def plot_rhythm(g, sigma, PLOT=False):
"""
calculate the frequency and plot the histogram of
activity and filtered activety
"""
len_g = len(g)
len_sigma = len(sigma)
freq = np.zeros((len_g, len_sigma))
for i in range(len_g):
for j in range(len_sigma):
subname = str("%.3f-%.3f" % (g[i], sigma[j]))
fname = str("spk-%s.npz" % subname)
pop = np.load("npz/" + fname)
if PLOT:
fig0, ax = pl.subplots(2, figsize=(8, 5))
pl.subplots_adjust(hspace=.4)
ts = pop['ts']
gids = pop['gids']
if len(ts):
t_bins, heights = lib.calculate_histogram(
ts, gids, hist_binwidth)
filtered = lib.filter_gaussian(heights, fwhm)
# filtered = lib.filter_bandpass(heights, fs, 2, 1000, 5)
f, P = welch(filtered, fs=fs, nperseg=nperseg)
freq[i, j] = f[np.argmax(P)]
if PLOT:
lib.plot_rhythms_from_file(t_bins, heights, filtered,
ax[0], xlim)
lib.plot_power_spectrum(f, P, ax[1])
if PLOT:
pl.savefig('fig/r-' + subname + ".png")
pl.close()
def plot_activity(fname, fwhm, ax):
number = 10
cmap = pl.get_cmap('afmhot')
colors = [cmap(i) for i in np.linspace(0, 1, number)]
# fname = str("spk-%s.npz" % subname)
pop = np.load("npz/" + fname)
ts = pop['ts']
gids = pop['gids']
if len(ts) > 3:
tmp = lib.calculate_spike_synchrony(ts, gids)
R = 0 if ((tmp > 1) or (tmp < 0)) else tmp
R = int(round(R, 1) * 10)
t_bins, heights = lib.calculate_histogram(ts, gids, hist_binwidth)
filtered = lib.filter_gaussian(heights, fwhm)
# ax1.tick_params(axis='y', labelcolor='royalblue')
ax.plot(t_bins, filtered, lw=2, c=colors[R])
else:
print "empty plot for %s" % fname