current = log['current']
voltage = log['voltage']
del (log)
#
# Load protocol
#
if protocol_name == 'sine-wave':
protocol_file = os.path.join(root, 'steps.mmt')
protocol = myokit.load_protocol(protocol_file)
sw = 1
#
# Apply capacitance filter based on protocol
#
print('Applying capacitance filtering')
time, voltage, current = forwardModel.capacitance(
protocol, 0.1, time, voltage, current)
elif protocol_name == 'original-sine':
root = os.path.abspath('original-sine-data')
protocol_file = os.path.join(root, 'steps.mmt')
protocol = myokit.load_protocol(
protocol_file) # Same steps before sine wave
print('Applying capacitance filtering')
time, voltage, current = forwardModel.capacitance(
protocol, 0.1, time, voltage, current)
if protocol_name != 'sine-wave':
sw = 0
print('Defining the protocol from ', root)
protocol_file = os.path.join(root, protocol_name + '.csv')
log = myokit.DataLog.load_csv(protocol_file).npview()
model_metrics = np.zeros((30, 8))
for i in xrange(30):
model_name = 'model-' + str(i + 1)
root = os.path.abspath('models_myokit')
myo_model = os.path.join(root, model_name + '.mmt')
root = os.path.abspath('rate_dictionaries')
rate_file = os.path.join(root, model_name + '-priors.p')
rate_dict = cPickle.load(open(rate_file, 'rb'))
sys.path.append(os.path.abspath('models_forward'))
print("loading model: " + str(i + 1))
model_name = 'model-' + str(i + 1)
temperature = forwardModel.temperature(cell)
lower_conductance = forwardModel.conductance_limit(cell)
print('Applying capacitance filtering')
time, voltage, current = forwardModel.capacitance(protocol_sine, 0.1,
time_sine, voltage_sine,
current_sine)
sigma_noise_sine = np.std(current_sine[:2000], ddof=1)
sigma_noise_ap = np.std(current_ap[:2000], ddof=1)
#
# Create forward model
#
transform = 0
model = forwardModel.ForwardModel(protocol_sine,
temperature,
myo_model,
rate_dict,
transform,
sine_wave=True)
model_ap = forwardModel.ForwardModel(protocol_ap,
temperature,