"""Utility functions for argument types."""
import numbers
from typing import Optional
import numpy as np
from probnum.typing import DTypeLike, ScalarLike, ShapeLike, ShapeType
__all__ = ["as_shape", "as_numpy_scalar"]
[docs]def as_shape(x: ShapeLike, ndim: Optional[numbers.Integral] = None) -> ShapeType:
"""Convert a shape representation into a shape defined as a tuple of ints.
Parameters
----------
x
Shape representation.
ndim
The required number of dimensions in the shape.
Raises
------
TypeError
If ``x`` is not a valid :const:`ShapeLike`.
TypeError
If ``x`` does not feature the required number of dimensions.
"""
if isinstance(x, (int, numbers.Integral, np.integer)):
shape = (int(x),)
elif isinstance(x, tuple) and all(isinstance(item, int) for item in x):
shape = x
else:
try:
_ = iter(x)
except TypeError as e:
raise TypeError(
f"The given shape {x} must be an integer or an iterable of integers."
) from e
if not all(isinstance(item, (int, numbers.Integral, np.integer)) for item in x):
raise TypeError(f"The given shape {x} must only contain integer values.")
shape = tuple(int(item) for item in x)
if isinstance(ndim, numbers.Integral):
if len(shape) != ndim:
raise TypeError(f"The given shape {shape} must have {ndim} dimensions.")
return shape
[docs]def as_numpy_scalar(x: ScalarLike, dtype: DTypeLike = None) -> np.ndarray:
"""Convert a scalar into a scalar NumPy array.
Parameters
----------
x
Scalar value.
dtype
Data type of the scalar.
Raises
------
ValueError
If :code:`x` can not be interpreted as a scalar.
"""
if np.ndim(x) != 0:
raise ValueError("The given input is not a scalar.")
return np.asarray(x, dtype=dtype)