def update(self):
try:
sessions_df = utils.get_sessions(self.Animal.folder)
lines = sessions_df['task'].tolist()
lines = '\n'.join(lines)
model = PandasModel(sessions_df[['date','time','task']])
self.Table.setModel(model)
except ValueError:
pass
def reaches_during_delay_across_sess(animal_fd_path, tasks_names,
init_day_idx):
SessionsDf = utils.get_sessions(animal_fd_path)
animal_meta = pd.read_csv(animal_fd_path / 'animal_meta.csv')
# Filter sessions to the ones of the task we want to see
FilteredSessionsDf = pd.concat(
[SessionsDf.groupby('task').get_group(name) for name in tasks_names])
log_paths = [
Path(path) / 'arduino_log.txt' for path in FilteredSessionsDf['path']
]
fig, axes = plt.subplots(ncols=2, figsize=[6, 4], sharey=True, sharex=True)
colors = sns.color_palette(palette='turbo', n_colors=len(log_paths))
for j, log_path in enumerate(log_paths[init_day_idx:]):
LogDf = bhv.get_LogDf_from_path(log_path)
# ADD SINGLE GO_CUE_EVENT
LogDf = bhv.add_go_cue_LogDf(LogDf)
TrialSpans = bhv.get_spans_from_names(LogDf, "TRIAL_ENTRY_STATE",
"ITI_STATE")
TrialDfs = []
for i, row in tqdm(TrialSpans.iterrows(), position=0, leave=True):
TrialDfs.append(bhv.time_slice(LogDf, row['t_on'], row['t_off']))
metrics = (met.get_start, met.get_stop, met.get_correct_side,
met.get_outcome, met.get_interval_category,
met.get_chosen_side, met.has_reach_left,
met.has_reach_right)
SessionDf = bhv.parse_trials(TrialDfs, metrics)
CDF_of_reaches_during_delay(SessionDf,
TrialDfs,
axes=axes,
color=colors[j],
alpha=0.75,
label='day ' + str(j + 1))
fig.suptitle('CDF of first reach split on trial type \n' +
animal_meta['value'][5] + '-' + animal_meta['value'][0])
axes[0].set_ylabel('Fraction of trials')
axes[0].legend(frameon=False, fontsize='x-small')
fig.tight_layout()
return axes
def load_last_vars(self):
""" try to get arduino variables from last run for the task
only loads, does not send! """
config = self.parent().config
folder = Path(
config['paths']['animals_folder']) / config['current']['animal']
SessionsDf = utils.get_sessions(folder)
try:
previous_sessions = SessionsDf.groupby('task').get_group(
config['current']['task'])
except KeyError:
utils.printer(
"trying to use last vars, but animal has not been run on this task before.",
'error')
return None
# to allow for this functionalty while task is running
if self.parent().parent().running:
ix = -2
else:
ix = -1
try:
prev_session_path = Path(previous_sessions.iloc[ix]['path'])
prev_vars_path = prev_session_path / config['current'][
'task'] / "Arduino" / "src" / "interface_variables.h"
if prev_vars_path.exists():
prev_vars = utils.parse_arduino_vars(prev_vars_path)
return prev_vars
else:
utils.printer(
"found variables from last session, but can't set them",
"error")
return None
except IndexError:
# thrown when there is no previous session
return None
def grasp_dur_across_sess(animal_fd_path, tasks_names):
SessionsDf = utils.get_sessions(animal_fd_path)
animal_meta = pd.read_csv(animal_fd_path / 'animal_meta.csv')
# Filter sessions to the ones of the task we want to see
FilteredSessionsDf = pd.concat(
[SessionsDf.groupby('task').get_group(name) for name in tasks_names])
log_paths = [
Path(path) / 'arduino_log.txt' for path in FilteredSessionsDf['path']
]
fig, axes = plt.subplots(ncols=2, figsize=[8, 4], sharey=True, sharex=True)
sides = ['LEFT', 'RIGHT']
Df = []
# gather data
for day, log_path in enumerate(log_paths):
LogDf = bhv.get_LogDf_from_path(log_path)
TrialSpans = bhv.get_spans_from_names(LogDf, "TRIAL_ENTRY_STATE",
"ITI_STATE")
TrialDfs = []
for i, row in tqdm(TrialSpans.iterrows(), position=0, leave=True):
TrialDfs.append(bhv.time_slice(LogDf, row['t_on'], row['t_off']))
metrics = (met.get_start, met.get_stop, met.get_correct_side,
met.get_outcome, met.get_interval_category,
met.get_chosen_side, met.has_reach_left,
met.has_reach_right)
SessionDf = bhv.parse_trials(TrialDfs, metrics)
for side in sides:
event_on, event_off = 'REACH_' + str(side) + '_ON', 'REACH_' + str(
side) + '_OFF' # event names
# reaches
grasp_spansDf = bhv.get_spans_from_names(LogDf, event_on,
event_off)
reach_durs = np.array(grasp_spansDf['dt'].values, dtype=object)
Df.append([reach_durs], columns=['durs'], ignore_index=True)
# grasps
choiceDf = bhv.groupby_dict(
SessionDf, dict(has_choice=True, chosen_side=side.lower()))
grasp_durs = choiceDf[~choiceDf['grasp_dur'].isna(
)]['grasp_dur'].values # filter out Nans
Df.append([grasp_durs, 'g', side],
columns=['durs', 'type', 'side'],
ignore_index=True)
sns.violinplot(data=Df[Df['type'] == 'r'],
x=day,
y='durs',
hue='side',
split=True,
cut=0,
legend='reaches')
sns.violinplot(data=Df[Df['type'] == 'g'],
x=day,
y='durs',
hue='side',
split=True,
cut=0,
legend='grasps')
fig.suptitle('CDF of first reach split on trial type \n' +
animal_meta['value'][5] + '-' + animal_meta['value'][0])
axes.legend
return axes
Nicknames = ['Lifeguard', 'Lumberjack', 'Teacher', 'Plumber', 'Poolboy', 'Policeman', 'Therapist']
# Nicknames = ['Therapist']
task_name = 'learn_to_choose_v2'
# get animals by Nickname
Animals_folder = Path("/media/georg/htcondor/shared-paton/georg/Animals_reaching")
Animals = utils.get_Animals(Animals_folder)
Animals = [a for a in Animals if a.Nickname in Nicknames]
overwrite = False
for i, Animal in enumerate(Animals):
utils.printer("processing animal %s" % Animal, 'msg')
SessionsDf = utils.get_sessions(Animal.folder).groupby('task').get_group(task_name)
SessionsDf = SessionsDf.reset_index()
for i, row in SessionsDf.iterrows():
session_folder = Path(row['path'])
Session = utils.Session(session_folder)
# session overview
if 0:
outpath = Animal.folder / 'plots' / 'session_overviews' / ('session_overview_%s_%s_day_%s.png' % (Session.date, Session.time, Session.day))
if not outpath.exists() or overwrite:
plot_session_overview(session_folder, save=outpath)
# init histograms
if 1:
outpath = Animal.folder / 'plots' / 'init_histograms' / ('init_histogram_%s_%s_day_%s.png' % (Session.date, Session.time, Session.day))
def plot_bias_over_sessions(Animal_folder, task_name, save=None):
Animal = utils.Animal(Animal_folder)
# get BiasDfs
SessionsDf = utils.get_sessions(Animal.folder).groupby('task').get_group(task_name)
BiasDfs = []
autodeliver = []
p_lefts = []
for i, row in SessionsDf.iterrows():
session_folder = Path(row['path'])
LogDf = bhv.get_LogDf_from_path(session_folder / "arduino_log.txt")
LogDf['min'] = LogDf['t'] / 60000
# one sesion bias
BiasDf = LogDf.groupby('var').get_group('bias')
t_min = BiasDf['t'].values[0]
t_max = BiasDf['t'].values[-1]
BiasDf['t_rel'] = (BiasDf['t'].values - t_min)/t_max
BiasDfs.append(BiasDf)
# get autodeliver value for session
fname = session_folder / task_name / 'Arduino' / 'src' / 'interface_variables.h'
value = utils.parse_arduino_vars(fname).groupby('name').get_group('autodeliver_rewards').iloc[0]['value']
autodeliver.append(value)
# get static bias corr if possible
fname = session_folder / task_name / 'Arduino' / 'src' / 'interface_variables.h'
try:
p_left = utils.parse_arduino_vars(fname).groupby('name').get_group('p_left').iloc[0]['value']
except KeyError:
p_left = 0.5
p_lefts.append(p_left)
fig, axes = plt.subplots(nrows=2, sharex=True, gridspec_kw=dict(height_ratios=(0.1,1)))
w = 0.5
axes[0].set_ylabel('auto\nrewards')
axes[0].set_xticks([])
axes[0].set_yticks([])
for i in range(SessionsDf.shape[0]):
BiasDf = BiasDfs[i]
tvec = np.linspace(i-w/2,i+w/2,BiasDf.shape[0])
axes[1].plot(tvec, BiasDf['value'])
axes[1].plot(i, np.average(BiasDf['value']),'o',color='k')
axes[1].set_ylim(-0.1,1.1)
if autodeliver[i] == 1:
axes[0].plot(i,0,'o',color='black')
# axes[0].text(i,0.03,str(p_lefts[i]),ha='center')
axes[1].axhline(0.5,linestyle=':',lw=1,alpha=0.5,color='k')
axes[1].set_xticks(range(SessionsDf.shape[0]))
axes[1].set_xticklabels(SessionsDf['date'],rotation=45, ha="right")
axes[1].set_xlabel('date')
axes[1].set_ylabel('bias\n1=right')
title = Animal.Nickname + ' - bias over sessions'
axes[0].set_title(title)
sns.despine(fig)
fig.tight_layout()
fig.subplots_adjust(hspace=0.1)
if save is not None:
os.makedirs(save.parent, exist_ok=True)
plt.savefig(save, dpi=600)
plt.close(fig)
# %%
# Animal_folder = Path("/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02911_Lumberjack")
# task_name = 'learn_to_choose_v2'
# plot_bias_over_sessions(Animal_folder, task_name=task_name, save=None)
######## ## ## ## ##
## ## ## ## ### ##
## ## ## ## #### ##
######## ## ## ## ## ##
## ## ## ## ## ####
## ## ## ## ## ###
## ## ####### ## ##
"""
# Borges = Path("/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-01977")
Marquez = Path("/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-01975") # TODO TO BE CHANGED BY PACO
task_name = 'learn_to_fixate_discrete_v1'
SessionsDf = utils.get_sessions(Marquez)
SessionsDf = SessionsDf.groupby('task').get_group('learn_to_fixate_discrete_v1')
log_path = Path(SessionsDf.iloc[-1]['path']) / 'arduino_log.txt'
LogDf = bhv.get_LogDf_from_path(log_path)
animal = utils.Animal(log_path.parent)
date = log_path.parent.stem.split('_')[0]
# slice into trials
def get_SessionDf(LogDf, metrics, trial_entry_event="TRIAL_AVAILABLE_STATE", trial_exit_event="ITI_STATE"):
TrialSpans = bhv.get_spans_from_names(LogDf, trial_entry_event, trial_exit_event)
TrialDfs = []
for i, row in tqdm(TrialSpans.iterrows(),position=0, leave=True):
animals = [ 'JJP-02909_Lifeguard','JJP-02911_Lumberjack','JJP-02912_Teacher','JJP-02994_Plumber',
'JJP-02995_Poolboy','JJP-02996_Policeman','JJP-02997_Therapist']
animals_dir_plots = animals_dir / 'plots'
os.makedirs(animals_dir_plots, exist_ok=True)
no_sessions_to_analyze = 10
n_rews_collected = np.zeros((len(animals), no_sessions_to_analyze))
n_anticipatory = np.zeros((len(animals), no_sessions_to_analyze))
no_trials = np.zeros((len(animals), no_sessions_to_analyze))
session_length = np.zeros((len(animals), no_sessions_to_analyze))
for j, animal in enumerate(animals):
SessionsDf = utils.get_sessions(animals_dir / animal)
# Filter sessions to the ones of the task we want to see
task_name = ['learn_to_choose_v2']
FilteredSessionsDf = pd.concat([SessionsDf.groupby('task').get_group(name) for name in task_name])
log_paths = [Path(path)/'arduino_log.txt' for path in FilteredSessionsDf['path']]
for k,log_path in enumerate(tqdm(log_paths[:no_sessions_to_analyze], position=0, leave=True, desc=animal)):
LogDf = bhv.get_LogDf_from_path(log_path)
# Getting metrics
TrialSpans = bhv.get_spans_from_names(LogDf, "TRIAL_ENTRY_STATE", "ITI_STATE")
TrialDfs = []
for i, row in TrialSpans.iterrows():
folders = dict(
Lifeguard="/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02909",
Lumberjack="/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02911",
Teacher="/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02912",
Plumber="/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02994",
Poolboy="/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02995",
Policeman="/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02996",
Therapist="/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02997")
# %%
for animal, folder in folders.items():
print("processing %s" % animal)
folder = Path(folder)
Animal = utils.Animal(folder)
SessionsDf = utils.get_sessions(Animal.folder).groupby('task').get_group('learn_to_choose_v2')
SessionsDf = SessionsDf.reset_index()
for day, row in SessionsDf.iterrows():
print(day)
folder = Path(SessionsDf.loc[day,'path'])
LogDf = bhv.get_LogDf_from_path(folder / "arduino_log.txt")
LogDf['min'] = LogDf['t'] / 60000
# check each reach
ReachesLeftDf = bhv.get_spans_from_names(LogDf, "REACH_LEFT_ON", "REACH_LEFT_OFF")
# drop invalid
min_th = 5
max_th = 2000
import behav_plotters_reach as bhv_plt_reach """ # ####### # ###### ### # # ##### # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # #### # # # ####### # # # # # # # # # # # # # # # # # ## # # ####### ####### # # ###### ### # # ##### """ animal_fd_path = sys.argv[1] fd_path = Path(utils.get_sessions(animal_fd_path).iloc[-1]['path']) # Get last session fd_path # Arduino data log_path = fd_path / 'arduino_log.txt' LogDf = bhv.get_LogDf_from_path(log_path) # LoadCell data LoadCellDf = bhv.parse_bonsai_LoadCellData(fd_path / 'bonsai_LoadCellData.csv') # Parse sync events/triggers lc_sync_event = sync.parse_harp_sync(fd_path / 'bonsai_harp_sync.csv') arduino_sync_event = sync.get_arduino_sync(fd_path / 'arduino_log.txt') # Get the values out of them Sync = sync.Syncer() Sync.data['arduino'] = arduino_sync_event['t'].values
import os
from Utils import utils
# %%
folder = Path("/home/georg/data/grasping_animals/")
folder = Path("/media/georg/htcondor/shared-paton/georg/Animals_reaching")
Animals = utils.get_Animals(folder)
# %%
# lifeguard
folder = "/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02909"
Animal = utils.Animal(folder)
day = 0
folder = Path(utils.get_sessions(Animal.folder).path[day])
LogDf = bhv.get_LogDf_from_path(folder / "arduino_log.txt")
LogDf['min'] = LogDf['t'] / 60000
# %% check each reach
ReachesDf = bhv.get_spans_from_names(LogDf, "REACH_ON", "REACH_OFF")
# drop invalid
min_th = 5
max_th = 2000
binds = np.logical_and(ReachesDf['dt'].values > min_th, ReachesDf['dt'].values < max_th)
ReachesDf = ReachesDf.loc[binds]
# %%
folder = Path("/home/georg/data/grasping_animals/")
folder = Path("/media/georg/htcondor/shared-paton/georg/Animals_reaching")
Animals = utils.get_Animals(folder)
# %%
# Lifeguard
folder = "/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02909"
# Lumberjack
folder = "/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02911"
# Teacher
folder = "/media/georg/htcondor/shared-paton/georg/Animals_reaching/JJP-02912"
Animal = utils.Animal(folder)
SessionsDf = utils.get_sessions(Animal.folder).groupby('task').get_group('learn_to_grasp')
for day, row in SessionsDf.iterrows():
folder = Path(utils.get_sessions(Animal.folder).path[day])
LogDf = bhv.get_LogDf_from_path(folder / "arduino_log.txt")
LogDf['min'] = LogDf['t'] / 60000
# check each reach
ReachesDf = bhv.get_spans_from_names(LogDf, "REACH_ON", "REACH_OFF")
# drop invalid
min_th = 5
max_th = 2000
binds = np.logical_and(ReachesDf['dt'].values > min_th, ReachesDf['dt'].values < max_th)
# # # ###### # # ##### ##### ##### ##### ##### ##### # # # # # # #####
####### # # # # # # # # # # # # # # # # # #
# # # # # # # # # # # # # # # # # # # # # # # ## # #
# # ##### # # ####### ##### ##### ##### ####### ##### ##### ### ####### # # #####
"""
# %% Obtain log_paths and plot dirs
animal_fd_path = utils.get_folder_dialog(initial_dir="/media/storage/shared-paton/georg/Animals_reaching/")
across_session_plot_dir = animal_fd_path / 'plots'
animal_meta = pd.read_csv(animal_fd_path / 'animal_meta.csv')
nickname = animal_meta[animal_meta['name'] == 'Nickname']['value'].values[0]
os.makedirs(across_session_plot_dir, exist_ok=True)
# %% across sessions - plot weight
SessionsDf = utils.get_sessions(animal_fd_path)
Df = pd.read_csv(animal_fd_path / 'animal_meta.csv')
ini_weight = float(Df[Df['name'] == 'Weight']['value'])
for i,row in SessionsDf.iterrows():
try:
path = row['path']
Df = pd.read_csv(Path(path) / 'animal_meta.csv')
current_weight = float(Df[Df['name'] == 'current_weight']['value'])
SessionsDf.loc[row.name,'weight'] = current_weight
SessionsDf.loc[row.name,'weight_frac'] = current_weight / ini_weight
except:
pass
# Formatting
fig, axes = plt.subplots()