Best Python code snippet using localstack_python
test_es.py
Source:test_es.py
...154 u'sea', u'seas', u'seamos', u'seáis', u'sean', 155 u'fuera', u'fueras', u'fuéramos', u'fuerais', u'fueran'156 ])157 print "pattern.es.inflect.lexeme()"158 def test_tenses(self):159 # Assert tense recognition.160 self.assertTrue((es.PRESENT, 3, es.SG) in es.tenses("es"))161 self.assertTrue("2sg" in es.tenses("eres"))162 # The CONDITIONAL is sometimes described as a mood, 163 # and sometimes as a tense of the indicative mood (e.g., in Spanish):164 t1 = (es.CONDITIONAL, 1, es.SG)165 t2 = (es.PRESENT, 1, es.SG, es.CONDITIONAL)166 self.assertTrue("1sg->" in es.tenses(u"serÃa"))167 self.assertTrue(t1 in es.tenses(u"serÃa"))168 self.assertTrue(t2 in es.tenses(u"serÃa"))169 self.assertTrue(t1 in es.tenses(es.conjugate("ser", mood=es.INDICATIVE, tense=es.CONDITIONAL)))170 self.assertTrue(t2 in es.tenses(es.conjugate("ser", mood=es.CONDITIONAL)))171 print "pattern.es.tenses()"172#---------------------------------------------------------------------------------------------------173class TestParser(unittest.TestCase):174 175 def setUp(self):176 pass177 178 def test_find_lemmata(self):179 # Assert lemmata for nouns, adjectives, verbs and determiners.180 v = es.parser.find_lemmata([181 ["Los", "DT"], ["gatos", "NNS"], [u"negros", "JJ"], ["se", "PRP"], [u"sentó", "VB"],182 ["en", "IN"], ["la", "DT"], ["alfombra", "NN"]])183 self.assertEqual(v, [184 ["Los", "DT", "el"], 185 ["gatos", "NNS", "gato"], 186 ["negros", "JJ", "negro"], 187 ["se", "PRP", "se"], 188 [u"sentó", "VB", "sentar"],189 ["en", "IN", "en"], 190 ["la", "DT", "el"], 191 ["alfombra", "NN", "alfombra"]])192 print "pattern.es.parser.find_lemmata()"193 def test_parse(self):194 # Assert parsed output with Penn Treebank II tags (slash-formatted).195 # "el gato negro" is a noun phrase, "en la alfombra" is a prepositional noun phrase.196 v = es.parser.parse(u"El gato negro se sentó en la alfombra.")197 self.assertEqual(v, # XXX - shouldn't "se" be part of the verb phrase?198 u"El/DT/B-NP/O gato/NN/I-NP/O negro/JJ/I-NP/O " + \199 u"se/PRP/B-NP/O sentó/VB/B-VP/O " + \200 u"en/IN/B-PP/B-PNP la/DT/B-NP/I-PNP alfombra/NN/I-NP/I-PNP ././O/O"201 )202 # Assert the accuracy of the Spanish tagger.203 i, n = 0, 0204 for sentence in open(os.path.join(PATH, "corpora", "tagged-es-wikicorpus.txt")).readlines():205 sentence = sentence.decode("utf-8").strip()206 s1 = [w.split("/") for w in sentence.split(" ")]207 s2 = [[w for w, pos in s1]]208 s2 = es.parse(s2, tokenize=False, tagset=es.PAROLE)209 s2 = [w.split("/") for w in s2.split(" ")]210 for j in range(len(s1)):211 if s1[j][1] == s2[j][1]:212 i += 1213 n += 1214 #print float(i) / n215 self.assertTrue(float(i) / n > 0.92)216 print "pattern.es.parser.parse()"217 def test_tag(self):218 # Assert [("el", "DT"), ("gato", "NN"), ("negro", "JJ")]....
easyscan.py_backup
Source:easyscan.py_backup
1#!/usr/bin/env python2#########################################################################3"""4 ____ ____ ____ _ _ ____ ____ ____ _ _ _ _ ____ ___5 |___ |__| [__ \_/ [__ | |__| |\ | |__| |___ |__]6 |___ | | ___] | ___] |___ | | | \| | | |___ |7 An Easy-to-use tool providing a comfortable way connecting programs 8 to Scan the parameter space for high energy physics(HEP) models.9 10 Author: Junjie Cao, Liangliang Shang, Jin Min Yang and Yang Zhang11 Version: Beta_1.0.112 Date: 2016.07.2813 """14##########################################################################15## External modules.16import os,sys,math17sys.path.append(os.path.join(os.path.split(os.path.split(os.path.realpath(__file__))[0])[0], "Tools"))18## Internal modules.19import subfun as sf20import manfun as mf21import statfun as stat22import readin23# define basic class object24ES = mf.EasyScanInput()25Programs ={}26CS = mf.constraint()27Ploter = mf.plot()28ProgID = readin.ReadIn(sys.argv[1],ES,Programs,CS,Ploter)29# logarithm of likelihood function30def LogLikelihood(cube, ndim, nparams):31 # pass the input value from cube to InPar32 for i,name in enumerate(ES.InPar) :33 ES.InPar [name]=cube[i]34 ES.AllPar[name]=cube[i]35 # Run each programs36 for ii in ProgID:37 if Programs[ii].getRunFlag(ES.AllPar):38 Programs[ii].WriteInputFile(ES.AllPar)39 Programs[ii].RunProgram()40 Phy = Programs[ii].ReadOutputFile(ES.AllPar,ES.getFileName())41 else:42 Phy = Programs[ii].SetOutput(ES.AllPar)43 # if the point is unphysical, return log(0)44 if not Phy : return sf.log_zero45 # pass the output value to AllPar46 for i,name in enumerate(ES.OutPar) :47 48 #yuanfang49 50 # yy=raw_input('yuanang cube begin....')51 # print 'cube=',cube52 # print 'nparams',nparams53 # print 'enumerate(ES.OutPar)=',ES.OutPar54 # print 'i=',i55 # print 'ndim=',ndim56 # print 'name=',name57 # print 'i+ndim=',i+ndim58 # print 'ES.AllPar[name]=',ES.AllPar[name]59 60# yuanfang modified in 11.661 if ES.getScanMethod() == 'MULTINEST':62 try:63 float(ES.AllPar[name])64 except:65 # yy=raw_input('yuanang cube string exception begin....')66 # print 'i=',i67 # print 'name=',name68 # print 'ES.AllPar[name]=',ES.AllPar[name]69 cube[i+ndim]=0.0 70 # yy=raw_input('yuanang cube string exception end....')71 continue # skip this loop72 cube[i+ndim] = ES.AllPar[name]73 # print(type(ES.AllPar))74 # print(type(ES.AllPar[name]))75 # import ctypes76 # import numpy77 # array_length=378 # buffer=numpy.core.multiarray.int_asbuffer(ctypes.addressof(cube.contents),8*array_length)79 # yuanfang_cube=numpy.frombuffer(buffer,float)80 # print "yuanfang_cube",yuanfang_cube81 # a=raw_input('yuanfang cube end,waiting for the input1...')82 # a=raw_input('yuanfang cube end,waiting for the input2...')83 84 85 return - CS.getChisq(ES.AllPar)/2.086def Prior(cube, ndim, nparams):87 #print "easyscan.py 01llllllllllllllllllllllllllll"88 for i,name in enumerate(ES.InPar):89 if ES.InputPar[name][1].lower() == 'flat':90 min = float(ES.InputPar[name][2])91 max = float(ES.InputPar[name][3])92 cube[i] = cube[i] * (max - min) + min93 #print cube[i]94 elif ES.InputPar[name][1].lower() == 'log':95 min = math.log10(float(ES.InputPar[name][2]))96 max = math.log10(float(ES.InputPar[name][3]))97 cube[i] = 10.0**(cube[i]*(max - min) + min )98 else:99 sf.ErrorStop( 'Not ready. Only "flat" and "log" prior can be used.' )100""" Scan the parameter space """101if ES.getScanMethod() == 'RANDOM':102 from scanmanner import randomrun103 ResultFile = 'RandomData.txt'104 randomrun(105 LogLikelihood = LogLikelihood,106 Prior = Prior,107 n_dims = len(ES.InPar),108 n_params = len(ES.AllPar),109 n_live_points = ES.getPointNum(),110 n_print = ES.getPrintNum(),111 outputfiles_basename = ES.getFileName(),112 outputfiles_filename = ResultFile )113elif ES.getScanMethod() == 'MCMC':114 from scanmanner import mcmcrun115 ResultFile = 'MCMCData.txt'116 mcmcrun(117 LogLikelihood = LogLikelihood,118 Prior = Prior,119 n_dims = len(ES.InPar),120 n_params = len(ES.AllPar),121 n_live_points = ES.getPointNum(),122 inpar = ES.InPar,123 outpar = ES.OutPar,124 StepSize = ES.getStepSize(),125 AccepRate = ES.getAccepRate(),126 FalgTune = ES.getFalgTuneR(),127 InitVal = ES.getInitialValue(),128 n_print = ES.getPrintNum(),129 outputfiles_basename = ES.getFileName(),130 outputfiles_filename = ResultFile)131elif ES.getScanMethod() == 'MULTINEST':132 import pymultinest133 ResultFile = 'MultiNestData/ev.dat'134 pymultinest.run(135 LogLikelihood = LogLikelihood, 136 Prior = Prior,137 n_dims = len(ES.InPar),138 n_params = len(ES.AllPar),139 seed = ES.getRandomSeed(),140 outputfiles_basename = ES.MNOutputFile,141 n_live_points = ES.getPointNum(),142 n_clustering_params = 2,143 wrapped_params = None,144 multimodal = True,145 const_efficiency_mode = False,146 evidence_tolerance = 1.0,147 sampling_efficiency = 2.0,148 n_iter_before_update = 1,149 null_log_evidence = -1e+90,150 max_modes = 5,151 verbose = True,152 resume = False, #!!!!!!!!!153 context = 0,154 importance_nested_sampling = True)155elif ES.getScanMethod() == 'GRID':156 from scanmanner import gridrun157 ResultFile = 'GridData.txt'158 gridrun(159 LogLikelihood = LogLikelihood,160 Prior = Prior,161 n_dims = len(ES.InPar),162 n_params = len(ES.AllPar),163 inpar = ES.InPar,164 bin_num = ES.GridBin,165 n_print = ES.getPrintNum(),166 outputfiles_basename = ES.getFileName(),167 outputfiles_filename = ResultFile )168elif ES.getScanMethod() == 'READ':169 from scanmanner import readrun170 ResultFile = 'READData.txt'171 readrun(172 LogLikelihood = LogLikelihood,173 Prior = Prior,174 n_dims = len(ES.InPar),175 n_params = len(ES.AllPar),176 inpar = ES.InPar,177 bin_num = ES.GridBin,178 n_print = ES.getPrintNum(),179 outputfiles_basename = ES.getFileName(),180 outputfiles_filename = ResultFile )181""" After programs run """182if ES.getScanMethod() != 'PLOT':183 for ii in Programs: Programs[ii].Recover()184 sf.WriteResultInf(ES.InPar,ES.OutPar,ES.getFileName(),ResultFile,ES.getScanMethod())185""" Plot """186Ploter.setPlotPar(ES.getFileName())...
es.py
Source:es.py
...48 else:49 raise Exception("insert_es_data func just support list or dict to insert")50 except Exception as e:51 print "[Error]%s" % e52 def get_field_from_es(self, es_index, field_list, es = "", start = 0, depth = 10):53 '''54 this func return dict like:55 {u'hits': {u'hits': [{u'_source': {u'CVE': u'CVE-0000-0000'}}, \56 {u'_source': {u'CVE': u'CVE-0000-0001'}}, {u'_source': \57 {u'CVE': u'CVE-0000-0002'}}]}} 58 '''59 es = self.get_es_conn() if es == "" else es60 try:61 body = {"from": start, "size": depth}62 filter_path = []63 for field in field_list:64 filter_path.append("hits.hits._source." + field)65 print filter_path66 data = es.search(index = es_index, filter_path = filter_path, body = body)67 return data68 except Exception as e:69 print "[Error]%s" % e70 def search_from_es(self, es_index, field, value, multi = False, fuzz = True, es = ''):71 es = self.get_es_conn() if es == "" else es72 try:73 body = {}74 if fuzz:75 if multi:76 if type(field) is not list:77 raise Exception("Use fuzz search and multi field,need set list type' field")78 else:79 field_list = [f for f in field] 80 body = {81 "query":{82 "multi_match":{83 "query" : value, 84 "fields": field_list...
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