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Fig-2-tuning-curves.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# Copyright INRIA
# Contributors: Wahiba Taouali ([email protected])
# Nicolas P. Rougier ([email protected])
#
# This software is governed by the CeCILL license under French law and abiding
# by the rules of distribution of free software. You can use, modify and/ or
# redistribute the software under the terms of the CeCILL license as circulated
# by CEA, CNRS and INRIA at the following URL
# http://www.cecill.info/index.en.html.
#
# As a counterpart to the access to the source code and rights to copy, modify
# and redistribute granted by the license, users are provided only with a
# limited warranty and the software's author, the holder of the economic
# rights, and the successive licensors have only limited liability.
#
# In this respect, the user's attention is drawn to the risks associated with
# loading, using, modifying and/or developing or reproducing the software by
# the user in light of its specific status of free software, that may mean that
# it is complicated to manipulate, and that also therefore means that it is
# reserved for developers and experienced professionals having in-depth
# computer knowledge. Users are therefore encouraged to load and test the
# software's suitability as regards their requirements in conditions enabling
# the security of their systems and/or data to be ensured and, more generally,
# to use and operate it in the same conditions as regards security.
#
# The fact that you are presently reading this means that you have had
# knowledge of the CeCILL license and that you accept its terms.
# -----------------------------------------------------------------------------
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
from model import *
from projections import *
font = {'size' : 18}
matplotlib.rc('font', **font)
model = Model()
p = 200
X = np.linspace(0,25,p)
Z = np.zeros(shape=(p, colliculus_shape[1]))
# size = 2.0 °, intensity = 0.5
if 0 or not os.path.exists('data/tuning.npy'):
for i in range(p):
model.reset()
model.R = stimulus((X[i], 0.0), size=2.0, intensity=0.5)
model.run(duration=20*second, dt=5*millisecond, epsilon=0.001)
Z[i] = model.SC_V[colliculus_shape[0]/2]
print "%d/%d: %f" % (i,p, Z[i].max())
np.save('data/tuning.npy', Z)
else:
Z = np.load('data/tuning.npy')
fig = plt.figure(figsize=(8,7), facecolor='w')
ax = plt.subplot(1,1,1)
ax.tick_params(direction="outward")
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
# ax.spines['left'].set_color('none')
ax.spines['bottom'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
# ax.spines['bottom'].set_position(('data',-0.05))
for i in [3,5,10,15]:
x,y = polar_to_logpolar( i/90.0, 0 )
index = int(x*Z.shape[1])
plt.plot(X,Z[:,index], linewidth=1.5, color='k')
ax.text(2.8, 1.05, u"a",
ha="left", va="bottom", fontsize=16, fontweight='bold')
ax.text(5., 0.75, u"b",
ha="left", va="bottom", fontsize=16, fontweight='bold')
ax.text(9.5, 0.4, u"c",
ha="left", va="bottom", fontsize=16, fontweight='bold')
ax.text(13.5, 0.25, u"d",
ha="left", va="bottom", fontsize=16, fontweight='bold')
plt.xlim(0.0, 25.0)
plt.ylim(0.0, 1.1)
plt.yticks([0.0,1.0],['0','500'])
#plt.vlines([3,5,10,15], [0,0,0,0], [1.1,1.1,1.1,1.1], linewidth=1, color='.75')
plt.xticks([0,3,5,10,15,25])
plt.xlabel('Target eccentricity ($^\circ$)')
plt.ylabel('Discharge rate (spike/s)')
plt.savefig('figures/Fig-2.eps')
plt.savefig('figures/Fig-2.pdf')
plt.tight_layout()
plt.show()