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plot_fig3.py
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import numpy as np
import matplotlib.pyplot as plt
from zrnn import analysis
def _get_plots_abc(axs, iccs=(-1, 0.5, 1.8)):
y0 = [0.075, 0.075, -0.01]
params = analysis.DEF_PARAMS
time = np.linspace(0, 0.5, int(0.5 * 1e3 + 1))
for i, (icc, ax) in enumerate(zip(iccs, axs)):
params["I_cc"] = icc
solution = analysis.solver(params, y0, 0.5)
ax.plot(time, solution)
ax.set_xlabel('Time (ms)', fontsize=16)
ax.set_ylabel('Activity', fontsize=16)
ax.set_title(f'I_cc = {icc}', fontsize=16)
ax.set_ylim([-0.2, 0.2])
ax.set_xlim([time[0], time[-1]])
def _get_plot_d(ax, icc_i = 0.19, icc_f = 1):
i_cc_range = np.linspace(icc_i, icc_f, 100)
y0 = [0.075, 0.075, -0.01]
params = analysis.DEF_PARAMS
periods = []
for icc in i_cc_range:
params["I_cc"] = icc
solution = analysis.solver(params, y0, 5)
periods.append(analysis.get_oscillation_period(solution))
ax.plot(i_cc_range, periods, c='g')
ax.set_xlim([0, 1]), ax.set_ylim([0, 1000])
ax.set_xlabel('Context Cue (I_cc)', fontsize=16)
ax.set_ylabel('Oscillation Period [ms]', fontsize=16)
def _get_plot_e(ax):
i_cc_range = np.linspace(-2, 2, 1000)
y0 = [0.075, 0.075, -0.01]
params = analysis.DEF_PARAMS
fpss = []
osc = []
for icc in i_cc_range:
params["I_cc"] = icc
model = analysis.DynamicalSystem(params)
fps, stability, spirality = model.get_fixed_points(100)
fpss.append(fps)
cmap = {0: 'k', 1: 'r'}
for fp, t, p in zip(fps, stability, spirality):
ax.plot(icc, fp[-1], 'o', c=cmap[t])
if not t and len(fps) < 2:
osc.append(icc)
solution = analysis.solver(params, y0, 2)
z_max, z_min = solution[1000:, -1].max(), solution[1000:, -1].min()
ax.plot([icc] * 2, [z_max, z_min], 'o', c='g')
i_hc = min(osc)
i_hb = max(osc)
ax.axvline(x=i_hc, ls='--', c='k')
ax.axvline(x=i_hb, ls='--', c='k')
ax.axvline(x=-1, ls=':', c='k')
ax.axvline(x=0.5, ls=':', c='k')
ax.axvline(x=1.8, ls=':', c='k')
ax.set_xlabel('Context Cue (I_cc)', fontsize=16)
ax.set_ylabel('Int-I (z)', fontsize=16)
def _get_plot_f(ax, iccs=(0.197, 0.3, 0.5, 0.8, 1.2)):
import matplotlib as mpl
y0 = [0.075, 0.075, -0.01]
params = analysis.DEF_PARAMS
cmap = mpl.colormaps["PuBuGn"]
c = 1.
for icc in iccs:
params["I_cc"] = icc
solution = analysis.solver(params, y0, 5)
period = analysis.get_oscillation_period(solution)
to_plot = solution[500:500 + int(period)]
ax.plot(to_plot[:, 0], to_plot[:, -1], 'o', c=cmap(c))
c -= .2
ax.set_xlabel('Tap-E (x)', fontsize=16)
ax.set_ylabel('Int-I (z)', fontsize=16)
ax.set_xlim([-.2, .2]), ax.set_ylim([-.2, .2])
def main():
fig, axs = plt.subplots(nrows=2, ncols=3, figsize=(1000/96, 800/96), dpi=96)
_get_plots_abc(axs[0])
_get_plot_d(axs[1, 0])
_get_plot_e(axs[1, 1])
_get_plot_f(axs[1, 2])
plt.tight_layout()
plt.savefig('plots/fig_3.png', dpi=96)
if __name__ == '__main__':
main()