Python iaf_recoverable Examples

Example #1

File: iaf_pop_demo.py Project: bionet/ted.python

else:
    fig_title = 'IAF Input Signal with %d dB of Noise' % noise_power
print fig_title
u = func_timer(bl.gen_band_limited)(dur, dt, f, noise_power)
pl.plot_signal(t, u, fig_title,
               output_name + str(output_count) + output_ext)

# Test leaky IAF algorithms:

b1 = 3.5   # bias
d1 = 0.7   # threshold
R1 = 10.0  # resistance
C1 = 0.01  # capacitance

try:
    iaf.iaf_recoverable(u, bw, b1, d1, R1, C1)
except ValueError('reconstruction condition not satisfied'):
    sys.exit()

b2 = 3.4   # bias
d2 = 0.8   # threshold
R2 = 9.0   # resistance
C2 = 0.01  # capacitance

try:
    iaf.iaf_recoverable(u, bw, b2, d2, R2, C2)
except ValueError('reconstruction condition not satisfied'):
    sys.exit()

b_list = np.array([b1, b2])
d_list = np.array([d1, d2])

Example #2

File: iaf_demo.py Project: bionet/ted.python

if noise_power == None:
    fig_title = 'IAF Input Signal with no Noise';
else:
    fig_title = 'IAF Input Signal with %d dB of Noise' % noise_power;
print fig_title
u = func_timer(bl.gen_band_limited)(dur, dt, f, noise_power)
pl.plot_signal(t, u, fig_title,
               output_name + str(output_count) + output_ext)

b = 3.5   # bias
d = 0.7   # threshold
R = 10.0  # resistance
C = 0.01  # capacitance

try:
    iaf.iaf_recoverable(u, bw, b, d, R, C)
except ValueError('reconstruction condition not satisfied'):
    sys.exit()

M = 5 # number of bins for fast decoding algorithm
L = 5 # number of recursions for recursive decoding algorithm

# Test leaky algorithms:

output_count += 1
fig_title = 'Signal Encoded Using Leaky IAF Encoder'
print fig_title
s = func_timer(iaf.iaf_encode)(u, dt, b, d, R, C)
pl.plot_encoded(t, u, s, fig_title,
                output_name + str(output_count) + output_ext)

Example #3

File: iaf_demo.py Project: era1erushe/ted.python

noise_power = None
if noise_power == None:
    fig_title = 'IAF Input Signal with no Noise'
else:
    fig_title = 'IAF Input Signal with %d dB of Noise' % noise_power
print fig_title
u = func_timer(bl.gen_band_limited)(dur, dt, f, noise_power)
pl.plot_signal(t, u, fig_title, output_name + str(output_count) + output_ext)

b = 3.5  # bias
d = 0.7  # threshold
R = 10.0  # resistance
C = 0.01  # capacitance

try:
    iaf.iaf_recoverable(u, bw, b, d, R, C)
except ValueError('reconstruction condition not satisfied'):
    sys.exit()

M = 5  # number of bins for fast decoding algorithm
L = 5  # number of recursions for recursive decoding algorithm

# Test leaky algorithms:

output_count += 1
fig_title = 'Signal Encoded Using Leaky IAF Encoder'
print fig_title
s = func_timer(iaf.iaf_encode)(u, dt, b, d, R, C)
pl.plot_encoded(t, u, s, fig_title,
                output_name + str(output_count) + output_ext)

Example #4

File: iaf_pop_trig_demo.py Project: era1erushe/ted.python

u = func_timer(bl.gen_band_limited)(dur, dt, f, noise_power)
pl.plot_signal(t, u, fig_title,
               output_name + str(output_count) + output_ext)

# Trigonometric polynomial order:
M = 32

# Test leaky IAF algorithms:

b1 = 3.5   # bias
d1 = 0.7   # threshold
R1 = 10.0  # resistance
C1 = 0.01  # capacitance

try:
    iaf.iaf_recoverable(u, bw, b1, d1, R1, C1)
except ValueError('reconstruction condition not satisfied'):
    sys.exit()

b2 = 3.4   # bias
d2 = 0.8   # threshold
R2 = 9.0   # resistance
C2 = 0.01  # capacitance

try:
    iaf.iaf_recoverable(u, bw, b2, d2, R2, C2)
except ValueError('reconstruction condition not satisfied'):
    sys.exit()

b_list = np.array([b1, b2])
d_list = np.array([d1, d2])