How to use computeNull method in avocado

Best Python code snippet using avocado_python

spark.py

Source:spark.py

...66        if self.ruleschanged:67            #68            #  XXX - duplicated from parse()69            #70            self.computeNull()71            self.newrules = {}72            self.new2old = {}73            self.makeNewRules()74            self.ruleschanged = 075            self.edges, self.cores = {}, {}76            self.states = { 0: self.makeState0() }77            self.makeState(0, self._BOF)78        #79        #  XXX - should find a better way to do this..80        #81        changes = 182        while changes:83            changes = 084            for k, v in self.edges.items():85                if v is None:86                    state, sym = k87                    if self.states.has_key(state):88                        self.goto(state, sym)89                        changes = 190        rv = self.__dict__.copy()91        for s in self.states.values():92            del s.items93        del rv['rule2func']94        del rv['nullable']95        del rv['cores']96        return rv97    def __setstate__(self, D):98        self.rules = {}99        self.rule2func = {}100        self.rule2name = {}101        self.collectRules()102        start = D['rules'][self._START][0][1][1]	# Blech.103        self.augment(start)104        D['rule2func'] = self.rule2func105        D['makeSet'] = self.makeSet_fast106        self.__dict__ = D107    #108    #  A hook for GenericASTBuilder and GenericASTMatcher.  Mess109    #  thee not with this; nor shall thee toucheth the _preprocess110    #  argument to addRule.111    #112    def preprocess(self, rule, func):	return rule, func113    def addRule(self, doc, func, _preprocess=1):114        fn = func115        rules = doc.split()116        index = []117        for i in xrange(len(rules)):118            if rules[i] == '::=':119                index.append(i-1)120        index.append(len(rules))121        for i in xrange(len(index)-1):122            lhs = rules[index[i]]123            rhs = rules[index[i]+2:index[i+1]]124            rule = (lhs, tuple(rhs))125            if _preprocess:126                rule, fn = self.preprocess(rule, func)127            if self.rules.has_key(lhs):128                self.rules[lhs].append(rule)129            else:130                self.rules[lhs] = [ rule ]131            self.rule2func[rule] = fn132            self.rule2name[rule] = func.__name__[2:]133        self.ruleschanged = 1134    def collectRules(self):135        for name in _namelist(self):136            if name[:2] == 'p_':137                func = getattr(self, name)138                doc = func.__doc__139                self.addRule(doc, func)140    def augment(self, start):141        rule = '%s ::= %s %s' % (self._START, self._BOF, start)142        self.addRule(rule, lambda args: args[1], 0)143    def computeNull(self):144        self.nullable = {}145        tbd = []146        for rulelist in self.rules.values():147            lhs = rulelist[0][0]148            self.nullable[lhs] = 0149            for rule in rulelist:150                rhs = rule[1]151                if len(rhs) == 0:152                    self.nullable[lhs] = 1153                    continue154                #155                #  We only need to consider rules which156                #  consist entirely of nonterminal symbols.157                #  This should be a savings on typical158                #  grammars.159                #160                for sym in rhs:161                    if not self.rules.has_key(sym):162                        break163                else:164                    tbd.append(rule)165        changes = 1166        while changes:167            changes = 0168            for lhs, rhs in tbd:169                if self.nullable[lhs]:170                    continue171                for sym in rhs:172                    if not self.nullable[sym]:173                        break174                else:175                    self.nullable[lhs] = 1176                    changes = 1177    def makeState0(self):178        s0 = _State(0, [])179        for rule in self.newrules[self._START]:180            s0.items.append((rule, 0))181        return s0182    def finalState(self, tokens):183        #184        #  Yuck.185        #186        if len(self.newrules[self._START]) == 2 and len(tokens) == 0:187            return 1188        start = self.rules[self._START][0][1][1]189        return self.goto(1, start)190    def makeNewRules(self):191        worklist = []192        for rulelist in self.rules.values():193            for rule in rulelist:194                worklist.append((rule, 0, 1, rule))195        for rule, i, candidate, oldrule in worklist:196            lhs, rhs = rule197            n = len(rhs)198            while i < n:199                sym = rhs[i]200                if not self.rules.has_key(sym) or \201                    not self.nullable[sym]:202                        candidate = 0203                        i = i + 1204                        continue205                newrhs = list(rhs)206                newrhs[i] = self._NULLABLE+sym207                newrule = (lhs, tuple(newrhs))208                worklist.append((newrule, i+1,209                                 candidate, oldrule))210                candidate = 0211                i = i + 1212            else:213                if candidate:214                    lhs = self._NULLABLE+lhs215                    rule = (lhs, rhs)216                if self.newrules.has_key(lhs):217                    self.newrules[lhs].append(rule)218                else:219                    self.newrules[lhs] = [ rule ]220                self.new2old[rule] = oldrule221    def typestring(self, token):222        return None223    def error(self, token):224        print "Syntax error at or near `%s' token" % token225        raise SystemExit226    def parse(self, tokens):227        sets = [ [(1,0), (2,0)] ]228        self.links = {}229        if self.ruleschanged:230            self.computeNull()231            self.newrules = {}232            self.new2old = {}233            self.makeNewRules()234            self.ruleschanged = 0235            self.edges, self.cores = {}, {}236            self.states = { 0: self.makeState0() }237            self.makeState(0, self._BOF)238        for i in xrange(len(tokens)):239            sets.append([])240            if sets[i] == []:241                break				242            self.makeSet(tokens[i], sets, i)243        else:244            sets.append([])...

SigAvg.py

Source:SigAvg.py

1"""File which does the actual analysis for the signature visualization2   Written/modified by Mike Ambrose, mikeambrose@berkeley.edu3Feel free to email with any questions!4"""5import os6from optparse import OptionParser7import math8import iSigDBUtilities as util9#TODO: uncomment this when on server10#os.environ["MPLCONFIGDIR"] = "/UCSC/Pathways-Auxiliary/UCLApathways-Scratch-Space"11import matplotlib12matplotlib.use('Agg')13import nullmodel14from matplotlib.backends.backend_pdf import PdfPages15from collections import OrderedDict16import bisect17import iSigDBConstants1819def getSigGenes(sigFile,selectedSigs,n):20    """Returns dictionary of signature : [top n genes]21    sigFile is the file with the shortened signatures22    n is the number of genes"""23    sigGenes = {}24    with open(sigFile) as sigToGenes:25        for line in sigToGenes:26            splitLine = line.strip("\n").split("\t")27            sig = splitLine[0]28            if sig in selectedSigs:29                sigGenes[sig] = []30                for gene in splitLine[1:n+1]:31                    sigGenes[sig].append(gene)32    return sigGenes3334def ranked(sams):35    """for each sample, replaces the gene's value with its rank"""36    rankedSams = OrderedDict()37    for sam in sams:38        samvals = [sams[sam][gene] for gene in sams[sam]]39        ranks = util.getRanks(tuple(samvals))40        rankedSams[sam] = {gene:ranks[sams[sam][gene]] for gene in sams[sam]}41    return rankedSams4243def logall(sams):44    """for each sample, replace the gene's value with the log of its value"""45    logSams = OrderedDict()46    for sam in sams:47        if any(sams[sam][gene] < 0 for gene in sams[sam]):48            util.displayErrorMessage("Log of negative value")49        logSams[sam] = {gene:math.log10(sams[sam][gene]+1) for gene in sams[sam]}50    return logSams5152def delta(sams):53    """for each sample, replaces the gene's value with the difference between its value and the54    mean value across all samples"""55    genes = sams[sams.keys()[0]].keys()56    for gene in genes:57        av = util.average([sams[sam][gene] for sam in sams])58        for sam in sams:59            sams[sam][gene] = sams[sam][gene] - av60    return sams6162def writeValues(sams,sigGenes,compOutput,version,abbrevsDict,av=True,nullVals=None):63    """Writes the values after computation by version to compOutput64    inputFile - user-provided input file65    sigGenes - dictionary of signature : list of genes in signature66    compOutput - where to write output67    version - how to process input68    abbrevsDict - dictionary of abbreviation : full name for each signature in sigGenes"""69    samSigVal = OrderedDict()70    for sam in sams:71        samSigVal[sam] = {}72        for sig in sigGenes:73            geneVals = []74            for gene in sigGenes[sig]:75                if gene not in sams[sam]:76                    #the gene does not exist in our input, so it is reported as a N/A77                    continue78                geneVals.append(sams[sam][gene])79            if len(geneVals) == 0:80                continue81            if av:82                samSigVal[sam][sig] = util.average(geneVals)83            else:84                samSigVal[sam][sig] = sum(geneVals)85    if 'null' in version:86        #add tooltips with the p-value87        tooltips = {}88        for sam in samSigVal:89            tooltips[sam] = {}90            nullDist = nullVals[sam]91            for sig in samSigVal[sam]:92                currentLoc = bisect.bisect_left(nullDist,samSigVal[sam][sig])93                numGreaterThan = len(nullDist)-currentLoc94                signame = sig if sig not in abbrevsDict else abbrevsDict[sig]95                if 'delta' in version:96                    tooltips[sam][signame] = "left-tail <b>{0}</b>; right-tail <b>{1}</b>".format(currentLoc/float(len(nullDist)),numGreaterThan/float(len(nullDist)))97                else:98                    tooltips[sam][signame] = "<b>{0}</b>".format(numGreaterThan/float(len(nullDist)))99                if 'sig' in version:100                    #replace the value itself101                    samSigVal[sam][sig] = numGreaterThan/float(len(nullDist))102    if 'null' not in version or 'sig' in version:103        tooltips = None104    util.writeRegularOutput(samSigVal,compOutput,abbrevsDict)105    util.writeDetailedOutput(sigGenes,sams,compOutput+'.full.txt',abbrevsDict)106    return tooltips107108def writeNullModelHists(filename,sigNames,allValues,n,num_iter=100000,num_buckets=100):109    """Writes each of the histograms to a pdf110    sigNames[i] should correspond with allValues[i]"""111    nullVals = {}112    pdf = PdfPages(filename) #version-dependent, but this seems to work for all versions113    for i in range(len(allValues)):114        sigVals = nullmodel.getStatistics(allValues[i],n,pdf,sigNames[i],num_iter,num_buckets)115        nullVals[sigNames[i]] = sigVals116    pdf.close()117    return nullVals118119def writeInputFileHist(filename,sigNames,allValues,num_buckets=100):120    """Writes the distribution of each input signature121    sigNames is the names of the signatures, allValues is the set of values in the signature122    sigNames[i] corresponds to allValues[i]"""123    pdf = PdfPages(filename)124    for i in range(len(allValues)):125        matplotlib.pyplot.hist(allValues[i],num_buckets)126        matplotlib.pyplot.title(sigNames[i])127        pdf.savefig()128        matplotlib.pyplot.close()129    pdf.close()130131def writeNull(sams,nullFilename,n,numIter,genes=None):132    """Writes the null distribution of inputFile to nullFilename133    n is the number of genes we're averaging over134    numIter is the number of iterations135    genes is the set of genes which we're considering136    returns a dictionary of sample:values simulated137    """138    names = [sam for sam in sorted(sams.keys())]139    if not genes:140        allVals = [[sams[sam][gene] for gene in sams[sam]] for sam in names]141    else:142        allVals = []143        for sam in sams:144            genevals = []145            for gene in genes:146                if gene in sams[sam]:147                    genevals.append(sams[sam][gene])148            allVals.append(genevals)149    return writeNullModelHists(nullFilename,names,allVals,n,numIter)150151def writeInDist(sams,inDistFilename):152    """Writes the distribution of the input samples to inDistFilename"""153    names = [sam for sam in sorted(sams.keys())]154    allVals = [[sams[sam][gene] for gene in sams[sam]] for sam in names]155    writeInputFileHist(inDistFilename,names,allVals)156157def generateHeatmap(inputFile,sigfile,abbrevs,n,version,zTransform,jobID,rowMetric,colMetric,invert,\158                    computeNull,isClient,nullIterations,mn,mx,av,color,fileName):159    """Main function which generates the heatmap160    inputFile - user-provided input161    sigfile - file with most important genes for each signature162        format: sigName\tgene1\tgene2...\nsigName2\t...163    abbrevs - file with abbreviations\tfull names164    n - number of genes to take from each signature165    version - what computation to do. looks for certain strings166        "avg" - use average values, or "delta" - difference from average167        "log" - log-transform values, or nothing168        "rank" - rank rather than raw values, or nothing169    zTransform - "matrix", "column", "row" if going to be transformed by those metrics, otherwise "none"170    jobID - ID of the current job, used for identifying and writing to file171    rowMetric, colMetric - "euclidean", "pearson", "none", used to cluster columns/rows172    invert - invert the axes of the heatmap173    computeNull - compute the null distribution (only works for rank average, value, log)174    isClient - always false when run on server (debug option)175    nullIterations - number of iterations to run the simulation to find null distribution176    mn - min value in the heatmap color range (or None to automatically scale)177    mx - max value in the heatmap color range (or None)178    av - whether to average the values (if True) or report the sum (if False)179    color - which color axis to use180        'bwr' goes blue->white->red181        'wr' goes white->red182        'rw' goes red->white183        None sets it automatically depending on what computation options were selected184    """185    #checks for errors and corrects whatever errors it can186    util.reformatFile(inputFile)187    util.checkForErrors(inputFile)188189    #set up constants190    C = iSigDBConstants.Constants(jobID)191192    #get sample values193    sams = util.readMatrix(inputFile,ordered=True)194195    if 'rank' in version:196        sams = ranked(sams)197    if 'log' in version:198        sams = logall(sams)199    if 'delta' in version:200        sams = delta(sams)201202    #computing sample distribution203    writeInDist(sams,C.INPUT_DIST_PDF)204205    #get signatures206    abbrevsDict = util.loadAbbrevs(abbrevs)207    sigGenes = getSigGenes(sigfile,abbrevsDict.keys(),n) 208209    #computing null distribution210    if computeNull:211        allSigGenes = set()212        for sig in sigGenes:213            allSigGenes = allSigGenes.union(set(sigGenes[sig]))214        nullVals = writeNull(sams,C.NULL_PDF,n,nullIterations,allSigGenes)215    else:216        nullVals = None217    tooltips = writeValues(sams,sigGenes,C.COMP_OUTPUT,version,abbrevsDict,av,nullVals)218    optionsUsed = util.getOptionsUsed(version,n,zTransform,rowMetric,colMetric,fileName)219    util.createHeatmap(C,version,zTransform,rowMetric,colMetric,invert,isClient,computeNull,True,True,mn,mx,tooltips,color,optionsUsed)220        221#----------------------------------------------------------------------------222# main function call223#----------------------------------------------------------------------------224if __name__ == "__main__":225    parser = OptionParser()226    parser.add_option("--input", dest="input", help="user-provided input")227    parser.add_option("--sigfile",dest="sigfile",help="path to precomputed signatures")228    parser.add_option("--abbrev", dest="abbrev", help="path to abbrevs file")229    parser.add_option("--n",dest='n', help="number of genes to use")230    parser.add_option("--version", dest="version", help="metric version with avg, log, rank, delta ")231    parser.add_option("--zTransform", dest="zTransform", help="how to transform matrix")232    parser.add_option("--row_metric", dest="row_metric", help="metric for clustering rows (samples)")233    parser.add_option("--col_metric", dest="col_metric", help="metric for clustering columns (signatures)")234    parser.add_option("--invert",default=False,dest="invert",action="store_true",help="heatmap columns/rows swtiched")235    parser.add_option("--null",default=False,action="store_true", dest="null", help="compute null model")236    parser.add_option("--nullIter",dest="nullIterations",help="how many iterations to use in null model")237    parser.add_option("--range",dest="range",help="range of output")238    parser.add_option("--color",dest="color",help="color axis")239    (options, args) = parser.parse_args()240    mn,mx = options.range.split(',') if options.range != "None" else (None,None)241    color = options.color if options.color != 'None' else None
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