Installation#
The package requires Python 3.12 or newer, and it installs motulator and motulator-multiphase as its dependencies. It supports motulator 0.23. A new release of motulator is supported after it has been tested.
Option 1: Use pip#
Install the package in a virtual environment. On Linux and macOS:
python3 -m venv .venv
source .venv/bin/activate
pip install motulator-bearingless
On Windows:
py -m venv .venv
.venv\Scripts\activate
pip install motulator-bearingless
If PowerShell does not allow running the activation script, allow it with Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser.
The plots need a GUI library for matplotlib. On some Linux systems, it must be installed separately; see the installation of motulator.
Option 2: Clone the Repository#
Clone the repository to run the examples or to develop the package. On Linux and macOS:
git clone https://github.com/Aalto-Electric-Drives/motulator-bearingless
cd motulator-bearingless
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,doc]"
On Windows, create and activate the virtual environment as in Option 1. The optional dependencies are installed with the following extras:
Extra |
Purpose |
|---|---|
|
Tests, linting, and type checking |
|
Building this documentation |
|
Generating the finite-element dataset and training the networks, see Finite-Element Data |
The trained networks are evaluated with NumPy, so that PyTorch is needed only in the training. The examples with the gradient networks are run in the clone, since they load the trained networks and the dataset from examples/. The scripts downloaded from the example pages do not include these data files. Run an example, e.g.:
python examples/plot_3kw_bsyrm_dfc.py
The tests are run with pytest, and the documentation is built with the command:
sphinx-build -b html docs/source docs/build/html