def create_figure(xmin, xmax):
ncols = 7
nrows = 6
f, axarr = plt.subplots(figsize=(25, 12),
ncols=ncols,
nrows=nrows,
sharey='row')
titles = [
"Aligned to stim onset",
"Aligned to escape onset",
"Aligned to speed peak",
"Aligned to at shelter",
"Aligned to spont homing",
"Aligned to spont homing max speed",
"Aligned to spont runs",
]
ylables = [
'Shelter dist, px',
'Speed, px/frame',
'Ang vel, def/frame',
'Raw ROI sig',
'Mean ROI sig',
]
all_axes = []
for i, title in enumerate(titles):
axes = []
for n, ylabel in enumerate(ylables):
ax = axarr[n, i]
if n == 0:
ax.set(title=title)
if i == 0:
ax.set(ylabel=ylabel)
if n == nrows - 1:
ax.set(xlabel="Time (s)")
if "Ang vel" in ylabel:
ax.set(ylim=[-20, 20])
ax.set(xlim=[xmin, xmax])
axes.append(ax)
all_axes.append(axes)
set_figure_subplots_aspect(left=0.06,
right=0.97,
bottom=0.05,
top=0.93,
wspace=0.17,
hspace=0.4)
clean_axes(f)
return f, all_axes
if longest == 0: continue
x = np.arange(60, longest + 30, 30)
axarr[1, 0].set(title='Signal',
ylabel=f'{roi}\nDFF',
xlim=[x.min(), x.max()],
xticks=x,
xticklabels=((x - n_frames_pre) / 30).astype(np.int32),
xlabel='s')
axarr[0, 0].set(
ylim=[0, 80],
ylabel='X position\n$cm$',
xticks=[],
xlim=[x.min(), x.max()],
)
clean_axes(f)
axes, titles = tag_axes, ('stim', 'start', 'run', 'shelter', 'stop')
for ax, ttl in zip(tag_axes, titles):
ax.set(title=ttl)
ax.set(xticks=[0, 30, 60],
xticklabels=[-1, 0, 1],
xlabel='s',
yticks=[],
ylim=axarr[1, 0].get_ylim())
ax.spines['left'].set_visible(False)
ax.axvline(30, color=[.2, .2, .2], lw=3)
save_figure(
f,
'''
liftoff_th = 6 # paw < 6% of boy weight is liftoff
xkwargs = dict(
xticks=[-1.5, -1, -0.5, -0.25, 0, 0.25, 0.5, 1, 1.5],
xticklabels=[-1.5, -1, -.5, -0.25, 0, 0.25, 0.5, 1, 1.5],
)
cog_fig, cog_ax = plt.subplots(figsize=(12, 12))
main_fig, main_axes = plt.subplots(figsize=(18, 12),
ncols=2,
nrows=2,
sharex=True,
sharey=True)
main_axes = main_axes.flatten()
clean_axes(main_fig)
# style main figure
for ch, ax in zip(sensors, main_axes):
ax.set(title=ch,
ylabel='weight %',
xlabel='time wrt RF take off (s)',
xlim=[-.5, .5],
**xkwargs)
ax.axvline(0, lw=4, ls='--', color=[.2, .2, .2], zorder=-1)
ax.axhline(0, lw=2, color='k', zorder=-1)
step_start_frames, all_sigs = [], []
for i, trial in track(data.iterrows(), total=len(data)):
start = np.where(trial.fr_on_sensor == 0)[0][0]
step_start_frames.append(start)