fdfd_tools/fdfd_tools/vectorization.py

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"""
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,...].
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Vectorized versions of the field use row-major (ie., C-style) ordering.
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"""
from typing import List
import numpy
__author__ = 'Jan Petykiewicz'
# Types
field_t = List[numpy.ndarray] # vector field (eg. [E_x, E_y, E_z]
vfield_t = numpy.ndarray # linearized vector field
def vec(f: field_t) -> vfield_t:
"""
Create a 1D ndarray from a 3D vector field which spans a 1-3D region.
Returns None if called with f=None.
:param f: A vector field, [f_x, f_y, f_z] where each f_ component is a 1 to
3D ndarray (f_* should all be the same size). Doesn't fail with f=None.
:return: A 1D ndarray containing the linearized field (or None)
"""
if numpy.any(numpy.equal(f, None)):
return None
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return numpy.hstack(tuple((fi.ravel(order='C') for fi in f)))
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def unvec(v: vfield_t, shape: numpy.ndarray) -> field_t:
"""
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.
:param v: 1D ndarray representing a 3D vector field of shape shape (or None)
:param shape: shape of the vector field
:return: [f_x, f_y, f_z] where each f_ is a len(shape) dimensional ndarray
(or None)
"""
if numpy.any(numpy.equal(v, None)):
return None
return vi.reshape((3, *shape), order='C')
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