def cohort(data_dir, mouse_id):
c = Cohort.init_from_files(data_dir, [mouse_id])
yield c
trials["reaction_time"] = trials.end - trials.start
trials.loc[trials["outcome"] == Outcomes.MISSED, "reaction_time"] = np.nan
trials.loc[trials["outcome"] == Outcomes.CANCELLED,
"reaction_time"] = np.nan
sns.stripplot(
data=trials,
x='day',
y='reaction_time',
hue='mouse_id',
dodge=True,
)
plt.show()
if __name__ == '__main__':
mouse_ids = []
for i in sys.argv[2:]:
mouse_ids.append(i)
if not mouse_ids:
raise SystemError(
f'Usage: {__file__} /path/to/json/folder mouse1 mouse2')
cohort = Cohort.init_from_files(
data_dir=sys.argv[1],
mouse_ids=mouse_ids,
)
main(cohort)
import seaborn as sns
import pandas as pd
from pixtools import utils
from reach import Cohort
from reach.session import Outcomes
mouse_ids = [
"HFR18",
"HFR29",
"HFR30",
]
cohort = Cohort.init_from_files(
data_dir=Path(
'~/duguidlab/CuedBehaviourAnalysis/Data/TrainingJSON').expanduser(),
mouse_ids=mouse_ids,
)
# Find best days
results = pd.DataFrame(cohort.get_results())
results['correct'] = results['correct_l'] + results['correct_r']
results['incorrect'] = results['incorrect_l'] + results['incorrect_r']
best_days = []
max_rewards = []
incorrects = []
for mouse in mouse_ids:
mouse_results = results[results['mouse_id'] == mouse]
max_reward = mouse_results['correct'].max()