SYMBOL INDEX (207 symbols across 32 files)

FILE: classEval.py
  function getScores (line 5) | def getScores( true_classes, pred_classes, average):

FILE: corpusLoader.py
  function extractSentenceWords (line 10) | def extractSentenceWords(doc, remove_url=True, remove_punc="utf-8", min_...
  function load_20news (line 51) | def load_20news(setName):
  function load_reuters (line 98) | def load_reuters(setName):

FILE: csv2topic.py
  function usage (line 45) | def usage():
  function getOptions (line 60) | def getOptions():
  function main (line 108) | def main():

FILE: file2topic.py
  function usage (line 44) | def usage():
  function getOptions (line 59) | def getOptions():
  function main (line 106) | def main():

FILE: psdvec/analogy.py
  function pred_ana (line 5) | def pred_ana( model, a, a2, b, maxcands = 10 ):

FILE: psdvec/benchspeed.py
  class Timer (line 4) | class Timer(object):
    method __init__ (line 5) | def __init__(self, name=None):
    method getElapseTime (line 11) | def getElapseTime(self, isStr=True):
    method printElapseTime (line 32) | def printElapseTime(self):
  function timeToStr (line 35) | def timeToStr(timeNum, fmt="%H:%M:%S"):
  function block_factorize (line 39) | def block_factorize( core_size, noncore_size, N0, tikhonovCoeff ):

FILE: psdvec/corpus2liblinear.py
  function usage (line 11) | def usage():
  function parseConfigFile (line 25) | def parseConfigFile(configFilename):
  function getFileFeatures (line 34) | def getFileFeatures(filename, V, word2id, sentword2id, remove_stop=False):
  function processDir (line 86) | def processDir( outFilename, docDir, label, appendToOutput, V, word2ID, ...
  function main (line 123) | def main():

FILE: psdvec/evaluate-toefl.py
  function loadToeflTestset (line 12) | def loadToeflTestset(toeflTestsetFilename):
  function usage (line 31) | def usage():

FILE: psdvec/evaluate.py
  function usage (line 45) | def usage():

FILE: psdvec/factorize.py
  function uniwe_factorize (line 16) | def uniwe_factorize(G, u, N0, MAXITERS=0, tikhonovCoeff=0, testenv=None):
  function nowe_factorize (line 86) | def nowe_factorize(G, N, tikhonovCoeff=0):
  function we_factorize_GD (line 144) | def we_factorize_GD(G, Weight, N0, MAXITERS=5000, tikhonovCoeff=0, teste...
  function we_factorize_EM (line 239) | def we_factorize_EM(G, Weight, N0, MAXITERS=5, tikhonovCoeff=0, testenv=...
  function we_factorize_FW (line 303) | def we_factorize_FW(G, Weight, N0, MAXITERS=6, tikhonovCoeff=0, testenv=...
  function normalizeWeight (line 490) | def normalizeWeight( RawCounts, do_weight_cutoff, cutQuantile=0.0002, ze...
  function block_factorize (line 529) | def block_factorize( G, F, V1, N0, tikhonovCoeff, do_weight_cutoff ):
  function factorize (line 591) | def factorize( alg, algName, G, Weight, N0, MAX_ITERS, tikhonovCoeff, vo...
  function usage (line 606) | def usage():
  function main (line 629) | def main():

FILE: psdvec/patch to gensim.py
  function get_texts (line 5) | def get_texts(self):
  function tokenize (line 15) | def tokenize(content):
  function get_texts (line 19) | def get_texts(self):
  function tokenize (line 31) | def tokenize(text, lowercase=False, deacc=False, errors="strict", to_low...

FILE: psdvec/perlxs.h
  function XS_pack_charPtrPtr (line 58) | void XS_pack_charPtrPtr( SV * st, char ** s )
  function XS_release_charPtrPtr (line 76) | void XS_release_charPtrPtr(char** s)

FILE: psdvec/topwordsInList.py
  function usage (line 10) | def usage():
  function parseConfigFile (line 21) | def parseConfigFile(configFilename):
  function getListWordCount (line 30) | def getListWordCount( docPath, word2freq ):
  function processDir (line 45) | def processDir( docDir, word2freq ):
  function main (line 65) | def main():

FILE: psdvec/utils.py
  function str2dict (line 26) | def str2dict(s):
  function initConsoleLogger (line 53) | def initConsoleLogger(loggerName):
  function initFileLogger (line 59) | def initFileLogger(loggerName, isAppending=False):
  function warning (line 78) | def warning(*objs):
  class Timer (line 81) | class Timer(object):
    method __init__ (line 82) | def __init__(self, name=None):
    method getElapseTime (line 88) | def getElapseTime(self, isStr=True):
    method printElapseTime (line 109) | def printElapseTime(self):
  function timeToStr (line 112) | def timeToStr(timeNum, fmt="%H:%M:%S"):
  function norm1 (line 117) | def norm1(M, Weight=None):
  function normF (line 140) | def normF(M, Weight=None):
  function normalize (line 167) | def normalize(data, axis=1):
  function normalizeF (line 182) | def normalizeF(data, axis=1):
  function cosine (line 203) | def cosine(x, y):
  function matSizes (line 209) | def matSizes( norm, Ms, Weight=None ):
  function sym (line 216) | def sym(M):
  function skew (line 219) | def skew(M):
  function getQuantileCut (line 227) | def getQuantileCut(A, fraction):
  function power_iter (line 247) | def power_iter(M):
  function lowrank_fact (line 277) | def lowrank_fact(VV, N0):
  function save_embeddings (line 289) | def save_embeddings( filename, vocab, V, matrixName ):
  function save_matrix_as_text (line 307) | def save_matrix_as_text( filename, rowTypeName, T, *extraCols, **kwargs ):
  function load_matrix_from_text (line 333) | def load_matrix_from_text( filename, rowTypeName, colSep=" " ):
  function load_embeddings (line 401) | def load_embeddings( filename, maxWordCount=-1, extraWords={}, record_sk...
  function load_embeddings_bin (line 498) | def load_embeddings_bin( filename, maxWordCount=-1, extraWords={}, recor...
  function load_embeddings_hyper (line 587) | def load_embeddings_hyper(modelPath, vecType):
  function load_residuals (line 609) | def load_residuals( filename, word2id={}, maxRowCount=-1, maxColCount=-1 ):
  function loadBigramFile (line 679) | def loadBigramFile( bigram_filename, topWordNum, extraWords, kappa=0.01 ):
  function loadBigramFileInBlock (line 894) | def loadBigramFileInBlock( bigram_filename, core_size, noncore_size=-1, ...
  function loadUnigramFile (line 1368) | def loadUnigramFile(filename):
  function loadExtraWordFile (line 1384) | def loadExtraWordFile(filename):
  function loadSimTestset (line 1396) | def loadSimTestset(path, extraArgs=None):
  function loadAnaTestset (line 1405) | def loadAnaTestset(path, extraArgs=None):
  function loadTestsets (line 1430) | def loadTestsets(loader, testsetDir, testsetNames, extraArgs=None):
  function predict_ana (line 1458) | def predict_ana( model, a, a2, b, realb2 ):
  function evaluate_sim (line 1522) | def evaluate_sim(model, testsets, testsetNames, getAbsentWords=False, vo...
  function evaluate_ana (line 1572) | def evaluate_ana(model, testsets, testsetNames, getAbsentWords=False, vo...
  function bench (line 1648) | def bench(func, N, topEigenNum=0):
  function isMemEnoughGramian (line 1665) | def isMemEnoughGramian(D, extraVarsRatio=0):
  function isMemEnoughEigen (line 1692) | def isMemEnoughEigen(D, extraVarsRatio=5):
  function extractSentenceWords (line 1711) | def extractSentenceWords(doc, remove_url=True, remove_punc="utf-8", min_...
  function randomsample (line 1752) | def randomsample( X, n ):
  function relu (line 1759) | def relu(v, bias):
  function maxpool (line 1764) | def maxpool(vs):
  function avgpool (line 1771) | def avgpool(vs):
  class VecModel (line 1777) | class VecModel:
    method __init__ (line 1778) | def __init__(self, V, vocab, word2id, vecNormalize=True, precompute_gr...
    method __contains__ (line 1799) | def __contains__(self, w):
    method __getitem__ (line 1802) | def __getitem__(self, w):
    method orig (line 1811) | def orig(self, w):
    method precomputeGramian (line 1817) | def precomputeGramian(self):
    method similarity (line 1822) | def similarity(self, x, y):
    method sim_row (line 1842) | def sim_row(self, x):
    method most_similar (line 1859) | def most_similar(self, vx, top_num=1):

FILE: psdvec/vecnorms.py
  function usage (line 12) | def usage():
  function expectation (line 15) | def expectation(value_probs):
  function var_div (line 24) | def var_div(value_probs):

FILE: snippet2topic.py
  function usage (line 44) | def usage():
  function getOptions (line 59) | def getOptions():
  function main (line 107) | def main():

FILE: topic-competitors/LDA/classEval.py
  function getScores (line 6) | def getScores( true_classes, pred_classes, average):

FILE: topic-competitors/LDA/corpusLoader.py
  function extractSentenceWords (line 17) | def extractSentenceWords(doc, remove_url=True, remove_punc="utf-8", min_...
  function load_20news (line 62) | def load_20news(setName):
  function load_reuters (line 109) | def load_reuters(setName):

FILE: topic-competitors/LDA/ldaExp.py
  function usage (line 14) | def usage():

FILE: topic-competitors/kmeans.py
  function kmeans (line 18) | def kmeans( X, centres, delta=.001, maxiter=10, metric="euclidean", p=2,...
  function randomsample (line 72) | def randomsample( X, n ):

FILE: topic-competitors/labelEval.py
  function getScores (line 4) | def getScores( true_classes, pred_classes, average):

FILE: topic-competitors/liu-doc2vec.py
  function genDocEmbedding (line 4) | def genDocEmbedding( setName, words_file, topics_file, label_file, V, wo...

FILE: topic-competitors/slda/corpus.h
  function class (line 29) | class document
  function class (line 67) | class corpus

FILE: topic-competitors/slda/main.cpp
  function help (line 28) | void help( void ) {
  function main (line 33) | int main(int argc, char* argv[])

FILE: topic-competitors/slda/opt.cpp
  function softmax_f (line 30) | double softmax_f(const gsl_vector * x, void * opt_param)
  function softmax_df (line 85) | void softmax_df(const gsl_vector * x, void * opt_param, gsl_vector * df)
  function softmax_fdf (line 159) | void softmax_fdf(const gsl_vector * x, void * opt_param, double * f, gsl...

FILE: topic-competitors/slda/opt.h
  type opt_parameter (line 31) | struct opt_parameter

FILE: topic-competitors/slda/slda.cpp
  function suffstats (line 214) | suffstats * slda::new_suffstats(int num_docs)

FILE: topic-competitors/slda/slda.h
  type z_stat (line 27) | typedef struct {
  type suffstats (line 32) | typedef struct {
  function class (line 41) | class slda

FILE: topic-competitors/slda/utils.cpp
  function log_sum (line 8) | double log_sum(double log_a, double log_b)
  function trigamma (line 29) | double trigamma(double x)
  function digamma (line 51) | double digamma(double x)
  function make_directory (line 114) | void make_directory(char* name)
  function argmax (line 125) | int argmax(double* x, int n)
  function map_idx (line 148) | int map_idx(int row, int col, int dim)

FILE: topicExp.py
  function usage (line 49) | def usage():

FILE: topicvecDir.py
  class topicvecDir (line 23) | class topicvecDir:
    method __init__ (line 24) | def __init__(self, **kwargs):
    method setK (line 167) | def setK(self, K):
    method precompute (line 177) | def precompute(self):
    method calcEm (line 192) | def calcEm(self, docs_Pi):
    method calcLoglikelihood (line 199) | def calcLoglikelihood(self):
    method updateTheta (line 220) | def updateTheta(self):
    method updatePi (line 224) | def updatePi(self, docs_theta):
    method calcTopicResiduals (line 256) | def calcTopicResiduals(self, T):
    method updateTopicEmbeddings (line 269) | def updateTopicEmbeddings(self):
    method calcSum_pi_v (line 326) | def calcSum_pi_v(self):
    method genOutputter (line 349) | def genOutputter(self, screenVerboseThres=1):
    method genProgressor (line 356) | def genProgressor(self):
    method printTopWordsInTopics (line 366) | def printTopWordsInTopics( self, docs_theta, outputToScreen=False ):
    method docSentences2wids (line 486) | def docSentences2wids( self, docs_wordsInSentences ):
    method setDocs (line 537) | def setDocs( self, docs_wordsInSentences, docs_name ):
    method kmeans (line 579) | def kmeans( self, maxiter=10 ):
    method inferTopicProps (line 647) | def inferTopicProps( self, T, MAX_ITERS=5 ):
    method inference (line 683) | def inference(self):

FILE: utils.py
  function str2dict (line 26) | def str2dict(s):
  function initConsoleLogger (line 53) | def initConsoleLogger(loggerName):
  function initFileLogger (line 59) | def initFileLogger(loggerName, isAppending=False):
  function warning (line 78) | def warning(*objs):
  class Timer (line 81) | class Timer(object):
    method __init__ (line 82) | def __init__(self, name=None):
    method getElapseTime (line 88) | def getElapseTime(self, isStr=True):
    method printElapseTime (line 109) | def printElapseTime(self):
  function timeToStr (line 112) | def timeToStr(timeNum, fmt="%H:%M:%S"):
  function norm1 (line 117) | def norm1(M, Weight=None):
  function normF (line 140) | def normF(M, Weight=None):
  function normalize (line 167) | def normalize(data, axis=1):
  function normalizeF (line 182) | def normalizeF(data, axis=1):
  function cosine (line 203) | def cosine(x, y):
  function matSizes (line 209) | def matSizes( norm, Ms, Weight=None ):
  function sym (line 216) | def sym(M):
  function skew (line 219) | def skew(M):
  function getQuantileCut (line 227) | def getQuantileCut(A, fraction):
  function power_iter (line 247) | def power_iter(M):
  function lowrank_fact (line 277) | def lowrank_fact(VV, N0):
  function save_embeddings (line 289) | def save_embeddings( filename, vocab, V, matrixName ):
  function save_matrix_as_text (line 307) | def save_matrix_as_text( filename, rowTypeName, T, *extraCols, **kwargs ):
  function load_matrix_from_text (line 333) | def load_matrix_from_text( filename, rowTypeName, colSep=" " ):
  function load_embeddings (line 401) | def load_embeddings( filename, maxWordCount=-1, extraWords={}, record_sk...
  function load_embeddings_bin (line 498) | def load_embeddings_bin( filename, maxWordCount=-1, extraWords={}, recor...
  function load_embeddings_hyper (line 587) | def load_embeddings_hyper(modelPath, vecType):
  function load_residuals (line 609) | def load_residuals( filename, word2id={}, maxRowCount=-1, maxColCount=-1 ):
  function loadBigramFile (line 679) | def loadBigramFile( bigram_filename, topWordNum, extraWords, kappa=0.01 ):
  function loadBigramFileInBlock (line 894) | def loadBigramFileInBlock( bigram_filename, core_size, noncore_size=-1, ...
  function loadUnigramFile (line 1368) | def loadUnigramFile(filename):
  function loadExtraWordFile (line 1384) | def loadExtraWordFile(filename):
  function loadSimTestset (line 1396) | def loadSimTestset(path, extraArgs=None):
  function loadAnaTestset (line 1405) | def loadAnaTestset(path, extraArgs=None):
  function loadTestsets (line 1430) | def loadTestsets(loader, testsetDir, testsetNames, extraArgs=None):
  function predict_ana (line 1458) | def predict_ana( model, a, a2, b, realb2 ):
  function evaluate_sim (line 1522) | def evaluate_sim(model, testsets, testsetNames, getAbsentWords=False, vo...
  function evaluate_ana (line 1572) | def evaluate_ana(model, testsets, testsetNames, getAbsentWords=False, vo...
  function bench (line 1648) | def bench(func, N, topEigenNum=0):
  function isMemEnoughGramian (line 1665) | def isMemEnoughGramian(D, extraVarsRatio=0):
  function isMemEnoughEigen (line 1692) | def isMemEnoughEigen(D, extraVarsRatio=5):
  function extractSentenceWords (line 1711) | def extractSentenceWords(doc, remove_url=True, remove_punc="utf-8", min_...
  function randomsample (line 1752) | def randomsample( X, n ):
  function relu (line 1759) | def relu(v, bias):
  function maxpool (line 1764) | def maxpool(vs):
  function avgpool (line 1771) | def avgpool(vs):
  class VecModel (line 1777) | class VecModel:
    method __init__ (line 1778) | def __init__(self, V, vocab, word2id, vecNormalize=True, precompute_gr...
    method __contains__ (line 1799) | def __contains__(self, w):
    method __getitem__ (line 1802) | def __getitem__(self, w):
    method orig (line 1811) | def orig(self, w):
    method precomputeGramian (line 1817) | def precomputeGramian(self):
    method similarity (line 1822) | def similarity(self, x, y):
    method sim_row (line 1842) | def sim_row(self, x):
    method most_similar (line 1859) | def most_similar(self, vx, top_num=1):