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4 Commits
76511b95e6
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7336545f07
Author | SHA1 | Date | |
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7336545f07 | |||
4e40e3f829 | |||
79f2088180 | |||
e89d912ce8 |
@ -21,6 +21,7 @@ Notes:
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"""
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"""
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from typing import IO, cast, Any
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from typing import IO, cast, Any
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from collections.abc import Iterable, Mapping, Callable
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from collections.abc import Iterable, Mapping, Callable
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from types import MappingProxyType
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import io
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import io
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import mmap
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import mmap
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import logging
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import logging
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@ -52,6 +53,8 @@ path_cap_map = {
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4: Path.Cap.SquareCustom,
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4: Path.Cap.SquareCustom,
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}
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}
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RO_EMPTY_DICT: Mapping[int, bytes] = MappingProxyType({})
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def rint_cast(val: ArrayLike) -> NDArray[numpy.int32]:
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def rint_cast(val: ArrayLike) -> NDArray[numpy.int32]:
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return numpy.rint(val).astype(numpy.int32)
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return numpy.rint(val).astype(numpy.int32)
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@ -399,11 +402,15 @@ def _mrefs_to_grefs(refs: dict[str | None, list[Ref]]) -> list[klamath.library.R
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return grefs
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return grefs
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def _properties_to_annotations(properties: dict[int, bytes]) -> annotations_t:
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def _properties_to_annotations(properties: Mapping[int, bytes]) -> annotations_t:
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if not properties:
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return None
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return {str(k): [v.decode()] for k, v in properties.items()}
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return {str(k): [v.decode()] for k, v in properties.items()}
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def _annotations_to_properties(annotations: annotations_t, max_len: int = 126) -> dict[int, bytes]:
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def _annotations_to_properties(annotations: annotations_t, max_len: int = 126) -> Mapping[int, bytes]:
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if annotations is None:
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return RO_EMPTY_DICT
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cum_len = 0
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cum_len = 0
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props = {}
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props = {}
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for key, vals in annotations.items():
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for key, vals in annotations.items():
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@ -1,5 +1,5 @@
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"""
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"""
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GDSII file format readers and writers using the `klamath` library.
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GDSII file format readers and writers using the `TODO` library.
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Note that GDSII references follow the same convention as `masque`,
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Note that GDSII references follow the same convention as `masque`,
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with this order of operations:
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with this order of operations:
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@ -18,6 +18,9 @@ Notes:
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* GDS does not support library- or structure-level annotations
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* GDS does not support library- or structure-level annotations
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* GDS creation/modification/access times are set to 1900-01-01 for reproducibility.
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* GDS creation/modification/access times are set to 1900-01-01 for reproducibility.
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* Gzip modification time is set to 0 (start of current epoch, usually 1970-01-01)
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* Gzip modification time is set to 0 (start of current epoch, usually 1970-01-01)
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TODO writing
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TODO warn on boxes, nodes
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"""
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"""
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from typing import IO, cast, Any
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from typing import IO, cast, Any
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from collections.abc import Iterable, Mapping, Callable
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from collections.abc import Iterable, Mapping, Callable
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@ -134,35 +137,76 @@ def read_arrow(
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cell_ids = libarr['cells'].values.field('id').to_numpy()
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cell_ids = libarr['cells'].values.field('id').to_numpy()
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cell_names = libarr['cell_names'].as_py()
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cell_names = libarr['cell_names'].as_py()
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bnd = libarr['cells'].values.field('boundaries')
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def get_geom(libarr: pyarrow.Array, geom_type: str) -> dict[str, Any]:
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boundary = dict(
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el = libarr['cells'].values.field(geom_type)
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offsets = bnd.offsets.to_numpy(),
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elem = dict(
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xy_arr = bnd.values.field('xy').values.to_numpy().reshape((-1, 2)),
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offsets = el.offsets.to_numpy(),
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xy_off = bnd.values.field('xy').offsets.to_numpy() // 2,
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xy_arr = el.values.field('xy').values.to_numpy().reshape((-1, 2)),
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layer_tups = layer_tups,
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xy_off = el.values.field('xy').offsets.to_numpy() // 2,
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layer_inds = bnd.values.field('layer').to_numpy(),
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layer_inds = el.values.field('layer').to_numpy(),
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prop_off = bnd.values.field('properties').offsets.to_numpy(),
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prop_off = el.values.field('properties').offsets.to_numpy(),
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prop_key = bnd.values.field('properties').values.field('key').to_numpy(),
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prop_key = el.values.field('properties').values.field('key').to_numpy(),
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prop_val = bnd.values.field('properties').values.field('value').to_pylist(),
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prop_val = el.values.field('properties').values.field('value').to_pylist(),
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)
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return elem
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rf = libarr['cells'].values.field('refs')
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refs = dict(
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offsets = rf.offsets.to_numpy(),
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targets = rf.values.field('target').to_numpy(),
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xy = rf.values.field('xy').to_numpy().view('i4').reshape((-1, 2)),
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invert_y = rf.values.field('invert_y').fill_null(False).to_numpy(zero_copy_only=False),
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angle_rad = numpy.rad2deg(rf.values.field('angle_deg').fill_null(0).to_numpy()),
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scale = rf.values.field('mag').fill_null(1).to_numpy(),
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rep_valid = rf.values.field('repetition').is_valid().to_numpy(zero_copy_only=False),
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rep_xy0 = rf.values.field('repetition').field('xy0').fill_null(0).to_numpy().view('i4').reshape((-1, 2)),
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rep_xy1 = rf.values.field('repetition').field('xy1').fill_null(0).to_numpy().view('i4').reshape((-1, 2)),
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rep_counts = rf.values.field('repetition').field('counts').fill_null(0).to_numpy().view('i2').reshape((-1, 2)),
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prop_off = rf.values.field('properties').offsets.to_numpy(),
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prop_key = rf.values.field('properties').values.field('key').to_numpy(),
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prop_val = rf.values.field('properties').values.field('value').to_pylist(),
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)
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)
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pth = libarr['cells'].values.field('boundaries')
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txt = libarr['cells'].values.field('texts')
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path = dict(
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texts = dict(
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offsets = pth.offsets.to_numpy(),
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offsets = txt.offsets.to_numpy(),
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xy_arr = pth.values.field('xy').values.to_numpy().reshape((-1, 2)),
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layer_inds = txt.values.field('layer').to_numpy(),
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xy_off = pth.values.field('xy').offsets.to_numpy() // 2,
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xy = txt.values.field('xy').to_numpy().view('i4').reshape((-1, 2)),
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layer_tups = layer_tups,
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string = txt.values.field('string').to_pylist(),
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layer_inds = pth.values.field('layer').to_numpy(),
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prop_off = txt.values.field('properties').offsets.to_numpy(),
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prop_off = pth.values.field('properties').offsets.to_numpy(),
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prop_key = txt.values.field('properties').values.field('key').to_numpy(),
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prop_key = pth.values.field('properties').values.field('key').to_numpy(),
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prop_val = txt.values.field('properties').values.field('value').to_pylist(),
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prop_val = pth.values.field('properties').values.field('value').to_pylist(),
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)
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)
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elements = dict(
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boundaries = get_geom(libarr, 'boundaries'),
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paths = get_geom(libarr, 'paths'),
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boxes = get_geom(libarr, 'boxes'),
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nodes = get_geom(libarr, 'nodes'),
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texts = texts,
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refs = refs,
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)
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paths = libarr['cells'].values.field('paths')
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elements['paths'].update(dict(
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width = paths.values.field('width').to_numpy(),
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path_type = paths.values.field('path_type').to_numpy(),
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extensions = numpy.stack((
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paths.values.field('extension_start').to_numpy(zero_copy_only=False),
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paths.values.field('extension_end').to_numpy(zero_copy_only=False),
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), axis=-1),
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))
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global_args = dict(
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cell_names = cell_names,
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layer_tups = layer_tups,
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raw_mode = raw_mode,
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)
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mlib = Library()
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mlib = Library()
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for cc, cell in enumerate(libarr['cells']):
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for cc, cell in enumerate(libarr['cells']):
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name = cell_names[cell_ids[cc]]
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name = cell_names[cell_ids[cc]]
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pat = read_cell(cc, cell, libarr['cell_names'], raw_mode=raw_mode, boundary=boundary)
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pat = read_cell(cc, cell, libarr['cell_names'], global_args=global_args, elements=elements)
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mlib[name] = pat
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mlib[name] = pat
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return mlib, library_info
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return mlib, library_info
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@ -184,8 +228,8 @@ def read_cell(
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cc: int,
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cc: int,
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cellarr: pyarrow.Array,
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cellarr: pyarrow.Array,
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cell_names: pyarrow.Array,
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cell_names: pyarrow.Array,
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boundary: dict[str, NDArray],
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elements: dict[str, Any],
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raw_mode: bool = True,
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global_args: dict[str, Any],
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) -> Pattern:
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) -> Pattern:
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"""
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"""
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TODO
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TODO
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@ -202,81 +246,96 @@ def read_cell(
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"""
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"""
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pat = Pattern()
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pat = Pattern()
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for refarr in cellarr['refs']:
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_boundaries_to_polygons(pat, global_args, elements['boundaries'], cc)
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target = cell_names[refarr['target'].as_py()].as_py()
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_gpaths_to_mpaths(pat, global_args, elements['paths'], cc)
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args = dict(
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_grefs_to_mrefs(pat, global_args, elements['refs'], cc)
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offset = (refarr['x'].as_py(), refarr['y'].as_py()),
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_texts_to_labels(pat, global_args, elements['texts'], cc)
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)
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if (mirr := refarr['invert_y']).is_valid:
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args['mirrored'] = mirr.as_py()
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if (rot := refarr['angle_deg']).is_valid:
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args['rotation'] = numpy.deg2rad(rot.as_py())
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if (mag := refarr['mag']).is_valid:
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args['scale'] = mag.as_py()
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if (rep := refarr['repetition']).is_valid:
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repetition = Grid(
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a_vector = (rep['x0'].as_py(), rep['y0'].as_py()),
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b_vector = (rep['x1'].as_py(), rep['y1'].as_py()),
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a_count = rep['count0'].as_py(),
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b_count = rep['count1'].as_py(),
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)
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args['repetition'] = repetition
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ref = Ref(**args)
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pat.refs[target].append(ref)
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_boundaries_to_polygons(pat, cellarr)
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for gpath in cellarr['paths']:
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layer = (gpath['layer'].as_py(),)
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args = dict(
|
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vertices = gpath['xy'].values.to_numpy().reshape((-1, 2)),
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offset = numpy.zeros(2),
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raw = raw_mode,
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)
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if (gcap := gpath['path_type']).is_valid:
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mcap = path_cap_map[gcap.as_py()]
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args['cap'] = mcap
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if mcap == Path.Cap.SquareCustom:
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extensions = [0, 0]
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if (ext0 := gpath['extension_start']).is_valid:
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extensions[0] = ext0.as_py()
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if (ext1 := gpath['extension_end']).is_valid:
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extensions[1] = ext1.as_py()
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|
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args['extensions'] = extensions
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if (width := gpath['width']).is_valid:
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args['width'] = width.as_py()
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else:
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args['width'] = 0
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|
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if (props := gpath['properties']).is_valid:
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args['annotations'] = _properties_to_annotations(props)
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|
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mpath = Path(**args)
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pat.shapes[layer].append(mpath)
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|
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for gtext in cellarr['texts']:
|
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layer = (gtext['layer'].as_py(),)
|
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args = dict(
|
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offset = (gtext['x'].as_py(), gtext['y'].as_py()),
|
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string = gtext['string'].as_py(),
|
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)
|
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|
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if (props := gtext['properties']).is_valid:
|
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args['annotations'] = _properties_to_annotations(props)
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|
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mlabel = Label(**args)
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pat.labels[layer].append(mlabel)
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|
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return pat
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return pat
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|
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|
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def _paths_to_paths(pat: Pattern, paths: dict[str, Any], cc: int) -> None:
|
def _grefs_to_mrefs(
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|
pat: Pattern,
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|
global_args: dict[str, Any],
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|
elem: dict[str, Any],
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|
cc: int,
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|
) -> None:
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|
cell_names = global_args['cell_names']
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|
elem_off = elem['offsets'] # which elements belong to each cell
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xy = elem['xy']
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prop_key = elem['prop_key']
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|
prop_val = elem['prop_val']
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targets = elem['targets']
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rep_valid = elem['rep_valid']
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|
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elem_count = elem_off[cc + 1] - elem_off[cc]
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elem_slc = slice(elem_off[cc], elem_off[cc] + elem_count + 1) # +1 to capture ending location for last elem
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prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
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|
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|
for ee in range(elem_count):
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|
target = cell_names[targets[ee]]
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|
offset = xy[ee]
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|
mirr = elem['invert_y'][ee]
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|
rot = elem['angle_rad'][ee]
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|
mag = elem['scale'][ee]
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|
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|
rep: None | Grid = None
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|
if rep_valid[ee]:
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|
a_vector = elem['rep_xy0'][ee]
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|
b_vector = elem['rep_xy1'][ee]
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|
a_count, b_count = elem['rep_counts'][ee]
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|
rep = Grid(a_vector=a_vector, b_vector=b_vector, a_count=a_count, b_count=b_count)
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|
|
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|
annotations: None | dict[int, str] = None
|
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|
prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
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|
if prop_ii < prop_ff:
|
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|
annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
|
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|
|
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|
ref = Ref(offset=offset, mirrored=mirr, rotation=rot, scale=mag, repetition=rep, annotations=annotations)
|
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|
pat.refs[target].append(ref)
|
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|
|
||||||
|
|
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|
def _texts_to_labels(
|
||||||
|
pat: Pattern,
|
||||||
|
global_args: dict[str, Any],
|
||||||
|
elem: dict[str, Any],
|
||||||
|
cc: int,
|
||||||
|
) -> None:
|
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|
elem_off = elem['offsets'] # which elements belong to each cell
|
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|
xy = elem['xy']
|
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|
layer_tups = global_args['layer_tups']
|
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|
layer_inds = elem['layer_inds']
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|
prop_key = elem['prop_key']
|
||||||
|
prop_val = elem['prop_val']
|
||||||
|
|
||||||
|
elem_count = elem_off[cc + 1] - elem_off[cc]
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|
elem_slc = slice(elem_off[cc], elem_off[cc] + elem_count + 1) # +1 to capture ending location for last elem
|
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|
prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
|
||||||
|
|
||||||
|
for ee in range(elem_count):
|
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|
layer = layer_tups[layer_inds[ee]]
|
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|
offset = xy[ee]
|
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|
string = elem['string'][ee]
|
||||||
|
|
||||||
|
annotations: None | dict[int, str] = None
|
||||||
|
prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
|
||||||
|
if prop_ii < prop_ff:
|
||||||
|
annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
|
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|
|
||||||
|
mlabel = Label(string=string, offset=offset, annotations=annotations)
|
||||||
|
pat.labels[layer].append(mlabel)
|
||||||
|
|
||||||
|
|
||||||
|
def _gpaths_to_mpaths(
|
||||||
|
pat: Pattern,
|
||||||
|
global_args: dict[str, Any],
|
||||||
|
elem: dict[str, Any],
|
||||||
|
cc: int,
|
||||||
|
) -> None:
|
||||||
elem_off = elem['offsets'] # which elements belong to each cell
|
elem_off = elem['offsets'] # which elements belong to each cell
|
||||||
xy_val = elem['xy_arr']
|
xy_val = elem['xy_arr']
|
||||||
layer_tups = elem['layer_tups']
|
layer_tups = global_args['layer_tups']
|
||||||
layer_inds = elem['layer_inds']
|
layer_inds = elem['layer_inds']
|
||||||
prop_key = elem['prop_key']
|
prop_key = elem['prop_key']
|
||||||
prop_val = elem['prop_val']
|
prop_val = elem['prop_val']
|
||||||
@ -287,42 +346,59 @@ def _paths_to_paths(pat: Pattern, paths: dict[str, Any], cc: int) -> None:
|
|||||||
prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
|
prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
|
||||||
|
|
||||||
zeros = numpy.zeros((elem_count, 2))
|
zeros = numpy.zeros((elem_count, 2))
|
||||||
|
raw_mode = global_args['raw_mode']
|
||||||
for ee in range(elem_count):
|
for ee in range(elem_count):
|
||||||
|
elem_ind = elem_off[cc] + ee
|
||||||
layer = layer_tups[layer_inds[ee]]
|
layer = layer_tups[layer_inds[ee]]
|
||||||
vertices = xy_val[xy_offs[ee]:xy_offs[ee + 1]]
|
vertices = xy_val[xy_offs[ee]:xy_offs[ee + 1]]
|
||||||
|
width = elem['width'][elem_ind]
|
||||||
|
cap_int = elem['path_type'][elem_ind]
|
||||||
|
cap = path_cap_map[cap_int]
|
||||||
|
if cap_int == 4:
|
||||||
|
cap_extensions = elem['extensions'][elem_ind]
|
||||||
|
else:
|
||||||
|
cap_extensions = None
|
||||||
|
|
||||||
|
annotations: None | dict[int, str] = None
|
||||||
prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
|
prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
|
||||||
if prop_ii < prop_ff:
|
if prop_ii < prop_ff:
|
||||||
ann = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
|
annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
|
||||||
args = dict(annotations = ann)
|
|
||||||
|
|
||||||
path = Polygon(vertices=vertices, offset=zeros[ee], raw=raw_mode)
|
path = Path(vertices=vertices, offset=zeros[ee], annotations=annotations, raw=raw_mode,
|
||||||
|
width=width, cap=cap,cap_extensions=cap_extensions)
|
||||||
pat.shapes[layer].append(path)
|
pat.shapes[layer].append(path)
|
||||||
|
|
||||||
|
|
||||||
def _boundaries_to_polygons(pat: Pattern, elem: dict[str, Any], cc: int) -> None:
|
def _boundaries_to_polygons(
|
||||||
|
pat: Pattern,
|
||||||
|
global_args: dict[str, Any],
|
||||||
|
elem: dict[str, Any],
|
||||||
|
cc: int,
|
||||||
|
) -> None:
|
||||||
elem_off = elem['offsets'] # which elements belong to each cell
|
elem_off = elem['offsets'] # which elements belong to each cell
|
||||||
xy_val = elem['xy_arr']
|
xy_val = elem['xy_arr']
|
||||||
layer_tups = elem['layer_tups']
|
layer_tups = global_args['layer_tups']
|
||||||
layer_inds = elem['layer_inds']
|
layer_inds = elem['layer_inds']
|
||||||
prop_key = elem['prop_key']
|
prop_key = elem['prop_key']
|
||||||
prop_val = elem['prop_val']
|
prop_val = elem['prop_val']
|
||||||
|
|
||||||
elem_slc = slice(elem_off[cc], elem_off[cc + 1] + 1)
|
elem_count = elem_off[cc + 1] - elem_off[cc]
|
||||||
|
elem_slc = slice(elem_off[cc], elem_off[cc] + elem_count + 1) # +1 to capture ending location for last elem
|
||||||
xy_offs = elem['xy_off'][elem_slc] # which xy coords belong to each element
|
xy_offs = elem['xy_off'][elem_slc] # which xy coords belong to each element
|
||||||
prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
|
prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
|
||||||
|
|
||||||
zeros = numpy.zeros((len(xy_offs) - 1, 2))
|
zeros = numpy.zeros((elem_count, 2))
|
||||||
for ee in range(len(xy_offs) - 1):
|
raw_mode = global_args['raw_mode']
|
||||||
|
for ee in range(elem_count):
|
||||||
layer = layer_tups[layer_inds[ee]]
|
layer = layer_tups[layer_inds[ee]]
|
||||||
vertices = xy_val[xy_offs[ee]:xy_offs[ee + 1] - 1] # -1 to drop closing point
|
vertices = xy_val[xy_offs[ee]:xy_offs[ee + 1] - 1] # -1 to drop closing point
|
||||||
|
|
||||||
|
annotations: None | dict[int, str] = None
|
||||||
prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
|
prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
|
||||||
if prop_ii < prop_ff:
|
if prop_ii < prop_ff:
|
||||||
ann = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
|
annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
|
||||||
args = dict(annotations = ann)
|
|
||||||
|
|
||||||
poly = Polygon(vertices=vertices, offset=zeros[ee], raw=raw_mode)
|
poly = Polygon(vertices=vertices, offset=zeros[ee], annotations=annotations, raw=raw_mode)
|
||||||
pat.shapes[layer].append(poly)
|
pat.shapes[layer].append(poly)
|
||||||
|
|
||||||
|
|
||||||
|
@ -671,6 +671,8 @@ def repetition_masq2fata(
|
|||||||
|
|
||||||
def annotations_to_properties(annotations: annotations_t) -> list[fatrec.Property]:
|
def annotations_to_properties(annotations: annotations_t) -> list[fatrec.Property]:
|
||||||
#TODO determine is_standard based on key?
|
#TODO determine is_standard based on key?
|
||||||
|
if annotations is None:
|
||||||
|
return []
|
||||||
properties = []
|
properties = []
|
||||||
for key, values in annotations.items():
|
for key, values in annotations.items():
|
||||||
vals = [AString(v) if isinstance(v, str) else v
|
vals = [AString(v) if isinstance(v, str) else v
|
||||||
|
@ -332,7 +332,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
|
|||||||
))
|
))
|
||||||
|
|
||||||
self.ports = dict(sorted(self.ports.items()))
|
self.ports = dict(sorted(self.ports.items()))
|
||||||
self.annotations = dict(sorted(self.annotations.items()))
|
self.annotations = dict(sorted(self.annotations.items())) if self.annotations is not None else None
|
||||||
|
|
||||||
return self
|
return self
|
||||||
|
|
||||||
@ -354,10 +354,13 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
|
|||||||
for layer, lseq in other_pattern.labels.items():
|
for layer, lseq in other_pattern.labels.items():
|
||||||
self.labels[layer].extend(lseq)
|
self.labels[layer].extend(lseq)
|
||||||
|
|
||||||
annotation_conflicts = set(self.annotations.keys()) & set(other_pattern.annotations.keys())
|
if other_pattern.annotations is not None:
|
||||||
if annotation_conflicts:
|
if self.annotations is None:
|
||||||
raise PatternError(f'Annotation keys overlap: {annotation_conflicts}')
|
self.annotations = {}
|
||||||
self.annotations.update(other_pattern.annotations)
|
annotation_conflicts = set(self.annotations.keys()) & set(other_pattern.annotations.keys())
|
||||||
|
if annotation_conflicts:
|
||||||
|
raise PatternError(f'Annotation keys overlap: {annotation_conflicts}')
|
||||||
|
self.annotations.update(other_pattern.annotations)
|
||||||
|
|
||||||
port_conflicts = set(self.ports.keys()) & set(other_pattern.ports.keys())
|
port_conflicts = set(self.ports.keys()) & set(other_pattern.ports.keys())
|
||||||
if port_conflicts:
|
if port_conflicts:
|
||||||
@ -415,7 +418,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
|
|||||||
elif default_keep:
|
elif default_keep:
|
||||||
pat.refs = copy.copy(self.refs)
|
pat.refs = copy.copy(self.refs)
|
||||||
|
|
||||||
if annotations is not None:
|
if annotations is not None and self.annotations is not None:
|
||||||
pat.annotations = {k: v for k, v in self.annotations.items() if annotations(k, v)}
|
pat.annotations = {k: v for k, v in self.annotations.items() if annotations(k, v)}
|
||||||
elif default_keep:
|
elif default_keep:
|
||||||
pat.annotations = copy.copy(self.annotations)
|
pat.annotations = copy.copy(self.annotations)
|
||||||
|
@ -5,7 +5,7 @@ from numpy import pi
|
|||||||
try:
|
try:
|
||||||
from numpy import trapezoid
|
from numpy import trapezoid
|
||||||
except ImportError:
|
except ImportError:
|
||||||
from numpy import trapz as trapezoid
|
from numpy import trapz as trapezoid # type:ignore
|
||||||
|
|
||||||
|
|
||||||
def bezier(
|
def bezier(
|
||||||
|
@ -5,7 +5,7 @@ from typing import Protocol
|
|||||||
|
|
||||||
|
|
||||||
layer_t = int | tuple[int, int] | str
|
layer_t = int | tuple[int, int] | str
|
||||||
annotations_t = dict[str, list[int | float | str]]
|
annotations_t = dict[str, list[int | float | str]] | None
|
||||||
|
|
||||||
|
|
||||||
class SupportsBool(Protocol):
|
class SupportsBool(Protocol):
|
||||||
|
Loading…
x
Reference in New Issue
Block a user