meanas/meanas/fdmath/vectorization.py
2026-04-18 23:55:40 -07:00

126 lines
3.6 KiB
Python

"""
Functions for moving between a vector field (list of 3 ndarrays, `[f_x, f_y, f_z]`)
and a 1D array representation of that field `[f_x0, f_x1, f_x2,... f_y0,... f_z0,...]`.
Vectorized versions of the field use row-major (ie., C-style) ordering.
"""
from typing import overload
from collections.abc import Sequence
import numpy
from numpy.typing import ArrayLike, NDArray
from .types import (
fdfield_t, vfdfield_t, cfdfield_t, vcfdfield_t,
fdslice_t, vfdslice_t, cfdslice_t, vcfdslice_t,
fdfield2_t, vfdfield2_t, cfdfield2_t, vcfdfield2_t,
)
@overload
def vec(f: None) -> None:
pass # pragma: no cover
@overload
def vec(f: fdfield_t) -> vfdfield_t:
pass # pragma: no cover
@overload
def vec(f: cfdfield_t) -> vcfdfield_t:
pass # pragma: no cover
@overload
def vec(f: fdfield2_t) -> vfdfield2_t:
pass # pragma: no cover
@overload
def vec(f: cfdfield2_t) -> vcfdfield2_t:
pass # pragma: no cover
@overload
def vec(f: fdslice_t) -> vfdslice_t:
pass # pragma: no cover
@overload
def vec(f: cfdslice_t) -> vcfdslice_t:
pass # pragma: no cover
@overload
def vec(f: ArrayLike) -> NDArray:
pass # pragma: no cover
def vec(
f: fdfield_t | cfdfield_t | fdfield2_t | cfdfield2_t | fdslice_t | cfdslice_t | ArrayLike | None,
) -> vfdfield_t | vcfdfield_t | vfdfield2_t | vcfdfield2_t | vfdslice_t | vcfdslice_t | NDArray | None:
"""
Create a 1D ndarray from a vector field which spans a 1-3D region.
Returns `None` if called with `f=None`.
Args:
f: A vector field, e.g. `[f_x, f_y, f_z]` where each `f_` component is a 1- to
3-D ndarray (`f_*` should all be the same size). Doesn't fail with `f=None`.
Returns:
1D ndarray containing the linearized field (or `None`)
"""
if f is None:
return None
return numpy.ravel(f, order='C') # type: ignore
@overload
def unvec(v: None, shape: Sequence[int], nvdim: int = 3) -> None:
pass # pragma: no cover
@overload
def unvec(v: vfdfield_t, shape: Sequence[int], nvdim: int = 3) -> fdfield_t:
pass # pragma: no cover
@overload
def unvec(v: vcfdfield_t, shape: Sequence[int], nvdim: int = 3) -> cfdfield_t:
pass # pragma: no cover
@overload
def unvec(v: vfdfield2_t, shape: Sequence[int], nvdim: int = 3) -> fdfield2_t:
pass
@overload
def unvec(v: vcfdfield2_t, shape: Sequence[int], nvdim: int = 3) -> cfdfield2_t:
pass
@overload
def unvec(v: vfdslice_t, shape: Sequence[int], nvdim: int = 3) -> fdslice_t:
pass
@overload
def unvec(v: vcfdslice_t, shape: Sequence[int], nvdim: int = 3) -> cfdslice_t:
pass
@overload
def unvec(v: ArrayLike, shape: Sequence[int], nvdim: int = 3) -> NDArray:
pass
def unvec(
v: vfdfield_t | vcfdfield_t | vfdfield2_t | vcfdfield2_t | vfdslice_t | vcfdslice_t | ArrayLike | None,
shape: Sequence[int],
nvdim: int = 3,
) -> fdfield_t | cfdfield_t | fdfield2_t | cfdfield2_t | fdslice_t | cfdslice_t | NDArray | None:
"""
Perform the inverse of vec(): take a 1D ndarray and output an `nvdim`-component field
of form e.g. `[f_x, f_y, f_z]` (`nvdim=3`) where each of `f_*` is a len(shape)-dimensional
ndarray.
Returns `None` if called with `v=None`.
Args:
v: 1D ndarray representing a vector field of shape shape (or None)
shape: shape of the vector field
nvdim: Number of components in each vector
Returns:
`[f_x, f_y, f_z]` where each `f_` is a `len(shape)` dimensional ndarray (or `None`)
"""
if v is None:
return None
return v.reshape((nvdim, *shape), order='C') # type: ignore