def parsing_yaml_files(self, loop_counter=0, list_of_updated_yamls=[]):
if loop_counter == 0:
yaml_instance = yp.Parser()
else:
yaml_instance = yp.Parser(original_experimental_conditions=self.
original_experimental_conditions_local)
#print(self.original_experimental_conditions_local[0]['coupledCoefficients'],'other copy')
self.yaml_instance = yaml_instance
if loop_counter == 0:
list_of_yaml_objects = yaml_instance.load_yaml_list(
yaml_list=self.yaml_file_list_with_working_directory)
self.list_of_yaml_objects = list_of_yaml_objects
list_of_parsed_yamls = yaml_instance.parsing_multiple_dictonaries(
list_of_yaml_objects=list_of_yaml_objects,
loop_counter=loop_counter)
list_of_parsed_yamls_original = copy.deepcopy(list_of_parsed_yamls)
self.list_of_parsed_yamls_original = list_of_parsed_yamls_original
self.list_of_parsed_yamls = list_of_parsed_yamls_original
else:
list_of_yaml_objects = yaml_instance.load_yaml_list(
yaml_list=self.updated_yaml_file_name_list)
self.list_of_yaml_objects = list_of_yaml_objects
list_of_parsed_yamls = yaml_instance.parsing_multiple_dictonaries(
list_of_yaml_objects=list_of_yaml_objects,
loop_counter=loop_counter)
self.list_of_parsed_yamls = list_of_parsed_yamls
return
def parsing_yaml_files(self, loop_counter=0):
yaml_instance = yp.Parser()
self.yaml_instance = yaml_instance
list_of_yaml_objects = yaml_instance.load_yaml_list(
yaml_list=self.yaml_file_list_with_working_directory)
self.list_of_yaml_objects = list_of_yaml_objects
list_of_parsed_yamls = yaml_instance.parsing_multiple_dictonaries(
list_of_yaml_objects=list_of_yaml_objects,
loop_counter=loop_counter)
self.list_of_parsed_yamls = list_of_parsed_yamls
#print(yaml_instance.original_experimental_conditions)
return
temperature=Temp,
observables=['h2o2', 'ho2'],
kineticSens=0,
physicalSens=0,
conditions=conditions_dict,
initialTime=0,
finalTime=0.02,
thermalBoundary='Adiabatic',
mechanicalBoundary='constant volume',
processor=test_p,
save_timeHistories=1,
save_physSensHistories=1)
test_tube.run()
time_History = test_tube.timeHistory
parser = yp.Parser()
abs_instance = csp.Absorb()
abs_loaded = parser.load_to_obj(
'MSI/data/automating_kircher_Ar_1983/abs_kircher.yaml')
abs_data = abs_instance.superimpose_shock_tube(test_tube,
abs_loaded,
670.0,
kinetic_sens=0)
plt.plot(test_tube.timeHistories[0]['time'] * 1e3,
abs_data[wavelength],
label='constant value rate constants')
# fall_off = time_History['O'][0]/time_History['O']
import MSI.optimization.matrix_loader as ml
import MSI.optimization.opt_runner as opt
import MSI.simulations.absorbance.curve_superimpose as csp
import MSI.simulations.yaml_parser as yp
import cantera as ct
#
test_p = pr.Processor(
'/Users/carlylagrotta/Desktop/MSI/data/test_data/FFCM1_custom.cti')
yaml_file_list = [
('MSI/data/test_data/Hong_4.yaml', 'MSI/data/test_data/Hong_4_abs.yaml'),
('MSI/data/test_data/Hong_1.yaml', ),
('MSI/data/test_data/Troe_6.yaml', 'MSI/data/test_data/Troe_6_abs.yaml'),
('MSI/data/test_data/Hong_4.yaml', 'MSI/data/test_data/Hong_4_abs.yaml')
]
yaml_instance = yp.Parser()
list_of_yaml_objects = yaml_instance.load_yaml_list(yaml_list=yaml_file_list)
list_of_experiment_dicts = yaml_instance.parsing_multiple_dictonaries(
list_of_yaml_objects=list_of_yaml_objects)
optimization_instance = opt.Optimization_Utility()
test = optimization_instance.looping_over_parsed_yaml_files(
list_of_experiment_dicts,
yaml_file_list,
processor=test_p,
kineticSens=1,
physicalSens=1,
dk=.01)
matix_instance = ml.OptMatrix()
def running_shock_tube_absorption_only(self,processor=None,
experiment_dictonary:dict={},
absorbance_yaml_file_path = '',
kineticSens = 1,
physicalSens = 1,
dk = .01,
exp_number=1):
shock_tube = st.shockTube(pressure = experiment_dictonary['pressure'],
temperature = experiment_dictonary['temperature'],
observables = experiment_dictonary['observables'],
kineticSens = kineticSens,
physicalSens = physicalSens,
conditions = experiment_dictonary['conditions'],
initialTime = experiment_dictonary['initialTime'],
finalTime = experiment_dictonary['finalTime'],
thermalBoundary = experiment_dictonary['thermalBoundary'],
mechanicalBoundary = experiment_dictonary['mechanicalBoundary'],
processor = processor,
save_timeHistories = 1,
save_physSensHistories = 1,
moleFractionObservables = experiment_dictonary['moleFractionObservables'],
absorbanceObservables = experiment_dictonary['absorbanceObservables'],
concentrationObservables = experiment_dictonary['concentrationObservables'],
fullParsedYamlFile = experiment_dictonary)
shock_tube.run()
abs_instance = csp.Absorb()
parser = yp.Parser()
abs_loaded = parser.load_to_obj(absorbance_yaml_file_path)
abs_data = abs_instance.superimpose_shock_tube(shock_tube,abs_loaded,experiment_dictonary['pathLength'],
kinetic_sens=kineticSens)
#print(abs_data)
perturbed_coef = abs_instance.perturb_abs_coef(dk,
shock_tube,
abs_loaded,
experiment_dictonary['pathLength'],
summed_data = abs_data[0])
shock_tube.sensitivity_adjustment(temp_del = dk)
shock_tube.sensitivity_adjustment(pres_del = dk)
shock_tube.species_adjustment(dk)
abs_phys_sens = abs_instance.absorb_phys_sensitivities(shock_tube,abs_data[0],abs_loaded,
experiment_dictonary['pathLength'],
dk = dk)
#int_ksens_exp_mapped= shock_tube.map_and_interp_ksens()
loaded_experimental_data_absorbance = abs_instance.import_experimental_data(experiment_dictonary['absorbanceCsvFiles'])
interp_abs_exp= abs_instance.interpolate_experimental(shock_tube,loaded_experimental_data_absorbance,
original_summed_absorption=abs_data[0],
abs_kinetic_sens = abs_data[1],
abs_phys_sens = abs_phys_sens,
abs_coef_sens = perturbed_coef)
time_history_interp_against_experiment_dict = abs_instance.interpolate_experimental(shock_tube,
loaded_experimental_data_absorbance,
time_history = shock_tube.timeHistories[0])
experiment = self.build_single_exp_dict(exp_number,
shock_tube,
None,
None,
None,
interpolated_absorbance=interp_abs_exp,
absorbance_experimental_data = loaded_experimental_data_absorbance,
time_history_interpolated_against_absorbance_experiment = time_history_interp_against_experiment_dict)
return experiment
def running_full_shock_tube_absorption(self,processor=None,
experiment_dictonary:dict={},
absorbance_yaml_file_path = '',
kineticSens = 1,
physicalSens = 1,
dk = .01,
exp_number=1):
shock_tube = st.shockTube(pressure = experiment_dictonary['pressure'],
temperature = experiment_dictonary['temperature'],
observables = experiment_dictonary['observables'],
kineticSens = kineticSens,
physicalSens = physicalSens,
conditions = experiment_dictonary['conditions'],
initialTime = experiment_dictonary['initialTime'],
finalTime = experiment_dictonary['finalTime'],
thermalBoundary = experiment_dictonary['thermalBoundary'],
mechanicalBoundary = experiment_dictonary['mechanicalBoundary'],
processor = processor,
save_timeHistories = 1,
save_physSensHistories = 1,
moleFractionObservables = experiment_dictonary['moleFractionObservables'],
absorbanceObservables = experiment_dictonary['absorbanceObservables'],
concentrationObservables = experiment_dictonary['concentrationObservables'],
fullParsedYamlFile = experiment_dictonary)
csv_paths = [x for x in experiment_dictonary['moleFractionCsvFiles'] + experiment_dictonary['concentrationCsvFiles'] if x is not None]
exp_data = shock_tube.importExperimentalData(csv_paths)
shock_tube.run()
#this might be in the wrong spot
int_ksens_exp_mapped= shock_tube.map_and_interp_ksens()
abs_instance = csp.Absorb()
parser = yp.Parser()
abs_loaded = parser.load_to_obj(absorbance_yaml_file_path)
abs_data = abs_instance.superimpose_shock_tube(shock_tube,abs_loaded,experiment_dictonary['pathLength'],
kinetic_sens=kineticSens)
perturbed_coef = abs_instance.perturb_abs_coef(dk,
shock_tube,
abs_loaded,
experiment_dictonary['pathLength'],
summed_data = abs_data[0])
shock_tube.sensitivity_adjustment(temp_del = dk)
shock_tube.sensitivity_adjustment(pres_del = dk)
shock_tube.species_adjustment(dk)
int_tp_psen_against_experimental = shock_tube.interpolate_experimental([shock_tube.interpolate_physical_sensitivities(index=1),
shock_tube.interpolate_physical_sensitivities(index=2)])
int_spec_psen_against_experimental = shock_tube.interpolate_experimental(pre_interpolated=shock_tube.interpolate_species_sensitivities())
abs_phys_sens = abs_instance.absorb_phys_sensitivities(shock_tube,abs_data[0],abs_loaded,
experiment_dictonary['pathLength'],
dk = dk)
loaded_experimental_data_absorbance = abs_instance.import_experimental_data(experiment_dictonary['absorbanceCsvFiles'])
interp_abs_exp= abs_instance.interpolate_experimental(shock_tube,loaded_experimental_data_absorbance,
original_summed_absorption=abs_data[0],
abs_kinetic_sens = abs_data[1],
abs_phys_sens = abs_phys_sens,
abs_coef_sens = perturbed_coef)
time_history_interp_against_experiment_dict = abs_instance.interpolate_experimental(shock_tube,
loaded_experimental_data_absorbance,
time_history = shock_tube.timeHistories[0])
#################################################################################
single_data = shock_tube.interpolate_experimental(single=shock_tube.timeHistories[0])
shock_tube.savingInterpTimeHistoryAgainstExp(single_data)
shock_tube.interpolatePressureandTempToExperiment(shock_tube,exp_data)
####################################################################################
experiment = self.build_single_exp_dict(exp_number,
shock_tube,
int_ksens_exp_mapped,
int_tp_psen_against_experimental,
int_spec_psen_against_experimental,
interpolated_absorbance=interp_abs_exp,
experimental_data = exp_data,
absorbance_experimental_data = loaded_experimental_data_absorbance,
time_history_interpolated_against_absorbance_experiment = time_history_interp_against_experiment_dict )
return experiment
os.chdir(
'../../'
) #get rid of this at some point with central test script or when package is built
import MSI.simulations.instruments.shock_tube as st
import MSI.cti_core.cti_processor as pr
import MSI.simulations.absorbance.curve_superimpose as csp
import MSI.simulations.yaml_parser as yp
import cantera as ct
import pandas as pd
import matplotlib.pyplot as plt
value = 15
#MSI YAML FILES AND CONDITIONS
parser = yp.Parser()
exp = parser.load_to_obj(
'MSI/data/klip_optimization_with_raw_data/Hong_HO2_fake_data_' +
str(value) + '_updated.yaml')
absp = parser.load_to_obj(
'MSI/data/klip_optimization_with_raw_data/Hong_HO2_fake_data_' +
str(value) + '_abs_updated.yaml')
loaded_tube = parser.parse_shock_tube_obj(loaded_exp=exp,
loaded_absorption=absp)
pressure = loaded_tube['pressure']
temperature = loaded_tube['temperature']
conditions = loaded_tube['conditions']
print("THESE ARE THE MSI CONDITIONS")
print(pressure)
