raise ValueError
uneliminable = []
#~ uneliminable = ['plant.sigma']
#~ uneliminable = ['plant.sigma', 'der(plant.evaporator.alpha)']
caus_opts = sp.CausalizationOptions()
caus_opts['linear_solver'] = linear_solver
caus_opts['solve_blocks'] = True
if source != "Modelica":
raise ValueError
class_name = "CombinedCycleStartup.Startup6Reference"
file_paths = (os.path.join(get_files_path(), "CombinedCycle.mo"),
os.path.join(get_files_path(), "CombinedCycleStartup.mop"))
init_res = ResultDymolaTextual('ccpp_init.txt')
opts = {'generate_html_diagnostics': True}
model = transfer_model(class_name, file_paths, compiler_options=opts)
model = sp.BLTModel(model, caus_opts)
# Get model variable vectors
model.calculateValuesForDependentParameters()
var_kinds = {
'dx': model.DERIVATIVE,
'x': model.DIFFERENTIATED,
'w': model.REAL_ALGEBRAIC
}
mvar_vectors = {
'dx':
N.array([
var for var in model.getVariables(var_kinds['dx'])
if not var.isAlias()
]),
if source == "strings":
eqs_str = ['$x + y = 2$', '$x = 1$']
varis_str = ['$x$', '$y$']
edg_indices = [(0, 0), (0, 1), (1, 0)]
else:
class_name = "Simple"
file_paths = "simple.mop"
#~ opts = {'eliminate_alias_variables': False, 'generate_html_diagnostics': True, 'index_reduction': False,
#~ 'equation_sorting': False, 'automatic_add_initial_equations': False}
#~ opts = {'eliminate_alias_variables': False, 'generate_html_diagnostics': True, 'inline_functions': 'none'}
opts = {
'eliminate_alias_variables': False,
'generate_html_diagnostics': True
}
model = transfer_model(class_name,
file_paths,
compiler_options=opts)
init_fmu = load_fmu(
compile_fmu(class_name, file_paths, compiler_options=opts))
elif problem == "circuit":
caus_opts['tearing'] = True
caus_opts['tear_vars'] = ['i3']
caus_opts['tear_res'] = [8]
#~ caus_opts['analyze_var'] = 'u2'
start_time = 0.
final_time = 100.
input = lambda t: []
if source == "strings":
eqs_str = [
'$u_0 = \sin(t)$', '$u_1 = R_1 \cdot i_1$',
'$u_2 = R_2 \cdot i_2$', '$u_2 = R_3 \cdot i_3$',
#~ caus_opts['solve_blocks'] = True
#~ caus_opts['inline'] = False
#~ caus_opts['closed_form'] = True
caus_opts['dense_tol'] = 1e10
#~ caus_opts['inline_solved'] = True
#~ sim_res = ResultDymolaTextual(os.path.join(get_files_path(), "vehicle_turn_dymola.txt"))
sim_res = ResultDymolaTextual("opt_asphalt.txt")
start_time = 0.
final_time = sim_res.get_variable_data('time').t[-1]
ncp = 500
ncp = 0
class_name = "Car"
file_paths = "st_wf.mop"
opts = {'generate_html_diagnostics': True, 'state_initial_equations': True}
model = transfer_model(class_name, file_paths, compiler_options=opts)
grad_model = transfer_model("Car", file_paths, compiler_options=opts)
init_fmu = load_fmu(compile_fmu(class_name, file_paths, compiler_options=opts))
# Create input data
# This would have worked if one input was not constant...
#~ columns = [0]
#~ columns += [sim_res.get_column(input_var.getName()) for input_var in model.getVariables(model.REAL_INPUT)]
#~ input = sim_res.get_data_matrix()[:, columns]
input_matrix = sim_res.get_variable_data("time").x.reshape([-1, 1])
for input_var in model.getVariables(model.REAL_INPUT):
input_data = sim_res.get_variable_data(input_var.getName()).x.reshape([-1, 1])
if len(input_data) <= 2:
input_data = np.array(input_matrix.shape[0] * [input_data[-1]]).reshape([-1, 1])
input_matrix = np.hstack([input_matrix, input_data])
start_time = 0.0
final_time = 2.0
input = lambda t: []
ncp = 500
if source == "strings":
eqs_str = ["$x + y = 2$", "$x = 1$"]
varis_str = ["$x$", "$y$"]
edg_indices = [(0, 0), (0, 1), (1, 0)]
else:
class_name = "Simple"
file_paths = "simple.mop"
# ~ opts = {'eliminate_alias_variables': False, 'generate_html_diagnostics': True, 'index_reduction': False,
# ~ 'equation_sorting': False, 'automatic_add_initial_equations': False}
# ~ opts = {'eliminate_alias_variables': False, 'generate_html_diagnostics': True, 'inline_functions': 'none'}
opts = {"eliminate_alias_variables": False, "generate_html_diagnostics": True}
model = transfer_model(class_name, file_paths, compiler_options=opts)
init_fmu = load_fmu(compile_fmu(class_name, file_paths, compiler_options=opts))
elif problem == "circuit":
caus_opts["tearing"] = True
caus_opts["tear_vars"] = ["i3"]
caus_opts["tear_res"] = [8]
# ~ caus_opts['analyze_var'] = 'u2'
start_time = 0.0
final_time = 100.0
input = lambda t: []
if source == "strings":
eqs_str = [
"$u_0 = \sin(t)$",
"$u_1 = R_1 \cdot i_1$",
"$u_2 = R_2 \cdot i_2$",
"$u_2 = R_3 \cdot i_3$",
