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Dymoval (Dynamic Model Validation) is a Python package for analyzing datasets and validate models.
It does not matter if your model is a Deep Neural Network, an ODE or something more complex, nor is important if you use Modelica or Simulink or whatever as modeling tool. All you need to do is to feed Dymoval with real-world measurements and model-generated data and you will get a model quality evaluation in r-squared fit, residuals norms and coverage region.
If you are developing your models in a CI/CD environment, then Dymoval can help you in deciding if merging or not the latest model changes. In-fact, Dymoval functions can also be included in development pipelines scripts, so the whole CI/CD process can be fully automatized.
Dymoval finally provides you with some essential functions for dealing with dataset analysis and manipulation.
Although the tool has been thought with engineers in mind, no one prevents you to use it in other application domains.
Datasets analysis and manipulation
Model validation
Dymoval exists on both pip
and conda
, so you can choose between the
following:
pip install dymoval
conda install -c ubaldot dymoval
conda install -c conda-forge dymoval
If you are already familiar with model validation, then the best way to get started with dymoval is to run the tutorial scripts that you can open with
import dymoval as dmv
dmv.open_tutorial()
This create a dymoval_tutorial
folder containing all the files needed to
run the tutorial in your home
folder. All you have to do is to run Jupyter notebook named
dymoval_tutorial.ipynb
. You need an app for opening .ipynb
files.
For more info on what is model validation and what is implemented in dymoval along with the dymoval complete API, you can check the docs.
Dymoval is licensed under BSD 3 license.
FAQs
Dymoval is a Python package for validating models and analyzing datasets.
We found that dymoval demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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