API documentation

otfmi facilitates the analysis of FMUs over time.

Main API

The class FMUPointToFieldFunction wraps the FMU in an openturns.PointToFieldFunction. Its output is a openturns.Field gathering the outputs as function of time.

FMUPointToFieldFunction(path_fmu[, mesh, ...])

Define a PointToFieldFunction from a FMU file.

Its lower-level counterpart is OpenTURNSFMUPointToFieldFunction, closer to PyFMI’s methods but not directly usable with OpenTURNS.

OpenTURNSFMUPointToFieldFunction(path_fmu[, ...])

Define a PointToFieldFunction from a FMU file.

For convenience the FMUFunction is provided for cases in which we absolutely need a openturns.Function instead of a openturns.PointToFieldFunction.

FMUFunction([path_fmu, inputs_fmu, ...])

Define a Function from a FMU file.

Common low-level functions

The submodule otfmi.fmi gathers a set of useful functions, employed by the (higher-level) classes mentionned above.

fmi.load_fmu(path_fmu[, kind])	Load and FMU.
fmi.simulate(model[, initialization_script, ...])	Simulate an FMU.
fmi.parse_kwargs_simulate([value_input, ...])	Parse simulation keyword arguments and feed the simulate method of pyfmi's object.
fmi.apply_initialization_script(model, ...)	Apply an initialization script to a model.
fmi.get_name_variable(model, **kwargs)	Get the list of variable names.
fmi.get_causality_str(model, name)	Get the causality of a variable (input, output, or other).
fmi.get_variability(model)	Get the variability of the variables (constant, discrete, continuous, or other).
fmi.get_fixed_value(model)	Get the values of the variables with 'fixed' variability, ignoring aliases.
fmi.get_start_value(model)	Get the values of the variables with a start value ignoring aliases.
fmi.set_dict_value(model, dict_value)	Set values from a dictionary with variable names as keys.

From OpenTURNS to FMI

OTFMI can also export an OpenTURNS function in a Modelica source model (.mo) or Functional Mock-up Unit (.fmu).

FunctionExporter(function[, start])

Fonction export.