plots

ampullary.py

@@ -1,5 +1,4 @@
-
+from threefish.core_cell_choice import p_units_to_show, update_cell_names
-from threefish.utils0 import p_units_to_show, update_cell_names
 from threefish.plot_suscept import ampullary_punit
 
 if __name__ == '__main__':

cells_suscept.py

@@ -1,5 +1,5 @@
-from threefish.utils0 import p_units_to_show
+from threefish.core_cell_choice import p_units_to_show
-from threefish.utils1_suscept import fr_name_rm
+from threefish.core_plot_labels import label_fr_name_rm
 from threefish.plot_suscept import ampullary_punit
 
 if __name__ == '__main__':
@@ -7,4 +7,4 @@ if __name__ == '__main__':
 
     #stack_file = pd.read_csv('..\calc_RAM\calc_nix_RAM-eod_2022-01-28-ag-invivo-1_all__amp_20.0_filename_InputArr_400hz_30_P-unitApteronotusleptorhynchus.csv')
     cells_plot2 = p_units_to_show(type_here = 'contrasts')#permuted = True,
-    ampullary_punit(eod_metrice = False, color_same = False,base_extra = True, fr_name = fr_name_rm(),   cells_plot2=[cells_plot2[0]], isi_delta = 5, titles=[''],tags_individual = True, xlim_p = [0,1.15])#Low-CV P-unit,
+    ampullary_punit(eod_metrice = False, color_same = False, base_extra = True, fr_name = label_fr_name_rm(), cells_plot2=[cells_plot2[0]], isi_delta = 5, titles=[''], tags_individual = True, xlim_p = [0, 1.15])#Low-CV P-unit,

cells_suscept_high_CV.py

@@ -1,9 +1,9 @@
-from threefish.utils0 import p_units_to_show
+from threefish.core_cell_choice import p_units_to_show
-from threefish.utils1_suscept import fr_name_rm
+from threefish.core_plot_labels import label_fr_name_rm
 from threefish.plot_suscept import ampullary_punit
 
 
 if __name__ == '__main__':
 
     cells_plot2 = p_units_to_show(type_here='contrasts')#permuted = True,
-    ampullary_punit(base_extra = True,eod_metrice = False, color_same = False, fr_name = fr_name_rm(),  tags_individual = True, isi_delta = 5, cells_plot2=[cells_plot2[1]], titles=['', 'Ampullary cell,'],)#High-CV P-unit,
+    ampullary_punit(base_extra = True, eod_metrice = False, color_same = False, fr_name = label_fr_name_rm(), tags_individual = True, isi_delta = 5, cells_plot2=[cells_plot2[1]], titles=['', 'Ampullary cell,'], )#High-CV P-unit,

data_overview_mod.py

@@ -2,12 +2,17 @@ from IPython import embed
 from matplotlib import gridspec as gridspec, pyplot as plt
 import numpy as np
 
-from threefish.utils0 import basename_small, colors_overview, default_figsize, exclude_nans_for_corr, get_grid_4, \
+from threefish.core_cell_choice import update_cell_names
-    scatter_with_marginals_colorcoded, update_cell_names, \
+from threefish.core_filenames import version_final
-    load_overview_susept, \
+from threefish.core_plot_suscept import get_grid_4, scatter_with_marginals_colorcoded
-    make_log_ticks, save_visualization, setting_overview_score, version_final
+from threefish.defaults import default_figsize
-from threefish.core_plot_labels import pearson_label
+from threefish.core_plot_colors import colors_overview
-from threefish.utils1_suscept import plt_specific_cells, stimname_small, NLI_scorename2_small, start_name
+from threefish.core_reformat import exclude_nans_for_corr, load_overview_susept
+from threefish.core_load import save_visualization
+from threefish.core_bursts import setting_overview_score
+from threefish.core_plot_labels import basename_small, label_NLI_scorename2_small, label_pearson, label_stimname_small, \
+    make_log_ticks
+from threefish.utils1_suscept import plt_specific_cells, start_name
 from scipy import stats
 try:
     from plotstyle import plot_style, spines_params
@@ -126,14 +131,14 @@ def data_overview3():
         var_item_names = [var_it,var_it,var_it2]#,var_it2]#['Response Modulation [Hz]',]
         var_types = ['response_modulation','response_modulation','']#,'']#'response_modulation'
         max_x = max_xs[c]
-        x_axis_names = ['CV$'+basename_small()+'$','CV$'+stimname_small()+'$','Response Modulation [Hz]']#$'+basename()+'$,'Fr$'+basename()+'$',]
+        x_axis_names = ['CV$' + basename_small() +'$','CV$' + label_stimname_small() + '$', 'Response Modulation [Hz]']#$'+basename()+'$,'Fr$'+basename()+'$',]
         #score = scores[0]
         score_n = ['Perc99/Med', 'Perc99/Med', 'Perc99/Med']
         score = scores[c]
         scores_here = [score,score,score]#,score]
         score_name = ['max(diag5Hz)/med_diagonal_proj_fr','max(diag5Hz)/med_diagonal_proj_fr']#,'max(diag5Hz)/med_diagonal_proj_fr']#'Perc99/Med'
         score_name = ['Fr/Med', 'Fr/Med']#'Fr/Med']  # 'Perc99/Med'
-        score_name = [NLI_scorename2_small(), NLI_scorename2_small(), NLI_scorename2_small()]#NLI_scorename()]  # 'Fr/Med''Perc99/Med'
+        score_name = [label_NLI_scorename2_small(), label_NLI_scorename2_small(), label_NLI_scorename2_small()]#NLI_scorename()]  # 'Fr/Med''Perc99/Med'
         ax_j = []
         axls = []
         axss = []
@@ -246,7 +251,7 @@ def data_overview3():
                 print('frame file lost')
                 embed()
             corr, p_value = stats.pearsonr(x_axis, y_axis)
-            pears_l = pearson_label(corr, p_value, y_axis, n=True)
+            pears_l = label_pearson(corr, p_value, y_axis, n=True)
             print(start_name(cell_type_here, species) + ' ' + corr_var + ' to '+str(score) + pears_l)
             #if corr_var == 'ser_first_base':#
             #    embed()
@@ -256,7 +261,7 @@ def data_overview3():
         c_axis, x_axis, y_axis, exclude_here = exclude_nans_for_corr(frame_file, 'fr_base', cv_name='fr_base',
                                                                      score='cv_base')
         corr, p_value = stats.pearsonr(x_axis, y_axis)
-        pears_l = pearson_label(corr, p_value, y_axis, n=True)
+        pears_l = label_pearson(corr, p_value, y_axis, n=True)
         print(start_name(cell_type_here, species) + ' ' + 'fr_base' + ' to ' + 'cv_base' + pears_l)
 
 
@@ -266,7 +271,7 @@ def data_overview3():
         c_axis, x_axis, y_axis, exclude_here = exclude_nans_for_corr(frame_file, 'burst_fraction_burst_corr_individual_base', cv_name='burst_fraction_burst_corr_individual_base',
                                                                      score='cv_base')
         corr, p_value = stats.pearsonr(x_axis, y_axis)
-        pears_l = pearson_label(corr, p_value, y_axis, n=True)
+        pears_l = label_pearson(corr, p_value, y_axis, n=True)
         print(start_name(cell_type_here, species) + ' amprange: ' + 'burst_fraction_individual_base' + ' to ' + 'cv_base' + pears_l)
         ###############################
         # fr to nonline but for both modulations
@@ -274,7 +279,7 @@ def data_overview3():
         c_axis, x_axis, y_axis, exclude_here = exclude_nans_for_corr(frame_file, 'fr_base', cv_name='fr_base',
                                                                      score=score)
         corr, p_value = stats.pearsonr(x_axis, y_axis)
-        pears_l = pearson_label(corr, p_value, y_axis, n=True)
+        pears_l = label_pearson(corr, p_value, y_axis, n=True)
         print(start_name(cell_type_here, species) + ' amprange: ' + ' ' + 'fr_base' + ' to score' + pears_l)
         ##################################
         print('\n')

flowchart.py

@@ -1,18 +1,21 @@
 #from utils0import default_settings
 #from plt_RAM import model_and_data_isi, model_cells
-from plotstyle import plot_style
-from threefish.utils0 import default_figsize, save_visualization
-from threefish.plot_suscept import model_sheme_split2
 #from threefish.utils0 import default_settings, resave_small_files
 #from plt_RAM import model_and_data, model_and_data_sheme, model_and_data_vertical2
-import matplotlib.gridspec as gridspec
+# from threefish.utils0 import default_settings, resave_small_files
+# from plt_RAM import model_and_data, model_and_data_sheme, model_and_data_vertical2
+
+from threefish.plot_suscept import model_sheme_split2
+# from threefish.utils0 import default_settings, resave_small_files
+# from plt_RAM import model_and_data, model_and_data_sheme, model_and_data_vertical2
 # from threefish.utils0 import default_settings, resave_small_files
 # from plt_RAM import model_and_data, model_and_data_sheme, model_and_data_vertical2
 import matplotlib.gridspec as gridspec
 
 from plotstyle import plot_style
+from threefish.core_load import save_visualization
 from threefish.plot_suscept import model_sheme_split2
-from threefish.utils0 import default_figsize, save_visualization
+from threefish.defaults import default_figsize
 
 
 def flowchart():

model_and_data.py

@@ -7,18 +7,18 @@ from IPython import embed
 from matplotlib import gridspec, pyplot as plt
 
 from plotstyle import plot_style
-from threefish.utils0 import default_settings, find_cell_add, get_flowchart_params, load_model_susept, \
+from threefish.core_plot_subplots import plot_lowpass2, plt_single_square_modl, plt_time_arrays
-    nonlin_title, overlap_cells, \
+from threefish.core_plot_suscept import perc_model_full, plt_data_susept
-    perc_model_full, plot_lowpass2, plt_data_susept, plt_single_square_modl, plt_time_arrays, \
+from threefish.core_filenames import overlap_cells
-    remove_xticks, \
+from threefish.core_load import save_visualization
-    remove_yticks, \
+from threefish.core_reformat import get_flowchart_params, load_model_susept
-    save_visualization, set_same_ylim
+from threefish.core_calc_model import resave_small_files
-from threefish.core_calc_model import load_folder_name, resave_small_files
+from threefish.core import find_folder_name
-from threefish.core_plot_labels import noise_name
+from threefish.core_plot_labels import label_noise_name, nonlin_title, remove_xticks, remove_yticks, set_xlabel_arrow, \
+    set_ylabel_arrow, title_find_cell_add, xlabel_xpos_y_modelanddata
 import itertools as it
-from threefish.utils0 import default_figsize
+from threefish.defaults import default_figsize, default_settings
-from threefish.utils1_suscept import xpos_y_modelanddata
+from threefish.core_plot_lims import join_x, join_y, set_clim_same, set_same_ylim
-from threefish.utils0 import join_x, join_y, set_clim_same, set_xlabel_arrow, set_ylabel_arrow
 
 
 #from plt_RAM import model_and_data, model_and_data_sheme, model_and_data_vertical2
@@ -35,22 +35,10 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
                     contrasts=[0], noises_added=[''], D_extraction_method=['additiv_cv_adapt_factor_scaled'],
                     internal_noise=['RAM'], external_noise=['RAM'], level_extraction=[''], receiver_contrast=[1],
                     dendrids=[''], ref_types=[''], adapt_types=[''], c_noises=[0.1], c_signal=[0.9], cut_offs1=[300]):  # ['eRAM']
-    # plot_style()#['_RAMscaled']'_RAMscaled'
 
-    duration_noise = '_short',
-    formula = 'code'  ##'formula'
-    # ,int(2 ** 16) int(2 ** 16), int(2 ** 15),
     stimulus_length = 1  # 20#550  # 30  # 15#45#0.5#1.5 15 45 100
     trials_nrs = [1]  # [100, 500, 1000, 3000, 10000, 100000, 1000000]  # 500
-    stimulus_type = '_StimulusOrig_'  # ,#
-    # ,3]#, 3, 1, 1.5, 0.5, ]  # ,1,1.5, 0.5] #[1,1.5, 0.5] # 1.5,0.5]3, 1,
-    variant = 'sinz'
-    mimick = 'no'
-    cell_recording_save_name = ''
-    trans = 1  # 5
     rep = 1000000  # 500000#0
-    repeats = [20, rep]  # 250000
-    aa = 0
     good_data, remaining = overlap_cells()
     cells_all = [good_data[0]]
 
@@ -64,8 +52,7 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
     mins = []
     mats = []
     ims = []
-    perc05 = []
+
-    perc95 = []
     iternames = [D_extraction_method, external_noise,
                  internal_noise, powers, nffts, dendrids, cut_offs1, trials_nrs, c_signal,
                  c_noises,
@@ -95,28 +82,16 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
 
         grid_data = gridspec.GridSpecFromSubplotSpec(1, 1, grid[0, 0],
                                                      hspace=hs)
-
+        fr_print = False
-        fr_print = False  #True
-        #ypos_x_modelanddata()
         nr = 1
         ax_data, stack_spikes_all, eod_frs = plt_data_susept(fig, grid_data, cells_all, cell_type='p-unit', width=width,
                                                              cbar_label=True, fr_print=fr_print,
                                                              eod_metrice=eod_metrice, nr=nr, amp_given=1, xlabel=False,
                                                              lp=lp, title=True)
         for ax_external in ax_data:
-            # ax.set_ylabel(F2_xlabel())
-            # remove_xticks(ax)
             ax_external.set_xticks_delta(100)
-            set_ylabel_arrow(ax_external, xpos=xpos_y_modelanddata(), ypos=0.87)
+            set_ylabel_arrow(ax_external, xpos=xlabel_xpos_y_modelanddata(), ypos=0.87)
-
-            #embed()
             set_xlabel_arrow(ax_external, ypos=ypos_x_modelanddata())
-            # ax.text(-0.42, 0.87, F2_xlabel(), ha='center', va='center',
-            #        transform=ax.transAxes, rotation = 90)
-            # ax.text(1.66, 0.5, nonlin_title(), rotation=90, ha='center', va='center',
-            #        transform=ax.transAxes)
-
-            #ax_external.arrow_spines('lb')
 
         #embed()
         #plt.show()
@@ -128,7 +103,7 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
         cell = '2012-07-03-ak-invivo-1'
         print('cell' + str(cell))
         cells_given = [cell]
-        save_name_rev = load_folder_name(
+        save_name_rev = find_folder_name(
             'calc_model') + '/' + 'calc_RAM_model-2__nfft_whole_power_1_RAM_additiv_cv_adapt_factor_scaled_cNoise_0.1_cSig_0.9_cutoff1_300_cutoff2_300no_sinz_length1_TrialsStim_' + str(
             trial_nr) + '_a_fr_1__trans1s__TrialsNr_1_fft_o_forward_fft_i_forward_Hz_mV_revQuadrant_'
         # for trial in trials:#.009
@@ -164,7 +139,10 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
         # Hier werde ich nun mit dem Fehler von 0.36 verfahren
         # das bedeutet aber das sich den Stimulus zwar mit 0.009 ins Modell reintue später für die
         # Susceptiblitätsberechnung sollte ich ihn aber um den Faktor 0.36 teilen
-        bias_factor = 0.36
+
+        # oben habe ich einen bias factor weil die Zelle zu sensitiv gefittet ist, also passe ich das an dass die den
+        # gleichen CV und feurrate hat, wie die Zelle in der Stimulation, deswegen ist dieser Bias faktor nur oben!
+        bias_factors = [0.36, 0.36, 1, 1]#0.36
         save_names = [
             'calc_RAM_model-2__nfft_whole_power_1_afe_0.009_RAM_cutoff1_300_cutoff2_300no_sinz_length1_TrialsStim_11_a_fr_1__trans1s__TrialsNr_1_fft_o_forward_fft_i_forward_Hz_mV',
             'calc_RAM_model-2__nfft_whole_power_1_afe_0.009_RAM_cutoff1_300_cutoff2_300no_sinz_length1_TrialsStim_' + str(
@@ -187,8 +165,8 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
         c = 2.5
         cs = ['$c=%.1f$' % c + '$\,\%$', '$c=0\,\%$']
         titles = ['Model\n$N=11$', 'Model\n' + '$N=10^6$',
-                  'Model\,(' + noise_name().lower() + ')' + '\n' + '$N=11$',
+                  'Model\,(' + label_noise_name().lower() + ')' + '\n' + '$N=11$',
-                  'Model\,(' + noise_name().lower() + ')' + '\n' + '$N=10^6$'
+                  'Model\,(' + label_noise_name().lower() + ')' + '\n' + '$N=10^6$'
                   ]  #%#%s$' % (tr_name) + '\,million'
         #'Model\,('+noise_name().lower()+')' + '\n' + '$N=11$\n $c=1\,\%$',$N=%s $' % (tr_name) +'\,million'
         #          'Model\,('+noise_name().lower()+')' + '\n' + '$N=%s$' % (tr_name) + '\,million\n $c=1\,\%$ '
@@ -202,28 +180,28 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
                 embed()
             ax_model.append(ax_external)
 
-            save_name = load_folder_name('calc_model') + '/' + sav_name
+            save_name = find_folder_name('calc_model') + '/' + sav_name
 
-            cell_add, cells_save = find_cell_add(cells_given)
+            cell_add, cells_save = title_find_cell_add(cells_given)
             perc = 'perc'
 
             path = save_name + '.pkl'  # '../'+
-            # stack = get_stack_one_quadrant(cell, cell_add, cells_save, path, save_name)
+            # model = get_stack_one_quadrant(cell, cell_add, cells_save, path, save_name)
 
-            # full_matrix = create_full_matrix2(np.array(stack), np.array(stack_rev))
+            # full_matrix = create_full_matrix2(np.array(model), np.array(stack_rev))
-            # stack_final = get_axis_on_full_matrix(full_matrix, stack)
+            # stack_final = get_axis_on_full_matrix(full_matrix, model)
-            # im = plt_RAM_perc(ax, perc, np.abs(stack))
+            # im = plt_RAM_perc(ax, perc, np.abs(model))
 
-            stack = load_model_susept(path, cells_save, save_name.split(r'/')[-1] + cell_add)
+            model = load_model_susept(path, cells_save, save_name.split(r'/')[-1] + cell_add)
 
             #embed()
-            if len(stack) > 0:
+            if len(model) > 0:
-                add_nonlin_title, cbar, fig, stack_plot, im = plt_single_square_modl(ax_external, cell, stack, perc,
+                add_nonlin_title, cbar, fig, stack_plot, im = plt_single_square_modl(ax_external, cell, model, perc,
                                                                                      titles[s],
                                                                                      width, eod_metrice=eod_metrice,
                                                                                      titles_plot=True,
                                                                                      resize=True,
-                                                                                     bias_factor=bias_factor,
+                                                                                     bias_factor=bias_factors[s],
                                                                                      fr_print=fr_print, nr=nr)
 
                 # if s in [1,3,5]:
@@ -242,7 +220,7 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
                 if s in np.arange(col - 1, 100, col):  # | (s == 0)
                     remove_yticks(ax_external)
                 else:
-                    set_ylabel_arrow(ax_external, xpos=xpos_y_modelanddata(), ypos=0.87)
+                    set_ylabel_arrow(ax_external, xpos=xlabel_xpos_y_modelanddata(), ypos=0.87)
 
                 if s >= row * col - col:
                     set_xlabel_arrow(ax_external, ypos=ypos_x_modelanddata())
@@ -258,15 +236,44 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
         #################################################
         # Flowcharts
 
-        var_types = ['', 'additiv_cv_adapt_factor_scaled']  #'additiv_cv_adapt_factor_scaled',
+        ax_ams, ax_external = plt_model_flowcharts(a_fr, ax_external, c, cs, grid, model, stimulus_length)
+
+        set_same_ylim(ax_ams, up='up')
+
+        axes = np.concatenate([ax_data, ax_model])
+
+        axes = [ax_ams[0], axes[1], axes[2], ax_ams[1], axes[3], axes[4], ]  #ax_ams[2], axes[5], axes[6],
+        #axd1 = plt.subplot(grid[1, 1])
+        #axd2 = plt.subplot(grid[2, 1])
+        #ax_data.extend([,])
+        #axd1.show_spines('')
+        #axd2.show_spines('')
+        #embed()
+        #axes = [[ax_ams[0],ax_data[0],axes[2], axes[3]],[ax_ams[1],axd1,axes[4], axes[5]],[axd2,axd2, axes[6],  axes[7]]]
+
+        fig.tag([ax_data], xoffs=-3, yoffs=1.6)  # ax_ams[3],
+        fig.tag([axes[0:3]], xoffs=-3, yoffs=1.6)  # ax_ams[3],
+        #fig.tag([[axes[4]]], xoffs=-3, yoffs=1.6, minor_index=0)  # ax_ams[3],
+        fig.tag([axes[3:6]], xoffs=-3, yoffs=1.6)  #, major_index = 1, minor_index = 2 ax_ams[3],
+        #fig.tag([[axes[7]]], xoffs=-3, yoffs=1.6, major_index=2,minor_index=0)  # ax_ams[3],
+        #fig.tag([axes[8::]], xoffs=-3, yoffs=1.6, major_index=2, minor_index=2)  # ax_ams[3],
+        #fig.tag([axes[7::]], xoffs=-3, yoffs=1.6)  # ax_ams[3],
+
+        #fig.tag([ax_ams[0],ax_data[0],axes[2], axes[3]], xoffs=-3, yoffs=1.6)#ax_ams[3],
+
+        save_visualization(pdf=True)
+
+
+def plt_model_flowcharts(a_fr, ax_external, c, cs, grid, stack, stimulus_length):
+    var_types = ['', 'additiv_cv_adapt_factor_scaled']  # 'additiv_cv_adapt_factor_scaled',
     ##additiv_cv_adapt_factor_scaled
-        a_fes = [c / 100, 0]  #, 0.009
+    a_fes = [c / 100, 0]  # , 0.009
-        eod_fe = [750, 750]  #, 750
+    eod_fe = [750, 750]  # , 750
     ylim = [-0.5, 0.5]
-        c_sigs = [0, 0.9]  #, 0.9
+    c_sigs = [0, 0.9]  # , 0.9
-        grid_left = [[], grid[1, 0]]  #, grid[2, 0]
+    grid_left = [[], grid[1, 0]]  # , grid[2, 0]
     ax_ams = []
-        for g, grid_here in enumerate([grid[0, 2], grid[1, 2]]):  #, grid[2, 0]
+    for g, grid_here in enumerate([grid[0, 2], grid[1, 2]]):  # , grid[2, 0]
         grid_lowpass = gridspec.GridSpecFromSubplotSpec(4, 1,
                                                         subplot_spec=grid_here, hspace=0.2,
                                                         height_ratios=[1, 1, 1, 0.1])
@@ -298,10 +305,10 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
             ax_intrinsic.show_spines('l')
             ax_external.show_spines('l')
             # ax_ams.append(axt_p2)
-                #color_timeseries = 'black'
+            # color_timeseries = 'black'
-                #axt_p2.set_xlabel('Time [ms]')
+            # axt_p2.set_xlabel('Time [ms]')
-                #axt_p2.text(-0.6, 0.5, '$\%$', rotation=90, va='center', transform=axt_p2.transAxes)
+            # axt_p2.text(-0.6, 0.5, '$\%$', rotation=90, va='center', transform=axt_p2.transAxes)
-                #ax_ams.append(axt_p2)
+            # ax_ams.append(axt_p2)
             vers = 'all'
         elif len(np.unique(frame.RAM_afe)) > 1:
             color_timeseries = 'red'
@@ -366,8 +373,8 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
                                                    extract=False, color1='grey', lw=1)
         remove_yticks(ax_n)
         if g == 1:
-                #ax_n.set_xlabel('Time [ms]', labelpad=-0.5)
+            # ax_n.set_xlabel('Time [ms]', labelpad=-0.5)
-                ax_n.text(0.5, xpos_y_modelanddata()*3, 'Time [ms]', transform = ax_n.transAxes, ha = 'center')
+            ax_n.text(0.5, xlabel_xpos_y_modelanddata() * 3, 'Time [ms]', transform=ax_n.transAxes, ha='center')
         else:
             remove_xticks(ax_n)
         ax_n.set_ylim(ylim)
@@ -391,32 +398,9 @@ def model_and_data2(eod_metrice=False, width=0.005, nffts=['whole'], powers=[1],
         ax_external.tick_params(axis='y', which='major', labelsize=8.4)
         ax_intrinsic.tick_params(axis='y', which='major', labelsize=8.4)
         ax_n.tick_params(axis='y', which='major', labelsize=8.4)
-            #xtick_labelsize =
+        # xtick_labelsize =
-            #embed()
+        # embed()
-        set_same_ylim(ax_ams, up='up')
+    return ax_ams, ax_external
-
-        axes = np.concatenate([ax_data, ax_model])
-
-        axes = [ax_ams[0], axes[1], axes[2], ax_ams[1], axes[3], axes[4], ]  #ax_ams[2], axes[5], axes[6],
-        #axd1 = plt.subplot(grid[1, 1])
-        #axd2 = plt.subplot(grid[2, 1])
-        #ax_data.extend([,])
-        #axd1.show_spines('')
-        #axd2.show_spines('')
-        #embed()
-        #axes = [[ax_ams[0],ax_data[0],axes[2], axes[3]],[ax_ams[1],axd1,axes[4], axes[5]],[axd2,axd2, axes[6],  axes[7]]]
-
-        fig.tag([ax_data], xoffs=-3, yoffs=1.6)  # ax_ams[3],
-        fig.tag([axes[0:3]], xoffs=-3, yoffs=1.6)  # ax_ams[3],
-        #fig.tag([[axes[4]]], xoffs=-3, yoffs=1.6, minor_index=0)  # ax_ams[3],
-        fig.tag([axes[3:6]], xoffs=-3, yoffs=1.6)  #, major_index = 1, minor_index = 2 ax_ams[3],
-        #fig.tag([[axes[7]]], xoffs=-3, yoffs=1.6, major_index=2,minor_index=0)  # ax_ams[3],
-        #fig.tag([axes[8::]], xoffs=-3, yoffs=1.6, major_index=2, minor_index=2)  # ax_ams[3],
-        #fig.tag([axes[7::]], xoffs=-3, yoffs=1.6)  # ax_ams[3],
-
-        #fig.tag([ax_ams[0],ax_data[0],axes[2], axes[3]], xoffs=-3, yoffs=1.6)#ax_ams[3],
-
-        save_visualization(pdf=True)
 
 
 def start_pos_modeldata():

motivation.py

@@ -1,14 +1,17 @@
 ##from update_project import **
 import numpy as np
 
-from threefish.utils0 import chose_mat_max_value, cr_spikes_mat, default_figsize, find_all_dir_cells, \
+from threefish.core_cell_choice import find_all_dir_cells
-    plot_arrays_ROC_psd_single3, plot_shemes4, plt_coherences, save_visualization
+from threefish.core_reformat import chose_mat_max_value, load_b_public
-from threefish.core_calc_model import find_code_vs_not
+from threefish.core_plot_suscept import plt_coherences
+from threefish.defaults import default_figsize
+from threefish.core_time import cr_spikes_mat
+from threefish.core import find_code_vs_not
 import time
-from threefish.utils1_suscept import check_var_substract_method, chose_certain_group, circle_plot, colors_suscept_paper_dots, \
+from threefish.utils1_suscept import check_var_substract_method, chose_certain_group, circle_plot, extract_waves, load_cells_three, predefine_grouping_frame, restrict_cell_type, save_arrays_susept, ws_nonlin_systems
-    extract_waves, load_cells_three, predefine_grouping_frame, restrict_cell_type, save_arrays_susept, title_motivation, \
+from threefish.core_plot_labels import title_motivation
-    ws_nonlin_systems
+from threefish.core_plot_subplots import colors_suscept_paper_dots, plot_arrays_ROC_psd_single3, plot_shemes4
-from threefish.utils0 import load_b_public
+from threefish.core_load import save_visualization
 
 #from matplotlib import gridspec as gridspec, gridspec, mlab as ml, pyplot as plt, ticker as ticker
 from matplotlib import pyplot as plt

trialnr.py

@@ -4,10 +4,13 @@ import numpy as np
 import pandas as pd
 from matplotlib import pyplot as plt
 from plotstyle import plot_style
-from threefish.utils0 import default_figsize, default_settings, find_cell_add, get_stack, load_model_susept, \
+from threefish.core_plot_labels import title_find_cell_add
-    overlap_cells, \
+from threefish.defaults import default_figsize, default_settings
-    save_visualization  # utils0_project
+from threefish.core_filenames import overlap_cells
-from threefish.core_calc_model import load_folder_name, resave_small_files
+from threefish.core_load import save_visualization
+from threefish.core_reformat import get_stack, load_model_susept
+from threefish.core_calc_model import resave_small_files
+from threefish.core import find_folder_name
 from threefish.utils1_suscept import trial_nrs_ram_model
 import itertools as it
 
@@ -89,7 +92,7 @@ def trialnr(nffts=['whole'], powers=[1], contrasts=[0], noises_added=[''], D_ext
         cell = '2012-07-03-ak-invivo-1'
         print('cell'+str(cell))
         cells_given = [cell]
-        save_name_rev = load_folder_name(
+        save_name_rev = find_folder_name(
             'calc_model') + '/' + 'calc_RAM_model-2__nfft_whole_power_1_RAM_additiv_cv_adapt_factor_scaled_cNoise_0.1_cSig_0.9_cutoff1_300_cutoff2_300no_sinz_length1_TrialsStim_' + str(
             trial_nr) + '_a_fr_1__trans1s__TrialsNr_1_fft_o_forward_fft_i_forward_Hz_mV_revQuadrant_'
         # for trial in trials:#.009
@@ -121,9 +124,9 @@ def trialnr(nffts=['whole'], powers=[1], contrasts=[0], noises_added=[''], D_ext
 
             for s, sav_name in enumerate(save_names):
 
-                save_name = load_folder_name('calc_model') + '/' + sav_name
+                save_name = find_folder_name('calc_model') + '/' + sav_name
 
-                cell_add, cells_save = find_cell_add(cells_given)
+                cell_add, cells_save = title_find_cell_add(cells_given)
                 perc = 'perc'
 
                 path = save_name + '.pkl'  # '../'+

update_project.py

@@ -130,9 +130,9 @@ if cont_other_dir == False:
                             embed()
                         #print(new_dir+dir)
                         #try:
-                        shutil.copy2("../suseptibility/" + dir, new_dir + directory)
+                        shutil.copy2("../suseptibility/" + directory,new_dir + directory)
                         #print(new_dir + directory)
-                        #shutil.copy("../suseptibility/" + dir, new_dir + directory)
+                        #shutil.copy("../suseptibility/" + directory,new_dir + directory)
                         #shutil.copyfile("../suseptibility/"+dir, new_dir+dir)
                         #except:
                         #    print('shutil stuff')