Cells#

This documentation is auto-generated from the NeuroML schema.

AdExIaFCell#

class neuroml.nml.nml.AdExIaFCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, C: a Nml2Quantity_capacitance (required) = None, g_l: a Nml2Quantity_conductance (required) = None, EL: a Nml2Quantity_voltage (required) = None, reset: a Nml2Quantity_voltage (required) = None, VT: a Nml2Quantity_voltage (required) = None, thresh: a Nml2Quantity_voltage (required) = None, del_t: a Nml2Quantity_voltage (required) = None, tauw: a Nml2Quantity_time (required) = None, refract: a Nml2Quantity_time (required) = None, a: a Nml2Quantity_conductance (required) = None, b: a Nml2Quantity_current (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseCellMembPotCap

AdExIaFCell – Model based on Brette R and Gerstner W ( 2005 ) Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity. J Neurophysiol 94:3637-3642

Parameters:

gL (conductance) – Leak conductance
EL (voltage) – Leak reversal potential
VT (voltage) – Spike threshold
thresh (voltage) – Spike detection threshold
reset (voltage) – Reset potential
delT (voltage) – Slope factor
tauw (time) – Adaptation time constant
refract (time) – Refractory period
a (conductance) – Sub-threshold adaptation variable
b (current) – Spike-triggered adaptation variable
C (capacitance) – Total capacitance of the cell membrane

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Generic function to allow easy addition of a new member to a NeuroML object. Without arguments, when obj=None, it simply calls the info() method to provide the list of valid member types for the NeuroML class.

Please use the info() method directly for more information on the current contents of this component object.

When obj is given a string name of a NeuroML class (“NeuroMLDocument”), or the class itself (neuroml.NeuroMLDocument), a new object will be created of this type and added as a member to the calling (parent) component type object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

This is useful to quickly check what members can go into a particular NeuroML class (which will match the Schema definitions). It lists these members and notes whether they are “single” type elements (Child elements) or “List” elements (Children elements). It will also note whether a member is optional or required.

To get a list of possible parents, use the parentinfo() method.

By default, this will only show the members, and not their contents. To see contents that have been set, use show_contents=True. This will not show empty/unset contents. To see all contents, set show_contents=all.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

It is similar to the info() method. However, where in the info() method, it is possible to find the contents of members for a component (object) rather easily, it is not so easily possible to get all the objects that may refer to another object.

So, this will provide information on possible parents. It will not provide information on whether the components (objects) of the particular parent have already been instantiated and what their values are. The user should be able to gather this information easily by reading the sources.

Please also note that various component types in NeuroML take ids of components as parameters. For example, an ExplicitInput will take the id of a cell as its target, and the id of a PulseGenerator as input. However, these are string fields, and the cell/pulse generator classes do not currently know that their ids can be used in ExplicitInput. This information does not live in the XSD schema, and so cannot be obtained here either.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

BaseCell#

class neuroml.nml.nml.BaseCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: Standalone

BaseCell – Base type of any cell ( e. g. point neuron like izhikevich2007Cell , or a morphologically detailed Cell with segment s ) which can be used in a population

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

BaseCellMembPotCap#

class neuroml.nml.nml.BaseCellMembPotCap(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, C: a Nml2Quantity_capacitance (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

BaseCellMembPotCap – Any cell with a membrane potential v with voltage units and a membrane capacitance C. Also defines exposed value iSyn for current due to external synapses and iMemb for total transmembrane current ( usually channel currents plus iSyn )

Parameters:: C (capacitance) – Total capacitance of the cell membrane

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

BiophysicalProperties#

class neuroml.nml.nml.BiophysicalProperties(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, membrane_properties: a MembraneProperties (required) = None, intracellular_properties: a IntracellularProperties (optional) = None, extracellular_properties: a ExtracellularProperties (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Standalone

BiophysicalProperties – The biophysical properties of the cell , including the membraneProperties and the intracellularProperties

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

BiophysicalProperties2CaPools#

class neuroml.nml.nml.BiophysicalProperties2CaPools(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, membrane_properties2_ca_pools: a MembraneProperties2CaPools (required) = None, intracellular_properties2_ca_pools: a IntracellularProperties2CaPools (optional) = None, extracellular_properties: a ExtracellularProperties (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Standalone

BiophysicalProperties2CaPools – The biophysical properties of the cell , including the membraneProperties2CaPools and the intracellularProperties2CaPools for a cell with two Ca pools

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Cell#

class neuroml.nml.nml.Cell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, morphology_attr: a NmlId (optional) = None, biophysical_properties_attr: a NmlId (optional) = None, morphology: a Morphology (optional) = None, biophysical_properties: a BiophysicalProperties (optional) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

Cell – Cell with segment s specified in a morphology element along with details on its biophysicalProperties . NOTE: this can only be correctly simulated using jLEMS when there is a single segment in the cell, and v of this cell represents the membrane potential in that isopotential segment.

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

add_channel_density(nml_cell_doc, cd_id, ion_channel, cond_density, erev='0.0 mV', group_id='all', ion='non_specific', ion_chan_def_file='')#

Add channel density.

Parameters:

nml_cell_doc (NeuroMLDocument) – cell NeuroML document to which channel density is to be added
cd_id (str) – id for channel density
ion_channel (str) – name of ion channel
cond_density (str) – value of conductance density with units
erev (str) – value of reversal potential with units
group_id (str) – segment groups to add to
ion (str) – name of ion
ion_chan_def_file (str) – path to NeuroML2 file defining the ion channel, if empty, it assumes the channel is defined in the same file

Returns:

added channel density

Return type:

ChannelDensity

add_channel_density_v(channel_density_type, nml_cell_doc, ion_chan_def_file='', **kwargs)#

Generic function to add channel density components to a Cell.

Parameters:

channel_density_type (str or class) – name or class of channel density type to add. See https://docs.neuroml.org/Userdocs/Schemas/Cells.html for the complete list.
nml_cell_doc (NeuroMLDocument) – cell NeuroML document to which channel density is to be added
ion_chan_def_file (str) – path to NeuroML2 file defining the ion channel, if empty, it assumes the channel is defined in the same file
kwargs (Any) – named arguments for required channel density type

Returns:

added channel density

add_intracellular_property(property_name, **kwargs)#

Generic function to add an intracellular property to the cell.

For a full list of membrane properties, see: https://docs.neuroml.org/Userdocs/Schemas/Cells.html?#intracellularproperties

Parameters:

property_name (str) – name of intracellular property to add
kwargs (Any) – named arguments for intracellular property to be added

Returns:

added property

add_membrane_property(property_name, **kwargs)#

Generic function to add a membrane property to the cell.

For a full list of membrane properties, see: https://docs.neuroml.org/Userdocs/Schemas/Cells.html?#membraneproperties

Please also see specific functions in this module, which are designed to be easier to use than this generic function.

Parameters:

property_name (str or class) – name or class of membrane property to add
kwargs (Any) – named arguments for membrane property to be added

Returns:

added property

add_segment(prox, dist, seg_id=None, name=None, parent=None, fraction_along=1.0, group_id=None, use_convention=True, seg_type=None, reorder_segment_groups=True, optimise_segment_groups=True)#

Add a segment to the cell, to the provided segment group, creating it if required.

Parameters:

prox (list with 4 float entries: [x, y, z, diameter]) – proximal segment information
dist (list with 4 float entries: [x, y, z, diameter]) – dist segment information
seg_id (str) – explicit ID to set for segment When not provided, the function will automatically add an ID based on the number of segments already included in the cell. It is best to either always set an explicit ID or let the function set it automatically, but not to mix the two. A ValueError is raised if a segment with the provided ID already exists
name (str) – name of segment If a name is given, it is used. If no name is given, but a segment group is provided, the segment is named: “Seg<number>_<group name>” where <number> is the number of the segment in the segment group. (to be read as “segment <number> in <group>”; the group name should indicate the type here) If no name is given, and no segment group is provided, the segment is simply named: “Seg<segment id>”.
parent (Segment) – parent segment object
fraction_along (float) – where the new segment is connected to the parent (0: distal point, 1: proximal point)
group_id (str) –
id of segment group to add the segment to If a segment group with this id does not exist, a new segment group will be created.

The suggested convention is: axon_, soma_, dend_ for axonal, somatic, and dendritic segment groups respectively.

Note that a newly created segment group will not be marked as an unbranched segment group. If you wish to add a segment to an unbranched segment group, please create one using add_unbranched_segment_group and then add segments to it.
use_convention (bool) – whether the segment or its group should be added to the global segment groups. The seg_type notes what global group this segment or its segment group should also be added to.
reorder_segment_groups (bool) –
whether the groups should be reordered to put the default segment groups last after the segment has been added. This is required for a valid NeuroML file because segment groups included in the default groups should be declared before they are used in the default groups. When adding lots of segments, one may want to only reorder at the end of the process instead of after each segment is added.

This is only relevant if use_convention=True.
optimise_segment_groups (bool) – toggle whether segment groups should be optimised after operation

Seg_type:

type of segment (“axon”, “dendrite”, “soma”) If use_convention is True, and a group_id is provided, the segment group will also be added to the default segment groups if it has not been previously added. If group_id is None, the segment will be added to the default groups instead.

If use_convention is False, this is unused.

Returns:

the created segment

Return type:

Segment

Raises:

ValueError – if seg_id is provided and a segment with this ID already exists

add_segment_group(group_id, neuro_lex_id=None, notes=None)#

Add a new general segment group.

The segments included in this group do not need to be contiguous. This segment group will not be automatically marked as a section using the required NeuroLex ID.

If a segment group with provided ID already exists, it will not be overwritten.

Parameters:

group_id (str) – ID of segment group
neuro_lex_id (str) – NeuroLex ID to use for segment group
notes (str) – Notes text to add

Returns:

new segment group

Return type:

SegmentGroup

add_unbranched_segment_group(group_id, notes=None)#

Add a new unbranched segment group.

This is similar to the add_segment_group method, but this segment group will be used to store contiguous segments, which form an unbranched section of a cell. It adds the NeuroLex ID for a neuronal branch to the segment group.

Parameters:

group_id (str) – ID of segment group
notes (str) – notes to add

Returns:

new segment group

Return type:

SegmentGroup

add_unbranched_segments(points, parent=None, fraction_along=1.0, group_id=None, use_convention=True, seg_type=None, reorder_segment_groups=True, optimise_segment_groups=True)#

Add an unbranched list of segments to the cell.

The list of points will include the first proximal point where this should be joined to the cell, followed by a list of distal points:

|-----|-----|-----|------|.....---|
p1    d1    d2    d3     d4       d N-1

So, a list of N points will create a list of N-1 segments

The list of points will be of the form:

[[x1, y1, z1, d1], [x2, y2, z2, d2] ...]

Please ensure that the first point, p1, is correctly set to ensure that this segment list is correctly connected to the rest of the cell.

Parameters:

points (list of [x, y, z, d] points) – 3D points to create the segments
parent (SegmentParent) – parent segment where first segment of list is to be attached
fraction_along (float) – where the new segment list is connected to the parent (0: distal point, 1: proximal point) Note that the second and following segments will all be added at the distal point of the previous segment
group_id (SegmentGroup) – segment group to add the segment to if a segment group does not already exist, it will be created
use_convention (bool) – whether helper segment groups should be created using the default convention See the documentation of the add_segment method for more information on the convention
seg_type (str) – type of segments (“axon”, “soma”, “dendrite”)
reorder_segment_groups (bool) –
whether the groups should be reordered to put the default segment groups last after the segment has been added. This is required for a valid NeuroML file because segment groups included in the default groups should be declared before they are used in the default groups. When adding lots of segments, one may want to only reorder at the end of the process instead of after each segment is added.

This is only relevant if use_convention=True.
optimise_segment_groups (bool) – toggle whether segment groups should be optimised after operation

Returns:

the segment group containing this new list of segments

Return type:

SegmentGroup

biophysinfo()#: Get information on the biophysical properties of the cell. :returns: None

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

create_unbranched_segment_group_branches(root_segment_id: int, use_convention: bool = True, reorder_segment_groups=True, optimise_segment_groups=True)#

Organise the segments of the cell into new segment groups that each form a single contiguous unbranched cell branch.

Note that the first segment (root segment) of a branch must have a proximal point that connects it to the rest of the neuronal morphology. If, when constructing these branches, a root segment is found that does not include a proximal point, one will be added using the get_actual_proximal method.

No other changes will be made to any segments, or to any pre-existing segment groups.

Parameters:

root_segment_id (int) – id of segment considered the root of the tree, generally the first soma segment
use_convention (bool) – toggle using NeuroML convention for segment groups
reorder_segment_groups (bool) –
whether the groups should be reordered to put the default segment groups last after the segment has been added. This is required for a valid NeuroML file because segment groups included in the default groups should be declared before they are used in the default groups. When adding lots of segments, one may want to only reorder at the end of the process instead of after each segment is added.

This is only relevant if use_convention=True.
optimise_segment_groups (bool) – toggle whether segment groups should be optimised after operation

get_actual_proximal(segment_id: str)#

Get the proximal point of a segment.

If the proximal for the segment is set to None, calculate the proximal on the parent using fraction_along and return it.

Parameters:: segment_id – ID of segment
Returns:: proximal point

get_all_distances_from_segment(seg_id=0)#

Get distances of all segments from the segment with id seg_id.

Useful to get distances of segments from the soma.

Uses networkx.single_source_dijkstra on the cell graph, without a target.

Parameters:: seg_id (int) – id of segment to get distances from
Returns:: pair of dictionaries for distance, path The return value is a tuple of two dictionaries keyed by target nodes. The first dictionary stores distance to each target node. The second stores the path to each target node.

get_all_segments_in_group(segment_group: str | SegmentGroup, assume_all_means_all: bool = True) → List[int]#

Get all the segments in a segment group of the cell.

Parameters:

segment_group – segment group id (str) or object (SegmentGroup) to get all segments of
assume_all_means_all – return all segments if the “all” segment group wasn’t explicitly defined

Returns:

list of segment ids

Return type:

list[int]

Raises:

Exception – if no segment group is found in the cell.

get_branching_points()#

Get segments where the cell morphology branches.

That is, the out-degree of the segment is > 1

Returns:: list of segment ids

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

get_distance(dest, source=0)#

Get path length between between two segments on a cell.

Uses networkx.dijkstra_path_length to compute the shortest path between source and dest

Parameters:

from (int) – id of segment to get distance from
to (int) – id of segment to get distance to

Returns:

float

get_extremeties()#

Get segments that are at the ends/tips of the neuronal morphology, with their distances from the soma.

Returns:: dict of segment ids and their distances from cell root as values

get_graph()#

Get a networkx DiGraph of the morphology of the cell with distances between the proximal point of a parent and the point where a child connects to it as the weights of the edges of the graph.

Please see https://networkx.org/documentation/stable/reference for information on networkx routines that can be used on this graph.

This method also stores the graph in the self.cell_graph attribute for future use.

Returns:: networkx.Graph

get_morphology_root()#

Return the root of the complete cell morphology.

This is usually the first segment of the soma, and there should only be one such segment.

Returns:: id of the root segment

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

get_ordered_segments_in_groups(group_list: List[str], check_parentage: bool = False, include_cumulative_lengths: bool = False, include_path_lengths: bool = False, path_length_metric: str = 'Path Length from root') → Any#

Get ordered list of segments in specified groups, with additional information.

Note that this method orders segments by id, so the assumption is that all segment with id N + m will be a descendent of segment with id N in the segment group.

Parameters:

group_list (str or list(str)) – a group id or list of group ids to get segments from
check_parentage (bool) – verify parentage
include_cumulative_lengths (bool) – also include cummulative length of each segment from root
include_path_lengths (bool) – also include path lengths from segment group’s root segment to proximal and distal points of each segment
path_length_metric (str) – metric to use for path length (“Path Length from root” is currently the only supported option, and the default)

Returns:

depending on provided arguments:

if no additional options are provided, returns a dictionary with segment group ids as keys, and lists of ordered segments in those segment groups as values (ord_segs)
if only include_path_lengths is set, returns a tuple: [ord_segs, path_lengths_to_proximal , path_lengths_to_distal]
if only include_cumulative_lengths is set, returns a tuple: [ord_segs, cumulative_lengths]
if both include_path_lengths and include_cumulative_lengths are set, returns a tuple: [ord_segs, cumulative_lengths, path_lengths_to_proximal , path_lengths_to_distal]

Raises:

Exception if check_parentage is True and parentage cannot be verified

get_segment(segment_id: int) → Segment#

Get segment object by its id

Parameters:: segment_id – ID of segment
Returns:: segment
Raises:: ValueError – if the segment is not found in the cell

get_segment_adjacency_list()#

Get the adjacency list of all segments in the cell morphology. Returns a dict where each key is a parent segment, and the value is the list of its children segments.

Segment without children (leaf segments) are not included as parents in the adjacency list.

This method also stores the computed adjacency list in self.adjacency_list for future use by other methods.

self.adjacency_list is populated each time this method is run, to ensure that users can regenerate it after making modifications to the cell morphology. If the morphology has not changed, one only needs to populate it once and then re-use it as required.

Returns:: dict with parent segment ids as keys and ids of their children as values
Return type:: dict[int, list[int]]

get_segment_group(sg_id: str) → SegmentGroup#

Return the SegmentGroup object for the specified segment group id.

Parameters:: sg_id (str) – id of segment group to find
Returns:: SegmentGroup object of specified ID
Raises:: ValueError – if segment group is not found in cell

get_segment_group_info(group_id)#

Get information about a segment group

Parameters:: group_id (int) – id of segment group
Returns:: None

get_segment_groups_by_substring(substring: str, unbranched: bool = False) → Dict[str, SegmentGroup]#

Get a dictionary of segment group IDs and the segment groups matching the specified substring

Parameters:

substring (str) – substring to match, an empty string “” matches all groups
unbranced – toggle selecting unbranched segment groups

Returns:

dictionary with segment group ID as key, and segment group as value

Raises:

ValueError – if no matching segment groups are found in cell

get_segment_ids_vs_segments() → Dict[str, Segment]#

Get a dictionary of segment IDs and the segments in the cell.

Returns:: dictionary with segment ID as key, and segment as value

get_segment_length(segment_id: str) → float#

Get the length of the segment.

Parameters:: segment_id – ID of segment
Returns:: length of segment

get_segment_location_info(seg_id)#

Get location information about a particular segment.

Parameters:

seg_id (int) – id of segment to get information for

Returns:

a dictionary with various metrics about the segment

length of segment
distance from cell root
distance from nearest branching point
name of unbranched segment group segment belongs to (if any)
id of root segment of the unbranched segment group
distance from the segment group root segment

get_segment_surface_area(segment_id: str) → float#

Get the surface area of the segment.

Parameters:: segment_id – ID of the segment
Returns:: surface area of segment

get_segment_volume(segment_id: str) → float#

Get volume of segment

Parameters:: segment_id – ID of the segment
Returns:: volume of the segment

get_segments_at_distance(distance, src_seg=0)#

Get all segments at distance from the provided src_seg.

For each segment, it returns the fraction along the segment that the provided distance is at. For example, if segment N is 500 units long, and the distance cut-off is at 200, the fraction along is: 200/500.

Parameters:

src_seg (int) – id of segment to get distances from
distance (float) – distance to get segments at

Returns:

dict with segment ids as keys, and fraction along at which the cut off is as values

get_segments_by_substring(substring: str) → Dict[str, Segment]#

Get a dictionary of segment IDs and the segment matching the specified substring

Parameters:: substring (str) – substring to match
Returns:: dictionary with segment ID as key, and segment as value
Raises:: Exception – if no segments are found

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

morphinfo(segment_detail=False)#

Show info on morphology of the cell. By default, since cells can have large numbers of segments and segment groups, it only provides metrics on the total numbers. To see details, pass segment_detail=True.

Cell2CaPools#

class neuroml.nml.nml.Cell2CaPools(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, morphology_attr: a NmlId (optional) = None, biophysical_properties_attr: a NmlId (optional) = None, morphology: a Morphology (optional) = None, biophysical_properties: a BiophysicalProperties (optional) = None, biophysical_properties2_ca_pools: a BiophysicalProperties2CaPools (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Cell

Cell2CaPools – Variant of cell with two independent Ca2+ pools. Cell with segment s specified in a morphology element along with details on its biophysicalProperties . NOTE: this can only be correctly simulated using jLEMS when there is a single segment in the cell, and v of this cell represents the membrane potential in that isopotential segment.

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

add_channel_density(nml_cell_doc, cd_id, ion_channel, cond_density, erev='0.0 mV', group_id='all', ion='non_specific', ion_chan_def_file='')#

Add channel density.

Parameters:

nml_cell_doc (NeuroMLDocument) – cell NeuroML document to which channel density is to be added
cd_id (str) – id for channel density
ion_channel (str) – name of ion channel
cond_density (str) – value of conductance density with units
erev (str) – value of reversal potential with units
group_id (str) – segment groups to add to
ion (str) – name of ion
ion_chan_def_file (str) – path to NeuroML2 file defining the ion channel, if empty, it assumes the channel is defined in the same file

Returns:

added channel density

Return type:

ChannelDensity

add_channel_density_v(channel_density_type, nml_cell_doc, ion_chan_def_file='', **kwargs)#

Generic function to add channel density components to a Cell.

Parameters:

channel_density_type (str or class) – name or class of channel density type to add. See https://docs.neuroml.org/Userdocs/Schemas/Cells.html for the complete list.
nml_cell_doc (NeuroMLDocument) – cell NeuroML document to which channel density is to be added
ion_chan_def_file (str) – path to NeuroML2 file defining the ion channel, if empty, it assumes the channel is defined in the same file
kwargs (Any) – named arguments for required channel density type

Returns:

added channel density

add_intracellular_property(property_name, **kwargs)#

Generic function to add an intracellular property to the cell.

For a full list of membrane properties, see: https://docs.neuroml.org/Userdocs/Schemas/Cells.html?#intracellularproperties

Parameters:

property_name (str) – name of intracellular property to add
kwargs (Any) – named arguments for intracellular property to be added

Returns:

added property

add_membrane_property(property_name, **kwargs)#

Generic function to add a membrane property to the cell.

For a full list of membrane properties, see: https://docs.neuroml.org/Userdocs/Schemas/Cells.html?#membraneproperties

Please also see specific functions in this module, which are designed to be easier to use than this generic function.

Parameters:

property_name (str or class) – name or class of membrane property to add
kwargs (Any) – named arguments for membrane property to be added

Returns:

added property

Add a segment to the cell, to the provided segment group, creating it if required.

Parameters:

prox (list with 4 float entries: [x, y, z, diameter]) – proximal segment information
dist (list with 4 float entries: [x, y, z, diameter]) – dist segment information
seg_id (str) – explicit ID to set for segment When not provided, the function will automatically add an ID based on the number of segments already included in the cell. It is best to either always set an explicit ID or let the function set it automatically, but not to mix the two. A ValueError is raised if a segment with the provided ID already exists
name (str) – name of segment If a name is given, it is used. If no name is given, but a segment group is provided, the segment is named: “Seg<number>_<group name>” where <number> is the number of the segment in the segment group. (to be read as “segment <number> in <group>”; the group name should indicate the type here) If no name is given, and no segment group is provided, the segment is simply named: “Seg<segment id>”.
parent (Segment) – parent segment object
fraction_along (float) – where the new segment is connected to the parent (0: distal point, 1: proximal point)
group_id (str) –
id of segment group to add the segment to If a segment group with this id does not exist, a new segment group will be created.

The suggested convention is: axon_, soma_, dend_ for axonal, somatic, and dendritic segment groups respectively.

Note that a newly created segment group will not be marked as an unbranched segment group. If you wish to add a segment to an unbranched segment group, please create one using add_unbranched_segment_group and then add segments to it.
use_convention (bool) – whether the segment or its group should be added to the global segment groups. The seg_type notes what global group this segment or its segment group should also be added to.
reorder_segment_groups (bool) –
whether the groups should be reordered to put the default segment groups last after the segment has been added. This is required for a valid NeuroML file because segment groups included in the default groups should be declared before they are used in the default groups. When adding lots of segments, one may want to only reorder at the end of the process instead of after each segment is added.

This is only relevant if use_convention=True.
optimise_segment_groups (bool) – toggle whether segment groups should be optimised after operation

Seg_type:

If use_convention is False, this is unused.

Returns:

the created segment

Return type:

Segment

Raises:

ValueError – if seg_id is provided and a segment with this ID already exists

add_segment_group(group_id, neuro_lex_id=None, notes=None)#

Add a new general segment group.

The segments included in this group do not need to be contiguous. This segment group will not be automatically marked as a section using the required NeuroLex ID.

If a segment group with provided ID already exists, it will not be overwritten.

Parameters:

group_id (str) – ID of segment group
neuro_lex_id (str) – NeuroLex ID to use for segment group
notes (str) – Notes text to add

Returns:

new segment group

Return type:

SegmentGroup

add_unbranched_segment_group(group_id, notes=None)#

Add a new unbranched segment group.

Parameters:

group_id (str) – ID of segment group
notes (str) – notes to add

Returns:

new segment group

Return type:

SegmentGroup

add_unbranched_segments(points, parent=None, fraction_along=1.0, group_id=None, use_convention=True, seg_type=None, reorder_segment_groups=True, optimise_segment_groups=True)#

Add an unbranched list of segments to the cell.

The list of points will include the first proximal point where this should be joined to the cell, followed by a list of distal points:

|-----|-----|-----|------|.....---|
p1    d1    d2    d3     d4       d N-1

So, a list of N points will create a list of N-1 segments

The list of points will be of the form:

[[x1, y1, z1, d1], [x2, y2, z2, d2] ...]

Please ensure that the first point, p1, is correctly set to ensure that this segment list is correctly connected to the rest of the cell.

Parameters:

points (list of [x, y, z, d] points) – 3D points to create the segments
parent (SegmentParent) – parent segment where first segment of list is to be attached
fraction_along (float) – where the new segment list is connected to the parent (0: distal point, 1: proximal point) Note that the second and following segments will all be added at the distal point of the previous segment
group_id (SegmentGroup) – segment group to add the segment to if a segment group does not already exist, it will be created
use_convention (bool) – whether helper segment groups should be created using the default convention See the documentation of the add_segment method for more information on the convention
seg_type (str) – type of segments (“axon”, “soma”, “dendrite”)
reorder_segment_groups (bool) –
whether the groups should be reordered to put the default segment groups last after the segment has been added. This is required for a valid NeuroML file because segment groups included in the default groups should be declared before they are used in the default groups. When adding lots of segments, one may want to only reorder at the end of the process instead of after each segment is added.

This is only relevant if use_convention=True.
optimise_segment_groups (bool) – toggle whether segment groups should be optimised after operation

Returns:

the segment group containing this new list of segments

Return type:

SegmentGroup

biophysinfo()#: Get information on the biophysical properties of the cell. :returns: None

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

create_unbranched_segment_group_branches(root_segment_id: int, use_convention: bool = True, reorder_segment_groups=True, optimise_segment_groups=True)#

Organise the segments of the cell into new segment groups that each form a single contiguous unbranched cell branch.

No other changes will be made to any segments, or to any pre-existing segment groups.

Parameters:

root_segment_id (int) – id of segment considered the root of the tree, generally the first soma segment
use_convention (bool) – toggle using NeuroML convention for segment groups
reorder_segment_groups (bool) –
whether the groups should be reordered to put the default segment groups last after the segment has been added. This is required for a valid NeuroML file because segment groups included in the default groups should be declared before they are used in the default groups. When adding lots of segments, one may want to only reorder at the end of the process instead of after each segment is added.

This is only relevant if use_convention=True.
optimise_segment_groups (bool) – toggle whether segment groups should be optimised after operation

get_actual_proximal(segment_id: str)#

Get the proximal point of a segment.

If the proximal for the segment is set to None, calculate the proximal on the parent using fraction_along and return it.

Parameters:: segment_id – ID of segment
Returns:: proximal point

get_all_distances_from_segment(seg_id=0)#

Get distances of all segments from the segment with id seg_id.

Useful to get distances of segments from the soma.

Uses networkx.single_source_dijkstra on the cell graph, without a target.

Parameters:: seg_id (int) – id of segment to get distances from
Returns:: pair of dictionaries for distance, path The return value is a tuple of two dictionaries keyed by target nodes. The first dictionary stores distance to each target node. The second stores the path to each target node.

get_all_segments_in_group(segment_group: str | SegmentGroup, assume_all_means_all: bool = True) → List[int]#

Get all the segments in a segment group of the cell.

Parameters:

segment_group – segment group id (str) or object (SegmentGroup) to get all segments of
assume_all_means_all – return all segments if the “all” segment group wasn’t explicitly defined

Returns:

list of segment ids

Return type:

list[int]

Raises:

Exception – if no segment group is found in the cell.

get_branching_points()#

Get segments where the cell morphology branches.

That is, the out-degree of the segment is > 1

Returns:: list of segment ids

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

get_distance(dest, source=0)#

Get path length between between two segments on a cell.

Uses networkx.dijkstra_path_length to compute the shortest path between source and dest

Parameters:

from (int) – id of segment to get distance from
to (int) – id of segment to get distance to

Returns:

float

get_extremeties()#

Get segments that are at the ends/tips of the neuronal morphology, with their distances from the soma.

Returns:: dict of segment ids and their distances from cell root as values

get_graph()#

Get a networkx DiGraph of the morphology of the cell with distances between the proximal point of a parent and the point where a child connects to it as the weights of the edges of the graph.

Please see https://networkx.org/documentation/stable/reference for information on networkx routines that can be used on this graph.

This method also stores the graph in the self.cell_graph attribute for future use.

Returns:: networkx.Graph

get_morphology_root()#

Return the root of the complete cell morphology.

This is usually the first segment of the soma, and there should only be one such segment.

Returns:: id of the root segment

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

Get ordered list of segments in specified groups, with additional information.

Note that this method orders segments by id, so the assumption is that all segment with id N + m will be a descendent of segment with id N in the segment group.

Parameters:

group_list (str or list(str)) – a group id or list of group ids to get segments from
check_parentage (bool) – verify parentage
include_cumulative_lengths (bool) – also include cummulative length of each segment from root
include_path_lengths (bool) – also include path lengths from segment group’s root segment to proximal and distal points of each segment
path_length_metric (str) – metric to use for path length (“Path Length from root” is currently the only supported option, and the default)

Returns:

depending on provided arguments:

if no additional options are provided, returns a dictionary with segment group ids as keys, and lists of ordered segments in those segment groups as values (ord_segs)
if only include_path_lengths is set, returns a tuple: [ord_segs, path_lengths_to_proximal , path_lengths_to_distal]
if only include_cumulative_lengths is set, returns a tuple: [ord_segs, cumulative_lengths]
if both include_path_lengths and include_cumulative_lengths are set, returns a tuple: [ord_segs, cumulative_lengths, path_lengths_to_proximal , path_lengths_to_distal]

Raises:

Exception if check_parentage is True and parentage cannot be verified

get_segment(segment_id: int) → Segment#

Get segment object by its id

Parameters:: segment_id – ID of segment
Returns:: segment
Raises:: ValueError – if the segment is not found in the cell

get_segment_adjacency_list()#

Get the adjacency list of all segments in the cell morphology. Returns a dict where each key is a parent segment, and the value is the list of its children segments.

Segment without children (leaf segments) are not included as parents in the adjacency list.

This method also stores the computed adjacency list in self.adjacency_list for future use by other methods.

Returns:: dict with parent segment ids as keys and ids of their children as values
Return type:: dict[int, list[int]]

get_segment_group(sg_id: str) → SegmentGroup#

Return the SegmentGroup object for the specified segment group id.

Parameters:: sg_id (str) – id of segment group to find
Returns:: SegmentGroup object of specified ID
Raises:: ValueError – if segment group is not found in cell

get_segment_group_info(group_id)#

Get information about a segment group

Parameters:: group_id (int) – id of segment group
Returns:: None

get_segment_groups_by_substring(substring: str, unbranched: bool = False) → Dict[str, SegmentGroup]#

Get a dictionary of segment group IDs and the segment groups matching the specified substring

Parameters:

substring (str) – substring to match, an empty string “” matches all groups
unbranced – toggle selecting unbranched segment groups

Returns:

dictionary with segment group ID as key, and segment group as value

Raises:

ValueError – if no matching segment groups are found in cell

get_segment_ids_vs_segments() → Dict[str, Segment]#

Get a dictionary of segment IDs and the segments in the cell.

Returns:: dictionary with segment ID as key, and segment as value

get_segment_length(segment_id: str) → float#

Get the length of the segment.

Parameters:: segment_id – ID of segment
Returns:: length of segment

get_segment_location_info(seg_id)#

Get location information about a particular segment.

Parameters:

seg_id (int) – id of segment to get information for

Returns:

a dictionary with various metrics about the segment

length of segment
distance from cell root
distance from nearest branching point
name of unbranched segment group segment belongs to (if any)
id of root segment of the unbranched segment group
distance from the segment group root segment

get_segment_surface_area(segment_id: str) → float#

Get the surface area of the segment.

Parameters:: segment_id – ID of the segment
Returns:: surface area of segment

get_segment_volume(segment_id: str) → float#

Get volume of segment

Parameters:: segment_id – ID of the segment
Returns:: volume of the segment

get_segments_at_distance(distance, src_seg=0)#

Get all segments at distance from the provided src_seg.

Parameters:

src_seg (int) – id of segment to get distances from
distance (float) – distance to get segments at

Returns:

dict with segment ids as keys, and fraction along at which the cut off is as values

get_segments_by_substring(substring: str) → Dict[str, Segment]#

Get a dictionary of segment IDs and the segment matching the specified substring

Parameters:: substring (str) – substring to match
Returns:: dictionary with segment ID as key, and segment as value
Raises:: Exception – if no segments are found

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

morphinfo(segment_detail=False)#

CellSet#

class neuroml.nml.nml.CellSet(id: a NmlId (required) = None, select: a string (required) = None, anytypeobjs_=None, gds_collector_=None, **kwargs_)#

Bases: Base

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensity#

class neuroml.nml.nml.ChannelDensity(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, cond_density: a Nml2Quantity_conductanceDensity (optional) = None, erev: a Nml2Quantity_voltage (required) = None, segment_groups: a NmlId (optional) = 'all', segments: a NonNegativeInteger (optional) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelDensity – Specifies a time varying ohmic conductance density, gDensity, which is distributed on an area of the cell ( specified in membraneProperties ) with fixed reversal potential erev producing a current density iDensity

Parameters:

erev (voltage) – The reversal potential of the current produced
condDensity (conductanceDensity)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityGHK#

class neuroml.nml.nml.ChannelDensityGHK(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, permeability: a Nml2Quantity_permeability (required) = None, segment_groups: a NmlId (optional) = 'all', segments: a NonNegativeInteger (optional) = None, ion: a NmlId (required) = None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelDensityGHK – Specifies a time varying conductance density, gDensity, which is distributed on an area of the cell, producing a current density iDensity and whose reversal potential is calculated from the Goldman Hodgkin Katz equation. Hard coded for Ca only! See OpenSourceBrain/ghk-nernst.

Parameters:: permeability (permeability)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityGHK2#

class neuroml.nml.nml.ChannelDensityGHK2(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, cond_density: a Nml2Quantity_conductanceDensity (optional) = None, segment_groups: a NmlId (optional) = 'all', segments: a NonNegativeInteger (optional) = None, ion: a NmlId (required) = None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelDensityGHK2 – Time varying conductance density, gDensity, which is distributed on an area of the cell, producing a current density iDensity. Modified version of Jaffe et al. 1994 ( used also in Lawrence et al. 2006 ). See OpenSourceBrain/ghk-nernst.

Parameters:: condDensity (conductanceDensity)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityNernst#

class neuroml.nml.nml.ChannelDensityNernst(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, cond_density: a Nml2Quantity_conductanceDensity (optional) = None, segment_groups: a NmlId (optional) = 'all', segments: a NonNegativeInteger (optional) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelDensityNernst – Specifies a time varying conductance density, gDensity, which is distributed on an area of the cell, producing a current density iDensity and whose reversal potential is calculated from the Nernst equation. Hard coded for Ca only! See OpenSourceBrain/ghk-nernst.

Parameters:: condDensity (conductanceDensity)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityNernstCa2#

class neuroml.nml.nml.ChannelDensityNernstCa2(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, cond_density: a Nml2Quantity_conductanceDensity (optional) = None, segment_groups: a NmlId (optional) = 'all', segments: a NonNegativeInteger (optional) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: ChannelDensityNernst

ChannelDensityNernstCa2 – This component is similar to the original component type channelDensityNernst but it is changed in order to have a reversal potential that depends on a second independent Ca++ pool ( ca2 ). See OpenSourceBrain/ghk-nernst.

Parameters:: condDensity (conductanceDensity)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityNonUniform#

class neuroml.nml.nml.ChannelDensityNonUniform(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, erev: a Nml2Quantity_voltage (required) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelDensityNonUniform – Specifies a time varying ohmic conductance density, which is distributed on a region of the cell. The conductance density of the channel is not uniform, but is set using the variableParameter . Note, there is no dynamical description of this in LEMS yet, as this type only makes sense for multicompartmental cells. A ComponentType for this needs to be present to enable export of NeuroML 2 multicompartmental cells via LEMS/jNeuroML to NEURON

Parameters:: erev (voltage) – The reversal potential of the current produced

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityNonUniformGHK#

class neuroml.nml.nml.ChannelDensityNonUniformGHK(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelDensityNonUniformGHK – Specifies a time varying conductance density, which is distributed on a region of the cell, and whose current is calculated from the Goldman-Hodgkin-Katz equation. Hard coded for Ca only!. The conductance density of the channel is not uniform, but is set using the variableParameter . Note, there is no dynamical description of this in LEMS yet, as this type only makes sense for multicompartmental cells. A ComponentType for this needs to be present to enable export of NeuroML 2 multicompartmental cells via LEMS/jNeuroML to NEURON

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityNonUniformNernst#

class neuroml.nml.nml.ChannelDensityNonUniformNernst(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelDensityNonUniformNernst – Specifies a time varying conductance density, which is distributed on a region of the cell, and whose reversal potential is calculated from the Nernst equation. Hard coded for Ca only!. The conductance density of the channel is not uniform, but is set using the variableParameter . Note, there is no dynamical description of this in LEMS yet, as this type only makes sense for multicompartmental cells. A ComponentType for this needs to be present to enable export of NeuroML 2 multicompartmental cells via LEMS/jNeuroML to NEURON

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelDensityVShift#

class neuroml.nml.nml.ChannelDensityVShift(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, cond_density: a Nml2Quantity_conductanceDensity (optional) = None, erev: a Nml2Quantity_voltage (required) = None, segment_groups: a NmlId (optional) = 'all', segments: a NonNegativeInteger (optional) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, v_shift: a Nml2Quantity_voltage (required) = None, gds_collector_=None, **kwargs_)#

Bases: ChannelDensity

ChannelDensityVShift – Same as channelDensity , but with a vShift parameter to change voltage activation of gates. The exact usage of vShift in expressions for rates is determined by the individual gates.

Parameters:

vShift (voltage)
erev (voltage) – The reversal potential of the current produced
condDensity (conductanceDensity)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ChannelPopulation#

class neuroml.nml.nml.ChannelPopulation(id: a NmlId (required) = None, ion_channel: a NmlId (required) = None, number: a NonNegativeInteger (required) = None, erev: a Nml2Quantity_voltage (required) = None, segment_groups: a NmlId (optional) = 'all', segments: a NonNegativeInteger (optional) = None, ion: a NmlId (required) = None, variable_parameters: list of VariableParameter(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

ChannelPopulation – Population of a number of ohmic ion channels. These each produce a conductance channelg across a reversal potential erev, giving a total current i. Note that active membrane currents are more frequently specified as a density over an area of the cell using channelDensity

Parameters:

number (none) – The number of channels present. This will be multiplied by the time varying conductance of the individual ion channel ( which extends baseIonChannel ) to produce the total conductance
erev (voltage) – The reversal potential of the current produced

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

DecayingPoolConcentrationModel#

class neuroml.nml.nml.DecayingPoolConcentrationModel(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, ion: a NmlId (required) = None, resting_conc: a Nml2Quantity_concentration (required) = None, decay_constant: a Nml2Quantity_time (required) = None, shell_thickness: a Nml2Quantity_length (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: Standalone

DecayingPoolConcentrationModel – Model of an intracellular buffering mechanism for ion ( currently hard Coded to be calcium, due to requirement for iCa ) which has a baseline level restingConc and tends to this value with time course decayConstant. The ion is assumed to occupy a shell inside the membrane of thickness shellThickness.

Parameters:

restingConc (concentration)
decayConstant (time)
shellThickness (length)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

DistalDetails#

class neuroml.nml.nml.DistalDetails(normalization_end: a double (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

DistalDetails – What to do at the distal point when creating an inhomogeneous parameter

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ExtracellularProperties#

class neuroml.nml.nml.ExtracellularProperties(id: a NmlId (required) = None, species: list of Species(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ExtracellularPropertiesLocal#

class neuroml.nml.nml.ExtracellularPropertiesLocal(id: a NmlId (required) = None, species: list of Species(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

FitzHughNagumo1969Cell#

class neuroml.nml.nml.FitzHughNagumo1969Cell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, a: a Nml2Quantity_none (required) = None, b: a Nml2Quantity_none (required) = None, I: a Nml2Quantity_none (required) = None, phi: a Nml2Quantity_none (required) = None, V0: a Nml2Quantity_none (required) = None, W0: a Nml2Quantity_none (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

FitzHughNagumo1969Cell – The Fitzhugh Nagumo model is a two-dimensional simplification of the Hodgkin-Huxley model of spike generation in squid giant axons. This system was suggested by FitzHugh ( FitzHugh R. [1961]: Impulses and physiological states in theoretical models of nerve membrane. Biophysical J. 1:445-466 ), who called it “ Bonhoeffer-van der Pol model “, and the equivalent circuit by Nagumo et al. ( Nagumo J. , Arimoto S. , and Yoshizawa S. [1962] An active pulse transmission line simulating nerve axon. Proc IRE. 50:2061-2070. 1962 ). This version corresponds to the one described in FitzHugh R. [1969]: Mathematical models of excitation and propagation in nerve. Chapter 1 ( pp. 1-85 in H. P. Schwan, ed. Biological Engineering, McGraw-Hill Book Co. , N. Y. )

Parameters:

a (none)
b (none)
I (none) – plays the role of an external injected current
phi (none)
V0 (none)
W0 (none)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

FitzHughNagumoCell#

class neuroml.nml.nml.FitzHughNagumoCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, I: a Nml2Quantity_none (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

FitzHughNagumoCell – Simple dimensionless model of spiking cell from FitzHugh and Nagumo. Superseded by fitzHughNagumo1969Cell ( See NeuroML/NeuroML2#42 )

Parameters:: I (none)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

FixedFactorConcentrationModel#

class neuroml.nml.nml.FixedFactorConcentrationModel(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, ion: a NmlId (required) = None, resting_conc: a Nml2Quantity_concentration (required) = None, decay_constant: a Nml2Quantity_time (required) = None, rho: a Nml2Quantity_rhoFactor (required) = None, gds_collector_=None, **kwargs_)#

Bases: Standalone

FixedFactorConcentrationModel – Model of buffering of concentration of an ion ( currently hard coded to be calcium, due to requirement for iCa ) which has a baseline level restingConc and tends to this value with time course decayConstant. A fixed factor rho is used to scale the incoming current independently of the size of the compartment to produce a concentration change.

Parameters:

restingConc (concentration)
decayConstant (time)
rho (rho_factor)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

HindmarshRose1984Cell#

class neuroml.nml.nml.HindmarshRose1984Cell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, C: a Nml2Quantity_capacitance (required) = None, a: a Nml2Quantity_none (required) = None, b: a Nml2Quantity_none (required) = None, c: a Nml2Quantity_none (required) = None, d: a Nml2Quantity_none (required) = None, s: a Nml2Quantity_none (required) = None, x1: a Nml2Quantity_none (required) = None, r: a Nml2Quantity_none (required) = None, x0: a Nml2Quantity_none (required) = None, y0: a Nml2Quantity_none (required) = None, z0: a Nml2Quantity_none (required) = None, v_scaling: a Nml2Quantity_voltage (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseCellMembPotCap

HindmarshRose1984Cell – The Hindmarsh Rose model is a simplified point cell model which captures complex firing patterns of single neurons, such as periodic and chaotic bursting. It has a fast spiking subsystem, which is a generalization of the FitzHugh-Nagumo system, coupled to a slower subsystem which allows the model to fire bursts. The dynamical variables x, y, z correspond to the membrane potential, a recovery variable, and a slower adaptation current, respectively. See Hindmarsh J. L. , and Rose R. M. ( 1984 ) A model of neuronal bursting using three coupled first order differential equations. Proc. R. Soc. London, Ser. B 221:87 – 102.

Parameters:

a (none) – cubic term in x nullcline
b (none) – quadratic term in x nullcline
c (none) – constant term in y nullcline
d (none) – quadratic term in y nullcline
r (none) – timescale separation between slow and fast subsystem ( r greater than 0; r much less than 1 )
s (none) – related to adaptation
x1 (none) – related to the system’s resting potential
v_scaling (voltage) – scaling of x for physiological membrane potential
x0 (none)
y0 (none)
z0 (none)
C (capacitance) – Total capacitance of the cell membrane

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

IafCell#

class neuroml.nml.nml.IafCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, leak_reversal: a Nml2Quantity_voltage (required) = None, thresh: a Nml2Quantity_voltage (required) = None, reset: a Nml2Quantity_voltage (required) = None, C: a Nml2Quantity_capacitance (required) = None, leak_conductance: a Nml2Quantity_conductance (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

IafCell – Integrate and fire cell with capacitance C, leakConductance and leakReversal

Parameters:

leakConductance (conductance)
leakReversal (voltage)
thresh (voltage)
reset (voltage)
C (capacitance) – Total capacitance of the cell membrane

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

IafRefCell#

class neuroml.nml.nml.IafRefCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, leak_reversal: a Nml2Quantity_voltage (required) = None, thresh: a Nml2Quantity_voltage (required) = None, reset: a Nml2Quantity_voltage (required) = None, C: a Nml2Quantity_capacitance (required) = None, leak_conductance: a Nml2Quantity_conductance (required) = None, refract: a Nml2Quantity_time (required) = None, gds_collector_=None, **kwargs_)#

Bases: IafCell

IafRefCell – Integrate and fire cell with capacitance C, leakConductance, leakReversal and refractory period refract

Parameters:

refract (time)
leakConductance (conductance)
leakReversal (voltage)
thresh (voltage)
reset (voltage)
C (capacitance) – Total capacitance of the cell membrane

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

IafTauCell#

class neuroml.nml.nml.IafTauCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, leak_reversal: a Nml2Quantity_voltage (required) = None, thresh: a Nml2Quantity_voltage (required) = None, reset: a Nml2Quantity_voltage (required) = None, tau: a Nml2Quantity_time (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

IafTauCell – Integrate and fire cell which returns to its leak reversal potential of leakReversal with a time constant tau

Parameters:

leakReversal (voltage)
tau (time)
thresh (voltage) – The membrane potential at which to emit a spiking event and reset voltage
reset (voltage) – The value the membrane potential is reset to on spiking

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

IafTauRefCell#

class neuroml.nml.nml.IafTauRefCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, leak_reversal: a Nml2Quantity_voltage (required) = None, thresh: a Nml2Quantity_voltage (required) = None, reset: a Nml2Quantity_voltage (required) = None, tau: a Nml2Quantity_time (required) = None, refract: a Nml2Quantity_time (required) = None, gds_collector_=None, **kwargs_)#

Bases: IafTauCell

IafTauRefCell – Integrate and fire cell which returns to its leak reversal potential of leakReversal with a time course tau. It has a refractory period of refract after spiking

Parameters:

refract (time)
leakReversal (voltage)
tau (time)
thresh (voltage) – The membrane potential at which to emit a spiking event and reset voltage
reset (voltage) – The value the membrane potential is reset to on spiking

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Include#

class neuroml.nml.nml.Include(segment_groups: a NmlId (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

Include – Include all members of another segmentGroup in this group

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

InhomogeneousParameter#

class neuroml.nml.nml.InhomogeneousParameter(id: a NmlId (required) = None, variable: a string (required) = None, metric: a Metric (required) = None, proximal: a ProximalDetails (optional) = None, distal: a DistalDetails (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

InhomogeneousParameter – An inhomogeneous parameter specified across the segmentGroup ( see variableParameter for usage ).

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

InhomogeneousValue#

class neuroml.nml.nml.InhomogeneousValue(inhomogeneous_parameters: a string (required) = None, value: a string (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

InhomogeneousValue – Specifies the value of an inhomogeneousParameter. For usage see variableParameter

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

InitMembPotential#

class neuroml.nml.nml.InitMembPotential(value: a Nml2Quantity_voltage (required) = None, segment_groups: a NmlId (optional) = 'all', gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

InitMembPotential – Explicitly set initial membrane potential for the cell

Parameters:: value (voltage)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

IntracellularProperties#

class neuroml.nml.nml.IntracellularProperties(species: list of Species(s) (optional) = None, resistivities: list of Resistivity(s) (optional) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

IntracellularProperties – Biophysical properties related to the intracellular space within the cell , such as the resistivity and the list of ionic species present. caConc and caConcExt are explicitly exposed here to facilitate accessing these values from other Components, even though caConcExt is clearly not an intracellular property

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

IntracellularProperties2CaPools#

class neuroml.nml.nml.IntracellularProperties2CaPools(species: list of Species(s) (optional) = None, resistivities: list of Resistivity(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: IntracellularProperties

IntracellularProperties2CaPools – Variant of intracellularProperties with 2 independent Ca pools

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Izhikevich2007Cell#

class neuroml.nml.nml.Izhikevich2007Cell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, C: a Nml2Quantity_capacitance (required) = None, v0: a Nml2Quantity_voltage (required) = None, k: a Nml2Quantity_conductancePerVoltage (required) = None, vr: a Nml2Quantity_voltage (required) = None, vt: a Nml2Quantity_voltage (required) = None, vpeak: a Nml2Quantity_voltage (required) = None, a: a Nml2Quantity_pertime (required) = None, b: a Nml2Quantity_conductance (required) = None, c: a Nml2Quantity_voltage (required) = None, d: a Nml2Quantity_current (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseCellMembPotCap

Izhikevich2007Cell – Cell based on the modified Izhikevich model in Izhikevich 2007, Dynamical systems in neuroscience, MIT Press

Parameters:

v0 (voltage) – Initial membrane potential
k (conductance_per_voltage)
vr (voltage) – Resting membrane potential
vt (voltage) – Spike threshold
vpeak (voltage) – Peak action potential value
a (per_time) – Time scale of recovery variable u
b (conductance) – Sensitivity of recovery variable u to subthreshold fluctuations of membrane potential v
c (voltage) – After-spike reset value of v
d (current) – After-spike increase to u
C (capacitance) – Total capacitance of the cell membrane

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

IzhikevichCell#

class neuroml.nml.nml.IzhikevichCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, v0: a Nml2Quantity_voltage (required) = None, thresh: a Nml2Quantity_voltage (required) = None, a: a Nml2Quantity_none (required) = None, b: a Nml2Quantity_none (required) = None, c: a Nml2Quantity_none (required) = None, d: a Nml2Quantity_none (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

IzhikevichCell – Cell based on the 2003 model of Izhikevich, see http://izhikevich.org/publications/spikes.htm

Parameters:

v0 (voltage) – Initial membrane potential
a (none) – Time scale of the recovery variable U
b (none) – Sensitivity of U to the subthreshold fluctuations of the membrane potential V
c (none) – After-spike reset value of V
d (none) – After-spike increase to U
thresh (voltage) – Spike threshold

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Member#

class neuroml.nml.nml.Member(segments: a NonNegativeInteger (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

Member – A single identified segment which is part of the segmentGroup

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

MembraneProperties#

class neuroml.nml.nml.MembraneProperties(channel_populations: list of ChannelPopulation(s) (optional) = None, channel_densities: list of ChannelDensity(s) (optional) = None, channel_density_v_shifts: list of ChannelDensityVShift(s) (optional) = None, channel_density_nernsts: list of ChannelDensityNernst(s) (optional) = None, channel_density_ghks: list of ChannelDensityGHK(s) (optional) = None, channel_density_ghk2s: list of ChannelDensityGHK2(s) (optional) = None, channel_density_non_uniforms: list of ChannelDensityNonUniform(s) (optional) = None, channel_density_non_uniform_nernsts: list of ChannelDensityNonUniformNernst(s) (optional) = None, channel_density_non_uniform_ghks: list of ChannelDensityNonUniformGHK(s) (optional) = None, spike_threshes: list of SpikeThresh(s) (required) = None, specific_capacitances: list of SpecificCapacitance(s) (required) = None, init_memb_potentials: list of InitMembPotential(s) (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

MembraneProperties – Properties specific to the membrane, such as the populations of channels, channelDensities, specificCapacitance, etc.

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

MembraneProperties2CaPools#

class neuroml.nml.nml.MembraneProperties2CaPools(channel_populations: list of ChannelPopulation(s) (optional) = None, channel_densities: list of ChannelDensity(s) (optional) = None, channel_density_v_shifts: list of ChannelDensityVShift(s) (optional) = None, channel_density_nernsts: list of ChannelDensityNernst(s) (optional) = None, channel_density_ghks: list of ChannelDensityGHK(s) (optional) = None, channel_density_ghk2s: list of ChannelDensityGHK2(s) (optional) = None, channel_density_non_uniforms: list of ChannelDensityNonUniform(s) (optional) = None, channel_density_non_uniform_nernsts: list of ChannelDensityNonUniformNernst(s) (optional) = None, channel_density_non_uniform_ghks: list of ChannelDensityNonUniformGHK(s) (optional) = None, spike_threshes: list of SpikeThresh(s) (required) = None, specific_capacitances: list of SpecificCapacitance(s) (required) = None, init_memb_potentials: list of InitMembPotential(s) (required) = None, channel_density_nernst_ca2s: list of ChannelDensityNernstCa2(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: MembraneProperties

MembraneProperties2CaPools – Variant of membraneProperties with 2 independent Ca pools

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Morphology#

class neuroml.nml.nml.Morphology(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, segments: list of Segment(s) (required) = None, segment_groups: list of SegmentGroup(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Standalone

Morphology – The collection of segment s which specify the 3D structure of the cell, along with a number of segmentGroup s

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

property num_segments#

Get the number of segments included in this cell morphology.

Returns:: number of segments
Return type:: int

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Path#

class neuroml.nml.nml.Path(from_: a SegmentEndPoint (optional) = None, to: a SegmentEndPoint (optional) = None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

Path – Include all the segment s between those specified by from and to , inclusive

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

PinskyRinzelCA3Cell#

class neuroml.nml.nml.PinskyRinzelCA3Cell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, i_soma: a Nml2Quantity_currentDensity (required) = None, i_dend: a Nml2Quantity_currentDensity (required) = None, gc: a Nml2Quantity_conductanceDensity (required) = None, g_ls: a Nml2Quantity_conductanceDensity (required) = None, g_ld: a Nml2Quantity_conductanceDensity (required) = None, g_na: a Nml2Quantity_conductanceDensity (required) = None, g_kdr: a Nml2Quantity_conductanceDensity (required) = None, g_ca: a Nml2Quantity_conductanceDensity (required) = None, g_kahp: a Nml2Quantity_conductanceDensity (required) = None, g_kc: a Nml2Quantity_conductanceDensity (required) = None, g_nmda: a Nml2Quantity_conductanceDensity (required) = None, g_ampa: a Nml2Quantity_conductanceDensity (required) = None, e_na: a Nml2Quantity_voltage (required) = None, e_ca: a Nml2Quantity_voltage (required) = None, e_k: a Nml2Quantity_voltage (required) = None, e_l: a Nml2Quantity_voltage (required) = None, qd0: a Nml2Quantity_none (required) = None, pp: a Nml2Quantity_none (required) = None, alphac: a Nml2Quantity_none (required) = None, betac: a Nml2Quantity_none (required) = None, cm: a Nml2Quantity_specificCapacitance (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

PinskyRinzelCA3Cell – Reduced CA3 cell model from Pinsky, P. F. , Rinzel, J. Intrinsic and network rhythmogenesis in a reduced traub model for CA3 neurons. J Comput Neurosci 1, 39-60 ( 1994 ). See OpenSourceBrain/PinskyRinzelModel

Parameters:

iSoma (currentDensity)
iDend (currentDensity)
gLs (conductanceDensity)
gLd (conductanceDensity)
gNa (conductanceDensity)
gKdr (conductanceDensity)
gCa (conductanceDensity)
gKahp (conductanceDensity)
gKC (conductanceDensity)
gc (conductanceDensity)
eNa (voltage)
eCa (voltage)
eK (voltage)
eL (voltage)
pp (none)
cm (specificCapacitance)
alphac (none)
betac (none)
gNmda (conductanceDensity)
gAmpa (conductanceDensity)
qd0 (none)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

ProximalDetails#

class neuroml.nml.nml.ProximalDetails(translation_start: a double (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

ProximalDetails – What to do at the proximal point when creating an inhomogeneous parameter

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Resistivity#

class neuroml.nml.nml.Resistivity(value: a Nml2Quantity_resistivity (required) = None, segment_groups: a NmlId (optional) = 'all', gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

Resistivity – The resistivity, or specific axial resistance, of the cytoplasm

Parameters:: value (resistivity)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

validate_Nml2Quantity_resistivity(value)#

validate_Nml2Quantity_resistivity_patterns_ = [['^(-?([0-9]*(\\.[0-9]+)?)([eE]-?[0-9]+)?[\\s]*(ohm_cm|kohm_cm|ohm_m))$']]#

Segment#

class neuroml.nml.nml.Segment(id: a NonNegativeInteger (required) = None, name: a string (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, parent: a SegmentParent (optional) = None, proximal: a Point3DWithDiam (optional) = None, distal: a Point3DWithDiam (required) = None, gds_collector_=None, **kwargs_)#

Bases: BaseNonNegativeIntegerId

Segment – A segment defines the smallest unit within a possibly branching structure ( morphology ), such as a dendrite or axon. Its id should be a nonnegative integer ( usually soma/root = 0 ). Its end points are given by the proximal and distal points. The proximal point can be omitted, usually because it is the same as a point on the parent segment, see proximal for details. parent specifies the parent segment. The first segment of a cell ( with no parent ) usually represents the soma. The shape is normally a cylinder ( radii of the proximal and distal equal, but positions different ) or a conical frustum ( radii and positions different ). If the x, y, x positions of the proximal and distal are equal, the segment can be interpreted as a sphere, and in this case the radii of these points must be equal. NOTE: LEMS does not yet support multicompartmental modelling, so the Dynamics here is only appropriate for single compartment modelling.

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

property length#

Get the length of the segment.

Returns:: length of the segment
Return type:: float

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

property surface_area#

Get the surface area of the segment.

Returns:: surface area of segment
Return type:: float

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

property volume#

Get the volume of the segment.

Returns:: volume of segment
Return type:: float

SegmentGroup#

class neuroml.nml.nml.SegmentGroup(id: a NonNegativeInteger (required) = None, neuro_lex_id: a NeuroLexId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, members: list of Member(s) (optional) = None, includes: list of Include(s) (optional) = None, paths: list of Path(s) (optional) = None, sub_trees: list of SubTree(s) (optional) = None, inhomogeneous_parameters: list of InhomogeneousParameter(s) (optional) = None, gds_collector_=None, **kwargs_)#

Bases: Base

SegmentGroup – A method to describe a group of segment s in a morphology , e. g. soma_group, dendrite_group, axon_group. While a name is useful to describe the group, the neuroLexId attribute can be used to explicitly specify the meaning of the group, e. g. sao1044911821 for ‘Neuronal Cell Body’, sao1211023249 for ‘Dendrite’. The segment s in this group can be specified as: a list of individual member segments; a path , all of the segments along which should be included; a subTree of the cell to include; other segmentGroups to include ( so all segments from those get included here ). An inhomogeneousParameter can be defined on the region of the cell specified by this group ( see variableParameter for usage ).

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

Species#

class neuroml.nml.nml.Species(id: a NmlId (required) = None, concentration_model: a NmlId (required) = None, ion: a NmlId (optional) = None, initial_concentration: a Nml2Quantity_concentration (required) = None, initial_ext_concentration: a Nml2Quantity_concentration (required) = None, segment_groups: a NmlId (optional) = 'all', gds_collector_=None, **kwargs_)#

Bases: Base

Species – Description of a chemical species identified by ion, which has internal, concentration, and external, extConcentration values for its concentration

Parameters:

initialConcentration (concentration)
initialExtConcentration (concentration)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

SpecificCapacitance#

class neuroml.nml.nml.SpecificCapacitance(value: a Nml2Quantity_specificCapacitance (required) = None, segment_groups: a NmlId (optional) = 'all', gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

SpecificCapacitance – Capacitance per unit area

Parameters:: value (specificCapacitance)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

SpikeThresh#

class neuroml.nml.nml.SpikeThresh(value: a Nml2Quantity_voltage (required) = None, segment_groups: a NmlId (optional) = 'all', gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

SpikeThresh – Membrane potential at which to emit a spiking event. Note, usually the spiking event will not be emitted again until the membrane potential has fallen below this value and rises again to cross it in a positive direction

Parameters:: value (voltage)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

SubTree#

class neuroml.nml.nml.SubTree(from_: a SegmentEndPoint (optional) = None, to: a SegmentEndPoint (optional) = None, gds_collector_=None, **kwargs_)#

Bases: BaseWithoutId

SubTree – Include all the segment s distal to that specified by from in the segmentGroup

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

VariableParameter#

class neuroml.nml.nml.VariableParameter(parameter: a string (required) = None, segment_groups: a string (required) = None, inhomogeneous_value: a InhomogeneousValue (optional) = None, gds_collector_=None, **kwargs_)#

Bases: GeneratedsSuper

VariableParameter – Specifies a parameter ( e. g. condDensity ) which can vary its value across a segmentGroup. The value is calculated from value attribute of the inhomogeneousValue subelement. This element is normally a child of channelDensityNonUniform , channelDensityNonUniformNernst or channelDensityNonUniformGHK and is used to calculate the value of the conductance, etc. which will vary on different parts of the cell. The segmentGroup specified here needs to define an inhomogeneousParameter ( referenced from inhomogeneousParameter in the inhomogeneousValue ), which calculates a variable ( e. g. p ) varying across the cell ( e. g. based on the path length from soma ), which is then used in the value attribute of the inhomogeneousValue ( so for example condDensity = f( p ) )

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

basePyNNCell#

class neuroml.nml.nml.basePyNNCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, cm: a float (required) = None, i_offset: a float (required) = None, tau_syn_E: a float (required) = None, tau_syn_I: a float (required) = None, v_init: a float (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: BaseCell

basePyNNCell – Base type of any PyNN standard cell model. Note: membrane potential v has dimensions voltage, but all other parameters are dimensionless. This is to facilitate translation to and from PyNN scripts in Python, where these parameters have implicit units, see http://neuralensemble.org/trac/PyNN/wiki/StandardModels

Parameters:

cm (none)
i_offset (none)
tau_syn_E (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
tau_syn_I (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
v_init (none)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

basePyNNIaFCell#

class neuroml.nml.nml.basePyNNIaFCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, cm: a float (required) = None, i_offset: a float (required) = None, tau_syn_E: a float (required) = None, tau_syn_I: a float (required) = None, v_init: a float (required) = None, tau_m: a float (required) = None, tau_refrac: a float (required) = None, v_reset: a float (required) = None, v_rest: a float (required) = None, v_thresh: a float (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: basePyNNCell

basePyNNIaFCell – Base type of any PyNN standard integrate and fire model

Parameters:

tau_refrac (none)
v_thresh (none)
tau_m (none)
v_rest (none)
v_reset (none)
cm (none)
i_offset (none)
tau_syn_E (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
tau_syn_I (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
v_init (none)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid

basePyNNIaFCondCell#

class neuroml.nml.nml.basePyNNIaFCondCell(id: a NmlId (required) = None, metaid: a MetaId (optional) = None, notes: a string (optional) = None, properties: list of Property(s) (optional) = None, annotation: a Annotation (optional) = None, neuro_lex_id: a NeuroLexId (optional) = None, cm: a float (required) = None, i_offset: a float (required) = None, tau_syn_E: a float (required) = None, tau_syn_I: a float (required) = None, v_init: a float (required) = None, tau_m: a float (required) = None, tau_refrac: a float (required) = None, v_reset: a float (required) = None, v_rest: a float (required) = None, v_thresh: a float (required) = None, e_rev_E: a float (required) = None, e_rev_I: a float (required) = None, extensiontype_=None, gds_collector_=None, **kwargs_)#

Bases: basePyNNIaFCell

basePyNNIaFCondCell – Base type of conductance based PyNN IaF cell models

Parameters:

e_rev_E (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
e_rev_I (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
tau_refrac (none)
v_thresh (none)
tau_m (none)
v_rest (none)
v_reset (none)
cm (none)
i_offset (none)
tau_syn_E (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
tau_syn_I (none) – This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell
v_init (none)

add(obj=None, hint=None, force=False, validate=True, **kwargs)#

Please use the info() method directly for more information on the current contents of this component object.

Parameters:

obj (Object) – member object or class type (neuroml.NeuroMLDocument) or name of class type (“NeuroMLDocument”), or None
hint (string) – member name to add to when there are multiple members that obj can be added to
force (bool) – boolean to force addition when an obj has already been added previously
validate (bool) – validate component after adding (default: True)

Returns obj:

the provided or created object

Raises:

Exception – if a member compatible to obj could not be found
Exception – if multiple members can accept the object and no hint is provided.

classmethod component_factory(component_type, validate=True, **kwargs)#

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.

Parameters:

component_type (str/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.
validate (bool) – toggle validation (default: True)
kwargs (named arguments) – named arguments to be passed to ComponentType constructor

Returns:

new Component (object) of provided ComponentType

Return type:

object

Raises:

ValueError – if validation/checks fail

classmethod get_class_hierarchy()#

Get the class hierarchy for a component classs.

Reference: https://stackoverflow.com/a/75161393/375067

See the methods in neuroml.utils to use this generated hierarchy.

Returns:: nested single key dictionaries where the key of each dictionary is the root node of that subtree, and keys are its immediate descendents

classmethod get_nml2_class_hierarchy()#

Return the NeuroML class hierarchy.

The root here is NeuroMLDocument. This is useful in calculating paths to different components to aid in construction of relative paths.

This caches the value as a class variable so that it is not re-calculated when used multiple times.

has__content()#

info(show_contents=False, return_format='string')#

Provide information on NeuroML component.

To get a list of possible parents, use the parentinfo() method.

Note that not all members will have ids (since not all NeuroML2 ComponentTypes have ids). For members that do not have ids, the object reference is listed instead.

See http://www.davekuhlman.org/generateDS.html#user-methods for more information on the MemberSpec_ class that generateDS uses.

Parameters:

show_contents (bool or str) – toggle to print out the contents of the members
return_format (str) –
select what format to return information in “string” (default), or “dict” or “list”.

If “dict” or “list” is provided, the information is returned as a dict/list instead of being printed. Note that if show_contents is False, only a list of members is available and will be returned even if “dict” is supplied. If show_contents is True or “all” but “list” is provided, only the list of members will be returned. If something other than “string”, “list”, or “dict” is provided, the string representation is returned and printed.

Returns:

info string, or list of members or dict with members as keys and member values as values

Return type:

str, list/dict

parentinfo(return_format='string')#

Show the list of possible parents.

This object can then be added to objects of the parents using the add method.

Parameters:: return_format (str) – format in which to return information. If “string” (default), an information string is returned. If “list” or “dict”, a list or dictionary is returned. The list will only contain the parent names, whereas the dict will also include the member of the parent that the component type matches to.
Returns:: info string, or list of parents or dict with parents as keys and member information as values
Return type:: str, list/dict

validate(recursive=False)#

Validate the component.

Throws a Python ValueError if a the component is invalid. You can ignore this by using a try .. except ValueError: pass block.

Note: validating your NeuroML file against the schema, which pynml and jnml do, will also check this.

Note: that this is different from the validate_ method, which does not validate inherited members.

Parameters:: recursive (bool) – toggle recursive validation (default: False)
Returns:: None
Return type:: None
Raises:: ValueError – if component is invalid