diff --git a/Figures_results.py b/Figures_results.py index 49da72e..e21137a 100644 --- a/Figures_results.py +++ b/Figures_results.py @@ -29,12 +29,13 @@ def main(): # behaviour_correlations_plot(fits_info) # - # labels, corr_values, corrected_p_values = parameter_correlations(fits_info) - # par_labels = [parameter_titles[l] for l in labels] - # fig, ax = plt.subplots(1, 1) - # create_correlation_plot(ax, par_labels, corr_values, corrected_p_values, "", colorbar=True) - # plt.savefig(consts.SAVE_FOLDER + "parameter_correlations.png") - # plt.close() + labels, corr_values, corrected_p_values = parameter_correlations(fits_info) + par_labels = [parameter_titles[l] for l in labels] + fig, ax = plt.subplots(1, 1) + #ax, labels, correlations, p_values, title, y_label=True + create_correlation_plot(ax, par_labels, corr_values, corrected_p_values, "") + plt.savefig(consts.SAVE_FOLDER + "parameter_correlations.png") + plt.close() # create_parameter_distributions(get_parameter_values(fits_info)) @@ -102,8 +103,9 @@ def create_correlation_plot(ax, labels, correlations, p_values, title, y_label=T for j in range(correlations.shape[1]): if abs(p_values[i, j]) < 0.05: cleaned_cors[i, j] = correlations[i, j] - - im = ax.imshow(correlations, vmin=-1, vmax=1) + else: + cleaned_cors[i, j] = np.NAN + im = ax.imshow(cleaned_cors, vmin=-1, vmax=1) # We want to show all ticks... ax.set_xticks(np.arange(len(labels))) diff --git a/Fitter.py b/Fitter.py index 4c914cb..168cee2 100644 --- a/Fitter.py +++ b/Fitter.py @@ -552,6 +552,7 @@ def calculate_list_error(fit, reference): return norm_error + def calculate_histogram_bins(isis): isis = np.array(isis) * 1000 step = 0.1 diff --git a/analysis.py b/analysis.py index fa74c0d..ed69d4c 100644 --- a/analysis.py +++ b/analysis.py @@ -63,8 +63,13 @@ def get_filtered_fit_info(folder): if model_behaviour["f_zero_slope"] > 50000 or cell_behaviour["f_zero_slope"] > 50000: print("f_zero_slope used to filter a fit") continue - if 1 - abs(model_behaviour["f_inf_slope"] - cell_behaviour["f_inf_slope"]) > 0.1: - print("f_inf_slope used to filter a fit") + # if (abs(model_behaviour["f_inf_slope"] - cell_behaviour["f_inf_slope"]) / cell_behaviour["f_inf_slope"]) > 0.25: + # print("f_inf_slope used to filter a fit") + # print((abs(model_behaviour["f_inf_slope"] - cell_behaviour["f_inf_slope"]) / cell_behaviour["f_inf_slope"])) + # continue + if abs((model_behaviour["coefficient_of_variation"] - cell_behaviour["coefficient_of_variation"]) / + cell_behaviour["coefficient_of_variation"]) > 0.25: + print("CV used to filter a fit") continue fits_info[item] = [results.get_final_parameters(), model_behaviour, cell_behaviour] diff --git a/thesis/figures/behaviour_correlations.png b/thesis/figures/behaviour_correlations.png index 8904979..b6b31b2 100644 Binary files a/thesis/figures/behaviour_correlations.png and b/thesis/figures/behaviour_correlations.png differ diff --git a/thesis/figures/fit_adaption_comparison.png b/thesis/figures/fit_adaption_comparison.png index f97dc61..f7aa785 100644 Binary files a/thesis/figures/fit_adaption_comparison.png and b/thesis/figures/fit_adaption_comparison.png differ diff --git a/thesis/figures/fit_baseline_comparison.png b/thesis/figures/fit_baseline_comparison.png index 9cb766b..827b14b 100644 Binary files a/thesis/figures/fit_baseline_comparison.png and b/thesis/figures/fit_baseline_comparison.png differ diff --git a/thesis/figures/fit_burstiness_comparison.png b/thesis/figures/fit_burstiness_comparison.png index c971c0f..3a5004b 100644 Binary files a/thesis/figures/fit_burstiness_comparison.png and b/thesis/figures/fit_burstiness_comparison.png differ diff --git a/thesis/figures/parameter_correlations.png b/thesis/figures/parameter_correlations.png index 9f2f5e7..1d1ee2f 100644 Binary files a/thesis/figures/parameter_correlations.png and b/thesis/figures/parameter_correlations.png differ