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This package provides Python libNeuroML, for working with neuronal models specified in NeuroML 2.

For more about libNeuroML see:

Michael Vella, Robert C. Cannon, Sharon Crook, Andrew P. Davison, Gautham Ganapathy, Hugh P. C. Robinson, R. Angus Silver and Padraig Gleeson, libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience Frontiers in Neuroinformatics 2014, doi: 10.3389/fninf.2014.00038

PLEASE CITE THE PAPER ABOVE IF YOU USE libNeuroML!

Documentation is available at http://readthedocs.org/docs/libneuroml/en/latest/

For installation instructions, see http://readthedocs.org/docs/libneuroml/en/latest/install.html

For an overview of all NeuroML related libraries/documentation/publications see https://docs.neuroml.org

A related package, pyNeuroML builds on this and provides functionality, scripts and modules for reading, writing, simulating and analysing NeuroML2/LEMS models.

pyNeuroML builds on: libNeuroML & PyLEMS and wraps functionality from jNeuroML.

Most of the work happens in the development branch. That branch is kept up to date with the development branches for NeuroML 2 and related libraries. See https://docs.neuroml.org/ for an overview of the various NeuroML libraries.

• drop py3.7, add py3,12
• fix loader to check for given path and fall back to relative path
• extend get_segment_groups_from_substring to also include an unbranched filter
• more type hint/doc fixes

• more documentation for writes/loaders

• documentation fixes to writer modules

• update schema, changes for NML 2.3 release

• use natsort to improve sorting of segments/groups when optimising

• add links to schema documentation
• move from legacy setup.py to pyproject.toml build system

• explicitly depend on numpy

• updates to GHA

• enable CI on py3.11
• fix to loaders
• format code with black
• add graph representation for morphology, and methods to calculate distances b/w segments

• add multiple cell builder utility functions
• performance improvements in generic helper functions
• documentation fixes/improvements
• add type annotations to all nml classes to aid users
• add level 1 validation method
• add generic component inspection methods

• update to use schema version 2.3
• drop python 2 support

• include schema documentation in generated nml.py API
• introduce generic methods to add child/children elements to components

• multiple documentation fixes

• Enable Python 3.10 support
• Regenerate nml.py with generateDS using Python 3
• Add generic add method to all NeuroML ComponentType classes that allows users to easily construct their NeuroML documents.
• Improve unit tests
• DEPRECATION notice: append_to_element will be deprecated in future releases, please use the add method instead

• Documentation updates for RTD and other minor fixes.

• Patch release with minor changes under the hood.
• Use PyTest for testing.
• Enable CI on GitHub Actions

• Using Schema for NeuroML v2.1. Better compatibility with Python 3

• Updated to use the final stable Schema for NeuroML v2.0

• Updated to use the final stable Schema for NeuroML v2beta5

• Updated to use the final stable Schema for NeuroML v2beta4
• Tested with Python 3

• Updated to use the Schema for NeuroML v2beta4

• Updated to use the Schema for NeuroML v2beta3
• Ensures numpy & pytables are only required when using non-XML loaders/writers

• Updated to use the Schema for NeuroML v2beta2

• Minor release: Update to latest schema

• Several Bug fixes and small enhamcements
• Support for latest NeuroML schema (see change outline)
• JSON serialization
• MongoDB backend
• HDF5 serialization
• Improved installation process
• All usage examples are now run on the Travis-CI continuous integration server to confirm that that they do not error.
• Schema validation utility
• Improved documentation and documentation new look

©️ Copyright 2023 by the libNeuroML team, see AUTHORS. Modified BSD License, see LICENSE for details.