import netpyne
# Legacy code so that new plots produce same output as originals
[docs]
def 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,
):
if 'timeSeries' in plots:
netpyne.plotting.plotLFPTimeSeries(
timeRange=timeRange,
electrodes=electrodes,
pop=pop,
separation=separation,
logy=logy,
normSignal=normSignal,
filtFreq=filtFreq,
filtOrder=filtOrder,
detrend=detrend,
colorList=colors,
figSize=figSize,
legend=False,
overlay=True,
dpi=dpi,
saveFig=saveFig,
showFig=showFig,
)
if 'PSD' in plots:
netpyne.plotting.plotLFPPSD(
timeRange=timeRange,
electrodes=electrodes,
pop=pop,
roundOffset=True,
separation=separation,
NFFT=NFFT,
noverlap=noverlap,
nperseg=nperseg,
minFreq=minFreq,
maxFreq=maxFreq,
stepFreq=stepFreq,
smooth=smooth,
logx=logx,
logy=logy,
normSignal=normSignal,
normPSD=normPSD,
filtFreq=filtFreq,
filtOrder=filtOrder,
detrend=detrend,
transformMethod=transformMethod,
colorList=colors,
figSize=figSize,
dpi=dpi,
saveFig=saveFig,
showFig=showFig,
)
if 'spectrogram' in plots:
netpyne.plotting.plotLFPSpectrogram(
timeRange=timeRange,
electrodes=electrodes,
pop=pop,
NFFT=NFFT,
noverlap=noverlap,
nperseg=nperseg,
minFreq=minFreq,
maxFreq=maxFreq,
stepFreq=stepFreq,
smooth=smooth,
logx=logx,
logy=logy,
normSignal=normSignal,
normPSD=normPSD,
filtFreq=filtFreq,
filtOrder=filtOrder,
detrend=detrend,
transformMethod=transformMethod,
figSize=figSize,
dpi=dpi,
saveFig=saveFig,
showFig=showFig,
)
if 'locations' in plots:
netpyne.plotting.plotLFPLocations(
electrodes=['all'],
includeAxon=includeAxon,
NFFT=NFFT,
noverlap=noverlap,
nperseg=nperseg,
minFreq=minFreq,
maxFreq=maxFreq,
stepFreq=stepFreq,
smooth=smooth,
logx=logx,
logy=logy,
normSignal=normSignal,
normPSD=normPSD,
filtFreq=filtFreq,
filtOrder=filtOrder,
detrend=detrend,
transformMethod=transformMethod,
figSize=figSize,
dpi=dpi,
saveFig=saveFig,
showFig=showFig,
)
[docs]
def 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
):
if measure == 'rate':
netpyne.plotting.plotSpikeFreq(
include=include,
timeRange=timeRange,
popColors=popColors,
legend=True,
returnPlotter=False,
binSize=binSize,
norm=norm,
smooth=smooth,
filtFreq=filtFreq,
filtOrder=filtOrder,
figSize=figSize,
dpi=dpi,
saveData=saveData,
saveFig=saveFig,
showFig=showFig,
)
else:
netpyne.plotting.plotSpikeHist(
include=include,
timeRange=timeRange,
binSize=binSize,
norm=norm,
smooth=smooth,
filtFreq=filtFreq,
filtOrder=filtOrder,
popColors=popColors,
figSize=figSize,
dpi=dpi,
saveData=saveData,
saveFig=saveFig,
showFig=showFig,
)
[docs]
def plotRaster(
include=['allCells'],
timeRange=None,
maxSpikes=1e8,
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
):
legend = False
if labels == 'legend':
legend = True
netpyne.plotting.plotRaster(
include=include,
timeRange=timeRange,
maxSpikes=maxSpikes,
orderBy=orderBy,
orderInverse=orderInverse,
legend=legend,
popRates=popRates,
linewidth=lw,
marker=marker,
markersize=markerSize,
popColors=popColors,
figSize=figSize,
fontSize=fontSize,
dpi=dpi,
saveData=saveData,
saveFig=saveFig,
showFig=showFig,
syncLines=syncLines
)