Validating NeuroML Models

Validate NeuroML 2 files before using them.

It is good practice to validate NeuroML 2 files to check them for correctness before using them.

Models described in NeuroML must adhere to the NeuroML specification. This allows all NeuroML models to be checked for correctness: validation. There are a number of ways of validating NeuroML model files.

Using the command line tools

Both pynml (provided by pyNeuroML) and jnml (provided by jNeuroML) can validate individual NeuroML files:

Usage:

# For NeuroML 2
jnml -validate <NML file(s)>
pynml <NML file(s)> -validate

# For NeuroML 1 (deprecated)
jnml -validatev1 <NML file>
pynml <NML file(s)> -validatev1

Using the Python API

The pyNeuroML Python API provides a number of methods to validate NeuroML 2 files. The first is the aptly named validate_neuroml2 function:

from pyneuroml.pynml import validate_neuroml2

...

validate_neuroml2(nml_filename)

Similarly, the validate_neuroml1 function can be used to validate NeuroML v1 files.

If you are loading NeuroML files into your Python script, the read_neuroml2_file function also includes validation:

from pyneuroml.pynml import read_neuroml2_file


....


read_neuroml2_file(nml_filename, include_includes=True, check_validity_pre_include=True)

This will read (load) the provided NeuroML 2 file and all the files that are recursively included by it, and validate them all while it loads them.