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from rmgpy.tools.uncertainty import Uncertainty
from IPython.display import display
import copy


    

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chemFile = 'data/parseSource/chem_annotated.inp'
dictFile = 'data/parseSource/species_dictionary.txt'


    

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uncertainty = Uncertainty(outputDirectory='testUncertainty')


    

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uncertainty.loadModel(chemFile, dictFile)


    

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uncertainty.loadDatabase()


    

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uncertainty.extractSourcesFromModel()


    

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print 'All Kinetic Sources'
for sourceType in uncertainty.allKineticSources.keys():
    if sourceType == 'Library':
        print '============'
        print 'Library kinetics'
        print ''
        print '\tReactions: ', uncertainty.allKineticSources['Library']
    elif sourceType == 'PDep':
        print '============'
        print 'PDep kinetics'
        print ''
        print '\tReactions: ', uncertainty.allKineticSources['PDep']
    elif sourceType == 'Rate Rules':
        print '============'
        print 'Rate rule kinetics'
        print ''
        for familyLabel, entries in uncertainty.allKineticSources['Rate Rules'].iteritems():
            print '\t', familyLabel
            for entry in entries:
                print '\t\t', entry
    elif sourceType == 'Training':
        print '============'
        print 'Training reaction kinetics'
        print ''
        for familyLabel, entries in uncertainty.allKineticSources['Training'].iteritems():
            print '\t', familyLabel
            for entry in entries:
                print '\t\t', entry
    else:
        print sourceType
        raise Exception('Kinetics source mut be Library, PDep, Rate Rules, or Training')


    

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print 'All Thermo Sources'
for sourceType in uncertainty.allThermoSources.keys():
    if sourceType == 'Library':
        print '============'
        print 'Library thermo'
        print ''
        print '\tSpecies: ', uncertainty.allThermoSources['Library']
    elif sourceType == 'QM':
        print '============'
        print 'QM thermo'
        print ''
        print '\tSpecies: ', uncertainty.allThermoSources['QM']
    elif sourceType == 'GAV':
        print '============'
        print 'Group additivity thermo'
        print ''
        for groupType, entries in uncertainty.allThermoSources['GAV'].iteritems():
            print '\t', groupType
            for entry in entries:
                print '\t\t', entry
    else:
        raise Exception('Thermo source must be GAV, QM, or Library')


    

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# Assign all the uncertainties using the Uncertainty() class function
# ThermoParameterUncertainty and KineticParameterUncertainty classes may be customized and passed into this function
# if non-default constants for constructing the uncertainties are desired
uncertainty.assignParameterUncertainties()


    

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T = 623 # temperature in Kelvin for which to evaluate kinetics
P = 1e5  # Pa


    

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for rxn, source in uncertainty.reactionSourcesDict.iteritems():
    print '======'
    print rxn
    display(rxn)
    if 'Library' in source:
        print 'Library reaction'
    elif 'PDep' in source:
        print 'PDep reaction'
    elif 'Rate Rules' in source:
        print 'Rate rule estimate'
        family = source['Rate Rules'][0]
        sourceDict = source['Rate Rules'][1]
        originalTemplate = sourceDict['template']
        print '\tFamily = ', family
        print '\tOriginal Template = ', [group.label for group in originalTemplate]
        print '\tExact = ', sourceDict['exact']
        rules = sourceDict['rules']
        training = sourceDict['training']
        if rules:
            print '\tRate rule sources:'
            for ruleEntry, weight in rules:
                print '\t\t', ruleEntry, '=', weight
        if training:
            print '\tTraining sources:'
            for ruleEntry, trainingEntry, weight in training:
                print '\t\t', ruleEntry , 'mapped to', trainingEntry , '=', weight
    elif 'Training' in source:
        print 'Training reaction'
        family = source['Training'][0]
        training = source['Training'][1]
        print '\t Family = ', family
        print '\t\t', training



    print ''
    print 'Rate coefficient at {} K = {:.2e}'.format(T, rxn.kinetics.getRateCoefficient(T,P))

    # Uncomment the following lines if you want to verify that the parsing has been performed correctly by
    # checking the values for both the original and reconstructed kinetics

#     print '---------'
#     print 'Original kinetics:'
#     print rxn.kinetics
#     print ''
#     print 'Reconstructed kinetics from parsing:'
#     reconstructedKinetics=uncertainty.database.kinetics.reconstructKineticsFromSource(rxn,source,fixBarrierHeight=True)
#     print reconstructedKinetics

    rxnIndex = uncertainty.reactionList.index(rxn)
    print 'Uncertainty dln(k) = ', uncertainty.kineticInputUncertainties[rxnIndex]


    

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for species, source in uncertainty.speciesSourcesDict.iteritems():
    print '=========='
    print species
    display(species)
    if 'Library' in source:
        print 'Thermo Library: ', source['Library']
    if 'QM' in source:
        print 'QM: ', source['QM']
    if 'GAV' in source:
        print 'Group additivity:'
        for groupType, groupList in source['GAV'].iteritems():
            print '\t', groupType
            for group, weight in groupList:
                print '\t\t', group, '=', weight
                
    spcIndex = uncertainty.speciesList.index(species)    
    print ''
    print 'Uncertainty dG = ', uncertainty.thermoInputUncertainties[spcIndex], ' kcal/mol'