update figures based on discussion with Jan and Lukas and added gmax distribution figure

Figures/diversity_in_firing.py

@@ -140,7 +140,7 @@ gs00 = gs0[:,0].subgridspec(5, 3, wspace=1.8, hspace=1.5)
 gs01 = gs0[:,1].subgridspec(5, 3, wspace=1.8, hspace=1.5)
 gs02 = gs0[:,2].subgridspec(5, 3, wspace=1.8, hspace=1.5)
 
-ax_diag = fig.add_subplot(gs02[:3, :])
+ax_diag = fig.add_subplot(gs02[2:, :])
 import matplotlib.image as mpimg
 img = mpimg.imread('./Figures/model_diagram2.png')
 ax_diag.imshow(img)
@@ -156,26 +156,26 @@ ax1_spikes = fig.add_subplot(gs00[0,0:2])
 ax1_fI = fig.add_subplot(gs00[0, 2])
 ax2_spikes = fig.add_subplot(gs01[0,0:2])
 ax2_fI = fig.add_subplot(gs01[0, 2])
-ax3_spikes = fig.add_subplot(gs00[1,0:2])
-ax3_fI = fig.add_subplot(gs00[1, 2])
-ax4_spikes = fig.add_subplot(gs01[1,0:2])
-ax4_fI = fig.add_subplot(gs01[1, 2])
-ax5_spikes = fig.add_subplot(gs00[2, 0:2])
-ax5_fI = fig.add_subplot(gs00[2,  2])
-ax6_spikes = fig.add_subplot(gs01[2, 0:2])
-ax6_fI = fig.add_subplot(gs01[2,  2])
-ax7_spikes = fig.add_subplot(gs00[3,0:2])
-ax7_fI = fig.add_subplot(gs00[3, 2])
-ax8_spikes = fig.add_subplot(gs01[3,0:2])
-ax8_fI = fig.add_subplot(gs01[3, 2])
-ax9_spikes = fig.add_subplot(gs00[4,0:2])
-ax9_fI = fig.add_subplot(gs00[4, 2])
-ax10_spikes = fig.add_subplot(gs01[4,0:2])
-ax10_fI = fig.add_subplot(gs01[4, 2])
-ax11_spikes = fig.add_subplot(gs02[3,0:2])
-ax11_fI = fig.add_subplot(gs02[3, 2])
-ax12_spikes = fig.add_subplot(gs02[4,0:2])
-ax12_fI = fig.add_subplot(gs02[4, 2])
+ax3_spikes = fig.add_subplot(gs02[0,0:2])
+ax3_fI = fig.add_subplot(gs02[0, 2])
+ax4_spikes = fig.add_subplot(gs00[1,0:2])
+ax4_fI = fig.add_subplot(gs00[1, 2])
+ax5_spikes = fig.add_subplot(gs01[1, 0:2])
+ax5_fI = fig.add_subplot(gs01[1,  2])
+ax6_spikes = fig.add_subplot(gs02[1,0:2])
+ax6_fI = fig.add_subplot(gs02[1, 2])
+ax7_spikes = fig.add_subplot(gs00[2,0:2])
+ax7_fI = fig.add_subplot(gs00[2, 2])
+ax8_spikes = fig.add_subplot(gs01[2,0:2])
+ax8_fI = fig.add_subplot(gs01[2, 2])
+ax9_spikes = fig.add_subplot(gs00[3,0:2])
+ax9_fI = fig.add_subplot(gs00[3, 2])
+ax10_spikes = fig.add_subplot(gs01[3,0:2])
+ax10_fI = fig.add_subplot(gs01[3, 2])
+ax11_spikes = fig.add_subplot(gs00[4,0:2])
+ax11_fI = fig.add_subplot(gs00[4, 2])
+ax12_spikes = fig.add_subplot(gs01[4, 0:2])
+ax12_fI = fig.add_subplot(gs01[4,  2])
 
 spike_axs = [ax1_spikes, ax2_spikes, ax3_spikes, ax4_spikes, ax5_spikes,ax6_spikes, ax7_spikes, ax8_spikes,
               ax11_spikes,ax9_spikes,ax10_spikes,   ax12_spikes]#, ax13_spikes, ax14_spikes]
@@ -195,12 +195,12 @@ for i in range(len(models)):
     plot_fI(fI_axs[i], model=models[i])
 
 # add scalebars
-add_scalebar(ax9_spikes, matchx=False, matchy=False, hidex=True, hidey=True, sizex=100, sizey=50, labelx='100\u2009ms',
+add_scalebar(ax6_spikes, matchx=False, matchy=False, hidex=True, hidey=True, sizex=100, sizey=50, labelx='100\u2009ms',
                  labely='50\u2009mV', loc=3, pad=-0.5, borderpad=-1.0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.275, -0.05, 1, 1),
-                          bbox_transform=ax9_spikes.transAxes)
-add_scalebar(ax10_spikes, matchx=False, matchy=False, hidex=True, hidey=True, sizex=100, sizey=50, labelx='100\u2009ms',
+                          bbox_transform=ax6_spikes.transAxes)
+add_scalebar(ax11_spikes, matchx=False, matchy=False, hidex=True, hidey=True, sizex=100, sizey=50, labelx='100\u2009ms',
                  labely='50\u2009mV', loc=3, pad=-0.5, borderpad=-1.0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.275, -0.05, 1, 1),
-                          bbox_transform=ax10_spikes.transAxes)
+                          bbox_transform=ax11_spikes.transAxes)
 add_scalebar(ax12_spikes, matchx=False, matchy=False, hidex=True, hidey=True, sizex=100, sizey=50, labelx='100\u2009ms',
                  labely='50\u2009mV', loc=3, pad=-0.5, borderpad=-1.0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.275, -0.05, 1, 1),
                           bbox_transform=ax12_spikes.transAxes)

Figures/model_g.py

@@ -0,0 +1,177 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.ticker as ticker
+import string
+from plotstyle import scheme_style
+import pandas as pd
+from matplotlib import cm
+
+def cm2inch(*tupl):
+    inch = 2.54
+    if isinstance(tupl[0], tuple):
+        return tuple(i / inch for i in tupl[0])
+    else:
+        return tuple(i / inch for i in tupl)
+
+
+def show_spines(ax, spines='lrtb'):
+    """ Show and hide spines.
+
+    From github.com/janscience/plottools.git  spines.py
+
+    Parameters
+    ----------
+    ax: matplotlib figure, matplotlib axis, or list of matplotlib axes
+        Axis on which spine and ticks visibility is manipulated.
+        If figure, then apply manipulations on all axes of the figure.
+        If list of axes, apply manipulations on each of the given axes.
+    spines: string
+        Specify which spines and ticks should be shown.
+        All other ones or hidden.
+        'l' is the left spine, 'r' the right spine,
+        't' the top one and 'b' the bottom one.
+        E.g. 'lb' shows the left and bottom spine, and hides the top
+        and and right spines, as well as their tick marks and labels.
+        '' shows no spines at all.
+        'lrtb' shows all spines and tick marks.
+
+    Examples
+    --------
+    ```py
+    import matplotlib.pyplot as plt
+    import plottools.spines
+
+    fig, (ax0, ax1, ax2) = plt.subplots(1, 3)
+    ax0.show_spines('lb')
+    ax1.show_spines('bt')
+    ax2.show_spines('tr')
+    ```
+    ![show](figures/spines-show.png)
+    """
+    # collect spine visibility:
+    xspines = []
+    if 't' in spines:
+        xspines.append('top')
+    if 'b' in spines:
+        xspines.append('bottom')
+    yspines = []
+    if 'l' in spines:
+        yspines.append('left')
+    if 'r' in spines:
+        yspines.append('right')
+    # collect axes:
+    if isinstance(ax, (list, tuple, np.ndarray)):
+        axs = ax
+    elif hasattr(ax, 'get_axes'):
+        # ax is figure:
+        axs = ax.get_axes()
+    else:
+        axs = [ax]
+    if not isinstance(axs, (list, tuple)):
+        axs = [axs]
+    for ax in axs:
+        # hide spines:
+        ax.spines['top'].set_visible('top' in xspines)
+        ax.spines['bottom'].set_visible('bottom' in xspines)
+        ax.spines['left'].set_visible('left' in yspines)
+        ax.spines['right'].set_visible('right' in yspines)
+        # ticks:
+        if len(xspines) == 0:
+            ax.xaxis.set_ticks_position('none')
+            ax.xaxis.label.set_visible(False)
+            ax.xaxis._orig_major_locator = ax.xaxis.get_major_locator()
+            ax.xaxis.set_major_locator(ticker.NullLocator())
+        else:
+            if hasattr(ax.xaxis, '_orig_major_locator'):
+                ax.xaxis.set_major_locator(ax.xaxis._orig_major_locator)
+                delattr(ax.xaxis, '_orig_major_locator')
+            elif isinstance(ax.xaxis.get_major_locator(), ticker.NullLocator):
+                ax.xaxis.set_major_locator(ticker.AutoLocator())
+            if len(xspines) == 1:
+                ax.xaxis.set_ticks_position(xspines[0])
+                ax.xaxis.set_label_position(xspines[0])
+            else:
+                ax.xaxis.set_ticks_position('both')
+                ax.xaxis.set_label_position('bottom')
+        if len(yspines) == 0:
+            ax.yaxis.set_ticks_position('none')
+            ax.yaxis.label.set_visible(False)
+            ax.yaxis._orig_major_locator = ax.yaxis.get_major_locator()
+            ax.yaxis.set_major_locator(ticker.NullLocator())
+        else:
+            if hasattr(ax.yaxis, '_orig_major_locator'):
+                ax.yaxis.set_major_locator(ax.yaxis._orig_major_locator)
+                delattr(ax.yaxis, '_orig_major_locator')
+            elif isinstance(ax.yaxis.get_major_locator(), ticker.NullLocator):
+                ax.yaxis.set_major_locator(ticker.AutoLocator())
+            if len(yspines) == 1:
+                ax.yaxis.set_ticks_position(yspines[0])
+                ax.yaxis.set_label_position(yspines[0])
+            else:
+                ax.yaxis.set_ticks_position('both')
+                ax.yaxis.set_label_position('left')
+
+def plot_g(ax, df, models, i, let_x, let_y, titlesize=10, letsize=12):
+    # c = [cm.plasma(x) for x in np.linspace(0., 1., 9)]
+    # c = [cm.turbo(x) for x in np.linspace(0., 1., 9)]
+    c = [cm.gray(x) for x in np.linspace(0., 0.75, 9)]
+    myorder = [0, 4, 1, 6, 2,7, 3,8]
+    colors = [c[i] for i in myorder]
+    df.plot.bar(y=models[i], rot=90, ax=ax, legend=False,
+                ylabel='$\mathrm{g}_{\mathrm{max}}$ [$\mathrm{mS}/ \mathrm{cm}^2$]',
+                color=colors)
+    ax.set_title(models[i], fontsize=titlesize)
+    show_spines(ax, spines='lb')
+    ax.text(let_x, let_y, string.ascii_uppercase[i], transform=ax.transAxes, size=letsize, weight='bold')
+    ax.set_yscale('log')
+    return ax
+
+
+index = ['$\mathrm{g}_{\mathrm{Na}}$', '$\mathrm{g}_{\mathrm{Kd}}$', '$\mathrm{g}_{\mathrm{K_V1.1}}$',
+         '$\mathrm{g}_{\mathrm{A}}$', '$\mathrm{g}_{\mathrm{M}}$', '$\mathrm{g}_{\mathrm{L}}$',
+         '$\mathrm{g}_{\mathrm{T}}$', ' $\mathrm{g}_{\mathrm{Ca,K}}$', ' $\mathrm{g}_{\mathrm{Leak}}$']
+df = pd.DataFrame({'RS Pyramidal': [56, 6, 0, 0, 0.075, 0, 0, 0, 0.0205],
+                   'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': [56, 5.4, 0.6, 0, 0.075, 0, 0, 0, 0.0205],
+                   'RS Inhibitory': [10, 2.1, 0, 0, 0.0098, 0, 0, 0, 0.0205],
+                   'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': [10, 1.89, 0.21, 0, 0.0098, 0, 0, 0, 0.0205],
+                   'FS': [58, 3.9, 0, 0, 0.075, 0, 0, 0, 0.038],
+                   'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': [58, 3.51, 0.39, 0, 0.075, 0, 0, 0, 0.038],
+                   'Cb stellate': [3.4, 9.0556, 0, 15.0159, 0, 0, 0.4545, 0, 0.07407],
+                   'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': [3.4, 8.15, 0.90556, 15.0159, 0, 0, 0.4545, 0, 0.07407],
+                   'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': [3.4, 9.0556, 1.50159, 0, 0, 0, 0.4545, 0, 0.07407],
+                   'STN': [49, 57, 0, 5, 0, 5, 5, 1, 0.035],
+                   'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': [49, 56.43, 0.57, 5, 0, 5, 5, 1, 0.035],
+                   'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': [49, 57, 0.5, 0, 0, 5, 5, 1, 0.035]},
+                  index=index)
+
+
+#% with legend
+scheme_style()
+models = ['Cb stellate', 'RS Inhibitory', 'FS', 'RS Pyramidal', 'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
+          'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
+          'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
+          'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
+          'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', 'STN']
+fig, axs = plt.subplots(4, 3, figsize=cm2inch(17.2, 20))  # ,  sharey=True)
+plt.subplots_adjust(hspace=1.5, wspace=1.0)
+let_x = -0.6
+let_y = 1.2
+titlesize = 9
+letsize = 10
+axs[0, 0] = plot_g(axs[0, 0], df, models, 0, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[0, 1] = plot_g(axs[0, 1], df, models, 1, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[0, 2] = plot_g(axs[0, 2], df, models, 2, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[1, 0] = plot_g(axs[1, 0], df, models, 3, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[1, 1] = plot_g(axs[1, 1], df, models, 4, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[1, 2] = plot_g(axs[1, 2], df, models, 5, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[2, 0] = plot_g(axs[2, 0], df, models, 6, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[2, 1] = plot_g(axs[2, 1], df, models, 7, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[2, 2] = plot_g(axs[2, 2], df, models, 8, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[3, 0] = plot_g(axs[3, 0], df, models, 9, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[3, 1] = plot_g(axs[3, 1], df, models, 10, let_x, let_y, titlesize=titlesize, letsize=letsize)
+axs[3, 2] = plot_g(axs[3, 2], df, models, 11, let_x, let_y, titlesize=titlesize, letsize=letsize)
+# save
+# fig.set_size_inches(cm2inch(21,20))
+fig.savefig('./Figures/model_g.jpg', dpi=300, bbox_inches='tight')  # pdf # eps
+plt.show()
+

Figures/summary_fig.py

@@ -6,20 +6,22 @@ from matplotlib.colors import colorConverter as cc
 from matplotlib.colors import to_hex
 import string
 from plotstyle import scheme_style
+import pandas as pd
+from matplotlib import cm
 
-colorslist = ['#40A787',  # cyan'#
-              '#F0D730',  # yellow
-              '#C02717',  # red
-              '#007030',  # dark green
-              '#AAB71B',  # lightgreen
-              '#008797',  # light blue
-              '#F78017',  # orange
-              '#478010',  # green
-              '#53379B',  # purple
-              '#2060A7',  # blue
-              '#873770',  # magenta
-              '#D03050'  # pink
-              ]
+colorslist = [  '#40A787', # cyan'#
+        '#F0D730',  # yellow
+        '#C02717',  # red
+        '#007030',  # dark green
+        '#AAB71B',  # lightgreen
+        '#008797',  # light blue
+        '#F78017',  # orange
+        '#478010',  # green
+        '#53379B',  # purple
+        '#2060A7',  # blue
+        '#873770',  # magenta
+        '#D03050'  # pink
+    ]
 
 
 def cm2inch(*tupl):
@@ -247,22 +249,41 @@ def plot_quadrant(ax):
     b[0] = '\u2212'
     b[1] = '+'
     ax.set_yticklabels(b)
-#
-# #%%
-#
-# imgplot = plt.imshow(img)
-# plt.show()
 
+def plot_g(ax, df, i):
+    # c = [cm.plasma(x) for x in np.linspace(0., 1., 9)]
+    # c = [cm.turbo(x) for x in np.linspace(0., 1., 9)]
+    # c = [cm.gray(x) for x in np.linspace(0., 0.75, 8)]
+    # myorder = [0, 4, 1, 6, 2, 7, 3]
+    # colors = [c[i] for i in myorder]
+    tab10 = [cm.tab10(x) for x in np.linspace(0., 1, 10)]
+    Accent = [cm.Accent(x) for x in np.linspace(0., 1, 8)]
+    colors = [colorslist[2], Accent[7], tab10[4], 'limegreen', tab10[5], tab10[9], tab10[1], 'fuchsia']
+    df.plot.bar(y=i, rot=90, ax=ax, legend=False, color=colors, ylabel='$\mathrm{g}_{\mathrm{max}}$')
+    # ax.set_title(models[i], fontsize=titlesize)
+    show_spines(ax, spines='lb')
+    ax.set_xticks([])
+    ax.set_yticks([])
+    ax.set_ylim(0, 8)
 
+    ax.set_xlim(-0.75, 8)
+    # ax.text(let_x, let_y, string.ascii_uppercase[i], transform=ax.transAxes, size=letsize, weight='bold')
+    # ax.set_yscale('log')
+    return ax
+
+index =               ['1', '2',   '3','4','5','6','7','8']
+df = pd.DataFrame({1: [6,   5.5,    2,  0,  1., 0,  6,  1.5],
+                   2: [8,   5,      8,  4,  0., 4,  0,  6.],
+                   3: [4,   4,      3,  3,  0., 1,  3,  0.]}, index=index)
 
 # %% with legend
 scheme_style()
 import matplotlib.image as mpimg
-img = mpimg.imread('./Figures/summary_diagram2.png')
+img = mpimg.imread('./Figures/summary_diagram3.png')
 inset_ylim = (0, 100)
-lfsize = 8
+lfsize = 7
 fig = plt.figure(figsize=cm2inch(17.2, 12))
-gs = gridspec.GridSpec(14, 3, top=0.95, bottom=0.1, left=0.15, right=0.95, hspace=0.2, wspace=0.1)
+gs = gridspec.GridSpec(15, 3, top=0.95, bottom=0.1, left=0.15, right=0.95, hspace=0.4, wspace=0.2)
 
 
 # gs0 = gs[1:13, 2].subgridspec(3, 1, hspace=0.9, wspace=0.25) # width_ratios=[0.3, 0.3,0.3], height_ratios=[0.35],
@@ -281,7 +302,15 @@ ax0 = fig.add_subplot(gs[:, :2])
 
 ax0.imshow(img)
 show_spines(ax0, '')
-
+axin1 = ax0.inset_axes([2200, 0, 400.0, 300], transform=ax0.transData)
+axin1 = plot_g(axin1, df, 1)
+axin2 = ax0.inset_axes([2200, 1200, 400.0, 300], transform=ax0.transData)
+axin2 = plot_g(axin2, df, 2)
+axin3 = ax0.inset_axes([2200, 2400, 400.0, 300], transform=ax0.transData)
+axin3 = plot_g(axin3, df, 3)
+# show_spines(axin1, '')
+# show_spines(axin2, '')
+# show_spines(axin3, '')
 
 # ax1.text(-0.95, -0.55, 'GOF/\nLOF?', ha='right')
 plot_diff_sqrt(ax1, b2=0.06, c2=65)
@@ -290,9 +319,11 @@ ax1.annotate('', (0.225, 7), (0.07, 7),
                 arrowprops=dict(arrowstyle="<|-", color=colorslist[2], lw=0.5, mutation_scale=5), zorder=-10)  #
 ax1.annotate('', (0.8, 80), (0.85, 55),
                 arrowprops=dict(arrowstyle="<|-", color=colorslist[2], lw=0.5, mutation_scale=5), zorder=-10)  #
-ax1.text(x=0.05, y=95, s='$\\downarrow$ AUC $\downarrow$ rheobase', fontsize=lfsize)
-
+ax1.text(x=0.85, y=90, s='WT',color=colorslist[9],rotation=17.5, fontsize=lfsize, weight='bold')
+ax1.text(x=0.75, y=37.5, s='Mutant',color=colorslist[2],rotation=10, fontsize=lfsize, weight='bold')
 
+# colorslist[9]
+# colorslist[2]
 
 # ax2.text(0.95, 0.35, 'LOF/\nGOF?')
 plot_diff_sqrt(ax2, b2=0.4, c2=200)
@@ -301,8 +332,10 @@ ax2.annotate('', (0.19, 7), (0.41, 7),
                 arrowprops=dict(arrowstyle="<|-", color=colorslist[2], lw=0.5, mutation_scale=5), zorder=-10)  #
 ax2.annotate('', (0.75, 70), (0.6, 90),
                 arrowprops=dict(arrowstyle="<|-", color=colorslist[2], lw=0.5, mutation_scale=5), zorder=-10)  #
-ax2.text(x=0.05, y=110, s='$\\uparrow$ AUC $\\uparrow$ rheobase', fontsize=lfsize)
-#
+# ax2.text(x=0.05, y=110, s='$\\uparrow$ AUC $\\uparrow$ rheobase', fontsize=lfsize)
+ax2.text(x=0.85, y=90, s='WT',color=colorslist[9],rotation=17.5, fontsize=lfsize, weight='bold')
+ax2.text(x=0.4, y=60, s='Mutant',color=colorslist[2],rotation=52, fontsize=lfsize, weight='bold')
+
 
 
 
@@ -316,12 +349,12 @@ ax3.annotate('', (0.225, 7), (0.085, 7),
                 arrowprops=dict(arrowstyle="<|-", color=colorslist[2], lw=0.5, mutation_scale=5), zorder=-10)  #
 ax3.annotate('', (0.55, 55), (0.3, 90),
                 arrowprops=dict(arrowstyle="<|-", color=colorslist[2], lw=0.5, mutation_scale=5), zorder=-10)  #
-ax3.text(x=0.05, y=110, s='$\\uparrow$ AUC $\\downarrow$ rheobase', fontsize=lfsize)
+# ax3.text(x=0.05, y=110, s='$\\uparrow$ AUC $\\downarrow$ rheobase', fontsize=lfsize)
+ax3.text(x=0.85, y=90, s='WT',color=colorslist[9],rotation=17.5, fontsize=lfsize, weight='bold')
+ax3.text(x=0.09, y=60, s='Mutant',color=colorslist[2],rotation=53, fontsize=lfsize, weight='bold')
 
 # fig.set_size_inches(cm2inch(17, 12))
-# fig.savefig('./Figures/summary_fig.jpg', dpi=300, bbox_inches='tight')  # , dpi=fig.dpi #pdf #eps
-#
-
+fig.savefig('./Figures/summary_fig.jpg', dpi=300, bbox_inches='tight')  # , dpi=fig.dpi #pdf #eps
 plt.show()