netpyne.analysis.mapping

Functions:

plotLFP([timeRange, electrodes, pop, plots, ...])
plotSpikeHist([include, timeRange, binSize, ...])
plotRaster([include, timeRange, maxSpikes, ...])

netpyne.analysis.mapping.plotLFP(timeRange=None, electrodes=['avg', 'all'], pop=None, plots=['timeSeries', 'PSD', 'spectrogram', 'locations'], inputLFP=None, NFFT=256, noverlap=128, nperseg=256, minFreq=1, maxFreq=100, stepFreq=1, smooth=0, separation=1.0, includeAxon=True, logx=False, logy=False, normSignal=False, normPSD=False, normSpec=False, filtFreq=False, filtOrder=3, detrend=False, transformMethod='morlet', maxPlots=8, overlay=False, colors=None, figSize=(8, 8), fontSize=14, lineWidth=1.5, dpi=200, saveData=None, saveFig=None, showFig=True)

netpyne.analysis.mapping.plotSpikeHist(include=['eachPop', 'allCells'], timeRange=None, binSize=5, graphType='line', measure='rate', norm=False, smooth=None, filtFreq=None, filtOrder=3, axis=True, popColors=None, figSize=(10, 8), dpi=100, saveData=None, saveFig=None, showFig=True, **kwargs)

netpyne.analysis.mapping.plotRaster(include=['allCells'], timeRange=None, maxSpikes=100000000.0, orderBy='gid', orderInverse=False, labels='legend', popRates=False, spikeHist=None, spikeHistBin=5, syncLines=False, lw=2, marker='|', markerSize=5, popColors=None, figSize=(10, 8), fontSize=12, dpi=100, saveData=None, saveFig=None, showFig=True, **kwargs)