def on_click(self, event):
if event.inaxes == self.ax:
self.params = model.parameters_one()
self.g_inh = model.params['g_inh_0']
length = self.system.N_output(self.CYCLES)
self.t = self.system.dt * np.arange(length)
self.trajectory = np.zeros((length, self.num_osci), float)
for i in xrange(self.num_osci):
self.li[i].set_data(self.t, self.trajectory[:, i] - i * 2.)
ticks = np.asarray(self.t[::self.t.size / 10], dtype=int)
self.ax.set_xticks(ticks)
self.ax.set_xticklabels(ticks)
self.ax.set_xlim(self.t[0], self.t[-1])
self.fig.canvas.draw()
self.anim = animation.FuncAnimation(
self.fig,
self.compute_step,
init_func=self.init,
frames=self.trajectory.shape[0],
interval=0,
blit=True,
repeat=False)
def on_click(self, event):
if event.inaxes == self.ax:
self.params = model.parameters_one()
self.g_inh = model.params["g_inh_0"]
length = self.system.N_output(self.CYCLES)
self.t = self.system.dt * np.arange(length)
self.trajectory = np.zeros((length, self.num_osci), float)
for i in xrange(self.num_osci):
self.li[i].set_data(self.t, self.trajectory[:, i] - i * 2.0)
ticks = np.asarray(self.t[:: self.t.size / 10], dtype=int)
self.ax.set_xticks(ticks)
self.ax.set_xticklabels(ticks)
self.ax.set_xlim(self.t[0], self.t[-1])
self.fig.canvas.draw()
self.anim = animation.FuncAnimation(
self.fig,
self.compute_step,
init_func=self.init,
frames=self.trajectory.shape[0],
interval=0,
blit=True,
repeat=False,
)
def compute_step(self, idx):
self.params = model.parameters_one()
self.g_inh = model.params['g_inh_0']
model.step_n_em(self.state, self.params, self.g_inh,
self.system.dt / float(self.system.stride),
self.system.stride)
self.trajectory[idx, :] = self.state[::model.N_EQ1]
if self.pulsed:
self.trajectory[idx - 1, self.pulsed - 1] = -0.1
self.trajectory[idx, self.pulsed - 1] = 0.1
self.pulsed = 0
for i in xrange(self.num_osci):
self.li[i].set_data(self.t, self.trajectory[:, i] - 2. * i)
return self.li
def compute_step(self, idx):
self.params = model.parameters_one()
self.g_inh = model.params["g_inh_0"]
model.step_n_em(
self.state, self.params, self.g_inh, self.system.dt / float(self.system.stride), self.system.stride
)
self.trajectory[idx, :] = self.state[:: model.N_EQ1]
if self.pulsed:
self.trajectory[idx - 1, self.pulsed - 1] = -0.1
self.trajectory[idx, self.pulsed - 1] = 0.1
self.pulsed = 0
for i in xrange(self.num_osci):
self.li[i].set_data(self.t, self.trajectory[:, i] - 2.0 * i)
return self.li