linewidth=20,
suppress=True # print small results as 0
)
D = loadmat('test/testSignal')
sr = float(D['Fs'][0][0])
s = D['signal'][0] # analytical signal (generated in matlab)
s = s[:10]
# plt.plot(real(s))
zp1 = Zparam(0.00001, 0, -2.0, 0, 0, 1)
zp2 = Zparam(-0.4, 1.75, -1.25, 0, 0, 1)
n1 = GrFNN(zp1, name='L1', frequency_range=(1., 4.), num_oscs=5, z0=0.5+0.5j, stimulus_conn_type='active')
n2 = GrFNN(zp2, name='L2', frequency_range=(1., 4.), num_oscs=5, z0=0.5+0.5j)
# C = np.eye(len(n1.f), len(n2.f))
C = make_connections(n1, n2, 1., 1.005)
M = Model()
M.add_layer(n1, input_channel=0)
M.add_layer(n2)
M.connect_layers(n1, n2, C, connection_type='2freq',
self_connect=False # to match connectAdd.m
)
M.run(s, np.arange(len(s), dtype=float)/sr, 1./sr)
# n1 = GrFNN(zp1, name='L1', frequency_range=(1., 4.), num_oscs=num_oscs, z0=0.5+0.5j, stimulus_conn_type='active') # n2 = GrFNN(zp2, name='L2', frequency_range=(1., 4.), num_oscs=num_oscs, z0=0.5+0.5j) n1 = GrFNN(zp1, name='L1', frequency_range=(1., 4.), num_oscs=num_oscs, stimulus_conn_type='active') n2 = GrFNN(zp2, name='L2', frequency_range=(1., 4.), num_oscs=num_oscs) M = Model() M.add_layer(n1, input_channel=0) M.add_layer(n2) # Connections modes = [1/3, 1/2, 1/1, 2/1, 3/1] amps = [1, 1, 1, 1, 1 ] C11 = make_connections(n1, n1, 1.0, 1.05, modes=modes, mode_amps=amps) C12 = make_connections(n1, n2, 1.0, 1.05, modes=modes, mode_amps=amps) C22 = make_connections(n2, n2, 1.0, 1.05, modes=modes, mode_amps=amps) C21 = make_connections(n2, n1, 1.0, 1.05, modes=modes, mode_amps=amps) c11 = M.connect_layers(n1, n1, C11, '2freq', weight=.10) c12 = M.connect_layers(n1, n2, C12, '2freq', weight=.40) c22 = M.connect_layers(n2, n2, C22, '2freq', weight=.10) c21 = M.connect_layers(n2, n1, C21, '2freq', weight=.05) M.run(s, np.arange(len(s), dtype=float)/sr, 1./sr) plt.ion() plt.clf() plt.plot(n1.f, np.abs(n1.z),'b')