DemandVectorSP¶

Class Description¶

class paminco.net.demand.DemandVectorSP(data, shared=None, dtype_int=None, dtype_float=None, copy: bool = True, is_label: bool = True)[source]¶

Class that builds on a number of commodities k.

A DemandVectorSP object can be instantiated in several ways:

DemandVectorSP(dv)

where dv is a DemandVectorSP.

DemandVectorSP(arr)

where arr is array_like. The resulting array from numpy.array(arr) is expected to look like:

[source_1,   sink_1,   rate_1]
            ...
[source_k,   sink_k,   rate_k]

Parameters

dataDemandVector or array_like: Commodity data in processed or unprocessed form.
sharedShared, optional: Shared object for all network objects.
copybool, default=True: Whether to copy data in data.
is_labelbool, default=True: Whether commodity nodes are given as labels or ids in data.

Attributes

k: Number of commodities in demand vector.
shared: Shared object for network objects.
all_single: Whether is comprised only of commodities with single sink / source.
rate: ndarray (k, ) of flow: rates.
total_rate: np.ndarray (k, ): total flow per commodity.
source_lbl: ndarray (k, ) of str: source labels.
sink_lbl: ndarray (k, ) of str: sink labels.
source_id: ndarray (k, ) of int: source indices.
sink_id: ndarray (k, ) of int: sink indices.

Methods¶

Value¶

`DemandVectorSP.__call__`(args, *kw)	Get demand as sparse matrix of shape (n, k).
`DemandVectorSP.sparse`([dtype])	Get demand as sparse matrix.

Load / Save¶

`DemandVectorSP.make_save_dict`([prefix, ...])	Generate dict to save object with numpy.savez.
`DemandVectorSP.save_to_numpy`(file, **kwargs)	Save object into a single file in uncompressed `.npz` format.
`DemandVectorSP.from_npz`(data[, shared, prefix])	Construct object from `.npz` file.
`DemandVectorSP.add_to_etree`(root[, name])	Add demand data to xml.etree.ElementTree.Element.
`DemandVectorSP.from_xml`()

Misc¶

`DemandVectorSP.delete_nodes`(nodes)	Delete all commodities that are made up by `nodes`.
`DemandVectorSP.to_single_pairs`([as_label])	Returns self.
`DemandVectorSP.reset_cache`([hard])	Reset cache values.
`DemandVectorSP.map_node_label_to_id`()	Map labels -> ids for all commodities.
`DemandVectorSP.map_node_id_to_label`()	Delete all commodities that are made up by `nodes`.
`DemandVectorSP.scaled_copy`([f])	Get a copy where every commodity is scaled by f.

Attributes¶

`DemandVectorSP.k`	Number of commodities in demand vector.
`DemandVectorSP.n`
`DemandVectorSP.shared`	Shared object for network objects.
`DemandVectorSP.dtype_int`
`DemandVectorSP.dtype_float`
`DemandVectorSP.all_single`	Whether is comprised only of commodities with single sink / source.
`DemandVectorSP.rate`	ndarray (k, ) of flow: rates.
`DemandVectorSP.source_lbl`	ndarray (k, ) of str: source labels.
`DemandVectorSP.sink_lbl`	ndarray (k, ) of str: sink labels.
`DemandVectorSP.source_id`	ndarray (k, ) of int: source indices.
`DemandVectorSP.sink_id`	ndarray (k, ) of int: sink indices.
`DemandVectorSP.total_rate`	np.ndarray (k, ): total flow per commodity.