def execute_thermodynamicSampling(self,simulation_id_I,models_I,
data_dir_I,rxn_ids_I=[],
inconsistent_dG_f_I=[],inconsistent_concentrations_I=[],
inconsistent_tcc_I=[],
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99,
solver_I='glpk'):
'''execute a thermodynamic analysis using the thermodynamic
module for cobrapy
Input:
inconsistent_dG_f_I = dG_f measured values to be substituted for estimated values
inconsistent_concentrations_I = concentration measured values to be substituted for estimated values
inconsistent_tcc_I = reactions considered feasible to be changed to infeasible so that dG0_r constraints do not break the model
measured_concentration_coverage_criteria_I = float, minimum concentration coverage to consider for feasibility
measured_dG_f_coveragea_criteria_I = float, minimum dG_f coverage to consider for feasibility
data_dir_I = directory of sampled points
solver_I = string, solver name
'''
modelsCOBRA = models_COBRA_dependencies();
print('execute_thermodynamicSampling...')
# get simulation information
simulation_info_all = [];
simulation_info_all = self.get_rows_simulationIDAndSimulationType_dataStage03QuantificationSimulation(simulation_id_I,'sampling')
if not simulation_info_all:
print('simulation not found!')
return;
simulation_info = simulation_info_all[0]; # unique constraint guarantees only 1 row will be returned
# get simulation parameters
simulation_parameters_all = [];
simulation_parameters_all = self.get_rows_simulationID_dataStage03QuantificationSimulationParameters(simulation_id_I);
if not simulation_parameters_all:
print('simulation not found!')
return;
simulation_parameters = simulation_parameters_all[0]; # unique constraint guarantees only 1 row will be returned
# get the cobra model
cobra_model = models_I[simulation_info['model_id']];
# copy the model
cobra_model_copy = cobra_model.copy();
# get rxn_ids
if rxn_ids_I:
rxn_ids = rxn_ids_I;
else:
rxn_ids = [];
rxn_ids = self.get_rows_experimentIDAndModelIDAndSampleNameAbbreviation_dataStage03QuantificationMeasuredFluxes(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['sample_name_abbreviation']);
for rxn in rxn_ids:
# constrain the model
cobra_model_copy.reactions.get_by_id(rxn['rxn_id']).lower_bound = rxn['flux_lb'];
cobra_model_copy.reactions.get_by_id(rxn['rxn_id']).upper_bound = rxn['flux_ub'];
# make the model irreversible
convert_to_irreversible(cobra_model_copy);
# get otherData
pH,temperature,ionic_strength = {},{},{}
pH,temperature,ionic_strength = self.get_rowsFormatted_experimentIDAndTimePointAndSampleNameAbbreviation_dataStage03QuantificationOtherData(simulation_info['experiment_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation']);
# load pH, ionic_strength, and temperature parameters
other_data = thermodynamics_otherData(pH_I=pH,temperature_I=temperature,ionic_strength_I=ionic_strength);
other_data.check_data();
# get dG_f data:
dG_f = {};
dG_f = self.get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGf(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation']);
dG_f_data = thermodynamics_dG_f_data(dG_f_I=dG_f);
dG_f_data.format_dG_f();
dG_f_data.generate_estimated_dG_f(cobra_model)
dG_f_data.check_data();
# remove an inconsistent dGf values
if inconsistent_dG_f_I: dG_f_data.remove_measured_dG_f(inconsistent_dG_f_I)
# query metabolomicsData
concentrations = [];
concentrations = self.get_rowsDict_experimentIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationMetabolomicsData(simulation_info['experiment_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation']);
# load metabolomicsData
metabolomics_data = thermodynamics_metabolomicsData(measured_concentrations_I=concentrations);
metabolomics_data.generate_estimated_metabolomics_data(cobra_model);
# remove an inconsistent concentration values
if inconsistent_concentrations_I: metabolomics_data.remove_measured_concentrations(inconsistent_concentrations_I);
# get dG0r, dGr, and tcc data
dG0_r = {};
dG0_r = self.get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDG0r(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation'])
measured_concentration_coverage,measured_dG_f_coverage,feasible = {},{},{};
measured_concentration_coverage,measured_dG_f_coverage,feasible = self.get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationTCC(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation'],0,0)
tcc = thermodynamics_dG_r_data(dG0_r_I = dG0_r,
dG_r_coverage_I = measured_dG_f_coverage,
metabolomics_coverage_I = measured_concentration_coverage,
thermodynamic_consistency_check_I = feasible);
if inconsistent_tcc_I: tcc.change_feasibleReactions(inconsistent_tcc_I);
# apply tfba constraints
tfba = thermodynamics_tfba()
tfba._add_conc_ln_constraints_transport(cobra_model_copy, metabolomics_data.measured_concentrations, metabolomics_data.estimated_concentrations,
tcc.dG0_r, other_data.pH,other_data.temperature,tcc.metabolomics_coverage,
tcc.dG_r_coverage, tcc.thermodynamic_consistency_check,
measured_concentration_coverage_criteria_I, measured_dG_f_coverage_criteria_I,
use_measured_concentrations=True,use_measured_dG0_r=True);
# Test model
if modelsCOBRA.test_model(cobra_model_I=cobra_model_copy):
sampling = cobra_sampling(data_dir_I = data_dir_I);
if simulation_parameters['sampler_id']=='gpSampler':
filename_model = simulation_id_I + '.mat';
filename_script = simulation_id_I + '.m';
filename_points = simulation_id_I + '_points' + '.mat';
sampling.export_sampling_matlab(cobra_model=cobra_model_copy,filename_model=filename_model,filename_script=filename_script,filename_points=filename_points,\
solver_id_I = simulation_parameters['solver_id'],\
n_points_I = simulation_parameters['n_points'],\
n_steps_I = simulation_parameters['n_steps'],\
max_time_I = simulation_parameters['max_time']);
elif simulation_parameters['sampler_id']=='optGpSampler':
return;
else:
print('sampler_id not recognized');
else:
print('no solution found!');
def execute_analyzeThermodynamicSamplingPoints(self,simulation_id_I,models_I,
data_dir_I,data_dir_O,rxn_ids_I=[],
inconsistent_dG_f_I=[],inconsistent_concentrations_I=[],
inconsistent_tcc_I=[],
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99,
remove_pointsNotInSolutionSpace_I=True,
min_pointsInSolutionSpace_I=1000):
'''Load and analyze sampling points
Input:
inconsistent_dG_f_I = dG_f measured values to be substituted for estimated values
inconsistent_concentrations_I = concentration measured values to be substituted for estimated values
inconsistent_tcc_I = reactions considered feasible to be changed to infeasible so that dG0_r constraints do not break the model
measured_concentration_coverage_criteria_I = float, minimum concentration coverage to consider for feasibility
measured_dG_f_coveragea_criteria_I = float, minimum dG_f coverage to consider for feasibility
remove_pointsNotInSolutionSpace_I = boolean, remove points not in the solution space (i.e., within the lower/upper bounds)
min_pointsInSolutionSpace_I = int, minimum number of points in the solution space.
if the number of points is less that the minimum, the solution space will be increased by
(upper_bounds-lower_bounds)/4 until the minimum number of points is met
data_dir_I = directory of sampled points
data_dir_O = director to write QC'd sampled points
solver_I = string, solver name
'''
print('analyzing sampling points');
modelsCOBRA = models_COBRA_dependencies();
# get simulation information
simulation_info_all = [];
simulation_info_all = self.get_rows_simulationIDAndSimulationType_dataStage03QuantificationSimulation(simulation_id_I,'sampling')
if not simulation_info_all:
print('simulation not found!')
return;
simulation_info = simulation_info_all[0]; # unique constraint guarantees only 1 row will be returned
# get simulation parameters
simulation_parameters_all = [];
simulation_parameters_all = self.get_rows_simulationID_dataStage03QuantificationSimulationParameters(simulation_id_I);
if not simulation_parameters_all:
print('simulation not found!')
return;
simulation_parameters = simulation_parameters_all[0]; # unique constraint guarantees only 1 row will be returned
# get the cobra model
cobra_model = models_I[simulation_info['model_id']];
# copy the model
cobra_model_copy = cobra_model.copy();
# get rxn_ids
if rxn_ids_I:
rxn_ids = rxn_ids_I;
else:
rxn_ids = [];
rxn_ids = self.get_rows_experimentIDAndModelIDAndSampleNameAbbreviation_dataStage03QuantificationMeasuredFluxes(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['sample_name_abbreviation']);
for rxn in rxn_ids:
# constrain the model
cobra_model_copy.reactions.get_by_id(rxn['rxn_id']).lower_bound = rxn['flux_lb'];
cobra_model_copy.reactions.get_by_id(rxn['rxn_id']).upper_bound = rxn['flux_ub'];
# make the model irreversible
convert_to_irreversible(cobra_model_copy);
# get otherData
pH,temperature,ionic_strength = {},{},{}
pH,temperature,ionic_strength = self.get_rowsFormatted_experimentIDAndTimePointAndSampleNameAbbreviation_dataStage03QuantificationOtherData(simulation_info['experiment_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation']);
# load pH, ionic_strength, and temperature parameters
other_data = thermodynamics_otherData(pH_I=pH,temperature_I=temperature,ionic_strength_I=ionic_strength);
other_data.check_data();
# get dG_f data:
dG_f = {};
dG_f = self.get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGf(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation']);
dG_f_data = thermodynamics_dG_f_data(dG_f_I=dG_f);
dG_f_data.format_dG_f();
dG_f_data.generate_estimated_dG_f(cobra_model)
dG_f_data.check_data();
# remove an inconsistent dGf values
if inconsistent_dG_f_I: dG_f_data.remove_measured_dG_f(inconsistent_dG_f_I)
# query metabolomicsData
concentrations = [];
concentrations = self.get_rowsDict_experimentIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationMetabolomicsData(simulation_info['experiment_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation']);
# load metabolomicsData
metabolomics_data = thermodynamics_metabolomicsData(measured_concentrations_I=concentrations);
metabolomics_data.generate_estimated_metabolomics_data(cobra_model);
# remove an inconsistent concentration values
if inconsistent_concentrations_I: metabolomics_data.remove_measured_concentrations(inconsistent_concentrations_I);
# get dG0r, dGr, and tcc data
dG0_r = {};
dG0_r = self.get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDG0r(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation'])
measured_concentration_coverage,measured_dG_f_coverage,feasible = {},{},{};
measured_concentration_coverage,measured_dG_f_coverage,feasible = self.get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationTCC(simulation_info['experiment_id'],simulation_info['model_id'],simulation_info['time_point'],simulation_info['sample_name_abbreviation'],0,0)
tcc = thermodynamics_dG_r_data(dG0_r_I = dG0_r,
dG_r_coverage_I = measured_dG_f_coverage,
metabolomics_coverage_I = measured_concentration_coverage,
thermodynamic_consistency_check_I = feasible);
if inconsistent_tcc_I: tcc.change_feasibleReactions(inconsistent_tcc_I);
# apply tfba constraints
tfba = thermodynamics_tfba()
tfba._add_conc_ln_constraints_transport(cobra_model_copy, metabolomics_data.measured_concentrations, metabolomics_data.estimated_concentrations,
tcc.dG0_r, other_data.pH,other_data.temperature,tcc.metabolomics_coverage,
tcc.dG_r_coverage, tcc.thermodynamic_consistency_check,
measured_concentration_coverage_criteria_I, measured_dG_f_coverage_criteria_I,
use_measured_concentrations=True,use_measured_dG0_r=True);
# Test each model
if modelsCOBRA.test_model(cobra_model_I=cobra_model_copy):
sampling = cobra_sampling(data_dir_I = data_dir_I,model_I = cobra_model_copy);
if simulation_parameters['sampler_id']=='gpSampler':
# load the results of sampling
filename_points = simulation_id_I + '_points' + '.mat';
sampling.get_points_matlab(filename_points,'sampler_out');
# check if points were sampled outside the solution space
if remove_pointsNotInSolutionSpace_I:
pruned_reactions = sampling.remove_points_notInSolutionSpace(min_points_I=min_pointsInSolutionSpace_I);
## check if the model contains loops
#sampling.simulate_loops(data_fva=settings.workspace_data + '/loops_fva_tmp.json');
#sampling.find_loops(data_fva=settings.workspace_data + '/loops_fva_tmp.json');
#sampling.remove_loopsFromPoints();
sampling.descriptive_statistics();
elif simulation_parameters['sampler_id']=='optGpSampler':
return;
else:
print('sampler_id not recognized');
# add data to the database
row = {'simulation_id':simulation_id_I,
'simulation_dateAndTime':sampling.simulation_dateAndTime,
'mixed_fraction':sampling.mixed_fraction,
'data_dir':data_dir_I+'/'+filename_points,
'infeasible_loops':sampling.loops,
'used_':True,
'comment_':None
};
self.add_dataStage03QuantificationSampledPoints([row])
#row = None;
#row = data_stage03_quantification_sampledPoints(
# simulation_id_I,
# sampling.simulation_dateAndTime,
# sampling.mixed_fraction,
# data_dir_I+'/'+filename_points,
# sampling.loops,
# True,
# None);
#self.session.add(row);
# write points to json file
# add data to the database
sampledData_O = [];
for k,v in sampling.points_statistics.items():
type,units = tfba.get_variableTypeAndUnits(k);
row = {'simulation_id':simulation_id_I,
'simulation_dateAndTime':sampling.simulation_dateAndTime,
'variable_id':k,
'variable_type':type,
'variable_units':units,
'sampling_points':None, #v['points'],
'sampling_ave':v['ave'],
'sampling_var':v['var'],
'sampling_lb':v['lb'],
'sampling_ub':v['ub'],
'sampling_ci':0.95,
'sampling_min':v['min'],
'sampling_max':v['max'],
'sampling_median':v['median'],
'sampling_iq_1':v['iq_1'],
'sampling_iq_3':v['iq_3'],
'used_':True,
'comment_':None};
sampledData_O.append(row);
#row = None;
#row = data_stage03_quantification_sampledData(
# simulation_id_I,
# sampling.simulation_dateAndTime,
# k,
# type,
# units,
# None, #v['points'],
# v['ave'],
# v['var'],
# v['lb'],
# v['ub'],
# v['min'],
# 0.95,
# v['max'],
# v['median'],
# v['iq_1'],
# v['iq_3'],
# True,
# None);
#self.session.add(row);
self.add_dataStage03QuantificationSampledData(sampledData_O);
else:
print('no solution found!');