def plot_good_cell_connections(self, fig_cnt=1):
ax = self.fig.add_subplot(self.n_fig_y, self.n_fig_x, fig_cnt)
for gid in self.good_gids:
x, y, u, v = self.tuning_prop[gid]
thetas = np.arctan2(v, u)
h = ((thetas + np.pi) / (2 * np.pi)) * 360. # theta determines h, h must be [0, 360)
l = np.sqrt(u**2 + v**2) / np.sqrt(2 * self.params['v_max_tp']**2) # lightness [0, 1]
s = 1. # saturation
assert (0 <= h and h < 360)
assert (0 <= l and l <= 1)
assert (0 <= s and s <= 1)
(r, g, b) = utils.convert_hsl_to_rgb(h, s, l)
ax.plot(x, y, 'o', c=(r,g,b), markersize=7, markeredgewidth=0)#, edgecolors=None)
ax.set_xlabel('X-position')
ax.set_ylabel('Y-position')
def plot_cells_by_euclidean_tuning_distance(subplot_code=111, direction=False):
def get_dist(x, y):
d = 0.
for i in xrange(len(x)):
d += (x[i] - y[i])**2
dist = np.sqrt(d)
return dist
ax2 = fig.add_subplot(subplot_code)
dist = np.zeros(len(tgts_ee))
for i_, tgt in enumerate(tgts_ee):
x_tgt, y_tgt, u_tgt, v_tgt = tp_exc[tgt, :]
if direction:
x = (u_tgt, v_tgt)
y = (u0, v0)
else:
x = (x_tgt, y_tgt, u_tgt, v_tgt)
y = (x0, y0, u0, v0)
dist[i_] = get_dist(x, y)
#sorted_idx = np.argsort(dist)
dist_min, dist_max = dist.min(), dist.max()
print 'direction %s, dist_min=%.2e dist_max=%.2e' % (str(direction), dist_min, dist_max)
for i in xrange(dist.size):
x_tgt, y_tgt, u_tgt, v_tgt = tp_exc[i, :]
h = 0
l = (dist[i] - dist_min) / (dist_max - dist_min)
s = 0. # saturation
assert (0 <= h and h < 360)
assert (0 <= l and l <= 1)
assert (0 <= s and s <= 1)
(r, g, b) = utils.convert_hsl_to_rgb(h, s, l)
x, y, u, v = tp_exc[i, :]
ax2.plot(x, y, 'o', c=(r,g,b), markersize=4)
if with_annotations:
ax2.annotate('(%d, %.2e, %.2e)' % (tgt, w, d), (x_tgt, y_tgt), fontsize=8)
if direction:
ax2.set_title('Distance to cell %d\nin direction space' % (exc_cell))
else:
ax2.set_title('Euclidean distance to cell %d\nin tuning_prop space' % (exc_cell))
ax2.set_xlabel('x position')
ax2.set_ylabel('y position')
return ax2
fig1 = plt.figure()
n_frames = activity[:, 0].size
pos = np.zeros((n_cells, 2))
pos[:, 0], pos[:, 1] = tp[:, 0], tp[:, 1]
colors = np.zeros((n_frames, n_cells, 3))
s = 1.0 # saturation
for frame in xrange(n_frames):
for cell in xrange(n_cells):
if activity[frame, cell] < 0:
l = 1.0 - 0.5 * activity[frame, cell] / activity_min
h = 0.0
else:
l = 1.0 - 0.5 * activity[frame, cell] / activity_max
h = 240.0
assert 0 <= h and h < 360
assert 0 <= l and l <= 1
assert 0 <= s and s <= 1
(r, g, b) = utils.convert_hsl_to_rgb(h, s, l)
colors[frame, cell, :] = [r, g, b]
dot_ani = animation.FuncAnimation(fig1, paint_dots, n_frames, fargs=(pos, colors), interval=50, blit=True)
output_fn = "dynamic_images.mp4"
print "Saving movie", output_fn
dot_ani.save(output_fn)
print "Finished"
# plt.show()