if int(sys.argv[1]):
with_plots = False
# read 500x2 S matrix
wl_span = np.arange(180, 230, 10)
S_parameters = Lorentzian_parameters()
S_frame = generate_absorbance_data(wl_span, S_parameters)
# components
concentrations = {'A': 1, 'B': 0}
# create template model
builder = TemplateBuilder()
builder.add_mixture_component(concentrations)
builder.add_parameter('k', 0.1)
builder.add_absorption_data(S_frame)
builder.add_measurement_times([i for i in range(0, 50, 10)])
dataDirectory = os.path.abspath(
os.path.join(
os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe()))),
'..', 'data_sets'))
# filename = os.path.join(dataDirectory,'Dij_case52a.txt')
filename = os.path.join(dataDirectory, 'Sij_small.txt')
write_absorption_data_to_txt(filename, S_frame)
# define explicit system of ODEs
def rule_odes(m, t):
exprs = dict()
exprs['A'] = -m.P['k'] * m.Z[t, 'A']
os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe()))),
'..', '..', 'data_sets'))
filename = os.path.join(dataDirectory, 'Slk_case51a.txt')
S_frame = read_absorption_data_from_txt(filename)
# create template model
builder = TemplateBuilder()
builder.add_mixture_component('A', 1)
builder.add_mixture_component('B', 0)
builder.add_mixture_component('C', 0)
builder.add_parameter('k1', 2.0)
builder.add_parameter('k2', 0.2)
# includes absorption data in the template and defines measurement sets
builder.add_absorption_data(S_frame)
builder.add_measurement_times([i * 0.0333 for i in range(300)])
# 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)
# 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']
# - C variables indexed over measurement t_i and components names e.g. m.C[t_i,'A']
# this defines the measurement points t_i and l_j as well
dataDirectory = os.path.abspath(
os.path.join(
os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe()))),
'..', '..', 'data_sets'))
filename = os.path.join(dataDirectory, 'Slk_sawall.txt')
S_frame = read_absorption_data_from_txt(filename)
# create template model
builder = TemplateBuilder()
builder.add_mixture_component({'A': 1, 'B': 0})
builder.add_parameter('k', 0.01)
# includes spectra data in the template and defines measurement sets
builder.add_absorption_data(S_frame)
builder.add_measurement_times([i for i in range(200)])
# define explicit system of ODEs
def rule_odes(m, t):
exprs = dict()
exprs['A'] = -m.P['k'] * m.Z[t, 'A']
exprs['B'] = m.P['k'] * m.Z[t, 'A']
return exprs
builder.set_odes_rule(rule_odes)
# create an instance of a casadi model template
# the template includes
# - Z variables indexed over time and components names e.g. m.Z[t,'A']
# - C variables indexed over measurement t_i and components names e.g. m.C[t_i,'A']
# - P parameters indexed over the parameter names m.P['k']
builder.add_parameter(params)
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']
exprs['D'] = -m.P['k3']*m.Z[t,'D']
exprs['E'] = m.P['k3']*m.Z[t,'D']
return exprs
builder.set_odes_rule(rule_odes)
builder.add_measurement_times([i for i in frange(0., 10., 0.1)])
#Add time points where feed as discrete jump should take place:
#feed_times=[101.035, 303.126]#, 400.
#builder.add_feed_times(feed_times)
model = builder.create_pyomo_model(0, 10)
builder.add_absorption_data(S_frame)
write_absorption_data_to_txt('Sij_multexp1.txt', S_frame)
model = builder.create_pyomo_model(0., 10.)
#=========================================================================
#USER INPUT SECTION - FE Factory
#=========================================================================
(210.0 - m.Y[t, '5']) /
((210.0 - m.Y[t, '5'])**2 + eta**2)**0.5)
exprs['V'] = 7.27609e-05 * step
V = m.X[t, 'V']
# mass balances
for c in m.mixture_components:
exprs[c] = gammas[c][0] * m.Y[t, '0'] + gammas[c][1] * m.Y[
t, '1'] + gammas[c][2] * m.Y[t, '2'] + gammas[c][3] * m.Y[
t, '3'] + gammas[c][4] * m.Y[
t, '4'] - exprs['V'] / V * m.Z[t, c]
if c == 'C':
exprs[c] += 0.02247311828 / (m.X[t, 'V'] * 210) * step
return exprs
builder.set_odes_rule(rule_odes)
builder.add_measurement_times([i for i in frange(0., 600., 2.)])
#Add time points where feed as discrete jump should take place:
feed_times = [101.035, 303.126] #, 400.
builder.add_feed_times(feed_times)
model = builder.create_pyomo_model(0, 600.)
builder.add_absorption_data(S_frame)
write_absorption_data_to_txt('Sij_FEcaseexample5-2.txt', S_frame)
model = builder.create_pyomo_model(0., 600.)
#=========================================================================
#USER INPUT SECTION - FE Factory
#=========================================================================
