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improve docs and variable names

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jan 2023-10-12 01:30:23 -07:00
parent 8f2f672137
commit ecf37580c5
1 changed files with 80 additions and 16 deletions
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96
masque/utils/pack2d.py
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@ -17,8 +17,26 @@ def maxrects_bssf(
allow_rejects: bool = True,
) -> tuple[NDArray[numpy.float64], set[int]]:
"""
sizes should be Nx2
regions should be Mx4 (xmin, ymin, xmax, ymax)
Pack rectangles `rects` into regions `containers` using the "maximal rectangles best short side fit"
algorithm (maxrects_bssf) from "A thousand ways to pack the bin", Jukka Jylanki, 2010.
This algorithm gives the best results, but is asymptotically slower than `guillotine_bssf_sas`.
Args:
rects: Nx2 array of rectangle sizes `[[x_size0, y_size0], ...]`.
containers: Mx4 array of regions into which `rects` will be placed, specified using their
corner coordinates ` [[x_min0, y_min0, x_max0, y_max0], ...]`.
presort: If `True` (default), largest-shortest-side rectangles will be placed
first. Otherwise, they will be placed in the order provided.
allow_rejects: If `False`, `MasqueError` will be raised if any rectangle cannot be placed.
Returns:
`[[x_min0, y_min0], ...]` placement locations for `rects`, with the same ordering.
The second argument is a set of indicies of `rects` entries which were rejected; their
corresponding placement locations should be ignored.
Raises:
MasqueError if `allow_rejects` is `True` but some `rects` could not be placed.
"""
regions = numpy.array(containers, copy=False, dtype=float)
rect_sizes = numpy.array(rects, copy=False, dtype=float)
@ -96,10 +114,30 @@ def guillotine_bssf_sas(
allow_rejects: bool = True,
) -> tuple[NDArray[numpy.float64], set[int]]:
"""
sizes should be Nx2
regions should be Mx4 (xmin, ymin, xmax, ymax)
#TODO: test me!
# TODO add rectangle-merge?
Pack rectangles `rects` into regions `containers` using the "guillotine best short side fit with
shorter axis split rule" algorithm (guillotine-BSSF-SAS) from "A thousand ways to pack the bin",
Jukka Jylanki, 2010.
This algorithm gives the worse results than `maxrects_bssf`, but is asymptotically faster.
# TODO consider adding rectangle-merge?
# TODO guillotine could use some additional testing
Args:
rects: Nx2 array of rectangle sizes `[[x_size0, y_size0], ...]`.
containers: Mx4 array of regions into which `rects` will be placed, specified using their
corner coordinates ` [[x_min0, y_min0, x_max0, y_max0], ...]`.
presort: If `True` (default), largest-shortest-side rectangles will be placed
first. Otherwise, they will be placed in the order provided.
allow_rejects: If `False`, `MasqueError` will be raised if any rectangle cannot be placed.
Returns:
`[[x_min0, y_min0], ...]` placement locations for `rects`, with the same ordering.
The second argument is a set of indicies of `rects` entries which were rejected; their
corresponding placement locations should be ignored.
Raises:
MasqueError if `allow_rejects` is `True` but some `rects` could not be placed.
"""
regions = numpy.array(containers, copy=False, dtype=float)
rect_sizes = numpy.array(rects, copy=False, dtype=float)
@ -133,15 +171,15 @@ def guillotine_bssf_sas(
new_region0 = regions[rr].copy()
new_region1 = new_region0.copy()
split_vert = loc + rect_size
split_vertex = loc + rect_size
if split_horiz:
new_region0[2] = split_vert[0]
new_region0[1] = split_vert[1]
new_region1[0] = split_vert[0]
new_region0[2] = split_vertex[0]
new_region0[1] = split_vertex[1]
new_region1[0] = split_vertex[0]
else:
new_region0[3] = split_vert[1]
new_region0[0] = split_vert[0]
new_region1[1] = split_vert[1]
new_region0[3] = split_vertex[1]
new_region0[0] = split_vertex[0]
new_region1[1] = split_vertex[1]
regions = numpy.vstack((regions[:rr], regions[rr + 1:],
new_region0, new_region1))
@ -157,19 +195,45 @@ def guillotine_bssf_sas(
def pack_patterns(
library: Mapping[str, Pattern],
patterns: Sequence[str],
regions: numpy.ndarray,
containers: ArrayLike,
spacing: tuple[float, float],
presort: bool = True,
allow_rejects: bool = True,
packer: Callable = maxrects_bssf,
) -> tuple[Pattern, list[str]]:
half_spacing = numpy.array(spacing) / 2
"""
Pick placement locations for `patterns` inside the regions specified by `containers`.
No rotations are performed.
Args:
library: Library from which `Pattern` objects will be drawn.
patterns: Sequence of pattern names which are to be placed.
containers: Mx4 array of regions into which `patterns` will be placed, specified using their
corner coordinates ` [[x_min0, y_min0, x_max0, y_max0], ...]`.
spacing: (x, y) spacing between adjacent patterns. Patterns are effectively expanded outwards
by `spacing / 2` prior to placement, so this also affects pattern position relative to
container edges.
presort: If `True` (default), largest-shortest-side rectangles will be placed
first. Otherwise, they will be placed in the order provided.
allow_rejects: If `False`, `MasqueError` will be raised if any rectangle cannot be placed.
packer: Bin-packing method; see the other functions in this module (namely `maxrects_bssf`
and `guillotine_bssf_sas`).
Returns:
A `Pattern` containing one `Ref` for each entry in `patterns`.
A list of "rejected" pattern names, for which a valid placement location could not be found.
Raises:
MasqueError if `allow_rejects` is `True` but some `rects` could not be placed.
"""
half_spacing = numpy.array(spacing, copy=False, dtype=float) / 2
bounds = [library[pp].get_bounds() for pp in patterns]
sizes = [bb[1] - bb[0] + spacing if bb is not None else spacing for bb in bounds]
offsets = [half_spacing - bb[0] if bb is not None else (0, 0) for bb in bounds]
locations, reject_inds = packer(sizes, regions, presort=presort, allow_rejects=allow_rejects)
locations, reject_inds = packer(sizes, containers, presort=presort, allow_rejects=allow_rejects)
pat = Pattern()
for pp, oo, loc in zip(patterns, offsets, locations):