bluepysnap.edges.edge_population

Edge population access.

Classes

EdgePopulation(circuit, population_name)

Edge population access.

class bluepysnap.edges.edge_population.EdgePopulation(circuit, population_name)

Edge population access.

Initializes a EdgePopulation object from a EdgeStorage and a population name.

Parameters:

• circuit (bluepysnap.Circuit) – the circuit object containing the edge population

• population_name (str) – the name of the edge population

Returns:

An EdgePopulation object.

Return type:

EdgePopulation

afferent_edges(node_id, properties=None)

Get afferent edges for given node_id.

Parameters:

• node_id (CircuitNodeIds/int/sequence/str/mapping/None) – Target node ID.

• properties – An edge property name, a list of edge property names, or None.

Returns:

• A pandas Series indexed by edge ID if properties is a string.

• A pandas DataFrame indexed by edge ID if properties is a list.

• A list of edge IDs, if properties is None.

Return type:

pandas.Series/pandas.DataFrame/list

afferent_nodes(target, unique=True)

Get afferent node IDs for given target node_id.

Notes

Afferent nodes are nodes projecting an outgoing edge to one of the target node.

Parameters:

• target (CircuitNodeIds/int/sequence/str/mapping/None) – the target you want to resolve

• nodes. (and use as target) –

• unique (bool) – If True, return only unique afferent node IDs.

Returns:

Afferent node IDs for all the targets.

Return type:

numpy.ndarray

property config

Access the configuration for the population.

This configuration is extended with:

• ‘components’ of the circuit config

• ‘edges_file’: the path the h5 file containing the population.

container_property_names(container)

Lists the ConstContainer properties shared with the EdgePopulation.

Parameters:

container (ConstContainer) – a container class for edge properties.

Returns:

A list of strings corresponding to the properties that you can use from the container class

Return type:

list

Examples

>>> from bluepysnap.sonata_constants import Edge
>>> print(my_edge_population.container_property_names(Edge))
>>> ["AXONAL_DELAY", "SYN_WEIGHT"] # values you can use with my_edge_population

efferent_edges(node_id, properties=None)

Get efferent edges for given node_id.

Parameters:

• node_id (CircuitNodeIds/int/sequence/str/mapping/None) – source node ID

• properties – None / edge property name / list of edge property names

Returns:

• List of edge IDs, if properties is None;

• Pandas Series indexed by edge IDs if properties is string;

• Pandas DataFrame indexed by edge IDs if properties is list.

efferent_nodes(source, unique=True)

Get efferent node IDs for given source node_id.

Notes

Efferent nodes are nodes receiving an incoming edge from one of the source node.

Parameters:

• source (CircuitNodeIds/int/sequence/str/mapping/None) – the source you want to resolve and use as source nodes.

• unique (bool) – If True, return only unique afferent node IDs.

Returns:

Efferent node IDs for all the sources.

Return type:

numpy.ndarray

get(edge_ids, properties)

Edge properties as pandas DataFrame.

Parameters:

• edge_ids (array-like) – array-like of edge IDs

• properties (str/list) – an edge property name or a list of edge property names

Returns:

• A pandas Series indexed by edge IDs if properties is scalar.

• A pandas DataFrame indexed by edge IDs if properties is list.

Return type:

pandas.Series/pandas.DataFrame

Notes

The EdgePopulation.property_names function will give you all the usable properties for the properties argument.

property h5_filepath

Get the H5 edges file associated with population.

ids(group=None, limit=None, sample=None, raise_missing_property=True)

Edge IDs corresponding to edges edge_ids.

Parameters:

• group (None/int/CircuitEdgeId/CircuitEdgeIds/sequence) –

  Which IDs will be returned depends on the type of the group argument:

  • None: return all IDs.

  • int, CircuitEdgeId: return a single edge ID.

  • CircuitEdgeIds return IDs of edges the edge population in an array.

  • sequence: return IDs of edges in an array.

• sample (int) – If specified, randomly choose sample number of IDs from the match result. If the size of the sample is greater than the size of the EdgePopulation then all ids are taken and shuffled.

• limit (int) – If specified, return the first limit number of IDs from the match result. If limit is greater than the size of the population all node IDs are returned.

• raise_missing_property (bool) – if True, raises if a property is not listed in this population. Otherwise the ids are just not selected if a property is missing.

Returns:

A numpy array of IDs.

Return type:

numpy.array

iter_connections(source=None, target=None, unique_node_ids=False, shuffle=False, return_edge_ids=False, return_edge_count=False)

Iterate through source -> target connections.

Parameters:

• source (CircuitNodeIds/int/sequence/str/mapping/None) – source node group

• target (CircuitNodeIds/int/sequence/str/mapping/None) – target node group

• unique_node_ids – if True, no node ID will be used more than once as source or target for edges. Careful, this flag does not provide unique (source, target) pairs but unique node IDs.

• shuffle – if True, result order would be (somewhat) randomized

• return_edge_count – if True, edge count is added to yield result

• return_edge_ids – if True, edge ID list is added to yield result

return_edge_count and return_edge_ids are mutually exclusive.

Yields:

• (source_node_id, target_node_id, edge_ids) if return_edge_ids is True;

• (source_node_id, target_node_id, edge_count) if return_edge_count is True;

• (source_node_id, target_node_id) otherwise.

pair_edges(source_node_id, target_node_id, properties=None)

Get edges corresponding to source_node_id -> target_node_id connection.

Parameters:

• source_node_id (CircuitNodeIds/int/sequence/str/mapping/None) – source node ID

• target_node_id (CircuitNodeIds/int/sequence/str/mapping/None) – target node ID

• properties – None / edge property name / list of edge property names

Returns:

• List of edge IDs, if properties is None;

• Pandas Series indexed by edge IDs if properties is string;

• Pandas DataFrame indexed by edge IDs if properties is list.

pathway_edges(source=None, target=None, properties=None)

Get edges corresponding to source -> target connections.

Parameters:

• source (CircuitNodeIds/int/sequence/str/mapping/None) – source node group

• target (CircuitNodeIds/int/sequence/str/mapping/None) – target node group

• properties – None / edge property name / list of edge property names

Returns:

• List of edge IDs, if properties is None;

• Pandas Series indexed by edge IDs if properties is string;

• Pandas DataFrame indexed by edge IDs if properties is list.

positions(edge_ids, side, kind)

Edge positions as a pandas DataFrame.

Parameters:

• edge_ids (array-like) – array-like of edge IDs

• side (str) – afferent or efferent

• kind (str) – center or surface

Returns:

Pandas Dataframe with (‘x’, ‘y’, ‘z’) columns indexed by edge IDs.

properties(edge_ids, properties)

Edge properties as pandas DataFrame.

Parameters:

• edge_ids (array-like) – array-like of edge IDs

• properties (str/list) – an edge property name or a list of edge property names

Returns:

• A pandas Series indexed by edge IDs if properties is scalar.

• A pandas DataFrame indexed by edge IDs if properties is list.

Return type:

pandas.Series/pandas.DataFrame

Notes

The EdgePopulation.property_names function will give you all the usable properties for the properties argument.

property_dtypes

Returns the dtypes of all the properties.

Returns:

series indexed by field name with the corresponding dtype as value.

Return type:

pandas.Series

property property_names

Set of available edge properties.

Notes

Properties are a combination of the group attributes, the dynamics_params and the topology properties.

property size

Population size.

source

Source NodePopulation.

spatial_synapse_index

Access to edges spatial index.

target

Target NodePopulation.

property type

Population type.