How to use the netpyne.analysis.utils.getCellsInclude function in netpyne

def plotEPSPAmp(include=None, trace=None, start=0, interval=50, number=2, amp='absolute', polarity='exc', saveFig=False, showFig=True):

    from .. import sim

    print('Plotting EPSP amplitudes...')

    if include is None: include = [] # If not defined, initialize as empty list

    cells, cellGids, _ = getCellsInclude(include)
    gidPops = {cell['gid']: cell['tags']['pop'] for cell in cells}

    if not trace: 
        print('Error: Missing trace to to plot EPSP amplitudes')
        return
    step = sim.cfg.recordStep

    peaksAbs = np.zeros((number, len(cellGids)))
    peaksRel = np.zeros((number, len(cellGids)))
    for icell, gid in enumerate(cellGids):
        vsoma = sim.allSimData[trace]['cell_'+str(gid)]
        for ipeak in range(number):
            if polarity == 'exc':
                peakAbs = max(vsoma[int(start/step+(ipeak*interval/step)):int(start/step+(ipeak*interval/step)+(interval-1)/step)]) 
            elif polarity == 'inh':
                peakAbs = min(vsoma[int(start/step+(ipeak*interval/step)):int(start/step+(ipeak*interval/step)+(interval-1)/step)])

preLabelIndex = connsFormat.index('preLabel') if 'preLabel' in connsFormat else -1
        
        if len(missing) > 0:
            print("  Error: cfg.compactConnFormat missing:")
            print(missing)
            return None, None, None 
    else:  
        # using long conn format (dict)
        preGidIndex = 'preGid' 
        synMechIndex = 'synMech'
        weightIndex = 'weight'
        delayIndex = 'delay'
        preLabelIndex = 'preLabel'

    # Calculate pre and post cells involved
    cellsPre, cellGidsPre, netStimPopsPre = getCellsInclude(includePre)
    if includePre == includePost:
        cellsPost, cellGidsPost, netStimPopsPost = cellsPre, cellGidsPre, netStimPopsPre 
    else:
        cellsPost, cellGidsPost, netStimPopsPost = getCellsInclude(includePost) 

    if isinstance(synMech, basestring): synMech = [synMech]  # make sure synMech is a list
    
    # Calculate matrix if grouped by cell
    if groupBy == 'cell': 
        if feature in ['weight', 'delay', 'numConns']: 
            connMatrix = np.zeros((len(cellGidsPre), len(cellGidsPost)))
            countMatrix = np.zeros((len(cellGidsPre), len(cellGidsPost)))
        else: 
            print('Conn matrix with groupBy="cell" only supports features= "weight", "delay" or "numConns"')
            return fig
        cellIndsPre = {cell['gid']: ind for ind,cell in enumerate(cellsPre)}

print missing
            return None, None, None 
    else:  
        # using long conn format (dict)
        preGidIndex = 'preGid' 
        synMechIndex = 'synMech'
        weightIndex = 'weight'
        delayIndex = 'delay'
        preLabelIndex = 'preLabel'

    # Calculate pre and post cells involved
    cellsPre, cellGidsPre, netStimPopsPre = getCellsInclude(includePre)
    if includePre == includePost:
        cellsPost, cellGidsPost, netStimPopsPost = cellsPre, cellGidsPre, netStimPopsPre 
    else:
        cellsPost, cellGidsPost, netStimPopsPost = getCellsInclude(includePost) 

    if isinstance(synMech, basestring): synMech = [synMech]  # make sure synMech is a list
    
    # Calculate matrix if grouped by cell
    if groupBy == 'cell': 
        if feature in ['weight', 'delay', 'numConns']: 
            connMatrix = np.zeros((len(cellGidsPre), len(cellGidsPost)))
            countMatrix = np.zeros((len(cellGidsPre), len(cellGidsPost)))
        else: 
            print 'Conn matrix with groupBy="cell" only supports features= "weight", "delay" or "numConns"'
            return fig
        cellIndsPre = {cell['gid']: ind for ind,cell in enumerate(cellsPre)}
        cellIndsPost = {cell['gid']: ind for ind,cell in enumerate(cellsPost)}

        # Order by
        if len(cellsPre) > 0 and len(cellsPost) > 0:

preLabelIndex = connsFormat.index('preLabel') if 'preLabel' in connsFormat else -1
        
        if len(missing) > 0:
            print "  Error: cfg.compactConnFormat missing:"
            print missing
            return None, None, None 
    else:  
        # using long conn format (dict)
        preGidIndex = 'preGid' 
        synMechIndex = 'synMech'
        weightIndex = 'weight'
        delayIndex = 'delay'
        preLabelIndex = 'preLabel'

    # Calculate pre and post cells involved
    cellsPre, cellGidsPre, netStimPopsPre = getCellsInclude(includePre)
    if includePre == includePost:
        cellsPost, cellGidsPost, netStimPopsPost = cellsPre, cellGidsPre, netStimPopsPre 
    else:
        cellsPost, cellGidsPost, netStimPopsPost = getCellsInclude(includePost) 

    if isinstance(synMech, basestring): synMech = [synMech]  # make sure synMech is a list
    
    # Calculate matrix if grouped by cell
    if groupBy == 'cell': 
        if feature in ['weight', 'delay', 'numConns']: 
            connMatrix = np.zeros((len(cellGidsPre), len(cellGidsPost)))
            countMatrix = np.zeros((len(cellGidsPre), len(cellGidsPost)))
        else: 
            print 'Conn matrix with groupBy="cell" only supports features= "weight", "delay" or "numConns"'
            return fig
        cellIndsPre = {cell['gid']: ind for ind,cell in enumerate(cellsPre)}

else:
            yaxisLabel = 'Spike count'
            
    figs=[]
    if overlay:
        figs.append(figure(title="Spike Historgram", tools=TOOLS, x_axis_label="Time (ms)", y_axis_label=yaxisLabel, toolbar_location='above'))
        fig = figs[0]
        legendItems = []  
      
    for iplot, subset in enumerate(include):
        if not overlay:
            figs.append(figure(title=str(subset), tools=TOOLS, x_axis_label="Time (ms)", y_axis_label=yaxisLabel))
            fig = figs[iplot]
                    
        if isinstance(subset, list):
            cells, cellGids, netStimLabels = getCellsInclude(subset)
        else:
            cells, cellGids, netStimLabels = getCellsInclude([subset])        
        numNetStims = 0

        # Select cells to include
        if len(cellGids) > 0:
            try:
                spkinds,spkts = list(zip(*[(spkgid,spkt) for spkgid,spkt in zip(sim.allSimData['spkid'],sim.allSimData['spkt']) if spkgid in cellGids]))
            except:
                spkinds,spkts = [],[]
        else:
            spkinds,spkts = [],[]

        spkts, spkinds = list(spkts), list(spkinds)
        numNetStims = 0
        if 'stims' in sim.allSimData:

legendItems = []
    
    
    figs=[]
    if overlay:
        figs.append(figure(title="PSD Rate Plot", tools=TOOLS, x_axis_label="Frequncy (Hz)", y_axis_label="Power Spectral Density (db/Hz)", toolbar_location='above'))
        fig = figs[0]
        legendItems = []  

    # Plot separate line for each entry in include
    for iplot, subset in enumerate(include):
        if not overlay:
            figs.append(figure(title=str(subset), tools=TOOLS, x_axis_label="Frequency (HZ)", y_axis_label="Power Spectral Density (db/Hz)"))
            fig = figs[iplot]
            
        cells, cellGids, netStimLabels = getCellsInclude([subset])
        numNetStims = 0

        # Select cells to include
        if len(cellGids) > 0:
            try:
                spkinds,spkts = list(zip(*[(spkgid,spkt) for spkgid,spkt in zip(sim.allSimData['spkid'],sim.allSimData['spkt']) if spkgid in cellGids]))
            except:
                spkinds,spkts = [],[]
        else:
            spkinds,spkts = [],[]


        # Add NetStim spikes
        spkts, spkinds = list(spkts), list(spkinds)
        numNetStims = 0
        if 'stims' in sim.allSimData:

if 'nte' not in dir(h): 
        try: 
            print(' Warning: support/nte.mod not compiled; attempting to compile from %s via "nrnivmodl support"'%(root))
            os.system('cd ' + root + '; nrnivmodl support')
            from neuron import load_mechanisms
            load_mechanisms(root)
            print(' Compilation of support folder mod files successful')
        except:
            print(' Error compiling support folder mod files')
            return

    h.load_file(root+'/support/nte.hoc') # nTE code (also requires support/net.mod)
    
    if not spks1:  # if doesnt contain a list of spk times, obtain from cells specified
        cells, cellGids, netStimPops = getCellsInclude(cells1)
        numNetStims = 0

        # Select cells to include
        if len(cellGids) > 0:
            try:
                spkts = [spkt for spkgid,spkt in zip(sim.allSimData['spkid'],sim.allSimData['spkt']) if spkgid in cellGids]
            except:
                spkts = []
        else: 
            spkts = []

        # Add NetStim spikes
        spkts = list(spkts)
        numNetStims = 0
        for netStimPop in netStimPops:
            if 'stims' in sim.allSimData:

if not set(prePreGids).isdisjoint(preGidsAll):
                    numDis += 1

    else:
        if sim.cfg.compactConnFormat: 
            if 'preGid' in sim.cfg.compactConnFormat:
                preGidIndex = sim.cfg.compactConnFormat.index('preGid')  # using compact conn format (list)
            else:
                print '   Error: cfg.compactConnFormat does not include "preGid"'
                return -1
        else:  
            preGidIndex = 'preGid' # using long conn format (dict)

        _, cellsPreGids, _ =  getCellsInclude(includePre)
        _, cellsPrePreGids, _ = getCellsInclude(includePrePre)
        cellsPost, _, _ = getCellsInclude(includePost)

        for postCell in cellsPost:
            print postCell['gid']
            preGidsAll = [conn[preGidIndex] for conn in postCell['conns'] if isinstance(conn[preGidIndex], Number) and conn[preGidIndex] in cellsPreGids+cellsPrePreGids]
            preGids = [gid for gid in preGidsAll if gid in cellsPreGids]
            for preGid in preGids:
                preCell = sim.net.allCells[preGid]
                prePreGids = [conn[preGidIndex] for conn in preCell['conns'] if conn[preGidIndex] in cellsPrePreGids]
                totCon += 1
                if not set(prePreGids).isdisjoint(preGidsAll):
                    numDis += 1

    print '    Total disynaptic connections: %d / %d (%.2f%%)' % (numDis, totCon, float(numDis)/float(totCon)*100 if totCon>0 else 0.0)
    try:
        sim.allSimData['disynConns'] = numDis
    except: