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fig8.py
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# -*- coding: utf-8 -*-
# @Author: Theo Lemaire
# @Email: theo.lemaire@epfl.ch
# @Date: 2018-11-27 17:57:45
# @Last Modified by: Theo Lemaire
# @Last Modified time: 2019-06-12 23:13:05
''' Sub-panels of threshold curves for various sonophore radii and US frequencies. '''
import os
import logging
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from argparse import ArgumentParser
from PySONIC.neurons import getPointNeuron
from PySONIC.utils import logger, si_format, selectDirDialog
from PySONIC.plt import cm2inch
# Plot parameters
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
matplotlib.rcParams['font.family'] = 'arial'
# Figure basename
figbase = os.path.splitext(__file__)[0]
def getThresholdAmplitudes(root, neuron, a, Fdrive, tstim, PRF):
subfolder = '{} {:.0f}nm {}Hz PRF{}Hz {}s'.format(
neuron, a * 1e9,
*si_format([Fdrive, PRF, tstim], 0, space='')
)
fname = 'log_ASTIM.xlsx'
fpath = os.path.join(root, subfolder, fname)
df = pd.read_excel(fpath, sheet_name='Data')
DCs = df['Duty factor'].values
Athrs = df['Adrive (kPa)'].values
iDCs = np.argsort(DCs)
DCs = DCs[iDCs]
Athrs = Athrs[iDCs]
return DCs, Athrs
def plotThresholdAmps(root, neurons, radii, freqs, PRF, tstim, fs=10, colors=None, figsize=None):
''' Plot threshold excitation amplitudes of several neurons determined by titration procedures,
as a function of duty cycle, for various combinations of sonophore radius and US frequency.
:param neurons: list of neuron names
:param radii: list of sonophore radii (m)
:param freqs: list US frequencies (Hz)
:param PRF: pulse repetition frequency used for titration procedures (Hz)
:param tstim: stimulus duration used for titration procedures
:return: figure handle
'''
if figsize is None:
figsize = cm2inch(8, 7)
linestyles = ['--', ':', '-.']
assert len(freqs) <= len(linestyles), 'too many frequencies'
fig, ax = plt.subplots(figsize=figsize)
ax.set_xlabel('Duty cycle (%)', fontsize=fs)
ax.set_ylabel('Amplitude (kPa)', fontsize=fs)
for item in ax.get_xticklabels() + ax.get_yticklabels():
item.set_fontsize(fs)
ax.set_yscale('log')
ax.set_xlim([0, 100])
ax.set_ylim([10, 600])
linestyles = ['-', '--']
for neuron, ls in zip(neurons, linestyles):
icolor = 0
for i, a in enumerate(radii):
for j, Fdrive in enumerate(freqs):
if colors is None:
color = 'C{}'.format(icolor)
else:
color = colors[icolor]
DCs, Athrs = getThresholdAmplitudes(root, neuron, a, Fdrive, tstim, PRF)
lbl = '{} neuron, {:.0f} nm, {}Hz, {}Hz PRF'.format(
neuron, a * 1e9, *si_format([Fdrive, PRF], 0, space=' '))
ax.plot(DCs * 1e2, Athrs, ls, c=color, label=lbl)
icolor += 1
ax.legend(fontsize=fs - 5, frameon=False)
fig.tight_layout()
return fig
def main():
ap = ArgumentParser()
# Runtime options
ap.add_argument('-v', '--verbose', default=False, action='store_true',
help='Increase verbosity')
ap.add_argument('-i', '--inputdir', type=str, help='Input directory')
ap.add_argument('-f', '--figset', type=str, nargs='+', help='Figure set', default='all')
ap.add_argument('-s', '--save', default=False, action='store_true',
help='Save output figures as pdf')
args = ap.parse_args()
loglevel = logging.DEBUG if args.verbose is True else logging.INFO
logger.setLevel(loglevel)
inputdir = selectDirDialog() if args.inputdir is None else args.inputdir
if inputdir == '':
logger.error('No input directory chosen')
return
figset = args.figset
if figset == 'all':
figset = ['a', 'b']
logger.info('Generating panels {} of {}'.format(figset, figbase))
# Parameters
neurons = ['RS', 'LTS']
radii = np.array([16, 32, 64]) * 1e-9 # m
a = radii[1]
freqs = np.array([20, 500, 4000]) * 1e3 # Hz
Fdrive = freqs[1]
PRFs = np.array([1e1, 1e2, 1e3]) # Hz
PRF = PRFs[1]
tstim = 1 # s
colors = plt.get_cmap('tab20c').colors
# Generate figures
figs = []
if 'a' in figset:
fig = plotThresholdAmps(inputdir, neurons, radii, [Fdrive], PRF, tstim,
fs=12, colors=colors[:3][::-1])
fig.canvas.set_window_title(figbase + 'a')
figs.append(fig)
if 'b' in figset:
fig = plotThresholdAmps(inputdir, neurons, [a], freqs, PRF, tstim,
fs=12, colors=colors[8:11][::-1])
fig.canvas.set_window_title(figbase + 'b')
figs.append(fig)
if args.save:
for fig in figs:
figname = '{}.pdf'.format(fig.canvas.get_window_title())
fig.savefig(os.path.join(inputdir, figname), transparent=True)
else:
plt.show()
if __name__ == '__main__':
main()

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