def plot_kmeans_components(self,
fig1,
gs,
kmeans_clusters,
uncentered_clrs,
plot_title='Hb',
num_subplots=1,
flag_separate=1,
gridspecs=[0, 0],
model_center=0,
removeclusters=0):
with sns.axes_style('darkgrid'):
if flag_separate:
ax1 = fig1.add_subplot(2, 1, num_subplots)
else:
ax1 = eval('fig1.add_subplot(gs' + gridspecs + ')')
if model_center == 1: # Models colors according to trace
clrs_cmap = Colorize.optimize(kmeans_clusters.T, asCmap=True)
clrs = clrs_cmap.colors
else:
clrs_cmap = uncentered_clrs
clrs = clrs_cmap.colors
# Update kmeans if clusters were removed
kmeans_clusters_new = copy(kmeans_clusters)
if removeclusters != 0:
newclrs_updated = copy(clrs_cmap)
for index, value in enumerate(clrs_cmap.colors):
if index in removeclusters:
newclrs_updated.colors[index] = [0, 0, 0]
clrs_cmap = newclrs_updated
clrs = clrs_cmap.colors
for ii in removeclusters:
print ii
kmeans_clusters_new[:,
ii] = zeros(size(kmeans_clusters, 0))
plt.gca().set_color_cycle(clrs)
# remove those clusters that are ignored before plotting
for ii in xrange(0, size(kmeans_clusters_new, 1)):
plt.plot(kmeans_clusters_new[:, ii], lw=4, label=str(ii))
plt.locator_params(axis='y', nbins=4)
ax1.set(xlabel="Time (seconds)", ylabel="a.u")
ax1.legend(prop={'size': 14},
loc='center left',
bbox_to_anchor=(1, 0.5),
ncol=1,
fancybox=True,
shadow=True)
plt.title(plot_title, fontsize=14)
plt.ylim((min(kmeans_clusters_new) - 0.0001,
max(kmeans_clusters_new) + 0.0001))
plt.xlim((0, size(kmeans_clusters_new, 0)))
plt.axhline(y=0, linestyle='-', color='k', linewidth=1)
self.plot_vertical_lines_onset()
self.plot_vertical_lines_offset()
self.plot_stimulus_patch(ax1)
return clrs_cmap
