def run_simulation(self, num_sites):
voltages, concentrations, conc_labels = self.simulation_frame.get_run_simulation_settings()
if not self.Q_value:
self.Q_value = [1] # hack
barriers = self.parameter_frame.energy_barriers
"""
results have the class Results found in numpy_helper_functions and has the attributes
voltage, matrix_specs, ion_transport self.fitting, current and steady_state
"""
results_eig, results_svd, results_qr = eyring_rate_script.eyring_rate_algo(voltages, concentrations,
barriers,
num_barriers=num_sites,
Qs=self.Q_value, Rs=self.R_value)
solutes = []
for solute in results_eig[0].ion_transport:
solutes.append(solute)
result_toplevel.MultiPlotWindows(self, voltages, barriers, results_eig, solutes, conc_labels, "Eig results")
result_toplevel.MultiPlotWindows(self, voltages, barriers, results_svd, solutes, conc_labels, "SVD results")
result_toplevel.MultiPlotWindows(self, voltages, barriers, results_qr, solutes, conc_labels, "QR results")
'GFe': [10.47, -12.62, 9.68, -12.44, 6.3, -8, 10, -12, 10],
'GBa': [10.47, -12.62, 9.68, -12.44, 6.3, -8, 10, -8, 8]}
voltages = range(-150, 110, 10)
voltages2 = [-100, 100]
dps = range(50, 150, 10)
# print voltages
num_barriers = 3
# results_eig,
ion_conc = {'solute_1i': 0.001, 'solute_1e': 0.001}
energy_barriers = {'distance': [0.25, 0.5, 0.75], 'solute_1': [8.0, -10.0, 8.0]}
results_eig, results_svd = test.eyring_rate_algo(voltages,
ion_conc,
energy_barriers,
2,
[1],
[0.5, 0.9, 1, 0.5, 0.9, 0.5, 1, 0.9, 0.5],
10)
print 'test1'
"""
results has the fields
voltage
matrix_spec
ion_transport
fitting
current
"""
print 'test a'
result_shelf = shelve.open("Results1")
