cgid.plotting_helper_functions module

Helper functions for making figures

cgid.plotting_helper_functions.add_spectrum_colorbar(data=None, COLORMAP=<matplotlib.colors.ListedColormap object>, ax=None, vmin=None, vmax=None)

cgid.plotting_helper_functions.add_wavelet_colorbar(data=None, COLORMAP=<matplotlib.colors.ListedColormap object>, ax=None, vmin=None, vmax=None)

cgid.plotting_helper_functions.array_imshow(data, vmin=None, vmax=None, cmap=<matplotlib.colors.ListedColormap object>, origin=u'lower', drawlines=1, interpolation=u'bicubic', extent=(0, 4, 0, 4), ctitle=u'', W=4, H=4)

cgid.plotting_helper_functions.coherence(session, area, unit, window=100, FMAX=250)

cgid.plotting_helper_functions.compare_ppc_approaches(session, area, unit, start, stop, window=100, FMAX=250)

Try with compare_ppc_approaches(‘RUS120523’,’PMv’,42,-1000,0,200)

cgid.plotting_helper_functions.do_unit_ISI_plot(session, area, unit, INFOXPOS=70, LABELSIZE=8, NBINS=20, FMAX=250)

Add statistical summary printout to the ISI example figures

cgid.plotting_helper_functions.getRaster(session, area, unit, trial)

cgid.plotting_helper_functions.getSTLFP(session, area, unit, start, stop, window=100)

cgid.plotting_helper_functions.getSpec(session, area, unit, trial, epoch, lowf, highf)

cgid.plotting_helper_functions.getTrial(session, area, unit, start, stop, trial)

cgid.plotting_helper_functions.isimodefreq(session, area, unit, start, stop, FS=1000)

cgid.plotting_helper_functions.phase_delay_plot(mean_analytic_signal, cm=<matplotlib.colors.ListedColormap object>, UPSAMPLE=50, smooth=2.3, NLINE=6)

Accepts an analytic signal map, upsamples it, and plots in the current axis the phases. For now, expects a 10x10 array 4x4mm is size.

cgid.plotting_helper_functions.plotAllTrials(session, area, unit, start, stop, FS=1000.0, s=4, clip_on=False)

cgid.plotting_helper_functions.plotISIhist(session, area, unit, start, stop)

cgid.plotting_helper_functions.plotISIhistHz(session, area, unit, start, stop, FS=1000, style=u'bar', color=u'k', nbins=30, label=None, fmin=0, FMAX=100, linestyle=u'-', lw=2, w=0.8)

cgid.plotting_helper_functions.plotLFP(lfp)

cgid.plotting_helper_functions.plotLFPSpikes(lfp, start, stop, spikes, zoom=1000, vrange=100, FS=1000.0, SPIKECOLOR=(1, 0.5, 0), lw=2)

cgid.plotting_helper_functions.plotPPC(unit)

cgid.plotting_helper_functions.plotSTA(session, area, unit, start, stop, window=100, texttop=False, color=u'k', label=None, lw=1.5, linestyle=u'-')

cgid.plotting_helper_functions.plotWaveforms(session, area, unit)

cgid.plotting_helper_functions.ppc(session, area, unit, start, stop, window=100, FMAX=250, color=u'k', label=None, nTapers=None, lw=1.5, linestyle=u'-')

cgid.plotting_helper_functions.specshow(freqs, specdata, start, stop, FS=1000, aspect=u'auto', cmap=<matplotlib.colors.ListedColormap object>)

cgid.plotting_helper_functions.time_upsample(x, factor=4)

Uses fourier transform to upsample x by some factor Will detrend, then mirror signal, then FFT, then add padding zeros to FFT, then iFFT, then crop, etc, etc factor should be an integer (default is 4) data is converted to float64

cgid.plotting_helper_functions.unit_ISI_plot(session, area, unit, epoch=((6, -1000, 0), (8, -1000, 0)), INFOXPOS=70, LABELSIZE=8, NBINS=20, TMAX=300, INFOYSTART=0, BURST=10)

cgid.plotting_helper_functions.waveletshow(freqs, specdata, start, stop, FS=1000, aspect=u'auto', cmap=<matplotlib.colors.ListedColormap object>)

basically specshow – diffent units for scale bar uV^2