"""Read from and write to incidece matrices."""
import numpy as np
from ..convert import from_incidence_matrix
from ..linalg import incidence_matrix
__all__ = [
"read_incidence_matrix",
"write_incidence_matrix",
]
[docs]def read_incidence_matrix(
path, comments="#", delimiter=None, create_using=None, encoding="utf-8"
):
"""Read a file containing an incidence matrix and
convert it to a Hypergraph object.
Parameters
----------
path: string
The path of the file to read from
comments: string, default: "#"
The token that denotes comments in the file
delimiter: char, default: space (" ")
Specifies the delimiter between hyperedge members
create_using : Hypergraph constructor, optional
The hypergraph object to add the data to, by default None
nodetype: type
type that the node labels will be cast to
encoding: string, default: "utf-8"
Encoding of the file
Returns
-------
A Hypergraph object
The loaded hypergraph
See Also
--------
write_incidence_matrix
Examples
--------
>>> import xgi
>>> # H = xgi.read_incidence_matrix("test.csv", delimiter=",")
"""
return from_incidence_matrix(
np.loadtxt(path, comments=comments, delimiter=delimiter, encoding=encoding),
create_using=create_using,
)
[docs]def write_incidence_matrix(H, path, delimiter=" ", encoding="utf-8"):
"""Write a Hypergraph object to a file as an incidence matrix.
Parameters
----------
H: Hypergraph object
The hypergraph of interest
path: string
The path of the file to write to
delimiter: char, default: space (" ")
Specifies the delimiter between hyperedge members
encoding: string, default: "utf-8"
Encoding of the file
See Also
--------
read_incidence_matrix
Examples
--------
>>> import xgi
>>> H = xgi.random_hypergraph(50, [0.01, 0.001])
>>> # xgi.write_incidence_matrix(H, "test.csv", delimiter=",")
"""
eye = incidence_matrix(H, sparse=False)
np.savetxt(path, eye, delimiter=delimiter, newline="\n", encoding=encoding)