def plot(self, fig=None, ax=None):
try:
self.min
except AttributeError:
self.getLimits()
if not fig:
fig = pl.figure(figsize=(12, 7))
if not ax:
ax = fig.add_subplot(111)
ylabels = []
last_id = self.id_list()[-1] + 1
for id, csc in enumerate(self):
s = csc.signal.copy()
s -= s.mean()
s /= self.max * .8
pl.plot(csc.times,
s + id,
'-',
linewidth=1,
color=custom_plot.pretty_colors_set2[
id % custom_plot.pretty_colors_set2.__len__()])
ylabels.append(str(csc.tags['channel']).split('.')[0])
custom_plot.huebschMachen(ax)
ax.set_xlabel('Time (' + self.timeUnit + ')')
yticks = numpy.arange(last_id)
ax.set_yticks(yticks)
ax.set_yticklabels(ylabels, rotation=0)
ax.set_xlim(csc.times[0], csc.times[-1])
ax.set_ylim(-1, id + 1)
return fig, ax
def plotPhase(self, fig, ax, pooled=False):
self.placeCell.phasePlot(fig=fig,labelx=False, labely=False, ax=ax, lfp=self.csc, labelsize=8)
ax.axvline(x=traj.places[self.index_start,0],linewidth=1, color='g')
ax.axvline(x=traj.places[self.index_stop-2,0],linewidth=1, color='k')
ax.axvline(x=traj.places[self.index_gain,0],linewidth=1, color='r')
fig.canvas.draw()
custom_plot.huebschMachen(ax)
def plotData(csc):
csc.fft()
fig = pl.figure(figsize=(12, 7))
pos1 = [.1, .7, .8, .22]
ax1 = fig.add_axes(pos1)
pos2 = pos1
pos2[1] = .39
ax2 = fig.add_axes(pos2)
pos3 = pos1
pos3[1] = .1
ax3 = fig.add_axes(pos3)
ax1.set_title(csc.tags['file'])
csc.plot(fig, ax1)
custom_plot.huebschMachen(ax1)
csc.fft_plot(fig, ax2)
custom_plot.huebschMachen(ax2)
ax2.set_xlabel('')
ax2.set_xticklabels([])
csc.fft_plot(fig, ax3)
ax3.set_xlim(0, 15.)
custom_plot.huebschMachen(ax3)
def fft_plot(self, freq_min=0., freq_max=60., fig=None, ax=None):
try:
self.min
except AttributeError:
self.getLimits()
if not fig:
fig = pl.figure(figsize=(12, 7))
if not ax:
ax = fig.add_subplot(111)
ylabels = []
last_id = self.id_list()[-1] + 1
for id, csc in enumerate(self):
if not hasattr(csc, 'spPower'):
csc.fft()
index_freq_min = numpy.searchsorted(csc.freq, freq_min)
index_freq_max = numpy.searchsorted(csc.freq, freq_max)
s = csc.spPower
s -= s[index_freq_min:index_freq_max].mean()
s /= s[index_freq_min:index_freq_max].max() * 1.1
pl.plot(csc.freq,
s + id,
'-',
linewidth=1,
color=custom_plot.pretty_colors_set2[
id % custom_plot.pretty_colors_set2.__len__()])
ylabels.append(str(csc.tags['channel']).split('.')[0])
custom_plot.huebschMachen(ax)
ax.set_xlabel('Frequency (Hz)')
yticks = numpy.arange(last_id)
ax.set_yticks(yticks)
ax.set_yticklabels(ylabels, rotation=0)
ax.set_xlim(freq_min, freq_max)
ax.set_ylim(0, id + 1)
return fig, ax
alpha=0.6,
zorder=.1)
# plot csc trace
ax.plot(csc.time_axis(), csc.signal, 'k', linewidth=1)
ax.plot(csc.time_axis(),
csc.signal_filtered,
color=[0, .75, 1],
linewidth=2)
ax.set_xlim(time_closeUp[0], time_closeUp[1])
custom_plot.turnOffAxes(ax, spines=['left'])
ax.set_ylim(numpy.percentile(csc.signal, .5),
numpy.percentile(csc.signal, 99.5))
ax.set_xticklabels([])
custom_plot.huebschMachen(ax)
# custom_plot.turnOffAxes(ax, spines=['top'])
ax2 = ax.twinx()
for tl in ax2.get_yticklabels():
tl.set_color('k')
ax2.plot(t * 1000, s / (s.mean() + 4 * s.std()), color='k', alpha=0.5)
ax2.plot((traj.times - traj.times[0]) * 1000,
traj.getXComponents() / traj.getXComponents().max(),
color='g',
alpha=0.5)
ax2.set_xlim(time_closeUp[0], time_closeUp[1])
custom_plot.turnOffAxes(ax2, spines=['right'])
# ax2.plot(csc.time_axis(), csc.hilbertPhase,'g', alpha=.3, zorder=.1)
# ax2.set_ylim(0, 360)
def plotPlace(self, row, fig):
pos = [(row+1)*.08, (row+1)*.21, .05, .13] # [left, bottom, width, height]
ax = fig.add_axes(pos)
self.placeCell.plotSpikesvsPlace(fig=fig, ax=ax)
custom_plot.huebschMachen(ax)