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new firing_characterization-jb figure

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Jan Benda 2022-05-19 11:06:16 +02:00
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Figures/firing_characterization-jb.py Normal file
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import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import matplotlib.ticker as ticker
from matplotlib.colors import colorConverter as cc
from matplotlib.colors import to_hex
import string
# from plotstyle import plot_style
from plotstyle import scheme_style
colorslist = ['#40A787', # cyan'#
'#F0D730', # yellow
'#C02717', # red
'#007030', # dark green
'#AAB71B', # lightgreen
'#008797', # light blue
'#F78017', # orange
'#478010', # green
'#53379B', # purple
'#2060A7', # blue
'#873770', # magenta
'#D03050' # pink
]
def cm2inch(*tupl):
inch = 2.54
if isinstance(tupl[0], tuple):
return tuple(i/inch for i in tupl[0])
else:
return tuple(i/inch for i in tupl)
def show_spines(ax, spines='lrtb'):
""" Show and hide spines.
From github.com/janscience/plottools.git spines.py
Parameters
----------
ax: matplotlib figure, matplotlib axis, or list of matplotlib axes
Axis on which spine and ticks visibility is manipulated.
If figure, then apply manipulations on all axes of the figure.
If list of axes, apply manipulations on each of the given axes.
spines: string
Specify which spines and ticks should be shown.
All other ones or hidden.
'l' is the left spine, 'r' the right spine,
't' the top one and 'b' the bottom one.
E.g. 'lb' shows the left and bottom spine, and hides the top
and and right spines, as well as their tick marks and labels.
'' shows no spines at all.
'lrtb' shows all spines and tick marks.
Examples
--------
```py
import matplotlib.pyplot as plt
import plottools.spines
fig, (ax0, ax1, ax2) = plt.subplots(1, 3)
ax0.show_spines('lb')
ax1.show_spines('bt')
ax2.show_spines('tr')
```
![show](figures/spines-show.png)
"""
# collect spine visibility:
xspines = []
if 't' in spines:
xspines.append('top')
if 'b' in spines:
xspines.append('bottom')
yspines = []
if 'l' in spines:
yspines.append('left')
if 'r' in spines:
yspines.append('right')
# collect axes:
if isinstance(ax, (list, tuple, np.ndarray)):
axs = ax
elif hasattr(ax, 'get_axes'):
# ax is figure:
axs = ax.get_axes()
else:
axs = [ax]
if not isinstance(axs, (list, tuple)):
axs = [axs]
for ax in axs:
# hide spines:
ax.spines['top'].set_visible('top' in xspines)
ax.spines['bottom'].set_visible('bottom' in xspines)
ax.spines['left'].set_visible('left' in yspines)
ax.spines['right'].set_visible('right' in yspines)
# ticks:
if len(xspines) == 0:
ax.xaxis.set_ticks_position('none')
ax.xaxis.label.set_visible(False)
ax.xaxis._orig_major_locator = ax.xaxis.get_major_locator()
ax.xaxis.set_major_locator(ticker.NullLocator())
else:
if hasattr(ax.xaxis, '_orig_major_locator'):
ax.xaxis.set_major_locator(ax.xaxis._orig_major_locator)
delattr(ax.xaxis, '_orig_major_locator')
elif isinstance(ax.xaxis.get_major_locator(), ticker.NullLocator):
ax.xaxis.set_major_locator(ticker.AutoLocator())
if len(xspines) == 1:
ax.xaxis.set_ticks_position(xspines[0])
ax.xaxis.set_label_position(xspines[0])
else:
ax.xaxis.set_ticks_position('both')
ax.xaxis.set_label_position('bottom')
if len(yspines) == 0:
ax.yaxis.set_ticks_position('none')
ax.yaxis.label.set_visible(False)
ax.yaxis._orig_major_locator = ax.yaxis.get_major_locator()
ax.yaxis.set_major_locator(ticker.NullLocator())
else:
if hasattr(ax.yaxis, '_orig_major_locator'):
ax.yaxis.set_major_locator(ax.yaxis._orig_major_locator)
delattr(ax.yaxis, '_orig_major_locator')
elif isinstance(ax.yaxis.get_major_locator(), ticker.NullLocator):
ax.yaxis.set_major_locator(ticker.AutoLocator())
if len(yspines) == 1:
ax.yaxis.set_ticks_position(yspines[0])
ax.yaxis.set_label_position(yspines[0])
else:
ax.yaxis.set_ticks_position('both')
ax.yaxis.set_label_position('left')
def lighter(color, lightness):
""" Make a color lighter.
From github.com/janscience/plottools.git colors.py
![lighter](figures/colors-lighter.png)
Parameters
----------
color: dict or matplotlib color spec
A matplotlib color (hex string, name color string, rgb tuple)
or a dictionary with an 'color' or 'facecolor' key.
lightness: float
The smaller the lightness, the lighter the returned color.
A lightness of 0 returns white.
A lightness of 1 leaves the color untouched.
A lightness of 2 returns black.
Returns
-------
color: string or dict
The lighter color as a hexadecimal RGB string (e.g. '#rrggbb').
If `color` is a dictionary, a copy of the dictionary is returned
with the value of 'color' or 'facecolor' set to the lighter color.
Examples
--------
For 40% lightness of blue do
```py
import plottools.colors as c
colors = c.palettes['muted']
lightblue = c.lighter(colors['blue'], 0.4)
```
"""
try:
c = color['color']
cd = dict(**color)
cd['color'] = lighter(c, lightness)
return cd
except (KeyError, TypeError):
try:
c = color['facecolor']
cd = dict(**color)
cd['facecolor'] = lighter(c, lightness)
return cd
except (KeyError, TypeError):
if lightness > 2:
lightness = 2
if lightness > 1:
return darker(color, 2.0-lightness)
if lightness < 0:
lightness = 0
r, g, b = cc.to_rgb(color)
rl = r + (1.0-lightness)*(1.0 - r)
gl = g + (1.0-lightness)*(1.0 - g)
bl = b + (1.0-lightness)*(1.0 - b)
return to_hex((rl, gl, bl)).upper()
def plot_sqrt(ax, a=1, b=0.2, c=100, d=0):
x = np.linspace(0, 1, 10000)
y = c*np.sqrt(a*(x - b)) + d
ax.plot(x, y)
ax.set_xlabel('Current [nA]')
ax.set_ylabel('Frequency [Hz]')
ax.set_xlim(0,1)
ax.set_ylim(0, ax.get_ylim()[1])
def plot_AUC(ax, a=1, b=0.2, c=180, d=0, width=0.2):
x = np.linspace(0, 1, 1000)
y = c*np.sqrt(a*(x - b)) + d
ax.plot(x, y, colorslist[2])
ax.set_xlabel('Current [nA]')
ax.set_ylabel('Frequency [Hz]')
ax.fill_between(x, y, where=(x<=b+width), color=lighter(colorslist[2], 0.3))
ax.text(0.3, 15, 'AUC', ha='center')
ax.annotate('', (0.2, 10), (0, 10), arrowprops=dict(arrowstyle="<->"))
ax.text(0.1, 20, 'rheobase', ha='center')
ax.set_xlim(0, 0.5)
ax.set_ylim(0, 100)
ax.yaxis.set_major_locator(ticker.MultipleLocator(50))
def plot_diff_sqrt(ax, a=1, b=0.2, c=100, d=0, a2=1, b2=0.2, c2=100, d2=0):
show_spines(ax, 'lb')
x = np.linspace(0, 1, 10000)
y = c*np.sqrt(a*(x - b)) + d
y2 = c2 * np.sqrt(a2 * (x - b2)) + d2
ax.plot(x, y, colorslist[9])
ax.plot(x, y2, colorslist[2])
ax.set_xlim(0,1)
ax.set_ylim(0, ax.get_ylim()[1])
ax.set_xticks([])
ax.set_yticks([])
def plot_quadrant(ax):
ax.spines['left'].set_position('zero')
ax.spines['bottom'].set_position('zero')
ax.text(1.15, -0.15, '$\\Delta$ rheobase', ha='right')
ax.text(-0.05, 0.9, '$\\Delta$ AUC', ha='right')
ax.tick_params(length=0)
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.annotate('', (1, 0), (-1, 0), arrowprops=dict(arrowstyle="->"))
ax.annotate('', (0, 1), (0, -1), arrowprops=dict(arrowstyle="->"))
ax.set_xticks([-0.4, 0.4])
a = ax.get_xticks().tolist()
a[0] = '\u2212'
a[1] = '+'
ax.set_xticklabels(a)
ax.set_yticks([-0.4, 0.4])
b = ax.get_xticks().tolist()
b[0] = '\u2212'
b[1] = '+'
ax.set_yticklabels(b)
# ax.tick_params(labelsize=16)
# ax.set_yticks([0])
# ax.axis('off')
scheme_style()
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)
ax1 = fig.add_subplot(gs[0,:])
show_spines(ax1, 'lb')
plot_AUC(ax1, width=0.2)
ax3 = fig.add_subplot(gs[1:, :])
# add panel letter labels
ax_list = fig.axes
i =0
for a in ax_list:
a.text(-0.25, 1.08, string.ascii_uppercase[i], transform=a.transAxes,size=16, weight='bold')
i += 1
show_spines(ax3, '')
ax3.set_ylabel('$\Delta$ AUC')
ax3.set_xlabel('$\Delta$ rheobase')
plot_quadrant(ax3) # plot delineation into quadrants
inset_ylim = (0, 100)
# top left
lfsize = 8
ax3.text(x=-0.9, y=0.7, s='$\\uparrow$ AUC\n$\\downarrow$ rheobase', fontsize=lfsize)
ax3_TL = ax3.inset_axes([0.07, 0.6, 0.3, 0.2])
plot_diff_sqrt(ax3_TL, b2=0.1, c2=200)
ax3_TL.set_ylim(inset_ylim)
# top right
ax3.text(x=0.22, y=0.7, s='$\\uparrow$ AUC\n$\\uparrow$ rheobase', fontsize=lfsize)
ax3_TR = ax3.inset_axes([0.63, 0.6, 0.3, 0.2])
plot_diff_sqrt(ax3_TR, b2=0.4, c2=200)
ax3_TR.set_ylim(inset_ylim)
# bottom left
ax3.text(x=-0.9, y=-0.95, s='$\\downarrow$ AUC\n$\downarrow$ rheobase', fontsize=lfsize)
ax3_BL = ax3.inset_axes([0.07, 0.15, 0.3, 0.2])
plot_diff_sqrt(ax3_BL, b2=0.1, c2=75)
ax3_BL.set_ylim(inset_ylim)
# bottom right
ax3.text(x=0.22, y=-0.95, s='$\\downarrow$ AUC\n$\\uparrow$ rheobase', fontsize=lfsize)
ax3_BR = ax3.inset_axes([0.63, 0.15, 0.3, 0.2])
plot_diff_sqrt(ax3_BR, b2=0.4, c2=75)
ax3_BR.set_ylim(inset_ylim)
fig.set_size_inches(cm2inch(8.17,12))
fig.savefig('./Figures/firing_characterization.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi

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Figures/firing_characterization.pdf
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Figures/firing_characterization.py
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@ -29,7 +29,8 @@ def plot_AUC(ax, a=1, b=0.2, c=100, d=0, width=0.2):
ax.set_ylabel('Frequency [Hz]')
ax.fill_between(x,y, where=(x<=b+width), color='c')
ax.set_xlim(0,1)
ax.set_ylim(0, ax.get_ylim()[1])
ax.set_ylim(0, 100)
ax.yaxis.set_major_locator(ticker.MultipleLocator(50))
def plot_diff_sqrt(ax, a=1, b=0.2, c=100, d=0, a2=1, b2=0.2, c2=100, d2=0):
x = np.linspace(0, 1, 10000)

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manuscript.tex
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@ -276,7 +276,6 @@ To examine the role of cell-type specific ionic current environments on the impa
\begin{figure}[tp]
\centering
\includegraphics[width=0.5\linewidth]{Figures/firing_characterization.pdf}
\\\notejb{Ok, thanks. plotstyle.py is missing in the repository. Can you please add it?}\notenk{Sorry it should now be in \path{./Figures},}
\linespread{1.}\selectfont
\caption[]{Characterization of firing with AUC and rheobase. (A) The area under the curve (AUC) of the repetitive firing frequency-current (fI) curve. (B)
Changes in firing as characterized by \(\Delta\)AUC and \(\Delta\)rheobase occupy 4 quadrants separated by no changes in AUC and rheobase. Representative schematic fI curves in blue with respect to a reference fI curve (black) depict the general changes associated with each quadrant.}