def load_aroc_res(res_dir, nrate, tstep, n_perm, offsets):
"""Load AROC results."""
fres = aroc_res_fname(res_dir, nrate, tstep, n_perm, offsets)
aroc_res = util.read_objects(fres)
return aroc_res
def plot_response(f_sealcombined, resp_plot_dir, plot_DR=True, plot_sel=True):
"""Plot basic unit activity figures."""
print('\nStarting plotting unit activity...')
putil.inline_off()
# Init folders.
ftempl_dr = util.join([resp_plot_dir, 'direction_response', '{}.png'])
ftempl_sel = util.join([resp_plot_dir, 'stimulus_selectivity', '{}.png'])
# Read in Units.
print(' Reading in UnitArray...')
UA = util.read_objects(f_sealcombined, 'UnitArr')
# Test stimulus response to all directions.
if plot_DR:
print(' Plotting direction response...')
DR_plot(UA, ftempl_dr)
# Plot feature selectivity summary plots.
if plot_sel:
print(' Plotting selectivity summary figures...')
selectivity_summary(UA, ftempl_sel)
# Re-enable inline plotting
putil.inline_on()
def test_DS_frecs(frecs):
"""Test DS of list of recordings."""
print('Testing DS...')
for frec in frecs:
print(frec)
UA = util.read_objects(frec, 'UnitArr')
test_DS(UA)
util.write_objects({'UnitArr': UA}, frec)
def create_UA_from_recs(frecs, ua_name='UA'):
"""Create combined UnitArray from multiple recordings."""
UA = unitarray.UnitArray(ua_name)
for frec in frecs:
rUA = util.read_objects(frec, 'UnitArr')
UA.add_recording(rUA)
return UA
def plot_ROC_mean(d_faroc,
t1=None,
t2=None,
ylim=None,
colors=None,
ylab='AROC',
ffig=None):
"""Plot mean ROC curves over given period."""
# Import results.
d_aroc = {}
for name, faroc in d_faroc.items():
aroc = util.read_objects(faroc, 'aroc')
d_aroc[name] = aroc.unstack().T
# Format results.
laroc = pd.DataFrame(pd.concat(d_aroc), columns=['aroc'])
laroc['task'] = laroc.index.get_level_values(0)
laroc['time'] = laroc.index.get_level_values(1)
laroc['unit'] = laroc.index.get_level_values(2)
laroc.index = np.arange(len(laroc.index))
# Init figure.
fig = putil.figure(figsize=(6, 6))
ax = sns.tsplot(laroc,
time='time',
value='aroc',
unit='unit',
condition='task',
color=colors)
# Highlight stimulus periods.
putil.plot_periods(ax=ax)
# Plot mean results.
[ax.lines[i].set_linewidth(3) for i in range(len(ax.lines))]
# Add chance level line.
putil.add_chance_level(ax=ax, alpha=0.8, color='k')
ax.lines[-1].set_linewidth(1.5)
# Format plot.
xlab = 'Time since S1 onset (ms)'
putil.set_labels(ax, xlab, ylab)
putil.set_limits(ax, [t1, t2], ylim)
putil.set_spines(ax, bottom=True, left=True, top=False, right=False)
putil.set_legend(ax, loc=0)
# Save plot.
putil.save_fig(ffig, fig, ytitle=1.05, w_pad=15)
def load_res(res_dir, list_n_most_DS=None, **par_kws):
"""Load decoding results."""
if list_n_most_DS is None:
list_n_most_DS = [par_kws['n_most_DS']]
# Load results for each number of units included.
all_rt_res = {}
for n_most_DS in list_n_most_DS:
par_kws['n_most_DS'] = n_most_DS
fres = res_fname(res_dir, 'results', **par_kws)
rt_res = util.read_objects(fres, 'rt_res')
all_rt_res[n_most_DS] = rt_res
return all_rt_res
def quality_control(data_dir,
proj_name,
task_order,
plot_qm=True,
plot_stab=True,
fselection=None):
"""Run quality control (SNR, rate drift, ISI, etc) on each recording."""
# Data directory with all recordings to be processed in subfolders.
rec_data_dir = data_dir + 'recordings'
# Init combined UnitArray object.
combUA = unitarray.UnitArray(proj_name, task_order)
print('\nStarting quality control...')
putil.inline_off()
for recording in sorted(os.listdir(rec_data_dir)):
if recording[0] == '_':
continue
# Report progress.
print(' ' + recording)
# Init folder.
rec_dir = util.join([rec_data_dir, recording])
qc_dir = util.join([rec_dir, 'quality_control'])
# Read in Units.
f_data = util.join([rec_dir, 'SealCells', recording + '.data'])
UA = util.read_objects(f_data, 'UnitArr')
# Test unit quality, save result figures, add stats to units and
# exclude low quality trials and units.
ftempl = util.join([qc_dir, 'QC_plots', '{}.png'])
quality_test(UA, ftempl, plot_qm, fselection)
# Report unit exclusion stats.
report_unit_exclusion_stats(UA)
# Test stability of recording session across tasks.
if plot_stab:
print(' Plotting recording stability...')
fname = util.join([qc_dir, 'recording_stability.png'])
test_stability.rec_stability_test(UA, fname)
# Add to combined UA.
combUA.add_recording(UA)
# Add index to unit names.
combUA.index_units()
# Save Units with quality metrics added.
print('\nExporting combined UnitArray...')
fname = util.join([data_dir, 'all_recordings.data'])
util.write_objects({'UnitArr': combUA}, fname)
# Export unit and trial selection results.
if fselection is None:
print('Exporting automatic unit and trial selection results...')
fname = util.joint([data_dir, 'unit_trial_selection.xlsx'])
export.export_unit_trial_selection(combUA, fname)
# Export unit list.
print('Exporting combined unit list...')
export.export_unit_list(combUA, util.join([data_dir, 'unit_list.xlsx']))
# Re-enable inline plotting
putil.inline_on()