def make_stim_df(self):
stim_df = fg.load_visual_stimuli(self.pkl)
stim_df['jcam_onframe'] = get_jcam_index(self.session.timeline.times,
stim_df['frame'])
stim_df['jcam_offframe'] = get_jcam_index(self.session.timeline.times,
stim_df['end_frame'])
stim_df['image_id'] = None
if stim_df['image_name'][0] is not None:
stim_df['image_id'] = stim_df['image_name']
else:
stim_df['image_id'] = stim_df['orientation']
self.stim_df = stim_df
return self.stim_df
def make_change_df(self):
change_df = pd.DataFrame()
change_df['frame'] = self.trials_df['change_frame'].dropna()
change_df['jcam_changeframe'] = get_jcam_index(
self.session.timeline.times, change_df['frame'])
self.change_df = change_df
return self.change_df
def make_trials_df(self):
trials_df = beh_pkl_path_to_df(self.pkl_path)
trials_df['jcam_startframe'] = get_jcam_index(
self.session.timeline.times, trials_df['startframe'])
for idx in trials_df.index:
if trials_df.at[idx, 'trial_type'] == 'autorewarded':
trials_df.at[idx, 'response_type'] = 'AUTOREWARDED'
self.trials_df = trials_df
return self.trials_df
def get_session_dataframe(self, date, path, session_manifest, save=False):
if (date == self.date):
try:
session = self.session
except AttributeError:
session = self.get_IB_session_object(date, path, session_manifest)
else:
session = self.get_IB_session_object(date, path, session_manifest)
pkl_path = os.path.join(self.path, self.session_manifest['behavior_pkl'])
df = beh_pkl_path_to_df(pkl_path)
df_jcam = add_jcam_to_df(df, session)
running_speed = load_running_speed(pd.read_pickle(pkl_path))
df_jcam['lick_frames_jcam'] = None
df_jcam['run_speeds'] = None
for idx in df_jcam.index:
start_f = df_jcam.at[idx, 'startframe']
try:
end_f = df_jcam.at[idx+1, 'startframe']
except:
end_f = df_jcam.startframe.iloc[-1]
speed = list(running_speed[running_speed['frame'].between(start_f-1, end_f, inclusive=False)].speed)
df_jcam.at[idx, 'run_speeds'] = speed
if len(df_jcam.iloc[idx]['lick_frames']) > 0:
lick_frames = df_jcam.iloc[idx]['lick_frames']
licks = []
for l in lick_frames:
lick = get_jcam_index(self.session.timeline.times,l)
licks.append(lick)
df_jcam.at[idx, 'lick_frames_jcam'] = licks
if save==True:
df_name = '{}_{}_beh_jcam_df.pkl'.format(self.date, self.mouse_id)
pd.to_pickle(df_jcam, os.path.join(self.path, df_name))
self.df = df_jcam
return self.df
def make_rewards_df(self):
rewards_df = fg.load_rewards(self.pkl)
rewards_df['jcam_rew_frame'] = get_jcam_index(
self.session.timeline.times, rewards_df['frame'])
self.rewards_df = rewards_df
return self.rewards_df
def make_licks_df(self):
licks_df = fg.load_licks(self.pkl)
licks_df['jcam_lick_frame'] = get_jcam_index(
self.session.timeline.times, licks_df['frame'])
self.licks_df = licks_df
return self.licks_df