def _plot(self, trial, figure, channel_separation_std=8.0,
invert_colors=False):
pf_traces = getattr(trial, self.requires[0]).data
pf_sf = getattr(trial, self.requires[1]).data
f_traces, f_sf = self._get_auxiliary_results(trial)
have_filtered_results = (f_traces is not None)
def as_frac(x=None, y=None):
f = figure
canvas_size_in_pixels = (f.get_figwidth()*f.get_dpi(),
f.get_figheight()*f.get_dpi())
return as_fraction(x=x, y=y,
canvas_size_in_pixels=canvas_size_in_pixels)
figure.set_facecolor(background[invert_colors])
figure.set_edgecolor(foreground[invert_colors])
figure.subplots_adjust(left=as_frac(x=75),
right=1.0-as_frac(x=10),
bottom=as_frac(y=30),
top=1.0-as_frac(y=10))
pf_times = create_times_array(pf_traces, pf_sf)
if have_filtered_results:
f_times = create_times_array(f_traces, f_sf)
channel_separation = (numpy.std(pf_traces[0]) +
numpy.std(f_traces[0]))*(channel_separation_std/2.0)
else:
channel_separation = (numpy.std(pf_traces[0]))*channel_separation_std
axes = figure.add_subplot(111)
axes.set_axis_bgcolor(background[invert_colors])
make_into_publication_axes(axes, base_unit_prefix=('', 'm'),
scale_bar_origin_frac=as_frac(-25, -5),
target_size_frac=as_frac(150, 80),
y_label_rotation='vertical',
color=foreground[invert_colors])
axes.lock_axes()
offsets = []
y_mins = []
y_maxs = []
for i, pf_trace in enumerate(pf_traces):
offset = -i*channel_separation
offsets.append(offset)
y_values = pf_trace+offset
y_mins.append(numpy.min(y_values))
y_maxs.append(numpy.max(y_values))
axes.signal_plot(pf_times, pf_trace+offset,
color=foreground[invert_colors],
alpha=0.5,
label='Pre-Filtered')
if have_filtered_results:
for i, f_trace in enumerate(f_traces):
color = colors[invert_colors][i%len(colors[invert_colors])]
offset = offsets[i]
y_values = f_trace+offset
y_mins.append(numpy.min(y_values))
y_maxs.append(numpy.max(y_values))
axes.signal_plot(f_times, y_values, color=color,
label='Filtered')
axes.set_ylabel('Channel', color=foreground[invert_colors])
axes.set_yticks(offsets)
axes.set_yticklabels([str((i+1)) for i in range(len(offsets))],
color=foreground[invert_colors])
y_min = min(y_mins)
y_max = max(y_maxs)
y_range = y_max - y_min
axes.unlock_axes()
axes.set_xlim(pf_times[0], pf_times[-1])
axes.set_ylim((y_min - 0.03*y_range, y_max + 0.20*y_range))
def _plot(self, trial, figure, channel_separation_std=8.0,
invert_colors=False,
raster_position='center',
raster_size=20,
trace_opacity=0.25):
f_traces = trial.df_traces.data
f_sf = trial.df_sampling_freq.data
f_times = create_times_array(f_traces, f_sf)
if hasattr(trial, 'event_times'):
event_times = trial.event_times.data
else:
event_times = None
have_event_times = (event_times is not None)
def as_frac(x=None, y=None):
f = figure
canvas_size_in_pixels = (f.get_figwidth()*f.get_dpi(),
f.get_figheight()*f.get_dpi())
return as_fraction(x=x, y=y,
canvas_size_in_pixels=canvas_size_in_pixels)
figure.set_facecolor(background[invert_colors])
figure.set_edgecolor(foreground[invert_colors])
figure.subplots_adjust(left=as_frac(x=75),
right=1.0-as_frac(x=10),
bottom=as_frac(y=30),
top=1.0-as_frac(y=10))
channel_separation = numpy.std(f_traces[0]) * channel_separation_std
axes = figure.add_subplot(111)
axes.set_axis_bgcolor(background[invert_colors])
make_into_publication_axes(axes, base_unit_prefix=('', 'm'),
scale_bar_origin_frac=as_frac(-25, -5),
target_size_frac=as_frac(150, 80),
y_label_rotation='vertical',
color=foreground[invert_colors])
axes.lock_axes()
# plot traces
offsets = []
y_mins = []
y_maxs = []
for i, f_trace in enumerate(f_traces):
offset = -i*channel_separation
offsets.append(offset)
y_values = f_trace+offset
y_mins.append(numpy.min(y_values))
y_maxs.append(numpy.max(y_values))
axes.signal_plot(f_times, y_values, color=foreground[invert_colors],
alpha=trace_opacity)
axes.set_ylabel('Channel', color=foreground[invert_colors])
axes.set_yticks(offsets)
axes.set_yticklabels([str((i+1)) for i in range(len(offsets))],
color=foreground[invert_colors])
y_min = min(y_mins)
y_max = max(y_maxs)
y_range = y_max - y_min
if have_event_times:
for i, event_sequence in enumerate(event_times):
if len(event_sequence) > 0:
color = colors[invert_colors][i%len(colors[invert_colors])]
e_xs = event_sequence
if raster_position == 'center':
e_ys = [offsets[i] for e in e_xs]
else:
# 0.1 corrects for roundoff error
event_indexes = [int(f_sf*e+0.1) for e in e_xs]
e_ys = [f_traces[i][ei]+offsets[i]
for ei in event_indexes]
axes.plot(numpy.array(e_xs), numpy.array(e_ys),
linewidth=0, marker='|',
markersize=raster_size, color=color,
markeredgewidth=2)
axes.unlock_axes()
axes.set_xlim(f_times[0], f_times[-1])
axes.set_ylim((y_min - 0.03*y_range, y_max + 0.20*y_range))
self.axes = axes
def _plot(self, trial, figure, channel_separation_std=8.0,
invert_colors=False,
raster_size=20,
trace_opacity=0.25,
traces_shown='Extraction Filtered'):
def as_frac(x=None, y=None):
f = figure
canvas_size_in_pixels = (f.get_figwidth()*f.get_dpi(),
f.get_figheight()*f.get_dpi())
return as_fraction(x=x, y=y,
canvas_size_in_pixels=canvas_size_in_pixels)
figure.set_facecolor(background[invert_colors])
figure.set_edgecolor(foreground[invert_colors])
figure.subplots_adjust(left=as_frac(x=75),
right=1.0-as_frac(x=40),
bottom=as_frac(y=30),
top=1.0-as_frac(y=10))
if traces_shown != 'None':
tn = {
'Detection Filtered':('df_traces', 'df_sampling_freq'),
'Extraction Filtered':('ef_traces', 'ef_sampling_freq'),
'Unfiltered':('pf_traces', 'pf_sampling_freq')}
# check to see if we can proceed.
missing_requirements = []
for attr in tn[traces_shown]:
if not (hasattr(trial, attr) and
getattr(trial, attr).data is not None):
missing_requirements.append(attr)
if missing_requirements:
figure.text(0.5, 0.5, 'This visualization cannot be completed due to unmet requirements:\n\n%s' % '\n'.join(missing_requirements))
return
else:
traces = getattr(trial, tn[traces_shown][0]).data
sf = getattr(trial, tn[traces_shown][1]).data
axes = figure.add_subplot(111)
axes.set_axis_bgcolor(background[invert_colors])
make_into_publication_axes(axes, base_unit_prefix=('', 'm'),
scale_bar_origin_frac=as_frac(-25, -5),
target_size_frac=as_frac(150, 80),
y_label_rotation='vertical',
color=foreground[invert_colors])
axes.lock_axes()
# plot traces
offsets = []
y_mins = []
y_maxs = []
times = create_times_array(traces, sf)
channel_separation = numpy.std(traces[0]) * channel_separation_std
for i, trace in enumerate(traces):
offset = -i*channel_separation
offsets.append(offset)
y_values = trace+offset
y_mins.append(numpy.min(y_values))
y_maxs.append(numpy.max(y_values))
axes.signal_plot(times, y_values,
color=foreground[invert_colors],
alpha=trace_opacity)
axes.set_ylabel('Channel', color=foreground[invert_colors])
axes.set_yticks(offsets)
axes.set_yticklabels([str((i+1)) for i in range(len(offsets))],
color=foreground[invert_colors])
axes.unlock_axes()
y_min = min(y_mins)
y_max = max(y_maxs)
y_range = y_max - y_min
axes.set_xlim(times[0], times[-1])
axes.set_ylim((y_min - 0.03*y_range, y_max + 0.20*y_range))
axes.get_yaxis().set_ticks_position('left')
# plot rasters
if traces_shown != 'None':
ra = figure.add_axes(axes.get_position(), frameon=False)
xlims = (times[0], times[-1])
else:
ra = figure.add_subplot(111, frameon=False)
xlims = None
ra.text(1+as_frac(28), 0.5, 'Cluster',
color=foreground[invert_colors],
clip_on=False,
verticalalignment='center',
horizontalalignment='center',
rotation='vertical',
transform=ra.transAxes)
ymin, ymax = (0.0, 1.0)
yrange = ymax - ymin
cft = trial.clustered_feature_times
minx = 1e30
maxx = -1e30
poss = []
for i, cluster_name in enumerate(sorted(cft.keys())):
color = cluster_colors[invert_colors][
i%len(cluster_colors[invert_colors])]
e_xs = cft[cluster_name]
pos = ymax - i/max(1.0, float(len(cft.keys())-1))*yrange
poss.append(pos)
if len(e_xs) > 0:
minx = min(minx, min(e_xs))
maxx = max(maxx, max(e_xs))
ra.plot(numpy.array(e_xs),
numpy.ones(len(e_xs))*pos,
linewidth=0,
marker='|',
markersize=raster_size,
color=color,
markeredgewidth=2)
if xlims is not None:
ra.set_xlim(xlims)
ra.set_ylim(ymin-0.1*yrange, ymax+0.1*yrange)
ra.get_yaxis().set_ticks_position('right')
ra.set_yticks(poss)
ra.set_yticklabels(sorted(cft.keys()))
ra.set_xticks([])
ra.set_xticklabels([''], visible=False)
make_into_raster_axes(ra)
# fix colors
lines = ra.get_xticklines()
if traces_shown != 'None':
lines.extend(axes.get_yticklines())
for line in lines:
line.set_color(foreground[invert_colors])
labels = ra.get_xticklabels()
labels.extend(ra.get_yticklabels())
for label in labels:
label.set_color(foreground[invert_colors])