How to use the bioservices.BioModels function in bioservices

def biomodels():
    return BioModels(verbose=False)

def analyzeSpaceDistribution(analyzedModels):
    bio = bioservices.BioModels()
    number,spaceCovered = zip(*analyzedModels)
    
    hist,bin_edges = np.histogram(spaceCovered,bins=5)
    binIndexArray = np.digitize(spaceCovered,bin_edges)
    modelAnnotationBin = defaultdict(list)
    
    for element,binIndex in zip(number,binIndexArray):
        try:
            info = bio.getSimpleModelsByIds('BIOMD%010i' % element)
            parsedInfo = bioservices.Service('name').easyXML(info)
            modelName = stats.removeTags(str(parsedInfo['modelname'][0]))
            modelName = modelName.split(' - ')
            if len(modelName) > 1:
                modelName = modelName[1]
            else:
                modelName = modelName[0].split('_')

def __init__(self, debug=False):
        """ Creates and displays the search form. """
        self.debug = debug

        self.s = bioservices.BioModels()
        self.ch = bioservices.ChEBI()

        # Define widgets
        # 
        self.wSearchTerm = w.Text(description='Search biomodels by species:', value="CHEBI:17925")
        self.wSearchTerm.on_submit(self.searchChebi)
        self.wSearchButton = w.Button(description='Search')
        self.wSearchButton.on_click(self.searchChebi)
        self.wSearchChebi = w.HBox(children=[
            self.wSearchTerm, self.wSearchButton
        ])

        self.wSelectChebis = w.Select(description='Matching ChEBI:', width='600px', height='250px')
        # FIXME: update the deprecated functions
        self.wSelectChebis.on_trait_change(self.selectChebi)
        self.wSelectModels = w.Select(description='Matching BioModels:', width='200px')

def analyzeGroupingCDF():
    bio = bioservices.BioModels()

    with open('groupedProcessList.dump', 'rb') as f:
        groupedDict = pickle.load(f)
    elementList, groupedProcessList, redundantProcessList = zip(*groupedDict)
    hist, bin_edges = np.histogram(redundantProcessList, bins=5)
    binIndexArray = np.digitize(redundantProcessList, bin_edges)
    modelAnnotationBin = defaultdict(list)

    for element, binIndex in zip(elementList, binIndexArray):
        try:
            info = bio.getSimpleModelsByIds('BIOMD%010i' % element)
            parsedInfo = bioservices.Service('name').easyXML(info)
            modelName = stats.removeTags(str(parsedInfo['modelname'][0]))
            modelName = modelName.split(' - ')
            if len(modelName) > 1:
                modelName = modelName[1]

ev2.append([x['index'],x['nreactions'],x['nspecies'],x['compression']])
        except:
            continue
    number,rulesLength,speciesLength,evaluation2 =  zip(*ev2)
    trueRatio = []


    #with open('ratomization.dump','rb') as f:
    #    ratomizationDict = pickle.load(f) 
    
    
    for x,z,w in zip(rulesLength,number,evaluation2):
        if x>=0:
            trueRatio.append([z,1-w])
    
    bio = bioservices.BioModels()
    
    modelAnnotationArray = []
    for element,compression in trueRatio:
        try:
            info = bio.getSimpleModelsByIds('BIOMD%010i' % element)
            parsedInfo = bioservices.Service('name').easyXML(info)
            modelName = removeTags(str(parsedInfo['modelname'][0]))
            modelName = modelName.split(' - ')
            if len(modelName) > 1:
                modelName = modelName[1]
            else:
                modelName = modelName[0].split('_')
                if len(modelName) > 1:
                    modelName = ' '.join(modelName[1:])
                else:
                    modelName = modelName[0]

ev2.append([x['index'],x['nreactions'],x['nspecies'],x['compression']])
        except:
            continue
    number,rulesLength,speciesLength,evaluation2 =  zip(*ev2)
    trueRatio = []


    #with open('ratomization.dump','rb') as f:
    #    ratomizationDict = pickle.load(f) 
    
    
    for x,z,w in zip(rulesLength,number,evaluation2):
        if x>=0:
            trueRatio.append([z,1-w])
    
    bio = bioservices.BioModels()
    
    modelAnnotationArray = []
    for element,compression in trueRatio:
        try:
            info = bio.getSimpleModelsByIds('BIOMD%010i' % element)
            parsedInfo = bioservices.Service('name').easyXML(info)
            modelName = removeTags(str(parsedInfo['modelname'][0]))
            modelName = modelName.split(' - ')
            if len(modelName) > 1:
                modelName = modelName[1]
            else:
                modelName = modelName[0].split('_')
                if len(modelName) > 1:
                    modelName = ' '.join(modelName[1:])
                else:
                    modelName = modelName[0]

def analyzeGroupingCDF():
    bio = bioservices.BioModels()

    with open('groupedProcessList.dump','rb') as f:
        groupedDict = pickle.load(f)
    elementList,groupedProcessList,redundantProcessList = zip(*groupedDict)
    hist,bin_edges = np.histogram(redundantProcessList,bins=5)
    binIndexArray = np.digitize(redundantProcessList,bin_edges)
    modelAnnotationBin = defaultdict(list)
    
    for element,binIndex in zip(elementList,binIndexArray):
        try:
            info = bio.getSimpleModelsByIds('BIOMD%010i' % element)
            parsedInfo = bioservices.Service('name').easyXML(info)
            modelName = stats.removeTags(str(parsedInfo['modelname'][0]))
            modelName = modelName.split(' - ')
            if len(modelName) > 1:
                modelName = modelName[1]

def resolveAnnotation(annotation):
    if not hasattr(resolveAnnotation, 'db'):
        resolveAnnotation.db = {}
        resolveAnnotation.ch = bioservices.ChEBI(verbose=False)
        resolveAnnotation.bio = bioservices.BioModels(verbose=False)
        resolveAnnotation.uni = bioservices.UniProt(verbose=False)
        resolveAnnotation.k = bioservices.kegg.KeggParser(verbose=False)
        resolveAnnotation.s = bioservices.Service('name')
        resolveAnnotation.qg = bioservices.QuickGO(verbose=False)
        resolveAnnotation.db['http://identifiers.org/uniprot/P62988'] = 'http://identifiers.org/uniprot/P62988'
        resolveAnnotation.db['http://identifiers.org/uniprot/P06842'] = 'http://identifiers.org/uniprot/P06842'
        resolveAnnotation.db['http://identifiers.org/uniprot/P07006'] = 'http://identifiers.org/uniprot/P06842'
        
    if annotation in resolveAnnotation.db:
        return resolveAnnotation.db[annotation]
    
        
    tAnnotation = annotation.replace('%3A',':')
    tAnnotation = annotation.split('/')[-1]
    #tAnnotation = re.search(':([^:]+:[^:]+$)',tAnnotation).group(1)
    tmpArray = {}