changes from meeting 06.03.2023; changed cell-type to neuron-type throughout, K to Kd throughout (including Fig 3 and 4), added references
This commit is contained in:
nkoch1
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@@ -1,38 +1,48 @@
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# -*- coding: utf-8 -*-
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"""
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Created on Sat Jul 3 19:52:04 2021
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Script to plot AUC correlations - Figure 3
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@author: nils
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"""
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__author__ = "Nils A. Koch"
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__copyright__ = "Copyright 2022, Nils A. Koch"
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__license__ = "MIT"
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import pandas as pd
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import numpy as np
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from numpy import ndarray
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import string
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import textwrap
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import json
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import seaborn as sns
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import matplotlib
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import matplotlib.pyplot as plt
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import matplotlib.lines as mlines
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import matplotlib.transforms
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import matplotlib.path
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import matplotlib.colors
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from matplotlib import ticker
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from matplotlib.ticker import NullFormatter
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from Figures.plotstyle import boxplot_style
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from matplotlib.axes._axes import Axes
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from matplotlib.markers import MarkerStyle
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from matplotlib.collections import LineCollection
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from Figures.plotstyle import corr_style
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def cm2inch(*tupl):
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'''
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convert cm to inch for plots size tuple
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'''
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inch = 2.54
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if isinstance(tupl[0], tuple):
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return tuple(i/inch for i in tupl[0])
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else:
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return tuple(i/inch for i in tupl)
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#%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ##
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# to change marker types in seaborn swarmplot
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import seaborn as sns
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import matplotlib.pyplot as plt
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############## Begin hack ##############
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from matplotlib.axes._axes import Axes
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from matplotlib.markers import MarkerStyle
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from numpy import ndarray
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#%% Modified from https://stackoverflow.com/a/52935294 (ImportanceOfBeingErnest and Miguel) under CC BY-SA 4.0 license
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def GetColor2Marker(markers):
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'''
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Modified from https://stackoverflow.com/a/52935294 (ImportanceOfBeingErnest and Miguel) under CC BY-SA 4.0 license
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'''
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colorslist = ['#40A787', # cyan'#
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'#F0D730', # yellow
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'#C02717', # red
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@@ -52,6 +62,9 @@ def GetColor2Marker(markers):
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return dict(zip(mkcolors,markers))
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def fixlegend(ax,markers,markersize=3,**kwargs):
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'''
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Modified from https://stackoverflow.com/a/52935294 (ImportanceOfBeingErnest and Miguel) under CC BY-SA 4.0 license
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'''
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# Fix Legend
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legtitle = ax.get_legend().get_title().get_text()
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_,l = ax.get_legend_handles_labels()
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@@ -79,6 +92,9 @@ def fixlegend(ax,markers,markersize=3,**kwargs):
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old_scatter = Axes.scatter
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def new_scatter(self, *args, **kwargs):
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'''
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Modified from https://stackoverflow.com/a/52935294 (ImportanceOfBeingErnest and Miguel) under CC BY-SA 4.0 license
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'''
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colors = kwargs.get("c", None)
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co2mk = kwargs.pop("co2mk",None)
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FinalCollection = old_scatter(self, *args, **kwargs)
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@@ -92,16 +108,32 @@ def new_scatter(self, *args, **kwargs):
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FinalCollection.set_paths(paths)
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return FinalCollection
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Axes.scatter = new_scatter
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############## End hack. ##############
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########################################################################################################################
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#%% add gradient arrows
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import matplotlib.pyplot as plt
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import matplotlib.transforms
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import matplotlib.path
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from matplotlib.collections import LineCollection
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def gradientaxis(ax, start, end, cmap, n=100,lw=1):
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# Arrow shaft: LineCollection
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'''
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add color gradient to axis
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Parameters
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----------
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ax : matplotlib axis
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axis to apply gradient to
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start : tuple
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start coordinates on axis
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end : tuple
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end coordinates on axis
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cmap : colormap
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colormap for gradient
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n : int
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number of segments in gradient
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lw : float
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width of axis line
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Returns
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-------
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ax : matplotlib axis
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updated axis with gradient
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'''
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x = np.linspace(start[0],end[0],n)
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y = np.linspace(start[1],end[1],n)
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points = np.array([x,y]).T.reshape(-1,1,2)
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@@ -110,15 +142,26 @@ def gradientaxis(ax, start, end, cmap, n=100,lw=1):
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lc.set_array(np.linspace(0,1,n))
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ax.add_collection(lc)
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return ax
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#%%
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#%%
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def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
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def corr_with_markers(ax,max_width, alteration='shift', msize=3):
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'''
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Plot Model Correlation as markers
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Parameters
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----------
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ax : matplotlib axis
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axis to plot on
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max_width :
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maximum width of label text
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alteration : string
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'shift', 'slope' or 'g'
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msize : float
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marker size
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'''
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hlinewidth = 0.5
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model_names = ['RS pyramidal','RS inhibitory','FS',
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'RS pyramidal +$K_V1.1$','RS inhibitory +$K_V1.1$',
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'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$',
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'Cb stellate $\Delta$$K_V1.1$','STN','STN +$K_V1.1$',
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'STN $\Delta$$K_V1.1$']
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model_names = ['RS pyramidal','RS inhibitory','FS', 'RS pyramidal +$K_V1.1$','RS inhibitory +$K_V1.1$',
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'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$', 'Cb stellate $\Delta$$K_V1.1$','STN',
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'STN +$K_V1.1$', 'STN $\Delta$$K_V1.1$']
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colorslist = ['#007030', # dark green
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'#F0D730', # yellow
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@@ -135,11 +178,12 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
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]
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import matplotlib.colors
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colors = [matplotlib.colors.to_rgb(c) for c in colorslist]
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clr_dict = {}
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for m in range(len(model_names)):
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clr_dict[model_names[m]] = colors[m]
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print(colors)
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print(clr_dict)
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Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
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if alteration=='shift':
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i = 2 # Kd act
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@@ -155,7 +199,7 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
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ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
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ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
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ax.set_title("Shift ($\Delta V_{1/2}$)", y=1.05)
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ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'K \nactivation', '$K_V1.1$ \nactivation',
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ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'Kd \nactivation', '$K_V1.1$ \nactivation',
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'$K_V1.1$ \ninactivation', 'A \nactivation', 'A \ninactivation'])
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elif alteration=='slope':
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i = 3 # Kv1.1 act
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@@ -173,7 +217,7 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
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ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
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ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
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ax.set_title("Slope (k)", y=1.05)
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ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'K \nactivation', '$K_V1.1$ \nactivation',
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ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'Kd \nactivation', '$K_V1.1$ \nactivation',
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'$K_V1.1$ \ninactivation', 'A \nactivation', 'A \ninactivation'])
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elif alteration=='g':
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i = 1 # Kd
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@@ -192,7 +236,8 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
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ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
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# Tweak the visual presentation
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ax.set_title("Conductance (g)", y=1.05)
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ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
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# ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
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ax.set_xticklabels(['Na', 'Kd', '$K_V1.1$', 'A', 'Leak'])
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else:
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print('Please chose "shift", "slope" or "g"')
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ax.get_legend().remove()
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@@ -202,19 +247,34 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
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def model_legend(ax, marker_s_leg, pos, ncol):
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colorslist = [ '#40A787', # cyan'#
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'#F0D730', # yellow
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'#C02717', # red
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'#007030', # dark green
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'#AAB71B', # lightgreen
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'#008797', # light blue
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'#F78017', # orange
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'#478010', # green
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'#53379B', # purple
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'#2060A7', # blue
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'#873770', # magenta
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'#D03050' # pink
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]
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'''
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plot model legend on axis
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Parameters
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----------
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ax : matplotlib axis
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axis to plot legend on
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marker_s_leg : int
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marker size in legend
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pos : tuple
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position in axis
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ncol : int
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number of columns in legend
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'''
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colorslist = ['#007030', # dark green
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'#F0D730', # yellow
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'#C02717', # red
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'#478010', # green
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'#AAB71B', # lightgreen
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'#F78017', # orange
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'#40A787', # cyan'#
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'#008797', # light blue
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'#2060A7', # blue
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'#D03050', # pink
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'#53379B', # purple
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'#873770', # magenta
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]
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import matplotlib.colors
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colors = [matplotlib.colors.to_rgb(c) for c in colorslist]
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model_pos = {'Cb stellate':0, 'RS Inhibitory':1, 'FS':2, 'RS Pyramidal':3,
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@@ -224,38 +284,44 @@ def model_legend(ax, marker_s_leg, pos, ncol):
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'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':9,
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'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':10, 'STN':11}
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Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
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RS_p = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal']], marker=Markers[model_pos['RS Pyramidal']], markersize=marker_s_leg, linestyle='None',
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label='RS pyramidal')
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RS_i = mlines.Line2D([], [], color=colors[model_pos['RS Inhibitory']], marker=Markers[model_pos['RS Inhibitory']], markersize=marker_s_leg, linestyle='None',
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label='RS inhibitory')
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FS = mlines.Line2D([], [], color=colors[model_pos['FS']], marker=Markers[model_pos['FS']], markersize=marker_s_leg, linestyle='None', label='FS')
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RS_p_Kv = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
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label='RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
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RS_i_Kv = mlines.Line2D([], [], color=colors[model_pos['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
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label='RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
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FS_Kv = mlines.Line2D([], [], color=colors[model_pos['Cb stellate']], marker=Markers[model_pos['Cb stellate']], markersize=marker_s_leg, linestyle='None', label='FS +$K_V1.1$')
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Cb = mlines.Line2D([], [], color=colors[8], marker=Markers[8], markersize=marker_s_leg, linestyle='None',
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label='Cb stellate')
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Cb_pl = mlines.Line2D([], [], color=colors[model_pos['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
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label='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
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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',
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label='Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
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STN = mlines.Line2D([], [], color=colors[model_pos['STN']], marker=Markers[model_pos['STN']], markersize=marker_s_leg, linestyle='None', label='STN')
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STN_pl = mlines.Line2D([], [], color=colors[model_pos['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
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label='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
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STN_sw = mlines.Line2D([], [], color=colors[model_pos['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
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label='STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
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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',
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bbox_to_anchor=pos, ncol=ncol, frameon=False)
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def plot_AUC_alt(ax, model='FS', color1='red', color2='dodgerblue', alteration='shift'):
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RS_p = mlines.Line2D([], [], color='#007030', marker="^", markersize=marker_s_leg, linestyle='None', label='Model D')
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RS_i = mlines.Line2D([], [], color='#F0D730', marker="o", markersize=marker_s_leg, linestyle='None', label='Model B')
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FS = mlines.Line2D([], [], color='#C02717', marker="o", markersize=marker_s_leg, linestyle='None', label='Model C')
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RS_p_Kv = mlines.Line2D([], [], color='#478010', marker="D", markersize=marker_s_leg, linestyle='None', label='Model H')
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RS_i_Kv = mlines.Line2D([], [], color='#AAB71B', marker="^", markersize=marker_s_leg, linestyle='None', label='Model E')
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FS_Kv = mlines.Line2D([], [], color='#F78017', marker="D", markersize=marker_s_leg, linestyle='None', label='Model G')
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Cb = mlines.Line2D([], [], color='#40A787', marker="o", markersize=marker_s_leg, linestyle='None', label='Model A')
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Cb_pl = mlines.Line2D([], [], color='#008797', marker="^", markersize=marker_s_leg, linestyle='None', label='Model F')
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Cb_sw = mlines.Line2D([], [], color='#2060A7', marker="s", markersize=marker_s_leg, linestyle='None', label='Model J')
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STN = mlines.Line2D([], [], color='#D03050', marker="s", markersize=marker_s_leg, linestyle='None', label='Model L')
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STN_pl = mlines.Line2D([], [], color='#53379B', marker="D", markersize=marker_s_leg, linestyle='None', label='Model I')
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STN_sw = mlines.Line2D([], [], color='#873770', marker="s", markersize=marker_s_leg, linestyle='None', label='Model K')
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ax.legend(handles=[Cb, RS_i, FS, RS_p, RS_i_Kv, Cb_pl, FS_Kv, RS_p_Kv, STN_pl, Cb_sw, STN_sw, STN], loc='center',
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bbox_to_anchor=pos, ncol=ncol, frameon=False)
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def plot_AUC_alt(ax, model='FS', alteration='shift'):
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'''
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plot the AUC across an alteration for all models with one emphasized
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Parameters
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----------
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ax : matplotlib axis
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axis to plot on
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model : string
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model to emphasize with thicker line
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alteration : string
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'shift', 'slope' or 'g'
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Returns
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-------
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ax : matplotlib axis
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updated axis with plot data
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'''
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ax.spines["right"].set_visible(False)
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ax.spines["top"].set_visible(False)
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model_names = ['RS Pyramidal','RS Inhibitory','FS',
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'RS Pyramidal +$K_V1.1$','RS Inhibitory +$K_V1.1$',
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'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$',
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'Cb stellate $\Delta$$K_V1.1$','STN','STN +$K_V1.1$',
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'STN $\Delta$$K_V1.1$']
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model_names = ['RS Pyramidal','RS Inhibitory','FS', 'RS Pyramidal +$K_V1.1$','RS Inhibitory +$K_V1.1$',
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'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$', 'Cb stellate $\Delta$$K_V1.1$','STN',
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'STN +$K_V1.1$', 'STN $\Delta$$K_V1.1$']
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model_name_dict = {'RS Pyramidal': 'RS Pyramidal',
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'RS Inhibitory': 'RS Inhibitory',
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@@ -337,6 +403,29 @@ def plot_AUC_alt(ax, model='FS', color1='red', color2='dodgerblue', alteration='
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return ax
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def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color2='dodgerblue'):
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'''
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plot fI curves for a model across an alteration in current parameters
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Parameters
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----------
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ax : matplotlib axis
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axis to plot on
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model : string
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model to plot
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type : string
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type of alteration: 'shift', 'slope', or 'g'
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alt : string
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model parameter that is altered
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color1 : string
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color at start of gradient
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color2 : string
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color at end of gradient
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Returns
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-------
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ax : matplotlib axis
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updated axis with plot data
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'''
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model_save_name = {'RS Pyramidal': 'RS_pyr_posp',
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'RS Inhibitory': 'RS_inhib_posp',
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'FS': 'FS_posp',
|
||||
@@ -366,7 +455,12 @@ def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color
|
||||
c += 1
|
||||
ax.set_ylabel('Frequency [Hz]')
|
||||
ax.set_xlabel('Current [nA]')
|
||||
ax.set_title(model, x=0.2, y=1.0)
|
||||
if model == 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':
|
||||
ax.set_title("Model G", x=0.2, y=1.0)
|
||||
elif model == 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':
|
||||
ax.set_title("Model I", x=0.2, y=1.0)
|
||||
else:
|
||||
ax.set_title("", x=0.2, y=1.0)
|
||||
ax.spines["right"].set_visible(False)
|
||||
ax.spines["top"].set_visible(False)
|
||||
L = ax.get_ylim()
|
||||
@@ -375,7 +469,7 @@ def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color
|
||||
|
||||
|
||||
#%%
|
||||
boxplot_style()
|
||||
corr_style()
|
||||
color_dict = {'Cb stellate': '#40A787', # cyan'#
|
||||
'RS Inhibitory': '#F0D730', # yellow
|
||||
'FS': '#C02717', # red
|
||||
@@ -443,19 +537,19 @@ rec = ax2_fI.add_patch(rec)
|
||||
rec.set_clip_on(False)
|
||||
|
||||
# plot boxplots
|
||||
boxplot_with_markers(ax0,max_width, alteration='shift')
|
||||
boxplot_with_markers(ax1,max_width, alteration='slope')
|
||||
boxplot_with_markers(ax2,max_width, alteration='g')
|
||||
corr_with_markers(ax0,max_width, alteration='shift')
|
||||
corr_with_markers(ax1,max_width, alteration='slope')
|
||||
corr_with_markers(ax2,max_width, alteration='g')
|
||||
|
||||
# plot legend
|
||||
pos = (0.225, -0.9)
|
||||
ncol = 5
|
||||
ncol = 6
|
||||
model_legend(ax2, marker_s_leg, pos, ncol)
|
||||
|
||||
# plot examples
|
||||
plot_AUC_alt(ax0_ex,model='FS +$\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}$', color1='lightgrey', color2='k', alteration='g')
|
||||
plot_AUC_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', alteration='shift')
|
||||
plot_AUC_alt(ax1_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', alteration='slope')
|
||||
plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', alteration='g')
|
||||
|
||||
# label subplots with letters
|
||||
ax0_fI.text(-0.875, 1.35, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=10, weight='bold')
|
||||
@@ -472,6 +566,6 @@ ax2.text(-0.075, 1.35, string.ascii_uppercase[8], transform=ax2.transAxes, size=
|
||||
|
||||
#save
|
||||
fig.set_size_inches(cm2inch(20.75,12))
|
||||
fig.savefig('./Figures/AUC_correlation.pdf', dpi=fig.dpi) #pdf #eps
|
||||
# fig.savefig('./Figures/AUC_correlation.png', dpi=fig.dpi) #pdf #eps
|
||||
fig.savefig('./Figures/AUC_correlation.pdf', dpi=fig.dpi)
|
||||
# fig.savefig('./Figures/AUC_correlation.png', dpi=fig.dpi) #png
|
||||
plt.show()
|
||||
|
||||
Binary file not shown.
@@ -1,22 +1,37 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Created on Sat Jul 3 19:52:04 2021
|
||||
Script to plot rheobase correlations - Figure 4
|
||||
|
||||
@author: nils
|
||||
"""
|
||||
__author__ = "Nils A. Koch"
|
||||
__copyright__ = "Copyright 2022, Nils A. Koch"
|
||||
__license__ = "MIT"
|
||||
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
from numpy import ndarray
|
||||
import string
|
||||
import textwrap
|
||||
import json
|
||||
import seaborn as sns
|
||||
import matplotlib
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.lines as mlines
|
||||
import matplotlib.transforms
|
||||
import matplotlib.path
|
||||
import matplotlib.colors
|
||||
from matplotlib import ticker
|
||||
from matplotlib.ticker import NullFormatter
|
||||
from Figures.plotstyle import boxplot_style
|
||||
from matplotlib.axes._axes import Axes
|
||||
from matplotlib.markers import MarkerStyle
|
||||
from matplotlib.collections import LineCollection
|
||||
from Figures.plotstyle import corr_style
|
||||
|
||||
|
||||
def cm2inch(*tupl):
|
||||
'''
|
||||
convert cm to inch for plots size tuple
|
||||
'''
|
||||
inch = 2.54
|
||||
if isinstance(tupl[0], tuple):
|
||||
return tuple(i/inch for i in tupl[0])
|
||||
@@ -24,16 +39,10 @@ def cm2inch(*tupl):
|
||||
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):
|
||||
'''
|
||||
Modified from https://stackoverflow.com/a/52935294 (ImportanceOfBeingErnest and Miguel) under CC BY-SA 4.0 license
|
||||
'''
|
||||
colorslist = ['#40A787', # cyan'#
|
||||
'#F0D730', # yellow
|
||||
'#C02717', # red
|
||||
@@ -53,6 +62,9 @@ def GetColor2Marker(markers):
|
||||
return dict(zip(mkcolors,markers))
|
||||
|
||||
def fixlegend(ax,markers,markersize=3,**kwargs):
|
||||
'''
|
||||
Modified from https://stackoverflow.com/a/52935294 (ImportanceOfBeingErnest and Miguel) under CC BY-SA 4.0 license
|
||||
'''
|
||||
# Fix Legend
|
||||
legtitle = ax.get_legend().get_title().get_text()
|
||||
_,l = ax.get_legend_handles_labels()
|
||||
@@ -80,6 +92,9 @@ def fixlegend(ax,markers,markersize=3,**kwargs):
|
||||
|
||||
old_scatter = Axes.scatter
|
||||
def new_scatter(self, *args, **kwargs):
|
||||
'''
|
||||
Modified from https://stackoverflow.com/a/52935294 (ImportanceOfBeingErnest and Miguel) under CC BY-SA 4.0 license
|
||||
'''
|
||||
colors = kwargs.get("c", None)
|
||||
co2mk = kwargs.pop("co2mk",None)
|
||||
FinalCollection = old_scatter(self, *args, **kwargs)
|
||||
@@ -93,33 +108,32 @@ def new_scatter(self, *args, **kwargs):
|
||||
FinalCollection.set_paths(paths)
|
||||
return FinalCollection
|
||||
Axes.scatter = new_scatter
|
||||
############## End hack. ##############
|
||||
########################################################################################################################
|
||||
#%% add gradient arrows
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.transforms
|
||||
import matplotlib.path
|
||||
from matplotlib.collections import LineCollection
|
||||
def rainbowarrow(ax, start, end, cmap, n=50,lw=3):
|
||||
# Arrow shaft: LineCollection
|
||||
x = np.linspace(start[0],end[0],n)
|
||||
y = np.linspace(start[1],end[1],n)
|
||||
points = np.array([x,y]).T.reshape(-1,1,2)
|
||||
segments = np.concatenate([points[:-1],points[1:]], axis=1)
|
||||
lc = LineCollection(segments, cmap=cmap, linewidth=lw)
|
||||
lc.set_array(np.linspace(0,1,n))
|
||||
ax.add_collection(lc)
|
||||
# Arrow head: Triangle
|
||||
tricoords = [(0,-0.02),(0.025,0),(0,0.02),(0,-0.02)]
|
||||
angle = np.arctan2(end[1]-start[1],end[0]-start[0])
|
||||
rot = matplotlib.transforms.Affine2D().rotate(angle)
|
||||
tricoords2 = rot.transform(tricoords)
|
||||
tri = matplotlib.path.Path(tricoords2, closed=True)
|
||||
ax.scatter(end[0],end[1], c=1, s=(4*lw)**2, marker=tri, cmap=cmap,vmin=0)
|
||||
ax.autoscale_view()
|
||||
return ax
|
||||
|
||||
def gradientaxis(ax, start, end, cmap, n=100,lw=1):
|
||||
'''
|
||||
add color gradient to axis
|
||||
Parameters
|
||||
----------
|
||||
ax : matplotlib axis
|
||||
axis to apply gradient to
|
||||
start : tuple
|
||||
start coordinates on axis
|
||||
end : tuple
|
||||
end coordinates on axis
|
||||
cmap : colormap
|
||||
colormap for gradient
|
||||
n : int
|
||||
number of segments in gradient
|
||||
lw : float
|
||||
width of axis line
|
||||
|
||||
|
||||
Returns
|
||||
-------
|
||||
ax : matplotlib axis
|
||||
updated axis with gradient
|
||||
'''
|
||||
# Arrow shaft: LineCollection
|
||||
x = np.linspace(start[0],end[0],n)
|
||||
y = np.linspace(start[1],end[1],n)
|
||||
@@ -129,8 +143,22 @@ def gradientaxis(ax, start, end, cmap, n=100,lw=1):
|
||||
lc.set_array(np.linspace(0,1,n))
|
||||
ax.add_collection(lc)
|
||||
return ax
|
||||
#%%
|
||||
def boxplot_with_markers(ax,max_width, alteration='shift', msize=2.2):
|
||||
|
||||
def corr_with_markers(ax,max_width, alteration='shift', msize=2.2):
|
||||
'''
|
||||
Plot Model Correlation as markers
|
||||
|
||||
Parameters
|
||||
----------
|
||||
ax : matplotlib axis
|
||||
axis to plot on
|
||||
max_width :
|
||||
maximum width of label text
|
||||
alteration : string
|
||||
'shift', 'slope' or 'g'
|
||||
msize : float
|
||||
marker size
|
||||
'''
|
||||
hlinewidth = 0.5
|
||||
model_names = ['RS pyramidal','RS inhibitory','FS',
|
||||
'RS pyramidal +$K_V1.1$','RS inhibitory +$K_V1.1$',
|
||||
@@ -157,8 +185,6 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=2.2):
|
||||
clr_dict = {}
|
||||
for m in range(len(model_names)):
|
||||
clr_dict[model_names[m]] = colors[m]
|
||||
print(colors)
|
||||
print(clr_dict)
|
||||
Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
|
||||
if alteration=='shift':
|
||||
i = 3 # Kv1.1 act
|
||||
@@ -174,7 +200,7 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=2.2):
|
||||
ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
|
||||
ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
|
||||
ax.set_title("Shift ($\Delta V_{1/2}$)", y=1.05)
|
||||
ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'K \nactivation', '$K_V1.1$ \nactivation',
|
||||
ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'Kd \nactivation', '$K_V1.1$ \nactivation',
|
||||
'$K_V1.1$ \ninactivation', 'A \nactivation', 'A \ninactivation'])
|
||||
elif alteration=='slope':
|
||||
i = 4 # Kv1.1 inact
|
||||
@@ -192,7 +218,7 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=2.2):
|
||||
ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
|
||||
ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
|
||||
ax.set_title("Slope (k)", y=1.05)
|
||||
ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'K \nactivation', '$K_V1.1$ \nactivation',
|
||||
ax.set_xticklabels(['Na \nactivation', 'Na \ninactivation', 'Kd \nactivation', '$K_V1.1$ \nactivation',
|
||||
'$K_V1.1$ \ninactivation', 'A \nactivation', 'A \ninactivation'])
|
||||
elif alteration=='g':
|
||||
i = 4 # Leak
|
||||
@@ -209,7 +235,8 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=2.2):
|
||||
ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
|
||||
ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
|
||||
ax.set_title("Conductance (g)", y=1.05)
|
||||
ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
|
||||
# ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
|
||||
ax.set_xticklabels(['Na', 'Kd', '$K_V1.1$', 'A', 'Leak'])
|
||||
else:
|
||||
print('Please chose "shift", "slope" or "g"')
|
||||
ax.get_legend().remove()
|
||||
@@ -219,78 +246,88 @@ def boxplot_with_markers(ax,max_width, alteration='shift', msize=2.2):
|
||||
|
||||
|
||||
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]
|
||||
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}$':10, 'STN':11}
|
||||
'''
|
||||
plot model legend on axis
|
||||
Parameters
|
||||
----------
|
||||
ax : matplotlib axis
|
||||
axis to plot legend on
|
||||
marker_s_leg : int
|
||||
marker size in legend
|
||||
pos : tuple
|
||||
position in axis
|
||||
ncol : int
|
||||
number of columns in legend
|
||||
|
||||
# model_pos = {'Cb stellate': 0, 'RS Inhibitory': 1, 'FS': 2, 'RS Pyramidal': 3,
|
||||
# 'RS Inhibitory +$\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}$': 10, 'STN': 11}
|
||||
colorslist = ['#007030', # dark green
|
||||
'#F0D730', # yellow
|
||||
'#C02717', # red
|
||||
'#478010', # green
|
||||
'#AAB71B', # lightgreen
|
||||
'#F78017', # orange
|
||||
'#40A787', # cyan'#
|
||||
'#008797', # light blue
|
||||
'#2060A7', # blue
|
||||
'#D03050', # pink
|
||||
'#53379B', # purple
|
||||
'#873770', # magenta
|
||||
]
|
||||
'''
|
||||
colorslist = [ '#40A787', # cyan'#
|
||||
'#F0D730', # yellow
|
||||
'#C02717', # red
|
||||
'#007030', # dark green
|
||||
'#AAB71B', # lightgreen
|
||||
'#008797', # light blue
|
||||
'#F78017', # orange
|
||||
'#478010', # green
|
||||
'#53379B', # purple
|
||||
'#2060A7', # blue
|
||||
'#873770', # magenta
|
||||
'#D03050' # pink
|
||||
]
|
||||
model_names = ['RS pyramidal', 'RS inhibitory', 'FS',
|
||||
'RS pyramidal +$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$']
|
||||
|
||||
|
||||
import matplotlib.colors
|
||||
colors = [matplotlib.colors.to_rgb(c) for c in colorslist]
|
||||
clr_dict = {}
|
||||
for m in range(len(model_names)):
|
||||
clr_dict[model_names[m]] = colors[m]
|
||||
|
||||
import matplotlib.colors
|
||||
colors = [matplotlib.colors.to_rgb(c) for c in colorslist]
|
||||
Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
|
||||
RS_p = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal']], marker=Markers[model_pos['RS Pyramidal']], markersize=marker_s_leg, linestyle='None',
|
||||
label='RS pyramidal')
|
||||
RS_i = mlines.Line2D([], [], color=colors[model_pos['RS Inhibitory']], marker=Markers[model_pos['RS Inhibitory']], markersize=marker_s_leg, linestyle='None',
|
||||
label='RS inhibitory')
|
||||
FS = mlines.Line2D([], [], color=colors[model_pos['FS']], marker=Markers[model_pos['FS']], markersize=marker_s_leg, linestyle='None', label='FS')
|
||||
RS_p_Kv = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal +$\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}$')
|
||||
ax.legend(handles=[RS_p, RS_i, FS, RS_p_Kv, RS_i_Kv, FS_Kv, Cb, Cb_pl, Cb_sw, STN, STN_pl, STN_sw], loc='center',
|
||||
|
||||
model_pos = {'RS Pyramidal':0, 'RS Inhibitory':1, 'FS':2,
|
||||
'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':3, 'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':4,
|
||||
'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':5, 'Cb stellate':6, 'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':7,
|
||||
'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':8, 'STN':9, 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':10,
|
||||
'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':11}
|
||||
|
||||
RS_p = mlines.Line2D([], [], color='#007030', marker="^", markersize=marker_s_leg, linestyle='None', label='Model D')
|
||||
RS_i = mlines.Line2D([], [], color='#F0D730', marker="o", markersize=marker_s_leg, linestyle='None', label='Model B')
|
||||
FS = mlines.Line2D([], [], color='#C02717', marker="o", markersize=marker_s_leg, linestyle='None', label='Model C')
|
||||
RS_p_Kv = mlines.Line2D([], [], color='#478010', marker="D", markersize=marker_s_leg, linestyle='None', label='Model H')
|
||||
RS_i_Kv = mlines.Line2D([], [], color='#AAB71B', marker="^", markersize=marker_s_leg, linestyle='None', label='Model E')
|
||||
FS_Kv = mlines.Line2D([], [], color='#F78017', marker="D", markersize=marker_s_leg, linestyle='None', label='Model G')
|
||||
Cb = mlines.Line2D([], [], color='#40A787', marker="o", markersize=marker_s_leg, linestyle='None', label='Model A')
|
||||
Cb_pl = mlines.Line2D([], [], color='#008797', marker="^", markersize=marker_s_leg, linestyle='None', label='Model F')
|
||||
Cb_sw = mlines.Line2D([], [], color='#2060A7', marker="s", markersize=marker_s_leg, linestyle='None', label='Model J')
|
||||
STN = mlines.Line2D([], [], color='#D03050', marker="s", markersize=marker_s_leg, linestyle='None', label='Model L')
|
||||
STN_pl = mlines.Line2D([], [], color='#53379B', marker="D", markersize=marker_s_leg, linestyle='None', label='Model I')
|
||||
STN_sw = mlines.Line2D([], [], color='#873770', marker="s", markersize=marker_s_leg, linestyle='None', label='Model K')
|
||||
ax.legend(handles=[Cb, RS_i, FS, RS_p, RS_i_Kv, Cb_pl, FS_Kv, RS_p_Kv, STN_pl, Cb_sw, STN_sw, STN], loc='center',
|
||||
bbox_to_anchor=pos, ncol=ncol, frameon=False)
|
||||
|
||||
def plot_rheo_alt(ax, model='FS', color1='red', color2='dodgerblue', alteration='shift'):
|
||||
def plot_rheo_alt(ax, model='FS', alteration='shift'):
|
||||
'''
|
||||
plot the rheobase across an alteration for all models with one emphasized
|
||||
Parameters
|
||||
----------
|
||||
ax : matplotlib axis
|
||||
axis to plot on
|
||||
model : string
|
||||
model to emphasize with thicker line
|
||||
alteration : string
|
||||
'shift', 'slope' or 'g'
|
||||
|
||||
Returns
|
||||
-------
|
||||
ax : matplotlib axis
|
||||
updated axis with plot data
|
||||
'''
|
||||
ax.spines["right"].set_visible(False)
|
||||
ax.spines["top"].set_visible(False)
|
||||
model_names = ['RS Pyramidal','RS Inhibitory','FS',
|
||||
@@ -373,15 +410,32 @@ def plot_rheo_alt(ax, model='FS', color1='red', color2='dodgerblue', alteration=
|
||||
end = (xend, ystart*1.0)
|
||||
ax = gradientaxis(ax, start, end, cmap, n=200,lw=4)
|
||||
ax.spines['bottom'].set_visible(False)
|
||||
# ax.set_ylim(ystart, yend)
|
||||
|
||||
#xlabel tick colors
|
||||
# my_colors = ['lightgrey', 'grey', 'k']
|
||||
# for ticklabel, tickcolor in zip(ax.get_xticklabels(), my_colors):
|
||||
# ticklabel.set_color(tickcolor)
|
||||
return ax
|
||||
|
||||
def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color2='dodgerblue'):
|
||||
'''
|
||||
plot fI curves for a model across an alteration in current parameters
|
||||
Parameters
|
||||
----------
|
||||
ax : matplotlib axis
|
||||
axis to plot on
|
||||
model : string
|
||||
model to plot
|
||||
type : string
|
||||
type of alteration: 'shift', 'slope', or 'g'
|
||||
alt : string
|
||||
model parameter that is altered
|
||||
color1 : string
|
||||
color at start of gradient
|
||||
color2 : string
|
||||
color at end of gradient
|
||||
|
||||
Returns
|
||||
-------
|
||||
ax : matplotlib axis
|
||||
updated axis with plot data
|
||||
|
||||
'''
|
||||
model_save_name = {'RS Pyramidal': 'RS_pyr_posp',
|
||||
'RS Inhibitory': 'RS_inhib_posp',
|
||||
'FS': 'FS_posp',
|
||||
@@ -409,30 +463,16 @@ def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color
|
||||
for i in newdf.index:
|
||||
ax.plot(json.loads(newdf.loc[i, 'I']), json.loads(newdf.loc[i, 'F']), color=colors[c])
|
||||
c += 1
|
||||
|
||||
# colors2 = [colors[10, :], 'k']
|
||||
# norm2 = plt.Normalize(min(cvals), max(cvals))
|
||||
# tuples2 = list(zip(map(norm2, cvals), colors2))
|
||||
# cmap2 = matplotlib.colors.LinearSegmentedColormap.from_list("", tuples2)
|
||||
#
|
||||
# colors3 = [colors[11, :], 'lightgrey']
|
||||
# norm3 = plt.Normalize(min(cvals), max(cvals))
|
||||
# tuples3 = list(zip(map(norm3, cvals), colors3))
|
||||
# cmap3 = matplotlib.colors.LinearSegmentedColormap.from_list("", tuples3)
|
||||
#
|
||||
# start = (1.1, json.loads(newdf.loc[10, 'F'])[-1])
|
||||
# end = (1.1, json.loads(newdf.loc[20, 'F'])[-1])#-json.loads(newdf.loc[20, 'F'])[-1]*0.1)
|
||||
# ax = rainbowarrow(ax, start, end, cmap2, n=50, lw=1)
|
||||
# ax.text(1.15, json.loads(newdf.loc[20, 'F'])[-1], '$+ \Delta V$', fontsize=4, color='k')
|
||||
#
|
||||
# start = (1.1, json.loads(newdf.loc[10, 'F'])[-1])
|
||||
# end = (1.1, json.loads(newdf.loc[0, 'F'])[-1])#-json.loads(newdf.loc[0, 'F'])[-1]*0.1)
|
||||
# ax = rainbowarrow(ax, start, end, cmap3, n=50, lw=1)
|
||||
# ax.text(1.15, json.loads(newdf.loc[0, 'F'])[-1], '$- \Delta V$', fontsize=4, color='lightgrey')
|
||||
|
||||
ax.set_ylabel('Frequency [Hz]')
|
||||
ax.set_xlabel('Current [nA]')
|
||||
ax.set_title(model, x=0.2, y=1.025)
|
||||
if model == 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':
|
||||
ax.set_title("Model G", x=0.2, y=1.0)
|
||||
elif model == 'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':
|
||||
ax.set_title("Model F", x=0.2, y=1.0)
|
||||
elif model == 'Cb stellate':
|
||||
ax.set_title("Model A", x=0.2, y=1.0)
|
||||
else:
|
||||
ax.set_title("", x=0.2, y=1.0)
|
||||
ax.spines["right"].set_visible(False)
|
||||
ax.spines["top"].set_visible(False)
|
||||
L = ax.get_ylim()
|
||||
@@ -441,7 +481,7 @@ def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color
|
||||
|
||||
|
||||
#%%
|
||||
boxplot_style()
|
||||
corr_style()
|
||||
color_dict = {'Cb stellate': '#40A787', # cyan'#
|
||||
'RS Inhibitory': '#F0D730', # yellow
|
||||
'FS': '#C02717', # red
|
||||
@@ -495,19 +535,19 @@ rec.set_clip_on(False)
|
||||
|
||||
|
||||
# plot boxplots
|
||||
boxplot_with_markers(ax0,max_width, alteration='shift')
|
||||
boxplot_with_markers(ax1,max_width, alteration='slope')
|
||||
boxplot_with_markers(ax2,max_width, alteration='g')
|
||||
corr_with_markers(ax0,max_width, alteration='shift')
|
||||
corr_with_markers(ax1,max_width, alteration='slope')
|
||||
corr_with_markers(ax2,max_width, alteration='g')
|
||||
|
||||
# plot legend
|
||||
pos = (0.225, -0.9)
|
||||
ncol = 5
|
||||
ncol = 6
|
||||
model_legend(ax2, marker_s_leg, pos, ncol)
|
||||
|
||||
# plot rheo across model for example alteration
|
||||
plot_rheo_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='shift')
|
||||
plot_rheo_alt(ax1_ex,model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k',alteration='slope')
|
||||
plot_rheo_alt(ax2_ex, model='Cb stellate', color1='lightgrey', color2='k', alteration='g')
|
||||
plot_rheo_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', alteration='shift')
|
||||
plot_rheo_alt(ax1_ex,model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', alteration='slope')
|
||||
plot_rheo_alt(ax2_ex, model='Cb stellate', alteration='g')
|
||||
|
||||
# label subplots with letters
|
||||
ax0_fI.text(-0.875, 1.35, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=10, weight='bold')
|
||||
@@ -525,40 +565,6 @@ ax2.text(-0.075, 1.35, string.ascii_uppercase[8], transform=ax2.transAxes, size=
|
||||
# save
|
||||
fig.set_size_inches(cm2inch(20.75,12))
|
||||
fig.savefig('./Figures/rheobase_correlation.pdf', dpi=fig.dpi)
|
||||
# fig.savefig('./Figures/rheobase_correlation.png', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi # eps # pdf
|
||||
# fig.savefig('./Figures/rheobase_correlation.png', dpi=fig.dpi)
|
||||
plt.show()
|
||||
|
||||
|
||||
#%%
|
||||
# fig, axs = plt.subplots(1,2)
|
||||
# axs[0] = plot_fI(axs[0] , model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s', color1='lightgrey', color2='k')
|
||||
# plt.show()
|
||||
#%%
|
||||
#
|
||||
#
|
||||
# cvals = [-2., 2]
|
||||
# colors = ['lightgrey', 'k']
|
||||
#
|
||||
# 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))
|
||||
#
|
||||
# colors2 = [colors[10,:], 'k']
|
||||
# norm2 = plt.Normalize(min(cvals), max(cvals))
|
||||
# tuples2 = list(zip(map(norm2, cvals), colors2))
|
||||
# cmap2 = matplotlib.colors.LinearSegmentedColormap.from_list("", tuples2)
|
||||
#
|
||||
# colors3 = [colors[11,:], 'lightgrey']
|
||||
# norm3 = plt.Normalize(min(cvals), max(cvals))
|
||||
# tuples3 = list(zip(map(norm3, cvals), colors3))
|
||||
# cmap3 = matplotlib.colors.LinearSegmentedColormap.from_list("", tuples3)
|
||||
#
|
||||
# fig, axs = plt.subplots(1,2)
|
||||
# start = (0,0)
|
||||
# end = (1,1)
|
||||
# axs[0] = rainbowarrow(axs[0], start, end, cmap2, n=50,lw=3)
|
||||
# start = (0,0)
|
||||
# end = (-1,-1)
|
||||
# axs[0] = rainbowarrow(axs[0], start, end, cmap3, n=50,lw=3)
|
||||
# plt.show()
|
||||
|
||||
Reference in New Issue
Block a user