def plot_order_vs_time(DIR, colA, colB, df=pd.DataFrame(), fn=''):
if len(df) < 1:
df = pd.read_pickle(DIR +
'track/frame_means_rotation_polarization.pickle')
if not 'coheXXXXXrence' in df.columns: #FIXME
ret, df = stim_handling.synch_coherence_with_rotation(DIR)
if ret == 0:
print DIR.split('/')[-1], 'logged stim does not match timestamps'
return
df = df[df['FrameNumber'].notnull()]
fig = plt.figure()
fig.suptitle(DIR.split('/')[-2])
subs = ['coherence', colA, colB]
colourlist = ['black', 'red', 'blue']
ylabs = ['% Clockwise', 'Order', 'Order']
ax1 = fig.add_subplot(311)
ax2 = fig.add_subplot(312, sharex=ax1)
ax3 = fig.add_subplot(313, sharex=ax1)
axes = [ax1, ax2, ax3]
for REP in range(len(subs)):
ax = axes[REP]
fig.add_axes(ax)
plt.plot(df.Time, df[subs[REP]].values, color=colourlist[REP])
ax.set_title(subs[REP])
ax.set_ylabel(ylabs[REP])
if REP < 2:
plt.setp(ax.get_xticklabels(), visible=False)
else:
ax.set_xlabel('Time (s)')
if subs[REP] == 'dRotation':
ax.set_ylim(-1, 1)
ax.set_yticks([-1, 0, 1])
plt.axhline(y=0.0, color='k', linestyle='-')
elif subs[REP] == 'coherence':
ax.set_ylim(-0.1, 1.1)
ax.set_yticks([0, 0.5, 1])
axR = ax.twinx()
plt.plot(df['Time'], df['speed'] * df['dir'] * 1000.0, color='r')
axR.set_ylabel('speed', color='r')
axR.tick_params('y', colors='r')
axR.set_ylim(-110, 110)
axR.set_yticks([-100, 0, 100])
else:
ax.set_ylim(0, 1)
ax.set_yticks([0, 0.5, 1])
#ax.legend(loc=0)
#plt.colorbar()
plt.savefig(DIR + 'track/vsTime_' + fn + colA + '_' + colB + '.svg',
bbox_inches='tight',
pad_inches=0)
plt.savefig(DIR + 'track/vsTime_' + fn + colA + '_' + colB +
'.png') #, bbox_inches='tight',pad_inches = 0)
plt.close('all')
return
def setup(filelist, prestim_frames=400, **kwargs):
stores = []
framenums = []
for vid in filelist:
pf = pd.read_pickle(vid + '/track/perframe_stats.pickle')
log = stims.get_logfile(vid)
store = imgstore.new_for_filename(vid + '/metadata.yaml')
stores.append(store)
ret, pf2 = stims.synch_coherence_with_rotation(pf, log,
store) #sync_reversals
pf3 = sync_by_stimStart(pf2)
startframe = pf3.loc[pf3['stimStart'].idxmax() - prestim_frames,
'FrameNumber']
framenums.append(startframe)
return filelist, stores, framenums
def run(DIR):
TRACK_DIR = slashdir(DIR) + 'track/'
frame_means = pd.read_pickle(TRACK_DIR + 'frame_means_rotation_polarization.pickle')
#if not 'coherence' in frame_means.columns:
ret, frame_means = stim_handling.synch_coherence_with_rotation(DIR)
if ret == 0:
print DIR.split('/')[-1], 'logged stim does not match timestamps'
if os.path.exists(TRACK_DIR + 'centroid_rotation.pickle'):
os.remove(TRACK_DIR + 'centroid_rotation.pickle')
return
frame_means['timedelta'] = pd.to_timedelta(frame_means['Time'], unit='s')
frame_means.index = frame_means['timedelta']
frame_means = frame_means.resample('1s').median()
frame_means['cRotation'] = get_centroid_rotation(DIR, frame_means, 10)
frame_means['stateDepRotOrder'] = stateDependentRotationOrder(frame_means)
frame_means.to_pickle(TRACK_DIR + 'centroid_rotation.pickle')
plot_order_vs_time(slashdir(DIR), 'dRotation','cRotation', 'stateDepRotOrder', df=frame_means)
return
DATA = pd.DataFrame()
for handle in HANDLES:
for directory in DIRECTORIES:
for fn in glob.glob(
directory + '*' + handle +
'*/track/frame_means_rotation_polarization.pickle'):
gonogo = True
for x in EXCLUDE:
if x in fn:
gonogo = False
if gonogo:
print 'processing: ', fn
try:
ret, df = stim_handling.synch_coherence_with_rotation(
fn.rsplit('/', 2)[0])
if ret == 0:
print fn.split('/')[
-3], 'logged stim does not match timestamps'
if os.path.exists(
fn.rsplit('/')[0] +
'/centroid_rotation.pickle'):
os.remove(
fn.rsplit('/')[0] +
'/centroid_rotation.pickle')
continue
else:
#df = pd.read_pickle(fn)
expid, groupsize, _, expdate, exptime = fn.rsplit(
'/', 3)[1].split('_')
df['cRotation'] = centroid_rotation.get_centroid_rotation(
groupData = pd.DataFrame()
for DIR in DIRS:
for fn in glob.glob('/media/recnodes/' + DIR +
'/coherencetestangular_' + str(groupsize) +
'_dotbot_*/track/perframe_stats.pickle'):
try:
if fn.split('/track/perframe_stats')[0] in blacklist:
print "excluding", fn
continue
elif '20171219' in fn:
print "excluding", fn
continue
print fn
ret, pf = stims.synch_coherence_with_rotation(
pd.read_pickle(fn),
stims.get_logfile(fn.rsplit('/', 2)[0]),
imgstore.new_for_filename(
fn.rsplit('/', 2)[0] + '/metadata.yaml'))
pf['dir'] = pd.to_numeric(pf['dir'], errors='coerce')
pf['coh'] = pf['coh'].fillna(method='pad').fillna(
method='backfill')
pf['coh'] = min(coherences,
key=lambda x: abs(x - pf['coh'].median()))
pf = sync_by_stimStart(pf)
fileID = fn.split('/')[-3].split('.')[0].split('_', 3)[-1]
aligned = align_by_stim(pf, fileID)
aligned['groupsize'] = groupsize
groupData = pd.concat([groupData, aligned], axis=0)
except Exception as E:
print "ERROR", fn, '\n', E