NestML is a domain specific language that supports the specification of neuron models in a precise and concise syntax, based on the syntax of Python. Model equations can either be given as a simple string of mathematical notation or as an algorithm written in the built-in procedural language. The equations are analyzed by NESTML to compute an exact solution if possible or use an appropriate numeric solver otherwise.
models - Example neuron models in NESTML format.
pynestml - The source code of NESTML.
tests - A collection of tests for testing of the toolchains behavior.
In order to execute the language tool-chain, Python in version 2 or 3 is required. A setup file is provided and can be installed by
python2 setup.py install --user
For Python in version 3, respectively:
python3 setup.py install --user
Correct installation can be tested by
python2 setup.py test
\# respectively python3 setup.py test
In order to ensure correct installation and resolving of dependencies, Python's package manager pip, the distribution tool setuptools as well as the python-dev package are required and should be installed in advance. The setup file additionally installs the following components:
In the case that no 'enum' package is found, additionally, enum34 has to be updated by
pip install --upgrade pip enum34
All requirements are stored in the requirements.txt and can be installed in one step by pip
pip install -r requirements.txt
After the installation, the toolchain can be executed by the following command.
python PyNestML.py -ARGUMENTS
where arguments are:
| Command | Description |
|---|---|
| -h or --help | Print help message. |
| -path | Path to the source file or directory containing the model. |
| -target | (Optional) Path to target directory where models will be generated to. Default is /target . |
| -dry | (Optional) Executes the analysis of the model without generating target code. Default is OFF. |
| -logging_level | (Optional) Sets the logging level, i.e., which level of messages should be printed. Default is ERROR, available are [INFO, WARNING, ERROR, NO] |
| -module_name | (Optional) Sets the name of the module which shall be generated. Default is the name of the directory containing the models. |
| -store_log | (Optional) Stores a log.txt containing all messages in JSON notation. Default is OFF. |
| -dev | (Optional) Executes the toolchain in the development mode where errors in models are ignored. Default is OFF. |
Generated artifacts are copied to the selected target directory (default is /target). In order to install the models into NEST, the following commands have to be executed:
cmake -Dwith-nest=<nest_install_dir>/bin/nest-config .
make all
make install
where nest_install_dir points to the installation directory of NEST (e.g. work/nest-install). Subsequently, PyNEST can be used to set up and execute a simulation.
For an in-depth introduction to the underlying modeling language NestML, we refer to the following introduction. For those interested in the implementation of PyNestML or the general structure of a DSL-processing toolchain, a documentation of all implemented components is provided.