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Update figures to be correct widths (17.6 and 8.5 cm)

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nkoch1 2022-03-13 22:51:10 -04:00
parent b13c5127e5
commit c5b2192d59
13 changed files with 911 additions and 131 deletions
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Figures/AUC_correlation.py
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@ -13,7 +13,14 @@ import matplotlib
import matplotlib.lines as mlines import matplotlib.lines as mlines
from matplotlib import ticker from matplotlib import ticker
from matplotlib.ticker import NullFormatter from matplotlib.ticker import NullFormatter
from plotstyle import boxplot_style
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)
#%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ## #%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ##
# to change marker types in seaborn swarmplot # to change marker types in seaborn swarmplot
@ -44,7 +51,7 @@ def GetColor2Marker(markers):
mkcolors = [(palette[i]) for i in range(len(markers))] mkcolors = [(palette[i]) for i in range(len(markers))]
return dict(zip(mkcolors,markers)) return dict(zip(mkcolors,markers))
def fixlegend(ax,markers,markersize=8,**kwargs): def fixlegend(ax,markers,markersize=3,**kwargs):
# Fix Legend # Fix Legend
legtitle = ax.get_legend().get_title().get_text() legtitle = ax.get_legend().get_title().get_text()
_,l = ax.get_legend_handles_labels() _,l = ax.get_legend_handles_labels()
@ -90,7 +97,7 @@ Axes.scatter = new_scatter
######################################################################################################################## ########################################################################################################################
#%% #%%
def boxplot_with_markers(ax,max_width, alteration='shift'): def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
# size =4 # size =4
# ax.tick_params(axis='x', rotation=90) # ax.tick_params(axis='x', rotation=90)
model_names = ['RS pyramidal','RS inhibitory','FS', model_names = ['RS pyramidal','RS inhibitory','FS',
@ -126,7 +133,7 @@ def boxplot_with_markers(ax,max_width, alteration='shift'):
# '#873770', # magenta # '#873770', # magenta
# '#D03050' # pink # '#D03050' # pink
# ] # ]
hlinewidth =0.5
import matplotlib.colors import matplotlib.colors
colors = [matplotlib.colors.to_rgb(c) for c in colorslist] # sns.color_palette("hls", 14, desat=0.75)#[cm.tab20(i) for i in range(20)] colors = [matplotlib.colors.to_rgb(c) for c in colorslist] # sns.color_palette("hls", 14, desat=0.75)#[cm.tab20(i) for i in range(20)]
@ -139,14 +146,14 @@ def boxplot_with_markers(ax,max_width, alteration='shift'):
ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor = 'k') ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor = 'k')
df = pd.read_csv('./Figures/Data/AUC_shift_corr.csv') df = pd.read_csv('./Figures/Data/AUC_shift_corr.csv')
sns.swarmplot(y="corr", x="$\Delta V_{1/2}$", hue="model", data=df, sns.swarmplot(y="corr", x="$\Delta V_{1/2}$", hue="model", data=df,
palette=clr_dict, linewidth=0, orient='v', ax=ax, palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation', order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
'$K_V1.1$ inactivation', 'A activation', 'A inactivation'], '$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
hue_order=model_names, co2mk=Markers) hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim() lim = ax.get_xlim()
ax.plot([lim[0], lim[1]], [0, 0], ':r') ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k') ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k') ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
# ax.get_legend().remove() # ax.get_legend().remove()
# sns.despine(trim=True, bottom=True, ax=ax) # sns.despine(trim=True, bottom=True, ax=ax)
# ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$') # ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
@ -158,15 +165,15 @@ def boxplot_with_markers(ax,max_width, alteration='shift'):
# Add in points to show each observation # Add in points to show each observation
sns.swarmplot(y="corr", x="Slope (k)", hue="model", data=df, #dodge=True, sns.swarmplot(y="corr", x="Slope (k)", hue="model", data=df, #dodge=True,
palette=clr_dict, linewidth=0, orient='v', ax=ax, palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation', order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
'$K_V1.1$ inactivation', 'A activation', 'A inactivation'], '$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
hue_order=model_names, co2mk=Markers) hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim() lim = ax.get_xlim()
# ax.plot([lim[0], lim[1]], [0,0], ':k') # ax.plot([lim[0], lim[1]], [0,0], ':k')
ax.plot([lim[0], lim[1]], [0, 0], ':r') ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k') ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k') ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
# Markers = ["o","s","v","^","<",">","p","h","P","X","D","*","8","o"] # Markers = ["o","s","v","^","<",">","p","h","P","X","D","*","8","o"]
# ax=fixlegend(ax, Markers) # ax=fixlegend(ax, Markers)
# Tweak the visual presentation # Tweak the visual presentation
@ -183,14 +190,14 @@ def boxplot_with_markers(ax,max_width, alteration='shift'):
# Add in points to show each observation # Add in points to show each observation
sns.swarmplot(y="corr", x="g", hue="model", data=df, #dodge=True, sns.swarmplot(y="corr", x="g", hue="model", data=df, #dodge=True,
palette=clr_dict, linewidth=0, orient='v', ax=ax, palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na', 'K', '$K_V1.1$', 'A', 'Leak'], order=['Na', 'K', '$K_V1.1$', 'A', 'Leak'],
hue_order=model_names, co2mk=Markers) hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim() lim = ax.get_xlim()
# ax.plot([lim[0], lim[1]], [0,0], ':k') # ax.plot([lim[0], lim[1]], [0,0], ':k')
ax.plot([lim[0], lim[1]], [0, 0], ':r') ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k') ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k') ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
# Tweak the visual presentation # Tweak the visual presentation
# ax.xaxis.grid(False) # ax.xaxis.grid(False)
# sns.despine(trim=True, bottom=True, ax=ax) # sns.despine(trim=True, bottom=True, ax=ax)
@ -365,6 +372,7 @@ def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color
#%% #%%
boxplot_style()
color_dict = {'Cb stellate': '#40A787', # cyan'# color_dict = {'Cb stellate': '#40A787', # cyan'#
'RS Inhibitory': '#F0D730', # yellow 'RS Inhibitory': '#F0D730', # yellow
'FS': '#C02717', # red 'FS': '#C02717', # red
@ -380,16 +388,18 @@ color_dict = {'Cb stellate': '#40A787', # cyan'#
} }
# plot setup # plot setup
marker_s_leg = 8 marker_s_leg = 2
max_width = 10 max_width = 10
pad_x = 0.6 pad_x = 0.65
pad_y= 0.3 pad_y= 0.4
pad_w = 0.8 pad_w = 0.85
pad_h = 0.5 pad_h = 0.7
fig = plt.figure(figsize=(18,10)) fig = plt.figure()
gs = fig.add_gridspec(3, 6, wspace=0.9) # fig = plt.figure()
plt.subplots_adjust(hspace=0.8) #, wspace=0.6 # fig.set_size_inches(cm2inch(17.6,10))
gs = fig.add_gridspec(3, 6, wspace=1., hspace=0.8)
# plt.subplots_adjust(hspace=0.8) #, wspace=0.6
ax0 = fig.add_subplot(gs[0,2:6]) ax0 = fig.add_subplot(gs[0,2:6])
ax0_ex = fig.add_subplot(gs[0,1]) ax0_ex = fig.add_subplot(gs[0,1])
ax0_fI = fig.add_subplot(gs[0,0]) ax0_fI = fig.add_subplot(gs[0,0])
@ -400,27 +410,552 @@ ax2 = fig.add_subplot(gs[2,2:6])
ax2_ex = fig.add_subplot(gs[2,1]) ax2_ex = fig.add_subplot(gs[2,1])
ax2_fI = fig.add_subplot(gs[2,0]) ax2_fI = fig.add_subplot(gs[2,0])
line_width = 1
# plot fI examples
ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax0_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax0_fI.add_patch(rec)
rec.set_clip_on(False)
ax1_fI = plot_fI(ax1_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax1_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax1_fI.add_patch(rec)
rec.set_clip_on(False)
ax2_fI = plot_fI(ax2_fI, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='g', alt='Leak', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax2_fI.transAxes, color=color_dict['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax2_fI.add_patch(rec)
rec.set_clip_on(False)
# label subplots with letters
ax0_fI.text(-0.95, 1.12, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=10, weight='bold') #-0.09
ax1_fI.text(-0.95, 1.12, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=10, weight='bold')
ax2_fI.text(-0.95, 1.12, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=10, weight='bold')
# plot boxplots
boxplot_with_markers(ax0,max_width, alteration='shift')
boxplot_with_markers(ax1,max_width, alteration='slope')
boxplot_with_markers(ax2,max_width, alteration='g')
# plot legend
pos = (0.25, -0.6)
ncol = 6
model_legend(ax2, marker_s_leg, pos, ncol)
# plot examples
plot_AUC_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='shift')
plot_AUC_alt(ax1_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k',alteration='slope')
plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='g')
#save
# plt.tight_layout(pad=0)
print(fig.dpi)
fig.set_size_inches(cm2inch(21,10))
fig.savefig('./Figures/AUC_correlation.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show()
# #%% alternative layout
# # boxplot_style()
# marker_s_leg = 8
# max_width = 10
# pad_x = 0.2
# pad_y= 0.4
# pad_w = 0.22
# pad_h = 0.6
#
# fig = plt.figure(figsize=(12,20))
# gs = fig.add_gridspec(3, 1, hspace=0.4, wspace=0.4)
# gs0 = gs[0].subgridspec(2, 4, wspace=0.6, hspace=1.)
# gs1 = gs[1].subgridspec(2, 4, wspace=0.6, hspace=1.)
# gs2 = gs[2].subgridspec(2, 4, wspace=0.6, hspace=1.)
# ax0 = fig.add_subplot(gs0[1,:])
# ax0_ex = fig.add_subplot(gs0[0,2:])
# ax0_fI = fig.add_subplot(gs0[0,:2])
# ax1 = fig.add_subplot(gs1[1,:])
# ax1_ex = fig.add_subplot(gs1[0,2:])
# ax1_fI = fig.add_subplot(gs1[0,:2])
# ax2 = fig.add_subplot(gs2[1,:])
# ax2_ex = fig.add_subplot(gs2[0,2:])
# ax2_fI = fig.add_subplot(gs2[0,:2])
#
#
# ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s', color1='lightgrey', color2='k')
# rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax0_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
# rec = ax0_fI.add_patch(rec)
# rec.set_clip_on(False)
#
# ax1_fI = plot_fI(ax1_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u', color1='lightgrey', color2='k')
# rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax1_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
# rec = ax1_fI.add_patch(rec)
# rec.set_clip_on(False)
#
# ax2_fI = plot_fI(ax2_fI, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='g', alt='Leak', color1='lightgrey', color2='k')
# rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax2_fI.transAxes, color=color_dict['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
# rec = ax2_fI.add_patch(rec)
# rec.set_clip_on(False)
#
# # label subplots with letters
# ax0_fI.text(-0.2, 1.38, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=16, weight='bold') #-0.09
# ax1_fI.text(-0.2, 1.38, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=16, weight='bold')
# ax2_fI.text(-0.2, 1.38, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=16, weight='bold')
#
# # plot boxplots
# boxplot_with_markers(ax0,max_width, alteration='shift')
# boxplot_with_markers(ax1,max_width, alteration='slope')
# boxplot_with_markers(ax2,max_width, alteration='g')
# # plot legend
# pos = (0.5, -1.)
# ncol = 6
# model_legend(ax2, marker_s_leg, pos, ncol)
#
# # # plot rheo across model for example alteration
# # plot_rheo_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='red', color2='maroon', alteration='shift')
# # plot_rheo_alt(ax1_ex,model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='orchid', color2='purple',alteration='slope')
# # plot_rheo_alt(ax2_ex, model='Cb stellate', color1='darkviolet', color2='indigo', alteration='g')
# # plot_rheo_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='shift')
# # plot_rheo_alt(ax1_ex,model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k',alteration='slope')
# # plot_rheo_alt(ax2_ex, model='Cb stellate', color1='lightgrey', color2='k', alteration='g')
#
# # plot examples
# plot_AUC_alt(ax0_ex,model='FS', color1='lightgrey', color2='k', alteration='shift')
# plot_AUC_alt(ax1_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k',alteration='slope')
# plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='g')
# fig.savefig('AUC_correlation_2.pdf', bbox_inches='tight') #
# # plt.saveas(fig, 'AUC_correlation_2.png')
# plt.show()
# -*- coding: utf-8 -*-
"""
Created on Sat Jul 3 19:52:04 2021
@author: nils
"""
import pandas as pd
import numpy as np
import string
import textwrap
import json
import matplotlib
import matplotlib.lines as mlines
from matplotlib import ticker
from matplotlib.ticker import NullFormatter
from plotstyle import boxplot_style
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)
#%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ##
# to change marker types in seaborn swarmplot
import seaborn as sns
import matplotlib.pyplot as plt
############## Begin hack ##############
from matplotlib.axes._axes import Axes
from matplotlib.markers import MarkerStyle
from numpy import ndarray
def GetColor2Marker(markers):
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
]
import matplotlib.colors
palette = [matplotlib.colors.to_rgb(c) for c in colorslist]
mkcolors = [(palette[i]) for i in range(len(markers))]
return dict(zip(mkcolors,markers))
def fixlegend(ax,markers,markersize=3,**kwargs):
# Fix Legend
legtitle = ax.get_legend().get_title().get_text()
_,l = ax.get_legend_handles_labels()
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
]
import matplotlib.colors
palette = [matplotlib.colors.to_rgb(c) for c in colorslist]
mkcolors = [(palette[i]) for i in range(len(markers))]
newHandles = [plt.Line2D([0],[0], ls="none", marker=m, color=c, mec="none", markersize=markersize,**kwargs) \
for m,c in zip(markers, mkcolors)]
ax.legend(newHandles,l)
leg = ax.get_legend()
leg.set_title(legtitle)
old_scatter = Axes.scatter
def new_scatter(self, *args, **kwargs):
colors = kwargs.get("c", None)
co2mk = kwargs.pop("co2mk",None)
FinalCollection = old_scatter(self, *args, **kwargs)
if co2mk is not None and isinstance(colors, ndarray):
Color2Marker = GetColor2Marker(co2mk)
paths=[]
for col in colors:
mk=Color2Marker[tuple(col)]
marker_obj = MarkerStyle(mk)
paths.append(marker_obj.get_path().transformed(marker_obj.get_transform()))
FinalCollection.set_paths(paths)
return FinalCollection
Axes.scatter = new_scatter
############## End hack. ##############
########################################################################################################################
#%%
def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
# size =4
# ax.tick_params(axis='x', rotation=90)
model_names = ['RS pyramidal','RS inhibitory','FS',
'RS pyramidal +$K_V1.1$','RS inhibitory +$K_V1.1$',
'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$',
'Cb stellate $\Delta$$K_V1.1$','STN','STN +$K_V1.1$',
'STN $\Delta$$K_V1.1$']
colorslist = ['#007030', # dark green
'#F0D730', # yellow
'#C02717', # red
'#478010', # green
'#AAB71B', # lightgreen
'#F78017', # orange
'#40A787', # cyan'#
'#008797', # light blue
'#2060A7', # blue
'#D03050', # pink
'#53379B', # purple
'#873770', # magenta
]
# colorslist = ['#40A787', # cyan'#
# '#F0D730', # yellow
# 'C02717', # red
# '#007030', # dark green
# '#AAB71B', # lightgreen
# '#008797', # light blue
# '#F78017', # orange
# '#478010', # green
# '#53379B', # purple
# '#2060A7', # blue
# '#873770', # magenta
# '#D03050' # pink
# ]
hlinewidth =0.5
import matplotlib.colors
colors = [matplotlib.colors.to_rgb(c) for c in colorslist] # sns.color_palette("hls", 14, desat=0.75)#[cm.tab20(i) for i in range(20)]
clr_dict = {}
for m in range(len(model_names)):
clr_dict[model_names[m]] = colors[m]
Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
if alteration=='shift':
i = 2 # Kd act
ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor = 'k')
df = pd.read_csv('./Figures/Data/AUC_shift_corr.csv')
sns.swarmplot(y="corr", x="$\Delta V_{1/2}$", hue="model", data=df,
palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
'$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim()
ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
# ax.get_legend().remove()
# sns.despine(trim=True, bottom=True, ax=ax)
# ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
ax.set_title("Shift ($\Delta V_{1/2}$)", y=1.05)
elif alteration=='slope':
i = 3 # Kv1.1 act
ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor='k')
df = pd.read_csv('./Figures/Data/AUC_scale_corr.csv')
# Add in points to show each observation
sns.swarmplot(y="corr", x="Slope (k)", hue="model", data=df, #dodge=True,
palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
'$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim()
# ax.plot([lim[0], lim[1]], [0,0], ':k')
ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
# Markers = ["o","s","v","^","<",">","p","h","P","X","D","*","8","o"]
# ax=fixlegend(ax, Markers)
# Tweak the visual presentation
# ax.get_legend().remove()
# ax.xaxis.grid(False)
# ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
# ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
ax.set_title("Slope (k)", y=1.05)
# sns.despine(trim=True, bottom=True, ax=ax)
elif alteration=='g':
i = 1 # Kd
ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor='k')
df = pd.read_csv('./Figures/Data/AUC_g_corr.csv')
# Add in points to show each observation
sns.swarmplot(y="corr", x="g", hue="model", data=df, #dodge=True,
palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na', 'K', '$K_V1.1$', 'A', 'Leak'],
hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim()
# ax.plot([lim[0], lim[1]], [0,0], ':k')
ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
# Tweak the visual presentation
# ax.xaxis.grid(False)
# sns.despine(trim=True, bottom=True, ax=ax)
# ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
ax.set_title("Conductance (g)", y=1.05)
# ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
else:
print('Please chose "shift", "slope" or "g"')
ax.get_legend().remove()
ax.xaxis.grid(False)
sns.despine(trim=True, bottom=True, ax=ax)
ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
# fixlegend(ax, Markers)
def model_legend(ax, marker_s_leg, pos, ncol):
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
]
import matplotlib.colors
colors = [matplotlib.colors.to_rgb(c) for c in colorslist] #sns.color_palette("hls", 14, desat=0.75) #[cm.tab20(i) for i in range(20)]
model_pos = {'Cb stellate':0, 'RS Inhibitory':1, 'FS':2, 'RS Pyramidal':3,
'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':4,
'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':5, 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':6,
'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':7, 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':8,
'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':9,
'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':10, 'STN':11}
Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
RS_p = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal']], marker=Markers[model_pos['RS Pyramidal']], markersize=marker_s_leg, linestyle='None',
label='RS pyramidal')
RS_i = mlines.Line2D([], [], color=colors[model_pos['RS Inhibitory']], marker=Markers[model_pos['RS Inhibitory']], markersize=marker_s_leg, linestyle='None',
label='RS inhibitory')
FS = mlines.Line2D([], [], color=colors[model_pos['FS']], marker=Markers[model_pos['FS']], markersize=marker_s_leg, linestyle='None', label='FS')
RS_p_Kv = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
label='RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
RS_i_Kv = mlines.Line2D([], [], color=colors[model_pos['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
label='RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
FS_Kv = mlines.Line2D([], [], color=colors[model_pos['Cb stellate']], marker=Markers[model_pos['Cb stellate']], markersize=marker_s_leg, linestyle='None', label='FS +$K_V1.1$')
Cb = mlines.Line2D([], [], color=colors[8], marker=Markers[8], markersize=marker_s_leg, linestyle='None',
label='Cb stellate')
Cb_pl = mlines.Line2D([], [], color=colors[model_pos['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
label='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
Cb_sw = mlines.Line2D([], [], color=colors[model_pos['Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
label='Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
STN = mlines.Line2D([], [], color=colors[model_pos['STN']], marker=Markers[model_pos['STN']], markersize=marker_s_leg, linestyle='None', label='STN')
STN_pl = mlines.Line2D([], [], color=colors[model_pos['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
label='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
STN_sw = mlines.Line2D([], [], color=colors[model_pos['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
label='STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
ax.legend(handles=[RS_p, RS_i, FS, RS_p_Kv, RS_i_Kv, FS_Kv, Cb, Cb_pl, Cb_sw, STN, STN_pl, STN_sw], loc='center',
bbox_to_anchor=pos, ncol=ncol, frameon=False)
def plot_AUC_alt(ax, model='FS', color1='red', color2='dodgerblue', alteration='shift'):
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
model_names = ['RS Pyramidal','RS Inhibitory','FS',
'RS Pyramidal +$K_V1.1$','RS Inhibitory +$K_V1.1$',
'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$',
'Cb stellate $\Delta$$K_V1.1$','STN','STN +$K_V1.1$',
'STN $\Delta$$K_V1.1$']
model_name_dict = {'RS Pyramidal': 'RS Pyramidal',
'RS Inhibitory': 'RS Inhibitory',
'FS': 'FS',
'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS Pyramidal +$K_V1.1$',
'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS Inhibitory +$K_V1.1$',
'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'FS +$K_V1.1$',
'Cb stellate': 'Cb stellate',
'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb stellate +$K_V1.1$',
'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb stellate $\Delta$$K_V1.1$',
'STN': 'STN',
'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN +$K_V1.1$',
'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN $\Delta$$K_V1.1$'}
colorslist = ['#007030', # dark green
'#F0D730', # yellow
'#C02717', # red
'#478010', # green
'#AAB71B', # lightgreen
'#F78017', # orange
'#40A787', # cyan'#
'#008797', # light blue
'#2060A7', # blue
'#D03050', # pink
'#53379B', # purple
'#873770', # magenta
]
import matplotlib.colors
colors = [matplotlib.colors.to_rgb(c) for c in
colorslist] #sns.color_palette("hls", 14, desat=0.75)#[cm.tab20(i) for i in range(20)]
clr_dict = {}
for m in range(len(model_names)):
clr_dict[model_names[m]] = colors[m]
if alteration=='shift':
df = pd.read_csv('./Figures/Data/AUC_shift_ex.csv')
df = df.sort_values('alteration')
ax.set_xlabel('$\Delta$$V_{1/2}$')
elif alteration=='slope':
df = pd.read_csv('./Figures/Data/AUC_slope_ex.csv')
ax.set_xscale("log")
ax.set_xticks([0.5, 1, 2])
ax.xaxis.set_major_formatter(ticker.ScalarFormatter())
ax.xaxis.set_minor_formatter(NullFormatter())
ax.set_xlabel('Slope factor k')
elif alteration=='g':
df = pd.read_csv('./Figures/Data/AUC_g_ex.csv')
ax.set_xscale("log")
ax.set_xticks([0.5, 1, 2])
ax.xaxis.set_major_formatter(ticker.ScalarFormatter())
ax.xaxis.set_minor_formatter(NullFormatter())
ax.set_xlabel('g')
for mod in model_names:
if mod == model_name_dict[model]:
ax.plot(df['alteration'], df[mod], color=clr_dict[mod], alpha=1, zorder=10, linewidth=2)
else:
ax.plot(df['alteration'], df[mod], color=clr_dict[mod],alpha=1, zorder=1, linewidth=1)
ax.set_ylabel('Normalized AUC')
x = df['alteration']
y = df[model_name_dict[model]]
ax.set_xlim(x.min(), x.max())
ax.set_ylim(df[model_names].min().min(), df[model_names].max().max())
return ax
def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color2='dodgerblue'):
model_save_name = {'RS Pyramidal': 'RS_pyr_posp',
'RS Inhibitory': 'RS_inhib_posp',
'FS': 'FS_posp',
'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS_pyr_Kv',
'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS_inhib_Kv',
'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'FS_Kv',
'Cb stellate': 'Cb_stellate',
'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb_stellate_Kv',
'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb_stellate_Kv_only',
'STN': 'STN',
'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN_Kv',
'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN_Kv_only'}
cvals = [-2., 2]
colors = [color1, color2]
norm = plt.Normalize(min(cvals), max(cvals))
tuples = list(zip(map(norm, cvals), colors))
cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", tuples)
colors = cmap(np.linspace(0, 1, 22))
df = pd.read_csv('./Figures/Data/Model_fI/{}_fI.csv'.format(model_save_name[model]))
df.drop(['Unnamed: 0'], axis=1)
newdf = df.loc[df.index[(df['alt'] == alt) & (df['type'] == type)], :]
newdf['mag'] = newdf['mag'].astype('float')
newdf = newdf.sort_values('mag').reset_index()
c = 0
for i in newdf.index:
ax.plot(json.loads(newdf.loc[i, 'I']), json.loads(newdf.loc[i, 'F']), color=colors[c])
c += 1
ax.set_ylabel('Frequency [Hz]')
ax.set_xlabel('Current [nA]')
ax.set_title(model)
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
L = ax.get_ylim()
ax.set_ylim([0, L[1]])
return ax
#%%
boxplot_style()
color_dict = {'Cb stellate': '#40A787', # cyan'#
'RS Inhibitory': '#F0D730', # yellow
'FS': '#C02717', # red
'RS Pyramidal': '#007030', # dark green
'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#AAB71B', # lightgreen
'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#008797', # light blue
'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#F78017', # orange
'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#478010', # green
'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#53379B', # purple
'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#2060A7', # blue
'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#873770', # magenta
'STN': '#D03050' # pink
}
# plot setup
marker_s_leg = 2
max_width = 10
pad_x = 0.65
pad_y= 0.4
pad_w = 0.85
pad_h = 0.7
fig = plt.figure()
# fig = plt.figure()
# fig.set_size_inches(cm2inch(17.6,10))
gs = fig.add_gridspec(3, 6, wspace=1., hspace=0.8)
# plt.subplots_adjust(hspace=0.8) #, wspace=0.6
ax0 = fig.add_subplot(gs[0,2:6])
ax0_ex = fig.add_subplot(gs[0,1])
ax0_fI = fig.add_subplot(gs[0,0])
ax1 = fig.add_subplot(gs[1,2:6])
ax1_ex = fig.add_subplot(gs[1,1])
ax1_fI = fig.add_subplot(gs[1,0])
ax2 = fig.add_subplot(gs[2,2:6])
ax2_ex = fig.add_subplot(gs[2,1])
ax2_fI = fig.add_subplot(gs[2,0])
line_width = 1
# plot fI examples # plot fI examples
ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s', color1='lightgrey', color2='k') ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax0_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1) rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax0_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax0_fI.add_patch(rec) rec = ax0_fI.add_patch(rec)
rec.set_clip_on(False) rec.set_clip_on(False)
ax1_fI = plot_fI(ax1_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u', color1='lightgrey', color2='k') ax1_fI = plot_fI(ax1_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax1_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1) rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax1_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax1_fI.add_patch(rec) rec = ax1_fI.add_patch(rec)
rec.set_clip_on(False) rec.set_clip_on(False)
ax2_fI = plot_fI(ax2_fI, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='g', alt='Leak', color1='lightgrey', color2='k') ax2_fI = plot_fI(ax2_fI, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='g', alt='Leak', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax2_fI.transAxes, color=color_dict['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1) rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax2_fI.transAxes, color=color_dict['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax2_fI.add_patch(rec) rec = ax2_fI.add_patch(rec)
rec.set_clip_on(False) rec.set_clip_on(False)
# label subplots with letters # label subplots with letters
ax0_fI.text(-0.6, 1.28, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=16, weight='bold') #-0.09 ax0_fI.text(-0.95, 1.12, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=10, weight='bold') #-0.09
ax1_fI.text(-0.6, 1.28, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=16, weight='bold') ax1_fI.text(-0.95, 1.12, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=10, weight='bold')
ax2_fI.text(-0.6, 1.28, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=16, weight='bold') ax2_fI.text(-0.95, 1.12, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=10, weight='bold')
# plot boxplots # plot boxplots
boxplot_with_markers(ax0,max_width, alteration='shift') boxplot_with_markers(ax0,max_width, alteration='shift')
@ -438,7 +973,10 @@ plot_AUC_alt(ax1_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='l
plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='g') plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='g')
#save #save
fig.savefig('./Figures/AUC_correlation.pdf', bbox_inches='tight', dpi=fig.dpi) # plt.tight_layout(pad=0)
print(fig.dpi)
fig.set_size_inches(cm2inch(20.3,10))
fig.savefig('./Figures/AUC_correlation.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show() plt.show()
# #%% alternative layout # #%% alternative layout

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Figures/diversity_in_firing.py
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@ -6,6 +6,15 @@ from matplotlib.transforms import Bbox
import string import string
# from plotstyle import plot_style # from plotstyle import plot_style
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)
plt.rcParams['xtick.labelsize'] = 6
plt.rcParams['ytick.labelsize'] = 6
#### from https://gist.github.com/dmeliza/3251476 ##################################################################### #### from https://gist.github.com/dmeliza/3251476 #####################################################################
from matplotlib.offsetbox import AnchoredOffsetbox from matplotlib.offsetbox import AnchoredOffsetbox
class AnchoredScaleBar(AnchoredOffsetbox): class AnchoredScaleBar(AnchoredOffsetbox):
@ -41,7 +50,7 @@ class AnchoredScaleBar(AnchoredOffsetbox):
AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad, AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad,
child=bars, prop=prop, frameon=False, **kwargs) child=bars, prop=prop, frameon=False, **kwargs)
plt.rcParams.update({'font.size': 6})
def add_scalebar(ax, matchx=True, matchy=True, hidex=True, hidey=True, **kwargs): def add_scalebar(ax, matchx=True, matchy=True, hidex=True, hidey=True, **kwargs):
""" Add scalebars to axes """ Add scalebars to axes
Adds a set of scale bars to *ax*, matching the size to the ticks of the plot Adds a set of scale bars to *ax*, matching the size to the ticks of the plot
@ -83,7 +92,7 @@ def plot_spike_train(ax, model='RS Pyramidal', stop=750):
ax.set_xlabel('Time [s]') ax.set_xlabel('Time [s]')
ax.set_ylim(-80, 60) ax.set_ylim(-80, 60)
ax.axis('off') ax.axis('off')
ax.set_title(model) ax.set_title(model, fontsize=10)
def plot_fI(ax, model='RS Pyramidal'): def plot_fI(ax, model='RS Pyramidal'):
@ -119,10 +128,10 @@ def plot_fI(ax, model='RS Pyramidal'):
#%% #%%
# plot layout # plot layout
fig = plt.figure(figsize=(10,10)) fig = plt.figure() #figsize=cm2inch(17.6,17.6)
gs0 = fig.add_gridspec(3, 2, wspace=0.3) gs0 = fig.add_gridspec(3, 2, wspace=0.3, hspace=0)
gs00 = gs0[:,0].subgridspec(6, 3, wspace=0.7, hspace=1) gs00 = gs0[:,0].subgridspec(6, 3, wspace=1.5, hspace=1.5)
gs01 = gs0[:,1].subgridspec(6, 3, wspace=0.7, hspace=1) gs01 = gs0[:,1].subgridspec(6, 3, wspace=1.2, hspace=1.3)
ax1_spikes = fig.add_subplot(gs00[0,0:2]) ax1_spikes = fig.add_subplot(gs00[0,0:2])
ax1_fI = fig.add_subplot(gs00[0, 2]) ax1_fI = fig.add_subplot(gs00[0, 2])
@ -175,10 +184,13 @@ add_scalebar(ax12_spikes, matchx=False, matchy=False, hidex=True, hidey=True, si
bbox_transform=ax12_spikes.transAxes) bbox_transform=ax12_spikes.transAxes)
# add subplot labels # add subplot labels
for i in range(0,len(models)): 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') spike_axs[i].text(-0.18, 1.08, string.ascii_uppercase[i], transform=spike_axs[i].transAxes, size=10, weight='bold')
# save # save
fig.savefig('./Figures/diversity_in_firing.pdf', bbox_inches='tight') # fig.savefig('./Figures/diversity_in_firing.pdf', bbox_inches='tight')
print(fig.dpi)
fig.set_size_inches(cm2inch(17.6,20))
fig.savefig('./Figures/diversity_in_firing.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show() plt.show()

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Figures/firing_characterization.pdf
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31
Figures/firing_characterization.py
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@ -2,7 +2,15 @@ import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec import matplotlib.gridspec as gridspec
import string import string
from plotstyle import plot_style # from plotstyle import plot_style
from plotstyle import scheme_style
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 plot_sqrt(ax, a=1, b=0.2, c=100, d=0): def plot_sqrt(ax, a=1, b=0.2, c=100, d=0):
x = np.linspace(0, 1, 10000) x = np.linspace(0, 1, 10000)
@ -51,14 +59,15 @@ def plot_quadrant(ax):
b[2] = '+' b[2] = '+'
ax.set_yticklabels(b) ax.set_yticklabels(b)
ax.tick_params(labelsize=16) # ax.tick_params(labelsize=16)
# ax.set_yticks([0]) # ax.set_yticks([0])
# ax.axis('off') # ax.axis('off')
plot_style() # plot_style()
scheme_style()
fig = plt.figure(figsize=(4, 6)) fig = plt.figure(figsize=cm2inch(7, 12))
gs = gridspec.GridSpec(3,2, top=0.95, bottom=0.1, left=0.15, right = 0.95, hspace=0.8, wspace=0.6) gs = gridspec.GridSpec(3,2, top=0.95, bottom=0.1, left=0.15, right = 0.95, hspace=0.8, wspace=0.6)
ax1 = fig.add_subplot(gs[0,:]) ax1 = fig.add_subplot(gs[0,:])
plot_AUC(ax1, width=0.2) plot_AUC(ax1, width=0.2)
@ -80,30 +89,34 @@ plot_quadrant(ax3) # plot delineation into quadrants
inset_ylim = (0, 100) inset_ylim = (0, 100)
# top left # top left
lfsize = 8
ax3.text(x=-0.75, y=0.25, s=r'''$\uparrow$ AUC ax3.text(x=-0.75, y=0.25, s=r'''$\uparrow$ AUC
$\downarrow$ rheobase''') $\downarrow$ rheobase''', fontsize=lfsize)
ax3_TL = ax3.inset_axes([0, 0.8, 0.3, 0.2]) ax3_TL = ax3.inset_axes([0, 0.8, 0.3, 0.2])
plot_diff_sqrt(ax3_TL, b2=0.1, c2=200) plot_diff_sqrt(ax3_TL, b2=0.1, c2=200)
ax3_TL.set_ylim(inset_ylim) ax3_TL.set_ylim(inset_ylim)
# top right # top right
ax3.text(x=0.25, y=0.25, s=r'''$\uparrow$ AUC ax3.text(x=0.25, y=0.25, s=r'''$\uparrow$ AUC
$\uparrow$ rheobase''') $\uparrow$ rheobase''', fontsize=lfsize)
ax3_TR = ax3.inset_axes([0.7, 0.8, 0.3, 0.2]) ax3_TR = ax3.inset_axes([0.7, 0.8, 0.3, 0.2])
plot_diff_sqrt(ax3_TR, b2=0.4, c2=200) plot_diff_sqrt(ax3_TR, b2=0.4, c2=200)
ax3_TR.set_ylim(inset_ylim) ax3_TR.set_ylim(inset_ylim)
# bottom left # bottom left
ax3.text(x=-0.75, y=-0.35, s=r'''$\downarrow$ AUC ax3.text(x=-0.75, y=-0.35, s=r'''$\downarrow$ AUC
$\downarrow$ rheobase''') $\downarrow$ rheobase''', fontsize=lfsize)
ax3_BL = ax3.inset_axes([0, 0, 0.3, 0.2]) ax3_BL = ax3.inset_axes([0, 0, 0.3, 0.2])
plot_diff_sqrt(ax3_BL, b2=0.1, c2=75) plot_diff_sqrt(ax3_BL, b2=0.1, c2=75)
ax3_BL.set_ylim(inset_ylim) ax3_BL.set_ylim(inset_ylim)
# bottom right # bottom right
ax3.text(x=0.25, y=-0.35, s=r'''$\downarrow$ AUC ax3.text(x=0.25, y=-0.35, s=r'''$\downarrow$ AUC
$\uparrow$ rheobase''') $\uparrow$ rheobase''', fontsize=lfsize)
ax3_BR = ax3.inset_axes([0.7, 0, 0.3, 0.2]) ax3_BR = ax3.inset_axes([0.7, 0, 0.3, 0.2])
plot_diff_sqrt(ax3_BR, b2=0.4, c2=75) plot_diff_sqrt(ax3_BR, b2=0.4, c2=75)
ax3_BR.set_ylim(inset_ylim) ax3_BR.set_ylim(inset_ylim)
fig.savefig('./Figures/firing_characterization.pdf', bbox_inches='tight') # fig.savefig('./Figures/firing_characterization.pdf', bbox_inches='tight')
print(fig.dpi)
fig.set_size_inches(cm2inch(8.17,15))
fig.savefig('./Figures/firing_characterization.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show() plt.show()

210
Figures/ramp_examples.py
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@ -1,3 +1,150 @@
# # plot ramp protocol and responses of each model to ramp
# import numpy as np
# import pandas as pd
# import matplotlib.pyplot as plt
# import matplotlib.gridspec as gridspec
# from matplotlib.transforms import Bbox
# import string
#
# 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)
#
# #### from https://gist.github.com/dmeliza/3251476 #####################################################################
# from matplotlib.offsetbox import AnchoredOffsetbox
# class AnchoredScaleBar(AnchoredOffsetbox):
# def __init__(self, transform, sizex=0, sizey=0, labelx=None, labely=None, loc=4,
# pad=0.1, borderpad=0.1, sep=2, prop=None, barcolor="black", barwidth=None,
# **kwargs):
# """
# Draw a horizontal and/or vertical bar with the size in data coordinate
# of the give axes. A label will be drawn underneath (center-aligned).
# - transform : the coordinate frame (typically axes.transData)
# - sizex,sizey : width of x,y bar, in data units. 0 to omit
# - labelx,labely : labels for x,y bars; None to omit
# - loc : position in containing axes
# - pad, borderpad : padding, in fraction of the legend font size (or prop)
# - sep : separation between labels and bars in points.
# - **kwargs : additional arguments passed to base class constructor
# """
# from matplotlib.patches import Rectangle
# from matplotlib.offsetbox import AuxTransformBox, VPacker, HPacker, TextArea, DrawingArea
# bars = AuxTransformBox(transform)
# if sizex:
# bars.add_artist(Rectangle((0, 0), sizex, 0, ec=barcolor, lw=barwidth, fc="none"))
# if sizey:
# bars.add_artist(Rectangle((0, 0), 0, sizey, ec=barcolor, lw=barwidth, fc="none"))
#
# if sizex and labelx:
# self.xlabel = TextArea(labelx)
# bars = VPacker(children=[bars, self.xlabel], align="center", pad=0, sep=sep)
# if sizey and labely:
# self.ylabel = TextArea(labely)
# bars = HPacker(children=[self.ylabel, bars], align="center", pad=0, sep=sep)
#
# AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad,
# child=bars, prop=prop, frameon=False, **kwargs)
#
#
# def add_scalebar(ax, matchx=True, matchy=True, hidex=True, hidey=True, **kwargs):
# """ Add scalebars to axes
# Adds a set of scale bars to *ax*, matching the size to the ticks of the plot
# and optionally hiding the x and y axes
# - ax : the axis to attach ticks to
# - matchx,matchy : if True, set size of scale bars to spacing between ticks
# if False, size should be set using sizex and sizey params
# - hidex,hidey : if True, hide x-axis and y-axis of parent
# - **kwargs : additional arguments passed to AnchoredScaleBars
# Returns created scalebar object
# """
#
# def f(axis):
# l = axis.get_majorticklocs()
# return len(l) > 1 and (l[1] - l[0])
#
# if matchx:
# kwargs['sizex'] = f(ax.xaxis)
# kwargs['labelx'] = str(kwargs['sizex'])
# if matchy:
# kwargs['sizey'] = f(ax.yaxis)
# kwargs['labely'] = str(kwargs['sizey'])
#
# sb = AnchoredScaleBar(ax.transData, **kwargs)
# ax.add_artist(sb)
#
# if hidex: ax.xaxis.set_visible(False)
# if hidey: ax.yaxis.set_visible(False)
# if hidex and hidey: ax.set_frame_on(False)
#
# return sb
# ########################################################################################################################
#
#
# def plot_ramp_V(ax, model='RS Pyramidal'): # , stop=750
# model_ramp = pd.read_csv('./Figures/Data/model_ramp.csv')
# ax.plot(model_ramp['t'], model_ramp[model], 'k', linewidth=0.025)
# ax.set_ylabel('V')
# ax.set_xlabel('Time [s]')
# ax.set_ylim(-80, 60)
# ax.axis('off')
# ax.set_title(model)
#
# #% plot setup
# fig = plt.figure(figsize=cm2inch(17.6,17.6))
#
# gs0 = fig.add_gridspec(3, 2, wspace=0.1)
# gs00 = gs0[:,0].subgridspec(7, 2, wspace=0.6, hspace=1)
# gs01 = gs0[:,1].subgridspec(7, 2, wspace=0.6, hspace=1)
#
# ax1_ramp = fig.add_subplot(gs00[0,0:2])
# ax2_ramp = fig.add_subplot(gs01[0,0:2])
# ax3_ramp = fig.add_subplot(gs00[1,0:2])
# ax4_ramp = fig.add_subplot(gs01[1,0:2])
# ax5_ramp = fig.add_subplot(gs00[2, 0:2])
# ax6_ramp = fig.add_subplot(gs01[2, 0:2])
# ax7_ramp = fig.add_subplot(gs00[3,0:2])
# ax8_ramp = fig.add_subplot(gs01[3,0:2])
# ax9_ramp = fig.add_subplot(gs00[4,0:2])
# ax10_ramp = fig.add_subplot(gs01[4,0:2])
# ax11_ramp = fig.add_subplot(gs00[5,0:2])
# ax12_ramp = fig.add_subplot(gs01[5,0:2])
#
# ramp_axs = [ax1_ramp, ax2_ramp, ax3_ramp, ax4_ramp, ax5_ramp,ax6_ramp, ax7_ramp, ax8_ramp,
# ax9_ramp, ax10_ramp, ax11_ramp, ax12_ramp]
#
# # order of models
# 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']
#
# # plot ramps
# for i in range(len(models)):
# plot_ramp_V(ramp_axs[i], model=models[i])
#
# # add scalebar
# plt.rcParams.update({'font.size': 6})
#
# add_scalebar(ax11_ramp, matchx=False, matchy=False, hidex=True, hidey=True, sizex=1000, sizey=50, labelx='1 s',
# labely='50 mV', loc=3, pad=-2, borderpad=0, barwidth=1, bbox_to_anchor=Bbox.from_bounds(-0.05, 0.1, 1, 1),
# bbox_transform=ax11_ramp.transAxes)
# # add_scalebar(ax12_ramp, matchx=False, matchy=False, hidex=True, hidey=True, sizex=1000, sizey=25, labelx='1 s',
# # labely='25 mV', loc=3, pad=-2, borderpad=0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.05, 0.1, 1, 1),
# # bbox_transform=ax12_ramp.transAxes)
#
# # add subplot labels
# 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=10, weight='bold')
#
# fig.savefig('./Figures/ramp_firing.pdf', dpi=3000)
# plt.show()
# plot ramp protocol and responses of each model to ramp # plot ramp protocol and responses of each model to ramp
import numpy as np import numpy as np
import pandas as pd import pandas as pd
@ -6,6 +153,13 @@ import matplotlib.gridspec as gridspec
from matplotlib.transforms import Bbox from matplotlib.transforms import Bbox
import string import string
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)
#### from https://gist.github.com/dmeliza/3251476 ##################################################################### #### from https://gist.github.com/dmeliza/3251476 #####################################################################
from matplotlib.offsetbox import AnchoredOffsetbox from matplotlib.offsetbox import AnchoredOffsetbox
class AnchoredScaleBar(AnchoredOffsetbox): class AnchoredScaleBar(AnchoredOffsetbox):
@ -78,32 +232,32 @@ def add_scalebar(ax, matchx=True, matchy=True, hidex=True, hidey=True, **kwargs)
def plot_ramp_V(ax, model='RS Pyramidal'): # , stop=750 def plot_ramp_V(ax, model='RS Pyramidal'): # , stop=750
model_ramp = pd.read_csv('./Figures/Data/model_ramp.csv') model_ramp = pd.read_csv('./Figures/Data/model_ramp.csv')
ax.plot(model_ramp['t'], model_ramp[model], 'k', linewidth=0.25) ax.plot(model_ramp['t'], model_ramp[model], 'k', linewidth=0.0025)
ax.set_ylabel('V') ax.set_ylabel('V')
ax.set_xlabel('Time [s]') ax.set_xlabel('Time [s]')
ax.set_ylim(-80, 60) ax.set_ylim(-80, 60)
ax.axis('off') ax.axis('off')
ax.set_title(model) ax.set_title(model, fontsize=8)
#% plot setup #% plot setup
fig = plt.figure(figsize=(20,10)) fig = plt.figure(figsize=cm2inch(17.6,25))
gs0 = fig.add_gridspec(3, 2, wspace=0.1) gs0 = fig.add_gridspec(2, 1, wspace=0.)
gs00 = gs0[:,0].subgridspec(7, 2, wspace=0.6, hspace=1) gs00 = gs0[:].subgridspec(12, 1, wspace=0.7, hspace=1.0)
gs01 = gs0[:,1].subgridspec(7, 2, wspace=0.6, hspace=1) # gs01 = gs0[1:].subgridspec(7, 2, wspace=0.6, hspace=1)
ax1_ramp = fig.add_subplot(gs00[0,0:2]) ax1_ramp = fig.add_subplot(gs00[0])
ax2_ramp = fig.add_subplot(gs01[0,0:2]) ax2_ramp = fig.add_subplot(gs00[1])
ax3_ramp = fig.add_subplot(gs00[1,0:2]) ax3_ramp = fig.add_subplot(gs00[2])
ax4_ramp = fig.add_subplot(gs01[1,0:2]) ax4_ramp = fig.add_subplot(gs00[3])
ax5_ramp = fig.add_subplot(gs00[2, 0:2]) ax5_ramp = fig.add_subplot(gs00[4])
ax6_ramp = fig.add_subplot(gs01[2, 0:2]) ax6_ramp = fig.add_subplot(gs00[5])
ax7_ramp = fig.add_subplot(gs00[3,0:2]) ax7_ramp = fig.add_subplot(gs00[6])
ax8_ramp = fig.add_subplot(gs01[3,0:2]) ax8_ramp = fig.add_subplot(gs00[7])
ax9_ramp = fig.add_subplot(gs00[4,0:2]) ax9_ramp = fig.add_subplot(gs00[8])
ax10_ramp = fig.add_subplot(gs01[4,0:2]) ax10_ramp = fig.add_subplot(gs00[9])
ax11_ramp = fig.add_subplot(gs00[5,0:2]) ax11_ramp = fig.add_subplot(gs00[10])
ax12_ramp = fig.add_subplot(gs01[5,0:2]) ax12_ramp = fig.add_subplot(gs00[11])
ramp_axs = [ax1_ramp, ax2_ramp, ax3_ramp, ax4_ramp, ax5_ramp,ax6_ramp, ax7_ramp, ax8_ramp, ramp_axs = [ax1_ramp, ax2_ramp, ax3_ramp, ax4_ramp, ax5_ramp,ax6_ramp, ax7_ramp, ax8_ramp,
ax9_ramp, ax10_ramp, ax11_ramp, ax12_ramp] ax9_ramp, ax10_ramp, ax11_ramp, ax12_ramp]
@ -120,16 +274,22 @@ for i in range(len(models)):
plot_ramp_V(ramp_axs[i], model=models[i]) plot_ramp_V(ramp_axs[i], model=models[i])
# add scalebar # add scalebar
add_scalebar(ax11_ramp, matchx=False, matchy=False, hidex=True, hidey=True, sizex=1000, sizey=25, labelx='1 s', plt.rcParams.update({'font.size': 6})
labely='25 mV', loc=3, pad=-2, borderpad=0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.05, 0.1, 1, 1),
bbox_transform=ax11_ramp.transAxes) add_scalebar(ax12_ramp, matchx=False, matchy=False, hidex=True, hidey=True, sizex=1000, sizey=50, labelx='1 s',
labely='50 mV', loc=3, pad=-2, borderpad=0, barwidth=1, bbox_to_anchor=Bbox.from_bounds(0.01, 0.05, 1, 1),
bbox_transform=ax12_ramp.transAxes)
# add_scalebar(ax12_ramp, matchx=False, matchy=False, hidex=True, hidey=True, sizex=1000, sizey=25, labelx='1 s', # add_scalebar(ax12_ramp, matchx=False, matchy=False, hidex=True, hidey=True, sizex=1000, sizey=25, labelx='1 s',
# labely='25 mV', loc=3, pad=-2, borderpad=0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.05, 0.1, 1, 1), # labely='25 mV', loc=3, pad=-2, borderpad=0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.05, 0.1, 1, 1),
# bbox_transform=ax12_ramp.transAxes) # bbox_transform=ax12_ramp.transAxes)
# add subplot labels # add subplot labels
for i in range(0,len(models)): 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') ramp_axs[i].text(-0.01, 1.1, string.ascii_uppercase[i], transform=ramp_axs[i].transAxes, size=10, weight='bold')
fig.savefig('./Figures/ramp_firing.pdf') # fig.savefig('./Figures/ramp_firing.pdf') #, bbox_inches='tight'
print(fig.dpi)
fig.set_size_inches(cm2inch(17.6,20))
fig.savefig('./Figures/ramp_firing.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show() plt.show()

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Figures/rheobase_correlation.pdf
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74
Figures/rheobase_correlation.py
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@ -13,7 +13,15 @@ import matplotlib
import matplotlib.lines as mlines import matplotlib.lines as mlines
from matplotlib import ticker from matplotlib import ticker
from matplotlib.ticker import NullFormatter from matplotlib.ticker import NullFormatter
from plotstyle import boxplot_style
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)
#%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ## #%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ##
# to change marker types in seaborn swarmplot # to change marker types in seaborn swarmplot
@ -44,7 +52,7 @@ def GetColor2Marker(markers):
mkcolors = [(palette[i]) for i in range(len(markers))] mkcolors = [(palette[i]) for i in range(len(markers))]
return dict(zip(mkcolors,markers)) return dict(zip(mkcolors,markers))
def fixlegend(ax,markers,markersize=8,**kwargs): def fixlegend(ax,markers,markersize=3,**kwargs):
# Fix Legend # Fix Legend
legtitle = ax.get_legend().get_title().get_text() legtitle = ax.get_legend().get_title().get_text()
_,l = ax.get_legend_handles_labels() _,l = ax.get_legend_handles_labels()
@ -90,8 +98,9 @@ Axes.scatter = new_scatter
######################################################################################################################## ########################################################################################################################
#%% #%%
def boxplot_with_markers(ax,max_width, alteration='shift'): def boxplot_with_markers(ax,max_width, alteration='shift', msize=2.2):
# size =4 # size =4
hlinewidth = 0.5
# ax.tick_params(axis='x', rotation=90) # ax.tick_params(axis='x', rotation=90)
model_names = ['RS pyramidal','RS inhibitory','FS', model_names = ['RS pyramidal','RS inhibitory','FS',
'RS pyramidal +$K_V1.1$','RS inhibitory +$K_V1.1$', 'RS pyramidal +$K_V1.1$','RS inhibitory +$K_V1.1$',
@ -125,14 +134,14 @@ def boxplot_with_markers(ax,max_width, alteration='shift'):
df = pd.read_csv('./Figures/Data/rheo_shift_corr.csv') df = pd.read_csv('./Figures/Data/rheo_shift_corr.csv')
sns.swarmplot(y="corr", x="$\Delta V_{1/2}$", hue="model", data=df, #dodge=True, sns.swarmplot(y="corr", x="$\Delta V_{1/2}$", hue="model", data=df, #dodge=True,
palette=clr_dict, linewidth=0, orient='v', ax=ax, palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation', order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
'$K_V1.1$ inactivation', 'A activation', 'A inactivation'], '$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
hue_order=model_names, co2mk=Markers) hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim() lim = ax.get_xlim()
ax.plot([lim[0], lim[1]], [0, 0], ':r') ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k') ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k') ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
ax.set_title("Shift ($\Delta V_{1/2}$)", y=1.05) ax.set_title("Shift ($\Delta V_{1/2}$)", y=1.05)
elif alteration=='slope': elif alteration=='slope':
i = 4 # Kv1.1 inact i = 4 # Kv1.1 inact
@ -141,14 +150,14 @@ def boxplot_with_markers(ax,max_width, alteration='shift'):
# Add in points to show each observation # Add in points to show each observation
sns.swarmplot(y="corr", x="Slope (k)", hue="model", data=df, #dodge=True, sns.swarmplot(y="corr", x="Slope (k)", hue="model", data=df, #dodge=True,
palette=clr_dict, linewidth=0, orient='v', ax=ax, palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation', order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
'$K_V1.1$ inactivation', 'A activation', 'A inactivation'], '$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
hue_order=model_names, co2mk=Markers) hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim() lim = ax.get_xlim()
ax.plot([lim[0], lim[1]], [0, 0], ':r') ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k') ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k') ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
ax.set_title("Slope (k)", y=1.05) ax.set_title("Slope (k)", y=1.05)
elif alteration=='g': elif alteration=='g':
i = 4 # Leak i = 4 # Leak
@ -157,13 +166,13 @@ def boxplot_with_markers(ax,max_width, alteration='shift'):
# Add in points to show each observation # Add in points to show each observation
sns.swarmplot(y="corr", x="g", hue="model", data=df, #dodge=True, sns.swarmplot(y="corr", x="g", hue="model", data=df, #dodge=True,
palette=clr_dict, linewidth=0, orient='v', ax=ax, palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
order=['Na', 'K', '$K_V1.1$', 'A', 'Leak'], order=['Na', 'K', '$K_V1.1$', 'A', 'Leak'],
hue_order=model_names, co2mk=Markers) hue_order=model_names, co2mk=Markers)
lim = ax.get_xlim() lim = ax.get_xlim()
ax.plot([lim[0], lim[1]], [0, 0], ':r') ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [1, 1], ':k') ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
ax.plot([lim[0], lim[1]], [-1, -1], ':k') ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
ax.set_title("Conductance (g)", y=1.05) ax.set_title("Conductance (g)", y=1.05)
else: else:
print('Please chose "shift", "slope" or "g"') print('Please chose "shift", "slope" or "g"')
@ -335,6 +344,7 @@ def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color
#%% #%%
boxplot_style()
color_dict = {'Cb stellate': '#40A787', # cyan'# color_dict = {'Cb stellate': '#40A787', # cyan'#
'RS Inhibitory': '#F0D730', # yellow 'RS Inhibitory': '#F0D730', # yellow
'FS': '#C02717', # red 'FS': '#C02717', # red
@ -350,16 +360,16 @@ color_dict = {'Cb stellate': '#40A787', # cyan'#
} }
# plot setup # plot setup
marker_s_leg = 8 marker_s_leg = 2
max_width = 10 max_width = 10
pad_x = 0.6 pad_x = 0.65
pad_y= 0.3 pad_y= 0.4
pad_w = 0.8 pad_w = 0.85
pad_h = 0.5 pad_h = 0.7
fig = plt.figure(figsize=(18,10)) fig = plt.figure(figsize=cm2inch(17.6,10))
gs = fig.add_gridspec(3, 6, wspace=0.9) gs = fig.add_gridspec(3, 6, wspace=1., hspace=0.8)
plt.subplots_adjust(hspace=0.8) #, wspace=0.6 # plt.subplots_adjust(hspace=0.8) #, wspace=0.6
ax0 = fig.add_subplot(gs[0,2:6]) ax0 = fig.add_subplot(gs[0,2:6])
ax0_ex = fig.add_subplot(gs[0,1]) ax0_ex = fig.add_subplot(gs[0,1])
ax0_fI = fig.add_subplot(gs[0,0]) ax0_fI = fig.add_subplot(gs[0,0])
@ -370,26 +380,27 @@ ax2 = fig.add_subplot(gs[2,2:6])
ax2_ex = fig.add_subplot(gs[2,1]) ax2_ex = fig.add_subplot(gs[2,1])
ax2_fI = fig.add_subplot(gs[2,0]) ax2_fI = fig.add_subplot(gs[2,0])
line_width = 1
# plot fI curves # plot fI curves
ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s', color1='lightgrey', color2='k') ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax0_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1) rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax0_fI.transAxes, color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax0_fI.add_patch(rec) rec = ax0_fI.add_patch(rec)
rec.set_clip_on(False) rec.set_clip_on(False)
ax1_fI = plot_fI(ax1_fI, model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u', color1='lightgrey', color2='k') ax1_fI = plot_fI(ax1_fI, model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax1_fI.transAxes, color=color_dict['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1) rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax1_fI.transAxes, color=color_dict['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax1_fI.add_patch(rec) rec = ax1_fI.add_patch(rec)
rec.set_clip_on(False) rec.set_clip_on(False)
ax2_fI = plot_fI(ax2_fI, model='Cb stellate', type='g', alt='Leak', color1='lightgrey', color2='k') ax2_fI = plot_fI(ax2_fI, model='Cb stellate', type='g', alt='Leak', color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=2,transform=ax2_fI.transAxes, color=color_dict['Cb stellate'], alpha=1, zorder=-1) rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1 + pad_h, fill=False, lw=line_width,transform=ax2_fI.transAxes, color=color_dict['Cb stellate'], alpha=1, zorder=-1)
rec = ax2_fI.add_patch(rec) rec = ax2_fI.add_patch(rec)
rec.set_clip_on(False) rec.set_clip_on(False)
# label fI subplots with letters # label fI subplots with letters
ax0_fI.text(-0.6, 1.28, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=16, weight='bold') #-0.09 ax0_fI.text(-0.95, 1.12, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=10, weight='bold') #-0.09
ax1_fI.text(-0.6, 1.28, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=16, weight='bold') ax1_fI.text(-0.95, 1.12, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=10, weight='bold')
ax2_fI.text(-0.6, 1.28, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=16, weight='bold') ax2_fI.text(-0.95, 1.12, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=10, weight='bold')
# plot boxplots # plot boxplots
boxplot_with_markers(ax0,max_width, alteration='shift') boxplot_with_markers(ax0,max_width, alteration='shift')
@ -407,7 +418,10 @@ 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') plot_rheo_alt(ax2_ex, model='Cb stellate', color1='lightgrey', color2='k', alteration='g')
# save # save
fig.savefig('./Figures/rheobase_correlation.pdf', bbox_inches='tight') # fig.savefig('./Figures/rheobase_correlation.pdf', bbox_inches='tight')
print(fig.dpi)
fig.set_size_inches(cm2inch(20.3,10))
fig.savefig('./Figures/rheobase_correlation.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show() plt.show()
# #%% alternative layout # #%% alternative layout

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45
Figures/simulation_model_comparison.py
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@ -3,11 +3,18 @@ import matplotlib.pyplot as plt
import pandas as pd import pandas as pd
import os import os
import string import string
from plotstyle import plot_style # from plotstyle import plot_style
from plotstyle import sim_style
import seaborn as sns import seaborn as sns
import scipy.stats as stats import scipy.stats as stats
import matplotlib.lines as mlines import matplotlib.lines as mlines
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 Kendall_tau(df): def Kendall_tau(df):
tau = df.corr(method='kendall') tau = df.corr(method='kendall')
@ -82,7 +89,7 @@ def correlation_plot(ax, df='AUC', title='', cbar=False):
else: else:
res = sns.heatmap(tau, annot=False, mask=mask, center=0, vmax=1, vmin=-1, linewidths=.5, square=True, ax=ax, res = sns.heatmap(tau, annot=False, mask=mask, center=0, vmax=1, vmin=-1, linewidths=.5, square=True, ax=ax,
cbar=True, cmap=cmap, cbar_ax=cbar_ax, ) cbar=True, cmap=cmap, cbar_ax=cbar_ax, )
cbar_ax.set_title(r'Kendall $\tau$', y=1.05) cbar_ax.set_title(r'Kendall $\tau$', y=1.02, loc='left')
ax.set_title(title) ax.set_title(title)
def mutation_plot2(ax, model='RS_pramidal'): def mutation_plot2(ax, model='RS_pramidal'):
@ -138,7 +145,7 @@ def mutation_plot2(ax, model='RS_pramidal'):
mut_names = AUC.index mut_names = AUC.index
ax.plot(rheo.loc[mut_names, model_names[mod]], AUC.loc[mut_names, model_names[mod]], linestyle='', ax.plot(rheo.loc[mut_names, model_names[mod]], AUC.loc[mut_names, model_names[mod]], linestyle='',
markeredgecolor='grey', markerfacecolor='grey', marker=Marker_dict[model_display_names[mod]], markeredgecolor='grey', markerfacecolor='grey', marker=Marker_dict[model_display_names[mod]],
markersize=4) # markeredgecolor=clr_dict[model_names[mod]],markerfacecolor=clr_dict[model_names[mod]], markersize=2) # markeredgecolor=clr_dict[model_names[mod]],markerfacecolor=clr_dict[model_names[mod]],
ax.plot(rheo.loc['wt', model_names[mod]], AUC.loc['wt', model_names[mod]], 'sk') ax.plot(rheo.loc['wt', model_names[mod]], AUC.loc['wt', model_names[mod]], 'sk')
@ -151,9 +158,9 @@ def mutation_plot2(ax, model='RS_pramidal'):
markeredgecolor=mut_col[2], markerfacecolor=mut_col[2], marker=Marker_dict[model_display_names[mod]],markersize=4) markeredgecolor=mut_col[2], markerfacecolor=mut_col[2], marker=Marker_dict[model_display_names[mod]],markersize=4)
ax.plot(rheo.loc['V404I', model_names[mod]], AUC.loc['V404I', model_names[mod]], linestyle='', ax.plot(rheo.loc['V404I', model_names[mod]], AUC.loc['V404I', model_names[mod]], linestyle='',
markeredgecolor=mut_col[3], markerfacecolor=mut_col[5], marker=Marker_dict[model_display_names[mod]],markersize=4) markeredgecolor=mut_col[3], markerfacecolor=mut_col[5], marker=Marker_dict[model_display_names[mod]],markersize=4)
ax.set_title(model_display_names[mod], fontsize=14)#, color=clr_dict[models[mod]]) ax.set_title(model_display_names[mod])#, color=clr_dict[models[mod]]) , fontsize=14
ax.set_xlabel('$\Delta$ Rheobase (nA)') ax.set_xlabel('$\Delta$ Rheobase (nA)', fontsize=6)
ax.set_ylabel('$AUC_{contrast}$') ax.set_ylabel('$AUC_{contrast}$', fontsize=6)
ax.spines['right'].set_visible(False) ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False) ax.spines['top'].set_visible(False)
return ax return ax
@ -169,19 +176,19 @@ 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') 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', V404I = mlines.Line2D([], [], color=colors[5], marker=Markers[3], markersize=marker_s_leg, linestyle='None',
label='V404I') label='V404I')
WT = mlines.Line2D([], [], color='k', marker='s', markersize=marker_s_leg+5, linestyle='None', label='Wild type') WT = mlines.Line2D([], [], color='k', marker='s', markersize=marker_s_leg+2, linestyle='None', label='Wild type')
ax.legend(handles=[WT, 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)
plot_style() # plot_style()
sim_style()
# plot setup # plot setup
fig = plt.figure(figsize=(18,12)) fig = plt.figure() #figsize=cm2inch(17.6,15)
gs0 = fig.add_gridspec(1, 5, wspace=3.5) gs0 = fig.add_gridspec(1, 6, wspace=3.5)
gsl = gs0[0:3].subgridspec(3, 3, wspace=0.6, hspace=0.6) gsl = gs0[0:4].subgridspec(3, 3, wspace=0.9, hspace=0.8)
gsr = gs0[3:5].subgridspec(2, 1, wspace=0.6, hspace=0.8) gsr = gs0[4:6].subgridspec(2, 1, wspace=0.6, hspace=1)
ax00 = fig.add_subplot(gsl[0,0]) ax00 = fig.add_subplot(gsl[0,0])
ax01 = fig.add_subplot(gsl[0,1]) ax01 = fig.add_subplot(gsl[0,1])
@ -220,11 +227,15 @@ correlation_plot(axr0,df = 'rheo', title='$\Delta rheobase$', cbar=True)
axs = [ax00, ax01,ax02, ax10, ax11, ax12, ax20, ax21, ax22] axs = [ax00, ax01,ax02, ax10, ax11, ax12, ax20, ax21, ax22]
j=0 j=0
for i in range(0,9): for i in range(0,9):
axs[i].text(-0.28, 1.08, string.ascii_uppercase[i], transform=axs[i].transAxes, size=16, weight='bold') axs[i].text(-0.48, 1.08, string.ascii_uppercase[i], transform=axs[i].transAxes, size=10, weight='bold')
j +=1 j +=1
axr0.text(-0.38, 1.2, string.ascii_uppercase[j], transform=axr0.transAxes, size=16, weight='bold') axr0.text(-0.38, 1.2, string.ascii_uppercase[j], transform=axr0.transAxes, size=10, weight='bold')
axr1.text(-0.38, 1.2, string.ascii_uppercase[j+1], transform=axr1.transAxes, size=16, weight='bold') axr1.text(-0.38, 1.2, string.ascii_uppercase[j+1], transform=axr1.transAxes, size=10, weight='bold')
# save # save
fig.savefig('./Figures/simulation_model_comparison.pdf', bbox_inches='tight') # fig.savefig('./Figures/simulation_model_comparison.pdf') #, bbox_inches='tight'
print(fig.dpi)
fig.set_size_inches(cm2inch(17.95,15))
fig.savefig('./Figures/simulation_model_comparison.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show() plt.show()

50
plotstyle.py
View File

@ -1,27 +1,59 @@
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
def plot_style():
def scheme_style():
plt.rcParams['xtick.direction'] = 'out' plt.rcParams['xtick.direction'] = 'out'
plt.rcParams['ytick.direction'] = 'out' plt.rcParams['ytick.direction'] = 'out'
plt.rcParams['axes.titlesize'] = 20 plt.rcParams['axes.titlesize'] = 20
plt.rcParams['axes.labelsize'] = 12 plt.rcParams['axes.labelsize'] = 8
plt.rcParams['lines.linewidth'] = 2 plt.rcParams['lines.linewidth'] = 2
plt.rcParams['lines.markersize'] = 10 plt.rcParams['lines.markersize'] = 10
plt.rcParams['xtick.labelsize'] = 10 plt.rcParams['xtick.labelsize'] = 10
plt.rcParams['ytick.labelsize'] = 10 plt.rcParams['ytick.labelsize'] = 10
plt.rcParams['savefig.bbox'] = 'tight' plt.rcParams['savefig.bbox'] = 'tight'
# plt.rcParams['figure.figsize'] = [8.0, 8.0]
plt.rcParams['figure.dpi'] = 300
def boxplot_style():
def plot_style():
plt.rcParams['xtick.direction'] = 'out' plt.rcParams['xtick.direction'] = 'out'
plt.rcParams['ytick.direction'] = 'out' plt.rcParams['ytick.direction'] = 'out'
plt.rcParams['axes.titlesize'] = 20
plt.rcParams['axes.labelsize'] = 12
plt.rcParams['lines.linewidth'] = 2 plt.rcParams['lines.linewidth'] = 2
plt.rcParams['lines.markersize'] = 1 plt.rcParams['lines.markersize'] = 10
plt.rcParams['xtick.labelsize'] = 10 plt.rcParams['xtick.labelsize'] = 10
plt.rcParams['ytick.labelsize'] = 10 plt.rcParams['ytick.labelsize'] = 10
plt.rcParams['savefig.bbox'] = 'tight' plt.rcParams['savefig.bbox'] = 'tight'
plt.rcParams['axes.titlesize'] = 12 plt.rcParams['figure.dpi'] = 300
plt.rcParams['axes.labelsize'] = 12
plt.rcParams['legend.fontsize']=10 def boxplot_style():
plt.rcParams['xtick.labelsize'] = 10 plt.rcParams['xtick.direction'] = 'out'
plt.rcParams['ytick.labelsize']=10 plt.rcParams['ytick.direction'] = 'out'
plt.rcParams['lines.linewidth'] = 1
plt.rcParams['lines.markersize'] = 0.5
plt.rcParams['xtick.labelsize'] = 4
plt.rcParams['ytick.labelsize'] = 4
plt.rcParams['savefig.bbox'] = 'tight'
plt.rcParams['axes.titlesize'] = 5
plt.rcParams['axes.labelsize'] = 4
plt.rcParams['legend.fontsize']= 4
plt.rcParams['xtick.labelsize'] = 3
plt.rcParams['ytick.labelsize']= 3
plt.rcParams['mathtext.default'] = 'regular' plt.rcParams['mathtext.default'] = 'regular'
plt.rcParams['figure.dpi'] = 300
def sim_style():
plt.rcParams['xtick.direction'] = 'out'
plt.rcParams['ytick.direction'] = 'out'
plt.rcParams['axes.titlesize'] = 6
plt.rcParams['axes.labelsize'] = 4
plt.rcParams['lines.linewidth'] = 1
plt.rcParams['lines.markersize'] = 4
plt.rcParams['xtick.labelsize'] = 4
plt.rcParams['ytick.labelsize'] = 4
plt.rcParams['savefig.bbox'] = 'tight'
plt.rcParams.update({'font.size': 4})
plt.rcParams['figure.dpi'] = 300