def __init__(self, params=None, **kwargs):
super(ChemostatSimple, self).__init__(**kwargs)
if params == None:
params = AttributeDict(kwargs)
# Initialize update progress function
self.updateProgress = params.updateProgress
# Initialize parameters
self.m = params.m
self.K = params.K
self.S_in = params.S_in
self.X_in = params.X_in
self.gamma = params.gamma
self.D_vals = params.D_vals
# Create state vector and derivative vector
stateVarNames = ['S', 'X']
self.y = NamedStateVector(stateVarNames)
self.yRes = NamedStateVector(stateVarNames)
self.yDot = NamedStateVector(stateVarNames)
# Initialize data storage
self.resultStorage = ResultStorage(filePath=dataStorageFilePath,
datasetPath=dataStorageDatasetPath)
if (kwargs.get('initDataStorage', True)):
self.resultStorage.initializeWriting(varList=['t'] +
stateVarNames + ['D'],
chunkSize=1e4)
# Register time event (changed of D)
D_val = self.D_vals[0]
self.D = D_val[1]
tChangedD = D_val[0]
for i in range(len(self.D_vals) - 1):
self.D_val = self.D_vals[i + 1]
self.timeEventRegistry.add(
ChemostatSimpleTimeEvent(t=tChangedD,
newValue_D=self.D_val[1]))
tChangedD += self.D_val[0]
# Set initial values of the states
self.y.S = params.S0
self.y.X = params.X0
# Set all the initial state values
self.y0 = self.y.get(copy=True)
# Set the initial flags
self.sw0 = [True]
def __init__(self, params=None, **kwargs):
"""
#params.reactions = [reactionEquation, rateConstants]
#params.species = [speciesVariable, initialValue]
"""
super(BiochemicalReactions, self).__init__(**kwargs)
if params == None:
params = AttributeDict(kwargs)
# Initialize update progress function
self.updateProgress = params.updateProgress
# Get the species variables Xs = [X1, X2, ..., Xn] and their initial values
self.Xs = np.empty(len(params.species), dtype=(np.str_, 256))
self.X0s = np.zeros(len(params.species))
for i, itSpecies in enumerate(params.species):
self.Xs[i] = itSpecies[0]
self.X0s[i] = itSpecies[1]
# Get the reactions = [[left Xs, right Xs, k, ss, rs, f], ...], where:
# left Xs - the species variables of reactants (i.e. the species variables of the left parts of the reactions)
# rigth Xs - the species variables of products (i.e. the species variables of the right parts of the reactions)
# k - the rate constant of the reaction
# ss - the stoichiometric coefficients of reactants (e.g. [0,1,1,0,...,1])
# rs - the stoichiometric coefficients of products (e.g. [1,0,...,0])
# f - the fluxs (e.g. k*X2*X3*...*Xn)
self.reactions = self.readReactions(params.reactions, self.Xs)
#for reaction in self.reactions: print reaction
# Create a vector with state variable names
stateVarNames = list(self.Xs)
# Initialize data storage
self.resultStorage = ResultStorage(filePath=dataStorageFilePath,
datasetPath=dataStorageDatasetPath)
if (kwargs.get('initDataStorage', True)):
self.resultStorage.initializeWriting(varList=['t'] + stateVarNames,
chunkSize=1e4)
# Set the initial state values
self.y0 = self.X0s
# Set the initial flags
self.sw0 = [True]
def __init__(self, webModel, paramsRH2, concentrsRH2, paramsRCH4,
concentrsRCH4, **kwargs):
super(ADM1H2CH4Bioreactors, self).__init__(**kwargs)
# Initialize update progress function
self.updateProgress = webModel.updateProgress
# Initialize parameters
self.paramsRH2 = paramsRH2
self.paramsRCH4 = paramsRCH4
# Initialize concentrations
self.concentrsRH2 = concentrsRH2
self.concentrsRCH4 = concentrsRCH4
# Create state vector and derivative vector
stateVarNames = [
'S_su_RH2', 'S_aa_RH2', 'S_fa_RH2', 'S_ac_RH2', 'X_c_RH2',
'X_ch_RH2', 'X_pr_RH2', 'X_li_RH2', 'X_suaa_RH2', 'X_fa_RH2',
'intQ_h2_RH2', 'S_ac_RCH4', 'X_ac_RCH4', 'intQ_ch4_RCH4'
]
self.y = NamedStateVector(stateVarNames)
self.yRes = NamedStateVector(stateVarNames)
self.yDot = NamedStateVector(stateVarNames)
# Initialize data storage
self.resultStorage = ResultStorage(filePath=dataStorageFilePath,
datasetPath=dataStorageDatasetPath)
if (kwargs.get('initDataStorage', True)):
self.resultStorage.initializeWriting(
varList=['time'] + stateVarNames +
['Q_h2_RH2', 'Q_ch4_RCH4', 'D_RH2', 'D_RCH4'],
chunkSize=1e4)
# Register time event (changed of D)
tChangedD = paramsRH2.D_liq_arr[0][0]
self.D_RH2 = paramsRH2.D_liq_arr[0][1]
self.D_RCH4 = self.D_RH2 / paramsRCH4.V_liq_RCH4_del_V_liq_RH2
for i in range(len(paramsRH2.D_liq_arr) - 1):
self.timeEventRegistry.add(
ADM1TimeEvent(t=tChangedD,
newValue_D=paramsRH2.D_liq_arr[i + 1][1]))
tChangedD += paramsRH2.D_liq_arr[i + 1][0]
# Set initial values of the states
self.y.S_su_RH2 = concentrsRH2.S_su_0
self.y.S_aa_RH2 = concentrsRH2.S_aa_0
self.y.S_fa_RH2 = concentrsRH2.S_fa_0
self.y.S_ac_RH2 = concentrsRH2.S_ac_0
self.y.X_c_RH2 = concentrsRH2.X_c_0
self.y.X_ch_RH2 = concentrsRH2.X_ch_0
self.y.X_pr_RH2 = concentrsRH2.X_pr_0
self.y.X_li_RH2 = concentrsRH2.X_li_0
self.y.X_suaa_RH2 = concentrsRH2.X_suaa_0
self.y.X_fa_RH2 = concentrsRH2.X_fa_0
self.y.intQ_h2_RH2 = 0.0
self.Q_h2_RH2 = 0.0
self.y.S_ac_RCH4 = concentrsRCH4.S_ac_0
self.y.X_ac_RCH4 = concentrsRCH4.X_ac_0
self.y.intQ_ch4_RCH4 = 0.0
self.Q_ch4_RCH4 = 0.0
# Set all the initial state values
self.y0 = self.y.get(copy=True)
# Set the initial flags
self.sw0 = [True]
