from __future__ import annotations
import itertools as it
from collections.abc import Mapping, Sequence
from typing import Any, cast
import kfactory as kf
import gdsfactory as gf
from gdsfactory.component import Component
from gdsfactory.grid import grid, grid_with_text
from gdsfactory.pack import pack
from gdsfactory.typings import CellSpec, ComponentSpec
def generate_doe(
doe: ComponentSpec,
settings: Mapping[str, Sequence[Any]],
do_permutations: bool = False,
function: CellSpec | None = None,
) -> tuple[list[Component], list[dict[str, Any]]]:
"""Generates a component DOE (Design of Experiment).
which can then be packed, or used elsewhere.
Args:
doe: function to return Components.
settings: component settings.
do_permutations: for each setting.
function: for the component (add padding, grating couplers ...)
"""
if do_permutations:
settings_list = [dict(zip(settings, t)) for t in it.product(*settings.values())]
else:
settings_list = [dict(zip(settings, t)) for t in zip(*settings.values())]
if function:
function = gf.get_cell(function)
component_list = [
function(gf.get_component(doe, **settings)) for settings in settings_list
]
else:
component_list = [
gf.get_component(doe, **settings) for settings in settings_list
]
return component_list, settings_list
[docs]
@gf.cell
def pack_doe(
doe: ComponentSpec,
settings: Mapping[str, Sequence[kf.typings.MetaData]],
do_permutations: bool = False,
function: CellSpec | None = None,
**kwargs: Any,
) -> Component:
"""Packs a component DOE (Design of Experiment) using pack.
Args:
doe: function to return Components.
settings: component settings.
do_permutations: for each setting.
function: to apply (add padding, grating couplers).
kwargs: for pack.
Keyword Args:
spacing: Minimum distance between adjacent shapes.
aspect_ratio: (width, height) ratio of the rectangular bin.
max_size: Limits the size into which the shapes will be packed.
sort_by_area: Pre-sorts the shapes by area.
density: Values closer to 1 pack tighter but require more computation.
precision: Desired precision for rounding vertex coordinates.
text: Optional function to add text labels.
text_prefix: for labels. For example. 'A' for 'A1', 'A2'...
text_offsets: relative to component size info anchor. Defaults to center.
text_anchors: relative to component (ce cw nc ne nw sc se sw center cc).
name_prefix: for each packed component (avoids the Unnamed cells warning).
Note that the suffix contains a uuid so the name will not be deterministic.
rotation: for each component in degrees.
h_mirror: horizontal mirror in y axis (x, 1) (1, 0). This is the most common.
v_mirror: vertical mirror using x axis (1, y) (0, y).
"""
component_list, settings_list = generate_doe(
doe=doe, settings=settings, do_permutations=do_permutations, function=function
)
components = pack(component_list, **kwargs)
if len(components) > 1:
raise ValueError(
f"failed to pack in one Component, it created {len(components)} Components"
)
component = components[0]
component.info["doe_names"] = [component.name for component in component_list]
component.info["doe_settings"] = cast(kf.typings.MetaData, settings_list)
return component
[docs]
@gf.cell
def pack_doe_grid(
doe: ComponentSpec,
settings: Mapping[str, Sequence[kf.typings.MetaData]],
do_permutations: bool = False,
function: CellSpec | None = None,
with_text: bool = False,
**kwargs: Any,
) -> Component:
"""Packs a component DOE (Design of Experiment) using grid.
Args:
doe: function to return Components.
settings: component settings.
do_permutations: for each setting.
function: to apply to component (add padding, grating couplers).
with_text: includes text label.
kwargs: for grid.
Keyword Args:
spacing: between adjacent elements on the grid, can be a tuple for
different distances in height and width.
separation: If True, guarantees elements are separated with fixed spacing
if False, elements are spaced evenly along a grid.
shape: x, y shape of the grid (see np.reshape).
If no shape and the list is 1D, if np.reshape were run with (1, -1).
align_x: {'x', 'xmin', 'xmax'} for x (column) alignment along.
align_y: {'y', 'ymin', 'ymax'} for y (row) alignment along.
edge_x: {'x', 'xmin', 'xmax'} for x (column) (ignored if separation = True).
edge_y: {'y', 'ymin', 'ymax'} for y (row) (ignored if separation = True).
rotation: for each component in degrees.
h_mirror: horizontal mirror y axis (x, 1) (1, 0). most common mirror.
v_mirror: vertical mirror using x axis (1, y) (0, y).
"""
if do_permutations:
settings_list = [dict(zip(settings, t)) for t in it.product(*settings.values())]
else:
settings_list = [dict(zip(settings, t)) for t in zip(*settings.values())]
if function:
function = gf.get_cell(function)
component_list = [
function(gf.get_component(doe, settings=None, **settings))
for settings in settings_list
]
else:
component_list = [
gf.get_component(doe, settings=None, **settings)
for settings in settings_list
]
if with_text:
c = grid_with_text(component_list, **kwargs)
else:
c = grid(component_list, **kwargs)
c.info["doe_names"] = [component.name for component in component_list]
c.info["doe_settings"] = cast(kf.typings.MetaData, settings_list)
return c
if __name__ == "__main__":
c = pack_doe_grid(
doe="mmi1x2",
settings=dict(length_mmi=(2.5, 100), width_mmi=(4, 10)),
with_text=True,
spacing=(100, 100),
shape=(2, 2),
do_permutations=True,
)
c = pack_doe(doe="mmi1x2", settings=dict(length_mmi=(2, 100), width_mmi=(4, 10)))
c.show()
