feat: migrate factory functions to libNeuroML

pyneuroml/utils/CellBuilder.py

@@ -32,7 +32,7 @@
     ChannelDensityNonUniformNernst,
     ChannelDensityNonUniformGHK,
 )
-from . import component_factory
+from neuroml.utils import component_factory
 
 neuro_lex_ids = {
     "axon": "GO:0030424",

pyneuroml/utils/__init__.py

@@ -7,105 +7,13 @@
 Author: Ankur Sinha <sanjay DOT ankur AT gmail DOT com>
 """
 
-from typing import Any, Union
 import neuroml
 import logging
 
 
 logger = logging.getLogger(__name__)
 
 
-def component_factory(component_type: Union[str, type], validate: bool = True, **kwargs: Any) -> Any:
-    """Factory function to create a NeuroML Component object.
-
-    Users can provide the name of the component as a string or the class
-    variable, along with its named constructor arguments, and this function
-    will create a new object of the Component and return it.
-
-    Users can use the `add()` helper function to further modify components
-
-    This factory runs two checks while creating the component object:
-
-    - that all arguments given do belong to the ComponentType (useful for
-      caching typos)
-    - that the created component is valid NeuroML
-
-    It is therefore less error prone than creating Components directly using
-    the ComponentType constructors.
-
-    It may be useful to disable validation when starting a model. The `validate`
-    parameter can be set to False for this.
-
-    :param component_type: component type to create component from:
-        this can either be the name of the component as a string, e.g.
-        "NeuroMLDocument", or it can be the class type itself: NeuroMLDocument.
-        Note that when providing the class type, one will need to import it,
-        e.g.: `import NeuroMLDocument`, to ensure that it is defined, whereas
-        this will not be required when using the string.
-    :type component_type: str/type
-    :param validate: toggle validation (default: True)
-    :type validate: bool
-    :param **kwargs: named arguments to be passed to ComponentType constructor
-    :type **kwargs: named arguments
-    :returns: new Component (object) of provided ComponentType
-    :rtype: object
-    :raises ValueError: if validation/checks fail
-
-    """
-    if isinstance(component_type, str):
-        comp_type_class = getattr(neuroml.nml.nml, component_type)
-    else:
-        comp_type_class = getattr(neuroml.nml.nml, component_type.__name__)
-
-    comp = comp_type_class(**kwargs)
-    check_component_type_arg_list(comp, **kwargs)
-    if validate:
-        comp.validate()
-    return comp
-
-
-def check_component_type_arg_list(comp: Any, **kwargs: Any) -> None:
-    """Check that the correct arguments have been passed for creation of a
-    particular Component comp.
-
-    This is required because generally, in Python, if one passes a keyword
-    argument that is not listed in a Class constructor, Python will error.
-    However, in libNeuroML/nml.py, all constructors have a last keyword
-    argument `**kwargs` which means extra keyword arguments that do not match
-    the members are silently accepted and then ignored---because they are not
-    used in the constructor.
-
-    This means that common mistakes like typos will not be caught by Python,
-    and in larger models, one will have to inspect the model in great detail to
-    realise that a mistake has been made while creating a component from a
-    NeuroML ComponentType.
-
-    This function makes this check manually.
-
-    :param comp: component to check
-    :type comp: Any
-    :param **kwargs: arg list passed for creation of component
-    :type **kwargs: Any
-    :returns: None
-    :rtype: None
-    :raises ValueError: if given argument list does not match permitted  member
-
-    """
-    members = comp.get_members()
-    member_names = []
-    for m in members:
-        member_names.append(m.get_name())
-
-    args = list(kwargs.keys())
-
-    for arg in args:
-        if arg not in member_names:
-            err = f"'{arg}' is not a permitted argument for ComponentType '{comp.__class__.__name__}'\n"
-            logger.error(err)
-            comp.info()
-            raise ValueError(err)
-
-
 def extract_position_info(nml_model, verbose):
 
     cell_id_vs_cell = {}