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dev #111

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22 changes: 15 additions & 7 deletions src/aind_dynamic_foraging_basic_analysis/metrics/trial_metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -140,13 +140,21 @@ def compute_side_bias(nwb):
C.append(np.nan)
elif len(unique) == 2:
# Fit model
out = model.fit_logistic_regression(
choice, reward, n_trial_back=n_trials_back, cv=cv, fit_exponential=False
)
bias.append(out["df_beta"].loc["bias"]["bootstrap_mean"].values[0])
ci_lower.append(out["df_beta"].loc["bias"]["bootstrap_CI_lower"].values[0])
ci_upper.append(out["df_beta"].loc["bias"]["bootstrap_CI_upper"].values[0])
C.append(out["C"])
try:
out = model.fit_logistic_regression(
choice, reward, n_trial_back=n_trials_back, cv=cv, fit_exponential=False
)
bias.append(out["df_beta"].loc["bias"]["bootstrap_mean"].values[0])
ci_lower.append(out["df_beta"].loc["bias"]["bootstrap_CI_lower"].values[0])
ci_upper.append(out["df_beta"].loc["bias"]["bootstrap_CI_upper"].values[0])
C.append(out["C"])

except:
print('error computing logistic')
bias.append(np.nan)
ci_lower.append(-BIAS_LIMIT)
ci_upper.append(BIAS_LIMIT)
C.append(np.nan)
elif unique[0] == 0:
# only left choices, report bias confidence as (-inf, 0)
bias.append(-1)
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