A Python library for working with the Low Entropy Model Specification language (LEMS)
Project description
A LEMS (http://lems.github.io/LEMS) simulator written in Python which can be used to run NeuroML2 (http://neuroml.org/neuroml2.php) models
Usage as a LEMS model simulator
pylems [options] LEMS_file
Options
-I/-include path - Adds a directory to the model file include search path
Examples
NeuroML examples (from https://github.com/NeuroML/NeuroML2/tree/development/NeuroML2CoreTypes)
Example 0 – Working
Example 1 – Working
Example 2 – Working
Example 3 – Working
Example 4 – Not working (Unsupported in PyLEMS: KSChannel)
Example 5 – Working
Example 6 – Working
Example 7 – Working
Example 8 – Working
Example 9 – Working
Example 10 – Working
Example 11 – Working
Example 12 – Not working (Unsupported in PyLEMS: Property)
Example 13 – Working
Example 14 – Not working (Unsupported in PyLEMS: Property)
Example 15 – Working
Example 16 – Working (apart from spikeArray)
Example 17 – Working
Example 18 – Working
LEMS elements that do not work
XPath based parameters - PathParameter
Assertions
Tasks TODO
Implement flattening
Decouple events from runnables
Perform dimension-checking on expressions.
Implement LEMS API over lems.model.* (NeuroML API?) - Interface with libNeuroML and Pyramidal to export Neuron MOD files - Export C files (Interface? Steve Marsh’s project?)
Assertions.
XPath implementation.
Implement Runnables from Component types instead of expanded typeless Components (Required for efficient C/C++ code generation, but conflicts with flattening)
Travis integration
pylems is integrated with the the [Travis Continuous Integration service](http://travis-ci.org/).
[](https://travis-ci.org/LEMS/pylems)
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file PyLEMS-0.3.2.tar.gz.
File metadata
- Download URL: PyLEMS-0.3.2.tar.gz
- Upload date:
- Size: 45.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | f96f4c989cf261534c080fb8d343e7a3fef1da62d09e15a58a45018a2fff7412 |
|
| MD5 | 47697f8faedf9721fcbeb5810a84a0b1 |
|
| BLAKE2b-256 | 872dbf8b1bd9ed21af4df0bca66733a7d73c86048730f747756b667fdf7ad4d1 |
](https://travis-ci.org/LEMS/pylems){kind=link}