269 lines
9.1 KiB
Python
269 lines
9.1 KiB
Python
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
import scipy.io as spio
|
|
import scipy.stats as spst
|
|
import scipy as sp
|
|
from IPython import embed
|
|
|
|
|
|
def set_axis_fontsize(axis, label_size, tick_label_size=None, legend_size=None):
|
|
"""
|
|
Sets axis, tick label and legend font sizes to the desired size.
|
|
|
|
:param axis: the axes object
|
|
:param label_size: the size of the axis label
|
|
:param tick_label_size: the size of the tick labels. If None, lable_size is used
|
|
:param legend_size: the size of the font used in the legend.If None, the label_size is used.
|
|
|
|
"""
|
|
if not tick_label_size:
|
|
tick_label_size = label_size
|
|
if not legend_size:
|
|
legend_size = label_size
|
|
axis.xaxis.get_label().set_fontsize(label_size)
|
|
axis.yaxis.get_label().set_fontsize(label_size)
|
|
for tick in axis.xaxis.get_major_ticks() + axis.yaxis.get_major_ticks():
|
|
tick.label.set_fontsize(tick_label_size)
|
|
|
|
l = axis.get_legend()
|
|
if l:
|
|
for t in l.get_texts():
|
|
t.set_fontsize(legend_size)
|
|
|
|
|
|
def get_instantaneous_rate(times, max_t=30., dt=1e-4):
|
|
time = np.arange(0., max_t, dt)
|
|
indices = np.asarray(times / dt, dtype=int)
|
|
intervals = np.diff(np.hstack(([0], times)))
|
|
inst_rate = np.zeros(time.shape)
|
|
|
|
for i, index in enumerate(indices[1:]):
|
|
inst_rate[indices[i-1]:indices[i]] = 1/intervals[i]
|
|
return time, inst_rate
|
|
|
|
|
|
def plot_isi_rate(spike_times, max_t=30, dt=1e-4):
|
|
times = np.squeeze(spike_times[0][0])[:50000]
|
|
time, rate = get_instantaneous_rate(times, max_t=50000*dt)
|
|
|
|
rates = np.zeros((len(rate), len(spike_times)))
|
|
for i in range(len(spike_times)):
|
|
_, rates[:, i] = get_instantaneous_rate(np.squeeze(spike_times[i][0])[:50000],
|
|
max_t=50000*dt)
|
|
avg_rate = np.mean(rates, axis=1)
|
|
rate_std = np.std(rates, axis=1)
|
|
|
|
fig = plt.figure()
|
|
ax1 = fig.add_subplot(311)
|
|
ax2 = fig.add_subplot(312)
|
|
ax3 = fig.add_subplot(313)
|
|
|
|
ax1.vlines(times[times < (50000*dt)], ymin=0, ymax=1, color="dodgerblue", lw=1.5)
|
|
ax1.set_ylabel("skpikes", fontsize=12)
|
|
set_axis_fontsize(ax1, 12)
|
|
ax1.set_xlim([0, 5])
|
|
ax2.plot(time, rate, label="instantaneous rate, trial 1")
|
|
ax2.set_ylabel("firing rate [Hz]", fontsize=12)
|
|
ax2.legend(fontsize=12)
|
|
set_axis_fontsize(ax2, 12)
|
|
|
|
ax3.fill_between(time, avg_rate+rate_std, avg_rate-rate_std, color="dodgerblue",
|
|
alpha=0.5, label="standard deviation")
|
|
ax3.plot(time, avg_rate, label="average rate")
|
|
ax3.set_xlabel("times [s]", fontsize=12)
|
|
ax3.set_ylabel("firing rate [Hz]", fontsize=12)
|
|
ax3.legend(fontsize=12)
|
|
ax3.set_ylim([0, 450])
|
|
set_axis_fontsize(ax3, 12)
|
|
|
|
fig.set_size_inches(15, 10)
|
|
fig.subplots_adjust(left=0.1, bottom=0.125, top=0.95, right=0.95)
|
|
fig.set_facecolor("white")
|
|
fig.savefig("figures/instantaneous_rate.png")
|
|
plt.close()
|
|
|
|
|
|
def get_binned_rate(times, bin_width=0.05, max_t=30., dt=1e-4):
|
|
time = np.arange(0., max_t, dt)
|
|
bins = np.arange(0., max_t, bin_width)
|
|
bin_indices = bins / dt
|
|
hist, _ = sp.histogram(times, bins)
|
|
rate = np.zeros(time.shape)
|
|
|
|
for i, b in enumerate(bin_indices[1:]):
|
|
rate[bin_indices[i-1]:b] = hist[i-1]/bin_width
|
|
return time, rate
|
|
|
|
|
|
def plot_bin_rate(spike_times, bin_width, max_t=30, dt=1e-4):
|
|
times = np.squeeze(spike_times[0][0])
|
|
time, rate = get_binned_rate(times)
|
|
rates = np.zeros((len(rate), len(spike_times)))
|
|
for i in range(len(spike_times)):
|
|
_, rates[:, i] = get_binned_rate(np.squeeze(spike_times[i][0]))
|
|
avg_rate = np.mean(rates, axis=1)
|
|
rate_std = np.std(rates, axis=1)
|
|
|
|
fig = plt.figure()
|
|
ax1 = fig.add_subplot(311)
|
|
ax2 = fig.add_subplot(312)
|
|
ax3 = fig.add_subplot(313)
|
|
|
|
ax1.vlines(times[times < (100000*dt)], ymin=0, ymax=1, color="dodgerblue", lw=1.5)
|
|
ax1.set_ylabel("skpikes", fontsize=12)
|
|
ax1.set_xlim([0, 5])
|
|
set_axis_fontsize(ax1, 12)
|
|
|
|
ax2.plot(time, rate, label="binned rate, trial 1")
|
|
ax2.set_ylabel("firing rate [Hz]", fontsize=12)
|
|
ax2.legend(fontsize=12)
|
|
ax2.set_xlim([0, 5])
|
|
set_axis_fontsize(ax2, 12)
|
|
|
|
ax3.fill_between(time, avg_rate+rate_std, avg_rate-rate_std, color="dodgerblue",
|
|
alpha=0.5, label="standard deviation")
|
|
ax3.plot(time, avg_rate, label="average rate")
|
|
ax3.set_xlabel("times [s]", fontsize=12)
|
|
ax3.set_ylabel("firing rate [Hz]", fontsize=12)
|
|
ax3.legend(fontsize=12)
|
|
ax3.set_xlim([0, 5])
|
|
ax3.set_ylim([0, 450])
|
|
set_axis_fontsize(ax3, 12)
|
|
|
|
fig.set_size_inches(15, 10)
|
|
fig.subplots_adjust(left=0.1, bottom=0.125, top=0.95, right=0.95)
|
|
fig.set_facecolor("white")
|
|
fig.savefig("figures/binned_rate.png")
|
|
plt.close()
|
|
|
|
|
|
def get_convolved_rate(times, sigma, max_t=30., dt=1.e-4):
|
|
time = np.arange(0., max_t, dt)
|
|
kernel = spst.norm.pdf(np.arange(-8*sigma, 8*sigma, dt),loc=0,scale=sigma)
|
|
indices = np.asarray(times/dt, dtype=int)
|
|
rate = np.zeros(time.shape)
|
|
rate[indices] = 1.;
|
|
conv_rate = np.convolve(rate, kernel, mode="same")
|
|
return time, conv_rate
|
|
|
|
|
|
def plot_conv_rate(spike_times, sigma=0.05, max_t=30, dt=1e-4):
|
|
times = np.squeeze(spike_times[0][0])
|
|
time, rate = get_convolved_rate(times, sigma)
|
|
|
|
rates = np.zeros((len(rate), len(spike_times)))
|
|
for i in range(len(spike_times)):
|
|
_, rates[:, i] = get_convolved_rate(np.squeeze(spike_times[i][0]), sigma)
|
|
avg_rate = np.mean(rates, axis=1)
|
|
rate_std = np.std(rates, axis=1)
|
|
|
|
fig = plt.figure()
|
|
ax1 = fig.add_subplot(311)
|
|
ax2 = fig.add_subplot(312)
|
|
ax3 = fig.add_subplot(313)
|
|
|
|
ax1.vlines(times[times < (100000*dt)], ymin=0, ymax=1, color="dodgerblue", lw=1.5)
|
|
ax1.set_ylabel("skpikes", fontsize=12)
|
|
ax1.set_xlim([0, 5])
|
|
set_axis_fontsize(ax1, 12)
|
|
|
|
ax2.plot(time, rate, label="convolved rate, trial 1")
|
|
ax2.set_ylabel("firing rate [Hz]", fontsize=12)
|
|
ax2.legend(fontsize=12)
|
|
ax2.set_xlim([0, 5])
|
|
set_axis_fontsize(ax2, 12)
|
|
|
|
ax3.fill_between(time, avg_rate+rate_std, avg_rate-rate_std, color="dodgerblue",
|
|
alpha=0.5, label="standard deviation")
|
|
ax3.plot(time, avg_rate, label="average rate")
|
|
ax3.set_xlabel("times [s]", fontsize=12)
|
|
ax3.set_ylabel("firing rate [Hz]", fontsize=12)
|
|
ax3.legend(fontsize=12)
|
|
ax3.set_xlim([0, 5])
|
|
ax3.set_ylim([0, 450])
|
|
set_axis_fontsize(ax3, 12)
|
|
|
|
fig.set_size_inches(15, 10)
|
|
fig.subplots_adjust(left=0.1, bottom=0.125, top=0.95, right=0.95)
|
|
fig.set_facecolor("white")
|
|
fig.savefig("figures/convolved_rate.png")
|
|
plt.close()
|
|
|
|
|
|
def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
|
|
times = np.squeeze(spike_times[0][0])
|
|
time, conv_rate = get_convolved_rate(times, bin_width/np.sqrt(12.))
|
|
time, inst_rate = get_instantaneous_rate(times)
|
|
time, binn_rate = get_binned_rate(times, bin_width)
|
|
|
|
fig = plt.figure()
|
|
ax1 = fig.add_subplot(411)
|
|
ax2 = fig.add_subplot(412)
|
|
ax3 = fig.add_subplot(413)
|
|
ax4 = fig.add_subplot(414)
|
|
ax1.spines["right"].set_visible(False)
|
|
ax1.spines["top"].set_visible(False)
|
|
ax1.yaxis.set_ticks_position('left')
|
|
ax1.xaxis.set_ticks_position('bottom')
|
|
ax2.spines["right"].set_visible(False)
|
|
ax2.spines["top"].set_visible(False)
|
|
ax2.yaxis.set_ticks_position('left')
|
|
ax2.xaxis.set_ticks_position('bottom')
|
|
ax3.spines["right"].set_visible(False)
|
|
ax3.spines["top"].set_visible(False)
|
|
ax3.yaxis.set_ticks_position('left')
|
|
ax3.xaxis.set_ticks_position('bottom')
|
|
ax4.spines["right"].set_visible(False)
|
|
ax4.spines["top"].set_visible(False)
|
|
ax4.yaxis.set_ticks_position('left')
|
|
ax4.xaxis.set_ticks_position('bottom')
|
|
|
|
|
|
|
|
ax1.vlines(times[times < (100000*dt)], ymin=0, ymax=1, color="dodgerblue", lw=1.5)
|
|
ax1.set_ylabel("spikes", fontsize=10)
|
|
ax1.set_xlim([1.5, 3.5])
|
|
ax1.set_ylim([0, 1])
|
|
ax1.set_yticks([0, 1])
|
|
set_axis_fontsize(ax1, 10)
|
|
ax1.set_xticklabels([])
|
|
|
|
ax2.plot(time, inst_rate, lw=1.5, label="instantaneous rate")
|
|
ax2.set_ylabel("firing rate [Hz]", fontsize=10)
|
|
ax2.legend(fontsize=10)
|
|
ax2.set_xlim([1.5, 3.5])
|
|
ax2.set_ylim([0, 300])
|
|
set_axis_fontsize(ax2, 10)
|
|
ax2.set_xticklabels([])
|
|
|
|
ax3.plot(time, binn_rate, lw=1.5, label="binned rate")
|
|
ax3.set_ylabel("firing rate [Hz]", fontsize=10)
|
|
ax3.legend(fontsize=10)
|
|
ax3.set_xlim([1.5, 3.5])
|
|
ax3.set_ylim([0, 300])
|
|
set_axis_fontsize(ax3, 10)
|
|
ax3.set_xticklabels([])
|
|
|
|
ax4.plot(time, conv_rate, lw=1.5, label="convolved rate")
|
|
ax4.set_xlabel("time [s]", fontsize=10)
|
|
ax4.set_ylabel("firing rate [Hz]", fontsize=10)
|
|
ax4.legend(fontsize=10)
|
|
ax4.set_xlim([1.5, 3.5])
|
|
ax4.set_ylim([0, 300])
|
|
set_axis_fontsize(ax4, 10)
|
|
|
|
fig.set_size_inches(7.5, 5)
|
|
fig.subplots_adjust(left=0.1, bottom=0.125, top=0.95, right=0.95, )
|
|
fig.set_facecolor("white")
|
|
fig.savefig("firingrates.pdf")
|
|
plt.close()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
spike_times = spio.loadmat('lifoustim.mat')["spikes"]
|
|
# plot_isi_rate(spike_times)
|
|
# plot_bin_rate(spike_times, 0.05)
|
|
# plot_conv_rate(spike_times, 0.025)
|
|
plot_comparison(spike_times, 0.05, 0.025)
|
|
|