def __init__(self):
self.simulation = oc.simulation()
self.simulation.data().setStartingPoint(0)
self.simulation.data().setEndingPoint(3900)
self.simulation.data().setPointInterval(1)
self.constants = self.simulation.data().constants()
self.constant_parameter_names = sorted(list(self.constants.keys()))
for i in range(0, len(fit_parameters_exclude)):
self.constant_parameter_names.remove(fit_parameters_exclude[i])
self.model_constants = OrderedDict(
{k: self.constants[k]
for k in self.constant_parameter_names})
# default the parameter bounds to something sensible, needs to be set directly
bounds = []
for c in self.constant_parameter_names:
v = self.constants[c]
bounds.append([bounds_dictionary[c][0], bounds_dictionary[c][1]])
# define our sensitivity analysis problem
self.problem = {
'num_vars': len(self.constant_parameter_names),
'names': self.constant_parameter_names,
'bounds': bounds
}
self.samples = saltelli.sample(self.problem, num_samples)
#print(self.samples)
np.savetxt("self.samples.txt", self.samples)
def __init__(self):
self.simulation = oc.simulation()
self.simulation.data().setStartingPoint(0)
self.simulation.data().setEndingPoint(3600)
self.simulation.data().setPointInterval(1)
self.constants = self.simulation.data().constants()
self.model_constants = OrderedDict({k: self.constants[k]
for k in self.constants.keys()})
def __init__(self):
self.simulation = oc.simulation()
self.simulation.data().setStartingPoint(0)
self.simulation.data().setEndingPoint(3600)
self.simulation.data().setPointInterval(1)
self.constants = self.simulation.data().constants()
self.simulation.resetParameters()
self.simulation.clearResults()
for k, v in dict.items():
self.constants[k] = v
self.model_constants = OrderedDict(
{k: self.constants[k]
for k in self.constants.keys()})
def __init__(self):
self.simulation = oc.simulation()
self.simulation.data().setStartingPoint(0)
self.simulation.data().setEndingPoint(3900)
self.simulation.data().setPointInterval(1)
self.constants = self.simulation.data().constants()
self.model_constants = OrderedDict(
{k: self.constants[k]
for k in self.constants.keys()})
#print(self.model_constants)
# default the parameter bounds to something sensible, needs to be set directly
bounds = []
#print(self.constants)
for c in self.constants:
v = self.constants[c]
print(c)
#print(bounds_dictionary[c][1])
print(v)
bounds.append([bounds_dictionary[c][0], bounds_dictionary[c][1]])
# Define sensitivity analysis problem
self.problem = {
'num_vars': len(self.constants),
'names': self.constants.keys(),
'bounds': bounds
}
self.problem = {
'num_vars':
12,
'names': [
'FCepsilonRI/k_f1', 'FCepsilonRI/k_f2', 'FCepsilonRI/k_f3',
'FCepsilonRI/k_f4', 'FCepsilonRI/k_f5', 'FCepsilonRI/k_f6',
'FCepsilonRI/k_f7', 'FCepsilonRI/k_r1', 'FCepsilonRI/k_r3',
'FCepsilonRI/k_r5', 'FCepsilonRI/k_r7', 'FCepsilonRI/k_f8'
],
'bounds': [[-5, 2], [-5, 2], [-5, 2], [-5, 2], [-5, 2], [-5, 2],
[-5, 2], [-10, -9], [-10, -9], [-10, -9], [-10, -9],
[-0.03, -0.027]]
}
# Generate Samples
self.samples = saltelli.sample(
self.problem, 50
) #Generate no of sample using N*(2D+2) where N is the supplied argument and D is no of constant
def figure(**kwds):
return plt.figure(FigureClass=Figure, tight_layout=True, **kwds)
if __name__ == '__main__':
import OpenCOR as oc
'''
s = oc.openSimulation('noble_1962.cellml')
s.data().setEndingPoint(0.6)
s.data().setPointInterval(0.005)
s.reset()
s.run()
'''
s = oc.simulation()
diagram = Diagram('noble_1962.svg', s, 0.04, 0.60, 's')
diagram.add_channel('sodium_channel/i_Na', 'i_Na', (183.849, 49.756), 'V', 'red')
diagram.add_channel('potassium_channel/i_K', 'i_K', (80.867, 49.756), 'V-', '#b666d2')
diagram.add_channel('leakage_current/i_Leak', 'i_Leak', (133.551, 167.485), 'V', 'orange')
svg = diagram.generate_svg(speed=0.5, period=25)
browser = oc.browserWebView()
browser.setContent(svg, "image/svg+xml")
f = open('noble_1962_animated.svg', 'w')
f.write(svg)
f.close()
def __init__(self):
print("Hello World")
self.simulation = oc.simulation()
print(filename)
print('oh year')