def plot(self, dir_plot):
"""
Plotting stats about the spikes.
"""
# pylint: disable=too-many-locals
data = self.data
run_param = self.run_param
# String to put before output to the terminal.
str_start = self.name
str_start += " "*(20 - len(self.name)) + ":"
# Set global matplotlib parameters.
LFPy_util.plot.set_rc_param()
# Plot spike amps I {{{1 #
fname = self.name + '_spike_amps_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['r_vec'],
data['amps_I_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['r_vec'],
data['amps_I_mean'] - data['amps_I_std'],
data['amps_I_mean'] + data['amps_I_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel(r"Amplitude \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Distance from Soma \textbf{[\si{\micro\metre}]}")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# {{{ Plot spike amps I log
fname = self.name + '_spike_amps_I_log'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['r_vec'],
data['amps_I_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['r_vec'],
data['amps_I_mean'] - data['amps_I_std'],
data['amps_I_mean'] + data['amps_I_std'],
color=lcmaps.get_color(0),
alpha=0.2)
# Ugly way to put in some graphs for power laws.
# Left side.
x0 = data['r_vec'][0]
x1 = data['r_vec'][1]
y0 = data['amps_I_mean'][0]
for p in [1.0, 2.0, 3.0]:
y1 = np.power( 1.0 / data['r_vec'][1], p) * \
data['amps_I_mean'][ 0] / \
np.power(1.0 / data['r_vec'][0], p)
ax.plot([x0, x1], [y0, y1], color='black')
ax.annotate(
'-'+str(int(p)),
xy=(x1,y1),
xytext=(x1*1.01, y1*0.95),
)
# Right side.
x0 = data['r_vec'][-3]
x1 = data['r_vec'][-1]
y1 = data['amps_I_mean'][-1]
for p in [1.0, 2.0, 3.0]:
y0 = np.power(1.0 / data['r_vec'][-3], p) * \
data['amps_I_mean'][-1] / \
np.power(1.0 / data['r_vec'][-1], p)
ax.plot([x0, x1], [y0, y1], color='black')
ax.annotate(
'-'+str(int(p)),
xy=(x0,y0),
xytext=(x0*0.99, y0*0.95),
horizontalalignment='right',
)
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlim([data['r_vec'].min(), data['r_vec'].max()])
ticker = mpl.ticker.MaxNLocator(nbins=7)
ax.xaxis.set_major_locator(ticker)
ax.xaxis.get_major_formatter().labelOnlyBase = False
# ticker = mpl.ticker.MaxNLocator(nbins=7)
# ax.yaxis.set_major_locator(ticker)
# ax.yaxis.get_major_formatter().labelOnlyBase = False
# Set a label formatter to use normal numbers.
ax.xaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.yaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.set_ylabel(r"Amplitude \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Distance from Soma \textbf{[\si{\micro\metre}]}")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# Plot spike amps II {{{1 #
fname = self.name + '_spike_amps_II'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['r_vec'],
data['amps_II_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['r_vec'],
data['amps_II_mean'] - data['amps_II_std'],
data['amps_II_mean'] + data['amps_II_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel("Amplitude")
ax.set_xlabel("Distance from Soma")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# {{{ Plot spike amps II log
fname = self.name + '_spike_amps_II_log'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['r_vec'],
data['amps_II_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['r_vec'],
data['amps_II_mean'] - data['amps_II_std'],
data['amps_II_mean'] + data['amps_II_std'],
color=lcmaps.get_color(0),
alpha=0.2)
# Ugly way to put in some graphs for power laws.
# Left side.
x0 = data['r_vec'][0]
x1 = data['r_vec'][1]
y0 = data['amps_II_mean'][0]
for p in [1.0, 2.0, 3.0]:
y1 = np.power( 1.0 / data['r_vec'][1], p) * \
data['amps_II_mean'][ 0] / \
np.power(1.0 / data['r_vec'][0], p)
ax.plot([x0, x1], [y0, y1], color='black')
ax.annotate(
'-'+str(int(p)),
xy=(x1,y1),
xytext=(x1*1.01, y1*0.95),
)
# Right side.
x0 = data['r_vec'][-3]
x1 = data['r_vec'][-1]
y1 = data['amps_II_mean'][-1]
for p in [1.0, 2.0, 3.0]:
y0 = np.power(1.0 / data['r_vec'][-3], p) * \
data['amps_II_mean'][-1] / \
np.power(1.0 / data['r_vec'][-1], p)
ax.plot([x0, x1], [y0, y1], color='black')
ax.annotate(
'-'+str(int(p)),
xy=(x0,y0),
xytext=(x0*0.99, y0*0.95),
horizontalalignment='right',
)
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlim([data['r_vec'].min(), data['r_vec'].max()])
ticker = mpl.ticker.MaxNLocator(nbins=7)
ax.xaxis.set_major_locator(ticker)
ax.xaxis.get_major_formatter().labelOnlyBase = False
# ticker = mpl.ticker.MaxNLocator(nbins=7)
# ax.yaxis.set_major_locator(ticker)
# ax.yaxis.get_major_formatter().labelOnlyBase = False
# Set a label formatter to use normal numbers.
ax.xaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.yaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.set_ylabel(r"Amplitude \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Distance from Soma \textbf{[\si{\micro\metre}]}")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# Plot spike width I {{{1 #
fname = self.name + '_spike_width_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['r_vec'],
data['widths_I_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['r_vec'],
data['widths_I_mean'] - data['widths_I_std'],
data['widths_I_mean'] + data['widths_I_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel("Spike Width")
ax.set_xlabel("Distance from Soma")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot spike widths II {{{1 #
fname = self.name + '_spike_width_II'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['r_vec'],
data['widths_II_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(
data['r_vec'],
data['widths_II_mean'] - data['widths_II_std'],
data['widths_II_mean'] + data['widths_II_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel("Spike Width")
ax.set_xlabel("Distance from Soma")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot spike widths III {{{1 #
fname = self.name + '_spike_width_III'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['r_vec'],
data['widths_III_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(
data['r_vec'],
data['widths_III_mean'] - data['widths_III_std'],
data['widths_III_mean'] + data['widths_III_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel("Spike Width")
ax.set_xlabel("Distance from Soma")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot morphology xz {{{ #
LFPy_util.plot.morphology(data['poly_morph_xz'],
data['poly_morph_axon_xz'],
elec_x=data['elec_x'],
elec_y=data['elec_z'],
fig_size=lplot.size_square,
fname=self.name + "_morph_elec_xz",
plot_save_dir=dir_plot,
x_label='x',
y_label='z',
show=False)
# }}} #
# Spike to plot.
elec_index = run_param['n']/2
# title_str = r"Distance from Soma = \SI{{{}}}{{\micro\metre}}"
# title_str = title_str.format(round(data['r_vec'][elec_index]),2)
c = lcmaps.get_short_color_array(2 + 1)
# Plot middle electrode spike {{{1 #
fname = self.name + '_middle_elec_spike'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['spikes_t_vec'],
data['spikes'][elec_index],
color=c[0])
# Trace I
plt.plot(data['spikes_t_vec'],
data['widths_I_trace'][elec_index],
color=c[1],
)
# Trace II
plt.plot(data['spikes_t_vec'],
data['widths_II_trace'][elec_index],
color=c[1])
# plt.title(title_str)
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot middle electrode spike freq {{{1 #
fname = self.name + '_middle_elec_spike_fourier'
freq, amp, phase = de.find_freq_and_fft(
data['dt'],
data['spikes'][elec_index],
)
# Remove the first coefficient as we don't care about the baseline.
freq = np.delete(freq, 0)
amp = np.delete(amp, 0)
# Delete frequencies above the option.
if self.plot_param['freq_end'] is not None:
idx = min(
range(len(freq)),
key=lambda i: abs(freq[i] - self.plot_param['freq_end'])
)
freq = freq[0:idx]
amp = amp[0:idx]
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(freq, amp, color=lcmaps.get_color(0))
# plt.title(title_str)
ax.set_ylabel(r'Amplitude \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Frequency \textbf[$\mathbf{kHz}$\textbf]')
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot middle electrode signal {{{1 #
fname = self.name + '_middle_elec'
print "plotting :", fname
c = lcmaps.get_short_color_array(2 + 1)
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['t_vec'],
data['LFP'][elec_index],
color=lcmaps.get_color(0))
# plt.title(title_str)
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot middle electrode signal freq {{{1 #
fname = self.name + '_middle_elec_fourier'
freq, amp, phase = de.find_freq_and_fft(
data['dt'],
data['LFP'][elec_index],
)
# Remove the first coefficient as we don't care about the baseline.
freq = np.delete(freq, 0)
amp = np.delete(amp, 0)
if self.plot_param['freq_end'] is not None:
idx = min(
range(len(freq)),
key=lambda i: abs(freq[i] - self.plot_param['freq_end'])
)
freq = freq[0:idx]
amp = amp[0:idx]
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(freq, amp, color=lcmaps.get_color(0))
ax.set_ylabel(r'Amplitude \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Frequency \textbf[$\mathbf{kHz}$\textbf]')
# plt.title(title_str)
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
if self.plot_param['plot_detailed']:
# Create the directory if it does not exist.
sub_dir = os.path.join(dir_plot, self.name + "_detailed")
if not os.path.exists(sub_dir):
os.makedirs(sub_dir)
# t = len(run_param['theta'])
# p = run_param['n_phi']
p = 1
n = run_param['n']
# This title string should be formatted.
title_str = r"Distance from Soma = \SI{{{}}}{{\micro\metre}}"
cnt = 0
for j in xrange(p):
for k in xrange(n):
title_str_1 = title_str.format(data['r_vec'][k])
# Plot all elec spikes {{{1 #
fname = self.name + '_elec_p_{}_n_{}'.format(j * 360 / p, k)
print "plotting :", fname
c = lcmaps.get_short_color_array(2 + 1)
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['spikes_t_vec'],
data['spikes'][cnt],
color=c[0])
# Trace I
plt.plot(data['spikes_t_vec'],
data['widths_I_trace'][cnt],
color=c[1],
)
# Trace II
plt.plot(data['spikes_t_vec'],
data['widths_II_trace'][cnt],
color=c[1])
# Trace III
plt.plot(data['spikes_t_vec'],
data['widths_III_trace'][cnt],
color=c[1])
# plt.title(title_str_1)
# Save plt.
lplot.save_plt(plt, fname, sub_dir)
plt.close()
# 1}}} #
# Plot all elec spikes freq {{{1 #
# Fourier plot.
fname = self.name + '_freq_elec_p_{}_n_{}'.format(j * 360 / p, k)
freq, amp, phase = de.find_freq_and_fft(
data['dt'],
data['spikes'][cnt],
)
# Remove the first coefficient as we don't care about the baseline.
freq = np.delete(freq, 0)
amp = np.delete(amp, 0)
if self.plot_param['freq_end'] is not None:
idx = min(
range(len(freq)),
key=lambda i: abs(freq[i] - self.plot_param['freq_end'])
)
freq = freq[0:idx]
amp = amp[0:idx]
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(freq, amp, color=c[0])
ax.set_ylabel(r'Amplitude \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Frequency \textbf[$\mathbf{kHz}$\textbf]')
# plt.title(title_str_1)
lplot.save_plt(plt, fname, sub_dir)
plt.close()
# 1}}} #
cnt += 1
##############################################################################################
if __name__ == "__main__":
# Set global matplotlib parameters.
lplot.set_rc_param()
## set parameters
p = set_parameters()
## simulate
Vm, I = simulate(p)
print "plotting original signal"
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
ax.set_ylabel(r"Mem. Pot. \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
plt.plot(p['time'], Vm, color=lcmaps.get_color(0))
lplot.save_plt(plt, "cs_ap_original_signal", ".")
plt.close()
# Remove the preparation part of the signal.
I = I[int(-p['t_start'] / p['dt']):-1]
Vm = Vm[int(-p['t_start'] / p['dt']):-1]
p['time'] = p['time'][int(-p['t_start'] / p['dt']):-1]
pre_dur = 8.35
post_dur = 8.35
spikes, t_vec, _ = LFPy_util.data_extraction.extract_spikes(
def plot(self, dir_plot):
data = self.data
run_param = self.run_param
process_param = self.process_param
# Set global matplotlib parameters.
LFPy_util.plot.set_rc_param(self.plot_param['use_tex'])
# Plot Spike Width I hist {{{1 #
# New plot.
fname = self.name + '_spike_width_I_hist'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
bins = np.arange(0, 2.5, data['dt'])
n, _, patches = plt.hist(data['widths_I'], bins)
ax.set_xlabel("Width Peak-to-peak")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# Plot Spike Width II hist {{{1 #
# New plot.
fname = self.name + '_spike_width_II_hist'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
bins = np.arange(0, 2.5, data['dt'])
n, _, patches = plt.hist(data['widths_II'], bins)
ax.set_xlabel("Width Peak-to-peak")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# Plot morphology {{{ #
LFPy_util.plot.morphology(data['poly_morph'],
data['poly_morph_axon'],
elec_x=data['elec_x'],
elec_y=data['elec_y'],
fig_size=lplot.size_square,
fname=self.name + "_morph_elec_xy",
plot_save_dir=dir_plot,
show=False)
# }}} #
# Plot 3d points {{{1 #
# 3D plot.
fname = self.name + "_elec_pos"
c = lcmaps.get_short_color_array(5)[2]
fig = plt.figure(figsize=lplot.size_common)
ax = fig.add_subplot(111, projection='3d')
ax.scatter(data['elec_x'], data['elec_y'], data['elec_z'], c=c)
ax.set_xlim(-run_param['R'], run_param['R'])
ax.set_ylim(-run_param['R'], run_param['R'])
ax.set_zlim(-run_param['R'], run_param['R'])
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot spike amps I {{{1 #
# New plot.
fname = self.name + '_spike_amps_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['bins'],
data['amps_I_mean'],
color=lplot.color_array_long[0],
marker='o',
markersize=5)
ax.fill_between(data['bins'],
data['amps_I_mean'] - data['amps_I_std'],
data['amps_I_mean'] + data['amps_I_std'],
color=lplot.color_array_long[0],
alpha=0.2)
ax.set_ylabel(r"Amplitude \textbf{[\si{\micro\volt}]}")
ax.set_xlabel(r"Distance from Soma \textbf{[\si{\micro\metre}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot spike amps II {{{1 #
# New plot.
fname = self.name + '_spike_amps_II'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['bins'],
data['amps_II_mean'],
color=lplot.color_array_long[0],
marker='o',
markersize=5)
ax.fill_between(data['bins'],
data['amps_II_mean'] - data['amps_II_std'],
data['amps_II_mean'] + data['amps_II_std'],
color=lplot.color_array_long[0],
alpha=0.2)
ax.set_ylabel("Amplitude")
ax.set_xlabel("Distance from Soma")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot Spike Width I {{{1 #
# New plot.
fname = self.name + '_spike_width_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['bins'],
data['widths_I_mean'],
color=lplot.color_array_long[0],
marker='o',
markersize=5)
ax.fill_between(data['bins'],
data['widths_I_mean'] - data['widths_I_std'],
data['widths_I_mean'] + data['widths_I_std'],
color=lplot.color_array_long[0],
alpha=0.2)
ax.set_ylabel("Width Type I")
ax.set_xlabel("Distance from Soma")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# Plot Spike Width II {{{1 #
# New plot.
fname = self.name + '_spike_width_II'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['bins'],
data['widths_II_mean'],
color=lplot.color_array_long[0],
marker='o',
markersize=5)
ax.fill_between(data['bins'],
data['widths_II_mean'] - data['widths_II_std'],
data['widths_II_mean'] + data['widths_II_std'],
color=lplot.color_array_long[0],
alpha=0.2)
ax.set_ylabel("Width Type II")
ax.set_xlabel("Distance from Soma")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# Plot Single Electrodes {{{1 #
# Title string that can be formatted.
title_str = r"Distance from Soma = \SI{{{}}}{{\micro\metre}}"
for i in self.plot_param['elec_to_plot']:
title_str_1 = title_str.format(round(data['elec_r'][[i]],2))
fname = self.name + '_elec_{}'.format(i)
print "plotting :", fname
c = lcmaps.get_short_color_array(2 + 1)
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['spikes_t_vec'], data['spikes'][i], color=c[0])
# Trace I
plt.plot(data['spikes_t_vec'],
data['widths_I_trace'][i],
color=c[1],
)
# Trace II
plt.plot(data['spikes_t_vec'],
data['widths_II_trace'][i],
color=c[1])
plt.title(title_str_1)
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# Plot Correlation {{{1 #
# Correlation scatter plot of spike widths.
fname = self.name + '_correlation'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.scatter(data['widths_II_original'],
data['widths_I_original'],
color=lplot.color_array_long[0],
marker='x')
# Add lines to represent the cutoff limits.
if process_param['assert_width']:
plt.axhline(
process_param['assert_width_I_low'],
color=lcmaps.get_color(0.8),
)
plt.axhline(
process_param['assert_width_I_high'],
color=lcmaps.get_color(0.8),
)
plt.axvline(
process_param['assert_width_II_low'],
color=lcmaps.get_color(0.8),
)
plt.axvline(
process_param['assert_width_II_high'],
color=lcmaps.get_color(0.8),
)
ax.set_xlabel("Spike Width Type II")
ax.set_ylabel("Spike Width Type I")
# ax.set_aspect('equal')
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# Plot Electrode Histo {{{1 #
fname = self.name + '_r_hist'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.hist(data['elec_r_all'],
self.process_param['bins'] - 1,
range=(0, data['elec_r_all'].max()),
facecolor=lplot.color_array_long[0],
alpha=0.5)
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
def plot(self, dir_plot):
"""
Plotting stats about the spikes.
"""
# pylint: disable=too-many-locals
data = self.data
run_param = self.run_param
# String to put before output to the terminal.
str_start = self.name
str_start += " "*(20 - len(self.name)) + ":"
# Set global matplotlib parameters.
LFPy_util.plot.set_rc_param()
# 3D plot {{{1 #
fname = self.name + "_elec_pos"
c = lplot.get_short_color_array(5)[2]
fig = plt.figure(figsize=lplot.size_common)
ax = fig.add_subplot(111, projection='3d')
cnt = 0
for i, theta in enumerate(run_param['theta']):
for j in xrange(run_param['n_phi']):
for k in xrange(run_param['n']):
ax.scatter(data['elec_x'][cnt],
data['elec_y'][cnt],
data['elec_z'][cnt],
c=c)
cnt += 1
ax.set_xlim(-run_param['R'], run_param['R'])
ax.set_ylim(-run_param['R'], run_param['R'])
ax.set_zlim(-run_param['R'], run_param['R'])
ax.set_xlabel("X axis")
ax.set_ylabel("Y axis")
ax.set_zlabel("Z axis")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot spike amps I {{{1 #
fname = self.name + '_spike_amps_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
c = lplot.get_short_color_array(data['amps_I_mean'].shape[0] + 1)
for t in xrange(data['amps_I_mean'].shape[0]):
label = r'$\theta = {}\degree$'.format(run_param['theta'][t])
plt.plot(data['r_vec'],
data['amps_I_mean'][t],
color=c[t],
marker='o',
markersize=5,
label=label)
ax.fill_between(data['r_vec'],
data['amps_I_mean'][t] - data['amps_I_std'][t],
data['amps_I_mean'][t] + data['amps_I_std'][t],
color=c[t],
alpha=0.2)
handles, labels = ax.get_legend_handles_labels()
# Position the legen on the right side of the plot.
ax.legend(handles,
labels,
loc='upper left',
bbox_to_anchor=(1.0, 1.04), )
ax.set_ylabel(r"Amplitude \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Distance from Soma \textbf{[\si{\micro\metre}]}")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}} #
# {{{ Plot spike amps I log
fname = self.name + '_spike_amps_I_log'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
c = lplot.get_short_color_array(data['amps_I_mean'].shape[0] + 1)
for t in xrange(data['amps_I_mean'].shape[0]):
label = r'$\theta = {}\degree$'.format(run_param['theta'][t])
plt.plot(data['r_vec'],
data['amps_I_mean'][t],
color=c[t],
marker='o',
markersize=5,
label=label)
ax.fill_between(data['r_vec'],
data['amps_I_mean'][t] - data['amps_I_std'][t],
data['amps_I_mean'][t] + data['amps_I_std'][t],
color=c[t],
alpha=0.2)
# # Ugly way to put in some graphs for power laws.
# # Left side.
# x0 = data['r_vec'][0]
# x1 = data['r_vec'][1]
# y0 = data['amps_I_mean'][t, 0]
# for p in [1.0, 2.0, 3.0]:
# y1 = np.power( 1.0 / data['r_vec'][1], p) * \
# data['amps_I_mean'][t, 0] / \
# np.power(1.0 / data['r_vec'][0], p)
# ax.plot([x0, x1], [y0, y1], color='black')
# # Right side.
# x0 = data['r_vec'][-3]
# x1 = data['r_vec'][-1]
# y1 = data['amps_I_mean'][t,-1]
# for p in [1.0, 2.0, 3.0]:
# y0 = np.power(1.0 / data['r_vec'][-3], p) * \
# data['amps_I_mean'][t, -1] / \
# np.power(1.0 / data['r_vec'][-1], p)
# ax.plot([x0, x1], [y0, y1], color='black')
handles, labels = ax.get_legend_handles_labels()
# Position the legen on the right side of the plot.
ax.legend(handles,
labels,
loc='upper left',
bbox_to_anchor=(1.0, 1.04), )
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlim([data['r_vec'].min(), data['r_vec'].max()])
ticker = mpl.ticker.MaxNLocator(nbins=7)
ax.xaxis.set_major_locator(ticker)
ax.xaxis.get_major_formatter().labelOnlyBase = False
# ticker = mpl.ticker.MaxNLocator(nbins=7)
# ax.yaxis.set_major_locator(ticker)
# ax.yaxis.get_major_formatter().labelOnlyBase = False
# Set a label formatter to use normal numbers.
ax.xaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.yaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.set_ylabel(r"Amplitude \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Distance from Soma \textbf{[\si{\micro\metre}]}")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# Plot spike amps II {{{1 #
fname = self.name + '_spike_amps_II'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
c = lplot.get_short_color_array(data['amps_II_mean'].shape[0] + 1)
for t in xrange(data['amps_II_mean'].shape[0]):
label = r'$\theta = {}\degree$'.format(run_param['theta'][t])
plt.plot(data['r_vec'],
data['amps_II_mean'][t],
color=c[t],
marker='o',
markersize=5,
label=label)
ax.fill_between(data['r_vec'],
data['amps_II_mean'][t] - data['amps_II_std'][t],
data['amps_II_mean'][t] + data['amps_II_std'][t],
color=c[t],
alpha=0.2)
handles, labels = ax.get_legend_handles_labels()
# Position the legen on the right side of the plot.
ax.legend(handles,
labels,
loc='upper left',
bbox_to_anchor=(1.0, 1.04), )
ax.set_ylabel("Amplitude")
ax.set_xlabel("Distance from Soma")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# {{{ Plot spike amps II log
fname = self.name + '_spike_amps_II_log'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
c = lplot.get_short_color_array(data['amps_II_mean'].shape[0] + 1)
for t in xrange(data['amps_II_mean'].shape[0]):
label = r'$\theta = {}\degree$'.format(run_param['theta'][t])
plt.plot(data['r_vec'],
data['amps_II_mean'][t],
color=c[t],
marker='o',
markersize=5,
label=label)
ax.fill_between(data['r_vec'],
data['amps_II_mean'][t] - data['amps_II_std'][t],
data['amps_II_mean'][t] + data['amps_II_std'][t],
color=c[t],
alpha=0.2)
handles, labels = ax.get_legend_handles_labels()
# Position the legen on the right side of the plot.
ax.legend(handles,
labels,
loc='upper left',
bbox_to_anchor=(1.0, 1.04), )
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlim([data['r_vec'].min(), data['r_vec'].max()])
ticker = mpl.ticker.MaxNLocator(nbins=7)
ax.xaxis.set_major_locator(ticker)
ax.xaxis.get_major_formatter().labelOnlyBase = False
# ticker = mpl.ticker.MaxNLocator(nbins=7)
# ax.yaxis.set_major_locator(ticker)
# ax.yaxis.get_major_formatter().labelOnlyBase = False
# Set a label formatter to use normal numbers.
ax.xaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.yaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.set_ylabel(r"Amplitude \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Distance from Soma \textbf{[\si{\micro\metre}]}")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# Plot spike width I {{{1 #
fname = self.name + '_spike_width_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
c = lplot.get_short_color_array(data['widths_I_mean'].shape[0] + 1)
for t in xrange(data['widths_I_mean'].shape[0]):
label = r'$\theta = {}\degree$'.format(run_param['theta'][t])
plt.plot(data['r_vec'],
data['widths_I_mean'][t],
color=c[t],
marker='o',
markersize=5,
label=label)
ax.fill_between(data['r_vec'],
data['widths_I_mean'][t] - data['widths_I_std'][t],
data['widths_I_mean'][t] + data['widths_I_std'][t],
color=c[t],
alpha=0.2)
handles, labels = ax.get_legend_handles_labels()
# Position the legen on the right side of the plot.
ax.legend(handles,
labels,
loc='upper left',
bbox_to_anchor=(1.0, 1.04), )
ax.set_ylabel("Spike Width")
ax.set_xlabel("Distance from Soma")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot spike widths II {{{1 #
fname = self.name + '_spike_width_II'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
c = lplot.get_short_color_array(data['widths_II_mean'].shape[0] + 1)
for t in xrange(data['widths_II_mean'].shape[0]):
label = r'$\theta = {}\degree$'.format(run_param['theta'][t])
plt.plot(data['r_vec'],
data['widths_II_mean'][t],
color=c[t],
marker='o',
markersize=5,
label=label)
ax.fill_between(
data['r_vec'],
data['widths_II_mean'][t] - data['widths_II_std'][t],
data['widths_II_mean'][t] + data['widths_II_std'][t],
color=c[t],
alpha=0.2)
handles, labels = ax.get_legend_handles_labels()
# Position the legen on the right side of the plot.
ax.legend(handles,
labels,
loc='upper left',
bbox_to_anchor=(1.0, 1.04), )
ax.set_ylabel("Spike Width")
ax.set_xlabel("Distance from Soma")
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot morphology {{{1 #
LFPy_util.plot.morphology(data['poly_morph'],
data['poly_morph_axon'],
elec_x=data['elec_x'],
elec_y=data['elec_y'],
fig_size=lplot.size_common,
fname=self.name + "_morph_elec_xy",
plot_save_dir=dir_plot,
show=False)
# 1}}} #
# Plot morphology xz {{{ #
LFPy_util.plot.morphology(data['poly_morph_xz'],
data['poly_morph_axon_xz'],
elec_x=data['elec_x'],
elec_y=data['elec_z'],
fig_size=lplot.size_common,
fname=self.name + "_morph_elec_xz",
plot_save_dir=dir_plot,
show=False)
# }}} #
# Spike to plot.
elec_index = run_param['n']/2
# title_str = r"Distance from Soma = \SI{{{}}}{{\micro\metre}}"
# title_str = title_str.format(round(data['r_vec'][elec_index]),2)
c = lplot.get_short_color_array(2 + 1)
# Plot middle electrode spike {{{1 #
fname = self.name + '_middle_elec_spike'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['spikes_t_vec'],
data['spikes'][elec_index],
color=c[0])
# Trace I
plt.plot(data['spikes_t_vec'],
data['widths_I_trace'][elec_index],
color=c[1],
)
# Trace II
plt.plot(data['spikes_t_vec'],
data['widths_II_trace'][elec_index],
color=c[1])
# plt.title(title_str)
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot middle electrode spike freq {{{1 #
fname = self.name + '_middle_elec_spike_fourier'
freq, amp, phase = de.find_freq_and_fft(
data['dt'],
data['spikes'][elec_index],
)
# Remove the first coefficient as we don't care about the baseline.
freq = np.delete(freq, 0)
amp = np.delete(amp, 0)
# Delete frequencies above the option.
if self.plot_param['freq_end'] is not None:
idx = min(
range(len(freq)),
key=lambda i: abs(freq[i] - self.plot_param['freq_end'])
)
freq = freq[0:idx]
amp = amp[0:idx]
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(freq, amp, color=c[0])
# plt.title(title_str)
ax.set_ylabel(r'Amplitude \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Frequency \textbf[$\mathbf{kHz}$\textbf]')
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot middle electrode signal {{{1 #
fname = self.name + '_middle_elec'
print "plotting :", fname
c = lplot.get_short_color_array(2 + 1)
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['t_vec'],
data['LFP'][elec_index],
color=c[0])
# plt.title(title_str)
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
# Plot middle electrode signal freq {{{1 #
fname = self.name + '_middle_elec_fourier'
freq, amp, phase = de.find_freq_and_fft(
data['dt'],
data['LFP'][elec_index],
)
# Remove the first coefficient as we don't care about the baseline.
freq = np.delete(freq, 0)
amp = np.delete(amp, 0)
if self.plot_param['freq_end'] is not None:
idx = min(
range(len(freq)),
key=lambda i: abs(freq[i] - self.plot_param['freq_end'])
)
freq = freq[0:idx]
amp = amp[0:idx]
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(freq, amp, color=c[0])
ax.set_ylabel(r'Amplitude \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Frequency \textbf[$\mathbf{kHz}$\textbf]')
# plt.title(title_str)
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# 1}}} #
if self.plot_param['plot_detailed']:
# Create the directory if it does not exist.
sub_dir = os.path.join(dir_plot, self.name + "_detailed")
if not os.path.exists(sub_dir):
os.makedirs(sub_dir)
t = len(run_param['theta'])
# p = run_param['n_phi']
p = 1
n = run_param['n']
# This title string should be formatted.
title_str = r"Distance from Soma = \SI{{{}}}{{\micro\metre}}"
cnt = 0
for i in xrange(t):
for j in xrange(p):
for k in xrange(n):
title_str_1 = title_str.format(data['r_vec'][k])
# Plot all elec spikes {{{1 #
fname = self.name + '_elec_t_{}_p_{}_n_{}'.format(
run_param['theta'][i], j * 360 / p, k)
print "plotting :", fname
c = lplot.get_short_color_array(2 + 1)
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['spikes_t_vec'],
data['spikes'][cnt],
color=c[0])
# Trace I
plt.plot(data['spikes_t_vec'],
data['widths_I_trace'][cnt],
color=c[1],
)
# Trace II
plt.plot(data['spikes_t_vec'],
data['widths_II_trace'][cnt],
color=c[1])
# plt.title(title_str_1)
# Save plt.
lplot.save_plt(plt, fname, sub_dir)
plt.close()
# 1}}} #
# Plot all elec spikes freq {{{1 #
# Fourier plot.
fname = self.name + '_freq_elec_t_{}_p_{}_n_{}'.format(
run_param['theta'][i], j * 360 / p, k)
freq, amp, phase = de.find_freq_and_fft(
data['dt'],
data['spikes'][cnt],
)
# Remove the first coefficient as we don't care about the baseline.
freq = np.delete(freq, 0)
amp = np.delete(amp, 0)
if self.plot_param['freq_end'] is not None:
idx = min(
range(len(freq)),
key=lambda i: abs(freq[i] - self.plot_param['freq_end'])
)
freq = freq[0:idx]
amp = amp[0:idx]
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(freq, amp, color=c[0])
ax.set_ylabel(r'Amplitude \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Frequency \textbf[$\mathbf{kHz}$\textbf]')
# plt.title(title_str_1)
lplot.save_plt(plt, fname, sub_dir)
plt.close()
# 1}}} #
cnt += 1
int_amps_I_std = int_amps_I_std[start_cutoff:]
int_amps_II = int_amps_II[start_cutoff:]
int_amps_II_mean = int_amps_II_mean[start_cutoff:]
int_amps_II_std = int_amps_II_std[start_cutoff:]
# }}}
lplot.set_rc_param(True)
lplot.plot_format = ['pdf', 'png']
# {{{ Plot interneuron and pyramidal amp. coefficient of var.
fig, ax = plt.subplots(1,2,
sharex=True,
sharey=True,
figsize=lplot.size_common)
lplot.nice_axes(ax[0])
lplot.nice_axes(ax[1])
ax[0].set_title('Base-to-Peak $c_v$')
ax[1].set_title('Peak-to-Peak $c_v$')
colors = lcmaps.get_short_color_array(3)
ax[0].plot(
r,
pyr_amps_I_std/pyr_amps_I_mean,
color=colors[0],
marker='o',
markersize=5,
label=pyram,
)
ax[0].plot(
def plot(self, dir_plot):
data = self.data
run_param = self.run_param
# String to put before output to the terminal.
str_start = self.name
str_start += " "*(20 - len(self.name)) + ": "
if self.only_apply_electrode:
if self.verbose:
print str_start + "Only apply electrode, nothing to plot."
return
# Set global matplotlib parameters.
LFPy_util.plot.set_rc_param(self.plot_param['use_tex'])
# New plot.
fname = self.name + '_all_spikes'
if run_param['pre_dur'] != 0 and run_param['post_dur'] != 0:
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
ax.set_ylabel(r'Membrane Potential \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Time \textbf[$\mathbf{ms}$\textbf]')
lplot.nice_axes(ax)
rows = data['spikes'].shape[0]
colors = cmaps.get_short_color_array(rows)
for row in xrange(rows):
plt.plot(
data['t_vec_spike'],
data['spikes'][row],
color=colors[row],
label="Spike {}".format(row)
)
handles, labels = ax.get_legend_handles_labels()
ax.legend(handles, labels)
lplot.save_plt(plt, fname, dir_plot)
else:
if self.verbose:
print str_start + " Missing pre and post dur, not plotting " + fname
# New plot.
fname = self.name + '_soma_mem'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
ax.set_ylabel(r'Membrane Potential \textbf[$\mathbf{mV}$\textbf]')
ax.set_xlabel(r'Time \textbf[$\mathbf{ms}$\textbf]')
lplot.nice_axes(ax)
plt.plot(data['soma_t'], data['soma_v'], color=cmaps.get_color(0))
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# New plot.
fname = self.name + '_soma_v_mem_i_mem'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.subplot(2, 1, 1)
lplot.nice_axes(ax)
plt.plot(data['soma_t'], data['soma_v'], color=cmaps.get_color(0))
ax.set_ylabel(r'Membrane Potential \textbf[$\mathbf{mV}$\textbf]')
ax = plt.subplot(2, 1, 2)
lplot.nice_axes(ax)
plt.plot(data['soma_t'], data['stimulus_i'], color=cmaps.get_color(0))
ax.set_ylabel(r'Stimulus Current \textbf[$\mathbf{nA}$\textbf]')
ax.set_xlabel(r'Time \textbf[$\mathbf{ms}$\textbf]')
lplot.save_plt(plt, fname, dir_plot)
plt.close()
def plot(self, dir_plot):
"""
Plotting stats about the spikes.
"""
# pylint: disable=too-many-locals
data = self.data
run_param = self.run_param
# String to put before output to the terminal.
str_start = self.name
str_start += " "*(20 - len(self.name)) + ":"
# Set global matplotlib parameters.
LFPy_util.plot.set_rc_param()
# {{{ Plot Ext. Elec. Overlay
fname = self.name + '_ext_all'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
for i in xrange(run_param['N']):
# Plot
plt.plot(data['spikes_t_vec'],
data['spikes'][i]/np.abs(data['spikes'][i].min()),
color=lcmaps.get_color(0),
alpha=0.3,
)
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot Ext. Elec. Fourier
freq = data['freq']
amps = data['amp']
if self.plot_param['freq_end'] is not None:
idx = min(
range(len(freq)),
key=lambda i: abs(freq[i] - self.plot_param['freq_end'])
)
freq = freq[0:idx]
amps = amps[:,:idx]
for i in xrange(run_param['N']):
amp = amps[i]
fname = self.name + '_ext'+str(i+1) + "_fourier"
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(freq, amp, color=lcmaps.get_color(0))
ax.set_ylabel(r'Amplitude \textbf{[\si{\milli\volt}]}')
ax.set_xlabel(r'Frequency \textbf{[\si{\kilo\hertz}]}')
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot soma voltage.
fname = self.name + '_soma_mem'
print "plotting :", fname
fig = plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['spikes_t_vec'],
data['spike_soma'],
color=lcmaps.get_color(0),
)
plt.plot(data['spikes_t_vec'],
data['width_I_trace_soma'],
color=lcmaps.get_color(0.5),
)
plt.plot(data['spikes_t_vec'],
data['width_II_trace_soma'],
color=lcmaps.get_color(0.5),
)
# Plot annotations type I.
# Get linesegments from the trace.
lines_x, lines_y = lplot._get_line_segments(
data['spikes_t_vec'],
data['width_II_trace_soma'],
)
width = round(data['width_II_soma'], 3)
plt.hold('on')
text = r"\SI{" + str(width) + "}{\milli\second}"
ax.annotate(text,
xy=(lines_x[0, 0] + 0.5*width, lines_y[0, 0]),
xycoords='data',
xytext=(20, -20),
textcoords='offset points',
va="center",
ha="left",
bbox=dict(boxstyle="round4",
fc="w"),
arrowprops=dict(arrowstyle="-|>",
connectionstyle="arc3,rad=-0.2",
fc="w"), )
# Plot annotations type II.
# Get linesegments from the trace.
lines_x, lines_y = lplot._get_line_segments(
data['spikes_t_vec'],
data['width_I_trace_soma'],
)
width = round(data['width_I_soma'], 3)
plt.hold('on')
text = r"\SI{" + str(width) + r"}{\milli\second}"
ax.annotate(text,
xy=(lines_x[0, 0] + 0.5*width, lines_y[0, 0]),
xycoords='data',
xytext=(20, -20),
textcoords='offset points',
va="center",
ha="left",
bbox=dict(boxstyle="round4",
fc="w"),
arrowprops=dict(arrowstyle="-|>",
connectionstyle="arc3,rad=-0.2",
fc="w"), )
ax.set_ylabel(r"Membrane Potential \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
# Change size and save again.
fig.set_size_inches(lplot.size_square)
lplot.save_plt(plt, fname+'_small', dir_plot)
plt.close()
# }}}
# {{{ Plot Ext. Elec.
for i in xrange(run_param['N']):
fname = self.name + '_ext'+str(i+1)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['spikes_t_vec'],
data['spikes'][i],
color=lcmaps.get_color(0),
)
plt.plot(data['spikes_t_vec'],
data['width_I_trace'][i],
color=lcmaps.get_color(0.5),
)
plt.plot(data['spikes_t_vec'],
data['width_II_trace'][i],
color=lcmaps.get_color(0.5),
)
ax.set_ylabel(r"Potential \textbf{[\si{\micro\volt}]}")
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
fname = self.name + '_ext'+str(i+1)+'_full'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
# Plot
plt.plot(data['t_vec'],
data['LFP'][i],
color=lcmaps.get_color(0),
)
ax.set_ylabel(r"Potential \textbf{[\si{\micro\volt}]}")
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Morphology
LFPy_util.plot.morphology(data['poly_morph'],
data['poly_morph_axon'],
elec_x=data['elec_x'],
elec_y=data['elec_y'],
fig_size=lplot.size_square,
fname=self.name + "_morph_elec_xy",
plot_save_dir=dir_plot,
show=False,
numbering=True,
)
# }}}
# {{{ Morphology xz
LFPy_util.plot.morphology(data['poly_morph_xz'],
data['poly_morph_axon_xz'],
elec_x=data['elec_x'],
elec_y=data['elec_z'],
x_label='x',
y_label='z',
fig_size=lplot.size_square,
fname=self.name + "_morph_elec_xz",
plot_save_dir=dir_plot,
show=False,
numbering=True,
)
def plot(self, dir_plot):
data = self.data
run_param = self.run_param
LFPy_util.plot.set_rc_param(self.plot_param['use_tex'])
LFPy_util.plot.plot_format = self.plot_param['formats']
# {{{ Plot elec spikes overlay
# Create the directory if it does not exist.
for elec in xrange(run_param['n_elec']):
sub_dir = os.path.join(dir_plot, 'elec_{}_all_spikes'.format(elec))
if not os.path.exists(sub_dir):
os.makedirs(sub_dir)
for i in xrange(run_param['sweeps']):
fname = self.name + '_elec_all_spikes_sweep_{}'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
for j in xrange(data['spikes_elec'][i][elec].shape[0]):
plt.plot(data['spikes_t_vec'],
data['spikes_elec'][i][elec][j],
color=lcmaps.get_color(0),
alpha=0.2,
)
# ax.set_xlabel(r"Stimulus Current \textbf{[\si{\nano\ampere}]}")
# Save plt.
lplot.save_plt(plt, fname, sub_dir)
plt.close()
# }}}
# {{{ Plot soma spikes overlay
# Create the directory if it does not exist.
sub_dir = os.path.join(dir_plot, 'soma_all_spikes')
if not os.path.exists(sub_dir):
os.makedirs(sub_dir)
for i in xrange(run_param['sweeps']):
fname = self.name + '_soma_all_spikes_sweep_{}'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
for j in xrange(data['spikes_soma'][i].shape[0]):
plt.plot(data['spikes_t_vec'],
data['spikes_soma'][i][j],
color=lcmaps.get_color(0),
alpha=0.2,
)
# ax.set_xlabel(r"Stimulus Current \textbf{[\si{\nano\ampere}]}")
# Save plt.
lplot.save_plt(plt, fname, sub_dir)
plt.close()
# }}}
# Plotting all sweeps {{{
if run_param['sweeps'] <= 10:
fname = self.name + '_soma_mem'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
colors = lcmaps.get_short_color_array(run_param['sweeps']+1)
for i in xrange(run_param['sweeps']):
plt.plot(data['t_vec'],
data['v_vec_soma'][i],
color=colors[i],
)
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# Plotting all sweeps elec {{{
if run_param['sweeps'] <= 10:
for i in xrange(run_param['n_elec']):
fname = self.name + '_elec_{}'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
colors = lcmaps.get_short_color_array(run_param['sweeps']+1)
for j in xrange(run_param['sweeps']):
plt.plot(data['t_vec'],
data['v_vec_elec'][j, i],
color=colors[j],
)
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot f_i
fname = self.name + '_f_i'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['amps']*1000,
data['freqs'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.set_xlabel(r"Stimulus Current \textbf{[\si{\nano\ampere}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike width over frequency I soma
fname = self.name + '_soma_width_frequency_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['widths_I_soma_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['freqs'],
data['widths_I_soma_mean'] - data['widths_I_soma_std'],
data['widths_I_soma_mean'] + data['widths_I_soma_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel(r"Peak-to-Peak Width \textbf{[\si{\milli\second}]}")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# ax.set_xlabel(r"Stimulus Current \textbf{[\si{\nano\ampere}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike width over frequency II soma
fname = self.name + '_soma_width_frequency_II'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['widths_II_soma_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['freqs'],
data['widths_II_soma_mean'] - data['widths_II_soma_std'],
data['widths_II_soma_mean'] + data['widths_II_soma_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel(r"Half Max Width \textbf{[\si{\milli\second}]}")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# ax.set_xlabel(r"Stimulus Current \textbf{[\si{\nano\ampere}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike width over frequency I elec
for i in xrange(run_param['n_elec']):
fname = self.name + '_elec_{}_width_frequency_I'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['widths_I_elec_mean'][:, i],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(
data['freqs'],
data['widths_I_elec_mean'][:,i]
- data['widths_I_elec_std'][:,i],
data['widths_I_elec_mean'][:,i]
+ data['widths_I_elec_std'][:,i],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel(r"Peak-to-Peak Width \textbf{[\si{\milli\second}]}")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike width over frequency II elec
for i in xrange(run_param['n_elec']):
fname = self.name + '_elec_{}_width_frequency_II'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['widths_II_elec_mean'][:,i],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(
data['freqs'],
data['widths_II_elec_mean'][:,i]
- data['widths_II_elec_std'][:,i],
data['widths_II_elec_mean'][:,i]
+ data['widths_II_elec_std'][:,i],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel(r"Half Max Width \textbf{[\si{\milli\second}]}")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike width over frequency I elec soma
for i in xrange(run_param['n_elec']):
fname = self.name + '_elec_{}_soma_width_frequency_I'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['widths_I_soma_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
label='Soma',
)
ax.fill_between(data['freqs'],
data['widths_I_soma_mean'] - data['widths_I_soma_std'],
data['widths_I_soma_mean'] + data['widths_I_soma_std'],
color=lcmaps.get_color(0),
alpha=0.2)
plt.plot(data['freqs'],
data['widths_I_elec_mean'][:, i],
color=lcmaps.get_color(0.5),
marker='o',
markersize=5,
label='Elec.'
)
ax.fill_between(
data['freqs'],
data['widths_I_elec_mean'][:,i]
- data['widths_I_elec_std'][:,i],
data['widths_I_elec_mean'][:,i]
+ data['widths_I_elec_std'][:,i],
color=lcmaps.get_color(0.5),
alpha=0.2)
ax.set_ylabel(r"Peak-to-Peak Width \textbf{[\si{\milli\second}]}")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# handles, labels = ax.get_legend_handles_labels()
# ax.legend(handles,
# labels,
# loc='upper right',
# # bbox_to_anchor=(1, 0.5),
# )
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike width over frequency II elec soma
for i in xrange(run_param['n_elec']):
fname = self.name + '_elec_{}_soma_width_frequency_II'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['widths_II_soma_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
label='Soma',
)
ax.fill_between(data['freqs'],
data['widths_II_soma_mean'] - data['widths_II_soma_std'],
data['widths_II_soma_mean'] + data['widths_II_soma_std'],
color=lcmaps.get_color(0),
alpha=0.2)
plt.plot(data['freqs'],
data['widths_II_elec_mean'][:,i],
color=lcmaps.get_color(0.5),
marker='o',
markersize=5,
label='Elec.',
)
ax.fill_between(
data['freqs'],
data['widths_II_elec_mean'][:,i]
- data['widths_II_elec_std'][:,i],
data['widths_II_elec_mean'][:,i]
+ data['widths_II_elec_std'][:,i],
color=lcmaps.get_color(0.5),
alpha=0.2)
ax.set_ylabel(r"Half Max Width \textbf{[\si{\milli\second}]}")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike amplitude over frequency I soma
fname = self.name + '_soma_amp_frequency_I'
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['amps_I_soma_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(data['freqs'],
data['amps_I_soma_mean'] - data['amps_I_soma_std'],
data['amps_I_soma_mean'] + data['amps_I_soma_std'],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel(r"Base-to-Peak Amp.")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike amplitude over frequency I elec
for i in xrange(run_param['n_elec']):
fname = self.name + '_elec_{}_amp_frequency_I'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['amps_I_elec_mean'][:, i],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
)
ax.fill_between(
data['freqs'],
data['amps_I_elec_mean'][:,i]
- data['amps_I_elec_std'][:,i],
data['amps_I_elec_mean'][:,i]
+ data['amps_I_elec_std'][:,i],
color=lcmaps.get_color(0),
alpha=0.2)
ax.set_ylabel(r"Base-to-Peak Amp.")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()
# }}}
# {{{ Plot spike amplitude over frequency I elec soma
for i in xrange(run_param['n_elec']):
fname = self.name + '_elec_{}_soma_amp_frequency_I'.format(i)
print "plotting :", fname
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
plt.plot(data['freqs'],
data['amps_I_soma_mean'],
color=lcmaps.get_color(0),
marker='o',
markersize=5,
label='Soma',
)
ax.fill_between(data['freqs'],
data['amps_I_soma_mean'] - data['amps_I_soma_std'],
data['amps_I_soma_mean'] + data['amps_I_soma_std'],
color=lcmaps.get_color(0),
alpha=0.2)
plt.plot(data['freqs'],
data['amps_I_elec_mean'][:, i],
color=lcmaps.get_color(0.5),
marker='o',
markersize=5,
label='Elec.'
)
ax.fill_between(
data['freqs'],
data['amps_I_elec_mean'][:,i]
- data['amps_I_elec_std'][:,i],
data['amps_I_elec_mean'][:,i]
+ data['amps_I_elec_std'][:,i],
color=lcmaps.get_color(0.5),
alpha=0.2)
ax.set_ylabel(r"Base-to-Peak Amp.")
ax.set_xlabel(r"Frequency \textbf{[\si{\hertz}]}")
# Save plt.
lplot.save_plt(plt, fname, dir_plot)
plt.close()