os.path.join(
os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe()))),
'data_sets'))
filename = os.path.join(dataDirectory, 'Ex_1_C_data.txt')
C_frame = read_concentration_data_from_txt(filename)
# Then we build dae block for as described in the section 4.2.1. Note the addition
# of the data using .add_spectral_data
#################################################################################
builder = TemplateBuilder()
components = {'A': 1e-3, 'B': 0, 'C': 0}
builder.add_mixture_component(components)
builder.add_parameter('k1', bounds=(0.0, 5.0))
builder.add_parameter('k2', bounds=(0.0, 1.0))
builder.add_concentration_data(C_frame)
# define explicit system of ODEs
def rule_odes(m, t):
exprs = dict()
exprs['A'] = -m.P['k1'] * m.Z[t, 'A']
exprs['B'] = m.P['k1'] * m.Z[t, 'A'] - m.P['k2'] * m.Z[t, 'B']
exprs['C'] = m.P['k2'] * m.Z[t, 'B']
return exprs
builder.set_odes_rule(rule_odes)
opt_model = builder.create_pyomo_model(0.0, 10.0)
#opt_model.C.pprint()
#=========================================================================
#USER INPUT SECTION - VARIANCE GIVEN
#=========================================================================
# create an instance of a pyomo model template
# the template includes
# - Z variables indexed over time and components names e.g. m.Z[t,'A']
# - P parameters indexed over the parameter names e.g. m.P['k']
feed_times=[2.51, 10.0, 15.0]#set with declared feeding points
builder.add_feed_times(feed_times)#have to add feed times first!
# Load concentration data
#################################################################################
dataDirectory = os.path.abspath(
os.path.join( os.path.dirname( os.path.abspath( inspect.getfile(
inspect.currentframe() ) ) ), 'data_sets'))
filename = os.path.join(dataDirectory,'Ad5_C_data_input_noise2.csv')
C_frame = read_concentration_data_from_csv(filename)
builder.add_concentration_data(C_frame) #has to be added here already to use for initialization as well
pyomo_model = builder.create_pyomo_model(0.0,20.0)
#=========================================================================
#USER INPUT SECTION - FE Factory
#=========================================================================
# call FESimulator
# FESimulator re-constructs the current TemplateBuilder into fe_factory syntax
# there is no need to call PyomoSimulator any more as FESimulator is a child class
sim = FESimulator(pyomo_model)
# defines the discrete points wanted in the concentration profile
sim.apply_discretization('dae.collocation', nfe=40, ncp=3, scheme='LAGRANGE-RADAU')
#New Inputs for discrete feeds
