110 lines
3.5 KiB
Python
110 lines
3.5 KiB
Python
"""
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Functionality for extracting geometry and label info from `masque` patterns.
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"""
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from typing import Sequence, Dict, List, Any, Tuple, Optional, Mapping
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from collections import defaultdict
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import numpy
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from numpy.typing import NDArray
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from masque import Pattern
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from masque.file import oasis, gdsii
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from masque.shapes import Polygon
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from ..types import layer_t
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from ..utils import connectivity2layers
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def read_cell(
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cell: Pattern,
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connectivity: Sequence[Tuple[layer_t, Optional[layer_t], layer_t]],
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label_mapping: Optional[Mapping[layer_t, layer_t]] = None,
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) -> Tuple[
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defaultdict[layer_t, List[NDArray[numpy.float64]]],
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defaultdict[layer_t, List[Tuple[float, float, str]]]]:
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"""
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Extract `polys` and `labels` from a `masque.Pattern`.
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This function extracts the data needed by `snarl.trace_connectivity`.
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Args:
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cell: A `masque` `Pattern` object. Usually your topcell.
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connectivity: A sequence of 3-tuples specifying the layer connectivity.
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Same as what is provided to `snarl.trace_connectivity`.
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label_mapping: A mapping of `{label_layer: metal_layer}`. This allows labels
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to refer to nets on metal layers without the labels themselves being on
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that layer.
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Returns:
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`polys` and `labels` data structures, to be passed to `snarl.trace_connectivity`.
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"""
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metal_layers, via_layers = connectivity2layers(connectivity)
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poly_layers = metal_layers | via_layers
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if label_mapping is None:
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label_mapping = {layer: layer for layer in metal_layers}
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label_layers = {label_layer for label_layer in label_mapping.keys()}
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cell = cell.deepcopy().subset(
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shapes_func=lambda ss: ss.layer in poly_layers,
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labels_func=lambda ll: ll.layer in label_layers,
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subpatterns_func=lambda ss: True,
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)
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cell = cell.flatten()
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polys = load_polys(cell, list(poly_layers))
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metal_labels = defaultdict(list)
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for label_layer, metal_layer in label_mapping.items():
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labels = []
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for ll in cell.labels:
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if ll.layer != label_layer:
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continue
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if ll.repetition is None:
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displacements = [(0, 0)]
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else:
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displacements = ll.repetition.displacements
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for displacement in displacements:
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offset = ll.offset + displacement
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metal_labels[metal_layer].append(
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(*offset, ll.string)
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)
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return polys, metal_labels
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def load_polys(
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cell: Pattern,
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layers: Sequence[layer_t],
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) -> defaultdict[layer_t, List[NDArray[numpy.float64]]]:
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"""
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Given a *flat* `masque.Pattern`, extract the polygon info into the format used by `snarl`.
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Args:
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cell: The `Pattern` object to extract from.
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layers: The layers to extract.
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Returns:
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`{layer0: [poly0, [(x0, y0), (x1, y1), ...], poly2, ...]}`
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`polys` structure usable by `snarl.trace_connectivity`.
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"""
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polys = defaultdict(list)
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for ss in cell.shapes:
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if ss.layer not in layers:
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continue
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assert(isinstance(ss, Polygon))
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if ss.repetition is None:
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displacements = [(0, 0)]
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else:
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displacements = ss.repetition.displacements
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for displacement in displacements:
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polys[ss.layer].append(
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ss.vertices + ss.offset + displacement
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)
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return polys
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