def v1_kcat_mwc_ident():
name = MPI.Get_processor_name()
rank = MPI.COMM_WORLD.Get_rank()
size = MPI.COMM_WORLD.Get_size()
if rank == 0: # master
print('I am %s Master with rank %s of %s' %
(name, str(rank), str(size)))
v1_obj = ModelIdent(
ident_fun=kotte_model.flux_1_kcat_ident,
arranged_data_file_name=os.path.join(
os.getcwd(), 'exp/exp_v1_2_experiments_mwc'),
ident_data_file_name=os.path.join(os.getcwd(),
'ident/ident_v1_kcat_mwc'),
**{
'original_exp_file':
os.path.join(os.getcwd(), 'exp/experiments_mwc'),
'flux_id':
1,
'flux_choice':
2,
'values_figure':
os.path.join(os.getcwd(),
'results/v1_kcat_mwc_parameter_values.eps'),
'ident_figure':
os.path.join(os.getcwd(), 'results/v1_kcat_mwc_ident.eps'),
'exp_figure':
os.path.join(os.getcwd(), 'results/v1_kcat_mwc_exp.eps'),
'figure_format':
'eps'
})
exp_df = v1_obj.retrieve_df_from_file()
job = ParallelProcess(slaves=range(1, size))
ident_result = job.run_all(task='ident',
**{
'exp_df': exp_df,
'ident_fun': v1_obj.ident_fun,
'flux_id': v1_obj.flux_id,
'flux_choice': v1_obj.flux_choice
})
job.terminate_slaves()
# process ident data
ident_processing(v1_obj, ident_result)
else:
print('I am %s Slave with rank %s of %s' %
(name, str(rank), str(size)))
ProcessSlave().run()
return None
def v1_kcat_mwc_validate():
name = MPI.Get_processor_name()
rank = MPI.COMM_WORLD.Get_rank()
size = MPI.COMM_WORLD.Get_size()
if rank == 0:
# create ident object first
v1_ident = ModelIdent(
ident_fun=kotte_model.flux_1_kcat_ident,
arranged_data_file_name=os.path.join(
os.getcwd(), 'exp/exp_v1_2_experiments_mwc'),
ident_data_file_name=os.path.join(os.getcwd(),
'ident/ident_v1_kcat_mwc'),
**{
'original_exp_file':
os.path.join(os.getcwd(), 'exp/experiments_mwc'),
'flux_id':
1,
'flux_choice':
2,
'values_figure':
os.path.join(os.getcwd(),
'results/v1_kcat_mwc_parameter_values.eps'),
'ident_figure':
os.path.join(os.getcwd(), 'results/v1_kcat_mwc_ident.eps'),
'exp_figure':
os.path.join(os.getcwd(), 'results/v1_kcat_mwc_exp.eps'),
'figure_format':
'eps',
'ident_index_label': ['sample_name', 'data_set_id']
})
# retrieve identifiability data and process it for validation
v1_ident.validation_info()
user_ode_opts = {
'iter': 'Newton',
'discr': 'Adams',
'atol': 1e-10,
'rtol': 1e-10,
'time_points': 200,
'display_progress': True,
'verbosity': 30
}
# initial ss to begin all simulations from
y0 = np.array([5, 1, 1])
# get and set true parameter values, if available separately
default_parameters = true_parameter_values()
v1_valid_obj = ValidateSim(
kotte_model.kotte_ode, kotte_model.kotte_flux, **{
'kinetics':
1,
'ode_opts':
user_ode_opts,
't_final':
200,
'wt_y0':
y0,
'i_parameter':
default_parameters,
'sample_size':
1,
'noise_std':
0.05,
'validate_index_label':
['estimate_id', 'sample_name', 'data_set_id', 'experiment_id'],
'validate_file_name':
os.path.join(os.getcwd(), 'validate/v1_kcat_mwc_validate'),
'original_exp_file':
v1_ident.original_exp_file,
'c_validate_file':
os.path.join(os.getcwd(),
'results/v1_kcat_mwc_c_validate.eps'),
'f_validate_file':
os.path.join(os.getcwd(),
'results/v1_kcat_mwc_f_validate.eps'),
'c_exp_file':
os.path.join(os.getcwd(), 'results/v1_kcat_mwc_c_exp.eps'),
'v_exp_file':
os.path.join(os.getcwd(), 'results/v1_kcat_mwc_f_exp.eps'),
'format':
v1_ident.figure_format
})
parameter_estimates, estimate_info = v1_valid_obj.create_parameter_list(
v1_ident.select_values)
job = ParallelValidate(slaves=range(1, size))
validate_results = job.run_all(task='initial_sim',
**{
'parameters': parameter_estimates,
'estimate_info': estimate_info,
'sim_obj': v1_valid_obj
})
job.terminate_slaves()
# process validation data for plots
validate_processing(v1_valid_obj, validate_results)
else:
print('I am %s Slave with rank %s of %s' %
(name, str(rank), str(size)))
ValidateSlave().run()
return None
