Minor figure updates 02.03.2022

Figures/AUC_correlation.py

@@ -4,20 +4,15 @@ Created on Sat Jul  3 19:52:04 2021
 
 @author: nils
 """
-import seaborn as sns
-import matplotlib.pyplot as plt
 import pandas as pd
 import numpy as np
 import string
 import textwrap
 import json
 import matplotlib
-import matplotlib.cm as cm
 import matplotlib.lines as mlines
 from matplotlib import ticker
-from matplotlib.collections import LineCollection
-from matplotlib.ticker import StrMethodFormatter, NullFormatter
-from plotstyle import boxplot_style
+from matplotlib.ticker import NullFormatter
 
 #%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ##
 # to change marker types in seaborn swarmplot
@@ -28,7 +23,6 @@ import matplotlib.pyplot as plt
 ############## Begin hack ##############
 from matplotlib.axes._axes import Axes
 from matplotlib.markers import MarkerStyle
-from seaborn import color_palette
 from numpy import ndarray
 
 def GetColor2Marker(markers):
@@ -444,7 +438,7 @@ plot_AUC_alt(ax1_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='l
 plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='g')
 
 #save
-fig.savefig('AUC_correlation.pdf', bbox_inches='tight', dpi=fig.dpi)
+fig.savefig('./Figures/AUC_correlation.pdf', bbox_inches='tight', dpi=fig.dpi)
 plt.show()
 
 # #%% alternative layout

Figures/diversity_in_firing.py

@@ -178,7 +178,7 @@ for i in range(0,len(models)):
     spike_axs[i].text(-0.18, 1.08, string.ascii_uppercase[i], transform=spike_axs[i].transAxes, size=16, weight='bold')
 
 # save
-fig.savefig('diversity_in_firing.pdf', bbox_inches='tight')
+fig.savefig('./Figures/diversity_in_firing.pdf', bbox_inches='tight')
 plt.show()
 
 

Figures/firing_characterization.py

@@ -103,7 +103,7 @@ $\uparrow$ rheobase''')
 ax3_BR = ax3.inset_axes([0.7, 0, 0.3, 0.2])
 plot_diff_sqrt(ax3_BR, b2=0.4, c2=75)
 ax3_BR.set_ylim(inset_ylim)
-fig.savefig('firing_characterization.pdf', bbox_inches='tight')
+fig.savefig('./Figures/firing_characterization.pdf', bbox_inches='tight')
 plt.show()
 
 

Figures/ramp_examples.py

@@ -131,5 +131,5 @@ add_scalebar(ax11_ramp, matchx=False, matchy=False, hidex=True, hidey=True, size
 for i in range(0,len(models)):
     ramp_axs[i].text(-0.05, 1.08, string.ascii_uppercase[i], transform=ramp_axs[i].transAxes, size=16, weight='bold')
 
-fig.savefig('ramp_firing.pdf')
+fig.savefig('./Figures/ramp_firing.pdf')
 plt.show()

Figures/rheobase_correlation.py

@@ -4,20 +4,15 @@ Created on Sat Jul  3 19:52:04 2021
 
 @author: nils
 """
-import seaborn as sns
-import matplotlib.pyplot as plt
 import pandas as pd
 import numpy as np
 import string
 import textwrap
 import json
 import matplotlib
-import matplotlib.cm as cm
 import matplotlib.lines as mlines
 from matplotlib import ticker
-from matplotlib.collections import LineCollection
-from matplotlib.ticker import StrMethodFormatter, NullFormatter
-from plotstyle import boxplot_style
+from matplotlib.ticker import NullFormatter
 
 #%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ##
 # to change marker types in seaborn swarmplot
@@ -28,7 +23,6 @@ import matplotlib.pyplot as plt
 ############## Begin hack ##############
 from matplotlib.axes._axes import Axes
 from matplotlib.markers import MarkerStyle
-from seaborn import color_palette
 from numpy import ndarray
 
 def GetColor2Marker(markers):
@@ -413,7 +407,7 @@ plot_rheo_alt(ax1_ex,model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
 plot_rheo_alt(ax2_ex, model='Cb stellate', color1='lightgrey', color2='k', alteration='g')
 
 # save
-fig.savefig('rheobase_correlation.pdf', bbox_inches='tight')
+fig.savefig('./Figures/rheobase_correlation.pdf', bbox_inches='tight')
 plt.show()
 
 # #%% alternative layout

Figures/simulation_model_comparison.py

@@ -1,14 +1,9 @@
 import numpy as np
 import matplotlib.pyplot as plt
-from matplotlib.collections import LineCollection
-import os
-import json
-import matplotlib.cm as cm
 import pandas as pd
 import os
 import string
 from plotstyle import plot_style
-from adjustText import adjust_text
 import seaborn as sns
 import scipy.stats as stats
 import matplotlib.lines as mlines
@@ -27,7 +22,13 @@ def Kendall_tau(df):
 
 def correlation_plot(ax, df='AUC', title='', cbar=False):
     cbar_ax = fig.add_axes([0.94, .25, .03, .4])
-
+    cbar_ax.spines['left'].set_visible(False)
+    cbar_ax.spines['bottom'].set_visible(False)
+    cbar_ax.spines['right'].set_visible(False)
+    cbar_ax.spines['top'].set_visible(False)
+    # cbar_ax.axis('off')
+    cbar_ax.set_xticks([])
+    cbar_ax.set_yticks([])
     if df == 'AUC':
         df = pd.read_csv(os.path.join('./Figures/Data/sim_mut_AUC.csv'), index_col='Unnamed: 0')
     elif df == 'rheo':
@@ -168,8 +169,9 @@ def mutation_legend(ax, marker_s_leg, pos, ncol):
     E283K = mlines.Line2D([], [], color=colors[2], marker=Markers[2], markersize=marker_s_leg, linestyle='None', label='E283K')
     V404I = mlines.Line2D([], [], color=colors[5], marker=Markers[3], markersize=marker_s_leg, linestyle='None',
                          label='V404I')
+    WT = mlines.Line2D([], [], color='k', marker='s', markersize=marker_s_leg+5, linestyle='None', label='Wild type')
 
-    ax.legend(handles=[V174F, F414C, E283K, V404I], loc='center', bbox_to_anchor=pos, ncol=ncol, frameon=False)
+    ax.legend(handles=[WT, V174F, F414C, E283K, V404I], loc='center', bbox_to_anchor=pos, ncol=ncol, frameon=False)
 
 
 
@@ -207,7 +209,7 @@ ax22 = mutation_plot2(ax22, model='STN_Kv_only')
 
 marker_s_leg = 4
 pos = (0.25, -0.45)
-ncol = 4
+ncol = 5
 mutation_legend(ax21, marker_s_leg, pos, ncol)
 
 # plot correlation matrices
@@ -224,5 +226,5 @@ axr0.text(-0.38, 1.2, string.ascii_uppercase[j], transform=axr0.transAxes, size=
 axr1.text(-0.38, 1.2, string.ascii_uppercase[j+1], transform=axr1.transAxes, size=16, weight='bold')
 
 # save
-fig.savefig('simulation_model_comparison.pdf', bbox_inches='tight')
+fig.savefig('./Figures/simulation_model_comparison.pdf', bbox_inches='tight')
 plt.show()