonan sol[:,2] = v2a_nonan else: sol = np.zeros((len(ga),3)) sol[:,0] = v1a sol[:,1] = ga sol[:,2] = v2a sol = np.transpose(sol) points = np.array([sol[0,:],sol[1,:],sol[2,:]]).T.reshape(-1,1,3) segs = np.concatenate([points[:-1],points[1:]],axis = 1) # shift width and colormap #lwidths = (1.+(ga_nonan-gshift)/(.001+np.amax(ga_nonan-gshift))*lwfactor) lwidths = np.linspace(lwstart,lwend,len(ga_nonan)) cmap = plt.get_cmap('copper') #my_cmap = truncate_colormap(cmap,gshift/ga[-1],cmapmax) my_cmap = truncate_colormap(cmap,cmapmin,cmapmax) line3d = Line3DCollection(segs,linewidths=lwidths, cmap=my_cmap,zorder=zorder) line3d.set_array(ga_nonan) return line3d def clean(x,y,smallscale=False,tol=.5): if smallscale: tol = .5 else: tol = tol pos = np.where(np.abs(np.diff(y)) >= tol)[0] pos2 = np.where(np.abs(np.diff(x)) >= tol)[0] x[pos] = np.nan y[pos] = np.nan x[pos2] = np.nan y[pos2] = np.nan return x,y def clean3d(x,y,z,smallscale=False,tol=.5): if smallscale: tol = .5 else: tol = tol pos = np.where(np.abs(np.diff(y)) >= tol)[0] pos2 = np.where(np.abs(np.diff(x)) >= tol)[0] pos3 = np.where(np.abs(np.diff(z)) >= tol)[0] x[pos] = np.nan y[pos] = np.nan z[pos] = np.nan x[pos2] = np.nan y[pos2] = np.nan z[pos2] = np.nan x[pos3] = np.nan y[pos3] = np.nan z[pos3] = np.nan return x,y,z def remove_redundant(x,y,tol=.01): pos = np.where(np.abs(np.diff(y)) < tol)[0] pos2 = np.where(np.abs(np.diff(x)) < tol)[0] x[pos] = np.nan y[pos] = np.nan x[pos2] = np.nan y[pos2] = np.nan return x,y def remove_redundant_x(x,y,tol=.01): pos = np.where(np.abs(np.diff(x)) < tol)[0] x[pos] = np.nan y[pos] = np.nan return x,y def remove_redundant_y(x,y,tol=.01): pos2 = np.where(np.abs(np.diff(x)) < tol)[0] x[pos2] = np.nan y[pos2] = np.nan return x,y def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100): #http://stackoverflow.com/questions/18926031/how-to-extract-a-subset-of-a-colormap-as-a-new-colormap-in-matplotlib new_cmap = colors.LinearSegmentedColormap.from_list( 'trunc({n},{a:.2f},{b:.2f})'.format(n=cmap.name, a=minval, b=maxval), cmap(np.linspace(minval, maxval, n))) return new_cmap def unlink_wrap(dat, lims=[-np.pi, np.pi], thresh = 0.95): # http://stackoverflow.com/questions/27138751/preventing-plot-joining-when-values-wrap-in-matplotlib-plots """ Iterate over contiguous regions of `dat` (i.e. where it does not jump from near one limit to the other). This function returns an iterator object that yields slice objects, which index the contiguous portions of `dat`. This function implicitly assumes that all points in `dat` fall within `lims`. """ jump = np.nonzero(np.abs(np.diff(dat)) > ((lims[1] - lims[0]) * thresh))[0] lasti = 0 for ind in jump: yield slice(lasti, ind + 1) lasti = ind + 1 yield slice(lasti, len(dat)) def ss_bump_fig(): """ plot steady-state bumps with arrows to bump peaks """ fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121) dat = oned_simple.SimDat() ax1.set_title(r'\textbf{(a)}',x=0,y=1.02) ax1.set_xlabel(r'$x$') ax1.set_ylabel(r'\textbf{Activity}') ax1.plot(dat.domain-pi,np.roll(dat.u0b(dat.domain),dat.N/2),color='black',lw=3) # label peak 1d ax1.scatter(0,np.amax(dat.u0b(dat.domain)),edgecolor='black',facecolor='red',s=80,zorder=3) ax1.annotate(r'$\theta$', xy=(0, np.amax(dat.u0b(dat.domain))+.02), xycoords='data', xytext=(0, 30), textcoords='offset points', arrowprops=dict(arrowstyle="->") ) # add text to peak ax1.set_xlim(-pi,pi) ax1.set_ylim(-1,1) ax2 = fig.add_subplot(122, projection='3d') dat = twod.SimDat() ax2 = twod.plot_s(ax2,dat.u0ss) # get/label peak 2d idx = np.argmax(np.reshape(dat.u0ss,dat.N_idx)) peak_z = np.reshape(dat.u0ss,dat.N_idx)[idx] peak_x = np.reshape(dat.XX,dat.N_idx)[idx] peak_y = np.reshape(dat.YY,dat.N_idx)[idx] #ax2.scatter(peak_x+0.,peak_y+0.,peak_z,s=80,edgecolor='black',facecolor='white',zorder=1) ax2.plot([peak_x,peak_x],[peak_y,peak_y],[peak_z,peak_z+.01],marker='o',markersize=8,markeredgecolor='black',markerfacecolor='red',color='red',zorder=1) # http://stackoverflow.com/questions/10374930/matplotlib-annotating-a-3d-scatter-plot x2, y2, _ = proj3d.proj_transform(peak_x,peak_y,peak_z+.14,ax2.get_proj()) ax2.annotate(r'$(\theta_1,\theta_2)$', xy=(x2,y2), xycoords='data', xytext=(0, 30), textcoords='offset points', arrowprops=dict(arrowstyle="->") ) ax2.set_title(r'\textbf{(b)}',x=0,y=1.1) ax2.set_xlabel(r'$x$') ax2.set_ylabel(r'$y$') # add text to peak plt.tight_layout() return fig def oned_const_vel_bump(g=3.5,total=10000): """ make figure for traveling bump """ dat = oned_simple.SimDat(g=g,q=0,zshift=.1,T=total) # get four bumps at four equal time intervals. use second half of sim, # use velocity to determine time intervals # Peaks of phase plot over time are at pi. # using second half of solution, subtract -(pi-.8*pi), find index of min fig = plt.figure(figsize=(5,5)) ax = fig.add_subplot(111) ax.set_xlabel(r'$x$') ax.set_ylabel('t') #start_idx = len(dat.t)/2. #end_idx = int(1.5*start_idx) total_time_idx = dat.t[-1]/dat.dt pad = 10 start_idx = np.argmin(np.mod(dat.ph_angle[total_time_idx/2:]+pi,2*pi)-pi)+total_time_idx/2+pad/2 print start_idx edge_travel_time = (dat.b - dat.a)/dat.c_num # time it takes to go from -pi to pi edge_travel_idx = edge_travel_time/dat.dt-pad # total indices of travel time wraps = 5 end_idx = start_idx+pad + wraps*(edge_travel_idx+pad) #idx = np.arange(start_idx,end_idx+1,1,dtype='int') cax = ax.matshow(np.roll(dat.sol[start_idx:end_idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) fig.colorbar(cax) ax.xaxis.tick_bottom() ax.xaxis.set_label_position('bottom') for i in range(wraps): start_temp = start_idx+i*edge_travel_idx + pad*i end_temp = start_idx+(i+1)*edge_travel_idx idx_temp = np.arange(start_temp,end_temp+1,1,dtype='int') ax.plot(dat.ph_angle[idx_temp],np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),lw=3,color='black') ax.plot(-(np.mod(dat.solph[idx_temp+578,0]+pi,2*pi)-pi),np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),ls='--',lw=2,color='.65') print 'shifted oned const vel analytic by', 578, 'with dt=',dat.dt ax.set_aspect('auto') ax.set_xlim(-pi,pi) ax.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax.set_xticklabels(x_label) plt.tight_layout() return fig def oned_nonconst_vel_bump(g=3.,q=1.,shift=-700,sign=1,total=10000): """ make figure for traveling bump """ dat = oned_simple.SimDat(g=g,q=q,zshift=.1,T=total) # period is approx 525 time units fig = plt.figure(figsize=(5,5)) ax = fig.add_subplot(111) ax.set_xlabel(r'$x$') ax.set_ylabel('t') start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') cax = ax.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) fig.colorbar(cax) ax.xaxis.tick_bottom() ax.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) for slc in unlink_wrap(dat.ph_angle[idx]): ax.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign for slc in unlink_wrap(modsolph): ax.plot(modsolph[slc],timearr[slc],ls='--',color='.65',lw=2) #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax.set_aspect('auto') ax.set_xlim(-pi,pi) ax.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax.set_xticklabels(x_label) """ ax.set_title('(b)',x=-.13) ax.set_xlabel(r'$t$') ax.set_ylabel(r'$\theta$') idx_beginning = int(dat.t[-1]/(1.2*dat.dt)) ax.plot(dat.t[idx_beginning:],dat.ph_angle[idx_beginning:],color='black',lw=2) ax.plot(dat.t[idx_beginning:],-(np.mod(dat.solph[idx_beginning:,0]+pi,2*pi)-pi),color='gray',ls='--',lw=2) """ plt.tight_layout() return fig def oned_bump_combined(): """ display all 1d traveling bump figures in one. """ fig = plt.figure(figsize=(10,4)) """ oned_const_vel #(oned_const_vel_bump,[],['oned_const_vel_bump_fig.pdf']), """ ######################################################################################### ax1 = fig.add_subplot(131) dat = oned_simple.SimDat(g=3.5,q=0.,zshift=.1,T=10000,phase=True) ax1.set_xlabel(r'$x$') ax1.set_ylabel('$t$') ax1.set_title(r"\textbf{(a)}",x=0) #start_idx = len(dat.t)/2. #end_idx = int(1.5*start_idx) total_time_idx = dat.t[-1]/dat.dt pad = 10 start_idx = np.argmin(np.mod(dat.ph_angle[total_time_idx/2:]+pi,2*pi)-pi)+total_time_idx/2+pad/2 print start_idx edge_travel_time = (dat.b - dat.a)/dat.c_num # time it takes to go from -pi to pi edge_travel_idx = edge_travel_time/dat.dt-pad # total indices of travel time wraps = 5 end_idx = start_idx+pad + wraps*(edge_travel_idx+pad) #idx = np.arange(start_idx,end_idx+1,1,dtype='int') cax = ax1.matshow(np.roll(dat.sol[start_idx:end_idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax1.xaxis.tick_bottom() ax1.xaxis.set_label_position('bottom') for i in range(wraps): start_temp = start_idx+i*edge_travel_idx + pad*i end_temp = start_idx+(i+1)*edge_travel_idx idx_temp = np.arange(start_temp,end_temp+1,1,dtype='int') ax1.plot(dat.ph_angle[idx_temp],np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),lw=3,color='black') ax1.plot(-(np.mod(dat.solph[idx_temp+578,0]+pi,2*pi)-pi),np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),ls='--',lw=2,color='#3399ff') print 'shifted oned const vel analytic by', 578, 'with dt=',dat.dt ax1.set_aspect('auto') ax1.set_xlim(-pi,pi) ax1.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax1.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax1.set_xticklabels(x_label) ######################################################################################### """ ### oned_nonconst_vel1 #(oned_nonconst_vel_bump,[],['oned_nonconst_vel_bump_fig.pdf']), """ ax2 = fig.add_subplot(132) dat = oned_simple.SimDat(g=3.,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units shift = -1800 sign = 1 ax2.set_xlabel(r'$x$') ax2.set_title(r"\textbf{(b)}",x=0) #ax2.set_ylabel(r'$t$') start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') cax = ax2.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax2.xaxis.tick_bottom() ax2.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) for slc in unlink_wrap(dat.ph_angle[idx]): ax2.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign for slc in unlink_wrap(modsolph): ax2.plot(modsolph[slc],timearr[slc],ls='--',lw=2,color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax2.set_aspect('auto') ax2.set_xlim(-pi,pi) ax2.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax2.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax2.set_xticklabels(x_label) ######################################################################################### """ ### oned_nonconst_vel2 #(oned_nonconst_vel_bump,[5.5,1.,-950,-1],['oned_nonconst_vel_bump_fig2.pdf']), """ sign = -1 shift = -950 ax3 = fig.add_subplot(133) dat = oned_simple.SimDat(g=5.5,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units ax3.set_xlabel(r'$x$') ax3.set_title(r"\textbf{(c)}",x=0) start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') cax = ax3.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) fig.colorbar(cax) ax3.xaxis.tick_bottom() ax3.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) for slc in unlink_wrap(dat.ph_angle[idx]): ax3.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign for slc in unlink_wrap(modsolph): ax3.plot(modsolph[slc],timearr[slc],ls='--',lw=2,color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax3.set_aspect('auto') ax3.set_xlim(-pi,pi) ax3.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax3.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax3.set_xticklabels(x_label) #ax3.set_yticklabels([]) plt.tight_layout() return fig def oned_pitchfork(g0=.1,g1=2.5,N=50): """ get figure for 1d pitchfork bifurcation """ fig = plt.figure(figsize=(5,3)) ax = fig.add_subplot(111) ax.set_xlabel(r'$g$') ax.set_ylabel('Bump Velocity') glist = np.linspace(g0,g1,N) an_arr_plus = np.zeros(N) # analytic speed num_arr_plus = np.zeros(N) # numerical speed an_arr_minus = np.zeros(N) # analytic speed num_arr_minus = np.zeros(N) # numerical speed num_arr_zero = np.zeros(N) for i,g in enumerate(glist): dat = oned_simple.SimDat(g=g,q=0,zshift=.1) dat2 = oned_simple.SimDat(g=g,q=0,zshift=-.1) dat3 = oned_simple.SimDat(g=g,q=0,zshift=0.) dat.params() an_arr_plus[i] = dat.c_theory_eqn an_arr_minus[i] = -dat2.c_theory_eqn num_arr_plus[i] = dat.c_num num_arr_minus[i] = dat2.c_num ax.plot(glist,num_arr_plus,lw=3,color='black') ax.plot(glist,num_arr_minus,lw=3,color='black') ax.plot(glist,an_arr_plus,lw=2,linestyle='--',color='gray') #ax.scatter(glist,num_arr_plus,marker='x',s=80,color='black') ax.plot(glist,an_arr_minus,lw=2,linestyle='--',color='gray') #ax.scatter(glist,num_arr_minus,marker='x',s=80,color='black') ax.plot(glist,np.zeros(N),lw=2,linestyle='--',color='gray') ax.set_xlim(g0,g1) return fig def oned_hopf(g0=1,g1=3.5,N=50): """ Get limsup of simulation https://stackoverflow.com/questions/35149843/running-max-limsup-in-numpy-what-optimization/35150222#35150222?newreg=d630fa97367849d39f64defea1386dd2 limsup code doesn't work as expected """ # get index of peaks., get values of peaks. take last value. fig = plt.figure(figsize=(5,3)) ax = fig.add_subplot(111) ax.set_xlabel(r'$g$') ax.set_ylabel('Oscillation Amplitude') glist = np.linspace(g0,g1,N) amp_num_plus = np.zeros(N) # numerical amplitude amp_ana_plus = np.zeros(N) # analytic amplitude amp_num_minus = np.zeros(N) # numerical amplitude amp_ana_minus = np.zeros(N) # analytic amplitude for i,g in enumerate(glist): dat = oned_simple.SimDat(g=g,q=1,zshift=.1,T=20000) dat.params() dat.plot('phase_angle') #plt.show() # get peak indices #get amplitude of last 20% of data N_num = len(dat.ph_angle) N_ana = len(dat.solph[:,0]) amp_num_plus[i] = np.amax(dat.ph_angle[int(.8*N_num):]) amp_ana_plus[i] = np.amax(dat.solph[:,0][int(.8*N_ana):]) amp_num_minus[i] = np.amin(dat.ph_angle[int(.8*N_num):]) amp_ana_minus[i] = np.amin(dat.solph[:,0][int(.8*N_ana):]) """ dsol_num = np.gradient(dat.ph_angle) dsol_ana = np.gradient(dat.solph[:,0]) peak_idx_num = np.where(np.diff(np.sign(dsol_num)))[0][-1] peak_idx_ana = np.where(np.diff(np.sign(dsol_ana)))[0][-1] print peak_idx_num print peak_idx_ana # peak values. get last peak. amp_num[i] = dat.ph_angle[peak_idx_num] amp_ana[i] = dat.solph[:,0][peak_idx_ana] """ ax.plot(glist,amp_num_plus,lw=3,color='black') ax.plot(glist,amp_num_minus,lw=3,color='black') #ax.scatter(glist,num_arr_plus,marker='x',s=80,color='black') ax.plot(glist,amp_ana_plus,lw=2,linestyle='--',color='gray') ax.plot(glist,amp_ana_minus,lw=2,linestyle='--',color='gray') ax.set_xlim(g0,g1) return fig def oned_bifurcations(): """ combined hopf and pitchfork figure functions from above """ fig = plt.figure(figsize=(10,4)) subtitle_shift = -.0 subtitle_shift_y = 1.05 g0=.1;g1=2.5;N=50 ax1 = fig.add_subplot(121) ax1.set_title(r'\textbf{(a)}',x=subtitle_shift,y=subtitle_shift_y,fontsize=20) ax1.set_xlabel(r'$g$') ax1.set_ylabel('Bump Velocity') glist = np.linspace(g0,g1,N) an_arr_plus = np.zeros(N) # analytic speed num_arr_plus = np.zeros(N) # numerical speed an_arr_minus = np.zeros(N) # analytic speed num_arr_minus = np.zeros(N) # numerical speed num_arr_zero = np.zeros(N) for i,g in enumerate(glist): dat = oned_simple.SimDat(g=g,q=0,zshift=.1) dat2 = oned_simple.SimDat(g=g,q=0,zshift=-.1) dat3 = oned_simple.SimDat(g=g,q=0,zshift=0.) dat.params() an_arr_plus[i] = dat.c_theory_eqn an_arr_minus[i] = -dat2.c_theory_eqn num_arr_plus[i] = dat.c_num num_arr_minus[i] = dat2.c_num del dat,dat2,dat3 ax1.plot(glist,num_arr_plus,lw=3,color='black') ax1.plot(glist,num_arr_minus,lw=3,color='black') ax1.plot(glist,an_arr_plus,lw=2,linestyle='--',color='gray') ax1.plot(glist,an_arr_minus,lw=2,linestyle='--',color='gray') ax1.plot(glist,np.zeros(N),lw=2,linestyle='--',color='gray') ax1.set_xlim(g0,g1) g0=1;g1=3.5;N=50 ax = fig.add_subplot(122) ax.set_title(r'\textbf{(b)}',x=subtitle_shift,y=subtitle_shift_y,fontsize=20) ax.set_xlabel(r'$g$') ax.set_ylabel('Oscillation Amplitude') glist = np.linspace(g0,g1,N) amp_num_plus = np.zeros(N) # numerical amplitude amp_ana_plus = np.zeros(N) # analytic amplitude amp_num_minus = np.zeros(N) # numerical amplitude amp_ana_minus = np.zeros(N) # analytic amplitude for i,g in enumerate(glist): dat = oned_simple.SimDat(g=g,q=1,zshift=.1,T=20000) dat.params() dat.plot('phase_angle') #plt.show() # get peak indices #get amplitude of last 20% of data N_num = len(dat.ph_angle) N_ana = len(dat.solph[:,0]) amp_num_plus[i] = np.amax(dat.ph_angle[int(.8*N_num):]) amp_ana_plus[i] = np.amax(dat.solph[:,0][int(.8*N_ana):]) amp_num_minus[i] = np.amin(dat.ph_angle[int(.8*N_num):]) amp_ana_minus[i] = np.amin(dat.solph[:,0][int(.8*N_ana):]) del dat ax.plot(glist,amp_num_plus,lw=3,color='black') ax.plot(glist,amp_num_minus,lw=3,color='black') #ax.scatter(glist,num_arr_plus,marker='x',s=80,color='black') ax.plot(glist,amp_ana_plus,lw=2,linestyle='--',color='gray') ax.plot(glist,amp_ana_minus,lw=2,linestyle='--',color='gray') ax.set_xlim(g0,g1) return fig def twod_full_fig(q=1,g=3.,zshift_angle=pi/4.,zshift_rad=.3,T=5000,factor=.5,increment=13): """ peak dynamics of full model """ print 'initial angle',zshift_angle,'inital rad',zshift_rad #ushift1=1.;ushift2=1. zshift1=ushift1-zshift_rad*np.cos(zshift_angle);zshift2=ushift2-zshift_rad*np.sin(zshift_angle) ishift1=0.;ishift2=0. ushift1=0. ushift2=0. #zshift1 = ushift1+.5#-.1 #zshift2 = ushift2+1.#-.1 eps = .005 dat = twod.SimDat(q=q,g=g,T=T,zshift1=zshift1,zshift2=zshift2,ushift1=ushift1,ushift2=ushift2,eps=eps) # remove first half of sim to ignore transients start_idx = int(dat.TN*factor) total_idx = dat.TN - start_idx fig = plt.figure(figsize=(5,5)) ax = fig.add_subplot(111) arrow_idx_increment = total_idx/increment back_idx = 2 for i in range(start_idx,dat.TN-1): color = ((1.*total_idx - (i-start_idx))/total_idx)*.75 if i%arrow_idx_increment == 0: ax.annotate("", xy=(dat.th1[i], dat.th2[i]), xycoords='data', xytext=(dat.th1[i-back_idx], dat.th2[i-back_idx]), textcoords='data', size=22, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color=str(color)), ) #print color #ax.scatter(dat.th1[i],dat.th2[i],edgecolors='none',facecolors=str(color),s=(1-color)*30) #colors = np.arange(75,0,len(dat.th1[1:-1])) colors = np.linspace(.85,0.,len(dat.th1[start_idx:-1])) cmap = plt.get_cmap('gray') my_cmap = truncate_colormap(cmap,.0,.75) #my_cmap.set_under('w') size = (1-colors)*30 #ax.set_title('g='+str(g)+'; q='+str(q)+'; eps='+str(eps)) ax.scatter(dat.th1[start_idx:-1],dat.th2[start_idx:-1],edgecolors='none',c=colors,s=size,cmap=my_cmap) ax.scatter(dat.th1[-1],dat.th2[-1],marker="*",color='black',s=200,facecolors='white') ax.scatter(dat.th1[start_idx],dat.th2[start_idx],marker="o",color='black',s=50,facecolors='white') ax.set_xlim(-pi,pi) ax.set_ylim(-pi,pi) ax.set_xlabel(r'$\theta_1$') ax.set_ylabel(r'$\theta_2$') ax.set_xticks(np.arange(-1,1+.5,.5)*pi) ax.set_yticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] ax.set_xticklabels(x_label) ax.set_yticklabels(x_label) del dat return fig def twod_phase_fig(q=1,g=4.2,T=104,factor=.71,increment=13,phase_option='approx'): """ peak dynamics of phase model. full or approx. """ ph = twodp.Phase(q=q,x0=1,y0=.01,g=g,dde_T=T,phase_option=phase_option) # remove first half of sim to ignore transients start_idx = int(ph.dde_TN*factor) total_idx = ph.dde_TN - start_idx arrow_idx_increment = total_idx/increment back_idx = 1 fig = plt.figure(figsize=(5,5)) ax = fig.add_subplot(111) th1 = np.mod(ph.th1+pi,2*pi)-pi th2 = np.mod(ph.th2+pi,2*pi)-pi for i in range(start_idx,ph.dde_TN-1): color = ((1.*total_idx - (i-start_idx))/total_idx)*.75 if i%arrow_idx_increment == 0: ax.annotate("", xy=(th1[i], th2[i]), xycoords='data', xytext=(th1[i-back_idx], th2[i-back_idx]), textcoords='data', size=22, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color=str(color)), ) #print color #ax.scatter(ph.th1[i],ph.th2[i],edgecolors='none',facecolors=str(color),s=(1-color)*30) # for speedup consider using http://stackoverflow.com/questions/17682216/scatter-plot-and-color-mapping-in-python colors = np.linspace(.75,0.,len(ph.th1[start_idx:-1])) cmap = plt.get_cmap('gray') my_cmap = truncate_colormap(cmap,.0,.75) size = (1-colors)*30 ax.scatter(th1[start_idx:-1],th2[start_idx:-1],edgecolors='none',c=colors,s=size,cmap=my_cmap) ax.scatter(th1[-1],th2[-1],marker="*",color='black',s=200,facecolors='white') ax.scatter(th1[start_idx],th2[start_idx],marker="o",color='black',s=50,facecolors='white') ax.set_xlim(-pi,pi) ax.set_ylim(-pi,pi) ax.set_xlabel(r'$\theta_1$') ax.set_ylabel(r'$\theta_2$') ax.set_xticks(np.arange(-1,1+.5,.5)*pi) ax.set_yticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] ax.set_xticklabels(x_label) ax.set_yticklabels(x_label) del ph return fig def combined_phase_fig(option ="limit_cycle"): """ plot all three 2D full, 2D phase, 2D phase approx at once. """ r0=1.;nu0=.01 ushift1=0. ushift2=0. zshift_rad=.8;zshift_angle=pi/3.5 zshift1=ushift1-zshift_rad*np.cos(zshift_angle);zshift2=ushift2-zshift_rad*np.sin(zshift_angle) ishift1=0.;ishift2=0. #zshift1 = ushift1+.4#-.1 #zshift2 = ushift2+1.#-.1 fig = plt.figure(figsize=(15,5)) cmap = plt.get_cmap('gray') my_cmap = truncate_colormap(cmap,.0,.75) if option == "const": full_q=0;full_g=3;full_T=7000 full_factor=.4;full_increment=13 ph_full_q=0;ph_full_g=2.2;ph_full_dde_T=200 ph_full_factor=.9;ph_full_increment=12 ph_approx_q=0;ph_approx_g=3;ph_approx_dde_T=100 ph_approx_factor=.8;ph_approx_increment=13 elif option == "limit_cycle": #(twod_full_fig, [2.,5.,5000,.84,13],['twod_full_fig_q=2_g=5.pdf']), #(twod_phase_fig,[1.,4.,300,.0,20,'full'],['twod_phase_full_fig_test']), #(twod_phase_fig,[1.,4.,110,.956,13,'approx'],['twod_phase_approx_fig_q=1_g=4.pdf']), full_q=2;full_g=5;full_T=5000 full_factor=.84;full_increment=13 ph_full_q=1;ph_full_g=3.;ph_full_dde_T=110 ph_full_factor=.949;ph_full_increment=7 ph_approx_q=1;ph_approx_g=3;ph_approx_dde_T=110 ph_approx_factor=.953;ph_approx_increment=6 elif option == "non_const": #(twod_full_fig, [1.,5.,5000,.45,13],['twod_full_fig_q=1_g=5.pdf']), #(twod_phase_fig,[1.,5.,100,.85,5,'approx'],['twod_phase_approx_fig_q=1_g=5.pdf']), #(twod_phase_fig,[1.,5.,100,.8,12,'full'],['twod_phase_full_fig_q=1_g=5.pdf']), full_q=1;full_g=5;full_T=5000 full_factor=.45;full_increment=13 ph_full_q=1;ph_full_g=5.;ph_full_dde_T=100 ph_full_factor=.85;ph_full_increment=5 ph_approx_q=1;ph_approx_g=5;ph_approx_dde_T=100 ph_approx_factor=.8;ph_approx_increment=12 dat = twod.SimDat(q=full_q,g=full_g,T=full_T,zshift1=zshift1,zshift2=zshift2,ushift1=ushift1,ushift2=ushift2) ph_full = twodp.Phase(q=ph_full_q,x0=r0,y0=nu0,g=ph_full_g,dde_T=ph_full_dde_T,phase_option='full') ph_approx = twodp.Phase(q=ph_approx_q,x0=r0,y0=nu0,g=ph_approx_g,dde_T=ph_approx_dde_T,phase_option='approx') subtitle_shift = -.0 subtitle_shift_y = 1.05 ## Plot full ax1 = fig.add_subplot(131) ax1.set_title(r"\textbf{(a)}",x=subtitle_shift,y=subtitle_shift_y,fontsize=20) # remove first half of sim to ignore transients start_idx = int(dat.TN*full_factor) total_idx = dat.TN - start_idx arrow_idx_increment = total_idx/full_increment back_idx = 2 for i in range(start_idx,dat.TN-1): color = ((1.*total_idx - (i-start_idx))/total_idx)*.75 if i%arrow_idx_increment == 0: ax1.annotate("", xy=(dat.th1[i], dat.th2[i]), xycoords='data', xytext=(dat.th1[i-back_idx], dat.th2[i-back_idx]), textcoords='data', size=22, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color=str(color)), ) colors = np.linspace(.85,0.,len(dat.th1[start_idx:-1])) #my_cmap.set_under('w') size = (1-colors)*30 #ax.set_title('g='+str(g)+'; q='+str(q)+'; eps='+str(eps)) ax1.scatter(dat.th1[start_idx:-1],dat.th2[start_idx:-1],edgecolors='none',c=colors,s=size,cmap=my_cmap) ax1.scatter(dat.th1[-1],dat.th2[-1],marker="*",color='black',s=200,facecolors='white') ax1.scatter(dat.th1[start_idx],dat.th2[start_idx],marker="o",color='black',s=50,facecolors='white') ax1.set_xlim(-pi,pi) ax1.set_ylim(-pi,pi) ax1.set_xlabel(r'$\theta_1$',fontsize=20) ax1.set_ylabel(r'$\theta_2$',fontsize=20) ax1.set_xticks(np.arange(-1,1+.5,.5)*pi) ax1.set_yticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] ax1.set_xticklabels(x_label,fontsize=20) ax1.set_yticklabels(x_label,fontsize=20) ## Plot phase full ax2 = fig.add_subplot(132) ax2.set_title(r"\textbf{(b)}",x=subtitle_shift,y=subtitle_shift_y,fontsize=20) # remove first half of sim to ignore transients start_idx = int(ph_full.dde_TN*ph_full_factor) total_idx = ph_full.dde_TN - start_idx arrow_idx_increment = total_idx/ph_full_increment back_idx = 1 th1 = np.mod(ph_full.th1+pi,2*pi)-pi th2 = np.mod(ph_full.th2+pi,2*pi)-pi for i in range(start_idx,ph_full.dde_TN-1): color = ((1.*total_idx - (i-start_idx))/total_idx)*.75 if i%arrow_idx_increment == 0: ax2.annotate("", xy=(th1[i], th2[i]), xycoords='data', xytext=(th1[i-back_idx], th2[i-back_idx]), textcoords='data', size=22, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color=str(color)), ) # http://stackoverflow.com/questions/17682216/scatter-plot-and-color-mapping-in-python colors = np.linspace(.75,0.,len(ph_full.th1[start_idx:-1])) size = (1-colors)*30 ax2.scatter(th1[start_idx:-1],th2[start_idx:-1],edgecolors='none',c=colors,s=size,cmap=my_cmap) ax2.scatter(th1[-1],th2[-1],marker="*",color='black',s=200,facecolors='white') ax2.scatter(th1[start_idx],th2[start_idx],marker="o",color='black',s=50,facecolors='white') ax2.set_xlim(-pi,pi) ax2.set_ylim(-pi,pi) ax2.set_xlabel(r'$\theta_1$',fontsize=20) #ax2.set_ylabel(r'$\theta_2$') ax2.set_xticks(np.arange(-1,1+.5,.5)*pi) #ax.set_yticks([]) ax2.set_xticklabels(x_label,fontsize=20) ax2.set_yticklabels([]) ## Plot phase approx ax3 = fig.add_subplot(133) ax3.set_title(r"\textbf{(c)}",x=subtitle_shift,y=subtitle_shift_y,fontsize=20) # remove first half of sim to ignore transients start_idx = int(ph_approx.dde_TN*ph_approx_factor) total_idx = ph_approx.dde_TN - start_idx arrow_idx_increment = total_idx/ph_approx_increment back_idx = 1 th1 = np.mod(ph_approx.th1+pi,2*pi)-pi th2 = np.mod(ph_approx.th2+pi,2*pi)-pi for i in range(start_idx,ph_approx.dde_TN-1): color = ((1.*total_idx - (i-start_idx))/total_idx)*.75 if i%arrow_idx_increment == 0: ax3.annotate("", xy=(th1[i], th2[i]), xycoords='data', xytext=(th1[i-back_idx], th2[i-back_idx]), textcoords='data', size=22, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color=str(color)), ) # http://stackoverflow.com/questions/17682216/scatter-plot-and-color-mapping-in-python colors = np.linspace(.75,0.,len(ph_approx.th1[start_idx:-1])) size = (1-colors)*30 ax3.scatter(th1[start_idx:-1],th2[start_idx:-1],edgecolors='none',c=colors,s=size,cmap=my_cmap) ax3.scatter(th1[-1],th2[-1],marker="*",color='black',s=200,facecolors='white') ax3.scatter(th1[start_idx],th2[start_idx],marker="o",color='black',s=50,facecolors='white') ax3.set_xlim(-pi,pi) ax3.set_ylim(-pi,pi) ax3.set_xlabel(r'$\theta_1$',fontsize=20) #ax2.set_ylabel(r'$\theta_2$') ax3.set_xticks(np.arange(-1,1+.5,.5)*pi) #ax.set_yticks(np.arange(-1,1+.5,.5)*pi) ax3.set_xticklabels(x_label,fontsize=20) ax3.set_yticklabels([]) return fig def HJ_i_fig(): """ plot H_i in first row J_i in second row """ dat = twodp.Phase(recompute_h=False,recompute_j=False) H1,H2 = dat.H1,dat.H2 J1,J2 = dat.J1,dat.J2 fig = plt.figure(figsize=(10,10)) subtitle_shift = -.0 ax11 = fig.add_subplot(2,2,1,projection='3d') ax11.set_title(r'\textbf{(a)}',x=subtitle_shift) #ax11.set_title(r"$H_1$") ax11 = twod.plot_s(ax11,H1) ax11.set_zlabel(r'$H_1$') ax12 = fig.add_subplot(2,2,2,projection='3d') ax12.set_title(r'\textbf{(b)}',x=subtitle_shift) #ax12.set_title(r"$H_2$") ax12 = twod.plot_s(ax12,H2) ax12.set_zlabel(r'$H_2$') ax21 = fig.add_subplot(2,2,3,projection='3d') ax21.set_title(r'\textbf{(c)}',x=subtitle_shift) #ax21.set_title(r"$J_1$") ax21 = twod.plot_s(ax21,J1) ax21.set_zlabel(r'$J_1$') ax22 = fig.add_subplot(2,2,4,projection='3d') ax22.set_title(r'\textbf{(d)}',x=subtitle_shift) #ax22.set_title(r"$J_2$") ax22 = twod.plot_s(ax22,J2) ax22.set_zlabel(r'$J_2$') plt.tight_layout() return fig def HJ_fig(): """ plot H in first row J in second row """ dat = oned_simple.SteadyState() #dat.plot('J') #dat.plot('H') #plt.show() fig = plt.figure(figsize=(10,3)) subtitle_shift = -0.05 subtitle_shift_y = 1.1 ax11 = fig.add_subplot(1,2,1) ax11.set_title(r'\textbf{(a)}',x=subtitle_shift,y=subtitle_shift_y,fontsize=20) newdom = np.linspace(-pi,pi,dat.N) ax11.plot(newdom,np.roll(dat.H_numerical,dat.N/2),color='black',lw=4,label='H') ax11.plot(newdom,np.roll(dat.H(dat.domain),dat.N/2),color='#3399ff',ls='--',lw=3,label='H approx.') ax11.tick_params(labelsize=15) #plot.tick_params(axis='both', which='major', labelsize=10) ax11.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] ax11.set_xticklabels(x_label,fontsize=15) ax11.set_xlim(-pi,pi) ax11.legend(loc=4) ax12 = fig.add_subplot(1,2,2) ax12.set_title(r'\textbf{(b)}',x=subtitle_shift,y=subtitle_shift_y,fontsize=20) ax12.plot(newdom,np.roll(dat.J_numerical,dat.N/2),color='black',lw=4,label='J') ax12.plot(newdom,np.roll(dat.J(dat.domain),dat.N/2),color='#3399ff',ls='--',lw=3,label='J approx.') ax12.tick_params(labelsize=15) ax12.set_xticks(np.arange(-1,1+.5,.5)*pi) ax12.set_xticklabels(x_label,fontsize=15) ax12.set_xlim(-pi,pi) ax12.legend(loc=3) plt.tight_layout() return fig def H_approx_fig(): fig = plt.figure(figsize=(10,10)) subtitle_shift = -.0 dat = twodp.Phase() h1_approx_p = dat.h1_approx_p(dat.XX,dat.YY) h2_approx_p = dat.h2_approx_p(dat.XX,dat.YY) dat2 = twodp.Phase(recompute_h=False,recompute_j=False) H1 = dat2.H1 J1 = dat2.J1 ax11 = fig.add_subplot(2,2,1,projection='3d') ax11 = twod.plot_s(ax11,h1_approx_p) ax11.set_title(r'\textbf{(a)}',x=subtitle_shift) ax11.set_zlabel(r'$\hat H_1$') ax12 = fig.add_subplot(2,2,2,projection='3d') ax12 = twod.plot_s(ax12,-h1_approx_p) ax12.set_title(r'\textbf{(b)}',x=subtitle_shift) ax12.set_zlabel(r'$\hat J_1$') ax21 = fig.add_subplot(2,2,3,projection='3d') ax21 = twod.plot_s(ax21,H1) ax21.set_title(r'\textbf{(c)}',x=subtitle_shift) ax21.set_zlabel(r'$H_1$') ax22 = fig.add_subplot(2,2,4,projection='3d') ax22 = twod.plot_s(ax22,J1) ax22.set_title(r'\textbf{(d)}',x=subtitle_shift) ax22.set_zlabel(r'$J_1$') return fig def H_approx_nullclines(): """ plot level curves z=0. intersections denote existence of limit cycles. """ ncx = np.loadtxt("nc_phase_approx_q=0.5_g=1.5_x_mesh=100.dat") ncy = np.loadtxt("nc_phase_approx_q=0.5_g=1.5_y_mesh=100.dat") #ncx = np.loadtxt("nc_phase_approx_q=1_g=3_x_mesh100.dat") #ncy = np.loadtxt("nc_phase_approx_q=1_g=3_y_mesh100.dat") fig = plt.figure(figsize=(10,5)) ax = fig.add_subplot(131) #ncy[:,0] = np.sort(ncy[:,0]) #ncy[:,1] = ncy[:,1][np.argsort(ncy[:,0])] ncy[ncy[:,1]>.85]=np.nan #ncx,ncy = remove_redundant(ncx,ncy,tol=.01) index_to_order_x_by = ncx[:,1].argsort() index_to_order_y_by = ncy[:,0].argsort() ncx_ordered = ncx[index_to_order_x_by] ncy_ordered = ncy[index_to_order_y_by] #ncx = np.loadtxt("nc_phase_approx_q=1_g=3_x_mesh100.dat") #ncy = np.loadtxt("nc_phase_approx_q=1_g=3_y_mesh100.dat") #ncy[:,0] = np.sort(ncy[:,0]) #ncy[:,1] = ncy[:,1][np.argsort(ncy[:,0])] #ax2.scatter(ncx[:,0],ncx[:,1],edgecolor='none',facecolor='green',s=15) #ax2.scatter(ncy[:,0],ncy[:,1],edgecolor='none',facecolor='blue',s=15) #ax2.plot(ncy[:,0],ncy[:,1],color='blue') ax.plot(ncx_ordered[:,0],ncx_ordered[:,1],color='green',lw=3) ax.plot(ncy_ordered[:,0],ncy_ordered[:,1],color='blue',lw=3) #ax.scatter(ncx[:,0],ncx[:,1],edgecolor='none',facecolor='green',s=15) #ax.scatter(ncy[:,0],ncy[:,1],edgecolor='none',facecolor='blue',s=15) ax.set_xlabel(r'$r$') ax.set_ylabel(r'$\nu$') ax.set_title(r'$g=1.501$') # nullcline intersections (from XPP) r1 = .021405 nu1 = .707 r2 = 1.7474 nu2 = .18074 ax.scatter(r1,nu1,edgecolor='black',facecolor='white',s=60) ax.scatter(r2,nu2,edgecolor='black',facecolor='white',s=60) ax.annotate(r'$r='+str(r1)+r'$ \\ $\nu='+str(nu1)+r'$', xy=(r1+.1, nu1), xycoords='data', xytext=(40, 0), textcoords='offset points', arrowprops=dict(arrowstyle="->", connectionstyle="arc,angleA=0,armA=20,angleB=0,armB=15,rad=10"), ) ax.annotate(r'$r='+str(r2)+r'$ \\ $\nu='+str(nu2)+r'$', xy=(r2-.02, nu2-.02), xycoords='data', xytext=(-60, -40), textcoords='offset points', arrowprops=dict(arrowstyle="->", connectionstyle="arc,angleA=0,armA=20,angleB=-130,armB=15,rad=7"), ) ax.set_xlim(0,2) ax.set_ylim(0,1) ##### #PART 2 #ncx = np.loadtxt("nc_phase_approx_q=0.5_g=1.75_x_mesh=100.dat") #ncy = np.loadtxt("nc_phase_approx_q=0.5_g=1.75_y_mesh=100.dat") ncx = np.loadtxt("nc_phase_approx_q=0.5_g=2_x_mesh=100.dat") ncy = np.loadtxt("nc_phase_approx_q=0.5_g=2_y_mesh=100.dat") ncy[ncy[:,1]>.85]=np.nan #ncx,ncy = remove_redundant(ncx,ncy,tol=.01) index_to_order_x_by = ncx[:,1].argsort() index_to_order_y_by = ncy[:,0].argsort() ncx_ordered = ncx[index_to_order_x_by] ncy_ordered = ncy[index_to_order_y_by] #ncx = np.loadtxt("nc_phase_approx_q=1_g=3_x_mesh100.dat") #ncy = np.loadtxt("nc_phase_approx_q=1_g=3_y_mesh100.dat") ax2 = fig.add_subplot(132) #ncy[:,0] = np.sort(ncy[:,0]) #ncy[:,1] = ncy[:,1][np.argsort(ncy[:,0])] #ax2.scatter(ncx[:,0],ncx[:,1],edgecolor='none',facecolor='green',s=15) #ax2.scatter(ncy[:,0],ncy[:,1],edgecolor='none',facecolor='blue',s=15) #ax2.plot(ncy[:,0],ncy[:,1],color='blue') ax2.plot(ncx_ordered[:,0],ncx_ordered[:,1],color='green',lw=3) ax2.plot(ncy_ordered[:,0],ncy_ordered[:,1],color='blue',lw=3) ax2.set_xlabel(r'$r$') #ax2.set_ylabel(r'$\nu$') ax2.set_title(r'$g=2$') ax2.set_yticklabels([]) # nullcline intersections (from XPP) r1 = 0.59458 nu1 = 0.69031 r2 = 1.4227 nu2 = 0.33135 #r1 = .41087 #nu1 = .70345 #r2 = 1.5752 #nu2 = .25322 ax2.scatter(r1,nu1,edgecolor='black',facecolor='white',s=60) ax2.scatter(r2,nu2,edgecolor='black',facecolor='white',s=60) ax2.annotate(r'$r='+str(r1)+r'$ \\ $\nu='+str(nu1)+r'$', xy=(r1, nu1-.025), xycoords='data', xytext=(-40, -80), textcoords='offset points', arrowprops=dict(arrowstyle="->", connectionstyle="arc,angleA=0,armA=20,angleB=-90,armB=15,rad=10"), ) ax2.annotate(r'$r='+str(1.4928)+r'$ \\ $\nu='+str(0.4808)+'$', xy=(r2-.02, nu2-.02), xycoords='data', xytext=(-60, -40), textcoords='offset points', arrowprops=dict(arrowstyle="->", connectionstyle="arc,angleA=0,armA=20,angleB=-130,armB=15,rad=7"), ) ax2.set_xlim(0,2) ax2.set_ylim(0,.8) ###### ## PART 3 ncx = np.loadtxt("nc_phase_approx_q=0.5_g=2.44_x_mesh=100.dat") ncy = np.loadtxt("nc_phase_approx_q=0.5_g=2.44_y_mesh=100.dat") #ncx = np.loadtxt("nc_phase_approx_q=1_g=3_x_mesh100.dat") #ncy = np.loadtxt("nc_phase_approx_q=1_g=3_y_mesh100.dat") ax3 = fig.add_subplot(133) #ncy[:,0] = np.sort(ncy[:,0]) #ncy[:,1] = ncy[:,1][np.argsort(ncy[:,0])] ax3.scatter(ncx[:,0],ncx[:,1],edgecolor='none',facecolor='green',s=15) ax3.scatter(ncy[:,0],ncy[:,1],edgecolor='none',facecolor='blue',s=15) ax3.set_xlabel(r'$r$') #ax3.set_ylabel(r'$\nu$') ax3.set_title(r'$g=2.44$') ax3.set_yticklabels([]) # nullcline intersections (from XPP) r1 = .41087 nu1 = .70345 r2 = 1.5752 nu2 = .25322 #ax3.scatter(r1,nu1,edgecolor='black',facecolor='white',s=60) #ax3.scatter(r2,nu2,edgecolor='black',facecolor='white',s=60) """ ax2.annotate(r'$r='+str(r1)+r'$ \\ $\nu='+str(nu1)+r'$', xy=(r1, nu1-.05), xycoords='data', xytext=(-30, -50), textcoords='offset points', arrowprops=dict(arrowstyle="->", connectionstyle="arc,angleA=0,armA=20,angleB=-90,armB=15,rad=10"), ) ax2.annotate(r'$r='+str(1.4928)+r'$ \\ $\nu='+str(0.4808)+'$', xy=(r2-.02, nu2-.02), xycoords='data', xytext=(-60, -40), textcoords='offset points', arrowprops=dict(arrowstyle="->", connectionstyle="arc,angleA=0,armA=20,angleB=-90,armB=15,rad=7"), ) """ ax3.set_xlim(0,2) ax3.set_ylim(0,1) return fig def oned_phase_auto(choice='q1'): """ 1d bifurcation diagram of reduced system from auto see 1d.ode """ fig = plt.figure(figsize=(10,5)) ax = fig.add_subplot(121) if choice == 'q1': filelist = ["bif_q1_gvary1.dat","bif_q1_gvary2a.dat","bif_q1_gvary2b.dat","bif_q1_gvary2c.dat"] elif choice == 'q0.5': filelist = ["bif_q0.5_gvary1.dat","bif_q0.5_gvary2a.dat","bif_q0.5_gvary2b.dat","bif_q0.5_gvary_travel.dat"]#,"bif_q0.5_gvary2c.dat"] branchidx = 0 for filename in filelist: # get all branches bif_qg1 = np.loadtxt(filename) branchlist = np.unique(bif_qg1[:,-2]) #if len(bif_qg1[0,:]==6): # branchlist = np.unique(bif_qg1[:,-2]) print branchlist # first branch stabe = False ustabe = False stabp = False ustabp = False for b in branchlist: b_idx = bif_qg1[:,-2] == b typelist = np.unique(bif_qg1[b_idx,-3]) for t in typelist: t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] label = None if t == 1: lw=3;color='red' marker = None if branchidx == 0 and not(stabe): label='Stable Equilibrium' ls = '-' stab = True else: label=None elif t == 2: lw=1;color='black' marker = None if branchidx == 0 and not(ustabe): label='Unstable Equilibrium' ls = '-' ustabe = True else: label=None elif t == 3: lw=3;color='green' #marker = 'o' marker = None if branchidx == 0 and not(stabp): label='Stable Periodic' ls='-' stabp = True else: label=None elif t == 4: lw=1;color='blue' #marker = 'o' marker = None if branchidx == 0 and not(ustabp): label='Unstable Periodic' ls='-' ustabp = True else: label=None #print b,t alpha = 1 me = 5 if filename == "bif_q0.5_gvary_travel.dat": ls = '--' else: ls = '-' if filename == "bif_q1_gvary1.dat" or \ filename == "bif_q0.5_gvary1.dat" or \ filename == "bif_q0.5_gvary2a.dat" or \ filename == "bif_q0.5_gvary2b.dat": ax.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1]+2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1]+2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) if filename == "bif_q1_gvary1.dat" or \ filename == "bif_q0.5_gvary1.dat": ax.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1]-2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1]-2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) """ if filename == "bif_q1_gvary2a.dat" or \ filename == "bif_q0.5_gvary2a.dat" or \ filename == "bif_q0.5_gvary2c.dat": label = None alpha = 0.5 else: alpha = 1. """ if filename == "bif_q0.5_gvary_travel.dat": label = None ax.plot(clean(dat[:,0],dat[:,1])[0],-(clean(dat[:,0],dat[:,1])[1]-2*pi-pi)+pi, lw=lw,color=color,alpha=alpha,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1]-2*pi, lw=lw,color=color,alpha=alpha,label=label,marker=marker,markevery=me,ls=ls) else: ax.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1], lw=lw,color=color,alpha=alpha,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1], lw=lw,color=color,alpha=alpha,label=label,marker=marker,markevery=me,ls=ls) print branchidx, label branchidx += 1 if choice == 'q0.5': ax.annotate("BP",color='teal', xy=(2.36581,1.7138), xycoords='data', xytext=(2, 2.5), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='teal'), ) ax.annotate("HB",color='orange', xy=(1.5,0), xycoords='data', xytext=(1.2, 1.2), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='orange'), ) ax.annotate("LP 2",color='purple', xy=(2.65599, 11.8292-2*pi), xycoords='data', xytext=(2.3, 2*pi-.3), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='purple'), ) #ax.annotate(r"\colorbox{blue!20}{{\color{yellow}LP Large}}", ax.annotate("LP 1", xy=(2.20126, 0.847046), xycoords='data', xytext=(2.7, .40746), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w"), ) # unstable equilib ax.plot([0,5],[pi,pi],color='black') ax.plot([0,5],[-pi,-pi],color='black') # mark bistability ax.plot([2.20126,2.20126],[-10,10],color='black',ls=':') ax.plot([2.34017,2.34017],[-10,10],color='black',ls=':') # labels ax.set_xlabel(r'$\bm{g}$',size=15) ax.set_ylabel(r'$\bm{\theta}$',size=15) # set y axis ticks to multiples of pi ax.set_ylim(-pi-.1,2*pi+.1) ax.set_xlim(0,5) ax.set_yticks(np.arange(-1,2+1.,1.)*pi) #y_label = [r"$-3\pi$", r"$-2\pi$", # r"$-\pi$", r"$0$", # r"$\pi$",r"$2\pi$",r"$3\pi$"] y_label = [r"$-\pi$", r"$0$", r"$\pi$", r"$2\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax.set_yticklabels(y_label) ax.legend(loc='lower left',fontsize=10) """ 2 param bifurcation diagram from auto """ #fig = plt.figure(figsize=(7.5,7.5)) #fig = plt.figure() ax2 = fig.add_subplot(122) namelist = ['BP','HB','LP 2','LP 1'] colorlist = ['teal','orange','purple','black'] filelist = ["bif_gq_bp.dat","bif_gq_hb.dat","bif_gq_lp_travel.dat","bif_gq_lp_large.dat"] ls = ['-', '--', '-.', ':'] i = 0 for filename in filelist: # get all branches bif_qg1 = np.loadtxt(filename) branchlist = np.unique(bif_qg1[:,-2]) #if len(bif_qg1[0,:]==6): # branchlist = np.unique(bif_qg1[:,-2]) print branchlist # first branch bidx = 0 for b in branchlist: b_idx = bif_qg1[:,-2] == b typelist = np.unique(bif_qg1[b_idx,-3]) for t in typelist: t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] if bidx == 0: label = namelist[i] else: label = None ax2.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1], lw=2,color=colorlist[i],label=label,ls=ls[i]) #ax2.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1], # lw=2,color=colorlist[i],label=label) bidx += 1 i += 1 ax2.text(1.5,2.6,'1. Stationary Bump',rotation=0,size=15) ax2.text(3.3,2.5,'2. Wobbling Bump',rotation=37,size=15) ax2.text(3.5,1.55,'3. Bistability',rotation=27,size=15) ax2.text(3.2,.3,'4. Traveling Bump',rotation=0,size=15) ax2.plot([0,5],[.5,.5],color='gray') #ax2.text(1.5,.075,'reminder: added line from g=2 to g=1 for LP2') ax2.legend(loc='upper left',fontsize=10) ax2.set_xlabel(r'$\bm{g}$',size=15) ax2.set_ylabel(r'$\bm{q}$',size=15) ax2.set_xlim(1,5) return fig def draw_branches(ax,filelist,smallscale=False): branchidx = 0 for filename in filelist: # get all branches bif_qg1 = np.loadtxt(filename) branchlist = np.unique(bif_qg1[:,-2]) #if len(bif_qg1[0,:]==6): # branchlist = np.unique(bif_qg1[:,-2]) #print branchlist # first branch stabe = False ustabe = False stabp = False ustabp = False for b in branchlist: b_idx = bif_qg1[:,-2] == b typelist = np.unique(bif_qg1[b_idx,-3]) #print typelist for t in typelist: print 'branch',b,'type',t t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] label = None if t == 1: lw=3;color='red' marker = None if branchidx == 0 and not(stabe): label='Stable Equilibrium' ls = '-' stab = True else: label=None elif t == 2: lw=1;color='black' marker = None if branchidx == 0 and not(ustabe): label='Unstable Equilibrium' ls = '-' ustabe = True else: label=None elif t == 3: lw=3;color='green' #marker = 'o' marker = None if branchidx == 0 and not(stabp): label='Stable Periodic' ls='-' stabp = True else: label=None elif t == 4: lw=1;color='blue' #marker = 'o' marker = None if branchidx == 0 and not(ustabp): label='Unstable Periodic' ls='-' ustabp = True else: label=None #print b,t alpha = 1 me = 5 if (filename == 'bif_full_q0.5_gvary2c.dat') or\ (filename == "bif_full_q0.5_gvary_travel.dat") or\ (filename == "bif_full_a2_q0.5_gvary2.dat") or\ (filename == "bif_full_a3_q0.5_gvary2.dat"): ls='--' else: ls='-' if filename == "bif_full_q1_gvary1.dat" or \ filename == "bif_full_q0.5_gvary1.dat" or \ filename == "bif_full_q0.5_gvary2a.dat" or \ filename == "bif_full_q0.5_gvary2b.dat": ax.plot(clean(dat[:,0],dat[:,1],smallscale=smallscale)[0],clean(dat[:,0],dat[:,1],smallscale=smallscale)[1]+2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2],smallscale=smallscale)[0],clean(dat[:,0],dat[:,2],smallscale=smallscale)[1]+2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) elif filename == "bif_full_q1_gvary1.dat" or \ filename == "bif_full_q0.5_gvary1.dat" or \ filename == "bif_full_q0.5_gvary2c.dat": #print 'gvary_2c',filename ax.plot(clean(dat[:,0],dat[:,1],smallscale=smallscale)[0],clean(dat[:,0],dat[:,1],smallscale=smallscale)[1]-2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2],smallscale=smallscale)[0],clean(dat[:,0],dat[:,2],smallscale=smallscale)[1]-2*pi,lw=lw,color=color,marker=marker,markevery=me,ls=ls) """ if filename == "bif_q1_gvary2a.dat" or \ filename == "bif_q0.5_gvary2a.dat" or \ filename == "bif_q0.5_gvary2c.dat": label = None alpha = 0.5 else: alpha = 1. """ if filename == "bif_full_q0.5_gvary_travel.dat" or\ filename == "bif_full_q0.5_gvary2c.dat": label = None ax.plot(clean(dat[:,0],dat[:,1],smallscale=smallscale)[0],-(clean(dat[:,0],dat[:,1],smallscale=smallscale)[1]-2*pi-pi)+pi, lw=lw,color=color,alpha=alpha,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2],smallscale=smallscale)[0],clean(dat[:,0],dat[:,2],smallscale=smallscale)[1]-2*pi, lw=lw,color=color,alpha=alpha,label=label,marker=marker,markevery=me,ls=ls) else: ax.plot(clean(dat[:,0],dat[:,1],smallscale=smallscale)[0],clean(dat[:,0],dat[:,1],smallscale=smallscale)[1], lw=lw,color=color,alpha=alpha,marker=marker,markevery=me,ls=ls) ax.plot(clean(dat[:,0],dat[:,2],smallscale=smallscale)[0],clean(dat[:,0],dat[:,2],smallscale=smallscale)[1], lw=lw,color=color,alpha=alpha,label=label,marker=marker,markevery=me,ls=ls) branchidx += 1 return ax def draw_branches_twop(ax,filelist,namelist,colorlist,ls): i = 0 for filename in filelist: # get all branches bif_qg1 = np.loadtxt(filename) branchlist = np.unique(bif_qg1[:,-2]) #if len(bif_qg1[0,:]==6): # branchlist = np.unique(bif_qg1[:,-2]) print branchlist # first branch bidx = 0 for b in branchlist: b_idx = bif_qg1[:,-2] == b typelist = np.unique(bif_qg1[b_idx,-3]) for t in typelist: t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] if bidx == 0: label = namelist[i] else: label = None ax.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1], lw=2,color=colorlist[i],label=label,ls=ls[i]) #ax2.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1], # lw=2,color=colorlist[i],label=label) bidx += 1 i += 1 return ax def oned_phase_2par(subplots=1,with_numerics=True): """ 1d domain, 2par bifurcation diagram of reduced system from auto see 1d.ode """ fig = plt.figure(figsize=(7,7)) gs = gridspec.GridSpec(3,3) ax1 = plt.subplot(gs[:2,:2]) """ 2 param bifurcation diagram from auto """ namelist = ['BP','HB','LP 2','LP 1'] colorlist = ['teal','orange','purple','black'] filelist = ["bif_gq_bp.dat","bif_gq_hb.dat","bif_gq_lp_travel.dat","bif_gq_lp_large.dat"] ls = ['-', '--', '-.', ':'] i = 0 for filename in filelist: # get all branches bif_qg1 = np.loadtxt(filename) branchlist = np.unique(bif_qg1[:,-2]) #if len(bif_qg1[0,:]==6): # branchlist = np.unique(bif_qg1[:,-2]) print branchlist # first branch bidx = 0 for b in branchlist: b_idx = bif_qg1[:,-2] == b typelist = np.unique(bif_qg1[b_idx,-3]) for t in typelist: t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] if bidx == 0: label = namelist[i] else: label = None ax1.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1], lw=2,color=colorlist[i],label=label,ls=ls[i]) ax1.fill_between() #ax2.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1], # lw=2,color=colorlist[i],label=label) bidx += 1 i += 1 ax1.text(1.5,2.6,'1. Stationary Bump',rotation=0,size=15) ax1.text(3.3,2.5,'2. Wobbling Bump',rotation=37,size=15) ax1.text(3.5,1.6,'3. Bistability',rotation=27,size=15) ax1.text(3.1,.3,'4. Traveling Bump',rotation=0,size=15) # plot solutions # ######################################################################################### if subplots >= 1: ax13 = plt.subplot(gs[0,-1]) dat = oned_simple.SimDat(g=0.,q=0.,zshift=0,T=1000,phase=True) ax13.set_xlabel(r'$x$') ax13.set_ylabel('$t$') ax13.set_title(r"\textbf{(a)}",x=0.1) #start_idx = len(dat.t)/2. #end_idx = int(1.5*start_idx) total_time_idx = dat.t[-1]/dat.dt pad = 10 start_idx = 100 print start_idx #edge_travel_time = (dat.b - dat.a)/dat.c_num # time it takes to go from -pi to pi edge_travel_idx = 500#edge_travel_time/dat.dt-pad # total indices of travel time wraps = 5 end_idx = start_idx+500 print end_idx #idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax13.matshow(np.roll(dat.sol[start_idx:end_idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax13.xaxis.tick_bottom() ax13.xaxis.set_label_position('bottom') for i in range(wraps): start_temp = start_idx+i*edge_travel_idx + pad*i end_temp = start_idx+(i+1)*edge_travel_idx idx_temp = np.arange(start_temp,end_temp+1,1,dtype='int') if with_numerics: ax13.plot(dat.ph_angle[idx_temp],np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),lw=3,color='black') ax13.plot(-(np.mod(dat.solph[idx_temp+578,0]+pi,2*pi)-pi),np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),ls='--',lw=2,dashes=(5,2),color='#3399ff') print 'shifted oned const vel analytic by', 578, 'with dt=',dat.dt ax13.set_aspect('auto') ax13.set_xlim(-pi,pi) ax13.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax13.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax13.set_xticklabels(x_label) ax1.annotate('', xy=(.5, .7), xycoords='axes fraction', xytext=(1.2, 1.02), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) # ######################################################################################### if subplots >= 3: ax13 = plt.subplot(gs[2,-1]) dat = oned_simple.SimDat(g=3.5,q=0.,zshift=.1,T=10000,phase=True) ax13.set_xlabel(r'$x$') ax13.set_ylabel('$t$') ax13.set_title(r"\textbf{(c)}",x=0.1) #start_idx = len(dat.t)/2. #end_idx = int(1.5*start_idx) total_time_idx = dat.t[-1]/dat.dt pad = 10 start_idx = np.argmin(np.mod(dat.ph_angle[total_time_idx/2:]+pi,2*pi)-pi)+total_time_idx/2+pad/2 print start_idx edge_travel_time = (dat.b - dat.a)/dat.c_num # time it takes to go from -pi to pi edge_travel_idx = edge_travel_time/dat.dt-pad # total indices of travel time wraps = 5 end_idx = start_idx+pad + wraps*(edge_travel_idx+pad) #idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax13.matshow(np.roll(dat.sol[start_idx:end_idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax13.xaxis.tick_bottom() ax13.xaxis.set_label_position('bottom') for i in range(wraps): start_temp = start_idx+i*edge_travel_idx + pad*i end_temp = start_idx+(i+1)*edge_travel_idx idx_temp = np.arange(start_temp,end_temp+1,1,dtype='int') if with_numerics: ax13.plot(dat.ph_angle[idx_temp],np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),lw=3,color='black') ax13.plot(-(np.mod(dat.solph[idx_temp+578,0]+pi,2*pi)-pi),np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),ls='--',lw=2,dashes=(5,2),color='#3399ff') print 'shifted oned const vel analytic by', 578, 'with dt=',dat.dt ax13.set_aspect('auto') ax13.set_xlim(-pi,pi) ax13.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax13.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax13.set_xticklabels(x_label) ax1.annotate('', xy=(.8, .01), xycoords='axes fraction', xytext=(1.2, -.2), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 2: """ ### oned_nonconst_vel1 #(oned_nonconst_vel_bump,[],['oned_nonconst_vel_bump_fig.pdf']), """ ax23 = plt.subplot(gs[1,-1]) dat = oned_simple.SimDat(g=3.,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units shift = -1800 sign = 1 ax23.set_xlabel(r'$x$') ax23.set_title(r"\textbf{(b)}",x=0.1) #ax2.set_ylabel(r'$t$') start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax23.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax23.xaxis.tick_bottom() ax23.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) if with_numerics: for slc in unlink_wrap(dat.ph_angle[idx]): ax23.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign for slc in unlink_wrap(modsolph): ax23.plot(modsolph[slc],timearr[slc],ls='--',lw=2,dashes=(5,2),color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax23.set_aspect('auto') ax23.set_xlim(-pi,pi) ax23.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax23.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax23.set_xticklabels(x_label) ax1.annotate('', xy=(.9, .55), xycoords='axes fraction', xytext=(1.2, .45), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ax1.annotate('', xy=(.9, .42), xycoords='axes fraction', xytext=(1.2, .45), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 4: """ ### oned_nonconst_vel2 #(oned_nonconst_vel_bump,[5.5,1.,-950,-1],['oned_nonconst_vel_bump_fig2.pdf']), """ sign = -1 shift = 3700#-550 ax32 = plt.subplot(gs[-1,-2]) dat = oned_simple.SimDat(g=3.5,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units ax32.set_xlabel(r'$x$') ax32.set_title(r"\textbf{(d)}",x=0.1) start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax32.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax32.xaxis.tick_bottom() ax32.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) if with_numerics: for slc in unlink_wrap(dat.ph_angle[idx]): ax32.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign for slc in unlink_wrap(modsolph): ax32.plot(modsolph[slc],timearr[slc],ls='--',dashes=(5,2),lw=2,color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax32.set_aspect('auto') ax32.set_xlim(-pi,pi) ax32.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax32.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax32.set_xticklabels(x_label) ax1.annotate('', xy=(.75, .32), xycoords='axes fraction', xytext=(.65, -.16), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 5: """ ### oned_nonconst_vel2 #(oned_nonconst_vel_bump,[5.5,1.,-950,-1],['oned_nonconst_vel_bump_fig2.pdf']), """ sign = -1 shift = -950 ax31 = plt.subplot(gs[-1,-3]) dat = oned_simple.SimDat(g=5.5,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units ax31.set_xlabel(r'$x$') ax31.set_title(r"\textbf{(e)}",x=0.1) start_idx = len(dat.t)/2. end_idx = int(1.3*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax31.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) fig.colorbar(cax) ax31.xaxis.tick_bottom() ax31.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) if with_numerics: for slc in unlink_wrap(dat.ph_angle[idx]): ax31.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign for slc in unlink_wrap(modsolph): ax31.plot(modsolph[slc],timearr[slc],ls='--',dashes=(5,2),lw=2,color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax31.set_aspect('auto') ax31.set_xlim(-pi,pi) ax31.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax31.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax31.set_xticklabels(x_label) ax1.annotate('', xy=(.3, .05), xycoords='axes fraction', xytext=(.05, -.16), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) #ax1.plot([0,5],[.5,.5],color='gray') #ax2.text(1.5,.075,'reminder: added line from g=2 to g=1 for LP2') ax1.legend(loc='upper left',fontsize=10) ax1.set_xlabel(r'$\bm{g}$',size=15) ax1.set_ylabel(r'$\bm{q}$',size=15) ax1.set_xlim(1,5) return fig def draw_branches_twop(ax,filelist,namelist,colorlist,ls): i = 0 for filename in filelist: # get all branches bif_qg1 = np.loadtxt(filename) branchlist = np.unique(bif_qg1[:,-2]) #if len(bif_qg1[0,:]==6): # branchlist = np.unique(bif_qg1[:,-2]) print branchlist # first branch bidx = 0 for b in branchlist: b_idx = bif_qg1[:,-2] == b typelist = np.unique(bif_qg1[b_idx,-3]) for t in typelist: t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] if bidx == 0: label = namelist[i] else: label = None ax.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1], lw=2,color=colorlist[i],label=label,ls=ls[i]) #ax2.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1], # lw=2,color=colorlist[i],label=label) bidx += 1 i += 1 return ax def oned_full_2par(subplots=1,with_numerics=True): """ 1d domain, 2par bifurcation diagram of full system from auto """ fig = plt.figure(figsize=(7,7)) gs = gridspec.GridSpec(3,3) ax1 = plt.subplot(gs[:2,:2]) """ 2 param bifurcation diagram from auto """ namelist = ['HB','LP 2']#['BP','HB','LP 2','LP 1'] colorlist = ['orange','purple']#['teal','orange','purple','black'] filelist = ['bif_full_a2_gq_hb.dat','bif_full_a2_gq_lp2.dat']#,'bif_full_gq_lp2.dat']#["bif_gq_bp.dat","bif_gq_hb.dat","bif_gq_lp_travel.dat","bif_gq_lp_large.dat"] ls = ['--','-.','-', '--', '-.', ':'] ax1 = draw_branches_twop(ax1,filelist,namelist,colorlist,ls) ax1.text(1.5,2.6,'1. Stationary Bump',rotation=0,size=15) ax1.text(3.3,2.5,'2. Wobbling Bump',rotation=37,size=15) #ax2.text(3.5,1.55,'3. Bistability',rotation=27,size=15) ax1.text(3.2,.3,'4. Traveling Bump',rotation=0,size=15) # plot solutions # ######################################################################################### if subplots >= 1: ax13 = plt.subplot(gs[0,-1]) dat = oned_simple.SimDat(g=0.,q=0.,zshift=0,T=1000,phase=True) ax13.set_xlabel(r'$x$') ax13.set_ylabel('$t$') ax13.set_title(r"\textbf{(a)}",x=0.1) #start_idx = len(dat.t)/2. #end_idx = int(1.5*start_idx) total_time_idx = dat.t[-1]/dat.dt pad = 10 start_idx = 100 print start_idx #edge_travel_time = (dat.b - dat.a)/dat.c_num # time it takes to go from -pi to pi edge_travel_idx = 500#edge_travel_time/dat.dt-pad # total indices of travel time wraps = 5 end_idx = start_idx+500 print end_idx #idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax13.matshow(np.roll(dat.sol[start_idx:end_idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax13.xaxis.tick_bottom() ax13.xaxis.set_label_position('bottom') for i in range(wraps): start_temp = start_idx+i*edge_travel_idx + pad*i end_temp = start_idx+(i+1)*edge_travel_idx idx_temp = np.arange(start_temp,end_temp+1,1,dtype='int') if with_numerics: pass #ax13.plot(dat.ph_angle[idx_temp],np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),lw=3,color='black') if False: ax13.plot(-(np.mod(dat.solph[idx_temp+578,0]+pi,2*pi)-pi),np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),ls='--',lw=2,dashes=(5,2),color='#3399ff') print 'shifted oned const vel analytic by', 578, 'with dt=',dat.dt ax13.set_aspect('auto') ax13.set_xlim(-pi,pi) ax13.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax13.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax13.set_xticklabels(x_label) ax1.annotate('', xy=(.5, .7), xycoords='axes fraction', xytext=(1.2, 1.02), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) # ######################################################################################### if subplots >= 3: ax13 = plt.subplot(gs[2,-1]) dat = oned_simple.SimDat(g=3.5,q=0.,zshift=.1,T=10000,phase=True) ax13.set_xlabel(r'$x$') ax13.set_ylabel('$t$') ax13.set_title(r"\textbf{(c)}",x=0.1) #start_idx = len(dat.t)/2. #end_idx = int(1.5*start_idx) total_time_idx = dat.t[-1]/dat.dt pad = 10 start_idx = np.argmin(np.mod(dat.ph_angle[total_time_idx/2:]+pi,2*pi)-pi)+total_time_idx/2+pad/2 print start_idx edge_travel_time = (dat.b - dat.a)/dat.c_num # time it takes to go from -pi to pi edge_travel_idx = edge_travel_time/dat.dt-pad # total indices of travel time wraps = 5 end_idx = start_idx+pad + wraps*(edge_travel_idx+pad) #idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax13.matshow(np.roll(dat.sol[start_idx:end_idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax13.xaxis.tick_bottom() ax13.xaxis.set_label_position('bottom') for i in range(wraps): start_temp = start_idx+i*edge_travel_idx + pad*i end_temp = start_idx+(i+1)*edge_travel_idx idx_temp = np.arange(start_temp,end_temp+1,1,dtype='int') if with_numerics: pass #ax13.plot(dat.ph_angle[idx_temp],np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),lw=3,color='black') if False: ax13.plot(-(np.mod(dat.solph[idx_temp+578,0]+pi,2*pi)-pi),np.linspace(dat.t[start_temp],dat.t[end_temp],len(idx_temp)),ls='--',lw=2,dashes=(5,2),color='#3399ff') print 'shifted oned const vel analytic by', 578, 'with dt=',dat.dt ax13.set_aspect('auto') ax13.set_xlim(-pi,pi) ax13.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax13.set_xticks(np.arange(-1,1+.5,.5)*pi) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax13.set_xticklabels(x_label) ax1.annotate('', xy=(.8, .01), xycoords='axes fraction', xytext=(1.2, -.2), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 2: ### oned_nonconst_vel1 #(oned_nonconst_vel_bump,[],['oned_nonconst_vel_bump_fig.pdf']), ax23 = plt.subplot(gs[1,-1]) dat = oned_simple.SimDat(g=3.,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units shift = -1800 sign = 1 ax23.set_xlabel(r'$x$') ax23.set_title(r"\textbf{(b)}",x=0.1) #ax2.set_ylabel(r'$t$') start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax23.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax23.xaxis.tick_bottom() ax23.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) if with_numerics: for slc in unlink_wrap(dat.ph_angle[idx]): pass #ax23.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign if False: for slc in unlink_wrap(modsolph): ax23.plot(modsolph[slc],timearr[slc],ls='--',lw=2,dashes=(5,2),color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax23.set_aspect('auto') ax23.set_xlim(-pi,pi) ax23.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax23.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax23.set_xticklabels(x_label) ax1.annotate('', xy=(.9, .55), xycoords='axes fraction', xytext=(1.2, .45), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) #ax1.annotate('', xy=(.9, .42), xycoords='axes fraction', xytext=(1.2, .45), # arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 4: ### oned_nonconst_vel2 #(oned_nonconst_vel_bump,[5.5,1.,-950,-1],['oned_nonconst_vel_bump_fig2.pdf']), sign = -1 shift = 3700#-550 ax32 = plt.subplot(gs[-1,-2]) dat = oned_simple.SimDat(g=3.5,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units ax32.set_xlabel(r'$x$') ax32.set_title(r"\textbf{(d)}",x=0.1) start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax32.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax32.xaxis.tick_bottom() ax32.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) if with_numerics: pass #for slc in unlink_wrap(dat.ph_angle[idx]): # ax32.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign if False: for slc in unlink_wrap(modsolph): ax32.plot(modsolph[slc],timearr[slc],ls='--',dashes=(5,2),lw=2,color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax32.set_aspect('auto') ax32.set_xlim(-pi,pi) ax32.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax32.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax32.set_xticklabels(x_label) ax1.annotate('', xy=(.75, .32), xycoords='axes fraction', xytext=(.65, -.16), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 5: ### oned_nonconst_vel2 #(oned_nonconst_vel_bump,[5.5,1.,-950,-1],['oned_nonconst_vel_bump_fig2.pdf']), sign = -1 shift = -950 ax31 = plt.subplot(gs[-1,-3]) dat = oned_simple.SimDat(g=5.5,q=1.,zshift=.1,T=10000,phase=True) # period is approx 525 time units ax31.set_xlabel(r'$x$') ax31.set_title(r"\textbf{(e)}",x=0.1) start_idx = len(dat.t)/2. end_idx = int(1.3*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') if with_numerics: cax = ax31.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax31.xaxis.tick_bottom() ax31.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) if with_numerics: pass #for slc in unlink_wrap(dat.ph_angle[idx]): # ax31.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign if False: for slc in unlink_wrap(modsolph): ax31.plot(modsolph[slc],timearr[slc],ls='--',dashes=(5,2),lw=2,color='#3399ff') #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax31.set_aspect('auto') ax31.set_xlim(-pi,pi) ax31.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax31.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax31.set_xticklabels(x_label) ax1.annotate('', xy=(.3, .05), xycoords='axes fraction', xytext=(.05, -.16), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) #ax1.plot([0,5],[.5,.5],color='gray') #ax2.text(1.5,.075,'reminder: added line from g=2 to g=1 for LP2') ax1.legend(loc='upper left',fontsize=10) ax1.set_xlabel(r'$\bm{g}$',size=15) ax1.set_ylabel(r'$\bm{q}$',size=15) ax1.set_xlim(1,5) return fig def draw_branches_twop(ax,filelist,namelist,colorlist,ls): i = 0 for filename in filelist: # get all branches bif_qg1 = np.loadtxt(filename) branchlist = np.unique(bif_qg1[:,-2]) #if len(bif_qg1[0,:]==6): # branchlist = np.unique(bif_qg1[:,-2]) print branchlist # first branch bidx = 0 for b in branchlist: b_idx = bif_qg1[:,-2] == b typelist = np.unique(bif_qg1[b_idx,-3]) for t in typelist: t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] if bidx == 0: label = namelist[i] else: label = None ax.plot(clean(dat[:,0],dat[:,1])[0],clean(dat[:,0],dat[:,1])[1], lw=2,color=colorlist[i],label=label,ls=ls[i]) #ax2.plot(clean(dat[:,0],dat[:,2])[0],clean(dat[:,0],dat[:,2])[1], # lw=2,color=colorlist[i],label=label) bidx += 1 i += 1 return ax def oned_full_auto(): """ 1d bifurcation diagram from auto see numerical_bard_sep.ode """ filelista2 = ["bif_full_a2_q0.5_gvary1.dat","bif_full_a2_q0.5_gvary2.dat","bif_full_a2_q0.5_gvary2b.dat"] filelista3 = ["bif_full_a3_q0.5_gvary1.dat","bif_full_a3_q0.5_gvary2.dat","bif_full_a3_q0.5_gvary2b.dat"] # data files obtained using numerical_bard_sep.ode fig = plt.figure(figsize=(10,5)) ax = plt.subplot2grid((2,2),(0,0)) ax = draw_branches(ax,filelista2) # labels ax.set_xticks([]) ax.set_ylabel(r'$\bm{a_1}$',size=15) # set y axis ticks to multiples of pi ax.set_ylim(-1.5,1) ax.set_xlim(0,5) ax.set_title(r'\textbf{(a)}',x=0,y=1.05) #ax.legend(loc='lower left',fontsize=10) """ ax.annotate("BP",color='teal', xy=(2.36581,1.7138), xycoords='data', xytext=(2, 2.5), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='teal'), ) """ ax.annotate("HB",color='orange', xy=(1.50704,0.78737), xycoords='data', xytext=(.75, .5), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='orange'), ) # LP 2 label inset ax.annotate("LP 2",color='purple', xy=(2.75, .796), xycoords='data', xytext=(3.2, .4), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='purple'), ) #ax.annotate(r"\colorbox{blue!20}{{\color{yellow}LP Large}}", """ ax.annotate("LP 1", xy=(2.20126, 0.847046), xycoords='data', xytext=(2.7, .40746), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w"), ) """ # inset axins = inset_axes(ax, width="30%", # width = 30% of parent_bbox height="50%", # height : 1 inch loc=3) axins = draw_branches(axins,filelista2,smallscale=True) axins.set_xlim(2.1,2.9) axins.set_ylim(.78,.82) # bistability for inset axins.plot([2.25346,2.25346],[-2,2],ls=':',color='black') axins.plot([2.38425,2.38425],[-2,2],ls=':',color='black') # LP 2 label inset axins.annotate("LP 2",color='purple', xy=(2.81, .796), xycoords='data', xytext=(2.68, .785), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='purple'), ) plt.tick_params(axis='both', which='both', bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off') plt.xticks(visible=False) plt.yticks(visible=False) mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5") # mark bistability ax.plot([2.25346,2.25346],[-2,2],ls=':',color='black') ax.plot([2.38425,2.38425],[-2,2],ls=':',color='black') ax2 = plt.subplot2grid((2,2),(1,0)) ax2.set_title(r'\textbf{(b)}',x=0,y=1.05) ax2 = draw_branches(ax2,filelista3) ax2.set_ylabel(r'$\bm{a_2}$',size=15) ax2.set_xlabel(r'$\bm{g}$',size=15) ax2.set_ylim(-1,.1) ax2.set_xlim(0,5) # inset axins = inset_axes(ax2, width="30%", # width = 30% of parent_bbox height=1., # height : 1 inch loc=1) axins = draw_branches(axins,filelista3,smallscale=True) axins.set_xlim(2.1,3.) axins.set_ylim(-.83,-.73) # inset bistability axins.plot([2.25346,2.25346],[-2,2],ls=':',color='black') axins.plot([2.38425,2.38425],[-2,2],ls=':',color='black') # inset lp2 axins.annotate("LP 2",color='purple', xy=(2.84, -.779), xycoords='data', xytext=(2.7, -.75), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='purple'), ) plt.tick_params(axis='both', which='both', bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off') plt.xticks(visible=False) plt.yticks(visible=False) mark_inset(ax2, axins, loc1=2, loc2=4, fc="none", ec="0.5") """ ax2.annotate("BP",color='teal', xy=(2.36581,1.7138), xycoords='data', xytext=(2, 2.5), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='teal'), ) """ ax2.annotate("HB",color='orange', xy=(1.50704,0.), xycoords='data', xytext=(1., -.2), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='orange'), ) ax2.annotate("LP 2",color='purple', xy=(2.84, -.779), xycoords='data', xytext=(3., -.5), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w",color='purple'), ) #ax2.annotate(r"\colorbox{blue!20}{{\color{yellow}LP Large}}", """ ax2.annotate("LP 1", xy=(2.20126, 0.847046), xycoords='data', xytext=(2.7, .40746), textcoords='data', size=15, va="center", ha="center", arrowprops=dict(arrowstyle="->", relpos=(0., 0.), fc="w"), ) """ #ax.set_xlabel(r'$\bm{g}$',size=15) # mark bistability ax2.plot([2.25346,2.25346],[-2,2],ls=':',color='black') ax2.plot([2.38425,2.38425],[-2,2],ls=':',color='black') ax3 = plt.subplot2grid((2,2),(0,1),rowspan=2) ax3.set_title(r'\textbf{(c)}',x=0,y=1.02) namelist = ['HB','LP 2']#['BP','HB','LP 2','LP 1'] colorlist = ['orange','purple']#['teal','orange','purple','black'] filelist = ['bif_full_a2_gq_hb.dat','bif_full_a2_gq_lp2.dat']#,'bif_full_gq_lp2.dat']#["bif_gq_bp.dat","bif_gq_hb.dat","bif_gq_lp_travel.dat","bif_gq_lp_large.dat"] ls = ['--','-.','-', '--', '-.', ':'] ax3 = draw_branches_twop(ax3,filelist,namelist,colorlist,ls) ax3.text(1.5,2.6,'1. Stationary Bump',rotation=0,size=15) ax3.text(3.3,2.5,'2. Wobbling Bump',rotation=37,size=15) #ax2.text(3.5,1.55,'3. Bistability',rotation=27,size=15) ax3.text(3.2,.3,'4. Traveling Bump',rotation=0,size=15) ax3.plot([0,5],[.5,.5],color='gray') #ax2.text(1.5,.075,'reminder: added line from g=2 to g=1 for LP2') #ax3.legend(loc='upper left',fontsize=8) ax3.set_xlabel(r'$\bm{g}$',size=15) ax3.set_ylabel(r'$\bm{q}$',size=15) ax3.set_xlim(1,5) return fig def root(ushift,g): """ find slow limit cycle/wobbling bump """ time = 882.4*5 sim = oned_simple.SimDat(q=0.5,g=g,T=time,ushift=ushift,zshift=1e-5) max_loc = np.r_[True, sim.ph_angle[1:] > sim.ph_angle[:-1]] & np.r_[sim.ph_angle[:-1] > sim.ph_angle[1:], True] local_maxima = sim.ph_angle[max_loc][1:-1] diffraw = local_maxima[-2] - local_maxima[-3] print 'diffraw=',diffraw,'ushift=',ushift return diffraw def oned_normal_form(): """ 1d normal form calculation. probably incorrect. see bard's normal form calculation below. """ fig = plt.figure(figsize=(8,4)) #ax = fig.add_subplot(111) ax = plt.subplot2grid((1,2),(0,0)) ax2 = plt.subplot2grid((1,2),(0,1)) #ax3 = plt.subplot2grid((2,1),(1,1))#fig.add_subplot(132) ax.set_title(r"\textbf{(a)}",x=0,y=1.05) gvals_long = np.linspace(1.5,2.,201) # use in theory # theory ss = oned_simple.SteadyState() mu = ss.kap Aprime = ss.Hamp # get a better approximation later. eps = .01 period = eps*882.4 # period in tau (period in t times eps) #period = eps*441.2 # period in tau om = 2*pi/period # for a cosine kernel, H(x) = A'sin(x) h1 = Aprime*1. h3 = Aprime*(-1./6) be = 1. q = .5 gstar = (mu*be - q*(-Aprime))/Aprime#+.00625 print Aprime,om,gstar #B = 2*sqrt( -(be**2 + 4.*om**2)*h1/(gstar*h3) )/(6.*om) f1 = sqrt(be**2. + om**2.) #f2 = sqrt(be**2. + 4*om**2.) #B = 2*om*sqrt(h1*f2)/sqrt(h3*(12.*q*f1*f2-144.*gstar*om**4)) B = 2.*(2.*sqrt(h1*om))/(f1*sqrt(h3*((12.*q)/om - (144.*gstar*om**3.)/(be**4. + 5.*be**2.*om**2. + 4.*om**4.)))) amp = B*sqrt(gvals_long-gstar) #amp = sqrt(g-gstar) # numerics #gvals_short = [1.5,1.505,1.51,1.515] #gvals_short = np.linspace(1.5,1.75,41) gvals_short = np.arange(1.50625,2.,.00625) amp_num = np.zeros(len(gvals_short)) i = 0 ushift = 0. zshift = 1e-5 savedir = 'hopf_data/' if (not os.path.exists(savedir)): os.makedirs(savedir) for g in gvals_short: time = 1500.#882.4*2 print "g="+str(g) tol = 5e-4 filename = 'osc_g='+str(g)+'.dat' if os.path.isfile(savedir+filename): local_max = float(open(savedir+filename,'r').readline()) #print local_max else: #print #ss_time = sim.t[int(time/sim.dt/1.5):] sim = oned_simple.SimDat(q=0.5,g=g,T=time,ushift=0,zshift=.1,sim_factor=70) max_loc = np.r_[True, sim.ph_angle[1:] > sim.ph_angle[:-1]] & np.r_[sim.ph_angle[:-1] > sim.ph_angle[1:], True] local_maxima = sim.ph_angle[max_loc][1:-1] local_max = local_maxima[-1] file_ = open(savedir+filename,'w') file_.write(str(local_max)) file_.close() amp_num[i] = local_max #mp.figure() #mp.plot(sim.t,sim.ph_angle) #mp.show() #ushift = sp.optimize.brentq(root,0,pi,args=(g,),rtol=1e-4) i += 1 data = np.zeros((len(gvals_short),2)) data[:,0] = gvals_short data[:,1] = amp_num """ ax.annotate("("+str(data[20,0])+","+str(data[20,1])+")", xy=(data[20,0], data[20,1]), xycoords='data', xytext=(data[20,0]-.05, data[20,1]+.05), textcoords='data', size=12, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3") ) """ #np.savetxt("hopf_amplitude.dat") ax.plot(gvals_long,amp,color="#3399ff",ls='dashed',label="Theoretical",lw=3) ax.plot(gvals_short,amp_num,color="black",label="Numerical",lw=3) ax.set_xlim(data[:,0][0]-.01,data[:,0][-1]+.01) ax.set_ylabel(r"\textbf{Oscillation Amplitude (A)}") ax.set_xlabel(r"\textbf{Adaptation (g)}") ax.legend(loc=4) """ PLOT SOLUTION ARRAY """ x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] dat = oned_simple.SimDat(g=1.55,q=.5,zshift=.1,T=10000,phase=True) # period is approx 525 time units shift = -700 sign = 1 ax2.set_xlabel(r'$x$') ax2.set_title(r"\textbf{(b)}",x=0) #ax2.set_ylabel(r'$t$') start_idx = len(dat.t)/2. end_idx = int(1.5*start_idx) idx = np.arange(start_idx,end_idx+1,1,dtype='int') cax = ax2.matshow(np.roll(dat.sol[idx,:dat.N],dat.N/2),cmap='gray',extent=[-pi,pi,dat.t[end_idx],dat.t[start_idx]]) #fig.colorbar(cax) ax2.xaxis.tick_bottom() ax2.xaxis.set_label_position('bottom') timearr = np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)) for slc in unlink_wrap(dat.ph_angle[idx]): ax2.plot(dat.ph_angle[idx][slc],timearr[slc],color='black',lw=3) modsolph = -(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign for slc in unlink_wrap(modsolph): ax2.plot(modsolph[slc],timearr[slc],ls='--',color='#3399ff',lw=3) #ax.plot(dat.ph_angle[idx],np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),color='black',lw=3) #ax.plot(-(np.mod(dat.solph[idx+shift,0]+pi,2*pi)-pi)*sign,np.linspace(dat.t[start_idx],dat.t[end_idx],len(idx)),ls='--',color='.65',lw=2) print 'shifted oned_nonconst_vel_bump ana by ', shift, 'where dt=',dat.dt ax2.set_aspect('auto') ax2.set_xlim(-pi,pi) ax2.set_ylim(dat.t[end_idx],dat.t[start_idx]) ax2.set_xticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax2.set_xticklabels(x_label) return fig def oned_normal_form_bard(): """ oned normal form using bard's data """ filename = 'diagram.dat' filename2 = 'diagram.25.dat' # get all branches bif_qg1 = np.loadtxt(filename) branchlist = [2] b_idx = bif_qg1[:,-2] == branchlist[0] typelist = [3]#np.unique(bif_qg1[b_idx,-3]) #print typelist for t in typelist: t_idx = bif_qg1[:,-3] == t dat = bif_qg1[b_idx*t_idx,:] label = None # get all branches bif_qg2 = np.loadtxt(filename2) branchlist2 = [2] b_idx2 = bif_qg2[:,-2] == branchlist2[0] typelist2 = [3]#np.unique(bif_qg2[b_idx2,-3]) #print typelist for t in typelist2: t_idx2 = bif_qg2[:,-3] == t dat2 = bif_qg2[b_idx2*t_idx2,:] label = None fig = plt.figure(figsize=(10,4)) ax = fig.add_subplot(121) ax.plot(dat[:,0],dat[:,1],label='AUTO',lw=3,color='black') dom1 = np.linspace(2,2.5,100) ax.plot(dom1,2*np.sqrt((10./13.)*(dom1-2)),label='Normal Form',lw=3,ls='--',color='#3399ff') ax.set_title(r'\textbf{(a)}',x=0,y=1.03) ax.set_ylabel(r"\textbf{Oscillation Amplitude}") ax.set_xlabel(r"\textbf{Adaptation ($g$)}") #ax.set_xlabel(r'Adaptation ($g$)') #ax.set_ylabel(r'Oscillation Amplitude') ax.set_xlim(2,2.5) ax.set_ylim(0,1.4) #ax.legend() ax2 = fig.add_subplot(122) ax2.plot(dat2[:,0],dat2[:,1],label='AUTO',lw=3,color='black') dom2 = np.linspace(1.25,1.5,100) ax2.plot(dom2,2*np.sqrt(.5*(dom2-1.25)/.2175),label='Normal Form',lw=3,ls='--',color='#3399ff') ax2.set_title(r'\textbf{(b)}',x=0,y=1.03) ax2.set_ylabel(r"\textbf{Oscillation Amplitude}") ax2.set_xlabel(r"\textbf{Adaptation ($g$)}") #ax2.set_xlabel(r'Adaptation ($g$)') #ax2.set_ylabel(r'Oscillation Amplitude') ax2.set_xlim(1.25,1.5) ax2.set_ylim(0,1.6) ax2.legend(loc='lower right') return fig def g_nu_fig(): """ plot g(nu) """ N = 100 nu = np.linspace(.00001,1,N) s = np.linspace(0,10.,100) ds = (s[-1]-s[0])/len(s) g1 = np.zeros(N) g2 = np.zeros(N) for i in range(N): tot = 0 tot2 = 0 # find integral of exp(-s)*H(nu s) for j in range(len(s)): tot += np.exp(-s[j])*(sin(nu[i]*s[j])-(.25)*sin(2.*nu[i]*s[j]))*ds#np.sin(nu[i]*s[j])*ds tot2 += np.exp(-s[j])*(sin(nu[i]*s[j]))*ds#np.sin(nu[i]*s[j])*ds g1[i] = nu[i]/tot g2[i] = nu[i]/tot2 fig = plt.figure(figsize=(10,4)) ax2 = fig.add_subplot(121) ax2.plot(nu,g2,lw=3,ls='-',color='black') ax2.set_title(r'\textbf{(a)}',fontsize=20,x=0,y=1.03) ax2.set_ylabel(r'$g(\nu)$',fontsize=20) ax2.set_xlabel(r'$\nu$',fontsize=20) ax2.tick_params(labelsize=15) ax1 = fig.add_subplot(122) split_idx = np.argmin(g1) ax1.plot(nu[:split_idx],g1[:split_idx],lw=3,ls='--',color='black') ax1.plot(nu[split_idx:],g1[split_idx:],lw=3,ls='-',color='black') ax1.set_title(r'\textbf{(b)}',fontsize=20,x=0,y=1.03) ax1.set_xlabel(r'$\nu$',fontsize=20) ax1.tick_params(labelsize=15) return fig #plt.show() def oned_chaos_fig(): """ """ fig = plt.figure(figsize=(10,3)) x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] ax1 = fig.add_subplot(121) c1 = np.loadtxt("chaos_simple1.dat") c2 = np.loadtxt("chaos_simple2.dat") NT = len(c1) t = np.linspace(0,50000,NT) dt = t[-1]/NT start_t = 14000 end_t = 20000 sidx = int(start_t/dt) eidx = int(end_t/dt) for slc in unlink_wrap(c1[sidx:eidx]): ax1.plot(t[sidx:eidx][slc],c1[sidx:eidx][slc],color='black',lw=2) for slc in unlink_wrap(c2[sidx:eidx]): ax1.plot(t[sidx:eidx][slc],c2[sidx:eidx][slc],color='#3399ff',lw=2,ls='--',dashes=(5,1)) ax1.set_ylabel(r'$\bm{\theta}$') ax1.set_xlabel(r'$\bm{t}$') ax1.set_xlim(start_t,end_t) ax1.set_ylim(-pi,pi) ax1.set_yticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax1.set_yticklabels(x_label) ax2 = fig.add_subplot(122) ct1 = np.loadtxt("chaos_simple_theory1.dat") ct2 = np.loadtxt("chaos_simple_theory2.dat") NTt = len(ct1) t2 = np.linspace(0,50000,NTt) dt2 = t2[-1]/NTt start_t2 = 34000 end_t2 = 40000 sidx2 = int(start_t2/dt2) eidx2 = int(end_t2/dt2) for slc in unlink_wrap(ct1[sidx2:eidx2]): ax2.plot(t2[sidx2:eidx2][slc],ct1[sidx2:eidx2][slc],color='black',lw=2) for slc in unlink_wrap(ct2[sidx2:eidx2]): ax2.plot(t2[sidx2:eidx2][slc],ct2[sidx2:eidx2][slc],color='#3399ff',lw=2,ls='--',dashes=(5,1)) #ax2.set_ylabel(r'$\bm{\theta}$') ax2.set_xlabel(r'$\bm{t}$') ax2.set_xlim(start_t2,end_t2) ax2.set_ylim(-pi,pi) ax2.set_yticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] ax2.set_yticklabels(x_label) return fig def twod_auto_3terms_fig_old(): """ twod bifurcation diagram for truncated h """ #raw_data = np.loadtxt('twodphs_cys_wave_diagram_q=.125.dat') if True: raw_data = np.loadtxt('twodphs_sxs_wave_diagram_q=.125.dat') raw_data2 = np.loadtxt('twodphs_sxs_osc2_diagram_q=.125.dat') raw_data3 = np.loadtxt('twodphs_sxs_hopf_diagram_q=.125.dat') raw_data4 = np.loadtxt('twodphs_sxs_wave2_diagram_q=.125.dat') if False: raw_data = np.loadtxt('twodphs_cys_wave_diagram_q=.125.dat') raw_data2 = np.loadtxt('twodphs_cys_osc2_diagram_q=.125.dat') raw_data3 = np.loadtxt('twodphs_cys_hopf_diagram_q=.125.dat') raw_data4 = np.loadtxt('twodphs_cys_wave2_diagram_q=.125.dat') if False: raw_data = np.loadtxt('twodphs_x_wave_diagram_q=.125.dat') raw_data2 = np.loadtxt('twodphs_cys_osc2_diagram_q=.125.dat') raw_data3 = np.loadtxt('twodphs_x_hopf_diagram_q=.125.dat') raw_data4 = np.loadtxt('twodphs_x_wave2_diagram_q=.125.dat') data = diagram.read_diagram(raw_data) data2 = diagram.read_diagram(raw_data2) data3 = diagram.read_diagram(raw_data3) data4 = diagram.read_diagram(raw_data4) print np.shape(data) fig = plt.figure() ax = fig.add_subplot(111) # plot unstable fixed points ax.scatter(data[:,0],data[:,2],s=10,color='black') ax.scatter(data[:,0],data[:,6],s=10,color='black') ax.scatter(data3[:,0],data3[:,2],s=10,color='black') ax.scatter(data3[:,0],data3[:,6],s=10,color='black') # plot unstable periodic solutions ax.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') #ax.scatter(data[:,0],data[:,8],s=10,facecolor='none',edgecolor='blue') ax.scatter(data2[:,0],data2[:,4],s=10,facecolor='none',edgecolor='blue') ax.scatter(data2[:,0],data2[:,8],s=10,facecolor='none',edgecolor='blue') ax.scatter(data3[:,0],data3[:,4],s=10,facecolor='none',edgecolor='blue') ax.scatter(data3[:,0],data3[:,8],s=10,facecolor='none',edgecolor='blue') ax.scatter(data4[:,0],data4[:,4],s=10,facecolor='none',edgecolor='#0099ff') ax.scatter(data4[:,0],data4[:,8],s=10,facecolor='none',edgecolor='#0099ff') # plot stable fixed points ax.scatter(data[:,0],data[:,1],s=10,color='red') ax.scatter(data[:,0],data[:,5],s=10,color='red') ax.scatter(data3[:,0],data3[:,1],s=10,color='red') ax.scatter(data3[:,0],data3[:,5],s=10,color='red') # plot stable periodic solutions ax.scatter(data[:,0],data[:,3],s=20,color='green') ax.scatter(data[:,0],data[:,7],s=20,color='green') ax.scatter(data2[:,0],data2[:,3],s=20,color='green') ax.scatter(data2[:,0],data2[:,7],s=20,color='green') ax.scatter(data3[:,0],data3[:,3],s=20,color='green') ax.scatter(data3[:,0],data3[:,7],s=20,color='green') ax.scatter(data4[:,0],data4[:,3],s=20,color='#00cc00') ax.scatter(data4[:,0],data4[:,7],s=20,color='#00cc00') ax.set_xlim(.5,3) ax.set_ylim(-.01,1.) return fig def get_switch_points(data): """ given allinfo bifurcation diagram data, find all locations where stability changes. """ pass def twod_phase_auto_3terms_fig1(): """ twod bifurcation diagram for truncated h q = 0.01 """ #raw_data = np.loadtxt('twodphs_cys_wave_diagram_q=.125.dat') # all info data files are organized as follows: # Type, BR, 0, par1, par1/2, period, sv1 (high), ..., sv10 (high), sv1 (low),...,sv10(high), real/im eigenvalue pairs... # so I could use these values as initial conditions to plot. bif_data = np.loadtxt('twodphs_3_sxs_TR_q=.01.dat') init_data = np.loadtxt('twodphs_3_init_TR_q=.01.dat') # manually get index of sxs value idx = 5 fig = plt.figure(figsize=(6,7)) ### BIFURCATION DIAGRAM gs = gridspec.GridSpec(4, 4) gs.update(hspace=.75) gs.update(wspace=.3) ax11 = plt.subplot(gs[:3, :3]) #ax11 = plt.subplot2grid((4,4),(0,0),colspan=3,rowspan=2) #ax21 = plt.subplot2grid((4,4),(2,0),colspan=3,rowspan=1,sharex=ax11) #ax11 = plt.subplot2grid((4,4),(0,0),colspan=3,rowspan=3) # pre-allocate for conversion to simple bifurcation data bif_data_simple = np.zeros((len(bif_data[:,0]),6)) # remember write pts from auto gives: par, min, max, type, BR. # parameter value bif_data_simple[:,0] = bif_data[:,3] # max value # first get relative position of desired state variable bif_data_simple[:,1] = bif_data[:,5+idx] # min value bif_data_simple[:,2] = bif_data[:,5+idx+10] # type bif_data_simple[:,3] = bif_data[:,0] # branch bif_data_simple[:,4] = abs(bif_data[:,1]) data = diagram.read_diagram(bif_data_simple) for i in range(1,len(data[0,:])): x = data[:,0] y = data[:,i] data[:,0],data[:,i]=clean(x,y,tol=.1) if (i == 4): print i x = data[:,0] y = data[:,i] data[:,0],data[:,i]=remove_redundant_x(x,y,tol=1e-7) # plot unstable fixed points #ax11.scatter(data[:,0],data[:,2],s=10,color='black') ax11.plot(data[:,0],data[:,2],color='black') # plot unstable periodic solutions #ax11.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') ax11.plot(data[:,0],data[:,4],color='blue') #ax.scatter(data[:,0],data[:,8],s=10,facecolor='none',edgecolor='blue') # plot stable fixed points #ax11.scatter(data[:,0],data[:,1],s=10,color='red') #ax11.scatter(data[:,0],data[:,5],s=10,color='red') ax11.plot(data[:,0],data[:,1],color='red') ax11.plot(data[:,0],data[:,5],color='red') # plot stable periodic solutions #ax11.scatter(data[:,0],data[:,3],s=5,color='green') #ax11.scatter(data[:,0],data[:,7],s=5,color='green') ax11.plot(data[:,0],data[:,3],color='green',lw=3,ls='--') ax11.plot(data[:,0],data[:,7],color='green',lw=3,ls='--') ax11.set_xlabel('$g$') ax11.xaxis.set_label_coords(0.5,-.03) ax11.set_ylabel('$sx$') ax11.set_xlim(.5,1) ax11.set_ylim(.75,1) # bifurcation diagram inset axins11 = inset_axes(ax11, width="60%", # width = 30% of parent_bbox height="40%", # height : 1 inch loc=3) axins11.plot(data[:,0],data[:,4],color='blue') axins11.plot(data[:,0],data[:,3],color='green',lw=3,ls='--') axins11.plot(data[:,0],data[:,7],color='green',lw=3,ls='--') ax11.annotate("TR", xy=(.9095,.79), xycoords='data', xytext=(.9,.82), textcoords='data', size=15, color='red', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) axins11.annotate("PD", xy=(.5984,.9745), xycoords='data', xytext=(.595,.973), textcoords='data', size=15, color='black', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) axins11.annotate("BP", xy=(.59,.9795), xycoords='data', xytext=(.588,.977), textcoords='data', size=15, color='blue', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) #axins11.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') #axins11.scatter(data[:,0],data[:,3],s=5,color='green') #axins11.scatter(data[:,0],data[:,7],s=5,color='green') #axins11.scatter(g,sxsval,color='purple') mark_inset(ax11, axins11, loc1=2, loc2=4, fc="none", ec="0.5") plt.xticks(visible=False) plt.yticks(visible=False) axins11.set_xlim(.586105,.600328) axins11.set_ylim(.972532,.984061) # LOOP OVER SAMPLE SOLUTIONS rlist = [957,998,1206,655,634,587,8] loclist = [(3,0),(3,1),(3,2),(0,3),(1,3),(2,3),(3,3)] labellist = [r'\textbf{A}',r'\textbf{B}',r'\textbf{C}',r'\textbf{D}',r'\textbf{E}',r'\textbf{F}',r'\textbf{G}'] pos = [] axlist = [] for i in range(len(rlist)): rown = rlist[i] g = bif_data[rown,3] per = bif_data[rown,5] init = init_data[rown,5:] dt = .01 #print g,per,bif_data[rown,6:6+10] print init_data[rown,2],init_data[rown,4],init npa, vn = xpprun('twodphs3.ode', xppname='xppaut', inits={'x':init[0],'y':init[1], 'cxs':init[2],'cys':init[3], 'sxs':init[4],'sys':init[5], 'sxsys':init[6],'sxcys':init[7], 'cxsys':init[8],'cxcys':init[9]}, parameters={'total':per, 'g':g, 'q':0.01, 'dt':dt}, clean_after=True) t = npa[:,0] sv = npa[:,1:] idx = vn.index('sxs') sxsval = bif_data[rown,6+idx] #axlist.append(plt.subplot2grid((4,4),loclist[i])) axlist.append(plt.subplot(gs[loclist[i][0],loclist[i][1]])) """ ax41 = plt.subplot2grid((4,4),(3,0)) ax42 = plt.subplot2grid((4,4),(3,1)) ax43 = plt.subplot2grid((4,4),(3,2)) ax14 = plt.subplot2grid((4,4),(0,3)) ax24 = plt.subplot2grid((4,4),(1,3)) ax34 = plt.subplot2grid((4,4),(2,3)) ax44 = plt.subplot2grid((4,4),(3,3)) """ ### SAMPLE SOLUTIONS xval = np.mod(sv[:,vn.index('x')]+pi,2*pi)-pi yval = np.mod(sv[:,vn.index('y')]+pi,2*pi)-pi pos1 = np.where(np.abs(np.diff(xval)) >= 1)[0] pos2 = np.where(np.abs(np.diff(yval)) >= 1)[0] xval[pos1] = np.nan yval[pos2] = np.nan xval[pos2] = np.nan yval[pos2] = np.nan dashes = [] print bif_data[rown,0] if abs(bif_data[rown,0]) == 4.: dashes = (5,2) axlist[i].plot(xval,yval,color='black',lw=2,dashes=dashes) # label 2 points with arrows back_idx = 5 idxlist = [int(0.*(per/dt)),int(1.*(per/dt)/2.)]# depends on period for j in idxlist: axlist[i].annotate("", xy=(xval[j], yval[j]), xycoords='data', xytext=(xval[j-back_idx], yval[j-back_idx]), textcoords='data', size=15, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) axlist[i].set_xlim(-pi,pi) axlist[i].set_ylim(-pi,pi) axlist[i].tick_params(axis=u'both',which=u'both',length=0) axlist[i].set_xticks(np.arange(-1,1+1,1)*pi) axlist[i].set_yticks(np.arange(-1,1+1,1)*pi) x_label = [r"$-\pi$", r"$0$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] axlist[i].set_xticklabels(x_label) axlist[i].set_yticklabels(x_label) if i >= 3: axlist[i].yaxis.tick_right() if i < 3: axlist[i].set_yticklabels([]) if i >= 3 and i < len(labellist)-1: axlist[i].set_xticklabels([]) # annotations corresponding to solution plots axins11.annotate(labellist[i], xy=(g, sxsval), xycoords='data', xytext=(g, sxsval), textcoords='data', size=12, verticalalignment='top', horizontalalignment='right', backgroundcolor='yellow', zorder=-1 #arrowprops=dict(arrowstyle="-|>", # connectionstyle="arc3", # color=str(color)), ) ax11.annotate(labellist[i], xy=(g, sxsval), xycoords='data', xytext=(g, sxsval), textcoords='data', size=12, backgroundcolor='yellow', zorder=-1 #arrowprops=dict(arrowstyle="-|>", # connectionstyle="arc3", # color=str(color)), ) axlist[i].set_title(labellist[i]) """ ax11.annotate("", xy=(th1[i], th2[i]), xycoords='data', xytext=(th1[i-back_idx], th2[i-back_idx]), textcoords='data', size=22, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color=str(color)), ) """ #ax11. ax11.scatter(g,sxsval,s=10,color='black',marker='^') axins11.scatter(g,sxsval,s=10,color='black',marker='^') #ax2.plot(t,np.mod(sv[:,vn.index('x')],2*pi)) #ax2.plot(t,np.mod(sv[:,vn.index('sxs')],2*pi)) #ax2.plot(t,np.mod(npa[:,vn.index('sxs')],2*pi)) #ax2.plot(t,np.mod(npa[:,vn.index('y')],2*pi)) return fig def twod_phase_auto_3terms_fig2(): """ twod bifurcation diagram for truncated h q = 0.1 """ #raw_data = np.loadtxt('twodphs_cys_wave_diagram_q=.125.dat') # all info data files are organized as follows: # Type, BR, 0, par1, par1/2, period, sv1 (high), ..., sv10 (high), sv1 (low),...,sv10(high), real/im eigenvalue pairs... # so I could use these values as initial conditions to plot. bif_data = np.loadtxt('twodphs_3_HB_PD_q=.1_appended.dat') init_data = np.loadtxt('twodphs_3_init_HB_PD_q=.1_appended.dat') #bif_data = np.loadtxt('twodphs_3_HB_PD_q=.1_appended.dat') #init_data = np.loadtxt('twodphs_3_init_HB_PD_q=.1_appended.dat') # manually get index of sxs value idx = 5 fig = plt.figure(figsize=(7,9)) ### BIFURCATION DIAGRAM gs = gridspec.GridSpec(5, 4) gs.update(hspace=.4) gs.update(wspace=.3) ax11 = plt.subplot(gs[:2, :3]) #ax11 = plt.subplot2grid((4,4),(0,0),colspan=3,rowspan=2) #ax21 = plt.subplot2grid((4,4),(2,0),colspan=3,rowspan=1,sharex=ax11) ax21 = plt.subplot(gs[2:4,:3],sharex=ax11) # pre-allocate for conversion to simple bifurcation data bif_data_simple = np.zeros((len(bif_data[:,0]),6)) # remember write pts from auto gives: par, min, max, type, BR. # parameter value bif_data_simple[:,0] = bif_data[:,3] # max value # first get relative position of desired state variable bif_data_simple[:,1] = bif_data[:,5+idx] # min value bif_data_simple[:,2] = bif_data[:,5+idx+10] # type bif_data_simple[:,3] = bif_data[:,0] # branch bif_data_simple[:,4] = abs(bif_data[:,1]) data = diagram.read_diagram(bif_data_simple) for i in range(1,len(data[0,:])): x = data[:,0] y = data[:,i] data[:,0],data[:,i]=clean(x,y,tol=.1) if (i == 4): print i x = data[:,0] y = data[:,i] data[:,0],data[:,i]=remove_redundant_x(x,y,tol=1e-7) # plot unstable periodic solutions #ax11.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') #ax.scatter(data[:,0],data[:,8],s=10,facecolor='none',edgecolor='blue') ax11.plot(data[:,0],data[:,4],color='blue',zorder=0) # plot stable periodic solutions ax11.plot(data[:,0],data[:,3],color='green',lw=3,zorder=0) #ax11.scatter(data[:,0],data[:,3],s=5,color='green') #ax11.scatter(data[:,0],data[:,7],s=5,color='green') # plot stable periodic solutions ax21.plot(data[:,0],data[:,3],color='green',lw=3,zorder=0) #ax21.scatter(data[:,0],data[:,3],s=5,color='green') #ax21.scatter(data[:,0],data[:,7],s=5,color='green') # plot unstable fixed points #ax21.scatter(data[:,0],data[:,2],s=10,color='black') ax21.plot(data[:,0],data[:,2],color='black',zorder=0) # plot stable fixed points ax21.plot(data[:,0],data[:,1],color='red',lw=3,zorder=0) #ax21.scatter(data[:,0],data[:,1],s=10,color='red') #ax21.scatter(data[:,0],data[:,5],s=10,color='red') #ax21.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') ax21.plot(data[:,0],data[:,4],color='blue',lw=2,zorder=0) """ # bifurcation diagram inset axins11 = inset_axes(ax11, width="60%", # width = 30% of parent_bbox height="40%", # height : 1 inch loc=3) #axins11.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') #axins11.scatter(data[:,0],data[:,3],s=5,color='green') #axins11.scatter(data[:,0],data[:,7],s=5,color='green') #axins11.scatter(g,sxsval,color='purple') mark_inset(ax11, axins11, loc1=2, loc2=4, fc="none", ec="0.5") plt.xticks(visible=False) plt.yticks(visible=False) """ # bifurcation diagram inset ax11.add_patch( patches.Rectangle( (.865, .7), (.88-.865), (1.05-.7), fill=False, alpha=.5 ) ) ax11.text(.82,.66,'**',size=20) ax21.text(.82,.205,'**',size=20) #ax11.plot([.865,.84],[.7,.4],color='gray') #ax11.plot([.88,2.1],[1.05,.4],color='gray') axins21 = inset_axes(ax21, width="78%", height="78%", loc=1) #axins21.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') #axins21.scatter(data[:,0],data[:,3],s=5,color='green') #axins21.scatter(data[:,0],data[:,7],s=5,color='green') #axins11.scatter(g,sxsval,color='purple') axins21.plot(data[:,0],data[:,4],color='blue',zorder=0) axins21.plot(data[:,0],data[:,3],color='green',lw=3,zorder=0) #axins21.text(.866,1.04,'**',size=20) axins21.set_xlim(.865,.88) axins21.set_ylim(.7,1.1) axins21.set_xticks([]) axins21.set_yticks([]) axins21.spines['bottom'].set_color('gray') axins21.spines['top'].set_color('gray') axins21.spines['right'].set_color('gray') axins21.spines['left'].set_color('gray') #mark_inset(ax21, axins21, loc1=2, loc2=1, fc="none", ec="0.5") #plt.xticks(visible=False) #plt.yticks(visible=False) # label bifurcations ax11.annotate("LP1", xy=(.8188,.9727), xycoords='data', xytext=(.8188,1.05), textcoords='data', size=15, color='purple', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate("PD1", xy=(1.64,.59), xycoords='data', xytext=(1.2,.55), textcoords='data', size=15, color='black', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate("PD2", xy=(1.75,.58), xycoords='data', xytext=(1.5,.51), textcoords='data', size=15, color='black', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate("PD3", xy=(1.796,.58), xycoords='data', xytext=(1.7,.5), textcoords='data', size=15, color='black', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate("LP*", xy=(1.818,.59), xycoords='data', xytext=(1.9,.5), textcoords='data', size=15, color='purple', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate("BP1", xy=(2.,.56), xycoords='data', xytext=(2.1,.56), textcoords='data', size=15, color='blue', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate("LP2", xy=(2.03,.59), xycoords='data', xytext=(2.1,.65), textcoords='data', size=15, color='purple', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate('PD4', xy=(1.738, .65), xycoords='data', xytext=(1.5, .9), textcoords='data', size=12, color='.25', zorder=-1, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='.25'), ) ax11.annotate('PD5', xy=(1.738, .68), xycoords='data', xytext=(1.7, .85), textcoords='data', size=12, color='.25', zorder=-1, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='.25'), ) ax21.annotate("HB", xy=(.65,.0), xycoords='data', xytext=(.7,.06), textcoords='data', size=15, color='orange', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) axins21.annotate("TR*", xy=(.8761,.99), xycoords='data', xytext=(.878,1.02), textcoords='data', size=15, color='red', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) ax11.annotate("TR2", xy=(1.18,.95), xycoords='data', xytext=(1.4,1), textcoords='data', size=15, color='red', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) #ax11.xaxis.set_ticks_position('top') ax11.set_ylim(.48,1.1) ax21.set_ylim(-.01,.22) ax11.spines['bottom'].set_visible(False) ax21.spines['top'].set_visible(False) ax11.xaxis.tick_top() ax11.tick_params(labeltop='off') ax21.xaxis.tick_bottom() ax11.set_ylabel('$sx$') ax11.set_xlim(.51,2.3) #ax11.xaxis.set_ticks_position('top') #ax21.xaxis.set_ticks_position('bottom') ax21.set_xlabel('$g$') ax21.xaxis.set_label_coords(1.,0) d = .015 # how big to make the diagonal lines in axes coordinates # arguments to pass to plot, just so we don't keep repeating them kwargs = dict(transform=ax11.transAxes, color='k', clip_on=False) ax11.plot((-d, +d), (-d, +d), **kwargs) # top-left diagonal ax11.plot((1 - d, 1 + d), (-d, +d), **kwargs) # top-right diagonal kwargs.update(transform=ax21.transAxes) # switch to the bottom axes ax21.plot((-d, +d), (1 - d, 1 + d), **kwargs) # bottom-left diagonal ax21.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) # bottom-right diagonal # LOOP OVER SAMPLE SOLUTIONS rlist = [519,1372,886,1164,1654,2349,240,1900]#[957,998,1206,655,634,587,8] loclist = [(4,0),(4,1),(4,2),(0,3),(1,3),(2,3),(3,3),(4,3)] labellist = [r'\textbf{A}',r'\textbf{B}',r'\textbf{C}',r'\textbf{D}',r'\textbf{E}',r'\textbf{F}',r'\textbf{G}',r'\textbf{H}'] pos = [] axlist = [] for i in range(len(rlist)): rown = rlist[i] g = bif_data[rown,3] per = bif_data[rown,5] init = init_data[rown,5:] dt = .01 #print g,per,bif_data[rown,6:6+10] print 'g=',g,'g=',init_data[rown,2],'per=',init_data[rown,4],'init=',init npa, vn = xpprun('twodphs3.ode', xppname='xppaut', inits={'x':init[0],'y':init[1], 'cxs':init[2],'cys':init[3], 'sxs':init[4],'sys':init[5], 'sxsys':init[6],'sxcys':init[7], 'cxsys':init[8],'cxcys':init[9]}, parameters={'total':per, 'g':g, 'q':0.1, 'dt':dt}, clean_after=True) t = npa[:,0] sv = npa[:,1:] idx = vn.index('sxs') sxsval = bif_data[rown,6+idx] #axlist.append(plt.subplot2grid((4,4),loclist[i])) axlist.append(plt.subplot(gs[loclist[i][0],loclist[i][1]])) ### PLOT SAMPLE SOLUTIONS xval = np.mod(sv[:,vn.index('x')]+pi,2*pi)-pi yval = np.mod(sv[:,vn.index('y')]+pi,2*pi)-pi pos1 = np.where(np.abs(np.diff(xval)) >= 1)[0] pos2 = np.where(np.abs(np.diff(yval)) >= 1)[0] xval[pos1] = np.nan yval[pos2] = np.nan xval[pos2] = np.nan yval[pos2] = np.nan #for slc in unlink_wrap(xval): # axlist[i].plot(xval[slc],yval[slc],color='black',lw=2) dashes = [] print bif_data[rown,0] if abs(bif_data[rown,0]) == 4.: dashes = (5,3) axlist[i].plot(xval,yval,color='black',lw=2,dashes=dashes) # label 2 points with arrows back_idx = 10 idxlist = [10,int(1.*(per/dt)/2.)]# depends on period if i == 0: factor = 1.3 back_idx = 400 else: factor = 1. for j in idxlist: axlist[i].annotate("", xy=(factor*xval[j], factor*yval[j]), xycoords='data', xytext=(factor*xval[j-back_idx], factor*yval[j-back_idx]), textcoords='data', size=15, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black') ) axlist[i].set_xlim(-pi,pi) axlist[i].set_ylim(-pi,pi) axlist[i].tick_params(axis=u'both',which=u'both',length=0) axlist[i].set_xticks(np.arange(-1,1+1,1)*pi) axlist[i].set_yticks(np.arange(-1,1+1,1)*pi) x_label = [r"$-\pi$", r"$0$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] axlist[i].set_xticklabels(x_label) axlist[i].set_yticklabels(x_label) if i >= 3: axlist[i].yaxis.tick_right() if i < 3: axlist[i].set_yticklabels([]) if i >= 3 and i < len(labellist)-1: axlist[i].set_xticklabels([]) # annotations corresponding to solution plots ax21.annotate(labellist[i], xy=(g, sxsval), xycoords='data', xytext=(g, sxsval), textcoords='data', size=12, backgroundcolor='yellow', zorder=-1 #arrowprops=dict(arrowstyle="-|>", # connectionstyle="arc3", # color=str(color)), ) ax11.annotate(labellist[i], xy=(g, sxsval), xycoords='data', xytext=(g, sxsval), textcoords='data', size=12, backgroundcolor='yellow', zorder=-1 #arrowprops=dict(arrowstyle="-|>", # connectionstyle="arc3", # color=str(color)), ) axins21.annotate(labellist[i], xy=(g, sxsval), xycoords='data', xytext=(g, sxsval), textcoords='data', size=12, backgroundcolor='yellow', zorder=-1, horizontalalignment='right', #arrowprops=dict(arrowstyle="-|>", # connectionstyle="arc3", # color=str(color)), ) axlist[i].set_title(labellist[i]) #ax11. ax11.scatter(g,sxsval,s=10,color='black',marker='^',zorder=2) ax21.scatter(g,sxsval,s=10,color='black',marker='^',zorder=2) axins21.scatter(g,sxsval,s=10,color='black',marker='^',zorder=2) #axins11.scatter(g,sxsval,s=10,color='black',marker='^') #ax2.plot(t,np.mod(sv[:,vn.index('x')],2*pi)) #ax2.plot(t,np.mod(sv[:,vn.index('sxs')],2*pi)) #ax2.plot(t,np.mod(npa[:,vn.index('sxs')],2*pi)) #ax2.plot(t,np.mod(npa[:,vn.index('y')],2*pi)) return fig def twod_phase_auto_5terms_fig(): """ twod bifurcation diagram for truncated h """ #raw_data = np.loadtxt('twodphs_cys_wave_diagram_q=.125.dat') sv = 'cys' qval = '.5' raw_data = np.loadtxt('twodphs_5_'+sv+'_HB_q='+qval+'.dat') raw_data2 = np.loadtxt('twodphs_5_'+sv+'_TR_q='+qval+'.dat') data = diagram.read_diagram(raw_data) data2 = diagram.read_diagram(raw_data2) fig = plt.figure() ax = fig.add_subplot(111) # plot unstable fixed points ax.scatter(data[:,0],data[:,2],s=10,color='black') ax.scatter(data[:,0],data[:,6],s=10,color='black') #ax.scatter(data3[:,0],data3[:,2],s=10,color='black') #ax.scatter(data3[:,0],data3[:,6],s=10,color='black') # plot unstable periodic solutions ax.scatter(data[:,0],data[:,4],s=10,facecolor='none',edgecolor='blue') #ax.scatter(data[:,0],data[:,8],s=10,facecolor='none',edgecolor='blue') # plot traveling waves ax.scatter(data2[:,0],data2[:,4],s=10,facecolor='none',edgecolor='#0099ff') ax.scatter(data2[:,0],data2[:,8],s=10,facecolor='none',edgecolor='#0099ff') #ax.scatter(data3[:,0],data3[:,4],s=10,facecolor='none',edgecolor='blue') #ax.scatter(data3[:,0],data3[:,8],s=10,facecolor='none',edgecolor='blue') #ax.scatter(data4[:,0],data4[:,4],s=10,facecolor='none',edgecolor='#0099ff') #ax.scatter(data4[:,0],data4[:,8],s=10,facecolor='none',edgecolor='#0099ff') # plot stable fixed points ax.scatter(data[:,0],data[:,1],s=10,color='red') ax.scatter(data[:,0],data[:,5],s=10,color='red') #ax.scatter(data3[:,0],data3[:,1],s=10,color='red') #ax.scatter(data3[:,0],data3[:,5],s=10,color='red') # plot stable periodic solutions ax.scatter(data[:,0],data[:,3],s=20,color='green') ax.scatter(data[:,0],data[:,7],s=20,color='green') # plot stable traveling waves ax.scatter(data2[:,0],data2[:,3],s=20,color='#00cc00') ax.scatter(data2[:,0],data2[:,7],s=20,color='#00cc00') #ax.scatter(data3[:,0],data3[:,3],s=20,color='green') #ax.scatter(data3[:,0],data3[:,7],s=20,color='green') #ax.scatter(data4[:,0],data4[:,3],s=20,color='#00cc00') #ax.scatter(data4[:,0],data4[:,7],s=20,color='#00cc00') #ax.set_xlim(.5,3) #ax.set_ylim(.5,1.) ax.set_title('q='+qval) ax.set_ylabel(sv) return fig def twod_phase_auto_3terms_2par(): """ twod, 2par bifurcation diagram """ data = np.loadtxt('twodphs_3_2par.dat') data2 = np.loadtxt('twodphs_3_2par_TR.dat') # separate by branches # 6 = PD, 2 = LP, 3 = HB TR = data2[(data2[:,-1]==4)] PD = data[(data[:,-1]==6)*(data[:,-2]<9)] PD_gray = data[(data[:,-1]==6)*(data[:,-2]>=9)*(data[:,-2]<=11)] LP = data[data[:,-1]==2] HB = data[data[:,-1]==3] BP = data[data[:,-1]==5] # remove discontinuities TRx,TRy = clean(TR[:,0],TR[:,1],tol=.05) PDx,PDy = clean(PD[:,0],PD[:,1],tol=.05) PD_gx,PD_gy = clean(PD_gray[:,0],PD_gray[:,1],tol=.05) LPx,LPy = clean(LP[:,0],LP[:,1],tol=.05) HBx,HBy = clean(HB[:,0],HB[:,1],tol=.05) BPx,BPy = clean(BP[:,0],BP[:,1],tol=.05) fig = plt.figure(figsize=(5,5)) ax = fig.add_subplot(111) ax.plot([0,2],[.1,.1],color='gray') ax.plot(PD_gx,PD_gy,color='.35',lw=2,ls='--',dashes=(4,1)) ax.plot(TRx,TRy,color='red',lw=2) ax.plot(PDx,PDy,color='black',lw=2) ax.plot(HBx,HBy,color='orange',ls='--',lw=2) ax.plot(LPx,LPy,color='purple',ls='-.',lw=2) ax.plot(BPx,BPy,color='blue',ls='',marker='1',ms=10,lw=2) ax.set_xlabel(r'$g$') ax.set_ylabel(r'$q$') # label regions ax.annotate('1. Stationary Bump', xy=(.5, .55), xycoords='data', xytext=(.5, .55), textcoords='data', size=12, zorder=-1 ) ax.annotate('2. Wobbling Bump', xy=(1.2, .35), xycoords='data', xytext=(1.2, .35), textcoords='data', size=12, zorder=-1 ) ax.annotate('3. Sloshing and Chaos', xy=(1.1, .15), xycoords='data', xytext=(1.1, .25), textcoords='data', size=12, zorder=-1, rotation=30 ) ax.annotate('4. Chaos', xy=(1.1, .15), xycoords='data', xytext=(1.3, .11), textcoords='data', size=12, zorder=-1, rotation=22 ) # label branches ax.annotate('LP1', xy=(1.9, .35), xycoords='data', xytext=(1.9, .35), textcoords='data', size=12, color='purple', zorder=-1 ) ax.annotate('HB', xy=(1.15, .57), xycoords='data', xytext=(1.15, .57), textcoords='data', size=12, color='orange', zorder=-1 ) ax.annotate('PD1', xy=(1.616, .1), xycoords='data', xytext=(1.5, .13), textcoords='data', size=12, color='black', zorder=-1, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax.annotate('PD2', xy=(1.728, .1), xycoords='data', xytext=(1.7, .15), textcoords='data', size=12, color='black', zorder=-1, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax.annotate('PD3', xy=(1.81, .1), xycoords='data', xytext=(1.85, .18), textcoords='data', size=12, color='black', zorder=3, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax.annotate('LP2', xy=(1.8, .06), xycoords='data', xytext=(1.8, .06), textcoords='data', size=12, color='purple', zorder=-1 ) ax.annotate('BP1', xy=(1., .06), xycoords='data', xytext=(1., .06), textcoords='data', size=12, color='blue', zorder=-1 ) ax.annotate('PD4,5', xy=(1.75, .1), xycoords='data', xytext=(1.6, .02), textcoords='data', size=12, color='.25', zorder=-1, arrowprops=dict(arrowstyle="wedge,tail_width=.7", connectionstyle="arc3", color='.25'), ) ax.annotate('TR2', xy=(1.2, .125), xycoords='data', xytext=(1.2, .125), textcoords='data', size=12, color='red', zorder=-1 ) ax.set_xlim(.48,2.) ax.set_ylim(0,.6) return fig def get_solution(g,q,init,per,dt=1.): """ get solution value. specialized function for twod_full_auto_5terms_2par. """ npa, vn = xpprun('full2dbump.ode', xppname='xppaut', inits={'a0':init[0],'a10':init[1], 'a01':init[2],'a11':init[3], 'b10':init[4],'b01':init[5], 'b11':init[6],'c11':init[7],'d11':init[8], 'e0':init[9],'e10':init[10], 'e01':init[11],'e11':init[12], 'f10':init[13],'f01':init[14], 'f11':init[15],'g11':init[16],'h11':init[17] }, parameters={'total':per, 'g':g, 'q':q, 'eps':.05, 'dt':dt}, clean_after=True) t = npa[:,0] sv = npa[:,1:] idx = vn.index('a11') #print idx, vn b01 = sv[:,vn.index('b01')] a01 = sv[:,vn.index('a01')] b10 = sv[:,vn.index('b10')] a10 = sv[:,vn.index('a10')] xval = np.mod(np.arctan2(b01,a01)+5*pi,2*pi)-pi yval = np.mod(np.arctan2(b10,a10)+5*pi,2*pi)-pi pos1 = np.where(np.abs(np.diff(xval)) >= 1)[0] pos2 = np.where(np.abs(np.diff(yval)) >= 1)[0] xval[pos1] = np.nan yval[pos1] = np.nan xval[pos2] = np.nan yval[pos2] = np.nan return xval,yval def get_solution_phase(g,q,init,per,dt=1.): """ get solution value. specialized function for twod_phase_2par. """ npa, vn = xpprun('twodphs3.ode', xppname='xppaut', inits={'x':init[0],'y':init[1], 'cxs':init[2],'cys':init[3], 'sxs':init[4],'sys':init[5], 'sxsys':init[6],'sxcys':init[7], 'cxsys':init[8],'cxcys':init[9]}, parameters={'total':per, 'g':g, 'q':q, 'eps':.05, 'dt':dt}, clean_after=True) t = npa[:,0] sv = npa[:,1:] xval = np.mod(sv[:,vn.index('x')]+pi,2*pi)-pi yval = np.mod(sv[:,vn.index('y')]+pi,2*pi)-pi pos1 = np.where(np.abs(np.diff(xval)) >= 1)[0] pos2 = np.where(np.abs(np.diff(yval)) >= 1)[0] xval[pos1] = np.nan yval[pos2] = np.nan xval[pos2] = np.nan yval[pos2] = np.nan return xval,yval def twod_phase_2par(subplots=1): fig = plt.figure(figsize=(7,7)) gs = gridspec.GridSpec(3,3) ax = plt.subplot(gs[:2,:2]) data = np.loadtxt('twodphs_3_2par.dat') data2 = np.loadtxt('twodphs_3_2par_TR.dat') # separate by branches # 6 = PD, 2 = LP, 3 = HB TR = data2[(data2[:,-1]==4)] PD = data[(data[:,-1]==6)*(data[:,-2]<9)] PD_gray = data[(data[:,-1]==6)*(data[:,-2]>=9)*(data[:,-2]<=11)] LP = data[data[:,-1]==2] HB = data[data[:,-1]==3] BP = data[data[:,-1]==5] # remove discontinuities TRx,TRy = clean(TR[:,0],TR[:,1],tol=.05) PDx,PDy = clean(PD[:,0],PD[:,1],tol=.05) PD_gx,PD_gy = clean(PD_gray[:,0],PD_gray[:,1],tol=.05) LPx,LPy = clean(LP[:,0],LP[:,1],tol=.05) HBx,HBy = clean(HB[:,0],HB[:,1],tol=.05) BPx,BPy = clean(BP[:,0],BP[:,1],tol=.05) #fig = plt.figure(figsize=(5,5)) #ax = fig.add_subplot(111) #ax.plot([0,2],[.1,.1],color='gray') #ax.plot(PD_gx,PD_gy,color='.35',lw=2,ls='--',dashes=(4,1)) #ax.plot(TRx,TRy,color='red',lw=2) #ax.plot(PDx,PDy,color='black',lw=2) ax.plot(HBx,HBy,color='orange',ls='--',lw=2) ax.plot(LPx[:100],LPy[:100],color='purple',ls='-.',lw=2) #ax.plot(BPx,BPy,color='blue',ls='',marker='1',ms=10,lw=2) ax.set_xlabel(r'$g$') ax.set_ylabel(r'$q$') # label regions ax.annotate('1. Stationary Bump', xy=(.5, .55), xycoords='data', xytext=(.5, .55), textcoords='data', size=12, zorder=-1 ) ax.annotate('2. Wobbling Bump', xy=(1.2, .35), xycoords='data', xytext=(1.2, .35), textcoords='data', size=12, zorder=-1 ) ax.annotate('3. Chaos', xy=(1.1, .15), xycoords='data', xytext=(1.3, .11), textcoords='data', size=12, zorder=-1 ) # label branches ax.annotate('LP1', xy=(1.9, .35), xycoords='data', xytext=(1.9, .35), textcoords='data', size=12, color='purple', zorder=-1 ) ax.annotate('HB', xy=(1.15, .57), xycoords='data', xytext=(1.15, .57), textcoords='data', size=12, color='orange', zorder=-1 ) # plot solutions # ######################################################################################### if subplots >= 1: ax13 = plt.subplot(gs[0,-1]) x,y = get_solution_phase(0.,0.,np.zeros(18),1000,dt=1.) ax13.set_title(r"\textbf{(a)}",x=0.1) ax13.xaxis.tick_bottom() ax13.xaxis.set_label_position('bottom') ax13.scatter(x,y,color='black') ax13.set_xlim(-pi,pi) ax13.set_ylim(-pi,pi) ax13.set_xticks([]) ax13.set_yticks([]) #ax13.set_xticks(np.arange(-1,1+.5,.5)*pi) #ax13.set_yticks(np.arange(-1,1+.5,.5)*pi) #x_label = [r"$-\pi$", r"$-\pi/2$", r"$0$", r"$\pi/2$", r"$\pi$"] #x_label = [r"$0$", r"$\frac{\pi}{4}$", r"$\frac{\pi}{2}$", r"$\frac{3\pi}{4}$", r"$\pi$"] #ax13.set_xticklabels(x_label) ax.annotate('', xy=(.2, .7), xycoords='axes fraction', xytext=(1.07, 1.02), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 2: bif_data = np.loadtxt('twodphs_3_HB_PD_q=.1_appended.dat') init_data = np.loadtxt('twodphs_3_init_HB_PD_q=.1_appended.dat') rlist = [540] rown = rlist[0] g = bif_data[rown,3] per = bif_data[rown,5] init = init_data[rown,5:] dt = .01 ax23 = plt.subplot(gs[1,-1]) x,y = get_solution_phase(g,.1,init,per,dt=dt) ax23.set_title(r"\textbf{(b)}",x=0.1) ax23.xaxis.tick_bottom() ax23.xaxis.set_label_position('bottom') ax23.plot(x,y) ax23 = beautify_phase(ax23,x,y,per,dt) ax23.set_xlim(-pi,pi) ax23.set_ylim(-pi,pi) ax23.set_xticks([]) ax23.set_yticks([]) ax.annotate('', xy=(.8, .7), xycoords='axes fraction', xytext=(1.07, .45), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 3: ax33 = plt.subplot(gs[2,-1]) np.random.seed(0) x,y = get_solution_phase(2.,0.,np.random.randn(18),100,dt=.02) ax33.set_title(r"\textbf{(c)}",x=0.1) ax33.xaxis.tick_bottom() ax33.xaxis.set_label_position('bottom') xf = x[-int(10/.02):] yf = y[-int(10/.02):] ax33.plot(xf,yf,lw=3,color='black') ax33 = beautify_phase(ax33,xf,yf,10,.02,arrows=5) ax33.set_xlim(-pi,pi) ax33.set_ylim(-pi,pi) ax33.set_xticks([]) ax33.set_yticks([]) ax.annotate('', xy=(.8, .01), xycoords='axes fraction', xytext=(1.07, -.2), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ######################################################################################### if subplots >= 4: ax32 = plt.subplot(gs[-1,-2]) x,y = get_solution_phase(1.5,.1,np.random.randn(18),100,dt=.05) ax32.set_title(r"\textbf{(d)}",x=0.1) ax32.xaxis.tick_bottom() ax32.xaxis.set_label_position('bottom') xf = x[-int(30/.05):] yf = y[-int(30/.05):] ax32.plot(xf,yf,lw=3,color='black') ax32 = beautify_phase(ax32,xf,yf,30,.05,arrows=4) ax32.set_xlim(-pi,pi) ax32.set_ylim(-pi,pi) ax32.set_xticks([]) ax32.set_yticks([]) ax.annotate('', xy=(.75, .32), xycoords='axes fraction', xytext=(.65, -.16), arrowprops=dict(arrowstyle="<|-|>", color='k',lw=3)) ax.set_xlim(.48,2.) ax.set_ylim(0,.6) return fig def fac(nu,s0=0.,s1=10.,sn=101): """ nu/int e^-s H1(nu s,0)ds """ sarr = np.linspace(s0,s1,sn) ds = (s1 - s0)/sn g_denom = 0. for s in sarr: g_denom += np.exp(-s)*f2d.H1_fourier(nu*s,0)*ds #print f2d.H1_fourier(nu*s,0) #print g_denom return nu/g_denom def ix(nu,lam,choice=1,s0=0.,s1=10.,sn=101): sarr = np.linspace(s0,s1,sn) ds = (s1 - s0)/sn i = 0. for s in sarr: if choice == 1: h1x,h1y = f2d.H1_fourier(nu*s,0,d=True) else: h1x,h1y = f2d.H1_fourier(0,nu*s,d=True) i += np.exp(-s)*h1x*((np.exp(-lam*s)-1)/lam)*ds return i def L(nu,lam,choice=1,s0=0.,s1=40.,sn=501): """ L1 = 1 + g int_0^\infty e^-s \pa H_1/\pa x (nu s, 0) (e^{-\lambda s} - 1)/\lambda ds """ sarr = np.linspace(s0,s1,sn) ds = (s1 - s0)/sn g_denom = 0. for s in sarr: g_denom += np.exp(-s)*f2d.H1_fourier(nu*s,0)*ds #print f2d.H1_fourier(nu*s,0) #print g_denom factor = nu/g_denom i = 0. for s in sarr: if choice == 1: h1x,h1y = f2d.H1_fourier(nu*s,0,d=True) else: h1x,h1y = f2d.H1_fourier(0,nu*s,d=True) i += np.exp(-s)*h1x*((np.exp(-lam*s)-1.)/lam)*ds return 1. + factor*i def L_ana(nu,lam,choice=1): """ analytic version of above. found using long but finite fourier truncation """ print 'using analytic L1,L2' g = (1/(1.04609467947464/(1 + nu**2) + 0.06989538102574108/(1 + 4*nu**2) + 5.002469208435e-6/(1 + 9*nu**2))) if choice == 1: integral = (-1.04609467947464/(1 + nu**2) - 0.06989538102574108/(1 + 4*nu**2) - 5.002469208435e-6/(1 + 9*nu**2) + (1.04609467947464*(1 + lam))/(nu**2 + (1 + lam)**2) + (0.06989538102574108*(1 + lam))/(4*nu**2 + (1 + lam)**2) + (5.002469208435e-6*(1 + lam))/(9*nu**2 + (1 + lam)**2))/lam if choice == 2: integral = (-0.6474559245027758 - 0.46310403788291776/(1 + nu**2) - 0.005435100583895982/(1 + 4*nu**2) + 0.6474559245027758/(1. + lam) + (0.46310403788291776*(1 + lam))/(nu**2 + (1 + lam)**2) + (0.005435100583895982*(1 + lam))/(4*nu**2 + (1 + lam)**2))/lam return 1 + g*integral def wave_stbl_2d(choice='axial'): """ compute eigenvalue as a function of traveling bump velocity in axial or diagonal directions. \lambda_1 &= -\frac{\nu}{\int_0^\infty e^{-s} H_1(\nu s, 0) ds} \int_0^\infty e^{-s} \frac{\pa H_1}{\pa x}(\nu s, 0)[e^{-\lambda_1 s}-1]ds,\\ \lambda_2 &= \frac{\nu}{\int_0^\infty e^{-s} H_1(\nu s, 0) ds} \int_0^\infty e^{-s} \frac{\pa H_1}{\pa y}(0, \nu s)[e^{-\lambda_2 s}-1]ds. """ fig = plt.figure(figsize=(8,3)) ax = fig.add_subplot(121) nu = np.linspace(.001,1.5,200) lam = np.linspace(-.98,.98,200) X,Y = np.meshgrid(nu,lam,indexing='xy') #L(nu,lam,choice=1,s0=0,s1=10,sn=101): z = L(X,Y) z[z>=5] = 5 z[z<=-5] = -5 ax.plot([0,10],[0,0],color='gray') cs = ax.contour(X,Y,z,levels=[-0.00001,0.,.00001]) # remove other curves # customize desired curve cs.collections[0].set_color('black') cs.collections[1].set_color('black') cs.collections[2].set_color('black') cs.collections[1].set_linewidth(2) #cbar = plt.colorbar(cs) #cbar.add_lines(cs) ax.set_ylabel(r'$\lambda_1$') ax.set_xlabel(r'$\nu$') #ax.annotate(r'Stability of solution $\theta_1(\tau)=\nu\tau$',xy=(5.1,.75)) #ax.annotate(r'Unstable',xy=(7.2,.05)) #ax.annotate(r'Stable',xy=(7.2,-.12)) ax2 = fig.add_subplot(122) #nu = np.linspace(0,1.5,150) lam = np.linspace(-.25,.25,150) X,Y = np.meshgrid(nu,lam,indexing='xy') z2 = L_ana(X,Y,choice=2) z2[z2>=5] = 5 z2[z2<=-5] = -5 ax2.plot([0,10],[0,0],color='gray') cs2 = ax2.contour(X,Y,z2,levels=[-0.00001,0.,.00001]) cs2.collections[0].set_color('black') cs2.collections[1].set_color('black') cs2.collections[2].set_color('black') cs2.collections[1].set_linewidth(2) #ax2.annotate(r'Stability of solution $\theta_2(\tau)=0$',xy=(.1,.9)) #ax2.annotate(r'Unstable',xy=(1.25,.019)) #ax2.annotate(r'Stable',xy=(1.25,-.028)) ax2.set_ylabel(r'$\lambda_2$') ax2.set_xlabel(r'$\nu$') ax.set_xlim(0,1.5) ax2.set_xlim(0,1.5) ax2.set_ylim(-.1,.25) #ax2.set_ylabel(r'$\nu$') #p = cs.collections[0].get_paths()[1] #v = p.vertices #cbar2 = plt.colorbar(cs2) #cbar2.add_lines(cs2) #fig.set_clabel(cs, inline=1, fontsize=10) #print fig.__dict__ #ax.plot(v[:,0],v[:,1],color='black') return fig def L_gauss(nu,lam,choice=1,sig=5.): """ gaussian eigenvalue problem """ tot = 0 g_integral = 0 spi = sqrt(pi) L1 = 1 + (5*nu**4*\ ((4*lam*Sqrt(nu**2))/5. + (2*E**((4*Pi**2)/25.)*lam*Sqrt(nu**2))/5. + \ Sqrt(Pi)*(E**(25/(4.*nu**2) + (4*Pi**2)/25.)*Erfc(5/(2.*Sqrt(nu**2))) - \ E**((25*(1 + lam)**2)/(4.*nu**2) + (4*Pi**2)/25.)*(1 + lam)**2*\ Erfc((5*(1 + lam))/(2.*Sqrt(nu**2))) + \ E**((25 - 4*nu*Pi)**2/(100.*nu**2))*Erfc((25 - 4*nu*Pi)/(10.*Sqrt(nu**2))) - \ E**((25*(1 + lam) - 4*nu*Pi)**2/(100.*nu**2))*(1 + lam)**2*\ Erfc((25*(1 + lam) - 4*nu*Pi)/(10.*Sqrt(nu**2))) + \ E**((25 + 4*nu*Pi)**2/(100.*nu**2))*Erfc((25 + 4*nu*Pi)/(10.*Sqrt(nu**2)))) - \ E**((25*(1 + lam) + 4*nu*Pi)**2/(100.*nu**2))*(1 + lam)**2*Sqrt(Pi)*\ Erfc((25*(1 + lam) + 4*nu*Pi)/(10.*Sqrt(nu**2)))))/\ (lam*(nu**2)**1.5*(2*(2 + E**((4*Pi**2)/25.))*nu**2 - \ 5*E**(25/(4.*nu**2) + (4*Pi**2)/25.)*Sqrt(nu**2)*Sqrt(Pi)*(1 + 2*Cosh((2*Pi)/nu)) + \ 5*E**((25 - 4*nu*Pi)**2/(100.*nu**2))*nu*Sqrt(Pi)*\ (E**((2*Pi)/nu)*Erf(5/(2.*nu)) + Erf(5/(2.*nu) - (2*Pi)/5.)) + \ 5*E**((25 + 4*nu*Pi)**2/(100.*nu**2))*nu*Sqrt(Pi)*Erf(5/(2.*nu) + (2*Pi)/5.))) L2 = 1 - (2*(nu**2)**1.5*Sqrt(Pi)*(25*(2 + E**((4*Pi**2)/25.)) - 16*Pi**2)*\ (E**(25/(4.*nu**2) + (4*Pi**2)/25.)*Erfc(5/(2.*Sqrt(nu**2))) - \ E**((25*(1 + lam)**2)/(4.*nu**2) + (4*Pi**2)/25.)*Erfc((5*(1 + lam))/(2.*Sqrt(nu**2))) + \ E**((25 - 4*nu*Pi)**2/(100.*nu**2))*Erfc((25 - 4*nu*Pi)/(10.*Sqrt(nu**2))) - \ E**((25*(1 + lam) - 4*nu*Pi)**2/(100.*nu**2))*\ Erfc((25*(1 + lam) - 4*nu*Pi)/(10.*Sqrt(nu**2))) + \ E**((25 + 4*nu*Pi)**2/(100.*nu**2))*Erfc((25 + 4*nu*Pi)/(10.*Sqrt(nu**2))) - \ E**((25*(1 + lam) + 4*nu*Pi)**2/(100.*nu**2))*\ Erfc((25*(1 + lam) + 4*nu*Pi)/(10.*Sqrt(nu**2)))))/\ (125.*(2 + E**((4*Pi**2)/25.))*lam*\ (2*(2 + E**((4*Pi**2)/25.))*nu**2 - \ 5*E**(25/(4.*nu**2) + (4*Pi**2)/25.)*Sqrt(nu**2)*Sqrt(Pi)*(1 + 2*Cosh((2*Pi)/nu)) + \ 5*E**((25 - 4*nu*Pi)**2/(100.*nu**2))*nu*Sqrt(Pi)*\ (E**((2*Pi)/nu)*Erf(5/(2.*nu)) + Erf(5/(2.*nu) - (2*Pi)/5.)) + \ 5*E**((25 + 4*nu*Pi)**2/(100.*nu**2))*nu*Sqrt(Pi)*Erf(5/(2.*nu) + (2*Pi)/5.))) if choice == 1: return L1 return L2 def wave_stbl_2d_gauss(): """ compute eigenvalue as a function of traveling bump velocity in axial or diagonal directions. the h function is given to be the negative derivative of the gaussian. \lambda_1 &= -\frac{\nu}{\int_0^\infty e^{-s} H_1(\nu s, 0) ds} \int_0^\infty e^{-s} \frac{\pa H_1}{\pa x}(\nu s, 0)[e^{-\lambda_1 s}-1]ds,\\ \lambda_2 &= \frac{\nu}{\int_0^\infty e^{-s} H_1(\nu s, 0) ds} \int_0^\infty e^{-s} \frac{\pa H_1}{\pa y}(0, \nu s)[e^{-\lambda_2 s}-1]ds. """ fig = plt.figure(figsize=(8,3)) ax = fig.add_subplot(121) ax2 = fig.add_subplot(122) nu = np.linspace(.001,2.,100) lam = np.linspace(-3,.5,100) nu2 = np.linspace(.001,2.,100) lam2 = np.linspace(-3,.5,100) X,Y = np.meshgrid(nu,lam,indexing='xy') X2,Y2 = np.meshgrid(nu2,lam2,indexing='xy') #L(nu,lam,choice=1,s0=0,s1=10,sn=101): z = L_gauss(X,Y) z2 = L_gauss(X2,Y2,choice=2) z[z>=5] = 5 z[z<=-5] = -5 z2[z2>=5] = 5 z2[z2<=-5] = -5 ax.plot([0,nu[-1]],[0,0],color='gray') ax2.plot([0,nu2[-1]],[0,0],color='gray') cs = ax.contour(X,Y,z,levels=[-0.00001,0.,.00001]) cs2 = ax2.contour(X2,Y2,z2,levels=[-0.00001,0.,.00001]) #cs = ax.contour(X,Y,z) #cs2 = ax2.contour(X2,Y2,z2) # remove other curves # customize desired curve cs.collections[0].set_color('black') cs.collections[1].set_color('black') cs.collections[2].set_color('black') cs2.collections[0].set_color('black') cs2.collections[1].set_color('black') cs2.collections[2].set_color('black') cs.collections[1].set_linewidth(2) cs2.collections[1].set_linewidth(2) ax.set_xlabel(r'$\nu$') ax2.set_xlabel(r'$\nu$') ax.set_ylabel(r'$\lambda_1$') ax2.set_ylabel(r'$\lambda_2$') return fig def wave_exist_2d(choice='axial'): """ plot zeros of -nu1 + G(nu1,nu2) and -nu2 + G(nu2,nu1) """ nc1x = np.loadtxt('twod_wave_exist_nc_g=1x.dat') nc1y = np.loadtxt('twod_wave_exist_nc_g=1y.dat') nc2x = np.loadtxt('twod_wave_exist_nc_g=3x.dat') nc2y = np.loadtxt('twod_wave_exist_nc_g=3y.dat') # nc1 bifurcation values bif = np.loadtxt('twod_wave_exist_br1.dat') #bif2 = np.loadtxt('twod_wave_exist_br2.dat') bif_diag1 = np.loadtxt('twod_wave_exist_diag1.dat') bif_diag2 = np.loadtxt('twod_wave_exist_diag2.dat') # clean nc1xx,nc1xy = clean(nc1x[:,0],nc1x[:,1],tol=.05) nc1yx,nc1yy = clean(nc1y[:,0],nc1y[:,1],tol=.05) nc2xx,nc2xy = clean(nc2x[:,0],nc2x[:,1],tol=.1) nc2yx,nc2yy = clean(nc2y[:,0],nc2y[:,1],tol=.1) bifx,bify = clean(bif[:,3],bif[:,7],tol=1) bifx2,bify2 = clean(bif[:,3],bif[:,8],tol=.2) bif_diag1x,bif_diag1y = clean(bif_diag1[:,0],np.abs(bif_diag1[:,1]),tol=.2) bif_diag2x,bif_diag2y = clean(bif_diag2[:,0],np.abs(bif_diag2[:,1]),tol=.2) fig = plt.figure(figsize=(8,3)) ax1 = fig.add_subplot(121) ax1.plot(nc1xx,nc1xy) ax1.plot(nc1yx,nc1yy) ax1.plot(nc2xx,nc2xy) ax1.plot(nc2yx,nc2yy) #ax1.plot(nc2yx,nc2yy) ax1.annotate(r'$g=1$', xy=(.21, .21), xycoords='data', xytext=(.3, .75), textcoords='data', size=12, zorder=2, arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate(r'$g=3$', xy=(.934, 1.37), xycoords='data', xytext=(1.3, 1.7), textcoords='data', size=12, zorder=2, verticalalignment='top', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate(r'$g=3$', alpha=0.0, xy=(1.16, 1.16), xycoords='data', xytext=(1.3, 1.7), textcoords='data', size=12, zorder=2, verticalalignment='top', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate(r'$g=3$', alpha=0.0, xy=(1.379,.923), xycoords='data', xytext=(1.3, 1.7), textcoords='data', size=12, zorder=2, verticalalignment='top', arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) axins1 = inset_axes(ax1, width="30%", height="30%", loc=8) mark_inset(ax1, axins1, loc1=2, loc2=4, fc="none", ec="0.5") axins1.plot(nc1xx,nc1xy) axins1.plot(nc1yx,nc1yy) axins1.set_xlim(.1,.3) axins1.set_ylim(.1,.3) #mark_inset(ax21, axins21, loc1=2, loc2=1, fc="none", ec="0.5") plt.xticks(visible=False) plt.yticks(visible=False) ax2 = fig.add_subplot(122) ax2.plot(bifx,bify,color='black') ax2.plot(bifx2,bify2,color='black') ax2.plot(bif_diag1x,bif_diag1y,color='black') ax2.plot(bif_diag2x,bif_diag2y,color='black') ax2.plot([0,5],[0,0],color='black') ax2.annotate(r'$x$-axis direction', xy=(1.04,.37),xycoords='data',textcoords='data', xytext=(.6,.6), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(1.0,.0),xycoords='data',textcoords='data', xytext=(.55,.33), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.9,.0),xycoords='data',textcoords='data', xytext=(.8,.05), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Diagonal', xy=(1.1,.32),xycoords='data',textcoords='data', xytext=(1.4,.2), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', xy=(1.4,.41),xycoords='data',textcoords='data', xytext=(1.5,.34), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(1.4,.62),xycoords='data',textcoords='data', xytext=(1.5,.34), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) """ import matplotlib.patches as patches ax2.add_patch( patches.Rectangle( (1.17,-3),1,6, color='red', alpha=.25 ) ) """ ax2.annotate('Multiple non-axial directions',xy=(3.68,.1),xycoords='data',textcoords='data',xytext=(3.,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.plot([1.17,1.17],[-3,3],color='gray') ax2.plot([3.,3.],[-3,3],color='gray') ax1.set_ylabel(r'$\nu_2$') ax1.set_xlabel(r'$\nu_1$') ax2.set_ylabel(r'$\nu_1$') ax2.set_xlabel(r'$g$') ax1.set_xlim(-.05,2.) ax1.set_ylim(-.05,2.) ax2.set_xlim(.5,2.) ax2.set_ylim(-.1,1) return fig def wave_exist_2d_v2(): # nc1 bifurcation values L1 = np.loadtxt('twod_wave_exist_br1.dat') L2 = np.loadtxt('twod_wave_exist_diag1.dat') M1 = np.loadtxt('twod_wave_exist_br2.dat') M2 = np.loadtxt('twod_wave_exist_diag2.dat') # clean bifx,bify = clean(L1[:,3],L1[:,7],tol=1) bifx2,bify2 = clean(bif[:,3],bif[:,8],tol=.2) bif_diag1x,bif_diag1y = clean(bif_diag1[:,0],np.abs(bif_diag1[:,1]),tol=.2) bif_diag2x,bif_diag2y = clean(bif_diag2[:,0],np.abs(bif_diag2[:,1]),tol=.2) fig = plt.figure(figsize=(8,3)) ax1 = fig.add_subplot(121) ax1.plot(nc1xx,nc1xy) ax1.plot(nc1yx,nc1yy) ax1.plot(nc2xx,nc2xy) ax1.plot(nc2yx,nc2yy) plane1_z = 0.55 plane2_z = 0.889 g = np.linspace(0+.0*1j,2+0.*1j,1000) # nu1 branches L1 = Sqrt(-1 + 1.8*g) L2 = Sqrt(-5 + (4 + b)*g + Sqrt(9 + 6*(-4 + b)*g + (4 + b)**2*g**2))/(2.*Sqrt(2)) L3 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) - \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. L4 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) + \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. L5 = 0.*g # nu2 branches M1 = 0.*g M2 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-5 + (4 + b)*g + Sqrt(9 + 6*(-4 + b)*g + (4 + b)**2*g**2))))/(2.*Sqrt(2)*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M3 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) + Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))))/(2.*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M4 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) - Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))))/(2.*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M5 = Sqrt(-1 + 1.8*g) print M2 fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121, projection='3d') ax2 = fig.add_subplot(122) # get plane intersection idx g_int_p1 = np.argmin(np.abs(g-plane1_z)) g_int_p2 = np.argmin(np.abs(g-plane2_z)) ax1.scatter(L1[g_int_p1],g[g_int_p1],M1[g_int_p1],color='black',s=20) ax1.scatter(L1[g_int_p2],g[g_int_p2],M1[g_int_p2],color='black',s=20) ax1.scatter(L2[g_int_p1],g[g_int_p1],M2[g_int_p1],color='black',s=20) ax1.scatter(L2[g_int_p2],g[g_int_p2],M2[g_int_p2],color='black',s=20) ax1.scatter(L3[g_int_p1],g[g_int_p1],M3[g_int_p1],color='black',s=20) ax1.scatter(L3[g_int_p2],g[g_int_p2],M3[g_int_p2],color='black',s=20) ax1.scatter(L4[g_int_p1],g[g_int_p1],M4[g_int_p1],color='black',s=20) ax1.scatter(L4[g_int_p2],g[g_int_p2],M4[g_int_p2],color='black',s=20) # plot curves in 3d ax1.plot(L1,g,M1,color='black',lw=2) ax1.plot(L2,g,M2,color='black',lw=2) ax1.plot(L3,g,M3,color='black',lw=2) ax1.plot(L4,g,M4,color='black',lw=2) ax1.plot(L5,g,M5,color='black',lw=2) # plot curves in 2d ax2.plot(g,L1,color='black',lw=2) ax2.plot(g,L2,color='black',lw=2) ax2.plot(g,L3,color='black',lw=2) ax2.plot(g,L4,color='black',lw=2) # plot bifurcation planes X,Y = np.meshgrid(np.linspace(g[0],g[-1],10),np.linspace(g[0],g[-1],10)) ax1.plot_surface(X,0.*X+plane1_z,Y,alpha=.3,color='gray') ax1.plot_surface(X,0.*X+plane2_z,Y,alpha=.3,color='red') # plot bifurcation lines ax2.plot([plane1_z,plane1_z],[0,1.8],color='black',alpha=.5,lw=2) ax2.plot([plane2_z,plane2_z],[0,1.8],color='red',alpha=.5,lw=2) #ax1.plot([0,5],[0,0],color='black') ax2.annotate(r'$x$-axis direction', xy=(.65,.4),xycoords='data',textcoords='data', xytext=(.2,1.1), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(1.4,.0),xycoords='data',textcoords='data', xytext=(1.3,.3), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.55,.0),xycoords='data',textcoords='data', xytext=(.4,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Diagonal', xy=(1.6,1.05),xycoords='data',textcoords='data', xytext=(1.6,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', xy=(1.4,.63),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(1.4,1.14),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Multiple non-axial directions',xy=(3.68,.1),xycoords='data',textcoords='data',xytext=(3.,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.view_init(20,-8) #ax1.plot([.89,.89],[-3,3],color='gray') #ax1.plot([3.,3.],[-3,3],color='gray') ax1.set_xlabel(r'$\nu_2$') ax1.set_ylabel(r'$g$') ax1.set_zlabel(r'$\nu_1$') ax2.set_xlabel(r'$g$') ax2.set_ylabel(r'$\nu_1$') ax1.set_xlim(0,2.) ax1.set_ylim(0,2.) ax1.set_zlim(-.1,1.8) plt.show() return fig def wave_exist_2d_trunc(b=.8): """ plot zeros of -nu1 + G(nu1,nu2) and -nu2 + G(nu2,nu1) """ g = np.linspace(.0,2,1000) L1 = Sqrt(-1 + 1.8*g) L2 = Sqrt(-5 + (4 + b)*g + Sqrt(9 + 6*(-4 + b)*g + (4 + b)**2*g**2))/(2.*Sqrt(2)) L3 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) - \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. L4 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) + \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. fig = plt.figure(figsize=(5,3)) ax1 = fig.add_subplot(111) ax1.plot(g,L1,color='black') ax1.plot(g,L2,color='black') ax1.plot(g,L3,color='black') ax1.plot(g,L4,color='black') ax1.plot([0,5],[0,0],color='black') ax1.annotate(r'$x$-axis direction', xy=(.65,.4),xycoords='data',textcoords='data', xytext=(.2,1.1), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate(r'$y$-axis direction', xy=(1.4,.0),xycoords='data',textcoords='data', xytext=(1.3,.3), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate(r'$g^*$', xy=(.55,.0),xycoords='data',textcoords='data', xytext=(.4,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate('Diagonal', xy=(1.6,1.05),xycoords='data',textcoords='data', xytext=(1.6,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate('Off-diagonal', xy=(1.4,.63),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate('Off-diagonal', alpha=0., xy=(1.4,1.14),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.annotate('Multiple non-axial directions',xy=(3.68,.1),xycoords='data',textcoords='data',xytext=(3.,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.plot([.89,.89],[-3,3],color='gray') #ax1.plot([3.,3.],[-3,3],color='gray') ax1.set_ylabel(r'$\nu_1$') ax1.set_xlabel(r'$g$') ax1.set_xlim(0,2.) ax1.set_ylim(-.1,1.8) return fig def wave_exist_2d_trunc_v2(b=.8): """ plot zeros of -nu1 + G(nu1,nu2) and -nu2 + G(nu2,nu1) as a function of g """ plane1_z = 0.55 plane2_z = 0.889 g = np.linspace(0+.0*1j,2+0.*1j,1000) # nu1 branches L1 = Sqrt(-1 + 1.8*g) L2 = Sqrt(-5 + (4 + b)*g + Sqrt(9 + 6*(-4 + b)*g + (4 + b)**2*g**2))/(2.*Sqrt(2)) L3 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) - \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. L4 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) + \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. L5 = 0.*g # nu2 branches M1 = 0.*g M2 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-5 + (4 + b)*g + Sqrt(9 + 6*(-4 + b)*g + (4 + b)**2*g**2))))/(2.*Sqrt(2)*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M3 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) + Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))))/(2.*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M4 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) - Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))))/(2.*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M5 = Sqrt(-1 + 1.8*g) print M2 fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121, projection='3d') ax2 = fig.add_subplot(122) # get plane intersection idx g_int_p1 = np.argmin(np.abs(g-plane1_z)) g_int_p2 = np.argmin(np.abs(g-plane2_z)) ax1.scatter(L1[g_int_p1],g[g_int_p1],M1[g_int_p1],color='black',s=20) ax1.scatter(L1[g_int_p2],g[g_int_p2],M1[g_int_p2],color='black',s=20) ax1.scatter(L2[g_int_p1],g[g_int_p1],M2[g_int_p1],color='black',s=20) ax1.scatter(L2[g_int_p2],g[g_int_p2],M2[g_int_p2],color='black',s=20) ax1.scatter(L3[g_int_p1],g[g_int_p1],M3[g_int_p1],color='black',s=20) ax1.scatter(L3[g_int_p2],g[g_int_p2],M3[g_int_p2],color='black',s=20) ax1.scatter(L4[g_int_p1],g[g_int_p1],M4[g_int_p1],color='black',s=20) ax1.scatter(L4[g_int_p2],g[g_int_p2],M4[g_int_p2],color='black',s=20) # plot curves in 3d ax1.plot(L1,g,M1,color='black',lw=2) ax1.plot(L2,g,M2,color='black',lw=2) ax1.plot(L3,g,M3,color='black',lw=2) ax1.plot(L4,g,M4,color='black',lw=2) ax1.plot(L5,g,M5,color='black',lw=2) # plot curves in 2d ax2.plot(g,L1,color='black',lw=2) ax2.plot(g,L2,color='black',lw=2) ax2.plot(g,L3,color='black',lw=2) ax2.plot(g,L4,color='black',lw=2) # plot bifurcation planes X,Y = np.meshgrid(np.linspace(g[0],g[-1],10),np.linspace(g[0],g[-1],10)) ax1.plot_surface(X,0.*X+plane1_z,Y,alpha=.3,color='gray') ax1.plot_surface(X,0.*X+plane2_z,Y,alpha=.3,color='red') # plot bifurcation lines ax2.plot([plane1_z,plane1_z],[0,1.8],color='black',alpha=.5,lw=2) ax2.plot([plane2_z,plane2_z],[0,1.8],color='red',alpha=.5,lw=2) #ax1.plot([0,5],[0,0],color='black') ax2.annotate(r'$x$-axis direction', xy=(.65,.4),xycoords='data',textcoords='data', xytext=(.2,1.1), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(1.4,.0),xycoords='data',textcoords='data', xytext=(1.3,.3), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.55,.0),xycoords='data',textcoords='data', xytext=(.4,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Diagonal', xy=(1.6,1.05),xycoords='data',textcoords='data', xytext=(1.6,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', xy=(1.4,.63),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(1.4,1.14),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Multiple non-axial directions',xy=(3.68,.1),xycoords='data',textcoords='data',xytext=(3.,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.view_init(20,-8) #ax1.plot([.89,.89],[-3,3],color='gray') #ax1.plot([3.,3.],[-3,3],color='gray') ax1.set_xlabel(r'$\nu_2$') ax1.set_ylabel(r'$g$') ax1.set_zlabel(r'$\nu_1$') ax2.set_xlabel(r'$g$') ax2.set_ylabel(r'$\nu_1$') ax1.set_xlim(0,2.) ax1.set_ylim(0,2.) ax1.set_zlim(-.1,1.8) plt.show() return fig def wave_exist_2d_trunc_v3(b=.8): """ plot zeros of -nu1 + G(nu1,nu2) and -nu2 + G(nu2,nu1) as a function of g """ plane1_z = 0.53 plane2_z = 0.88 g = np.linspace(0+.0*1j,1.5+0.*1j,100) # nu1 branches L1 = Sqrt(-1 + 1.8*g) L2 = Sqrt(-5 + (4 + b)*g + Sqrt(9 + 6*(-4 + b)*g + (4 + b)**2*g**2))/(2.*Sqrt(2)) L3 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) - \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. L4 = Sqrt(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) + \ Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + \ 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))/2. L5 = 0.*g # nu2 branches M1 = 0.*g M2 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-5 + (4 + b)*g + Sqrt(9 + 6*(-4 + b)*g + (4 + b)**2*g**2))))/(2.*Sqrt(2)*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M3 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) + Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))))/(2.*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M4 = np.real(Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g)*(-6 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2) - Sqrt(-4*(-5 + Sqrt(16 + (2 + b)**2*g**2)) + 2*g*(-4 + b*(-2 + (2 + b)*g + Sqrt(16 + (2 + b)**2*g**2)))))))/(2.*Sqrt(-(g**3*(2 + g)*(5*(6 + b) + (1 + b)*(8 + 3*b)*g))))) M5 = Sqrt(-1 + 1.8*g) fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121, projection='3d') ax2 = fig.add_subplot(122) # get plane intersection idx g_int_p1 = np.argmin(np.abs(g-plane1_z)) g_int_p2 = np.argmin(np.abs(g-plane2_z)) # plot curves in 3d # prep for plotting with different line widths # add modified curves to figure ax1.add_collection3d(collect3d_colorgrad(L1,g,M1)) ax1.add_collection3d(collect3d_colorgrad(L2,g,M2)) ax1.add_collection3d(collect3d_colorgrad(L3,g,M3)) ax1.add_collection3d(collect3d_colorgrad(L4,g,M4)) ax1.add_collection3d(collect3d_colorgrad(L5,g,M5)) # plot bifurcation planes X,Y = np.meshgrid(np.linspace(0,1.2,10),np.linspace(0,1.2,10)) ax1.plot_surface(X,0.*X+plane1_z,Y,alpha=.2,color='gray') ax1.plot_surface(X,0.*X+plane2_z,Y,alpha=.2,color='red') # plot intersection points # ax1.scatter(L1[g_int_p1],g[g_int_p1],M1[g_int_p1],color='black',s=30) ax1.plot([M3[g_int_p1]],[g[g_int_p1]],[L3[g_int_p1]],color='black',marker='o',markersize=8,zorder=10) #ax1.scatter(L1[g_int_p2],g[g_int_p2],M1[g_int_p2],color='red',s=30) ax1.plot([np.real(L1[g_int_p2])],[np.real(g[g_int_p2])],[np.real(M1[g_int_p2])],marker='o',markersize=8,markeredgecolor='none',zorder=100,color='red') ax1.plot([L2[g_int_p1]],[g[g_int_p1]],[M2[g_int_p1]],color='black',marker='o',markersize=8,zorder=10) #ax1.scatter(L2[g_int_p1],g[g_int_p1],M2[g_int_p1],color='black',s=35) ax1.plot([L2[g_int_p2]],[g[g_int_p2]],[M2[g_int_p2]],marker='o',markersize=7,markeredgecolor='none',zorder=100,color='red') ax1.plot([L3[g_int_p1]],[g[g_int_p1]],[M3[g_int_p1]],color='black',marker='o',markersize=8,zorder=10) ax1.scatter(L3[g_int_p1],g[g_int_p1],M3[g_int_p1],color='black',s=30) ax1.plot([L3[g_int_p2]],[g[g_int_p2]],[M3[g_int_p2]],marker='o',markersize=6,markeredgecolor='none',zorder=100,color='red') #ax1.scatter(L4[g_int_p1],g[g_int_p1],M4[g_int_p1],color='black',s=30) #ax1.scatter(L4[g_int_p2],g[g_int_p2],M4[g_int_p2],color='red',s=30) # plot curves in 2d + 2d projection in 3d plot #ax2.plot([L1[g_int_p1],M1[g_int_p1]],color='black',marker='o',markersize=8,zorder=10) #ax2.scatter(L1[g_int_p2],M1[g_int_p2],color='red',s=50,zorder=10) ax1.plot([L1[g_int_p1]],[1.5],[M1[g_int_p1]],marker='o',markeredgecolor='none',color='black',markersize=8,zorder=100) ax1.plot([L1[g_int_p2]],[1.5],[M1[g_int_p2]],marker='o',markeredgecolor='none',color='red',markersize=8,zorder=100) ax2.plot([L2[g_int_p1]],[M2[g_int_p1]],color='black',marker='o',markersize=8) ax2.scatter(L2[g_int_p2],M2[g_int_p2],color='red',s=70,zorder=10) ax1.plot([L2[g_int_p1]],[1.5],[M2[g_int_p1]],marker='o',markeredgecolor='none',color='black',markersize=8,zorder=100) ax1.plot([L2[g_int_p2]],[1.5],[M2[g_int_p2]],marker='o',markeredgecolor='none',color='red',markersize=8,zorder=100) ax2.scatter(L3[g_int_p1],M3[g_int_p1],color='black',s=70,zorder=10) ax2.scatter(L3[g_int_p2],M3[g_int_p2],color='red',s=70,zorder=10) ax1.plot([L3[g_int_p1]],[1.5],[M3[g_int_p1]],marker='o',markeredgecolor='none',color='black',markersize=8,zorder=100) ax1.plot([L3[g_int_p2]],[1.5],[M3[g_int_p2]],marker='o',markeredgecolor='none',color='red',markersize=8,zorder=100) ax2.scatter(L4[g_int_p1],M4[g_int_p1],color='black',s=70,zorder=10) ax2.scatter(L4[g_int_p2],M4[g_int_p2],color='red',s=70,zorder=10) ax1.plot([L4[g_int_p1]],[1.5],[M4[g_int_p1]],marker='o',markeredgecolor='none',color='black',markersize=8,zorder=100) ax1.plot([L4[g_int_p2]],[1.5],[M4[g_int_p2]],marker='o',markeredgecolor='none',color='red',markersize=8,zorder=100) cmap = plt.get_cmap('gray_r') my_cmap = truncate_colormap(cmap,.0,.75) ax2.add_collection(collect(L1,M1,lwstart=3.,lwfactor=4.)) ax1.add_collection3d(collect(L1,M1,lwstart=3.,lwfactor=4.),zs=1.5,zdir='y') #ax2.plot(L1,M1) ax2.add_collection(collect(L2,M2,lwstart=3.,lwfactor=4.)) ax1.add_collection3d(collect(L2,M2,lwstart=3.,lwfactor=4.),zs=1.5,zdir='y') #ax2.plot(L2,M2) ax2.add_collection(collect(L3,M3,lwstart=3.,lwfactor=4.)) ax1.add_collection3d(collect(L3,M3,lwstart=3.,lwfactor=4.),zs=1.5,zdir='y') #ax2.plot(L3,M3) ax2.add_collection(collect(L4,M4,lwstart=3.,lwfactor=4.)) ax1.add_collection3d(collect(L4,M4,lwstart=3.,lwfactor=4.),zs=1.5,zdir='y') #ax2.plot(L4,M4) ax2.add_collection(collect(L5,M5,lwstart=3.,lwfactor=4.)) ax1.add_collection3d(collect(L5,M5,lwstart=3.,lwfactor=4.),zs=1.5,zdir='y') #ax2.plot(L5,M5) #ax1.plot([0,5],[0,0],color='black') ax2.annotate(r'$x$-axis direction', xy=(.65,.01),xycoords='data',textcoords='data', xytext=(.45,.2), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(.01,.65),xycoords='data',textcoords='data', xytext=(.1,.45), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.03,.015),xycoords='data',textcoords='data', xytext=(.2,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) """ ax2.annotate(r'$g^*$', alpha=0., xy=(.01,.01),xycoords='data',textcoords='data', xytext=(.4,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) """ ax2.annotate('Diagonal direction', xy=(.68,.7),xycoords='data',textcoords='data', xytext=(.2,.65), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal\\direction', xy=(1.4,.63),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(1.4,1.14),xycoords='data',textcoords='data', xytext=(1.3,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Multiple non-axial directions',xy=(3.68,.1),xycoords='data',textcoords='data',xytext=(3.,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) #ax1.plot([.89,.89],[-3,3],color='gray') #ax1.plot([3.,3.],[-3,3],color='gray') ax1.view_init(20,-8) ax1.set_xlim(0,1.2) ax1.set_ylim(0,1.5) ax1.set_zlim(0.,1.2) ax1.set_xlabel(r'$\nu_1$') ax1.set_ylabel(r'$g$') ax1.set_zlabel(r'$\nu_2$') ax2.set_xlabel(r'$\nu_1$') ax2.set_ylabel(r'$\nu_2$') ax2.set_xlim(-.05,1.2) ax2.set_ylim(-.05,1.2) return fig def wave_exist_2d_trunc_v4(b=.8): """ plot zeros of -nu1 + G(nu1,nu2) and -nu2 + G(nu2,nu1) as a function of g """ # get data # nc1 bifurcation values bif = np.loadtxt('twod_wave_trunc_exist_all.dat') #bif2 = np.loadtxt('twod_wave_exist_br2.dat') # get all possible disjoint branches val,ty = collect_disjoint_branches(bif,remove_isolated=True,isolated_number=50) if False: mp.figure() for key in val.keys(): mp.plot(val[key][:,1],val[key][:,2],label=key) mp.legend() mp.show() # fix branches to satisfy bounds # bound the values # .5 <= g <= 1.6 # 0 <= vi <= .8 gmin = 0. gmax = 4. vimin = 0. vimax = 2. # loop over each branch # add bounded guys to new dict val_final val_final = {} ty_final = {} for key in val.keys(): g = val[key][:,0] v1 = val[key][:,2] v2 = val[key][:,3] idx = ((g>=gmin)*(g<=gmax)* (v1>=vimin)*(v1<=vimax)* (v2>=vimin)*(v2<=vimax)) if (len(g[idx]) == 0) or\ (len(v1[idx]) == 0) or\ (len(v2[idx]) == 0): pass else: #print key,ty[key][0,1] val_final[key] = np.zeros((len(g[idx]),3)) val_final[key][:,0] = g[idx] val_final[key][:,1] = v1[idx] val_final[key][:,2] = v2[idx] ty_final[key] = ty[key] #print key,ty_final[key] #bifx_raw=bif[:,3];bify_raw=bif[:,7] #bifx2_raw=bif[:,3];bify2_raw=bif[:,8] # use this plot to choose branches if False: mp.figure() for key in val_final.keys(): mp.plot(val_final[key][:,1],val_final[key][:,2],label=key) mp.legend() mp.show() #print #br14 #br23 #br48 #br40 """ val_final.pop('br12') val_final.pop('br10') val_final.pop('br14') #val_final.pop('br29') # need. axial. #val_final.pop('br30') # need. axial. #val_final.pop('br35') # need. axial. #val_final.pop('br36') # need. axial. #val_final.pop('br2') # need. zero. val_final.pop('br20') #val_final.pop('br4') """ plane1_z = 0.75 plane2_z = 2.4 """ # get plane intersection idx bifx_int_p1 = np.argmin(np.abs(bifx_nonan-plane1_z)) bifx_int_p2 = np.argmin(np.abs(bifx_nonan-plane2_z)) bifx2_int_p1 = np.argmin(np.abs(bifx2_nonan-plane1_z)) bifx2_int_p2 = np.argmin(np.abs(bifx2_nonan-plane2_z)) """ fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121, projection='3d') ax1 = fig.add_axes(MyAxes3D(ax1, 'l')) ax2 = fig.add_subplot(122) # add modified curves to figure for key in val_final.keys(): g = val_final[key][:,0] v1 = val_final[key][:,1] v2 = val_final[key][:,2] #print g if key == 'br29' or key == 'br35': ax1.add_collection3d(collect3d_colorgrad(v1,g,v2,use_nonan=False,zorder=4, lwstart=2,lwend=4, cmapmin=.3,cmapmax=.7)) if key == 'br35': ax1.add_collection3d(collect3d_colorgrad(v2,g,v1,use_nonan=False,zorder=4, lwstart=2,lwend=4, cmapmin=.3,cmapmax=.7)) elif key == 'br30' or key == 'br36': ax1.add_collection3d(collect3d_colorgrad(v1,g,v2,use_nonan=False,zorder=4, lwstart=4,lwend=5, cmapmin=.7,cmapmax=1.)) elif key == 'br48' or key == 'br40': ax1.add_collection3d(collect3d_colorgrad(v1,g,v2,use_nonan=False,zorder=4, lwstart=4,lwend=5, cmapmin=.7,cmapmax=1.)) elif key == 'br2': pass #ax1.add_collection3d(collect3d_colorgrad(v1[v1>.01],g[v1>.01],v2[v1>.01],use_nonan=False,zorder=4, # lwstart=1,lwend=5, # cmapmin=.3,cmapmax=1.)) else: print key ax1.add_collection3d(collect3d_colorgrad(v1,g,v2,use_nonan=False,zorder=4, lwstart=1,lwend=5, cmapmin=.3,cmapmax=1.)) # plot beginning zero guy g = np.linspace(gmin,.75,10) ax1.add_collection3d(collect3d_colorgrad(0.*g,g,0.*g,use_nonan=False,zorder=2, lwstart=1,lwend=2, cmapmin=.1,cmapmax=.3)) # plot bifurcation planes X,Y = np.meshgrid(np.linspace(0,vimax,10),np.linspace(0,vimax,10)) Xhalf1,Yhalf1 = np.meshgrid(np.linspace(1.3,vimax,10),np.linspace(0,vimax,10)) Xhalf2,Yhalf2 = np.meshgrid(np.linspace(0,1.3,10),np.linspace(0,1.1,10)) Xhalf3,Yhalf3 = np.meshgrid(np.linspace(0,1.3,10),np.linspace(1.1,vimax,10)) #ax1.plot_surface(Xhalf1,0.*Xhalf1+plane2_z,Yhalf1,alpha=.6,color='green',lw=0,edgecolor='none',zorder=1) ax1.plot_surface(X,0.*X+plane1_z,Y,alpha=.6,color='red',lw=0,edgecolor='none') ax1.plot_surface(Xhalf1,0.*X+plane2_z,Yhalf1,alpha=.6,color='green',lw=0,edgecolor='none') ax1.plot_surface(Xhalf2,0.*X+plane2_z,Yhalf2,alpha=.6,color='green',lw=0,edgecolor='none',zorder=-1) ax1.plot_surface(Xhalf3,0.*X+plane2_z,Yhalf3,alpha=.6,color='green',lw=0,edgecolor='none',zorder=1) #ax1.plot_surface(X,0.*X+plane2_z,Y,alpha=.6,color='green') # plot intersection points #ax1.plot([0.],[1.17],[.51],marker='o',markersize='6',color='red',markeredgecolor='none',zorder=100) ax1.plot([0.],[plane1_z],[0],marker='o',color='black',markersize=8,zorder=100,markeredgecolor='none') ax1.plot([1.45],[plane2_z],[0],marker='o',color='red',markersize=8,zorder=100,markeredgecolor='none') ax1.plot([0],[plane2_z],[1.45],marker='o',color='red',markersize=8,zorder=100,markeredgecolor='none') ax1.plot([1.05],[plane2_z],[1.05],marker='o',color='red',markersize=8,zorder=100,markeredgecolor='none') # plot projection ax1.plot([0.],[gmax],[0],marker='o',color='black',markersize=8,zorder=100,markeredgecolor='none') ax1.plot([1.45],[gmax],[0],marker='o',color='red',markersize=8,zorder=100,markeredgecolor='none') ax1.plot([0],[gmax],[1.45],marker='o',color='red',markersize=8,zorder=100,markeredgecolor='none') ax1.plot([1.05],[gmax],[1.05],marker='o',color='red',markersize=8,zorder=100,markeredgecolor='none') # plot curves in 2d + 2d projection in 3d plot zs = gmax # axial guys for key in val_final.keys(): g = val_final[key][:,0] v1 = val_final[key][:,1] v2 = val_final[key][:,2] if key == 'br29' or key == 'br35': ax2.add_collection(collect(v1,v2,use_nonan=False,lwstart=2.,lwend=4.,cmapmin=.3,cmapmax=.7,zorder=5)) ax1.add_collection3d(collect(v1,v2,use_nonan=False,lwstart=2.,lwend=4.,cmapmin=.3,cmapmax=.7,zorder=5),zs=zs,zdir='y') elif key == 'br30' or key == 'br36': ax2.add_collection(collect(v1,v2,use_nonan=False,lwstart=4.,lwend=5.,cmapmin=.7,cmapmax=1,zorder=5)) ax1.add_collection3d(collect(v1,v2,use_nonan=False,lwstart=4.,lwend=5.,cmapmin=.7,cmapmax=1,zorder=5),zs=zs,zdir='y') elif key == 'br48' or key == 'br40': ax2.add_collection(collect(v1,v2,use_nonan=False,lwstart=4.,lwend=5.,cmapmin=.7,cmapmax=1,zorder=5)) ax1.add_collection3d(collect(v1,v2,use_nonan=False,lwstart=4.,lwend=5.,cmapmin=.7,cmapmax=1,zorder=5),zs=zs,zdir='y') ax2.add_collection(collect(v1,v2,use_nonan=False,lwstart=2.,lwend=5.,cmapmin=.3,zorder=5)) ax1.add_collection3d(collect(v1,v2,use_nonan=False,lwstart=2.,lwend=5.,cmapmin=.3,zorder=5),zs=zs,zdir='y') # plot intersections on 2d ax2.scatter([0],[0],marker='o',color='black',s=70,zorder=100) ax2.scatter([1.45],[0],marker='o',color='red',s=70,zorder=100) ax2.scatter([0],[1.45],marker='o',color='red',s=70,zorder=100) ax2.scatter([1.05],[1.05],marker='o',color='red',s=70,zorder=100) #ax1.plot([0,5],[0,0],color='black') ax2.annotate(r'$x$-axis direction', xy=(.65,.01),xycoords='data',textcoords='data', xytext=(.45,.2), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(.01,.65),xycoords='data',textcoords='data', xytext=(.1,1.), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.03,.015),xycoords='data',textcoords='data', xytext=(.2,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) """ ax2.annotate(r'$g^*$', alpha=0., xy=(.01,.01),xycoords='data',textcoords='data', xytext=(.4,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) """ ax2.annotate('Diagonal direction', xy=(.7,.7),xycoords='data',textcoords='data', xytext=(.9,.65), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', xy=(1.75,.5),xycoords='data',textcoords='data', xytext=(1.5,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(.5,1.75),xycoords='data',textcoords='data', xytext=(1.5,1.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Multiple non-axial directions',xy=(3.68,.1),xycoords='data',textcoords='data',xytext=(3.,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) #ax1.plot([.89,.89],[-3,3],color='gray') #ax1.plot([3.,3.],[-3,3],color='gray') ax1.view_init(20,-8) """ tmp_planes = ax1.zaxis._PLANES ax1.zaxis._PLANES = ( tmp_planes[2], tmp_planes[3], tmp_planes[0], tmp_planes[1], tmp_planes[4], tmp_planes[5]) """ ax1.set_xlim(vimin,vimax) ax1.set_ylim(gmin,gmax) ax1.set_zlim(vimin,vimax) ax1.set_xlabel(r'$\nu_1$') ax1.set_ylabel(r'$g$') ax1.set_zlabel(r'$\nu_2$') ax2.set_xlabel(r'$\nu_1$') ax2.set_ylabel(r'$\nu_2$') ax2.set_xlim(-.05+vimin,vimax) ax2.set_ylim(-.05+vimin,vimax) return fig def wave_exist_2d_full_v2(b=.8): """ plot zeros of -nu1 + G(nu1,nu2) and -nu2 + G(nu2,nu1) as a function of g use accurate fourier series """ # get data # nc1 bifurcation values bif = np.loadtxt('twod_wave_exist_br1.dat') #bif2 = np.loadtxt('twod_wave_exist_br2.dat') bif_diag1 = np.loadtxt('twod_wave_exist_diag1.dat') bif_diag2 = np.loadtxt('twod_wave_exist_diag2.dat') # clean bifx,bify = clean(bif[:,3],bif[:,7],tol=.47) bifx2,bify2 = clean(bif[:,3],bif[:,8],tol=.47) bif_diag1x,bif_diag1y = clean(bif_diag1[:,0],np.abs(bif_diag1[:,1]),tol=.2) bif_diag2x,bif_diag2y = clean(bif_diag2[:,0],np.abs(bif_diag2[:,1]),tol=.2) # remove nans for calculating minima (usually nans are taken to be max/min vals, which is bad) bifx_nonan = bifx[(~np.isnan(bifx))*(~np.isnan(bify))] bify_nonan = bify[(~np.isnan(bifx))*(~np.isnan(bify))] bifx2_nonan = bifx2[(~np.isnan(bifx2))*(~np.isnan(bify2))] bify2_nonan = bify2[(~np.isnan(bifx2))*(~np.isnan(bify2))] bif_diag1x_nonan = bif_diag1x[(~np.isnan(bif_diag1x))*(~np.isnan(bif_diag1y))] bif_diag1y_nonan = bif_diag1y[(~np.isnan(bif_diag1x))*(~np.isnan(bif_diag1y))] bif_diag2x_nonan = bif_diag2x[(~np.isnan(bif_diag2x))*(~np.isnan(bif_diag2y))] bif_diag2y_nonan = bif_diag2y[(~np.isnan(bif_diag2x))*(~np.isnan(bif_diag2y))] fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121, projection='3d') ax2 = fig.add_subplot(122) plane1_z = .895 plane2_z = 1.17 # get plane intersection idx bifx_int_p1 = np.argmin(np.abs(bifx_nonan-plane1_z)) bifx_int_p2 = np.argmin(np.abs(bifx_nonan-plane2_z)) bifx2_int_p1 = np.argmin(np.abs(bifx2_nonan-plane1_z)) bifx2_int_p2 = np.argmin(np.abs(bifx2_nonan-plane2_z)) bif_diagx_int_p1 = np.argmin(np.abs(bif_diag1x_nonan-plane1_z)) bif_diagx_int_p2 = np.argmin(np.abs(bif_diag1x_nonan-plane2_z)) bif_diagx2_int_p1 = np.argmin(np.abs(bif_diag2x_nonan-plane1_z)) bif_diagx2_int_p2 = np.argmin(np.abs(bif_diag2x_nonan-plane2_z)) ## plot curves in 3d # plot off diagonal and axial curves v1a = bify2[(bify>=0)*(bify2>=0)*(bify<=1)*(bify2<=1)*(bifx<=2)] v2a = bify[(bify>=0)*(bify2>=0)*(bify<=1)*(bify2<=1)*(bifx<=2)] ga = bifx[(bify>=0)*(bify2>=0)*(bify<=1)*(bify2<=1)*(bifx<=2)] #v1b = bif_diag1y[(bif_diag1y>=0)*(bif_diag2y>=0)*(bif_diag1y<=1)*(bif_diag2y<=1)*(bif_diag1x<=2)] #v2b = bif_diag1y[(bif_diag1y>=0)*(bif_diag2y>=0)*(bif_diag1y<=1)*(bif_diag2y<=1)*(bif_diag1x<=2)] gb = np.linspace(np.amin(bif_diag1x[~np.isnan(bif_diag1x)]),np.amax(bif_diag1x[~np.isnan(bif_diag1x)]),20) # clean ga,v1a,v2a = clean3d(ga,v1a,v2a,tol=.47) # remove nans for linewidth stuff later. ga_nonan = ga[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] v1a_nonan = v1a[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] v2a_nonan = v2a[~np.isnan(ga)*(~np.isnan(v1a))*(~np.isnan(v2a))] # prep for plotting with different line widths sol = np.zeros((len(ga),3)) sol[:,0] = v1a sol[:,1] = ga sol[:,2] = v2a sol = np.transpose(sol) points = np.array([sol[0,:],sol[1,:],sol[2,:]]).T.reshape(-1,1,3) segs = np.concatenate([points[:-1],points[1:]],axis = 1) line3d = Line3DCollection(segs,linewidths=(1.+(v1a_nonan)/np.amax(v1a_nonan)*3.),colors='k') # add modified curves to figure ax1.add_collection3d(line3d) # repleat above to capture remaining axial branch(es) # prep for plotting with different line widths sol = np.zeros((len(ga),3)) sol[:,0] = v2a sol[:,1] = ga sol[:,2] = v1a sol = np.transpose(sol) points = np.array([sol[0,:],sol[1,:],sol[2,:]]).T.reshape(-1,1,3) segs = np.concatenate([points[:-1],points[1:]],axis = 1) line3d = Line3DCollection(segs,linewidths=(1.+(v2a_nonan)/np.amax(v2a_nonan)*3.),colors='k') # add modified curves to figure ax1.add_collection3d(line3d) # plot diagonal guys # prep for plotting with different line widths diagx = bif_diag2y[(bif_diag2y<=1)*(bif_diag2x<=2.)] diagy = bif_diag2x[(bif_diag2y<=1)*(bif_diag2x<=2.)] diagz = bif_diag2y[(bif_diag2y<=1)*(bif_diag2x<=2.)] diagx_nonan = diagx[~np.isnan(diagx)] sol = np.zeros((len(diagx),3)) sol[:,0] = diagx sol[:,1] = diagy sol[:,2] = diagz sol = np.transpose(sol) points2 = np.array([sol[0,:],sol[1,:],sol[2,:]]).T.reshape(-1,1,3) segs2 = np.concatenate([points2[:-1],points2[1:]],axis = 1) line3d2 = Line3DCollection(segs2,linewidths=(1.+(diagx_nonan)/np.amax(diagx_nonan)*3.),colors='k') ax1.add_collection3d(line3d2) # plot zero solution ax1.plot([.0,0],[.5,plane1_z],[.0,0],color='black',lw=1) # plot bifurcation planes X,Y = np.meshgrid(np.linspace(0,1,10),np.linspace(0,1,10)) ax1.plot_surface(X,0.*X+plane1_z,Y,alpha=.5,color='gray') ax1.plot_surface(X,0.*X+plane2_z,Y,alpha=.5,color='red') # plot plane intersections ax1.scatter(bify[bifx_int_p1],bifx[bifx_int_p1],bify2[bifx_int_p1],color='black',s=20) #ax1.scatter(bify[bifx_int_p2],bifx[bifx_int_p2],bify2[bifx_int_p2],color='black',s=20) #ax1.scatter(bif_diag2y_nonan[bif_diagx_int_p2],bif_diag1x_nonan[bif_diagx_int_p2],bif_diag1y_nonan[bif_diagx_int_p2],color='black',s=20) ax1.scatter(0,1.17,.51,color='red',s=20,zorder=10) ax1.scatter(.5,1.17,0.,color='red',s=40,zorder=10) ax1.scatter(.37,1.17,.37,color='red',s=50,zorder=10) """ ax1.scatter(L1[g_int_p2],g[g_int_p2],M1[g_int_p2],color='black',s=20) ax1.scatter(L2[g_int_p1],g[g_int_p1],M2[g_int_p1],color='black',s=20) ax1.scatter(L2[g_int_p2],g[g_int_p2],M2[g_int_p2],color='black',s=20) ax1.scatter(L3[g_int_p1],g[g_int_p1],M3[g_int_p1],color='black',s=20) ax1.scatter(L3[g_int_p2],g[g_int_p2],M3[g_int_p2],color='black',s=20) ax1.scatter(L4[g_int_p1],g[g_int_p1],M4[g_int_p1],color='black',s=20) ax1.scatter(L4[g_int_p2],g[g_int_p2],M4[g_int_p2],color='black',s=20) """ ## plot curves in 2d # bifurcation lines ax2.plot([plane1_z,plane1_z],[-1,1.8],color='black',alpha=.5,lw=2) ax2.plot([plane2_z,plane2_z],[-1,1.8],color='red',alpha=.5,lw=2) ax2.plot(bifx,bify,color='black') ax2.plot(bifx2,bify2,color='black') ax2.plot(bif_diag1x,bif_diag1y,color='black') ax2.plot(bif_diag2x,bif_diag2y,color='black') ax2.plot([0,5],[0,0],color='black') # label curves ax2.annotate(r'$x$-axis direction', xy=(1.04,.37),xycoords='data',textcoords='data', xytext=(.6,.6), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(1.0,.0),xycoords='data',textcoords='data', xytext=(.55,.33), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.9,.0),xycoords='data',textcoords='data', xytext=(.8,.05), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Diagonal', xy=(1.1,.32),xycoords='data',textcoords='data', xytext=(1.4,.2), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', xy=(1.4,.41),xycoords='data',textcoords='data', xytext=(1.5,.34), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(1.4,.62),xycoords='data',textcoords='data', xytext=(1.5,.34), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) # plot params ax1.view_init(20,-8) # set labels ax1.set_xlabel(r'$\nu_2$') ax2.set_xlabel(r'$g$') ax1.set_ylabel(r'$g$') ax2.set_ylabel(r'$\nu_1$') ax1.set_zlabel(r'$\nu_1$') ax1.set_xlim(0.,1.) ax2.set_xlim(.5,2.) ax1.set_ylim(.5,2.) ax2.set_ylim(-.05,1.) ax1.set_zlim(0.,1.) #plt.show() return fig def wave_exist_2d_full_v2_testing(b=.8): """ testing to figure out how to implement lw changes in 1 plot. """ #from matplotlib.collections import LineCollection from matplotlib.collections import PolyCollection from matplotlib import colors as mcolors fig = plt.figure() ax = fig.gca(projection='3d') xcoord = np.linspace(0,pi,100) ycoord = np.linspace(0,pi,100) xs = cos(xcoord)+6. ys = 3*sin(ycoord)+1.5 zs = .25+0.*np.sqrt(xcoord**2.+ycoord**2.) sol = np.zeros((len(xs),3)) sol[:,0] = xs sol[:,1] = ys sol[:,2] = zs sol = np.transpose(sol) points = np.array([sol[0,:],sol[1,:],sol[2,:]]).T.reshape(-1,1,3) segs = np.concatenate([points[:-1],points[1:]],axis = 1) line3d = Line3DCollection(segs,linewidths=ys) line3d.set_alpha(0.7) ax.add_collection3d(line3d)#, zs=zs) ax.set_xlabel('X') ax.set_xlim3d(0, 10) ax.set_ylabel('Y') ax.set_ylim3d(-1, 4) ax.set_zlabel('Z') ax.set_zlim3d(0, 1) plt.show() """ from matplotlib.collections import LineCollection x=np.linspace(0,4*pi,10000) y=cos(x) lwidths=1+x[:-1] points = np.array([x, y]).T.reshape(-1, 1, 2) segments = np.concatenate([points[:-1], points[1:]], axis=1) lc = LineCollection(segments, linewidths=lwidths,color='blue') fig,a = plt.subplots() a.add_collection(lc) a.set_xlim(0,4*pi) a.set_ylim(-1.1,1.1) fig.show() """ return fig def wave_exist_2d_full_v3(b=.8): """ plot zeros of -nu1 + G(nu1,nu2) and -nu2 + G(nu2,nu1) as a function of g. g is shown implicitly as color/thickness. scatter dots included at countour lines to give an additional sense of depth use accurate fourier series """ # get data # nc1 bifurcation values bif = np.loadtxt('twod_wave_exist_br1.dat') #bif2 = np.loadtxt('twod_wave_exist_br2.dat') bif_diag1 = np.loadtxt('twod_wave_exist_diag1.dat') bif_diag2 = np.loadtxt('twod_wave_exist_diag2.dat') # bound the values # .5 <= g <= 1.6 # 0 <= vi <= .8 gmin = .5 gmax = 1.6 vimin = 0. vimax = 1. bifx_raw=bif[:,3];bify_raw=bif[:,7] bifx2_raw=bif[:,3];bify2_raw=bif[:,8] bif_diagx_raw=bif_diag2[:,0];bif_diagy_raw=np.abs(bif_diag2[:,1]) # get true/false arrays for entries satisfying the bounds bnd_idx_bool = ((bifx_raw>=gmin)*(bifx_raw<=gmax)* (bify_raw>=vimin)*(bify_raw<=vimax)* (bify2_raw>=vimin)*(bify2_raw<=vimax)) print bifx2_raw[bnd_idx_bool] print bify2_raw[bnd_idx_bool] # get actual indices bnd_idx = np.arange(0,len(bnd_idx_bool),1)[bnd_idx_bool] # extract only 1 copy of a branch diff = 0 i = 1 final_bnd_idx = [] """ while diff <= 10: # as long as the next index is no more than 10 units, append. diff = np.abs(bnd_idx[i] - bnd_idx[i-1]) final_bnd_idx.append(bnd_idx[i-1]) i += 1 """ #final_bnd_idx = np.array(final_bnd_idx,dtype=int) # convert back to np array final_bnd_idx = bnd_idx_bool bifx_bndd = bifx_raw[final_bnd_idx] bify_bndd = bify_raw[final_bnd_idx] bifx2_bndd = bifx2_raw[final_bnd_idx] bify2_bndd = bify2_raw[final_bnd_idx] bif_diagx_bndd = bif_diagx_raw[(bif_diagx_raw>=gmin)*(bif_diagx_raw<=gmax)* (bif_diagy_raw>=vimin)*(bif_diagy_raw<=vimax)] bif_diagy_bndd = bif_diagy_raw[(bif_diagx_raw>=gmin)*(bif_diagx_raw<=gmax)* (bif_diagy_raw>=vimin)*(bif_diagy_raw<=vimax)] # clean bifx,bify = clean(bifx_bndd,bify_bndd,tol=.3) bifx2,bify2 = clean(bifx2_bndd,bify2_bndd,tol=.3) bif_diagx,bif_diagy = clean(bif_diagx_bndd,bif_diagy_bndd,tol=5) # clean #bifx,bify = clean(bif[:,3],bif[:,7],tol=.47) #bifx2,bify2 = clean(bif[:,3],bif[:,8],tol=.47) #bif_diag1x,bif_diag1y = clean(bif_diag1[:,0],np.abs(bif_diag1[:,1]),tol=.2) #bif_diag2x,bif_diag2y = clean(bif_diag2[:,0],np.abs(bif_diag2[:,1]),tol=.2) # create equivalent arrays without nans for calculating minima (usually nans are taken to be max/min vals, which is bad) bifx_nonan = bifx[(~np.isnan(bifx))*(~np.isnan(bify))] bify_nonan = bify[(~np.isnan(bifx))*(~np.isnan(bify))] bifx2_nonan = bifx2[(~np.isnan(bifx2))*(~np.isnan(bify2))] bify2_nonan = bify2[(~np.isnan(bifx2))*(~np.isnan(bify2))] bif_diagx_nonan = bif_diagx[(~np.isnan(bif_diagx))*(~np.isnan(bif_diagy))] bif_diagy_nonan = bif_diagy[(~np.isnan(bif_diagx))*(~np.isnan(bif_diagy))] plane1_z = .895 plane2_z = 1.17 # get plane intersection idx bifx_int_p1 = np.argmin(np.abs(bifx_nonan-plane1_z)) bifx_int_p2 = np.argmin(np.abs(bifx_nonan-plane2_z)) bifx2_int_p1 = np.argmin(np.abs(bifx2_nonan-plane1_z)) bifx2_int_p2 = np.argmin(np.abs(bifx2_nonan-plane2_z)) bif_diagx_int_p1 = np.argmin(np.abs(bif_diagx_nonan-plane1_z)) bif_diagx_int_p2 = np.argmin(np.abs(bif_diagx_nonan-plane2_z)) fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121,projection='3d') ax2 = fig.add_subplot(122) # prep for plotting with different line widths diagx = bif_diagy diagy = bif_diagx diagz = bif_diagy ## plot curves in 3d # plot off diagonal and axial curves # clean for 3d plot ga,v1a,v2a = clean3d(bifx,bify2,bify,tol=.391) # add modified curves to figure (non diagonal guys) #ax1.add_collection3d(collect3d_colorgrad(v1a,ga,v2a,use_nonan=False,zorder=2,lwstart=3,lwend=6,cmapmin=.2,cmapmax=1.)) ax1.add_collection3d(collect3d_colorgrad(v2a,ga,v1a,use_nonan=False,zorder=2, cmapmin=.2,cmapmax=1., lwstart=2,lwend=6.)) ax1.add_collection3d(collect3d_colorgrad(v1a,ga,v2a,use_nonan=False,zorder=2, cmapmin=.2,cmapmax=1., lwstart=2,lwend=6.)) # plot diagonal guys ax1.add_collection3d(collect3d_colorgrad(diagx,diagy,diagz,use_nonan=False,zorder=2, cmapmin=.2,cmapmax=1., lwstart=6.,lwend=2.)) # plot hacky shit to fix clipping/zorder issue #ax1.plot([.55],[1.458],[.55],marker='s',color='#ffae6e',markeredgecolor='#ffae6e',zorder=10,markersize=5) #ax1.plot([.565],[1.46],[.565],marker='s',color='#ffae6e',markeredgecolor='#ffae6e',zorder=10,markersize=5) #ax1.plot([.32],[1.11],[.32],marker='s',color='#b77449',markeredgecolor='#b77449',zorder=10,markersize=3) print 'diagx,diagy,diagz',diagx,diagy,diagz # plot zero solution gt = np.linspace(.5,.9,10) ax1.add_collection3d(collect3d_colorgrad(0.*gt,gt,0.*gt,zorder=10,cmapmax=.4,lwend=2.)) #ax1.plot([.0,0],[.5,plane1_z],[.0,0],color='black',lw=1) # plot bifurcation planes X,Y = np.meshgrid(np.linspace(0,.8,2),np.linspace(0,.8,2)) ax1.plot_surface(X,0.*X+plane1_z,Y,alpha=.2,color='gray') ax1.plot_surface(X,0.*X+plane2_z,Y,alpha=.2,color='red') # plot plane intersections ax1.plot([bify[bifx_int_p1]],[bifx[bifx_int_p1]],[bify2[bifx_int_p1]],color='black',marker='o',markersize='8',zorder=100) #ax1.scatter(bify[bifx_int_p2],bifx[bifx_int_p2],bify2[bifx_int_p2],color='black',s=20) ax1.plot([0.],[1.17],[.51],marker='o',markersize='6',color='red',markeredgecolor='none',zorder=100) ax1.plot([.51],[1.17],[0.],marker='o',markersize='8',color='red',markeredgecolor='none',zorder=100) ax1.plot([.38],[1.17],[.38],marker='o',markersize='7',color='red',markeredgecolor='none',zorder=100) # plot projection of plane intersections ax1.plot([0.],[1.6],[.51],marker='o',markersize=8,color='red',markeredgecolor='none',zorder=5) ax1.plot([.51],[1.6],[0.],marker='o',markersize=8,color='red',markeredgecolor='none',zorder=100) ax1.plot([.38],[1.6],[.38],marker='o',markersize=8,color='red',markeredgecolor='none',zorder=2) ax1.plot([0],[1.6],[0],marker='o',markersize=8,color='black',markeredgecolor='none',zorder=2) ## plot curves in 2d zs = 1.6 # axial guys ax2.add_collection(collect(bify,bify2,use_nonan=False,lwstart=3.,lwend=6.,cmapmin=.2,cmapmax=1.)) ax2.add_collection(collect(bify2,bify,use_nonan=False,lwstart=3.,lwend=6.,cmapmin=.2,cmapmax=1.)) ax1.add_collection3d(collect(bify,bify2,use_nonan=False,lwstart=3.,lwend=6.,cmapmin=.2,cmapmax=1.),zs=zs,zdir='y') ax1.add_collection3d(collect(bify2,bify,use_nonan=False,lwstart=3.,lwend=6.,cmapmin=.2,cmapmax=1.),zs=zs,zdir='y') # diagonal ax2.add_collection(collect(diagx,diagz,lwstart=3.,lwend=6,cmapmin=.2,cmapmax=1.)) ax1.add_collection3d(collect(diagx,diagz,lwstart=3.,lwend=6,cmapmin=.2,cmapmax=1.),zs=zs,zdir='y') # bifurcation points lines ax2.scatter(0,.52,s=70,color='red',zorder=10) # axial intersection (y-axis) ax2.scatter(.52,0.,s=70,color='red',zorder=10) # axial intersection (x-axis) ax2.scatter(.38,.38,s=70,color='red',zorder=10) # diagonal intersection ax2.scatter(0.,0.,s=70,color='black',zorder=10) # diagonal intersection # label curves ax2.annotate(r'$x$-axis direction', xy=(.6,.01),xycoords='data',textcoords='data', xytext=(.6,.1), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(.01,.6),xycoords='data',textcoords='data', xytext=(.1,.7), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.03,.015),xycoords='data',textcoords='data', xytext=(.15,.05), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Diagonal', xy=(1.1,.32),xycoords='data',textcoords='data', xytext=(1.4,.2), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', xy=(1.4,.41),xycoords='data',textcoords='data', xytext=(1.5,.34), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(1.4,.62),xycoords='data',textcoords='data', xytext=(1.5,.34), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax1.view_init(20,-8) # set labels ax1.set_xlabel(r'$\nu_1$') ax1.set_ylabel(r'$g$') ax1.set_zlabel(r'$\nu_2$') ax2.set_xlabel(r'$\nu_1$') ax2.set_ylabel(r'$\nu_2$') ax1.set_xlim(0.,.8) ax1.set_ylim(.5,1.6) ax1.set_zlim(0,.8) ax2.set_xlim(-.05,.8) ax2.set_ylim(-.05,.8) # plot params #ax1.view_init(20,-8) #plt.show() return fig def truncate_branches(val,ty,gmin,gmax,vimin,vimax): val_final = {} ty_final = {} for key in val.keys(): g = val[key][:,0] v1 = val[key][:,2] v2 = val[key][:,3] idx = ((g>=gmin)*(g<=gmax)* (v1>=vimin)*(v1<=vimax)* (v2>=vimin)*(v2<=vimax)) if (len(g[idx]) == 0) or\ (len(v1[idx]) == 0) or\ (len(v2[idx]) == 0): pass else: print key,ty[key][0,1] val_final[key] = np.zeros((len(g[idx]),3)) val_final[key][:,0] = g[idx] val_final[key][:,1] = v1[idx] val_final[key][:,2] = v2[idx] ty_final[key] = ty[key] return val_final,ty_final def wave_exist_2d_full_v4(b=.8): # get data bif = np.loadtxt('twod_wave_exist_v2.dat') #bif2 = np.loadtxt('twod_wave_exist_br2.dat') #bif_diag1 = np.loadtxt('twod_wave_exist_diag1.dat') bif_diag2 = np.loadtxt('twod_wave_exist_diag_v2.dat') # get all possible disjoint branches val,ty = collect_disjoint_branches(bif,remove_isolated=True,isolated_number=3,remove_redundant=False,N=10) val_di,ty_di = collect_disjoint_branches(bif_diag2,remove_isolated=True,isolated_number=3,remove_redundant=False,N=10) plane1_z = .895 plane2_z = 1.16 if False: mp.figure() for key in val.keys(): mp.plot(val[key][:,1],val[key][:,2],label=key) mp.legend() mp.show() # fix branches to satisfy bounds # bound the values # .5 <= g <= 1.6 # 0 <= vi <= .8 gmin = .7 gmax = 1.6 vimin = 0. vimax = .85 val_final,ty_final = truncate_branches(val,ty,gmin,gmax,vimin,vimax) val_di_final,ty_di_final = truncate_branches(val_di,ty_di,gmin,gmax,vimin,vimax) # use this plot to choose branches if False: mp.figure() for key in val_final.keys(): mp.plot(val_final[key][:,1],val_final[key][:,2],label=key) mp.legend() mp.show() fig = plt.figure(figsize=(10,5)) ax1 = fig.add_subplot(121, projection='3d') ax1 = fig.add_axes(MyAxes3D(ax1, 'l')) ax2 = fig.add_subplot(122) # add modified curves to figure for key in val_final.keys(): g = val_final[key][:,0] v1 = val_final[key][:,1] v2 = val_final[key][:,2] if key == 'br13' or key == 'br6': ax1.add_collection3d(collect3d_colorgrad(v1,g,v2,use_nonan=False,zorder=2, lwstart=2,lwend=4, cmapmin=.3,cmapmax=.7)) elif key == 'br26' or key == 'br14' or key == 'br2' or key == 'br8': ax1.add_collection3d(collect3d_colorgrad(v1,g,v2,use_nonan=False,zorder=2, lwstart=4,lwend=5, cmapmin=.7,cmapmax=1.)) for key in val_di_final.keys(): g = val_di_final[key][:,0] v1 = val_di_final[key][:,1] v2 = val_di_final[key][:,2] ax1.add_collection3d(collect3d_colorgrad(v1,g,v2,use_nonan=False,zorder=2, lwstart=2,lwend=5, cmapmin=.3,cmapmax=1.)) # plot beginning zero guy g = np.linspace(gmin,plane1_z,10) ax1.add_collection3d(collect3d_colorgrad(0.*g,g,0.*g,use_nonan=False,zorder=2, lwstart=1,lwend=2, cmapmin=.1,cmapmax=.3)) # plot bifurcation planes X,Y = np.meshgrid(np.linspace(0,vimax,10),np.linspace(0,vimax,10)) Xhalf1,Yhalf1 = np.meshgrid(np.linspace(0.,.5,10),np.linspace(0,.5,20)) Xhalf2,Yhalf2 = np.meshgrid(np.linspace(.5,vimax,10),np.linspace(0,vimax,20)) Xhalf1b,Yhalf1b = np.meshgrid(np.linspace(.0,.5,10),np.linspace(.5,vimax,20)) #Xhalf2b,Yhalf2b = np.meshgrid(np.linspace(.5,vimax,10),np.linspace(0,vimax,20)) ax1.plot_surface(X,0.*X+plane1_z,Y,alpha=.5,color='red',edgecolor='none') ax1.plot_surface(Xhalf1,0.*Xhalf1+plane2_z,Yhalf1,alpha=.6,color='green',lw=0,edgecolor='none',zorder=1) ax1.plot_surface(Xhalf2,0.*Xhalf2+plane2_z,Yhalf2,alpha=.6,color='green',lw=0,edgecolor='none',zorder=3) ax1.plot_surface(Xhalf1b,0.*Xhalf1b+plane2_z,Yhalf1b,alpha=.6,color='green',lw=0,edgecolor='none',zorder=3) #ax1.plot_surface(X2,0.*X2+plane2_z,Y2,alpha=.5,color='red',edgecolor='none') #ax1.plot_surface(X[X>3],0.*X[X>3]+plane2_z,Y[X>3],alpha=.5,color='red',edgecolor='none') # plot intersection points #ax1.plot([bify[bifx_int_p1]],[bifx[bifx_int_p1]],[bify2[bifx_int_p1]],color='black',marker='o',markersize='8',zorder=100) #ax1.scatter(bify[bifx_int_p2],bifx[bifx_int_p2],bify2[bifx_int_p2],color='black',s=20) ax1.plot([0.],[plane1_z],[.0],marker='o',markersize='8',color='black',markeredgecolor='none',zorder=100) ax1.plot([0.],[1.17],[.51],marker='o',markersize='8',color='red',markeredgecolor='none',zorder=100) ax1.plot([.51],[1.17],[0.],marker='o',markersize='8',color='red',markeredgecolor='none',zorder=100) ax1.plot([.38],[1.17],[.38],marker='o',markersize='8',color='red',markeredgecolor='none',zorder=100) # plot projection of plane intersections ax1.plot([0.],[1.6],[.51],marker='o',markersize=8,color='red',markeredgecolor='none',zorder=5) ax1.plot([.51],[1.6],[0.],marker='o',markersize=8,color='red',markeredgecolor='none',zorder=5) ax1.plot([.38],[1.6],[.38],marker='o',markersize=8,color='red',markeredgecolor='none',zorder=5) ax1.plot([0],[1.6],[0],marker='o',markersize=8,color='black',markeredgecolor='none',zorder=2) # plot curves in 2d + 2d projection in 3d plot zs = gmax for key in val_final.keys(): g = val_final[key][:,0] v1 = val_final[key][:,1] v2 = val_final[key][:,2] if key == 'br13' or key == 'br6': ax2.add_collection(collect(v1,v2,use_nonan=False,zorder=3, lwstart=2,lwend=4, cmapmin=.3,cmapmax=1.)) ax1.add_collection3d(collect(v1,v2,use_nonan=False,zorder=2, lwstart=2,lwend=4, cmapmin=.3,cmapmax=1.),zs=zs,zdir='y') elif key == 'br26' or key == 'br14' or key == 'br2' or key == 'br8': ax2.add_collection(collect(v1,v2,use_nonan=False,zorder=3, lwstart=4,lwend=5, cmapmin=.6,cmapmax=1.)) ax1.add_collection3d(collect(v1,v2,use_nonan=False,zorder=2, lwstart=4,lwend=5, cmapmin=.6,cmapmax=1.),zs=zs,zdir='y') # bifurcation points ax2.scatter(0,.52,s=70,color='red',zorder=10) # axial intersection (y-axis) ax2.scatter(.52,0.,s=70,color='red',zorder=10) # axial intersection (x-axis) ax2.scatter(.38,.38,s=70,color='red',zorder=10) # diagonal intersection ax2.scatter(0.,0.,s=70,color='black',zorder=10) # diagonal intersection for key in val_di_final.keys(): g = val_di_final[key][:,0] v1 = val_di_final[key][:,1] v2 = val_di_final[key][:,2] ax2.add_collection(collect(v1,v2,use_nonan=False,zorder=3, lwstart=2,lwend=5, cmapmin=.3,cmapmax=1.)) ax1.add_collection3d(collect(v1,v2,use_nonan=False,zorder=2, lwstart=2,lwend=5, cmapmin=.3,cmapmax=1.),zs=zs,zdir='y') ax2.annotate(r'$x$-axis direction', xy=(.3,.01),xycoords='data',textcoords='data', xytext=(.3,.17), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$y$-axis direction', xy=(.01,.3),xycoords='data',textcoords='data', xytext=(.1,.45), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate(r'$g^*$', xy=(.03,.015),xycoords='data',textcoords='data', xytext=(.2,.07), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Diagonal direction', xy=(.48,.5),xycoords='data',textcoords='data', xytext=(.15,.65), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', xy=(.7,.55),xycoords='data',textcoords='data', xytext=(.65,.75), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Off-diagonal', alpha=0., xy=(.55,.7),xycoords='data',textcoords='data', xytext=(.65,.75), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) ax2.annotate('Multiple non-axial directions',xy=(3.68,.1),xycoords='data',textcoords='data',xytext=(3.,.5), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3", color='black'), ) #ax1.plot([.89,.89],[-3,3],color='gray') #ax1.plot([3.,3.],[-3,3],color='gray') ax1.view_init(20,-8) """ tmp_planes = ax1.zaxis._PLANES ax1.zaxis._PLANES = ( tmp_planes[2], tmp_planes[3], tmp_planes[0], tmp_planes[1], tmp_planes[4], tmp_planes[5]) """ ax1.set_xlim(vimin,vimax) ax1.set_ylim(gmin,gmax) ax1.set_zlim(vimin,vimax) ax1.set_xlabel(r'$\nu_1$') ax1.set_ylabel(r'$g$') ax1.set_zlabel(r'$\nu_2$') ax2.set_xlabel(r'$\nu_1$') ax2.set_ylabel(r'$\nu_2$') ax2.set_xlim(-.05+vimin,vimax) ax2.set_ylim(-.05+vimin,vimax) return fig def twod_superfig(): """ create summary of dynamics """ fig = plt.figure(figsize=(7,7)) gs = gridspec.GridSpec(6, 6) axl = [] #gs.update(hspace=.4) #gs.update(wspace=.3) # params g = np.zeros((6,6)) q = np.zeros((6,6)) # slosh, large slosh, const vel (per), const vel (nonper), nonconst vel (per), nonconst vel (chaos) # list of models models = ['2dfull','2dfulltrunc','2dphs','2dphstrunc','2dphsgauss'] # 2d full g[0,:] = np.array([3., -1, 3., 3., -1., 3.]) q[0,:] = np.array([1., -1, 0., 0., -1., 1.]) # 2d full trunc for i in range(6): # loop over rows. each axl[i,:] is for plots of model i for j in range(6): # loop over params each axl[i,j] is plot j of model i axl.append(plt.subplot(gs[i,j])) """ ax11 = plt.subplot(gs[0, 0]) ax12 = plt.subplot(gs[0, 1]) ax13 = plt.subplot(gs[0, 2]) ax14 = plt.subplot(gs[0, 3]) ax15 = plt.subplot(gs[0, 4]) ax16 = plt.subplot(gs[0, 5]) """ #ax11 = plt.subplot2grid((4,4),(0,0),colspan=3,rowspan=2) #ax21 = plt.subplot2grid((4,4),(2,0),colspan=3,rowspan=1,sharex=ax11) #ax21 = plt.subplot(gs[2,:3],sharex=ax11) def generate_figure(function, args, filenames, title="", title_pos=(0.5,0.95)): # workaround for python bug where forked processes use the same random # filename. #tempfile._name_sequence = None; fig = function(*args) #fig.text(title_pos[0], title_pos[1], title, ha='center') if type(filenames) == list: for name in filenames: if name.split('.')[-1] == 'ps': fig.savefig(name, orientation='landscape') else: fig.savefig(name) else: if name.split('.')[-1] == 'ps': fig.savefig(filenames,orientation='landscape') else: fig.savefig(filenames) def main(): figures = [ #(oned_phase_2par,[1,False],['oned_phase_2par1.pdf']), #(oned_phase_2par,[2,False],['oned_phase_2par2.pdf']), #(oned_phase_2par,[3,False],['oned_phase_2par3.pdf']), #(oned_phase_2par,[4,False],['oned_phase_2par4.pdf']), #(oned_phase_2par,[5,False],['oned_phase_2par5.pdf']), #(oned_phase_2par,[5,True],['oned_phase_2par5b.pdf']), #(oned_full_2par,[1,True],['oned_full_2par1.pdf']), #(oned_full_2par,[2,True],['oned_full_2par2.pdf']), #(oned_full_2par,[3,True],['oned_full_2par3.pdf']), #(oned_full_2par,[4,True],['oned_full_2par4.pdf']), #(oned_full_2par,[5,True],['oned_full_2par5.pdf']), # run this one in generate_figures.py #(twod_full_auto_5terms_2par,[],['twod_full_auto_5terms_2par.pdf']) (twod_phase_2par,[1],['twod_phase_2par1.pdf']), (twod_phase_2par,[2],['twod_phase_2par2.pdf']), (twod_phase_2par,[3],['twod_phase_2par3.pdf']), (twod_phase_2par,[4],['twod_phase_2par4.pdf']), ] for fig in figures: generate_figure(*fig) if __name__ == "__main__": main()

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3ebf6d1a066f0eb14ae871dec1b57e45675a70fe

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py

Python

conda.recipe/run_test.py

ianthomas23/tile-fetch

c5cf4328523ed2859aa5c6012eb36da9657f582f

[ "BSD-2-Clause" ]

5

2018-01-31T21:20:59.000Z

2022-01-07T00:46:00.000Z

conda.recipe/run_test.py

ianthomas23/tile-fetch

c5cf4328523ed2859aa5c6012eb36da9657f582f

[ "BSD-2-Clause" ]

5

2018-01-30T16:21:52.000Z

2018-01-31T06:01:41.000Z

conda.recipe/run_test.py

parietal-io/tile-fetch

9e91899adeeaf1ed307d086e3e5e4015657ddd3d

[ "BSD-2-Clause" ]

1

2021-09-29T11:05:34.000Z

import tile_fetch; tile_fetch.test()

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py

Python

carrierx/resources/mediator/__init__.py

EugeneSqr/carrierx-python

3bdd9728165e73584116ae63af03e2f7bcd7ca9f

[ "MIT" ]

null

carrierx/resources/mediator/__init__.py

EugeneSqr/carrierx-python

3bdd9728165e73584116ae63af03e2f7bcd7ca9f

[ "MIT" ]

null

carrierx/resources/mediator/__init__.py

EugeneSqr/carrierx-python

3bdd9728165e73584116ae63af03e2f7bcd7ca9f

[ "MIT" ]

1

2020-03-26T15:13:10.000Z

from carrierx.resources.mediator.bindings import Binding, Bindings from carrierx.resources.mediator.dids import Did, Dids

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41084dc3ab9c3312410036cd788bd63344b8bdb7

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py

Python

bempp/api/operators/far_field/helmholtz.py

pescap/bempp-cl

3a68666e8db0e873d418b734289067483f68f12e

[ "MIT" ]

70

2019-09-04T15:15:05.000Z

2022-03-22T16:54:40.000Z

bempp/api/operators/far_field/helmholtz.py

pescap/bempp-cl

3a68666e8db0e873d418b734289067483f68f12e

[ "MIT" ]

66

2020-01-16T08:31:00.000Z

2022-03-25T11:18:59.000Z

bempp/api/operators/far_field/helmholtz.py

pescap/bempp-cl

3a68666e8db0e873d418b734289067483f68f12e

[ "MIT" ]

22

2019-09-30T08:50:33.000Z

2022-03-20T19:37:22.000Z

"""Helmholtz far-field operators.""" import numpy as _np def single_layer( space, points, wavenumber, parameters=None, assembler="dense", device_interface=None, precision=None, ): """Return a Helmholtz single-layer far-field potential operator.""" import bempp.api from bempp.api.operators import OperatorDescriptor from bempp.api.assembly.potential_operator import PotentialOperator from bempp.api.assembly.assembler import PotentialAssembler if precision is None: precision = bempp.api.DEFAULT_PRECISION operator_descriptor = OperatorDescriptor( "helmholtz_far_field_single_layer_potential", # Identifier [_np.real(wavenumber), _np.imag(wavenumber)], # Options "helmholtz_far_field_single_layer", # Kernel type "default_scalar", # Assembly type precision, # Precision True, # Is complex None, # Singular part 1, # Kernel dimension ) return PotentialOperator( PotentialAssembler( space, points, operator_descriptor, device_interface, assembler, parameters ) ) def double_layer( space, points, wavenumber, parameters=None, assembler="dense", device_interface=None, precision=None, ): """Return a Helmholtz double-layer far-field potential operator.""" import bempp.api from bempp.api.operators import OperatorDescriptor from bempp.api.assembly.potential_operator import PotentialOperator from bempp.api.assembly.assembler import PotentialAssembler if precision is None: precision = bempp.api.DEFAULT_PRECISION operator_descriptor = OperatorDescriptor( "helmholtz_far_field_double_layer_potential", # Identifier [_np.real(wavenumber), _np.imag(wavenumber)], # Options "helmholtz_far_field_double_layer", # Kernel type "default_scalar", # Assembly type precision, # Precision True, # Is complex None, # Singular part 1, # Kernel dimension ) return PotentialOperator( PotentialAssembler( space, points, operator_descriptor, device_interface, assembler, parameters ) )

29.693333

87

0.683431

222

2,227

6.68018

0.225225

0.053945

0.04855

0.053945

0.952124

0.935941

0

0.001182

0.240234

2,227

74

88

30.094595

0.875296

0.156713

0

0.786885

0

0.100704

0.08013

0

1

0.032787

false

0

0.147541

0

0.213115

0

null

0

1

0

1

0

null

0

7

f5af44ea4676182c23f4bba121b6e926da2a96ce

13,402

py

Python

app/uBrain/model/model_hub.py

jingjieli95/UnarySim

775b38fa2d6b05a69fd73acb4766e50200a5cc37

[ "MIT" ]

1

2021-11-29T23:51:15.000Z

app/uBrain/model/model_hub.py

pan185/UnarySim

c03386efdbb8151f3c33f34b44d1d6a6fc960434

[ "MIT" ]

null

app/uBrain/model/model_hub.py

pan185/UnarySim

c03386efdbb8151f3c33f34b44d1d6a6fc960434

[ "MIT" ]

null

import math import warnings import numbers from typing import List, Tuple, Optional, overload, Union import torch import torch.nn as nn import torch.nn.functional as F from UnarySim.kernel.conv import HUBConv2d from UnarySim.kernel.linear import HUBLinear from UnarySim.kernel.sigmoid import ScaleHardsigmoid from UnarySim.kernel.relu import ScaleReLU from UnarySim.kernel.rnn import HUBMGUCell, HardMGUCell from UnarySim.metric.metric import SourceGen, RNG, BSGen, ProgError from UnarySim.kernel.utils import progerror_report class Cascade_CNN_RNN(torch.nn.Module): """ This is the hybrid unary binary version of the cascade CNN RNN for BCI, i.e., uBrain """ def __init__(self, input_sz=[10, 11], linear_act="scalerelu", cnn_chn=16, cnn_kn_sz=3, cnn_padding=1, # default perform same conv fc_sz=256, rnn="mgu", rnn_win_sz=10, rnn_hidden_sz=64, rnn_hard=True, bias=False, init_std=None, keep_prob=0.5, num_class=[5, 2], bitwidth_tc=8, bitwidth_rc=8, rng="Sobol", conv1_weight=None, conv1_bias=None, conv2_weight=None, conv2_bias=None, fc3_weight=None, fc3_bias=None, rnn4_weight_f=None, rnn4_bias_f=None, rnn4_weight_n=None, rnn4_bias_n=None, fc5_weight=None, fc5_bias=None, depth=10, depth_ismul=5): super(Cascade_CNN_RNN, self).__init__() self.input_sz = input_sz self.cnn_chn = cnn_chn self.cnn_kn_sz = cnn_kn_sz self.cnn_padding = cnn_padding self.fc_sz = fc_sz self.rnn_win_sz = rnn_win_sz self.rnn_hidden_sz = rnn_hidden_sz self.bias = bias self.num_class = num_class self.bitwidth_tc = bitwidth_tc self.bitwidth_rc = bitwidth_rc self.rng = rng self.conv1_weight = conv1_weight self.conv1_bias = conv1_bias self.conv2_weight = conv2_weight self.conv2_bias = conv2_bias self.fc3_weight = fc3_weight self.fc3_bias = fc3_bias self.rnn4_weight_f = rnn4_weight_f self.rnn4_bias_f = rnn4_bias_f self.rnn4_weight_n = rnn4_weight_n self.rnn4_bias_n = rnn4_bias_n self.fc5_weight = fc5_weight self.fc5_bias = fc5_bias self.cycle_tc = 2**(bitwidth_tc-1) self.mode = "bipolar" # CNN self.conv1 = HUBConv2d(1 , cnn_chn , (cnn_kn_sz, cnn_kn_sz), bias=bias, padding=cnn_padding, binary_weight=self.conv1_weight, binary_bias=self.conv1_bias, rng=self.rng, cycle=self.cycle_tc) self.conv2 = HUBConv2d(cnn_chn , cnn_chn*2, (cnn_kn_sz, cnn_kn_sz), bias=bias, padding=cnn_padding, binary_weight=self.conv2_weight, binary_bias=self.conv2_bias, rng=self.rng, cycle=self.cycle_tc) self.fc3 = HUBLinear((input_sz[0]+2*2*(cnn_padding-1))*(input_sz[1]+2*2*(cnn_padding-1))*cnn_chn*2, fc_sz, bias=bias, binary_weight=self.fc3_weight, binary_bias=self.fc3_bias, rng=self.rng, cycle=self.cycle_tc) self.fc3_drop = nn.Dropout(p=1-keep_prob) # RNN if rnn.lower() == "mgu": self.rnncell4 = HUBMGUCell(fc_sz, rnn_hidden_sz, bias=bias, binary_weight_f=self.rnn4_weight_f, binary_bias_f=self.rnn4_bias_f, binary_weight_n=self.rnn4_weight_n, binary_bias_n=self.rnn4_bias_n, rng=rng, bitwidth=bitwidth_rc, mode=self.mode, depth=depth, depth_ismul=depth_ismul) else: print("rnn type needs to be 'mgu'.") # MLP self.fc5 = HUBLinear(rnn_hidden_sz, sum(num_class), bias=bias, binary_weight=self.fc5_weight, binary_bias=self.fc5_bias, rng=self.rng, cycle=self.cycle_tc) self.linear_act = linear_act.lower() if self.linear_act == "scalehardsigmoid": self.conv1_act = ScaleHardsigmoid() self.conv2_act = ScaleHardsigmoid() self.fc3_act = ScaleHardsigmoid() elif self.linear_act == "scalerelu": self.conv1_act = ScaleReLU() self.conv2_act = ScaleReLU() self.fc3_act = ScaleReLU() elif self.linear_act == "sigmoid": self.conv1_act = nn.Sigmoid() self.conv2_act = nn.Sigmoid() self.fc3_act = nn.Sigmoid() elif self.linear_act == "hardtanh": self.conv1_act = nn.Hardtanh() self.conv2_act = nn.Hardtanh() self.fc3_act = nn.Hardtanh() elif self.linear_act == "tanh": self.conv1_act = nn.Tanh() self.conv2_act = nn.Tanh() self.fc3_act = nn.Tanh() elif self.linear_act == "relu": self.conv1_act = nn.ReLU() self.conv2_act = nn.ReLU() self.fc3_act = nn.ReLU() elif self.linear_act == "relu6": self.conv1_act = nn.ReLU6() self.conv2_act = nn.ReLU6() self.fc3_act = nn.ReLU6() elif self.linear_act == "elu": self.conv1_act = nn.ELU() self.conv2_act = nn.ELU() self.fc3_act = nn.ELU() def forward(self, input, binary_fm_dict=None): # input is (batch, win, h, w) # CNN self.conv1_i = input.view(-1, 1, self.input_sz[0], self.input_sz[1]) self.conv1_o = self.conv1(self.conv1_i) self.conv1_act_o = self.conv1_act(self.conv1_o) self.conv2_o = self.conv2(self.conv1_act_o) self.conv2_act_o = self.conv2_act(self.conv2_o) self.fc3_i = self.conv2_act_o.view(self.conv2_act_o.shape[0], -1) self.fc3_o = self.fc3(self.fc3_i) self.fc3_act_o = self.fc3_act(self.fc3_o) self.fc3_drop_o = self.fc3_drop(self.fc3_act_o) self.fc3_view_o = self.fc3_drop_o.view(-1, self.rnn_win_sz, self.fc_sz) self.fc3_trans_o = self.fc3_view_o.transpose(0, 1) # RNN self.rnn_out = [] hx = torch.zeros(self.fc3_trans_o[0].size()[0], self.rnn_hidden_sz, dtype=input.dtype, device=input.device) for i in range(self.rnn_win_sz): hx = self.rnncell4(self.fc3_trans_o[i], hx) self.rnn_out.append(hx) # MLP self.fc5_i = self.rnn_out[-1] self.fc5_o = self.fc5(self.fc5_i) return nn.Hardtanh()(self.fc5_o) class Cascade_CNN_RNN_fp_rnn(torch.nn.Module): """ This is the hybrid unary binary version of the cascade CNN RNN for BCI, i.e., uBrain But the rnn is in fp format, so that entire model is trainable. """ def __init__(self, input_sz=[10, 11], linear_act="scalerelu", cnn_chn=16, cnn_kn_sz=3, cnn_padding=1, # default perform same conv fc_sz=256, rnn="mgu", rnn_win_sz=10, rnn_hidden_sz=64, rnn_hard=True, bias=False, init_std=None, keep_prob=0.5, num_class=[5, 2], bitwidth_tc=8, bitwidth_rc=8, rng="Sobol", conv1_weight=None, conv1_bias=None, conv2_weight=None, conv2_bias=None, fc3_weight=None, fc3_bias=None, rnn4_weight_f=None, rnn4_bias_f=None, rnn4_weight_n=None, rnn4_bias_n=None, fc5_weight=None, fc5_bias=None, depth=10, depth_ismul=5): super(Cascade_CNN_RNN, self).__init__() self.input_sz = input_sz self.cnn_chn = cnn_chn self.cnn_kn_sz = cnn_kn_sz self.cnn_padding = cnn_padding self.fc_sz = fc_sz self.rnn_win_sz = rnn_win_sz self.rnn_hidden_sz = rnn_hidden_sz self.bias = bias self.num_class = num_class self.bitwidth_tc = bitwidth_tc self.bitwidth_rc = bitwidth_rc self.rng = rng self.conv1_weight = conv1_weight self.conv1_bias = conv1_bias self.conv2_weight = conv2_weight self.conv2_bias = conv2_bias self.fc3_weight = fc3_weight self.fc3_bias = fc3_bias self.rnn4_weight_f = rnn4_weight_f self.rnn4_bias_f = rnn4_bias_f self.rnn4_weight_n = rnn4_weight_n self.rnn4_bias_n = rnn4_bias_n self.fc5_weight = fc5_weight self.fc5_bias = fc5_bias self.cycle_tc = 2**(bitwidth_tc-1) self.mode = "bipolar" # CNN self.conv1 = HUBConv2d(1 , cnn_chn , (cnn_kn_sz, cnn_kn_sz), bias=bias, padding=cnn_padding, binary_weight=self.conv1_weight, binary_bias=self.conv1_bias, rng=self.rng, cycle=self.cycle_tc) self.conv2 = HUBConv2d(cnn_chn , cnn_chn*2, (cnn_kn_sz, cnn_kn_sz), bias=bias, padding=cnn_padding, binary_weight=self.conv2_weight, binary_bias=self.conv2_bias, rng=self.rng, cycle=self.cycle_tc) self.fc3 = HUBLinear((input_sz[0]+2*2*(cnn_padding-1))*(input_sz[1]+2*2*(cnn_padding-1))*cnn_chn*2, fc_sz, bias=bias, binary_weight=self.fc3_weight, binary_bias=self.fc3_bias, rng=self.rng, cycle=self.cycle_tc) self.fc3_drop = nn.Dropout(p=1-keep_prob) # RNN if rnn.lower() == "mgu": self.rnncell4 = HardMGUCell(fc_sz, rnn_hidden_sz, bias=bias, hard=rnn_hard) else: print("rnn type needs to be 'mgu'.") # MLP self.fc5 = HUBLinear(rnn_hidden_sz, sum(num_class), bias=bias, binary_weight=self.fc5_weight, binary_bias=self.fc5_bias, rng=self.rng, cycle=self.cycle_tc) self.linear_act = linear_act.lower() if self.linear_act == "scalehardsigmoid": self.conv1_act = ScaleHardsigmoid() self.conv2_act = ScaleHardsigmoid() self.fc3_act = ScaleHardsigmoid() elif self.linear_act == "scalerelu": self.conv1_act = ScaleReLU() self.conv2_act = ScaleReLU() self.fc3_act = ScaleReLU() elif self.linear_act == "sigmoid": self.conv1_act = nn.Sigmoid() self.conv2_act = nn.Sigmoid() self.fc3_act = nn.Sigmoid() elif self.linear_act == "hardtanh": self.conv1_act = nn.Hardtanh() self.conv2_act = nn.Hardtanh() self.fc3_act = nn.Hardtanh() elif self.linear_act == "tanh": self.conv1_act = nn.Tanh() self.conv2_act = nn.Tanh() self.fc3_act = nn.Tanh() elif self.linear_act == "relu": self.conv1_act = nn.ReLU() self.conv2_act = nn.ReLU() self.fc3_act = nn.ReLU() elif self.linear_act == "relu6": self.conv1_act = nn.ReLU6() self.conv2_act = nn.ReLU6() self.fc3_act = nn.ReLU6() elif self.linear_act == "elu": self.conv1_act = nn.ELU() self.conv2_act = nn.ELU() self.fc3_act = nn.ELU() def forward(self, input, binary_fm_dict=None): # input is (batch, win, h, w) # CNN self.conv1_i = input.view(-1, 1, self.input_sz[0], self.input_sz[1]) self.conv1_o = self.conv1(self.conv1_i) self.conv1_act_o = self.conv1_act(self.conv1_o) self.conv2_o = self.conv2(self.conv1_act_o) self.conv2_act_o = self.conv2_act(self.conv2_o) self.fc3_i = self.conv2_act_o.view(self.conv2_act_o.shape[0], -1) self.fc3_o = self.fc3(self.fc3_i) self.fc3_act_o = self.fc3_act(self.fc3_o) self.fc3_drop_o = self.fc3_drop(self.fc3_act_o) self.fc3_view_o = self.fc3_drop_o.view(-1, self.rnn_win_sz, self.fc_sz) self.fc3_trans_o = self.fc3_view_o.transpose(0, 1) # RNN self.rnn_out = [] hx = torch.zeros(self.fc3_trans_o[0].size()[0], self.rnn_hidden_sz, dtype=input.dtype, device=input.device) for i in range(self.rnn_win_sz): hx = self.rnncell4(self.fc3_trans_o[i], hx) self.rnn_out.append(hx) # MLP self.fc5_i = self.rnn_out[-1] self.fc5_o = self.fc5(self.fc5_i) return nn.Hardtanh()(self.fc5_o)

42.277603

168

0.550366

1,770

13,402

3.875141

0.087006

0.061233

0.041989

0.034699

0.899256

0.893425

0.886718

0

0.038992

0.351291

13,402

316

169

42.411392

0.749942

0.0291

0

0.925373

0

0.016974

0

1

0.014925

false

0

0.052239

0

0.08209

0.007463

0

null

0

1

0

1

0

null

0

7

f5b844593d16ec6af3c38a06c0e651e64153ec9e

258

py

Python

dnd5gen/char_backgrounds/__init__.py

r3valkyrie/dnd5gen

e88b055aaf24b25f689cb07013f02a73a0d976d7

[ "MIT" ]

null

dnd5gen/char_backgrounds/__init__.py

r3valkyrie/dnd5gen

e88b055aaf24b25f689cb07013f02a73a0d976d7

[ "MIT" ]

1

2020-01-16T21:15:46.000Z

dnd5gen/char_backgrounds/__init__.py

r3valkyrie/dnd5gen

e88b055aaf24b25f689cb07013f02a73a0d976d7

[ "MIT" ]

null

from dnd5gen.char_backgrounds.acolyte import Acolyte from dnd5gen.char_backgrounds.folk_hero import FolkHero from dnd5gen.char_backgrounds.noble import Noble from dnd5gen.char_backgrounds.sage import Sage from dnd5gen.char_backgrounds.soldier import Soldier

43

55

0.883721

36

258

6.166667

0.333333

0.247748

0.337838

0.585586

0

0.021008

0.077519

258

5

56

51.6

0.911765

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

eb18fe689d67a11c7164ae60030bb3a78ad8eaa3

5,976

py

Python

plotting/regenerate_run_scripts (optional).py

GustikS/NeuraLifting

c7e59175f50200897a362dff09b7fe2e7b89e7b6

[ "MIT" ]

1

2020-07-21T04:35:52.000Z

plotting/regenerate_run_scripts (optional).py

GustikS/NeuraLifting

c7e59175f50200897a362dff09b7fe2e7b89e7b6

[ "MIT" ]

null

plotting/regenerate_run_scripts (optional).py

GustikS/NeuraLifting

c7e59175f50200897a362dff09b7fe2e7b89e7b6

[ "MIT" ]

null

from grid import * #%% grid = GridSetup(experiment_id="digits_lrnn", param_ranges={"iso": [1, 2, 3, 4], "prune": [1], "xval": [5], "isocheck": [-1], "isoinits": [1], "ts": [10]}, datasets=["molecules/MDA_MB_231_ATCC"], templates=["molecules/LRNN_template_embeddings"], walltime="10:00:00", memory_max="20g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) # %% grid = GridSetup(experiment_id="digits_gnn", param_ranges={"iso": [1, 2, 3, 4], "prune": [1], "xval": [5], "isocheck": [-1], "isoinits": [1], "ts": [10]}, datasets=["molecules/MDA_MB_231_ATCC"], templates=["molecules/GNN_template_embeddings"], walltime="10:00:00", memory_max="20g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) # %% grid = GridSetup(experiment_id="digits_kinships", param_ranges={"iso": [1, 2, 3, 4], "prune": [1], "xval": [5], "isocheck": [-1], "isoinits": [1], "ts": [10]}, datasets=["kbs/kinships"], templates=["template_embeddings"], walltime="10:00:00", memory_max="20g", rci=True, template_per_dataset=True, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) # %% grid = GridSetup(experiment_id="lossless_kbc", param_ranges={"iso": [-1, 14], "prune": [-1, 1], "opt": ["adam"], "lr": [0.01], "xval": [5], "ts": [1000]}, datasets="kbs", templates=["template_embeddings"], walltime="23:59:00", memory_max="30g", rci=True, template_per_dataset=True, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) # %% grid = GridSetup(experiment_id="lossless_lrnn", param_ranges={"iso": [-1, 14], "prune": [-1, 1], "opt": ["adam"], "lr": [0.01], "xval": [5], "ts": [1000]}, datasets="molecules", templates=["molecules/LRNN_template_embeddings"], walltime="23:59:00", memory_max="30g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) # %% grid = GridSetup(experiment_id="lossless_gnn", param_ranges={"iso": [-1, 14], "prune": [-1, 1], "opt": ["adam"], "lr": [0.01], "xval": [5], "ts": [1000]}, datasets="molecules", templates=["molecules/GNN_template_embeddings"], walltime="23:59:00", memory_max="30g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) # %% grid = GridSetup(experiment_id="digits_lrnn_scalar", param_ranges={"iso": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "prune": [1], "xval": [5], "isocheck": [-1], "isoinits": [1], "opt": ["adam"], "lr": [0.01], "ts": [1000]}, datasets=["molecules/MDA_MB_231_ATCC"], templates=["molecules/scalar_template_embeddings"], walltime="23:59:00", memory_max="40g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) #%% grid = GridSetup(experiment_id="lrnn_scalar", param_ranges={"iso": [-1], "prune": [-1], "opt": ["adam"], "lr": [0.01], "xval": [5], "ts": [1000]}, datasets=["molecules/MDA_MB_231_ATCC"], templates=["molecules/scalar_template_embeddings"], walltime="23:59:00", memory_max="80g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) # %% grid = GridSetup(experiment_id="digits_lrnn_scalar_inits", param_ranges={"iso": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "prune": [1], "xval": [5], "isocheck": [1], "isoinits": [1, 2, 3], "ts": [10]}, datasets=["molecules/MDA_MB_231_ATCC"], templates=["molecules/scalar_template_embeddings"], walltime="20:00:00", memory_max="40g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments) #%% grid = GridSetup(experiment_id="digits_lrnn_vector", param_ranges={"iso": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "prune": [1], "xval": [5], "isocheck": [1], "isoinits": [1, 2, 3], "ts": [10]}, datasets=["molecules/MDA_MB_231_ATCC"], templates=["molecules/LRNN_template_embeddings"], walltime="20:00:00", memory_max="20g", rci=True, template_per_dataset=False, user="XXXXX") experiments = grid.generate_experiments() grid.export_experiments(experiments)

36.888889

113

0.499331

591

5,976

4.846024

0.125212

0.151885

0.080307

0.087291

0.972067

0.968575

0.939944

0.937849

0

0.064262

0.341198

5,976

161

114

37.118012

0.663195

0.004518

0

0.859504

0

0.182186

0.07577

0

1

0

false

0

0.008264

0

0.008264

0

null

0

1

0

1

0

null

0

7

de1933a8be911c333678d0764ad3ecb315e7398a

71,037

py

Python

3_Go_Nogo/Go_Nogo_Formal_lastrun.py

Brinks0211/cognitive_paradigms_patients

30e3f8268e5c2b5ebfffcc4ebbcb46d8e60d039e

[ "MIT" ]

2

2020-07-01T12:53:40.000Z

2020-07-01T13:30:23.000Z

3_Go_Nogo/Go_Nogo_Formal_lastrun.py

Brinks0211/cognitive_paradigms_patients

30e3f8268e5c2b5ebfffcc4ebbcb46d8e60d039e

[ "MIT" ]

null

3_Go_Nogo/Go_Nogo_Formal_lastrun.py

Brinks0211/cognitive_paradigms_patients

30e3f8268e5c2b5ebfffcc4ebbcb46d8e60d039e

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ This experiment was created using PsychoPy3 Experiment Builder (v2020.1.3), on 六月 15, 2020, at 21:14 If you publish work using this script the most relevant publication is: Peirce J, Gray JR, Simpson S, MacAskill M, Höchenberger R, Sogo H, Kastman E, Lindeløv JK. (2019) PsychoPy2: Experiments in behavior made easy Behav Res 51: 195. https://doi.org/10.3758/s13428-018-01193-y """ from __future__ import absolute_import, division from psychopy import locale_setup from psychopy import prefs from psychopy import sound, gui, visual, core, data, event, logging, clock from psychopy.constants import (NOT_STARTED, STARTED, PLAYING, PAUSED, STOPPED, FINISHED, PRESSED, RELEASED, FOREVER) import numpy as np # whole numpy lib is available, prepend 'np.' from numpy import (sin, cos, tan, log, log10, pi, average, sqrt, std, deg2rad, rad2deg, linspace, asarray) from numpy.random import random, randint, normal, shuffle import os # handy system and path functions import sys # to get file system encoding from psychopy.hardware import keyboard # Ensure that relative paths start from the same directory as this script _thisDir = os.path.dirname(os.path.abspath(__file__)) os.chdir(_thisDir) # Store info about the experiment session psychopyVersion = '2020.1.3' expName = 'Go_Nogo_Formal' # from the Builder filename that created this script expInfo = {'participant': '', '姓名拼音': '', '男1/女2': '', '入院1/出院2': ''} dlg = gui.DlgFromDict(dictionary=expInfo, sortKeys=False, title=expName) if dlg.OK == False: core.quit() # user pressed cancel expInfo['date'] = data.getDateStr() # add a simple timestamp expInfo['expName'] = expName expInfo['psychopyVersion'] = psychopyVersion # Data file name stem = absolute path + name; later add .psyexp, .csv, .log, etc filename = _thisDir + os.sep + u'data/%s_%s_%s' % (expInfo['participant'], expName, expInfo['date']) # An ExperimentHandler isn't essential but helps with data saving thisExp = data.ExperimentHandler(name=expName, version='', extraInfo=expInfo, runtimeInfo=None, originPath='C:\\Users\\zhang\\Desktop\\张以昊\\课题组\\3_Go_Nogo\\Go_Nogo_Formal_lastrun.py', savePickle=True, saveWideText=True, dataFileName=filename) # save a log file for detail verbose info logFile = logging.LogFile(filename+'.log', level=logging.EXP) logging.console.setLevel(logging.WARNING) # this outputs to the screen, not a file endExpNow = False # flag for 'escape' or other condition => quit the exp frameTolerance = 0.001 # how close to onset before 'same' frame # Start Code - component code to be run before the window creation # Setup the Window win = visual.Window( size=[1536, 864], fullscr=True, screen=0, winType='pyglet', allowGUI=False, allowStencil=False, monitor='testMonitor', color=[0,0,0], colorSpace='rgb', blendMode='avg', useFBO=True, units='height') # store frame rate of monitor if we can measure it expInfo['frameRate'] = win.getActualFrameRate() if expInfo['frameRate'] != None: frameDur = 1.0 / round(expInfo['frameRate']) else: frameDur = 1.0 / 60.0 # could not measure, so guess # create a default keyboard (e.g. to check for escape) defaultKeyboard = keyboard.Keyboard() # Initialize components for Routine "introduction1" introduction1Clock = core.Clock() introduction_1 = visual.TextStim(win=win, name='introduction_1', text='欢迎参加测试\n（正式部分）\n\n本测试分两种类型\n\n（继续，请按空格键）', font='Arial', pos=(0, 0), height=0.05, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); key_resp = keyboard.Keyboard() # Initialize components for Routine "introduction4" introduction4Clock = core.Clock() introduction_4 = visual.TextStim(win=win, name='introduction_4', text='如果准备好了，请开始正式测试\n\n（继续，请按空格键）', font='Arial', pos=(0, 0), height=0.05, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); key_resp_4 = keyboard.Keyboard() # Initialize components for Routine "introduction2" introduction2Clock = core.Clock() introduction_2 = visual.TextStim(win=win, name='introduction_2', text='第一种类型\n\n测试开始时,屏幕中间会出现注视点“+”\n之后会出现不同类型的红绿灯图片\n\n如果为绿灯或者黄灯，请按下空格键\n如果为红灯，请不要按键\n\n（继续，请按空格键）', font='Arial', pos=(0, 0), height=0.05, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); key_resp_2 = keyboard.Keyboard() # Initialize components for Routine "light" lightClock = core.Clock() concentration = visual.TextStim(win=win, name='concentration', text='+', font='Arial', pos=(0, 0), height=0.1, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); image = visual.ImageStim( win=win, name='image', image='sin', mask=None, ori=0, pos=(0, 0), size=(0.5, 0.5), color=[1,1,1], colorSpace='rgb', opacity=1, flipHoriz=False, flipVert=False, texRes=128, interpolate=True, depth=-1.0) key_resp_light = keyboard.Keyboard() # Initialize components for Routine "introduction3" introduction3Clock = core.Clock() introduction_3 = visual.TextStim(win=win, name='introduction_3', text='第二种类型\n\n测试开始时,屏幕中间会出现注视点“+”\n之后会出现一个表情图片\n\n在每个表情图片出现时\n如果为快乐或者中性，请按下空格键\n如果为悲伤，请不要按键\n\n（继续，请按空格键）', font='Arial', pos=(0, 0), height=0.05, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); key_resp_3 = keyboard.Keyboard() # Initialize components for Routine "face" faceClock = core.Clock() concentration2 = visual.TextStim(win=win, name='concentration2', text='+', font='Arial', pos=(0, 0), height=0.1, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); image_2 = visual.ImageStim( win=win, name='image_2', image='sin', mask=None, ori=0, pos=(0, 0), size=(0.4, 0.5), color=[1,1,1], colorSpace='rgb', opacity=1, flipHoriz=False, flipVert=False, texRes=128, interpolate=True, depth=-1.0) key_resp_face = keyboard.Keyboard() # Initialize components for Routine "tip1" tip1Clock = core.Clock() tip_1 = visual.TextStim(win=win, name='tip_1', text='现在，测试第一种类型\n\n如果为绿灯或者黄灯，请按下空格键\n如果为红灯，请不要按键\n\n（继续，请按空格键）\n', font='Arial', pos=(0, 0), height=0.05, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); key_resp_5 = keyboard.Keyboard() # Initialize components for Routine "light" lightClock = core.Clock() concentration = visual.TextStim(win=win, name='concentration', text='+', font='Arial', pos=(0, 0), height=0.1, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); image = visual.ImageStim( win=win, name='image', image='sin', mask=None, ori=0, pos=(0, 0), size=(0.5, 0.5), color=[1,1,1], colorSpace='rgb', opacity=1, flipHoriz=False, flipVert=False, texRes=128, interpolate=True, depth=-1.0) key_resp_light = keyboard.Keyboard() # Initialize components for Routine "tip2" tip2Clock = core.Clock() tip_2 = visual.TextStim(win=win, name='tip_2', text='现在，测试第二种类型\n\n在每个表情图片出现时\n如果为快乐或者中性，请按下空格键\n如果为悲伤，请不要按键\n\n（继续，请按空格键）\n', font='Arial', pos=(0, 0), height=0.05, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); key_resp_7 = keyboard.Keyboard() # Initialize components for Routine "face" faceClock = core.Clock() concentration2 = visual.TextStim(win=win, name='concentration2', text='+', font='Arial', pos=(0, 0), height=0.1, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); image_2 = visual.ImageStim( win=win, name='image_2', image='sin', mask=None, ori=0, pos=(0, 0), size=(0.4, 0.5), color=[1,1,1], colorSpace='rgb', opacity=1, flipHoriz=False, flipVert=False, texRes=128, interpolate=True, depth=-1.0) key_resp_face = keyboard.Keyboard() # Initialize components for Routine "thanks" thanksClock = core.Clock() text = visual.TextStim(win=win, name='text', text='测试结束，谢谢您的参与', font='Arial', pos=(0, 0), height=0.1, wrapWidth=None, ori=0, color='white', colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); # Create some handy timers globalClock = core.Clock() # to track the time since experiment started routineTimer = core.CountdownTimer() # to track time remaining of each (non-slip) routine # ------Prepare to start Routine "introduction1"------- continueRoutine = True # update component parameters for each repeat key_resp.keys = [] key_resp.rt = [] _key_resp_allKeys = [] # keep track of which components have finished introduction1Components = [introduction_1, key_resp] for thisComponent in introduction1Components: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") introduction1Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "introduction1"------- while continueRoutine: # get current time t = introduction1Clock.getTime() tThisFlip = win.getFutureFlipTime(clock=introduction1Clock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *introduction_1* updates if introduction_1.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later introduction_1.frameNStart = frameN # exact frame index introduction_1.tStart = t # local t and not account for scr refresh introduction_1.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(introduction_1, 'tStartRefresh') # time at next scr refresh introduction_1.setAutoDraw(True) # *key_resp* updates waitOnFlip = False if key_resp.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later key_resp.frameNStart = frameN # exact frame index key_resp.tStart = t # local t and not account for scr refresh key_resp.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp, 'tStartRefresh') # time at next scr refresh key_resp.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp.status == STARTED and not waitOnFlip: theseKeys = key_resp.getKeys(keyList=['space'], waitRelease=False) _key_resp_allKeys.extend(theseKeys) if len(_key_resp_allKeys): key_resp.keys = _key_resp_allKeys[-1].name # just the last key pressed key_resp.rt = _key_resp_allKeys[-1].rt # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in introduction1Components: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "introduction1"------- for thisComponent in introduction1Components: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('introduction_1.started', introduction_1.tStartRefresh) thisExp.addData('introduction_1.stopped', introduction_1.tStopRefresh) # the Routine "introduction1" was not non-slip safe, so reset the non-slip timer routineTimer.reset() # ------Prepare to start Routine "introduction4"------- continueRoutine = True # update component parameters for each repeat key_resp_4.keys = [] key_resp_4.rt = [] _key_resp_4_allKeys = [] # keep track of which components have finished introduction4Components = [introduction_4, key_resp_4] for thisComponent in introduction4Components: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") introduction4Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "introduction4"------- while continueRoutine: # get current time t = introduction4Clock.getTime() tThisFlip = win.getFutureFlipTime(clock=introduction4Clock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *introduction_4* updates if introduction_4.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later introduction_4.frameNStart = frameN # exact frame index introduction_4.tStart = t # local t and not account for scr refresh introduction_4.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(introduction_4, 'tStartRefresh') # time at next scr refresh introduction_4.setAutoDraw(True) # *key_resp_4* updates waitOnFlip = False if key_resp_4.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later key_resp_4.frameNStart = frameN # exact frame index key_resp_4.tStart = t # local t and not account for scr refresh key_resp_4.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_4, 'tStartRefresh') # time at next scr refresh key_resp_4.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_4.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_4.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_4.status == STARTED and not waitOnFlip: theseKeys = key_resp_4.getKeys(keyList=['space'], waitRelease=False) _key_resp_4_allKeys.extend(theseKeys) if len(_key_resp_4_allKeys): key_resp_4.keys = _key_resp_4_allKeys[-1].name # just the last key pressed key_resp_4.rt = _key_resp_4_allKeys[-1].rt # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in introduction4Components: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "introduction4"------- for thisComponent in introduction4Components: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('introduction_4.started', introduction_4.tStartRefresh) thisExp.addData('introduction_4.stopped', introduction_4.tStopRefresh) # the Routine "introduction4" was not non-slip safe, so reset the non-slip timer routineTimer.reset() # ------Prepare to start Routine "introduction2"------- continueRoutine = True # update component parameters for each repeat key_resp_2.keys = [] key_resp_2.rt = [] _key_resp_2_allKeys = [] # keep track of which components have finished introduction2Components = [introduction_2, key_resp_2] for thisComponent in introduction2Components: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") introduction2Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "introduction2"------- while continueRoutine: # get current time t = introduction2Clock.getTime() tThisFlip = win.getFutureFlipTime(clock=introduction2Clock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *introduction_2* updates if introduction_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later introduction_2.frameNStart = frameN # exact frame index introduction_2.tStart = t # local t and not account for scr refresh introduction_2.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(introduction_2, 'tStartRefresh') # time at next scr refresh introduction_2.setAutoDraw(True) # *key_resp_2* updates waitOnFlip = False if key_resp_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later key_resp_2.frameNStart = frameN # exact frame index key_resp_2.tStart = t # local t and not account for scr refresh key_resp_2.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_2, 'tStartRefresh') # time at next scr refresh key_resp_2.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_2.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_2.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_2.status == STARTED and not waitOnFlip: theseKeys = key_resp_2.getKeys(keyList=['space'], waitRelease=False) _key_resp_2_allKeys.extend(theseKeys) if len(_key_resp_2_allKeys): key_resp_2.keys = _key_resp_2_allKeys[-1].name # just the last key pressed key_resp_2.rt = _key_resp_2_allKeys[-1].rt # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in introduction2Components: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "introduction2"------- for thisComponent in introduction2Components: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('introduction_2.started', introduction_2.tStartRefresh) thisExp.addData('introduction_2.stopped', introduction_2.tStopRefresh) # the Routine "introduction2" was not non-slip safe, so reset the non-slip timer routineTimer.reset() # set up handler to look after randomisation of conditions etc loop_light1 = data.TrialHandler(nReps=12, method='random', extraInfo=expInfo, originPath=-1, trialList=data.importConditions('documents\\light.xlsx'), seed=None, name='loop_light1') thisExp.addLoop(loop_light1) # add the loop to the experiment thisLoop_light1 = loop_light1.trialList[0] # so we can initialise stimuli with some values # abbreviate parameter names if possible (e.g. rgb = thisLoop_light1.rgb) if thisLoop_light1 != None: for paramName in thisLoop_light1: exec('{} = thisLoop_light1[paramName]'.format(paramName)) for thisLoop_light1 in loop_light1: currentLoop = loop_light1 # abbreviate parameter names if possible (e.g. rgb = thisLoop_light1.rgb) if thisLoop_light1 != None: for paramName in thisLoop_light1: exec('{} = thisLoop_light1[paramName]'.format(paramName)) # ------Prepare to start Routine "light"------- continueRoutine = True routineTimer.add(2.400000) # update component parameters for each repeat image.setImage(path1) key_resp_light.keys = [] key_resp_light.rt = [] _key_resp_light_allKeys = [] # keep track of which components have finished lightComponents = [concentration, image, key_resp_light] for thisComponent in lightComponents: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") lightClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "light"------- while continueRoutine and routineTimer.getTime() > 0: # get current time t = lightClock.getTime() tThisFlip = win.getFutureFlipTime(clock=lightClock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *concentration* updates if concentration.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later concentration.frameNStart = frameN # exact frame index concentration.tStart = t # local t and not account for scr refresh concentration.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(concentration, 'tStartRefresh') # time at next scr refresh concentration.setAutoDraw(True) if concentration.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > concentration.tStartRefresh + 0.4-frameTolerance: # keep track of stop time/frame for later concentration.tStop = t # not accounting for scr refresh concentration.frameNStop = frameN # exact frame index win.timeOnFlip(concentration, 'tStopRefresh') # time at next scr refresh concentration.setAutoDraw(False) # *image* updates if image.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later image.frameNStart = frameN # exact frame index image.tStart = t # local t and not account for scr refresh image.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(image, 'tStartRefresh') # time at next scr refresh image.setAutoDraw(True) if image.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > image.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later image.tStop = t # not accounting for scr refresh image.frameNStop = frameN # exact frame index win.timeOnFlip(image, 'tStopRefresh') # time at next scr refresh image.setAutoDraw(False) # *key_resp_light* updates waitOnFlip = False if key_resp_light.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later key_resp_light.frameNStart = frameN # exact frame index key_resp_light.tStart = t # local t and not account for scr refresh key_resp_light.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_light, 'tStartRefresh') # time at next scr refresh key_resp_light.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_light.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_light.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_light.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > key_resp_light.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later key_resp_light.tStop = t # not accounting for scr refresh key_resp_light.frameNStop = frameN # exact frame index win.timeOnFlip(key_resp_light, 'tStopRefresh') # time at next scr refresh key_resp_light.status = FINISHED if key_resp_light.status == STARTED and not waitOnFlip: theseKeys = key_resp_light.getKeys(keyList=['space'], waitRelease=False) _key_resp_light_allKeys.extend(theseKeys) if len(_key_resp_light_allKeys): key_resp_light.keys = _key_resp_light_allKeys[-1].name # just the last key pressed key_resp_light.rt = _key_resp_light_allKeys[-1].rt # was this correct? if (key_resp_light.keys == str(path1_corr)) or (key_resp_light.keys == path1_corr): key_resp_light.corr = 1 else: key_resp_light.corr = 0 # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in lightComponents: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "light"------- for thisComponent in lightComponents: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) loop_light1.addData('concentration.started', concentration.tStartRefresh) loop_light1.addData('concentration.stopped', concentration.tStopRefresh) loop_light1.addData('image.started', image.tStartRefresh) loop_light1.addData('image.stopped', image.tStopRefresh) # check responses if key_resp_light.keys in ['', [], None]: # No response was made key_resp_light.keys = None # was no response the correct answer?! if str(path1_corr).lower() == 'none': key_resp_light.corr = 1; # correct non-response else: key_resp_light.corr = 0; # failed to respond (incorrectly) # store data for loop_light1 (TrialHandler) loop_light1.addData('key_resp_light.keys',key_resp_light.keys) loop_light1.addData('key_resp_light.corr', key_resp_light.corr) if key_resp_light.keys != None: # we had a response loop_light1.addData('key_resp_light.rt', key_resp_light.rt) loop_light1.addData('key_resp_light.started', key_resp_light.tStartRefresh) loop_light1.addData('key_resp_light.stopped', key_resp_light.tStopRefresh) thisExp.nextEntry() # completed 12 repeats of 'loop_light1' # ------Prepare to start Routine "introduction3"------- continueRoutine = True # update component parameters for each repeat key_resp_3.keys = [] key_resp_3.rt = [] _key_resp_3_allKeys = [] # keep track of which components have finished introduction3Components = [introduction_3, key_resp_3] for thisComponent in introduction3Components: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") introduction3Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "introduction3"------- while continueRoutine: # get current time t = introduction3Clock.getTime() tThisFlip = win.getFutureFlipTime(clock=introduction3Clock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *introduction_3* updates if introduction_3.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later introduction_3.frameNStart = frameN # exact frame index introduction_3.tStart = t # local t and not account for scr refresh introduction_3.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(introduction_3, 'tStartRefresh') # time at next scr refresh introduction_3.setAutoDraw(True) # *key_resp_3* updates waitOnFlip = False if key_resp_3.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later key_resp_3.frameNStart = frameN # exact frame index key_resp_3.tStart = t # local t and not account for scr refresh key_resp_3.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_3, 'tStartRefresh') # time at next scr refresh key_resp_3.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_3.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_3.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_3.status == STARTED and not waitOnFlip: theseKeys = key_resp_3.getKeys(keyList=['space'], waitRelease=False) _key_resp_3_allKeys.extend(theseKeys) if len(_key_resp_3_allKeys): key_resp_3.keys = _key_resp_3_allKeys[-1].name # just the last key pressed key_resp_3.rt = _key_resp_3_allKeys[-1].rt # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in introduction3Components: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "introduction3"------- for thisComponent in introduction3Components: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('introduction_3.started', introduction_3.tStartRefresh) thisExp.addData('introduction_3.stopped', introduction_3.tStopRefresh) # the Routine "introduction3" was not non-slip safe, so reset the non-slip timer routineTimer.reset() # set up handler to look after randomisation of conditions etc loop_face1 = data.TrialHandler(nReps=2, method='random', extraInfo=expInfo, originPath=-1, trialList=data.importConditions('documents\\face.xlsx'), seed=None, name='loop_face1') thisExp.addLoop(loop_face1) # add the loop to the experiment thisLoop_face1 = loop_face1.trialList[0] # so we can initialise stimuli with some values # abbreviate parameter names if possible (e.g. rgb = thisLoop_face1.rgb) if thisLoop_face1 != None: for paramName in thisLoop_face1: exec('{} = thisLoop_face1[paramName]'.format(paramName)) for thisLoop_face1 in loop_face1: currentLoop = loop_face1 # abbreviate parameter names if possible (e.g. rgb = thisLoop_face1.rgb) if thisLoop_face1 != None: for paramName in thisLoop_face1: exec('{} = thisLoop_face1[paramName]'.format(paramName)) # ------Prepare to start Routine "face"------- continueRoutine = True routineTimer.add(2.400000) # update component parameters for each repeat image_2.setImage(path2) key_resp_face.keys = [] key_resp_face.rt = [] _key_resp_face_allKeys = [] # keep track of which components have finished faceComponents = [concentration2, image_2, key_resp_face] for thisComponent in faceComponents: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") faceClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "face"------- while continueRoutine and routineTimer.getTime() > 0: # get current time t = faceClock.getTime() tThisFlip = win.getFutureFlipTime(clock=faceClock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *concentration2* updates if concentration2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later concentration2.frameNStart = frameN # exact frame index concentration2.tStart = t # local t and not account for scr refresh concentration2.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(concentration2, 'tStartRefresh') # time at next scr refresh concentration2.setAutoDraw(True) if concentration2.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > concentration2.tStartRefresh + 0.4-frameTolerance: # keep track of stop time/frame for later concentration2.tStop = t # not accounting for scr refresh concentration2.frameNStop = frameN # exact frame index win.timeOnFlip(concentration2, 'tStopRefresh') # time at next scr refresh concentration2.setAutoDraw(False) # *image_2* updates if image_2.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later image_2.frameNStart = frameN # exact frame index image_2.tStart = t # local t and not account for scr refresh image_2.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(image_2, 'tStartRefresh') # time at next scr refresh image_2.setAutoDraw(True) if image_2.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > image_2.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later image_2.tStop = t # not accounting for scr refresh image_2.frameNStop = frameN # exact frame index win.timeOnFlip(image_2, 'tStopRefresh') # time at next scr refresh image_2.setAutoDraw(False) # *key_resp_face* updates waitOnFlip = False if key_resp_face.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later key_resp_face.frameNStart = frameN # exact frame index key_resp_face.tStart = t # local t and not account for scr refresh key_resp_face.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_face, 'tStartRefresh') # time at next scr refresh key_resp_face.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_face.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_face.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_face.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > key_resp_face.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later key_resp_face.tStop = t # not accounting for scr refresh key_resp_face.frameNStop = frameN # exact frame index win.timeOnFlip(key_resp_face, 'tStopRefresh') # time at next scr refresh key_resp_face.status = FINISHED if key_resp_face.status == STARTED and not waitOnFlip: theseKeys = key_resp_face.getKeys(keyList=['space'], waitRelease=False) _key_resp_face_allKeys.extend(theseKeys) if len(_key_resp_face_allKeys): key_resp_face.keys = _key_resp_face_allKeys[-1].name # just the last key pressed key_resp_face.rt = _key_resp_face_allKeys[-1].rt # was this correct? if (key_resp_face.keys == str(path2_corr)) or (key_resp_face.keys == path2_corr): key_resp_face.corr = 1 else: key_resp_face.corr = 0 # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in faceComponents: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "face"------- for thisComponent in faceComponents: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) loop_face1.addData('concentration2.started', concentration2.tStartRefresh) loop_face1.addData('concentration2.stopped', concentration2.tStopRefresh) loop_face1.addData('image_2.started', image_2.tStartRefresh) loop_face1.addData('image_2.stopped', image_2.tStopRefresh) # check responses if key_resp_face.keys in ['', [], None]: # No response was made key_resp_face.keys = None # was no response the correct answer?! if str(path2_corr).lower() == 'none': key_resp_face.corr = 1; # correct non-response else: key_resp_face.corr = 0; # failed to respond (incorrectly) # store data for loop_face1 (TrialHandler) loop_face1.addData('key_resp_face.keys',key_resp_face.keys) loop_face1.addData('key_resp_face.corr', key_resp_face.corr) if key_resp_face.keys != None: # we had a response loop_face1.addData('key_resp_face.rt', key_resp_face.rt) loop_face1.addData('key_resp_face.started', key_resp_face.tStartRefresh) loop_face1.addData('key_resp_face.stopped', key_resp_face.tStopRefresh) thisExp.nextEntry() # completed 2 repeats of 'loop_face1' # ------Prepare to start Routine "tip1"------- continueRoutine = True # update component parameters for each repeat key_resp_5.keys = [] key_resp_5.rt = [] _key_resp_5_allKeys = [] # keep track of which components have finished tip1Components = [tip_1, key_resp_5] for thisComponent in tip1Components: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") tip1Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "tip1"------- while continueRoutine: # get current time t = tip1Clock.getTime() tThisFlip = win.getFutureFlipTime(clock=tip1Clock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *tip_1* updates if tip_1.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later tip_1.frameNStart = frameN # exact frame index tip_1.tStart = t # local t and not account for scr refresh tip_1.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(tip_1, 'tStartRefresh') # time at next scr refresh tip_1.setAutoDraw(True) # *key_resp_5* updates waitOnFlip = False if key_resp_5.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later key_resp_5.frameNStart = frameN # exact frame index key_resp_5.tStart = t # local t and not account for scr refresh key_resp_5.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_5, 'tStartRefresh') # time at next scr refresh key_resp_5.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_5.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_5.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_5.status == STARTED and not waitOnFlip: theseKeys = key_resp_5.getKeys(keyList=['space'], waitRelease=False) _key_resp_5_allKeys.extend(theseKeys) if len(_key_resp_5_allKeys): key_resp_5.keys = _key_resp_5_allKeys[-1].name # just the last key pressed key_resp_5.rt = _key_resp_5_allKeys[-1].rt # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in tip1Components: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "tip1"------- for thisComponent in tip1Components: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('tip_1.started', tip_1.tStartRefresh) thisExp.addData('tip_1.stopped', tip_1.tStopRefresh) # the Routine "tip1" was not non-slip safe, so reset the non-slip timer routineTimer.reset() # set up handler to look after randomisation of conditions etc loop_light2 = data.TrialHandler(nReps=12, method='random', extraInfo=expInfo, originPath=-1, trialList=data.importConditions('documents\\light.xlsx'), seed=None, name='loop_light2') thisExp.addLoop(loop_light2) # add the loop to the experiment thisLoop_light2 = loop_light2.trialList[0] # so we can initialise stimuli with some values # abbreviate parameter names if possible (e.g. rgb = thisLoop_light2.rgb) if thisLoop_light2 != None: for paramName in thisLoop_light2: exec('{} = thisLoop_light2[paramName]'.format(paramName)) for thisLoop_light2 in loop_light2: currentLoop = loop_light2 # abbreviate parameter names if possible (e.g. rgb = thisLoop_light2.rgb) if thisLoop_light2 != None: for paramName in thisLoop_light2: exec('{} = thisLoop_light2[paramName]'.format(paramName)) # ------Prepare to start Routine "light"------- continueRoutine = True routineTimer.add(2.400000) # update component parameters for each repeat image.setImage(path1) key_resp_light.keys = [] key_resp_light.rt = [] _key_resp_light_allKeys = [] # keep track of which components have finished lightComponents = [concentration, image, key_resp_light] for thisComponent in lightComponents: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") lightClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "light"------- while continueRoutine and routineTimer.getTime() > 0: # get current time t = lightClock.getTime() tThisFlip = win.getFutureFlipTime(clock=lightClock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *concentration* updates if concentration.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later concentration.frameNStart = frameN # exact frame index concentration.tStart = t # local t and not account for scr refresh concentration.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(concentration, 'tStartRefresh') # time at next scr refresh concentration.setAutoDraw(True) if concentration.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > concentration.tStartRefresh + 0.4-frameTolerance: # keep track of stop time/frame for later concentration.tStop = t # not accounting for scr refresh concentration.frameNStop = frameN # exact frame index win.timeOnFlip(concentration, 'tStopRefresh') # time at next scr refresh concentration.setAutoDraw(False) # *image* updates if image.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later image.frameNStart = frameN # exact frame index image.tStart = t # local t and not account for scr refresh image.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(image, 'tStartRefresh') # time at next scr refresh image.setAutoDraw(True) if image.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > image.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later image.tStop = t # not accounting for scr refresh image.frameNStop = frameN # exact frame index win.timeOnFlip(image, 'tStopRefresh') # time at next scr refresh image.setAutoDraw(False) # *key_resp_light* updates waitOnFlip = False if key_resp_light.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later key_resp_light.frameNStart = frameN # exact frame index key_resp_light.tStart = t # local t and not account for scr refresh key_resp_light.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_light, 'tStartRefresh') # time at next scr refresh key_resp_light.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_light.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_light.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_light.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > key_resp_light.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later key_resp_light.tStop = t # not accounting for scr refresh key_resp_light.frameNStop = frameN # exact frame index win.timeOnFlip(key_resp_light, 'tStopRefresh') # time at next scr refresh key_resp_light.status = FINISHED if key_resp_light.status == STARTED and not waitOnFlip: theseKeys = key_resp_light.getKeys(keyList=['space'], waitRelease=False) _key_resp_light_allKeys.extend(theseKeys) if len(_key_resp_light_allKeys): key_resp_light.keys = _key_resp_light_allKeys[-1].name # just the last key pressed key_resp_light.rt = _key_resp_light_allKeys[-1].rt # was this correct? if (key_resp_light.keys == str(path1_corr)) or (key_resp_light.keys == path1_corr): key_resp_light.corr = 1 else: key_resp_light.corr = 0 # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in lightComponents: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "light"------- for thisComponent in lightComponents: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) loop_light2.addData('concentration.started', concentration.tStartRefresh) loop_light2.addData('concentration.stopped', concentration.tStopRefresh) loop_light2.addData('image.started', image.tStartRefresh) loop_light2.addData('image.stopped', image.tStopRefresh) # check responses if key_resp_light.keys in ['', [], None]: # No response was made key_resp_light.keys = None # was no response the correct answer?! if str(path1_corr).lower() == 'none': key_resp_light.corr = 1; # correct non-response else: key_resp_light.corr = 0; # failed to respond (incorrectly) # store data for loop_light2 (TrialHandler) loop_light2.addData('key_resp_light.keys',key_resp_light.keys) loop_light2.addData('key_resp_light.corr', key_resp_light.corr) if key_resp_light.keys != None: # we had a response loop_light2.addData('key_resp_light.rt', key_resp_light.rt) loop_light2.addData('key_resp_light.started', key_resp_light.tStartRefresh) loop_light2.addData('key_resp_light.stopped', key_resp_light.tStopRefresh) thisExp.nextEntry() # completed 12 repeats of 'loop_light2' # ------Prepare to start Routine "tip2"------- continueRoutine = True # update component parameters for each repeat key_resp_7.keys = [] key_resp_7.rt = [] _key_resp_7_allKeys = [] # keep track of which components have finished tip2Components = [tip_2, key_resp_7] for thisComponent in tip2Components: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") tip2Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "tip2"------- while continueRoutine: # get current time t = tip2Clock.getTime() tThisFlip = win.getFutureFlipTime(clock=tip2Clock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *tip_2* updates if tip_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later tip_2.frameNStart = frameN # exact frame index tip_2.tStart = t # local t and not account for scr refresh tip_2.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(tip_2, 'tStartRefresh') # time at next scr refresh tip_2.setAutoDraw(True) # *key_resp_7* updates waitOnFlip = False if key_resp_7.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later key_resp_7.frameNStart = frameN # exact frame index key_resp_7.tStart = t # local t and not account for scr refresh key_resp_7.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_7, 'tStartRefresh') # time at next scr refresh key_resp_7.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_7.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_7.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_7.status == STARTED and not waitOnFlip: theseKeys = key_resp_7.getKeys(keyList=['space'], waitRelease=False) _key_resp_7_allKeys.extend(theseKeys) if len(_key_resp_7_allKeys): key_resp_7.keys = _key_resp_7_allKeys[-1].name # just the last key pressed key_resp_7.rt = _key_resp_7_allKeys[-1].rt # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in tip2Components: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "tip2"------- for thisComponent in tip2Components: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('tip_2.started', tip_2.tStartRefresh) thisExp.addData('tip_2.stopped', tip_2.tStopRefresh) # the Routine "tip2" was not non-slip safe, so reset the non-slip timer routineTimer.reset() # set up handler to look after randomisation of conditions etc loop_face2 = data.TrialHandler(nReps=2, method='random', extraInfo=expInfo, originPath=-1, trialList=data.importConditions('documents\\face.xlsx'), seed=None, name='loop_face2') thisExp.addLoop(loop_face2) # add the loop to the experiment thisLoop_face2 = loop_face2.trialList[0] # so we can initialise stimuli with some values # abbreviate parameter names if possible (e.g. rgb = thisLoop_face2.rgb) if thisLoop_face2 != None: for paramName in thisLoop_face2: exec('{} = thisLoop_face2[paramName]'.format(paramName)) for thisLoop_face2 in loop_face2: currentLoop = loop_face2 # abbreviate parameter names if possible (e.g. rgb = thisLoop_face2.rgb) if thisLoop_face2 != None: for paramName in thisLoop_face2: exec('{} = thisLoop_face2[paramName]'.format(paramName)) # ------Prepare to start Routine "face"------- continueRoutine = True routineTimer.add(2.400000) # update component parameters for each repeat image_2.setImage(path2) key_resp_face.keys = [] key_resp_face.rt = [] _key_resp_face_allKeys = [] # keep track of which components have finished faceComponents = [concentration2, image_2, key_resp_face] for thisComponent in faceComponents: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") faceClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "face"------- while continueRoutine and routineTimer.getTime() > 0: # get current time t = faceClock.getTime() tThisFlip = win.getFutureFlipTime(clock=faceClock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *concentration2* updates if concentration2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later concentration2.frameNStart = frameN # exact frame index concentration2.tStart = t # local t and not account for scr refresh concentration2.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(concentration2, 'tStartRefresh') # time at next scr refresh concentration2.setAutoDraw(True) if concentration2.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > concentration2.tStartRefresh + 0.4-frameTolerance: # keep track of stop time/frame for later concentration2.tStop = t # not accounting for scr refresh concentration2.frameNStop = frameN # exact frame index win.timeOnFlip(concentration2, 'tStopRefresh') # time at next scr refresh concentration2.setAutoDraw(False) # *image_2* updates if image_2.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later image_2.frameNStart = frameN # exact frame index image_2.tStart = t # local t and not account for scr refresh image_2.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(image_2, 'tStartRefresh') # time at next scr refresh image_2.setAutoDraw(True) if image_2.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > image_2.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later image_2.tStop = t # not accounting for scr refresh image_2.frameNStop = frameN # exact frame index win.timeOnFlip(image_2, 'tStopRefresh') # time at next scr refresh image_2.setAutoDraw(False) # *key_resp_face* updates waitOnFlip = False if key_resp_face.status == NOT_STARTED and tThisFlip >= 0.4-frameTolerance: # keep track of start time/frame for later key_resp_face.frameNStart = frameN # exact frame index key_resp_face.tStart = t # local t and not account for scr refresh key_resp_face.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(key_resp_face, 'tStartRefresh') # time at next scr refresh key_resp_face.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(key_resp_face.clock.reset) # t=0 on next screen flip win.callOnFlip(key_resp_face.clearEvents, eventType='keyboard') # clear events on next screen flip if key_resp_face.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > key_resp_face.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later key_resp_face.tStop = t # not accounting for scr refresh key_resp_face.frameNStop = frameN # exact frame index win.timeOnFlip(key_resp_face, 'tStopRefresh') # time at next scr refresh key_resp_face.status = FINISHED if key_resp_face.status == STARTED and not waitOnFlip: theseKeys = key_resp_face.getKeys(keyList=['space'], waitRelease=False) _key_resp_face_allKeys.extend(theseKeys) if len(_key_resp_face_allKeys): key_resp_face.keys = _key_resp_face_allKeys[-1].name # just the last key pressed key_resp_face.rt = _key_resp_face_allKeys[-1].rt # was this correct? if (key_resp_face.keys == str(path2_corr)) or (key_resp_face.keys == path2_corr): key_resp_face.corr = 1 else: key_resp_face.corr = 0 # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in faceComponents: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "face"------- for thisComponent in faceComponents: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) loop_face2.addData('concentration2.started', concentration2.tStartRefresh) loop_face2.addData('concentration2.stopped', concentration2.tStopRefresh) loop_face2.addData('image_2.started', image_2.tStartRefresh) loop_face2.addData('image_2.stopped', image_2.tStopRefresh) # check responses if key_resp_face.keys in ['', [], None]: # No response was made key_resp_face.keys = None # was no response the correct answer?! if str(path2_corr).lower() == 'none': key_resp_face.corr = 1; # correct non-response else: key_resp_face.corr = 0; # failed to respond (incorrectly) # store data for loop_face2 (TrialHandler) loop_face2.addData('key_resp_face.keys',key_resp_face.keys) loop_face2.addData('key_resp_face.corr', key_resp_face.corr) if key_resp_face.keys != None: # we had a response loop_face2.addData('key_resp_face.rt', key_resp_face.rt) loop_face2.addData('key_resp_face.started', key_resp_face.tStartRefresh) loop_face2.addData('key_resp_face.stopped', key_resp_face.tStopRefresh) thisExp.nextEntry() # completed 2 repeats of 'loop_face2' # ------Prepare to start Routine "thanks"------- continueRoutine = True routineTimer.add(2.000000) # update component parameters for each repeat # keep track of which components have finished thanksComponents = [text] for thisComponent in thanksComponents: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") thanksClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "thanks"------- while continueRoutine and routineTimer.getTime() > 0: # get current time t = thanksClock.getTime() tThisFlip = win.getFutureFlipTime(clock=thanksClock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *text* updates if text.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later text.frameNStart = frameN # exact frame index text.tStart = t # local t and not account for scr refresh text.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(text, 'tStartRefresh') # time at next scr refresh text.setAutoDraw(True) if text.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > text.tStartRefresh + 2-frameTolerance: # keep track of stop time/frame for later text.tStop = t # not accounting for scr refresh text.frameNStop = frameN # exact frame index win.timeOnFlip(text, 'tStopRefresh') # time at next scr refresh text.setAutoDraw(False) # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in thanksComponents: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "thanks"------- for thisComponent in thanksComponents: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('text.started', text.tStartRefresh) thisExp.addData('text.stopped', text.tStopRefresh) # Flip one final time so any remaining win.callOnFlip() # and win.timeOnFlip() tasks get executed before quitting win.flip() # these shouldn't be strictly necessary (should auto-save) thisExp.saveAsWideText(filename+'.csv') thisExp.saveAsPickle(filename) logging.flush() # make sure everything is closed down thisExp.abort() # or data files will save again on exit win.close() core.quit()

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de9f6a0fc1195d27353cc03aa58ff5735b9edee9

27,066

py

Python

tests/e2e/interOp/validation_of_operating_modes/nat_mode/client_connectivity_test/android/test_general_security_modes.py

dutta-rohan/wlan-testing

77264245b62e21dff5f38c7eae74c22e0cdeefbb

[ "BSD-3-Clause" ]

7

2020-08-19T16:45:46.000Z

2022-02-10T09:55:22.000Z

tests/e2e/interOp/validation_of_operating_modes/nat_mode/client_connectivity_test/android/test_general_security_modes.py

dutta-rohan/wlan-testing

77264245b62e21dff5f38c7eae74c22e0cdeefbb

[ "BSD-3-Clause" ]

47

2020-12-20T16:06:03.000Z

2022-03-23T03:01:22.000Z

tests/e2e/interOp/validation_of_operating_modes/nat_mode/client_connectivity_test/android/test_general_security_modes.py

dutta-rohan/wlan-testing

77264245b62e21dff5f38c7eae74c22e0cdeefbb

[ "BSD-3-Clause" ]

9

2021-02-04T22:32:06.000Z

2021-12-14T17:45:51.000Z

from logging import exception import unittest import warnings from perfecto.test import TestResultFactory import pytest import sys import time from selenium.common.exceptions import NoSuchElementException from selenium.webdriver.common.by import By from appium import webdriver from selenium.common.exceptions import NoSuchElementException import sys import allure if 'perfecto_libs' not in sys.path: sys.path.append(f'../libs/perfecto_libs') pytestmark = [pytest.mark.sanity, pytest.mark.interop, pytest.mark.android, pytest.mark.interop_and, pytest.mark.client_connectivity ,pytest.mark.interop_uc_sanity, pytest.mark.nat] from android_lib import closeApp, set_APconnMobileDevice_android, Toggle_AirplaneMode_android, ForgetWifiConnection, openApp, \ get_ip_address_and, verifyUploadDownloadSpeed_android, wifi_connect, wifi_disconnect_and_forget setup_params_general = { "mode": "NAT", "ssid_modes": { "wpa": [{"ssid_name": "ssid_wpa_2g", "appliedRadios": ["2G"], "security_key": "something"}, {"ssid_name": "ssid_wpa_5g", "appliedRadios": ["5G"], "security_key": "something"}], "open": [{"ssid_name": "ssid_open_2g", "appliedRadios": ["2G"]}, {"ssid_name": "ssid_open_5g", "appliedRadios": ["5G"]}], "wpa2_personal": [ {"ssid_name": "ssid_wpa2_2g", "appliedRadios": ["2G"], "security_key": "something"}, {"ssid_name": "ssid_wpa2_5g", "appliedRadios": ["5G"], "security_key": "something"}]}, "rf": {}, "radius": False } @allure.suite(suite_name="interop sanity") @allure.sub_suite(sub_suite_name="NAT Mode Client Connectivity : Suite-A") @pytest.mark.InteropsuiteA @allure.feature("NAT MODE CLIENT CONNECTIVITY") @pytest.mark.parametrize( 'setup_profiles', [setup_params_general], indirect=True, scope="class" ) @pytest.mark.usefixtures("setup_profiles") class TestNatModeConnectivitySuiteOne(object): """ Client Connect SuiteA pytest -m "client_connectivity and nat and InteropsuiteA" """ @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4536", name="WIFI-4536") @pytest.mark.fiveg @pytest.mark.wpa2_personal def test_ClientConnectivity_5g_WPA2_Personal_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general["ssid_modes"]["wpa2_personal"][1] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print("SSID_NAME: " + ssidName) print("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4535", name="WIFI-4535") @pytest.mark.twog @pytest.mark.wpa2_personal def test_ClientConnectivity_2g_WPA2_Personal_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general["ssid_modes"]["wpa2_personal"][0] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4534", name="WIFI-4534") @pytest.mark.fiveg @pytest.mark.wpa def test_ClientConnectivity_5g_WPA_Personal_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general["ssid_modes"]["wpa"][1] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4533", name="WIFI-4533") @pytest.mark.twog @pytest.mark.wpa def test_ClientConnectivity_2g_WPA_Personal_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general["ssid_modes"]["wpa"][0] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4531", name="WIFI-4531") @pytest.mark.fiveg @pytest.mark.open def test_ClientConnectivity_5g_Open_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general["ssid_modes"]["open"][1] ssidName = profile_data["ssid_name"] ssidPassword = "[BLANK]" print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4530", name="WIFI-4530") @pytest.mark.twog @pytest.mark.open def test_ClientConnectivity_2g_Open_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general["ssid_modes"]["open"][0] ssidName = profile_data["ssid_name"] ssidPassword = "[BLANK]" print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False setup_params_general_two = { "mode": "NAT", "ssid_modes": { "wpa3_personal": [ {"ssid_name": "ssid_wpa3_p_2g", "appliedRadios": ["2G"], "security_key": "something"}, {"ssid_name": "ssid_wpa3_p_5g", "appliedRadios": ["5G"], "security_key": "something"}], "wpa3_personal_mixed": [ {"ssid_name": "ssid_wpa3_p_m_2g", "appliedRadios": ["2G"], "security_key": "something"}, {"ssid_name": "ssid_wpa3_p_m_5g", "appliedRadios": ["5G"], "security_key": "something"}], "wpa_wpa2_personal_mixed": [ {"ssid_name": "ssid_wpa_wpa2_p_m_2g", "appliedRadios": ["2G"], "security_key": "something"}, {"ssid_name": "ssid_wpa_wpa2_p_m_5g", "appliedRadios": ["5G"], "security_key": "something"}] }, "rf": {}, "radius": False } @allure.suite(suite_name="interop sanity") @allure.sub_suite(sub_suite_name="Bridge Mode Client Connectivity : Suite-B") @pytest.mark.InteropsuiteB @allure.feature("NAT MODE CLIENT CONNECTIVITY") @pytest.mark.parametrize( 'setup_profiles', [setup_params_general_two], indirect=True, scope="class" ) @pytest.mark.usefixtures("setup_profiles") class TestNatModeConnectivitySuiteTwo(object): """ Client Connectivity SuiteB pytest -m "client_connectivity and nat and InteropsuiteB" """ @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4539", name="WIFI-4539") @pytest.mark.wpa3_personal @pytest.mark.twog @allure.story('open 2.4 GHZ Band') def test_wpa3_personal_2g_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general_two["ssid_modes"]["wpa3_personal"][0] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4540", name="WIFI-4540") @pytest.mark.wpa3_personal @pytest.mark.fiveg @allure.story('open 5 GHZ Band') def test_wpa3_personal_5g_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general_two["ssid_modes"]["wpa3_personal"][1] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4541", name="WIFI-4541") @pytest.mark.wpa3_personal_mixed @pytest.mark.twog @allure.story('open 2.4 GHZ Band') def test_wpa3_personal_mixed_2g_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general_two["ssid_modes"]["wpa3_personal_mixed"][0] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4542", name="WIFI-4542") @pytest.mark.wpa3_personal_mixed @pytest.mark.fiveg @allure.story('open 5 GHZ Band') def test_wpa3_personal_mixed_5g(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general_two["ssid_modes"]["wpa3_personal_mixed"][1] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4543", name="WIFI-4543") @pytest.mark.wpa_wpa2_personal_mixed @pytest.mark.twog @allure.story('wpa wpa2 personal mixed 2.4 GHZ Band') def test_wpa_wpa2_personal_2g_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general_two["ssid_modes"]["wpa_wpa2_personal_mixed"][0] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4544", name="WIFI-4544") @pytest.mark.wpa_wpa2_personal_mixed @pytest.mark.fiveg @allure.story('wpa wpa2 personal mixed 5 GHZ Band') def test_wpa_wpa2_personal_5g_Nat(self, request, get_vif_state, get_ap_logs, get_ToggleAirplaneMode_data, setup_perfectoMobile_android): profile_data = setup_params_general_two["ssid_modes"]["wpa_wpa2_personal_mixed"][1] ssidName = profile_data["ssid_name"] ssidPassword = profile_data["security_key"] print ("SSID_NAME: " + ssidName) print ("SSID_PASS: " + ssidPassword) get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data # Set Wifi/AP Mode ip, is_internet = get_ip_address_and(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) # if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False

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1

0

null

0

1

0

8

dec644cbd63f52c01ed79355da5f6076e4de28ee

6,929

py

Python

tests/test_views.py

Teddy-Schmitz/temperature_admin

dd899b4b7bd9d1e27f9e00c1eb65d11fdf49bfc8

[ "MIT" ]

null

tests/test_views.py

Teddy-Schmitz/temperature_admin

dd899b4b7bd9d1e27f9e00c1eb65d11fdf49bfc8

[ "MIT" ]

1

2015-07-13T12:30:06.000Z

tests/test_views.py

Teddy-Schmitz/temperature_admin

dd899b4b7bd9d1e27f9e00c1eb65d11fdf49bfc8

[ "MIT" ]

null

import base64 import json from models.users import User from models.event import Event, EventType import pytest def test_login_success(test_client, fake_users): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/users', headers=header) assert resp.status_code == 200 def test_login_failure(test_client, fake_users): auth_string = base64.b64encode('test_user:fail_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/users', headers=header) assert resp.status_code == 401 def test_required_login_views(test_client, session): resp = test_client.get('/users') assert resp.status_code == 401 resp = test_client.post('/users/test') assert resp.status_code == 401 resp = test_client.post('/users/create') assert resp.status_code == 401 resp = test_client.get('/users/delete/test') assert resp.status_code == 401 resp = test_client.get('/poweron') assert resp.status_code == 401 resp = test_client.get('/poweroff') assert resp.status_code == 401 def test_index(test_client): resp = test_client.get('/') assert resp.status_code == 200 assert 'Temperature Admin' in resp.data def test_receive_data_fail(test_client): resp = test_client.post('/data') assert resp.status_code == 400 def test_receive_data_success(test_client, fake_temperatures): resp = test_client.post('/data', content_type='application/json', data=json.dumps(dict(temperature=45.4, humidity=50.0))) assert resp.status_code == 201 assert resp.data == 'Created' def test_receive_event_fail(test_client): resp = test_client.post('/event') assert resp.status_code == 400 def test_receive_event_success(test_client, fake_events): resp = test_client.post('/event', content_type='application/json', data=json.dumps(dict(event='on', description='test'))) assert resp.status_code == 201 assert resp.data == 'Created' def test_send_latest_event(test_client, fake_events): resp = test_client.get('/event/last') assert resp.status_code == 200 data = json.loads(resp.data) assert data['results']['timestamp'] == fake_events.timestamp.timestamp def test_send_events(test_client, fake_events): resp = test_client.get('/event?range=15') assert resp.status_code == 200 data = json.loads(resp.data) assert len(data['results']) == 2 def test_send_data(test_client, fake_temperatures): resp = test_client.get('/data?range=15') assert resp.status_code == 200 data = json.loads(resp.data) assert len(data['results']) == 2 def test_modify_user_success(test_client, fake_users): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.post('/users/test_user', headers=header, data=dict(password='changed_password')) user = User.query.filter(User.username == 'test_user').first() assert resp.status_code == 200 assert user.password == 'changed_password' assert user.username == 'test_user' def test_modify_user_failure(test_client, fake_users): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.post('/users/bad_user', headers=header, data=dict(password='changed_password')) user = User.query.filter(User.username == 'test_user').first() assert resp.status_code == 404 assert user.password == 'test_password' assert user.username == 'test_user' def test_delete_user_success(test_client, fake_users): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/users/delete/test_user', headers=header) user = User.query.filter(User.username == 'test_user').first() assert resp.status_code == 200 assert user is None def test_delete_user_failure(test_client, fake_users): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/users/delete/bad_user', headers=header) user = User.query.filter(User.username == 'test_user').first() assert resp.status_code == 404 assert user.password == 'test_password' assert user.username == 'test_user' def test_create_user_success(test_client, fake_users): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.post('/users/create', headers=header, data=dict(username='test_user2', password='test_password')) user = User.query.filter(User.username == 'test_user2').first() assert resp.status_code == 200 assert user is not None assert user.username == 'test_user2' assert user.password == 'test_password' def test_create_user_failure(test_client, fake_users): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.post('/users/create', headers=header, data=dict(username='test_user2')) user = User.query.filter(User.username == 'test_user2').first() assert resp.status_code == 400 assert resp.data == 'Error' assert user is None @pytest.mark.json_data('{ "return_value": 1}') def test_power_on(test_client, fake_users, arduino): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/poweron', headers=header) event = Event.last_event() assert resp.status_code == 200 assert event.event == EventType.on @pytest.mark.json_data('{ "return_value": 1}') def test_power_off(test_client, fake_users, arduino): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/poweroff', headers=header) event = Event.last_event() assert resp.status_code == 200 assert event.event == EventType.off @pytest.mark.json_data('{ "return_value": 0}') def test_power_on_failure(test_client, fake_users, arduino): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/poweron', headers=header) event = Event.last_event() assert resp.status_code == 500 assert event is None @pytest.mark.json_data('{ "return_value": 0}') def test_power_off_failure(test_client, fake_users, arduino): auth_string = base64.b64encode('test_user:test_password') header = {'Authorization': 'Basic ' + auth_string} resp = test_client.get('/poweroff', headers=header) event = Event.last_event() assert resp.status_code == 500 assert event is None

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0

null

0

1

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null

0

1

0

7

deea040a0e883c011f092468ee3a32523a966081

31,016

py

Python

deep_models.py

iiscleap/deep-cca-for-audio-EEG

44879e4a44566eaf41f2db1d7daffff7bcba6093

[ "MIT" ]

4

2020-12-03T08:08:03.000Z

2021-06-23T14:54:51.000Z

deep_models.py

iiscleap/deep-cca-for-audio-EEG

44879e4a44566eaf41f2db1d7daffff7bcba6093

[ "MIT" ]

null

deep_models.py

iiscleap/deep-cca-for-audio-EEG

44879e4a44566eaf41f2db1d7daffff7bcba6093

[ "MIT" ]

2

2021-06-23T14:55:25.000Z

2021-11-04T21:14:26.000Z

import numpy as np from os import path import scipy.io from pdb import set_trace as bp #################added break point accessor#################### from scipy.signal import lfilter try: # SciPy >= 0.19 from scipy.special import comb, logsumexp except ImportError: from scipy.misc import comb, logsumexp # noqa import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torch.nn import Parameter from torch.utils.data import DataLoader from cca_functions import my_standardize, my_corr from deep_nets import * from deep_losses import * device = torch.device('cuda') torch.cuda.empty_cache() # IF GIVEN 10 SEEDS, ALL THE MODELS GET ONE FORWARD PASS AND SEED WITH BEST VALIDATION IS SELECTED # IF ONLY ONE SEED, THE WEIGHTS ARE INITIALIZED ACCORDINGLY # TRAIN AND RETURN THE MODEL # MODEL : model2_13 # LOSS : cca_loss def dcca_model(stim_data, resp_data, o_dim, learning_rate=1e-3, use_all_singular_values=False, epoch_num=12, batch_size=2048, reg_par=1e-4, dropout=0.05, best_only=True, path_name="", seeds=np.ceil(np.random.rand(10)*100)): """ ARGUMENTS: stim_data : A THREE ELEMENT LIST OF STIMULI DATA ARRANGED AS: [STIM_TRAINING, STIM_VALIDATION, STIM_TEST] resp_data : A THREE ELEMENT LIST OF RESPONSE DATA ARRANGED AS: [RESP_TRAINING, RESP_VALIDATION, RESP_TEST] learning_rate : LEARNING RATE OF THE MODEL (DEFAULT: 1e-3) use_all_singular_values : WHETHER THE MODEL SHOULD USE ALL THE SINGULAR VALUES IN THE CCA LOSS (DEFAULT: False) epoch_num : NUMBER OF EPOCHS OF TRAINING (DEFAULT: 12) batch_size : MINIBATCH SIZES FOR TRAINING THE MODEL (DEFAULT: 2048) reg_par : REGULARIZATION PARAMETER FOR WEIGHT DECAY (DEFAULT: 1e-4) dropout : DROPOUTS PERCENTAGE IN THE MODEL (DEFAULT: 0.05) best_only : SAVE THE MODEL ONLY WITH THE BEST VALIDATION LOSS (DEFAULT: True) path_name : WHERE THE MODEL IS TO BE SAVED. (DEFAULT: "") seeds : SEED FOR THE DEEP MODEL. If given one seed, the model will be initialized with that seed. IF given more than one seed, the seed with best val loss is selected. RETURNS: new_data : NEW REPRESENTATIONS AFTER PERFORMING DEEP CCA correlations : THE TRAINING, VALIDATION AND TEST SET LOSSES WHILE TRAINING THE MODEL - TO TRACK THE MODEL AS TRAINING PROGRESSED. model : THE TRAINED MODEL. """ stimtr = stim_data[0] stimval = stim_data[1] stimte = stim_data[2] resptr = resp_data[0] respval = resp_data[1] respte = resp_data[2] stimtr, mean1, std1 = my_standardize(stimtr) resptr, mean2, std2 = my_standardize(resptr) stimval = (stimval - mean1) / std1 stimte = (stimte - mean1) / std1 respval = (respval - mean2) / std2 respte = (respte - mean2) / std2 resp_tr = torch.from_numpy(resptr ).float() resp_val = torch.from_numpy(respval).float() resp_te = torch.from_numpy(respte ).float() stim_tr = torch.from_numpy(stimtr ).float(); stim_val = torch.from_numpy(stimval).float(); stim_te = torch.from_numpy(stimte ).float(); data_tr = torch.cat([resp_tr, stim_tr ], 1) data_val = torch.cat([resp_val, stim_val], 1) data_te = torch.cat([resp_te, stim_te ], 1) i_shape1 = resp_tr.shape[1] i_shape2 = stim_tr.shape[1] # best_only = True act = "sigmoid" o_act = 'leaky_relu' if (isinstance(seeds, int)): seed = seeds elif not(isinstance(seeds, int)) and len(seeds) == 1: seed = seeds[0] else: torch.backends.cudnn.deterministic = True first_and_last = np.zeros((len(seeds),3)) models = [None] * len(seeds) print('seeds: ', seeds) for seed_num, seed in enumerate(seeds) : torch.manual_seed(seed) if torch.cuda.is_available() : torch.cuda.manual_seed_all(seed) model = model2_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) model = model.to(device) model_optimizer = optim.Adam(model.parameters(), lr=learning_rate, weight_decay=reg_par) print('MODEL : {}'.format(seed_num)) model.eval() torch.cuda.empty_cache() tr_loss = 0 ; count = 0 dataloader = DataLoader(data_tr, batch_size, shuffle=True) with torch.no_grad(): for trs in dataloader : trs = trs.to(device) outputs = model(trs) loss = cca_loss(outputs, o_dim, use_all_singular_values) tr_loss = tr_loss + loss count = count + 1 del trs tr_loss = tr_loss / count data_val = data_val.to(device) val_ops = model(data_val) val_loss = cca_loss(val_ops, o_dim, use_all_singular_values) data_val = data_val.cpu() torch.cuda.empty_cache() data_te = data_te.to(device) test_ops = model(data_te) test_loss = cca_loss(test_ops, o_dim, use_all_singular_values) data_te = data_te.cpu() torch.cuda.empty_cache() models[seed_num] = model first_and_last[seed_num] = [-tr_loss, -val_loss, -test_loss] print('{:0.4f} {:0.4f} {:0.4f}'.format(-tr_loss, -val_loss, -test_loss)) np.set_printoptions(precision=4) idx = np.argsort(-first_and_last[:,1]) print(first_and_last[idx,1:]) print(seeds[idx]) seed = seeds[idx[0]] print("seed: ", seed ) torch.manual_seed(seed) if torch.cuda.is_available() : torch.cuda.manual_seed_all(seed) model = model2_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) model = model.to(device) model_optimizer = optim.Adam(model.parameters(), lr=learning_rate, weight_decay=reg_par) model_state_dict = [] min_loss = 0.00 ; min_loss2 = 0.00 correlations = np.zeros((epoch_num, 3)) for epoch in range(epoch_num): # loop over the dataset multiple times model.train() dataloader = DataLoader(data_tr, batch_size, shuffle=True) for trs in dataloader : model_optimizer.zero_grad() trs = trs.to(device) outputs = model(trs) loss = cca_loss(outputs, o_dim, use_all_singular_values) loss.backward() model_optimizer.step() del trs model.eval() torch.cuda.empty_cache() tr_loss = 0 count = 0 dataloader = DataLoader(data_tr, batch_size, shuffle=True) with torch.no_grad(): for trs in dataloader : trs = trs.to(device) outputs = model(trs) loss = cca_loss(outputs, o_dim, use_all_singular_values) loss = loss.item() tr_loss = tr_loss + loss count = count + 1 del trs correlations[epoch, 0] = -tr_loss / (count) torch.cuda.empty_cache() print('EPOCH : {}'.format(epoch)) print(' Training CORRELATION : {:0.4f}'.format(correlations[epoch, 0])) data_val = data_val.to(device) val_ops = model(data_val) val_loss = cca_loss(val_ops, o_dim, use_all_singular_values) correlations[epoch, 1] = -val_loss data_val = data_val.cpu() torch.cuda.empty_cache() print(' Validation CORRELATION : {:0.4f}'.format(-val_loss)) data_te = data_te.to(device) test_ops = model(data_te) test_loss = cca_loss(test_ops, o_dim, use_all_singular_values) correlations[epoch, 2] = -test_loss data_te = data_te.cpu() torch.cuda.empty_cache() print(' Test CORRELATION : {:0.4f}'.format(-test_loss)) print(" val. loss is : {:0.4f} & the min. loss is : {:0.4f}".format(val_loss, min_loss)) print(" AND since, val_loss < min_loss is {}".format(val_loss < min_loss)) if val_loss < min_loss2: min_loss2 = val_loss model_file_name = path_name + '/best_model.pth' if best_only == True: if val_loss < min_loss or epoch == 0: torch.save({ 'epoch' : epoch, 'model_state_dict' : model.state_dict(), 'optimizer_state_dict': model_optimizer.state_dict(), 'loss': loss}, model_file_name) print(' Saved the model at epoch : {}\n'.format(epoch)) min_loss = val_loss else: if epoch != 0: checkpoint = torch.load(model_file_name) model.load_state_dict(checkpoint['model_state_dict']) model_optimizer.load_state_dict(checkpoint['optimizer_state_dict']) best_epoch = checkpoint['epoch'] # loss = checkpoint['loss'] print(' Loaded the model from epoch : {}.\n'.format(best_epoch)) model.train() model.eval() data2 = [data_tr, data_val, data_te] with torch.no_grad(): new_data = [] for k in range(3): temp = data2[k].to(device) pred_out = model(temp) new_data.append([pred_out[0].cpu().numpy(), pred_out[1].cpu().numpy()]) # x1 = new_data[2][0] # x2 = new_data[2][1] # result = np.squeeze(my_corr(x1, x2, o_dim)) # print(result) return new_data, correlations, model # DMCCA MODEL WITH N RESPS AND 1 STIM # IF GIVEN 10 SEEDS, ALL THE MODELS GET ONE FORWARD PASS AND SEED WITH BEST VALIDATION IS SELECTED # IF ONLY ONE SEED, THE WEIGHTS ARE INITIALIZED ACCORDINGLY # THE MODEL GETS TRAINED AND # MODEL : dmcca_model_n_resp_1_stim # LOSS : dmcca_model_loss # RETURNS : NEW DATA, TRAINING LOSSES, AND THE TRAINED MODEL def dmcca_model(all_data, o_dim, learning_rate=1e-3, use_all_singular_values=False, epoch_num=12, batch_size=2048, reg_par=1e-4, dropout=0.05, best_only=True, lambda_=0.1, path_name="", mid_shape=60, seeds=np.ceil(np.random.rand(10)*100)): """ ARGUMENTS: all_data : AN (N) ELEMENT LIST OF DATA WITH EACH ELEMENT AS: [DATA_i_TRAINING, DATA_i_VALIDATION, DATA_i_TEST] ASSUMPTION : THE FIRST (N-1) ELEMENTS ARE THE (N-1) EEG RESPONSES FOR A COMMON STIMULUS. THE LAST 1 ELEMENT IS THE COMMON AUDITORY STIMULUS. learning_rate : LEARNING RATE OF THE MODEL (DEFAULT: 1e-3) use_all_singular_values : WHETHER THE MODEL SHOULD USE ALL THE SINGULAR VALUES IN THE CCA LOSS (DEFAULT: False) epoch_num : NUMBER OF EPOCHS OF TRAINING (DEFAULT: 12) batch_size : MINIBATCH SIZES FOR TRAINING THE MODEL (DEFAULT: 2048) reg_par : REGULARIZATION PARAMETER FOR WEIGHT DECAY (DEFAULT: 1e-4) dropout : DROPOUTS PERCENTAGE IN THE MODEL (DEFAULT: 0.05) best_only : SAVE THE MODEL ONLY WITH THE BEST VALIDATION LOSS (DEFAULT: True) lambda_ : MSE REGULARIZATION PARAMETER path_name : WHERE THE MODEL IS TO BE SAVED. (DEFAULT: "") seeds : SEED FOR THE DEEP MODEL. (DEFAULT: 10 RANDOM SEEDS) RETURNS: new_data : NEW REPRESENTATIONS AFTER PERFORMING DEEP CCA training_losses : THE TRAINING, VALIDATION AND TEST SET LOSSES WHILE TRAINING THE MODEL - TO TRACK THE MODEL AS TRAINING PROGRESSED. model : THE TRAINED MODEL. """ print('Started multiway DCCA.') # data = [resp1, resp2, ..., respn, stim] N = len(all_data) torch.cuda.empty_cache() data_tr = np.concatenate([i[0] for i in all_data], 1) data_val = np.concatenate([i[1] for i in all_data], 1) data_te = np.concatenate([i[2] for i in all_data], 1) data = [data_tr, data_val, data_te] i_shape1 = all_data[0][0].shape[1] i_shape2 = all_data[-1][0].shape[1] print(i_shape1) print(i_shape2) # EACH ONE : T x (R1 + R2 + STIM) train_set = torch.from_numpy(data_tr).float() val_set = torch.from_numpy(data_val).float() te_set = torch.from_numpy(data_te).float() [data_tr, data_val, data_te] = [train_set, val_set, te_set] best_only = True act = "sigmoid" o_act = 'leaky_relu' if (isinstance(seeds, int)): seed = seeds elif not(isinstance(seeds, int)) and len(seeds) == 1: seed = seeds[0] else: torch.backends.cudnn.deterministic = True first_and_last = np.zeros((len(seeds),3)) to_append = np.zeros((len(seeds), 3, int(comb(N,2))+1)) models=[None]*len(seeds) print('seeds: ', seeds) for seed_num, seed in enumerate(seeds) : torch.manual_seed(seed) if torch.cuda.is_available() : torch.cuda.manual_seed_all(seed) model = dmcca_model_n_resp_1_stim(N-1, i_shape1, i_shape2, mid_shape, o_dim, dropout) model = model.to(device) model_optimizer = optim.Adam(model.parameters(), learning_rate, weight_decay=reg_par) print('MODEL : {} for seed : {}'.format(seed_num, seed)) model.eval() torch.cuda.empty_cache() tr_corr_loss = 0 count = 0 dataloader = DataLoader(data_tr, batch_size, shuffle=True) with torch.no_grad(): for trs in dataloader : trs = trs.to(device) outputs = model(trs) _, corr_loss, _,neg_corrs,_ = dmcca_model_loss(trs, outputs, i_shape1, o_dim, lambda_, use_all_singular_values) trs = trs.cpu() tr_corr_loss = tr_corr_loss + corr_loss count = count + 1 del trs tr_corr_loss = tr_corr_loss / (count) to_append[seed_num, 0, :] = np.concatenate([[-tr_corr_loss.detach().numpy()], -neg_corrs.detach().numpy()]) data_val = data_val.to(device) val_ops = model(data_val) _, val_corr_loss, _,neg_corrs,_ = dmcca_model_loss(data_val, val_ops, i_shape1, o_dim, lambda_, use_all_singular_values) data_val = data_val.cpu() torch.cuda.empty_cache() to_append[seed_num, 1, :] = np.concatenate([[-val_corr_loss.detach().numpy()], -neg_corrs.detach().numpy()]) data_te = data_te.to(device) test_ops = model(data_te) _, test_corr_loss, _,neg_corrs,_ = dmcca_model_loss(data_te, test_ops, i_shape1, o_dim, lambda_, use_all_singular_values) data_te = data_te.cpu() torch.cuda.empty_cache() to_append[seed_num, 2, :] = np.concatenate([[-test_corr_loss.detach().numpy()], -neg_corrs.detach().numpy()]) models[seed_num] = model first_and_last[seed_num] = [-tr_corr_loss, -val_corr_loss, -test_corr_loss] print('{:0.4f} {:0.4f} {:0.4f}'.format(-tr_corr_loss, -val_corr_loss, -test_corr_loss)) nums = 1 results = np.zeros(nums) idx = np.argsort(-first_and_last[:,1]) # print(first_and_last[idx,1:]) # print(idx) # print(np.array(seeds)[idx]) seed = seeds[idx[0]] print("seed: ", seed ) training_lossses = [] new_data = [] torch.manual_seed(seed) if torch.cuda.is_available() : torch.cuda.manual_seed_all(seed) model = dmcca_model_n_resp_1_stim(N-1, i_shape1, i_shape2, mid_shape, o_dim, dropout) model = model.to(device) model_optimizer = optim.Adam(model.parameters(), lr=learning_rate, weight_decay=reg_par) model, training_losses = train_the_dmcca_model(model, model_optimizer, train_set, val_set, te_set, N, epoch_num, batch_size, o_dim, i_shape1, lambda_, use_all_singular_values, path_name) model.eval() data = [train_set, val_set, te_set] with torch.no_grad(): new_data = [] for k in range(3): temp = data[k].to(device) pred_out = model(temp) del temp new_data.append(pred_out) return new_data, training_losses, model # TRAINS THE MODEL IN dmcca_model def train_the_dmcca_model(model, model_optimizer, data_tr, data_val, data_te, N, epoch_num, batch_size, o_dim, i_shape1, lambda_, use_all_singular_values, path_name, best_only=True): """ ARGUMENTS: THE DMCCA MODEL TO BE TRAINED, THE MODEL'S OPTIMIZER, THE DATA FOR TRAINING, VALIDATING AND TESTING THE MODEL; AND ALL OTHER HYPERPARAMETERS REQUIRED TO TRAIN THE MODEL. RETURNS: THE TRAINED MODEL AND THE LOSSES WHILE TRAINING THE MODEL. """ print("Started training.") best_epoch = 0 min_loss = 0.00 loss_epochs = np.zeros((epoch_num, 3)) corr_epochs = np.zeros((epoch_num, 3, int(comb(N,2)) + 1)) mses_epochs = np.zeros((epoch_num, 3, N+1)) model.to(device) for epoch in range(epoch_num): # loop over the dataset multiple times model.train() dataloader = DataLoader(data_tr, batch_size, shuffle=True) for trs in dataloader : model_optimizer.zero_grad() trs = trs.to(device) outputs = model(trs) loss, _, _, _, _ = dmcca_model_loss(trs, outputs, i_shape1, o_dim, lambda_, use_all_singular_values) loss.backward() model_optimizer.step() del trs model.eval() torch.cuda.empty_cache() tr_loss = 0 ; tr_corrs = np.zeros(int(comb(N, 2))+1) ; tr_mses = np.zeros(N+1) count = 0 dataloader = DataLoader(data_tr, batch_size, shuffle=True) with torch.no_grad(): for trs in dataloader : trs = trs.to(device) outputs = model(trs) loss, corr, mse, neg_corrs, mses = dmcca_model_loss(trs, outputs, i_shape1, o_dim, lambda_, use_all_singular_values) trs = trs.cpu() tr_loss = tr_loss + loss tr_corrs = tr_corrs + np.concatenate([[-corr], -neg_corrs.detach().numpy()]) tr_mses = tr_mses + np.concatenate([[mse], mses.detach().numpy()]) count = count + 1 del trs loss_epochs[epoch, 0] = tr_loss / (count) corr_epochs[epoch, 0, :] = tr_corrs / (count) mses_epochs[epoch, 0, :] = tr_mses / (count) torch.cuda.empty_cache() print('EPOCH : {}'.format(epoch)) print(' Training corr LOSS : {:0.4f}'.format(corr_epochs[epoch, 0, 0])) # print("{} - {} = {} {}".format(corr_epochs[epoch, 0, 0], mses_epochs[epoch, 0, 0], -loss_epochs[epoch,0], corr_epochs[epoch, 0, 1:])) print("{} - {} = {}".format(corr_epochs[epoch, 0, 0], mses_epochs[epoch, 0, 0], -loss_epochs[epoch,0])) data_val = data_val.to(device) val_ops = model(data_val) val_loss, corr, mse, neg_corrs, mses = dmcca_model_loss(data_val, val_ops, i_shape1, o_dim, lambda_, use_all_singular_values) loss_epochs[epoch, 1] = val_loss corr_epochs[epoch, 1, :] = np.concatenate([[-corr], -neg_corrs.detach().numpy()]) mses_epochs[epoch, 1, :] = np.concatenate([[mse], mses.detach().numpy()]) data_val = data_val.cpu() torch.cuda.empty_cache() print(' Validation corr LOSS : {:0.4f}'.format(-corr)) # print("{} - {} = {} {}".format(-corr, mse, -val_loss, -neg_corrs)) print("{} - {} = {}".format(-corr, mse, -val_loss)) data_te = data_te.to(device) print(data_te.shape) test_ops = model(data_te) test_loss, corr, mse, neg_corrs, mses = dmcca_model_loss(data_te, test_ops, i_shape1, o_dim, lambda_, use_all_singular_values) loss_epochs[epoch, 2] = test_loss corr_epochs[epoch, 2, :] = np.concatenate([[-corr], -neg_corrs.detach().numpy()]) mses_epochs[epoch, 2, :] = np.concatenate([[mse], mses.detach().numpy()]) data_te = data_te.cpu() torch.cuda.empty_cache() print(' Test corr LOSS : {:0.4f}'.format(-corr)) # print("{} - {} = {} {}".format(-corr, mse, -test_loss, -neg_corrs)) print("{} - {} = {}".format(-corr, mse, -test_loss)) print(" val. loss is : {:0.4f} & the min. loss is : {:0.4f}".format(val_loss, min_loss)) print(" AND since, val_loss < min_loss is {}".format(val_loss < min_loss)) model_file_name = path_name + 'best_model.pth' if best_only == True: if val_loss < min_loss or epoch == 0: torch.save({ 'epoch' : epoch, 'model_state_dict' : model.state_dict(), 'optimizer_state_dict': model_optimizer.state_dict(), 'loss': loss}, model_file_name) print(' Saved the model at epoch : {}\n'.format(epoch)) min_loss = val_loss else: if epoch != 0: checkpoint = torch.load(model_file_name) model.load_state_dict(checkpoint['model_state_dict']) model_optimizer.load_state_dict(checkpoint['optimizer_state_dict']) best_epoch = checkpoint['epoch'] # loss = checkpoint['loss'] print(' Loaded the model from epoch : {}.\n'.format(best_epoch)) model.train() return model, [loss_epochs, corr_epochs, mses_epochs] # DCCA MODELS WITH DIFFERENT ARCHITECTURES # 13_2, 13_3, 15_4, 13_5, 100_2, 100_3, 100_4, 100_5, 10000_2, 10000_3, 10000_4, def generic_dcca3(stim_data, resp_data, type, o_dim, learning_rate=1e-3, use_all_singular_values=False, epoch_num=12, batch_size=2048, reg_par=1e-4, dropout=0.05, path_name="", seeds=np.ceil(np.random.rand(10)*100)): """ CAN BE USED TO ACCESS DIFFERENT DCCA MODELS FROM THE deep_nets.py. THESE ARE THE MODELS EXPLORED AND REPORTED IN THE PAPER. OTHER THAN SETTING THE DCCA MODEL, EVERYTHING ELSE IS SAME AS THE "dcca_model". """ stimtr = stim_data[0] stimval = stim_data[1] stimte = stim_data[2] resptr = resp_data[0] respval = resp_data[1] respte = resp_data[2] stimtr, mean1, std1 = my_standardize(stimtr) resptr, mean2, std2 = my_standardize(resptr) stimval = (stimval - mean1) / std1 stimte = (stimte - mean1) / std1 respval = (respval - mean2) / std2 respte = (respte - mean2) / std2 resp_tr = torch.from_numpy(resptr ).float() resp_val = torch.from_numpy(respval).float() resp_te = torch.from_numpy(respte ).float() stim_tr = torch.from_numpy(stimtr ).float(); stim_val = torch.from_numpy(stimval).float(); stim_te = torch.from_numpy(stimte ).float(); data_tr = torch.cat([resp_tr, stim_tr ], 1) data_val = torch.cat([resp_val, stim_val], 1) data_te = torch.cat([resp_te, stim_te ], 1) i_shape1 = resp_tr.shape[1] i_shape2 = stim_tr.shape[1] best_only = True act = "sigmoid" o_act = 'leaky_relu' if (isinstance(seeds, int)): seed = seeds elif not(isinstance(seeds, int)) and len(seeds) == 1: seed = seeds[0] else: torch.backends.cudnn.deterministic = True first_and_last = np.zeros((len(seeds),3)) models = [None] * len(seeds) print('seeds: ', seeds) for seed_num, seed in enumerate(seeds) : torch.manual_seed(seed) if torch.cuda.is_available() : torch.cuda.manual_seed_all(seed) model = None if type == "13_2": model = model2_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "13_3": model = model3_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "15_4": model = model2_15(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "13_5": model = model5_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_2": model = model_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_3": model = model_3_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_4": model = model_4_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_5": model = model_5_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "10000_2": model = model_10000s(i_shape1, i_shape2, act, o_act, o_dim, dropout) model = model.to(device) model_optimizer = optim.Adam(model.parameters(), lr=learning_rate, weight_decay=reg_par) print('MODEL : {}'.format(seed_num)) model.eval() torch.cuda.empty_cache() tr_loss = 0 ; count = 0 dataloader = DataLoader(data_tr, batch_size, shuffle=True) with torch.no_grad(): for trs in dataloader : trs = trs.to(device) outputs = model(trs) loss = cca_loss(outputs, o_dim, use_all_singular_values) tr_loss = tr_loss + loss count = count + 1 del trs tr_loss = tr_loss / count data_val = data_val.to(device) val_ops = model(data_val) val_loss = cca_loss(val_ops, o_dim, use_all_singular_values) data_val = data_val.cpu() torch.cuda.empty_cache() data_te = data_te.to(device) test_ops = model(data_te) test_loss = cca_loss(test_ops, o_dim, use_all_singular_values) data_te = data_te.cpu() torch.cuda.empty_cache() models[seed_num] = model first_and_last[seed_num] = [-tr_loss, -val_loss, -test_loss] print('{:0.4f} {:0.4f} {:0.4f}'.format(-tr_loss, -val_loss, -test_loss)) np.set_printoptions(precision=4) idx = np.argsort(-first_and_last[:,1]) print(first_and_last[idx,1:]) print(seeds[idx]) seed = seeds[idx[0]] print("seed: ", seed ) torch.manual_seed(seed) if torch.cuda.is_available() : torch.cuda.manual_seed_all(seed) model = None if type == "13_2": model = model2_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "13_3": model = model3_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "15_4": model = model2_15(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "13_5": model = model5_13(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_2": model = model_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_3": model = model_3_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_4": model = model_4_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "100_5": model = model_5_100s(i_shape1, i_shape2, act, o_act, o_dim, dropout) if type == "10000_2": model = model_10000s(i_shape1, i_shape2, act, o_act, o_dim, dropout) model = model.to(device) model_optimizer = optim.Adam(model.parameters(), lr=learning_rate, weight_decay=reg_par) model_state_dict = [] min_loss = 0.00 ; min_loss2 = 0.00 correlations = np.zeros((epoch_num, 3)) for epoch in range(epoch_num): # loop over the dataset multiple times model.train() dataloader = DataLoader(data_tr, batch_size, shuffle=True) for trs in dataloader : model_optimizer.zero_grad() trs = trs.to(device) outputs = model(trs) loss = cca_loss(outputs, o_dim, use_all_singular_values) loss.backward() model_optimizer.step() del trs model.eval() torch.cuda.empty_cache() tr_loss = 0 count = 0 dataloader = DataLoader(data_tr, batch_size, shuffle=True) with torch.no_grad(): for trs in dataloader : trs = trs.to(device) outputs = model(trs) loss = cca_loss(outputs, o_dim, use_all_singular_values) loss = loss.item() tr_loss = tr_loss + loss count = count + 1 del trs correlations[epoch, 0] = -tr_loss / (count) torch.cuda.empty_cache() print('EPOCH : {}'.format(epoch)) print(' Training CORRELATION : {:0.4f}'.format(correlations[epoch, 0])) data_val = data_val.to(device) val_ops = model(data_val) val_loss = cca_loss(val_ops, o_dim, use_all_singular_values) correlations[epoch, 1] = -val_loss data_val = data_val.cpu() torch.cuda.empty_cache() print(' Validation CORRELATION : {:0.4f}'.format(-val_loss)) data_te = data_te.to(device) test_ops = model(data_te) test_loss = cca_loss(test_ops, o_dim, use_all_singular_values) correlations[epoch, 2] = -test_loss data_te = data_te.cpu() torch.cuda.empty_cache() print(' Test CORRELATION : {:0.4f}'.format(-test_loss)) print(" val. loss is : {:0.4f} & the min. loss is : {:0.4f}".format(val_loss, min_loss)) print(" AND since, val_loss < min_loss is {}".format(val_loss < min_loss)) if val_loss < min_loss2: min_loss2 = val_loss model_file_name = path_name + '/best_model.pth' if best_only == True: if val_loss < min_loss or epoch == 0: torch.save({ 'epoch' : epoch, 'model_state_dict' : model.state_dict(), 'optimizer_state_dict': model_optimizer.state_dict(), 'loss': loss}, model_file_name) print(' Saved the model at epoch : {}\n'.format(epoch)) min_loss = val_loss else: if epoch != 0: checkpoint = torch.load(model_file_name) model.load_state_dict(checkpoint['model_state_dict']) model_optimizer.load_state_dict(checkpoint['optimizer_state_dict']) best_epoch = checkpoint['epoch'] # loss = checkpoint['loss'] print(' Loaded the model from epoch : {}.\n'.format(best_epoch)) model.train() model.eval() data2 = [data_tr, data_val, data_te] with torch.no_grad(): new_data = [] for k in range(3): temp = data2[k].to(device) pred_out = model(temp) new_data.append([pred_out[0].cpu().numpy(), pred_out[1].cpu().numpy()]) # x1 = new_data[2][0] # x2 = new_data[2][1] # result = np.squeeze(my_corr(x1, x2, o_dim)) # print(result) return new_data, correlations, model

42.141304

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31,016

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null

0

7

defa5ba8c7b7d2953ce455770a6e1c357bd3069e

4,983

py

Python

tests/test_selection_criteria.py

jofrony/Neuromodulation

b5e1502701399c02cecff20b85d4ff8af7772ec9

[ "MIT" ]

2

2021-12-21T11:10:45.000Z

2021-12-21T11:11:04.000Z

tests/test_selection_criteria.py

jofrony/Neuromodcell

b5e1502701399c02cecff20b85d4ff8af7772ec9

[ "MIT" ]

1

2021-03-27T23:15:29.000Z

2021-03-27T23:20:23.000Z

tests/test_selection_criteria.py

jofrony/Neuromodcell

b5e1502701399c02cecff20b85d4ff8af7772ec9

[ "MIT" ]

1

2021-03-27T23:13:48.000Z

import neuromodcell.selection_criteria as sc import numpy as np def test_number_AP_decrease(): voltage_control = np.array([-100, -100, 100, -100, -100, -100]) voltage = np.array([-100, -100, -100, -100, -100, -100]) criteria = {"selection": {"mean": 1, "std": 1, "threshold": 1}, "parameters": {'dt': 0.1}} result = sc.number_AP_decrease(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0 def test_number_AP_increase(): voltage_control = np.array([-100, -100, -100, -100, -100, -100]) voltage = np.array([-100, -100, 100, -100, -100, -100]) criteria = {"selection": {"mean": 1, "std": 1, "threshold": 1}, "parameters": {'dt': 0.1}} result = sc.number_AP_increase(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0 def test_frequency_change(): voltage_control = np.array([-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100]) voltage = np.array([-100, 100, -100, 100, -100, 100, -100, 100, -100, 100, -100]) criteria = {"selection": {"mean": 5, "std": 1, "threshold": 1}, "parameters": {"tstart": 0, "tstop": 1000, 'dt': 100}} result = sc.frequency_change(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0 def test_frequency_increase(): voltage_control = np.array([-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100]) voltage = np.array([-100, 100, -100, 100, -100, 100, -100, 100, -100, 100, -100]) criteria = {"selection": {"mean": 5, "std": 1, "threshold": 1}, "parameters": {"tstart": 0, "tstop": 1000, 'dt': 100}} result = sc.frequency_change_increase(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0 def test_frequency_decrease(): voltage_control = np.array([-100, 100, -100, 100, -100, 100, -100, 100, -100, 100, -100]) voltage = np.array([-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100]) criteria = {"selection": {"mean": 5, "std": 1, "threshold": 1}, "parameters": {"tstart": 0, "tstop": 1000, 'dt': 100}} result = sc.frequency_change_decrease(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0 def test_cv_change(): voltage_control = np.array([-100, 100, -100, 100, -100, 100, -100, 100, -100, 100, -100]) voltage = np.array([-100, -100, -100, 100, -100, -100, -100, 100, -100, 100, -100]) criteria = {"selection": {"mean": 0.333, "std": 1, "threshold": 1}, "parameters": {'dt': 100}} result = sc.cv_change(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True def test_membrane_amplitude_increase(): voltage_control = np.array([-100, -100, -100, -100, -90, -90, -90, -90, -100, -100, -100, -100]) voltage = np.array([-100, -100, -100, -100, -80, -80, -80, -80, -100, -100, -100, -100]) criteria = {"selection": {"mean": 10, "std": 1, "threshold": 1}, "parameters": {'start_base': 0, 'stop_base': 0.2, 'start_measure': 0.4, 'stop_measure': 0.8, 'dt': 0.1}} result = sc.membrane_amplitude_increase(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0 def test_membrane_amplitude_increase_percentage(): voltage_control = np.array([-100, -100, -100, -100, -90, -90, -90, -90, -100, -100, -100, -100]) voltage = np.array([-100, -100, -100, -100, -80, -80, -80, -80, -100, -100, -100, -100]) criteria = {"selection": {"mean": 200, "std": 1, "threshold": 1}, "parameters": {'start_base': 0, 'stop_base': 0.2, 'start_measure': 0.4, 'stop_measure': 0.8, 'dt': 0.1}} result = sc.membrane_amplitude_increase_percentage(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0 def test_membrane_amplitude_decrease_percentage(): voltage_control = np.array([-100, -100, -100, -100, -80, -80, -80, -80, -100, -100, -100, -100]) voltage = np.array([-100, -100, -100, -100, -90, -90, -90, -90, -100, -100, -100, -100]) criteria = {"selection": {"mean": 50, "std": 1, "threshold": 1}, "parameters": {'start_base': 0, 'stop_base': 0.2, 'start_measure': 0.4, 'stop_measure': 0.8, 'dt': 0.1}} result = sc.membrane_amplitude_decrease_percentage(criteria, [voltage_control, voltage]) boolean = result['boolean'] zscore = result['zscore'] assert boolean == True assert zscore == 0

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0.601244

648

4,983

4.509259

0.08179

0.279261

0.344969

0.361396

0.959274

0.948323

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0.932238

0.917864

0

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0.198876

4,983

142

121

35.091549

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0.636364

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0.125

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null

1

0

null

0

9

a0e8ac09bbc8bf9740d2eeb7260d972e1f3973bb

99

py

Python

tmp/test_c.py

wiki918/python_pytest_demo

32180f726cabbd7685dda04e72aa111b00677930

[ "BSD-3-Clause" ]

null

tmp/test_c.py

wiki918/python_pytest_demo

32180f726cabbd7685dda04e72aa111b00677930

[ "BSD-3-Clause" ]

null

tmp/test_c.py

wiki918/python_pytest_demo

32180f726cabbd7685dda04e72aa111b00677930

[ "BSD-3-Clause" ]

null

def test_c_1(): assert True def test_c_2(): assert True def test_c_3(): assert True

9.9

15

0.636364

18

99

3.166667

0.444444

0.368421

0.421053

0.596491

0.631579

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null

0

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1

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8

a0f26b7bc6eb071bde286a7a88407f38a19ed08c

659

py

Python

flatdata-generator/tests/generators/py_expectations/structs/namespaces.py

gferon/flatdata

8839fb36be105e496fea8acc3fc907ae878dd063

[ "Apache-2.0" ]

null

flatdata-generator/tests/generators/py_expectations/structs/namespaces.py

gferon/flatdata

8839fb36be105e496fea8acc3fc907ae878dd063

[ "Apache-2.0" ]

null

flatdata-generator/tests/generators/py_expectations/structs/namespaces.py

gferon/flatdata

8839fb36be105e496fea8acc3fc907ae878dd063

[ "Apache-2.0" ]

1

2021-07-16T07:51:16.000Z

class n_Foo(flatdata.structure.Structure): """""" _SCHEMA = """namespace n { struct Foo { f : u32 : 32; } } """ _SIZE_IN_BITS = 32 _SIZE_IN_BYTES = 4 _FIELDS = { "f": flatdata.structure.FieldSignature(offset=0, width=32, is_signed=False, dtype="u4"), } _FIELD_KEYS = { "f", } class m_Foo(flatdata.structure.Structure): """""" _SCHEMA = """namespace m { struct Foo { f : u32 : 32; } } """ _SIZE_IN_BITS = 32 _SIZE_IN_BYTES = 4 _FIELDS = { "f": flatdata.structure.FieldSignature(offset=0, width=32, is_signed=False, dtype="u4"), } _FIELD_KEYS = { "f", }

17.342105

96

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78

659

4.410256

0.371795

0.197674

0.093023

0.168605

0.959302

0.703488

0

0.046414

0.280728

659

37

97

17.810811

0.679325

0

0.5625

0

0.166924

0

1

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false

0

0.375

0

null

0

1

0

null

0

7

9d0c51224de13c525b0522e8364009d1ee6fa542

189,319

py

Python

QuantLib-SWIG/Python/test/assetswap.py

txu2014/quantlib

95c7d94906c30d0c3c4e0758a2ebfe2a62b075ec

[ "BSD-3-Clause" ]

1

2021-08-17T14:59:58.000Z

QuantLib-SWIG/Python/test/assetswap.py

txu2014/quantlib

95c7d94906c30d0c3c4e0758a2ebfe2a62b075ec

[ "BSD-3-Clause" ]

1

2019-02-20T05:37:59.000Z

QuantLib-SWIG/Python/test/assetswap.py

txu2014/quantlib

95c7d94906c30d0c3c4e0758a2ebfe2a62b075ec

[ "BSD-3-Clause" ]

1

2020-01-14T11:55:16.000Z

""" Copyright (C) 2011 Lluis Pujol Bajador This file is part of QuantLib, a free-software/open-source library for financial quantitative analysts and developers - http://quantlib.org/ QuantLib is free software: you can redistribute it and/or modify it under the terms of the QuantLib license. You should have received a copy of the license along with this program; if not, please email <quantlib-dev@lists.sf.net>. The license is also available online at <http://quantlib.org/license.shtml>. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the license for more details. """ from QuantLib import * import unittest class AssetSwapTest(unittest.TestCase): def setUp(self): # initial setup self.termStructure = RelinkableYieldTermStructureHandle() self.swapSettlementDays = 2 self.faceAmount = 100.0 self.fixedConvention = Unadjusted self.compounding = Continuous self.fixedFrequency = Annual self.floatingFrequency = Semiannual self.iborIndex = Euribor(Period(self.floatingFrequency), self.termStructure) self.calendar = self.iborIndex.fixingCalendar() self.swapIndex= SwapIndex("EuriborSwapIsdaFixA", Period(10,Years), self.swapSettlementDays, self.iborIndex.currency(), self.calendar, Period(self.fixedFrequency), self.fixedConvention, self.iborIndex.dayCounter(), self.iborIndex) self.spread = 0.0 self.nonnullspread = 0.003 self.today = Date(24,April,2007) Settings.instance().evaluationDate = self.today self.termStructure.linkTo(FlatForward(self.today, 0.05, Actual365Fixed())) self.yieldCurve = FlatForward(self.today, 0.05, Actual365Fixed()) self.pricer = BlackIborCouponPricer() self.swaptionVolatilityStructure = SwaptionVolatilityStructureHandle(ConstantSwaptionVolatility(self.today, NullCalendar(),Following, 0.2, Actual365Fixed())) self.meanReversionQuote = QuoteHandle(SimpleQuote(0.01)) self.cmspricer = AnalyticHaganPricer(self.swaptionVolatilityStructure, GFunctionFactory.Standard, self.meanReversionQuote) def testConsistency(self) : """Testing consistency between fair price and fair spread...""" bondCalendar = TARGET() settlementDays = 3 ## Fixed Underlying bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day bondSchedule = Schedule(Date(4,January,2005), Date(4,January,2037), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) bond = FixedRateBond(settlementDays, self.faceAmount, bondSchedule,[0.04], ActualActual(ActualActual.ISDA), Following, 100.0, Date(4,January,2005)) payFixedRate = True bondPrice = 95.0 isPar = True parAssetSwap = AssetSwap(payFixedRate, bond, bondPrice, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), isPar) swapEngine = DiscountingSwapEngine(self.termStructure, True, bond.settlementDate(), Settings.instance().evaluationDate) parAssetSwap.setPricingEngine(swapEngine) fairCleanPrice = parAssetSwap.fairCleanPrice() fairSpread = parAssetSwap.fairSpread() tolerance = 1.0e-13 assetSwap2 = AssetSwap(payFixedRate, bond, fairCleanPrice, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap2.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap2.NPV())>tolerance, "\npar asset swap fair clean price doesn't zero the NPV: " + "\n clean price: " + str(bondPrice) + "\n fair clean price: " + str(fairCleanPrice) + "\n NPV: " + str(assetSwap2.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap2.fairCleanPrice() - fairCleanPrice)>tolerance, "\npar asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(fairCleanPrice) + "\n fair clean price: " + str(assetSwap2.fairCleanPrice()) + "\n NPV: " + str(assetSwap2.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap2.fairSpread() - self.spread)>tolerance, "\npar asset swap fair spread doesn't equal input spread " + "at zero NPV: " + "\n input spread: " + str(self.spread ) + "\n fair spread: " + str(assetSwap2.fairSpread() ) + "\n NPV: " + str(assetSwap2.NPV() ) + "\n tolerance: " + str(tolerance)) assetSwap3 = AssetSwap(payFixedRate, bond, bondPrice, self.iborIndex, fairSpread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap3.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap3.NPV())>tolerance, "\npar asset swap fair spread doesn't zero the NPV: " + "\n spread: " + str(self.spread) + "\n fair spread: " + str(fairSpread) + "\n NPV: " + str(assetSwap3.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap3.fairCleanPrice() - bondPrice)>tolerance, "\npar asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(bondPrice) + "\n fair clean price: " + str(assetSwap3.fairCleanPrice()) + "\n NPV: " + str(assetSwap3.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap3.fairSpread() - fairSpread)>tolerance, "\npar asset swap fair spread doesn't equal input spread at" + " zero NPV: " + "\n input spread: " + str(fairSpread) + "\n fair spread: " + str(assetSwap3.fairSpread()) + "\n NPV: " + str(assetSwap3.NPV()) + "\n tolerance: " + str(tolerance)) ## let's change the npv date swapEngine = DiscountingSwapEngine(self.termStructure, True, bond.settlementDate(), bond.settlementDate()) parAssetSwap.setPricingEngine(swapEngine) ## fair clean price and fair spread should not change self.assertFalse(abs(parAssetSwap.fairCleanPrice() - fairCleanPrice)>tolerance, "\npar asset swap fair clean price changed with NpvDate:" + "\n expected clean price: " + str(fairCleanPrice) + "\n fair clean price: " + str(parAssetSwap.fairCleanPrice()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(parAssetSwap.fairSpread() - fairSpread)>tolerance, "\npar asset swap fair spread changed with NpvDate:" + "\n expected spread: " + str(fairSpread) + "\n fair spread: " + str(parAssetSwap.fairSpread()) + "\n tolerance: " + str(tolerance)) assetSwap2 = AssetSwap(payFixedRate, bond, fairCleanPrice, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap2.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap2.NPV())>tolerance, "\npar asset swap fair clean price doesn't zero the NPV: " + "\n clean price: " + str(bondPrice) + "\n fair clean price: " + str(fairCleanPrice) + "\n NPV: " + str(assetSwap2.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap2.fairCleanPrice() - fairCleanPrice)>tolerance, "\npar asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(fairCleanPrice) + "\n fair clean price: " + str(assetSwap2.fairCleanPrice()) + "\n NPV: " + str(assetSwap2.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap2.fairSpread() - self.spread)>tolerance, "\npar asset swap fair spread doesn't equal input spread at zero NPV: " + "\n input spread: " + str(self.spread) + "\n fair spread: " + str(assetSwap2.fairSpread()) + "\n NPV: " + str(assetSwap2.NPV()) + "\n tolerance: " + str(tolerance)) assetSwap3 = AssetSwap(payFixedRate, bond, bondPrice, self.iborIndex, fairSpread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap3.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap3.NPV())>tolerance, "\npar asset swap fair spread doesn't zero the NPV: " + "\n spread: " + str(self.spread) + "\n fair spread: " + str(fairSpread) + "\n NPV: " + str(assetSwap3.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap3.fairCleanPrice() - bondPrice)>tolerance, "\npar asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(bondPrice) + "\n fair clean price: " + str(assetSwap3.fairCleanPrice()) + "\n NPV: " + str(assetSwap3.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap3.fairSpread() - fairSpread)>tolerance, "\npar asset swap fair spread doesn't equal input spread at zero NPV: " + "\n input spread: " + str(fairSpread) + "\n fair spread: " + str(assetSwap3.fairSpread()) + "\n NPV: " + str(assetSwap3.NPV()) + "\n tolerance: " + str(tolerance)) ## now market asset swap isPar = False mktAssetSwap = AssetSwap (payFixedRate, bond, bondPrice, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), isPar) swapEngine = DiscountingSwapEngine(self.termStructure, True, bond.settlementDate(), Settings.instance().evaluationDate) mktAssetSwap.setPricingEngine(swapEngine) fairCleanPrice = mktAssetSwap.fairCleanPrice() fairSpread = mktAssetSwap.fairSpread() assetSwap4 = AssetSwap (payFixedRate, bond, fairCleanPrice, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap4.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap4.NPV())>tolerance, "\nmarket asset swap fair clean price doesn't zero the NPV: " + "\n clean price: " + str(bondPrice) + "\n fair clean price: " + str(fairCleanPrice) + "\n NPV: " + str(assetSwap4.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap4.fairCleanPrice() - fairCleanPrice)>tolerance, "\nmarket asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(fairCleanPrice) + "\n fair clean price: " + str(assetSwap4.fairCleanPrice()) + "\n NPV: " + str(assetSwap4.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap4.fairSpread() - self.spread)>tolerance, "\nmarket asset swap fair spread doesn't equal input spread" + " at zero NPV: " + "\n input spread: " + str(self.spread) + "\n fair spread: " + str(assetSwap4.fairSpread()) + "\n NPV: " + str(assetSwap4.NPV()) + "\n tolerance: " + str(tolerance)) assetSwap5 = AssetSwap(payFixedRate, bond, bondPrice, self.iborIndex, fairSpread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap5.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap5.NPV())>tolerance, "\nmarket asset swap fair spread doesn't zero the NPV: " + "\n spread: " + str(self.spread) + "\n fair spread: " + str(fairSpread) + "\n NPV: " + str(assetSwap5.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap5.fairCleanPrice() - bondPrice)>tolerance, "\nmarket asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(bondPrice) + "\n fair clean price: " + str(assetSwap5.fairCleanPrice()) + "\n NPV: " + str(assetSwap5.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap5.fairSpread() - fairSpread)>tolerance, "\nmarket asset swap fair spread doesn't equal input spread at zero NPV: " + "\n input spread: " + str(fairSpread) + "\n fair spread: " + str(assetSwap5.fairSpread()) + "\n NPV: " + str(assetSwap5.NPV()) + "\n tolerance: " + str(tolerance)) ## let's change the npv date swapEngine = DiscountingSwapEngine(self.termStructure, True, bond.settlementDate(), bond.settlementDate()) mktAssetSwap.setPricingEngine(swapEngine) ## fair clean price and fair spread should not change self.assertFalse(abs(mktAssetSwap.fairCleanPrice() - fairCleanPrice)>tolerance, "\nmarket asset swap fair clean price changed with NpvDate:" + "\n expected clean price: " + str(fairCleanPrice) + "\n fair clean price: " + str(mktAssetSwap.fairCleanPrice()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(mktAssetSwap.fairSpread() - fairSpread)>tolerance, "\nmarket asset swap fair spread changed with NpvDate:" + "\n expected spread: " + str(fairSpread) + "\n fair spread: " + str(mktAssetSwap.fairSpread()) + "\n tolerance: " + str(tolerance)) assetSwap4 = AssetSwap(payFixedRate, bond, fairCleanPrice, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap4.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap4.NPV())>tolerance, "\nmarket asset swap fair clean price doesn't zero the NPV: " + "\n clean price: " + str(bondPrice) + "\n fair clean price: " + str(fairCleanPrice) + "\n NPV: " + str(assetSwap4.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap4.fairCleanPrice() - fairCleanPrice)>tolerance, "\nmarket asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(fairCleanPrice) + "\n fair clean price: " + str(assetSwap4.fairCleanPrice()) + "\n NPV: " + str(assetSwap4.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap4.fairSpread() - self.spread)>tolerance, "\nmarket asset swap fair spread doesn't equal input spread at zero NPV: " + "\n input spread: " + str(self.spread) + "\n fair spread: " + str(assetSwap4.fairSpread()) + "\n NPV: " + str(assetSwap4.NPV()) + "\n tolerance: " + str(tolerance)) assetSwap5 = AssetSwap(payFixedRate, bond, bondPrice, self.iborIndex, fairSpread, Schedule(), self.iborIndex.dayCounter(), isPar) assetSwap5.setPricingEngine(swapEngine) self.assertFalse(abs(assetSwap5.NPV())>tolerance, "\nmarket asset swap fair spread doesn't zero the NPV: " + "\n spread: " + str(self.spread) + "\n fair spread: " + str(fairSpread) + "\n NPV: " + str(assetSwap5.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap5.fairCleanPrice() - bondPrice)>tolerance, "\nmarket asset swap fair clean price doesn't equal input " + "clean price at zero NPV: " + "\n input clean price: " + str(bondPrice) + "\n fair clean price: " + str(assetSwap5.fairCleanPrice()) + "\n NPV: " + str(assetSwap5.NPV()) + "\n tolerance: " + str(tolerance)) self.assertFalse(abs(assetSwap5.fairSpread() - fairSpread)>tolerance, "\nmarket asset swap fair spread doesn't equal input spread at zero NPV: " + "\n input spread: " + str(fairSpread) + "\n fair spread: " + str(assetSwap5.fairSpread()) + "\n NPV: " + str(assetSwap5.NPV()) + "\n tolerance: " + str(tolerance)) def testImpliedValue(self): """Testing implied bond value against asset-swap fair price with null spread...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 payFixedRate = True parAssetSwap = True inArrears = False ## Fixed Underlying bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondSchedule1 = Schedule(Date(4,January,2005), Date(4,January,2037), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBond1 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule1, [0.04], ActualActual(ActualActual.ISDA), Following, 100.0, Date(4,January,2005)) bondEngine = DiscountingBondEngine(self.termStructure) swapEngine = DiscountingSwapEngine(self.termStructure, False) fixedBond1.setPricingEngine(bondEngine) fixedBondPrice1 = fixedBond1.cleanPrice() fixedBondAssetSwap1 = AssetSwap(payFixedRate, fixedBond1, fixedBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondAssetSwap1.setPricingEngine(swapEngine) fixedBondAssetSwapPrice1 = fixedBondAssetSwap1.fairCleanPrice() tolerance = 1.0e-13 error1 = abs(fixedBondAssetSwapPrice1-fixedBondPrice1) self.assertFalse(error1>tolerance, "wrong zero spread asset swap price for fixed bond:" + "\n bond's clean price: " + str(fixedBondPrice1) + "\n asset swap fair price: " + str(fixedBondAssetSwapPrice1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) ## Fixed Underlying bond (Isin: IT0006527060 IBRD 5 02/05/19) ## maturity occurs on a business day fixedBondSchedule2 = Schedule(Date(5,February,2005), Date(5,February,2019), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBond2 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule2, [0.05], Thirty360(Thirty360.BondBasis), Following, 100.0, Date(5,February,2005)) fixedBond2.setPricingEngine(bondEngine) fixedBondPrice2 = fixedBond2.cleanPrice() fixedBondAssetSwap2 = AssetSwap(payFixedRate, fixedBond2, fixedBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondAssetSwap2.setPricingEngine(swapEngine) fixedBondAssetSwapPrice2 = fixedBondAssetSwap2.fairCleanPrice() error2 = abs(fixedBondAssetSwapPrice2-fixedBondPrice2) self.assertFalse(error2>tolerance, "wrong zero spread asset swap price for fixed bond:" + "\n bond's clean price: " + str(fixedBondPrice2) + "\n asset swap fair price: " + str(fixedBondAssetSwapPrice2) + "\n error: " + str(error2) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: IT0003543847 ISPIM 0 09/29/13) ## maturity doesn't occur on a business day floatingBondSchedule1 = Schedule(Date(29,September,2003), Date(29,September,2013), Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBond1 =FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule1, self.iborIndex, Actual360(), Following, fixingDays, [1], [0.0056], [], [], inArrears, 100.0, Date(29,September,2003)) floatingBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) floatingBondPrice1 = floatingBond1.cleanPrice() floatingBondAssetSwap1 = AssetSwap(payFixedRate, floatingBond1, floatingBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondAssetSwap1.setPricingEngine(swapEngine) floatingBondAssetSwapPrice1 = floatingBondAssetSwap1.fairCleanPrice() error3 = abs(floatingBondAssetSwapPrice1-floatingBondPrice1) self.assertFalse(error3>tolerance, "wrong zero spread asset swap price for floater:" + "\n bond's clean price: " + str(floatingBondPrice1) + "\n asset swap fair price: " + str(floatingBondAssetSwapPrice1) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: XS0090566539 COE 0 09/24/18) ## maturity occurs on a business day floatingBondSchedule2 = Schedule(Date(24,September,2004), Date(24,September,2018), Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBond2 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule2, self.iborIndex, Actual360(), ModifiedFollowing, fixingDays, [1], [0.0025], [], [], inArrears, 100.0, Date(24,September,2004)) floatingBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) currentCoupon=0.04013+0.0025 floatingCurrentCoupon= floatingBond2.nextCouponRate() error4= abs(floatingCurrentCoupon-currentCoupon) self.assertFalse(error4>tolerance, "wrong current coupon is returned for floater bond:" + "\n bond's calculated current coupon: " + str(currentCoupon) + "\n current coupon asked to the bond: " + str(floatingCurrentCoupon) + "\n error: " + str(error4) + "\n tolerance: " + str(tolerance)) floatingBondPrice2 = floatingBond2.cleanPrice() floatingBondAssetSwap2 = AssetSwap(payFixedRate, floatingBond2, floatingBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondAssetSwap2.setPricingEngine(swapEngine) floatingBondAssetSwapPrice2 = floatingBondAssetSwap2.fairCleanPrice() error5 = abs(floatingBondAssetSwapPrice2-floatingBondPrice2) self.assertFalse(error5>tolerance, "wrong zero spread asset swap price for floater:" + "\n bond's clean price: " + str(floatingBondPrice2) + "\n asset swap fair price: " + str(floatingBondAssetSwapPrice2) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0228052402 CRDIT 0 8/22/20) ## maturity doesn't occur on a business day cmsBondSchedule1 = Schedule(Date(22,August,2005), Date(22,August,2020), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBond1 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule1, self.swapIndex, Thirty360(), Following, fixingDays, [1.0], [0.0], [0.055], [0.025], inArrears, 100.0, Date(22,August,2005)) cmsBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondPrice1 = cmsBond1.cleanPrice() cmsBondAssetSwap1 = AssetSwap(payFixedRate, cmsBond1, cmsBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondAssetSwap1.setPricingEngine(swapEngine) cmsBondAssetSwapPrice1 = cmsBondAssetSwap1.fairCleanPrice() error6 = abs(cmsBondAssetSwapPrice1-cmsBondPrice1) self.assertFalse(error6>tolerance, "wrong zero spread asset swap price for cms bond:" + "\n bond's clean price: " + str(cmsBondPrice1) + "\n asset swap fair price: " + str(cmsBondAssetSwapPrice1) + "\n error: " + str(error6) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0218766664 ISPIM 0 5/6/15) ## maturity occurs on a business day cmsBondSchedule2 = Schedule(Date(6,May,2005), Date(6,May,2015), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBond2 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule2, self.swapIndex, Thirty360(), Following, fixingDays, [0.84], [0.0], [], [], inArrears, 100.0, Date(6,May,2005)) cmsBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondPrice2 = cmsBond2.cleanPrice() cmsBondAssetSwap2 = AssetSwap(payFixedRate, cmsBond2, cmsBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondAssetSwap2.setPricingEngine(swapEngine) cmsBondAssetSwapPrice2 = cmsBondAssetSwap2.fairCleanPrice() error7 = abs(cmsBondAssetSwapPrice2-cmsBondPrice2) self.assertFalse(error7>tolerance, "wrong zero spread asset swap price for cms bond:" + "\n bond's clean price: " + str(cmsBondPrice2) + "\n asset swap fair price: " + str(cmsBondAssetSwapPrice2) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBond1 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(20,December,2015), Following, 100.0, Date(19,December,1985)) zeroCpnBond1.setPricingEngine(bondEngine) zeroCpnBondPrice1 = zeroCpnBond1.cleanPrice() zeroCpnAssetSwap1 = AssetSwap(payFixedRate, zeroCpnBond1, zeroCpnBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnAssetSwap1.setPricingEngine(swapEngine) zeroCpnBondAssetSwapPrice1 = zeroCpnAssetSwap1.fairCleanPrice() error8 = abs(cmsBondAssetSwapPrice1-cmsBondPrice1) self.assertFalse(error8>tolerance, "wrong zero spread asset swap price for zero cpn bond:" + "\n bond's clean price: " + str(zeroCpnBondPrice1) + "\n asset swap fair price: " + str(zeroCpnBondAssetSwapPrice1) + "\n error: " + str(error8) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity occurs on a business day zeroCpnBond2 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(17,February,2028), Following, 100.0, Date(17,February,1998)) zeroCpnBond2.setPricingEngine(bondEngine) zeroCpnBondPrice2 = zeroCpnBond2.cleanPrice() zeroCpnAssetSwap2 = AssetSwap(payFixedRate, zeroCpnBond2, zeroCpnBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnAssetSwap2.setPricingEngine(swapEngine) zeroCpnBondAssetSwapPrice2 = zeroCpnAssetSwap2.fairCleanPrice() error9 = abs(cmsBondAssetSwapPrice2-cmsBondPrice2) self.assertFalse(error9>tolerance, "wrong zero spread asset swap price for zero cpn bond:" + "\n bond's clean price: " + str(zeroCpnBondPrice2) + "\n asset swap fair price: " + str(zeroCpnBondAssetSwapPrice2) + "\n error: " + str(error9) + "\n tolerance: " + str(tolerance)) def testMarketASWSpread(self) : """Testing relationship between market asset swap and par asset swap...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 payFixedRate = True parAssetSwap = True mktAssetSwap = False inArrears = False ## Fixed Underlying bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondSchedule1 = Schedule (Date(4,January,2005), Date(4,January,2037), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBond1 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule1, [0.04], ActualActual(ActualActual.ISDA), Following, 100.0, Date(4,January,2005)) bondEngine = DiscountingBondEngine(self.termStructure) swapEngine = DiscountingSwapEngine(self.termStructure,False) fixedBond1.setPricingEngine(bondEngine) fixedBondMktPrice1 = 89.22 ## market price observed on 7th June 2007 fixedBondMktFullPrice1=fixedBondMktPrice1+fixedBond1.accruedAmount() fixedBondParAssetSwap1 = AssetSwap(payFixedRate, fixedBond1, fixedBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondParAssetSwap1.setPricingEngine(swapEngine) fixedBondParAssetSwapSpread1 = fixedBondParAssetSwap1.fairSpread() fixedBondMktAssetSwap1 = AssetSwap(payFixedRate, fixedBond1, fixedBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) fixedBondMktAssetSwap1.setPricingEngine(swapEngine) fixedBondMktAssetSwapSpread1 = fixedBondMktAssetSwap1.fairSpread() tolerance = 1.0e-13 error1 = abs(fixedBondMktAssetSwapSpread1- 100*fixedBondParAssetSwapSpread1/fixedBondMktFullPrice1) self.assertFalse (error1>tolerance, "wrong asset swap spreads for fixed bond:" + "\n market ASW spread: " + str(fixedBondMktAssetSwapSpread1) + "\n par ASW spread: " + str(fixedBondParAssetSwapSpread1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) ## Fixed Underlying bond (Isin: IT0006527060 IBRD 5 02/05/19) ## maturity occurs on a business day fixedBondSchedule2 = Schedule(Date(5,February,2005), Date(5,February,2019), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBond2 =FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule2, [0.05], Thirty360(Thirty360.BondBasis), Following, 100.0, Date(5,February,2005)) fixedBond2.setPricingEngine(bondEngine) fixedBondMktPrice2 = 99.98 ## market price observed on 7th June 2007 fixedBondMktFullPrice2 = fixedBondMktPrice2+fixedBond2.accruedAmount() fixedBondParAssetSwap2 = AssetSwap (payFixedRate, fixedBond2, fixedBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondParAssetSwap2.setPricingEngine(swapEngine) fixedBondParAssetSwapSpread2 = fixedBondParAssetSwap2.fairSpread() fixedBondMktAssetSwap2 = AssetSwap(payFixedRate, fixedBond2, fixedBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) fixedBondMktAssetSwap2.setPricingEngine(swapEngine) fixedBondMktAssetSwapSpread2 = fixedBondMktAssetSwap2.fairSpread() error2 = abs(fixedBondMktAssetSwapSpread2- 100*fixedBondParAssetSwapSpread2/fixedBondMktFullPrice2) self.assertFalse(error2>tolerance, "wrong asset swap spreads for fixed bond:" + "\n market ASW spread: " + str(fixedBondMktAssetSwapSpread2) + "\n par ASW spread: " + str(fixedBondParAssetSwapSpread2) + "\n error: " + str(error2) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: IT0003543847 ISPIM 0 09/29/13) ## maturity doesn't occur on a business day floatingBondSchedule1 = Schedule(Date(29,September,2003), Date(29,September,2013), Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBond1 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule1, self.iborIndex, Actual360(), Following, fixingDays, [1], [0.0056], [],[], inArrears, 100.0, Date(29,September,2003)) floatingBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) ## market price observed on 7th June 2007 floatingBondMktPrice1 = 101.64 floatingBondMktFullPrice1 = floatingBondMktPrice1+floatingBond1.accruedAmount() floatingBondParAssetSwap1 = AssetSwap(payFixedRate, floatingBond1, floatingBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondParAssetSwap1.setPricingEngine(swapEngine) floatingBondParAssetSwapSpread1 = floatingBondParAssetSwap1.fairSpread() floatingBondMktAssetSwap1 = AssetSwap(payFixedRate, floatingBond1, floatingBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) floatingBondMktAssetSwap1.setPricingEngine(swapEngine) floatingBondMktAssetSwapSpread1 = floatingBondMktAssetSwap1.fairSpread() error3 = abs(floatingBondMktAssetSwapSpread1- 100*floatingBondParAssetSwapSpread1/floatingBondMktFullPrice1) self.assertFalse(error3>tolerance, "wrong asset swap spreads for floating bond:" + "\n market ASW spread: " + str(floatingBondMktAssetSwapSpread1) + "\n par ASW spread: " + str(floatingBondParAssetSwapSpread1) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: XS0090566539 COE 0 09/24/18) ## maturity occurs on a business day floatingBondSchedule2 = Schedule (Date(24,September,2004), Date(24,September,2018), Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBond2 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule2, self.iborIndex, Actual360(), ModifiedFollowing, fixingDays, [1], [0.0025], [], [], inArrears, 100.0, Date(24,September,2004)) floatingBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) ## market price observed on 7th June 2007 floatingBondMktPrice2 = 101.248 floatingBondMktFullPrice2 = floatingBondMktPrice2+floatingBond2.accruedAmount() floatingBondParAssetSwap2 = AssetSwap (payFixedRate, floatingBond2, floatingBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondParAssetSwap2.setPricingEngine(swapEngine) floatingBondParAssetSwapSpread2 = floatingBondParAssetSwap2.fairSpread() floatingBondMktAssetSwap2 = AssetSwap(payFixedRate, floatingBond2, floatingBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) floatingBondMktAssetSwap2.setPricingEngine(swapEngine) floatingBondMktAssetSwapSpread2 = floatingBondMktAssetSwap2.fairSpread() error4 = abs(floatingBondMktAssetSwapSpread2- 100*floatingBondParAssetSwapSpread2/floatingBondMktFullPrice2) self.assertFalse(error4>tolerance , "wrong asset swap spreads for floating bond:" + "\n market ASW spread: " + str(floatingBondMktAssetSwapSpread2) + "\n par ASW spread: " + str(floatingBondParAssetSwapSpread2) + "\n error: " + str(error4) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0228052402 CRDIT 0 8/22/20) ## maturity doesn't occur on a business day cmsBondSchedule1 = Schedule(Date(22,August,2005), Date(22,August,2020), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBond1 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule1, self.swapIndex, Thirty360(), Following, fixingDays, [1,1.0], [0.0], [0.055], [0.025], inArrears, 100.0, Date(22,August,2005)) cmsBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondMktPrice1 = 88.45 ## market price observed on 7th June 2007 cmsBondMktFullPrice1 = cmsBondMktPrice1+cmsBond1.accruedAmount() cmsBondParAssetSwap1 = AssetSwap(payFixedRate, cmsBond1, cmsBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondParAssetSwap1.setPricingEngine(swapEngine) cmsBondParAssetSwapSpread1 = cmsBondParAssetSwap1.fairSpread() cmsBondMktAssetSwap1 = AssetSwap(payFixedRate, cmsBond1, cmsBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) cmsBondMktAssetSwap1.setPricingEngine(swapEngine) cmsBondMktAssetSwapSpread1 = cmsBondMktAssetSwap1.fairSpread() error5 = abs(cmsBondMktAssetSwapSpread1- 100*cmsBondParAssetSwapSpread1/cmsBondMktFullPrice1) self.assertFalse(error5>tolerance, "wrong asset swap spreads for cms bond:" + "\n market ASW spread: " + str(cmsBondMktAssetSwapSpread1) + "\n par ASW spread: " + str(cmsBondParAssetSwapSpread1) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0218766664 ISPIM 0 5/6/15) ## maturity occurs on a business day cmsBondSchedule2 = Schedule(Date(6,May,2005), Date(6,May,2015), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBond2 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule2, self.swapIndex, Thirty360(), Following, fixingDays, [0.84], [0.0], [], [], inArrears, 100.0, Date(6,May,2005)) cmsBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondMktPrice2 = 94.08 ## market price observed on 7th June 2007 cmsBondMktFullPrice2 = cmsBondMktPrice2+cmsBond2.accruedAmount() cmsBondParAssetSwap2 = AssetSwap(payFixedRate, cmsBond2, cmsBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondParAssetSwap2.setPricingEngine(swapEngine) cmsBondParAssetSwapSpread2 = cmsBondParAssetSwap2.fairSpread() cmsBondMktAssetSwap2 = AssetSwap(payFixedRate, cmsBond2, cmsBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) cmsBondMktAssetSwap2.setPricingEngine(swapEngine) cmsBondMktAssetSwapSpread2 = cmsBondMktAssetSwap2.fairSpread() error6 = abs(cmsBondMktAssetSwapSpread2- 100*cmsBondParAssetSwapSpread2/cmsBondMktFullPrice2) self.assertFalse(error6>tolerance, "wrong asset swap spreads for cms bond:" + "\n market ASW spread: " + str(cmsBondMktAssetSwapSpread2) + "\n par ASW spread: " + str(cmsBondParAssetSwapSpread2) + "\n error: " + str(error6) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBond1 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(20,December,2015), Following, 100.0, Date(19,December,1985)) zeroCpnBond1.setPricingEngine(bondEngine) ## market price observed on 12th June 2007 zeroCpnBondMktPrice1 = 70.436 zeroCpnBondMktFullPrice1 = zeroCpnBondMktPrice1+zeroCpnBond1.accruedAmount() zeroCpnBondParAssetSwap1 = AssetSwap(payFixedRate,zeroCpnBond1, zeroCpnBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondParAssetSwap1.setPricingEngine(swapEngine) zeroCpnBondParAssetSwapSpread1 = zeroCpnBondParAssetSwap1.fairSpread() zeroCpnBondMktAssetSwap1 = AssetSwap(payFixedRate,zeroCpnBond1, zeroCpnBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) zeroCpnBondMktAssetSwap1.setPricingEngine(swapEngine) zeroCpnBondMktAssetSwapSpread1 = zeroCpnBondMktAssetSwap1.fairSpread() error7 = abs(zeroCpnBondMktAssetSwapSpread1- 100*zeroCpnBondParAssetSwapSpread1/zeroCpnBondMktFullPrice1) self.assertFalse(error7>tolerance, "wrong asset swap spreads for zero cpn bond:" + "\n market ASW spread: " + str(zeroCpnBondMktAssetSwapSpread1) + "\n par ASW spread: " + str(zeroCpnBondParAssetSwapSpread1) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity occurs on a business day zeroCpnBond2 =ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(17,February,2028), Following, 100.0, Date(17,February,1998)) zeroCpnBond2.setPricingEngine(bondEngine) ## zeroCpnBondPrice2 = zeroCpnBond2.cleanPrice() ## market price observed on 12th June 2007 zeroCpnBondMktPrice2 = 35.160 zeroCpnBondMktFullPrice2 = zeroCpnBondMktPrice2+zeroCpnBond2.accruedAmount() zeroCpnBondParAssetSwap2 = AssetSwap(payFixedRate,zeroCpnBond2, zeroCpnBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondParAssetSwap2.setPricingEngine(swapEngine) zeroCpnBondParAssetSwapSpread2 = zeroCpnBondParAssetSwap2.fairSpread() zeroCpnBondMktAssetSwap2 = AssetSwap(payFixedRate,zeroCpnBond2, zeroCpnBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) zeroCpnBondMktAssetSwap2.setPricingEngine(swapEngine) zeroCpnBondMktAssetSwapSpread2 = zeroCpnBondMktAssetSwap2.fairSpread() error8 = abs(zeroCpnBondMktAssetSwapSpread2- 100*zeroCpnBondParAssetSwapSpread2/zeroCpnBondMktFullPrice2) self.assertFalse(error8>tolerance, "wrong asset swap spreads for zero cpn bond:" + "\n market ASW spread: " + str(zeroCpnBondMktAssetSwapSpread2) + "\n par ASW spread: " + str(zeroCpnBondParAssetSwapSpread2) + "\n error: " + str(error8) + "\n tolerance: " + str(tolerance)) def testZSpread(self) : """Testing clean and dirty price with null Z-spread against theoretical prices...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 inArrears = False ## Fixed bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondSchedule1 = Schedule(Date(4,January,2005), Date(4,January,2037), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBond1 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule1, [0.04], ActualActual(ActualActual.ISDA), Following, 100.0, Date(4,January,2005)) bondEngine = DiscountingBondEngine(self.termStructure) fixedBond1.setPricingEngine(bondEngine) fixedBondImpliedValue1 = fixedBond1.cleanPrice() fixedBondSettlementDate1= fixedBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YC... fixedBondCleanPrice1 = cleanPriceFromZSpread(fixedBond1,self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, fixedBondSettlementDate1) tolerance = 1.0e-13 error1 = abs(fixedBondImpliedValue1-fixedBondCleanPrice1) self.assertFalse(error1>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(fixedBondImpliedValue1) + "\n par asset swap spread: " + str(fixedBondCleanPrice1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) ## Fixed bond (Isin: IT0006527060 IBRD 5 02/05/19) ## maturity occurs on a business day fixedBondSchedule2 = Schedule (Date(5,February,2005), Date(5,February,2019), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBond2 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule2, [0.05], Thirty360(Thirty360.BondBasis), Following, 100.0, Date(5,February,2005)) fixedBond2.setPricingEngine(bondEngine) fixedBondImpliedValue2 = fixedBond2.cleanPrice() fixedBondSettlementDate2= fixedBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve fixedBondCleanPrice2 = cleanPriceFromZSpread( fixedBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, fixedBondSettlementDate2) error3 = abs(fixedBondImpliedValue2-fixedBondCleanPrice2) self.assertFalse(error3>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(fixedBondImpliedValue2) + "\n par asset swap spread: " + str(fixedBondCleanPrice2) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) ## FRN bond (Isin: IT0003543847 ISPIM 0 09/29/13) ## maturity doesn't occur on a business day floatingBondSchedule1 = Schedule(Date(29,September,2003), Date(29,September,2013), Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBond1 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule1, self.iborIndex, Actual360(), Following, fixingDays, [1], [0.0056], [], [], inArrears, 100.0, Date(29,September,2003)) floatingBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) floatingBondImpliedValue1 = floatingBond1.cleanPrice() floatingBondSettlementDate1= floatingBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve floatingBondCleanPrice1 = cleanPriceFromZSpread( floatingBond1, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Semiannual, fixedBondSettlementDate1) error5 = abs(floatingBondImpliedValue1-floatingBondCleanPrice1) self.assertFalse(error5>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(floatingBondImpliedValue1) + "\n par asset swap spread: " + str(floatingBondCleanPrice1) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) ## FRN bond (Isin: XS0090566539 COE 0 09/24/18) ## maturity occurs on a business day floatingBondSchedule2 = Schedule(Date(24,September,2004), Date(24,September,2018), Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBond2 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule2, self.iborIndex, Actual360(), ModifiedFollowing, fixingDays, [1], [0.0025], [], [], inArrears, 100.0, Date(24,September,2004)) floatingBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) floatingBondImpliedValue2 = floatingBond2.cleanPrice() floatingBondSettlementDate2= floatingBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve floatingBondCleanPrice2 = cleanPriceFromZSpread( floatingBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Semiannual, fixedBondSettlementDate1) error7 = abs(floatingBondImpliedValue2-floatingBondCleanPrice2) self.assertFalse(error7>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(floatingBondImpliedValue2) + "\n par asset swap spread: " + str(floatingBondCleanPrice2) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) #### CMS bond (Isin: XS0228052402 CRDIT 0 8/22/20) #### maturity doesn't occur on a business day cmsBondSchedule1 = Schedule(Date(22,August,2005), Date(22,August,2020), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBond1 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule1, self.swapIndex, Thirty360(), Following, fixingDays, [1.0], [0.0], [0.055], [0.025], inArrears, 100.0, Date(22,August,2005)) cmsBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondImpliedValue1 = cmsBond1.cleanPrice() cmsBondSettlementDate1= cmsBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve cmsBondCleanPrice1 = cleanPriceFromZSpread( cmsBond1, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, cmsBondSettlementDate1) error9 = abs(cmsBondImpliedValue1-cmsBondCleanPrice1) self.assertFalse(error9>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(cmsBondImpliedValue1) + "\n par asset swap spread: " + str(cmsBondCleanPrice1) + "\n error: " + str(error9) + "\n tolerance: " + str(tolerance)) ## CMS bond (Isin: XS0218766664 ISPIM 0 5/6/15) ## maturity occurs on a business day cmsBondSchedule2 = Schedule(Date(6,May,2005), Date(6,May,2015), Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBond2 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule2, self.swapIndex, Thirty360(), Following, fixingDays, [0.84], [0.0], [], [], inArrears, 100.0, Date(6,May,2005)) cmsBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondImpliedValue2 = cmsBond2.cleanPrice() cmsBondSettlementDate2= cmsBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve cmsBondCleanPrice2 = cleanPriceFromZSpread( cmsBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, cmsBondSettlementDate2) error11 = abs(cmsBondImpliedValue2-cmsBondCleanPrice2) self.assertFalse(error11>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(cmsBondImpliedValue2) + "\n par asset swap spread: " + str(cmsBondCleanPrice2) + "\n error: " + str(error11) + "\n tolerance: " + str(tolerance)) ## Zero-Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBond1 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(20,December,2015), Following, 100.0, Date(19,December,1985)) zeroCpnBond1.setPricingEngine(bondEngine) zeroCpnBondImpliedValue1 = zeroCpnBond1.cleanPrice() zeroCpnBondSettlementDate1= zeroCpnBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve zeroCpnBondCleanPrice1 = cleanPriceFromZSpread(zeroCpnBond1, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, zeroCpnBondSettlementDate1) error13 = abs(zeroCpnBondImpliedValue1-zeroCpnBondCleanPrice1) self.assertFalse(error13>tolerance, "wrong clean price for zero coupon bond:" + "\n zero cpn implied value: " + str(zeroCpnBondImpliedValue1) + "\n zero cpn price: " + str(zeroCpnBondCleanPrice1) + "\n error: " + str(error13) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity doesn't occur on a business day zeroCpnBond2 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(17,February,2028), Following, 100.0, Date(17,February,1998)) zeroCpnBond2.setPricingEngine(bondEngine) zeroCpnBondImpliedValue2 = zeroCpnBond2.cleanPrice() zeroCpnBondSettlementDate2= zeroCpnBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve zeroCpnBondCleanPrice2 = cleanPriceFromZSpread(zeroCpnBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, zeroCpnBondSettlementDate2) error15 = abs(zeroCpnBondImpliedValue2-zeroCpnBondCleanPrice2) self.assertFalse(error15>tolerance, "wrong clean price for zero coupon bond:" + "\n zero cpn implied value: " + str(zeroCpnBondImpliedValue2) + "\n zero cpn price: " + str(zeroCpnBondCleanPrice2) + "\n error: " + str(error15) + "\n tolerance: " + str(tolerance)) def testGenericBondImplied(self): """Testing implied generic-bond value against asset-swap fair price with null spread...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 payFixedRate = True parAssetSwap = True inArrears = False ## Fixed Underlying bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondStartDate1 = Date(4,January,2005) fixedBondMaturityDate1 = Date(4,January,2037) fixedBondSchedule1 = Schedule(fixedBondStartDate1, fixedBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg1 = list(FixedRateLeg(fixedBondSchedule1, ActualActual(ActualActual.ISDA), [self.faceAmount], [0.04])) fixedbondRedemption1 = bondCalendar.adjust(fixedBondMaturityDate1, Following) fixedBondLeg1.append(SimpleCashFlow(100.0, fixedbondRedemption1)) fixedBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate1, fixedBondStartDate1, tuple(fixedBondLeg1)) bondEngine = DiscountingBondEngine(self.termStructure) swapEngine = DiscountingSwapEngine(self.termStructure,True) fixedBond1.setPricingEngine(bondEngine) fixedBondPrice1 = fixedBond1.cleanPrice() fixedBondAssetSwap1 = AssetSwap(payFixedRate, fixedBond1, fixedBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondAssetSwap1.setPricingEngine(swapEngine) fixedBondAssetSwapPrice1 = fixedBondAssetSwap1.fairCleanPrice() tolerance = 1.0e-13 error1 = abs(fixedBondAssetSwapPrice1-fixedBondPrice1) self.assertFalse(error1>tolerance, "wrong zero spread asset swap price for fixed bond:" + "\n bond's clean price: " + str(fixedBondPrice1) + "\n asset swap fair price: " + str(fixedBondAssetSwapPrice1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) ## Fixed Underlying bond (Isin: IT0006527060 IBRD 5 02/05/19) ## maturity occurs on a business day fixedBondStartDate2 = Date(5,February,2005) fixedBondMaturityDate2 = Date(5,February,2019) fixedBondSchedule2 = Schedule(fixedBondStartDate2, fixedBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg2 = list(FixedRateLeg(fixedBondSchedule2,Thirty360(Thirty360.BondBasis), [self.faceAmount],[0.05])) fixedbondRedemption2 = bondCalendar.adjust(fixedBondMaturityDate2,Following) fixedBondLeg2.append(SimpleCashFlow(100.0, fixedbondRedemption2)) fixedBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate2, fixedBondStartDate2, tuple(fixedBondLeg2)) fixedBond2.setPricingEngine(bondEngine) fixedBondPrice2 = fixedBond2.cleanPrice() fixedBondAssetSwap2 = AssetSwap(payFixedRate, fixedBond2, fixedBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondAssetSwap2.setPricingEngine(swapEngine) fixedBondAssetSwapPrice2 = fixedBondAssetSwap2.fairCleanPrice() error2 = abs(fixedBondAssetSwapPrice2-fixedBondPrice2) self.assertFalse(error2>tolerance, "wrong zero spread asset swap price for fixed bond:" + "\n bond's clean price: " + str(fixedBondPrice2) + "\n asset swap fair price: " + str(fixedBondAssetSwapPrice2) + "\n error: " + str(error2) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: IT0003543847 ISPIM 0 09/29/13) ## maturity doesn't occur on a business day floatingBondStartDate1 = Date(29,September,2003) floatingBondMaturityDate1 = Date(29,September,2013) floatingBondSchedule1 = Schedule(floatingBondStartDate1, floatingBondMaturityDate1, Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBondLeg1 = list(IborLeg([self.faceAmount],floatingBondSchedule1, self.iborIndex, Actual360(),ModifiedFollowing, [fixingDays],[],[0.0056],[],[],inArrears)) floatingbondRedemption1 = bondCalendar.adjust(floatingBondMaturityDate1, Following) floatingBondLeg1.append(SimpleCashFlow(100.0, floatingbondRedemption1)) floatingBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate1, floatingBondStartDate1, tuple(floatingBondLeg1)) floatingBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) floatingBondPrice1 = floatingBond1.cleanPrice() floatingBondAssetSwap1 = AssetSwap (payFixedRate, floatingBond1, floatingBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondAssetSwap1.setPricingEngine(swapEngine) floatingBondAssetSwapPrice1 = floatingBondAssetSwap1.fairCleanPrice() error3 = abs(floatingBondAssetSwapPrice1-floatingBondPrice1) self.assertFalse(error3>tolerance, "wrong zero spread asset swap price for floater:" + "\n bond's clean price: " + str(floatingBondPrice1) + "\n asset swap fair price: " + str(floatingBondAssetSwapPrice1) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: XS0090566539 COE 0 09/24/18) ## maturity occurs on a business day floatingBondStartDate2 = Date(24,September,2004) floatingBondMaturityDate2 = Date(24,September,2018) floatingBondSchedule2 =Schedule(floatingBondStartDate2, floatingBondMaturityDate2, Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBondLeg2 = list(IborLeg([self.faceAmount],floatingBondSchedule2, self.iborIndex, Actual360(),ModifiedFollowing,[fixingDays],[],[0.0025],[],[],inArrears)) floatingbondRedemption2 = bondCalendar.adjust(floatingBondMaturityDate2, ModifiedFollowing) floatingBondLeg2.append(SimpleCashFlow(100.0, floatingbondRedemption2)) floatingBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate2, floatingBondStartDate2, tuple(floatingBondLeg2)) floatingBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) currentCoupon=0.04013+0.0025 floatingCurrentCoupon= floatingBond2.nextCouponRate() error4= abs(floatingCurrentCoupon-currentCoupon) self.assertFalse(error4>tolerance, "wrong current coupon is returned for floater bond:" + "\n bond's calculated current coupon: " + str(currentCoupon) + "\n current coupon asked to the bond: " + str(floatingCurrentCoupon) + "\n error: " + str(error4) + "\n tolerance: " + str(tolerance)) floatingBondPrice2 = floatingBond2.cleanPrice() floatingBondAssetSwap2 = AssetSwap(payFixedRate, floatingBond2, floatingBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondAssetSwap2.setPricingEngine(swapEngine) floatingBondAssetSwapPrice2 = floatingBondAssetSwap2.fairCleanPrice() error5 = abs(floatingBondAssetSwapPrice2-floatingBondPrice2) self.assertFalse(error5>tolerance, "wrong zero spread asset swap price for floater:" + "\n bond's clean price: " + str(floatingBondPrice2) + "\n asset swap fair price: " + str(floatingBondAssetSwapPrice2) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0228052402 CRDIT 0 8/22/20) ## maturity doesn't occur on a business day cmsBondStartDate1 = Date(22,August,2005) cmsBondMaturityDate1 = Date(22,August,2020) cmsBondSchedule1 = Schedule(cmsBondStartDate1, cmsBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg1 = list(CmsLeg([self.faceAmount],cmsBondSchedule1, self.swapIndex, Thirty360(),Following,[fixingDays],[],[0.055],[0.025],[],inArrears)) cmsbondRedemption1 = bondCalendar.adjust(cmsBondMaturityDate1, Following) cmsBondLeg1.append(SimpleCashFlow(100.0, cmsbondRedemption1)) cmsBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate1, cmsBondStartDate1, tuple(cmsBondLeg1)) cmsBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondPrice1 = cmsBond1.cleanPrice() cmsBondAssetSwap1 = AssetSwap(payFixedRate, cmsBond1, cmsBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondAssetSwap1.setPricingEngine(swapEngine) cmsBondAssetSwapPrice1 = cmsBondAssetSwap1.fairCleanPrice() error6 = abs(cmsBondAssetSwapPrice1-cmsBondPrice1) self.assertFalse(error6>tolerance, "wrong zero spread asset swap price for cms bond:" + "\n bond's clean price: " + str(cmsBondPrice1) + "\n asset swap fair price: " + str(cmsBondAssetSwapPrice1) + "\n error: " + str(error6) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0218766664 ISPIM 0 5/6/15) ## maturity occurs on a business day cmsBondStartDate2 = Date(6,May,2005) cmsBondMaturityDate2 = Date(6,May,2015) cmsBondSchedule2 = Schedule(cmsBondStartDate2, cmsBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg2 = list(CmsLeg([self.faceAmount],cmsBondSchedule2, self.swapIndex, Thirty360(),Following,[fixingDays],[0.84],[],[],[],inArrears)) cmsbondRedemption2 = bondCalendar.adjust(cmsBondMaturityDate2, Following) cmsBondLeg2.append(SimpleCashFlow(100.0, cmsbondRedemption2)) cmsBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate2, cmsBondStartDate2, tuple(cmsBondLeg2)) cmsBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondPrice2 = cmsBond2.cleanPrice() cmsBondAssetSwap2 = AssetSwap(payFixedRate, cmsBond2, cmsBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondAssetSwap2.setPricingEngine(swapEngine) cmsBondAssetSwapPrice2 = cmsBondAssetSwap2.fairCleanPrice() error7 = abs(cmsBondAssetSwapPrice2-cmsBondPrice2) self.assertFalse(error7>tolerance, "wrong zero spread asset swap price for cms bond:" + "\n bond's clean price: " + str(cmsBondPrice2) + "\n asset swap fair price: " + str(cmsBondAssetSwapPrice2) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBondStartDate1 = Date(19,December,1985) zeroCpnBondMaturityDate1 = Date(20,December,2015) zeroCpnBondRedemption1 = bondCalendar.adjust(zeroCpnBondMaturityDate1, Following) zeroCpnBondLeg1 = Leg([SimpleCashFlow(100.0, zeroCpnBondRedemption1)]) zeroCpnBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate1, zeroCpnBondStartDate1, zeroCpnBondLeg1) zeroCpnBond1.setPricingEngine(bondEngine) zeroCpnBondPrice1 = zeroCpnBond1.cleanPrice() zeroCpnAssetSwap1 = AssetSwap (payFixedRate, zeroCpnBond1, zeroCpnBondPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnAssetSwap1.setPricingEngine(swapEngine) zeroCpnBondAssetSwapPrice1 = zeroCpnAssetSwap1.fairCleanPrice() error8 = abs(zeroCpnBondAssetSwapPrice1-zeroCpnBondPrice1) self.assertFalse(error8>tolerance, "wrong zero spread asset swap price for zero cpn bond:" + "\n bond's clean price: " + str(zeroCpnBondPrice1) + "\n asset swap fair price: " + str(zeroCpnBondAssetSwapPrice1) + "\n error: " + str(error8) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity occurs on a business day zeroCpnBondStartDate2 = Date(17,February,1998) zeroCpnBondMaturityDate2 = Date(17,February,2028) zerocpbondRedemption2 = bondCalendar.adjust(zeroCpnBondMaturityDate2, Following) zeroCpnBondLeg2 = Leg([SimpleCashFlow(100.0, zerocpbondRedemption2)]) zeroCpnBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate2, zeroCpnBondStartDate2, zeroCpnBondLeg2) zeroCpnBond2.setPricingEngine(bondEngine) zeroCpnBondPrice2 = zeroCpnBond2.cleanPrice() zeroCpnAssetSwap2 = AssetSwap(payFixedRate, zeroCpnBond2, zeroCpnBondPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnAssetSwap2.setPricingEngine(swapEngine) zeroCpnBondAssetSwapPrice2 = zeroCpnAssetSwap2.fairCleanPrice() error9 = abs(cmsBondAssetSwapPrice2-cmsBondPrice2) self.assertFalse(error9>tolerance, "wrong zero spread asset swap price for zero cpn bond:" + "\n bond's clean price: " + str(zeroCpnBondPrice2) + "\n asset swap fair price: " + str(zeroCpnBondAssetSwapPrice2) + "\n error: " + str(error9) + "\n tolerance: " + str(tolerance)) def testMASWWithGenericBond(self): """Testing market asset swap against par asset swap with generic bond...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 payFixedRate = True parAssetSwap = True mktAssetSwap = False inArrears = False ## Fixed Underlying bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondStartDate1 = Date(4,January,2005) fixedBondMaturityDate1 = Date(4,January,2037) fixedBondSchedule1 = Schedule(fixedBondStartDate1, fixedBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg1 = list(FixedRateLeg(fixedBondSchedule1, ActualActual(ActualActual.ISDA), [self.faceAmount], [0.04])) fixedbondRedemption1 = bondCalendar.adjust(fixedBondMaturityDate1, Following) fixedBondLeg1.append(SimpleCashFlow(100.0, fixedbondRedemption1)) fixedBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate1, fixedBondStartDate1, fixedBondLeg1) bondEngine = DiscountingBondEngine(self.termStructure) swapEngine = DiscountingSwapEngine(self.termStructure, False) fixedBond1.setPricingEngine(bondEngine) fixedBondMktPrice1 = 89.22 ## market price observed on 7th June 2007 fixedBondMktFullPrice1=fixedBondMktPrice1+fixedBond1.accruedAmount() fixedBondParAssetSwap1 = AssetSwap (payFixedRate, fixedBond1, fixedBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondParAssetSwap1.setPricingEngine(swapEngine) fixedBondParAssetSwapSpread1 = fixedBondParAssetSwap1.fairSpread() fixedBondMktAssetSwap1 = AssetSwap(payFixedRate, fixedBond1, fixedBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) fixedBondMktAssetSwap1.setPricingEngine(swapEngine) fixedBondMktAssetSwapSpread1 = fixedBondMktAssetSwap1.fairSpread() tolerance = 1.0e-13 error1 = abs(fixedBondMktAssetSwapSpread1- 100*fixedBondParAssetSwapSpread1/fixedBondMktFullPrice1) self.assertFalse(error1>tolerance, "wrong asset swap spreads for fixed bond:" + "\n market asset swap spread: " + str(fixedBondMktAssetSwapSpread1) + "\n par asset swap spread: " + str(fixedBondParAssetSwapSpread1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) ## Fixed Underlying bond (Isin: IT0006527060 IBRD 5 02/05/19) ## maturity occurs on a business day fixedBondStartDate2 = Date(5,February,2005) fixedBondMaturityDate2 = Date(5,February,2019) fixedBondSchedule2 = Schedule(fixedBondStartDate2, fixedBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg2 = list(FixedRateLeg(fixedBondSchedule2, Thirty360(Thirty360.BondBasis),[self.faceAmount],[0.05])) fixedbondRedemption2 = bondCalendar.adjust(fixedBondMaturityDate2, Following) fixedBondLeg2.append(SimpleCashFlow(100.0, fixedbondRedemption2)) fixedBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate2, fixedBondStartDate2, fixedBondLeg2) fixedBond2.setPricingEngine(bondEngine) fixedBondMktPrice2 = 99.98 ## market price observed on 7th June 2007 fixedBondMktFullPrice2 = fixedBondMktPrice2+fixedBond2.accruedAmount() fixedBondParAssetSwap2 = AssetSwap(payFixedRate, fixedBond2, fixedBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondParAssetSwap2.setPricingEngine(swapEngine) fixedBondParAssetSwapSpread2 = fixedBondParAssetSwap2.fairSpread() fixedBondMktAssetSwap2 = AssetSwap(payFixedRate, fixedBond2, fixedBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) fixedBondMktAssetSwap2.setPricingEngine(swapEngine) fixedBondMktAssetSwapSpread2 = fixedBondMktAssetSwap2.fairSpread() error2 = abs(fixedBondMktAssetSwapSpread2- 100*fixedBondParAssetSwapSpread2/fixedBondMktFullPrice2) self.assertFalse(error2>tolerance, "wrong asset swap spreads for fixed bond:" + "\n market asset swap spread: " + str(fixedBondMktAssetSwapSpread2) + "\n par asset swap spread: " + str(fixedBondParAssetSwapSpread2) + "\n error: " + str(error2) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: IT0003543847 ISPIM 0 09/29/13) ## maturity doesn't occur on a business day floatingBondStartDate1 = Date(29,September,2003) floatingBondMaturityDate1 = Date(29,September,2013) floatingBondSchedule1 = Schedule(floatingBondStartDate1, floatingBondMaturityDate1, Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBondLeg1 = list(IborLeg([self.faceAmount],floatingBondSchedule1, self.iborIndex,Actual360(),Following, [fixingDays], [],[0.0056],[],[],inArrears)) floatingbondRedemption1 = bondCalendar.adjust(floatingBondMaturityDate1, Following) floatingBondLeg1.append(SimpleCashFlow(100.0, floatingbondRedemption1)) floatingBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate1, floatingBondStartDate1, floatingBondLeg1) floatingBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) ## market price observed on 7th June 2007 floatingBondMktPrice1 = 101.64 floatingBondMktFullPrice1 = floatingBondMktPrice1+floatingBond1.accruedAmount() floatingBondParAssetSwap1 = AssetSwap(payFixedRate, floatingBond1, floatingBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondParAssetSwap1.setPricingEngine(swapEngine) floatingBondParAssetSwapSpread1 = floatingBondParAssetSwap1.fairSpread() floatingBondMktAssetSwap1 = AssetSwap(payFixedRate, floatingBond1, floatingBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) floatingBondMktAssetSwap1.setPricingEngine(swapEngine) floatingBondMktAssetSwapSpread1 = floatingBondMktAssetSwap1.fairSpread() error3 = abs(floatingBondMktAssetSwapSpread1- 100*floatingBondParAssetSwapSpread1/floatingBondMktFullPrice1) self.assertFalse(error3>tolerance, "wrong asset swap spreads for floating bond:" + "\n market asset swap spread: " + str(floatingBondMktAssetSwapSpread1) + "\n par asset swap spread: " + str(floatingBondParAssetSwapSpread1) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: XS0090566539 COE 0 09/24/18) ## maturity occurs on a business day floatingBondStartDate2 = Date(24,September,2004) floatingBondMaturityDate2 = Date(24,September,2018) floatingBondSchedule2 = Schedule(floatingBondStartDate2, floatingBondMaturityDate2, Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBondLeg2 = list(IborLeg([self.faceAmount],floatingBondSchedule2, self.iborIndex, Actual360(), ModifiedFollowing, [fixingDays], [], [0.0025] , [],[], inArrears)) floatingbondRedemption2 = bondCalendar.adjust(floatingBondMaturityDate2, ModifiedFollowing) floatingBondLeg2.append(SimpleCashFlow(100.0, floatingbondRedemption2)) floatingBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate2, floatingBondStartDate2, floatingBondLeg2) floatingBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) ## market price observed on 7th June 2007 floatingBondMktPrice2 = 101.248 floatingBondMktFullPrice2 = floatingBondMktPrice2+floatingBond2.accruedAmount() floatingBondParAssetSwap2 = AssetSwap(payFixedRate, floatingBond2, floatingBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondParAssetSwap2.setPricingEngine(swapEngine) floatingBondParAssetSwapSpread2 = floatingBondParAssetSwap2.fairSpread() floatingBondMktAssetSwap2 = AssetSwap(payFixedRate, floatingBond2, floatingBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) floatingBondMktAssetSwap2.setPricingEngine(swapEngine) floatingBondMktAssetSwapSpread2 = floatingBondMktAssetSwap2.fairSpread() error4 = abs(floatingBondMktAssetSwapSpread2- 100*floatingBondParAssetSwapSpread2/floatingBondMktFullPrice2) self.assertFalse(error4>tolerance, "wrong asset swap spreads for floating bond:" + "\n market asset swap spread: " + str(floatingBondMktAssetSwapSpread2) + "\n par asset swap spread: " + str(floatingBondParAssetSwapSpread2) + "\n error: " + str(error4) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0228052402 CRDIT 0 8/22/20) ## maturity doesn't occur on a business day cmsBondStartDate1 = Date(22,August,2005) cmsBondMaturityDate1 = Date(22,August,2020) cmsBondSchedule1 = Schedule(cmsBondStartDate1, cmsBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg1 = list(CmsLeg([self.faceAmount],cmsBondSchedule1, self.swapIndex, Thirty360(),Following,[fixingDays],[],[],[0.055],[0.025],inArrears)) cmsbondRedemption1 = bondCalendar.adjust(cmsBondMaturityDate1, Following) cmsBondLeg1.append(SimpleCashFlow(100.0, cmsbondRedemption1)) cmsBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate1, cmsBondStartDate1, cmsBondLeg1) cmsBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondMktPrice1 = 88.45 ## market price observed on 7th June 2007 cmsBondMktFullPrice1 = cmsBondMktPrice1+cmsBond1.accruedAmount() cmsBondParAssetSwap1 = AssetSwap(payFixedRate, cmsBond1, cmsBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondParAssetSwap1.setPricingEngine(swapEngine) cmsBondParAssetSwapSpread1 = cmsBondParAssetSwap1.fairSpread() cmsBondMktAssetSwap1 = AssetSwap(payFixedRate, cmsBond1, cmsBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) cmsBondMktAssetSwap1.setPricingEngine(swapEngine) cmsBondMktAssetSwapSpread1 = cmsBondMktAssetSwap1.fairSpread() error5 = abs(cmsBondMktAssetSwapSpread1- 100*cmsBondParAssetSwapSpread1/cmsBondMktFullPrice1) self.assertFalse(error5>tolerance, "wrong asset swap spreads for cms bond:" + "\n market asset swap spread: " + str(cmsBondMktAssetSwapSpread1) + "\n par asset swap spread: " + str(100*cmsBondParAssetSwapSpread1/cmsBondMktFullPrice1) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0218766664 ISPIM 0 5/6/15) ## maturity occurs on a business day cmsBondStartDate2 = Date(6,May,2005) cmsBondMaturityDate2 = Date(6,May,2015) cmsBondSchedule2 = Schedule(cmsBondStartDate2, cmsBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg2 = list(CmsLeg([self.faceAmount],cmsBondSchedule2, self.swapIndex, Thirty360(),Following,[fixingDays],[0.84],[],[],[],inArrears)) cmsbondRedemption2 = bondCalendar.adjust(cmsBondMaturityDate2, Following) cmsBondLeg2.append(SimpleCashFlow(100.0, cmsbondRedemption2)) cmsBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate2, cmsBondStartDate2, cmsBondLeg2) cmsBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondMktPrice2 = 94.08 ## market price observed on 7th June 2007 cmsBondMktFullPrice2 = cmsBondMktPrice2+cmsBond2.accruedAmount() cmsBondParAssetSwap2 = AssetSwap(payFixedRate, cmsBond2, cmsBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondParAssetSwap2.setPricingEngine(swapEngine) cmsBondParAssetSwapSpread2 = cmsBondParAssetSwap2.fairSpread() cmsBondMktAssetSwap2 = AssetSwap(payFixedRate, cmsBond2, cmsBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) cmsBondMktAssetSwap2.setPricingEngine(swapEngine) cmsBondMktAssetSwapSpread2 = cmsBondMktAssetSwap2.fairSpread() error6 = abs(cmsBondMktAssetSwapSpread2- 100*cmsBondParAssetSwapSpread2/cmsBondMktFullPrice2) self.assertFalse(error6>tolerance, "wrong asset swap spreads for cms bond:" + "\n market asset swap spread: " + str(cmsBondMktAssetSwapSpread2) + "\n par asset swap spread: " + str(cmsBondParAssetSwapSpread2) + "\n error: " + str(error6) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBondStartDate1 = Date(19,December,1985) zeroCpnBondMaturityDate1 = Date(20,December,2015) zeroCpnBondRedemption1 = bondCalendar.adjust(zeroCpnBondMaturityDate1, Following) zeroCpnBondLeg1 = Leg([SimpleCashFlow(100.0, zeroCpnBondRedemption1)]) zeroCpnBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate1, zeroCpnBondStartDate1, zeroCpnBondLeg1) zeroCpnBond1.setPricingEngine(bondEngine) ## market price observed on 12th June 2007 zeroCpnBondMktPrice1 = 70.436 zeroCpnBondMktFullPrice1 = zeroCpnBondMktPrice1+zeroCpnBond1.accruedAmount() zeroCpnBondParAssetSwap1 = AssetSwap(payFixedRate,zeroCpnBond1, zeroCpnBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondParAssetSwap1.setPricingEngine(swapEngine) zeroCpnBondParAssetSwapSpread1 = zeroCpnBondParAssetSwap1.fairSpread() zeroCpnBondMktAssetSwap1 = AssetSwap(payFixedRate,zeroCpnBond1, zeroCpnBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) zeroCpnBondMktAssetSwap1.setPricingEngine(swapEngine) zeroCpnBondMktAssetSwapSpread1 = zeroCpnBondMktAssetSwap1.fairSpread() error7 = abs(zeroCpnBondMktAssetSwapSpread1- 100*zeroCpnBondParAssetSwapSpread1/zeroCpnBondMktFullPrice1) self.assertFalse(error7>tolerance, "wrong asset swap spreads for zero cpn bond:" + "\n market asset swap spread: " + str(zeroCpnBondMktAssetSwapSpread1) + "\n par asset swap spread: " + str(zeroCpnBondParAssetSwapSpread1) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity occurs on a business day zeroCpnBondStartDate2 = Date(17,February,1998) zeroCpnBondMaturityDate2 = Date(17,February,2028) zerocpbondRedemption2 = bondCalendar.adjust(zeroCpnBondMaturityDate2, Following) zeroCpnBondLeg2 = Leg([SimpleCashFlow(100.0, zerocpbondRedemption2)]) zeroCpnBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate2, zeroCpnBondStartDate2, zeroCpnBondLeg2) zeroCpnBond2.setPricingEngine(bondEngine) ## zeroCpnBondPrice2 = zeroCpnBond2.cleanPrice() ## market price observed on 12th June 2007 zeroCpnBondMktPrice2 = 35.160 zeroCpnBondMktFullPrice2 = zeroCpnBondMktPrice2+zeroCpnBond2.accruedAmount() zeroCpnBondParAssetSwap2 = AssetSwap(payFixedRate,zeroCpnBond2, zeroCpnBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondParAssetSwap2.setPricingEngine(swapEngine) zeroCpnBondParAssetSwapSpread2 = zeroCpnBondParAssetSwap2.fairSpread() zeroCpnBondMktAssetSwap2 = AssetSwap(payFixedRate,zeroCpnBond2, zeroCpnBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), mktAssetSwap) zeroCpnBondMktAssetSwap2.setPricingEngine(swapEngine) zeroCpnBondMktAssetSwapSpread2 = zeroCpnBondMktAssetSwap2.fairSpread() error8 = abs(zeroCpnBondMktAssetSwapSpread2- 100*zeroCpnBondParAssetSwapSpread2/zeroCpnBondMktFullPrice2) self.assertFalse(error8>tolerance, "wrong asset swap spreads for zero cpn bond:" + "\n market asset swap spread: " + str(zeroCpnBondMktAssetSwapSpread2) + "\n par asset swap spread: " + str(zeroCpnBondParAssetSwapSpread2) + "\n error: " + str(error8) + "\n tolerance: " + str(tolerance)) def testZSpreadWithGenericBond(self) : """Testing clean and dirty price with null Z-spread against theoretical prices...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 inArrears = False ## Fixed Underlying bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondStartDate1 = Date(4,January,2005) fixedBondMaturityDate1 = Date(4,January,2037) fixedBondSchedule1 = Schedule(fixedBondStartDate1, fixedBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg1 = list(FixedRateLeg(fixedBondSchedule1, ActualActual(ActualActual.ISDA), [self.faceAmount], [0.04])) fixedbondRedemption1 = bondCalendar.adjust(fixedBondMaturityDate1, Following) fixedBondLeg1.append(SimpleCashFlow(100.0, fixedbondRedemption1)) fixedBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate1, fixedBondStartDate1, fixedBondLeg1) bondEngine = DiscountingBondEngine(self.termStructure) fixedBond1.setPricingEngine(bondEngine) fixedBondImpliedValue1 = fixedBond1.cleanPrice() fixedBondSettlementDate1 = fixedBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve fixedBondCleanPrice1 = cleanPriceFromZSpread(fixedBond1, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, fixedBondSettlementDate1) tolerance = 1.0e-13 error1 = abs(fixedBondImpliedValue1-fixedBondCleanPrice1) self.assertFalse(error1>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(fixedBondImpliedValue1) + "\n par asset swap spread: " + str(fixedBondCleanPrice1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) ## Fixed Underlying bond (Isin: IT0006527060 IBRD 5 02/05/19) ## maturity occurs on a business day fixedBondStartDate2 = Date(5,February,2005) fixedBondMaturityDate2 = Date(5,February,2019) fixedBondSchedule2 = Schedule(fixedBondStartDate2, fixedBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg2 = list(FixedRateLeg(fixedBondSchedule2, Thirty360(Thirty360.BondBasis), [self.faceAmount],[0.05])) fixedbondRedemption2 = bondCalendar.adjust(fixedBondMaturityDate2, Following) fixedBondLeg2.append(SimpleCashFlow(100.0, fixedbondRedemption2)) fixedBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate2, fixedBondStartDate2, fixedBondLeg2) fixedBond2.setPricingEngine(bondEngine) fixedBondImpliedValue2 = fixedBond2.cleanPrice() fixedBondSettlementDate2= fixedBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve fixedBondCleanPrice2 = cleanPriceFromZSpread(fixedBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, fixedBondSettlementDate2) error3 = abs(fixedBondImpliedValue2-fixedBondCleanPrice2) self.assertFalse(error3>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(fixedBondImpliedValue2) + "\n par asset swap spread: " + str(fixedBondCleanPrice2) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: IT0003543847 ISPIM 0 09/29/13) ## maturity doesn't occur on a business day floatingBondStartDate1 = Date(29,September,2003) floatingBondMaturityDate1 = Date(29,September,2013) floatingBondSchedule1 = Schedule(floatingBondStartDate1, floatingBondMaturityDate1, Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBondLeg1 = list(IborLeg([self.faceAmount],floatingBondSchedule1, self.iborIndex, Actual360(),Following,[fixingDays], [],[0.0056],[],[], inArrears)) floatingbondRedemption1 = bondCalendar.adjust(floatingBondMaturityDate1, Following) floatingBondLeg1.append(SimpleCashFlow(100.0, floatingbondRedemption1)) floatingBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate1, floatingBondStartDate1, floatingBondLeg1) floatingBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) floatingBondImpliedValue1 = floatingBond1.cleanPrice() floatingBondSettlementDate1= floatingBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve floatingBondCleanPrice1 = cleanPriceFromZSpread(floatingBond1, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Semiannual, fixedBondSettlementDate1) error5 = abs(floatingBondImpliedValue1-floatingBondCleanPrice1) self.assertFalse(error5>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(floatingBondImpliedValue1) + "\n par asset swap spread: " + str(floatingBondCleanPrice1) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: XS0090566539 COE 0 09/24/18) ## maturity occurs on a business day floatingBondStartDate2 = Date(24,September,2004) floatingBondMaturityDate2 = Date(24,September,2018) floatingBondSchedule2 = Schedule(floatingBondStartDate2, floatingBondMaturityDate2, Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBondLeg2 = list(IborLeg([self.faceAmount],floatingBondSchedule2, self.iborIndex, Actual360(),ModifiedFollowing, [fixingDays],[],[0.0025],[],[], inArrears)) floatingbondRedemption2 = bondCalendar.adjust(floatingBondMaturityDate2, ModifiedFollowing) floatingBondLeg2.append(SimpleCashFlow(100.0, floatingbondRedemption2)) floatingBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate2, floatingBondStartDate2, floatingBondLeg2) floatingBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) floatingBondImpliedValue2 = floatingBond2.cleanPrice() floatingBondSettlementDate2= floatingBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve floatingBondCleanPrice2 = cleanPriceFromZSpread(floatingBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Semiannual, fixedBondSettlementDate1) error7 = abs(floatingBondImpliedValue2-floatingBondCleanPrice2) self.assertFalse(error7>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(floatingBondImpliedValue2) + "\n par asset swap spread: " + str(floatingBondCleanPrice2) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0228052402 CRDIT 0 8/22/20) ## maturity doesn't occur on a business day cmsBondStartDate1 = Date(22,August,2005) cmsBondMaturityDate1 = Date(22,August,2020) cmsBondSchedule1 = Schedule(cmsBondStartDate1, cmsBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg1 = list(CmsLeg([self.faceAmount],cmsBondSchedule1, self.swapIndex, Thirty360(),Following,[fixingDays],[],[],[0.055],[0.025],inArrears)) cmsbondRedemption1 = bondCalendar.adjust(cmsBondMaturityDate1, Following) cmsBondLeg1.append(SimpleCashFlow(100.0, cmsbondRedemption1)) cmsBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate1, cmsBondStartDate1, cmsBondLeg1) cmsBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondImpliedValue1 = cmsBond1.cleanPrice() cmsBondSettlementDate1= cmsBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve cmsBondCleanPrice1 = cleanPriceFromZSpread(cmsBond1, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, cmsBondSettlementDate1) error9 = abs(cmsBondImpliedValue1-cmsBondCleanPrice1) self.assertFalse(error9>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(cmsBondImpliedValue1) + "\n par asset swap spread: " + str(cmsBondCleanPrice1) + "\n error: " + str(error9) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0218766664 ISPIM 0 5/6/15) ## maturity occurs on a business day cmsBondStartDate2 = Date(6,May,2005) cmsBondMaturityDate2 = Date(6,May,2015) cmsBondSchedule2 = Schedule(cmsBondStartDate2, cmsBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg2 = list(CmsLeg([self.faceAmount],cmsBondSchedule2, self.swapIndex, Thirty360(),Following,[fixingDays],[0.84],[],[],[],inArrears)) cmsbondRedemption2 = bondCalendar.adjust(cmsBondMaturityDate2, Following) cmsBondLeg2.append(SimpleCashFlow(100.0, cmsbondRedemption2)) cmsBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate2, cmsBondStartDate2, cmsBondLeg2) cmsBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondImpliedValue2 = cmsBond2.cleanPrice() cmsBondSettlementDate2= cmsBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve cmsBondCleanPrice2 = cleanPriceFromZSpread(cmsBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, cmsBondSettlementDate2) error11 = abs(cmsBondImpliedValue2-cmsBondCleanPrice2) self.assertFalse(error11>tolerance, "wrong clean price for fixed bond:" + "\n market asset swap spread: " + str(cmsBondImpliedValue2) + "\n par asset swap spread: " + str(cmsBondCleanPrice2) + "\n error: " + str(error11) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBondStartDate1 = Date(19,December,1985) zeroCpnBondMaturityDate1 = Date(20,December,2015) zeroCpnBondRedemption1 = bondCalendar.adjust(zeroCpnBondMaturityDate1, Following) zeroCpnBondLeg1 = Leg([SimpleCashFlow(100.0, zeroCpnBondRedemption1)]) zeroCpnBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate1, zeroCpnBondStartDate1, zeroCpnBondLeg1) zeroCpnBond1.setPricingEngine(bondEngine) zeroCpnBondImpliedValue1 = zeroCpnBond1.cleanPrice() zeroCpnBondSettlementDate1= zeroCpnBond1.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve zeroCpnBondCleanPrice1 = cleanPriceFromZSpread(zeroCpnBond1, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, zeroCpnBondSettlementDate1) error13 = abs(zeroCpnBondImpliedValue1-zeroCpnBondCleanPrice1) self.assertFalse(error13>tolerance, "wrong clean price for zero coupon bond:" + "\n zero cpn implied value: " + str(zeroCpnBondImpliedValue1) + "\n zero cpn price: " + str(zeroCpnBondCleanPrice1) + "\n error: " + str(error13) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity occurs on a business day zeroCpnBondStartDate2 = Date(17,February,1998) zeroCpnBondMaturityDate2 = Date(17,February,2028) zerocpbondRedemption2 = bondCalendar.adjust(zeroCpnBondMaturityDate2, Following) zeroCpnBondLeg2 = Leg([SimpleCashFlow(100.0, zerocpbondRedemption2)]) zeroCpnBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate2, zeroCpnBondStartDate2, zeroCpnBondLeg2) zeroCpnBond2.setPricingEngine(bondEngine) zeroCpnBondImpliedValue2 = zeroCpnBond2.cleanPrice() zeroCpnBondSettlementDate2= zeroCpnBond2.settlementDate() ## standard market conventions: ## bond's frequency + coumpounding and daycounter of the YieldCurve zeroCpnBondCleanPrice2 = cleanPriceFromZSpread(zeroCpnBond2, self.yieldCurve, self.spread, Actual365Fixed(), self.compounding, Annual, zeroCpnBondSettlementDate2) error15 = abs(zeroCpnBondImpliedValue2-zeroCpnBondCleanPrice2) self.assertFalse(error15>tolerance, "wrong clean price for zero coupon bond:" + "\n zero cpn implied value: " + str(zeroCpnBondImpliedValue2) + "\n zero cpn price: " + str(zeroCpnBondCleanPrice2) + "\n error: " + str(error15) + "\n tolerance: " + str(tolerance)) def testSpecializedBondVsGenericBond(self) : """Testing clean and dirty prices for specialized bond against equivalent generic bond...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 inArrears = False ## Fixed Underlying bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondStartDate1 = Date(4,January,2005) fixedBondMaturityDate1 = Date(4,January,2037) fixedBondSchedule1 = Schedule(fixedBondStartDate1, fixedBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg1 = list(FixedRateLeg(fixedBondSchedule1, ActualActual(ActualActual.ISDA), [self.faceAmount], [0.04])) fixedbondRedemption1 = bondCalendar.adjust(fixedBondMaturityDate1, Following) fixedBondLeg1.append(SimpleCashFlow(100.0, fixedbondRedemption1)) ## generic bond fixedBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate1, fixedBondStartDate1, fixedBondLeg1) bondEngine = DiscountingBondEngine(self.termStructure) fixedBond1.setPricingEngine(bondEngine) ## equivalent specialized fixed rate bond fixedSpecializedBond1 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule1, [0.04], ActualActual(ActualActual.ISDA), Following, 100.0, Date(4,January,2005)) fixedSpecializedBond1.setPricingEngine(bondEngine) fixedBondTheoValue1 = fixedBond1.cleanPrice() fixedSpecializedBondTheoValue1 = fixedSpecializedBond1.cleanPrice() tolerance = 1.0e-13 error1 = abs(fixedBondTheoValue1-fixedSpecializedBondTheoValue1) self.assertFalse(error1>tolerance, "wrong clean price for fixed bond:" + "\n specialized fixed rate bond's theo clean price: " + str(fixedBondTheoValue1) + "\n generic equivalent bond's theo clean price: " + str(fixedSpecializedBondTheoValue1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) fixedBondTheoDirty1 = fixedBondTheoValue1+fixedBond1.accruedAmount() fixedSpecializedTheoDirty1 = fixedSpecializedBondTheoValue1+ fixedSpecializedBond1.accruedAmount() error2 = abs(fixedBondTheoDirty1-fixedSpecializedTheoDirty1) self.assertFalse(error2>tolerance, "wrong dirty price for fixed bond:" + "\n specialized fixed rate bond's theo dirty price: " + str(fixedBondTheoDirty1) + "\n generic equivalent bond's theo dirty price: " + str(fixedSpecializedTheoDirty1) + "\n error: " + str(error2) + "\n tolerance: " + str(tolerance)) ## Fixed Underlying bond (Isin: IT0006527060 IBRD 5 02/05/19) ## maturity occurs on a business day fixedBondStartDate2 = Date(5,February,2005) fixedBondMaturityDate2 = Date(5,February,2019) fixedBondSchedule2 = Schedule(fixedBondStartDate2, fixedBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg2 = list(FixedRateLeg(fixedBondSchedule2, Thirty360(Thirty360.BondBasis),[self.faceAmount],[0.05])) fixedbondRedemption2 = bondCalendar.adjust(fixedBondMaturityDate2, Following) fixedBondLeg2.append(SimpleCashFlow(100.0, fixedbondRedemption2)) ## generic bond fixedBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate2, fixedBondStartDate2, fixedBondLeg2) fixedBond2.setPricingEngine(bondEngine) ## equivalent specialized fixed rate bond fixedSpecializedBond2 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule2, [0.05],Thirty360(Thirty360.BondBasis), Following, 100.0, Date(5,February,2005)) fixedSpecializedBond2.setPricingEngine(bondEngine) fixedBondTheoValue2 = fixedBond2.cleanPrice() fixedSpecializedBondTheoValue2 = fixedSpecializedBond2.cleanPrice() error3 = abs(fixedBondTheoValue2-fixedSpecializedBondTheoValue2) self.assertFalse(error3>tolerance, "wrong clean price for fixed bond:" + "\n specialized fixed rate bond's theo clean price: " + str(fixedBondTheoValue2) + "\n generic equivalent bond's theo clean price: " + str(fixedSpecializedBondTheoValue2) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) fixedBondTheoDirty2 = fixedBondTheoValue2+ fixedBond2.accruedAmount() fixedSpecializedBondTheoDirty2 = fixedSpecializedBondTheoValue2+ fixedSpecializedBond2.accruedAmount() error4 = abs(fixedBondTheoDirty2-fixedSpecializedBondTheoDirty2) self.assertFalse(error4>tolerance, "wrong dirty price for fixed bond:" + "\n specialized fixed rate bond's dirty clean price: " + str(fixedBondTheoDirty2) + "\n generic equivalent bond's theo dirty price: " + str(fixedSpecializedBondTheoDirty2) + "\n error: " + str(error4) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: IT0003543847 ISPIM 0 09/29/13) ## maturity doesn't occur on a business day floatingBondStartDate1 = Date(29,September,2003) floatingBondMaturityDate1 = Date(29,September,2013) floatingBondSchedule1 = Schedule(floatingBondStartDate1, floatingBondMaturityDate1, Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBondLeg1 = list(IborLeg([self.faceAmount],floatingBondSchedule1, self.iborIndex, Actual360(),Following,[fixingDays],[],[0.0056],[],[],inArrears)) floatingbondRedemption1 = bondCalendar.adjust(floatingBondMaturityDate1, Following) floatingBondLeg1.append(SimpleCashFlow(100.0, floatingbondRedemption1)) ## generic bond floatingBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate1, floatingBondStartDate1, floatingBondLeg1) floatingBond1.setPricingEngine(bondEngine) ## equivalent specialized floater floatingSpecializedBond1 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule1, self.iborIndex, Actual360(), Following, fixingDays, [1], [0.0056], [], [], inArrears, 100.0, Date(29,September,2003)) floatingSpecializedBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) setCouponPricer(floatingSpecializedBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) floatingBondTheoValue1 = floatingBond1.cleanPrice() floatingSpecializedBondTheoValue1 = floatingSpecializedBond1.cleanPrice() error5 = abs(floatingBondTheoValue1- floatingSpecializedBondTheoValue1) self.assertFalse(error5>tolerance, "wrong clean price for fixed bond:" + "\n generic fixed rate bond's theo clean price: " + str(floatingBondTheoValue1) + "\n equivalent specialized bond's theo clean price: " + str(floatingSpecializedBondTheoValue1) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) floatingBondTheoDirty1 = floatingBondTheoValue1+ floatingBond1.accruedAmount() floatingSpecializedBondTheoDirty1 = floatingSpecializedBondTheoValue1 + floatingSpecializedBond1.accruedAmount() error6 = abs(floatingBondTheoDirty1- floatingSpecializedBondTheoDirty1) self.assertFalse(error6>tolerance, "wrong dirty price for frn bond:" + "\n generic frn bond's dirty clean price: " + str(floatingBondTheoDirty1) + "\n equivalent specialized bond's theo dirty price: " + str(floatingSpecializedBondTheoDirty1) + "\n error: " + str(error6) + "\n tolerance: " + str(tolerance)) ## FRN Underlying bond (Isin: XS0090566539 COE 0 09/24/18) ## maturity occurs on a business day floatingBondStartDate2 = Date(24,September,2004) floatingBondMaturityDate2 = Date(24,September,2018) floatingBondSchedule2 = Schedule(floatingBondStartDate2, floatingBondMaturityDate2, Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBondLeg2 = list(IborLeg([self.faceAmount], floatingBondSchedule2, self.iborIndex, Actual360(),ModifiedFollowing,[fixingDays], [],[0.0025],[],[],inArrears)) floatingbondRedemption2 = bondCalendar.adjust(floatingBondMaturityDate2, ModifiedFollowing) floatingBondLeg2.append(SimpleCashFlow(100.0, floatingbondRedemption2)) ## generic bond floatingBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate2, floatingBondStartDate2, floatingBondLeg2) floatingBond2.setPricingEngine(bondEngine) ## equivalent specialized floater floatingSpecializedBond2 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule2, self.iborIndex, Actual360(), ModifiedFollowing, fixingDays, [1], [0.0025], [], [], inArrears, 100.0, Date(24,September,2004)) floatingSpecializedBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) setCouponPricer(floatingSpecializedBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) floatingBondTheoValue2 = floatingBond2.cleanPrice() floatingSpecializedBondTheoValue2 = floatingSpecializedBond2.cleanPrice() error7 = abs(floatingBondTheoValue2-floatingSpecializedBondTheoValue2) self.assertFalse(error7>tolerance, "wrong clean price for floater bond:" + "\n generic floater bond's theo clean price: " + str(floatingBondTheoValue2) + "\n equivalent specialized bond's theo clean price: " + str(floatingSpecializedBondTheoValue2) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) floatingBondTheoDirty2 = floatingBondTheoValue2+ floatingBond2.accruedAmount() floatingSpecializedTheoDirty2 = floatingSpecializedBondTheoValue2+ floatingSpecializedBond2.accruedAmount() error8 = abs(floatingBondTheoDirty2-floatingSpecializedTheoDirty2) self.assertFalse(error8>tolerance, "wrong dirty price for floater bond:" + "\n generic floater bond's theo dirty price: " + str(floatingBondTheoDirty2) + "\n equivalent specialized bond's theo dirty price: " + str(floatingSpecializedTheoDirty2) + "\n error: " + str(error8) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0228052402 CRDIT 0 8/22/20) ## maturity doesn't occur on a business day cmsBondStartDate1 = Date(22,August,2005) cmsBondMaturityDate1 = Date(22,August,2020) cmsBondSchedule1 = Schedule(cmsBondStartDate1, cmsBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg1 = list(CmsLeg([self.faceAmount],cmsBondSchedule1, self.swapIndex, Thirty360(), Following, [fixingDays], [],[],[0.055],[0.025],inArrears)) cmsbondRedemption1 = bondCalendar.adjust(cmsBondMaturityDate1, Following) cmsBondLeg1.append(SimpleCashFlow(100.0, cmsbondRedemption1)) ## generic cms bond cmsBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate1, cmsBondStartDate1, cmsBondLeg1) cmsBond1.setPricingEngine(bondEngine) ## equivalent specialized cms bond cmsSpecializedBond1 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule1, self.swapIndex, Thirty360(), Following, fixingDays, [1.0], [0.0], [0.055],[0.025], inArrears, 100.0, Date(22,August,2005)) cmsSpecializedBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) setCouponPricer(cmsSpecializedBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondTheoValue1 = cmsBond1.cleanPrice() cmsSpecializedBondTheoValue1 = cmsSpecializedBond1.cleanPrice() error9 = abs(cmsBondTheoValue1-cmsSpecializedBondTheoValue1) self.assertFalse(error9>tolerance, "wrong clean price for cms bond:" + "\n generic cms bond's theo clean price: " + str(cmsBondTheoValue1) + "\n equivalent specialized bond's theo clean price: " + str(cmsSpecializedBondTheoValue1) + "\n error: " + str(error9) + "\n tolerance: " + str(tolerance)) cmsBondTheoDirty1 = cmsBondTheoValue1+cmsBond1.accruedAmount() cmsSpecializedBondTheoDirty1 = cmsSpecializedBondTheoValue1+ cmsSpecializedBond1.accruedAmount() error10 = abs(cmsBondTheoDirty1-cmsSpecializedBondTheoDirty1) self.assertFalse(error10>tolerance, "wrong dirty price for cms bond:" + "\n generic cms bond's theo dirty price: " + str(cmsBondTheoDirty1) + "\n specialized cms bond's theo dirty price: " + str(cmsSpecializedBondTheoDirty1) + "\n error: " + str(error10) + "\n tolerance: " + str(tolerance)) ## CMS Underlying bond (Isin: XS0218766664 ISPIM 0 5/6/15) ## maturity occurs on a business day cmsBondStartDate2 = Date(6,May,2005) cmsBondMaturityDate2 = Date(6,May,2015) cmsBondSchedule2 = Schedule(cmsBondStartDate2, cmsBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg2 = list(CmsLeg([self.faceAmount],cmsBondSchedule2, self.swapIndex, Thirty360(),Following,[fixingDays],[0.84],[],[],[],inArrears)) cmsbondRedemption2 = bondCalendar.adjust(cmsBondMaturityDate2, Following) cmsBondLeg2.append(SimpleCashFlow(100.0, cmsbondRedemption2)) ## generic bond cmsBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate2, cmsBondStartDate2, cmsBondLeg2) cmsBond2.setPricingEngine(bondEngine) ## equivalent specialized cms bond cmsSpecializedBond2 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule2, self.swapIndex, Thirty360(), Following, fixingDays, [0.84], [0.0], [], [], inArrears, 100.0, Date(6,May,2005)) cmsSpecializedBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) setCouponPricer(cmsSpecializedBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondTheoValue2 = cmsBond2.cleanPrice() cmsSpecializedBondTheoValue2 = cmsSpecializedBond2.cleanPrice() error11 = abs(cmsBondTheoValue2-cmsSpecializedBondTheoValue2) self.assertFalse(error11>tolerance, "wrong clean price for cms bond:" + "\n generic cms bond's theo clean price: " + str(cmsBondTheoValue2) + "\n cms bond's theo clean price: " + str(cmsSpecializedBondTheoValue2) + "\n error: " + str(error11) + "\n tolerance: " + str(tolerance)) cmsBondTheoDirty2 = cmsBondTheoValue2+cmsBond2.accruedAmount() cmsSpecializedBondTheoDirty2 = cmsSpecializedBondTheoValue2+cmsSpecializedBond2.accruedAmount() error12 = abs(cmsBondTheoDirty2-cmsSpecializedBondTheoDirty2) self.assertFalse(error12>tolerance, "wrong dirty price for cms bond:" + "\n generic cms bond's dirty price: " + str(cmsBondTheoDirty2) + "\n specialized cms bond's theo dirty price: " + str(cmsSpecializedBondTheoDirty2) + "\n error: " + str(error12) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBondStartDate1 = Date(19,December,1985) zeroCpnBondMaturityDate1 = Date(20,December,2015) zeroCpnBondRedemption1 = bondCalendar.adjust(zeroCpnBondMaturityDate1, Following) zeroCpnBondLeg1 = Leg([SimpleCashFlow(100.0, zeroCpnBondRedemption1)]) ## generic bond zeroCpnBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate1, zeroCpnBondStartDate1, zeroCpnBondLeg1) zeroCpnBond1.setPricingEngine(bondEngine) ## specialized zerocpn bond zeroCpnSpecializedBond1 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(20,December,2015), Following, 100.0, Date(19,December,1985)) zeroCpnSpecializedBond1.setPricingEngine(bondEngine) zeroCpnBondTheoValue1 = zeroCpnBond1.cleanPrice() zeroCpnSpecializedBondTheoValue1 = zeroCpnSpecializedBond1.cleanPrice() error13 = abs(zeroCpnBondTheoValue1-zeroCpnSpecializedBondTheoValue1) self.assertFalse(error13>tolerance, "wrong clean price for zero coupon bond:" + "\n generic zero bond's clean price: " + str(zeroCpnBondTheoValue1) + "\n specialized zero bond's clean price: " + str(zeroCpnSpecializedBondTheoValue1) + "\n error: " + str(error13) + "\n tolerance: " + str(tolerance)) zeroCpnBondTheoDirty1 = zeroCpnBondTheoValue1+ zeroCpnBond1.accruedAmount() zeroCpnSpecializedBondTheoDirty1 = zeroCpnSpecializedBondTheoValue1+ \ zeroCpnSpecializedBond1.accruedAmount() error14 = abs(zeroCpnBondTheoDirty1-zeroCpnSpecializedBondTheoDirty1) self.assertFalse(error14>tolerance, "wrong dirty price for zero bond:" + "\n generic zerocpn bond's dirty price: " + str(zeroCpnBondTheoDirty1) + "\n specialized zerocpn bond's clean price: " + str(zeroCpnSpecializedBondTheoDirty1) + "\n error: " + str(error14) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity occurs on a business day zeroCpnBondStartDate2 = Date(17,February,1998) zeroCpnBondMaturityDate2 = Date(17,February,2028) zerocpbondRedemption2 = bondCalendar.adjust(zeroCpnBondMaturityDate2, Following) zeroCpnBondLeg2 = Leg([SimpleCashFlow(100.0, zerocpbondRedemption2)]) ## generic bond zeroCpnBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate2, zeroCpnBondStartDate2, zeroCpnBondLeg2) zeroCpnBond2.setPricingEngine(bondEngine) ## specialized zerocpn bond zeroCpnSpecializedBond2 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(17,February,2028), Following, 100.0, Date(17,February,1998)) zeroCpnSpecializedBond2.setPricingEngine(bondEngine) zeroCpnBondTheoValue2 = zeroCpnBond2.cleanPrice() zeroCpnSpecializedBondTheoValue2 = zeroCpnSpecializedBond2.cleanPrice() error15 = abs(zeroCpnBondTheoValue2 -zeroCpnSpecializedBondTheoValue2) self.assertFalse(error15>tolerance, "wrong clean price for zero coupon bond:" + "\n generic zerocpn bond's clean price: " + str(zeroCpnBondTheoValue2) + "\n specialized zerocpn bond's clean price: " + str(zeroCpnSpecializedBondTheoValue2) + "\n error: " + str(error15) + "\n tolerance: " + str(tolerance)) zeroCpnBondTheoDirty2 = zeroCpnBondTheoValue2+ zeroCpnBond2.accruedAmount() zeroCpnSpecializedBondTheoDirty2 = \ zeroCpnSpecializedBondTheoValue2+ \ zeroCpnSpecializedBond2.accruedAmount() error16 = abs(zeroCpnBondTheoDirty2-zeroCpnSpecializedBondTheoDirty2) self.assertFalse(error16>tolerance, "wrong dirty price for zero coupon bond:" + "\n generic zerocpn bond's dirty price: " + str(zeroCpnBondTheoDirty2) + "\n specialized zerocpn bond's dirty price: " + str(zeroCpnSpecializedBondTheoDirty2) + "\n error: " + str(error16) + "\n tolerance: " + str(tolerance)) def testSpecializedBondVsGenericBondUsingAsw(self) : """Testing asset-swap prices and spreads for specialized bond against equivalent generic bond...""" bondCalendar = TARGET() settlementDays = 3 fixingDays = 2 payFixedRate = True parAssetSwap = True inArrears = False ## Fixed bond (Isin: DE0001135275 DBR 4 01/04/37) ## maturity doesn't occur on a business day fixedBondStartDate1 = Date(4,January,2005) fixedBondMaturityDate1 = Date(4,January,2037) fixedBondSchedule1 = Schedule(fixedBondStartDate1, fixedBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg1 = list(FixedRateLeg(fixedBondSchedule1, ActualActual(ActualActual.ISDA), [self.faceAmount],[0.04])) fixedbondRedemption1 = bondCalendar.adjust(fixedBondMaturityDate1, Following) fixedBondLeg1.append(SimpleCashFlow(100.0, fixedbondRedemption1)) ## generic bond fixedBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate1, fixedBondStartDate1, fixedBondLeg1) bondEngine = DiscountingBondEngine(self.termStructure) swapEngine = DiscountingSwapEngine(self.termStructure, False) fixedBond1.setPricingEngine(bondEngine) ## equivalent specialized fixed rate bond fixedSpecializedBond1 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule1, [0.04], ActualActual(ActualActual.ISDA), Following, 100.0, Date(4,January,2005)) fixedSpecializedBond1.setPricingEngine(bondEngine) fixedBondPrice1 = fixedBond1.cleanPrice() fixedSpecializedBondPrice1 = fixedSpecializedBond1.cleanPrice() fixedBondAssetSwap1 = AssetSwap(payFixedRate, fixedBond1, fixedBondPrice1, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondAssetSwap1.setPricingEngine(swapEngine) fixedSpecializedBondAssetSwap1 = AssetSwap(payFixedRate, fixedSpecializedBond1, fixedSpecializedBondPrice1, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedSpecializedBondAssetSwap1.setPricingEngine(swapEngine) fixedBondAssetSwapPrice1 = fixedBondAssetSwap1.fairCleanPrice() fixedSpecializedBondAssetSwapPrice1 = fixedSpecializedBondAssetSwap1.fairCleanPrice() tolerance = 1.0e-13 error1 = abs(fixedBondAssetSwapPrice1-fixedSpecializedBondAssetSwapPrice1) self.assertFalse(error1>tolerance, "wrong clean price for fixed bond:" + "\n generic fixed rate bond's clean price: " + str(fixedBondAssetSwapPrice1) + "\n equivalent specialized bond's clean price: " + str(fixedSpecializedBondAssetSwapPrice1) + "\n error: " + str(error1) + "\n tolerance: " + str(tolerance)) ## market executable price as of 4th sept 2007 fixedBondMktPrice1= 91.832 fixedBondASW1 = AssetSwap(payFixedRate, fixedBond1, fixedBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondASW1.setPricingEngine(swapEngine) fixedSpecializedBondASW1 = AssetSwap(payFixedRate, fixedSpecializedBond1, fixedBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedSpecializedBondASW1.setPricingEngine(swapEngine) fixedBondASWSpread1 = fixedBondASW1.fairSpread() fixedSpecializedBondASWSpread1 = fixedSpecializedBondASW1.fairSpread() error2 = abs(fixedBondASWSpread1-fixedSpecializedBondASWSpread1) self.assertFalse(error2>tolerance, "wrong asw spread for fixed bond:" + "\n generic fixed rate bond's asw spread: " + str(fixedBondASWSpread1) + "\n equivalent specialized bond's asw spread: " + str(fixedSpecializedBondASWSpread1) + "\n error: " + str(error2) + "\n tolerance: " + str(tolerance)) ##Fixed bond (Isin: IT0006527060 IBRD 5 02/05/19) ##maturity occurs on a business day fixedBondStartDate2 = Date(5,February,2005) fixedBondMaturityDate2 = Date(5,February,2019) fixedBondSchedule2 = Schedule(fixedBondStartDate2, fixedBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) fixedBondLeg2 = list(FixedRateLeg(fixedBondSchedule2, Thirty360(Thirty360.BondBasis),[self.faceAmount], [0.05])) fixedbondRedemption2 = bondCalendar.adjust(fixedBondMaturityDate2, Following) fixedBondLeg2.append(SimpleCashFlow(100.0, fixedbondRedemption2)) ## generic bond fixedBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, fixedBondMaturityDate2, fixedBondStartDate2, fixedBondLeg2) fixedBond2.setPricingEngine(bondEngine) ## equivalent specialized fixed rate bond fixedSpecializedBond2 = FixedRateBond(settlementDays, self.faceAmount, fixedBondSchedule2, [0.05], Thirty360(Thirty360.BondBasis), Following, 100.0, Date(5,February,2005)) fixedSpecializedBond2.setPricingEngine(bondEngine) fixedBondPrice2 = fixedBond2.cleanPrice() fixedSpecializedBondPrice2 = fixedSpecializedBond2.cleanPrice() fixedBondAssetSwap2 = AssetSwap(payFixedRate, fixedBond2, fixedBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondAssetSwap2.setPricingEngine(swapEngine) fixedSpecializedBondAssetSwap2 = AssetSwap(payFixedRate, fixedSpecializedBond2, fixedSpecializedBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedSpecializedBondAssetSwap2.setPricingEngine(swapEngine) fixedBondAssetSwapPrice2 = fixedBondAssetSwap2.fairCleanPrice() fixedSpecializedBondAssetSwapPrice2 = fixedSpecializedBondAssetSwap2.fairCleanPrice() error3 = abs(fixedBondAssetSwapPrice2-fixedSpecializedBondAssetSwapPrice2) self.assertFalse(error3>tolerance, "wrong clean price for fixed bond:" + "\n generic fixed rate bond's clean price: " + str(fixedBondAssetSwapPrice2) + "\n equivalent specialized bond's clean price: " + str(fixedSpecializedBondAssetSwapPrice2) + "\n error: " + str(error3) + "\n tolerance: " + str(tolerance)) ## market executable price as of 4th sept 2007 fixedBondMktPrice2= 102.178 fixedBondASW2 = AssetSwap(payFixedRate, fixedBond2, fixedBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedBondASW2.setPricingEngine(swapEngine) fixedSpecializedBondASW2 = AssetSwap(payFixedRate, fixedSpecializedBond2, fixedBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) fixedSpecializedBondASW2.setPricingEngine(swapEngine) fixedBondASWSpread2 = fixedBondASW2.fairSpread() fixedSpecializedBondASWSpread2 = fixedSpecializedBondASW2.fairSpread() error4 = abs(fixedBondASWSpread2-fixedSpecializedBondASWSpread2) self.assertFalse(error4>tolerance, "wrong asw spread for fixed bond:" + "\n generic fixed rate bond's asw spread: " + str(fixedBondASWSpread2) + "\n equivalent specialized bond's asw spread: " + str(fixedSpecializedBondASWSpread2) + "\n error: " + str(error4) + "\n tolerance: " + str(tolerance)) ##FRN bond (Isin: IT0003543847 ISPIM 0 09/29/13) ##maturity doesn't occur on a business day floatingBondStartDate1 = Date(29,September,2003) floatingBondMaturityDate1 = Date(29,September,2013) floatingBondSchedule1 = Schedule(floatingBondStartDate1, floatingBondMaturityDate1, Period(Semiannual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) floatingBondLeg1 = list(IborLeg([self.faceAmount],floatingBondSchedule1, self.iborIndex, Actual360(), Following,[fixingDays],[],[0.0056],[],[],inArrears)) floatingbondRedemption1 = bondCalendar.adjust(floatingBondMaturityDate1, Following) floatingBondLeg1.append(SimpleCashFlow(100.0, floatingbondRedemption1)) ## generic bond floatingBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate1, floatingBondStartDate1, floatingBondLeg1) floatingBond1.setPricingEngine(bondEngine) ## equivalent specialized floater floatingSpecializedBond1 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule1, self.iborIndex, Actual360(), Following, fixingDays, [1], [0.0056], [], [], inArrears, 100.0, Date(29,September,2003)) floatingSpecializedBond1.setPricingEngine(bondEngine) setCouponPricer(floatingBond1.cashflows(), self.pricer) setCouponPricer(floatingSpecializedBond1.cashflows(), self.pricer) self.iborIndex.addFixing(Date(27,March,2007), 0.0402) floatingBondPrice1 = floatingBond1.cleanPrice() floatingSpecializedBondPrice1= floatingSpecializedBond1.cleanPrice() floatingBondAssetSwap1 = AssetSwap(payFixedRate, floatingBond1, floatingBondPrice1, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondAssetSwap1.setPricingEngine(swapEngine) floatingSpecializedBondAssetSwap1 = AssetSwap(payFixedRate, floatingSpecializedBond1, floatingSpecializedBondPrice1, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingSpecializedBondAssetSwap1.setPricingEngine(swapEngine) floatingBondAssetSwapPrice1 = floatingBondAssetSwap1.fairCleanPrice() floatingSpecializedBondAssetSwapPrice1 = floatingSpecializedBondAssetSwap1.fairCleanPrice() error5 = abs(floatingBondAssetSwapPrice1-floatingSpecializedBondAssetSwapPrice1) self.assertFalse(error5>tolerance, "wrong clean price for frnbond:" + "\n generic frn rate bond's clean price: " + str(floatingBondAssetSwapPrice1) + "\n equivalent specialized bond's price: " + str(floatingSpecializedBondAssetSwapPrice1) + "\n error: " + str(error5) + "\n tolerance: " + str(tolerance)) ## market executable price as of 4th sept 2007 floatingBondMktPrice1= 101.33 floatingBondASW1 = AssetSwap(payFixedRate, floatingBond1, floatingBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondASW1.setPricingEngine(swapEngine) floatingSpecializedBondASW1 = AssetSwap(payFixedRate, floatingSpecializedBond1, floatingBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingSpecializedBondASW1.setPricingEngine(swapEngine) floatingBondASWSpread1 = floatingBondASW1.fairSpread() floatingSpecializedBondASWSpread1 = floatingSpecializedBondASW1.fairSpread() error6 = abs(floatingBondASWSpread1-floatingSpecializedBondASWSpread1) self.assertFalse(error6>tolerance, "wrong asw spread for fixed bond:" + "\n generic frn rate bond's asw spread: " + str(floatingBondASWSpread1) + "\n equivalent specialized bond's asw spread: " + str(floatingSpecializedBondASWSpread1) + "\n error: " + str(error6) + "\n tolerance: " + str(tolerance)) ##FRN bond (Isin: XS0090566539 COE 0 09/24/18) ##maturity occurs on a business day floatingBondStartDate2 = Date(24,September,2004) floatingBondMaturityDate2 = Date(24,September,2018) floatingBondSchedule2 = Schedule(floatingBondStartDate2, floatingBondMaturityDate2, Period(Semiannual), bondCalendar, ModifiedFollowing, ModifiedFollowing, DateGeneration.Backward, False) floatingBondLeg2 = list(IborLeg([self.faceAmount],floatingBondSchedule2, self.iborIndex, Actual360(),ModifiedFollowing,[fixingDays],[],[0.0025],[],[],inArrears)) floatingbondRedemption2 = bondCalendar.adjust(floatingBondMaturityDate2, ModifiedFollowing) floatingBondLeg2.append(SimpleCashFlow(100.0, floatingbondRedemption2)) ## generic bond floatingBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, floatingBondMaturityDate2, floatingBondStartDate2, floatingBondLeg2) floatingBond2.setPricingEngine(bondEngine) ## equivalent specialized floater floatingSpecializedBond2 = FloatingRateBond(settlementDays, self.faceAmount, floatingBondSchedule2, self.iborIndex, Actual360(), ModifiedFollowing, fixingDays, [1], [0.0025], [], [], inArrears, 100.0, Date(24,September,2004)) floatingSpecializedBond2.setPricingEngine(bondEngine) setCouponPricer(floatingBond2.cashflows(), self.pricer) setCouponPricer(floatingSpecializedBond2.cashflows(), self.pricer) self.iborIndex.addFixing(Date(22,March,2007), 0.04013) floatingBondPrice2 = floatingBond2.cleanPrice() floatingSpecializedBondPrice2= floatingSpecializedBond2.cleanPrice() floatingBondAssetSwap2 = AssetSwap(payFixedRate, floatingBond2, floatingBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondAssetSwap2.setPricingEngine(swapEngine) floatingSpecializedBondAssetSwap2 = AssetSwap(payFixedRate, floatingSpecializedBond2, floatingSpecializedBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingSpecializedBondAssetSwap2.setPricingEngine(swapEngine) floatingBondAssetSwapPrice2 = floatingBondAssetSwap2.fairCleanPrice() floatingSpecializedBondAssetSwapPrice2 = floatingSpecializedBondAssetSwap2.fairCleanPrice() error7 = abs(floatingBondAssetSwapPrice2-floatingSpecializedBondAssetSwapPrice2) self.assertFalse(error7>tolerance, "wrong clean price for frnbond:" + "\n generic frn rate bond's clean price: " + str(floatingBondAssetSwapPrice2) + "\n equivalent specialized frn bond's price: " + str(floatingSpecializedBondAssetSwapPrice2) + "\n error: " + str(error7) + "\n tolerance: " + str(tolerance)) ## market executable price as of 4th sept 2007 floatingBondMktPrice2 = 101.26 floatingBondASW2 = AssetSwap(payFixedRate, floatingBond2, floatingBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingBondASW2.setPricingEngine(swapEngine) floatingSpecializedBondASW2 = AssetSwap(payFixedRate, floatingSpecializedBond2, floatingBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) floatingSpecializedBondASW2.setPricingEngine(swapEngine) floatingBondASWSpread2 = floatingBondASW2.fairSpread() floatingSpecializedBondASWSpread2 = floatingSpecializedBondASW2.fairSpread() error8 = abs(floatingBondASWSpread2-floatingSpecializedBondASWSpread2) self.assertFalse(error8>tolerance, "wrong asw spread for frn bond:" + "\n generic frn rate bond's asw spread: " + str(floatingBondASWSpread2) + "\n equivalent specialized bond's asw spread: " + str(floatingSpecializedBondASWSpread2) + "\n error: " + str(error8) + "\n tolerance: " + str(tolerance)) ## CMS bond (Isin: XS0228052402 CRDIT 0 8/22/20) ## maturity doesn't occur on a business day cmsBondStartDate1 = Date(22,August,2005) cmsBondMaturityDate1 = Date(22,August,2020) cmsBondSchedule1 = Schedule(cmsBondStartDate1, cmsBondMaturityDate1, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg1 = list(CmsLeg([self.faceAmount],cmsBondSchedule1, self.swapIndex, Thirty360(),Following,[fixingDays], [],[],[0.055],[0.025],inArrears)) cmsbondRedemption1 = bondCalendar.adjust(cmsBondMaturityDate1,Following) cmsBondLeg1.append(SimpleCashFlow(100.0, cmsbondRedemption1)) ## generic cms bond cmsBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate1, cmsBondStartDate1, cmsBondLeg1) cmsBond1.setPricingEngine(bondEngine) ## equivalent specialized cms bond cmsSpecializedBond1 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule1, self.swapIndex, Thirty360(), Following, fixingDays, [1.0], [0.0], [0.055], [0.025], inArrears, 100.0, Date(22,August,2005)) cmsSpecializedBond1.setPricingEngine(bondEngine) setCouponPricer(cmsBond1.cashflows(), self.cmspricer) setCouponPricer(cmsSpecializedBond1.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(18,August,2006), 0.04158) cmsBondPrice1 = cmsBond1.cleanPrice() cmsSpecializedBondPrice1 = cmsSpecializedBond1.cleanPrice() cmsBondAssetSwap1 = AssetSwap(payFixedRate,cmsBond1, cmsBondPrice1, self.iborIndex, self.nonnullspread, Schedule(),self.iborIndex.dayCounter(), parAssetSwap) cmsBondAssetSwap1.setPricingEngine(swapEngine) cmsSpecializedBondAssetSwap1 = AssetSwap(payFixedRate,cmsSpecializedBond1, cmsSpecializedBondPrice1, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsSpecializedBondAssetSwap1.setPricingEngine(swapEngine) cmsBondAssetSwapPrice1 = cmsBondAssetSwap1.fairCleanPrice() cmsSpecializedBondAssetSwapPrice1 = cmsSpecializedBondAssetSwap1.fairCleanPrice() error9 = abs(cmsBondAssetSwapPrice1-cmsSpecializedBondAssetSwapPrice1) self.assertFalse(error9>tolerance, "wrong clean price for cmsbond:" + "\n generic bond's clean price: " + str(cmsBondAssetSwapPrice1) + "\n equivalent specialized cms rate bond's price: " + str(cmsSpecializedBondAssetSwapPrice1) + "\n error: " + str(error9) + "\n tolerance: " + str(tolerance)) cmsBondMktPrice1 = 87.02## market executable price as of 4th sept 2007 cmsBondASW1 = AssetSwap(payFixedRate, cmsBond1, cmsBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondASW1.setPricingEngine(swapEngine) cmsSpecializedBondASW1 = AssetSwap(payFixedRate, cmsSpecializedBond1, cmsBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsSpecializedBondASW1.setPricingEngine(swapEngine) cmsBondASWSpread1 = cmsBondASW1.fairSpread() cmsSpecializedBondASWSpread1 = cmsSpecializedBondASW1.fairSpread() error10 = abs(cmsBondASWSpread1-cmsSpecializedBondASWSpread1) self.assertFalse(error10>tolerance, "wrong asw spread for cm bond:" + "\n generic cms rate bond's asw spread: " + str(cmsBondASWSpread1) + "\n equivalent specialized bond's asw spread: " + str(cmsSpecializedBondASWSpread1) + "\n error: " + str(error10) + "\n tolerance: " + str(tolerance)) ##CMS bond (Isin: XS0218766664 ISPIM 0 5/6/15) ##maturity occurs on a business day cmsBondStartDate2 = Date(6,May,2005) cmsBondMaturityDate2 = Date(6,May,2015) cmsBondSchedule2 = Schedule(cmsBondStartDate2, cmsBondMaturityDate2, Period(Annual), bondCalendar, Unadjusted, Unadjusted, DateGeneration.Backward, False) cmsBondLeg2 = list(CmsLeg([self.faceAmount],cmsBondSchedule2, self.swapIndex, Thirty360(), Following, [fixingDays] , [0.84],[],[],[],inArrears)) cmsbondRedemption2 = bondCalendar.adjust(cmsBondMaturityDate2, Following) cmsBondLeg2.append(SimpleCashFlow(100.0, cmsbondRedemption2)) ## generic bond cmsBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, cmsBondMaturityDate2, cmsBondStartDate2, cmsBondLeg2) cmsBond2.setPricingEngine(bondEngine) ## equivalent specialized cms bond cmsSpecializedBond2 = CmsRateBond(settlementDays, self.faceAmount, cmsBondSchedule2, self.swapIndex, Thirty360(), Following, fixingDays, [0.84], [0.0], [], [], inArrears, 100.0, Date(6,May,2005)) cmsSpecializedBond2.setPricingEngine(bondEngine) setCouponPricer(cmsBond2.cashflows(), self.cmspricer) setCouponPricer(cmsSpecializedBond2.cashflows(), self.cmspricer) self.swapIndex.addFixing(Date(4,May,2006), 0.04217) cmsBondPrice2 = cmsBond2.cleanPrice() cmsSpecializedBondPrice2 = cmsSpecializedBond2.cleanPrice() cmsBondAssetSwap2 = AssetSwap(payFixedRate,cmsBond2, cmsBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondAssetSwap2.setPricingEngine(swapEngine) cmsSpecializedBondAssetSwap2 = AssetSwap(payFixedRate,cmsSpecializedBond2, cmsSpecializedBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsSpecializedBondAssetSwap2.setPricingEngine(swapEngine) cmsBondAssetSwapPrice2 = cmsBondAssetSwap2.fairCleanPrice() cmsSpecializedBondAssetSwapPrice2 = cmsSpecializedBondAssetSwap2.fairCleanPrice() error11 = abs(cmsBondAssetSwapPrice2-cmsSpecializedBondAssetSwapPrice2) self.assertFalse(error11>tolerance, "wrong clean price for cmsbond:" + "\n generic bond's clean price: " + str(cmsBondAssetSwapPrice2) + "\n equivalent specialized cms rate bond's price: " + str(cmsSpecializedBondAssetSwapPrice2) + "\n error: " + str(error11) + "\n tolerance: " + str(tolerance)) cmsBondMktPrice2 = 94.35## market executable price as of 4th sept 2007 cmsBondASW2 = AssetSwap(payFixedRate, cmsBond2, cmsBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsBondASW2.setPricingEngine(swapEngine) cmsSpecializedBondASW2 = AssetSwap(payFixedRate, cmsSpecializedBond2, cmsBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) cmsSpecializedBondASW2.setPricingEngine(swapEngine) cmsBondASWSpread2 = cmsBondASW2.fairSpread() cmsSpecializedBondASWSpread2 = cmsSpecializedBondASW2.fairSpread() error12 = abs(cmsBondASWSpread2-cmsSpecializedBondASWSpread2) self.assertFalse(error12>tolerance, "wrong asw spread for cm bond:" + "\n generic cms rate bond's asw spread: " + str(cmsBondASWSpread2) + "\n equivalent specialized bond's asw spread: " + str(cmsSpecializedBondASWSpread2) + "\n error: " + str(error12) + "\n tolerance: " + str(tolerance)) ## Zero-Coupon bond (Isin: DE0004771662 IBRD 0 12/20/15) ## maturity doesn't occur on a business day zeroCpnBondStartDate1 = Date(19,December,1985) zeroCpnBondMaturityDate1 = Date(20,December,2015) zeroCpnBondRedemption1 = bondCalendar.adjust(zeroCpnBondMaturityDate1, Following) zeroCpnBondLeg1 = Leg([SimpleCashFlow(100.0, zeroCpnBondRedemption1)]) ## generic bond zeroCpnBond1 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate1, zeroCpnBondStartDate1, zeroCpnBondLeg1) zeroCpnBond1.setPricingEngine(bondEngine) ## specialized zerocpn bond zeroCpnSpecializedBond1 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(20,December,2015), Following, 100.0, Date(19,December,1985)) zeroCpnSpecializedBond1.setPricingEngine(bondEngine) zeroCpnBondPrice1 = zeroCpnBond1.cleanPrice() zeroCpnSpecializedBondPrice1 = zeroCpnSpecializedBond1.cleanPrice() zeroCpnBondAssetSwap1 = AssetSwap(payFixedRate,zeroCpnBond1, zeroCpnBondPrice1, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondAssetSwap1.setPricingEngine(swapEngine) zeroCpnSpecializedBondAssetSwap1 = AssetSwap(payFixedRate, zeroCpnSpecializedBond1, zeroCpnSpecializedBondPrice1, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnSpecializedBondAssetSwap1.setPricingEngine(swapEngine) zeroCpnBondAssetSwapPrice1 = zeroCpnBondAssetSwap1.fairCleanPrice() zeroCpnSpecializedBondAssetSwapPrice1 = zeroCpnSpecializedBondAssetSwap1.fairCleanPrice() error13 = abs(zeroCpnBondAssetSwapPrice1-zeroCpnSpecializedBondAssetSwapPrice1) self.assertFalse(error13>tolerance, "wrong clean price for zerocpn bond:" + "\n generic zero cpn bond's clean price: " + str(zeroCpnBondAssetSwapPrice1) + "\n specialized equivalent bond's price: " + str(zeroCpnSpecializedBondAssetSwapPrice1) + "\n error: " + str(error13) + "\n tolerance: " + str(tolerance)) ## market executable price as of 4th sept 2007 zeroCpnBondMktPrice1 = 72.277 zeroCpnBondASW1 = AssetSwap(payFixedRate, zeroCpnBond1,zeroCpnBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondASW1.setPricingEngine(swapEngine) zeroCpnSpecializedBondASW1 = AssetSwap(payFixedRate, zeroCpnSpecializedBond1, zeroCpnBondMktPrice1, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnSpecializedBondASW1.setPricingEngine(swapEngine) zeroCpnBondASWSpread1 = zeroCpnBondASW1.fairSpread() zeroCpnSpecializedBondASWSpread1 = zeroCpnSpecializedBondASW1.fairSpread() error14 = abs(zeroCpnBondASWSpread1-zeroCpnSpecializedBondASWSpread1) self.assertFalse(error14>tolerance, "wrong asw spread for zeroCpn bond:" + "\n generic zeroCpn bond's asw spread: " + str(zeroCpnBondASWSpread1) + "\n equivalent specialized bond's asw spread: " + str(zeroCpnSpecializedBondASWSpread1) + "\n error: " + str(error14) + "\n tolerance: " + str(tolerance)) ## Zero Coupon bond (Isin: IT0001200390 ISPIM 0 02/17/28) ## maturity doesn't occur on a business day zeroCpnBondStartDate2 = Date(17,February,1998) zeroCpnBondMaturityDate2 = Date(17,February,2028) zerocpbondRedemption2 = bondCalendar.adjust(zeroCpnBondMaturityDate2, Following) zeroCpnBondLeg2 = Leg([SimpleCashFlow(100.0, zerocpbondRedemption2)]) ## generic bond zeroCpnBond2 = Bond(settlementDays, bondCalendar, self.faceAmount, zeroCpnBondMaturityDate2, zeroCpnBondStartDate2, zeroCpnBondLeg2) zeroCpnBond2.setPricingEngine(bondEngine) ## specialized zerocpn bond zeroCpnSpecializedBond2 = ZeroCouponBond(settlementDays, bondCalendar, self.faceAmount, Date(17,February,2028), Following, 100.0, Date(17,February,1998)) zeroCpnSpecializedBond2.setPricingEngine(bondEngine) zeroCpnBondPrice2 = zeroCpnBond2.cleanPrice() zeroCpnSpecializedBondPrice2 = zeroCpnSpecializedBond2.cleanPrice() zeroCpnBondAssetSwap2 = AssetSwap(payFixedRate,zeroCpnBond2, zeroCpnBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondAssetSwap2.setPricingEngine(swapEngine) zeroCpnSpecializedBondAssetSwap2 = AssetSwap(payFixedRate, zeroCpnSpecializedBond2, zeroCpnSpecializedBondPrice2, self.iborIndex, self.nonnullspread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnSpecializedBondAssetSwap2.setPricingEngine(swapEngine) zeroCpnBondAssetSwapPrice2 = zeroCpnBondAssetSwap2.fairCleanPrice() zeroCpnSpecializedBondAssetSwapPrice2 = zeroCpnSpecializedBondAssetSwap2.fairCleanPrice() error15 = abs(zeroCpnBondAssetSwapPrice2 -zeroCpnSpecializedBondAssetSwapPrice2) self.assertFalse(error8>tolerance, "wrong clean price for zerocpn bond:" + "\n generic zero cpn bond's clean price: " + str(zeroCpnBondAssetSwapPrice2) + "\n equivalent specialized bond's price: " + str(zeroCpnSpecializedBondAssetSwapPrice2) + "\n error: " + str(error15) + "\n tolerance: " + str(tolerance)) ## market executable price as of 4th sept 2007 zeroCpnBondMktPrice2 = 72.277 zeroCpnBondASW2 = AssetSwap(payFixedRate, zeroCpnBond2,zeroCpnBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnBondASW2.setPricingEngine(swapEngine) zeroCpnSpecializedBondASW2 = AssetSwap(payFixedRate, zeroCpnSpecializedBond2, zeroCpnBondMktPrice2, self.iborIndex, self.spread, Schedule(), self.iborIndex.dayCounter(), parAssetSwap) zeroCpnSpecializedBondASW2.setPricingEngine(swapEngine) zeroCpnBondASWSpread2 = zeroCpnBondASW2.fairSpread() zeroCpnSpecializedBondASWSpread2 = zeroCpnSpecializedBondASW2.fairSpread() error16 = abs(zeroCpnBondASWSpread2-zeroCpnSpecializedBondASWSpread2) self.assertFalse(error16>tolerance, "wrong asw spread for zeroCpn bond:" + "\n generic zeroCpn bond's asw spread: " + str(zeroCpnBondASWSpread2) + "\n equivalent specialized bond's asw spread: " + str(zeroCpnSpecializedBondASWSpread2) + "\n error: " + str(error16) + "\n tolerance: " + str(tolerance)) if __name__ == '__main__': print('testing QuantLib ' + QuantLib.__version__) suite = unittest.TestSuite() suite.addTest(unittest.makeSuite(AssetSwapTest,'test')) unittest.TextTestRunner(verbosity=2).run(suite)

54.543071

141

0.555607

12,830

189,319

8.197584

0.050585

0.027316

0.013596

0.023009

0.871367

0.853996

0.850269

0.847511

0.830425

0.805809

0

0.049868

0.367961

189,319

3,470

142

54.55879

0.829103

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py

Python

gcpflask/__init__.py

stanford-rc/gcp-flask-stanford

d0da1b5650792582ada90fac63796ee974805c17

[ "MIT" ]

3

2020-07-28T21:23:29.000Z

2021-07-14T17:37:02.000Z

gcpflask/__init__.py

stanford-rc/gcp-flask-stanford

d0da1b5650792582ada90fac63796ee974805c17

[ "MIT" ]

2

2020-07-22T22:07:43.000Z

2020-07-24T20:22:56.000Z

gcpflask/__init__.py

stanford-rc/gcp-flask-stanford

d0da1b5650792582ada90fac63796ee974805c17

[ "MIT" ]

null

from .server import app from . import views def create_app(): return app

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7

19b6dc4078ff33196d5b3c05c80c71222dd134e9

168

py

Python

products/permissions/products.py

julianarchila/ecommerce-django-api

d0665745c2a16dc8bc1acb54ead66f69da129271

[ "MIT" ]

null

products/permissions/products.py

julianarchila/ecommerce-django-api

d0665745c2a16dc8bc1acb54ead66f69da129271

[ "MIT" ]

null

products/permissions/products.py

julianarchila/ecommerce-django-api

d0665745c2a16dc8bc1acb54ead66f69da129271

[ "MIT" ]

null

""" Products custom permissions. """ # Django REST Framework from rest_framework.permissions import BasePermission from rest_framework.permissions import IsAdminUser

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dfae4a6cbae09fe6416854ab5aa68fe8b6ba6329

168,585

py

Python

pyboto3/opsworks.py

thecraftman/pyboto3

653a0db2b00b06708334431da8f169d1f7c7734f

[ "MIT" ]

null

pyboto3/opsworks.py

thecraftman/pyboto3

653a0db2b00b06708334431da8f169d1f7c7734f

[ "MIT" ]

null

pyboto3/opsworks.py

thecraftman/pyboto3

653a0db2b00b06708334431da8f169d1f7c7734f

[ "MIT" ]

null

''' The MIT License (MIT) Copyright (c) 2016 WavyCloud 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. ''' def assign_instance(InstanceId=None, LayerIds=None): """ Assign a registered instance to a layer. See also: AWS API Documentation :example: response = client.assign_instance( InstanceId='string', LayerIds=[ 'string', ] ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. :type LayerIds: list :param LayerIds: [REQUIRED] The layer ID, which must correspond to a custom layer. You cannot assign a registered instance to a built-in layer. (string) -- :returns: InstanceId (string) -- [REQUIRED] The instance ID. LayerIds (list) -- [REQUIRED] The layer ID, which must correspond to a custom layer. You cannot assign a registered instance to a built-in layer. (string) -- """ pass def assign_volume(VolumeId=None, InstanceId=None): """ Assigns one of the stack's registered Amazon EBS volumes to a specified instance. The volume must first be registered with the stack by calling RegisterVolume . After you register the volume, you must call UpdateVolume to specify a mount point before calling AssignVolume . For more information, see Resource Management . See also: AWS API Documentation :example: response = client.assign_volume( VolumeId='string', InstanceId='string' ) :type VolumeId: string :param VolumeId: [REQUIRED] The volume ID. :type InstanceId: string :param InstanceId: The instance ID. """ pass def associate_elastic_ip(ElasticIp=None, InstanceId=None): """ Associates one of the stack's registered Elastic IP addresses with a specified instance. The address must first be registered with the stack by calling RegisterElasticIp . For more information, see Resource Management . See also: AWS API Documentation :example: response = client.associate_elastic_ip( ElasticIp='string', InstanceId='string' ) :type ElasticIp: string :param ElasticIp: [REQUIRED] The Elastic IP address. :type InstanceId: string :param InstanceId: The instance ID. """ pass def attach_elastic_load_balancer(ElasticLoadBalancerName=None, LayerId=None): """ Attaches an Elastic Load Balancing load balancer to a specified layer. For more information, see Elastic Load Balancing . See also: AWS API Documentation :example: response = client.attach_elastic_load_balancer( ElasticLoadBalancerName='string', LayerId='string' ) :type ElasticLoadBalancerName: string :param ElasticLoadBalancerName: [REQUIRED] The Elastic Load Balancing instance's name. :type LayerId: string :param LayerId: [REQUIRED] The ID of the layer that the Elastic Load Balancing instance is to be attached to. """ pass def can_paginate(operation_name=None): """ Check if an operation can be paginated. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator('create_foo'). """ pass def clone_stack(SourceStackId=None, Name=None, Region=None, VpcId=None, Attributes=None, ServiceRoleArn=None, DefaultInstanceProfileArn=None, DefaultOs=None, HostnameTheme=None, DefaultAvailabilityZone=None, DefaultSubnetId=None, CustomJson=None, ConfigurationManager=None, ChefConfiguration=None, UseCustomCookbooks=None, UseOpsworksSecurityGroups=None, CustomCookbooksSource=None, DefaultSshKeyName=None, ClonePermissions=None, CloneAppIds=None, DefaultRootDeviceType=None, AgentVersion=None): """ Creates a clone of a specified stack. For more information, see Clone a Stack . By default, all parameters are set to the values used by the parent stack. See also: AWS API Documentation :example: response = client.clone_stack( SourceStackId='string', Name='string', Region='string', VpcId='string', Attributes={ 'string': 'string' }, ServiceRoleArn='string', DefaultInstanceProfileArn='string', DefaultOs='string', HostnameTheme='string', DefaultAvailabilityZone='string', DefaultSubnetId='string', CustomJson='string', ConfigurationManager={ 'Name': 'string', 'Version': 'string' }, ChefConfiguration={ 'ManageBerkshelf': True|False, 'BerkshelfVersion': 'string' }, UseCustomCookbooks=True|False, UseOpsworksSecurityGroups=True|False, CustomCookbooksSource={ 'Type': 'git'|'svn'|'archive'|'s3', 'Url': 'string', 'Username': 'string', 'Password': 'string', 'SshKey': 'string', 'Revision': 'string' }, DefaultSshKeyName='string', ClonePermissions=True|False, CloneAppIds=[ 'string', ], DefaultRootDeviceType='ebs'|'instance-store', AgentVersion='string' ) :type SourceStackId: string :param SourceStackId: [REQUIRED] The source stack ID. :type Name: string :param Name: The cloned stack name. :type Region: string :param Region: The cloned stack AWS region, such as 'ap-northeast-2'. For more information about AWS regions, see Regions and Endpoints . :type VpcId: string :param VpcId: The ID of the VPC that the cloned stack is to be launched into. It must be in the specified region. All instances are launched into this VPC, and you cannot change the ID later. If your account supports EC2 Classic, the default value is no VPC. If your account does not support EC2 Classic, the default value is the default VPC for the specified region. If the VPC ID corresponds to a default VPC and you have specified either the DefaultAvailabilityZone or the DefaultSubnetId parameter only, AWS OpsWorks Stacks infers the value of the other parameter. If you specify neither parameter, AWS OpsWorks Stacks sets these parameters to the first valid Availability Zone for the specified region and the corresponding default VPC subnet ID, respectively. If you specify a nondefault VPC ID, note the following: It must belong to a VPC in your account that is in the specified region. You must specify a value for DefaultSubnetId . For more information on how to use AWS OpsWorks Stacks with a VPC, see Running a Stack in a VPC . For more information on default VPC and EC2 Classic, see Supported Platforms . :type Attributes: dict :param Attributes: A list of stack attributes and values as key/value pairs to be added to the cloned stack. (string) -- (string) -- :type ServiceRoleArn: string :param ServiceRoleArn: [REQUIRED] The stack AWS Identity and Access Management (IAM) role, which allows AWS OpsWorks Stacks to work with AWS resources on your behalf. You must set this parameter to the Amazon Resource Name (ARN) for an existing IAM role. If you create a stack by using the AWS OpsWorks Stacks console, it creates the role for you. You can obtain an existing stack's IAM ARN programmatically by calling DescribePermissions . For more information about IAM ARNs, see Using Identifiers . Note You must set this parameter to a valid service role ARN or the action will fail; there is no default value. You can specify the source stack's service role ARN, if you prefer, but you must do so explicitly. :type DefaultInstanceProfileArn: string :param DefaultInstanceProfileArn: The Amazon Resource Name (ARN) of an IAM profile that is the default profile for all of the stack's EC2 instances. For more information about IAM ARNs, see Using Identifiers . :type DefaultOs: string :param DefaultOs: The stack's operating system, which must be set to one of the following. A supported Linux operating system: An Amazon Linux version, such as Amazon Linux 2016.09 , Amazon Linux 2016.03 , Amazon Linux 2015.09 , or Amazon Linux 2015.03 . A supported Ubuntu operating system, such as Ubuntu 16.04 LTS , Ubuntu 14.04 LTS , or Ubuntu 12.04 LTS . CentOS Linux 7 Red Hat Enterprise Linux 7 Microsoft Windows Server 2012 R2 Base , Microsoft Windows Server 2012 R2 with SQL Server Express , Microsoft Windows Server 2012 R2 with SQL Server Standard , or Microsoft Windows Server 2012 R2 with SQL Server Web . A custom AMI: Custom . You specify the custom AMI you want to use when you create instances. For more information on how to use custom AMIs with OpsWorks, see Using Custom AMIs . The default option is the parent stack's operating system. For more information on the supported operating systems, see AWS OpsWorks Stacks Operating Systems . Note You can specify a different Linux operating system for the cloned stack, but you cannot change from Linux to Windows or Windows to Linux. :type HostnameTheme: string :param HostnameTheme: The stack's host name theme, with spaces are replaced by underscores. The theme is used to generate host names for the stack's instances. By default, HostnameTheme is set to Layer_Dependent , which creates host names by appending integers to the layer's short name. The other themes are: Baked_Goods Clouds Europe_Cities Fruits Greek_Deities Legendary_creatures_from_Japan Planets_and_Moons Roman_Deities Scottish_Islands US_Cities Wild_Cats To obtain a generated host name, call GetHostNameSuggestion , which returns a host name based on the current theme. :type DefaultAvailabilityZone: string :param DefaultAvailabilityZone: The cloned stack's default Availability Zone, which must be in the specified region. For more information, see Regions and Endpoints . If you also specify a value for DefaultSubnetId , the subnet must be in the same zone. For more information, see the VpcId parameter description. :type DefaultSubnetId: string :param DefaultSubnetId: The stack's default VPC subnet ID. This parameter is required if you specify a value for the VpcId parameter. All instances are launched into this subnet unless you specify otherwise when you create the instance. If you also specify a value for DefaultAvailabilityZone , the subnet must be in that zone. For information on default values and when this parameter is required, see the VpcId parameter description. :type CustomJson: string :param CustomJson: A string that contains user-defined, custom JSON. It is used to override the corresponding default stack configuration JSON values. The string should be in the following format: '{\'key1\': \'value1\', \'key2\': \'value2\',...}' For more information on custom JSON, see Use Custom JSON to Modify the Stack Configuration Attributes :type ConfigurationManager: dict :param ConfigurationManager: The configuration manager. When you clone a stack we recommend that you use the configuration manager to specify the Chef version: 12, 11.10, or 11.4 for Linux stacks, or 12.2 for Windows stacks. The default value for Linux stacks is currently 12. Name (string) --The name. This parameter must be set to 'Chef'. Version (string) --The Chef version. This parameter must be set to 12, 11.10, or 11.4 for Linux stacks, and to 12.2 for Windows stacks. The default value for Linux stacks is 11.4. :type ChefConfiguration: dict :param ChefConfiguration: A ChefConfiguration object that specifies whether to enable Berkshelf and the Berkshelf version on Chef 11.10 stacks. For more information, see Create a New Stack . ManageBerkshelf (boolean) --Whether to enable Berkshelf. BerkshelfVersion (string) --The Berkshelf version. :type UseCustomCookbooks: boolean :param UseCustomCookbooks: Whether to use custom cookbooks. :type UseOpsworksSecurityGroups: boolean :param UseOpsworksSecurityGroups: Whether to associate the AWS OpsWorks Stacks built-in security groups with the stack's layers. AWS OpsWorks Stacks provides a standard set of built-in security groups, one for each layer, which are associated with layers by default. With UseOpsworksSecurityGroups you can instead provide your own custom security groups. UseOpsworksSecurityGroups has the following settings: True - AWS OpsWorks Stacks automatically associates the appropriate built-in security group with each layer (default setting). You can associate additional security groups with a layer after you create it but you cannot delete the built-in security group. False - AWS OpsWorks Stacks does not associate built-in security groups with layers. You must create appropriate Amazon Elastic Compute Cloud (Amazon EC2) security groups and associate a security group with each layer that you create. However, you can still manually associate a built-in security group with a layer on creation; custom security groups are required only for those layers that need custom settings. For more information, see Create a New Stack . :type CustomCookbooksSource: dict :param CustomCookbooksSource: Contains the information required to retrieve an app or cookbook from a repository. For more information, see Creating Apps or Custom Recipes and Cookbooks . Type (string) --The repository type. Url (string) --The source URL. Username (string) --This parameter depends on the repository type. For Amazon S3 bundles, set Username to the appropriate IAM access key ID. For HTTP bundles, Git repositories, and Subversion repositories, set Username to the user name. Password (string) --When included in a request, the parameter depends on the repository type. For Amazon S3 bundles, set Password to the appropriate IAM secret access key. For HTTP bundles and Subversion repositories, set Password to the password. For more information on how to safely handle IAM credentials, see http://docs.aws.amazon.com/general/latest/gr/aws-access-keys-best-practices.html . In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. SshKey (string) --In requests, the repository's SSH key. In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. Revision (string) --The application's version. AWS OpsWorks Stacks enables you to easily deploy new versions of an application. One of the simplest approaches is to have branches or revisions in your repository that represent different versions that can potentially be deployed. :type DefaultSshKeyName: string :param DefaultSshKeyName: A default Amazon EC2 key pair name. The default value is none. If you specify a key pair name, AWS OpsWorks installs the public key on the instance and you can use the private key with an SSH client to log in to the instance. For more information, see Using SSH to Communicate with an Instance and Managing SSH Access . You can override this setting by specifying a different key pair, or no key pair, when you create an instance . :type ClonePermissions: boolean :param ClonePermissions: Whether to clone the source stack's permissions. :type CloneAppIds: list :param CloneAppIds: A list of source stack app IDs to be included in the cloned stack. (string) -- :type DefaultRootDeviceType: string :param DefaultRootDeviceType: The default root device type. This value is used by default for all instances in the cloned stack, but you can override it when you create an instance. For more information, see Storage for the Root Device . :type AgentVersion: string :param AgentVersion: The default AWS OpsWorks Stacks agent version. You have the following options: Auto-update - Set this parameter to LATEST . AWS OpsWorks Stacks automatically installs new agent versions on the stack's instances as soon as they are available. Fixed version - Set this parameter to your preferred agent version. To update the agent version, you must edit the stack configuration and specify a new version. AWS OpsWorks Stacks then automatically installs that version on the stack's instances. The default setting is LATEST . To specify an agent version, you must use the complete version number, not the abbreviated number shown on the console. For a list of available agent version numbers, call DescribeAgentVersions . AgentVersion cannot be set to Chef 12.2. Note You can also specify an agent version when you create or update an instance, which overrides the stack's default setting. :rtype: dict :return: { 'StackId': 'string' } """ pass def create_app(StackId=None, Shortname=None, Name=None, Description=None, DataSources=None, Type=None, AppSource=None, Domains=None, EnableSsl=None, SslConfiguration=None, Attributes=None, Environment=None): """ Creates an app for a specified stack. For more information, see Creating Apps . See also: AWS API Documentation :example: response = client.create_app( StackId='string', Shortname='string', Name='string', Description='string', DataSources=[ { 'Type': 'string', 'Arn': 'string', 'DatabaseName': 'string' }, ], Type='aws-flow-ruby'|'java'|'rails'|'php'|'nodejs'|'static'|'other', AppSource={ 'Type': 'git'|'svn'|'archive'|'s3', 'Url': 'string', 'Username': 'string', 'Password': 'string', 'SshKey': 'string', 'Revision': 'string' }, Domains=[ 'string', ], EnableSsl=True|False, SslConfiguration={ 'Certificate': 'string', 'PrivateKey': 'string', 'Chain': 'string' }, Attributes={ 'string': 'string' }, Environment=[ { 'Key': 'string', 'Value': 'string', 'Secure': True|False }, ] ) :type StackId: string :param StackId: [REQUIRED] The stack ID. :type Shortname: string :param Shortname: The app's short name. :type Name: string :param Name: [REQUIRED] The app name. :type Description: string :param Description: A description of the app. :type DataSources: list :param DataSources: The app's data source. (dict) --Describes an app's data source. Type (string) --The data source's type, AutoSelectOpsworksMysqlInstance , OpsworksMysqlInstance , or RdsDbInstance . Arn (string) --The data source's ARN. DatabaseName (string) --The database name. :type Type: string :param Type: [REQUIRED] The app type. Each supported type is associated with a particular layer. For example, PHP applications are associated with a PHP layer. AWS OpsWorks Stacks deploys an application to those instances that are members of the corresponding layer. If your app isn't one of the standard types, or you prefer to implement your own Deploy recipes, specify other . :type AppSource: dict :param AppSource: A Source object that specifies the app repository. Type (string) --The repository type. Url (string) --The source URL. Username (string) --This parameter depends on the repository type. For Amazon S3 bundles, set Username to the appropriate IAM access key ID. For HTTP bundles, Git repositories, and Subversion repositories, set Username to the user name. Password (string) --When included in a request, the parameter depends on the repository type. For Amazon S3 bundles, set Password to the appropriate IAM secret access key. For HTTP bundles and Subversion repositories, set Password to the password. For more information on how to safely handle IAM credentials, see http://docs.aws.amazon.com/general/latest/gr/aws-access-keys-best-practices.html . In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. SshKey (string) --In requests, the repository's SSH key. In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. Revision (string) --The application's version. AWS OpsWorks Stacks enables you to easily deploy new versions of an application. One of the simplest approaches is to have branches or revisions in your repository that represent different versions that can potentially be deployed. :type Domains: list :param Domains: The app virtual host settings, with multiple domains separated by commas. For example: 'www.example.com, example.com' (string) -- :type EnableSsl: boolean :param EnableSsl: Whether to enable SSL for the app. :type SslConfiguration: dict :param SslConfiguration: An SslConfiguration object with the SSL configuration. Certificate (string) -- [REQUIRED]The contents of the certificate's domain.crt file. PrivateKey (string) -- [REQUIRED]The private key; the contents of the certificate's domain.kex file. Chain (string) --Optional. Can be used to specify an intermediate certificate authority key or client authentication. :type Attributes: dict :param Attributes: One or more user-defined key/value pairs to be added to the stack attributes. (string) -- (string) -- :type Environment: list :param Environment: An array of EnvironmentVariable objects that specify environment variables to be associated with the app. After you deploy the app, these variables are defined on the associated app server instance. For more information, see Environment Variables . There is no specific limit on the number of environment variables. However, the size of the associated data structure - which includes the variables' names, values, and protected flag values - cannot exceed 10 KB (10240 Bytes). This limit should accommodate most if not all use cases. Exceeding it will cause an exception with the message, 'Environment: is too large (maximum is 10KB).' Note This parameter is supported only by Chef 11.10 stacks. If you have specified one or more environment variables, you cannot modify the stack's Chef version. (dict) --Represents an app's environment variable. Key (string) -- [REQUIRED](Required) The environment variable's name, which can consist of up to 64 characters and must be specified. The name can contain upper- and lowercase letters, numbers, and underscores (_), but it must start with a letter or underscore. Value (string) -- [REQUIRED](Optional) The environment variable's value, which can be left empty. If you specify a value, it can contain up to 256 characters, which must all be printable. Secure (boolean) --(Optional) Whether the variable's value will be returned by the DescribeApps action. To conceal an environment variable's value, set Secure to true . DescribeApps then returns *****FILTERED***** instead of the actual value. The default value for Secure is false . :rtype: dict :return: { 'AppId': 'string' } """ pass def create_deployment(StackId=None, AppId=None, InstanceIds=None, LayerIds=None, Command=None, Comment=None, CustomJson=None): """ Runs deployment or stack commands. For more information, see Deploying Apps and Run Stack Commands . See also: AWS API Documentation :example: response = client.create_deployment( StackId='string', AppId='string', InstanceIds=[ 'string', ], LayerIds=[ 'string', ], Command={ 'Name': 'install_dependencies'|'update_dependencies'|'update_custom_cookbooks'|'execute_recipes'|'configure'|'setup'|'deploy'|'rollback'|'start'|'stop'|'restart'|'undeploy', 'Args': { 'string': [ 'string', ] } }, Comment='string', CustomJson='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. :type AppId: string :param AppId: The app ID. This parameter is required for app deployments, but not for other deployment commands. :type InstanceIds: list :param InstanceIds: The instance IDs for the deployment targets. (string) -- :type LayerIds: list :param LayerIds: The layer IDs for the deployment targets. (string) -- :type Command: dict :param Command: [REQUIRED] A DeploymentCommand object that specifies the deployment command and any associated arguments. Name (string) -- [REQUIRED]Specifies the operation. You can specify only one command. For stacks, the following commands are available: execute_recipes : Execute one or more recipes. To specify the recipes, set an Args parameter named recipes to the list of recipes to be executed. For example, to execute phpapp::appsetup , set Args to {'recipes':['phpapp::appsetup']} . install_dependencies : Install the stack's dependencies. update_custom_cookbooks : Update the stack's custom cookbooks. update_dependencies : Update the stack's dependencies. Note The update_dependencies and install_dependencies commands are supported only for Linux instances. You can run the commands successfully on Windows instances, but they do nothing. For apps, the following commands are available: deploy : Deploy an app. Ruby on Rails apps have an optional Args parameter named migrate . Set Args to {'migrate':['true']} to migrate the database. The default setting is {'migrate':['false']}. rollback Roll the app back to the previous version. When you update an app, AWS OpsWorks Stacks stores the previous version, up to a maximum of five versions. You can use this command to roll an app back as many as four versions. start : Start the app's web or application server. stop : Stop the app's web or application server. restart : Restart the app's web or application server. undeploy : Undeploy the app. Args (dict) --The arguments of those commands that take arguments. It should be set to a JSON object with the following format: {'arg_name1' : ['value1', 'value2', ...], 'arg_name2' : ['value1', 'value2', ...], ...} The update_dependencies command takes two arguments: upgrade_os_to - Specifies the desired Amazon Linux version for instances whose OS you want to upgrade, such as Amazon Linux 2014.09 . You must also set the allow_reboot argument to true. allow_reboot - Specifies whether to allow AWS OpsWorks Stacks to reboot the instances if necessary, after installing the updates. This argument can be set to either true or false . The default value is false . For example, to upgrade an instance to Amazon Linux 2014.09, set Args to the following. { 'upgrade_os_to':['Amazon Linux 2014.09'], 'allow_reboot':['true'] } (string) -- (list) -- (string) -- :type Comment: string :param Comment: A user-defined comment. :type CustomJson: string :param CustomJson: A string that contains user-defined, custom JSON. It is used to override the corresponding default stack configuration JSON values. The string should be in the following format: '{\'key1\': \'value1\', \'key2\': \'value2\',...}' For more information on custom JSON, see Use Custom JSON to Modify the Stack Configuration Attributes . :rtype: dict :return: { 'DeploymentId': 'string' } """ pass def create_instance(StackId=None, LayerIds=None, InstanceType=None, AutoScalingType=None, Hostname=None, Os=None, AmiId=None, SshKeyName=None, AvailabilityZone=None, VirtualizationType=None, SubnetId=None, Architecture=None, RootDeviceType=None, BlockDeviceMappings=None, InstallUpdatesOnBoot=None, EbsOptimized=None, AgentVersion=None, Tenancy=None): """ Creates an instance in a specified stack. For more information, see Adding an Instance to a Layer . See also: AWS API Documentation :example: response = client.create_instance( StackId='string', LayerIds=[ 'string', ], InstanceType='string', AutoScalingType='load'|'timer', Hostname='string', Os='string', AmiId='string', SshKeyName='string', AvailabilityZone='string', VirtualizationType='string', SubnetId='string', Architecture='x86_64'|'i386', RootDeviceType='ebs'|'instance-store', BlockDeviceMappings=[ { 'DeviceName': 'string', 'NoDevice': 'string', 'VirtualName': 'string', 'Ebs': { 'SnapshotId': 'string', 'Iops': 123, 'VolumeSize': 123, 'VolumeType': 'gp2'|'io1'|'standard', 'DeleteOnTermination': True|False } }, ], InstallUpdatesOnBoot=True|False, EbsOptimized=True|False, AgentVersion='string', Tenancy='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. :type LayerIds: list :param LayerIds: [REQUIRED] An array that contains the instance's layer IDs. (string) -- :type InstanceType: string :param InstanceType: [REQUIRED] The instance type, such as t2.micro . For a list of supported instance types, open the stack in the console, choose Instances , and choose + Instance . The Size list contains the currently supported types. For more information, see Instance Families and Types . The parameter values that you use to specify the various types are in the API Name column of the Available Instance Types table. :type AutoScalingType: string :param AutoScalingType: For load-based or time-based instances, the type. Windows stacks can use only time-based instances. :type Hostname: string :param Hostname: The instance host name. :type Os: string :param Os: The instance's operating system, which must be set to one of the following. A supported Linux operating system: An Amazon Linux version, such as Amazon Linux 2016.09 , Amazon Linux 2016.03 , Amazon Linux 2015.09 , or Amazon Linux 2015.03 . A supported Ubuntu operating system, such as Ubuntu 16.04 LTS , Ubuntu 14.04 LTS , or Ubuntu 12.04 LTS . CentOS Linux 7 Red Hat Enterprise Linux 7 A supported Windows operating system, such as Microsoft Windows Server 2012 R2 Base , Microsoft Windows Server 2012 R2 with SQL Server Express , Microsoft Windows Server 2012 R2 with SQL Server Standard , or Microsoft Windows Server 2012 R2 with SQL Server Web . A custom AMI: Custom . For more information on the supported operating systems, see AWS OpsWorks Stacks Operating Systems . The default option is the current Amazon Linux version. If you set this parameter to Custom , you must use the CreateInstance action's AmiId parameter to specify the custom AMI that you want to use. Block device mappings are not supported if the value is Custom . For more information on the supported operating systems, see Operating Systems For more information on how to use custom AMIs with AWS OpsWorks Stacks, see Using Custom AMIs . :type AmiId: string :param AmiId: A custom AMI ID to be used to create the instance. The AMI should be based on one of the supported operating systems. For more information, see Using Custom AMIs . Note If you specify a custom AMI, you must set Os to Custom . :type SshKeyName: string :param SshKeyName: The instance's Amazon EC2 key-pair name. :type AvailabilityZone: string :param AvailabilityZone: The instance Availability Zone. For more information, see Regions and Endpoints . :type VirtualizationType: string :param VirtualizationType: The instance's virtualization type, paravirtual or hvm . :type SubnetId: string :param SubnetId: The ID of the instance's subnet. If the stack is running in a VPC, you can use this parameter to override the stack's default subnet ID value and direct AWS OpsWorks Stacks to launch the instance in a different subnet. :type Architecture: string :param Architecture: The instance architecture. The default option is x86_64 . Instance types do not necessarily support both architectures. For a list of the architectures that are supported by the different instance types, see Instance Families and Types . :type RootDeviceType: string :param RootDeviceType: The instance root device type. For more information, see Storage for the Root Device . :type BlockDeviceMappings: list :param BlockDeviceMappings: An array of BlockDeviceMapping objects that specify the instance's block devices. For more information, see Block Device Mapping . Note that block device mappings are not supported for custom AMIs. (dict) --Describes a block device mapping. This data type maps directly to the Amazon EC2 BlockDeviceMapping data type. DeviceName (string) --The device name that is exposed to the instance, such as /dev/sdh . For the root device, you can use the explicit device name or you can set this parameter to ROOT_DEVICE and AWS OpsWorks Stacks will provide the correct device name. NoDevice (string) --Suppresses the specified device included in the AMI's block device mapping. VirtualName (string) --The virtual device name. For more information, see BlockDeviceMapping . Ebs (dict) --An EBSBlockDevice that defines how to configure an Amazon EBS volume when the instance is launched. SnapshotId (string) --The snapshot ID. Iops (integer) --The number of I/O operations per second (IOPS) that the volume supports. For more information, see EbsBlockDevice . VolumeSize (integer) --The volume size, in GiB. For more information, see EbsBlockDevice . VolumeType (string) --The volume type. gp2 for General Purpose (SSD) volumes, io1 for Provisioned IOPS (SSD) volumes, and standard for Magnetic volumes. DeleteOnTermination (boolean) --Whether the volume is deleted on instance termination. :type InstallUpdatesOnBoot: boolean :param InstallUpdatesOnBoot: Whether to install operating system and package updates when the instance boots. The default value is true . To control when updates are installed, set this value to false . You must then update your instances manually by using CreateDeployment to run the update_dependencies stack command or by manually running yum (Amazon Linux) or apt-get (Ubuntu) on the instances. Note We strongly recommend using the default value of true to ensure that your instances have the latest security updates. :type EbsOptimized: boolean :param EbsOptimized: Whether to create an Amazon EBS-optimized instance. :type AgentVersion: string :param AgentVersion: The default AWS OpsWorks Stacks agent version. You have the following options: INHERIT - Use the stack's default agent version setting. version_number - Use the specified agent version. This value overrides the stack's default setting. To update the agent version, edit the instance configuration and specify a new version. AWS OpsWorks Stacks then automatically installs that version on the instance. The default setting is INHERIT . To specify an agent version, you must use the complete version number, not the abbreviated number shown on the console. For a list of available agent version numbers, call DescribeAgentVersions . AgentVersion cannot be set to Chef 12.2. :type Tenancy: string :param Tenancy: The instance's tenancy option. The default option is no tenancy, or if the instance is running in a VPC, inherit tenancy settings from the VPC. The following are valid values for this parameter: dedicated , default , or host . Because there are costs associated with changes in tenancy options, we recommend that you research tenancy options before choosing them for your instances. For more information about dedicated hosts, see Dedicated Hosts Overview and Amazon EC2 Dedicated Hosts . For more information about dedicated instances, see Dedicated Instances and Amazon EC2 Dedicated Instances . :rtype: dict :return: { 'InstanceId': 'string' } """ pass def create_layer(StackId=None, Type=None, Name=None, Shortname=None, Attributes=None, CloudWatchLogsConfiguration=None, CustomInstanceProfileArn=None, CustomJson=None, CustomSecurityGroupIds=None, Packages=None, VolumeConfigurations=None, EnableAutoHealing=None, AutoAssignElasticIps=None, AutoAssignPublicIps=None, CustomRecipes=None, InstallUpdatesOnBoot=None, UseEbsOptimizedInstances=None, LifecycleEventConfiguration=None): """ Creates a layer. For more information, see How to Create a Layer . See also: AWS API Documentation :example: response = client.create_layer( StackId='string', Type='aws-flow-ruby'|'ecs-cluster'|'java-app'|'lb'|'web'|'php-app'|'rails-app'|'nodejs-app'|'memcached'|'db-master'|'monitoring-master'|'custom', Name='string', Shortname='string', Attributes={ 'string': 'string' }, CloudWatchLogsConfiguration={ 'Enabled': True|False, 'LogStreams': [ { 'LogGroupName': 'string', 'DatetimeFormat': 'string', 'TimeZone': 'LOCAL'|'UTC', 'File': 'string', 'FileFingerprintLines': 'string', 'MultiLineStartPattern': 'string', 'InitialPosition': 'start_of_file'|'end_of_file', 'Encoding': 'ascii'|'big5'|'big5hkscs'|'cp037'|'cp424'|'cp437'|'cp500'|'cp720'|'cp737'|'cp775'|'cp850'|'cp852'|'cp855'|'cp856'|'cp857'|'cp858'|'cp860'|'cp861'|'cp862'|'cp863'|'cp864'|'cp865'|'cp866'|'cp869'|'cp874'|'cp875'|'cp932'|'cp949'|'cp950'|'cp1006'|'cp1026'|'cp1140'|'cp1250'|'cp1251'|'cp1252'|'cp1253'|'cp1254'|'cp1255'|'cp1256'|'cp1257'|'cp1258'|'euc_jp'|'euc_jis_2004'|'euc_jisx0213'|'euc_kr'|'gb2312'|'gbk'|'gb18030'|'hz'|'iso2022_jp'|'iso2022_jp_1'|'iso2022_jp_2'|'iso2022_jp_2004'|'iso2022_jp_3'|'iso2022_jp_ext'|'iso2022_kr'|'latin_1'|'iso8859_2'|'iso8859_3'|'iso8859_4'|'iso8859_5'|'iso8859_6'|'iso8859_7'|'iso8859_8'|'iso8859_9'|'iso8859_10'|'iso8859_13'|'iso8859_14'|'iso8859_15'|'iso8859_16'|'johab'|'koi8_r'|'koi8_u'|'mac_cyrillic'|'mac_greek'|'mac_iceland'|'mac_latin2'|'mac_roman'|'mac_turkish'|'ptcp154'|'shift_jis'|'shift_jis_2004'|'shift_jisx0213'|'utf_32'|'utf_32_be'|'utf_32_le'|'utf_16'|'utf_16_be'|'utf_16_le'|'utf_7'|'utf_8'|'utf_8_sig', 'BufferDuration': 123, 'BatchCount': 123, 'BatchSize': 123 }, ] }, CustomInstanceProfileArn='string', CustomJson='string', CustomSecurityGroupIds=[ 'string', ], Packages=[ 'string', ], VolumeConfigurations=[ { 'MountPoint': 'string', 'RaidLevel': 123, 'NumberOfDisks': 123, 'Size': 123, 'VolumeType': 'string', 'Iops': 123 }, ], EnableAutoHealing=True|False, AutoAssignElasticIps=True|False, AutoAssignPublicIps=True|False, CustomRecipes={ 'Setup': [ 'string', ], 'Configure': [ 'string', ], 'Deploy': [ 'string', ], 'Undeploy': [ 'string', ], 'Shutdown': [ 'string', ] }, InstallUpdatesOnBoot=True|False, UseEbsOptimizedInstances=True|False, LifecycleEventConfiguration={ 'Shutdown': { 'ExecutionTimeout': 123, 'DelayUntilElbConnectionsDrained': True|False } } ) :type StackId: string :param StackId: [REQUIRED] The layer stack ID. :type Type: string :param Type: [REQUIRED] The layer type. A stack cannot have more than one built-in layer of the same type. It can have any number of custom layers. Built-in layers are not available in Chef 12 stacks. :type Name: string :param Name: [REQUIRED] The layer name, which is used by the console. :type Shortname: string :param Shortname: [REQUIRED] For custom layers only, use this parameter to specify the layer's short name, which is used internally by AWS OpsWorks Stacks and by Chef recipes. The short name is also used as the name for the directory where your app files are installed. It can have a maximum of 200 characters, which are limited to the alphanumeric characters, '-', '_', and '.'. The built-in layers' short names are defined by AWS OpsWorks Stacks. For more information, see the Layer Reference . :type Attributes: dict :param Attributes: One or more user-defined key-value pairs to be added to the stack attributes. To create a cluster layer, set the EcsClusterArn attribute to the cluster's ARN. (string) -- (string) -- :type CloudWatchLogsConfiguration: dict :param CloudWatchLogsConfiguration: Specifies CloudWatch Logs configuration options for the layer. For more information, see CloudWatchLogsLogStream . Enabled (boolean) --Whether CloudWatch Logs is enabled for a layer. LogStreams (list) --A list of configuration options for CloudWatch Logs. (dict) --Describes the Amazon CloudWatch logs configuration for a layer. For detailed information about members of this data type, see the CloudWatch Logs Agent Reference . LogGroupName (string) --Specifies the destination log group. A log group is created automatically if it doesn't already exist. Log group names can be between 1 and 512 characters long. Allowed characters include a-z, A-Z, 0-9, '_' (underscore), '-' (hyphen), '/' (forward slash), and '.' (period). DatetimeFormat (string) --Specifies how the time stamp is extracted from logs. For more information, see the CloudWatch Logs Agent Reference . TimeZone (string) --Specifies the time zone of log event time stamps. File (string) --Specifies log files that you want to push to CloudWatch Logs. File can point to a specific file or multiple files (by using wild card characters such as /var/log/system.log* ). Only the latest file is pushed to CloudWatch Logs, based on file modification time. We recommend that you use wild card characters to specify a series of files of the same type, such as access_log.2014-06-01-01 , access_log.2014-06-01-02 , and so on by using a pattern like access_log.* . Don't use a wildcard to match multiple file types, such as access_log_80 and access_log_443 . To specify multiple, different file types, add another log stream entry to the configuration file, so that each log file type is stored in a different log group. Zipped files are not supported. FileFingerprintLines (string) --Specifies the range of lines for identifying a file. The valid values are one number, or two dash-delimited numbers, such as '1', '2-5'. The default value is '1', meaning the first line is used to calculate the fingerprint. Fingerprint lines are not sent to CloudWatch Logs unless all specified lines are available. MultiLineStartPattern (string) --Specifies the pattern for identifying the start of a log message. InitialPosition (string) --Specifies where to start to read data (start_of_file or end_of_file). The default is start_of_file. This setting is only used if there is no state persisted for that log stream. Encoding (string) --Specifies the encoding of the log file so that the file can be read correctly. The default is utf_8 . Encodings supported by Python codecs.decode() can be used here. BufferDuration (integer) --Specifies the time duration for the batching of log events. The minimum value is 5000ms and default value is 5000ms. BatchCount (integer) --Specifies the max number of log events in a batch, up to 10000. The default value is 1000. BatchSize (integer) --Specifies the maximum size of log events in a batch, in bytes, up to 1048576 bytes. The default value is 32768 bytes. This size is calculated as the sum of all event messages in UTF-8, plus 26 bytes for each log event. :type CustomInstanceProfileArn: string :param CustomInstanceProfileArn: The ARN of an IAM profile to be used for the layer's EC2 instances. For more information about IAM ARNs, see Using Identifiers . :type CustomJson: string :param CustomJson: A JSON-formatted string containing custom stack configuration and deployment attributes to be installed on the layer's instances. For more information, see Using Custom JSON . This feature is supported as of version 1.7.42 of the AWS CLI. :type CustomSecurityGroupIds: list :param CustomSecurityGroupIds: An array containing the layer custom security group IDs. (string) -- :type Packages: list :param Packages: An array of Package objects that describes the layer packages. (string) -- :type VolumeConfigurations: list :param VolumeConfigurations: A VolumeConfigurations object that describes the layer's Amazon EBS volumes. (dict) --Describes an Amazon EBS volume configuration. MountPoint (string) -- [REQUIRED]The volume mount point. For example '/dev/sdh'. RaidLevel (integer) --The volume RAID level . NumberOfDisks (integer) -- [REQUIRED]The number of disks in the volume. Size (integer) -- [REQUIRED]The volume size. VolumeType (string) --The volume type: standard - Magnetic io1 - Provisioned IOPS (SSD) gp2 - General Purpose (SSD) Iops (integer) --For PIOPS volumes, the IOPS per disk. :type EnableAutoHealing: boolean :param EnableAutoHealing: Whether to disable auto healing for the layer. :type AutoAssignElasticIps: boolean :param AutoAssignElasticIps: Whether to automatically assign an Elastic IP address to the layer's instances. For more information, see How to Edit a Layer . :type AutoAssignPublicIps: boolean :param AutoAssignPublicIps: For stacks that are running in a VPC, whether to automatically assign a public IP address to the layer's instances. For more information, see How to Edit a Layer . :type CustomRecipes: dict :param CustomRecipes: A LayerCustomRecipes object that specifies the layer custom recipes. Setup (list) --An array of custom recipe names to be run following a setup event. (string) -- Configure (list) --An array of custom recipe names to be run following a configure event. (string) -- Deploy (list) --An array of custom recipe names to be run following a deploy event. (string) -- Undeploy (list) --An array of custom recipe names to be run following a undeploy event. (string) -- Shutdown (list) --An array of custom recipe names to be run following a shutdown event. (string) -- :type InstallUpdatesOnBoot: boolean :param InstallUpdatesOnBoot: Whether to install operating system and package updates when the instance boots. The default value is true . To control when updates are installed, set this value to false . You must then update your instances manually by using CreateDeployment to run the update_dependencies stack command or by manually running yum (Amazon Linux) or apt-get (Ubuntu) on the instances. Note To ensure that your instances have the latest security updates, we strongly recommend using the default value of true . :type UseEbsOptimizedInstances: boolean :param UseEbsOptimizedInstances: Whether to use Amazon EBS-optimized instances. :type LifecycleEventConfiguration: dict :param LifecycleEventConfiguration: A LifeCycleEventConfiguration object that you can use to configure the Shutdown event to specify an execution timeout and enable or disable Elastic Load Balancer connection draining. Shutdown (dict) --A ShutdownEventConfiguration object that specifies the Shutdown event configuration. ExecutionTimeout (integer) --The time, in seconds, that AWS OpsWorks Stacks will wait after triggering a Shutdown event before shutting down an instance. DelayUntilElbConnectionsDrained (boolean) --Whether to enable Elastic Load Balancing connection draining. For more information, see Connection Draining :rtype: dict :return: { 'LayerId': 'string' } """ pass def create_stack(Name=None, Region=None, VpcId=None, Attributes=None, ServiceRoleArn=None, DefaultInstanceProfileArn=None, DefaultOs=None, HostnameTheme=None, DefaultAvailabilityZone=None, DefaultSubnetId=None, CustomJson=None, ConfigurationManager=None, ChefConfiguration=None, UseCustomCookbooks=None, UseOpsworksSecurityGroups=None, CustomCookbooksSource=None, DefaultSshKeyName=None, DefaultRootDeviceType=None, AgentVersion=None): """ Creates a new stack. For more information, see Create a New Stack . See also: AWS API Documentation :example: response = client.create_stack( Name='string', Region='string', VpcId='string', Attributes={ 'string': 'string' }, ServiceRoleArn='string', DefaultInstanceProfileArn='string', DefaultOs='string', HostnameTheme='string', DefaultAvailabilityZone='string', DefaultSubnetId='string', CustomJson='string', ConfigurationManager={ 'Name': 'string', 'Version': 'string' }, ChefConfiguration={ 'ManageBerkshelf': True|False, 'BerkshelfVersion': 'string' }, UseCustomCookbooks=True|False, UseOpsworksSecurityGroups=True|False, CustomCookbooksSource={ 'Type': 'git'|'svn'|'archive'|'s3', 'Url': 'string', 'Username': 'string', 'Password': 'string', 'SshKey': 'string', 'Revision': 'string' }, DefaultSshKeyName='string', DefaultRootDeviceType='ebs'|'instance-store', AgentVersion='string' ) :type Name: string :param Name: [REQUIRED] The stack name. :type Region: string :param Region: [REQUIRED] The stack's AWS region, such as 'ap-south-1'. For more information about Amazon regions, see Regions and Endpoints . :type VpcId: string :param VpcId: The ID of the VPC that the stack is to be launched into. The VPC must be in the stack's region. All instances are launched into this VPC. You cannot change the ID later. If your account supports EC2-Classic, the default value is no VPC . If your account does not support EC2-Classic, the default value is the default VPC for the specified region. If the VPC ID corresponds to a default VPC and you have specified either the DefaultAvailabilityZone or the DefaultSubnetId parameter only, AWS OpsWorks Stacks infers the value of the other parameter. If you specify neither parameter, AWS OpsWorks Stacks sets these parameters to the first valid Availability Zone for the specified region and the corresponding default VPC subnet ID, respectively. If you specify a nondefault VPC ID, note the following: It must belong to a VPC in your account that is in the specified region. You must specify a value for DefaultSubnetId . For more information on how to use AWS OpsWorks Stacks with a VPC, see Running a Stack in a VPC . For more information on default VPC and EC2-Classic, see Supported Platforms . :type Attributes: dict :param Attributes: One or more user-defined key-value pairs to be added to the stack attributes. (string) -- (string) -- :type ServiceRoleArn: string :param ServiceRoleArn: [REQUIRED] The stack's AWS Identity and Access Management (IAM) role, which allows AWS OpsWorks Stacks to work with AWS resources on your behalf. You must set this parameter to the Amazon Resource Name (ARN) for an existing IAM role. For more information about IAM ARNs, see Using Identifiers . :type DefaultInstanceProfileArn: string :param DefaultInstanceProfileArn: [REQUIRED] The Amazon Resource Name (ARN) of an IAM profile that is the default profile for all of the stack's EC2 instances. For more information about IAM ARNs, see Using Identifiers . :type DefaultOs: string :param DefaultOs: The stack's default operating system, which is installed on every instance unless you specify a different operating system when you create the instance. You can specify one of the following. A supported Linux operating system: An Amazon Linux version, such as Amazon Linux 2016.09 , Amazon Linux 2016.03 , Amazon Linux 2015.09 , or Amazon Linux 2015.03 . A supported Ubuntu operating system, such as Ubuntu 16.04 LTS , Ubuntu 14.04 LTS , or Ubuntu 12.04 LTS . CentOS Linux 7 Red Hat Enterprise Linux 7 A supported Windows operating system, such as Microsoft Windows Server 2012 R2 Base , Microsoft Windows Server 2012 R2 with SQL Server Express , Microsoft Windows Server 2012 R2 with SQL Server Standard , or Microsoft Windows Server 2012 R2 with SQL Server Web . A custom AMI: Custom . You specify the custom AMI you want to use when you create instances. For more information, see Using Custom AMIs . The default option is the current Amazon Linux version. For more information on the supported operating systems, see AWS OpsWorks Stacks Operating Systems . :type HostnameTheme: string :param HostnameTheme: The stack's host name theme, with spaces replaced by underscores. The theme is used to generate host names for the stack's instances. By default, HostnameTheme is set to Layer_Dependent , which creates host names by appending integers to the layer's short name. The other themes are: Baked_Goods Clouds Europe_Cities Fruits Greek_Deities Legendary_creatures_from_Japan Planets_and_Moons Roman_Deities Scottish_Islands US_Cities Wild_Cats To obtain a generated host name, call GetHostNameSuggestion , which returns a host name based on the current theme. :type DefaultAvailabilityZone: string :param DefaultAvailabilityZone: The stack's default Availability Zone, which must be in the specified region. For more information, see Regions and Endpoints . If you also specify a value for DefaultSubnetId , the subnet must be in the same zone. For more information, see the VpcId parameter description. :type DefaultSubnetId: string :param DefaultSubnetId: The stack's default VPC subnet ID. This parameter is required if you specify a value for the VpcId parameter. All instances are launched into this subnet unless you specify otherwise when you create the instance. If you also specify a value for DefaultAvailabilityZone , the subnet must be in that zone. For information on default values and when this parameter is required, see the VpcId parameter description. :type CustomJson: string :param CustomJson: A string that contains user-defined, custom JSON. It can be used to override the corresponding default stack configuration attribute values or to pass data to recipes. The string should be in the following format: '{\'key1\': \'value1\', \'key2\': \'value2\',...}' For more information on custom JSON, see Use Custom JSON to Modify the Stack Configuration Attributes . :type ConfigurationManager: dict :param ConfigurationManager: The configuration manager. When you create a stack we recommend that you use the configuration manager to specify the Chef version: 12, 11.10, or 11.4 for Linux stacks, or 12.2 for Windows stacks. The default value for Linux stacks is currently 11.4. Name (string) --The name. This parameter must be set to 'Chef'. Version (string) --The Chef version. This parameter must be set to 12, 11.10, or 11.4 for Linux stacks, and to 12.2 for Windows stacks. The default value for Linux stacks is 11.4. :type ChefConfiguration: dict :param ChefConfiguration: A ChefConfiguration object that specifies whether to enable Berkshelf and the Berkshelf version on Chef 11.10 stacks. For more information, see Create a New Stack . ManageBerkshelf (boolean) --Whether to enable Berkshelf. BerkshelfVersion (string) --The Berkshelf version. :type UseCustomCookbooks: boolean :param UseCustomCookbooks: Whether the stack uses custom cookbooks. :type UseOpsworksSecurityGroups: boolean :param UseOpsworksSecurityGroups: Whether to associate the AWS OpsWorks Stacks built-in security groups with the stack's layers. AWS OpsWorks Stacks provides a standard set of built-in security groups, one for each layer, which are associated with layers by default. With UseOpsworksSecurityGroups you can instead provide your own custom security groups. UseOpsworksSecurityGroups has the following settings: True - AWS OpsWorks Stacks automatically associates the appropriate built-in security group with each layer (default setting). You can associate additional security groups with a layer after you create it, but you cannot delete the built-in security group. False - AWS OpsWorks Stacks does not associate built-in security groups with layers. You must create appropriate EC2 security groups and associate a security group with each layer that you create. However, you can still manually associate a built-in security group with a layer on creation; custom security groups are required only for those layers that need custom settings. For more information, see Create a New Stack . :type CustomCookbooksSource: dict :param CustomCookbooksSource: Contains the information required to retrieve an app or cookbook from a repository. For more information, see Creating Apps or Custom Recipes and Cookbooks . Type (string) --The repository type. Url (string) --The source URL. Username (string) --This parameter depends on the repository type. For Amazon S3 bundles, set Username to the appropriate IAM access key ID. For HTTP bundles, Git repositories, and Subversion repositories, set Username to the user name. Password (string) --When included in a request, the parameter depends on the repository type. For Amazon S3 bundles, set Password to the appropriate IAM secret access key. For HTTP bundles and Subversion repositories, set Password to the password. For more information on how to safely handle IAM credentials, see http://docs.aws.amazon.com/general/latest/gr/aws-access-keys-best-practices.html . In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. SshKey (string) --In requests, the repository's SSH key. In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. Revision (string) --The application's version. AWS OpsWorks Stacks enables you to easily deploy new versions of an application. One of the simplest approaches is to have branches or revisions in your repository that represent different versions that can potentially be deployed. :type DefaultSshKeyName: string :param DefaultSshKeyName: A default Amazon EC2 key pair name. The default value is none. If you specify a key pair name, AWS OpsWorks installs the public key on the instance and you can use the private key with an SSH client to log in to the instance. For more information, see Using SSH to Communicate with an Instance and Managing SSH Access . You can override this setting by specifying a different key pair, or no key pair, when you create an instance . :type DefaultRootDeviceType: string :param DefaultRootDeviceType: The default root device type. This value is the default for all instances in the stack, but you can override it when you create an instance. The default option is instance-store . For more information, see Storage for the Root Device . :type AgentVersion: string :param AgentVersion: The default AWS OpsWorks Stacks agent version. You have the following options: Auto-update - Set this parameter to LATEST . AWS OpsWorks Stacks automatically installs new agent versions on the stack's instances as soon as they are available. Fixed version - Set this parameter to your preferred agent version. To update the agent version, you must edit the stack configuration and specify a new version. AWS OpsWorks Stacks then automatically installs that version on the stack's instances. The default setting is the most recent release of the agent. To specify an agent version, you must use the complete version number, not the abbreviated number shown on the console. For a list of available agent version numbers, call DescribeAgentVersions . AgentVersion cannot be set to Chef 12.2. Note You can also specify an agent version when you create or update an instance, which overrides the stack's default setting. :rtype: dict :return: { 'StackId': 'string' } """ pass def create_user_profile(IamUserArn=None, SshUsername=None, SshPublicKey=None, AllowSelfManagement=None): """ Creates a new user profile. See also: AWS API Documentation :example: response = client.create_user_profile( IamUserArn='string', SshUsername='string', SshPublicKey='string', AllowSelfManagement=True|False ) :type IamUserArn: string :param IamUserArn: [REQUIRED] The user's IAM ARN; this can also be a federated user's ARN. :type SshUsername: string :param SshUsername: The user's SSH user name. The allowable characters are [a-z], [A-Z], [0-9], '-', and '_'. If the specified name includes other punctuation marks, AWS OpsWorks Stacks removes them. For example, my.name will be changed to myname . If you do not specify an SSH user name, AWS OpsWorks Stacks generates one from the IAM user name. :type SshPublicKey: string :param SshPublicKey: The user's public SSH key. :type AllowSelfManagement: boolean :param AllowSelfManagement: Whether users can specify their own SSH public key through the My Settings page. For more information, see Setting an IAM User's Public SSH Key . :rtype: dict :return: { 'IamUserArn': 'string' } """ pass def delete_app(AppId=None): """ Deletes a specified app. See also: AWS API Documentation :example: response = client.delete_app( AppId='string' ) :type AppId: string :param AppId: [REQUIRED] The app ID. """ pass def delete_instance(InstanceId=None, DeleteElasticIp=None, DeleteVolumes=None): """ Deletes a specified instance, which terminates the associated Amazon EC2 instance. You must stop an instance before you can delete it. For more information, see Deleting Instances . See also: AWS API Documentation :example: response = client.delete_instance( InstanceId='string', DeleteElasticIp=True|False, DeleteVolumes=True|False ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. :type DeleteElasticIp: boolean :param DeleteElasticIp: Whether to delete the instance Elastic IP address. :type DeleteVolumes: boolean :param DeleteVolumes: Whether to delete the instance's Amazon EBS volumes. """ pass def delete_layer(LayerId=None): """ Deletes a specified layer. You must first stop and then delete all associated instances or unassign registered instances. For more information, see How to Delete a Layer . See also: AWS API Documentation :example: response = client.delete_layer( LayerId='string' ) :type LayerId: string :param LayerId: [REQUIRED] The layer ID. """ pass def delete_stack(StackId=None): """ Deletes a specified stack. You must first delete all instances, layers, and apps or deregister registered instances. For more information, see Shut Down a Stack . See also: AWS API Documentation :example: response = client.delete_stack( StackId='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. """ pass def delete_user_profile(IamUserArn=None): """ Deletes a user profile. See also: AWS API Documentation :example: response = client.delete_user_profile( IamUserArn='string' ) :type IamUserArn: string :param IamUserArn: [REQUIRED] The user's IAM ARN. This can also be a federated user's ARN. """ pass def deregister_ecs_cluster(EcsClusterArn=None): """ Deregisters a specified Amazon ECS cluster from a stack. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.deregister_ecs_cluster( EcsClusterArn='string' ) :type EcsClusterArn: string :param EcsClusterArn: [REQUIRED] The cluster's ARN. """ pass def deregister_elastic_ip(ElasticIp=None): """ Deregisters a specified Elastic IP address. The address can then be registered by another stack. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.deregister_elastic_ip( ElasticIp='string' ) :type ElasticIp: string :param ElasticIp: [REQUIRED] The Elastic IP address. """ pass def deregister_instance(InstanceId=None): """ Deregister a registered Amazon EC2 or on-premises instance. This action removes the instance from the stack and returns it to your control. This action can not be used with instances that were created with AWS OpsWorks Stacks. See also: AWS API Documentation :example: response = client.deregister_instance( InstanceId='string' ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. """ pass def deregister_rds_db_instance(RdsDbInstanceArn=None): """ Deregisters an Amazon RDS instance. See also: AWS API Documentation :example: response = client.deregister_rds_db_instance( RdsDbInstanceArn='string' ) :type RdsDbInstanceArn: string :param RdsDbInstanceArn: [REQUIRED] The Amazon RDS instance's ARN. """ pass def deregister_volume(VolumeId=None): """ Deregisters an Amazon EBS volume. The volume can then be registered by another stack. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.deregister_volume( VolumeId='string' ) :type VolumeId: string :param VolumeId: [REQUIRED] The AWS OpsWorks Stacks volume ID, which is the GUID that AWS OpsWorks Stacks assigned to the instance when you registered the volume with the stack, not the Amazon EC2 volume ID. """ pass def describe_agent_versions(StackId=None, ConfigurationManager=None): """ Describes the available AWS OpsWorks Stacks agent versions. You must specify a stack ID or a configuration manager. DescribeAgentVersions returns a list of available agent versions for the specified stack or configuration manager. See also: AWS API Documentation :example: response = client.describe_agent_versions( StackId='string', ConfigurationManager={ 'Name': 'string', 'Version': 'string' } ) :type StackId: string :param StackId: The stack ID. :type ConfigurationManager: dict :param ConfigurationManager: The configuration manager. Name (string) --The name. This parameter must be set to 'Chef'. Version (string) --The Chef version. This parameter must be set to 12, 11.10, or 11.4 for Linux stacks, and to 12.2 for Windows stacks. The default value for Linux stacks is 11.4. :rtype: dict :return: { 'AgentVersions': [ { 'Version': 'string', 'ConfigurationManager': { 'Name': 'string', 'Version': 'string' } }, ] } """ pass def describe_apps(StackId=None, AppIds=None): """ Requests a description of a specified set of apps. See also: AWS API Documentation :example: response = client.describe_apps( StackId='string', AppIds=[ 'string', ] ) :type StackId: string :param StackId: The app stack ID. If you use this parameter, DescribeApps returns a description of the apps in the specified stack. :type AppIds: list :param AppIds: An array of app IDs for the apps to be described. If you use this parameter, DescribeApps returns a description of the specified apps. Otherwise, it returns a description of every app. (string) -- :rtype: dict :return: { 'Apps': [ { 'AppId': 'string', 'StackId': 'string', 'Shortname': 'string', 'Name': 'string', 'Description': 'string', 'DataSources': [ { 'Type': 'string', 'Arn': 'string', 'DatabaseName': 'string' }, ], 'Type': 'aws-flow-ruby'|'java'|'rails'|'php'|'nodejs'|'static'|'other', 'AppSource': { 'Type': 'git'|'svn'|'archive'|'s3', 'Url': 'string', 'Username': 'string', 'Password': 'string', 'SshKey': 'string', 'Revision': 'string' }, 'Domains': [ 'string', ], 'EnableSsl': True|False, 'SslConfiguration': { 'Certificate': 'string', 'PrivateKey': 'string', 'Chain': 'string' }, 'Attributes': { 'string': 'string' }, 'CreatedAt': 'string', 'Environment': [ { 'Key': 'string', 'Value': 'string', 'Secure': True|False }, ] }, ] } :returns: For Amazon S3 bundles, set Username to the appropriate IAM access key ID. For HTTP bundles, Git repositories, and Subversion repositories, set Username to the user name. """ pass def describe_commands(DeploymentId=None, InstanceId=None, CommandIds=None): """ Describes the results of specified commands. See also: AWS API Documentation :example: response = client.describe_commands( DeploymentId='string', InstanceId='string', CommandIds=[ 'string', ] ) :type DeploymentId: string :param DeploymentId: The deployment ID. If you include this parameter, DescribeCommands returns a description of the commands associated with the specified deployment. :type InstanceId: string :param InstanceId: The instance ID. If you include this parameter, DescribeCommands returns a description of the commands associated with the specified instance. :type CommandIds: list :param CommandIds: An array of command IDs. If you include this parameter, DescribeCommands returns a description of the specified commands. Otherwise, it returns a description of every command. (string) -- :rtype: dict :return: { 'Commands': [ { 'CommandId': 'string', 'InstanceId': 'string', 'DeploymentId': 'string', 'CreatedAt': 'string', 'AcknowledgedAt': 'string', 'CompletedAt': 'string', 'Status': 'string', 'ExitCode': 123, 'LogUrl': 'string', 'Type': 'string' }, ] } :returns: failed successful skipped pending """ pass def describe_deployments(StackId=None, AppId=None, DeploymentIds=None): """ Requests a description of a specified set of deployments. See also: AWS API Documentation :example: response = client.describe_deployments( StackId='string', AppId='string', DeploymentIds=[ 'string', ] ) :type StackId: string :param StackId: The stack ID. If you include this parameter, DescribeDeployments returns a description of the commands associated with the specified stack. :type AppId: string :param AppId: The app ID. If you include this parameter, DescribeDeployments returns a description of the commands associated with the specified app. :type DeploymentIds: list :param DeploymentIds: An array of deployment IDs to be described. If you include this parameter, DescribeDeployments returns a description of the specified deployments. Otherwise, it returns a description of every deployment. (string) -- :rtype: dict :return: { 'Deployments': [ { 'DeploymentId': 'string', 'StackId': 'string', 'AppId': 'string', 'CreatedAt': 'string', 'CompletedAt': 'string', 'Duration': 123, 'IamUserArn': 'string', 'Comment': 'string', 'Command': { 'Name': 'install_dependencies'|'update_dependencies'|'update_custom_cookbooks'|'execute_recipes'|'configure'|'setup'|'deploy'|'rollback'|'start'|'stop'|'restart'|'undeploy', 'Args': { 'string': [ 'string', ] } }, 'Status': 'string', 'CustomJson': 'string', 'InstanceIds': [ 'string', ] }, ] } :returns: execute_recipes : Execute one or more recipes. To specify the recipes, set an Args parameter named recipes to the list of recipes to be executed. For example, to execute phpapp::appsetup , set Args to {"recipes":["phpapp::appsetup"]} . install_dependencies : Install the stack's dependencies. update_custom_cookbooks : Update the stack's custom cookbooks. update_dependencies : Update the stack's dependencies. """ pass def describe_ecs_clusters(EcsClusterArns=None, StackId=None, NextToken=None, MaxResults=None): """ Describes Amazon ECS clusters that are registered with a stack. If you specify only a stack ID, you can use the MaxResults and NextToken parameters to paginate the response. However, AWS OpsWorks Stacks currently supports only one cluster per layer, so the result set has a maximum of one element. This call accepts only one resource-identifying parameter. See also: AWS API Documentation :example: response = client.describe_ecs_clusters( EcsClusterArns=[ 'string', ], StackId='string', NextToken='string', MaxResults=123 ) :type EcsClusterArns: list :param EcsClusterArns: A list of ARNs, one for each cluster to be described. (string) -- :type StackId: string :param StackId: A stack ID. DescribeEcsClusters returns a description of the cluster that is registered with the stack. :type NextToken: string :param NextToken: If the previous paginated request did not return all of the remaining results, the response object's``NextToken`` parameter value is set to a token. To retrieve the next set of results, call DescribeEcsClusters again and assign that token to the request object's NextToken parameter. If there are no remaining results, the previous response object's NextToken parameter is set to null . :type MaxResults: integer :param MaxResults: To receive a paginated response, use this parameter to specify the maximum number of results to be returned with a single call. If the number of available results exceeds this maximum, the response includes a NextToken value that you can assign to the NextToken request parameter to get the next set of results. :rtype: dict :return: { 'EcsClusters': [ { 'EcsClusterArn': 'string', 'EcsClusterName': 'string', 'StackId': 'string', 'RegisteredAt': 'string' }, ], 'NextToken': 'string' } """ pass def describe_elastic_ips(InstanceId=None, StackId=None, Ips=None): """ Describes Elastic IP addresses . See also: AWS API Documentation :example: response = client.describe_elastic_ips( InstanceId='string', StackId='string', Ips=[ 'string', ] ) :type InstanceId: string :param InstanceId: The instance ID. If you include this parameter, DescribeElasticIps returns a description of the Elastic IP addresses associated with the specified instance. :type StackId: string :param StackId: A stack ID. If you include this parameter, DescribeElasticIps returns a description of the Elastic IP addresses that are registered with the specified stack. :type Ips: list :param Ips: An array of Elastic IP addresses to be described. If you include this parameter, DescribeElasticIps returns a description of the specified Elastic IP addresses. Otherwise, it returns a description of every Elastic IP address. (string) -- :rtype: dict :return: { 'ElasticIps': [ { 'Ip': 'string', 'Name': 'string', 'Domain': 'string', 'Region': 'string', 'InstanceId': 'string' }, ] } """ pass def describe_elastic_load_balancers(StackId=None, LayerIds=None): """ Describes a stack's Elastic Load Balancing instances. See also: AWS API Documentation :example: response = client.describe_elastic_load_balancers( StackId='string', LayerIds=[ 'string', ] ) :type StackId: string :param StackId: A stack ID. The action describes the stack's Elastic Load Balancing instances. :type LayerIds: list :param LayerIds: A list of layer IDs. The action describes the Elastic Load Balancing instances for the specified layers. (string) -- :rtype: dict :return: { 'ElasticLoadBalancers': [ { 'ElasticLoadBalancerName': 'string', 'Region': 'string', 'DnsName': 'string', 'StackId': 'string', 'LayerId': 'string', 'VpcId': 'string', 'AvailabilityZones': [ 'string', ], 'SubnetIds': [ 'string', ], 'Ec2InstanceIds': [ 'string', ] }, ] } :returns: (string) -- """ pass def describe_instances(StackId=None, LayerId=None, InstanceIds=None): """ Requests a description of a set of instances. See also: AWS API Documentation :example: response = client.describe_instances( StackId='string', LayerId='string', InstanceIds=[ 'string', ] ) :type StackId: string :param StackId: A stack ID. If you use this parameter, DescribeInstances returns descriptions of the instances associated with the specified stack. :type LayerId: string :param LayerId: A layer ID. If you use this parameter, DescribeInstances returns descriptions of the instances associated with the specified layer. :type InstanceIds: list :param InstanceIds: An array of instance IDs to be described. If you use this parameter, DescribeInstances returns a description of the specified instances. Otherwise, it returns a description of every instance. (string) -- :rtype: dict :return: { 'Instances': [ { 'AgentVersion': 'string', 'AmiId': 'string', 'Architecture': 'x86_64'|'i386', 'AutoScalingType': 'load'|'timer', 'AvailabilityZone': 'string', 'BlockDeviceMappings': [ { 'DeviceName': 'string', 'NoDevice': 'string', 'VirtualName': 'string', 'Ebs': { 'SnapshotId': 'string', 'Iops': 123, 'VolumeSize': 123, 'VolumeType': 'gp2'|'io1'|'standard', 'DeleteOnTermination': True|False } }, ], 'CreatedAt': 'string', 'EbsOptimized': True|False, 'Ec2InstanceId': 'string', 'EcsClusterArn': 'string', 'EcsContainerInstanceArn': 'string', 'ElasticIp': 'string', 'Hostname': 'string', 'InfrastructureClass': 'string', 'InstallUpdatesOnBoot': True|False, 'InstanceId': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'LastServiceErrorId': 'string', 'LayerIds': [ 'string', ], 'Os': 'string', 'Platform': 'string', 'PrivateDns': 'string', 'PrivateIp': 'string', 'PublicDns': 'string', 'PublicIp': 'string', 'RegisteredBy': 'string', 'ReportedAgentVersion': 'string', 'ReportedOs': { 'Family': 'string', 'Name': 'string', 'Version': 'string' }, 'RootDeviceType': 'ebs'|'instance-store', 'RootDeviceVolumeId': 'string', 'SecurityGroupIds': [ 'string', ], 'SshHostDsaKeyFingerprint': 'string', 'SshHostRsaKeyFingerprint': 'string', 'SshKeyName': 'string', 'StackId': 'string', 'Status': 'string', 'SubnetId': 'string', 'Tenancy': 'string', 'VirtualizationType': 'paravirtual'|'hvm' }, ] } :returns: (string) -- """ pass def describe_layers(StackId=None, LayerIds=None): """ Requests a description of one or more layers in a specified stack. See also: AWS API Documentation :example: response = client.describe_layers( StackId='string', LayerIds=[ 'string', ] ) :type StackId: string :param StackId: The stack ID. :type LayerIds: list :param LayerIds: An array of layer IDs that specify the layers to be described. If you omit this parameter, DescribeLayers returns a description of every layer in the specified stack. (string) -- :rtype: dict :return: { 'Layers': [ { 'StackId': 'string', 'LayerId': 'string', 'Type': 'aws-flow-ruby'|'ecs-cluster'|'java-app'|'lb'|'web'|'php-app'|'rails-app'|'nodejs-app'|'memcached'|'db-master'|'monitoring-master'|'custom', 'Name': 'string', 'Shortname': 'string', 'Attributes': { 'string': 'string' }, 'CloudWatchLogsConfiguration': { 'Enabled': True|False, 'LogStreams': [ { 'LogGroupName': 'string', 'DatetimeFormat': 'string', 'TimeZone': 'LOCAL'|'UTC', 'File': 'string', 'FileFingerprintLines': 'string', 'MultiLineStartPattern': 'string', 'InitialPosition': 'start_of_file'|'end_of_file', 'Encoding': 'ascii'|'big5'|'big5hkscs'|'cp037'|'cp424'|'cp437'|'cp500'|'cp720'|'cp737'|'cp775'|'cp850'|'cp852'|'cp855'|'cp856'|'cp857'|'cp858'|'cp860'|'cp861'|'cp862'|'cp863'|'cp864'|'cp865'|'cp866'|'cp869'|'cp874'|'cp875'|'cp932'|'cp949'|'cp950'|'cp1006'|'cp1026'|'cp1140'|'cp1250'|'cp1251'|'cp1252'|'cp1253'|'cp1254'|'cp1255'|'cp1256'|'cp1257'|'cp1258'|'euc_jp'|'euc_jis_2004'|'euc_jisx0213'|'euc_kr'|'gb2312'|'gbk'|'gb18030'|'hz'|'iso2022_jp'|'iso2022_jp_1'|'iso2022_jp_2'|'iso2022_jp_2004'|'iso2022_jp_3'|'iso2022_jp_ext'|'iso2022_kr'|'latin_1'|'iso8859_2'|'iso8859_3'|'iso8859_4'|'iso8859_5'|'iso8859_6'|'iso8859_7'|'iso8859_8'|'iso8859_9'|'iso8859_10'|'iso8859_13'|'iso8859_14'|'iso8859_15'|'iso8859_16'|'johab'|'koi8_r'|'koi8_u'|'mac_cyrillic'|'mac_greek'|'mac_iceland'|'mac_latin2'|'mac_roman'|'mac_turkish'|'ptcp154'|'shift_jis'|'shift_jis_2004'|'shift_jisx0213'|'utf_32'|'utf_32_be'|'utf_32_le'|'utf_16'|'utf_16_be'|'utf_16_le'|'utf_7'|'utf_8'|'utf_8_sig', 'BufferDuration': 123, 'BatchCount': 123, 'BatchSize': 123 }, ] }, 'CustomInstanceProfileArn': 'string', 'CustomJson': 'string', 'CustomSecurityGroupIds': [ 'string', ], 'DefaultSecurityGroupNames': [ 'string', ], 'Packages': [ 'string', ], 'VolumeConfigurations': [ { 'MountPoint': 'string', 'RaidLevel': 123, 'NumberOfDisks': 123, 'Size': 123, 'VolumeType': 'string', 'Iops': 123 }, ], 'EnableAutoHealing': True|False, 'AutoAssignElasticIps': True|False, 'AutoAssignPublicIps': True|False, 'DefaultRecipes': { 'Setup': [ 'string', ], 'Configure': [ 'string', ], 'Deploy': [ 'string', ], 'Undeploy': [ 'string', ], 'Shutdown': [ 'string', ] }, 'CustomRecipes': { 'Setup': [ 'string', ], 'Configure': [ 'string', ], 'Deploy': [ 'string', ], 'Undeploy': [ 'string', ], 'Shutdown': [ 'string', ] }, 'CreatedAt': 'string', 'InstallUpdatesOnBoot': True|False, 'UseEbsOptimizedInstances': True|False, 'LifecycleEventConfiguration': { 'Shutdown': { 'ExecutionTimeout': 123, 'DelayUntilElbConnectionsDrained': True|False } } }, ] } :returns: (string) -- (string) -- """ pass def describe_load_based_auto_scaling(LayerIds=None): """ Describes load-based auto scaling configurations for specified layers. See also: AWS API Documentation :example: response = client.describe_load_based_auto_scaling( LayerIds=[ 'string', ] ) :type LayerIds: list :param LayerIds: [REQUIRED] An array of layer IDs. (string) -- :rtype: dict :return: { 'LoadBasedAutoScalingConfigurations': [ { 'LayerId': 'string', 'Enable': True|False, 'UpScaling': { 'InstanceCount': 123, 'ThresholdsWaitTime': 123, 'IgnoreMetricsTime': 123, 'CpuThreshold': 123.0, 'MemoryThreshold': 123.0, 'LoadThreshold': 123.0, 'Alarms': [ 'string', ] }, 'DownScaling': { 'InstanceCount': 123, 'ThresholdsWaitTime': 123, 'IgnoreMetricsTime': 123, 'CpuThreshold': 123.0, 'MemoryThreshold': 123.0, 'LoadThreshold': 123.0, 'Alarms': [ 'string', ] } }, ] } :returns: (string) -- """ pass def describe_my_user_profile(): """ Describes a user's SSH information. See also: AWS API Documentation :example: response = client.describe_my_user_profile() :rtype: dict :return: { 'UserProfile': { 'IamUserArn': 'string', 'Name': 'string', 'SshUsername': 'string', 'SshPublicKey': 'string' } } """ pass def describe_permissions(IamUserArn=None, StackId=None): """ Describes the permissions for a specified stack. See also: AWS API Documentation :example: response = client.describe_permissions( IamUserArn='string', StackId='string' ) :type IamUserArn: string :param IamUserArn: The user's IAM ARN. This can also be a federated user's ARN. For more information about IAM ARNs, see Using Identifiers . :type StackId: string :param StackId: The stack ID. :rtype: dict :return: { 'Permissions': [ { 'StackId': 'string', 'IamUserArn': 'string', 'AllowSsh': True|False, 'AllowSudo': True|False, 'Level': 'string' }, ] } :returns: If the request object contains only a stack ID, the array contains a Permission object with permissions for each of the stack IAM ARNs. If the request object contains only an IAM ARN, the array contains a Permission object with permissions for each of the user's stack IDs. If the request contains a stack ID and an IAM ARN, the array contains a single Permission object with permissions for the specified stack and IAM ARN. """ pass def describe_raid_arrays(InstanceId=None, StackId=None, RaidArrayIds=None): """ Describe an instance's RAID arrays. See also: AWS API Documentation :example: response = client.describe_raid_arrays( InstanceId='string', StackId='string', RaidArrayIds=[ 'string', ] ) :type InstanceId: string :param InstanceId: The instance ID. If you use this parameter, DescribeRaidArrays returns descriptions of the RAID arrays associated with the specified instance. :type StackId: string :param StackId: The stack ID. :type RaidArrayIds: list :param RaidArrayIds: An array of RAID array IDs. If you use this parameter, DescribeRaidArrays returns descriptions of the specified arrays. Otherwise, it returns a description of every array. (string) -- :rtype: dict :return: { 'RaidArrays': [ { 'RaidArrayId': 'string', 'InstanceId': 'string', 'Name': 'string', 'RaidLevel': 123, 'NumberOfDisks': 123, 'Size': 123, 'Device': 'string', 'MountPoint': 'string', 'AvailabilityZone': 'string', 'CreatedAt': 'string', 'StackId': 'string', 'VolumeType': 'string', 'Iops': 123 }, ] } """ pass def describe_rds_db_instances(StackId=None, RdsDbInstanceArns=None): """ Describes Amazon RDS instances. This call accepts only one resource-identifying parameter. See also: AWS API Documentation :example: response = client.describe_rds_db_instances( StackId='string', RdsDbInstanceArns=[ 'string', ] ) :type StackId: string :param StackId: [REQUIRED] The stack ID that the instances are registered with. The operation returns descriptions of all registered Amazon RDS instances. :type RdsDbInstanceArns: list :param RdsDbInstanceArns: An array containing the ARNs of the instances to be described. (string) -- :rtype: dict :return: { 'RdsDbInstances': [ { 'RdsDbInstanceArn': 'string', 'DbInstanceIdentifier': 'string', 'DbUser': 'string', 'DbPassword': 'string', 'Region': 'string', 'Address': 'string', 'Engine': 'string', 'StackId': 'string', 'MissingOnRds': True|False }, ] } """ pass def describe_service_errors(StackId=None, InstanceId=None, ServiceErrorIds=None): """ Describes AWS OpsWorks Stacks service errors. This call accepts only one resource-identifying parameter. See also: AWS API Documentation :example: response = client.describe_service_errors( StackId='string', InstanceId='string', ServiceErrorIds=[ 'string', ] ) :type StackId: string :param StackId: The stack ID. If you use this parameter, DescribeServiceErrors returns descriptions of the errors associated with the specified stack. :type InstanceId: string :param InstanceId: The instance ID. If you use this parameter, DescribeServiceErrors returns descriptions of the errors associated with the specified instance. :type ServiceErrorIds: list :param ServiceErrorIds: An array of service error IDs. If you use this parameter, DescribeServiceErrors returns descriptions of the specified errors. Otherwise, it returns a description of every error. (string) -- :rtype: dict :return: { 'ServiceErrors': [ { 'ServiceErrorId': 'string', 'StackId': 'string', 'InstanceId': 'string', 'Type': 'string', 'Message': 'string', 'CreatedAt': 'string' }, ] } """ pass def describe_stack_provisioning_parameters(StackId=None): """ Requests a description of a stack's provisioning parameters. See also: AWS API Documentation :example: response = client.describe_stack_provisioning_parameters( StackId='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID :rtype: dict :return: { 'AgentInstallerUrl': 'string', 'Parameters': { 'string': 'string' } } """ pass def describe_stack_summary(StackId=None): """ Describes the number of layers and apps in a specified stack, and the number of instances in each state, such as running_setup or online . See also: AWS API Documentation :example: response = client.describe_stack_summary( StackId='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. :rtype: dict :return: { 'StackSummary': { 'StackId': 'string', 'Name': 'string', 'Arn': 'string', 'LayersCount': 123, 'AppsCount': 123, 'InstancesCount': { 'Assigning': 123, 'Booting': 123, 'ConnectionLost': 123, 'Deregistering': 123, 'Online': 123, 'Pending': 123, 'Rebooting': 123, 'Registered': 123, 'Registering': 123, 'Requested': 123, 'RunningSetup': 123, 'SetupFailed': 123, 'ShuttingDown': 123, 'StartFailed': 123, 'Stopped': 123, 'Stopping': 123, 'Terminated': 123, 'Terminating': 123, 'Unassigning': 123 } } } """ pass def describe_stacks(StackIds=None): """ Requests a description of one or more stacks. See also: AWS API Documentation :example: response = client.describe_stacks( StackIds=[ 'string', ] ) :type StackIds: list :param StackIds: An array of stack IDs that specify the stacks to be described. If you omit this parameter, DescribeStacks returns a description of every stack. (string) -- :rtype: dict :return: { 'Stacks': [ { 'StackId': 'string', 'Name': 'string', 'Arn': 'string', 'Region': 'string', 'VpcId': 'string', 'Attributes': { 'string': 'string' }, 'ServiceRoleArn': 'string', 'DefaultInstanceProfileArn': 'string', 'DefaultOs': 'string', 'HostnameTheme': 'string', 'DefaultAvailabilityZone': 'string', 'DefaultSubnetId': 'string', 'CustomJson': 'string', 'ConfigurationManager': { 'Name': 'string', 'Version': 'string' }, 'ChefConfiguration': { 'ManageBerkshelf': True|False, 'BerkshelfVersion': 'string' }, 'UseCustomCookbooks': True|False, 'UseOpsworksSecurityGroups': True|False, 'CustomCookbooksSource': { 'Type': 'git'|'svn'|'archive'|'s3', 'Url': 'string', 'Username': 'string', 'Password': 'string', 'SshKey': 'string', 'Revision': 'string' }, 'DefaultSshKeyName': 'string', 'CreatedAt': 'string', 'DefaultRootDeviceType': 'ebs'|'instance-store', 'AgentVersion': 'string' }, ] } :returns: (string) -- (string) -- """ pass def describe_time_based_auto_scaling(InstanceIds=None): """ Describes time-based auto scaling configurations for specified instances. See also: AWS API Documentation :example: response = client.describe_time_based_auto_scaling( InstanceIds=[ 'string', ] ) :type InstanceIds: list :param InstanceIds: [REQUIRED] An array of instance IDs. (string) -- :rtype: dict :return: { 'TimeBasedAutoScalingConfigurations': [ { 'InstanceId': 'string', 'AutoScalingSchedule': { 'Monday': { 'string': 'string' }, 'Tuesday': { 'string': 'string' }, 'Wednesday': { 'string': 'string' }, 'Thursday': { 'string': 'string' }, 'Friday': { 'string': 'string' }, 'Saturday': { 'string': 'string' }, 'Sunday': { 'string': 'string' } } }, ] } :returns: (string) -- (string) -- """ pass def describe_user_profiles(IamUserArns=None): """ Describe specified users. See also: AWS API Documentation :example: response = client.describe_user_profiles( IamUserArns=[ 'string', ] ) :type IamUserArns: list :param IamUserArns: An array of IAM or federated user ARNs that identify the users to be described. (string) -- :rtype: dict :return: { 'UserProfiles': [ { 'IamUserArn': 'string', 'Name': 'string', 'SshUsername': 'string', 'SshPublicKey': 'string', 'AllowSelfManagement': True|False }, ] } """ pass def describe_volumes(InstanceId=None, StackId=None, RaidArrayId=None, VolumeIds=None): """ Describes an instance's Amazon EBS volumes. See also: AWS API Documentation :example: response = client.describe_volumes( InstanceId='string', StackId='string', RaidArrayId='string', VolumeIds=[ 'string', ] ) :type InstanceId: string :param InstanceId: The instance ID. If you use this parameter, DescribeVolumes returns descriptions of the volumes associated with the specified instance. :type StackId: string :param StackId: A stack ID. The action describes the stack's registered Amazon EBS volumes. :type RaidArrayId: string :param RaidArrayId: The RAID array ID. If you use this parameter, DescribeVolumes returns descriptions of the volumes associated with the specified RAID array. :type VolumeIds: list :param VolumeIds: Am array of volume IDs. If you use this parameter, DescribeVolumes returns descriptions of the specified volumes. Otherwise, it returns a description of every volume. (string) -- :rtype: dict :return: { 'Volumes': [ { 'VolumeId': 'string', 'Ec2VolumeId': 'string', 'Name': 'string', 'RaidArrayId': 'string', 'InstanceId': 'string', 'Status': 'string', 'Size': 123, 'Device': 'string', 'MountPoint': 'string', 'Region': 'string', 'AvailabilityZone': 'string', 'VolumeType': 'string', 'Iops': 123 }, ] } """ pass def detach_elastic_load_balancer(ElasticLoadBalancerName=None, LayerId=None): """ Detaches a specified Elastic Load Balancing instance from its layer. See also: AWS API Documentation :example: response = client.detach_elastic_load_balancer( ElasticLoadBalancerName='string', LayerId='string' ) :type ElasticLoadBalancerName: string :param ElasticLoadBalancerName: [REQUIRED] The Elastic Load Balancing instance's name. :type LayerId: string :param LayerId: [REQUIRED] The ID of the layer that the Elastic Load Balancing instance is attached to. """ pass def disassociate_elastic_ip(ElasticIp=None): """ Disassociates an Elastic IP address from its instance. The address remains registered with the stack. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.disassociate_elastic_ip( ElasticIp='string' ) :type ElasticIp: string :param ElasticIp: [REQUIRED] The Elastic IP address. """ pass def generate_presigned_url(ClientMethod=None, Params=None, ExpiresIn=None, HttpMethod=None): """ Generate a presigned url given a client, its method, and arguments :type ClientMethod: string :param ClientMethod: The client method to presign for :type Params: dict :param Params: The parameters normally passed to ClientMethod. :type ExpiresIn: int :param ExpiresIn: The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds) :type HttpMethod: string :param HttpMethod: The http method to use on the generated url. By default, the http method is whatever is used in the method's model. """ pass def get_hostname_suggestion(LayerId=None): """ Gets a generated host name for the specified layer, based on the current host name theme. See also: AWS API Documentation :example: response = client.get_hostname_suggestion( LayerId='string' ) :type LayerId: string :param LayerId: [REQUIRED] The layer ID. :rtype: dict :return: { 'LayerId': 'string', 'Hostname': 'string' } """ pass def get_paginator(operation_name=None): """ Create a paginator for an operation. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator('create_foo'). :rtype: L{botocore.paginate.Paginator} """ pass def get_waiter(): """ """ pass def grant_access(InstanceId=None, ValidForInMinutes=None): """ Grants RDP access to a Windows instance for a specified time period. See also: AWS API Documentation :example: response = client.grant_access( InstanceId='string', ValidForInMinutes=123 ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance's AWS OpsWorks Stacks ID. :type ValidForInMinutes: integer :param ValidForInMinutes: The length of time (in minutes) that the grant is valid. When the grant expires at the end of this period, the user will no longer be able to use the credentials to log in. If the user is logged in at the time, he or she automatically will be logged out. :rtype: dict :return: { 'TemporaryCredential': { 'Username': 'string', 'Password': 'string', 'ValidForInMinutes': 123, 'InstanceId': 'string' } } """ pass def reboot_instance(InstanceId=None): """ Reboots a specified instance. For more information, see Starting, Stopping, and Rebooting Instances . See also: AWS API Documentation :example: response = client.reboot_instance( InstanceId='string' ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. """ pass def register_ecs_cluster(EcsClusterArn=None, StackId=None): """ Registers a specified Amazon ECS cluster with a stack. You can register only one cluster with a stack. A cluster can be registered with only one stack. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.register_ecs_cluster( EcsClusterArn='string', StackId='string' ) :type EcsClusterArn: string :param EcsClusterArn: [REQUIRED] The cluster's ARN. :type StackId: string :param StackId: [REQUIRED] The stack ID. :rtype: dict :return: { 'EcsClusterArn': 'string' } """ pass def register_elastic_ip(ElasticIp=None, StackId=None): """ Registers an Elastic IP address with a specified stack. An address can be registered with only one stack at a time. If the address is already registered, you must first deregister it by calling DeregisterElasticIp . For more information, see Resource Management . See also: AWS API Documentation :example: response = client.register_elastic_ip( ElasticIp='string', StackId='string' ) :type ElasticIp: string :param ElasticIp: [REQUIRED] The Elastic IP address. :type StackId: string :param StackId: [REQUIRED] The stack ID. :rtype: dict :return: { 'ElasticIp': 'string' } """ pass def register_instance(StackId=None, Hostname=None, PublicIp=None, PrivateIp=None, RsaPublicKey=None, RsaPublicKeyFingerprint=None, InstanceIdentity=None): """ Registers instances that were created outside of AWS OpsWorks Stacks with a specified stack. Registered instances have the same requirements as instances that are created by using the CreateInstance API. For example, registered instances must be running a supported Linux-based operating system, and they must have a supported instance type. For more information about requirements for instances that you want to register, see Preparing the Instance . See also: AWS API Documentation :example: response = client.register_instance( StackId='string', Hostname='string', PublicIp='string', PrivateIp='string', RsaPublicKey='string', RsaPublicKeyFingerprint='string', InstanceIdentity={ 'Document': 'string', 'Signature': 'string' } ) :type StackId: string :param StackId: [REQUIRED] The ID of the stack that the instance is to be registered with. :type Hostname: string :param Hostname: The instance's hostname. :type PublicIp: string :param PublicIp: The instance's public IP address. :type PrivateIp: string :param PrivateIp: The instance's private IP address. :type RsaPublicKey: string :param RsaPublicKey: The instances public RSA key. This key is used to encrypt communication between the instance and the service. :type RsaPublicKeyFingerprint: string :param RsaPublicKeyFingerprint: The instances public RSA key fingerprint. :type InstanceIdentity: dict :param InstanceIdentity: An InstanceIdentity object that contains the instance's identity. Document (string) --A JSON document that contains the metadata. Signature (string) --A signature that can be used to verify the document's accuracy and authenticity. :rtype: dict :return: { 'InstanceId': 'string' } """ pass def register_rds_db_instance(StackId=None, RdsDbInstanceArn=None, DbUser=None, DbPassword=None): """ Registers an Amazon RDS instance with a stack. See also: AWS API Documentation :example: response = client.register_rds_db_instance( StackId='string', RdsDbInstanceArn='string', DbUser='string', DbPassword='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. :type RdsDbInstanceArn: string :param RdsDbInstanceArn: [REQUIRED] The Amazon RDS instance's ARN. :type DbUser: string :param DbUser: [REQUIRED] The database's master user name. :type DbPassword: string :param DbPassword: [REQUIRED] The database password. """ pass def register_volume(Ec2VolumeId=None, StackId=None): """ Registers an Amazon EBS volume with a specified stack. A volume can be registered with only one stack at a time. If the volume is already registered, you must first deregister it by calling DeregisterVolume . For more information, see Resource Management . See also: AWS API Documentation :example: response = client.register_volume( Ec2VolumeId='string', StackId='string' ) :type Ec2VolumeId: string :param Ec2VolumeId: The Amazon EBS volume ID. :type StackId: string :param StackId: [REQUIRED] The stack ID. :rtype: dict :return: { 'VolumeId': 'string' } """ pass def set_load_based_auto_scaling(LayerId=None, Enable=None, UpScaling=None, DownScaling=None): """ Specify the load-based auto scaling configuration for a specified layer. For more information, see Managing Load with Time-based and Load-based Instances . See also: AWS API Documentation :example: response = client.set_load_based_auto_scaling( LayerId='string', Enable=True|False, UpScaling={ 'InstanceCount': 123, 'ThresholdsWaitTime': 123, 'IgnoreMetricsTime': 123, 'CpuThreshold': 123.0, 'MemoryThreshold': 123.0, 'LoadThreshold': 123.0, 'Alarms': [ 'string', ] }, DownScaling={ 'InstanceCount': 123, 'ThresholdsWaitTime': 123, 'IgnoreMetricsTime': 123, 'CpuThreshold': 123.0, 'MemoryThreshold': 123.0, 'LoadThreshold': 123.0, 'Alarms': [ 'string', ] } ) :type LayerId: string :param LayerId: [REQUIRED] The layer ID. :type Enable: boolean :param Enable: Enables load-based auto scaling for the layer. :type UpScaling: dict :param UpScaling: An AutoScalingThresholds object with the upscaling threshold configuration. If the load exceeds these thresholds for a specified amount of time, AWS OpsWorks Stacks starts a specified number of instances. InstanceCount (integer) --The number of instances to add or remove when the load exceeds a threshold. ThresholdsWaitTime (integer) --The amount of time, in minutes, that the load must exceed a threshold before more instances are added or removed. IgnoreMetricsTime (integer) --The amount of time (in minutes) after a scaling event occurs that AWS OpsWorks Stacks should ignore metrics and suppress additional scaling events. For example, AWS OpsWorks Stacks adds new instances following an upscaling event but the instances won't start reducing the load until they have been booted and configured. There is no point in raising additional scaling events during that operation, which typically takes several minutes. IgnoreMetricsTime allows you to direct AWS OpsWorks Stacks to suppress scaling events long enough to get the new instances online. CpuThreshold (float) --The CPU utilization threshold, as a percent of the available CPU. A value of -1 disables the threshold. MemoryThreshold (float) --The memory utilization threshold, as a percent of the available memory. A value of -1 disables the threshold. LoadThreshold (float) --The load threshold. A value of -1 disables the threshold. For more information about how load is computed, see Load (computing) . Alarms (list) --Custom Cloudwatch auto scaling alarms, to be used as thresholds. This parameter takes a list of up to five alarm names, which are case sensitive and must be in the same region as the stack. Note To use custom alarms, you must update your service role to allow cloudwatch:DescribeAlarms . You can either have AWS OpsWorks Stacks update the role for you when you first use this feature or you can edit the role manually. For more information, see Allowing AWS OpsWorks Stacks to Act on Your Behalf . (string) -- :type DownScaling: dict :param DownScaling: An AutoScalingThresholds object with the downscaling threshold configuration. If the load falls below these thresholds for a specified amount of time, AWS OpsWorks Stacks stops a specified number of instances. InstanceCount (integer) --The number of instances to add or remove when the load exceeds a threshold. ThresholdsWaitTime (integer) --The amount of time, in minutes, that the load must exceed a threshold before more instances are added or removed. IgnoreMetricsTime (integer) --The amount of time (in minutes) after a scaling event occurs that AWS OpsWorks Stacks should ignore metrics and suppress additional scaling events. For example, AWS OpsWorks Stacks adds new instances following an upscaling event but the instances won't start reducing the load until they have been booted and configured. There is no point in raising additional scaling events during that operation, which typically takes several minutes. IgnoreMetricsTime allows you to direct AWS OpsWorks Stacks to suppress scaling events long enough to get the new instances online. CpuThreshold (float) --The CPU utilization threshold, as a percent of the available CPU. A value of -1 disables the threshold. MemoryThreshold (float) --The memory utilization threshold, as a percent of the available memory. A value of -1 disables the threshold. LoadThreshold (float) --The load threshold. A value of -1 disables the threshold. For more information about how load is computed, see Load (computing) . Alarms (list) --Custom Cloudwatch auto scaling alarms, to be used as thresholds. This parameter takes a list of up to five alarm names, which are case sensitive and must be in the same region as the stack. Note To use custom alarms, you must update your service role to allow cloudwatch:DescribeAlarms . You can either have AWS OpsWorks Stacks update the role for you when you first use this feature or you can edit the role manually. For more information, see Allowing AWS OpsWorks Stacks to Act on Your Behalf . (string) -- """ pass def set_permission(StackId=None, IamUserArn=None, AllowSsh=None, AllowSudo=None, Level=None): """ Specifies a user's permissions. For more information, see Security and Permissions . See also: AWS API Documentation :example: response = client.set_permission( StackId='string', IamUserArn='string', AllowSsh=True|False, AllowSudo=True|False, Level='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. :type IamUserArn: string :param IamUserArn: [REQUIRED] The user's IAM ARN. This can also be a federated user's ARN. :type AllowSsh: boolean :param AllowSsh: The user is allowed to use SSH to communicate with the instance. :type AllowSudo: boolean :param AllowSudo: The user is allowed to use sudo to elevate privileges. :type Level: string :param Level: The user's permission level, which must be set to one of the following strings. You cannot set your own permissions level. deny show deploy manage iam_only For more information on the permissions associated with these levels, see Managing User Permissions . """ pass def set_time_based_auto_scaling(InstanceId=None, AutoScalingSchedule=None): """ Specify the time-based auto scaling configuration for a specified instance. For more information, see Managing Load with Time-based and Load-based Instances . See also: AWS API Documentation :example: response = client.set_time_based_auto_scaling( InstanceId='string', AutoScalingSchedule={ 'Monday': { 'string': 'string' }, 'Tuesday': { 'string': 'string' }, 'Wednesday': { 'string': 'string' }, 'Thursday': { 'string': 'string' }, 'Friday': { 'string': 'string' }, 'Saturday': { 'string': 'string' }, 'Sunday': { 'string': 'string' } } ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. :type AutoScalingSchedule: dict :param AutoScalingSchedule: An AutoScalingSchedule with the instance schedule. Monday (dict) --The schedule for Monday. (string) -- (string) -- Tuesday (dict) --The schedule for Tuesday. (string) -- (string) -- Wednesday (dict) --The schedule for Wednesday. (string) -- (string) -- Thursday (dict) --The schedule for Thursday. (string) -- (string) -- Friday (dict) --The schedule for Friday. (string) -- (string) -- Saturday (dict) --The schedule for Saturday. (string) -- (string) -- Sunday (dict) --The schedule for Sunday. (string) -- (string) -- """ pass def start_instance(InstanceId=None): """ Starts a specified instance. For more information, see Starting, Stopping, and Rebooting Instances . See also: AWS API Documentation :example: response = client.start_instance( InstanceId='string' ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. """ pass def start_stack(StackId=None): """ Starts a stack's instances. See also: AWS API Documentation :example: response = client.start_stack( StackId='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. """ pass def stop_instance(InstanceId=None): """ Stops a specified instance. When you stop a standard instance, the data disappears and must be reinstalled when you restart the instance. You can stop an Amazon EBS-backed instance without losing data. For more information, see Starting, Stopping, and Rebooting Instances . See also: AWS API Documentation :example: response = client.stop_instance( InstanceId='string' ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. """ pass def stop_stack(StackId=None): """ Stops a specified stack. See also: AWS API Documentation :example: response = client.stop_stack( StackId='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. """ pass def unassign_instance(InstanceId=None): """ Unassigns a registered instance from all of it's layers. The instance remains in the stack as an unassigned instance and can be assigned to another layer, as needed. You cannot use this action with instances that were created with AWS OpsWorks Stacks. See also: AWS API Documentation :example: response = client.unassign_instance( InstanceId='string' ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. """ pass def unassign_volume(VolumeId=None): """ Unassigns an assigned Amazon EBS volume. The volume remains registered with the stack. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.unassign_volume( VolumeId='string' ) :type VolumeId: string :param VolumeId: [REQUIRED] The volume ID. """ pass def update_app(AppId=None, Name=None, Description=None, DataSources=None, Type=None, AppSource=None, Domains=None, EnableSsl=None, SslConfiguration=None, Attributes=None, Environment=None): """ Updates a specified app. See also: AWS API Documentation :example: response = client.update_app( AppId='string', Name='string', Description='string', DataSources=[ { 'Type': 'string', 'Arn': 'string', 'DatabaseName': 'string' }, ], Type='aws-flow-ruby'|'java'|'rails'|'php'|'nodejs'|'static'|'other', AppSource={ 'Type': 'git'|'svn'|'archive'|'s3', 'Url': 'string', 'Username': 'string', 'Password': 'string', 'SshKey': 'string', 'Revision': 'string' }, Domains=[ 'string', ], EnableSsl=True|False, SslConfiguration={ 'Certificate': 'string', 'PrivateKey': 'string', 'Chain': 'string' }, Attributes={ 'string': 'string' }, Environment=[ { 'Key': 'string', 'Value': 'string', 'Secure': True|False }, ] ) :type AppId: string :param AppId: [REQUIRED] The app ID. :type Name: string :param Name: The app name. :type Description: string :param Description: A description of the app. :type DataSources: list :param DataSources: The app's data sources. (dict) --Describes an app's data source. Type (string) --The data source's type, AutoSelectOpsworksMysqlInstance , OpsworksMysqlInstance , or RdsDbInstance . Arn (string) --The data source's ARN. DatabaseName (string) --The database name. :type Type: string :param Type: The app type. :type AppSource: dict :param AppSource: A Source object that specifies the app repository. Type (string) --The repository type. Url (string) --The source URL. Username (string) --This parameter depends on the repository type. For Amazon S3 bundles, set Username to the appropriate IAM access key ID. For HTTP bundles, Git repositories, and Subversion repositories, set Username to the user name. Password (string) --When included in a request, the parameter depends on the repository type. For Amazon S3 bundles, set Password to the appropriate IAM secret access key. For HTTP bundles and Subversion repositories, set Password to the password. For more information on how to safely handle IAM credentials, see http://docs.aws.amazon.com/general/latest/gr/aws-access-keys-best-practices.html . In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. SshKey (string) --In requests, the repository's SSH key. In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. Revision (string) --The application's version. AWS OpsWorks Stacks enables you to easily deploy new versions of an application. One of the simplest approaches is to have branches or revisions in your repository that represent different versions that can potentially be deployed. :type Domains: list :param Domains: The app's virtual host settings, with multiple domains separated by commas. For example: 'www.example.com, example.com' (string) -- :type EnableSsl: boolean :param EnableSsl: Whether SSL is enabled for the app. :type SslConfiguration: dict :param SslConfiguration: An SslConfiguration object with the SSL configuration. Certificate (string) -- [REQUIRED]The contents of the certificate's domain.crt file. PrivateKey (string) -- [REQUIRED]The private key; the contents of the certificate's domain.kex file. Chain (string) --Optional. Can be used to specify an intermediate certificate authority key or client authentication. :type Attributes: dict :param Attributes: One or more user-defined key/value pairs to be added to the stack attributes. (string) -- (string) -- :type Environment: list :param Environment: An array of EnvironmentVariable objects that specify environment variables to be associated with the app. After you deploy the app, these variables are defined on the associated app server instances.For more information, see Environment Variables . There is no specific limit on the number of environment variables. However, the size of the associated data structure - which includes the variables' names, values, and protected flag values - cannot exceed 10 KB (10240 Bytes). This limit should accommodate most if not all use cases. Exceeding it will cause an exception with the message, 'Environment: is too large (maximum is 10KB).' Note This parameter is supported only by Chef 11.10 stacks. If you have specified one or more environment variables, you cannot modify the stack's Chef version. (dict) --Represents an app's environment variable. Key (string) -- [REQUIRED](Required) The environment variable's name, which can consist of up to 64 characters and must be specified. The name can contain upper- and lowercase letters, numbers, and underscores (_), but it must start with a letter or underscore. Value (string) -- [REQUIRED](Optional) The environment variable's value, which can be left empty. If you specify a value, it can contain up to 256 characters, which must all be printable. Secure (boolean) --(Optional) Whether the variable's value will be returned by the DescribeApps action. To conceal an environment variable's value, set Secure to true . DescribeApps then returns *****FILTERED***** instead of the actual value. The default value for Secure is false . """ pass def update_elastic_ip(ElasticIp=None, Name=None): """ Updates a registered Elastic IP address's name. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.update_elastic_ip( ElasticIp='string', Name='string' ) :type ElasticIp: string :param ElasticIp: [REQUIRED] The address. :type Name: string :param Name: The new name. """ pass def update_instance(InstanceId=None, LayerIds=None, InstanceType=None, AutoScalingType=None, Hostname=None, Os=None, AmiId=None, SshKeyName=None, Architecture=None, InstallUpdatesOnBoot=None, EbsOptimized=None, AgentVersion=None): """ Updates a specified instance. See also: AWS API Documentation :example: response = client.update_instance( InstanceId='string', LayerIds=[ 'string', ], InstanceType='string', AutoScalingType='load'|'timer', Hostname='string', Os='string', AmiId='string', SshKeyName='string', Architecture='x86_64'|'i386', InstallUpdatesOnBoot=True|False, EbsOptimized=True|False, AgentVersion='string' ) :type InstanceId: string :param InstanceId: [REQUIRED] The instance ID. :type LayerIds: list :param LayerIds: The instance's layer IDs. (string) -- :type InstanceType: string :param InstanceType: The instance type, such as t2.micro . For a list of supported instance types, open the stack in the console, choose Instances , and choose + Instance . The Size list contains the currently supported types. For more information, see Instance Families and Types . The parameter values that you use to specify the various types are in the API Name column of the Available Instance Types table. :type AutoScalingType: string :param AutoScalingType: For load-based or time-based instances, the type. Windows stacks can use only time-based instances. :type Hostname: string :param Hostname: The instance host name. :type Os: string :param Os: The instance's operating system, which must be set to one of the following. You cannot update an instance that is using a custom AMI. A supported Linux operating system: An Amazon Linux version, such as Amazon Linux 2016.09 , Amazon Linux 2016.03 , Amazon Linux 2015.09 , or Amazon Linux 2015.03 . A supported Ubuntu operating system, such as Ubuntu 16.04 LTS , Ubuntu 14.04 LTS , or Ubuntu 12.04 LTS . CentOS Linux 7 Red Hat Enterprise Linux 7 A supported Windows operating system, such as Microsoft Windows Server 2012 R2 Base , Microsoft Windows Server 2012 R2 with SQL Server Express , Microsoft Windows Server 2012 R2 with SQL Server Standard , or Microsoft Windows Server 2012 R2 with SQL Server Web . For more information on the supported operating systems, see AWS OpsWorks Stacks Operating Systems . The default option is the current Amazon Linux version. If you set this parameter to Custom , you must use the AmiId parameter to specify the custom AMI that you want to use. For more information on the supported operating systems, see Operating Systems . For more information on how to use custom AMIs with OpsWorks, see Using Custom AMIs . Note You can specify a different Linux operating system for the updated stack, but you cannot change from Linux to Windows or Windows to Linux. :type AmiId: string :param AmiId: The ID of the AMI that was used to create the instance. The value of this parameter must be the same AMI ID that the instance is already using. You cannot apply a new AMI to an instance by running UpdateInstance. UpdateInstance does not work on instances that are using custom AMIs. :type SshKeyName: string :param SshKeyName: The instance's Amazon EC2 key name. :type Architecture: string :param Architecture: The instance architecture. Instance types do not necessarily support both architectures. For a list of the architectures that are supported by the different instance types, see Instance Families and Types . :type InstallUpdatesOnBoot: boolean :param InstallUpdatesOnBoot: Whether to install operating system and package updates when the instance boots. The default value is true . To control when updates are installed, set this value to false . You must then update your instances manually by using CreateDeployment to run the update_dependencies stack command or by manually running yum (Amazon Linux) or apt-get (Ubuntu) on the instances. Note We strongly recommend using the default value of true , to ensure that your instances have the latest security updates. :type EbsOptimized: boolean :param EbsOptimized: This property cannot be updated. :type AgentVersion: string :param AgentVersion: The default AWS OpsWorks Stacks agent version. You have the following options: INHERIT - Use the stack's default agent version setting. version_number - Use the specified agent version. This value overrides the stack's default setting. To update the agent version, you must edit the instance configuration and specify a new version. AWS OpsWorks Stacks then automatically installs that version on the instance. The default setting is INHERIT . To specify an agent version, you must use the complete version number, not the abbreviated number shown on the console. For a list of available agent version numbers, call DescribeAgentVersions . AgentVersion cannot be set to Chef 12.2. """ pass def update_layer(LayerId=None, Name=None, Shortname=None, Attributes=None, CloudWatchLogsConfiguration=None, CustomInstanceProfileArn=None, CustomJson=None, CustomSecurityGroupIds=None, Packages=None, VolumeConfigurations=None, EnableAutoHealing=None, AutoAssignElasticIps=None, AutoAssignPublicIps=None, CustomRecipes=None, InstallUpdatesOnBoot=None, UseEbsOptimizedInstances=None, LifecycleEventConfiguration=None): """ Updates a specified layer. See also: AWS API Documentation :example: response = client.update_layer( LayerId='string', Name='string', Shortname='string', Attributes={ 'string': 'string' }, CloudWatchLogsConfiguration={ 'Enabled': True|False, 'LogStreams': [ { 'LogGroupName': 'string', 'DatetimeFormat': 'string', 'TimeZone': 'LOCAL'|'UTC', 'File': 'string', 'FileFingerprintLines': 'string', 'MultiLineStartPattern': 'string', 'InitialPosition': 'start_of_file'|'end_of_file', 'Encoding': 'ascii'|'big5'|'big5hkscs'|'cp037'|'cp424'|'cp437'|'cp500'|'cp720'|'cp737'|'cp775'|'cp850'|'cp852'|'cp855'|'cp856'|'cp857'|'cp858'|'cp860'|'cp861'|'cp862'|'cp863'|'cp864'|'cp865'|'cp866'|'cp869'|'cp874'|'cp875'|'cp932'|'cp949'|'cp950'|'cp1006'|'cp1026'|'cp1140'|'cp1250'|'cp1251'|'cp1252'|'cp1253'|'cp1254'|'cp1255'|'cp1256'|'cp1257'|'cp1258'|'euc_jp'|'euc_jis_2004'|'euc_jisx0213'|'euc_kr'|'gb2312'|'gbk'|'gb18030'|'hz'|'iso2022_jp'|'iso2022_jp_1'|'iso2022_jp_2'|'iso2022_jp_2004'|'iso2022_jp_3'|'iso2022_jp_ext'|'iso2022_kr'|'latin_1'|'iso8859_2'|'iso8859_3'|'iso8859_4'|'iso8859_5'|'iso8859_6'|'iso8859_7'|'iso8859_8'|'iso8859_9'|'iso8859_10'|'iso8859_13'|'iso8859_14'|'iso8859_15'|'iso8859_16'|'johab'|'koi8_r'|'koi8_u'|'mac_cyrillic'|'mac_greek'|'mac_iceland'|'mac_latin2'|'mac_roman'|'mac_turkish'|'ptcp154'|'shift_jis'|'shift_jis_2004'|'shift_jisx0213'|'utf_32'|'utf_32_be'|'utf_32_le'|'utf_16'|'utf_16_be'|'utf_16_le'|'utf_7'|'utf_8'|'utf_8_sig', 'BufferDuration': 123, 'BatchCount': 123, 'BatchSize': 123 }, ] }, CustomInstanceProfileArn='string', CustomJson='string', CustomSecurityGroupIds=[ 'string', ], Packages=[ 'string', ], VolumeConfigurations=[ { 'MountPoint': 'string', 'RaidLevel': 123, 'NumberOfDisks': 123, 'Size': 123, 'VolumeType': 'string', 'Iops': 123 }, ], EnableAutoHealing=True|False, AutoAssignElasticIps=True|False, AutoAssignPublicIps=True|False, CustomRecipes={ 'Setup': [ 'string', ], 'Configure': [ 'string', ], 'Deploy': [ 'string', ], 'Undeploy': [ 'string', ], 'Shutdown': [ 'string', ] }, InstallUpdatesOnBoot=True|False, UseEbsOptimizedInstances=True|False, LifecycleEventConfiguration={ 'Shutdown': { 'ExecutionTimeout': 123, 'DelayUntilElbConnectionsDrained': True|False } } ) :type LayerId: string :param LayerId: [REQUIRED] The layer ID. :type Name: string :param Name: The layer name, which is used by the console. :type Shortname: string :param Shortname: For custom layers only, use this parameter to specify the layer's short name, which is used internally by AWS OpsWorks Stacks and by Chef. The short name is also used as the name for the directory where your app files are installed. It can have a maximum of 200 characters and must be in the following format: /A[a-z0-9-_.]+Z/. The built-in layers' short names are defined by AWS OpsWorks Stacks. For more information, see the Layer Reference :type Attributes: dict :param Attributes: One or more user-defined key/value pairs to be added to the stack attributes. (string) -- (string) -- :type CloudWatchLogsConfiguration: dict :param CloudWatchLogsConfiguration: Specifies CloudWatch Logs configuration options for the layer. For more information, see CloudWatchLogsLogStream . Enabled (boolean) --Whether CloudWatch Logs is enabled for a layer. LogStreams (list) --A list of configuration options for CloudWatch Logs. (dict) --Describes the Amazon CloudWatch logs configuration for a layer. For detailed information about members of this data type, see the CloudWatch Logs Agent Reference . LogGroupName (string) --Specifies the destination log group. A log group is created automatically if it doesn't already exist. Log group names can be between 1 and 512 characters long. Allowed characters include a-z, A-Z, 0-9, '_' (underscore), '-' (hyphen), '/' (forward slash), and '.' (period). DatetimeFormat (string) --Specifies how the time stamp is extracted from logs. For more information, see the CloudWatch Logs Agent Reference . TimeZone (string) --Specifies the time zone of log event time stamps. File (string) --Specifies log files that you want to push to CloudWatch Logs. File can point to a specific file or multiple files (by using wild card characters such as /var/log/system.log* ). Only the latest file is pushed to CloudWatch Logs, based on file modification time. We recommend that you use wild card characters to specify a series of files of the same type, such as access_log.2014-06-01-01 , access_log.2014-06-01-02 , and so on by using a pattern like access_log.* . Don't use a wildcard to match multiple file types, such as access_log_80 and access_log_443 . To specify multiple, different file types, add another log stream entry to the configuration file, so that each log file type is stored in a different log group. Zipped files are not supported. FileFingerprintLines (string) --Specifies the range of lines for identifying a file. The valid values are one number, or two dash-delimited numbers, such as '1', '2-5'. The default value is '1', meaning the first line is used to calculate the fingerprint. Fingerprint lines are not sent to CloudWatch Logs unless all specified lines are available. MultiLineStartPattern (string) --Specifies the pattern for identifying the start of a log message. InitialPosition (string) --Specifies where to start to read data (start_of_file or end_of_file). The default is start_of_file. This setting is only used if there is no state persisted for that log stream. Encoding (string) --Specifies the encoding of the log file so that the file can be read correctly. The default is utf_8 . Encodings supported by Python codecs.decode() can be used here. BufferDuration (integer) --Specifies the time duration for the batching of log events. The minimum value is 5000ms and default value is 5000ms. BatchCount (integer) --Specifies the max number of log events in a batch, up to 10000. The default value is 1000. BatchSize (integer) --Specifies the maximum size of log events in a batch, in bytes, up to 1048576 bytes. The default value is 32768 bytes. This size is calculated as the sum of all event messages in UTF-8, plus 26 bytes for each log event. :type CustomInstanceProfileArn: string :param CustomInstanceProfileArn: The ARN of an IAM profile to be used for all of the layer's EC2 instances. For more information about IAM ARNs, see Using Identifiers . :type CustomJson: string :param CustomJson: A JSON-formatted string containing custom stack configuration and deployment attributes to be installed on the layer's instances. For more information, see Using Custom JSON . :type CustomSecurityGroupIds: list :param CustomSecurityGroupIds: An array containing the layer's custom security group IDs. (string) -- :type Packages: list :param Packages: An array of Package objects that describe the layer's packages. (string) -- :type VolumeConfigurations: list :param VolumeConfigurations: A VolumeConfigurations object that describes the layer's Amazon EBS volumes. (dict) --Describes an Amazon EBS volume configuration. MountPoint (string) -- [REQUIRED]The volume mount point. For example '/dev/sdh'. RaidLevel (integer) --The volume RAID level . NumberOfDisks (integer) -- [REQUIRED]The number of disks in the volume. Size (integer) -- [REQUIRED]The volume size. VolumeType (string) --The volume type: standard - Magnetic io1 - Provisioned IOPS (SSD) gp2 - General Purpose (SSD) Iops (integer) --For PIOPS volumes, the IOPS per disk. :type EnableAutoHealing: boolean :param EnableAutoHealing: Whether to disable auto healing for the layer. :type AutoAssignElasticIps: boolean :param AutoAssignElasticIps: Whether to automatically assign an Elastic IP address to the layer's instances. For more information, see How to Edit a Layer . :type AutoAssignPublicIps: boolean :param AutoAssignPublicIps: For stacks that are running in a VPC, whether to automatically assign a public IP address to the layer's instances. For more information, see How to Edit a Layer . :type CustomRecipes: dict :param CustomRecipes: A LayerCustomRecipes object that specifies the layer's custom recipes. Setup (list) --An array of custom recipe names to be run following a setup event. (string) -- Configure (list) --An array of custom recipe names to be run following a configure event. (string) -- Deploy (list) --An array of custom recipe names to be run following a deploy event. (string) -- Undeploy (list) --An array of custom recipe names to be run following a undeploy event. (string) -- Shutdown (list) --An array of custom recipe names to be run following a shutdown event. (string) -- :type InstallUpdatesOnBoot: boolean :param InstallUpdatesOnBoot: Whether to install operating system and package updates when the instance boots. The default value is true . To control when updates are installed, set this value to false . You must then update your instances manually by using CreateDeployment to run the update_dependencies stack command or manually running yum (Amazon Linux) or apt-get (Ubuntu) on the instances. Note We strongly recommend using the default value of true , to ensure that your instances have the latest security updates. :type UseEbsOptimizedInstances: boolean :param UseEbsOptimizedInstances: Whether to use Amazon EBS-optimized instances. :type LifecycleEventConfiguration: dict :param LifecycleEventConfiguration: Shutdown (dict) --A ShutdownEventConfiguration object that specifies the Shutdown event configuration. ExecutionTimeout (integer) --The time, in seconds, that AWS OpsWorks Stacks will wait after triggering a Shutdown event before shutting down an instance. DelayUntilElbConnectionsDrained (boolean) --Whether to enable Elastic Load Balancing connection draining. For more information, see Connection Draining """ pass def update_my_user_profile(SshPublicKey=None): """ Updates a user's SSH public key. See also: AWS API Documentation :example: response = client.update_my_user_profile( SshPublicKey='string' ) :type SshPublicKey: string :param SshPublicKey: The user's SSH public key. """ pass def update_rds_db_instance(RdsDbInstanceArn=None, DbUser=None, DbPassword=None): """ Updates an Amazon RDS instance. See also: AWS API Documentation :example: response = client.update_rds_db_instance( RdsDbInstanceArn='string', DbUser='string', DbPassword='string' ) :type RdsDbInstanceArn: string :param RdsDbInstanceArn: [REQUIRED] The Amazon RDS instance's ARN. :type DbUser: string :param DbUser: The master user name. :type DbPassword: string :param DbPassword: The database password. """ pass def update_stack(StackId=None, Name=None, Attributes=None, ServiceRoleArn=None, DefaultInstanceProfileArn=None, DefaultOs=None, HostnameTheme=None, DefaultAvailabilityZone=None, DefaultSubnetId=None, CustomJson=None, ConfigurationManager=None, ChefConfiguration=None, UseCustomCookbooks=None, CustomCookbooksSource=None, DefaultSshKeyName=None, DefaultRootDeviceType=None, UseOpsworksSecurityGroups=None, AgentVersion=None): """ Updates a specified stack. See also: AWS API Documentation :example: response = client.update_stack( StackId='string', Name='string', Attributes={ 'string': 'string' }, ServiceRoleArn='string', DefaultInstanceProfileArn='string', DefaultOs='string', HostnameTheme='string', DefaultAvailabilityZone='string', DefaultSubnetId='string', CustomJson='string', ConfigurationManager={ 'Name': 'string', 'Version': 'string' }, ChefConfiguration={ 'ManageBerkshelf': True|False, 'BerkshelfVersion': 'string' }, UseCustomCookbooks=True|False, CustomCookbooksSource={ 'Type': 'git'|'svn'|'archive'|'s3', 'Url': 'string', 'Username': 'string', 'Password': 'string', 'SshKey': 'string', 'Revision': 'string' }, DefaultSshKeyName='string', DefaultRootDeviceType='ebs'|'instance-store', UseOpsworksSecurityGroups=True|False, AgentVersion='string' ) :type StackId: string :param StackId: [REQUIRED] The stack ID. :type Name: string :param Name: The stack's new name. :type Attributes: dict :param Attributes: One or more user-defined key-value pairs to be added to the stack attributes. (string) -- (string) -- :type ServiceRoleArn: string :param ServiceRoleArn: Do not use this parameter. You cannot update a stack's service role. :type DefaultInstanceProfileArn: string :param DefaultInstanceProfileArn: The ARN of an IAM profile that is the default profile for all of the stack's EC2 instances. For more information about IAM ARNs, see Using Identifiers . :type DefaultOs: string :param DefaultOs: The stack's operating system, which must be set to one of the following: A supported Linux operating system: An Amazon Linux version, such as Amazon Linux 2016.09 , Amazon Linux 2016.03 , Amazon Linux 2015.09 , or Amazon Linux 2015.03 . A supported Ubuntu operating system, such as Ubuntu 16.04 LTS , Ubuntu 14.04 LTS , or Ubuntu 12.04 LTS . CentOS Linux 7 Red Hat Enterprise Linux 7 A supported Windows operating system, such as Microsoft Windows Server 2012 R2 Base , Microsoft Windows Server 2012 R2 with SQL Server Express , Microsoft Windows Server 2012 R2 with SQL Server Standard , or Microsoft Windows Server 2012 R2 with SQL Server Web . A custom AMI: Custom . You specify the custom AMI you want to use when you create instances. For more information on how to use custom AMIs with OpsWorks, see Using Custom AMIs . The default option is the stack's current operating system. For more information on the supported operating systems, see AWS OpsWorks Stacks Operating Systems . :type HostnameTheme: string :param HostnameTheme: The stack's new host name theme, with spaces replaced by underscores. The theme is used to generate host names for the stack's instances. By default, HostnameTheme is set to Layer_Dependent , which creates host names by appending integers to the layer's short name. The other themes are: Baked_Goods Clouds Europe_Cities Fruits Greek_Deities Legendary_creatures_from_Japan Planets_and_Moons Roman_Deities Scottish_Islands US_Cities Wild_Cats To obtain a generated host name, call GetHostNameSuggestion , which returns a host name based on the current theme. :type DefaultAvailabilityZone: string :param DefaultAvailabilityZone: The stack's default Availability Zone, which must be in the stack's region. For more information, see Regions and Endpoints . If you also specify a value for DefaultSubnetId , the subnet must be in the same zone. For more information, see CreateStack . :type DefaultSubnetId: string :param DefaultSubnetId: The stack's default VPC subnet ID. This parameter is required if you specify a value for the VpcId parameter. All instances are launched into this subnet unless you specify otherwise when you create the instance. If you also specify a value for DefaultAvailabilityZone , the subnet must be in that zone. For information on default values and when this parameter is required, see the VpcId parameter description. :type CustomJson: string :param CustomJson: A string that contains user-defined, custom JSON. It can be used to override the corresponding default stack configuration JSON values or to pass data to recipes. The string should be in the following format: '{\'key1\': \'value1\', \'key2\': \'value2\',...}' For more information on custom JSON, see Use Custom JSON to Modify the Stack Configuration Attributes . :type ConfigurationManager: dict :param ConfigurationManager: The configuration manager. When you update a stack, we recommend that you use the configuration manager to specify the Chef version: 12, 11.10, or 11.4 for Linux stacks, or 12.2 for Windows stacks. The default value for Linux stacks is currently 11.4. Name (string) --The name. This parameter must be set to 'Chef'. Version (string) --The Chef version. This parameter must be set to 12, 11.10, or 11.4 for Linux stacks, and to 12.2 for Windows stacks. The default value for Linux stacks is 11.4. :type ChefConfiguration: dict :param ChefConfiguration: A ChefConfiguration object that specifies whether to enable Berkshelf and the Berkshelf version on Chef 11.10 stacks. For more information, see Create a New Stack . ManageBerkshelf (boolean) --Whether to enable Berkshelf. BerkshelfVersion (string) --The Berkshelf version. :type UseCustomCookbooks: boolean :param UseCustomCookbooks: Whether the stack uses custom cookbooks. :type CustomCookbooksSource: dict :param CustomCookbooksSource: Contains the information required to retrieve an app or cookbook from a repository. For more information, see Creating Apps or Custom Recipes and Cookbooks . Type (string) --The repository type. Url (string) --The source URL. Username (string) --This parameter depends on the repository type. For Amazon S3 bundles, set Username to the appropriate IAM access key ID. For HTTP bundles, Git repositories, and Subversion repositories, set Username to the user name. Password (string) --When included in a request, the parameter depends on the repository type. For Amazon S3 bundles, set Password to the appropriate IAM secret access key. For HTTP bundles and Subversion repositories, set Password to the password. For more information on how to safely handle IAM credentials, see http://docs.aws.amazon.com/general/latest/gr/aws-access-keys-best-practices.html . In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. SshKey (string) --In requests, the repository's SSH key. In responses, AWS OpsWorks Stacks returns *****FILTERED***** instead of the actual value. Revision (string) --The application's version. AWS OpsWorks Stacks enables you to easily deploy new versions of an application. One of the simplest approaches is to have branches or revisions in your repository that represent different versions that can potentially be deployed. :type DefaultSshKeyName: string :param DefaultSshKeyName: A default Amazon EC2 key-pair name. The default value is none . If you specify a key-pair name, AWS OpsWorks Stacks installs the public key on the instance and you can use the private key with an SSH client to log in to the instance. For more information, see Using SSH to Communicate with an Instance and Managing SSH Access . You can override this setting by specifying a different key pair, or no key pair, when you create an instance . :type DefaultRootDeviceType: string :param DefaultRootDeviceType: The default root device type. This value is used by default for all instances in the stack, but you can override it when you create an instance. For more information, see Storage for the Root Device . :type UseOpsworksSecurityGroups: boolean :param UseOpsworksSecurityGroups: Whether to associate the AWS OpsWorks Stacks built-in security groups with the stack's layers. AWS OpsWorks Stacks provides a standard set of built-in security groups, one for each layer, which are associated with layers by default. UseOpsworksSecurityGroups allows you to provide your own custom security groups instead of using the built-in groups. UseOpsworksSecurityGroups has the following settings: True - AWS OpsWorks Stacks automatically associates the appropriate built-in security group with each layer (default setting). You can associate additional security groups with a layer after you create it, but you cannot delete the built-in security group. False - AWS OpsWorks Stacks does not associate built-in security groups with layers. You must create appropriate EC2 security groups and associate a security group with each layer that you create. However, you can still manually associate a built-in security group with a layer on. Custom security groups are required only for those layers that need custom settings. For more information, see Create a New Stack . :type AgentVersion: string :param AgentVersion: The default AWS OpsWorks Stacks agent version. You have the following options: Auto-update - Set this parameter to LATEST . AWS OpsWorks Stacks automatically installs new agent versions on the stack's instances as soon as they are available. Fixed version - Set this parameter to your preferred agent version. To update the agent version, you must edit the stack configuration and specify a new version. AWS OpsWorks Stacks then automatically installs that version on the stack's instances. The default setting is LATEST . To specify an agent version, you must use the complete version number, not the abbreviated number shown on the console. For a list of available agent version numbers, call DescribeAgentVersions . AgentVersion cannot be set to Chef 12.2. Note You can also specify an agent version when you create or update an instance, which overrides the stack's default setting. """ pass def update_user_profile(IamUserArn=None, SshUsername=None, SshPublicKey=None, AllowSelfManagement=None): """ Updates a specified user profile. See also: AWS API Documentation :example: response = client.update_user_profile( IamUserArn='string', SshUsername='string', SshPublicKey='string', AllowSelfManagement=True|False ) :type IamUserArn: string :param IamUserArn: [REQUIRED] The user IAM ARN. This can also be a federated user's ARN. :type SshUsername: string :param SshUsername: The user's SSH user name. The allowable characters are [a-z], [A-Z], [0-9], '-', and '_'. If the specified name includes other punctuation marks, AWS OpsWorks Stacks removes them. For example, my.name will be changed to myname . If you do not specify an SSH user name, AWS OpsWorks Stacks generates one from the IAM user name. :type SshPublicKey: string :param SshPublicKey: The user's new SSH public key. :type AllowSelfManagement: boolean :param AllowSelfManagement: Whether users can specify their own SSH public key through the My Settings page. For more information, see Managing User Permissions . """ pass def update_volume(VolumeId=None, Name=None, MountPoint=None): """ Updates an Amazon EBS volume's name or mount point. For more information, see Resource Management . See also: AWS API Documentation :example: response = client.update_volume( VolumeId='string', Name='string', MountPoint='string' ) :type VolumeId: string :param VolumeId: [REQUIRED] The volume ID. :type Name: string :param Name: The new name. :type MountPoint: string :param MountPoint: The new mount point. """ pass

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Python

code/get_adj.py

xjy912/DGMP-1

36da2288f95b49829b85e3b42dc65b9eda9606b0

[ "MIT" ]

1

2022-03-11T18:33:33.000Z

code/get_adj.py

xjy912/DGMP-1

36da2288f95b49829b85e3b42dc65b9eda9606b0

[ "MIT" ]

null

code/get_adj.py

xjy912/DGMP-1

36da2288f95b49829b85e3b42dc65b9eda9606b0

[ "MIT" ]

null

import os.path as osp import numpy as np import scipy.sparse as sp import networkx as nx import pandas as pd import os import torch import torch_geometric.transforms as T from torch_geometric.data import Data from torch_geometric.utils import to_undirected, is_undirected, to_networkx from networkx.algorithms.components import is_weakly_connected from torch_geometric.utils import add_remaining_self_loops, add_self_loops, remove_self_loops from torch_scatter import scatter_add import scipy def get_undirected_adj(edge_index, num_nodes, dtype): edge_weight = torch.ones((edge_index.size(1), ), dtype=dtype, device=edge_index.device) fill_value = 1 edge_index, edge_weight = add_self_loops( edge_index, edge_weight, fill_value, num_nodes) row, col = edge_index deg = scatter_add(edge_weight, row, dim=0, dim_size=num_nodes) deg_inv_sqrt = deg.pow(-0.5) deg_inv_sqrt[deg_inv_sqrt == float('inf')] = 0 return edge_index, deg_inv_sqrt[row] * edge_weight * deg_inv_sqrt[col] def get_in_directed_adj(edge_index, num_nodes, dtype): edge_weight = torch.ones((edge_index.size(1), ), dtype=dtype, device=edge_index.device) fill_value = 1 edge_index, edge_weight = add_self_loops( edge_index, edge_weight, fill_value, num_nodes) row, col = edge_index deg = scatter_add(edge_weight, row, dim=0, dim_size=num_nodes) deg_inv = deg.pow(-1) deg_inv[deg_inv == float('inf')] = 0 p = deg_inv[row] * edge_weight p_dense = torch.sparse.FloatTensor(edge_index, p, torch.Size([num_nodes,num_nodes])).to_dense() L = torch.mm(p_dense.t(), p_dense) # make nan to 0 L[torch.isnan(L)] = 0 # transfer dense L to sparse L_indices = torch.nonzero(L,as_tuple=False).t() L_values = L[L_indices[0], L_indices[1]] edge_index = L_indices edge_weight = L_values # row normalization row, col = edge_index deg = scatter_add(edge_weight, row, dim=0, dim_size=num_nodes) deg_inv_sqrt = deg.pow(-0.5) deg_inv_sqrt[deg_inv_sqrt == float('inf')] = 0 return edge_index, deg_inv_sqrt[row] * edge_weight * deg_inv_sqrt[col] def get_out_directed_adj(edge_index, num_nodes, dtype): edge_weight = torch.ones((edge_index.size(1), ), dtype=dtype, device=edge_index.device) fill_value = 1 edge_index, edge_weight = add_self_loops( edge_index, edge_weight, fill_value, num_nodes) row, col = edge_index deg = scatter_add(edge_weight, row, dim=0, dim_size=num_nodes) deg_inv = deg.pow(-1) deg_inv[deg_inv == float('inf')] = 0 p = deg_inv[row] * edge_weight p_dense = torch.sparse.FloatTensor(edge_index, p, torch.Size([num_nodes,num_nodes])).to_dense() L = torch.mm(p_dense, p_dense.t()) # make nan to 0 L[torch.isnan(L)] = 0 # transfer dense L to sparse L_indices = torch.nonzero(L,as_tuple=False).t() L_values = L[L_indices[0], L_indices[1]] edge_index = L_indices edge_weight = L_values # row normalization row, col = edge_index deg = scatter_add(edge_weight, row, dim=0, dim_size=num_nodes) deg_inv_sqrt = deg.pow(-0.5) deg_inv_sqrt[deg_inv_sqrt == float('inf')] = 0 return edge_index, deg_inv_sqrt[row] * edge_weight * deg_inv_sqrt[col]

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7

a06a87087d2f7a3214022e6036d5967605ae5ab7

216

py

Python

pages/managers.py

buketkonuk/pythondotorg

4d8d9728eea7c7b2fef32eb6f24fda409cf24a06

[ "Apache-2.0" ]

911

2015-01-03T22:16:06.000Z

2022-03-31T23:56:22.000Z

pages/managers.py

buketkonuk/pythondotorg

4d8d9728eea7c7b2fef32eb6f24fda409cf24a06

[ "Apache-2.0" ]

1,342

2015-01-02T16:14:45.000Z

2022-03-28T08:01:20.000Z

pages/managers.py

buketkonuk/pythondotorg

4d8d9728eea7c7b2fef32eb6f24fda409cf24a06

[ "Apache-2.0" ]

551

2015-01-04T02:17:31.000Z

2022-03-23T11:59:25.000Z

from django.db.models.query import QuerySet class PageQuerySet(QuerySet): def published(self): return self.filter(is_published=True) def draft(self): return self.filter(is_published=False)

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0.261438

0.405229

0

0.189815

216

9

47

24

0.874286

0

1

0.333333

false

0

0.166667

0.333333

1

0

1

0

null

0

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0

1

0

null

0

1

0

1

0

7

a09546051c05f3cce2b05ebfd6611666c5ad53d2

7,040

py

Python

googlebooks.py

toza-mimoza/Python-Google-Books-CLI

bcadf5a7b5ddcd60ad6c37742917a38a13df9bc6

[ "MIT" ]

null

googlebooks.py

toza-mimoza/Python-Google-Books-CLI

bcadf5a7b5ddcd60ad6c37742917a38a13df9bc6

[ "MIT" ]

null

googlebooks.py

toza-mimoza/Python-Google-Books-CLI

bcadf5a7b5ddcd60ad6c37742917a38a13df9bc6

[ "MIT" ]

null

import json import click import requests import webbrowser __author__ = "toza-mimoza" @click.group() def main(): """ CLI for querying books on Google Books by toza-mimoza """ pass @main.command() @click.argument('query') def search(query): """This search and return results corresponding to the given query from Google Books""" url_format = 'https://www.googleapis.com/books/v1/volumes' query = "+".join(query.split()) query_params = { 'q': query } response = requests.get(url_format, params=query_params) #resp_list=[requests.get(url_format,params=query_params)] responseInJSON=response.json() with open('searchQuery.json','w') as json_file: #stores a query json.dump(responseInJSON,json_file) # click.echo(json.dumps(responseInJSON,indent=10)) for i in range(len(responseInJSON['items'])): volInfo=responseInJSON['items'][i]['volumeInfo'] salInfo=responseInJSON['items'][i]['saleInfo'] accInfo=responseInJSON['items'][i]['accessInfo'] click.echo("__________________________________________________________________________________") click.echo("Title:\t\t "+volInfo['title']) if ('subtitle' in volInfo): click.echo(" "+str(volInfo['subtitle'])) if('description' in volInfo): click.echo("Description:\t "+volInfo['description']) if ('authors' not in volInfo): click.echo("Authors:\t UNKNOWN") pass elif len(volInfo['authors'])==1: click.echo("Author:\t\t "+str(volInfo['authors'][0])) elif len(volInfo['authors'])>1: for author in volInfo['authors']: click.echo("Author:\t\t "+author) pass pass if ('publishedDate' not in volInfo): click.echo("Published date:\t UNKNOWN") else: click.echo("Published date:\t "+volInfo['publishedDate']) if ('pageCount' not in volInfo): click.echo("Page count:\t UNKNOWN") else: click.echo("Page count:\t "+str(volInfo['pageCount'])) click.echo("Language:\t "+volInfo['language']) click.echo("Sale Info: ") click.echo(" Country:\t "+salInfo['country']) if salInfo['saleability']=='FOR_SALE': click.echo(" Price:\t "+str(salInfo['retailPrice']['amount'])+" "+salInfo['retailPrice']['currencyCode']) if salInfo['retailPrice']['amount']==0.0: click.echo(" Opening...") url=accInfo['webReaderLink'] chrome_path="C:\\Program Files (x86)\\Google\\Chrome\\Application\\chrome.exe" webbrowser.register('chrome', None, webbrowser.BackgroundBrowser(chrome_path)) webbrowser.get('chrome').open_new_tab(url) elif salInfo['saleability']=='FREE': click.echo(" Price:\t The book is FREE!") click.echo(" Opening...") if 'downloadLink' not in accInfo['pdf']: click.echo("NO DOWNLOAD LINK...") if 'webReaderLink' not in accInfo: click.echo("NO WEB READER LINK") pass else: url=accInfo['webReaderLink'] chrome_path="C:\\Program Files (x86)\\Google\\Chrome\\Application\\chrome.exe" webbrowser.register('chrome', None,webbrowser.BackgroundBrowser(chrome_path)) webbrowser.get('chrome').open_new_tab(url) pass else: url=accInfo['pdf']['downloadLink'] # file_name=volInfo['title'] #later for naming the downloaded file chrome_path="C:\\Program Files (x86)\\Google\\Chrome\\Application\\chrome.exe" webbrowser.register('chrome', None,webbrowser.BackgroundBrowser(chrome_path)) webbrowser.get('chrome').open_new_tab(url) pass elif salInfo['saleability']=='NOT_FOR_SALE': click.echo(" Price:\t NOT FOR SALE") pass pass @main.command() @click.argument('id') def get(id): """This return a particular book from the given id on Google Books""" url_format = 'https://www.googleapis.com/books/v1/volumes/{}' click.echo(id) response = requests.get(url_format.format(id)) responseInJSON=response.json() with open('searchQuery.json','w') as json_file: #stores a query json.dump(responseInJSON,json_file) for i in range(len(responseInJSON['items'])): volInfo=responseInJSON['items'][i]['volumeInfo'] salInfo=responseInJSON['items'][i]['saleInfo'] accInfo=responseInJSON['items'][i]['accessInfo'] click.echo("__________________________________________________________________________________") click.echo("Title:\t\t "+volInfo['title']) if ('subtitle' in volInfo): click.echo(" "+str(volInfo['subtitle'])) if ('authors' not in volInfo): click.echo("Authors:\t UNKNOWN") pass elif len(volInfo['authors'])==1: click.echo("Author:\t\t "+str(volInfo['authors'][0])) elif len(volInfo['authors'])>1: for author in volInfo['authors']: click.echo("Author:\t\t "+author) pass pass if ('publishedDate' not in volInfo): click.echo("Published date:\t UNKNOWN") else: click.echo("Published date:\t "+volInfo['publishedDate']) if ('pageCount' not in volInfo): click.echo("Page count:\t UNKNOWN") else: click.echo("Page count:\t "+str(volInfo['pageCount'])) click.echo("Language:\t "+volInfo['language']) click.echo("Sale Info: ") click.echo(" Country:\t "+salInfo['country']) if salInfo['saleability']=='FOR_SALE': click.echo(" Price:\t "+str(salInfo['retailPrice']['amount'])+" "+salInfo['retailPrice']['currencyCode']) pass elif salInfo['saleability']=='FREE': click.echo(" Price:\t The book is FREE!") ###### click.echo(" Downloading...") url=accInfo['pdf']['downloadLink'] file_name=volInfo['title'] r=requests.get(url) with open(file_name+".pdf", "wb") as code: code.write(r.content) pass click.echo("File downloaded! ") ###### pass elif salInfo['saleability']=='NOT_FOR_SALE': click.echo(" Price:\t NOT FOR SALE") pass pass if __name__ == "__main__": main()

39.111111

121

0.547585

712

7,040

5.119382

0.19382

0.101235

0.034568

0.044444

0.799726

0.775583

0.755281

0.73059

0

0.003696

0.308239

7,040

180

122

39.111111

0.744764

0.056534

0

0.751773

0

0.279707

0.047033

0

1

0.021277

false

0.120567

0.028369

0

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0

null

0

1

0

1

0

null

0

1

0

7

cd578e0458d5ed79f927db11e9c635c287a460cb

19,467

py

Python

inn/inn_hotels/doctype/inn_key_card/inn_key_card.py

vinhnguyent090/front-desk

7384642e9206e30855986465a7ef63c8fd76ef2a

[ "MIT" ]

4

2021-08-19T03:33:36.000Z

2021-08-28T16:37:52.000Z

inn/inn_hotels/doctype/inn_key_card/inn_key_card.py

vinhnguyent090/front-desk

7384642e9206e30855986465a7ef63c8fd76ef2a

[ "MIT" ]

98

2020-02-24T08:12:47.000Z

2021-08-21T07:54:03.000Z

inn/inn_hotels/doctype/inn_key_card/inn_key_card.py

vinhnguyent090/front-desk

7384642e9206e30855986465a7ef63c8fd76ef2a

[ "MIT" ]

13

2021-01-24T18:08:43.000Z

2022-03-29T09:23:25.000Z

# -*- coding: utf-8 -*- # Copyright (c) 2020, Core Initiative and contributors # For license information, please see license.txt from __future__ import unicode_literals from datetime import datetime, timedelta import frappe import requests import json from frappe.model.document import Document class InnKeyCard(Document): pass @frappe.whitelist() def room_max_active_card(): return frappe.db.get_single_value('Inn Hotels Setting', 'room_max_active_card') @frappe.whitelist() def issue_card(reservation_id): door_lock_provider = frappe.db.get_single_value('Inn Hotels Setting', 'door_lock_api_provider') if door_lock_provider == 'TESA': doc = frappe.get_doc('Inn Reservation', reservation_id) room = doc.actual_room_id expiryDate = datetime.strftime(doc.departure, "%d/%m/%Y") cards = doc.issued_card active_card = 0 for card in cards: active_card += int(card.is_active) if active_card == 0: cmd = "CI" else: cmd = "CG" new_card = frappe.new_doc('Inn Key Card') new_card.card_number = tesa_checkin(cmd, room, expiryDate) if new_card.card_number == "E2" or new_card.card_number == "ED": return 'ERROR' else: new_card.room_id = doc.actual_room_id new_card.issue_date = datetime.today() new_card.expired_date = doc.departure new_card.parent = doc.name new_card.parentfield = 'issued_card' new_card.parenttype = 'Inn Reservation' new_card.insert() return new_card.card_number elif door_lock_provider == 'DOWS': doc = frappe.get_doc('Inn Reservation', reservation_id) room = doc.actual_room_id expiryDate = datetime.strftime(doc.departure, "%Y-%m-%d") new_card = frappe.new_doc('Inn Key Card') new_card.card_number = dows_checkin("01", room, expiryDate) if new_card.card_number is None: return 'ERROR' else: new_card.room_id = doc.actual_room_id new_card.issue_date = datetime.today() new_card.expired_date = doc.departure new_card.parent = doc.name new_card.parentfield = 'issued_card' new_card.parenttype = 'Inn Reservation' new_card.insert() return new_card.card_number @frappe.whitelist() def erase_card(flag, card_name): door_lock_provider = frappe.db.get_single_value('Inn Hotels Setting', 'door_lock_api_provider') if door_lock_provider == 'TESA': doc = frappe.get_doc('Inn Key Card', card_name) room = doc.room_id expiryDate = datetime.strftime(datetime.today() - timedelta(1), '%d/%m/%Y') if flag == 'with': card_number_returned = tesa_erase() if card_number_returned == doc.card_number: doc.expired_date = datetime.today() - timedelta(1) doc.is_active = 0 doc.save() return doc.is_active elif card_number_returned == "E2" or card_number_returned == "ED": return 'ERROR' elif flag == 'without': doc.expired_date = datetime.today() - timedelta(1) doc.is_active = 0 doc.save() return doc.is_active elif door_lock_provider == 'DOWS': doc = frappe.get_doc('Inn Key Card', card_name) room = doc.room_id if flag == 'with': message_erase = dows_erase(room) if message_erase is not None: doc.is_active = 0 doc.save() return doc.is_active elif flag == 'without': doc.expired_date = datetime.today() - timedelta(1) doc.is_active = 0 doc.save() return doc.is_active def tesa_erase(): # api-endpoint api_checkin_url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') + '/checkin' # defining a params dict for the parameters to be sent to the API params = { "cmd": "CI", "room": "999", "activationDate": datetime.today().strftime("%d/%m/%Y"), "activationTime": "12:00", "expiryDate": (datetime.today() - timedelta(1)).strftime("%d/%m/%Y"), "expiryTime": "12:00", "returnCardId": "1" } if api_checkin_url is not None: if int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) == 1: auth = (frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user'), frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password')) r = requests.post(api_checkin_url, json=params, auth=auth) else: r = requests.post(api_checkin_url, json=params) if r: returned = json.loads(r.text) msg_hex = returned['rawMsgHex'] data = msg_hex.split("B3") card_number = bytearray.fromhex(data[-2]).decode() r.close() return card_number else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def tesa_checkin(cmd, room_id, expiry_date): # api-endpoint api_checkin_url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') + '/checkin' # defining a params dict for the parameters to be sent to the API params = { "cmd": cmd, "room": room_id.replace('R-', ''), "activationDate": datetime.today().strftime("%d/%m/%Y"), "activationTime": "12:00", "expiryDate": expiry_date, "expiryTime": "14:00", "returnCardId": "1" } if api_checkin_url is not None: if int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) == 1: auth = (frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user'), frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password')) r = requests.post(api_checkin_url, json=params, auth=auth) else: r = requests.post(api_checkin_url, json=params) if r: returned = json.loads(r.text) msg_hex = returned['rawMsgHex'] data = msg_hex.split("B3") card_number = bytearray.fromhex(data[-2]).decode() r.close() return card_number else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def tesa_verify(track): # api-endpoint api_verify_url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') + '/verify' # defining a params dict for the parameters to be sent to the API params = { "cmd": "RC", "technology": "P", "cardOperation": "RP", "encoder": "1", "format": "T", "track": track } if api_verify_url is not None: if int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) == 1: auth = (frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user'), frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password')) r = requests.post(api_verify_url, json=params, auth=auth) else: r = requests.post(api_verify_url, json=params) if r: returned = json.loads(r.text) r.close() return returned else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def dows_checkin(building, room_id, expiry_date): api_checkin_url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') + '/checkin' params = { "building": building, "room": room_id.replace('R-', '').zfill(4), "door": "00", "arrival": datetime.today().strftime("%Y-%m-%d") + " 12:00:00", "departure": expiry_date + " 14:00:00", } if api_checkin_url is not None: s = requests.Session() headers = {"Content-Type": "application/json"} req = requests.Request('POST', api_checkin_url, json=params, headers=headers) prepped = s.prepare_request(req) del prepped.headers['Connection'] del prepped.headers['Accept-Encoding'] del prepped.headers['Accept'] r = s.send(prepped) if r: returned = json.loads(r.text) r.close() return returned['cardNo'] else: frappe.msgprint("Error. Fail to Connect to CardEncoder. Please wait a moment and try again.") def dows_verify(): api_checkin_url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') + '/verify' if api_checkin_url is not None: s = requests.Session() req = requests.Request('GET', api_checkin_url) prepped = s.prepare_request(req) del prepped.headers['Connection'] del prepped.headers['Accept-Encoding'] del prepped.headers['Accept'] r = s.send(prepped) if r: returned = json.loads(r.text) r.close() return returned def dows_erase(room_id): api_checkin_url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') + '/erase/' + room_id.replace('R-', '').zfill(4) if api_checkin_url is not None: s = requests.Session() req = requests.Request('DELETE', api_checkin_url) prepped = s.prepare_request(req) del prepped.headers['Connection'] del prepped.headers['Accept-Encoding'] del prepped.headers['Accept'] r = s.send(prepped) if r: returned = json.loads(r.text) r.close() return returned['cardNo'] @frappe.whitelist() def test_api(option): if option == "1": frappe.msgprint("tesa_read_card1") returned = tesa_read_card1("3") frappe.msgprint("User = " + returned['user']) frappe.msgprint("Expiry Date = " + returned['expiryDate']) frappe.msgprint("Info = " + returned['info']) elif option == "2": frappe.msgprint("tesa_read_card2") returned = tesa_read_card2("3") frappe.msgprint("User = " + returned['user']) frappe.msgprint("Expiry Date = " + returned['expiryDate']) frappe.msgprint("Info = " + returned['info']) elif option == "3": frappe.msgprint("tesa_read_card3") returned = tesa_read_card3("3") frappe.msgprint("User = " + returned['user']) frappe.msgprint("Expiry Date = " + returned['expiryDate']) frappe.msgprint("Info = " + returned['info']) elif option == "4": frappe.msgprint("tesa_read_card4") returned = tesa_read_card4("3") frappe.msgprint("User = " + returned['user']) frappe.msgprint("Expiry Date = " + returned['expiryDate']) frappe.msgprint("Info = " + returned['info']) @frappe.whitelist() def verify_card(track): door_lock_provider = frappe.db.get_single_value('Inn Hotels Setting', 'door_lock_api_provider') if door_lock_provider == 'TESA': returned = tesa_verify(track) frappe.msgprint("User = " + returned['user']) frappe.msgprint("Expiry Date = " + returned['expiryDate']) frappe.msgprint("Expiry Time = " + returned['expiryTime']) elif door_lock_provider == 'DOWS': returned = dows_verify() frappe.msgprint("Room = R-" + returned['room'].lstrip("0")) frappe.msgprint("Expiry Date = " + returned['departure']) def tesa_check_in(cmd, room, activationDate, activationTime, expiryDate, expiryTime, pcId="", technology="P", encoder="1", cardOperation="EF", grant=None, keypad=None, operator=None, track1=None, track2=None, room2=None, room3=None, room4=None, returnCardId=None, cardId=None): # Example Post # {"pcId": "1", "cmd": "PI", "room": "102", "activationDate": "16/05/2017", # "activationTime": "12:00", "expiryDate": "17/05/2017", "expiryTime": "12:00", # "cardOperation": "RP", "operator": "tesa"} # api-endpoint url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') username = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user') password = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password') is_card_use_auth = int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) # defining header JSON headers = {'Content-Type': 'application/json', 'Accept': 'text/plain'} # defining auth to be sent to the API if is_card_use_auth == 1: auth = (username, password) # defining a params dict for the parameters to be sent to the API params = { 'pcId': pcId, 'cmd': cmd, 'technology': technology, 'cardOperation': cardOperation, 'encoder': encoder, 'room': room, 'activationDate': activationDate, 'activationTime': activationTime, 'expiryDate': expiryDate, 'expiryTime': expiryTime, } # Optional params assignment if provided if grant is not None: params.update({'grant': grant}) if keypad is not None: params.update({'keypad': keypad}) if operator is not None: params.update({'operator': operator}) if track1 is not None: params.update({'track1': track1}) if track2 is not None: params.update({'track2': track2}) if room2 is not None: params.update({'room2': room2}) if room3 is not None: params.update({'room3': room3}) if room4 is not None: params.update({'room4': room4}) if returnCardId is not None: params.update({'returnCardId': returnCardId}) if cardId is not None: params.update({'cardId': cardId}) if url is not None: if is_card_use_auth == 1: r = requests.post(url, data=params, headers=headers, auth=auth) else: r = requests.post(url, data=params, headers=headers) if r: returned = json.loads(r.text) return returned['returnCardId'] else: return "CARD NUMBER FROM TESA CHECK IN" else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def tesa_read_card(track, pcId="", cmd="RC", technology="P", cardOperation="EF", encoder="1", format="T", message="" ): # Example Post # {"pcId": "", "cmd": "RC", "technology": "P", "cardOperation": "EF", "encoder": # "1", "format": "T", "track": "3", "message": ""} # api-endpoint url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') username = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user') password = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password') is_card_use_auth = int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) # defining header JSON headers = {'Content-Type': 'application/json', 'Accept': 'text/plain'} # defining auth to be sent to the API if is_card_use_auth == 1: auth = (username, password) # defining a params dict for the parameters to be sent to the API params = { 'pcId': pcId, 'cmd': cmd, 'technology': technology, 'cardOperation': cardOperation, 'encoder': encoder, 'format': format, 'track': track, 'message': message, } if url is not None: if is_card_use_auth == 1: r = requests.post(url, data=params, headers=headers, auth=auth) else: r = requests.post(url, data=params, headers=headers) if r: returned = json.loads(r.text) return returned else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def tesa_read_card1(track, pcId="", cmd="RC", technology="P", cardOperation="EF", encoder="1", format="T", message="" ): # Example Post # {"pcId": "", "cmd": "RC", "technology": "P", "cardOperation": "EF", "encoder": # "1", "format": "T", "track": "3", "message": ""} # api-endpoint url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') username = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user') password = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password') is_card_use_auth = int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) # defining header JSON headers = {'Content-Type': 'application/json', 'Accept': 'text/plain'} # defining auth to be sent to the API if is_card_use_auth == 1: auth = (username, password) # defining a params dict for the parameters to be sent to the API params = { 'pcId': pcId, 'cmd': cmd, 'technology': technology, 'cardOperation': cardOperation, 'encoder': encoder, 'format': format, 'track': track, 'message': message, } if url is not None: if is_card_use_auth == 1: r = requests.post(url, json=params, auth=auth) else: r = requests.post(url, json=params) if r: print("headers: ") print(r.headers) returned = json.loads(r.text) return returned else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def tesa_read_card2(track, pcId="", cmd="RC", technology="P", cardOperation="EF", encoder="1", format="T", message="" ): # Example Post # {"pcId": "", "cmd": "RC", "technology": "P", "cardOperation": "EF", "encoder": # "1", "format": "T", "track": "3", "message": ""} # api-endpoint url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') username = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user') password = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password') is_card_use_auth = int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) # defining header JSON headers = {'Content-Type': 'application/json', 'Accept': 'text/plain'} # defining auth to be sent to the API if is_card_use_auth == 1: auth = (username, password) # defining a params dict for the parameters to be sent to the API params = { 'pcId': pcId, 'cmd': cmd, 'technology': technology, 'cardOperation': cardOperation, 'encoder': encoder, 'format': format, 'track': track, 'message': message, } if url is not None: if is_card_use_auth == 1: r = requests.post(url, data=json.dumps(params), auth=auth) else: r = requests.post(url, data=json.dumps(params)) if r: print("headers: ") print(r.headers) returned = json.loads(r.text) return returned else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def tesa_read_card3(track, pcId="", cmd="RC", technology="P", cardOperation="EF", encoder="1", format="T", message="" ): # Example Post # {"pcId": "", "cmd": "RC", "technology": "P", "cardOperation": "EF", "encoder": # "1", "format": "T", "track": "3", "message": ""} # api-endpoint url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') username = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user') password = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password') is_card_use_auth = int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) # defining header JSON headers = {'Content-Type': 'application/json', 'Accept': 'text/plain'} # defining auth to be sent to the API if is_card_use_auth == 1: auth = (username, password) # defining a params dict for the parameters to be sent to the API params = { 'pcId': pcId, 'cmd': cmd, 'technology': technology, 'cardOperation': cardOperation, 'encoder': encoder, 'format': format, 'track': track, 'message': message, } if url is not None: if is_card_use_auth == 1: r = requests.post(url, data=params, headers=headers, auth=auth) else: r = requests.post(url, data=params, headers=headers) if r: print("headers: ") print(r.headers) returned = json.loads(r.text) return returned else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting") def tesa_read_card4(track, pcId="", cmd="RC", technology="P", cardOperation="EF", encoder="1", format="T", message="" ): # Example Post # {"pcId": "", "cmd": "RC", "technology": "P", "cardOperation": "EF", "encoder": # "1", "format": "T", "track": "3", "message": ""} # api-endpoint url = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_url') username = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_user') password = frappe.db.get_single_value('Inn Hotels Setting', 'card_api_password') is_card_use_auth = int(frappe.db.get_single_value('Inn Hotels Setting', 'card_use_auth')) # defining header JSON headers = {'Content-Type': 'application/json'} # defining auth to be sent to the API if is_card_use_auth == 1: auth = (username, password) # defining a params dict for the parameters to be sent to the API params = { 'pcId': pcId, 'cmd': cmd, 'technology': technology, 'cardOperation': cardOperation, 'encoder': encoder, 'format': format, 'track': track, 'message': message, } if url is not None: if is_card_use_auth == 1: r = requests.post(url, data=params, headers=headers, auth=auth) else: r = requests.post(url, data=params, headers=headers) if r: print("headers: ") print(r.headers) returned = json.loads(r.text) return returned else: frappe.msgprint("Card API url not defined yet. Define the URL in Inn Hotel Setting")

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null

0

7

cd65ca9a9290598c75c1bf6b3829eecd62633159

281

py

Python

Server/Controller/IndicatorController.py

admantiumblack/invest-trigger-fastapi

f21fb7d7b512bb80a5da3000bdb581023ac7a177

[ "MIT" ]

null

Server/Controller/IndicatorController.py

admantiumblack/invest-trigger-fastapi

f21fb7d7b512bb80a5da3000bdb581023ac7a177

[ "MIT" ]

null

Server/Controller/IndicatorController.py

admantiumblack/invest-trigger-fastapi

f21fb7d7b512bb80a5da3000bdb581023ac7a177

[ "MIT" ]

null

import pandas_ta as pdt def moving_average(prices, period, limit): res = pdt.sma(prices['prices'], period) return res.iloc[-limit:].to_numpy() def exponential_moving_average(prices, period, limit): res = pdt.ema(prices, period) return res.iloc[-limit:].to_numpy

25.545455

54

0.711744

41

281

4.731707

0.463415

0.247423

0.195876

0.257732

0.752577

0.381443

0

0.153025

281

11

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25.545455

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1

0

1

0

null

0

1

0

1

0

7

26e66627ab2a463b600658a3439cd1d4ee9df608

20,669

py

Python

mff/models/eam.py

alvarovm/mff

cd1b22b606dfd64d91dc94fece72ad6a707212af

[ "Apache-2.0" ]

14

2019-03-22T18:57:34.000Z

2021-12-15T11:37:17.000Z

mff/models/eam.py

alvarovm/mff

cd1b22b606dfd64d91dc94fece72ad6a707212af

[ "Apache-2.0" ]

4

2019-06-18T14:55:46.000Z

2019-11-26T19:34:59.000Z

mff/models/eam.py

alvarovm/mff

cd1b22b606dfd64d91dc94fece72ad6a707212af

[ "Apache-2.0" ]

3

2019-08-05T14:42:20.000Z

2022-03-16T18:48:54.000Z

# -*- coding: utf-8 -*- import json import warnings from itertools import combinations_with_replacement from pathlib import Path import numpy as np from mff import gp, interpolation, kernels, utility from mff.models.base import Model class NpEncoder(json.JSONEncoder): def default(self, obj): if isinstance(obj, np.integer): return int(obj) elif isinstance(obj, np.floating): return float(obj) elif isinstance(obj, np.ndarray): return obj.tolist() else: return super(NpEncoder, self).default(obj) def get_max_eam(X, rc, r0): t_max = 0 for c in X: dist = np.sum(c[:, :3]**2, axis=1)**0.5 cut_1 = 0.5*(1 + np.cos(np.pi*dist/rc)) t1 = np.exp(-(dist/r0 - 1)) t2 = -sum(cut_1*t1)**0.5 if t2 < t_max: t_max = t2 return t_max def get_max_eam_energy(X_glob, rc, r0): t_max = 0 for X in X_glob: t2 = get_max_eam(X, rc, r0) if t2 < t_max: t_max = t2 return t_max class EamSingleSpeciesModel(Model): """ Eam single species model class Class managing the Gaussian process and its mapped counterpart Args: element (int): The atomic number of the element considered r_cut (foat): The cutoff radius used to carve the atomic environments sigma (foat): Lengthscale parameter of the Gaussian process theta (float): decay ratio of the cutoff function in the Gaussian Process noise (float): noise value associated with the training output data Attributes: gp (method): The eam single species Gaussian Process grid (method): The eam single species tabulated potential grid_start (float): Minimum descriptor value for which the grid is defined grid_end (float): Maximum descriptor value for which the grid is defined grid_num (int): number of points used to create the eam multi grid """ def __init__(self, element, r_cut, sigma, r0, noise, **kwargs): super().__init__() self.element = element self.r_cut = r_cut kernel = kernels.EamSingleSpeciesKernel( theta=[sigma, r_cut, r0]) self.gp = gp.GaussianProcess(kernel=kernel, noise=noise, **kwargs) self.grid, self.grid_start, self.grid_end, self.grid_num = None, None, None, None def fit(self, confs, forces, ncores=1): """ Fit the GP to a set of training forces using a eam single species force-force kernel Args: confs (list): List of M x 5 arrays containing coordinates and atomic numbers of atoms within a cutoff from the central one forces (array) : Array containing the vector forces on the central atoms of the training configurations ncores (int): number of CPUs to use for the gram matrix evaluation """ self.gp.fit(confs, forces, ncores=ncores) def fit_energy(self, glob_confs, energies, ncores=1): """ Fit the GP to a set of training energies using a eam single species energy-energy kernel Args: glob_confs (list of lists): List of configurations arranged so that grouped configurations belong to the same snapshot energies (array) : Array containing the total energy of each snapshot ncores (int): number of CPUs to use for the gram matrix evaluation """ self.gp.fit_energy(glob_confs, energies, ncores=ncores) def fit_force_and_energy(self, confs, forces, glob_confs, energies, ncores=1): """ Fit the GP to a set of training forces and energies using eam single species force-force, energy-force and energy-energy kernels Args: confs (list): List of M x 5 arrays containing coordinates and atomic numbers of atoms within a cutoff from the central one forces (array) : Array containing the vector forces on the central atoms of the training configurations glob_confs (list of lists): List of configurations arranged so that grouped configurations belong to the same snapshot energies (array) : Array containing the total energy of each snapshot ncores (int): number of CPUs to use for the gram matrix evaluation """ self.gp.fit_force_and_energy( confs, forces, glob_confs, energies, ncores=ncores) def predict(self, confs, return_std=False, ncores=1): """ Predict the forces acting on the central atoms of confs using a GP Args: confs (list): List of M x 5 arrays containing coordinates and atomic numbers of atoms within a cutoff from the central one return_std (bool): if True, returns the standard deviation associated to predictions according to the GP framework Returns: forces (array): array of force vectors predicted by the GP forces_errors (array): errors associated to the force predictions, returned only if return_std is True """ return self.gp.predict(confs, return_std, ncores=ncores) def predict_energy(self, glob_confs, return_std=False, ncores=1): """ Predict the global energies of the central atoms of confs using a GP Args: glob_confs (list of lists): List of configurations arranged so that grouped configurations belong to the same snapshot return_std (bool): if True, returns the standard deviation associated to predictions according to the GP framework Returns: energies (array) : Array containing the total energy of each snapshot energies_errors (array): errors associated to the energies predictions, returned only if return_std is True """ return self.gp.predict_energy(glob_confs, return_std, ncores=ncores) def save_gp(self, filename): """ Saves the GP object, now obsolete """ warnings.warn('use save and load function', DeprecationWarning) self.gp.save(filename) def load_gp(self, filename): """ Loads the GP object, now obsolete """ warnings.warn('use save and load function', DeprecationWarning) self.gp.load(filename) def build_grid(self, num, ncores=1): """ Build the mapped eam potential. Calculates the energy predicted by the GP for a configuration which eam descriptor is evalued between start and end. These energies are stored and a 1D spline interpolation is created, which can be used to predict the energy and, through its analytic derivative, the force associated to any embedded atom. The prediction is done by the ``calculator`` module which is built to work within the ase python package. Args: num (int): number of points to use in the grid of the mapped potential ncores (int): number of CPUs to use for the gram matrix evaluation """ if 'force' in self.gp.fitted: self.grid_start = 3.0 * \ get_max_eam(self.gp.X_train_, self.r_cut, self.gp.kernel.theta[2]) else: self.grid_start = 3.0 * \ get_max_eam_energy(self.gp.X_glob_train_, self.r_cut, self.gp.kernel.theta[2]) self.grid_end = 0 self.grid_num = num dists = list(np.linspace(self.grid_start, self.grid_end, self.grid_num)) grid_data = self.gp.predict_energy(dists, ncores=ncores, mapping=True) self.grid = interpolation.Spline1D(dists, grid_data) def save(self, path): """ Save the model. This creates a .json file containing the parameters of the model and the paths to the GP objects and the mapped potential, which are saved as separate .gpy and .gpz files, respectively. Args: path (str): path to the file """ if not isinstance(path, Path): path = Path(path) params = { 'model': self.__class__.__name__, 'element': self.element, 'r_cut': self.r_cut, 'fitted': self.gp.fitted, 'gp': { 'kernel': self.gp.kernel.kernel_name, 'n_train': self.gp.n_train, 'sigma': self.gp.kernel.theta[0], 'noise': self.gp.noise, 'r0': self.gp.kernel.theta[2] }, 'grid': { 'r_min': self.grid_start, 'r_max': self.grid_end, 'r_num': self.grid_num, 'filename': {} } if self.grid else {} } gp_filename = "GP_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.npy".format( p=params) params['gp']['filename'] = gp_filename self.gp.save(path / gp_filename) if self.grid: grid_filename = 'GRID_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.npz'.format( p=params) params['grid']['filename'] = grid_filename self.grid.save(path / grid_filename) with open(path / 'MODEL_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.json'.format(p=params), 'w') as fp: json.dump(params, fp, indent=4, cls=NpEncoder) print("Saved model with name: MODEL_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.json".format(p=params)) @classmethod def from_json(cls, path): """ Load the model. Loads the model, the associated GP and the mapped potential, if available. Args: path (str): path to the .json model file Return: model (obj): the model object """ if not isinstance(path, Path): path = Path(path) directory, prefix = path.parent, path.stem with open(path) as fp: params = json.load(fp) model = cls(params['element'], params['r_cut'], params['gp']['sigma'], params['gp']['noise'], params['gp']['r0']) gp_filename = params['gp']['filename'] model.gp.load(directory / gp_filename) if params['grid']: grid_filename = params['grid']['filename'] model.grid = interpolation.Spline1D.load(directory / grid_filename) model.grid_start = params['grid']['r_min'] model.grid_end = params['grid']['r_max'] model.grid_num = params['grid']['r_num'] return model class EamManySpeciesModel(Model): """ Eam many species model class Class managing the Gaussian process and its mapped counterpart Args: elements (int): The atomic numbers of the element considered r_cut (foat): The cutoff radius used to carve the atomic environments sigma (foat): Lengthscale parameter of the Gaussian process r0 (float): radius in the exponent of the eam descriptor noise (float): noise value associated with the training output data Attributes: gp (method): The eam single species Gaussian Process grid (method): The eam single species tabulated potential grid_start (float): Minimum descriptor value for which the grid is defined grid_end (float): Maximum descriptor value for which the grid is defined grid_num (int): number of points used to create the eam multi grid """ def __init__(self, elements, r_cut, sigma, r0, noise, **kwargs): super().__init__() self.elements = list(np.sort(elements)) self.r_cut = r_cut kernel = kernels.EamManySpeciesKernel( theta=[sigma, r_cut, r0]) self.gp = gp.GaussianProcess(kernel=kernel, noise=noise, **kwargs) self.grid, self.grid_start, self.grid_end, self.grid_num = {}, None, None, None def fit(self, confs, forces, ncores=1): """ Fit the GP to a set of training forces using a eam single species force-force kernel Args: confs (list): List of M x 5 arrays containing coordinates and atomic numbers of atoms within a cutoff from the central one forces (array) : Array containing the vector forces on the central atoms of the training configurations ncores (int): number of CPUs to use for the gram matrix evaluation """ self.gp.fit(confs, forces, ncores=ncores) def fit_energy(self, glob_confs, energies, ncores=1): """ Fit the GP to a set of training energies using a eam single species energy-energy kernel Args: glob_confs (list of lists): List of configurations arranged so that grouped configurations belong to the same snapshot energies (array) : Array containing the total energy of each snapshot ncores (int): number of CPUs to use for the gram matrix evaluation """ self.gp.fit_energy(glob_confs, energies, ncores=ncores) def fit_force_and_energy(self, confs, forces, glob_confs, energies, ncores=1): """ Fit the GP to a set of training forces and energies using eam single species force-force, energy-force and energy-energy kernels Args: confs (list): List of M x 5 arrays containing coordinates and atomic numbers of atoms within a cutoff from the central one forces (array) : Array containing the vector forces on the central atoms of the training configurations glob_confs (list of lists): List of configurations arranged so that grouped configurations belong to the same snapshot energies (array) : Array containing the total energy of each snapshot ncores (int): number of CPUs to use for the gram matrix evaluation """ self.gp.fit_force_and_energy( confs, forces, glob_confs, energies, ncores=ncores) def predict(self, confs, return_std=False, ncores=1): """ Predict the forces acting on the central atoms of confs using a GP Args: confs (list): List of M x 5 arrays containing coordinates and atomic numbers of atoms within a cutoff from the central one return_std (bool): if True, returns the standard deviation associated to predictions according to the GP framework Returns: forces (array): array of force vectors predicted by the GP forces_errors (array): errors associated to the force predictions, returned only if return_std is True """ return self.gp.predict(confs, return_std, ncores=ncores) def predict_energy(self, glob_confs, return_std=False, ncores=1): """ Predict the global energies of the central atoms of confs using a GP Args: glob_confs (list of lists): List of configurations arranged so that grouped configurations belong to the same snapshot return_std (bool): if True, returns the standard deviation associated to predictions according to the GP framework Returns: energies (array) : Array containing the total energy of each snapshot energies_errors (array): errors associated to the energies predictions, returned only if return_std is True """ return self.gp.predict_energy(glob_confs, return_std, ncores=ncores) def save_gp(self, filename): """ Saves the GP object, now obsolete """ warnings.warn('use save and load function', DeprecationWarning) self.gp.save(filename) def load_gp(self, filename): """ Loads the GP object, now obsolete """ warnings.warn('use save and load function', DeprecationWarning) self.gp.load(filename) def build_grid(self, num, ncores=1): """ Build the mapped eam potential. Calculates the energy predicted by the GP for a configuration which eam descriptor is evalued between start and end. These energies are stored and a 1D spline interpolation is created, which can be used to predict the energy and, through its analytic derivative, the force associated to any embedded atom. The prediction is done by the ``calculator`` module which is built to work within the ase python package. Args: num (int): number of points to use in the grid of the mapped potential ncores (int): number of CPUs to use for the gram matrix evaluation """ if 'force' in self.gp.fitted: self.grid_start = 3.0 * \ get_max_eam(self.gp.X_train_, self.r_cut, self.gp.kernel.theta[2]) else: self.grid_start = 3.0 * \ get_max_eam_energy(self.gp.X_glob_train_, self.r_cut, self.gp.kernel.theta[2]) self.grid_end = 0 self.grid_num = num dists = list(np.linspace(self.grid_start, self.grid_end, self.grid_num)) for el in self.elements: grid_data = self.gp.predict_energy(dists, ncores=ncores, mapping=True, alpha_1_descr=el) self.grid[(el)] = interpolation.Spline1D(dists, grid_data) def save(self, path): """ Save the model. This creates a .json file containing the parameters of the model and the paths to the GP objects and the mapped potential, which are saved as separate .gpy and .gpz files, respectively. Args: path (str): path to the file """ if not isinstance(path, Path): path = Path(path) params = { 'model': self.__class__.__name__, 'elements': self.elements, 'r_cut': self.r_cut, 'fitted': self.gp.fitted, 'gp': { 'kernel': self.gp.kernel.kernel_name, 'n_train': self.gp.n_train, 'sigma': self.gp.kernel.theta[0], 'noise': self.gp.noise, 'r0': self.gp.kernel.theta[2] }, 'grid': { 'r_min': self.grid_start, 'r_max': self.grid_end, 'r_num': self.grid_num, 'filename': {} } if self.grid else {} } gp_filename = "GP_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.npy".format( p=params) params['gp']['filename'] = gp_filename self.gp.save(path / gp_filename) for k, grid in self.grid.items(): key = str(k) grid_filename = "GRID_{}_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.npz".format( key, p=params) params['grid']['filename'][key] = grid_filename grid.save(path / grid_filename) with open(path / "MODEL_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.json".format(p=params), 'w') as fp: json.dump(params, fp, indent=4, cls=NpEncoder) print("Saved model with name: MODEL_ker_{p[gp][kernel]}_ntr_{p[gp][n_train]}.json".format(p=params)) @classmethod def from_json(cls, path): """ Load the model. Loads the model, the associated GP and the mapped potential, if available. Args: path (str): path to the .json model file Return: model (obj): the model object """ if not isinstance(path, Path): path = Path(path) directory, prefix = path.parent, path.stem with open(path) as fp: params = json.load(fp) model = cls(params['elements'], params['r_cut'], params['gp']['sigma'], params['gp']['noise'], params['gp']['r0']) gp_filename = params['gp']['filename'] model.gp.load(directory / gp_filename) if params['grid']: model.grid_start = params['grid']['r_min'] model.grid_end = params['grid']['r_max'] model.grid_num = params['grid']['r_num'] for key, grid_filename in params['grid']['filename'].items(): k = tuple(key) model.grid[k] = interpolation.Spline1D.load( directory / grid_filename) return model

37.717153

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0.601287

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0.018939

0.911067

0.903327

0.891798

0.887681

0.881917

0

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null

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1

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null

0

7

26f981b5f4863b73b97912d52e167354264db414

1,363

py

Python

utilities/test/norm_mrow_test.py

frozstone/concept

359a386941d0752fd9ecf97edaa4e69c52952513

[ "MIT" ]

2

2018-01-21T20:06:37.000Z

2020-05-26T00:11:05.000Z

utilities/test/norm_mrow_test.py

frozstone/concept

359a386941d0752fd9ecf97edaa4e69c52952513

[ "MIT" ]

null

utilities/test/norm_mrow_test.py

frozstone/concept

359a386941d0752fd9ecf97edaa4e69c52952513

[ "MIT" ]

null

from norm_mrow import norm_mrow if __name__ == '__main__': dtd = '<!DOCTYPE math SYSTEM "../resources/xhtml-math11-f.dtd">' n = norm_mrow(dtd) assert(n.normalize('<math><mrow><mn>3</mn></mrow><mo>+</mo><mrow><mi>i</mi></mrow></math>') == '<math><mn>3</mn><mo>+</mo><mi>i</mi></math>') assert(n.normalize('<math><msub><mi>x</mi><mrow><mn>2</mn></mrow></msub></math>') == '<math><msub><mi>x</mi><mn>2</mn></msub></math>') assert(n.normalize('<math><msub><mi>x</mi><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>') == '<math><msub><mi>x</mi><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>') assert(n.normalize('<math><msub><mrow><mi>x</mi></mrow><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>') == '<math><msub><mi>x</mi><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>') assert(n.normalize('<math><msub><mrow><mi>x</mi><mo>*</mo><mi>y</mi></mrow><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>') == '<math><msub><mrow><mi>x</mi><mo>*</mo><mi>y</mi></mrow><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>') assert(n.normalize('<math><msub><mrow><mi>x</mi><mo>*</mo><mrow><mi>y</mi></mrow></mrow><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>') == '<math><msub><mrow><mi>x</mi><mo>*</mo><mi>y</mi></mrow><mrow><mn>2</mn><mo>+</mo><mi>k</mi></mrow></msub></math>')

113.583333

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0.548056

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2.897638

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0.747283

0.713315

0

0.010811

0.04989

1,363

11

271

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Python

tsdf/ewa.py

Algomorph/LevelSetFusion-Python

46625cd185da4413f9afaf201096203ee72d3803

[ "Apache-2.0" ]

8

2019-01-30T19:01:25.000Z

2021-03-05T14:10:51.000Z

tsdf/ewa.py

Algomorph/LevelSetFusion-Python

46625cd185da4413f9afaf201096203ee72d3803

[ "Apache-2.0" ]

58

2018-12-19T16:57:38.000Z

2019-06-06T19:52:36.000Z

tsdf/ewa.py

Algomorph/LevelSetFusion-Python

46625cd185da4413f9afaf201096203ee72d3803

[ "Apache-2.0" ]

2

2019-03-06T06:30:30.000Z

2019-06-03T11:00:15.000Z

# ================================================================ # Created by Gregory Kramida on 1/21/19. # Copyright (c) 2019 Gregory Kramida # 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. # ================================================================ # EWA = Elliptical Weighted Average, this module provides routines for EWA sampling of the depth image to generate # a TSDF import numpy as np import math import math_utils.elliptical_gaussians as eg import tsdf.common as common import level_set_fusion_optimization as cpp_module # C++ extension import level_set_fusion_optimization as cpp_extension near_clipping_distance = 0.05 def find_sampling_bounds_helper(bounds_max, depth_image, voxel_image): start_x = int(voxel_image[0] - bounds_max[0]) end_x = int(math.ceil(voxel_image[0] + bounds_max[0] + 1)) start_y = int(voxel_image[1] - bounds_max[1]) end_y = int(math.ceil(voxel_image[1] + bounds_max[1] + 1)) if end_y <= 0 or start_y >= depth_image.shape[0] or end_x <= 0 or start_x >= depth_image.shape[1]: return None start_y = max(0, start_y) end_y = min(depth_image.shape[0], end_y) start_x = max(0, start_x) end_x = min(depth_image.shape[1], end_x) return start_x, end_x, start_y, end_y def find_sampling_bounds_inclusive_helper(bounds_max, depth_image, voxel_image): start_x = int(voxel_image[0] - bounds_max[0]) end_x = int(math.ceil(voxel_image[0] + bounds_max[0] + 1)) start_y = int(voxel_image[1] - bounds_max[1]) end_y = int(math.ceil(voxel_image[1] + bounds_max[1] + 1)) if end_y <= 0 or start_y >= depth_image.shape[0] or end_x <= 0 or start_x >= depth_image.shape[1]: return None return start_x, end_x, start_y, end_y def generate_tsdf_3d_ewa_image(depth_image, camera, camera_extrinsic_matrix=np.eye(4, dtype=np.float32), field_shape=np.array([128, 128, 128]), default_value=1, voxel_size=0.004, array_offset=np.array([-64, -64, 64]), narrow_band_width_voxels=20, back_cutoff_voxels=np.inf, gaussian_covariance_scale=1.0): """ Generate 3D TSDF field based on elliptical Gaussian averages (EWA) of depth values from the provided image. Elliptical Gaussian filters are projected from spherical 3D Gaussian functions onto the depth image and convolved with a circular 2D Gaussain filter before averaging the depth values. :type depth_image: np.ndarray :param depth_image: depth image to use :type camera: calib.camera.DepthCamera :param camera: camera used to generate the depth image :param voxel_size: voxel size, in meters :param array_offset: offset of the TSDF grid from the world origin :param camera_extrinsic_matrix: matrix representing transformation of the camera (incl. rotation and translation) [ R | T] [ 0 | 1] :param default_value: default initial TSDF value :param field_shape: shape of the TSDF grid to generate :param narrow_band_width_voxels: span (in voxels) where signed distance is between -1 and 1 :param back_cutoff_voxels: where to truncate the negative voxel values (currently not supported!) :param gaussian_covariance_scale: scale of elliptical gaussians (relative to voxel size) :return: resulting 3D TSDF """ # TODO: use back_cutoff_voxels for additional limit on # "if signed_distance < -narrow_band_half_width" (maybe?) if default_value == 1: field = np.ones(field_shape, dtype=np.float32) elif default_value == 0: field = np.zeros(field_shape, dtype=np.float32) else: field = np.ndarray(field_shape, dtype=np.float32) field.fill(default_value) camera_intrinsic_matrix = camera.intrinsics.intrinsic_matrix depth_ratio = camera.depth_unit_ratio narrow_band_half_width = narrow_band_width_voxels / 2 * voxel_size # in metric units w_voxel = 1.0 camera_rotation_matrix = camera_extrinsic_matrix[0:3, 0:3] covariance_voxel_sphere_world_space = np.eye(3) * (gaussian_covariance_scale * voxel_size) covariance_camera_space = camera_rotation_matrix.dot(covariance_voxel_sphere_world_space) \ .dot(camera_rotation_matrix.T) image_space_scaling_matrix = camera.intrinsics.intrinsic_matrix[0:2, 0:2] squared_radius_threshold = 4.0 * gaussian_covariance_scale * voxel_size for z_field in range(field_shape[2]): for y_field in range(field_shape[1]): for x_field in range(field_shape[0]): # coordinates deliberately flipped here to maintain consistency between Python & C++ implementations # Eigen Tensors being used are column-major, whereas here we use row-major layout by default x_voxel = (z_field + array_offset[0]) * voxel_size y_voxel = (y_field + array_offset[1]) * voxel_size z_voxel = (x_field + array_offset[2]) * voxel_size voxel_world = np.array([[x_voxel, y_voxel, z_voxel, w_voxel]], dtype=np.float32).T voxel_camera = camera_extrinsic_matrix.dot(voxel_world).flatten()[:3] if voxel_camera[2] <= near_clipping_distance: continue # distance along ray from camera to voxel center ray_distance = np.linalg.norm(voxel_camera) # squared distance along optical axis from camera to voxel z_cam_squared = voxel_camera[2] ** 2 inv_z_cam = 1 / voxel_camera[2] projection_jacobian = \ np.array([[inv_z_cam, 0, -voxel_camera[0] / z_cam_squared], [0, inv_z_cam, -voxel_camera[1] / z_cam_squared], [voxel_camera[0] / ray_distance, voxel_camera[1] / ray_distance, voxel_camera[2] / ray_distance]]) remapped_covariance = projection_jacobian.dot(covariance_camera_space) \ .dot(projection_jacobian.T) final_covariance = image_space_scaling_matrix.dot(remapped_covariance[0:2, 0:2]).dot( image_space_scaling_matrix.T) + np.eye(2) Q = np.linalg.inv(final_covariance) gaussian = eg.EllipticalGaussian(eg.ImplicitEllipse(Q=Q, F=squared_radius_threshold)) voxel_image = (camera_intrinsic_matrix.dot(voxel_camera) / voxel_camera[2])[:2] voxel_image = voxel_image.reshape(-1, 1) bounds_max = gaussian.ellipse.get_bounds() result = find_sampling_bounds_helper(bounds_max, depth_image, voxel_image) if result is None: continue else: (start_x, end_x, start_y, end_y) = result weights_sum = 0.0 depth_sum = 0 for y_sample in range(start_y, end_y): for x_sample in range(start_x, end_x): sample_centered = np.array([[x_sample], [y_sample]], dtype=np.float64) - voxel_image dist_sq = gaussian.get_distance_from_center_squared(sample_centered) if dist_sq > squared_radius_threshold: continue weight = gaussian.compute(dist_sq) surface_depth = depth_image[y_sample, x_sample] * depth_ratio if surface_depth <= 0.0: continue depth_sum += weight * surface_depth weights_sum += weight if depth_sum <= 0.0: continue final_depth = depth_sum / weights_sum signed_distance = final_depth - voxel_camera[2] field[z_field, y_field, x_field] = common.compute_tsdf_value(signed_distance, narrow_band_half_width) return field # Mostly for debugging EWA -- compute matrix containing sampling areas for each field entry being considered def sampling_area_heatmap_2d_ewa_image(depth_image, camera, image_y_coordinate, camera_extrinsic_matrix=np.eye(4, dtype=np.float32), field_size=128, default_value=1, voxel_size=0.004, array_offset=np.array([-64, -64, 64], dtype=np.int32), narrow_band_width_voxels=20, back_cutoff_voxels=np.inf, gaussian_covariance_scale=1.0): if type(array_offset) != np.ndarray: array_offset = np.array(array_offset).astype(np.int32) return cpp_extension.sampling_area_heatmap_2d_ewa_image(image_y_coordinate, depth_image, camera.depth_unit_ratio, camera.intrinsics.intrinsic_matrix.astype( np.float32), camera_extrinsic_matrix.astype(np.float32), array_offset.astype(np.int32), field_size, voxel_size, narrow_band_width_voxels, gaussian_covariance_scale) def generate_tsdf_3d_ewa_image_visualization_cpp(depth_image, camera, field, camera_extrinsic_matrix=np.eye(4, dtype=np.float32), voxel_size=0.004, array_offset=np.array([-64, -64, 64], dtype=np.int32), scale=20, gaussian_covariance_scale=1.0): if type(array_offset) != np.ndarray: array_offset = np.array(array_offset).astype(np.int32) return cpp_extension.generate_tsdf_3d_ewa_image_visualization(depth_image, camera.depth_unit_ratio, field, camera.intrinsics.intrinsic_matrix.astype( np.float32), camera_extrinsic_matrix.astype(np.float32), array_offset, voxel_size, scale, 0.1, gaussian_covariance_scale) def generate_tsdf_2d_ewa_image(depth_image, camera, image_y_coordinate, camera_extrinsic_matrix=np.eye(4, dtype=np.float32), field_size=128, default_value=1, voxel_size=0.004, array_offset=np.array([-64, -64, 64]), narrow_band_width_voxels=20, back_cutoff_voxels=np.inf, gaussian_covariance_scale=1.0): """ Generate 2D TSDF field based on elliptical Gaussian averages (EWA) of depth values from the provided image. Elliptical Gaussian filters are projected from spherical 3D Gaussian functions onto the depth image and convolved with a circular 2D Gaussain filter before averaging the depth values. :param narrow_band_width_voxels: desired width, in voxels, of the narrow band (non-truncated region) of the TSDF :param array_offset: assumes camera is at array_offset voxels relative to TSDF grid :param camera_extrinsic_matrix: matrix representing transformation of the camera (incl. rotation and translation) [ R | T] [ 0 | 1] :param voxel_size: voxel size, in meters :param default_value: default initial TSDF value :param field_size: :param depth_image: :type depth_image: np.ndarray :param camera: :type camera: calib.camera.DepthCamera :param image_y_coordinate: :type image_y_coordinate: int :param gaussian_covariance_scale: scaling of the 3D gaussian, which controls the amount of smoothing :type gaussian_covariance_scale: float :return: resulting 2D TSDF """ # TODO: use back_cutoff_voxels for additional limit if default_value == 1: field = np.ones((field_size, field_size), dtype=np.float32) elif default_value == 0: field = np.zeros((field_size, field_size), dtype=np.float32) else: field = np.ndarray((field_size, field_size), dtype=np.float32) field.fill(default_value) camera_intrinsic_matrix = camera.intrinsics.intrinsic_matrix depth_ratio = camera.depth_unit_ratio narrow_band_half_width = narrow_band_width_voxels / 2 * voxel_size # in metric units w_voxel = 1.0 y_voxel = 0 camera_rotation_matrix = camera_extrinsic_matrix[0:3, 0:3] covariance_voxel_sphere_world_space = np.eye(3) * (gaussian_covariance_scale * voxel_size) covariance_camera_space = camera_rotation_matrix.dot(covariance_voxel_sphere_world_space) \ .dot(camera_rotation_matrix.T) image_space_scaling_matrix = camera_intrinsic_matrix[0:2, 0:2].copy() squared_radius_threshold = 4.0 * gaussian_covariance_scale * voxel_size for y_field in range(field_size): for x_field in range(field_size): x_voxel = (x_field + array_offset[0]) * voxel_size z_voxel = (y_field + array_offset[2]) * voxel_size voxel_world = np.array([[x_voxel, y_voxel, z_voxel, w_voxel]], dtype=np.float32).T voxel_camera = camera_extrinsic_matrix.dot(voxel_world).flatten()[:3] if voxel_camera[2] <= near_clipping_distance: continue # distance along ray from camera to voxel ray_distance = np.linalg.norm(voxel_camera) # squared distance along optical axis from camera to voxel z_cam_squared = voxel_camera[2] ** 2 projection_jacobian = \ np.array([[1 / voxel_camera[2], 0, -voxel_camera[0] / z_cam_squared], [0, 1 / voxel_camera[2], -voxel_camera[1] / z_cam_squared], [voxel_camera[0] / ray_distance, voxel_camera[1] / ray_distance, voxel_camera[2] / ray_distance]]) remapped_covariance = projection_jacobian.dot(covariance_camera_space) \ .dot(projection_jacobian.T) final_covariance = image_space_scaling_matrix.dot(remapped_covariance[0:2, 0:2]).dot( image_space_scaling_matrix.T) + np.eye(2) Q = np.linalg.inv(final_covariance) gaussian = eg.EllipticalGaussian(eg.ImplicitEllipse(Q=Q, F=squared_radius_threshold)) voxel_image = (camera_intrinsic_matrix.dot(voxel_camera) / voxel_camera[2])[:2] voxel_image[1] = image_y_coordinate voxel_image = voxel_image.reshape(-1, 1) bounds_max = gaussian.ellipse.get_bounds() result = find_sampling_bounds_helper(bounds_max, depth_image, voxel_image) if result is None: continue else: (start_x, end_x, start_y, end_y) = result weights_sum = 0.0 depth_sum = 0.0 for y_sample in range(start_y, end_y): for x_sample in range(start_x, end_x): sample_centered = np.array([[x_sample], [y_sample]], dtype=np.float64) - voxel_image dist_sq = gaussian.get_distance_from_center_squared(sample_centered) if dist_sq > squared_radius_threshold: continue weight = gaussian.compute(dist_sq) surface_depth = depth_image[y_sample, x_sample] * depth_ratio if surface_depth <= 0.0: continue depth_sum += weight * surface_depth weights_sum += weight if depth_sum <= 0.0: continue final_depth = depth_sum / weights_sum # signed distance from surface to voxel along camera axis signed_distance = final_depth - voxel_camera[2] field[y_field, x_field] = common.compute_tsdf_value(signed_distance, narrow_band_half_width) return field def generate_tsdf_2d_ewa_tsdf(depth_image, camera, image_y_coordinate, camera_extrinsic_matrix=np.eye(4, dtype=np.float32), field_size=128, default_value=1, voxel_size=0.004, array_offset=np.array([-64, -64, 64]), narrow_band_width_voxels=20, back_cutoff_voxels=np.inf, gaussian_covariance_scale=1.0): """ Generate 2D TSDF field based on elliptical Gaussian averages (EWA) of TSDF values based on corresponding depth values from the provided image. Elliptical Gaussian filters are projected from spherical 3D Gaussian functions onto the depth image and convolved with a circular 2D Gaussain filter before averaging the depth values. :param narrow_band_width_voxels: desired width, in voxels, of the narrow band (non-truncated region) of the TSDF :param array_offset: assumes camera is at array_offset voxels relative to TSDF grid :param camera_extrinsic_matrix: matrix representing transformation of the camera (incl. rotation and translation) [ R | T] [ 0 | 1] :param voxel_size: voxel size, in meters :param default_value: default initial TSDF value :param field_size: :param depth_image: :type depth_image: np.ndarray :param camera: :type camera: calib.camera.DepthCamera :param image_y_coordinate: pixel row in the depth image to use for TSDF generation :type image_y_coordinate: int :param gaussian_covariance_scale: scaling of the 3D gaussian, which controls the amount of smoothing :type gaussian_covariance_scale: float :return: resulting 2D TSDF """ # TODO: use back_cutoff_voxels for additional limit if default_value == 1: field = np.ones((field_size, field_size), dtype=np.float32) elif default_value == 0: field = np.zeros((field_size, field_size), dtype=np.float32) else: field = np.ndarray((field_size, field_size), dtype=np.float32) field.fill(default_value) camera_intrinsic_matrix = camera.intrinsics.intrinsic_matrix depth_ratio = camera.depth_unit_ratio narrow_band_half_width = narrow_band_width_voxels / 2 * voxel_size # in metric units w_voxel = 1.0 y_voxel = 0 camera_rotation_matrix = camera_extrinsic_matrix[0:3, 0:3] covariance_voxel_sphere_world_space = np.eye(3) * (gaussian_covariance_scale * voxel_size) covariance_camera_space = camera_rotation_matrix.dot(covariance_voxel_sphere_world_space) \ .dot(camera_rotation_matrix.T) image_space_scaling_matrix = camera_intrinsic_matrix[0:2, 0:2].copy() squared_radius_threshold = 4.0 * gaussian_covariance_scale * voxel_size for y_field in range(field_size): for x_field in range(field_size): x_voxel = (x_field + array_offset[0]) * voxel_size z_voxel = (y_field + array_offset[2]) * voxel_size voxel_world = np.array([[x_voxel, y_voxel, z_voxel, w_voxel]], dtype=np.float32).T voxel_camera = camera_extrinsic_matrix.dot(voxel_world).flatten()[:3] if voxel_camera[2] <= near_clipping_distance: continue # distance along ray from camera to voxel ray_distance = np.linalg.norm(voxel_camera) # squared distance along optical axis from camera to voxel z_cam_squared = voxel_camera[2] ** 2 projection_jacobian = \ np.array([[1 / voxel_camera[2], 0, -voxel_camera[0] / z_cam_squared], [0, 1 / voxel_camera[2], -voxel_camera[1] / z_cam_squared], [voxel_camera[0] / ray_distance, voxel_camera[1] / ray_distance, voxel_camera[2] / ray_distance]]) remapped_covariance = projection_jacobian.dot(covariance_camera_space) \ .dot(projection_jacobian.T) final_covariance = image_space_scaling_matrix.dot(remapped_covariance[0:2, 0:2]).dot( image_space_scaling_matrix.T) + np.eye(2) Q = np.linalg.inv(final_covariance) gaussian = eg.EllipticalGaussian(eg.ImplicitEllipse(Q=Q, F=squared_radius_threshold)) voxel_image = (camera_intrinsic_matrix.dot(voxel_camera) / voxel_camera[2])[:2] voxel_image[1] = image_y_coordinate voxel_image = voxel_image.reshape(-1, 1) bounds_max = gaussian.ellipse.get_bounds() result = find_sampling_bounds_helper(bounds_max, depth_image, voxel_image) if result is None: continue else: (start_x, end_x, start_y, end_y) = result weights_sum = 0.0 tsdf_sum = 0.0 for y_sample in range(start_y, end_y): for x_sample in range(start_x, end_x): sample_centered = np.array([[x_sample], [y_sample]], dtype=np.float64) - voxel_image dist_sq = gaussian.get_distance_from_center_squared(sample_centered) if dist_sq > squared_radius_threshold: continue weight = gaussian.compute(dist_sq) surface_depth = depth_image[y_sample, x_sample] * depth_ratio if surface_depth <= 0.0: continue # signed distance from surface to voxel along camera axis signed_distance = surface_depth - voxel_camera[2] tsdf_value = common.compute_tsdf_value(signed_distance, narrow_band_half_width) tsdf_sum += weight * tsdf_value weights_sum += weight if weights_sum == 0.0: continue field[y_field, x_field] = tsdf_sum / weights_sum return field def generate_tsdf_2d_ewa_tsdf_inclusive(depth_image, camera, image_y_coordinate, camera_extrinsic_matrix=np.eye(4, dtype=np.float32), field_size=128, default_value=1, voxel_size=0.004, array_offset=np.array([-64, -64, 64]), narrow_band_width_voxels=20, back_cutoff_voxels=np.inf, gaussian_covariance_scale=1.0): """ Generate 2D TSDF field based on elliptical Gaussian averages (EWA) of TSDF values based on corresponding depth values from the provided image. When the sampling range for a particular voxel partially falls outside the image, tsdf value of 1.0 is used during averaging for points that are outside. Elliptical Gaussian filters are projected from spherical 3D Gaussian functions onto the depth image and convolved with a circular 2D Gaussain filter before averaging the depth values. :param narrow_band_width_voxels: desired width, in voxels, of the narrow band (non-truncated region) of the TSDF :param array_offset: assumes camera is at array_offset voxels relative to TSDF grid :param camera_extrinsic_matrix: matrix representing transformation of the camera (incl. rotation and translation) [ R | T] [ 0 | 1] :param voxel_size: voxel size, in meters :param default_value: default initial TSDF value :param field_size: :param depth_image: :type depth_image: np.ndarray :param camera: :type camera: calib.camera.DepthCamera :param image_y_coordinate: pixel row in the depth image to use for TSDF generation :type image_y_coordinate: int :param gaussian_covariance_scale: scaling of the 3D gaussian, which controls the amount of smoothing :type gaussian_covariance_scale: float :return: resulting 2D TSDF """ # TODO: use back_cutoff_voxels for additional limit if default_value == 1: field = np.ones((field_size, field_size), dtype=np.float32) elif default_value == 0: field = np.zeros((field_size, field_size), dtype=np.float32) else: field = np.ndarray((field_size, field_size), dtype=np.float32) field.fill(default_value) camera_intrinsic_matrix = camera.intrinsics.intrinsic_matrix depth_ratio = camera.depth_unit_ratio narrow_band_half_width = narrow_band_width_voxels / 2 * voxel_size # in metric units w_voxel = 1.0 y_voxel = 0 camera_rotation_matrix = camera_extrinsic_matrix[0:3, 0:3] covariance_voxel_sphere_world_space = np.eye(3) * (gaussian_covariance_scale * voxel_size) covariance_camera_space = camera_rotation_matrix.dot(covariance_voxel_sphere_world_space) \ .dot(camera_rotation_matrix.T) image_space_scaling_matrix = camera_intrinsic_matrix[0:2, 0:2].copy() squared_radius_threshold = 4.0 * gaussian_covariance_scale * voxel_size for y_field in range(field_size): for x_field in range(field_size): x_voxel = (x_field + array_offset[0]) * voxel_size z_voxel = (y_field + array_offset[2]) * voxel_size voxel_world = np.array([[x_voxel, y_voxel, z_voxel, w_voxel]], dtype=np.float32).T voxel_camera = camera_extrinsic_matrix.dot(voxel_world).flatten()[:3] if voxel_camera[2] <= near_clipping_distance: continue voxel_image = (camera_intrinsic_matrix.dot(voxel_camera) / voxel_camera[2])[:2] voxel_image[1] = image_y_coordinate voxel_image = voxel_image.reshape(-1, 1) x_image = voxel_image[0] y_image = voxel_image[1] margin = 3 if y_image < -margin or y_image >= depth_image.shape[0] + margin \ or x_image < -margin or x_image >= depth_image.shape[1] + margin: continue # distance along ray from camera to voxel ray_distance = np.linalg.norm(voxel_camera) # squared distance along optical axis from camera to voxel z_cam_squared = voxel_camera[2] ** 2 projection_jacobian = \ np.array([[1 / voxel_camera[2], 0, -voxel_camera[0] / z_cam_squared], [0, 1 / voxel_camera[2], -voxel_camera[1] / z_cam_squared], [voxel_camera[0] / ray_distance, voxel_camera[1] / ray_distance, voxel_camera[2] / ray_distance]]) remapped_covariance = projection_jacobian.dot(covariance_camera_space) \ .dot(projection_jacobian.T) final_covariance = image_space_scaling_matrix.dot(remapped_covariance[0:2, 0:2]).dot( image_space_scaling_matrix.T) + np.eye(2) Q = np.linalg.inv(final_covariance) gaussian = eg.EllipticalGaussian(eg.ImplicitEllipse(Q=Q, F=squared_radius_threshold)) bounds_max = gaussian.ellipse.get_bounds() result = find_sampling_bounds_inclusive_helper(bounds_max, depth_image, voxel_image) if result is None: continue else: (start_x, end_x, start_y, end_y) = result weights_sum = 0.0 tsdf_sum = 0.0 for y_sample in range(start_y, end_y): for x_sample in range(start_x, end_x): sample_centered = np.array([[x_sample], [y_sample]], dtype=np.float64) - voxel_image dist_sq = gaussian.get_distance_from_center_squared(sample_centered) if dist_sq > squared_radius_threshold: continue weight = gaussian.compute(dist_sq) if y_sample < 0 or y_sample >= depth_image.shape[0] \ or x_sample < 0 or x_sample >= depth_image.shape[1]: tsdf_sum += weight * 1.0 else: surface_depth = depth_image[y_sample, x_sample] * depth_ratio if surface_depth <= 0.0: continue # signed distance from surface to voxel along camera axis signed_distance = surface_depth - voxel_camera[2] tsdf_value = common.compute_tsdf_value(signed_distance, narrow_band_half_width) tsdf_sum += weight * tsdf_value weights_sum += weight if weights_sum == 0.0: continue field[y_field, x_field] = tsdf_sum / weights_sum return field generate_tsdf_2d_ewa_functions = { cpp_module.tsdf.FilteringMethod.EWA_IMAGE_SPACE: generate_tsdf_2d_ewa_image, cpp_module.tsdf.FilteringMethod.EWA_VOXEL_SPACE: generate_tsdf_2d_ewa_tsdf, cpp_module.tsdf.FilteringMethod.EWA_VOXEL_SPACE_INCLUSIVE: generate_tsdf_2d_ewa_tsdf_inclusive, }

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6ef170737ab9a84a8ad654085d6e9788cdaeeac8

2,986

py

Python

src/data/layout.py

shendu-sw/TFR-HSS-Benchmark

3fbc93ff548d924050e2de5070007197f04be7f4

[ "MIT" ]

7

2021-08-24T10:01:28.000Z

2021-12-29T07:13:17.000Z

src/data/layout.py

idrl-lab/TFR-HSS-Benchmark

3fbc93ff548d924050e2de5070007197f04be7f4

[ "MIT" ]

null

src/data/layout.py

idrl-lab/TFR-HSS-Benchmark

3fbc93ff548d924050e2de5070007197f04be7f4

[ "MIT" ]

1

2021-08-25T01:38:39.000Z

# -*- encoding: utf-8 -*- """Layout dataset """ import os from .loadresponse import LoadResponse, LoadPointResponse, LoadVecResponse, mat_loader class LayoutDataset(LoadResponse): """Layout dataset (mutiple files) generated by 'layout-generator'.""" def __init__( self, root, list_path=None, train=True, transform=None, target_transform=None, load_name="u_obs", resp_name="u", ): test_name = os.path.splitext(os.path.basename(list_path))[0] subdir = ( os.path.join("train", "train") if train else os.path.join("test", test_name) ) # find the path of the list of train/test samples list_path = os.path.join(root, list_path) # find the root path of the samples root = os.path.join(root, subdir) super().__init__( root, mat_loader, list_path, load_name=load_name, resp_name=resp_name, extensions="mat", transform=transform, target_transform=target_transform, ) class LayoutPointDataset(LoadPointResponse): def __init__( self, root, list_path=None, train=True, load_name="u_obs", resp_name="u", layout_name="F", ): test_name = os.path.splitext(os.path.basename(list_path))[0] subdir = ( os.path.join("train", "train") if train else os.path.join("test", test_name) ) # find the path of the list of train/test samples list_path = os.path.join(root, list_path) # find the root path of the samples root = os.path.join(root, subdir) super().__init__( root, mat_loader, list_path, load_name=load_name, resp_name=resp_name, layout_name=layout_name, extensions="mat", ) class LayoutVecDataset(LoadVecResponse): """Layout dataset (mutiple files) generated by 'layout-generator'.""" def __init__( self, root, list_path=None, train=True, transform=None, div_num=4, target_transform=None, load_name="u_obs", resp_name="u", ): test_name = os.path.splitext(os.path.basename(list_path))[0] subdir = ( os.path.join("train", "train") if train else os.path.join("test", test_name) ) # find the path of the list of train/test samples list_path = os.path.join(root, list_path) # find the root path of the samples root = os.path.join(root, subdir) super().__init__( root, mat_loader, list_path, load_name=load_name, resp_name=resp_name, extensions="mat", div_num=div_num, transform=transform, target_transform=target_transform, )

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0.560281

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2,986

4.598266

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0.067882

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0.052797

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111

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0

null

0

1

0

1

0

null

0

7

e4d9924be93fd770fd6bd7bcf12837741c80db51

2,303

py

Python

base_de_dados/usuarios/models.py

thaynagome/DjangoEscola

a6387a0932c0798234fb09a5768849e8796e4303

[ "Apache-2.0" ]

null

base_de_dados/usuarios/models.py

thaynagome/DjangoEscola

a6387a0932c0798234fb09a5768849e8796e4303

[ "Apache-2.0" ]

null

base_de_dados/usuarios/models.py

thaynagome/DjangoEscola

a6387a0932c0798234fb09a5768849e8796e4303

[ "Apache-2.0" ]

1

2019-05-09T00:26:07.000Z

from django.db import models class categoria(models.Model): nome = models.CharField(max_length=100) dt_criacao = models.DateTimeField(auto_now_add=True) def __str__(self): return self.nome class usuario(models.Model): nome = models.CharField(max_length=100) cpf = models.CharField(max_length=11, blank=True, null=True) dtNascimento = models.DateField(blank=True, null=True, verbose_name='Data de nascimento') nrTelCelular = models.CharField(max_length=11, blank=True, null=True, verbose_name='Nº telefone celular') data_acesso = models.DateTimeField(auto_now_add=True) categoria = models.ForeignKey(categoria, on_delete=models.CASCADE) observacoes = models.TextField(null=True, blank=True) class Meta: verbose_name_plural = "usuarios" def __str__(self): return self.nome class professor(models.Model): nome = models.CharField(max_length=100) cpf = models.CharField(max_length=11, blank=True, null=True) dtNascimento = models.DateField(blank=True, null=True, verbose_name='Data de nascimento') nrTelCelular = models.CharField(max_length=11, blank=True, null=True, verbose_name='Nº telefone celular') salario = models.DecimalField(max_digits=7, decimal_places=2) data_acesso = models.DateTimeField(auto_now_add=True) categoria = models.ForeignKey(categoria, on_delete=models.CASCADE) observacoes = models.TextField(null=True, blank=True) class Meta: verbose_name_plural = "professores" def __str__(self): return self.nome class aluno(models.Model): nome = models.CharField(max_length=100) cpf = models.CharField(max_length=11, blank=True, null=True) dtNascimento = models.DateField(blank=True, null=True, verbose_name='Data de nascimento') nrTelCelular = models.CharField(max_length=11, blank=True, null=True, verbose_name='Nº telefone celular') curso = models.CharField(max_length=100) mensalidade = models.DecimalField(max_digits=7, decimal_places=2) categoria = models.ForeignKey(categoria, on_delete=models.CASCADE) data_acesso = models.DateTimeField(auto_now_add=True) observacoes = models.TextField(null=True, blank=True) class Meta: verbose_name_plural = "alunos" def __str__(self): return self.nome

41.125

109

0.737299

299

2,303

5.48495

0.210702

0.065854

0.120732

0.160976

0.929268

0.912805

0.878049

0.825

0.688415

0

0.015955

0.156318

2,303

56

110

41.125

0.828101

0

0.733333

0

0.059028

0

1

0.088889

false

0

0.022222

0.088889

0.933333

0

null

0

1

0

1

0

1

0

null

0

1

0

8

901b05ad82dbba361342cea4fcbc199d9b430ccd

131

py

Python

pineboolib/fllegacy/flparameterquery.py

deavid/pineboo

acc96ab6d5b8bb182990af6dea4bf0986af15549

[ "MIT" ]

2

2015-09-19T16:54:49.000Z

2016-09-12T08:06:29.000Z

pineboolib/fllegacy/flparameterquery.py

deavid/pineboo

acc96ab6d5b8bb182990af6dea4bf0986af15549

[ "MIT" ]

1

2017-08-14T17:07:14.000Z

2017-08-15T00:22:47.000Z

pineboolib/fllegacy/flparameterquery.py

deavid/pineboo

acc96ab6d5b8bb182990af6dea4bf0986af15549

[ "MIT" ]

9

2015-01-15T18:15:42.000Z

2019-05-05T18:53:00.000Z

from pineboolib.application.database.pnparameterquery import PNParameterQuery class FLParameterQuery(PNParameterQuery): pass

21.833333

77

0.854962

11

131

10.181818

0.818182

0

0.099237

131

5

78

26.2

0.949153

0

1

0

true

0.333333

0

0.666667

0

1

0

1

null

0

1

0

null

0

1

0

1

0

7

9036c20e4a113a0e27c0d8b02a144299c2a88179

5,579

py

Python

src/IceRayPy/core/geometry/transform.py

dmilos/IceRay

4e01f141363c0d126d3c700c1f5f892967e3d520

[ "MIT-0" ]

2

2020-09-04T12:27:15.000Z

2022-01-17T14:49:40.000Z

src/IceRayPy/core/geometry/transform.py

dmilos/IceRay

4e01f141363c0d126d3c700c1f5f892967e3d520

[ "MIT-0" ]

null

src/IceRayPy/core/geometry/transform.py

dmilos/IceRay

4e01f141363c0d126d3c700c1f5f892967e3d520

[ "MIT-0" ]

1

2020-09-04T12:27:52.000Z

import ctypes import IceRayPy import IceRayPy.type import IceRayPy.type.math.affine import IceRayPy.type.math.coord Pointer = ctypes.POINTER AddresOf = ctypes.addressof #Scalar = IceRayPy.type.basic.Scalar VoidPtr = IceRayPy.type.basic.VoidPtr Integer = IceRayPy.type.basic.Integer Coord3D = IceRayPy.type.math.coord.Scalar3D Affine3D = IceRayPy.type.math.affine.Scalar3D Matrix4D = IceRayPy.type.math.matrix.Scalar4D class Identity: def __init__( self, P_dll, P_child = None ): self.m_cargo = {} self.m_cargo['dll'] = P_dll self.m_cargo['this'] = self.m_cargo['dll'].IceRayC_Geometry_Transform_Identity0() self.child( IceRayPy.core.geometry.simple.Sphere( P_dll ) ) def __del__( self ): self.m_cargo['dll'].IceRayC_Geometry_Release( self.m_cargo['this'] ) self.m_cargo['child'] = None def child(self): return self.m_cargo['child']; def child( self, P_child ): self.m_cargo['child'] = P_child self.m_cargo['dll'].IceRayC_Geometry_Transform_Identity_Child( self.m_cargo['this'], P_child.m_cargo['this'] ) class Translate: def __init__( self, P_dll, P_child = None , P_move = None ): self.m_cargo = {} self.m_cargo['dll'] = P_dll self.m_cargo['this'] = self.m_cargo['dll'].IceRayC_Geometry_Transform_Translate0() self.child( IceRayPy.core.geometry.simple.Sphere( P_dll ) ) if( None != P_child ): self.child( P_child ) def __del__( self ): self.m_cargo['dll'].IceRayC_Geometry_Release( self.m_cargo['this'] ) self.m_cargo['child'] = None def child(self): return self.m_cargo['child']; def child( self, P_child ): self.m_cargo['child'] = P_child self.m_cargo['dll'].IceRayC_Geometry_Transform_Translate_Child( self.m_cargo['this'], P_child.m_cargo['this'] ) def move(self, P_move : Coord3D ): return self.m_cargo['dll'].IceRayC_Geometry_Transform_Translate_Move( self.m_cargo['this'], AddresOf( P_move ) ) class Affine: def __init__( self, P_dll, P_child = None , P_affine = None ): self.m_cargo = {} self.m_cargo['dll'] = P_dll self.m_cargo['this'] = self.m_cargo['dll'].IceRayC_Geometry_Transform_Affine0() self.child( IceRayPy.core.geometry.simple.Sphere( P_dll ) ) if( None != P_child ): self.child( P_child ) def __del__( self ): self.m_cargo['dll'].IceRayC_Geometry_Release( self.m_cargo['this'] ) self.m_cargo['child'] = None def child(self): return self.m_cargo['child']; def child( self, P_child ): self.m_cargo['dll'].IceRayC_Geometry_Transform_Affine_Child( self.m_cargo['this'], P_child.m_cargo['this'] ) self.m_cargo['child'] = P_child def toWorldGet( self ): result = Affine3D() self.m_cargo['dll'].IceRayC_Geometry_Transform_Affine_2World_Get( self.m_cargo['this'], AddresOf( result ) ) return result def toWorldSet( self, P_2world: Affine3D ): return self.m_cargo['dll'].IceRayC_Geometry_Transform_Affine_2World_Set( self.m_cargo['this'], AddresOf( P_2world ) ) def toLocalGet( self ): result = Affine3D() self.m_cargo['dll'].IceRayC_Geometry_Transform_Affine_2Local_Get( self.m_cargo['this'], AddresOf( result ) ) return result def toLocalSet( self, P_2local: Affine3D ): return self.m_cargo['dll'].IceRayC_Geometry_Transform_Affine_2Local_Set( self.m_cargo['this'], AddresOf( P_2local ) ) def move(self, P_move : Coord3D ): pass #TODO; def scaleV(self, P_move : Coord3D ): pass #TODO; def rotateX(self, P_alpha ): pass #TODO; def rotateY(self, P_alpha ): pass #TODO; def rotateZ(self, P_alpha ): pass #TODO; def rotateA(self, P_direction : Coord3D, P_alpha ): pass #TODO; class Homography: def __init__( self, P_dll, P_child = None , P_affine = None ): self.m_cargo = {} self.m_cargo['dll'] = P_dll self.m_cargo['this'] = self.m_cargo['dll'].IceRayC_Geometry_Transform_Homography0() self.child( IceRayPy.core.geometry.simple.Sphere(P_dll) ) if( None != P_child ): self.child( P_child ) def __del__( self ): self.m_cargo['dll'].IceRayC_Geometry_Release( self.m_cargo['this'] ) self.m_cargo['child'] = None def child(self): return self.m_cargo['child']; def child( self, P_child ): self.m_cargo['dll'].IceRayC_Geometry_Transform_Homography_Child( self.m_cargo['this'], P_child.m_cargo['this'] ) self.m_cargo['child'] = P_child def toWorldGet( self ): result = Matrix4D() self.m_cargo['dll'].IceRayC_Geometry_Transform_Homography_2World_Get( self.m_cargo['this'], AddresOf( result ) ) return result def toWorldSet( self, P_2world: Matrix4D ): return self.m_cargo['dll'].IceRayC_Geometry_Transform_Homography_2World_Set( self.m_cargo['this'], AddresOf( P_2world ) ) def toLocalGet( self ): result = Matrix4D() self.m_cargo['dll'].IceRayC_Geometry_Transform_Homography_2Local_Get( self.m_cargo['this'], AddresOf( result ) ) return result def toLocalSet( self, P_2local: Matrix4D ): return self.m_cargo['dll'].IceRayC_Geometry_Transform_Homography_2Local_Set( self.m_cargo['this'], AddresOf( P_2local ) )

35.310127

130

0.640796

731

5,579

4.573187

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0.118456

0.185462

0.097218

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0.808555

0.792402

0.763087

0.719115

0

0.008885

0.233375

5,579

157

131

35.535032

0.772738

0.01183

0

0.607143

0

0.043933

0

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0

1

0.276786

false

0.053571

0.044643

0.080357

0.473214

0

null

0

1

0

1

0

null

0

1

0

1

0

9

5f67c8e61bdd8fd2cfe6266b2e05f922471962da

134

py

Python

versions/util/__init__.py

DocTocToc/cleanerversion

becadbab5d7b474a0e9a596b99e97682402d2f2c

[ "Apache-2.0" ]

121

2015-01-03T05:08:55.000Z

2021-01-28T16:54:05.000Z

versions/util/__init__.py

DocTocToc/cleanerversion

becadbab5d7b474a0e9a596b99e97682402d2f2c

[ "Apache-2.0" ]

115

2015-01-06T14:04:24.000Z

2019-02-07T05:15:51.000Z

versions/util/__init__.py

DocTocToc/cleanerversion

becadbab5d7b474a0e9a596b99e97682402d2f2c

[ "Apache-2.0" ]

57

2015-01-06T11:34:41.000Z

2022-01-14T10:59:52.000Z

import datetime from django.utils.timezone import utc def get_utc_now(): return datetime.datetime.utcnow().replace(tzinfo=utc)

16.75

57

0.776119

19

134

5.368421

0.736842

0

0.126866

134

7

58

19.142857

0.871795

0

1

0.25

true

0

0.5

0.25

1

0

1

0

null

0

1

0

null

0

1

0

1

0

7

3971f26f22a5077791300e2bb60451100b433ed4

691

py

Python

Tensile/Tests/nightly/fractional/test_fractional.py

zjunweihit/Tensile

68b73083c92eecc1b04eec1f006f28aea5628030

[ "MIT" ]

null

Tensile/Tests/nightly/fractional/test_fractional.py

zjunweihit/Tensile

68b73083c92eecc1b04eec1f006f28aea5628030

[ "MIT" ]

null

Tensile/Tests/nightly/fractional/test_fractional.py

zjunweihit/Tensile

68b73083c92eecc1b04eec1f006f28aea5628030

[ "MIT" ]

5

2019-07-29T01:23:56.000Z

2022-03-08T09:28:10.000Z

import Tensile.Tensile as Tensile def test_dgemm_fractional_tile_sweep(tmpdir): Tensile.Tensile([Tensile.TensileTestPath("nightly/fractional/test_dgemm_fractional_tile_sweep.yaml"), tmpdir.strpath]) def test_hgemm_fractional_tile_sweep(tmpdir): Tensile.Tensile([Tensile.TensileTestPath("nightly/fractional/test_hgemm_fractional_tile_sweep.yaml"), tmpdir.strpath]) def test_sgemm_fractional_edge(tmpdir): Tensile.Tensile([Tensile.TensileTestPath("nightly/fractional/test_sgemm_fractional_edge.yaml"), tmpdir.strpath]) def test_sgemm_fractional_tile_sweep(tmpdir): Tensile.Tensile([Tensile.TensileTestPath("nightly/fractional/test_sgemm_fractional_tile_sweep.yaml"), tmpdir.strpath])

46.066667

119

0.852388

87

691

6.425287

0.195402

0.225403

0.203936

0.193202

0.928444

0.88551

0.838998

0.760286

0.60644

0

0.041968

691

14

120

49.357143

0.844411

0

0.315942

0

1

0.444444

false

0

0.111111

0

0.555556

0

null

1

0

1

0

null

0

1

0

1

0

10

39b355de9b26bf74516a81a40effb7eef22be6fe

611

py

Python

pfstratsim/utils/__init__.py

aarondorffeld/portfolio-strategy-simulation

8c4771df24e3c45865c7df2a68e51ef018f7be1b

[ "MIT" ]

null

pfstratsim/utils/__init__.py

aarondorffeld/portfolio-strategy-simulation

8c4771df24e3c45865c7df2a68e51ef018f7be1b

[ "MIT" ]

42

2021-11-06T15:19:49.000Z

2022-01-23T16:38:21.000Z

pfstratsim/utils/__init__.py

aarondorffeld/portfolio-strategy-simulation

8c4771df24e3c45865c7df2a68e51ef018f7be1b

[ "MIT" ]

null

from .parameter_calculation import ( calc_asset_returns, calc_asset_obsrvd_returns, calc_asset_obsrvd_risks, calc_corr_cf, calc_asset_expctd_returns, calc_asset_expctd_risks, calc_prtfl_obsrvd_return, calc_prtfl_obsrvd_risk, ) from .parameter_setting import read_params from .plotting import plot __all__ = [ "calc_asset_returns", "calc_asset_obsrvd_returns", "calc_asset_obsrvd_risks", "calc_corr_cf", "calc_asset_expctd_returns", "calc_asset_expctd_risks", "calc_prtfl_obsrvd_return", "calc_prtfl_obsrvd_risk", "read_params", "plot", ]

29.095238

90

0.747954

78

611

5.192308

0.269231

0.222222

0.237037

0.217284

0.740741

0

0.176759

611

20

91

30.55

0.805169

0

0.316413

0.240271

0

1

0

false

0

0.157895

0

0.157895

0

null

1

0

1

0

null

0

8

f2d35c0b892ea6cb0c929a246b521b441e3b20df

111,815

py

Python

angr/procedures/definitions/win32_msi.py

r4b3rt/angr

c133cfd4f83ffea2a1d9e064241e9459eaabc55f

[ "BSD-2-Clause" ]

null

angr/procedures/definitions/win32_msi.py

r4b3rt/angr

c133cfd4f83ffea2a1d9e064241e9459eaabc55f

[ "BSD-2-Clause" ]

null

angr/procedures/definitions/win32_msi.py

r4b3rt/angr

c133cfd4f83ffea2a1d9e064241e9459eaabc55f

[ "BSD-2-Clause" ]

null

# pylint:disable=line-too-long import logging from ...sim_type import SimTypeFunction, SimTypeShort, SimTypeInt, SimTypeLong, SimTypeLongLong, SimTypeDouble, SimTypeFloat, SimTypePointer, SimTypeChar, SimStruct, SimTypeFixedSizeArray, SimTypeBottom, SimUnion, SimTypeBool from ...calling_conventions import SimCCStdcall, SimCCMicrosoftAMD64 from .. import SIM_PROCEDURES as P from . import SimLibrary _l = logging.getLogger(name=__name__) lib = SimLibrary() lib.set_default_cc('X86', SimCCStdcall) lib.set_default_cc('AMD64', SimCCMicrosoftAMD64) lib.set_library_names("msi.dll") prototypes = \ { # 'MsiCloseHandle': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hAny"]), # 'MsiCloseAllHandles': SimTypeFunction([], SimTypeInt(signed=False, label="UInt32")), # 'MsiSetInternalUI': SimTypeFunction([SimTypeInt(signed=False, label="INSTALLUILEVEL"), SimTypePointer(SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), offset=0)], SimTypeInt(signed=False, label="INSTALLUILEVEL"), arg_names=["dwUILevel", "phWnd"]), # 'MsiSetExternalUIA': SimTypeFunction([SimTypePointer(SimTypeFunction([SimTypePointer(SimTypeBottom(label="Void"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=True, label="Int32"), arg_names=["pvContext", "iMessageType", "szMessage"]), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeBottom(label="Void"), offset=0)], SimTypePointer(SimTypeFunction([SimTypePointer(SimTypeBottom(label="Void"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=True, label="Int32"), arg_names=["pvContext", "iMessageType", "szMessage"]), offset=0), arg_names=["puiHandler", "dwMessageFilter", "pvContext"]), # 'MsiSetExternalUIW': SimTypeFunction([SimTypePointer(SimTypeFunction([SimTypePointer(SimTypeBottom(label="Void"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=True, label="Int32"), arg_names=["pvContext", "iMessageType", "szMessage"]), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeBottom(label="Void"), offset=0)], SimTypePointer(SimTypeFunction([SimTypePointer(SimTypeBottom(label="Void"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=True, label="Int32"), arg_names=["pvContext", "iMessageType", "szMessage"]), offset=0), arg_names=["puiHandler", "dwMessageFilter", "pvContext"]), # 'MsiSetExternalUIRecord': SimTypeFunction([SimTypePointer(SimTypeFunction([SimTypePointer(SimTypeBottom(label="Void"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=True, label="Int32"), arg_names=["pvContext", "iMessageType", "hRecord"]), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeBottom(label="Void"), offset=0), SimTypePointer(SimTypeFunction([SimTypePointer(SimTypeBottom(label="Void"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=True, label="Int32"), arg_names=["pvContext", "iMessageType", "hRecord"]), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["puiHandler", "dwMessageFilter", "pvContext", "ppuiPrevHandler"]), # 'MsiEnableLogA': SimTypeFunction([SimTypeInt(signed=False, label="INSTALLOGMODE"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["dwLogMode", "szLogFile", "dwLogAttributes"]), # 'MsiEnableLogW': SimTypeFunction([SimTypeInt(signed=False, label="INSTALLOGMODE"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["dwLogMode", "szLogFile", "dwLogAttributes"]), # 'MsiQueryProductStateA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct"]), # 'MsiQueryProductStateW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct"]), # 'MsiGetProductInfoA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szAttribute", "lpValueBuf", "pcchValueBuf"]), # 'MsiGetProductInfoW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szAttribute", "lpValueBuf", "pcchValueBuf"]), # 'MsiGetProductInfoExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "szProperty", "szValue", "pcchValue"]), # 'MsiGetProductInfoExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "szProperty", "szValue", "pcchValue"]), # 'MsiInstallProductA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "szCommandLine"]), # 'MsiInstallProductW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "szCommandLine"]), # 'MsiConfigureProductA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLLEVEL"), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iInstallLevel", "eInstallState"]), # 'MsiConfigureProductW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLLEVEL"), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iInstallLevel", "eInstallState"]), # 'MsiConfigureProductExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLLEVEL"), SimTypeInt(signed=False, label="INSTALLSTATE"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iInstallLevel", "eInstallState", "szCommandLine"]), # 'MsiConfigureProductExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLLEVEL"), SimTypeInt(signed=False, label="INSTALLSTATE"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iInstallLevel", "eInstallState", "szCommandLine"]), # 'MsiReinstallProductA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="REINSTALLMODE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szReinstallMode"]), # 'MsiReinstallProductW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="REINSTALLMODE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szReinstallMode"]), # 'MsiAdvertiseProductExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeShort(signed=False, label="UInt16"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "szScriptfilePath", "szTransforms", "lgidLanguage", "dwPlatform", "dwOptions"]), # 'MsiAdvertiseProductExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeShort(signed=False, label="UInt16"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "szScriptfilePath", "szTransforms", "lgidLanguage", "dwPlatform", "dwOptions"]), # 'MsiAdvertiseProductA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeShort(signed=False, label="UInt16")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "szScriptfilePath", "szTransforms", "lgidLanguage"]), # 'MsiAdvertiseProductW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeShort(signed=False, label="UInt16")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "szScriptfilePath", "szTransforms", "lgidLanguage"]), # 'MsiProcessAdvertiseScriptA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), SimTypeInt(signed=True, label="Int32"), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szScriptFile", "szIconFolder", "hRegData", "fShortcuts", "fRemoveItems"]), # 'MsiProcessAdvertiseScriptW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), SimTypeInt(signed=True, label="Int32"), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szScriptFile", "szIconFolder", "hRegData", "fShortcuts", "fRemoveItems"]), # 'MsiAdvertiseScriptA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), offset=0), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szScriptFile", "dwFlags", "phRegData", "fRemoveItems"]), # 'MsiAdvertiseScriptW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), offset=0), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szScriptFile", "dwFlags", "phRegData", "fRemoveItems"]), # 'MsiGetProductInfoFromScriptA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeShort(signed=False, label="UInt16"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szScriptFile", "lpProductBuf39", "plgidLanguage", "pdwVersion", "lpNameBuf", "pcchNameBuf", "lpPackageBuf", "pcchPackageBuf"]), # 'MsiGetProductInfoFromScriptW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeShort(signed=False, label="UInt16"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szScriptFile", "lpProductBuf39", "plgidLanguage", "pdwVersion", "lpNameBuf", "pcchNameBuf", "lpPackageBuf", "pcchPackageBuf"]), # 'MsiGetProductCodeA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "lpBuf39"]), # 'MsiGetProductCodeW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "lpBuf39"]), # 'MsiGetUserInfoA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="USERINFOSTATE"), arg_names=["szProduct", "lpUserNameBuf", "pcchUserNameBuf", "lpOrgNameBuf", "pcchOrgNameBuf", "lpSerialBuf", "pcchSerialBuf"]), # 'MsiGetUserInfoW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="USERINFOSTATE"), arg_names=["szProduct", "lpUserNameBuf", "pcchUserNameBuf", "lpOrgNameBuf", "pcchOrgNameBuf", "lpSerialBuf", "pcchSerialBuf"]), # 'MsiCollectUserInfoA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct"]), # 'MsiCollectUserInfoW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct"]), # 'MsiApplyPatchA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLTYPE"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchPackage", "szInstallPackage", "eInstallType", "szCommandLine"]), # 'MsiApplyPatchW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLTYPE"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchPackage", "szInstallPackage", "eInstallType", "szCommandLine"]), # 'MsiGetPatchInfoA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatch", "szAttribute", "lpValueBuf", "pcchValueBuf"]), # 'MsiGetPatchInfoW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatch", "szAttribute", "lpValueBuf", "pcchValueBuf"]), # 'MsiEnumPatchesA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iPatchIndex", "lpPatchBuf", "lpTransformsBuf", "pcchTransformsBuf"]), # 'MsiEnumPatchesW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iPatchIndex", "lpPatchBuf", "lpTransformsBuf", "pcchTransformsBuf"]), # 'MsiRemovePatchesA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLTYPE"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchList", "szProductCode", "eUninstallType", "szPropertyList"]), # 'MsiRemovePatchesW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLTYPE"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchList", "szProductCode", "eUninstallType", "szPropertyList"]), # 'MsiExtractPatchXMLDataA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchPath", "dwReserved", "szXMLData", "pcchXMLData"]), # 'MsiExtractPatchXMLDataW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchPath", "dwReserved", "szXMLData", "pcchXMLData"]), # 'MsiGetPatchInfoExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchCode", "szProductCode", "szUserSid", "dwContext", "szProperty", "lpValue", "pcchValue"]), # 'MsiGetPatchInfoExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchCode", "szProductCode", "szUserSid", "dwContext", "szProperty", "lpValue", "pcchValue"]), # 'MsiApplyMultiplePatchesA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchPackages", "szProductCode", "szPropertiesList"]), # 'MsiApplyMultiplePatchesW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPatchPackages", "szProductCode", "szPropertiesList"]), # 'MsiDeterminePatchSequenceA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimStruct({"szPatchData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "ePatchDataType": SimTypeInt(signed=False, label="MSIPATCHDATATYPE"), "dwOrder": SimTypeInt(signed=False, label="UInt32"), "uStatus": SimTypeInt(signed=False, label="UInt32")}, name="MSIPATCHSEQUENCEINFOA", pack=False, align=None), label="LPArray", offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "cPatchInfo", "pPatchInfo"]), # 'MsiDeterminePatchSequenceW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimStruct({"szPatchData": SimTypePointer(SimTypeChar(label="Char"), offset=0), "ePatchDataType": SimTypeInt(signed=False, label="MSIPATCHDATATYPE"), "dwOrder": SimTypeInt(signed=False, label="UInt32"), "uStatus": SimTypeInt(signed=False, label="UInt32")}, name="MSIPATCHSEQUENCEINFOW", pack=False, align=None), label="LPArray", offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "cPatchInfo", "pPatchInfo"]), # 'MsiDetermineApplicablePatchesA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimStruct({"szPatchData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "ePatchDataType": SimTypeInt(signed=False, label="MSIPATCHDATATYPE"), "dwOrder": SimTypeInt(signed=False, label="UInt32"), "uStatus": SimTypeInt(signed=False, label="UInt32")}, name="MSIPATCHSEQUENCEINFOA", pack=False, align=None), label="LPArray", offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductPackagePath", "cPatchInfo", "pPatchInfo"]), # 'MsiDetermineApplicablePatchesW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimStruct({"szPatchData": SimTypePointer(SimTypeChar(label="Char"), offset=0), "ePatchDataType": SimTypeInt(signed=False, label="MSIPATCHDATATYPE"), "dwOrder": SimTypeInt(signed=False, label="UInt32"), "uStatus": SimTypeInt(signed=False, label="UInt32")}, name="MSIPATCHSEQUENCEINFOW", pack=False, align=None), label="LPArray", offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductPackagePath", "cPatchInfo", "pPatchInfo"]), # 'MsiEnumPatchesExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "dwFilter", "dwIndex", "szPatchCode", "szTargetProductCode", "pdwTargetProductContext", "szTargetUserSid", "pcchTargetUserSid"]), # 'MsiEnumPatchesExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "dwFilter", "dwIndex", "szPatchCode", "szTargetProductCode", "pdwTargetProductContext", "szTargetUserSid", "pcchTargetUserSid"]), # 'MsiQueryFeatureStateA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szFeature"]), # 'MsiQueryFeatureStateW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szFeature"]), # 'MsiQueryFeatureStateExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "szFeature", "pdwState"]), # 'MsiQueryFeatureStateExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "szFeature", "pdwState"]), # 'MsiUseFeatureA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szFeature"]), # 'MsiUseFeatureW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szFeature"]), # 'MsiUseFeatureExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szFeature", "dwInstallMode", "dwReserved"]), # 'MsiUseFeatureExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szFeature", "dwInstallMode", "dwReserved"]), # 'MsiGetFeatureUsageA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeShort(signed=False, label="UInt16"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "pdwUseCount", "pwDateUsed"]), # 'MsiGetFeatureUsageW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeShort(signed=False, label="UInt16"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "pdwUseCount", "pwDateUsed"]), # 'MsiConfigureFeatureA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "eInstallState"]), # 'MsiConfigureFeatureW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "eInstallState"]), # 'MsiReinstallFeatureA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="REINSTALLMODE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "dwReinstallMode"]), # 'MsiReinstallFeatureW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="REINSTALLMODE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "dwReinstallMode"]), # 'MsiProvideComponentA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "szComponent", "dwInstallMode", "lpPathBuf", "pcchPathBuf"]), # 'MsiProvideComponentW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFeature", "szComponent", "dwInstallMode", "lpPathBuf", "pcchPathBuf"]), # 'MsiProvideQualifiedComponentA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szCategory", "szQualifier", "dwInstallMode", "lpPathBuf", "pcchPathBuf"]), # 'MsiProvideQualifiedComponentW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szCategory", "szQualifier", "dwInstallMode", "lpPathBuf", "pcchPathBuf"]), # 'MsiProvideQualifiedComponentExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szCategory", "szQualifier", "dwInstallMode", "szProduct", "dwUnused1", "dwUnused2", "lpPathBuf", "pcchPathBuf"]), # 'MsiProvideQualifiedComponentExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szCategory", "szQualifier", "dwInstallMode", "szProduct", "dwUnused1", "dwUnused2", "lpPathBuf", "pcchPathBuf"]), # 'MsiGetComponentPathA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szComponent", "lpPathBuf", "pcchBuf"]), # 'MsiGetComponentPathW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProduct", "szComponent", "lpPathBuf", "pcchBuf"]), # 'MsiGetComponentPathExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProductCode", "szComponentCode", "szUserSid", "dwContext", "lpOutPathBuffer", "pcchOutPathBuffer"]), # 'MsiGetComponentPathExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szProductCode", "szComponentCode", "szUserSid", "dwContext", "lpOutPathBuffer", "pcchOutPathBuffer"]), # 'MsiProvideAssemblyA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypeInt(signed=False, label="MSIASSEMBLYINFO"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szAssemblyName", "szAppContext", "dwInstallMode", "dwAssemblyInfo", "lpPathBuf", "pcchPathBuf"]), # 'MsiProvideAssemblyW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLMODE"), SimTypeInt(signed=False, label="MSIASSEMBLYINFO"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szAssemblyName", "szAppContext", "dwInstallMode", "dwAssemblyInfo", "lpPathBuf", "pcchPathBuf"]), # 'MsiQueryComponentStateA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "szComponentCode", "pdwState"]), # 'MsiQueryComponentStateW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "szComponentCode", "pdwState"]), # 'MsiEnumProductsA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["iProductIndex", "lpProductBuf"]), # 'MsiEnumProductsW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["iProductIndex", "lpProductBuf"]), # 'MsiEnumProductsExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "dwIndex", "szInstalledProductCode", "pdwInstalledContext", "szSid", "pcchSid"]), # 'MsiEnumProductsExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szUserSid", "dwContext", "dwIndex", "szInstalledProductCode", "pdwInstalledContext", "szSid", "pcchSid"]), # 'MsiEnumRelatedProductsA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["lpUpgradeCode", "dwReserved", "iProductIndex", "lpProductBuf"]), # 'MsiEnumRelatedProductsW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["lpUpgradeCode", "dwReserved", "iProductIndex", "lpProductBuf"]), # 'MsiEnumFeaturesA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iFeatureIndex", "lpFeatureBuf", "lpParentBuf"]), # 'MsiEnumFeaturesW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "iFeatureIndex", "lpFeatureBuf", "lpParentBuf"]), # 'MsiEnumComponentsA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["iComponentIndex", "lpComponentBuf"]), # 'MsiEnumComponentsW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["iComponentIndex", "lpComponentBuf"]), # 'MsiEnumComponentsExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szUserSid", "dwContext", "dwIndex", "szInstalledComponentCode", "pdwInstalledContext", "szSid", "pcchSid"]), # 'MsiEnumComponentsExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szUserSid", "dwContext", "dwIndex", "szInstalledComponentCode", "pdwInstalledContext", "szSid", "pcchSid"]), # 'MsiEnumClientsA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "iProductIndex", "lpProductBuf"]), # 'MsiEnumClientsW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "iProductIndex", "lpProductBuf"]), # 'MsiEnumClientsExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "szUserSid", "dwContext", "dwProductIndex", "szProductBuf", "pdwInstalledContext", "szSid", "pcchSid"]), # 'MsiEnumClientsExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "szUserSid", "dwContext", "dwProductIndex", "szProductBuf", "pdwInstalledContext", "szSid", "pcchSid"]), # 'MsiEnumComponentQualifiersA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "iIndex", "lpQualifierBuf", "pcchQualifierBuf", "lpApplicationDataBuf", "pcchApplicationDataBuf"]), # 'MsiEnumComponentQualifiersW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szComponent", "iIndex", "lpQualifierBuf", "pcchQualifierBuf", "lpApplicationDataBuf", "pcchApplicationDataBuf"]), # 'MsiOpenProductA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "hProduct"]), # 'MsiOpenProductW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "hProduct"]), # 'MsiOpenPackageA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "hProduct"]), # 'MsiOpenPackageW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "hProduct"]), # 'MsiOpenPackageExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "dwOptions", "hProduct"]), # 'MsiOpenPackageExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath", "dwOptions", "hProduct"]), # 'MsiGetPatchFileListA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szPatchPackages", "pcFiles", "pphFileRecords"]), # 'MsiGetPatchFileListW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCode", "szPatchPackages", "pcFiles", "pphFileRecords"]), # 'MsiGetProductPropertyA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hProduct", "szProperty", "lpValueBuf", "pcchValueBuf"]), # 'MsiGetProductPropertyW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hProduct", "szProperty", "lpValueBuf", "pcchValueBuf"]), # 'MsiVerifyPackageA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath"]), # 'MsiVerifyPackageW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szPackagePath"]), # 'MsiGetFeatureInfoA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hProduct", "szFeature", "lpAttributes", "lpTitleBuf", "pcchTitleBuf", "lpHelpBuf", "pcchHelpBuf"]), # 'MsiGetFeatureInfoW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hProduct", "szFeature", "lpAttributes", "lpTitleBuf", "pcchTitleBuf", "lpHelpBuf", "pcchHelpBuf"]), # 'MsiInstallMissingComponentA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szComponent", "eInstallState"]), # 'MsiInstallMissingComponentW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szComponent", "eInstallState"]), # 'MsiInstallMissingFileA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFile"]), # 'MsiInstallMissingFileW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szFile"]), # 'MsiLocateComponentA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szComponent", "lpPathBuf", "pcchBuf"]), # 'MsiLocateComponentW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="INSTALLSTATE"), arg_names=["szComponent", "lpPathBuf", "pcchBuf"]), # 'MsiSourceListClearAllA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szUserName", "dwReserved"]), # 'MsiSourceListClearAllW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szUserName", "dwReserved"]), # 'MsiSourceListAddSourceA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szUserName", "dwReserved", "szSource"]), # 'MsiSourceListAddSourceW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szUserName", "dwReserved", "szSource"]), # 'MsiSourceListForceResolutionA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szUserName", "dwReserved"]), # 'MsiSourceListForceResolutionW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "szUserName", "dwReserved"]), # 'MsiSourceListAddSourceExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szSource", "dwIndex"]), # 'MsiSourceListAddSourceExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szSource", "dwIndex"]), # 'MsiSourceListAddMediaDiskA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwDiskId", "szVolumeLabel", "szDiskPrompt"]), # 'MsiSourceListAddMediaDiskW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwDiskId", "szVolumeLabel", "szDiskPrompt"]), # 'MsiSourceListClearSourceA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szSource"]), # 'MsiSourceListClearSourceW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szSource"]), # 'MsiSourceListClearMediaDiskA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwDiskId"]), # 'MsiSourceListClearMediaDiskW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwDiskId"]), # 'MsiSourceListClearAllExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions"]), # 'MsiSourceListClearAllExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions"]), # 'MsiSourceListForceResolutionExA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions"]), # 'MsiSourceListForceResolutionExW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions"]), # 'MsiSourceListSetInfoA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szProperty", "szValue"]), # 'MsiSourceListSetInfoW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szProperty", "szValue"]), # 'MsiSourceListGetInfoA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szProperty", "szValue", "pcchValue"]), # 'MsiSourceListGetInfoW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "szProperty", "szValue", "pcchValue"]), # 'MsiSourceListEnumSourcesA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwIndex", "szSource", "pcchSource"]), # 'MsiSourceListEnumSourcesW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwIndex", "szSource", "pcchSource"]), # 'MsiSourceListEnumMediaDisksA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwIndex", "pdwDiskId", "szVolumeLabel", "pcchVolumeLabel", "szDiskPrompt", "pcchDiskPrompt"]), # 'MsiSourceListEnumMediaDisksW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSIINSTALLCONTEXT"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProductCodeOrPatchCode", "szUserSid", "dwContext", "dwOptions", "dwIndex", "pdwDiskId", "szVolumeLabel", "pcchVolumeLabel", "szDiskPrompt", "pcchDiskPrompt"]), # 'MsiGetFileVersionA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szFilePath", "lpVersionBuf", "pcchVersionBuf", "lpLangBuf", "pcchLangBuf"]), # 'MsiGetFileVersionW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szFilePath", "lpVersionBuf", "pcchVersionBuf", "lpLangBuf", "pcchLangBuf"]), # 'MsiGetFileHashA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimStruct({"dwFileHashInfoSize": SimTypeInt(signed=False, label="UInt32"), "dwData": SimTypeFixedSizeArray(SimTypeInt(signed=False, label="UInt32"), 4)}, name="MSIFILEHASHINFO", pack=False, align=None), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szFilePath", "dwOptions", "pHash"]), # 'MsiGetFileHashW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimStruct({"dwFileHashInfoSize": SimTypeInt(signed=False, label="UInt32"), "dwData": SimTypeFixedSizeArray(SimTypeInt(signed=False, label="UInt32"), 4)}, name="MSIFILEHASHINFO", pack=False, align=None), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szFilePath", "dwOptions", "pHash"]), # 'MsiGetFileSignatureInformationA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypePointer(SimStruct({"dwCertEncodingType": SimTypeInt(signed=False, label="UInt32"), "pbCertEncoded": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cbCertEncoded": SimTypeInt(signed=False, label="UInt32"), "pCertInfo": SimTypePointer(SimStruct({"dwVersion": SimTypeInt(signed=False, label="UInt32"), "SerialNumber": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None), "SignatureAlgorithm": SimStruct({"pszObjId": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "Parameters": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None)}, name="CRYPT_ALGORITHM_IDENTIFIER", pack=False, align=None), "Issuer": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None), "NotBefore": SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), "NotAfter": SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), "Subject": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None), "SubjectPublicKeyInfo": SimStruct({"Algorithm": SimStruct({"pszObjId": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "Parameters": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None)}, name="CRYPT_ALGORITHM_IDENTIFIER", pack=False, align=None), "PublicKey": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cUnusedBits": SimTypeInt(signed=False, label="UInt32")}, name="CRYPT_BIT_BLOB", pack=False, align=None)}, name="CERT_PUBLIC_KEY_INFO", pack=False, align=None), "IssuerUniqueId": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cUnusedBits": SimTypeInt(signed=False, label="UInt32")}, name="CRYPT_BIT_BLOB", pack=False, align=None), "SubjectUniqueId": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cUnusedBits": SimTypeInt(signed=False, label="UInt32")}, name="CRYPT_BIT_BLOB", pack=False, align=None), "cExtension": SimTypeInt(signed=False, label="UInt32"), "rgExtension": SimTypePointer(SimStruct({"pszObjId": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "fCritical": SimTypeInt(signed=True, label="Int32"), "Value": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None)}, name="CERT_EXTENSION", pack=False, align=None), offset=0)}, name="CERT_INFO", pack=False, align=None), offset=0), "hCertStore": SimTypePointer(SimTypeBottom(label="Void"), offset=0)}, name="CERT_CONTEXT", pack=False, align=None), offset=0), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=True, label="Int32"), arg_names=["szSignedObjectPath", "dwFlags", "ppcCertContext", "pbHashData", "pcbHashData"]), # 'MsiGetFileSignatureInformationW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypePointer(SimStruct({"dwCertEncodingType": SimTypeInt(signed=False, label="UInt32"), "pbCertEncoded": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cbCertEncoded": SimTypeInt(signed=False, label="UInt32"), "pCertInfo": SimTypePointer(SimStruct({"dwVersion": SimTypeInt(signed=False, label="UInt32"), "SerialNumber": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None), "SignatureAlgorithm": SimStruct({"pszObjId": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "Parameters": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None)}, name="CRYPT_ALGORITHM_IDENTIFIER", pack=False, align=None), "Issuer": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None), "NotBefore": SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), "NotAfter": SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), "Subject": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None), "SubjectPublicKeyInfo": SimStruct({"Algorithm": SimStruct({"pszObjId": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "Parameters": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None)}, name="CRYPT_ALGORITHM_IDENTIFIER", pack=False, align=None), "PublicKey": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cUnusedBits": SimTypeInt(signed=False, label="UInt32")}, name="CRYPT_BIT_BLOB", pack=False, align=None)}, name="CERT_PUBLIC_KEY_INFO", pack=False, align=None), "IssuerUniqueId": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cUnusedBits": SimTypeInt(signed=False, label="UInt32")}, name="CRYPT_BIT_BLOB", pack=False, align=None), "SubjectUniqueId": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "cUnusedBits": SimTypeInt(signed=False, label="UInt32")}, name="CRYPT_BIT_BLOB", pack=False, align=None), "cExtension": SimTypeInt(signed=False, label="UInt32"), "rgExtension": SimTypePointer(SimStruct({"pszObjId": SimTypePointer(SimTypeChar(label="Byte"), offset=0), "fCritical": SimTypeInt(signed=True, label="Int32"), "Value": SimStruct({"cbData": SimTypeInt(signed=False, label="UInt32"), "pbData": SimTypePointer(SimTypeChar(label="Byte"), offset=0)}, name="CRYPTOAPI_BLOB", pack=False, align=None)}, name="CERT_EXTENSION", pack=False, align=None), offset=0)}, name="CERT_INFO", pack=False, align=None), offset=0), "hCertStore": SimTypePointer(SimTypeBottom(label="Void"), offset=0)}, name="CERT_CONTEXT", pack=False, align=None), offset=0), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=True, label="Int32"), arg_names=["szSignedObjectPath", "dwFlags", "ppcCertContext", "pbHashData", "pcbHashData"]), # 'MsiGetShortcutTargetA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szShortcutPath", "szProductCode", "szFeatureId", "szComponentCode"]), # 'MsiGetShortcutTargetW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szShortcutPath", "szProductCode", "szFeatureId", "szComponentCode"]), # 'MsiIsProductElevatedA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "pfElevated"]), # 'MsiIsProductElevatedW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szProduct", "pfElevated"]), # 'MsiNotifySidChangeA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["pOldSid", "pNewSid"]), # 'MsiNotifySidChangeW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["pOldSid", "pNewSid"]), # 'MsiBeginTransactionA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szName", "dwTransactionAttributes", "phTransactionHandle", "phChangeOfOwnerEvent"]), # 'MsiBeginTransactionW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szName", "dwTransactionAttributes", "phTransactionHandle", "phChangeOfOwnerEvent"]), # 'MsiEndTransaction': SimTypeFunction([SimTypeInt(signed=False, label="MSITRANSACTIONSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["dwTransactionState"]), # 'MsiJoinTransaction': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypePointer(SimTypeInt(signed=True, label="Int"), label="IntPtr", offset=0), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hTransactionHandle", "dwTransactionAttributes", "phChangeOfOwnerEvent"]), # 'MsiDatabaseOpenViewA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szQuery", "phView"]), # 'MsiDatabaseOpenViewW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szQuery", "phView"]), # 'MsiViewGetErrorA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="MSIDBERROR"), arg_names=["hView", "szColumnNameBuffer", "pcchBuf"]), # 'MsiViewGetErrorW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="MSIDBERROR"), arg_names=["hView", "szColumnNameBuffer", "pcchBuf"]), # 'MsiViewExecute': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hView", "hRecord"]), # 'MsiViewFetch': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hView", "phRecord"]), # 'MsiViewModify': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="MSIMODIFY"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hView", "eModifyMode", "hRecord"]), # 'MsiViewGetColumnInfo': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="MSICOLINFO"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hView", "eColumnInfo", "phRecord"]), # 'MsiViewClose': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hView"]), # 'MsiDatabaseGetPrimaryKeysA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szTableName", "phRecord"]), # 'MsiDatabaseGetPrimaryKeysW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szTableName", "phRecord"]), # 'MsiDatabaseIsTablePersistentA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="MSICONDITION"), arg_names=["hDatabase", "szTableName"]), # 'MsiDatabaseIsTablePersistentW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="MSICONDITION"), arg_names=["hDatabase", "szTableName"]), # 'MsiGetSummaryInformationA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szDatabasePath", "uiUpdateCount", "phSummaryInfo"]), # 'MsiGetSummaryInformationW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szDatabasePath", "uiUpdateCount", "phSummaryInfo"]), # 'MsiSummaryInfoGetPropertyCount': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hSummaryInfo", "puiPropertyCount"]), # 'MsiSummaryInfoSetPropertyA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=True, label="Int32"), SimTypePointer(SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hSummaryInfo", "uiProperty", "uiDataType", "iValue", "pftValue", "szValue"]), # 'MsiSummaryInfoSetPropertyW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=True, label="Int32"), SimTypePointer(SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hSummaryInfo", "uiProperty", "uiDataType", "iValue", "pftValue", "szValue"]), # 'MsiSummaryInfoGetPropertyA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0), SimTypePointer(SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hSummaryInfo", "uiProperty", "puiDataType", "piValue", "pftValue", "szValueBuf", "pcchValueBuf"]), # 'MsiSummaryInfoGetPropertyW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0), SimTypePointer(SimStruct({"dwLowDateTime": SimTypeInt(signed=False, label="UInt32"), "dwHighDateTime": SimTypeInt(signed=False, label="UInt32")}, name="FILETIME", pack=False, align=None), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hSummaryInfo", "uiProperty", "puiDataType", "piValue", "pftValue", "szValueBuf", "pcchValueBuf"]), # 'MsiSummaryInfoPersist': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hSummaryInfo"]), # 'MsiOpenDatabaseA': SimTypeFunction([SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szDatabasePath", "szPersist", "phDatabase"]), # 'MsiOpenDatabaseW': SimTypeFunction([SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["szDatabasePath", "szPersist", "phDatabase"]), # 'MsiDatabaseImportA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szFolderPath", "szFileName"]), # 'MsiDatabaseImportW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szFolderPath", "szFileName"]), # 'MsiDatabaseExportA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szTableName", "szFolderPath", "szFileName"]), # 'MsiDatabaseExportW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szTableName", "szFolderPath", "szFileName"]), # 'MsiDatabaseMergeA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "hDatabaseMerge", "szTableName"]), # 'MsiDatabaseMergeW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "hDatabaseMerge", "szTableName"]), # 'MsiDatabaseGenerateTransformA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=True, label="Int32"), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "hDatabaseReference", "szTransformFile", "iReserved1", "iReserved2"]), # 'MsiDatabaseGenerateTransformW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=True, label="Int32"), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "hDatabaseReference", "szTransformFile", "iReserved1", "iReserved2"]), # 'MsiDatabaseApplyTransformA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSITRANSFORM_ERROR")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szTransformFile", "iErrorConditions"]), # 'MsiDatabaseApplyTransformW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSITRANSFORM_ERROR")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "szTransformFile", "iErrorConditions"]), # 'MsiCreateTransformSummaryInfoA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSITRANSFORM_ERROR"), SimTypeInt(signed=False, label="MSITRANSFORM_VALIDATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "hDatabaseReference", "szTransformFile", "iErrorConditions", "iValidation"]), # 'MsiCreateTransformSummaryInfoW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSITRANSFORM_ERROR"), SimTypeInt(signed=False, label="MSITRANSFORM_VALIDATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "hDatabaseReference", "szTransformFile", "iErrorConditions", "iValidation"]), # 'MsiDatabaseCommit': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase"]), # 'MsiGetDatabaseState': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="MSIDBSTATE"), arg_names=["hDatabase"]), # 'MsiCreateRecord': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["cParams"]), # 'MsiRecordIsNull': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=True, label="Int32"), arg_names=["hRecord", "iField"]), # 'MsiRecordDataSize': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField"]), # 'MsiRecordSetInteger': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "iValue"]), # 'MsiRecordSetStringA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "szValue"]), # 'MsiRecordSetStringW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "szValue"]), # 'MsiRecordGetInteger': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=True, label="Int32"), arg_names=["hRecord", "iField"]), # 'MsiRecordGetStringA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "szValueBuf", "pcchValueBuf"]), # 'MsiRecordGetStringW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "szValueBuf", "pcchValueBuf"]), # 'MsiRecordGetFieldCount': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord"]), # 'MsiRecordSetStreamA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "szFilePath"]), # 'MsiRecordSetStreamW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "szFilePath"]), # 'MsiRecordReadStream': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord", "iField", "szDataBuf", "pcbDataBuf"]), # 'MsiRecordClearData': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hRecord"]), # 'MsiGetActiveDatabase': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall"]), # 'MsiSetPropertyA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szName", "szValue"]), # 'MsiSetPropertyW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szName", "szValue"]), # 'MsiGetPropertyA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szName", "szValueBuf", "pcchValueBuf"]), # 'MsiGetPropertyW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szName", "szValueBuf", "pcchValueBuf"]), # 'MsiGetLanguage': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeShort(signed=False, label="UInt16"), arg_names=["hInstall"]), # 'MsiGetMode': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="MSIRUNMODE")], SimTypeInt(signed=True, label="Int32"), arg_names=["hInstall", "eRunMode"]), # 'MsiSetMode': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="MSIRUNMODE"), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "eRunMode", "fState"]), # 'MsiFormatRecordA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "hRecord", "szResultBuf", "pcchResultBuf"]), # 'MsiFormatRecordW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "hRecord", "szResultBuf", "pcchResultBuf"]), # 'MsiDoActionA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szAction"]), # 'MsiDoActionW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szAction"]), # 'MsiSequenceA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szTable", "iSequenceMode"]), # 'MsiSequenceW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szTable", "iSequenceMode"]), # 'MsiProcessMessage': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="INSTALLMESSAGE"), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=True, label="Int32"), arg_names=["hInstall", "eMessageType", "hRecord"]), # 'MsiEvaluateConditionA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="MSICONDITION"), arg_names=["hInstall", "szCondition"]), # 'MsiEvaluateConditionW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="MSICONDITION"), arg_names=["hInstall", "szCondition"]), # 'MsiGetFeatureStateA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "piInstalled", "piAction"]), # 'MsiGetFeatureStateW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "piInstalled", "piAction"]), # 'MsiSetFeatureStateA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "iState"]), # 'MsiSetFeatureStateW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "iState"]), # 'MsiSetFeatureAttributesA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "dwAttributes"]), # 'MsiSetFeatureAttributesW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "dwAttributes"]), # 'MsiGetComponentStateA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szComponent", "piInstalled", "piAction"]), # 'MsiGetComponentStateW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="INSTALLSTATE"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szComponent", "piInstalled", "piAction"]), # 'MsiSetComponentStateA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szComponent", "iState"]), # 'MsiSetComponentStateW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="INSTALLSTATE")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szComponent", "iState"]), # 'MsiGetFeatureCostA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="MSICOSTTREE"), SimTypeInt(signed=False, label="INSTALLSTATE"), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "iCostTree", "iState", "piCost"]), # 'MsiGetFeatureCostW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="MSICOSTTREE"), SimTypeInt(signed=False, label="INSTALLSTATE"), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "iCostTree", "iState", "piCost"]), # 'MsiEnumComponentCostsA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="INSTALLSTATE"), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szComponent", "dwIndex", "iState", "szDriveBuf", "pcchDriveBuf", "piCost", "piTempCost"]), # 'MsiEnumComponentCostsW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=False, label="INSTALLSTATE"), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0), SimTypePointer(SimTypeInt(signed=True, label="Int32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szComponent", "dwIndex", "iState", "szDriveBuf", "pcchDriveBuf", "piCost", "piTempCost"]), # 'MsiSetInstallLevel': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypeInt(signed=True, label="Int32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "iInstallLevel"]), # 'MsiGetFeatureValidStatesA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "lpInstallStates"]), # 'MsiGetFeatureValidStatesW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFeature", "lpInstallStates"]), # 'MsiGetSourcePathA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFolder", "szPathBuf", "pcchPathBuf"]), # 'MsiGetSourcePathW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFolder", "szPathBuf", "pcchPathBuf"]), # 'MsiGetTargetPathA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFolder", "szPathBuf", "pcchPathBuf"]), # 'MsiGetTargetPathW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), label="LPArray", offset=0), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFolder", "szPathBuf", "pcchPathBuf"]), # 'MsiSetTargetPathA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFolder", "szFolderPath"]), # 'MsiSetTargetPathW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall", "szFolder", "szFolderPath"]), # 'MsiVerifyDiskSpace': SimTypeFunction([SimTypeInt(signed=False, label="UInt32")], SimTypeInt(signed=False, label="UInt32"), arg_names=["hInstall"]), # 'MsiEnableUIPreview': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeInt(signed=False, label="UInt32"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hDatabase", "phPreview"]), # 'MsiPreviewDialogA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hPreview", "szDialogName"]), # 'MsiPreviewDialogW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hPreview", "szDialogName"]), # 'MsiPreviewBillboardA': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Byte"), offset=0), SimTypePointer(SimTypeChar(label="Byte"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hPreview", "szControlName", "szBillboard"]), # 'MsiPreviewBillboardW': SimTypeFunction([SimTypeInt(signed=False, label="UInt32"), SimTypePointer(SimTypeChar(label="Char"), offset=0), SimTypePointer(SimTypeChar(label="Char"), offset=0)], SimTypeInt(signed=False, label="UInt32"), arg_names=["hPreview", "szControlName", "szBillboard"]), # 'MsiGetLastErrorRecord': SimTypeFunction([], SimTypeInt(signed=False, label="UInt32")), } lib.set_prototypes(prototypes)

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1

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f2f2d18adc824fe733cd8317ac89b14299f81f21

11,468

py

Python

Expedisi Sederhana.py

dhimasdityaa/Program-Expedisi-Sederhana

6d17dc165c0b71e4831820a1ee5c2900aa679d99

[ "MIT" ]

1

2020-10-06T15:36:09.000Z

Expedisi Sederhana.py

dhimasdityaa/Program-Expedisi-Sederhana

6d17dc165c0b71e4831820a1ee5c2900aa679d99

[ "MIT" ]

null

Expedisi Sederhana.py

dhimasdityaa/Program-Expedisi-Sederhana

6d17dc165c0b71e4831820a1ee5c2900aa679d99

[ "MIT" ]

null

def menu(): print('++++++++++++++++++++++++++++++++++++++') print('+ Selamat Datang di Program Expedisi +') print('++++++++++++++++++++++++++++++++++++++') print('1. Kirim Paket') print('2. Cek Onkir') def kirimPaket(): namaP = str(input('Masukan Nama Pengirim : ')) descP = str(input('Masukan Deskripsi Paket : ')) noP = int(input('Masukan Nomer Handphone Pengirim : ')) namaPe = str(input('Masukan Nama Penerima : ')) AlaPe = str(input('Masukan Alamat Penerima : ')) noPe = int(input('Masukan Nomer Handphone Penerima : ')) AsalP = str(input('Masukan Lokasi Pengirim : ')) tujuPe = str(input('Masukan Lokasi Penerima : ')) berat = int(input('Masukan Berat Paket : ')) def result(): total = int(ongkir) * int(berat) print('+================================================+') print('+++++++++++ BUKTI PEMBAYARAN PENGIRIMAN ++++++++++') print('+================================================+') print('+ Nama Pengirim :', namaP) print('+ No Handphone pengirim :', noP) print('+ Nama Penerima :', namaPe) print('+ Alamat Penerima :', AlaPe) print('+ No Handphone Penerima :', noPe) print('+ Deskripsi Paket :', descP) print('+ Asal Paket dari :', AsalP) print('+ Tujuan Paket Ke :', tujuPe) print('+ Berat Paket Adalah :', berat) print('+ Biaya Pengiriman :', total) print('+================================================+') # AsalP Paket Dari Surabaya if AsalP == "Surabaya": if tujuPe == "Bekasi": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 50000 result() elif tujuPe == "Cikarang": ongkir = 40000 result() elif tujuPe == "Jogja": ongkir = 25000 result() elif tujuPe == "Malang": ongkir = 30000 result() elif tujuPe == "Cilacap": ongkir = 44000 result() elif tujuPe == "Brebes": ongkir = 42000 result() # AsalP Paket Bekasi elif AsalP == "Bekasi": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Cikarang elif AsalP == "Cikarang": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Bekasi": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Jogja elif AsalP == "Jogja": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Bekasi": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Malang elif AsalP == "Malang": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Bekasi": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Cilacap elif AsalP == "Cilacap": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Bekasi": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # Brebes elif AsalP == "Bekasi": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Bekasi": ongkir = 33000 result() def cekOnkir(): AsalP = str(input('Masukan Kota Asal Pengiriman :')) tujuPe = str(input('Masukan Kota Tujuan Penerima :')) berat = int(input('Masukan Berat Paket :')) def result(): total = int(ongkir) * int(berat) print('+--------------------------------------------+') print('|--------------- LACAK PAKET ----------------|') print('+--------------------------------------------+') print('| Kota Asal Pengirim :', AsalP) print('| Kota Tujuan Penerima :', tujuPe) print('| Biaya Ongkos Kirim :', ongkir, 'Per Kg') print('| Berat Paket :', berat, 'Kg') print('| Total Biaya Pengiriman :', total) print('+--------------------------------------------+') # AsalP Paket Dari Surabaya if AsalP == "Surabaya": if tujuPe == "Bekasi": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 50000 result() elif tujuPe == "Cikarang": ongkir = 40000 result() elif tujuPe == "Jogja": ongkir = 25000 result() elif tujuPe == "Malang": ongkir = 30000 result() elif tujuPe == "Cilacap": ongkir = 44000 result() elif tujuPe == "Brebes": ongkir = 42000 result() # AsalP Paket Bekasi elif AsalP == "Bekasi": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Cikarang elif AsalP == "Cikarang": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Bekasi": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Jogja elif AsalP == "Jogja": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Bekasi": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Malang elif AsalP == "Malang": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Bekasi": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # AsalP Paket Cilacap elif AsalP == "Cilacap": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Bekasi": ongkir = 28000 result() elif tujuPe == "Brebes": ongkir = 33000 result() # Brebes elif AsalP == "Bekasi": if tujuPe == "Surabaya": ongkir = 45000 result() elif tujuPe == "Jakarta": ongkir = 20000 result() elif tujuPe == "Cikarang": ongkir = 10000 result() elif tujuPe == "Jogja": ongkir = 40000 result() elif tujuPe == "Malang": ongkir = 35000 result() elif tujuPe == "Cilacap": ongkir = 28000 result() elif tujuPe == "Bekasi": ongkir = 33000 result() menu() pilih = int(input('Silahkan Pilih : ')) if pilih == 1: kirimPaket() else: cekOnkir()

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0.091013

0.174636

0.279418

0.061123

0.824948

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0.076983

0.441577

11,468

390

69

29.405128

0.67411

0.022585

0

0.891967

0

0.178376

0.033694

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0

1

0

1

0

1

0

null

0

8

f2fbc40499f546e3bbfb158071cbde1b4a268523

33,689

py

Python

wavefront_api_client/api/saved_app_map_search_api.py

httpsgithu/python-client

f85a530367cdabe458a11919ad35609b9bc0606b

[ "Apache-2.0" ]

null

wavefront_api_client/api/saved_app_map_search_api.py

httpsgithu/python-client

f85a530367cdabe458a11919ad35609b9bc0606b

[ "Apache-2.0" ]

null

wavefront_api_client/api/saved_app_map_search_api.py

httpsgithu/python-client

f85a530367cdabe458a11919ad35609b9bc0606b

[ "Apache-2.0" ]

null

# coding: utf-8 """ Wavefront REST API Documentation <p>The Wavefront REST API enables you to interact with Wavefront servers using standard REST API tools. You can use the REST API to automate commonly executed operations such as automatically tagging sources.</p><p>When you make REST API calls outside the Wavefront REST API documentation you must add the header \"Authorization: Bearer <<API-TOKEN>>\" to your HTTP requests.</p> # noqa: E501 OpenAPI spec version: v2 Contact: chitimba@wavefront.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from wavefront_api_client.api_client import ApiClient class SavedAppMapSearchApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def create_saved_app_map_search(self, **kwargs): # noqa: E501 """Create a search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_saved_app_map_search(async_req=True) >>> result = thread.get() :param async_req bool :param SavedAppMapSearch body: Example Body: <pre>{ \"name\": \"beachshirts shopping\", \"searchFilters\": { \"filters\": [ { \"filterType\": \"OPERATION\", \"values\": { \"logicalValue\": [ [ \"beachshirts.\", \"shopping\" ] ] } } ] } }</pre> :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_saved_app_map_search_with_http_info(**kwargs) # noqa: E501 else: (data) = self.create_saved_app_map_search_with_http_info(**kwargs) # noqa: E501 return data def create_saved_app_map_search_with_http_info(self, **kwargs): # noqa: E501 """Create a search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_saved_app_map_search_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param SavedAppMapSearch body: Example Body: <pre>{ \"name\": \"beachshirts shopping\", \"searchFilters\": { \"filters\": [ { \"filterType\": \"OPERATION\", \"values\": { \"logicalValue\": [ [ \"beachshirts.\", \"shopping\" ] ] } } ] } }</pre> :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_saved_app_map_search" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_saved_app_map_search(self, id, **kwargs): # noqa: E501 """Delete a search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_saved_app_map_search(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_saved_app_map_search_with_http_info(id, **kwargs) # noqa: E501 else: (data) = self.delete_saved_app_map_search_with_http_info(id, **kwargs) # noqa: E501 return data def delete_saved_app_map_search_with_http_info(self, id, **kwargs): # noqa: E501 """Delete a search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_saved_app_map_search_with_http_info(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_saved_app_map_search" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `delete_saved_app_map_search`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch/{id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_saved_app_map_search_for_user(self, id, **kwargs): # noqa: E501 """Delete a search belonging to the user # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_saved_app_map_search_for_user(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_saved_app_map_search_for_user_with_http_info(id, **kwargs) # noqa: E501 else: (data) = self.delete_saved_app_map_search_for_user_with_http_info(id, **kwargs) # noqa: E501 return data def delete_saved_app_map_search_for_user_with_http_info(self, id, **kwargs): # noqa: E501 """Delete a search belonging to the user # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_saved_app_map_search_for_user_with_http_info(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_saved_app_map_search_for_user" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `delete_saved_app_map_search_for_user`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch/owned/{id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_all_saved_app_map_searches(self, **kwargs): # noqa: E501 """Get all searches for a customer # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_all_saved_app_map_searches(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: :param int limit: :return: ResponseContainerPagedSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_all_saved_app_map_searches_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_all_saved_app_map_searches_with_http_info(**kwargs) # noqa: E501 return data def get_all_saved_app_map_searches_with_http_info(self, **kwargs): # noqa: E501 """Get all searches for a customer # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_all_saved_app_map_searches_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: :param int limit: :return: ResponseContainerPagedSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['offset', 'limit'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_all_saved_app_map_searches" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'offset' in params: query_params.append(('offset', params['offset'])) # noqa: E501 if 'limit' in params: query_params.append(('limit', params['limit'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerPagedSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_all_saved_app_map_searches_for_user(self, **kwargs): # noqa: E501 """Get all searches for a user # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_all_saved_app_map_searches_for_user(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: :param int limit: :return: ResponseContainerPagedSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_all_saved_app_map_searches_for_user_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_all_saved_app_map_searches_for_user_with_http_info(**kwargs) # noqa: E501 return data def get_all_saved_app_map_searches_for_user_with_http_info(self, **kwargs): # noqa: E501 """Get all searches for a user # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_all_saved_app_map_searches_for_user_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param int offset: :param int limit: :return: ResponseContainerPagedSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['offset', 'limit'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_all_saved_app_map_searches_for_user" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'offset' in params: query_params.append(('offset', params['offset'])) # noqa: E501 if 'limit' in params: query_params.append(('limit', params['limit'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch/owned', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerPagedSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_saved_app_map_search(self, id, **kwargs): # noqa: E501 """Get a specific search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_saved_app_map_search(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_saved_app_map_search_with_http_info(id, **kwargs) # noqa: E501 else: (data) = self.get_saved_app_map_search_with_http_info(id, **kwargs) # noqa: E501 return data def get_saved_app_map_search_with_http_info(self, id, **kwargs): # noqa: E501 """Get a specific search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_saved_app_map_search_with_http_info(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_saved_app_map_search" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `get_saved_app_map_search`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch/{id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_saved_app_map_search(self, id, **kwargs): # noqa: E501 """Update a search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_saved_app_map_search(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :param SavedAppMapSearch body: Example Body: <pre>{ \"name\": \"beachshirts shopping\", \"searchFilters\": { \"filters\": [ { \"filterType\": \"OPERATION\", \"values\": { \"logicalValue\": [ [ \"beachshirts.\", \"shopping\" ] ] } } ] } }</pre> :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.update_saved_app_map_search_with_http_info(id, **kwargs) # noqa: E501 else: (data) = self.update_saved_app_map_search_with_http_info(id, **kwargs) # noqa: E501 return data def update_saved_app_map_search_with_http_info(self, id, **kwargs): # noqa: E501 """Update a search # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_saved_app_map_search_with_http_info(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :param SavedAppMapSearch body: Example Body: <pre>{ \"name\": \"beachshirts shopping\", \"searchFilters\": { \"filters\": [ { \"filterType\": \"OPERATION\", \"values\": { \"logicalValue\": [ [ \"beachshirts.\", \"shopping\" ] ] } } ] } }</pre> :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_saved_app_map_search" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `update_saved_app_map_search`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch/{id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_saved_app_map_search_for_user(self, id, **kwargs): # noqa: E501 """Update a search belonging to the user # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_saved_app_map_search_for_user(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :param SavedAppMapSearch body: Example Body: <pre>{ \"name\": \"beachshirts shopping\", \"searchFilters\": { \"filters\": [ { \"filterType\": \"OPERATION\", \"values\": { \"logicalValue\": [ [ \"beachshirts.\", \"shopping\" ] ] } } ] } }</pre> :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.update_saved_app_map_search_for_user_with_http_info(id, **kwargs) # noqa: E501 else: (data) = self.update_saved_app_map_search_for_user_with_http_info(id, **kwargs) # noqa: E501 return data def update_saved_app_map_search_for_user_with_http_info(self, id, **kwargs): # noqa: E501 """Update a search belonging to the user # noqa: E501 # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_saved_app_map_search_for_user_with_http_info(id, async_req=True) >>> result = thread.get() :param async_req bool :param str id: (required) :param SavedAppMapSearch body: Example Body: <pre>{ \"name\": \"beachshirts shopping\", \"searchFilters\": { \"filters\": [ { \"filterType\": \"OPERATION\", \"values\": { \"logicalValue\": [ [ \"beachshirts.\", \"shopping\" ] ] } } ] } }</pre> :return: ResponseContainerSavedAppMapSearch If the method is called asynchronously, returns the request thread. """ all_params = ['id', 'body'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_saved_app_map_search_for_user" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in params or params['id'] is None): # noqa: E501 raise ValueError("Missing the required parameter `id` when calling `update_saved_app_map_search_for_user`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in params: path_params['id'] = params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['api_key'] # noqa: E501 return self.api_client.call_api( '/api/v2/savedappmapsearch/owned/{id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ResponseContainerSavedAppMapSearch', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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1

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null

0

7

fff945fa87817ab4c079f884fd28aed87b6b8a9c

50

py

Python

09/01/call_0.py

pylangstudy/201706

f1cc6af6b18e5bd393cda27f5166067c4645d4d3

[ "CC0-1.0" ]

null

09/01/call_0.py

pylangstudy/201706

f1cc6af6b18e5bd393cda27f5166067c4645d4d3

[ "CC0-1.0" ]

70

2017-06-01T11:02:51.000Z

2017-06-30T00:35:32.000Z

09/01/call_0.py

pylangstudy/201706

f1cc6af6b18e5bd393cda27f5166067c4645d4d3

[ "CC0-1.0" ]

null

import some_module_0 some_module_0.some_method()

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f22bc65ad3f696435f9d5dac653350edcc51575b

187

py

Python

neater/__init__.py

ju-leon/torch-neuroevolution

bc5f96193fa086ec49bf1c5581ed2eb22d9ce0ac

[ "MIT" ]

2

2021-07-05T11:10:53.000Z

2021-09-29T17:36:19.000Z

neater/__init__.py

ju-leon/torch-neuroevolution

bc5f96193fa086ec49bf1c5581ed2eb22d9ce0ac

[ "MIT" ]

3

2021-09-28T12:46:39.000Z

2021-10-03T13:14:31.000Z

neater/__init__.py

ju-leon/torch-neuroevolution

bc5f96193fa086ec49bf1c5581ed2eb22d9ce0ac

[ "MIT" ]

null

from neater.network import Network from neater.agent import Agent from neater.strategies.neat.neat import Neat from neater.strategies.strategy import Strategy #from neat.ext import Node

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1

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7

f22bda97064e74612c557ec0e4824bc66794da33

169

py

Python

david/typing/__init__.py

arthurTemporim/david

de4ea917e122a5ce99473b047e09e22a90641ff1

[ "MIT" ]

1

2020-01-07T01:15:43.000Z

david/typing/__init__.py

arthurTemporim/david

de4ea917e122a5ce99473b047e09e22a90641ff1

[ "MIT" ]

null

david/typing/__init__.py

arthurTemporim/david

de4ea917e122a5ce99473b047e09e22a90641ff1

[ "MIT" ]

null

from david.typing.message import Message from david.typing.model import Model from david.typing.module import Module from david.typing.training_data import TrainingData

33.8

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1

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1

0

7

f23b79e0abc6ffd100e51054efeb7dbb9c92dd4b

100

py

Python

basic/python/main.py

oglinuk/quines

842866c7c51d15c3fa1a673a732ab88247aff4e5

[ "Apache-2.0" ]

1

2022-01-31T04:56:42.000Z

basic/python/main.py

oglinuk/quines

842866c7c51d15c3fa1a673a732ab88247aff4e5

[ "Apache-2.0" ]

null

basic/python/main.py

oglinuk/quines

842866c7c51d15c3fa1a673a732ab88247aff4e5

[ "Apache-2.0" ]

null

s="s={}{}{}{}print(s.format(chr(34),s,chr(34),chr(10)))" print(s.format(chr(34),s,chr(34),chr(10)))

33.333333

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1

null

0

1

0

15

4b4857b1dca87c89e877a0c5d803c30deb6b96c2

9,071

py

Python

models.py

yanis-k/BSSS

eb20de0572c6a4efc48ed0b354b39609de10e2ea

[ "MIT" ]

1

2021-05-13T16:20:29.000Z

models.py

yanis-k/BSSS

eb20de0572c6a4efc48ed0b354b39609de10e2ea

[ "MIT" ]

null

models.py

yanis-k/BSSS

eb20de0572c6a4efc48ed0b354b39609de10e2ea

[ "MIT" ]

null

import tensorflow as tf from tensorflow import keras from tensorflow.keras import Model from tensorflow.keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPooling2D, Reshape, \ BatchNormalization, Input from tensorflow.keras.layers import LSTM, Concatenate, LeakyReLU from keras.losses import mean_squared_error def custom_mse(x): """ Permutation Invariant Training MSE custom function loss. Keras Implementation. Used in PIT with the CRNN. """ def pit_loss(y_true, y_pred): cost1 = mean_squared_error(y_pred[x], y_true[x]) def c1(): return tf.reduce_mean(cost1) cost2 = mean_squared_error(y_pred[x - 1], y_true[x]) def c2(): return tf.reduce_mean(cost2) result = tf.cond(tf.less(tf.reduce_mean(cost1), tf.reduce_mean(cost2)), c1, c2) return result return pit_loss def bl_dnn_mimo(bins, hl_nodes): """ Baseline DNN model Used as reference [Speaker1, Speaker2] Output :param bins: number of frequency bins :param hl_nodes: number of hidden nodes """ inp_x = Input(shape=(bins,)) x = inp_x x = Dense(hl_nodes)(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = Dropout(0.4)(x) x = Dense(hl_nodes)(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = Dropout(0.4)(x) x = Dense(hl_nodes)(x) x = BatchNormalization()(x) x = Dropout(0.4)(x) out_l = Dense(bins, activation='linear', name="Out1")(x) out_r = Dense(bins, activation='linear', name="Out2")(x) model = Model(inputs=inp_x, outputs=[out_l, out_r]) model.compile(optimizer='adam', loss=keras.losses.mean_squared_error) return model def cnn_twin(bins, time_frames): """ CNN Model "Twin" Implementation: Implemented w/ dilation rate (2) Used as reference to twin-CRNN [Speaker1, Speaker2] Output :param bins: number of frequency bins :param time_frames: number of consecutive time frames """ in_l = Input(shape=(bins, time_frames, 1)) x = in_l filters = 8 for i in range(2): x = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = MaxPooling2D(pool_size=(1, 2))(x) x = Dropout(0.25)(x) filters *= 2 in_r = Input(shape=(bins, time_frames, 1)) y = in_r filters = 8 for i in range(2): y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', dilation_rate=2, data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', dilation_rate=2, data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = MaxPooling2D(pool_size=(1, 2))(y) y = Dropout(0.25)(y) filters *= 2 y = Concatenate(axis=3)([x, y]) filters = 64 for i in range(1): y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = MaxPooling2D(pool_size=(1, 2))(y) y = Dropout(0.25)(y) filters *= 2 y = Flatten()(y) y = Dense(2048, activation=LeakyReLU())(y) # 2048 y = BatchNormalization()(y) y = Dropout(0.4)(y) out_l = Dense(bins * time_frames, activation='linear')(y) out_l = Reshape((bins, time_frames, 1))(out_l) out_r = Dense(bins * time_frames, activation='linear')(y) out_r = Reshape((bins, time_frames, 1))(out_r) model = Model(inputs=[in_l, in_r], outputs=[out_l, out_r]) model.compile(optimizer='adam', loss=keras.losses.mean_squared_error) return model def crnn_mimo(bins, time_frames): """ Twin CRNN (branch w/ dilation_rate = 2) Multiple, yet common, Input Multiple Outputs ([Speaker1, Speaker2]) :param bins: Num. of freq. bins :param time_frames: Num. of consecutive Time Frames """ in_l = Input(shape=(bins, time_frames, 1)) x = in_l filters = 64 for i in range(2): x = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = Conv2D(filters=filters // 4, kernel_size=(3, 3), padding='same', data_format='channels_last')(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = MaxPooling2D(pool_size=(2, 1))(x) x = Dropout(0.25)(x) filters //= 2 in_r = Input(shape=(bins, time_frames, 1)) y = in_r filters = 64 for i in range(2): y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', dilation_rate=2, data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = Conv2D(filters=filters // 4, kernel_size=(3, 3), padding='same', dilation_rate=2, data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = MaxPooling2D(pool_size=(2, 1))(y) y = Dropout(0.25)(y) filters //= 2 y = Concatenate(axis=3)([x, y]) filters = 32 for i in range(1): y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = Conv2D(filters=filters // 2, kernel_size=(3, 3), padding='same', data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = MaxPooling2D(pool_size=(2, 1))(y) y = Dropout(0.3)(y) filters *= 2 y = Reshape((time_frames, 512))(y) # hardcoded, ((time_frames, bins/8*last_conv_filter) y = LSTM(bins, return_sequences=True)(y) y = Dropout(0.3)(y) y = Flatten()(y) out_l = Dense(bins * time_frames, activation='linear')(y) out_l = Reshape((bins, time_frames, 1))(out_l) out_r = Dense(bins * time_frames, activation='linear')(y) out_r = Reshape((bins, time_frames, 1))(out_r) model = Model([in_l, in_r], [out_l, out_r]) model.compile(optimizer='adam', loss=keras.losses.mean_squared_error) return model def crnn_mimo_PIT(bins, time_frames): """ Twin-CRNN MIMO Designed for Permutation Invariant Training Makes use of custom_mse() :param bins: Num of freq. bins :param time_frames: Num of consecutive time frames """ in_l = Input(shape=(bins, time_frames, 1)) x = in_l filters = 64 for i in range(2): x = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = Conv2D(filters=filters // 4, kernel_size=(3, 3), padding='same', data_format='channels_last')(x) x = BatchNormalization()(x) x = LeakyReLU()(x) x = MaxPooling2D(pool_size=(2, 1))(x) x = Dropout(0.25)(x) filters //= 2 in_r = Input(shape=(bins, time_frames, 1)) y = in_r filters = 64 for i in range(2): y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', dilation_rate=2, data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = Conv2D(filters=filters // 4, kernel_size=(3, 3), padding='same', dilation_rate=2, data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = MaxPooling2D(pool_size=(2, 1))(y) y = Dropout(0.25)(y) filters //= 2 y = Concatenate(axis=3)([x, y]) filters = 32 for i in range(1): y = Conv2D(filters=filters, kernel_size=(3, 3), padding='same', data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = Conv2D(filters=filters // 2, kernel_size=(3, 3), padding='same', data_format='channels_last')(y) y = BatchNormalization()(y) y = LeakyReLU()(y) y = MaxPooling2D(pool_size=(2, 1))(y) y = Dropout(0.3)(y) filters *= 2 y = Reshape((time_frames, 512))(y) # hardcoded, ((time_frames, bins/8*last_conv_filter) y = LSTM(bins, return_sequences=True)(y) y = Dropout(0.3)(y) y = Flatten()(y) out_l = Dense(bins * time_frames, activation='linear')(y) out_l = Reshape((bins, time_frames, 1), name='out_l')(out_l) out_r = Dense(bins * time_frames, activation='linear')(y) out_r = Reshape((bins, time_frames, 1), name='out_r')(out_r) model = Model(inputs=[in_l, in_r], outputs=[out_l, out_r]) losses = {'out_l': custom_mse(0), 'out_r': custom_mse(1)} model.compile(loss=losses, optimizer='adam') return model

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null

0

7

4b612e60e6a5ecce238a0ae0e68bae5fdf58faf6

59,366

py

Python

optimization/second_sdEta_mjj_optimization/lumi_and_kin_plots/four_cuts_lum150/Output/Histos/MadAnalysis5job_0/selection_12.py

sheride/axion_pheno

7d3fc08f5ae5b17a3500eba19a2e43f87f076ce5

[ "MIT" ]

null

optimization/second_sdEta_mjj_optimization/lumi_and_kin_plots/four_cuts_lum150/Output/Histos/MadAnalysis5job_0/selection_12.py

sheride/axion_pheno

7d3fc08f5ae5b17a3500eba19a2e43f87f076ce5

[ "MIT" ]

null

optimization/second_sdEta_mjj_optimization/lumi_and_kin_plots/four_cuts_lum150/Output/Histos/MadAnalysis5job_0/selection_12.py

sheride/axion_pheno

7d3fc08f5ae5b17a3500eba19a2e43f87f076ce5

[ "MIT" ]

null

def selection_12(): # Library import import numpy import matplotlib import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec # Library version matplotlib_version = matplotlib.__version__ numpy_version = numpy.__version__ # Histo binning xBinning = numpy.linspace(0.0,2000.0,401,endpoint=True) # Creating data sequence: middle of each bin xData = numpy.array([2.5,7.5,12.5,17.5,22.5,27.5,32.5,37.5,42.5,47.5,52.5,57.5,62.5,67.5,72.5,77.5,82.5,87.5,92.5,97.5,102.5,107.5,112.5,117.5,122.5,127.5,132.5,137.5,142.5,147.5,152.5,157.5,162.5,167.5,172.5,177.5,182.5,187.5,192.5,197.5,202.5,207.5,212.5,217.5,222.5,227.5,232.5,237.5,242.5,247.5,252.5,257.5,262.5,267.5,272.5,277.5,282.5,287.5,292.5,297.5,302.5,307.5,312.5,317.5,322.5,327.5,332.5,337.5,342.5,347.5,352.5,357.5,362.5,367.5,372.5,377.5,382.5,387.5,392.5,397.5,402.5,407.5,412.5,417.5,422.5,427.5,432.5,437.5,442.5,447.5,452.5,457.5,462.5,467.5,472.5,477.5,482.5,487.5,492.5,497.5,502.5,507.5,512.5,517.5,522.5,527.5,532.5,537.5,542.5,547.5,552.5,557.5,562.5,567.5,572.5,577.5,582.5,587.5,592.5,597.5,602.5,607.5,612.5,617.5,622.5,627.5,632.5,637.5,642.5,647.5,652.5,657.5,662.5,667.5,672.5,677.5,682.5,687.5,692.5,697.5,702.5,707.5,712.5,717.5,722.5,727.5,732.5,737.5,742.5,747.5,752.5,757.5,762.5,767.5,772.5,777.5,782.5,787.5,792.5,797.5,802.5,807.5,812.5,817.5,822.5,827.5,832.5,837.5,842.5,847.5,852.5,857.5,862.5,867.5,872.5,877.5,882.5,887.5,892.5,897.5,902.5,907.5,912.5,917.5,922.5,927.5,932.5,937.5,942.5,947.5,952.5,957.5,962.5,967.5,972.5,977.5,982.5,987.5,992.5,997.5,1002.5,1007.5,1012.5,1017.5,1022.5,1027.5,1032.5,1037.5,1042.5,1047.5,1052.5,1057.5,1062.5,1067.5,1072.5,1077.5,1082.5,1087.5,1092.5,1097.5,1102.5,1107.5,1112.5,1117.5,1122.5,1127.5,1132.5,1137.5,1142.5,1147.5,1152.5,1157.5,1162.5,1167.5,1172.5,1177.5,1182.5,1187.5,1192.5,1197.5,1202.5,1207.5,1212.5,1217.5,1222.5,1227.5,1232.5,1237.5,1242.5,1247.5,1252.5,1257.5,1262.5,1267.5,1272.5,1277.5,1282.5,1287.5,1292.5,1297.5,1302.5,1307.5,1312.5,1317.5,1322.5,1327.5,1332.5,1337.5,1342.5,1347.5,1352.5,1357.5,1362.5,1367.5,1372.5,1377.5,1382.5,1387.5,1392.5,1397.5,1402.5,1407.5,1412.5,1417.5,1422.5,1427.5,1432.5,1437.5,1442.5,1447.5,1452.5,1457.5,1462.5,1467.5,1472.5,1477.5,1482.5,1487.5,1492.5,1497.5,1502.5,1507.5,1512.5,1517.5,1522.5,1527.5,1532.5,1537.5,1542.5,1547.5,1552.5,1557.5,1562.5,1567.5,1572.5,1577.5,1582.5,1587.5,1592.5,1597.5,1602.5,1607.5,1612.5,1617.5,1622.5,1627.5,1632.5,1637.5,1642.5,1647.5,1652.5,1657.5,1662.5,1667.5,1672.5,1677.5,1682.5,1687.5,1692.5,1697.5,1702.5,1707.5,1712.5,1717.5,1722.5,1727.5,1732.5,1737.5,1742.5,1747.5,1752.5,1757.5,1762.5,1767.5,1772.5,1777.5,1782.5,1787.5,1792.5,1797.5,1802.5,1807.5,1812.5,1817.5,1822.5,1827.5,1832.5,1837.5,1842.5,1847.5,1852.5,1857.5,1862.5,1867.5,1872.5,1877.5,1882.5,1887.5,1892.5,1897.5,1902.5,1907.5,1912.5,1917.5,1922.5,1927.5,1932.5,1937.5,1942.5,1947.5,1952.5,1957.5,1962.5,1967.5,1972.5,1977.5,1982.5,1987.5,1992.5,1997.5]) # Creating weights for histo: y13_PT_0 y13_PT_0_weights = numpy.array([0.184233745582,0.537348599613,0.782993643722,1.16681392202,1.6427506231,1.96516035287,2.3182750569,2.87097659365,3.25479627194,3.27015025907,4.31414038404,4.25273043551,4.51372721675,6.01830395566,5.89548105861,5.92618603287,6.58635797954,7.32329236187,8.56687081954,8.9813969721,8.95069199784,9.64156741877,10.485972211,11.8677260529,11.0386737478,12.3129571797,12.466486551,12.8656587164,14.8308190693,14.7540551337,15.8287517329,15.7980467586,16.7806209351,18.3619646096,17.8399650472,19.1449639533,19.7590784386,21.2943571518,20.7109476408,22.1234064569,22.6914559808,23.6279801958,24.4109795396,23.2748654918,24.8869141406,25.0097340377,24.1039147969,25.4856686388,27.2512421589,26.3147179439,26.3761428924,27.6350618372,27.2973071203,28.8018808593,28.8479458206,29.001470692,29.9533398941,29.8612249713,30.3678645467,30.0301098298,29.8458799842,29.1396505761,28.9093557692,29.3699303831,29.7077001,26.8674224806,27.5122419402,25.5624385744,26.0537331627,27.2051921975,25.3014387932,25.8387833428,25.7313234329,24.7794392307,23.3669804146,24.1806847326,24.1346197712,23.0445706848,22.829635865,23.1674055819,22.7682259165,22.3997512253,22.2001763926,21.4478820231,20.4038978982,20.8337675378,21.5707019202,19.5441286188,20.3271279625,19.0374890434,18.6997343265,19.6516035287,18.6536693651,18.6997343265,18.4694395195,17.1337356391,17.6250302273,16.074391527,16.6731610251,16.0283415656,16.427506231,16.2739813597,16.1818664369,15.0457523892,15.1532272991,14.2474125583,14.9843469406,14.4623518782,13.9403568157,13.8942978543,14.0171207513,13.4183602532,13.3876552789,13.4183602532,12.3283111668,12.1440768213,12.2976046926,12.1594293084,12.4050751025,11.9291375014,12.2515472312,11.652786733,11.4685523875,11.8523735657,11.3457309904,11.2843195419,10.6395015823,11.1154376834,10.3017393654,9.84115425148,10.5780901338,9.68762638016,10.5780901338,9.82580176435,9.33451167613,9.6108624445,9.79509679009,8.78181013939,9.58015597024,8.39799046109,8.6896937166,7.84528892435,7.90670037287,8.32122652543,8.16769715412,8.10628570559,7.81458245008,7.81458245008,7.10835304202,7.27723490047,6.9548251707,7.09300055489,7.55358566884,6.9548251707,6.63241544094,6.40212363396,6.60171046667,6.81664978652,5.74195318729,6.00295146853,6.55565150528,6.67847440233,6.64776942807,5.81871712295,5.66518925163,5.52701386745,5.94154002,5.58842531597,5.68054173876,5.57307132884,5.29672056047,5.43489594466,5.32742703473,5.25066309907,5.23531061194,5.23531061194,4.62119762667,4.45231576822,4.48302224248,4.95895984357,4.62119762667,4.75937301086,4.22202396124,4.65190260093,4.25273043551,4.11455505132,4.14526002559,4.22202396124,4.0070846414,3.80749780869,3.86890925721,3.89961573148,3.60791097597,3.76144034729,4.22202396124,3.74608636016,3.70002889876,3.70002889876,3.42367813039,3.56185351458,3.53114704031,3.51579455318,3.60791097597,2.91703555504,3.0398569521,3.08591591349,3.22409129768,3.07056342636,2.76350618372,2.87097659365,2.67138976093,2.41039147969,2.87097659365,3.10126840062,2.64068478667,2.85562410651,2.53321437675,2.79421265799,2.42574546682,2.42574546682,2.56392085101,2.53321437675,2.30292256977,2.21080464698,2.13404071132,2.30292256977,2.16474718558,2.7020947352,2.21080464698,2.16474718558,2.13404071132,1.91910139147,1.90374890434,1.79627999442,2.21080464698,2.0265718014,1.94980786574,2.11868822419,1.59669316171,1.90374890434,1.81163248155,1.71951455876,1.88839641721,1.85768994295,1.67345709737,2.19545215985,1.65810461023,1.45851747752,1.56598668744,1.3510476676,1.24357800768,1.6427506231,1.76557352016,1.6427506231,1.42781175326,1.42781175326,1.59669316171,1.38175339186,1.41245896613,1.56598668744,1.50457523892,1.44316469039,1.16681392202,1.48922305178,0.967227389303,0.982580176435,1.16681392202,1.24357800768,1.09004983636,1.3510476676,1.21287243341,1.21287243341,1.13610834775,1.22822522054,1.0132857507,0.951874602171,0.997932963567,1.3510476676,0.859757579381,1.10540262349,1.18216670915,0.93652166504,0.997932963567,0.782993643722,0.782993643722,0.997932963567,1.02863868783,0.844404792249,0.921168877908,0.905816090776,0.875110516512,0.782993643722,0.736935132326,0.675523833799,0.782993643722,0.829052005117,0.875110516512,0.736935132326,0.736935132326,0.614112535272,0.721582345194,0.844404792249,0.844404792249,0.675523833799,0.675523833799,0.76764070659,0.460584513954,0.76764070659,0.706229558063,0.475937301086,0.644818259535,0.660171046667,0.491290088217,0.59875974814,0.614112535272,0.583406961008,0.629465472404,0.42987878969,0.59875974814,0.59875974814,0.491290088217,0.644818259535,0.59875974814,0.706229558063,0.399173215427,0.368467491163,0.506642875349,0.460584513954,0.491290088217,0.491290088217,0.491290088217,0.445231576822,0.445231576822,0.353114704031,0.399173215427,0.322409129768,0.475937301086,0.353114704031,0.460584513954,0.383820428295,0.42987878969,0.475937301086,0.353114704031,0.368467491163,0.414526002559,0.307056342636,0.322409129768,0.414526002559,0.414526002559,0.399173215427,0.353114704031,0.214939469845,0.353114704031,0.353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# Creating weights for histo: y13_PT_1 y13_PT_1_weights = numpy.array([0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0912968591919,0.0,0.0,0.0454653083971,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0454926924109,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_2 y13_PT_2_weights = numpy.array([0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0375985630792,0.0375985630792,0.0751969092266,0.0376018480483,0.037652734079,0.0,0.0,0.0376234482696,0.0377193011884,0.0376123382562,0.03776126202,0.1129777571,0.0752863006732,0.0377260880585,0.188461155919,0.225943427993,0.0751962584308,0.112985504669,0.112761568946,0.0752603153281,0.150718519054,0.188208120328,0.0375701449976,0.112897941648,0.225815593111,0.112934649628,0.0376996843447,0.150720750353,0.113014511566,0.0752610745898,0.112927986719,0.226030200761,0.0376123382562,0.112913917135,0.0376333651574,0.0375576094316,0.0375985630792,0.0377286912416,0.0375576094316,0.0752228790765,0.0375701449976,0.0752773134936,0.112953460725,0.112804862359,0.0377635862906,0.0376714986901,0.03776126202,0.0377286912416,0.0,0.0,0.0376376263202,0.0,0.0376996843447,0.0,0.0,0.0,0.0,0.0,0.0376216663288,0.0,0.0,0.0,0.0,0.0752340045851,0.0376714986901,0.0,0.0,0.0,0.0,0.0376278488886,0.0377132115995,0.0375985630792,0.0,0.0,0.0,0.0,0.0377049526914,0.0,0.0,0.0,0.0,0.0377132115995,0.0,0.0377132115995,0.0,0.0,0.0,0.0,0.0,0.0376216663288,0.0,0.0,0.03776126202,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_3 y13_PT_3_weights = numpy.array([0.0,0.0,0.0206173151769,0.144168676778,0.206205449258,0.14430706847,0.144348918093,0.12361880546,0.185689536008,0.14441060325,0.268116992796,0.0823421883714,0.226891381364,0.165088918023,0.412619156379,0.185787647247,0.309546901079,0.350681256871,0.433226020576,0.2062375944,0.350633877065,0.453875541834,0.412182226202,0.371058382328,0.432826415327,0.288764381201,0.391784990988,0.247310706841,0.268078601442,0.433177574343,0.371182392497,0.516043027735,0.391823839382,0.722228824276,0.433208348365,0.288832784844,0.41265952824,0.535830266984,0.433087385129,0.66011283154,0.41263637155,0.412574366465,0.433062095586,0.330053521184,0.329859583905,0.226934038424,0.350629459012,0.371462253283,0.391765338271,0.18558182693,0.185637128762,0.37157361868,0.330193375404,0.329816469805,0.226835317798,0.247552328619,0.164868320081,0.309543701799,0.165002385129,0.206495821963,0.165075663865,0.330281127071,0.206253286104,0.24731664836,0.206283603087,0.268185548786,0.144401172992,0.082499623394,0.144527133198,0.082430244732,0.330095721204,0.082573222058,0.144296830775,0.165119082659,0.0618462477662,0.0824471095055,0.144540935804,0.0620128388222,0.103130192729,0.123837605712,0.0619774639313,0.0618680485711,0.0618347760639,0.0825847699337,0.0824654520416,0.123819994439,0.0618437645159,0.0206434883305,0.0412365499216,0.0205963979826,0.082550248184,0.0412681466157,0.0206173151769,0.0411700049072,0.0412723666177,0.0205470376697,0.0,0.0412543135403,0.0619128994233,0.0,0.0206242317146,0.0411644899586,0.0206213218937,0.0,0.0206783147734,0.0,0.0,0.0,0.0412052731554,0.0205802340036,0.0,0.0,0.0,0.0,0.0206614804692,0.0,0.0,0.0,0.0,0.0206405480402,0.0,0.0412488290611,0.0206022176244,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0205802340036,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0206041067228,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0205677872827,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0206099263647,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0206783147734,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_4 y13_PT_4_weights = numpy.array([0.0,0.0,0.125803766093,0.236813396866,0.273818275575,0.310878168056,0.314537786405,0.40708853791,0.421943458938,0.447820073609,0.347931446859,0.399719247696,0.384904309355,0.358946376513,0.395920441496,0.381114070874,0.299781619608,0.314609484682,0.310859379199,0.34039215507,0.299761177332,0.344214560074,0.27017008085,0.259023929821,0.396112087834,0.321904220713,0.355211602736,0.332986940562,0.303495951108,0.336744260966,0.307157222878,0.262638755536,0.262736156969,0.233143858,0.273845481839,0.225736088208,0.247960750382,0.233146262974,0.222036637482,0.2701666237,0.173913415252,0.177631654835,0.199880066124,0.207275059494,0.24044896548,0.173805341749,0.196184673791,0.136900555038,0.173921231417,0.181336967684,0.133215323718,0.129534556632,0.129487328961,0.114737445158,0.118503814276,0.0999140292845,0.111006474246,0.140651442138,0.0814197668407,0.118473210986,0.110987219425,0.0740681982766,0.0851136260029,0.0888341954038,0.0665784940381,0.0555107752122,0.0629130736894,0.0740029633662,0.0814061486774,0.066626563449,0.04073279831,0.055524303189,0.0444254850475,0.0406911321414,0.0443864493189,0.0665977187963,0.0333047215214,0.0370089521325,0.0295904802075,0.00740321086407,0.0296238341859,0.022199229578,0.025928982972,0.0333279595794,0.0222092402809,0.0185107665755,0.0221759313957,0.0111147120111,0.0111160798399,0.00370479277368,0.0222056177893,0.0110855186372,0.0222068202761,0.00370714814476,0.0148132759031,0.0110939886538,0.00738767473425,0.022189369186,0.00740516340205,0.0148099029275,0.0110909072813,0.00740490186117,0.0147980839851,0.0147822787988,0.00369858944476,0.00740791108445,0.011110168114,0.014813926749,0.0,0.0111173259169,0.0184891518747,0.00741379124504,0.0111051597564,0.00370835514091,0.00739627401818,0.00369801676041,0.0037037225604,0.0,0.0111091279629,0.0,0.0,0.00370564804244,0.0,0.0,0.00368965797384,0.00369868263749,0.0,0.0,0.0,0.00370323405013,0.0037037225604,0.0,0.0,0.0,0.00369887503538,0.00741044081612,0.00369613336541,0.0,0.00738969791834,0.00741129157555,0.00370479277368,0.0,0.0,0.00369082288296,0.00369801676041,0.00369613336541,0.00370448313332,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00370503627726,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00369801676041,0.0,0.00370564653933,0.0,0.0,0.00368965797384,0.0,0.00368965797384,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00370564804244,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00369535776141,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00370835514091,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00370047885219,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00369858944476,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_5 y13_PT_5_weights = numpy.array([0.0,0.0,0.0416079935461,0.0822384478336,0.10588608742,0.123838234077,0.120030960908,0.120062574777,0.138022823708,0.13894117136,0.165465973163,0.131365921046,0.139867216171,0.13138454127,0.148393568326,0.135152338364,0.153136113895,0.147445557352,0.128534461652,0.107754801706,0.124757436969,0.132345905991,0.126681801869,0.121933059561,0.128560809044,0.134233930696,0.135182256758,0.114407188101,0.111528435438,0.122894814391,0.107760653348,0.103992511158,0.0973601253742,0.0860244900463,0.100183857601,0.0907577330058,0.0794141004342,0.0794206272654,0.0765850867256,0.0822454848079,0.0614193268173,0.0690108566983,0.0652236441573,0.0567203084599,0.0680630707873,0.0633472627194,0.0614411579423,0.0604766873502,0.0538786311984,0.0529457594717,0.0548123731692,0.0661677690411,0.0510684177644,0.0368687188944,0.0415982558141,0.0491615477726,0.0434895064237,0.0463361500785,0.0425517283205,0.0311986881095,0.0293011357319,0.0330871929488,0.0368743004603,0.0311953721792,0.0283536499051,0.0292955991785,0.0226859297685,0.0208111987937,0.0273997422766,0.0217425700994,0.0179593036654,0.0236339107342,0.0208028414489,0.017022080718,0.0179604739938,0.0151307400831,0.0160618113047,0.015122712831,0.0179611791916,0.00850377532072,0.00850247595617,0.00850541077957,0.00472834558548,0.0122886261992,0.0122862765399,0.00944943813605,0.0056736137901,0.0103986629507,0.00661478434508,0.00756294986257,0.00944937961964,0.00189229190175,0.0047244594952,0.00378277429583,0.00378267376763,0.00283813326718,0.0066238063763,0.00661352249105,0.00188873440366,0.00377848159147,0.0,0.00567553132808,0.00378273078362,0.00189165272243,0.00472294407003,0.00189064593996,0.00189002176484,0.00473250025112,0.00094712047429,0.00283383005987,0.0,0.000945468960941,0.003783444984,0.000945490567002,0.00189377131682,0.000949241319314,0.00094518253058,0.00189290407351,0.0009447702149,0.0,0.00188862187209,0.00188920853668,0.00283383005987,0.00189338270779,0.000945336773854,0.0,0.0,0.0009447702149,0.000949241319314,0.000943555023966,0.0,0.0,0.00188886343986,0.0,0.00188867138598,0.0,0.00283532898041,0.0,0.000944141088393,0.00094366770558,0.0,0.0,0.0,0.000946146250961,0.0,0.000945323270066,0.0018902408263,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000945323270066,0.0,0.0,0.0,0.0,0.0,0.000945699725684,0.000945699725684,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00189076747406,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000944843135359,0.00188899097565,0.0,0.000944530597673,0.0,0.000945323270066,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000946217370915,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_6 y13_PT_6_weights = numpy.array([0.0,0.0,0.0161275102588,0.0268234986297,0.0418405165108,0.0568815386952,0.0407784113801,0.0514937479017,0.0494016283533,0.0515434585157,0.0547649012422,0.0429722015054,0.0536869382006,0.0655233502872,0.0601176396797,0.0493921435982,0.0461988552239,0.0579835322824,0.0709283486009,0.0697660724593,0.0525999777629,0.0590649818149,0.0730850244669,0.0461579920495,0.0494060895622,0.0343677216098,0.0536564220319,0.0333113823104,0.0354145836518,0.0354068533889,0.0343167251179,0.0354386741801,0.0257240168156,0.0322111619601,0.0343494643933,0.0257604600191,0.0300271977411,0.0224927969186,0.0268182688932,0.0204022331699,0.0279351494221,0.0236158706553,0.0203779177067,0.0182399076889,0.028999368941,0.0193558584869,0.0193294061421,0.0182320612096,0.0268073932905,0.0236089014221,0.0150642692068,0.0171744322835,0.015021749012,0.0214850623032,0.0182229850862,0.0161079184286,0.00646091023671,0.0203996876566,0.0118248429346,0.0150248006288,0.0171666045488,0.00858014568789,0.0139540055129,0.00964336799533,0.0107534929793,0.0075220818876,0.00967138738662,0.0107506625484,0.0107293274727,0.00751063644987,0.00858406705306,0.0064533224326,0.0118168015118,0.0118114255676,0.00644804021125,0.00643392554598,0.00751657848027,0.00536885502341,0.00429879844379,0.00429136059627,0.00537068824289,0.00428757419205,0.00644537098372,0.00430281353184,0.00430549400612,0.00321833300145,0.00429396609225,0.00215233687175,0.00430256610344,0.00644370271651,0.00321916451082,0.00215457234981,0.00107673264759,0.00429441221315,0.00322081703258,0.00215096814285,0.00107728636235,0.0,0.0,0.00107418863382,0.00213902972279,0.0,0.0021521006901,0.00215473467783,0.0,0.00107318917306,0.00107414777065,0.0,0.00215138577199,0.0,0.00106702670646,0.00106790582704,0.00107673264759,0.0010736821554,0.00107719713817,0.00107719713817,0.00107418863382,0.0,0.0,0.00107914769869,0.00107318917306,0.0,0.00107318917306,0.00106738285339,0.0,0.00106938289958,0.0,0.00214973474979,0.00107673264759,0.00107414777065,0.0,0.0,0.0,0.0,0.00429746383002,0.00322462330606,0.0,0.00107558660425,0.0,0.0,0.0,0.0010736821554,0.0,0.00107418863382,0.0,0.00107414777065,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00107414777065,0.0,0.0,0.0,0.00214993381718,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0010684108059,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_7 y13_PT_7_weights = numpy.array([0.0,0.0,0.0021871801519,0.00299713977265,0.00444646096453,0.00453647638499,0.00486105901594,0.00534800761375,0.00452929727959,0.00631305822787,0.00469156894997,0.00664378427454,0.00550445333323,0.00518235855776,0.00606334228775,0.00477835000113,0.0049401879077,0.0045361070571,0.00332132792999,0.00397030459894,0.00396853025349,0.0038073932841,0.00356340585518,0.00323955245035,0.00315919770434,0.00429248424124,0.00307810587417,0.00234294850833,0.00275350909875,0.0038069422326,0.00267234340301,0.00267394329997,0.00218692083658,0.00290866452805,0.00267274259144,0.00186388466791,0.00194361391393,0.00202331015618,0.0023480829517,0.00243047135847,0.00210588715591,0.00234919565017,0.00234989973056,0.00194364534609,0.00170134896739,0.00243118644012,0.00218117189447,0.00129536804271,0.00145781180416,0.0012963900594,0.00162013140858,0.00178180743952,0.00145868200352,0.00105378313096,0.0017013128204,0.00137729895439,0.00137676617927,0.00137691139585,0.0012152213776,0.000972915883577,0.00121513431052,0.0012153188173,0.0012148705947,0.000809472579428,0.000647621785677,0.000971614120661,0.00081047337941,0.00113416160824,0.000890826239487,0.000728841544733,0.000890623344892,0.000243179622403,0.000405051004218,0.000890708211725,0.000729075557166,0.00105241551766,0.000324589231706,0.000243013503436,0.000243294664109,0.000641646060536,0.000405333265017,0.000242677493643,0.000324352233218,0.000810245024766,0.00024299668723,0.000323939057472,0.000324029896415,0.00032386802079,0.000324193500809,0.000404628555985,0.000566567045463,0.0,0.000486509019049,0.00024276126035,0.0,0.000242740043642,0.000404708236511,0.000404820763645,0.000324013551692,0.000485976243933,0.000404787602716,0.000162179416986,0.000324335417012,8.0935329438e-05,0.000161913029428,0.000404877184372,8.09765527161e-05,8.10532629032e-05,0.000324426255955,0.000485586485146,0.000161800973777,0.000161931417242,0.000161901242368,0.000323991863501,0.000242871272911,8.10323133684e-05,0.0002432145121,0.000162061389224,0.0,0.000162259568994,0.00016181134639,0.000162063903797,8.09776214096e-05,0.000324320172415,0.000161968192869,8.09765527161e-05,8.09752325654e-05,0.000404644586387,0.000162039072391,8.12819475849e-05,0.000243123515997,8.12074847973e-05,0.0,8.07223136882e-05,8.07223136882e-05,0.000243239500668,0.000161934560458,0.0,0.000243243115366,0.0,0.0,0.0,8.12074847973e-05,0.0,8.10351579789e-05,0.0,8.08362867011e-05,0.0,0.0,8.09211849659e-05,0.0,0.0,0.0,0.0,8.08337249801e-05,8.08337249801e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.11095107539e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.09938718364e-05,0.0,8.09938718364e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.07223136882e-05,0.0,0.0,0.0,8.0935329438e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.09211849659e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_8 y13_PT_8_weights = numpy.array([0.0,0.0,0.000213065253097,0.000212802267456,0.000639311243562,0.000425833944364,0.00138280667362,0.000531402160305,0.00106379055852,0.000741113358129,0.000639150879674,0.000636853444244,0.000633163404353,0.000319452104416,0.000318190909252,0.00010653034359,0.000745845206476,0.000319605173975,0.000633945178309,0.000638855208755,0.000425782828374,0.0,0.000426393213424,0.000319823558409,0.000106490252618,0.000532625825865,0.000213060742862,0.000319377212253,0.000528389156705,0.000318429951673,0.0,0.000106490252618,0.000212980560918,0.00053102948131,0.0,0.000106609745988,0.000318960377507,0.000212872092566,0.000319332611046,0.0,0.000212912183538,0.0,0.000106609745988,0.0,0.0,0.000319025302609,0.000106381839948,0.000106609745988,0.000212763624213,0.000106381839948,0.000213293159137,0.000106683413149,0.0,0.000106609745988,0.0,0.000213100054288,0.000106490252618,0.000106490252618,0.000213366826298,0.000106381839948,0.0,0.000106609745988,0.000106609745988,0.000212995427987,0.0,0.0,0.0,0.000104897750115,0.000425932835428,0.0,0.0,0.0,0.0,0.0,0.000212802267456,0.000213065253097,0.000106490252618,0.000319481838553,0.0,0.000106683413149,0.0,0.000106381839948,0.0,0.0,0.0,0.0,0.0,0.000106490252618,0.0,0.0,0.0,0.0,0.000207938230265,0.0,0.0,0.000106381839948,0.0,0.000105748235543,0.0,0.0,0.0,0.000106683413149,0.0,0.0,0.0,0.0,0.0,0.000106683413149,0.0,0.000106312014838,0.0,0.0,0.000106609745988,0.0,0.000105748235543,0.000106609745988,0.0,0.0,0.0,0.0,0.0,0.000105949525632,0.0,0.0,0.0,0.0,0.0,0.0,0.000106312014838,0.0,0.0,0.0,0.000106381839948,0.0,0.00010653034359,0.0,0.0,0.000106490252618,0.0,0.0,0.000106490252618,0.0,0.0,0.0,0.0,0.0,0.0,0.00010560936487,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000106312014838,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000106381839948,0.0,0.0,0.0,0.000106381839948,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_9 y13_PT_9_weights = numpy.array([0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_10 y13_PT_10_weights = numpy.array([0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.95485645769,0.0,0.0,0.0,3.94542685761,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.948593127,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_11 y13_PT_11_weights = numpy.array([0.0,0.0,0.0,0.0,0.0,0.864704003404,0.864567251347,0.0,0.861387369757,3.45748250094,0.0,1.73006049712,0.0,0.0,0.0,1.72887886713,0.0,1.72902729139,2.5870866435,0.86224506021,3.45412206052,0.861387369757,1.72563226668,0.861387369757,1.72956334792,1.72618993839,0.0,0.0,0.0,1.72796670642,0.0,0.0,1.72550401659,3.45722311874,3.4555385755,0.862981993841,0.862575628405,0.863198433872,2.59508426113,0.864105983346,1.7300691432,0.864567251347,2.59198752594,0.864823751516,2.59005801063,0.864823751516,0.0,0.864919578827,0.863198433872,1.72789033277,0.862434409211,1.72577348587,0.865644552057,1.7260962726,0.0,2.59120505633,0.0,0.0,2.59159124759,0.0,0.0,0.0,0.0,0.0,0.863850635987,0.0,0.864704003404,0.862434409211,0.0,0.862575628405,0.862321722058,0.0,0.0,0.0,0.865024340412,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.862981993841,0.0,0.0,0.0,0.0,0.865024340412,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_12 y13_PT_12_weights = numpy.array([0.0,0.0,0.415405431739,1.45475582462,1.45385279881,0.934903917858,0.830163166054,0.83157252103,0.623413387643,1.03884478498,1.14170303091,0.934553959294,0.623284713678,0.830818364652,1.45353832657,0.934981093387,0.830356754015,1.45299593407,0.8304862935,0.830507498738,0.725923406044,1.14223287337,0.622957547139,1.55681937898,1.24583243712,1.03813736668,0.934523089083,0.935069376421,0.519237387602,1.34894168383,1.14351341012,1.454034558,0.830544139083,1.03879400781,0.830573134001,0.623195132364,0.72681027548,0.72723337048,0.414988539633,0.622699045182,0.415281950894,0.41518198334,0.207488211177,0.415680378575,0.311302856641,0.207940733854,0.415326092411,0.72795809918,0.207568560278,0.311245588071,0.623485658558,0.415307772239,0.207918807349,0.207685116964,0.207492971537,0.10395206118,0.207779602891,0.415158325795,0.207530044641,0.415353644796,0.103896985261,0.207964102893,0.0,0.415154863716,0.103514324469,0.20723230578,0.0,0.207676029005,0.207662180686,0.207479411724,0.103966746169,0.104014970055,0.0,0.0,0.0,0.103836312313,0.0,0.103811688271,0.0,0.0,0.10395206118,0.103761069779,0.0,0.0,0.0,0.0,0.103942179828,0.0,0.103973987686,0.103587864813,0.0,0.103720072985,0.0,0.0,0.0,0.0,0.0,0.103973136591,0.0,0.104111980415,0.0,0.10384853057,0.104111980415,0.0,0.0,0.1039572543,0.0,0.0,0.207751184987,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_13 y13_PT_13_weights = numpy.array([0.0,0.0,0.377215365226,0.378243809582,0.340406433675,0.453582877522,0.453908547775,0.302371516343,0.340057550029,0.302507610551,0.567013530783,0.302480983423,0.453924250952,0.189232919431,0.188774068023,0.15131322701,0.491688572945,0.22733943415,0.302581347212,0.377620689279,0.18921776245,0.378158011059,0.453608821902,0.22670381958,0.264578063817,0.302543113387,0.227004592331,0.151338329337,0.37792223581,0.11343902829,0.18915827244,0.15102761124,0.0755870643583,0.0756166955721,0.151096363849,0.189041044804,0.113539483111,0.340365013699,0.151236713846,0.0756410013603,0.0755334232132,0.0378816406616,0.0755660357549,0.075526937118,0.0377518049668,0.226620023782,0.0378559011049,0.113524166823,0.113517498662,0.151277200734,0.0377988689838,0.151200323438,0.0378199203453,0.113495286631,0.0,0.113416565918,0.0756445744022,0.037811135669,0.0378751773247,0.113278833118,0.0377751321512,0.113511331182,0.15113450664,0.0757032906323,0.0,0.0378457054185,0.0378875578011,0.113497562454,0.0376688284649,0.0756174921101,0.0,0.0,0.0754539287202,0.0,0.0376688284649,0.0,0.0,0.113572550818,0.113442783397,0.0378656871433,0.0,0.0,0.0378575852139,0.0377671440129,0.0,0.0378199203453,0.0378457054185,0.0378575852139,0.0,0.0378457054185,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0377988689838,0.0,0.0,0.0,0.0,0.0,0.0378021234105,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0376610906671,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0378656871433,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_14 y13_PT_14_weights = numpy.array([0.0,0.0,0.116736023473,0.0955217010204,0.20153625086,0.159176455988,0.106111447748,0.201548947429,0.0954254379408,0.116760320089,0.116678225227,0.148423327499,0.169654011212,0.137893297931,0.265264516078,0.307751998038,0.169721101038,0.148640900527,0.10611531443,0.138018820832,0.14850383529,0.159232436316,0.0742866600756,0.169638573338,0.106033089716,0.0848648356112,0.116701382038,0.0954570350847,0.0743192094622,0.148545820536,0.0848901133264,0.0424490604109,0.127292672552,0.0318250040909,0.0424693749217,0.0424424091399,0.0318519121609,0.0318437459584,0.0317922238575,0.0318636997713,0.0424261777304,0.0424217050753,0.031818525955,0.0530771276926,0.0318457514393,0.0318408026628,0.0,0.0212045836066,0.0212190692379,0.0212327324777,0.0318204304403,0.0318491852841,0.0423917527142,0.0212298468938,0.0424636037539,0.0211705625721,0.0318461409931,0.0,0.0,0.0318345120899,0.0212292986329,0.0,0.0318147025563,0.0105954010289,0.0106161685764,0.0106079634185,0.0318389270333,0.021216169226,0.0105821460991,0.021196965665,0.0,0.0212325304869,0.0106163604677,0.0,0.0106099111876,0.0,0.0424638778843,0.0106015646361,0.0,0.0318239508527,0.021193387541,0.0106200569007,0.0,0.0212011786175,0.0106099111876,0.0,0.0106140520006,0.0,0.010588048561,0.0106050201229,0.0,0.010588048561,0.021160708303,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0106218906893,0.0,0.0106050201229,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0106199284922,0.0,0.0106358554727,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0106129554787,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.010588048561,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_15 y13_PT_15_weights = numpy.array([0.0,0.0,0.0228252502637,0.0170665358471,0.0171468676969,0.0171039472206,0.00570723111907,0.00570723111907,0.00571686207685,0.00575000976816,0.0229268118824,0.0114364410323,0.0114157564119,0.0114455800267,0.0056668369409,0.0113737267881,0.0114221607994,0.0,0.00570977514566,0.011466871845,0.0057587144166,0.0171143582283,0.00565686027916,0.00576110775172,0.00565686027916,0.0,0.0114380410211,0.00570610979725,0.0,0.00570356133857,0.0,0.011467740537,0.0,0.00568977750116,0.0,0.00571145934444,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00565686027916,0.00576110775172,0.0057952881228,0.0,0.0,0.0,0.00574324194831,0.00570356133857,0.0,0.0,0.0,0.0,0.00574574165387,0.0,0.00568977750116,0.0,0.0,0.0,0.0,0.00575000976816,0.0,0.0,0.00572878443139,0.00576830548546,0.00570610979725,0.0,0.00570977514566,0.0,0.0,0.0,0.0,0.0,0.00567245241421,0.00571686207685,0.0,0.0,0.0,0.0,0.0,0.00565686027916,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0056668369409,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00572416618104,0.0,0.0,0.0,0.00567245241421,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00571686207685,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating weights for histo: y13_PT_16 y13_PT_16_weights = numpy.array([0.0,0.0,0.0,0.00135514604284,0.00202941842518,0.000677464239286,0.00203268116737,0.00203176586712,0.00135434955839,0.00270802404675,0.0,0.00135571225854,0.00135453810446,0.00338597278882,0.00135481211706,0.000675013573414,0.000675579644748,0.0,0.00135672962776,0.0,0.0,0.0006770517767,0.000675013573414,0.00203198963927,0.0,0.000677876124396,0.000678638393368,0.000675761261105,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000677572660498,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000676887629007,0.0,0.0,0.0,0.0,0.0,0.000675761261105,0.0,0.000676507649474,0.0,0.000674995094166,0.000677876124396,0.00135404262963,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000677831369968,0.0,0.0,0.0,0.000679381605616,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000675013573414,0.0,0.0,0.0,0.000678638393368,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.000675579644748,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]) # Creating a new Canvas fig = plt.figure(figsize=(12,6),dpi=80) frame = gridspec.GridSpec(1,1,right=0.7) pad = fig.add_subplot(frame[0]) # Creating a new Stack pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights+y13_PT_12_weights+y13_PT_13_weights+y13_PT_14_weights+y13_PT_15_weights+y13_PT_16_weights,\ label="$bg\_dip\_1600\_inf$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#e5e5e5", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights+y13_PT_12_weights+y13_PT_13_weights+y13_PT_14_weights+y13_PT_15_weights,\ label="$bg\_dip\_1200\_1600$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#f2f2f2", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights+y13_PT_12_weights+y13_PT_13_weights+y13_PT_14_weights,\ label="$bg\_dip\_800\_1200$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#ccc6aa", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights+y13_PT_12_weights+y13_PT_13_weights,\ label="$bg\_dip\_600\_800$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#ccc6aa", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights+y13_PT_12_weights,\ label="$bg\_dip\_400\_600$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#c1bfa8", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights,\ label="$bg\_dip\_200\_400$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#bab5a3", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights,\ label="$bg\_dip\_100\_200$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#b2a596", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights,\ label="$bg\_dip\_0\_100$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#b7a39b", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights,\ label="$bg\_vbf\_1600\_inf$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#ad998c", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights,\ label="$bg\_vbf\_1200\_1600$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#9b8e82", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights,\ label="$bg\_vbf\_800\_1200$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#876656", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights,\ label="$bg\_vbf\_600\_800$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#afcec6", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights,\ label="$bg\_vbf\_400\_600$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#84c1a3", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights,\ label="$bg\_vbf\_200\_400$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#89a8a0", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights,\ label="$bg\_vbf\_100\_200$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#829e8c", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights+y13_PT_1_weights,\ label="$bg\_vbf\_0\_100$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#adbcc6", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") pad.hist(x=xData, bins=xBinning, weights=y13_PT_0_weights,\ label="$signal$", histtype="step", rwidth=1.0,\ color=None, edgecolor="#7a8e99", linewidth=1, linestyle="solid",\ bottom=None, cumulative=False, normed=False, align="mid", orientation="vertical") # Axis plt.rc('text',usetex=False) plt.xlabel(r"p_{T} [ a_{2} ] ( GeV ) ",\ fontsize=16,color="black") plt.ylabel(r"$\mathrm{Events}$ $(\mathcal{L}_{\mathrm{int}} = 150.0\ \mathrm{fb}^{-1})$ ",\ fontsize=16,color="black") # Boundary of y-axis ymax=(y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights+y13_PT_12_weights+y13_PT_13_weights+y13_PT_14_weights+y13_PT_15_weights+y13_PT_16_weights).max()*1.1 #ymin=0 # linear scale ymin=min([x for x in (y13_PT_0_weights+y13_PT_1_weights+y13_PT_2_weights+y13_PT_3_weights+y13_PT_4_weights+y13_PT_5_weights+y13_PT_6_weights+y13_PT_7_weights+y13_PT_8_weights+y13_PT_9_weights+y13_PT_10_weights+y13_PT_11_weights+y13_PT_12_weights+y13_PT_13_weights+y13_PT_14_weights+y13_PT_15_weights+y13_PT_16_weights) if x])/100. # log scale plt.gca().set_ylim(ymin,ymax) # Log/Linear scale for X-axis plt.gca().set_xscale("linear") #plt.gca().set_xscale("log",nonposx="clip") # Log/Linear scale for Y-axis #plt.gca().set_yscale("linear") plt.gca().set_yscale("log",nonposy="clip") # Legend plt.legend(bbox_to_anchor=(1.05,1), loc=2, borderaxespad=0.) # Saving the image plt.savefig('../../HTML/MadAnalysis5job_0/selection_12.png') plt.savefig('../../PDF/MadAnalysis5job_0/selection_12.png') plt.savefig('../../DVI/MadAnalysis5job_0/selection_12.eps') # Running! if __name__ == '__main__': selection_12()

306.010309

5,718

0.704444

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0.027878

59,366

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307.595855

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1

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false

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1

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1

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null

0

7

4b8d048dccc653e740f0f9f42e336d4dff348559

1,626

py

Python

src/config/en_config.py

bestfitting/instance_level_recognition

683f021b4e65876835f028797ec28b0d1071bb45

[ "Apache-2.0" ]

103

2020-10-20T13:23:35.000Z

2022-03-27T15:08:41.000Z

src/config/en_config.py

solomonkimunyu/instance_level_recognition

683f021b4e65876835f028797ec28b0d1071bb45

[ "Apache-2.0" ]

3

2020-10-29T03:06:51.000Z

2022-02-12T02:44:57.000Z

src/config/en_config.py

solomonkimunyu/instance_level_recognition

683f021b4e65876835f028797ec28b0d1071bb45

[ "Apache-2.0" ]

23

2020-10-21T00:50:29.000Z

2022-03-09T16:01:57.000Z

en_m4_b7_b6_b5_r152_i800 = [ # b7, { 'is_20191st': False, 'module': 'efficientnet_gem_fc_face', 'model_name': 'class_efficientnet_b7_gem_fc_arcface2_1head', 'out_dir': 'v2x_sgd_ls_aug3b_norm1_0918_class_efficientnet_b7_gem_fc_arcface2_1head_i736', 'predict_epoch': '26.80', 'img_size': 800, 'batch_size': 4, 'num_classes': 81313, 'in_channels': 3, 'preprocessing': True, 'weight': 0.6, }, { 'is_20191st': False, 'module': 'efficientnet_gem_fc_face', 'model_name': 'class_efficientnet_b6_gem_fc_arcface2_1head', 'out_dir': 'v2x_sgd_ls_aug3b_norm1_0919_class_efficientnet_b6_gem_fc_arcface2_1head_i736', 'predict_epoch': '21.70', 'img_size': 800, 'batch_size': 4, 'num_classes': 81313, 'in_channels': 3, 'preprocessing': True, 'weight': 0.2, }, { 'is_20191st': False, 'module': 'efficientnet_gem_fc_face', 'model_name': 'class_efficientnet_b5_gem_fc_arcface2_1head', 'out_dir': 'v2x_sgd_ls_aug3b_norm1_0918_class_efficientnet_b5_gem_fc_arcface2_1head_i736', 'predict_epoch': '19.30', 'img_size': 800, 'batch_size': 4, 'num_classes': 81313, 'in_channels': 3, 'preprocessing': True, 'weight': 0.1, }, { 'is_20191st': False, 'module': 'resnet_gem_fc_face', 'model_name': 'class_resnet152_gem_fc_arcface_1head', 'out_dir': 'v2x_sgd_ls_aug3b_norm1_0919_class_resnet152_gem_fc_arcface_1head_i736', 'predict_epoch': '17.90', 'img_size': 800, 'batch_size': 4, 'num_classes': 81313, 'in_channels': 3, 'preprocessing': True, 'weight': 0.1, }, ]

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4b951ced25384d90524e9918f71c85e35c75f75d

7,736

py

Python

PIRM_VIDAR_final_code/track1/tools/loss.py

contstriver/DRAN

49ec70d1535a1a0a5839edb4b408be212644503b

[ "Apache-2.0" ]

null

PIRM_VIDAR_final_code/track1/tools/loss.py

contstriver/DRAN

49ec70d1535a1a0a5839edb4b408be212644503b

[ "Apache-2.0" ]

null

PIRM_VIDAR_final_code/track1/tools/loss.py

contstriver/DRAN

49ec70d1535a1a0a5839edb4b408be212644503b

[ "Apache-2.0" ]

null

#!/usr/local/bin/python from __future__ import division import torch import random import torch.nn as nn import torch.optim as optim from torch.autograd import Variable class reconstruct_loss(nn.Module): """the loss between the input and synthesized input""" def __init__(self, cie_matrix, batchsize): super(reconstruct_loss, self).__init__() self.cie = Variable(torch.from_numpy(cie_matrix).float().cuda(), requires_grad=False) self.batchsize = batchsize def forward(self, network_input, network_output): network_output = network_output.permute(3, 2, 0, 1) network_output = network_output.contiguous().view(-1, 31) reconsturct_input = torch.mm(network_output,self.cie) reconsturct_input = reconsturct_input.view(50, 50, 64, 3) reconsturct_input = reconsturct_input.permute(2,3,1,0) reconstruction_loss = torch.mean(torch.abs(reconsturct_input - network_input)) return reconstruction_loss def rrmse_loss(outputs, label): """Computes the rrmse value""" error = torch.abs(outputs-label)/(label + 1/65535) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def rrmse_loss2(outputs, label): """Computes the rrmse value""" zeros = torch.zeros(outputs.shape) outputs = torch.where(outputs>1/65535,outputs,zeros.cuda()) error = torch.abs(outputs-label)/(label + 1/65535) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def rrmse_loss3(outputs, label): """Computes the rrmse value""" zeros = torch.zeros(outputs.shape) ones = torch.ones(outputs.shape)*1/65535 twos = torch.ones(outputs.shape)*2/65535 outputs = torch.where(outputs>1/65535,outputs,zeros.cuda()) outputs = torch.where((outputs>2/65535)|(outputs<1/65535),outputs,ones.cuda()) outputs = torch.where((outputs>3/65535)|(outputs<2/65535),outputs,twos.cuda()) error = torch.abs(outputs-label)/(label + 1/65535) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def rrmse_loss_round(outputs, label): """Computes the rrmse value""" outputs = torch.clamp(outputs*65535,max=65535,min=0) outputs = torch.round(outputs) error = torch.abs(outputs-label)/(label + 1) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def rrmse_loss_ceil(outputs, label): """Computes the rrmse value""" outputs = torch.clamp(outputs*65535,max=65535,min=0) outputs = torch.ceil(outputs)-1 error = torch.abs(outputs-label)/(label + 1) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def rrmse_loss_con(outputs, label): """Computes the rrmse value""" zeros = torch.zeros(outputs.shape) outputs = torch.clamp(outputs*65535,max=65535,min=0) outputs = torch.round(torch.where(outputs>1,outputs,zeros.cuda())) error = torch.abs(outputs-label)/(label + 1) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def sid_loss(output, target): """For the network, the input image dimension is BxCxHxW""" a = torch.sum(torch.sum(output* torch.log10(torch.clamp((output + 1e-3/65536)/(target + 1e-3/65536),min=1e-8)),3),2) b = torch.sum(torch.sum(target* torch.log10(torch.clamp((target+ 1e-3/65536)/(output+ 1e-3/65536),min=1e-8)),3),2) sid = torch.sum(torch.abs(a + b))/(target.shape[0]*target.shape[1]*target.shape[2] * target.shape[3]) return sid def test_sid_loss(output, target): """For the network, the input image dimension is BxCxHxW""" a = torch.sum(torch.sum(output* torch.log10(torch.clamp((output + 1e-3)/(target + 1e-3),min=1e-8)),3),2) b = torch.sum(torch.sum(target* torch.log10(torch.clamp((target+ 1e-3)/(output+ 1e-3),min=1e-8)),3),2) sid = torch.sum(torch.abs(a + b))/(target.shape[0]*target.shape[1]*target.shape[2] * target.shape[3]) return sid def appsa_loss(output, target): nom = torch.sum(target* output, dim=1) denom = torch.norm(target,2,1) * torch.norm(output,2,1) cos = torch.clamp(nom/(denom + 1e-3/65536), max=1) appsa = torch.acos(torch.clamp(cos,min=1e-8)) appsa = torch.sum(appsa.view(-1))/(target.shape[0]*target.shape[2] * target.shape[3]) return appsa def test_appsa_loss(output, target): nom = torch.sum(target* output, dim=1) denom = torch.norm(target,2,1) * torch.norm(output,2,1) cos = torch.clamp(nom/(denom + 1e-3), max=1) appsa = torch.acos(torch.clamp(cos,min=1e-8)) appsa = torch.sum(appsa.view(-1))/(target.shape[0]*target.shape[2] * target.shape[3]) return appsa def tvloss(output, tv_weight): """Computes the total variation loss""" diff_i = torch.sum(torch.abs(output[:, :, :, 1:] - output[:, :, :, :-1])) diff_j = torch.sum(torch.abs(output[:, :, 1:, :] - output[:, :, :-1, :])) tv_loss = tv_weight*(diff_i + diff_j) return tv_loss def rrmse_loss_round(outputs, label): """Computes the rrmse value""" outputs = torch.clamp(outputs*65535,max=65535,min=0) outputs = torch.round(outputs) error = torch.abs(outputs-label)/(label + 1) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def rrmse_loss_ceil(outputs, label): """Computes the rrmse value""" outputs = torch.clamp(outputs*65535,max=65535,min=0) outputs = torch.ceil(outputs)-1 error = torch.abs(outputs-label)/(label + 1) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def rrmse_loss_con(outputs, label): """Computes the rrmse value""" zeros = torch.zeros(outputs.shape) outputs = torch.clamp(outputs*65535,max=65535,min=0) outputs = torch.round(torch.where(outputs>1,outputs,zeros.cuda())) error = torch.abs(outputs-label)/(label + 1) #1/65536 = 1.5e-5 rrmse = torch.mean(error.view(-1)) return rrmse def sid_loss(output, target): """For the network, the input image dimension is BxCxHxW""" a = torch.sum(torch.sum(output* torch.log10(torch.clamp((output + 1e-3/65536)/(target + 1e-3/65536),min=1e-8)),3),2) b = torch.sum(torch.sum(target* torch.log10(torch.clamp((target+ 1e-3/65536)/(output+ 1e-3/65536),min=1e-8)),3),2) sid = torch.sum(torch.abs(a + b))/(target.shape[0]*target.shape[1]*target.shape[2] * target.shape[3]) return sid def test_sid_loss(output, target): """For the network, the input image dimension is BxCxHxW""" a = torch.sum(torch.sum(output* torch.log10(torch.clamp((output + 1e-3)/(target + 1e-3),min=1e-8)),3),2) b = torch.sum(torch.sum(target* torch.log10(torch.clamp((target+ 1e-3)/(output+ 1e-3),min=1e-8)),3),2) sid = torch.sum(torch.abs(a + b))/(target.shape[0]*target.shape[1]*target.shape[2] * target.shape[3]) return sid def appsa_loss(output, target): nom = torch.sum(target* output, dim=1) denom = torch.norm(target,2,1) * torch.norm(output,2,1) cos = torch.clamp(nom/(denom + 1e-3/65536), max=1) appsa = torch.acos(torch.clamp(cos,min=1e-8)) appsa = torch.sum(appsa.view(-1))/(target.shape[0]*target.shape[2] * target.shape[3]) return appsa def test_appsa_loss(output, target): nom = torch.sum(target* output, dim=1) denom = torch.norm(target,2,1) * torch.norm(output,2,1) cos = torch.clamp(nom/(denom + 1e-3), max=1) appsa = torch.acos(torch.clamp(cos,min=1e-8)) appsa = torch.sum(appsa.view(-1))/(target.shape[0]*target.shape[2] * target.shape[3]) return appsa def tvloss(output, tv_weight): """Computes the total variation loss""" diff_i = torch.sum(torch.abs(output[:, :, :, 1:] - output[:, :, :, :-1])) diff_j = torch.sum(torch.abs(output[:, :, 1:, :] - output[:, :, :-1, :])) tv_loss = tv_weight*(diff_i + diff_j) return tv_loss

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7,736

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0

null

0

1

0

1

0

null

0

7

29e38561d157f63e390191afb73027bfd7af6f4a

2,143

py

Python

ideas/models.py

Adstefnum/ScrapBook

8391e86daf678f64a30dd693e34cd69939b6fe0d

[ "MIT" ]

null

ideas/models.py

Adstefnum/ScrapBook

8391e86daf678f64a30dd693e34cd69939b6fe0d

[ "MIT" ]

null

ideas/models.py

Adstefnum/ScrapBook

8391e86daf678f64a30dd693e34cd69939b6fe0d

[ "MIT" ]

null

from django.db import models from django.core.files.storage import FileSystemStorage CAT_CHOICES = ( ('tech','TECH'), ('class_mus','CLASSICAL MUSIC'), ('gen','GENERAL'), ('gen_music','GENERAL MUSIC'), ('novels','NOVELS'), ('physics','PHYSICS'), ('maths','MATHS'), ) class Video(models.Model): file_pic = models.FileField(storage=FileSystemStorage(location='/media/image/'),upload_to='image',default='/media/image/') cat_name = models.CharField(max_length=30, choices=CAT_CHOICES, default='notes') file_name = models.CharField(max_length=100) file = models.FileField(storage=FileSystemStorage(location='/media/video/'),upload_to='video',default='/media/video/') last_date = models.DateField() def __str__(self): return self.file_name class Audio(models.Model): file_pic = models.FileField(storage=FileSystemStorage(location='/media/image/'),upload_to='image',default='/media/image/') cat_name = models.CharField(max_length=30, choices=CAT_CHOICES, default='notes') file_name = models.CharField(max_length=100) file = models.FileField(storage=FileSystemStorage(location='/media/audio/'),upload_to='audio') last_date = models.DateField() def __str__(self): return self.file_name class Image(models.Model): file_pic = models.FileField(storage=FileSystemStorage(location='/media/image/'),upload_to='image',default='/media/image/') cat_name = models.CharField(max_length=30, choices=CAT_CHOICES, default='notes') file_name = models.CharField(max_length=100) file = models.FileField(storage=FileSystemStorage(location='/media/images/'),upload_to='images') last_date = models.DateField() def __str__(self): return self.file_name class Note(models.Model): file_pic = models.FileField(storage=FileSystemStorage(location='/media/image/'),upload_to='image',default='/media/image/') cat_name = models.CharField(max_length=30, choices=CAT_CHOICES, default='notes') file_name = models.CharField(max_length=100) file = models.FileField(storage=FileSystemStorage(location='/media/notes/'),upload_to='notes') last_date = models.DateField() def __str__(self): return self.file_name

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0

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null

0

1

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8

d9a9b5e70d454db4f3bd6755d13b70999d6b1425

68,637

py

Python

benchmarks/SimResults/combinations_spec_ml_fulltrained/old/cmp_bwavesgcccactusADMmilc/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/combinations_spec_ml_fulltrained/old/cmp_bwavesgcccactusADMmilc/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

benchmarks/SimResults/combinations_spec_ml_fulltrained/old/cmp_bwavesgcccactusADMmilc/power.py

TugberkArkose/MLScheduler

e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061

[ "Unlicense" ]

null

power = {'BUSES': {'Area': 1.33155, 'Bus/Area': 1.33155, 'Bus/Gate Leakage': 0.00662954, 'Bus/Peak Dynamic': 0.0, 'Bus/Runtime Dynamic': 0.0, 'Bus/Subthreshold Leakage': 0.0691322, 'Bus/Subthreshold Leakage with power gating': 0.0259246, 'Gate Leakage': 0.00662954, 'Peak Dynamic': 0.0, 'Runtime Dynamic': 0.0, 'Subthreshold Leakage': 0.0691322, 'Subthreshold Leakage with power gating': 0.0259246}, 'Core': [{'Area': 32.6082, 'Execution Unit/Area': 8.2042, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.134375, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.308232, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.791398, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.122718, 'Execution Unit/Instruction Scheduler/Area': 2.17927, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.347161, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.601157, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.34478, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 1.2931, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.221822, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 6.68559, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788, 'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.149512, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0125848, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968, 'Execution Unit/Register Files/Gate Leakage': 0.000622708, 'Execution Unit/Register Files/Integer RF/Area': 0.362673, 'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.138639, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0930726, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.288151, 'Execution Unit/Register Files/Runtime Dynamic': 0.105657, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.371823, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.911432, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155, 'Execution Unit/Runtime Dynamic': 3.0238, 'Execution Unit/Subthreshold Leakage': 1.83518, 'Execution Unit/Subthreshold Leakage with power gating': 0.709678, 'Gate Leakage': 0.372997, 'Instruction Fetch Unit/Area': 5.86007, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000824659, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000824659, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000720848, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000280459, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.001337, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00370716, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00781487, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 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'Load Store Unit/Gate Leakage': 0.0350888, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.0308219, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.0308218, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 2.33536, 'Load Store Unit/Runtime Dynamic': 0.649322, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate Leakage': 0.00329971, 'Load Store Unit/StoreQ/Peak Dynamic': 0.0760015, 'Load Store Unit/StoreQ/Runtime Dynamic': 0.152002, 'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621, 'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004, 'Load Store Unit/Subthreshold Leakage': 0.591321, 'Load Store Unit/Subthreshold Leakage with power gating': 0.283293, 'Memory Management Unit/Area': 0.4339, 'Memory Management Unit/Dtlb/Area': 0.0879726, 'Memory 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0.303608, 'Renaming Unit/FP Front End RAT/Area': 0.131045, 'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123, 'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468, 'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.0900952, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885, 'Renaming Unit/Free List/Area': 0.0340654, 'Renaming Unit/Free List/Gate Leakage': 2.5481e-05, 'Renaming Unit/Free List/Peak Dynamic': 0.0306032, 'Renaming Unit/Free List/Runtime Dynamic': 0.00544867, 'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144, 'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064, 'Renaming Unit/Gate Leakage': 0.00708398, 'Renaming Unit/Int Front End RAT/Area': 0.0941223, 'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242, 'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965, 'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0473959, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228, 'Renaming Unit/Peak Dynamic': 3.58947, 'Renaming Unit/Runtime Dynamic': 0.14294, 'Renaming Unit/Subthreshold Leakage': 0.0552466, 'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461, 'Runtime Dynamic': 2.28126, 'Subthreshold Leakage': 6.16288, 'Subthreshold Leakage with power gating': 2.55328}], 'DRAM': {'Area': 0, 'Gate Leakage': 0, 'Peak Dynamic': 6.118045548428725, 'Runtime Dynamic': 6.118045548428725, 'Subthreshold Leakage': 4.252, 'Subthreshold Leakage with power gating': 4.252}, 'L3': [{'Area': 61.9075, 'Gate Leakage': 0.0484137, 'Peak Dynamic': 0.283309, 'Runtime Dynamic': 0.085314, 'Subthreshold Leakage': 6.80085, 'Subthreshold Leakage with power gating': 3.32364}], 'Processor': {'Area': 191.908, 'Gate Leakage': 1.53485, 'Peak Dynamic': 73.5088, 'Peak Power': 106.621, 'Runtime Dynamic': 15.5123, 'Subthreshold Leakage': 31.5774, 'Subthreshold Leakage with power gating': 13.9484, 'Total Cores/Area': 128.669, 'Total Cores/Gate Leakage': 1.4798, 'Total Cores/Peak Dynamic': 73.2255, 'Total Cores/Runtime Dynamic': 15.4269, 'Total Cores/Subthreshold Leakage': 24.7074, 'Total Cores/Subthreshold Leakage with power gating': 10.2429, 'Total L3s/Area': 61.9075, 'Total L3s/Gate Leakage': 0.0484137, 'Total L3s/Peak Dynamic': 0.283309, 'Total L3s/Runtime Dynamic': 0.085314, 'Total L3s/Subthreshold Leakage': 6.80085, 'Total L3s/Subthreshold Leakage with power gating': 3.32364, 'Total Leakage': 33.1122, 'Total NoCs/Area': 1.33155, 'Total NoCs/Gate Leakage': 0.00662954, 'Total NoCs/Peak Dynamic': 0.0, 'Total NoCs/Runtime Dynamic': 0.0, 'Total NoCs/Subthreshold Leakage': 0.0691322, 'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}

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0.112876

0.093379

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0.930222

0.917438

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0.841738

0

0.132404

0.224238

68,637

914

125

75.095186

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0.657143

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false

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null

0

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1

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null

0

7

8a133c1363392ead67a9754e01c9275f4085f943

16,746

py

Python

numpy/typing/tests/data/reveal/arithmetic.py

takanori-pskq/numpy

ae7f9a2cb71cccc9d49cd343e238464107397814

[ "BSD-3-Clause" ]

3

2021-02-06T06:47:30.000Z

2021-08-11T10:05:27.000Z

numpy/typing/tests/data/reveal/arithmetic.py

RuSHi2381/numpy

5da4a8e1835a11d5a03b715e9c0afe3bb96c883b

[ "BSD-3-Clause" ]

null

numpy/typing/tests/data/reveal/arithmetic.py

RuSHi2381/numpy

5da4a8e1835a11d5a03b715e9c0afe3bb96c883b

[ "BSD-3-Clause" ]

null

import numpy as np c16 = np.complex128() f8 = np.float64() i8 = np.int64() u8 = np.uint64() c8 = np.complex64() f4 = np.float32() i4 = np.int32() u4 = np.uint32() dt = np.datetime64(0, "D") td = np.timedelta64(0, "D") b_ = np.bool_() b = bool() c = complex() f = float() i = int() AR = np.array([0], dtype=np.float64) AR.setflags(write=False) # unary ops reveal_type(-c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(-c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(-f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(-f4) # E: numpy.floating[numpy.typing._32Bit] reveal_type(-i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(-i4) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(-u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(-u4) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(-td) # E: numpy.timedelta64 reveal_type(-AR) # E: Union[numpy.ndarray*, numpy.generic] reveal_type(+c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(+c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(+f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(+f4) # E: numpy.floating[numpy.typing._32Bit] reveal_type(+i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(+i4) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(+u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(+u4) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(+td) # E: numpy.timedelta64 reveal_type(+AR) # E: Union[numpy.ndarray*, numpy.generic] reveal_type(abs(c16)) # E: numpy.floating[numpy.typing._64Bit] reveal_type(abs(c8)) # E: numpy.floating[numpy.typing._32Bit] reveal_type(abs(f8)) # E: numpy.floating[numpy.typing._64Bit] reveal_type(abs(f4)) # E: numpy.floating[numpy.typing._32Bit] reveal_type(abs(i8)) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(abs(i4)) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(abs(u8)) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(abs(u4)) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(abs(td)) # E: numpy.timedelta64 reveal_type(abs(b_)) # E: numpy.bool_ reveal_type(abs(AR)) # E: Union[numpy.ndarray*, numpy.generic] # Time structures reveal_type(dt + td) # E: numpy.datetime64 reveal_type(dt + i) # E: numpy.datetime64 reveal_type(dt + i4) # E: numpy.datetime64 reveal_type(dt + i8) # E: numpy.datetime64 reveal_type(dt - dt) # E: numpy.timedelta64 reveal_type(dt - i) # E: numpy.datetime64 reveal_type(dt - i4) # E: numpy.datetime64 reveal_type(dt - i8) # E: numpy.datetime64 reveal_type(td + td) # E: numpy.timedelta64 reveal_type(td + i) # E: numpy.timedelta64 reveal_type(td + i4) # E: numpy.timedelta64 reveal_type(td + i8) # E: numpy.timedelta64 reveal_type(td - td) # E: numpy.timedelta64 reveal_type(td - i) # E: numpy.timedelta64 reveal_type(td - i4) # E: numpy.timedelta64 reveal_type(td - i8) # E: numpy.timedelta64 reveal_type(td / f) # E: numpy.timedelta64 reveal_type(td / f4) # E: numpy.timedelta64 reveal_type(td / f8) # E: numpy.timedelta64 reveal_type(td / td) # E: numpy.floating[numpy.typing._64Bit] reveal_type(td // td) # E: numpy.signedinteger[numpy.typing._64Bit] # boolean reveal_type(b_ / b) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / i) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / i8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / i4) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / u8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / u4) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / f) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / f4) # E: numpy.floating[numpy.typing._32Bit] reveal_type(b_ / c) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(b_ / c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(b_ / c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(b / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i8 / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i4 / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(u8 / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(u4 / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 / b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f4 / b_) # E: numpy.floating[numpy.typing._32Bit] reveal_type(c / b_) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 / b_) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 / b_) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] # Complex reveal_type(c16 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + f8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + i8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + c8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + f4) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + i4) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + b_) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + b) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + c) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + f) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c16 + i) # E: numpy.complexfloating[Any, Any] reveal_type(c16 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(c16 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f8 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(i8 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f4 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(i4 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(b_ + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(b + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(i + c16) # E: numpy.complexfloating[Any, Any] reveal_type(AR + c16) # E: Union[numpy.ndarray, numpy.generic] reveal_type(c8 + c16) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 + f8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 + i8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 + c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(c8 + f4) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(c8 + i4) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(c8 + b_) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(c8 + b) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(c8 + c) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 + f) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 + i) # E: numpy.complexfloating[Any, Any] reveal_type(c8 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(c16 + c8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f8 + c8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(i8 + c8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(c8 + c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(f4 + c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(i4 + c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(b_ + c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(b + c8) # E: numpy.complexfloating[numpy.typing._32Bit, numpy.typing._32Bit] reveal_type(c + c8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f + c8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(i + c8) # E: numpy.complexfloating[Any, Any] reveal_type(AR + c8) # E: Union[numpy.ndarray, numpy.generic] # Float reveal_type(f8 + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 + i8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 + f4) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 + i4) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 + b_) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 + b) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 + c) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f8 + f) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f8 + i) # E: numpy.floating[Any] reveal_type(f8 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(f8 + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i8 + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f4 + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i4 + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b_ + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(b + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(c + f8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i + f8) # E: numpy.floating[Any] reveal_type(AR + f8) # E: Union[numpy.ndarray, numpy.generic] reveal_type(f4 + f8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f4 + i8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f4 + f4) # E: numpy.floating[numpy.typing._32Bit] reveal_type(f4 + i4) # E: numpy.floating[numpy.typing._32Bit] reveal_type(f4 + b_) # E: numpy.floating[numpy.typing._32Bit] reveal_type(f4 + b) # E: numpy.floating[numpy.typing._32Bit] reveal_type(f4 + c) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f4 + f) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f4 + i) # E: numpy.floating[Any] reveal_type(f4 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(f8 + f4) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i8 + f4) # E: numpy.floating[numpy.typing._64Bit] reveal_type(f4 + f4) # E: umpy.floating[numpy.typing._32Bit] reveal_type(i4 + f4) # E: umpy.floating[numpy.typing._32Bit] reveal_type(b_ + f4) # E: umpy.floating[numpy.typing._32Bit] reveal_type(b + f4) # E: umpy.floating[numpy.typing._32Bit] reveal_type(c + f4) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f + f4) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i + f4) # E: numpy.floating[Any] reveal_type(AR + f4) # E: Union[numpy.ndarray, numpy.generic] # Int reveal_type(i8 + i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(i8 + u8) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(i8 + i4) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(i8 + u4) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(i8 + b_) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(i8 + b) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(i8 + c) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(i8 + f) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i8 + i) # E: numpy.signedinteger[Any] reveal_type(i8 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(u8 + u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(u8 + i4) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(u8 + u4) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(u8 + b_) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(u8 + b) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(u8 + c) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(u8 + f) # E: numpy.floating[numpy.typing._64Bit] reveal_type(u8 + i) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(u8 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(i8 + i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(u8 + i8) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(i4 + i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(u4 + i8) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(b_ + i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(b + i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(c + i8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f + i8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i + i8) # E: numpy.signedinteger[Any] reveal_type(AR + i8) # E: Union[numpy.ndarray, numpy.generic] reveal_type(u8 + u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(i4 + u8) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(u4 + u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(b_ + u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(b + u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(c + u8) # E: numpy.complexfloating[numpy.typing._64Bit, numpy.typing._64Bit] reveal_type(f + u8) # E: numpy.floating[numpy.typing._64Bit] reveal_type(i + u8) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(AR + u8) # E: Union[numpy.ndarray, numpy.generic] reveal_type(i4 + i8) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(i4 + i4) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(i4 + i) # E: numpy.signedinteger[Any] reveal_type(i4 + b_) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(i4 + b) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(i4 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(u4 + i8) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(u4 + i4) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(u4 + u8) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(u4 + u4) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(u4 + i) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(u4 + b_) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(u4 + b) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(u4 + AR) # E: Union[numpy.ndarray, numpy.generic] reveal_type(i8 + i4) # E: numpy.signedinteger[numpy.typing._64Bit] reveal_type(i4 + i4) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(i + i4) # E: numpy.signedinteger[Any] reveal_type(b_ + i4) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(b + i4) # E: numpy.signedinteger[numpy.typing._32Bit] reveal_type(AR + i4) # E: Union[numpy.ndarray, numpy.generic] reveal_type(i8 + u4) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(i4 + u4) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(u8 + u4) # E: numpy.unsignedinteger[numpy.typing._64Bit] reveal_type(u4 + u4) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(b_ + u4) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(b + u4) # E: numpy.unsignedinteger[numpy.typing._32Bit] reveal_type(i + u4) # E: Union[numpy.signedinteger[Any], numpy.floating[numpy.typing._64Bit]] reveal_type(AR + u4) # E: Union[numpy.ndarray, numpy.generic]

57.349315

95

0.741789

2,509

16,746

4.745317

0.024312

0.218041

0.236519

0.242063

0.969931

0.968503

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0.90005

0.793214

0

0.056994

0.105219

16,746

291

96

57.546392

0.737587

0.651021

0

0.152

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1

0

false

0

0.004

0

0.004

0

null

1

0

null

0

9

8a6f93e9ef7c5b751f5ccfb1caee967e0d9863bd

15,639

py

Python

wagtail-repository/wagtail/admin/tests/test_privacy.py

TobiasSkovgaardJepsen/wagtail-on-heroku

17e4720f86023225e0704890688998a80bb87a17

[ "BSD-3-Clause" ]

null

wagtail-repository/wagtail/admin/tests/test_privacy.py

TobiasSkovgaardJepsen/wagtail-on-heroku

17e4720f86023225e0704890688998a80bb87a17

[ "BSD-3-Clause" ]

4

2020-06-05T17:00:01.000Z

2021-06-17T20:15:01.000Z

wagtail-repository/wagtail/admin/tests/test_privacy.py

TobiasSkovgaardJepsen/wagtail-on-heroku

17e4720f86023225e0704890688998a80bb87a17

[ "BSD-3-Clause" ]

1

2019-04-16T14:14:55.000Z

from django.contrib.auth.models import Group from django.test import TestCase from django.urls import reverse from wagtail.tests.testapp.models import SimplePage from wagtail.tests.utils import WagtailTestUtils from wagtail.core.models import Page, PageViewRestriction class TestSetPrivacyView(TestCase, WagtailTestUtils): def setUp(self): self.login() # Create some pages self.homepage = Page.objects.get(id=2) self.public_page = self.homepage.add_child(instance=SimplePage( title="Public page", content="hello", live=True, )) self.private_page = self.homepage.add_child(instance=SimplePage( title="Private page", content="hello", live=True, )) PageViewRestriction.objects.create( page=self.private_page, restriction_type='password', password='password123' ) self.private_child_page = self.private_page.add_child(instance=SimplePage( title="Private child page", content="hello", live=True, )) self.private_groups_page = self.homepage.add_child(instance=SimplePage( title="Private groups page", content="hello", live=True, )) restriction = PageViewRestriction.objects.create(page=self.private_groups_page, restriction_type='groups') self.group = Group.objects.create(name='Private page group') self.group2 = Group.objects.create(name='Private page group2') restriction.groups.add(self.group) restriction.groups.add(self.group2) self.private_groups_child_page = self.private_groups_page.add_child(instance=SimplePage( title="Private groups child page", content="hello", live=True, )) def test_get_public(self): """ This tests that a blank form is returned when a user opens the set_privacy view on a public page """ response = self.client.get(reverse('wagtailadmin_pages:set_privacy', args=(self.public_page.id, ))) # Check response self.assertEqual(response.status_code, 200) self.assertTemplateUsed(response, 'wagtailadmin/page_privacy/set_privacy.html') self.assertEqual(response.context['page'].specific, self.public_page) # Check form attributes self.assertEqual(response.context['form']['restriction_type'].value(), 'none') def test_get_private(self): """ This tests that the restriction type and password fields as set correctly when a user opens the set_privacy view on a public page """ response = self.client.get(reverse('wagtailadmin_pages:set_privacy', args=(self.private_page.id, ))) # Check response self.assertEqual(response.status_code, 200) self.assertTemplateUsed(response, 'wagtailadmin/page_privacy/set_privacy.html') self.assertEqual(response.context['page'].specific, self.private_page) # Check form attributes self.assertEqual(response.context['form']['restriction_type'].value(), 'password') self.assertEqual(response.context['form']['password'].value(), 'password123') self.assertEqual(response.context['form']['groups'].value(), []) def test_get_private_child(self): """ This tests that the set_privacy view tells the user that the password restriction has been applied to an ancestor """ response = self.client.get(reverse('wagtailadmin_pages:set_privacy', args=(self.private_child_page.id, ))) # Check response self.assertEqual(response.status_code, 200) self.assertTemplateUsed(response, 'wagtailadmin/page_privacy/ancestor_privacy.html') self.assertEqual(response.context['page_with_restriction'].specific, self.private_page) def test_set_password_restriction(self): """ This tests that setting a password restriction using the set_privacy view works """ post_data = { 'restriction_type': 'password', 'password': 'helloworld', 'groups': [], } response = self.client.post(reverse('wagtailadmin_pages:set_privacy', args=(self.public_page.id, )), post_data) # Check response self.assertEqual(response.status_code, 200) self.assertContains(response, "modal.respond('setPermission', false);") # Check that a page restriction has been created self.assertTrue(PageViewRestriction.objects.filter(page=self.public_page).exists()) restriction = PageViewRestriction.objects.get(page=self.public_page) # Check that the password is set correctly self.assertEqual(restriction.password, 'helloworld') # Check that the restriction_type is set correctly self.assertEqual(restriction.restriction_type, 'password') # Be sure there are no groups set self.assertEqual(restriction.groups.count(), 0) def test_set_password_restriction_password_unset(self): """ This tests that the password field on the form is validated correctly """ post_data = { 'restriction_type': 'password', 'password': '', 'groups': [], } response = self.client.post(reverse('wagtailadmin_pages:set_privacy', args=(self.public_page.id, )), post_data) # Check response self.assertEqual(response.status_code, 200) # Check that a form error was raised self.assertFormError(response, 'form', 'password', "This field is required.") def test_unset_password_restriction(self): """ This tests that removing a password restriction using the set_privacy view works """ post_data = { 'restriction_type': 'none', 'password': '', 'groups': [], } response = self.client.post( reverse('wagtailadmin_pages:set_privacy', args=(self.private_page.id, )), post_data) # Check response self.assertEqual(response.status_code, 200) self.assertContains(response, "modal.respond('setPermission', true);") # Check that the page restriction has been deleted self.assertFalse(PageViewRestriction.objects.filter(page=self.private_page).exists()) def test_get_private_groups(self): """ This tests that the restriction type and group fields as set correctly when a user opens the set_privacy view on a public page """ response = self.client.get(reverse('wagtailadmin_pages:set_privacy', args=(self.private_groups_page.id, ))) # Check response self.assertEqual(response.status_code, 200) self.assertTemplateUsed(response, 'wagtailadmin/page_privacy/set_privacy.html') self.assertEqual(response.context['page'].specific, self.private_groups_page) # Check form attributes self.assertEqual(response.context['form']['restriction_type'].value(), 'groups') self.assertEqual(response.context['form']['password'].value(), '') self.assertEqual(response.context['form']['groups'].value(), [self.group.id, self.group2.id]) def test_set_group_restriction(self): """ This tests that setting a group restriction using the set_privacy view works """ post_data = { 'restriction_type': 'groups', 'password': '', 'groups': [self.group.id, self.group2.id], } response = self.client.post(reverse('wagtailadmin_pages:set_privacy', args=(self.public_page.id, )), post_data) # Check response self.assertEqual(response.status_code, 200) self.assertContains(response, "modal.respond('setPermission', false);") # Check that a page restriction has been created self.assertTrue(PageViewRestriction.objects.filter(page=self.public_page).exists()) restriction = PageViewRestriction.objects.get(page=self.public_page) # restriction_type should be 'groups' self.assertEqual(restriction.restriction_type, 'groups') # Be sure there is no password set self.assertEqual(restriction.password, '') # Check that the groups are set correctly self.assertEqual( set(PageViewRestriction.objects.get(page=self.public_page).groups.all()), set([self.group, self.group2]) ) def test_set_group_restriction_password_unset(self): """ This tests that the group fields on the form are validated correctly """ post_data = { 'restriction_type': 'groups', 'password': '', 'groups': [], } response = self.client.post(reverse('wagtailadmin_pages:set_privacy', args=(self.public_page.id, )), post_data) # Check response self.assertEqual(response.status_code, 200) # Check that a form error was raised self.assertFormError(response, 'form', 'groups', "Please select at least one group.") def test_unset_group_restriction(self): """ This tests that removing a groups restriction using the set_privacy view works """ post_data = { 'restriction_type': 'none', 'password': '', 'groups': [], } response = self.client.post(reverse('wagtailadmin_pages:set_privacy', args=(self.private_page.id, )), post_data) # Check response self.assertEqual(response.status_code, 200) self.assertContains(response, "modal.respond('setPermission', true);") # Check that the page restriction has been deleted self.assertFalse(PageViewRestriction.objects.filter(page=self.private_page).exists()) class TestPrivacyIndicators(TestCase, WagtailTestUtils): def setUp(self): self.login() # Create some pages self.homepage = Page.objects.get(id=2) self.public_page = self.homepage.add_child(instance=SimplePage( title="Public page", content="hello", live=True, )) self.private_page = self.homepage.add_child(instance=SimplePage( title="Private page", content="hello", live=True, )) PageViewRestriction.objects.create( page=self.private_page, restriction_type='password', password='password123' ) self.private_child_page = self.private_page.add_child(instance=SimplePage( title="Private child page", content="hello", live=True, )) def test_explorer_public(self): """ This tests that the privacy indicator on the public pages explore view is set to "PUBLIC" """ response = self.client.get(reverse('wagtailadmin_explore', args=(self.public_page.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Check the privacy indicator is public self.assertTemplateUsed(response, 'wagtailadmin/pages/_privacy_switch.html') self.assertContains(response, '<div class="privacy-indicator public">') self.assertNotContains(response, '<div class="privacy-indicator private">') def test_explorer_private(self): """ This tests that the privacy indicator on the private pages explore view is set to "PRIVATE" """ response = self.client.get(reverse('wagtailadmin_explore', args=(self.private_page.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Check the privacy indicator is public self.assertTemplateUsed(response, 'wagtailadmin/pages/_privacy_switch.html') self.assertContains(response, '<div class="privacy-indicator private">') self.assertNotContains(response, '<div class="privacy-indicator public">') def test_explorer_private_child(self): """ This tests that the privacy indicator on the private child pages explore view is set to "PRIVATE" """ response = self.client.get(reverse('wagtailadmin_explore', args=(self.private_child_page.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Check the privacy indicator is public self.assertTemplateUsed(response, 'wagtailadmin/pages/_privacy_switch.html') self.assertContains(response, '<div class="privacy-indicator private">') self.assertNotContains(response, '<div class="privacy-indicator public">') def test_explorer_list_homepage(self): """ This tests that there is a padlock displayed next to the private page in the homepages explorer listing """ response = self.client.get(reverse('wagtailadmin_explore', args=(self.homepage.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Must have one privacy icon (next to the private page) self.assertContains(response, "<span class=\"indicator privacy-indicator icon icon-no-view\"", count=1) def test_explorer_list_private(self): """ This tests that there is a padlock displayed next to the private child page in the private pages explorer listing """ response = self.client.get(reverse('wagtailadmin_explore', args=(self.private_page.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Must have one privacy icon (next to the private child page) self.assertContains(response, "<span class=\"indicator privacy-indicator icon icon-no-view\"", count=1) def test_edit_public(self): """ This tests that the privacy indicator on the public pages edit view is set to "PUBLIC" """ response = self.client.get(reverse('wagtailadmin_pages:edit', args=(self.public_page.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Check the privacy indicator is public self.assertTemplateUsed(response, 'wagtailadmin/pages/_privacy_switch.html') self.assertContains(response, '<div class="privacy-indicator public">') self.assertNotContains(response, '<div class="privacy-indicator private">') def test_edit_private(self): """ This tests that the privacy indicator on the private pages edit view is set to "PRIVATE" """ response = self.client.get(reverse('wagtailadmin_pages:edit', args=(self.private_page.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Check the privacy indicator is public self.assertTemplateUsed(response, 'wagtailadmin/pages/_privacy_switch.html') self.assertContains(response, '<div class="privacy-indicator private">') self.assertNotContains(response, '<div class="privacy-indicator public">') def test_edit_private_child(self): """ This tests that the privacy indicator on the private child pages edit view is set to "PRIVATE" """ response = self.client.get(reverse('wagtailadmin_pages:edit', args=(self.private_child_page.id, ))) # Check the response self.assertEqual(response.status_code, 200) # Check the privacy indicator is public self.assertTemplateUsed(response, 'wagtailadmin/pages/_privacy_switch.html') self.assertContains(response, '<div class="privacy-indicator private">') self.assertNotContains(response, '<div class="privacy-indicator public">')

40.939791

134

0.659569

1,752

15,639

5.763128

0.0879

0.042785

0.066059

0.030306

0.877686

0.858077

0.820442

0.76389

0.743389

0.737348

0

0.00618

0.23435

15,639

381

135

41.047244

0.837064

0.18748

0

0.606796

0

0.184443

0.09856

0

0.334951

1

0.097087

false

0.101942

0.029126

0

0.135922

0

null

0

1

0

null

0

1

0

7

8a80396fab65436dec17e8fa17395034af49db54

5,311

py

Python

21_edgetpu-deeplab-slim/01_float32/05_float16_quantization.py

khanfarhan10/PINTO_model_zoo

4cad2e506d8c0fb604aa7b5f84115a840ab59ba1

[ "MIT" ]

1,529

2019-12-11T13:36:23.000Z

2022-03-31T18:38:27.000Z

21_edgetpu-deeplab-slim/01_float32/05_float16_quantization.py

khanfarhan10/PINTO_model_zoo

4cad2e506d8c0fb604aa7b5f84115a840ab59ba1

[ "MIT" ]

200

2020-01-06T09:24:42.000Z

2022-03-31T17:29:08.000Z

21_edgetpu-deeplab-slim/01_float32/05_float16_quantization.py

khanfarhan10/PINTO_model_zoo

4cad2e506d8c0fb604aa7b5f84115a840ab59ba1

[ "MIT" ]

288

2020-02-21T14:56:02.000Z

2022-03-30T03:00:35.000Z

### Tensorflow v1.15.2 import tensorflow as tf # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_257_os16.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,257,257,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_257_os16_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_257_os16_float16_quant.tflite") # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_257_os32.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,257,257,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_257_os32_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_257_os32_float16_quant.tflite") # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_321_os16.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,321,321,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_321_os16_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_321_os16_float16_quant.tflite") # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_321_os32.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,321,321,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_321_os32_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_321_os32_float16_quant.tflite") # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_513_os16.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,513,513,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_513_os16_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_513_os16_float16_quant.tflite") # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_513_os32.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,513,513,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_513_os32_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_513_os32_float16_quant.tflite") # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_769_os16.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,769,769,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_769_os16_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_769_os16_float16_quant.tflite") # Float16 Quantization - Input/Output=float32 graph_def_file="frozen_inference_graph_769_os32.pb" input_arrays=["ImageTensor"] output_arrays=['ArgMax'] input_tensor={"ImageTensor":[1,769,769,3]} converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays,input_tensor) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.target_spec.supported_types = [tf.float16] tflite_quant_model = converter.convert() with open('./edgetpu_deeplab_slim_769_os32_float16_quant.tflite', 'wb') as w: w.write(tflite_quant_model) print("Float16 Quantization complete! - edgetpu_deeplab_slim_769_os32_float16_quant.tflite")

49.635514

111

0.824515

736

5,311

5.580163

0.074728

0.07402

0.046749

0.058437

0.991478

0.986121

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Python

safeai/utils/utils.py

HanbumKo/SafeAI

ad7e5d66abcfe82b0de260b606853bddb68e68ee

[ "MIT" ]

13

2018-11-02T12:10:01.000Z

2020-05-18T17:38:25.000Z

safeai/utils/utils.py

HanbumKo/SafeAI

ad7e5d66abcfe82b0de260b606853bddb68e68ee

[ "MIT" ]

2

2018-11-15T06:16:06.000Z

2018-11-19T15:23:04.000Z

safeai/utils/utils.py

HanbumKo/SafeAI

ad7e5d66abcfe82b0de260b606853bddb68e68ee

[ "MIT" ]

4

2018-11-23T05:59:43.000Z

2020-08-28T04:21:27.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function # General utility functions here

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py

Python

cifar.py

jramapuram/datasets

270e189393fedecb4e4df68ea59600e3005b67ec

[ "MIT" ]

4

2020-07-28T08:47:31.000Z

2021-03-24T08:33:58.000Z

cifar.py

jramapuram/datasets

270e189393fedecb4e4df68ea59600e3005b67ec

[ "MIT" ]

2

2020-12-24T04:08:42.000Z

2021-05-12T13:00:01.000Z

cifar.py

jramapuram/datasets

270e189393fedecb4e4df68ea59600e3005b67ec

[ "MIT" ]

1

2018-07-24T08:52:01.000Z

import functools from torchvision import datasets from .abstract_dataset import AbstractLoader class CIFAR10Loader(AbstractLoader): """Simple CIFAR10 loader, there is no validation set.""" def __init__(self, path, batch_size, num_replicas=1, train_sampler=None, test_sampler=None, train_transform=None, train_target_transform=None, test_transform=None, test_target_transform=None, cuda=True, **kwargs): # Curry the train and test dataset generators. train_generator = functools.partial(datasets.CIFAR10, root=path, train=True, download=True) test_generator = functools.partial(datasets.CIFAR10, root=path, train=False, download=True) super(CIFAR10Loader, self).__init__(batch_size=batch_size, train_dataset_generator=train_generator, test_dataset_generator=test_generator, train_sampler=train_sampler, test_sampler=test_sampler, train_transform=train_transform, train_target_transform=train_target_transform, test_transform=test_transform, test_target_transform=test_target_transform, num_replicas=num_replicas, cuda=cuda, **kwargs) self.output_size = 10 # fixed self.loss_type = 'ce' # fixed # grab a test sample to get the size test_img, _ = self.train_loader.__iter__().__next__() self.input_shape = list(test_img.size()[1:]) print("derived image shape = ", self.input_shape) class CIFAR100Loader(AbstractLoader): """Simple CIFAR100 loader, there is no validation set.""" def __init__(self, path, batch_size, num_replicas=1, train_sampler=None, test_sampler=None, train_transform=None, train_target_transform=None, test_transform=None, test_target_transform=None, cuda=True, **kwargs): # Curry the train and test dataset generators. train_generator = functools.partial(datasets.CIFAR100, root=path, train=True, download=True) test_generator = functools.partial(datasets.CIFAR100, root=path, train=False, download=True) super(CIFAR100Loader, self).__init__(batch_size=batch_size, train_dataset_generator=train_generator, test_dataset_generator=test_generator, train_sampler=train_sampler, test_sampler=test_sampler, train_transform=train_transform, train_target_transform=train_target_transform, test_transform=test_transform, test_target_transform=test_target_transform, num_replicas=num_replicas, cuda=cuda, **kwargs) self.output_size = 100 # fixed self.loss_type = 'ce' # fixed # grab a test sample to get the size test_img, _ = self.train_loader.__iter__().__next__() self.input_shape = list(test_img.size()[1:]) print("derived image shape = ", self.input_shape)

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