""" 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, Sequence import numpy from numpy.typing import ArrayLike from .types import fdfield_t, vfdfield_t, cfdfield_t, vcfdfield_t @overload def vec(f: None) -> None: pass @overload def vec(f: fdfield_t) -> vfdfield_t: pass @overload def vec(f: cfdfield_t) -> vcfdfield_t: pass @overload def vec(f: ArrayLike) -> vfdfield_t | vcfdfield_t: pass def vec(f: fdfield_t | cfdfield_t | ArrayLike | None) -> vfdfield_t | vcfdfield_t | None: """ Create a 1D ndarray from a 3D vector field which spans a 1-3D region. Returns `None` if called with `f=None`. Args: f: A vector field, `[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') @overload def unvec(v: None, shape: Sequence[int]) -> None: pass @overload def unvec(v: vfdfield_t, shape: Sequence[int]) -> fdfield_t: pass @overload def unvec(v: vcfdfield_t, shape: Sequence[int]) -> cfdfield_t: pass def unvec(v: vfdfield_t | vcfdfield_t | None, shape: Sequence[int]) -> fdfield_t | cfdfield_t | None: """ Perform the inverse of vec(): take a 1D ndarray and output a 3D field of form `[f_x, f_y, f_z]` where each of `f_*` is a len(shape)-dimensional ndarray. Returns `None` if called with `v=None`. Args: v: 1D ndarray representing a 3D vector field of shape shape (or None) shape: shape of the vector field 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((3, *shape), order='C')