A curated list of Functional Mock-up Interface (FMI) libraries, tools and resources.
FMI.jl is a free-to-use software library for the Julia programming language which integrates FMI (fmi-standard.org): load or create, parameterize, differentiate and simulate FMUs seamlessly inside the Julia programming language!
FMIFlux.jl is a free-to-use software library for the Julia programming language, which offers the ability to place FMUs (fmi-standard.org) everywhere inside of your ML topologies and still keep the resulting model trainable with a standard (or custom) FluxML training process.
Tool that allows Functional Mock-up Units (FMUs) to be accessed through language independent RPC calls by wrapping the original FMU into a new one with network capabilities.
FMI-compliant Model Estimation in Python
RaPId (a recursive acronym for "Rapid Parameter Identification") utilizes different optimization and simulation technologies to provide a framework for model validation and calibration of any kind of dynamical systems, but specifically catered to power systems.
FMI4j is a software package for dealing with Functional Mockup Units (FMUs) on the JVM
Tool to compare curves from one csv files with curves from other csv files using an adjustable tolerance
Benchmarking building automation and control systems
FMIBuild.jl holds dependencies that are required to compile and zip a Functional Mock-Up Unit (FMU) compliant to the FMI-standard (fmi-standard.org). Because this dependencies should not be part of the compiled FMU, they are out-sourced into this package. FMIBuild.jl provides the build-commands for the Julia package FMIExport.jl.
FMU data standard and data export with rich metadata in the FMU context
This is a set of environments that support FMU based deep reinforcement learning (DRL) environment.
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