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test sorting out 'bad' fits

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a.ott 2020-08-19 17:17:32 +02:00
parent 68e7b75768
commit 5f5afd68a9
1 changed files with 15 additions and 1 deletions
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16
analysis.py
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@ -26,8 +26,22 @@ def main():
# exit(0)
# sensitivity_analysis(dir_path, max_models=3)
behaviour_keys = ["burstiness", "coefficient_of_variation", "serial_correlation",
"vector_strength", "f_inf_slope", "f_zero_slope", "f_zero_middle"]
fits_info = get_fit_info(dir_path)
for cell in sorted(fits_info.keys()):
model_values = fits_info[cell][1]
if model_values["vector_strength"] < 0.4:
del fits_info[cell]
print("excluded because of vs")
elif model_values["f_inf_slope"] / fits_info[cell][2]["f_inf_slope"] > 2:
del fits_info[cell]
print("f_inf bad")
errors = calculate_percent_errors(fits_info)
create_boxplots(errors)
labels, corr_values, corrected_p_values = behaviour_correlations(fits_info, model_values=False)
@ -48,7 +62,7 @@ def get_fit_info(folder):
for item in os.listdir(folder):
cell_folder = os.path.join(folder, item)
results = get_best_fit(cell_folder, use_comparable_error=True)
results = get_best_fit(cell_folder, use_comparable_error=False)
cell_behaviour, model_behaviour = results.get_behaviour_values()
fits_info[item] = [results.get_final_parameters(), model_behaviour, cell_behaviour]