def plot_buffer_to_axis(self, axis=None, idx=None, limits=None):
"""plots the current buffer on the passed axis handle"""
try:
from spikeplot import plt, COLOURS
except ImportError:
return None
# init
ax = axis
if ax is None:
f = plt.figure()
ax = f.add_subplot(111)
col = 'k'
if idx is not None:
col = COLOURS[idx % len(COLOURS)]
spks = self._xi_buf[:]
n, s, c = spks.shape
spks = spks.swapaxes(2, 1).reshape(n, s * c)
# plot
ax.plot(spks.T, color='gray')
ax.plot(spks.mean(axis=0), color=col, lw=2)
for i in xrange(1, c):
ax.axvline((self.tf * i), ls='dashed', color='y')
ax.set_xlim(0, s * c)
if limits is not None:
ax.set_ylim(*limits)
ax.set_xlabel('time [samples]')
ax.set_ylabel('amplitude [mV]')
return spks.min(), spks.max()
def plot(self, data, views=2, show=False, filename=None):
"""plot clustering"""
# get plotting tools
try:
from spikeplot import plt, cluster, save_figure
except ImportError:
return None
# init
views = min(views, int(data.shape[1] / 2))
fig = plt.figure()
fig.suptitle('clustering [%s]' % self.clus_type)
ax = [fig.add_subplot(2, views, v + 1) for v in xrange(views)]
axg = fig.add_subplot(212)
ncmp = int(self.labels.max() + 1)
cdata = dict(
zip(xrange(ncmp), [data[self.labels == c] for c in xrange(ncmp)]))
# plot clustering
for v in xrange(views):
cluster(cdata,
data_dim=(2 * v, 2 * v + 1),
plot_handle=ax[v],
plot_mean=sp.sqrt(self.sigma_factor),
xlabel='PC %d' % int(2 * v),
ylabel='PC %d' % int(2 * v + 1),
show=False)
# plot gof
axg.plot(self._gof, ls='steps')
for i in xrange(1, len(self.crange)):
axg.axvline(i * self.repeats - 0.5, c='y', ls='--')
axg.axvspan(self._winner - 0.5,
self._winner + 0.5,
fc='gray',
alpha=0.2)
labels = []
for k in self.crange:
labels += ['%d' % k]
labels += ['.'] * (self.repeats - 1)
axg.set_xticks(sp.arange(len(labels)))
axg.set_xticklabels(labels)
axg.set_xlabel('cluster count and repeats')
axg.set_ylabel(str(self.gof_type).upper())
axg.set_xlim(-1, len(labels))
# handle the resulting plot
if filename is not None:
save_figure(fig, filename, '')
if show is True:
plt.show()
return True
