ladbar machen

data_overview_mod.py

@@ -1,3 +1,6 @@
+import cProfile
+import pstats
+
 from IPython import embed
 from matplotlib import gridspec as gridspec, pyplot as plt
 import numpy as np
@@ -391,4 +394,7 @@ def printing_values_data_overview(cell_types, frame_load_sp, scores, species, x_
 
 if __name__ == '__main__':
 
+
+
+
     data_overview3()

model_full.py

@@ -1,4 +1,6 @@
 ##from update_project import **
+import cProfile
+import pstats
 import sys
 
 import numpy as np
@@ -630,5 +632,13 @@ def plt_data_full_model(c1, chose_score, detections, devs, dfs, end, grid, mult_
 
 if __name__ == '__main__':
     #embed()
+
+    #cells_plot2 = p_units_to_show(type_here='amp')  # permuted = True,
+    cProfile.run('model_full()', 'profiling_results')
+    p = pstats.Stats('profiling_results')
+    p.sort_stats('cumulative').print_stats(100)
+    p.sort_stats('cumulative').print_stats(400)
+    p.sort_stats('tottime').print_stats(400)
+    embed()
     sys.excepthook = info
     model_full()

nonlin_regime.py

@@ -14,6 +14,7 @@ from threefish.load import load_savedir, resave_small_files, save_visualization
 from threefish.plot.limits import join_x, join_y, set_same_ylim
 from threefish.RAM.calc_fft import log_calc_psd
 from threefish.RAM.calc_model import chose_old_vs_new_model
+from threefish.RAM.core import find_load_function
 from threefish.RAM.plot_labels import label_deltaf1, label_deltaf2, label_diff, label_f_eod_name_core_rm, \
     label_fbasename_small, label_sum, \
     onebeat_cond, \
@@ -130,7 +131,14 @@ def nonlin_regime(yposs=[450, 450, 450], printing=False, beat='',
                                                        wspace=0.1,
                                                        subplot_spec=grid00[1])  # 1.2hspace=0.4,wspace=0.2,len(chirps)
             for i, full_name in enumerate(full_names):
-                frame = pd.read_csv(find_folder_name('calc_cocktailparty') + '/' + full_name + '.csv')
+
+                if os.path.exists(find_folder_name('calc_cocktailparty') + '/' + full_name + '.csv'):
+                    frame = pd.read_csv(find_folder_name('calc_cocktailparty') + '/' + full_name + '.csv')
+                    load_function = find_load_function()
+                    frame.to_csv(find_project_data() +load_function+'traces.csv')
+                else:
+                    frame = pd.to_csv(find_project_data() +load_function+'traces')#resave_small_files(full_name + '.csv', load_folder='calc_cocktailparty')
+                #
 
                 frame_cell_orig = frame[(frame.cell == cell_here)]
                 if len(frame_cell_orig) > 0: