"""Utility functions for arrays and the like."""
from typing import Union
import numpy as np
import scipy
import probnum
def atleast_1d(*rvs):
"""Convert arrays or random variables to arrays or random variables with at least
one dimension.
Scalar inputs are converted to 1-dimensional arrays, whilst
higher-dimensional inputs are preserved. Sparse arrays are not
transformed.
Parameters
----------
rvs: array-like or RandomVariable
One or more input random variables or arrays.
Returns
-------
res : array-like or list
An array / random variable or list of arrays / random variables,
each with ``a.ndim >= 1``.
"""
res = []
for rv in rvs:
if isinstance(rv, scipy.sparse.spmatrix):
result = rv
elif isinstance(rv, np.ndarray):
result = np.atleast_1d(rv)
elif isinstance(rv, probnum.RandomVariable):
raise NotImplementedError
else:
result = rv
res.append(result)
if len(res) == 1:
return res[0]
else:
return res
[docs]def as_colvec(
vec: Union[np.ndarray, "probnum.RandomVariable"]
) -> Union[np.ndarray, "probnum.RandomVariable"]:
"""Transform the given vector or random variable to column format.
Given a vector (or random variable) of dimension (n,) return an array with
dimensions (n, 1) instead. Higher-dimensional arrays are not changed.
Parameters
----------
vec
Vector, array or random variable to be transformed into a column vector.
"""
if isinstance(vec, probnum.RandomVariable):
if vec.shape != (vec.shape[0], 1):
vec.reshape(newshape=(vec.shape[0], 1))
else:
if vec.ndim == 1:
return vec[:, None]
return vec