def learn(self,
step,
eta,
run,
rate,
T=500,
r0=.5,
tm=20,
ts=2,
reset=0,
trials=100,
start_state=0):
np.random.seed(run)
# maybe put this outside function to continue learning instead of fresh start
self.unlearn(r0)
pi = np.zeros((trials, self.num_states), dtype=int)
seq = [
[None]
] * trials # sequences might have differnt length -> list instead array
W = np.zeros((trials, self.K, self.K), dtype=float)
for t in xrange(trials):
res = cfn.run(self.W, step, rate, T, tm, ts, reset, run)
pi[t] = self.get_policy(step, res[0])
seq[t] = self.sample4Pi(pi[t], start_state)
self.update_weights(seq[t], eta)
W[t] = self.W
return np.array([pi, seq, W])
import cfunctions as cfn
from functions import simpleaxis, init_fig
savefig = False if len(argv) == 1 else True
net = Net()
step = .1
init_fig()
# colors for colorblind from http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/
col = ['#56B4E9', '#0072B2', '#F0E442', '#E69F00',
'#CC79A7', '#D55E00', '#40e0d0', '#009E73']
# Voltage
spikes, u = cfn.run(net.W, step, 400, 50, 20, 2, 20, 2)
fig1, ax = pl.subplots(nrows=2, ncols=1)
for i, j in enumerate([7, 1]):
ax[i].plot(u[:, j] + 2 * spikes[:, j], color=col[j], zorder=5)
ax[i].set_ylim(-1, 3.5)
ax[i].axis('off')
ax[-1].plot([0, 10 / step], [-1, -1], c='k', lw=7, clip_on=False, zorder=5)
ax[-1].plot([0, 0], [1, 2], c='k', lw=7, clip_on=False, zorder=5)
fig1.subplots_adjust(hspace=-.1)
fig1.subplots_adjust(.04, .1, 1, 1)
if savefig:
pl.savefig('u.pdf', dpi=600, transparent=True)
else:
pl.show()
# Spikes
from functions import simpleaxis, init_fig
savefig = False if len(argv) == 1 else True
net = Net()
step = .1
init_fig()
# colors for colorblind from http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/
col = [
'#56B4E9', '#0072B2', '#F0E442', '#E69F00', '#CC79A7', '#D55E00',
'#40e0d0', '#009E73'
]
# Voltage
spikes, u = cfn.run(net.W, step, 400, 50, 20, 2, 20, 2)
fig1, ax = pl.subplots(nrows=2, ncols=1)
for i, j in enumerate([7, 1]):
ax[i].plot(u[:, j] + 2 * spikes[:, j], color=col[j], zorder=5)
ax[i].set_ylim(-1, 3.5)
ax[i].axis('off')
ax[-1].plot([0, 10 / step], [-1, -1], c='k', lw=7, clip_on=False, zorder=5)
ax[-1].plot([0, 0], [1, 2], c='k', lw=7, clip_on=False, zorder=5)
fig1.subplots_adjust(hspace=-.1)
fig1.subplots_adjust(.04, .1, 1, 1)
if savefig:
pl.savefig('u.pdf', dpi=600, transparent=True)
else:
pl.show()
# Spikes