"""Return the indices of the minimum values along an axis."""
from __future__ import annotations
from typing import Any, Optional
import numpy
import numpoly
from ..baseclass import PolyLike
from ..dispatch import implements
[docs]@implements(numpy.argmin)
def argmin(
a: PolyLike,
axis: Optional[int] = None,
out: Optional[numpy.ndarray] = None,
) -> Any:
"""
Return the indices of the minimum values along an axis.
As polynomials are not inherently sortable, values are sorted using the
highest `lexicographical` ordering. Between the values that have the same
highest ordering, the elements are sorted using the coefficients. This also
ensures that the method behaves as expected with ``numpy.ndarray``.
Args:
a:
Input array.
axis:
By default, the index is into the flattened array, otherwise along
the specified axis.
out:
If provided, the result will be inserted into this array. It should
be of the appropriate shape and dtype.
Return:
Array of indices into the array. It has the same shape as `a.shape`
with the dimension along `axis` removed.
Note:
In case of multiple occurrences of the minimum values, the
indices corresponding to the first occurrence are returned.
Example:
>>> q0, q1 = numpoly.variable(2)
>>> numpoly.argmin([13, 7])
1
>>> numpoly.argmin([1, q0, q0**2, q1])
0
>>> numpoly.argmin([q0*q1, q0, q1])
1
>>> numpoly.argmin([[3*q0**2, q0**2], [2*q0**2, 4*q0**2]], axis=0)
array([1, 0])
"""
a = numpoly.aspolynomial(a)
options = numpoly.get_options()
proxy = numpoly.sortable_proxy(
a, graded=options["sort_graded"], reverse=options["sort_reverse"]
)
return numpy.argmin(proxy, axis=axis, out=out)