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19 commits

Author SHA1 Message Date
dc828cf5fc [wip] introduce BuildLibrary and make overlay first-class 2026-06-16 00:14:35 -07:00
e8e19a5a9b [wip] Rework load_libraryfile and LazyLibrary using overlays 2026-06-16 00:14:35 -07:00
058f210d31 [arrow] improve test coverage and error handling 2026-06-16 00:14:35 -07:00
1679deed4c [gdsii_arrow] remove non-raw-mode arrow option; fix gzip wrapper 2026-06-16 00:14:35 -07:00
3831cd4457 [svg] avoid mutating the original library 2026-06-16 00:14:35 -07:00
ab232879c4 [arrow] add lazy arrow reader 2026-06-16 00:14:35 -07:00
7941f01272 [shapes] move to per-shape purpose-built _from_raw constructors 2026-06-16 00:14:35 -07:00
3c457e8e0a [gdsii_arrow] more performance work 2026-06-16 00:14:35 -07:00
7398b1d560 [Polygon / PolyCollection] add raw constructors 2026-06-16 00:14:35 -07:00
c0f54fe585 [RectCollection] add a RectCollection shape 2026-06-16 00:14:35 -07:00
8b0eb2e83c enable annotations=None by default 2026-06-16 00:14:35 -07:00
08eb3c82d8 [gdsii_arrow] further improvements to speed 2026-06-16 00:14:35 -07:00
09d37724ae [Label / Ref / Grid] add raw constructors 2026-06-16 00:14:35 -07:00
9a8cfce03f [gdsii] add some profiling helpers 2026-06-16 00:14:35 -07:00
91454bbd8d [gdsii_arrow] misc correctness work 2026-06-16 00:14:35 -07:00
c19c820e1c add some missing deps 2026-06-16 00:14:35 -07:00
jan
bc727bec1b [gdsii_arrow] add gdsii_arrow 2026-06-16 00:14:35 -07:00
833f5dd159 [utils] add explicit spiral and circular arc helpers, and allow non-90deg bends 2026-06-16 00:14:24 -07:00
f4df8e0553 [utils] remove_duplicate_vertices now takes a tolerance (default exact) 2026-06-16 00:12:16 -07:00
38 changed files with 6619 additions and 414 deletions

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@ -0,0 +1,5 @@
from masque.file.gdsii_perf import main
if __name__ == '__main__':
raise SystemExit(main())

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@ -0,0 +1,131 @@
from __future__ import annotations
import argparse
import importlib
import json
import time
from pathlib import Path
from typing import Any
from masque import LibraryError
READERS: dict[str, tuple[str, tuple[str, ...]]] = {
'gdsii': ('masque.file.gdsii', ('readfile',)),
'gdsii_arrow': ('masque.file.gdsii_arrow', ('readfile', 'arrow_import', 'arrow_convert')),
}
def _summarize_library(path: Path, elapsed_s: float, info: dict[str, object], lib: object) -> dict[str, object]:
assert hasattr(lib, '__len__')
assert hasattr(lib, 'tops')
tops = lib.tops() # type: ignore[no-any-return, attr-defined]
try:
unique_top = lib.top() # type: ignore[no-any-return, attr-defined]
except LibraryError:
unique_top = None
return {
'path': str(path),
'elapsed_s': elapsed_s,
'library_name': info['name'],
'cell_count': len(lib), # type: ignore[arg-type]
'topcells': tops,
'topcell': unique_top,
}
def _summarize_arrow_import(path: Path, elapsed_s: float, arrow_arr: Any) -> dict[str, object]:
libarr = arrow_arr[0]
return {
'path': str(path),
'elapsed_s': elapsed_s,
'arrow_rows': len(arrow_arr),
'library_name': libarr['lib_name'].as_py(),
'cell_count': len(libarr['cells']),
'layer_count': len(libarr['layers']),
}
def _profile_stage(module: Any, stage: str, path: Path) -> dict[str, object]:
start = time.perf_counter()
if stage == 'readfile':
lib, info = module.readfile(path)
elapsed_s = time.perf_counter() - start
return _summarize_library(path, elapsed_s, info, lib)
if stage == 'arrow_import':
if hasattr(module, 'readfile_arrow'):
libarr, _info = module.readfile_arrow(path)
elapsed_s = time.perf_counter() - start
return {
'path': str(path),
'elapsed_s': elapsed_s,
'arrow_rows': 1,
'library_name': libarr['lib_name'].as_py(),
'cell_count': len(libarr['cells']),
'layer_count': len(libarr['layers']),
}
arrow_arr = module._read_to_arrow(path)
elapsed_s = time.perf_counter() - start
return _summarize_arrow_import(path, elapsed_s, arrow_arr)
if stage == 'arrow_convert':
arrow_arr = module._read_to_arrow(path)
libarr = arrow_arr[0]
start = time.perf_counter()
lib, info = module.read_arrow(libarr)
elapsed_s = time.perf_counter() - start
return _summarize_library(path, elapsed_s, info, lib)
raise ValueError(f'Unsupported stage {stage!r}')
def build_arg_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description='Profile GDS readers with a stable end-to-end workload.')
parser.add_argument('--reader', choices=sorted(READERS), required=True)
parser.add_argument('--stage', default='readfile')
parser.add_argument('--path', type=Path, required=True)
parser.add_argument('--warmup', type=int, default=1)
parser.add_argument('--repeat', type=int, default=1)
parser.add_argument('--output-json', type=Path)
return parser
def main(argv: list[str] | None = None) -> int:
parser = build_arg_parser()
args = parser.parse_args(argv)
module_name, stages = READERS[args.reader]
if args.stage not in stages:
parser.error(f'reader {args.reader!r} only supports stages: {", ".join(stages)}')
module = importlib.import_module(module_name)
path = args.path.expanduser().resolve()
for _ in range(args.warmup):
_profile_stage(module, args.stage, path)
runs = []
for _ in range(args.repeat):
runs.append(_profile_stage(module, args.stage, path))
payload = {
'reader': args.reader,
'stage': args.stage,
'warmup': args.warmup,
'repeat': args.repeat,
'runs': runs,
}
rendered = json.dumps(payload, indent=2, sort_keys=True)
if args.output_json is not None:
args.output_json.parent.mkdir(parents=True, exist_ok=True)
args.output_json.write_text(rendered + '\n')
print(rendered)
return 0
if __name__ == '__main__':
raise SystemExit(main())

View file

@ -20,10 +20,10 @@ Contents
* Use `Pather` to snap ports together into a circuit
* Check for dangling references
- [library](library.py)
* Continue from `devices.py` using a lazy library
* Create a `LazyLibrary`, which loads / generates patterns only when they are first used
* Continue from `devices.py` by declaring a mixed library with `BuildLibrary`
* Import source-backed GDS cells and register python-generated recipes together
* Call `build()` to produce a normal library for downstream `Pather` usage and writing
* Explore alternate ways of specifying a pattern for `.plug()` and `.place()`
* Design a pattern which is meant to plug into an existing pattern (via `.interface()`)
- [pather](pather.py)
* Use `Pather` to route individual wires and wire bundles
* Use `AutoTool` to generate paths

View file

@ -1,142 +1,114 @@
"""
Tutorial: using `LazyLibrary` and `Pather.interface()`.
Tutorial: authoring a mixed library with `BuildLibrary`.
This example assumes you have already read `devices.py` and generated the
`circuit.gds` file it writes. The goal here is not the photonic-crystal geometry
itself, but rather how Masque lets you mix lazily loaded GDS content with
python-generated devices inside one library.
itself, but rather how Masque lets you combine imported GDS cells with
python-generated recipes, then turn that declaration set into a normal library
for downstream assembly and writing.
"""
from typing import Any
from pprint import pformat
from masque import Pather, LazyLibrary
from masque.file.gdsii import writefile, load_libraryfile
from masque import BuildLibrary, Pather, Pattern, cell
from masque.file.gdsii import writefile
from masque.file.gdsii_lazy import readfile
import basic_shapes
import devices
from devices import data_to_ports
from basic_shapes import GDS_OPTS
def make_mixed_waveguide(lib: BuildLibrary) -> Pattern:
"""
Recipe which assembles imported and generated cells behind the builder API.
"""
circ = Pather(library=lib, ports='tri_l3cav')
# First way to specify what we are plugging in: request an explicit abstract.
circ.plug(lib.abstract('wg10'), {'input': 'right'})
# Second way: use an AbstractView, which behaves like a mapping of names
# to abstracts.
abstracts = lib.abstract_view()
circ.plug(abstracts['wg10'], {'output': 'left'})
# Third way: let Pather resolve a pattern name through its own library.
circ.plug('tri_wg10', {'input': 'right'})
circ.plug('tri_wg10', {'output': 'left'})
return circ.pattern
def main() -> None:
# A `LazyLibrary` delays work until a pattern is actually needed.
# That applies both to GDS cells we load from disk and to python callables
# that generate patterns on demand.
lib = LazyLibrary()
builder = BuildLibrary()
cells = builder.cells
#
# Load some devices from a GDS file
#
# Scan circuit.gds and prepare to lazy-load its contents
gds_lib, _properties = load_libraryfile('circuit.gds', postprocess=data_to_ports)
# Scan circuit.gds and prepare to lazy-load its contents. Port labels are
# imported on first materialization, but the raw source remains untouched
# until we build the final library.
gds_lib, _properties = readfile('circuit.gds')
builder.add_source(gds_lib.with_ports_from_data(layers=[(3, 0)], max_depth=1))
# Add those cells into our lazy library.
# Nothing is read yet; we are only registering how to fetch and postprocess
# each pattern when it is first requested.
lib.add(gds_lib)
print('Patterns loaded from GDS into library:\n' + pformat(list(lib.keys())))
print('Registered imported cells:\n' + pformat(list(gds_lib.keys())))
#
# Add some new devices to the library, this time from python code rather than GDS
# Register some new devices, this time from python code rather than GDS.
#
lib['triangle'] = lambda: basic_shapes.triangle(devices.RADIUS)
cells.triangle = basic_shapes.triangle(devices.RADIUS)
opts: dict[str, Any] = dict(
lattice_constant = devices.LATTICE_CONSTANT,
hole = 'triangle',
lattice_constant=devices.LATTICE_CONSTANT,
hole='triangle',
)
# Triangle-based variants. These lambdas are only recipes for building the
# patterns; they do not execute until someone asks for the cell.
lib['tri_wg10'] = lambda: devices.waveguide(length=10, mirror_periods=5, **opts)
lib['tri_wg05'] = lambda: devices.waveguide(length=5, mirror_periods=5, **opts)
lib['tri_wg28'] = lambda: devices.waveguide(length=28, mirror_periods=5, **opts)
lib['tri_bend0'] = lambda: devices.bend(mirror_periods=5, **opts)
lib['tri_ysplit'] = lambda: devices.y_splitter(mirror_periods=5, **opts)
lib['tri_l3cav'] = lambda: devices.perturbed_l3(xy_size=(4, 10), **opts, hole_lib=lib)
cells.tri_wg10 = cell(devices.waveguide)(length=10, mirror_periods=5, **opts)
cells.tri_wg05 = cell(devices.waveguide)(length=5, mirror_periods=5, **opts)
cells.tri_wg28 = cell(devices.waveguide)(length=28, mirror_periods=5, **opts)
cells.tri_bend0 = cell(devices.bend)(mirror_periods=5, **opts)
cells.tri_ysplit = cell(devices.y_splitter)(mirror_periods=5, **opts)
cells.tri_l3cav = cell(devices.perturbed_l3)(xy_size=(4, 10), **opts, hole_lib=builder)
cells.mixed_wg_cav = cell(make_mixed_waveguide)(builder)
print('Declared cells waiting to be built:\n' + pformat(list(builder.keys())))
#
# Build a mixed waveguide with an L3 cavity in the middle
# Build the declaration set into a normal library.
#
# Start a new design by copying the ports from an existing library cell.
# This gives `circ2` the same external interface as `tri_l3cav`.
circ2 = Pather(library=lib, ports='tri_l3cav')
# First way to specify what we are plugging in: request an explicit abstract.
# This works with `Pattern` methods directly as well as with `Pather`.
circ2.plug(lib.abstract('wg10'), {'input': 'right'})
# Second way: use an `AbstractView`, which behaves like a mapping of names
# to abstracts.
abstracts = lib.abstract_view()
circ2.plug(abstracts['wg10'], {'output': 'left'})
# Third way: let `Pather` resolve a pattern name through its own library.
# This shorthand is convenient, but it is specific to helpers that already
# carry a library reference.
circ2.plug('tri_wg10', {'input': 'right'})
circ2.plug('tri_wg10', {'output': 'left'})
# Add the circuit to the device library.
lib['mixed_wg_cav'] = circ2.pattern
built = builder.build()
print('Built library contains:\n' + pformat(list(built.keys())))
#
# Build a second device that is explicitly designed to mate with `circ2`.
# Continue designing against the built library.
#
# `Pather.interface()` makes a new pattern whose ports mirror an existing
# design's external interface. That is useful when you want to design an
# adapter, continuation, or mating structure.
circ3 = Pather.interface(source=circ2)
# Continue routing outward from those inherited ports.
circ3.plug('tri_bend0', {'input': 'right'})
circ3.plug('tri_bend0', {'input': 'left'}, mirrored=True) # mirror since no tri y-symmetry
circ3.plug('tri_bend0', {'input': 'right'})
circ3.plug('bend0', {'output': 'left'})
circ3.plug('bend0', {'output': 'left'})
circ3.plug('bend0', {'output': 'left'})
circ3.plug('tri_wg10', {'input': 'right'})
circ3.plug('tri_wg28', {'input': 'right'})
circ3.plug('tri_wg10', {'input': 'right', 'output': 'left'})
lib['loop_segment'] = circ3.pattern
# The built result behaves like a normal mutable library, so downstream code
# can use Pather, abstract views, and writing without going back through the
# builder interface.
circ = Pather.interface(source='mixed_wg_cav', library=built)
circ.plug('tri_bend0', {'input': 'right'})
circ.plug('tri_bend0', {'input': 'left'}, mirrored=True) # mirror since no tri y-symmetry
circ.plug('tri_bend0', {'input': 'right'})
circ.plug('bend0', {'output': 'left'})
circ.plug('bend0', {'output': 'left'})
circ.plug('bend0', {'output': 'left'})
circ.plug('tri_wg10', {'input': 'right'})
circ.plug('tri_wg28', {'input': 'right'})
circ.plug('tri_wg10', {'input': 'right', 'output': 'left'})
built['loop_segment'] = circ.pattern
#
# Write all devices into a GDS file
# Write all devices into a GDS file.
#
print('Writing library to file...')
writefile(lib, 'library.gds', **GDS_OPTS)
writefile(built, 'library.gds', **GDS_OPTS)
if __name__ == '__main__':
main()
#
#class prout:
# def place(
# self,
# other: Pattern,
# label_layer: layer_t = 'WATLAYER',
# *,
# port_map: Dict[str, str | None] | None = None,
# **kwargs,
# ) -> 'prout':
#
# Pattern.place(self, other, port_map=port_map, **kwargs)
# name: str | None
# for name in other.ports:
# if port_map:
# assert(name is not None)
# name = port_map.get(name, name)
# if name is None:
# continue
# self.pattern.label(string=name, offset=self.ports[name].offset, layer=label_layer)
# return self
#

View file

@ -42,6 +42,7 @@ from .error import (
from .shapes import (
Shape as Shape,
Polygon as Polygon,
RectCollection as RectCollection,
Path as Path,
Circle as Circle,
Arc as Arc,
@ -62,10 +63,15 @@ from .library import (
ILibrary as ILibrary,
LibraryView as LibraryView,
Library as Library,
BuiltLibrary as BuiltLibrary,
BuildLibrary as BuildLibrary,
BuildReport as BuildReport,
CellProvenance as CellProvenance,
LazyLibrary as LazyLibrary,
AbstractView as AbstractView,
TreeView as TreeView,
Tree as Tree,
cell as cell,
)
from .ports import (
Port as Port,

View file

@ -22,8 +22,6 @@ Notes:
from typing import IO, cast, Any
from collections.abc import Iterable, Mapping, Callable
from types import MappingProxyType
import io
import mmap
import logging
import pathlib
import gzip
@ -37,10 +35,10 @@ from klamath import records
from .utils import is_gzipped, tmpfile
from .. import Pattern, Ref, PatternError, LibraryError, Label, Shape
from ..shapes import Polygon, Path
from ..shapes import Polygon, Path, RectCollection
from ..repetition import Grid
from ..utils import layer_t, annotations_t
from ..library import LazyLibrary, Library, ILibrary, ILibraryView
from ..library import Library, ILibrary
logger = logging.getLogger(__name__)
@ -323,26 +321,40 @@ def _gpath_to_mpath(gpath: klamath.library.Path, raw_mode: bool) -> tuple[layer_
else:
raise PatternError(f'Unrecognized path type: {gpath.path_type}')
mpath = Path(
vertices=gpath.xy.astype(float),
vertices = gpath.xy.astype(float)
annotations = _properties_to_annotations(gpath.properties)
cap_extensions = None
if cap == Path.Cap.SquareCustom:
cap_extensions = numpy.asarray(gpath.extension, dtype=float)
if raw_mode:
mpath = Path._from_raw(
vertices=vertices,
width=gpath.width,
cap=cap,
offset=numpy.zeros(2),
annotations=_properties_to_annotations(gpath.properties),
raw=raw_mode,
cap_extensions=cap_extensions,
annotations=annotations,
)
else:
mpath = Path(
vertices=vertices,
width=gpath.width,
cap=cap,
cap_extensions=cap_extensions,
offset=numpy.zeros(2),
annotations=annotations,
)
if cap == Path.Cap.SquareCustom:
mpath.cap_extensions = gpath.extension
return gpath.layer, mpath
def _boundary_to_polygon(boundary: klamath.library.Boundary, raw_mode: bool) -> tuple[layer_t, Polygon]:
return boundary.layer, Polygon(
vertices=boundary.xy[:-1].astype(float),
offset=numpy.zeros(2),
annotations=_properties_to_annotations(boundary.properties),
raw=raw_mode,
)
vertices = boundary.xy[:-1].astype(float)
annotations = _properties_to_annotations(boundary.properties)
if raw_mode:
poly = Polygon._from_raw(vertices=vertices, annotations=annotations)
else:
poly = Polygon(vertices=vertices, offset=numpy.zeros(2), annotations=annotations)
return boundary.layer, poly
def _mrefs_to_grefs(refs: dict[str | None, list[Ref]]) -> list[klamath.library.Reference]:
@ -466,6 +478,20 @@ def _shapes_to_elements(
properties=properties,
)
elements.append(path)
elif isinstance(shape, RectCollection):
for rect in shape.rects:
xy_closed = numpy.empty((5, 2), dtype=numpy.int32)
xy_closed[0] = rint_cast((rect[0], rect[1]))
xy_closed[1] = rint_cast((rect[0], rect[3]))
xy_closed[2] = rint_cast((rect[2], rect[3]))
xy_closed[3] = rint_cast((rect[2], rect[1]))
xy_closed[4] = xy_closed[0]
boundary = klamath.elements.Boundary(
layer=(layer, data_type),
xy=xy_closed,
properties=properties,
)
elements.append(boundary)
elif isinstance(shape, Polygon):
polygon = shape
xy_closed = numpy.empty((polygon.vertices.shape[0] + 1, 2), dtype=numpy.int32)
@ -514,117 +540,6 @@ def _labels_to_texts(labels: dict[layer_t, list[Label]]) -> list[klamath.element
return texts
def load_library(
stream: IO[bytes],
*,
full_load: bool = False,
postprocess: Callable[[ILibraryView, str, Pattern], Pattern] | None = None
) -> tuple[LazyLibrary, dict[str, Any]]:
"""
Scan a GDSII stream to determine what structures are present, and create
a library from them. This enables deferred reading of structures
on an as-needed basis.
All structures are loaded as secondary
Args:
stream: Seekable stream. Position 0 should be the start of the file.
The caller should leave the stream open while the library
is still in use, since the library will need to access it
in order to read the structure contents.
full_load: If True, force all structures to be read immediately rather
than as-needed. Since data is read sequentially from the file, this
will be faster than using the resulting library's `precache` method.
postprocess: If given, this function is used to post-process each
pattern *upon first load only*.
Returns:
LazyLibrary object, allowing for deferred load of structures.
Additional library info (dict, same format as from `read`).
"""
stream.seek(0)
lib = LazyLibrary()
if full_load:
# Full load approach (immediately load everything)
patterns, library_info = read(stream)
for name, pattern in patterns.items():
if postprocess is not None:
lib[name] = postprocess(lib, name, pattern)
else:
lib[name] = pattern
return lib, library_info
# Normal approach (scan and defer load)
library_info = _read_header(stream)
structs = klamath.library.scan_structs(stream)
for name_bytes, pos in structs.items():
name = name_bytes.decode('ASCII')
def mkstruct(pos: int = pos, name: str = name) -> Pattern:
stream.seek(pos)
pat = read_elements(stream, raw_mode=True)
if postprocess is not None:
pat = postprocess(lib, name, pat)
return pat
lib[name] = mkstruct
return lib, library_info
def load_libraryfile(
filename: str | pathlib.Path,
*,
use_mmap: bool = True,
full_load: bool = False,
postprocess: Callable[[ILibraryView, str, Pattern], Pattern] | None = None
) -> tuple[LazyLibrary, dict[str, Any]]:
"""
Wrapper for `load_library()` that takes a filename or path instead of a stream.
Will automatically decompress the file if it is gzipped.
NOTE that any streams/mmaps opened will remain open until ALL of the
`PatternGenerator` objects in the library are garbage collected.
Args:
path: filename or path to read from
use_mmap: If `True`, will attempt to memory-map the file instead
of buffering. In the case of gzipped files, the file
is decompressed into a python `bytes` object in memory
and reopened as an `io.BytesIO` stream.
full_load: If `True`, immediately loads all data. See `load_library`.
postprocess: Passed to `load_library`
Returns:
LazyLibrary object, allowing for deferred load of structures.
Additional library info (dict, same format as from `read`).
"""
path = pathlib.Path(filename)
stream: IO[bytes]
if is_gzipped(path):
if use_mmap:
logger.info('Asked to mmap a gzipped file, reading into memory instead...')
gz_stream = gzip.open(path, mode='rb') # noqa: SIM115
stream = io.BytesIO(gz_stream.read()) # type: ignore
else:
gz_stream = gzip.open(path, mode='rb') # noqa: SIM115
stream = io.BufferedReader(gz_stream) # type: ignore
else: # noqa: PLR5501
if use_mmap:
base_stream = path.open(mode='rb', buffering=0) # noqa: SIM115
stream = mmap.mmap(base_stream.fileno(), 0, access=mmap.ACCESS_READ) # type: ignore
else:
stream = path.open(mode='rb') # noqa: SIM115
try:
return load_library(stream, full_load=full_load, postprocess=postprocess)
finally:
if full_load:
stream.close()
def check_valid_names(
names: Iterable[str],
max_length: int = 32,

882
masque/file/gdsii_arrow.py Normal file
View file

@ -0,0 +1,882 @@
# ruff: noqa: ARG001, F401
"""
GDSII file format readers and writers using the `TODO` library.
Note that GDSII references follow the same convention as `masque`,
with this order of operations:
1. Mirroring
2. Rotation
3. Scaling
4. Offset and array expansion (no mirroring/rotation/scaling applied to offsets)
Scaling, rotation, and mirroring apply to individual instances, not grid
vectors or offsets.
Notes:
* absolute positioning is not supported
* PLEX is not supported
* ELFLAGS are not supported
* GDS does not support library- or structure-level annotations
* GDS creation/modification/access times are set to 1900-01-01 for reproducibility.
* Gzip modification time is set to 0 (start of current epoch, usually 1970-01-01)
TODO writing
TODO warn on boxes, nodes
"""
from typing import IO, cast, Any
from collections.abc import Iterable, Mapping, Callable
from importlib.machinery import EXTENSION_SUFFIXES
import importlib.util
import mmap
import logging
import os
import pathlib
import gzip
import string
import sys
import tempfile
from pprint import pformat
from klamath.basic import KlamathError
import numpy
from numpy.typing import ArrayLike, NDArray
import pyarrow
from pyarrow.cffi import ffi
from .utils import is_gzipped, tmpfile
from .. import Pattern, Ref, PatternError, LibraryError, Label, Shape
from ..shapes import Polygon, Path, PolyCollection, RectCollection
from ..repetition import Grid
from ..utils import layer_t, annotations_t
from ..library import LazyLibrary, Library, ILibrary, ILibraryView
logger = logging.getLogger(__name__)
ffi.cdef(
"""
const char* last_error_message(void);
int read_path(const char* path, struct ArrowArray* array, struct ArrowSchema* schema);
int scan_bytes(uint8_t* data, size_t size, struct ArrowArray* array, struct ArrowSchema* schema);
int read_cells_bytes(
uint8_t* data,
size_t size,
uint64_t* ranges,
size_t range_count,
struct ArrowArray* array,
struct ArrowSchema* schema
);
"""
)
clib: Any | None = None
path_cap_map = {
0: Path.Cap.Flush,
1: Path.Cap.Circle,
2: Path.Cap.Square,
4: Path.Cap.SquareCustom,
}
def rint_cast(val: ArrayLike) -> NDArray[numpy.int32]:
return numpy.rint(val).astype(numpy.int32)
def _packed_layer_u32_to_pairs(values: NDArray[numpy.unsignedinteger[Any]]) -> NDArray[numpy.int16]:
layer = (values >> numpy.uint32(16)).astype(numpy.uint16).view(numpy.int16)
dtype = (values & numpy.uint32(0xffff)).astype(numpy.uint16).view(numpy.int16)
return numpy.stack((layer, dtype), axis=-1)
def _packed_counts_u32_to_pairs(values: NDArray[numpy.unsignedinteger[Any]]) -> NDArray[numpy.int64]:
a_count = (values >> numpy.uint32(16)).astype(numpy.uint16).astype(numpy.int64)
b_count = (values & numpy.uint32(0xffff)).astype(numpy.uint16).astype(numpy.int64)
return numpy.stack((a_count, b_count), axis=-1)
def _packed_xy_u64_to_pairs(values: NDArray[numpy.unsignedinteger[Any]]) -> NDArray[numpy.int32]:
xx = (values >> numpy.uint64(32)).astype(numpy.uint32).view(numpy.int32)
yy = (values & numpy.uint64(0xffff_ffff)).astype(numpy.uint32).view(numpy.int32)
return numpy.stack((xx, yy), axis=-1)
def _local_library_filename() -> str:
if sys.platform.startswith('linux'):
return 'libklamath_rs_ext.so'
if sys.platform == 'darwin':
return 'libklamath_rs_ext.dylib'
if sys.platform == 'win32':
return 'klamath_rs_ext.dll'
raise OSError(f'Unsupported platform for klamath_rs_ext: {sys.platform!r}')
def _installed_library_candidates() -> list[pathlib.Path]:
candidates: list[pathlib.Path] = []
try:
spec = importlib.util.find_spec('klamath_rs_ext.klamath_rs_ext')
except ModuleNotFoundError:
spec = None
if spec is not None and spec.origin is not None:
candidates.append(pathlib.Path(spec.origin))
try:
pkg_spec = importlib.util.find_spec('klamath_rs_ext')
except ModuleNotFoundError:
pkg_spec = None
if pkg_spec is not None and pkg_spec.submodule_search_locations is not None:
for location in pkg_spec.submodule_search_locations:
pkg_dir = pathlib.Path(location)
for suffix in EXTENSION_SUFFIXES:
candidates.extend(sorted(pkg_dir.glob(f'klamath_rs_ext*{suffix}')))
return candidates
def _repo_library_candidates() -> list[pathlib.Path]:
repo_root = pathlib.Path(__file__).resolve().parents[2]
library_name = _local_library_filename()
return [
repo_root / 'klamath-rs' / 'target' / 'release' / library_name,
repo_root / 'klamath-rs' / 'target' / 'debug' / library_name,
]
def find_klamath_rs_library() -> pathlib.Path | None:
env_path = os.environ.get('KLAMATH_RS_EXT_LIB')
if env_path:
candidate = pathlib.Path(env_path).expanduser()
if candidate.exists():
return candidate.resolve()
seen: set[pathlib.Path] = set()
for candidate in _installed_library_candidates() + _repo_library_candidates():
resolved = candidate.expanduser()
if resolved in seen:
continue
seen.add(resolved)
if resolved.exists():
return resolved.resolve()
return None
def is_available() -> bool:
return find_klamath_rs_library() is not None
def _get_clib() -> Any:
global clib
if clib is None:
lib_path = find_klamath_rs_library()
if lib_path is None:
raise ImportError(
'Could not locate klamath_rs_ext shared library. '
'Build klamath-rs with `cargo build --release --manifest-path klamath-rs/Cargo.toml` '
'or set KLAMATH_RS_EXT_LIB to the built library path.'
)
clib = ffi.dlopen(str(lib_path))
return clib
def _read_annotations(
prop_offs: NDArray[numpy.integer[Any]],
prop_key: NDArray[numpy.integer[Any]],
prop_val: list[str],
ee: int,
) -> annotations_t:
prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
if prop_ii >= prop_ff:
return None
return {str(prop_key[off]): [prop_val[off]] for off in range(prop_ii, prop_ff)}
def _read_to_arrow(
filename: str | pathlib.Path,
) -> pyarrow.Array:
path = pathlib.Path(filename).expanduser().resolve()
ptr_array = ffi.new('struct ArrowArray[]', 1)
ptr_schema = ffi.new('struct ArrowSchema[]', 1)
if is_gzipped(path):
with gzip.open(path, mode='rb') as src:
data = src.read()
with tempfile.NamedTemporaryFile(suffix='.gds', delete=False) as tmp_stream:
tmp_stream.write(data)
tmp_name = tmp_stream.name
try:
_call_native(_get_clib().read_path(tmp_name.encode(), ptr_array, ptr_schema), 'read_path')
finally:
pathlib.Path(tmp_name).unlink(missing_ok=True)
else:
_call_native(_get_clib().read_path(str(path).encode(), ptr_array, ptr_schema), 'read_path')
return _import_arrow_array(ptr_array, ptr_schema)
def _import_arrow_array(ptr_array: Any, ptr_schema: Any) -> pyarrow.Array:
iptr_schema = int(ffi.cast('uintptr_t', ptr_schema))
iptr_array = int(ffi.cast('uintptr_t', ptr_array))
return pyarrow.Array._import_from_c(iptr_array, iptr_schema)
def _call_native(status: int, action: str) -> None:
if status == 0:
return
err_ptr = _get_clib().last_error_message()
if err_ptr == ffi.NULL:
raise KlamathError(f'{action} failed')
message = ffi.string(err_ptr).decode(errors='replace')
raise KlamathError(message)
def _scan_buffer_to_arrow(buffer: bytes | mmap.mmap | memoryview) -> pyarrow.Array:
ptr_array = ffi.new('struct ArrowArray[]', 1)
ptr_schema = ffi.new('struct ArrowSchema[]', 1)
buf_view = memoryview(buffer)
cbuf = ffi.from_buffer('uint8_t[]', buf_view)
_call_native(_get_clib().scan_bytes(cbuf, len(buf_view), ptr_array, ptr_schema), 'scan_bytes')
return _import_arrow_array(ptr_array, ptr_schema)
def _read_selected_cells_to_arrow(
buffer: bytes | mmap.mmap | memoryview,
ranges: NDArray[numpy.uint64],
) -> pyarrow.Array:
ptr_array = ffi.new('struct ArrowArray[]', 1)
ptr_schema = ffi.new('struct ArrowSchema[]', 1)
buf_view = memoryview(buffer)
cbuf = ffi.from_buffer('uint8_t[]', buf_view)
flat_ranges = numpy.require(ranges, dtype=numpy.uint64, requirements=('C_CONTIGUOUS', 'ALIGNED'))
cranges = ffi.from_buffer('uint64_t[]', flat_ranges)
_call_native(
_get_clib().read_cells_bytes(cbuf, len(buf_view), cranges, int(flat_ranges.shape[0]), ptr_array, ptr_schema),
'read_cells_bytes',
)
return _import_arrow_array(ptr_array, ptr_schema)
def readfile(
filename: str | pathlib.Path,
) -> tuple[Library, dict[str, Any]]:
"""
Read a GDSII file from a path into `masque.Library` / `Pattern` objects.
Will automatically decompress gzipped files.
Args:
filename: Filename to read.
For callers that can consume Arrow directly, prefer `readfile_arrow()`
to skip Python `Pattern` construction entirely.
"""
arrow_arr = _read_to_arrow(filename)
assert len(arrow_arr) == 1
results = read_arrow(arrow_arr[0])
return results
def readfile_arrow(
filename: str | pathlib.Path,
) -> tuple[pyarrow.StructScalar, dict[str, Any]]:
"""
Read a GDSII file into the native Arrow representation without converting
it into `masque.Library` / `Pattern` objects.
This is the lowest-overhead public read path exposed by this module.
Args:
filename: Filename to read.
Returns:
- Arrow struct scalar for the library payload
- dict of GDSII library info
"""
arrow_arr = _read_to_arrow(filename)
assert len(arrow_arr) == 1
libarr = arrow_arr[0]
return libarr, _read_header(libarr)
def read_arrow(
libarr: pyarrow.Array,
) -> tuple[Library, dict[str, Any]]:
"""
# TODO check GDSII file for cycles!
Read a gdsii file and translate it into a dict of Pattern objects. GDSII structures are
translated into Pattern objects; boundaries are translated into polygons, and srefs and arefs
are translated into Ref objects.
Additional library info is returned in a dict, containing:
'name': name of the library
'meters_per_unit': number of meters per database unit (all values are in database units)
'logical_units_per_unit': number of "logical" units displayed by layout tools (typically microns)
per database unit
Args:
libarr: Arrow library payload as returned by `readfile_arrow()`.
Returns:
- dict of pattern_name:Patterns generated from GDSII structures
- dict of GDSII library info
"""
library_info = _read_header(libarr)
layer_names_np = _packed_layer_u32_to_pairs(libarr['layers'].values.to_numpy())
layer_tups = [(int(pair[0]), int(pair[1])) for pair in layer_names_np]
cell_ids = libarr['cells'].values.field('id').to_numpy()
cell_names = libarr['cell_names'].as_py()
def get_geom(libarr: pyarrow.Array, geom_type: str) -> dict[str, Any]:
el = libarr['cells'].values.field(geom_type)
elem = dict(
offsets = el.offsets.to_numpy(),
xy_arr = el.values.field('xy').values.to_numpy().reshape((-1, 2)),
xy_off = el.values.field('xy').offsets.to_numpy() // 2,
layer_inds = el.values.field('layer').to_numpy(),
prop_off = el.values.field('properties').offsets.to_numpy(),
prop_key = el.values.field('properties').values.field('key').to_numpy(),
prop_val = el.values.field('properties').values.field('value').to_pylist(),
)
return elem
def get_boundary_batches(libarr: pyarrow.Array) -> dict[str, Any]:
batches = libarr['cells'].values.field('boundary_batches')
return dict(
offsets = batches.offsets.to_numpy(),
layer_inds = batches.values.field('layer').to_numpy(),
vert_arr = batches.values.field('vertices').values.to_numpy().reshape((-1, 2)),
vert_off = batches.values.field('vertices').offsets.to_numpy() // 2,
poly_off = batches.values.field('vertex_offsets').offsets.to_numpy(),
poly_offsets = batches.values.field('vertex_offsets').values.to_numpy(),
)
def get_rect_batches(libarr: pyarrow.Array) -> dict[str, Any]:
batches = libarr['cells'].values.field('rect_batches')
return dict(
offsets = batches.offsets.to_numpy(),
layer_inds = batches.values.field('layer').to_numpy(),
rect_arr = batches.values.field('rects').values.to_numpy().reshape((-1, 4)),
rect_off = batches.values.field('rects').offsets.to_numpy() // 4,
)
def get_boundary_props(libarr: pyarrow.Array) -> dict[str, Any]:
boundaries = libarr['cells'].values.field('boundary_props')
return dict(
offsets = boundaries.offsets.to_numpy(),
layer_inds = boundaries.values.field('layer').to_numpy(),
vert_arr = boundaries.values.field('vertices').values.to_numpy().reshape((-1, 2)),
vert_off = boundaries.values.field('vertices').offsets.to_numpy() // 2,
prop_off = boundaries.values.field('properties').offsets.to_numpy(),
prop_key = boundaries.values.field('properties').values.field('key').to_numpy(),
prop_val = boundaries.values.field('properties').values.field('value').to_pylist(),
)
def get_refs(libarr: pyarrow.Array, geom_type: str, has_repetition: bool) -> dict[str, Any]:
refs = libarr['cells'].values.field(geom_type)
values = refs.values
elem = dict(
offsets = refs.offsets.to_numpy(),
targets = values.field('target').to_numpy(),
xy = _packed_xy_u64_to_pairs(values.field('xy').to_numpy()),
invert_y = values.field('invert_y').to_numpy(zero_copy_only=False),
angle_rad = values.field('angle_rad').to_numpy(),
scale = values.field('scale').to_numpy(),
)
if has_repetition:
elem.update(dict(
xy0 = _packed_xy_u64_to_pairs(values.field('xy0').to_numpy()),
xy1 = _packed_xy_u64_to_pairs(values.field('xy1').to_numpy()),
counts = _packed_counts_u32_to_pairs(values.field('counts').to_numpy()),
))
return elem
def get_ref_props(libarr: pyarrow.Array, geom_type: str, has_repetition: bool) -> dict[str, Any]:
refs = libarr['cells'].values.field(geom_type)
values = refs.values
elem = dict(
offsets = refs.offsets.to_numpy(),
targets = values.field('target').to_numpy(),
xy = _packed_xy_u64_to_pairs(values.field('xy').to_numpy()),
invert_y = values.field('invert_y').to_numpy(zero_copy_only=False),
angle_rad = values.field('angle_rad').to_numpy(),
scale = values.field('scale').to_numpy(),
prop_off = values.field('properties').offsets.to_numpy(),
prop_key = values.field('properties').values.field('key').to_numpy(),
prop_val = values.field('properties').values.field('value').to_pylist(),
)
if has_repetition:
elem.update(dict(
xy0 = _packed_xy_u64_to_pairs(values.field('xy0').to_numpy()),
xy1 = _packed_xy_u64_to_pairs(values.field('xy1').to_numpy()),
counts = _packed_counts_u32_to_pairs(values.field('counts').to_numpy()),
))
return elem
txt = libarr['cells'].values.field('texts')
texts = dict(
offsets = txt.offsets.to_numpy(),
layer_inds = txt.values.field('layer').to_numpy(),
xy = _packed_xy_u64_to_pairs(txt.values.field('xy').to_numpy()),
string = txt.values.field('string').to_pylist(),
prop_off = txt.values.field('properties').offsets.to_numpy(),
prop_key = txt.values.field('properties').values.field('key').to_numpy(),
prop_val = txt.values.field('properties').values.field('value').to_pylist(),
)
elements = dict(
srefs = get_refs(libarr, 'srefs', has_repetition=False),
arefs = get_refs(libarr, 'arefs', has_repetition=True),
sref_props = get_ref_props(libarr, 'sref_props', has_repetition=False),
aref_props = get_ref_props(libarr, 'aref_props', has_repetition=True),
rect_batches = get_rect_batches(libarr),
boundary_batches = get_boundary_batches(libarr),
boundary_props = get_boundary_props(libarr),
paths = get_geom(libarr, 'paths'),
texts = texts,
)
paths = libarr['cells'].values.field('paths')
elements['paths'].update(dict(
width = paths.values.field('width').fill_null(0).to_numpy(),
path_type = paths.values.field('path_type').fill_null(0).to_numpy(),
extensions = numpy.stack((
paths.values.field('extension_start').fill_null(0).to_numpy(),
paths.values.field('extension_end').fill_null(0).to_numpy(),
), axis=-1),
))
global_args = dict(
cell_names = cell_names,
layer_tups = layer_tups,
)
mlib = Library()
for cc in range(len(libarr['cells'])):
name = cell_names[int(cell_ids[cc])]
pat = Pattern()
_rect_batches_to_rectcollections(pat, global_args, elements['rect_batches'], cc)
_boundary_batches_to_polygons(pat, global_args, elements['boundary_batches'], cc)
_boundary_props_to_polygons(pat, global_args, elements['boundary_props'], cc)
_gpaths_to_mpaths(pat, global_args, elements['paths'], cc)
_srefs_to_mrefs(pat, global_args, elements['srefs'], cc)
_arefs_to_mrefs(pat, global_args, elements['arefs'], cc)
_sref_props_to_mrefs(pat, global_args, elements['sref_props'], cc)
_aref_props_to_mrefs(pat, global_args, elements['aref_props'], cc)
_texts_to_labels(pat, global_args, elements['texts'], cc)
mlib[name] = pat
return mlib, library_info
def _read_header(libarr: pyarrow.Array) -> dict[str, Any]:
"""
Read the file header and create the library_info dict.
"""
library_info = dict(
name = libarr['lib_name'].as_py(),
meters_per_unit = libarr['meters_per_db_unit'].as_py(),
logical_units_per_unit = libarr['user_units_per_db_unit'].as_py(),
)
return library_info
def _srefs_to_mrefs(
pat: Pattern,
global_args: dict[str, Any],
elem: dict[str, Any],
cc: int,
) -> None:
cell_names = global_args['cell_names']
elem_off = elem['offsets']
elem_count = elem_off[cc + 1] - elem_off[cc]
if elem_count == 0:
return
start = elem_off[cc]
stop = elem_off[cc + 1]
elem_targets = elem['targets'][start:stop]
elem_xy = elem['xy'][start:stop]
elem_invert_y = elem['invert_y'][start:stop]
elem_angle_rad = elem['angle_rad'][start:stop]
elem_scale = elem['scale'][start:stop]
_append_plain_refs_sorted(
pat=pat,
cell_names=cell_names,
elem_targets=elem_targets,
elem_xy=elem_xy,
elem_invert_y=elem_invert_y,
elem_angle_rad=elem_angle_rad,
elem_scale=elem_scale,
)
def _append_plain_refs_sorted(
*,
pat: Pattern,
cell_names: list[str],
elem_targets: NDArray[numpy.integer[Any]],
elem_xy: NDArray[numpy.integer[Any]],
elem_invert_y: NDArray[numpy.bool_ | numpy.bool],
elem_angle_rad: NDArray[numpy.floating[Any]],
elem_scale: NDArray[numpy.floating[Any]],
) -> None:
elem_count = len(elem_targets)
if elem_count == 0:
return
target_start = 0
while target_start < elem_count:
target_id = int(elem_targets[target_start])
target_stop = target_start + 1
while target_stop < elem_count and elem_targets[target_stop] == target_id:
target_stop += 1
append_refs = pat.refs[cell_names[target_id]].extend
append_refs(
Ref._from_raw(
offset=elem_xy[ee],
mirrored=elem_invert_y[ee],
rotation=elem_angle_rad[ee],
scale=elem_scale[ee],
repetition=None,
annotations=None,
)
for ee in range(target_start, target_stop)
)
target_start = target_stop
def _arefs_to_mrefs(
pat: Pattern,
global_args: dict[str, Any],
elem: dict[str, Any],
cc: int,
) -> None:
cell_names = global_args['cell_names']
elem_off = elem['offsets']
elem_count = elem_off[cc + 1] - elem_off[cc]
if elem_count == 0:
return
start = elem_off[cc]
stop = elem_off[cc + 1]
elem_targets = elem['targets'][start:stop]
elem_xy = elem['xy'][start:stop]
elem_invert_y = elem['invert_y'][start:stop]
elem_angle_rad = elem['angle_rad'][start:stop]
elem_scale = elem['scale'][start:stop]
elem_xy0 = elem['xy0'][start:stop]
elem_xy1 = elem['xy1'][start:stop]
elem_counts = elem['counts'][start:stop]
if len(elem_targets) == 0:
return
target = None
append_ref: Callable[[Ref], Any] | None = None
for ee in range(len(elem_targets)):
target_id = int(elem_targets[ee])
if target != target_id:
target = target_id
append_ref = pat.refs[cell_names[target_id]].append
assert append_ref is not None
a_count, b_count = elem_counts[ee]
append_ref(Ref._from_raw(
offset=elem_xy[ee],
mirrored=elem_invert_y[ee],
rotation=elem_angle_rad[ee],
scale=elem_scale[ee],
repetition=Grid._from_raw(a_vector=elem_xy0[ee], b_vector=elem_xy1[ee], a_count=a_count, b_count=b_count),
annotations=None,
))
def _sref_props_to_mrefs(
pat: Pattern,
global_args: dict[str, Any],
elem: dict[str, Any],
cc: int,
) -> None:
cell_names = global_args['cell_names']
elem_off = elem['offsets']
prop_key = elem['prop_key']
prop_val = elem['prop_val']
elem_count = elem_off[cc + 1] - elem_off[cc]
if elem_count == 0:
return
elem_slc = slice(elem_off[cc], elem_off[cc] + elem_count + 1)
prop_offs = elem['prop_off'][elem_slc]
elem_targets = elem['targets'][elem_off[cc]:elem_off[cc + 1]]
elem_xy = elem['xy'][elem_off[cc]:elem_off[cc + 1]]
elem_invert_y = elem['invert_y'][elem_off[cc]:elem_off[cc + 1]]
elem_angle_rad = elem['angle_rad'][elem_off[cc]:elem_off[cc + 1]]
elem_scale = elem['scale'][elem_off[cc]:elem_off[cc + 1]]
for ee in range(elem_count):
annotations = _read_annotations(prop_offs, prop_key, prop_val, ee)
ref = Ref._from_raw(
offset=elem_xy[ee],
mirrored=elem_invert_y[ee],
rotation=elem_angle_rad[ee],
scale=elem_scale[ee],
repetition=None,
annotations=annotations,
)
pat.refs[cell_names[int(elem_targets[ee])]].append(ref)
def _aref_props_to_mrefs(
pat: Pattern,
global_args: dict[str, Any],
elem: dict[str, Any],
cc: int,
) -> None:
cell_names = global_args['cell_names']
elem_off = elem['offsets']
prop_key = elem['prop_key']
prop_val = elem['prop_val']
elem_count = elem_off[cc + 1] - elem_off[cc]
if elem_count == 0:
return
elem_slc = slice(elem_off[cc], elem_off[cc] + elem_count + 1)
prop_offs = elem['prop_off'][elem_slc]
elem_targets = elem['targets'][elem_off[cc]:elem_off[cc + 1]]
elem_xy = elem['xy'][elem_off[cc]:elem_off[cc + 1]]
elem_invert_y = elem['invert_y'][elem_off[cc]:elem_off[cc + 1]]
elem_angle_rad = elem['angle_rad'][elem_off[cc]:elem_off[cc + 1]]
elem_scale = elem['scale'][elem_off[cc]:elem_off[cc + 1]]
elem_xy0 = elem['xy0'][elem_off[cc]:elem_off[cc + 1]]
elem_xy1 = elem['xy1'][elem_off[cc]:elem_off[cc + 1]]
elem_counts = elem['counts'][elem_off[cc]:elem_off[cc + 1]]
for ee in range(elem_count):
a_count, b_count = elem_counts[ee]
annotations = _read_annotations(prop_offs, prop_key, prop_val, ee)
ref = Ref._from_raw(
offset=elem_xy[ee],
mirrored=elem_invert_y[ee],
rotation=elem_angle_rad[ee],
scale=elem_scale[ee],
repetition=Grid._from_raw(a_vector=elem_xy0[ee], b_vector=elem_xy1[ee], a_count=a_count, b_count=b_count),
annotations=annotations,
)
pat.refs[cell_names[int(elem_targets[ee])]].append(ref)
def _texts_to_labels(
pat: Pattern,
global_args: dict[str, Any],
elem: dict[str, Any],
cc: int,
) -> None:
elem_off = elem['offsets'] # which elements belong to each cell
xy = elem['xy']
layer_tups = global_args['layer_tups']
layer_inds = elem['layer_inds']
prop_key = elem['prop_key']
prop_val = elem['prop_val']
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
prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
elem_xy = xy[elem_slc][:elem_count]
elem_layer_inds = layer_inds[elem_slc][:elem_count]
elem_strings = elem['string'][elem_slc][:elem_count]
for ee in range(elem_count):
layer = layer_tups[int(elem_layer_inds[ee])]
offset = elem_xy[ee]
string = elem_strings[ee]
annotations = _read_annotations(prop_offs, prop_key, prop_val, ee)
mlabel = Label._from_raw(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
xy_val = elem['xy_arr']
layer_tups = global_args['layer_tups']
layer_inds = elem['layer_inds']
prop_key = elem['prop_key']
prop_val = elem['prop_val']
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
prop_offs = elem['prop_off'][elem_slc] # which props belong to each element
elem_layer_inds = layer_inds[elem_slc][:elem_count]
elem_widths = elem['width'][elem_slc][:elem_count]
elem_path_types = elem['path_type'][elem_slc][:elem_count]
elem_extensions = elem['extensions'][elem_slc][:elem_count]
for ee in range(elem_count):
layer = layer_tups[int(elem_layer_inds[ee])]
vertices = xy_val[xy_offs[ee]:xy_offs[ee + 1]]
width = elem_widths[ee]
cap_int = int(elem_path_types[ee])
if cap_int not in path_cap_map:
raise PatternError(f'Unrecognized path type: {cap_int}')
cap = path_cap_map[cap_int]
if cap_int == 4:
cap_extensions = elem_extensions[ee]
else:
cap_extensions = None
annotations = _read_annotations(prop_offs, prop_key, prop_val, ee)
path = Path._from_raw(
vertices=vertices,
width=width,
cap=cap,
cap_extensions=cap_extensions,
annotations=annotations,
)
pat.shapes[layer].append(path)
def _boundary_batches_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
vert_arr = elem['vert_arr']
vert_off = elem['vert_off']
layer_inds = elem['layer_inds']
layer_tups = global_args['layer_tups']
poly_off = elem['poly_off']
poly_offsets = elem['poly_offsets']
batch_count = elem_off[cc + 1] - elem_off[cc]
if batch_count == 0:
return
elem_slc = slice(elem_off[cc], elem_off[cc] + batch_count + 1) # +1 to capture ending location for last elem
elem_vert_off = vert_off[elem_slc]
elem_poly_off = poly_off[elem_slc]
elem_layer_inds = layer_inds[elem_slc][:batch_count]
for bb in range(batch_count):
layer = layer_tups[int(elem_layer_inds[bb])]
vertices = vert_arr[elem_vert_off[bb]:elem_vert_off[bb + 1]]
vertex_offsets = poly_offsets[elem_poly_off[bb]:elem_poly_off[bb + 1]]
if vertex_offsets.size == 1:
poly = Polygon._from_raw(vertices=vertices, annotations=None)
pat.shapes[layer].append(poly)
else:
polys = PolyCollection._from_raw(vertex_lists=vertices, vertex_offsets=vertex_offsets, annotations=None)
pat.shapes[layer].append(polys)
def _rect_batches_to_rectcollections(
pat: Pattern,
global_args: dict[str, Any],
elem: dict[str, Any],
cc: int,
) -> None:
elem_off = elem['offsets']
rect_arr = elem['rect_arr']
rect_off = elem['rect_off']
layer_inds = elem['layer_inds']
layer_tups = global_args['layer_tups']
batch_count = elem_off[cc + 1] - elem_off[cc]
if batch_count == 0:
return
elem_slc = slice(elem_off[cc], elem_off[cc] + batch_count + 1)
elem_rect_off = rect_off[elem_slc]
elem_layer_inds = layer_inds[elem_slc][:batch_count]
for bb in range(batch_count):
layer = layer_tups[int(elem_layer_inds[bb])]
rects = rect_arr[elem_rect_off[bb]:elem_rect_off[bb + 1]]
rect_collection = RectCollection._from_raw(rects=rects, annotations=None)
pat.shapes[layer].append(rect_collection)
def _boundary_props_to_polygons(
pat: Pattern,
global_args: dict[str, Any],
elem: dict[str, Any],
cc: int,
) -> None:
elem_off = elem['offsets']
vert_arr = elem['vert_arr']
vert_off = elem['vert_off']
layer_inds = elem['layer_inds']
layer_tups = global_args['layer_tups']
prop_key = elem['prop_key']
prop_val = elem['prop_val']
elem_count = elem_off[cc + 1] - elem_off[cc]
if elem_count == 0:
return
elem_slc = slice(elem_off[cc], elem_off[cc] + elem_count + 1)
elem_vert_off = vert_off[elem_slc]
prop_offs = elem['prop_off'][elem_slc]
elem_layer_inds = layer_inds[elem_slc][:elem_count]
for ee in range(elem_count):
layer = layer_tups[int(elem_layer_inds[ee])]
vertices = vert_arr[elem_vert_off[ee]:elem_vert_off[ee + 1]]
annotations = _read_annotations(prop_offs, prop_key, prop_val, ee)
poly = Polygon._from_raw(vertices=vertices, annotations=annotations)
pat.shapes[layer].append(poly)
#def _properties_to_annotations(properties: pyarrow.Array) -> annotations_t:
# return {prop['key'].as_py(): prop['value'].as_py() for prop in properties}
def check_valid_names(
names: Iterable[str],
max_length: int = 32,
) -> None:
"""
Check all provided names to see if they're valid GDSII cell names.
Args:
names: Collection of names to check
max_length: Max allowed length
"""
allowed_chars = set(string.ascii_letters + string.digits + '_?$')
bad_chars = [
name for name in names
if not set(name).issubset(allowed_chars)
]
bad_lengths = [
name for name in names
if len(name) > max_length
]
if bad_chars:
logger.error('Names contain invalid characters:\n' + pformat(bad_chars))
if bad_lengths:
logger.error(f'Names too long (>{max_length}:\n' + pformat(bad_chars))
if bad_chars or bad_lengths:
raise LibraryError('Library contains invalid names, see log above')

388
masque/file/gdsii_lazy.py Normal file
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@ -0,0 +1,388 @@
"""
Classic source-backed lazy GDSII reader built on the pure-python klamath path.
This module provides the non-Arrow half of Masque's lazy GDS architecture:
- `GdsLibrarySource` scans a GDS stream once to discover library metadata,
struct order, and child edges without materializing every cell.
- cells are materialized on demand through the classic `gdsii` decoder
whenever a caller indexes the lazy view
- the source can be wrapped in `PortsLibraryView` or merged through
`OverlayLibrary`, both of which live in `gdsii_lazy_core`
The public surface intentionally parallels `gdsii_lazy_arrow` closely so that
callers can swap between the classic and Arrow-backed implementations with
minimal changes.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import IO, Any, cast
from collections import defaultdict
from collections.abc import Iterator, Sequence
import gzip
import io
import logging
import mmap
import pathlib
import klamath
import numpy
from numpy.typing import NDArray
from klamath import records
from . import gdsii
from .utils import is_gzipped
from .gdsii_lazy_core import OverlayLibrary, PortsLibraryView, _pattern_children, write, writefile
from ..error import LibraryError
from ..library import ILibraryView, LibraryView, dangling_mode_t
from ..pattern import Pattern
from ..utils import apply_transforms
logger = logging.getLogger(__name__)
@dataclass
class _SourceHandle:
""" Owns the underlying stream and any companion file handle for a source. """
path: pathlib.Path | None
stream: IO[bytes]
handle: IO[bytes] | None = None
def close(self) -> None:
self.stream.close()
if self.handle is not None and self.handle is not self.stream:
self.handle.close()
self.handle = None
@dataclass(frozen=True)
class _CellScan:
""" Scan-time metadata for one cell in the source stream. """
offset: int
children: set[str]
def _open_source_stream(
filename: str | pathlib.Path,
*,
use_mmap: bool,
) -> _SourceHandle:
path = pathlib.Path(filename).expanduser().resolve()
if is_gzipped(path):
if use_mmap:
logger.info('Asked to mmap a gzipped file, reading into memory instead...')
with gzip.open(path, mode='rb') as stream:
data = stream.read()
return _SourceHandle(path=path, stream=io.BytesIO(data))
stream = cast('IO[bytes]', gzip.open(path, mode='rb'))
return _SourceHandle(path=path, stream=stream)
if use_mmap:
handle = path.open(mode='rb', buffering=0)
mapped = cast('IO[bytes]', mmap.mmap(handle.fileno(), 0, access=mmap.ACCESS_READ))
return _SourceHandle(path=path, stream=mapped, handle=handle)
stream = path.open(mode='rb')
return _SourceHandle(path=path, stream=stream)
def _scan_library(
stream: IO[bytes],
) -> tuple[dict[str, Any], list[str], dict[str, _CellScan]]:
library_info = gdsii._read_header(stream)
order: list[str] = []
cells: dict[str, _CellScan] = {}
found_struct = records.BGNSTR.skip_past(stream)
while found_struct:
name = records.STRNAME.skip_and_read(stream).decode('ASCII')
offset = stream.tell()
elements = klamath.library.read_elements(stream)
children = {
element.struct_name.decode('ASCII')
for element in elements
if isinstance(element, klamath.elements.Reference)
}
order.append(name)
cells[name] = _CellScan(offset=offset, children=children)
found_struct = records.BGNSTR.skip_past(stream)
return library_info, order, cells
class GdsLibrarySource(ILibraryView):
"""
Read-only library backed by a seekable GDS stream.
Cells are scanned once up front to discover order and child edges, then
materialized one at a time through the classic `gdsii.read_elements` path.
The source owns the stream lifetime, preserves on-disk ordering through
`source_order()`, and answers graph queries from scan metadata whenever
possible so callers can inspect hierarchy without forcing a full load.
"""
def __init__(
self,
*,
source: _SourceHandle,
library_info: dict[str, Any],
cell_order: Sequence[str],
cells: dict[str, _CellScan],
) -> None:
self.path = source.path
self.library_info = library_info
self._source = source
self._cell_order = tuple(cell_order)
self._cells = cells
self._cache: dict[str, Pattern] = {}
self._lookups_in_progress: list[str] = []
@classmethod
def from_file(
cls,
filename: str | pathlib.Path,
*,
use_mmap: bool = True,
) -> GdsLibrarySource:
source = _open_source_stream(filename, use_mmap=use_mmap)
source.stream.seek(0)
library_info, cell_order, cells = _scan_library(source.stream)
return cls(source=source, library_info=library_info, cell_order=cell_order, cells=cells)
def __getitem__(self, key: str) -> Pattern:
return self._materialize_pattern(key, persist=True)
def __iter__(self) -> Iterator[str]:
return iter(self._cell_order)
def __len__(self) -> int:
return len(self._cell_order)
def __contains__(self, key: object) -> bool:
return key in self._cells
def source_order(self) -> tuple[str, ...]:
return self._cell_order
def materialize_many(
self,
names: Sequence[str],
*,
persist: bool = True,
) -> LibraryView:
mats = {
name: self._materialize_pattern(name, persist=persist)
for name in dict.fromkeys(names)
}
return LibraryView(mats)
def _materialize_pattern(self, name: str, *, persist: bool) -> Pattern:
if name in self._cache:
return self._cache[name]
if name not in self._cells:
raise KeyError(name)
if name in self._lookups_in_progress:
chain = ' -> '.join(self._lookups_in_progress + [name])
raise LibraryError(
f'Detected circular reference or recursive lookup of "{name}".\n'
f'Lookup chain: {chain}\n'
'This may be caused by an invalid (cyclical) reference, or buggy code.\n'
'If you are lazy-loading a file, try a non-lazy load and check for reference cycles.'
)
self._lookups_in_progress.append(name)
try:
self._source.stream.seek(self._cells[name].offset)
pat = gdsii.read_elements(self._source.stream, raw_mode=True)
finally:
self._lookups_in_progress.pop()
if persist:
self._cache[name] = pat
return pat
def _raw_children(self, name: str) -> set[str]:
return set(self._cells[name].children)
def child_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
graph: dict[str, set[str]] = {}
for name in self._cell_order:
if name in self._cache:
graph[name] = _pattern_children(self._cache[name])
else:
graph[name] = self._raw_children(name)
existing = set(graph)
dangling_refs = set().union(*(children - existing for children in graph.values()))
if dangling == 'error':
if dangling_refs:
raise self._dangling_refs_error(cast('set[str]', dangling_refs), 'building child graph')
return graph
if dangling == 'ignore':
return {name: {child for child in children if child in existing} for name, children in graph.items()}
for child in dangling_refs:
graph.setdefault(cast('str', child), set())
return graph
def parent_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
child_graph = self.child_graph(dangling='include' if dangling == 'include' else 'ignore')
existing = set(self.keys())
igraph: dict[str, set[str]] = {name: set() for name in child_graph}
for parent, children in child_graph.items():
for child in children:
if child in existing or dangling == 'include':
igraph.setdefault(child, set()).add(parent)
if dangling == 'error':
raw = self.child_graph(dangling='include')
dangling_refs = set().union(*(children - existing for children in raw.values()))
if dangling_refs:
raise self._dangling_refs_error(cast('set[str]', dangling_refs), 'building parent graph')
return igraph
def subtree(
self,
tops: str | Sequence[str],
) -> ILibraryView:
if isinstance(tops, str):
tops = (tops,)
keep = cast('set[str]', self.referenced_patterns(tops) - {None})
keep |= set(tops)
return self.materialize_many(tuple(keep), persist=True)
def tops(self) -> list[str]:
graph = self.child_graph(dangling='ignore')
names = set(graph)
not_toplevel: set[str] = set()
for children in graph.values():
not_toplevel |= children
return list(names - not_toplevel)
def with_ports_from_data(
self,
*,
layers: Sequence[tuple[int, int] | int],
max_depth: int = 0,
skip_subcells: bool = True,
) -> PortsLibraryView:
return PortsLibraryView(
self,
layers=layers,
max_depth=max_depth,
skip_subcells=skip_subcells,
)
def find_refs_local(
self,
name: str,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[str, list[NDArray[numpy.float64]]]:
instances: dict[str, list[NDArray[numpy.float64]]] = defaultdict(list)
if parent_graph is None:
graph_mode = 'ignore' if dangling == 'ignore' else 'include'
parent_graph = self.parent_graph(dangling=graph_mode)
if name not in self:
if name not in parent_graph:
return instances
if dangling == 'error':
raise self._dangling_refs_error({name}, f'finding local refs for {name!r}')
if dangling == 'ignore':
return instances
for parent in parent_graph.get(name, set()):
if parent in self._cache:
for ref in self._cache[parent].refs.get(name, []):
instances[parent].append(ref.as_transforms())
continue
pat = self._materialize_pattern(parent, persist=False)
for ref in pat.refs.get(name, []):
instances[parent].append(ref.as_transforms())
return instances
def find_refs_global(
self,
name: str,
order: list[str] | None = None,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[tuple[str, ...], NDArray[numpy.float64]]:
graph_mode = 'ignore' if dangling == 'ignore' else 'include'
if order is None:
order = self.child_order(dangling=graph_mode)
if parent_graph is None:
parent_graph = self.parent_graph(dangling=graph_mode)
if name not in self:
if name not in parent_graph:
return {}
if dangling == 'error':
raise self._dangling_refs_error({name}, f'finding global refs for {name!r}')
if dangling == 'ignore':
return {}
self_keys = set(self.keys())
transforms: dict[str, list[tuple[tuple[str, ...], NDArray[numpy.float64]]]]
transforms = defaultdict(list)
for parent, vals in self.find_refs_local(name, parent_graph=parent_graph, dangling=dangling).items():
transforms[parent] = [((name,), numpy.concatenate(vals))]
for next_name in order:
if next_name not in transforms:
continue
if not parent_graph.get(next_name, set()) & self_keys:
continue
outers = self.find_refs_local(next_name, parent_graph=parent_graph, dangling=dangling)
inners = transforms.pop(next_name)
for parent, outer in outers.items():
outer_tf = numpy.concatenate(outer)
for path, inner in inners:
combined = apply_transforms(outer_tf, inner)
transforms[parent].append(((next_name,) + path, combined))
result = {}
for parent, targets in transforms.items():
for path, instances in targets:
result[(parent,) + path] = instances
return result
def close(self) -> None:
self._source.close()
def __enter__(self) -> GdsLibrarySource:
return self
def __exit__(self, *_args: object) -> None:
self.close()
def read(
stream: IO[bytes],
) -> tuple[GdsLibrarySource, dict[str, Any]]:
source = _SourceHandle(path=None, stream=stream)
stream.seek(0)
library_info, cell_order, cells = _scan_library(stream)
lib = GdsLibrarySource(source=source, library_info=library_info, cell_order=cell_order, cells=cells)
return lib, library_info
def readfile(
filename: str | pathlib.Path,
*,
use_mmap: bool = True,
) -> tuple[GdsLibrarySource, dict[str, Any]]:
lib = GdsLibrarySource.from_file(filename, use_mmap=use_mmap)
return lib, lib.library_info

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@ -0,0 +1,519 @@
"""
Lazy GDSII readers and writers backed by native Arrow scan/materialize paths.
This module is intentionally separate from `gdsii_arrow` so the eager read path
keeps its current behavior and performance profile.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import IO, Any, cast
from collections import defaultdict
from collections.abc import Iterator, Sequence
import gzip
import logging
import mmap
import pathlib
import numpy
from numpy.typing import NDArray
import pyarrow
from . import gdsii_arrow
from .utils import is_gzipped
from .gdsii_lazy_core import OverlayLibrary, PortsLibraryView, _pattern_children, write, writefile
from ..library import ILibraryView, LibraryView, dangling_mode_t
from ..pattern import Pattern
from ..utils import apply_transforms
logger = logging.getLogger(__name__)
@dataclass(frozen=True)
class _StructRange:
start: int
end: int
@dataclass
class _SourceBuffer:
path: pathlib.Path
data: bytes | mmap.mmap
handle: IO[bytes] | None = None
def raw_slice(self, start: int, end: int) -> bytes:
return self.data[start:end]
@dataclass
class _ScanRefs:
offsets: NDArray[numpy.integer[Any]]
targets: NDArray[numpy.integer[Any]]
xy: NDArray[numpy.int32]
xy0: NDArray[numpy.int32]
xy1: NDArray[numpy.int32]
counts: NDArray[numpy.int64]
invert_y: NDArray[numpy.bool_ | numpy.bool]
angle_rad: NDArray[numpy.floating[Any]]
scale: NDArray[numpy.floating[Any]]
@dataclass(frozen=True)
class _CellScan:
cell_id: int
struct_range: _StructRange
ref_start: int
ref_stop: int
children: set[str]
@dataclass
class _ScanPayload:
libarr: pyarrow.StructScalar
library_info: dict[str, Any]
cell_names: list[str]
cell_order: list[str]
cells: dict[str, _CellScan]
refs: _ScanRefs
def is_available() -> bool:
return gdsii_arrow.is_available()
def _read_header(libarr: pyarrow.StructScalar) -> dict[str, Any]:
return gdsii_arrow._read_header(libarr)
def _open_source_buffer(path: pathlib.Path) -> _SourceBuffer:
if is_gzipped(path):
with gzip.open(path, mode='rb') as stream:
data = stream.read()
return _SourceBuffer(path=path, data=data)
handle = path.open(mode='rb', buffering=0)
mapped = mmap.mmap(handle.fileno(), 0, access=mmap.ACCESS_READ)
return _SourceBuffer(path=path, data=mapped, handle=handle)
def _extract_scan_payload(libarr: pyarrow.StructScalar) -> _ScanPayload:
library_info = _read_header(libarr)
cell_names = libarr['cell_names'].as_py()
cells = libarr['cells']
cell_values = cells.values
cell_ids = cell_values.field('id').to_numpy()
struct_starts = cell_values.field('struct_start_offset').to_numpy()
struct_ends = cell_values.field('struct_end_offset').to_numpy()
refs = cell_values.field('refs')
ref_values = refs.values
ref_offsets = refs.offsets.to_numpy()
targets = ref_values.field('target').to_numpy()
xy = gdsii_arrow._packed_xy_u64_to_pairs(ref_values.field('xy').to_numpy())
xy0 = gdsii_arrow._packed_xy_u64_to_pairs(ref_values.field('xy0').to_numpy())
xy1 = gdsii_arrow._packed_xy_u64_to_pairs(ref_values.field('xy1').to_numpy())
counts = gdsii_arrow._packed_counts_u32_to_pairs(ref_values.field('counts').to_numpy())
invert_y = ref_values.field('invert_y').to_numpy(zero_copy_only=False)
angle_rad = ref_values.field('angle_rad').to_numpy()
scale = ref_values.field('scale').to_numpy()
ref_payload = _ScanRefs(
offsets=ref_offsets,
targets=targets,
xy=xy,
xy0=xy0,
xy1=xy1,
counts=counts,
invert_y=invert_y,
angle_rad=angle_rad,
scale=scale,
)
cell_order = [cell_names[int(cell_id)] for cell_id in cell_ids]
cell_scan: dict[str, _CellScan] = {}
for cc, name in enumerate(cell_order):
ref_start = int(ref_offsets[cc])
ref_stop = int(ref_offsets[cc + 1])
children = {
cell_names[int(target)]
for target in targets[ref_start:ref_stop]
}
cell_scan[name] = _CellScan(
cell_id=int(cell_ids[cc]),
struct_range=_StructRange(int(struct_starts[cc]), int(struct_ends[cc])),
ref_start=ref_start,
ref_stop=ref_stop,
children=children,
)
return _ScanPayload(
libarr=libarr,
library_info=library_info,
cell_names=cell_names,
cell_order=cell_order,
cells=cell_scan,
refs=ref_payload,
)
def _make_ref_rows(
xy: NDArray[numpy.integer[Any]],
angle_rad: NDArray[numpy.floating[Any]],
invert_y: NDArray[numpy.bool_ | numpy.bool],
scale: NDArray[numpy.floating[Any]],
) -> NDArray[numpy.float64]:
rows = numpy.empty((len(xy), 5), dtype=float)
rows[:, :2] = xy
rows[:, 2] = angle_rad
rows[:, 3] = invert_y.astype(float)
rows[:, 4] = scale
return rows
def _expand_aref_row(
xy: NDArray[numpy.integer[Any]],
xy0: NDArray[numpy.integer[Any]],
xy1: NDArray[numpy.integer[Any]],
counts: NDArray[numpy.integer[Any]],
angle_rad: float,
invert_y: bool,
scale: float,
) -> NDArray[numpy.float64]:
a_count = int(counts[0])
b_count = int(counts[1])
aa, bb = numpy.meshgrid(numpy.arange(a_count), numpy.arange(b_count), indexing='ij')
displacements = aa.reshape(-1, 1) * xy0[None, :] + bb.reshape(-1, 1) * xy1[None, :]
rows = numpy.empty((displacements.shape[0], 5), dtype=float)
rows[:, :2] = xy + displacements
rows[:, 2] = angle_rad
rows[:, 3] = float(invert_y)
rows[:, 4] = scale
return rows
class ArrowLibrary(ILibraryView):
"""
Read-only library backed by the native lazy Arrow scan schema.
Materializing a cell via `__getitem__` caches a real `Pattern` for that cell.
Cached cells are treated as edited for future writes from this module.
"""
path: pathlib.Path
library_info: dict[str, Any]
def __init__(
self,
*,
path: pathlib.Path,
payload: _ScanPayload,
source: _SourceBuffer,
) -> None:
self.path = path
self.library_info = payload.library_info
self._payload = payload
self._source = source
self._cache: dict[str, Pattern] = {}
@classmethod
def from_file(cls, filename: str | pathlib.Path) -> ArrowLibrary:
path = pathlib.Path(filename).expanduser().resolve()
source = _open_source_buffer(path)
scan_arr = gdsii_arrow._scan_buffer_to_arrow(source.data)
assert len(scan_arr) == 1
payload = _extract_scan_payload(scan_arr[0])
return cls(path=path, payload=payload, source=source)
def __getitem__(self, key: str) -> Pattern:
return self._materialize_pattern(key, persist=True)
def __iter__(self) -> Iterator[str]:
return iter(self._payload.cell_order)
def __len__(self) -> int:
return len(self._payload.cell_order)
def __contains__(self, key: object) -> bool:
return key in self._payload.cells
def source_order(self) -> tuple[str, ...]:
return tuple(self._payload.cell_order)
def raw_struct_bytes(self, name: str) -> bytes:
struct_range = self._payload.cells[name].struct_range
return self._source.raw_slice(struct_range.start, struct_range.end)
def can_copy_raw_struct(self, name: str) -> bool:
return name not in self._cache
def materialize_many(
self,
names: Sequence[str],
*,
persist: bool = True,
) -> LibraryView:
mats = self._materialize_patterns(names, persist=persist)
return LibraryView(mats)
def _materialize_patterns(
self,
names: Sequence[str],
*,
persist: bool,
) -> dict[str, Pattern]:
ordered_names = list(dict.fromkeys(names))
missing = [name for name in ordered_names if name not in self._payload.cells]
if missing:
raise KeyError(missing[0])
materialized: dict[str, Pattern] = {}
uncached = [name for name in ordered_names if name not in self._cache]
if uncached:
ranges = numpy.asarray(
[
[
self._payload.cells[name].struct_range.start,
self._payload.cells[name].struct_range.end,
]
for name in uncached
],
dtype=numpy.uint64,
)
arrow_arr = gdsii_arrow._read_selected_cells_to_arrow(self._source.data, ranges)
assert len(arrow_arr) == 1
selected_lib, _info = gdsii_arrow.read_arrow(arrow_arr[0])
for name in uncached:
pat = selected_lib[name]
materialized[name] = pat
if persist:
self._cache[name] = pat
for name in ordered_names:
if name in self._cache:
materialized[name] = self._cache[name]
return materialized
def _materialize_pattern(self, name: str, *, persist: bool) -> Pattern:
return self._materialize_patterns((name,), persist=persist)[name]
def _raw_children(self, name: str) -> set[str]:
return set(self._payload.cells[name].children)
def _collect_raw_transforms(self, cell: _CellScan, target_id: int) -> list[NDArray[numpy.float64]]:
refs = self._payload.refs
start = cell.ref_start
stop = cell.ref_stop
if stop <= start:
return []
targets = refs.targets[start:stop]
mask = targets == target_id
if not mask.any():
return []
rows: list[NDArray[numpy.float64]] = []
counts = refs.counts[start:stop]
unit_mask = mask & (counts[:, 0] == 1) & (counts[:, 1] == 1)
if unit_mask.any():
rows.append(_make_ref_rows(
refs.xy[start:stop][unit_mask],
refs.angle_rad[start:stop][unit_mask],
refs.invert_y[start:stop][unit_mask],
refs.scale[start:stop][unit_mask],
))
aref_indices = numpy.nonzero(mask & ~unit_mask)[0]
for idx in aref_indices:
abs_idx = start + int(idx)
rows.append(_expand_aref_row(
xy=refs.xy[abs_idx],
xy0=refs.xy0[abs_idx],
xy1=refs.xy1[abs_idx],
counts=refs.counts[abs_idx],
angle_rad=float(refs.angle_rad[abs_idx]),
invert_y=bool(refs.invert_y[abs_idx]),
scale=float(refs.scale[abs_idx]),
))
return rows
def child_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
graph: dict[str, set[str]] = {}
for name in self._payload.cell_order:
if name in self._cache:
graph[name] = _pattern_children(self._cache[name])
else:
graph[name] = self._raw_children(name)
existing = set(graph)
dangling_refs = set().union(*(children - existing for children in graph.values()))
if dangling == 'error':
if dangling_refs:
raise self._dangling_refs_error(cast('set[str]', dangling_refs), 'building child graph')
return graph
if dangling == 'ignore':
return {name: {child for child in children if child in existing} for name, children in graph.items()}
for child in dangling_refs:
graph.setdefault(cast('str', child), set())
return graph
def parent_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
child_graph = self.child_graph(dangling='include' if dangling == 'include' else 'ignore')
existing = set(self.keys())
igraph: dict[str, set[str]] = {name: set() for name in child_graph}
for parent, children in child_graph.items():
for child in children:
if child in existing or dangling == 'include':
igraph.setdefault(child, set()).add(parent)
if dangling == 'error':
raw = self.child_graph(dangling='include')
dangling_refs = set().union(*(children - existing for children in raw.values()))
if dangling_refs:
raise self._dangling_refs_error(cast('set[str]', dangling_refs), 'building parent graph')
return igraph
def subtree(
self,
tops: str | Sequence[str],
) -> ILibraryView:
if isinstance(tops, str):
tops = (tops,)
keep = cast('set[str]', self.referenced_patterns(tops) - {None})
keep |= set(tops)
return self.materialize_many(tuple(keep), persist=True)
def tops(self) -> list[str]:
graph = self.child_graph(dangling='ignore')
names = set(graph)
not_toplevel: set[str] = set()
for children in graph.values():
not_toplevel |= children
return list(names - not_toplevel)
def with_ports_from_data(
self,
*,
layers: Sequence[tuple[int, int] | int],
max_depth: int = 0,
skip_subcells: bool = True,
) -> PortsLibraryView:
return PortsLibraryView(
self,
layers=layers,
max_depth=max_depth,
skip_subcells=skip_subcells,
)
def close(self) -> None:
data = self._source.data
if isinstance(data, mmap.mmap):
data.close()
if self._source.handle is not None:
self._source.handle.close()
self._source.handle = None
def __enter__(self) -> ArrowLibrary:
return self
def __exit__(self, *_args: object) -> None:
self.close()
def find_refs_local(
self,
name: str,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[str, list[NDArray[numpy.float64]]]:
instances: dict[str, list[NDArray[numpy.float64]]] = defaultdict(list)
if parent_graph is None:
graph_mode = 'ignore' if dangling == 'ignore' else 'include'
parent_graph = self.parent_graph(dangling=graph_mode)
if name not in self:
if name not in parent_graph:
return instances
if dangling == 'error':
raise self._dangling_refs_error({name}, f'finding local refs for {name!r}')
if dangling == 'ignore':
return instances
target_id = self._payload.cells.get(name)
for parent in parent_graph.get(name, set()):
if parent in self._cache:
for ref in self._cache[parent].refs.get(name, []):
instances[parent].append(ref.as_transforms())
continue
if target_id is None or parent not in self._payload.cells:
continue
rows = self._collect_raw_transforms(self._payload.cells[parent], target_id.cell_id)
if rows:
instances[parent].extend(rows)
return instances
def find_refs_global(
self,
name: str,
order: list[str] | None = None,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[tuple[str, ...], NDArray[numpy.float64]]:
graph_mode = 'ignore' if dangling == 'ignore' else 'include'
if order is None:
order = self.child_order(dangling=graph_mode)
if parent_graph is None:
parent_graph = self.parent_graph(dangling=graph_mode)
if name not in self:
if name not in parent_graph:
return {}
if dangling == 'error':
raise self._dangling_refs_error({name}, f'finding global refs for {name!r}')
if dangling == 'ignore':
return {}
self_keys = set(self.keys())
transforms: dict[str, list[tuple[tuple[str, ...], NDArray[numpy.float64]]]]
transforms = defaultdict(list)
for parent, vals in self.find_refs_local(name, parent_graph=parent_graph, dangling=dangling).items():
transforms[parent] = [((name,), numpy.concatenate(vals))]
for next_name in order:
if next_name not in transforms:
continue
if not parent_graph.get(next_name, set()) & self_keys:
continue
outers = self.find_refs_local(next_name, parent_graph=parent_graph, dangling=dangling)
inners = transforms.pop(next_name)
for parent, outer in outers.items():
outer_tf = numpy.concatenate(outer)
for path, inner in inners:
combined = apply_transforms(outer_tf, inner)
transforms[parent].append(((next_name,) + path, combined))
result = {}
for parent, targets in transforms.items():
for path, instances in targets:
full_path = (parent,) + path
result[full_path] = instances
return result
def readfile(
filename: str | pathlib.Path,
) -> tuple[ArrowLibrary, dict[str, Any]]:
lib = ArrowLibrary.from_file(filename)
return lib, lib.library_info
def load_libraryfile(
filename: str | pathlib.Path,
) -> tuple[ArrowLibrary, dict[str, Any]]:
return readfile(filename)

View file

@ -0,0 +1,706 @@
"""
Shared helpers for source-backed lazy GDS views.
This module contains the reusable pieces that sit between lazy source readers
and ordinary mutable library usage:
- `PortsLibraryView` layers a processed, ports-importing cache on top of a raw
source view without mutating the source itself
- `OverlayLibrary` exposes a mutable library surface that can mix source-backed
cells with overlay-owned materialized patterns
- the write helpers preserve source-backed copy-through behavior where
possible, falling back to normal pattern serialization when a cell has been
materialized or remapped
Both the classic and Arrow-backed lazy GDS readers rely on these helpers.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import IO, Any, cast
from collections import defaultdict
from collections.abc import Callable, Iterator, Mapping, Sequence
import copy
import gzip
import logging
import pathlib
import klamath
import numpy
from numpy.typing import NDArray
from . import gdsii
from .utils import tmpfile
from ..error import LibraryError
from ..library import ILibrary, ILibraryView, LibraryView, dangling_mode_t
from ..pattern import Pattern, map_targets
from ..utils import apply_transforms
from ..utils.ports2data import data_to_ports
logger = logging.getLogger(__name__)
@dataclass
class _SourceLayer:
""" One imported source layer tracked by an `OverlayLibrary`. """
library: ILibraryView
source_to_visible: dict[str, str]
visible_to_source: dict[str, str]
child_graph: dict[str, set[str]]
order: list[str]
@dataclass(frozen=True)
class _SourceEntry:
""" Reference to a single visible source-backed cell in an overlay. """
layer_index: int
source_name: str
def _pattern_children(pat: Pattern) -> set[str]:
return {child for child, refs in pat.refs.items() if child is not None and refs}
def _remap_pattern_targets(pat: Pattern, remap: Callable[[str | None], str | None]) -> Pattern:
if not pat.refs:
return pat
pat.refs = map_targets(pat.refs, remap)
return pat
def _coerce_library_view(source: Mapping[str, Pattern] | ILibraryView) -> ILibraryView:
if isinstance(source, ILibraryView):
return source
return LibraryView(source)
def _materialize_detached_pattern(view: ILibraryView, name: str) -> Pattern:
func = getattr(view, '_materialize_pattern', None)
if callable(func):
return cast('Pattern', func(name, persist=False))
return view[name].deepcopy()
class PortsLibraryView(ILibraryView):
"""
Read-only view which imports ports into cells on first materialization.
The wrapped source remains untouched; this view owns a separate processed
cache so direct-copy workflows can continue to use the raw source view.
Graph queries, source ordering, and copy-through capabilities are delegated
to the wrapped source whenever possible, while `__getitem__` and
`materialize_many()` return port-imported patterns.
"""
def __init__(
self,
source: ILibraryView,
*,
layers: Sequence[gdsii.layer_t],
max_depth: int = 0,
skip_subcells: bool = True,
) -> None:
self._source = source
self._layers = tuple(layers)
self._max_depth = max_depth
self._skip_subcells = skip_subcells
self._cache: dict[str, Pattern] = {}
self._lookups_in_progress: list[str] = []
if hasattr(source, 'library_info'):
self.library_info = cast('dict[str, Any]', getattr(source, 'library_info'))
def __getitem__(self, key: str) -> Pattern:
return self._materialize_pattern(key, persist=True)
def __iter__(self) -> Iterator[str]:
return iter(self._source)
def __len__(self) -> int:
return len(self._source)
def __contains__(self, key: object) -> bool:
return key in self._source
def _materialize_pattern(self, name: str, *, persist: bool) -> Pattern:
if name in self._cache:
return self._cache[name]
if name in self._lookups_in_progress:
chain = ' -> '.join(self._lookups_in_progress + [name])
raise LibraryError(
f'Detected circular reference or recursive lookup of "{name}".\n'
f'Lookup chain: {chain}\n'
'This may be caused by an invalid (cyclical) reference, or buggy code.'
)
self._lookups_in_progress.append(name)
try:
pat = _materialize_detached_pattern(self._source, name)
pat = data_to_ports(
layers=self._layers,
library=self,
pattern=pat,
name=name,
max_depth=self._max_depth,
skip_subcells=self._skip_subcells,
)
finally:
self._lookups_in_progress.pop()
if persist:
self._cache[name] = pat
return pat
def materialize_many(
self,
names: Sequence[str],
*,
persist: bool = True,
) -> LibraryView:
mats = {
name: self._materialize_pattern(name, persist=persist)
for name in dict.fromkeys(names)
}
return LibraryView(mats)
def source_order(self) -> tuple[str, ...]:
return self._source.source_order()
def child_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
return self._source.child_graph(dangling=dangling)
def parent_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
return self._source.parent_graph(dangling=dangling)
def subtree(
self,
tops: str | Sequence[str],
) -> ILibraryView:
if isinstance(tops, str):
tops = (tops,)
keep = cast('set[str]', self._source.referenced_patterns(tops) - {None})
keep |= set(tops)
return self.materialize_many(tuple(keep), persist=True)
def tops(self) -> list[str]:
return self._source.tops()
def find_refs_local(
self,
name: str,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[str, list[NDArray[numpy.float64]]]:
finder = getattr(self._source, 'find_refs_local', None)
if callable(finder):
return cast('dict[str, list[NDArray[numpy.float64]]]', finder(name, parent_graph=parent_graph, dangling=dangling))
return super().find_refs_local(name, parent_graph=parent_graph, dangling=dangling)
def find_refs_global(
self,
name: str,
order: list[str] | None = None,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[tuple[str, ...], NDArray[numpy.float64]]:
finder = getattr(self._source, 'find_refs_global', None)
if callable(finder):
return cast(
'dict[tuple[str, ...], NDArray[numpy.float64]]',
finder(name, order=order, parent_graph=parent_graph, dangling=dangling),
)
return super().find_refs_global(name, order=order, parent_graph=parent_graph, dangling=dangling)
def raw_struct_bytes(self, name: str) -> bytes:
reader = getattr(self._source, 'raw_struct_bytes', None)
if not callable(reader):
raise AttributeError('raw_struct_bytes')
return cast('bytes', reader(name))
def can_copy_raw_struct(self, name: str) -> bool:
can_copy = getattr(self._source, 'can_copy_raw_struct', None)
if not callable(can_copy):
return False
return bool(can_copy(name))
def close(self) -> None:
closer = getattr(self._source, 'close', None)
if callable(closer):
closer()
def __enter__(self) -> PortsLibraryView:
return self
def __exit__(self, *_args: object) -> None:
self.close()
class OverlayLibrary(ILibrary):
"""
Mutable overlay over one or more source libraries.
Source-backed cells remain lazy until accessed through `__getitem__`, at
which point that visible cell is promoted into an overlay-owned materialized
`Pattern`.
This is the main mutable integration surface for lazy GDS content. It lets
callers:
- expose one or more source-backed libraries behind a normal `ILibrary`
interface
- add or replace cells with overlay-owned patterns
- rename visible source cells
- remap references without immediately rewriting untouched source structs
"""
def __init__(self) -> None:
self._layers: list[_SourceLayer] = []
self._entries: dict[str, Pattern | _SourceEntry] = {}
self._order: list[str] = []
self._target_remap: dict[str, str] = {}
def __iter__(self) -> Iterator[str]:
return (name for name in self._order if name in self._entries)
def __len__(self) -> int:
return len(self._entries)
def __contains__(self, key: object) -> bool:
return key in self._entries
def __getitem__(self, key: str) -> Pattern:
return self._materialize_pattern(key, persist=True)
def __setitem__(
self,
key: str,
value: Pattern | Callable[[], Pattern],
) -> None:
if key in self._entries:
raise LibraryError(f'"{key}" already exists in the library. Overwriting is not allowed!')
pattern = value() if callable(value) else value
self._entries[key] = pattern
if key not in self._order:
self._order.append(key)
def __delitem__(self, key: str) -> None:
if key not in self._entries:
raise KeyError(key)
del self._entries[key]
def _merge(self, key_self: str, other: Mapping[str, Pattern], key_other: str) -> None:
self[key_self] = copy.deepcopy(other[key_other])
def add_source(
self,
source: Mapping[str, Pattern] | ILibraryView,
*,
rename_theirs: Callable[[ILibraryView, str], str] | None = None,
) -> dict[str, str]:
view = _coerce_library_view(source)
source_order = list(view.source_order())
child_graph = view.child_graph(dangling='include')
source_to_visible: dict[str, str] = {}
visible_to_source: dict[str, str] = {}
rename_map: dict[str, str] = {}
for name in source_order:
visible = name
if visible in self._entries or visible in visible_to_source:
if rename_theirs is None:
raise LibraryError(f'Conflicting name while adding source: {name!r}')
visible = rename_theirs(self, name)
if visible in self._entries or visible in visible_to_source:
raise LibraryError(f'Unresolved duplicate key encountered while adding source: {name!r} -> {visible!r}')
rename_map[name] = visible
source_to_visible[name] = visible
visible_to_source[visible] = name
layer = _SourceLayer(
library=view,
source_to_visible=source_to_visible,
visible_to_source=visible_to_source,
child_graph=child_graph,
order=[source_to_visible[name] for name in source_order],
)
layer_index = len(self._layers)
self._layers.append(layer)
for source_name, visible_name in source_to_visible.items():
self._entries[visible_name] = _SourceEntry(layer_index=layer_index, source_name=source_name)
if visible_name not in self._order:
self._order.append(visible_name)
return rename_map
def rename(
self,
old_name: str,
new_name: str,
move_references: bool = False,
) -> OverlayLibrary:
if old_name not in self._entries:
raise LibraryError(f'"{old_name}" does not exist in the library.')
if old_name == new_name:
return self
if new_name in self._entries:
raise LibraryError(f'"{new_name}" already exists in the library.')
entry = self._entries.pop(old_name)
self._entries[new_name] = entry
if isinstance(entry, _SourceEntry):
layer = self._layers[entry.layer_index]
layer.source_to_visible[entry.source_name] = new_name
del layer.visible_to_source[old_name]
layer.visible_to_source[new_name] = entry.source_name
idx = self._order.index(old_name)
self._order[idx] = new_name
if move_references:
self.move_references(old_name, new_name)
return self
def _resolve_target(self, target: str) -> str:
seen: set[str] = set()
current = target
while current in self._target_remap:
if current in seen:
raise LibraryError(f'Cycle encountered while resolving target remap for {target!r}')
seen.add(current)
current = self._target_remap[current]
return current
def _set_target_remap(self, old_target: str, new_target: str) -> None:
resolved_new = self._resolve_target(new_target)
if resolved_new == old_target:
raise LibraryError(f'Ref target remap would create a cycle: {old_target!r} -> {new_target!r}')
self._target_remap[old_target] = resolved_new
for key in list(self._target_remap):
self._target_remap[key] = self._resolve_target(self._target_remap[key])
def move_references(self, old_target: str, new_target: str) -> OverlayLibrary:
if old_target == new_target:
return self
self._set_target_remap(old_target, new_target)
for entry in list(self._entries.values()):
if isinstance(entry, Pattern) and old_target in entry.refs:
entry.refs[new_target].extend(entry.refs[old_target])
del entry.refs[old_target]
return self
def _effective_target(self, layer: _SourceLayer, target: str) -> str:
visible = layer.source_to_visible.get(target, target)
return self._resolve_target(visible)
def _materialize_pattern(self, name: str, *, persist: bool) -> Pattern:
if name not in self._entries:
raise KeyError(name)
entry = self._entries[name]
if isinstance(entry, Pattern):
return entry
layer = self._layers[entry.layer_index]
source_pat = layer.library[entry.source_name].deepcopy()
remap = lambda target: None if target is None else self._effective_target(layer, target)
pat = _remap_pattern_targets(source_pat, remap)
if persist:
self._entries[name] = pat
return pat
def child_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
graph: dict[str, set[str]] = {}
for name in self._order:
if name not in self._entries:
continue
entry = self._entries[name]
if isinstance(entry, Pattern):
graph[name] = _pattern_children(entry)
continue
layer = self._layers[entry.layer_index]
children = {self._effective_target(layer, child) for child in layer.child_graph.get(entry.source_name, set())}
graph[name] = children
existing = set(graph)
dangling_refs = set().union(*(children - existing for children in graph.values()))
if dangling == 'error':
if dangling_refs:
raise self._dangling_refs_error(cast('set[str]', dangling_refs), 'building child graph')
return graph
if dangling == 'ignore':
return {name: {child for child in children if child in existing} for name, children in graph.items()}
for child in dangling_refs:
graph.setdefault(cast('str', child), set())
return graph
def parent_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
child_graph = self.child_graph(dangling='include' if dangling == 'include' else 'ignore')
existing = set(self.keys())
igraph: dict[str, set[str]] = {name: set() for name in child_graph}
for parent, children in child_graph.items():
for child in children:
if child in existing or dangling == 'include':
igraph.setdefault(child, set()).add(parent)
if dangling == 'error':
raw = self.child_graph(dangling='include')
dangling_refs = set().union(*(children - existing for children in raw.values()))
if dangling_refs:
raise self._dangling_refs_error(cast('set[str]', dangling_refs), 'building parent graph')
return igraph
def subtree(
self,
tops: str | Sequence[str],
) -> ILibraryView:
if isinstance(tops, str):
tops = (tops,)
keep = cast('set[str]', self.referenced_patterns(tops) - {None})
keep |= set(tops)
return LibraryView({name: self[name] for name in keep})
def find_refs_local(
self,
name: str,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[str, list[NDArray[numpy.float64]]]:
instances: dict[str, list[NDArray[numpy.float64]]] = defaultdict(list)
if parent_graph is None:
graph_mode = 'ignore' if dangling == 'ignore' else 'include'
parent_graph = self.parent_graph(dangling=graph_mode)
if name not in self:
if name not in parent_graph:
return instances
if dangling == 'error':
raise self._dangling_refs_error({name}, f'finding local refs for {name!r}')
if dangling == 'ignore':
return instances
for parent in parent_graph.get(name, set()):
pat = self._materialize_pattern(parent, persist=False)
for ref in pat.refs.get(name, []):
instances[parent].append(ref.as_transforms())
return instances
def find_refs_global(
self,
name: str,
order: list[str] | None = None,
parent_graph: dict[str, set[str]] | None = None,
dangling: dangling_mode_t = 'error',
) -> dict[tuple[str, ...], NDArray[numpy.float64]]:
graph_mode = 'ignore' if dangling == 'ignore' else 'include'
if order is None:
order = self.child_order(dangling=graph_mode)
if parent_graph is None:
parent_graph = self.parent_graph(dangling=graph_mode)
if name not in self:
if name not in parent_graph:
return {}
if dangling == 'error':
raise self._dangling_refs_error({name}, f'finding global refs for {name!r}')
if dangling == 'ignore':
return {}
self_keys = set(self.keys())
transforms: dict[str, list[tuple[tuple[str, ...], NDArray[numpy.float64]]]]
transforms = defaultdict(list)
for parent, vals in self.find_refs_local(name, parent_graph=parent_graph, dangling=dangling).items():
transforms[parent] = [((name,), numpy.concatenate(vals))]
for next_name in order:
if next_name not in transforms:
continue
if not parent_graph.get(next_name, set()) & self_keys:
continue
outers = self.find_refs_local(next_name, parent_graph=parent_graph, dangling=dangling)
inners = transforms.pop(next_name)
for parent, outer in outers.items():
outer_tf = numpy.concatenate(outer)
for path, inner in inners:
combined = apply_transforms(outer_tf, inner)
transforms[parent].append(((next_name,) + path, combined))
result = {}
for parent, targets in transforms.items():
for path, instances in targets:
result[(parent,) + path] = instances
return result
def source_order(self) -> tuple[str, ...]:
return tuple(name for name in self._order if name in self._entries)
class BuiltOverlayLibrary(OverlayLibrary):
"""
Internal overlay output returned by `BuildLibrary.build(output='overlay')`.
The type is intentionally not part of the public API. It exists so build
outputs can carry a `build_report` while still behaving like an
`OverlayLibrary`.
"""
def __init__(self, *, build_report: Any | None = None) -> None:
super().__init__()
self.build_report = build_report
def _iter_library_infos(library: Mapping[str, Pattern] | ILibraryView) -> Iterator[dict[str, Any]]:
info = getattr(library, 'library_info', None)
if isinstance(info, dict):
yield info
if isinstance(library, OverlayLibrary):
for layer in library._layers:
yield from _iter_library_infos(layer.library)
def _get_write_info(
library: Mapping[str, Pattern] | ILibraryView,
*,
meters_per_unit: float | None,
logical_units_per_unit: float | None,
library_name: str | None,
) -> tuple[float, float, str]:
if meters_per_unit is not None and logical_units_per_unit is not None and library_name is not None:
return meters_per_unit, logical_units_per_unit, library_name
infos = list(_iter_library_infos(library))
if infos:
unit_pairs = {(info['meters_per_unit'], info['logical_units_per_unit']) for info in infos}
if len(unit_pairs) > 1:
raise LibraryError('Merged lazy GDS sources must have identical units before writing')
info = infos[0]
meters = info['meters_per_unit'] if meters_per_unit is None else meters_per_unit
logical = info['logical_units_per_unit'] if logical_units_per_unit is None else logical_units_per_unit
name = info['name'] if library_name is None else library_name
return meters, logical, name
if meters_per_unit is None or logical_units_per_unit is None or library_name is None:
raise LibraryError('meters_per_unit, logical_units_per_unit, and library_name are required for non-GDS-backed lazy writes')
return meters_per_unit, logical_units_per_unit, library_name
def _can_copy_raw_cell(library: Mapping[str, Pattern] | ILibraryView, name: str) -> bool:
can_copy = getattr(library, 'can_copy_raw_struct', None)
if not callable(can_copy):
return False
return bool(can_copy(name))
def _raw_struct_bytes(library: Mapping[str, Pattern] | ILibraryView, name: str) -> bytes:
reader = getattr(library, 'raw_struct_bytes', None)
if not callable(reader):
raise AttributeError('raw_struct_bytes')
return cast('bytes', reader(name))
def _can_copy_overlay_cell(library: OverlayLibrary, name: str, entry: _SourceEntry) -> bool:
layer = library._layers[entry.layer_index]
if name != entry.source_name:
return False
if not _can_copy_raw_cell(layer.library, entry.source_name):
return False
children = layer.child_graph.get(entry.source_name, set())
return all(library._effective_target(layer, child) == child for child in children)
def _write_pattern_struct(stream: IO[bytes], name: str, pat: Pattern) -> None:
elements: list[klamath.elements.Element] = []
elements += gdsii._shapes_to_elements(pat.shapes)
elements += gdsii._labels_to_texts(pat.labels)
elements += gdsii._mrefs_to_grefs(pat.refs)
klamath.library.write_struct(stream, name=name.encode('ASCII'), elements=elements)
def write(
library: Mapping[str, Pattern] | ILibraryView,
stream: IO[bytes],
*,
meters_per_unit: float | None = None,
logical_units_per_unit: float | None = None,
library_name: str | None = None,
) -> None:
meters_per_unit, logical_units_per_unit, library_name = _get_write_info(
library,
meters_per_unit=meters_per_unit,
logical_units_per_unit=logical_units_per_unit,
library_name=library_name,
)
header = klamath.library.FileHeader(
name=library_name.encode('ASCII'),
user_units_per_db_unit=logical_units_per_unit,
meters_per_db_unit=meters_per_unit,
)
header.write(stream)
if isinstance(library, OverlayLibrary):
for name in library.source_order():
entry = library._entries[name]
if isinstance(entry, _SourceEntry) and _can_copy_overlay_cell(library, name, entry):
layer = library._layers[entry.layer_index]
stream.write(_raw_struct_bytes(layer.library, entry.source_name))
else:
_write_pattern_struct(stream, name, library._materialize_pattern(name, persist=False))
klamath.records.ENDLIB.write(stream, None)
return
if hasattr(library, 'raw_struct_bytes'):
for name in library.source_order():
if _can_copy_raw_cell(library, name):
stream.write(_raw_struct_bytes(library, name))
else:
_write_pattern_struct(stream, name, _materialize_detached_pattern(cast('ILibraryView', library), name))
klamath.records.ENDLIB.write(stream, None)
return
gdsii.write(cast('Mapping[str, Pattern]', library), stream, meters_per_unit, logical_units_per_unit, library_name)
def writefile(
library: Mapping[str, Pattern] | ILibraryView,
filename: str | pathlib.Path,
*,
meters_per_unit: float | None = None,
logical_units_per_unit: float | None = None,
library_name: str | None = None,
) -> None:
path = pathlib.Path(filename)
with tmpfile(path) as base_stream:
streams: tuple[Any, ...] = (base_stream,)
if path.suffix == '.gz':
stream = cast('IO[bytes]', gzip.GzipFile(filename='', mtime=0, fileobj=base_stream, mode='wb', compresslevel=6))
streams = (stream,) + streams
else:
stream = base_stream
try:
write(
library,
stream,
meters_per_unit=meters_per_unit,
logical_units_per_unit=logical_units_per_unit,
library_name=library_name,
)
finally:
for ss in streams:
ss.close()

633
masque/file/gdsii_perf.py Normal file
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@ -0,0 +1,633 @@
"""
Synthetic GDS fixture generation for reader/writer performance testing.
The presets here are intentionally hierarchical and deterministic. They aim to
approximate a pair of real-world layout families discussed during GDS reader and
writer work:
* `many_cells`: tens of thousands of cells, moderate reference count, very heavy
box usage after flattening, and moderate polygon density.
* `many_instances`: a much smaller cell library with very high reference count,
similar box density, and far fewer polygons.
Fixtures are written by streaming structures through `klamath` directly so large
benchmark files can be produced without first materializing an equally large
`masque.Library` in Python.
"""
from __future__ import annotations
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Any
import argparse
import json
import math
import numpy
import klamath
from klamath import elements
EMPTY_PROPERTIES: dict[int, bytes] = {}
METERS_PER_DB_UNIT = 1e-9
USER_UNITS_PER_DB_UNIT = 1e-3
TOTAL_LAYERS = 200
@dataclass(frozen=True)
class FixturePreset:
name: str
total_layers: int
box_layers: int
heavy_box_layers: int
polygon_layers: int
box_cells: int
poly_cells: int
box_wrappers: int
poly_wrappers: int
box_clusters: int
poly_clusters: int
box_cluster_refs: int
poly_cluster_refs: int
top_direct_box_refs: int
top_direct_poly_refs: int
heavy_boxes_per_cell: int
regular_boxes_per_cell: int
polygons_per_cell: int
path_stride: int
text_stride: int
box_cluster_array: tuple[int, int]
top_box_array: tuple[int, int]
poly_cluster_array: tuple[int, int]
top_poly_array: tuple[int, int]
rare_annotation_stride: int
PRESETS: dict[str, FixturePreset] = {
'many_cells': FixturePreset(
name='many_cells',
total_layers=TOTAL_LAYERS,
box_layers=20,
heavy_box_layers=3,
polygon_layers=20,
box_cells=17_000,
poly_cells=6_000,
box_wrappers=18_000,
poly_wrappers=6_000,
box_clusters=2_000,
poly_clusters=999,
box_cluster_refs=24,
poly_cluster_refs=16,
top_direct_box_refs=21_000,
top_direct_poly_refs=7_000,
heavy_boxes_per_cell=6,
regular_boxes_per_cell=2,
polygons_per_cell=50,
path_stride=2,
text_stride=3,
box_cluster_array=(24, 16),
top_box_array=(8, 8),
poly_cluster_array=(4, 2),
top_poly_array=(3, 2),
rare_annotation_stride=1_250,
),
'many_instances': FixturePreset(
name='many_instances',
total_layers=TOTAL_LAYERS,
box_layers=25,
heavy_box_layers=3,
polygon_layers=10,
box_cells=2_500,
poly_cells=500,
box_wrappers=1_000,
poly_wrappers=500,
box_clusters=1_000,
poly_clusters=499,
box_cluster_refs=1_200,
poly_cluster_refs=400,
top_direct_box_refs=102_001,
top_direct_poly_refs=0,
heavy_boxes_per_cell=40,
regular_boxes_per_cell=16,
polygons_per_cell=60,
path_stride=1,
text_stride=2,
box_cluster_array=(1, 1),
top_box_array=(1, 1),
poly_cluster_array=(1, 1),
top_poly_array=(1, 1),
rare_annotation_stride=250,
),
}
@dataclass(frozen=True)
class FixtureManifest:
preset: str
scale: float
gds_path: str
library_name: str
cells: int
refs: int
layers: int
box_layers: int
heavy_box_layers: list[list[int]]
polygon_layers: list[list[int]]
hierarchical_boxes_per_heavy_layer: int
hierarchical_boxes_per_regular_layer: int
hierarchical_polygons_total: int
hierarchical_paths_total: int
hierarchical_texts_total: int
flattened_box_placements: int
flattened_poly_placements: int
estimated_flat_boxes_per_heavy_layer: int
estimated_flat_polygons_per_active_polygon_layer: int
def _scaled_count(value: int, scale: float, minimum: int = 0) -> int:
if value == 0:
return 0
scaled = int(math.ceil(value * scale))
return max(minimum, scaled)
def _scaled_preset(preset: FixturePreset, scale: float) -> FixturePreset:
if scale <= 0:
raise ValueError(f'scale must be positive, got {scale!r}')
return FixturePreset(
name=preset.name,
total_layers=preset.total_layers,
box_layers=min(preset.box_layers, preset.total_layers),
heavy_box_layers=min(preset.heavy_box_layers, preset.box_layers),
polygon_layers=min(preset.polygon_layers, preset.total_layers),
box_cells=_scaled_count(preset.box_cells, scale, minimum=1),
poly_cells=_scaled_count(preset.poly_cells, scale, minimum=1),
box_wrappers=_scaled_count(preset.box_wrappers, scale),
poly_wrappers=_scaled_count(preset.poly_wrappers, scale),
box_clusters=_scaled_count(preset.box_clusters, scale, minimum=1),
poly_clusters=_scaled_count(preset.poly_clusters, scale, minimum=1),
box_cluster_refs=_scaled_count(preset.box_cluster_refs, scale, minimum=1),
poly_cluster_refs=_scaled_count(preset.poly_cluster_refs, scale, minimum=1),
top_direct_box_refs=_scaled_count(preset.top_direct_box_refs, scale),
top_direct_poly_refs=_scaled_count(preset.top_direct_poly_refs, scale),
heavy_boxes_per_cell=max(1, preset.heavy_boxes_per_cell),
regular_boxes_per_cell=max(1, preset.regular_boxes_per_cell),
polygons_per_cell=max(1, preset.polygons_per_cell),
path_stride=max(1, preset.path_stride),
text_stride=max(1, preset.text_stride),
box_cluster_array=preset.box_cluster_array,
top_box_array=preset.top_box_array,
poly_cluster_array=preset.poly_cluster_array,
top_poly_array=preset.top_poly_array,
rare_annotation_stride=max(1, _scaled_count(preset.rare_annotation_stride, scale, minimum=1)),
)
def _rect_xy(xmin: int, ymin: int, xmax: int, ymax: int) -> numpy.ndarray[Any, numpy.dtype[numpy.int32]]:
return numpy.array(
[[xmin, ymin], [xmin, ymax], [xmax, ymax], [xmax, ymin], [xmin, ymin]],
dtype=numpy.int32,
)
def _poly_xy(points: list[tuple[int, int]]) -> numpy.ndarray[Any, numpy.dtype[numpy.int32]]:
closed = points + [points[0]]
return numpy.array(closed, dtype=numpy.int32)
def _sref(
target: str,
xy: tuple[int, int],
properties: dict[int, bytes] | None = None,
) -> elements.Reference:
return klamath.library.Reference(
struct_name=target.encode('ASCII'),
invert_y=False,
mag=1.0,
angle_deg=0.0,
xy=numpy.array([xy], dtype=numpy.int32),
colrow=None,
properties=EMPTY_PROPERTIES if properties is None else properties,
)
def _aref(
target: str,
origin: tuple[int, int],
counts: tuple[int, int],
step: tuple[int, int],
properties: dict[int, bytes] | None = None,
) -> elements.Reference:
cols, rows = counts
dx, dy = step
xy = numpy.array(
[
origin,
(origin[0] + cols * dx, origin[1]),
(origin[0], origin[1] + rows * dy),
],
dtype=numpy.int32,
)
return klamath.library.Reference(
struct_name=target.encode('ASCII'),
invert_y=False,
mag=1.0,
angle_deg=0.0,
xy=xy,
colrow=(cols, rows),
properties=EMPTY_PROPERTIES if properties is None else properties,
)
def _annotation(index: int) -> dict[int, bytes]:
return {1: f'perf-{index}'.encode('ASCII')}
def _make_box_cell(name: str, index: int, cfg: FixturePreset) -> list[elements.Element]:
cell_elements: list[elements.Element] = []
xbase = (index % 17) * 600
ybase = (index // 17) * 180
for layer in range(cfg.heavy_box_layers):
for box_idx in range(cfg.heavy_boxes_per_cell):
x0 = xbase + box_idx * 22
y0 = ybase + layer * 40
width = 10 + ((index + box_idx + layer) % 7) * 6
height = 10 + ((index * 3 + box_idx + layer) % 5) * 8
properties = _annotation(index) if index % cfg.rare_annotation_stride == 0 and box_idx == 0 and layer == 0 else EMPTY_PROPERTIES
cell_elements.append(elements.Boundary(
layer=(layer, 0),
xy=_rect_xy(x0, y0, x0 + width, y0 + height),
properties=properties,
))
for layer in range(cfg.heavy_box_layers, cfg.box_layers):
for box_idx in range(cfg.regular_boxes_per_cell):
x0 = xbase + box_idx * 38
y0 = ybase + (layer - cfg.heavy_box_layers) * 28 + 400
width = 18 + ((index + layer + box_idx) % 9) * 4
height = 12 + ((index + 2 * layer + box_idx) % 6) * 5
cell_elements.append(elements.Boundary(
layer=(layer, 0),
xy=_rect_xy(x0, y0, x0 + width, y0 + height),
properties=EMPTY_PROPERTIES,
))
return cell_elements
def _make_poly_cell(name: str, index: int, cfg: FixturePreset) -> list[elements.Element]:
cell_elements: list[elements.Element] = []
xbase = (index % 19) * 900
ybase = (index // 19) * 260
for poly_idx in range(cfg.polygons_per_cell):
layer = poly_idx % cfg.polygon_layers
dx = xbase + (poly_idx % 5) * 120
dy = ybase + (poly_idx // 5) * 80
size = 18 + ((index + poly_idx + layer) % 11) * 7
points = [
(dx, dy),
(dx + size, dy + size // 5),
(dx + size + size // 3, dy + size),
(dx + size // 2, dy + size + size // 2),
(dx - size // 4, dy + size // 2),
]
properties = _annotation(index) if poly_idx == 0 and index % cfg.rare_annotation_stride == 0 else EMPTY_PROPERTIES
cell_elements.append(elements.Boundary(
layer=(layer, 0),
xy=_poly_xy(points),
properties=properties,
))
if index % cfg.path_stride == 0:
layer = index % cfg.polygon_layers
cell_elements.append(elements.Path(
layer=(layer, 1),
path_type=2,
width=12 + (index % 5) * 4,
extension=(0, 0),
xy=numpy.array(
[
[xbase, ybase + 900],
[xbase + 240, ybase + 930],
[xbase + 420, ybase + 960],
],
dtype=numpy.int32,
),
properties=EMPTY_PROPERTIES,
))
if index % cfg.text_stride == 0:
layer = index % cfg.polygon_layers
properties = _annotation(index) if index % cfg.rare_annotation_stride == 0 else EMPTY_PROPERTIES
cell_elements.append(elements.Text(
layer=(layer, 2),
presentation=0,
path_type=0,
width=0,
invert_y=False,
mag=1.0,
angle_deg=0.0,
xy=numpy.array([[xbase + 64, ybase + 1536]], dtype=numpy.int32),
string=f'T{index:05d}'.encode('ASCII'),
properties=properties,
))
return cell_elements
def _write_struct(stream: Any, name: str, cell_elements: list[elements.Element]) -> None:
klamath.library.write_struct(stream, name=name.encode('ASCII'), elements=cell_elements)
def _box_name(index: int) -> str:
return f'box_{index:05d}'
def _poly_name(index: int) -> str:
return f'poly_{index:05d}'
def _box_wrapper_name(index: int) -> str:
return f'box_wrap_{index:05d}'
def _poly_wrapper_name(index: int) -> str:
return f'poly_wrap_{index:05d}'
def _box_cluster_name(index: int) -> str:
return f'box_cluster_{index:05d}'
def _poly_cluster_name(index: int) -> str:
return f'poly_cluster_{index:05d}'
def _write_box_cells(stream: Any, cfg: FixturePreset) -> None:
for idx in range(cfg.box_cells):
_write_struct(stream, _box_name(idx), _make_box_cell(_box_name(idx), idx, cfg))
def _write_poly_cells(stream: Any, cfg: FixturePreset) -> None:
for idx in range(cfg.poly_cells):
_write_struct(stream, _poly_name(idx), _make_poly_cell(_poly_name(idx), idx, cfg))
def _write_wrappers(stream: Any, cfg: FixturePreset) -> None:
for idx in range(cfg.box_wrappers):
target = _box_name(idx % cfg.box_cells)
origin = ((idx % 97) * 2_000, (idx // 97) * 2_000)
_write_struct(stream, _box_wrapper_name(idx), [_sref(target, origin)])
for idx in range(cfg.poly_wrappers):
target = _poly_name(idx % cfg.poly_cells)
origin = ((idx % 61) * 3_200, (idx // 61) * 3_200)
_write_struct(stream, _poly_wrapper_name(idx), [_sref(target, origin)])
def _write_box_clusters(stream: Any, cfg: FixturePreset) -> None:
array_refs = min(cfg.box_cluster_refs, max(1, (3 * cfg.box_cluster_refs) // 4))
for idx in range(cfg.box_clusters):
cell_elements: list[elements.Element] = []
for ref_idx in range(cfg.box_cluster_refs):
target = _box_name((idx * cfg.box_cluster_refs + ref_idx) % cfg.box_cells)
origin = (
(ref_idx % 6) * 48_000,
(ref_idx // 6) * 48_000,
)
if ref_idx < array_refs:
cell_elements.append(_aref(target, origin, cfg.box_cluster_array, (720, 900)))
else:
cell_elements.append(_sref(target, origin))
_write_struct(stream, _box_cluster_name(idx), cell_elements)
def _write_poly_clusters(stream: Any, cfg: FixturePreset) -> None:
array_refs = min(cfg.poly_cluster_refs, cfg.poly_cluster_refs // 2)
for idx in range(cfg.poly_clusters):
cell_elements: list[elements.Element] = []
for ref_idx in range(cfg.poly_cluster_refs):
target = _poly_name((idx * cfg.poly_cluster_refs + ref_idx) % cfg.poly_cells)
origin = (
(ref_idx % 10) * 96_000,
(ref_idx // 10) * 96_000,
)
if ref_idx < array_refs:
cell_elements.append(_aref(target, origin, cfg.poly_cluster_array, (12_000, 8_500)))
else:
cell_elements.append(_sref(target, origin))
_write_struct(stream, _poly_cluster_name(idx), cell_elements)
def _top_box_refs(cfg: FixturePreset) -> list[elements.Reference]:
refs: list[elements.Reference] = []
for idx in range(cfg.box_wrappers):
refs.append(_sref(
_box_wrapper_name(idx),
((idx % 240) * 240_000, (idx // 240) * 240_000),
))
for idx in range(cfg.box_clusters):
refs.append(_sref(
_box_cluster_name(idx),
((idx % 100) * 800_000, (idx // 100) * 800_000 + 14_000_000),
))
for idx in range(cfg.top_direct_box_refs):
target = _box_name(idx % cfg.box_cells)
origin = (
(idx % 150) * 160_000,
(idx // 150) * 160_000 + 26_000_000,
)
if cfg.top_box_array == (1, 1):
refs.append(_sref(target, origin))
else:
refs.append(_aref(target, origin, cfg.top_box_array, (1_100, 1_350)))
return refs
def _top_poly_refs(cfg: FixturePreset) -> list[elements.Reference]:
refs: list[elements.Reference] = []
for idx in range(cfg.poly_wrappers):
refs.append(_sref(
_poly_wrapper_name(idx),
((idx % 180) * 360_000, (idx // 180) * 360_000 + 44_000_000),
))
for idx in range(cfg.poly_clusters):
refs.append(_sref(
_poly_cluster_name(idx),
((idx % 70) * 1_100_000, (idx // 70) * 1_100_000 + 58_000_000),
))
for idx in range(cfg.top_direct_poly_refs):
target = _poly_name(idx % cfg.poly_cells)
origin = (
(idx % 110) * 420_000,
(idx // 110) * 420_000 + 72_000_000,
)
if cfg.top_poly_array == (1, 1):
refs.append(_sref(target, origin))
else:
refs.append(_aref(target, origin, cfg.top_poly_array, (16_000, 14_000)))
return refs
def _write_top(stream: Any, cfg: FixturePreset) -> None:
cell_elements: list[elements.Element] = []
cell_elements.extend(_top_box_refs(cfg))
cell_elements.extend(_top_poly_refs(cfg))
_write_struct(stream, 'TOP', cell_elements)
def _poly_paths_total(cfg: FixturePreset) -> int:
return (cfg.poly_cells - 1) // cfg.path_stride + 1
def _poly_texts_total(cfg: FixturePreset) -> int:
return (cfg.poly_cells - 1) // cfg.text_stride + 1
def _ref_instances_per_box_cluster(cfg: FixturePreset) -> int:
array_refs = min(cfg.box_cluster_refs, max(1, (3 * cfg.box_cluster_refs) // 4))
array_mult = cfg.box_cluster_array[0] * cfg.box_cluster_array[1]
return array_refs * array_mult + (cfg.box_cluster_refs - array_refs)
def _ref_instances_per_poly_cluster(cfg: FixturePreset) -> int:
array_refs = min(cfg.poly_cluster_refs, cfg.poly_cluster_refs // 2)
array_mult = cfg.poly_cluster_array[0] * cfg.poly_cluster_array[1]
return array_refs * array_mult + (cfg.poly_cluster_refs - array_refs)
def fixture_manifest(path: str | Path, preset: str, scale: float = 1.0) -> FixtureManifest:
base = PRESETS[preset]
cfg = _scaled_preset(base, scale)
flattened_box_placements = (
cfg.box_wrappers
+ cfg.box_clusters * _ref_instances_per_box_cluster(cfg)
+ cfg.top_direct_box_refs * cfg.top_box_array[0] * cfg.top_box_array[1]
)
flattened_poly_placements = (
cfg.poly_wrappers
+ cfg.poly_clusters * _ref_instances_per_poly_cluster(cfg)
+ cfg.top_direct_poly_refs * cfg.top_poly_array[0] * cfg.top_poly_array[1]
)
polygon_layers = max(1, cfg.polygon_layers)
polys_per_layer = (cfg.poly_cells * cfg.polygons_per_cell) // polygon_layers
return FixtureManifest(
preset=cfg.name,
scale=scale,
gds_path=str(Path(path)),
library_name=f'masque-perf-{cfg.name}',
cells=cfg.box_cells + cfg.poly_cells + cfg.box_wrappers + cfg.poly_wrappers + cfg.box_clusters + cfg.poly_clusters + 1,
refs=(
cfg.box_wrappers
+ cfg.poly_wrappers
+ cfg.box_clusters * cfg.box_cluster_refs
+ cfg.poly_clusters * cfg.poly_cluster_refs
+ cfg.box_wrappers + cfg.poly_wrappers + cfg.box_clusters + cfg.poly_clusters
+ cfg.top_direct_box_refs + cfg.top_direct_poly_refs
),
layers=cfg.total_layers,
box_layers=cfg.box_layers,
heavy_box_layers=[[layer, 0] for layer in range(cfg.heavy_box_layers)],
polygon_layers=[[layer, 0] for layer in range(cfg.polygon_layers)],
hierarchical_boxes_per_heavy_layer=cfg.box_cells * cfg.heavy_boxes_per_cell,
hierarchical_boxes_per_regular_layer=cfg.box_cells * cfg.regular_boxes_per_cell,
hierarchical_polygons_total=cfg.poly_cells * cfg.polygons_per_cell,
hierarchical_paths_total=_poly_paths_total(cfg),
hierarchical_texts_total=_poly_texts_total(cfg),
flattened_box_placements=flattened_box_placements,
flattened_poly_placements=flattened_poly_placements,
estimated_flat_boxes_per_heavy_layer=flattened_box_placements * cfg.heavy_boxes_per_cell,
estimated_flat_polygons_per_active_polygon_layer=flattened_poly_placements * polys_per_layer // cfg.poly_cells if cfg.poly_cells else 0,
)
def write_fixture(
path: str | Path,
*,
preset: str,
scale: float = 1.0,
write_manifest: bool = True,
) -> FixtureManifest:
if preset not in PRESETS:
known = ', '.join(sorted(PRESETS))
raise KeyError(f'unknown preset {preset!r}; expected one of: {known}')
manifest = fixture_manifest(path, preset, scale)
cfg = _scaled_preset(PRESETS[preset], scale)
output = Path(path)
output.parent.mkdir(parents=True, exist_ok=True)
with output.open('wb') as stream:
header = klamath.library.FileHeader(
name=manifest.library_name.encode('ASCII'),
user_units_per_db_unit=USER_UNITS_PER_DB_UNIT,
meters_per_db_unit=METERS_PER_DB_UNIT,
)
header.write(stream)
_write_box_cells(stream, cfg)
_write_poly_cells(stream, cfg)
_write_wrappers(stream, cfg)
_write_box_clusters(stream, cfg)
_write_poly_clusters(stream, cfg)
_write_top(stream, cfg)
klamath.records.ENDLIB.write(stream, None)
if write_manifest:
manifest_path = output.with_suffix(output.suffix + '.json')
manifest_path.write_text(json.dumps(asdict(manifest), indent=2, sort_keys=True) + '\n')
return manifest
def build_arg_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description='Generate synthetic GDS fixtures for GDS reader/writer performance work.')
parser.add_argument(
'preset',
nargs='?',
default='many_cells',
choices=sorted(PRESETS),
help='Fixture family to generate.',
)
parser.add_argument(
'output',
nargs='?',
help='Output .gds path. Defaults to build/gds_perf/<preset>.gds',
)
parser.add_argument(
'--scale',
type=float,
default=1.0,
help='Scale the preset counts down or up while keeping the same shape mix. Default: 1.0',
)
parser.add_argument(
'--no-manifest',
action='store_true',
help='Do not write the sidecar JSON manifest.',
)
return parser
def main(argv: list[str] | None = None) -> int:
parser = build_arg_parser()
args = parser.parse_args(argv)
output = Path(args.output) if args.output is not None else Path('build/gds_perf') / f'{args.preset}.gds'
manifest = write_fixture(output, preset=args.preset, scale=args.scale, write_manifest=not args.no_manifest)
print(json.dumps(asdict(manifest), indent=2, sort_keys=True))
return 0
if __name__ == '__main__':
raise SystemExit(main())

View file

@ -45,6 +45,10 @@ def _make_svg_ids(names: Mapping[str, Pattern]) -> dict[str, str]:
return svg_ids
def _detached_library(library: Mapping[str, Pattern]) -> dict[str, Pattern]:
return {name: pat.deepcopy() for name, pat in library.items()}
def writefile(
library: Mapping[str, Pattern],
top: str,
@ -53,13 +57,12 @@ def writefile(
annotate_ports: bool = False,
) -> None:
"""
Write a Pattern to an SVG file, by first calling .polygonize() on it
Write a Pattern to an SVG file, by first calling .polygonize() on a detached
materialized copy
to change the shapes into polygons, and then writing patterns as SVG
groups (<g>, inside <defs>), polygons as paths (<path>), and refs
as <use> elements.
Note that this function modifies the Pattern.
If `custom_attributes` is `True`, a non-standard `pattern_layer` attribute
is written to the relevant elements.
@ -71,19 +74,21 @@ def writefile(
prior to calling this function.
Args:
pattern: Pattern to write to file. Modified by this function.
library: Mapping of pattern names to patterns.
top: Name of the top-level pattern to render.
filename: Filename to write to.
custom_attributes: Whether to write non-standard `pattern_layer` attribute to the
SVG elements.
annotate_ports: If True, draw an arrow for each port (similar to
`Pattern.visualize(..., ports=True)`).
"""
pattern = library[top]
detached = _detached_library(library)
pattern = detached[top]
# Polygonize pattern
pattern.polygonize()
bounds = pattern.get_bounds(library=library)
bounds = pattern.get_bounds(library=detached)
if bounds is None:
bounds_min, bounds_max = numpy.array([[-1, -1], [1, 1]])
logger.warning('Pattern had no bounds (empty?); setting arbitrary viewbox', stacklevel=1)
@ -96,10 +101,10 @@ def writefile(
# Create file
svg = svgwrite.Drawing(filename, profile='full', viewBox=viewbox_string,
debug=(not custom_attributes))
svg_ids = _make_svg_ids(library)
svg_ids = _make_svg_ids(detached)
# Now create a group for each pattern and add in any Boundary and Use elements
for name, pat in library.items():
for name, pat in detached.items():
svg_group = svg.g(id=svg_ids[name], fill='blue', stroke='red')
for layer, shapes in pat.shapes.items():
@ -158,21 +163,21 @@ def writefile_inverted(
box and drawing the polygons with reverse vertex order inside it, all within
one `<path>` element.
Note that this function modifies the Pattern.
If you want pattern polygonized with non-default arguments, just call `pattern.polygonize()`
prior to calling this function.
Args:
pattern: Pattern to write to file. Modified by this function.
library: Mapping of pattern names to patterns.
top: Name of the top-level pattern to render.
filename: Filename to write to.
"""
pattern = library[top]
detached = _detached_library(library)
pattern = detached[top]
# Polygonize and flatten pattern
pattern.polygonize().flatten(library)
pattern.polygonize().flatten(detached)
bounds = pattern.get_bounds(library=library)
bounds = pattern.get_bounds(library=detached)
if bounds is None:
bounds_min, bounds_max = numpy.array([[-1, -1], [1, 1]])
logger.warning('Pattern had no bounds (empty?); setting arbitrary viewbox', stacklevel=1)

View file

@ -53,6 +53,22 @@ class Label(PositionableImpl, RepeatableImpl, AnnotatableImpl, Bounded, Pivotabl
self.repetition = repetition
self.annotations = annotations if annotations is not None else {}
@classmethod
def _from_raw(
cls,
string: str,
*,
offset: NDArray[numpy.float64],
repetition: Repetition | None = None,
annotations: annotations_t | None = None,
) -> Self:
new = cls.__new__(cls)
new._string = string
new._offset = offset
new._repetition = repetition
new._annotations = annotations
return new
def __copy__(self) -> Self:
return type(self)(
string=self.string,

View file

@ -14,7 +14,7 @@ Classes include:
- `AbstractView`: Provides a way to use []-indexing to generate abstracts for patterns in the linked
library. Generated with `ILibraryView.abstract_view()`.
"""
from typing import Self, TYPE_CHECKING, cast, TypeAlias, Protocol, Literal
from typing import Self, TYPE_CHECKING, Any, cast, TypeAlias, Protocol, Literal
from collections.abc import Iterator, Mapping, MutableMapping, Sequence, Callable
import logging
import re
@ -22,12 +22,14 @@ import copy
from pprint import pformat
from collections import defaultdict
from abc import ABCMeta, abstractmethod
from contextvars import ContextVar
from dataclasses import dataclass, replace
from graphlib import TopologicalSorter, CycleError
import numpy
from numpy.typing import ArrayLike, NDArray
from .error import LibraryError, PatternError
from .error import BuildError, LibraryError, PatternError
from .utils import layer_t, apply_transforms
from .shapes import Shape, Polygon
from .label import Label
@ -40,6 +42,11 @@ if TYPE_CHECKING:
logger = logging.getLogger(__name__)
_ACTIVE_BUILD_SESSIONS: ContextVar[dict[int, '_BuildSessionLibrary'] | None] = ContextVar(
'masque_active_build_sessions',
default=None,
)
class visitor_function_t(Protocol):
""" Signature for `Library.dfs()` visitor functions. """
@ -62,6 +69,69 @@ Tree: TypeAlias = MutableMapping[str, 'Pattern']
dangling_mode_t: TypeAlias = Literal['error', 'ignore', 'include']
""" How helpers should handle refs whose targets are not present in the library. """
emitted_via_t: TypeAlias = Literal['declaration', 'helper_write', 'tree_merge', 'source_import']
""" Build-provenance origin tags for emitted cells. """
@dataclass(frozen=True)
class CellProvenance:
"""
Provenance record for one cell in a completed build output.
Each output name in a `BuildReport` maps to one `CellProvenance`. The
record captures both where the cell came from and how its visible name was
chosen.
Attributes:
final_name: Name exposed by the completed library.
requested_name: First name requested for this cell during the build.
kind: Whether the cell came from a declaration, helper emission, or an
imported source library.
owner_declared_name: Declared cell responsible for this output cell, if
any. Imported source cells leave this as `None`.
emitted_via: High-level path by which the cell entered the output.
build_chain: Declared-cell dependency chain that was active when the
cell was emitted.
renamed_from: Original requested name when the final name differs.
source_name: Original on-source name for imported cells.
source_metadata: Optional source-library metadata copied through from
lazy GDS readers.
"""
final_name: str
requested_name: str
kind: Literal['declared', 'helper', 'source']
owner_declared_name: str | None
emitted_via: emitted_via_t
build_chain: tuple[str, ...]
renamed_from: str | None = None
source_name: str | None = None
source_metadata: dict[str, Any] | None = None
@dataclass(frozen=True)
class BuildReport:
"""
Immutable summary of one `BuildLibrary.validate()` or `.build()` run.
The report is designed to answer two questions after a build completes:
which declared cells depended on which other declared cells, and where each
output cell came from.
Attributes:
requested_roots: Roots explicitly requested for the run. A full
`build()` uses all declared cells.
provenance: Mapping from final output name to provenance metadata.
owned_cells: Mapping from declared cell name to all final output cell
names it owns, including helper cells emitted while that declared
cell was building.
dependency_graph: Declared-cell dependency graph discovered through
library-mediated reads and explicit recipe hints.
"""
requested_roots: tuple[str, ...]
provenance: Mapping[str, CellProvenance]
owned_cells: Mapping[str, tuple[str, ...]]
dependency_graph: Mapping[str, frozenset[str]]
SINGLE_USE_PREFIX = '_'
"""
@ -131,6 +201,15 @@ class ILibraryView(Mapping[str, 'Pattern'], metaclass=ABCMeta):
"""
return Abstract(name=name, ports=self[name].ports)
def source_order(self) -> tuple[str, ...]:
"""
Return names in the library's preferred source order.
Source-backed views may override this to preserve on-disk ordering
without materializing patterns.
"""
return tuple(self.keys())
def dangling_refs(
self,
tops: str | Sequence[str] | None = None,
@ -1388,6 +1467,819 @@ class Library(ILibrary):
return tree, pat
class BuiltLibrary(Library):
"""
Eager library returned by `BuildLibrary.build(output='library')`.
This is a normal materialized `Library` with one additional attribute,
`build_report`, which records how the library was assembled from
declarations, helper emissions, and imported source-backed cells.
"""
def __init__(
self,
mapping: MutableMapping[str, 'Pattern'] | None = None,
*,
build_report: BuildReport | None = None,
) -> None:
super().__init__(mapping=mapping)
self.build_report = build_report
class _CellFactory:
"""
Adapter that turns a plain pattern factory into a deferred recipe factory.
Calling the wrapper captures arguments and returns a `_BuildRecipe`
instead of executing the function immediately.
"""
def __init__(self, func: Callable[..., 'Pattern']) -> None:
self.func = func
self.__name__ = getattr(func, '__name__', type(self).__name__)
self.__doc__ = getattr(func, '__doc__')
def __call__(self, *args: Any, **kwargs: Any) -> '_BuildRecipe':
return _BuildRecipe(func=self.func, args=args, kwargs=kwargs)
@dataclass
class _BuildRecipe:
""" Captured deferred call to a pattern factory. """
func: Callable[..., 'Pattern']
args: tuple[Any, ...]
kwargs: dict[str, Any]
explicit_dependencies: tuple[str, ...] = ()
def depends_on(self, *names: str) -> '_BuildRecipe':
self.explicit_dependencies += tuple(names)
return self
@dataclass(frozen=True)
class _PatternDeclaration:
""" Declared cell backed by an already-built `Pattern`. """
pattern: 'Pattern'
@dataclass(frozen=True)
class _RecipeDeclaration:
""" Declared cell backed by a deferred recipe. """
recipe: _BuildRecipe
@dataclass(frozen=True)
class _SourceDeclaration:
"""
Imported source-backed names registered with a `BuildLibrary`.
The declaration stores visible-name remapping plus pre-scanned graph
metadata. Underlying source cells stay lazy until a build session
materializes or copies them through.
"""
library: ILibraryView
source_to_visible: Mapping[str, str]
visible_to_source: Mapping[str, str]
child_graph: Mapping[str, set[str]]
order: tuple[str, ...]
def cell(func: Callable[..., 'Pattern']) -> _CellFactory:
"""
Wrap a plain pattern factory so calls return deferred build recipes.
Use as either `cell(fn)(...)` or `@cell`.
"""
return _CellFactory(func)
class BuildCellsView:
"""
Attribute-based declaration namespace for `BuildLibrary`.
This is the ergonomic authoring surface exposed as `builder.cells`. It is
intentionally write-focused: attribute assignment and deletion register
declarations, while attribute reads fail with guidance to build first and
use the returned library.
"""
def __init__(self, library: 'BuildLibrary') -> None:
object.__setattr__(self, '_library', library)
def __getattr__(self, name: str) -> 'Pattern':
raise BuildError(
f'BuildLibrary.cells.{name} is write-only during authoring. '
'Call build() and index the returned library instead.'
)
def __setattr__(self, name: str, value: 'Pattern | _BuildRecipe') -> None:
if name.startswith('_'):
object.__setattr__(self, name, value)
return
self._library[name] = value
def __delattr__(self, name: str) -> None:
if name.startswith('_'):
raise AttributeError(name)
del self._library[name]
class BuildLibrary(ILibrary):
"""
Two-phase declaration surface for mixed imported/generated libraries.
A `BuildLibrary` collects three kinds of inputs:
- direct declared `Pattern` objects
- deferred recipes created with `cell(...)`
- imported source-backed library views added with `add_source(...)`
The builder itself is not a normal readable library during authoring.
Instead, `validate()` and `build()` create a temporary build-session library
that recipes can read from and write helper cells into while dependencies
are resolved. `build()` then freezes the builder on success and returns a
normal library-like object carrying a `build_report`.
"""
def __init__(self, *, check_on_register: bool = False) -> None:
self.check_on_register = check_on_register
self.cells = BuildCellsView(self)
self.last_build_report: BuildReport | None = None
self._frozen = False
self._declarations: dict[str, _PatternDeclaration | _RecipeDeclaration] = {}
self._sources: list[_SourceDeclaration] = []
self._names: set[str] = set()
self._order: list[str] = []
def _active_session(self) -> '_BuildSessionLibrary | None':
sessions = _ACTIVE_BUILD_SESSIONS.get()
if sessions is None:
return None
return sessions.get(id(self))
def _require_active_session(self, operation: str) -> '_BuildSessionLibrary':
session = self._active_session()
if session is None:
raise BuildError(
f'BuildLibrary.{operation}() is only available while validate() or build() is running. '
'Use the built output library for reads.'
)
return session
def _assert_editable(self) -> None:
if self._frozen:
raise BuildError('This BuildLibrary has already been built successfully and is now frozen.')
def __iter__(self) -> Iterator[str]:
session = self._active_session()
if session is not None:
return iter(session)
return iter(self._order)
def __len__(self) -> int:
session = self._active_session()
if session is not None:
return len(session)
return len(self._names)
def __contains__(self, key: object) -> bool:
session = self._active_session()
if session is not None:
return key in session
return key in self._names
def __getitem__(self, key: str) -> 'Pattern':
return self._require_active_session('__getitem__')[key]
def __setitem__(
self,
key: str,
value: 'Pattern | _BuildRecipe | Callable[[], Pattern]',
) -> None:
session = self._active_session()
if session is not None:
session[key] = value
return
self._assert_editable()
if key in self._names:
raise LibraryError(f'"{key}" already exists in the builder. Overwriting is not allowed!')
declaration: _PatternDeclaration | _RecipeDeclaration
if isinstance(value, _BuildRecipe):
declaration = _RecipeDeclaration(value)
else:
if callable(value):
raise TypeError('BuildLibrary recipes must be wrapped with cell(fn)(...) or @cell.')
declaration = _PatternDeclaration(value)
self._declarations[key] = declaration
self._names.add(key)
self._order.append(key)
if self.check_on_register:
try:
self.validate(names=(key,))
except Exception:
del self._declarations[key]
self._names.remove(key)
self._order.remove(key)
raise
def __delitem__(self, key: str) -> None:
session = self._active_session()
if session is not None:
del session[key]
return
self._assert_editable()
if key not in self._declarations:
raise KeyError(key)
del self._declarations[key]
self._names.remove(key)
self._order.remove(key)
def _merge(self, key_self: str, other: Mapping[str, 'Pattern'], key_other: str) -> None:
session = self._active_session()
if session is not None:
session._merge(key_self, other, key_other)
return
self[key_self] = copy.deepcopy(other[key_other])
def add(
self,
other: Mapping[str, 'Pattern'],
rename_theirs: Callable[['ILibraryView', str], str] = _rename_patterns,
mutate_other: bool = False,
) -> dict[str, str]:
session = self._active_session()
if session is not None:
return session.add(other, rename_theirs=rename_theirs, mutate_other=mutate_other)
return super().add(other, rename_theirs=rename_theirs, mutate_other=mutate_other)
def rename(
self,
old_name: str,
new_name: str,
move_references: bool = False,
) -> Self:
"""
Rename an imported source-backed visible name during authoring.
Only imported source-backed cells may be renamed on the builder itself.
Declared/generated cells must be registered under their intended final
names. `move_references=True` is intentionally unsupported here because
deferred recipes and declaration internals cannot be rewritten safely.
"""
session = self._active_session()
if session is not None:
session.rename(old_name, new_name, move_references=move_references)
return self
self._assert_editable()
if old_name == new_name:
return self
if old_name in self._declarations:
raise BuildError(
f'Cannot rename declared build cell "{old_name}" during authoring. '
'Register it under the intended final name instead.'
)
if old_name not in self._names:
raise LibraryError(f'"{old_name}" does not exist in the builder.')
if new_name in self._names:
raise LibraryError(f'"{new_name}" already exists in the builder.')
if move_references:
raise BuildError(
'BuildLibrary.rename(..., move_references=True) is not supported for imported source cells. '
'Builder-level renames only change the visible imported name.'
)
source_index = next(
(idx for idx, spec in enumerate(self._sources) if old_name in spec.visible_to_source),
None,
)
if source_index is None:
raise BuildError(
f'Cannot rename "{old_name}" during authoring because only imported source-backed '
'cells may be renamed on a BuildLibrary.'
)
spec = self._sources[source_index]
source_name = spec.visible_to_source[old_name]
source_to_visible = dict(spec.source_to_visible)
visible_to_source = dict(spec.visible_to_source)
order = list(spec.order)
source_to_visible[source_name] = new_name
del visible_to_source[old_name]
visible_to_source[new_name] = source_name
order[order.index(old_name)] = new_name
self._sources[source_index] = replace(
spec,
source_to_visible=source_to_visible,
visible_to_source=visible_to_source,
order=tuple(order),
)
self._names.remove(old_name)
self._names.add(new_name)
self._order[self._order.index(old_name)] = new_name
return self
def abstract(self, name: str) -> Abstract:
return self._require_active_session('abstract').abstract(name)
def resolve(
self,
other: 'Abstract | str | Pattern | TreeView',
append: bool = False,
) -> 'Abstract | Pattern':
return self._require_active_session('resolve').resolve(other, append=append)
def add_source(
self,
source: Mapping[str, 'Pattern'] | ILibraryView,
*,
rename_theirs: Callable[[ILibraryView, str], str] | None = None,
) -> dict[str, str]:
"""
Register an imported source-backed library with the builder.
The source is not materialized immediately. Instead, its names and
child graph are scanned once and stored as an import declaration. The
source may be renamed on entry to avoid collisions with existing
declarations or other imported sources.
Returns:
Mapping of `{source_name: visible_name}` for imported names that
were renamed while being added.
"""
self._assert_editable()
view = source if isinstance(source, ILibraryView) else LibraryView(source)
source_order = tuple(view.source_order())
child_graph = view.child_graph(dangling='include')
source_to_visible: dict[str, str] = {}
visible_to_source: dict[str, str] = {}
rename_map: dict[str, str] = {}
new_names: list[str] = []
for name in source_order:
visible = name
if visible in self._names or visible in visible_to_source:
if rename_theirs is None:
raise LibraryError(f'Conflicting name while adding source: {name!r}')
visible = rename_theirs(self, name)
if visible in self._names or visible in visible_to_source:
raise LibraryError(f'Unresolved duplicate key encountered while adding source: {name!r} -> {visible!r}')
rename_map[name] = visible
source_to_visible[name] = visible
visible_to_source[visible] = name
new_names.append(visible)
self._sources.append(_SourceDeclaration(
library=view,
source_to_visible=dict(source_to_visible),
visible_to_source=dict(visible_to_source),
child_graph={name: set(children) for name, children in child_graph.items()},
order=tuple(source_to_visible[name] for name in source_order),
))
for visible in new_names:
self._names.add(visible)
self._order.append(visible)
return rename_map
def validate(
self,
names: Sequence[str] | None = None,
*,
allow_dangling: bool = False,
) -> BuildReport:
"""
Run the full build logic and return a `BuildReport` without producing output.
This is a dry run over the same dependency resolution and recipe
execution path used by `build()`. Any generated library is discarded
after validation completes.
"""
report, _output = self._run_build(names=names, output='overlay', allow_dangling=allow_dangling, persist_output=False)
self.last_build_report = report
return report
def build(
self,
*,
output: Literal['overlay', 'library'] = 'overlay',
allow_dangling: bool = False,
) -> 'BuiltLibrary | ILibrary':
"""
Materialize declarations and return a usable output library.
Args:
output: `'overlay'` preserves imported source-backed cells where
possible, while `'library'` eagerly materializes the full
result.
allow_dangling: If `False`, fail the build when the completed
library still contains dangling references.
"""
self._assert_editable()
report, built_output = self._run_build(names=None, output=output, allow_dangling=allow_dangling, persist_output=True)
self._frozen = True
self.last_build_report = report
return built_output
def _run_build(
self,
*,
names: Sequence[str] | None,
output: Literal['overlay', 'library'],
allow_dangling: bool,
persist_output: bool,
) -> tuple[BuildReport, BuiltLibrary | ILibrary | None]:
roots = tuple(dict.fromkeys(names if names is not None else self._declarations.keys()))
unknown = [name for name in roots if name not in self._names]
if unknown:
raise BuildError(f'Unknown build roots requested: {unknown}')
session = _BuildSessionLibrary(self)
sessions = dict(_ACTIVE_BUILD_SESSIONS.get() or {})
sessions[id(self)] = session
token = _ACTIVE_BUILD_SESSIONS.set(sessions)
try:
session.materialize_many(roots)
if not allow_dangling:
session.child_graph(dangling='error')
if output == 'library':
built_output = session.to_library() if persist_output else None
elif persist_output:
built_output = session.to_overlay()
else:
built_output = None
finally:
_ACTIVE_BUILD_SESSIONS.reset(token)
report = session.build_report(roots)
if built_output is not None:
built_output.build_report = report
return report, built_output
class _BuildSessionLibrary(ILibrary):
"""
Internal overlay-backed library used while a `BuildLibrary` is executing.
This object provides the mutable-library surface that recipes expect while
also tracking declared-cell dependencies, helper-cell provenance, and
imported source cells. It exists only for the duration of a validation or
build run.
"""
def __init__(self, builder: BuildLibrary) -> None:
from .file.gdsii_lazy_core import BuiltOverlayLibrary, _SourceEntry, _SourceLayer # noqa: PLC0415
self._builder = builder
self._overlay = BuiltOverlayLibrary()
self._source_entry_type = _SourceEntry
self._source_layer_type = _SourceLayer
self._states: dict[str, Literal['unbuilt', 'building', 'built']] = {
name: 'unbuilt' for name in builder._declarations
}
self._declared_stack: list[str] = []
self._emission_stack: list[str] = []
self._emission_via_stack: list[emitted_via_t] = []
self._names = set(builder._names)
self._order = list(builder._order)
self._provenance: dict[str, CellProvenance] = {}
self._owned_cells: defaultdict[str, list[str]] = defaultdict(list)
self._dependency_graph: defaultdict[str, set[str]] = defaultdict(set)
self._install_sources()
def _install_sources(self) -> None:
for spec in self._builder._sources:
layer = self._source_layer_type(
library=spec.library,
source_to_visible=dict(spec.source_to_visible),
visible_to_source=dict(spec.visible_to_source),
child_graph={name: set(children) for name, children in spec.child_graph.items()},
order=list(spec.order),
)
layer_index = len(self._overlay._layers)
self._overlay._layers.append(layer)
source_info = getattr(spec.library, 'library_info', None)
source_meta = dict(source_info) if isinstance(source_info, dict) else None
for source_name, visible_name in spec.source_to_visible.items():
self._overlay._entries[visible_name] = self._source_entry_type(
layer_index=layer_index,
source_name=source_name,
)
if visible_name not in self._overlay._order:
self._overlay._order.append(visible_name)
self._provenance[visible_name] = CellProvenance(
final_name=visible_name,
requested_name=source_name,
kind='source',
owner_declared_name=None,
emitted_via='source_import',
build_chain=(),
renamed_from=source_name if visible_name != source_name else None,
source_name=source_name,
source_metadata=source_meta,
)
def __iter__(self) -> Iterator[str]:
return (name for name in self._order if name in self._names)
def __len__(self) -> int:
return len(self._names)
def __contains__(self, key: object) -> bool:
return key in self._names or key in self._overlay
def _touch_name(self, key: str) -> None:
if key not in self._names:
self._names.add(key)
self._order.append(key)
def _current_declared(self) -> str | None:
if not self._declared_stack:
return None
return self._declared_stack[-1]
def _record_dependency(self, target: str) -> None:
current = self._current_declared()
if current is None or current == target or target not in self._builder._declarations:
return
self._dependency_graph[current].add(target)
def _guard_mutable_output_name(self, key: str, *, operation: str) -> None:
if key in self._builder._declarations:
raise BuildError(f'Cannot {operation} declared build cell "{key}" during an active build session.')
provenance = self._provenance.get(key)
if provenance is not None and provenance.kind == 'source':
raise BuildError(f'Cannot {operation} imported source cell "{key}" during an active build session.')
def _remove_owned_cell(self, owner: str | None, name: str) -> None:
if owner is None or owner not in self._owned_cells:
return
cells = self._owned_cells[owner]
self._owned_cells[owner] = [cell for cell in cells if cell != name]
if not self._owned_cells[owner]:
del self._owned_cells[owner]
def rename(
self,
old_name: str,
new_name: str,
move_references: bool = False,
) -> Self:
if old_name == new_name:
return self
if old_name not in self._overlay:
if old_name in self._builder._declarations:
self._guard_mutable_output_name(old_name, operation='rename')
raise LibraryError(f'"{old_name}" does not exist in the library.')
self._guard_mutable_output_name(old_name, operation='rename')
if new_name in self._names:
raise LibraryError(f'"{new_name}" already exists in the library.')
self._overlay.rename(old_name, new_name, move_references=move_references)
self._names.discard(old_name)
self._names.add(new_name)
if old_name in self._order:
idx = self._order.index(old_name)
self._order[idx] = new_name
provenance = self._provenance.pop(old_name)
requested_name = provenance.requested_name
self._provenance[new_name] = replace(
provenance,
final_name=new_name,
renamed_from=requested_name if new_name != requested_name else None,
)
owner = provenance.owner_declared_name
if owner is not None and owner in self._owned_cells:
self._owned_cells[owner] = [
new_name if cell_name == old_name else cell_name
for cell_name in self._owned_cells[owner]
]
return self
def __getitem__(self, key: str) -> 'Pattern':
if key in self._builder._declarations:
self._record_dependency(key)
self._ensure_declared(key)
return self._overlay[key]
def __setitem__(
self,
key: str,
value: 'Pattern | Callable[[], Pattern]',
) -> None:
if key in self._overlay:
raise LibraryError(f'"{key}" already exists in the library. Overwriting is not allowed!')
current = self._current_declared()
if key in self._builder._declarations and key != current:
raise LibraryError(f'"{key}" is reserved for a declared cell and cannot be used as a helper name.')
pattern = value() if callable(value) else value
self._overlay[key] = pattern
self._touch_name(key)
kind: Literal['declared', 'helper']
via = self._emission_via_stack[-1] if self._emission_via_stack else 'helper_write'
if current is not None and key == current:
kind = 'declared'
via = 'declaration'
else:
kind = 'helper'
if not self._emission_via_stack:
via = 'helper_write'
self._emission_stack.append(key)
try:
self._record_provenance(
final_name=key,
requested_name=key,
kind=kind,
owner_declared_name=current if kind == 'helper' else key,
emitted_via=via,
build_chain=tuple(self._declared_stack),
renamed_from=None,
)
finally:
self._emission_stack.pop()
def __delitem__(self, key: str) -> None:
if key not in self._overlay:
if key in self._builder._declarations:
self._guard_mutable_output_name(key, operation='delete')
raise KeyError(key)
self._guard_mutable_output_name(key, operation='delete')
provenance = self._provenance.get(key)
if key in self._overlay:
del self._overlay[key]
self._names.discard(key)
if key in self._order:
self._order.remove(key)
self._provenance.pop(key, None)
if provenance is not None:
self._remove_owned_cell(provenance.owner_declared_name, key)
def _merge(self, key_self: str, other: Mapping[str, 'Pattern'], key_other: str) -> None:
self[key_self] = copy.deepcopy(other[key_other])
def add(
self,
other: Mapping[str, 'Pattern'],
rename_theirs: Callable[['ILibraryView', str], str] = _rename_patterns,
mutate_other: bool = False,
) -> dict[str, str]:
self._emission_via_stack.append('tree_merge')
try:
rename_map = super().add(other, rename_theirs=rename_theirs, mutate_other=mutate_other)
finally:
self._emission_via_stack.pop()
current = self._current_declared()
for old_name, new_name in rename_map.items():
if new_name in self._provenance:
self._provenance[new_name] = replace(
self._provenance[new_name],
requested_name=old_name,
renamed_from=old_name,
owner_declared_name=current if current is not None else self._provenance[new_name].owner_declared_name,
)
return rename_map
def _record_provenance(
self,
*,
final_name: str,
requested_name: str,
kind: Literal['declared', 'helper'],
owner_declared_name: str | None,
emitted_via: emitted_via_t,
build_chain: tuple[str, ...],
renamed_from: str | None,
) -> None:
self._provenance[final_name] = CellProvenance(
final_name=final_name,
requested_name=requested_name,
kind=kind,
owner_declared_name=owner_declared_name,
emitted_via=emitted_via,
build_chain=build_chain,
renamed_from=renamed_from,
)
if owner_declared_name is not None and final_name not in self._owned_cells[owner_declared_name]:
self._owned_cells[owner_declared_name].append(final_name)
def _wrap_error(self, name: str, exc: Exception) -> BuildError:
helper = self._emission_stack[-1] if self._emission_stack else None
chain = tuple(self._declared_stack)
msg = [f'Failed while building declared cell "{name}"']
if helper is not None and helper != name:
msg.append(f'while materializing helper/output "{helper}"')
if chain:
msg.append(f'Dependency chain: {" -> ".join(chain)}')
msg.append(f'Cause: {exc}')
return BuildError('\n'.join(msg))
def _ensure_named(self, name: str) -> None:
if name in self._builder._declarations:
self._record_dependency(name)
self._ensure_declared(name)
return
if name in self._overlay:
return
raise BuildError(f'Missing dependency "{name}"')
def _ensure_declared(self, name: str) -> None:
from .pattern import Pattern # noqa: PLC0415
state = self._states[name]
if state == 'built':
return
if state == 'building':
chain = ' -> '.join(self._declared_stack + [name])
raise BuildError(f'Cycle detected while building declared cells: {chain}')
declaration = self._builder._declarations[name]
self._states[name] = 'building'
self._declared_stack.append(name)
try:
if isinstance(declaration, _PatternDeclaration):
pattern = declaration.pattern.deepcopy()
else:
for dep in declaration.recipe.explicit_dependencies:
self._ensure_named(dep)
pattern = declaration.recipe.func(*declaration.recipe.args, **declaration.recipe.kwargs)
if not isinstance(pattern, Pattern):
raise BuildError(f'Recipe for "{name}" returned {type(pattern).__name__}, expected Pattern')
if name in self._overlay:
if self._overlay[name] is not pattern:
raise BuildError(
f'Recipe for "{name}" wrote a different pattern into the session under its own name.'
)
else:
self[name] = pattern
self._states[name] = 'built'
except Exception as exc:
self._states[name] = 'unbuilt'
raise self._wrap_error(name, exc) from exc
finally:
self._declared_stack.pop()
def materialize_many(self, names: Sequence[str]) -> None:
for name in dict.fromkeys(names):
self._ensure_named(name)
def source_order(self) -> tuple[str, ...]:
return self._overlay.source_order()
def child_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
return self._overlay.child_graph(dangling=dangling)
def parent_graph(
self,
dangling: dangling_mode_t = 'error',
) -> dict[str, set[str]]:
return self._overlay.parent_graph(dangling=dangling)
def build_report(self, requested_roots: Sequence[str]) -> BuildReport:
dependency_graph = {
name: frozenset(self._dependency_graph.get(name, set()))
for name in self._builder._declarations
if name in self._dependency_graph or name in requested_roots
}
owned_cells = {
name: tuple(cells)
for name, cells in self._owned_cells.items()
}
return BuildReport(
requested_roots=tuple(dict.fromkeys(requested_roots)),
provenance=dict(self._provenance),
owned_cells=owned_cells,
dependency_graph=dependency_graph,
)
def to_overlay(self) -> ILibrary:
return self._overlay
def to_library(self) -> BuiltLibrary:
mapping = {name: self._overlay[name] for name in self._overlay.source_order()}
return BuiltLibrary(mapping)
class LazyLibrary(ILibrary):
"""
This class is usually used to create a library of Patterns by mapping names to

View file

@ -86,6 +86,26 @@ class Ref(
self.repetition = repetition
self.annotations = annotations if annotations is not None else {}
@classmethod
def _from_raw(
cls,
*,
offset: NDArray[numpy.float64],
rotation: float,
mirrored: bool,
scale: float,
repetition: Repetition | None,
annotations: annotations_t | None,
) -> Self:
new = cls.__new__(cls)
new._offset = offset
new._rotation = rotation % (2 * pi)
new._scale = scale
new._mirrored = mirrored
new._repetition = repetition
new._annotations = annotations
return new
def __copy__(self) -> 'Ref':
new = Ref(
offset=self.offset.copy(),

View file

@ -113,6 +113,22 @@ class Grid(Repetition):
self.a_count = a_count
self.b_count = b_count
@classmethod
def _from_raw(
cls: type[GG],
*,
a_vector: NDArray[numpy.float64],
a_count: int,
b_vector: NDArray[numpy.float64],
b_count: int,
) -> GG:
new = cls.__new__(cls)
new._a_vector = a_vector
new._b_vector = b_vector
new._a_count = int(a_count)
new._b_count = int(b_count)
return new
@classmethod
def aligned(
cls: type[GG],

View file

@ -11,6 +11,7 @@ from .shape import (
from .polygon import Polygon as Polygon
from .poly_collection import PolyCollection as PolyCollection
from .rect_collection import RectCollection as RectCollection
from .circle import Circle as Circle
from .ellipse import Ellipse as Ellipse
from .arc import Arc as Arc

View file

@ -197,21 +197,7 @@ class Arc(PositionableImpl, Shape):
repetition: Repetition | None = None,
annotations: annotations_t = None,
angle_ref: ArcAngleRef | str = ArcAngleRef.Center,
raw: bool = False,
) -> None:
if raw:
assert isinstance(radii, numpy.ndarray)
assert isinstance(angles, numpy.ndarray)
assert isinstance(offset, numpy.ndarray)
self._radii = radii
self._angles = angles
self._width = width
self._offset = offset
self._rotation = rotation
self._angle_ref = ArcAngleRef(angle_ref)
self._repetition = repetition
self._annotations = annotations
else:
self.radii = radii
self.angles = angles
self.width = width
@ -221,6 +207,29 @@ class Arc(PositionableImpl, Shape):
self.repetition = repetition
self.annotations = annotations
@classmethod
def _from_raw(
cls,
*,
radii: NDArray[numpy.float64],
angles: NDArray[numpy.float64],
width: float,
offset: NDArray[numpy.float64],
rotation: float,
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> 'Arc':
new = cls.__new__(cls)
new._radii = radii
new._angles = angles
new._width = width
new._offset = offset
new._rotation = rotation % (2 * pi)
new._angle_ref = ArcAngleRef(angle_ref)
new._repetition = repetition
new._annotations = annotations
return new
def __deepcopy__(self, memo: dict | None = None) -> 'Arc':
memo = {} if memo is None else memo
new = copy.copy(self)

View file

@ -50,20 +50,28 @@ class Circle(PositionableImpl, Shape):
offset: ArrayLike = (0.0, 0.0),
repetition: Repetition | None = None,
annotations: annotations_t = None,
raw: bool = False,
) -> None:
if raw:
assert isinstance(offset, numpy.ndarray)
self._radius = radius
self._offset = offset
self._repetition = repetition
self._annotations = annotations
else:
self.radius = radius
self.offset = offset
self.repetition = repetition
self.annotations = annotations
@classmethod
def _from_raw(
cls,
*,
radius: float,
offset: NDArray[numpy.float64],
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> 'Circle':
new = cls.__new__(cls)
new._radius = radius
new._offset = offset
new._repetition = repetition
new._annotations = annotations
return new
def __deepcopy__(self, memo: dict | None = None) -> 'Circle':
memo = {} if memo is None else memo
new = copy.copy(self)

View file

@ -95,23 +95,31 @@ class Ellipse(PositionableImpl, Shape):
rotation: float = 0,
repetition: Repetition | None = None,
annotations: annotations_t = None,
raw: bool = False,
) -> None:
if raw:
assert isinstance(radii, numpy.ndarray)
assert isinstance(offset, numpy.ndarray)
self._radii = radii
self._offset = offset
self._rotation = rotation
self._repetition = repetition
self._annotations = annotations
else:
self.radii = radii
self.offset = offset
self.rotation = rotation
self.repetition = repetition
self.annotations = annotations
@classmethod
def _from_raw(
cls,
*,
radii: NDArray[numpy.float64],
offset: NDArray[numpy.float64],
rotation: float,
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> Self:
new = cls.__new__(cls)
new._radii = radii
new._offset = offset
new._rotation = rotation % pi
new._repetition = repetition
new._annotations = annotations
return new
def __deepcopy__(self, memo: dict | None = None) -> Self:
memo = {} if memo is None else memo
new = copy.copy(self)

View file

@ -201,20 +201,9 @@ class Path(Shape):
rotation: float = 0,
repetition: Repetition | None = None,
annotations: annotations_t = None,
raw: bool = False,
) -> None:
self._cap_extensions = None # Since .cap setter might access it
if raw:
assert isinstance(vertices, numpy.ndarray)
assert isinstance(cap_extensions, numpy.ndarray) or cap_extensions is None
self._vertices = vertices
self._repetition = repetition
self._annotations = annotations
self._width = width
self._cap = cap
self._cap_extensions = cap_extensions
else:
self.vertices = vertices
self.repetition = repetition
self.annotations = annotations
@ -229,6 +218,26 @@ class Path(Shape):
if numpy.any(offset):
self.translate(offset)
@classmethod
def _from_raw(
cls,
*,
vertices: NDArray[numpy.float64],
width: float,
cap: PathCap,
cap_extensions: NDArray[numpy.float64] | None = None,
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> Self:
new = cls.__new__(cls)
new._vertices = vertices
new._width = width
new._cap = cap
new._cap_extensions = cap_extensions
new._repetition = repetition
new._annotations = annotations
return new
def __deepcopy__(self, memo: dict | None = None) -> 'Path':
memo = {} if memo is None else memo
new = copy.copy(self)

View file

@ -34,7 +34,7 @@ class PolyCollection(Shape):
_vertex_lists: NDArray[numpy.float64]
""" 2D NDArray ((N+M+...) x 2) of vertices `[[xa0, ya0], [xa1, ya1], ..., [xb0, yb0], [xb1, yb1], ... ]` """
_vertex_offsets: NDArray[numpy.intp]
_vertex_offsets: NDArray[numpy.integer[Any]]
""" 1D NDArray specifying the starting offset for each polygon """
@property
@ -45,7 +45,7 @@ class PolyCollection(Shape):
return self._vertex_lists
@property
def vertex_offsets(self) -> NDArray[numpy.intp]:
def vertex_offsets(self) -> NDArray[numpy.integer[Any]]:
"""
Starting offset (in `vertex_lists`) for each polygon
"""
@ -63,7 +63,7 @@ class PolyCollection(Shape):
chain(self._vertex_offsets[1:], [self._vertex_lists.shape[0]]),
strict=True,
):
yield slice(ii, ff)
yield slice(int(ii), int(ff))
@property
def polygon_vertices(self) -> Iterator[NDArray[numpy.float64]]:
@ -100,16 +100,7 @@ class PolyCollection(Shape):
rotation: float = 0.0,
repetition: Repetition | None = None,
annotations: annotations_t = None,
raw: bool = False,
) -> None:
if raw:
assert isinstance(vertex_lists, numpy.ndarray)
assert isinstance(vertex_offsets, numpy.ndarray)
self._vertex_lists = vertex_lists
self._vertex_offsets = vertex_offsets
self._repetition = repetition
self._annotations = annotations
else:
self._vertex_lists = numpy.asarray(vertex_lists, dtype=float)
self._vertex_offsets = numpy.asarray(vertex_offsets, dtype=numpy.intp)
self.repetition = repetition
@ -119,6 +110,22 @@ class PolyCollection(Shape):
if numpy.any(offset):
self.translate(offset)
@classmethod
def _from_raw(
cls,
*,
vertex_lists: NDArray[numpy.float64],
vertex_offsets: NDArray[numpy.integer[Any]],
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> Self:
new = cls.__new__(cls)
new._vertex_lists = vertex_lists
new._vertex_offsets = vertex_offsets
new._repetition = repetition
new._annotations = annotations
return new
def __deepcopy__(self, memo: dict | None = None) -> Self:
memo = {} if memo is None else memo
new = copy.copy(self)
@ -132,7 +139,7 @@ class PolyCollection(Shape):
return (
type(self) is type(other)
and numpy.array_equal(self._vertex_lists, other._vertex_lists)
and numpy.array_equal(self._vertex_offsets, other._vertex_offsets)
and numpy.array_equal(self.vertex_offsets, other.vertex_offsets)
and self.repetition == other.repetition
and annotations_eq(self.annotations, other.annotations)
)
@ -215,11 +222,11 @@ class PolyCollection(Shape):
# TODO: normalize mirroring?
return ((type(self), rotated_vertices.data.tobytes() + self._vertex_offsets.tobytes()),
return ((type(self), rotated_vertices.data.tobytes() + self.vertex_offsets.tobytes()),
(offset, scale / norm_value, rotation, False),
lambda: PolyCollection(
vertex_lists=rotated_vertices * norm_value,
vertex_offsets=self._vertex_offsets.copy(),
vertex_offsets=self.vertex_offsets.copy(),
),
)

View file

@ -115,14 +115,7 @@ class Polygon(Shape):
rotation: float = 0.0,
repetition: Repetition | None = None,
annotations: annotations_t = None,
raw: bool = False,
) -> None:
if raw:
assert isinstance(vertices, numpy.ndarray)
self._vertices = vertices
self._repetition = repetition
self._annotations = annotations
else:
self.vertices = vertices
self.repetition = repetition
self.annotations = annotations
@ -131,6 +124,20 @@ class Polygon(Shape):
if numpy.any(offset):
self.translate(offset)
@classmethod
def _from_raw(
cls,
*,
vertices: NDArray[numpy.float64],
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> Self:
new = cls.__new__(cls)
new._vertices = vertices
new._repetition = repetition
new._annotations = annotations
return new
def __deepcopy__(self, memo: dict | None = None) -> 'Polygon':
memo = {} if memo is None else memo
new = copy.copy(self)

View file

@ -0,0 +1,249 @@
from typing import Any, cast, Self
from collections.abc import Iterator
import copy
import functools
import numpy
from numpy import pi
from numpy.typing import NDArray, ArrayLike
from . import Shape, normalized_shape_tuple
from .polygon import Polygon
from ..error import PatternError
from ..repetition import Repetition
from ..utils import annotations_lt, annotations_eq, rep2key, annotations_t
def _normalize_rects(rects: ArrayLike) -> NDArray[numpy.float64]:
arr = numpy.asarray(rects, dtype=float)
if arr.ndim != 2 or arr.shape[1] != 4:
raise PatternError('Rectangles must be an Nx4 array of [xmin, ymin, xmax, ymax]')
if numpy.any(arr[:, 0] > arr[:, 2]) or numpy.any(arr[:, 1] > arr[:, 3]):
raise PatternError('Rectangles must satisfy xmin <= xmax and ymin <= ymax')
if arr.shape[0] <= 1:
return arr
order = numpy.lexsort((arr[:, 3], arr[:, 2], arr[:, 1], arr[:, 0]))
return arr[order]
def _renormalize_rects_in_place(rects: NDArray[numpy.float64]) -> None:
x0 = numpy.minimum(rects[:, 0], rects[:, 2])
x1 = numpy.maximum(rects[:, 0], rects[:, 2])
y0 = numpy.minimum(rects[:, 1], rects[:, 3])
y1 = numpy.maximum(rects[:, 1], rects[:, 3])
rects[:, 0] = x0
rects[:, 1] = y0
rects[:, 2] = x1
rects[:, 3] = y1
@functools.total_ordering
class RectCollection(Shape):
"""
A collection of axis-aligned rectangles, stored as an Nx4 array of
`[xmin, ymin, xmax, ymax]` rows.
"""
__slots__ = (
'_rects',
'_repetition', '_annotations',
)
_rects: NDArray[numpy.float64]
@property
def rects(self) -> NDArray[numpy.float64]:
return self._rects
@rects.setter
def rects(self, val: ArrayLike) -> None:
self._rects = _normalize_rects(val)
@property
def offset(self) -> NDArray[numpy.float64]:
return numpy.zeros(2)
@offset.setter
def offset(self, val: ArrayLike) -> None:
if numpy.any(val):
raise PatternError('RectCollection offset is forced to (0, 0)')
def set_offset(self, val: ArrayLike) -> Self:
if numpy.any(val):
raise PatternError('RectCollection offset is forced to (0, 0)')
return self
def translate(self, offset: ArrayLike) -> Self:
delta = numpy.asarray(offset, dtype=float).reshape(2)
self._rects[:, [0, 2]] += delta[0]
self._rects[:, [1, 3]] += delta[1]
return self
def __init__(
self,
rects: ArrayLike,
*,
offset: ArrayLike = (0.0, 0.0),
rotation: float = 0.0,
repetition: Repetition | None = None,
annotations: annotations_t = None,
) -> None:
self.rects = rects
self.repetition = repetition
self.annotations = annotations
if rotation:
self.rotate(rotation)
if numpy.any(offset):
self.translate(offset)
@classmethod
def _from_raw(
cls,
*,
rects: NDArray[numpy.float64],
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> Self:
new = cls.__new__(cls)
new._rects = rects
new._repetition = repetition
new._annotations = annotations
return new
@property
def polygon_vertices(self) -> Iterator[NDArray[numpy.float64]]:
for rect in self._rects:
xmin, ymin, xmax, ymax = rect
yield numpy.array([
[xmin, ymin],
[xmin, ymax],
[xmax, ymax],
[xmax, ymin],
], dtype=float)
def __deepcopy__(self, memo: dict | None = None) -> Self:
memo = {} if memo is None else memo
new = copy.copy(self)
new._rects = self._rects.copy()
new._repetition = copy.deepcopy(self._repetition, memo)
new._annotations = copy.deepcopy(self._annotations)
return new
def _sorted_rects(self) -> NDArray[numpy.float64]:
if self._rects.shape[0] <= 1:
return self._rects
order = numpy.lexsort((self._rects[:, 3], self._rects[:, 2], self._rects[:, 1], self._rects[:, 0]))
return self._rects[order]
def __eq__(self, other: Any) -> bool:
return (
type(self) is type(other)
and numpy.array_equal(self._sorted_rects(), other._sorted_rects())
and self.repetition == other.repetition
and annotations_eq(self.annotations, other.annotations)
)
def __lt__(self, other: Shape) -> bool:
if type(self) is not type(other):
if repr(type(self)) != repr(type(other)):
return repr(type(self)) < repr(type(other))
return id(type(self)) < id(type(other))
other = cast('RectCollection', other)
self_rects = self._sorted_rects()
other_rects = other._sorted_rects()
if not numpy.array_equal(self_rects, other_rects):
min_len = min(self_rects.shape[0], other_rects.shape[0])
eq_mask = self_rects[:min_len] != other_rects[:min_len]
eq_lt = self_rects[:min_len] < other_rects[:min_len]
eq_lt_masked = eq_lt[eq_mask]
if eq_lt_masked.size > 0:
return bool(eq_lt_masked.flat[0])
return self_rects.shape[0] < other_rects.shape[0]
if self.repetition != other.repetition:
return rep2key(self.repetition) < rep2key(other.repetition)
return annotations_lt(self.annotations, other.annotations)
def to_polygons(
self,
num_vertices: int | None = None, # unused # noqa: ARG002
max_arclen: float | None = None, # unused # noqa: ARG002
) -> list[Polygon]:
return [
Polygon(
vertices=vertices,
repetition=copy.deepcopy(self.repetition),
annotations=copy.deepcopy(self.annotations),
)
for vertices in self.polygon_vertices
]
def get_bounds_single(self) -> NDArray[numpy.float64] | None:
if self._rects.size == 0:
return None
mins = self._rects[:, :2].min(axis=0)
maxs = self._rects[:, 2:].max(axis=0)
return numpy.vstack((mins, maxs))
def rotate(self, theta: float) -> Self:
quarter_turns = int(numpy.rint(theta / (pi / 2)))
if not numpy.isclose(theta, quarter_turns * (pi / 2)):
raise PatternError('RectCollection only supports Manhattan rotations')
turns = quarter_turns % 4
if turns == 0 or self._rects.size == 0:
return self
corners = numpy.stack((
self._rects[:, [0, 1]],
self._rects[:, [0, 3]],
self._rects[:, [2, 3]],
self._rects[:, [2, 1]],
), axis=1)
flat = corners.reshape(-1, 2)
if turns == 1:
rotated = numpy.column_stack((-flat[:, 1], flat[:, 0]))
elif turns == 2:
rotated = -flat
else:
rotated = numpy.column_stack((flat[:, 1], -flat[:, 0]))
corners = rotated.reshape(corners.shape)
self._rects[:, 0] = corners[:, :, 0].min(axis=1)
self._rects[:, 1] = corners[:, :, 1].min(axis=1)
self._rects[:, 2] = corners[:, :, 0].max(axis=1)
self._rects[:, 3] = corners[:, :, 1].max(axis=1)
return self
def mirror(self, axis: int = 0) -> Self:
if axis not in (0, 1):
raise PatternError('Axis must be 0 or 1')
if axis == 0:
self._rects[:, [1, 3]] *= -1
else:
self._rects[:, [0, 2]] *= -1
_renormalize_rects_in_place(self._rects)
return self
def scale_by(self, c: float) -> Self:
self._rects *= c
_renormalize_rects_in_place(self._rects)
return self
def normalized_form(self, norm_value: float) -> normalized_shape_tuple:
rects = self._sorted_rects()
centers = 0.5 * (rects[:, :2] + rects[:, 2:])
offset = centers.mean(axis=0)
zeroed = rects.copy()
zeroed[:, [0, 2]] -= offset[0]
zeroed[:, [1, 3]] -= offset[1]
normed = zeroed / norm_value
return (
(type(self), normed.data.tobytes()),
(offset, 1.0, 0.0, False),
lambda: RectCollection(rects=normed * norm_value),
)
def __repr__(self) -> str:
if self._rects.size == 0:
return '<RectCollection r0>'
centers = 0.5 * (self._rects[:, :2] + self._rects[:, 2:])
centroid = centers.mean(axis=0)
return f'<RectCollection centroid {centroid} r{self._rects.shape[0]}>'

View file

@ -73,18 +73,7 @@ class Text(PositionableImpl, RotatableImpl, Shape):
mirrored: bool = False,
repetition: Repetition | None = None,
annotations: annotations_t = None,
raw: bool = False,
) -> None:
if raw:
assert isinstance(offset, numpy.ndarray)
self._offset = offset
self._string = string
self._height = height
self._rotation = rotation
self._mirrored = mirrored
self._repetition = repetition
self._annotations = annotations
else:
self.offset = offset
self.string = string
self.height = height
@ -94,6 +83,30 @@ class Text(PositionableImpl, RotatableImpl, Shape):
self.annotations = annotations
self.font_path = font_path
@classmethod
def _from_raw(
cls,
*,
string: str,
height: float,
font_path: str,
offset: NDArray[numpy.float64],
rotation: float,
mirrored: bool,
annotations: annotations_t = None,
repetition: Repetition | None = None,
) -> Self:
new = cls.__new__(cls)
new._offset = offset
new._string = string
new._height = height
new._rotation = rotation % (2 * pi)
new._mirrored = mirrored
new._repetition = repetition
new._annotations = annotations
new.font_path = font_path
return new
def __deepcopy__(self, memo: dict | None = None) -> Self:
memo = {} if memo is None else memo
new = copy.copy(self)

View file

@ -0,0 +1,315 @@
import pytest
from ..builder import Pather
from ..error import BuildError
from ..library import BuildLibrary, BuiltLibrary, Library, cell
from ..pattern import Pattern
from ..ports import Port
def test_build_library_traces_declared_dependencies_out_of_order() -> None:
builder = BuildLibrary()
def make_parent(lib: BuildLibrary) -> Pattern:
pat = Pattern()
pat.ref("child")
assert lib.abstract("child").name == "child"
return pat
builder.cells.parent = cell(make_parent)(builder)
builder["child"] = Pattern(ports={"p": Port((0, 0), 0)})
built = builder.build()
assert "parent" in built
assert "child" in built
assert built.build_report.dependency_graph["parent"] == frozenset({"child"})
assert built.build_report.provenance["parent"].kind == "declared"
def test_build_library_tracks_helper_provenance_and_tree_merge_renames() -> None:
builder = BuildLibrary()
def make_top(lib: BuildLibrary) -> Pattern:
tree = Library({"_helper": Pattern()})
name_a = lib << tree
name_b = lib << tree
top = Pattern()
top.ref(name_a)
top.ref(name_b)
return top
builder.cells.top = cell(make_top)(builder)
built = builder.build()
report = built.build_report
helpers = [
prov for prov in report.provenance.values()
if prov.owner_declared_name == "top" and prov.kind == "helper"
]
assert "top" in report.owned_cells["top"]
assert len(helpers) == 2
assert all(prov.emitted_via == "tree_merge" for prov in helpers)
assert any(prov.renamed_from == "_helper" for prov in helpers)
def test_build_library_requires_build_session_for_reads_and_freezes_after_build() -> None:
builder = BuildLibrary()
builder["leaf"] = Pattern()
with pytest.raises(BuildError, match="validate\\(\\) or build\\(\\)"):
_ = builder["leaf"]
with pytest.raises(BuildError, match="write-only"):
_ = builder.cells.leaf
built = builder.build(output="library")
assert isinstance(built, BuiltLibrary)
assert built.build_report.requested_roots == ("leaf",)
with pytest.raises(BuildError, match="frozen"):
builder["later"] = Pattern()
with pytest.raises(BuildError, match="frozen"):
builder.build()
def test_build_library_validate_is_retryable_after_failure() -> None:
builder = BuildLibrary()
def make_parent(lib: BuildLibrary) -> Pattern:
pat = Pattern()
pat.ref("child")
lib.abstract("child")
return pat
builder.cells.parent = cell(make_parent)(builder)
with pytest.raises(BuildError, match='Failed while building declared cell "parent"'):
builder.validate()
builder["child"] = Pattern(ports={"p": Port((0, 0), 0)})
report = builder.validate()
assert report.dependency_graph["parent"] == frozenset({"child"})
def test_build_library_check_on_register_rolls_back_failed_declarations() -> None:
builder = BuildLibrary(check_on_register=True)
def make_parent(lib: BuildLibrary) -> Pattern:
pat = Pattern()
pat.ref("child")
lib.abstract("child")
return pat
with pytest.raises(BuildError, match='Failed while building declared cell "parent"'):
builder.cells.parent = cell(make_parent)(builder)
assert "parent" not in builder
def test_build_library_depends_on_supports_hidden_dependencies_for_partial_validation() -> None:
builder = BuildLibrary()
builder["child"] = Pattern()
def make_parent() -> Pattern:
pat = Pattern()
pat.ref("child")
return pat
builder.cells.parent = cell(make_parent)().depends_on("child")
report = builder.validate(names=("parent",))
assert report.requested_roots == ("parent",)
assert report.dependency_graph["parent"] == frozenset({"child"})
def test_build_library_validate_rejects_removed_output_argument() -> None:
builder = BuildLibrary()
builder["leaf"] = Pattern()
with pytest.raises(TypeError):
builder.validate(output="library") # type: ignore[call-arg]
def test_build_library_allows_helper_writes_via_pather() -> None:
builder = BuildLibrary()
builder["leaf"] = Pattern(ports={"a": Port((0, 0), 0)})
def make_top(lib: BuildLibrary) -> Pattern:
helper = Pather(library=lib, ports="leaf", name="_route")
top = Pattern()
top.ref("_route")
top.ref("leaf")
top.ports.update(helper.pattern.ports)
return top
builder.cells.top = cell(make_top)(builder)
built = builder.build()
helper_prov = built.build_report.provenance["_route"]
assert helper_prov.kind == "helper"
assert helper_prov.owner_declared_name == "top"
def test_build_library_preserves_source_cells_and_records_source_provenance() -> None:
source = Library({"src": Pattern()})
builder = BuildLibrary()
builder.add_source(source)
builder.cells.top = cell(lambda: Pattern())()
built = builder.build()
assert "src" in built
assert built.build_report.provenance["src"].kind == "source"
assert built.build_report.provenance["src"].emitted_via == "source_import"
def test_build_library_can_rename_imported_source_cells_during_authoring() -> None:
source = Library()
source["child"] = Pattern()
parent = Pattern()
parent.ref("child")
source["parent"] = parent
builder = BuildLibrary()
builder.add_source(source)
builder.rename("child", "renamed_child")
built = builder.build()
assert "renamed_child" in built
assert "child" not in built
assert "renamed_child" in built["parent"].refs
assert built.build_report.provenance["renamed_child"].source_name == "child"
def test_build_library_rejects_move_references_for_source_rename() -> None:
builder = BuildLibrary()
builder.add_source(Library({"src": Pattern()}))
with pytest.raises(BuildError, match="move_references=True"):
builder.rename("src", "renamed_src", move_references=True)
def test_build_library_rejects_renaming_declared_cells_during_authoring() -> None:
builder = BuildLibrary()
builder["declared"] = Pattern()
with pytest.raises(BuildError, match='Cannot rename declared build cell "declared"'):
builder.rename("declared", "renamed_declared")
def test_build_library_helper_rename_updates_provenance_and_owned_cells() -> None:
builder = BuildLibrary()
def make_top(lib: BuildLibrary) -> Pattern:
lib["_helper"] = Pattern()
lib.rename("_helper", "final_helper")
top = Pattern()
top.ref("final_helper")
return top
builder.cells.top = cell(make_top)(builder)
built = builder.build()
report = built.build_report
assert "final_helper" in built
assert "_helper" not in built
assert "final_helper" in report.owned_cells["top"]
assert "_helper" not in report.owned_cells["top"]
prov = report.provenance["final_helper"]
assert prov.kind == "helper"
assert prov.requested_name == "_helper"
assert prov.renamed_from == "_helper"
assert prov.final_name == "final_helper"
def test_build_library_helper_delete_removes_provenance_and_ownership() -> None:
builder = BuildLibrary()
def make_top(lib: BuildLibrary) -> Pattern:
lib["_helper"] = Pattern()
del lib["_helper"]
return Pattern()
builder.cells.top = cell(make_top)(builder)
built = builder.build()
report = built.build_report
assert "_helper" not in built
assert "_helper" not in report.provenance
assert report.owned_cells["top"] == ("top",)
def test_build_library_helper_rename_after_auto_rename_preserves_requested_name() -> None:
builder = BuildLibrary()
def make_top(lib: BuildLibrary) -> Pattern:
tree = Library({"_helper": Pattern()})
_ = lib << tree
renamed = lib << tree
lib.rename(renamed, "final_helper")
top = Pattern()
top.ref("_helper")
top.ref("final_helper")
return top
builder.cells.top = cell(make_top)(builder)
built = builder.build()
report = built.build_report
assert "final_helper" in built
prov = report.provenance["final_helper"]
assert prov.requested_name == "_helper"
assert prov.renamed_from == "_helper"
def test_build_library_rejects_renaming_declared_or_source_cells_during_build() -> None:
declared = BuildLibrary()
declared["leaf"] = Pattern()
def rename_declared(lib: BuildLibrary) -> Pattern:
lib.rename("leaf", "renamed_leaf")
return Pattern()
declared.cells.top = cell(rename_declared)(declared)
with pytest.raises(BuildError, match='Cannot rename declared build cell "leaf"'):
declared.build()
source = BuildLibrary()
source.add_source(Library({"src": Pattern()}))
def rename_source(lib: BuildLibrary) -> Pattern:
lib.rename("src", "renamed_src")
return Pattern()
source.cells.top = cell(rename_source)(source)
with pytest.raises(BuildError, match='Cannot rename imported source cell "src"'):
source.build()
def test_build_library_rejects_deleting_declared_or_source_cells_during_build() -> None:
declared = BuildLibrary()
declared["leaf"] = Pattern()
def delete_declared(lib: BuildLibrary) -> Pattern:
del lib["leaf"]
return Pattern()
declared.cells.top = cell(delete_declared)(declared)
with pytest.raises(BuildError, match='Cannot delete declared build cell "leaf"'):
declared.build()
source = BuildLibrary()
source.add_source(Library({"src": Pattern()}))
def delete_source(lib: BuildLibrary) -> Pattern:
del lib["src"]
return Pattern()
source.cells.top = cell(delete_source)(source)
with pytest.raises(BuildError, match='Cannot delete imported source cell "src"'):
source.build()

View file

@ -5,7 +5,7 @@ from numpy.testing import assert_allclose
from ..pattern import Pattern
from ..library import Library
from ..shapes import Path as MPath, Circle, Polygon
from ..shapes import Path as MPath, Circle, Polygon, RectCollection
from ..repetition import Grid, Arbitrary
def create_test_library(for_gds: bool = False) -> Library:
@ -109,3 +109,30 @@ def test_oasis_full_roundtrip(tmp_path: Path) -> None:
assert poly.repetition is not None
assert isinstance(poly.repetition, Grid)
assert poly.repetition.a_count == 5
def test_gdsii_rect_collection_roundtrip(tmp_path: Path) -> None:
from ..file import gdsii
lib = Library()
pat = Pattern()
pat.shapes[(5, 0)].append(
RectCollection(
rects=[[0, 0, 10, 5], [20, -5, 30, 10]],
annotations={'1': ['rects']},
)
)
lib['rects'] = pat
gds_file = tmp_path / 'rect_collection.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
read_lib, _ = gdsii.readfile(gds_file)
polys = read_lib['rects'].shapes[(5, 0)]
assert len(polys) == 2
assert all(isinstance(poly, Polygon) for poly in polys)
assert_allclose(polys[0].vertices, [[0, 0], [0, 5], [10, 5], [10, 0]])
assert_allclose(polys[1].vertices, [[20, -5], [20, 10], [30, 10], [30, -5]])
assert polys[0].annotations == {'1': ['rects']}
assert polys[1].annotations == {'1': ['rects']}

View file

@ -0,0 +1,603 @@
from pathlib import Path
import subprocess
import sys
import textwrap
import klamath
import numpy
import pytest
pytest.importorskip('pyarrow')
from .. import Ref, Label, PatternError
from ..library import Library
from ..pattern import Pattern
from ..repetition import Grid
from ..shapes import Path as MPath, Polygon, PolyCollection, RectCollection
from ..file import gdsii, gdsii_arrow
from ..file.gdsii_perf import write_fixture
if not gdsii_arrow.is_available():
pytest.skip('klamath_rs_ext shared library is not available', allow_module_level=True)
def _annotations_key(annotations: dict[str, list[object]] | None) -> tuple[tuple[str, tuple[object, ...]], ...] | None:
if not annotations:
return None
return tuple(sorted((key, tuple(values)) for key, values in annotations.items()))
def _coord_key(values: object) -> tuple[int, ...] | tuple[tuple[int, int], ...]:
arr = numpy.rint(numpy.asarray(values, dtype=float)).astype(int)
if arr.ndim == 1:
return tuple(arr.tolist())
return tuple(tuple(row.tolist()) for row in arr)
def _canonical_polygon_key(vertices: object) -> tuple[tuple[int, int], ...]:
arr = numpy.rint(numpy.asarray(vertices, dtype=float)).astype(int)
rows = [tuple(tuple(row.tolist()) for row in numpy.roll(arr, -shift, axis=0)) for shift in range(arr.shape[0])]
rev = arr[::-1]
rows.extend(tuple(tuple(row.tolist()) for row in numpy.roll(rev, -shift, axis=0)) for shift in range(rev.shape[0]))
return min(rows)
def _shape_key(shape: object, layer: tuple[int, int]) -> list[tuple[object, ...]]:
if isinstance(shape, MPath):
cap_extensions = None if shape.cap_extensions is None else _coord_key(shape.cap_extensions)
return [(
'path',
layer,
_coord_key(shape.vertices),
_coord_key(shape.offset),
int(round(float(shape.width))),
shape.cap.name,
cap_extensions,
_annotations_key(shape.annotations),
)]
keys = []
for poly in shape.to_polygons():
keys.append((
'polygon',
layer,
_canonical_polygon_key(poly.vertices),
_coord_key(poly.offset),
_annotations_key(poly.annotations),
))
return keys
def _ref_keys(target: str, ref: object) -> list[tuple[object, ...]]:
keys = []
for transform in ref.as_transforms():
keys.append((
target,
_coord_key(transform[:2]),
round(float(transform[2]), 8),
round(float(transform[4]), 8),
bool(int(round(float(transform[3])))),
_annotations_key(ref.annotations),
))
return keys
def _label_key(layer: tuple[int, int], label: object) -> tuple[object, ...]:
return (
layer,
label.string,
_coord_key(label.offset),
_annotations_key(label.annotations),
)
def _pattern_summary(pattern: Pattern) -> dict[str, object]:
shape_keys: list[tuple[object, ...]] = []
for layer, shapes in pattern.shapes.items():
for shape in shapes:
shape_keys.extend(_shape_key(shape, layer))
ref_keys: list[tuple[object, ...]] = []
for target, refs in pattern.refs.items():
for ref in refs:
ref_keys.extend(_ref_keys(target, ref))
label_keys = [
_label_key(layer, label)
for layer, labels in pattern.labels.items()
for label in labels
]
return {
'shapes': sorted(shape_keys),
'refs': sorted(ref_keys),
'labels': sorted(label_keys),
}
def _library_summary(lib: Library) -> dict[str, dict[str, object]]:
return {name: _pattern_summary(pattern) for name, pattern in lib.items()}
def _make_arrow_test_library() -> Library:
lib = Library()
leaf = Pattern()
leaf.polygon((1, 0), vertices=[[0, 0], [10, 0], [10, 10], [0, 10]], annotations={'1': ['leaf-poly']})
leaf.polygon((2, 0), vertices=[[40, 0], [50, 0], [50, 10], [40, 10]])
leaf.polygon((1, 0), vertices=[[20, 0], [30, 0], [30, 10], [20, 10]])
leaf.polygon((1, 0), vertices=[[80, 0], [90, 0], [90, 10], [80, 10]])
leaf.polygon((2, 0), vertices=[[60, 0], [70, 0], [70, 10], [60, 10]], annotations={'18': ['leaf-poly-2']})
leaf.label((10, 0), string='LEAF', offset=(3, 4), annotations={'10': ['leaf-label']})
lib['leaf'] = leaf
child = Pattern()
child.path(
(2, 0),
vertices=[[0, 0], [15, 5], [30, 5]],
width=6,
cap=MPath.Cap.SquareCustom,
cap_extensions=(2, 4),
annotations={'2': ['child-path']},
)
child.label((11, 0), string='CHILD', offset=(7, 8), annotations={'11': ['child-label']})
child.ref('leaf', offset=(100, 200), rotation=numpy.pi / 2, mirrored=True, scale=1.25, annotations={'12': ['child-ref']})
lib['child'] = child
sibling = Pattern()
sibling.polygon((3, 0), vertices=[[0, 0], [5, 0], [5, 6], [0, 6]])
sibling.label((12, 0), string='SIB', offset=(1, 2), annotations={'13': ['sib-label']})
sibling.ref(
'leaf',
offset=(-50, 60),
repetition=Grid(a_vector=(20, 0), a_count=3, b_vector=(0, 30), b_count=2),
annotations={'14': ['sib-ref']},
)
lib['sibling'] = sibling
fanout = Pattern()
fanout.ref('leaf', offset=(0, 0))
fanout.ref('child', offset=(10, 0), mirrored=True, rotation=numpy.pi / 6, scale=1.1)
fanout.ref('leaf', offset=(20, 0))
fanout.ref('leaf', offset=(30, 0), repetition=Grid(a_vector=(5, 0), a_count=2, b_vector=(0, 7), b_count=3))
fanout.ref('child', offset=(40, 0), mirrored=True, rotation=numpy.pi / 4, scale=1.2,
repetition=Grid(a_vector=(9, 0), a_count=2, b_vector=(0, 11), b_count=2))
fanout.ref('leaf', offset=(50, 0), repetition=Grid(a_vector=(6, 0), a_count=3, b_vector=(0, 8), b_count=2))
fanout.ref('leaf', offset=(60, 0), annotations={'19': ['fanout-sref']})
fanout.ref('child', offset=(70, 0), repetition=Grid(a_vector=(4, 0), a_count=2, b_vector=(0, 5), b_count=2),
annotations={'20': ['fanout-aref']})
lib['fanout'] = fanout
top = Pattern()
top.ref('child', offset=(500, 600), annotations={'15': ['top-child-ref']})
top.ref('sibling', offset=(-100, 50), rotation=numpy.pi, annotations={'16': ['top-sibling-ref']})
top.ref('fanout', offset=(250, -75))
top.label((13, 0), string='TOP', offset=(0, 0), annotations={'17': ['top-label']})
lib['top'] = top
return lib
def _write_invalid_path_type_fixture(path: Path) -> None:
with path.open('wb') as stream:
header = klamath.library.FileHeader(
name=b'test',
user_units_per_db_unit=1.0,
meters_per_db_unit=1e-9,
)
header.write(stream)
elem = klamath.elements.Path(
layer=(1, 0),
path_type=3,
width=10,
extension=(0, 0),
xy=numpy.array([[0, 0], [10, 0]], dtype=numpy.int32),
properties={},
)
klamath.library.write_struct(stream, name=b'top', elements=[elem])
klamath.records.ENDLIB.write(stream, None)
def test_gdsii_arrow_matches_gdsii_readfile(tmp_path: Path) -> None:
lib = _make_arrow_test_library()
gds_file = tmp_path / 'arrow_roundtrip.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
canonical_lib, canonical_info = gdsii.readfile(gds_file)
arrow_lib, arrow_info = gdsii_arrow.readfile(gds_file)
assert canonical_info == arrow_info
assert _library_summary(canonical_lib) == _library_summary(arrow_lib)
def test_gdsii_arrow_matches_gdsii_readfile_for_gzipped_file(tmp_path: Path) -> None:
lib = _make_arrow_test_library()
gds_file = tmp_path / 'arrow_roundtrip.gds.gz'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
canonical_lib, canonical_info = gdsii.readfile(gds_file)
arrow_lib, arrow_info = gdsii_arrow.readfile(gds_file)
assert canonical_info == arrow_info
assert _library_summary(canonical_lib) == _library_summary(arrow_lib)
def test_gdsii_arrow_readfile_arrow_returns_native_payload(tmp_path: Path) -> None:
gds_file = tmp_path / 'many_cells_native.gds'
manifest = write_fixture(gds_file, preset='many_cells', scale=0.001)
libarr, info = gdsii_arrow.readfile_arrow(gds_file)
assert info['name'] == manifest.library_name
assert libarr['lib_name'].as_py() == manifest.library_name
assert len(libarr['cells']) == manifest.cells
assert 0 < len(libarr['layers']) <= manifest.layers
def test_gdsii_arrow_readfile_arrow_reads_gzipped_file(tmp_path: Path) -> None:
lib = _make_arrow_test_library()
gds_file = tmp_path / 'native_payload.gds.gz'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
libarr, info = gdsii_arrow.readfile_arrow(gds_file)
assert info['name'] == 'masque-klamath'
assert libarr['lib_name'].as_py() == 'masque-klamath'
assert len(libarr['cells']) == len(lib)
assert len(libarr['layers']) > 0
def test_gdsii_arrow_removed_raw_mode_arg(tmp_path: Path) -> None:
lib = _make_arrow_test_library()
gds_file = tmp_path / 'removed_raw_mode.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
libarr, _ = gdsii_arrow.readfile_arrow(gds_file)
with pytest.raises(TypeError):
gdsii_arrow.readfile(gds_file, raw_mode=False)
with pytest.raises(TypeError):
gdsii_arrow.read_arrow(libarr, raw_mode=False)
def test_gdsii_arrow_invalid_input_raises_klamath_error(tmp_path: Path) -> None:
gds_file = tmp_path / 'invalid.gds'
gds_file.write_bytes(b'not-a-gds')
script = textwrap.dedent(f"""
from masque.file import gdsii_arrow
try:
gdsii_arrow.readfile({str(gds_file)!r})
except Exception as exc:
print(type(exc).__module__)
print(type(exc).__qualname__)
print(exc)
else:
raise SystemExit('expected gdsii_arrow.readfile() to fail')
""")
result = subprocess.run([sys.executable, '-c', script], capture_output=True, text=True, check=False)
assert result.returncode == 0, result.stderr
assert 'klamath.basic' in result.stdout
assert 'KlamathError' in result.stdout
def test_gdsii_arrow_reads_small_perf_fixture(tmp_path: Path) -> None:
gds_file = tmp_path / 'many_cells_smoke.gds'
manifest = write_fixture(gds_file, preset='many_cells', scale=0.001)
lib, info = gdsii_arrow.readfile(gds_file)
assert info['name'] == manifest.library_name
assert len(lib) == manifest.cells
assert 'TOP' in lib
assert sum(len(refs) for refs in lib['TOP'].refs.values()) > 0
def test_gdsii_arrow_degenerate_aref_decodes_as_single_transform(tmp_path: Path) -> None:
lib = Library()
leaf = Pattern()
leaf.polygon((1, 0), vertices=[[0, 0], [5, 0], [5, 5], [0, 5]])
lib['leaf'] = leaf
top = Pattern()
top.ref('leaf', offset=(100, 200), repetition=Grid(a_vector=(7, 0), a_count=1, b_vector=(0, 9), b_count=1))
lib['top'] = top
gds_file = tmp_path / 'degenerate_aref.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
canonical_lib, _ = gdsii.readfile(gds_file)
arrow_lib, _ = gdsii_arrow.readfile(gds_file)
assert _library_summary(arrow_lib) == _library_summary(canonical_lib)
decoded_ref = arrow_lib['top'].refs['leaf'][0]
assert decoded_ref.repetition is None
def test_gdsii_arrow_plain_srefs_decode_without_arbitrary(tmp_path: Path) -> None:
lib = _make_arrow_test_library()
gds_file = tmp_path / 'plain_srefs.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
arrow_lib, _ = gdsii_arrow.readfile(gds_file)
fanout = arrow_lib['fanout']
plain_leaf_refs = [
ref
for ref in fanout.refs['leaf']
if ref.annotations is None and ref.repetition is None
]
assert len(plain_leaf_refs) == 2
assert all(type(ref.repetition) is not Grid for ref in plain_leaf_refs)
def test_gdsii_arrow_degenerate_aref_schema_normalizes_to_sref(tmp_path: Path) -> None:
lib = Library()
leaf = Pattern()
leaf.polygon((1, 0), vertices=[[0, 0], [5, 0], [5, 5], [0, 5]])
lib['leaf'] = leaf
top = Pattern()
top.ref('leaf', offset=(100, 200), repetition=Grid(a_vector=(7, 0), a_count=1, b_vector=(0, 9), b_count=1))
lib['top'] = top
gds_file = tmp_path / 'degenerate_aref_schema.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
libarr = gdsii_arrow._read_to_arrow(gds_file)[0]
cells = libarr['cells'].values
cell_ids = cells.field('id').to_numpy()
cell_names = libarr['cell_names'].as_py()
top_index = next(ii for ii, cell_id in enumerate(cell_ids) if cell_names[cell_id] == 'top')
srefs = cells.field('srefs')[top_index].as_py()
arefs = cells.field('arefs')[top_index].as_py()
assert len(srefs) == 1
assert len(arefs) == 0
assert cell_names[srefs[0]['target']] == 'leaf'
def test_gdsii_arrow_boundary_batch_schema(tmp_path: Path) -> None:
lib = _make_arrow_test_library()
gds_file = tmp_path / 'arrow_batches.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
libarr = gdsii_arrow._read_to_arrow(gds_file)[0]
cells = libarr['cells'].values
cell_ids = cells.field('id').to_numpy()
cell_names = libarr['cell_names'].as_py()
layer_table = [
((int(layer) >> 16) & 0xFFFF, int(layer) & 0xFFFF)
for layer in libarr['layers'].values.to_numpy()
]
leaf_index = next(ii for ii, cell_id in enumerate(cell_ids) if cell_names[cell_id] == 'leaf')
rect_batches = cells.field('rect_batches')[leaf_index].as_py()
boundary_batches = cells.field('boundary_batches')[leaf_index].as_py()
boundary_props = cells.field('boundary_props')[leaf_index].as_py()
assert len(rect_batches) == 2
assert len(boundary_batches) == 0
assert len(boundary_props) == 2
rects_by_layer = {tuple(layer_table[entry['layer']]): entry for entry in rect_batches}
assert rects_by_layer[(1, 0)]['rects'] == [20, 0, 30, 10, 80, 0, 90, 10]
assert rects_by_layer[(2, 0)]['rects'] == [40, 0, 50, 10]
props_by_layer = {tuple(layer_table[entry['layer']]): entry for entry in boundary_props}
assert sorted(props_by_layer) == [(1, 0), (2, 0)]
assert props_by_layer[(1, 0)]['properties'][0]['value'] == 'leaf-poly'
assert props_by_layer[(2, 0)]['properties'][0]['value'] == 'leaf-poly-2'
def test_gdsii_arrow_rect_batch_schema_for_mixed_layer(tmp_path: Path) -> None:
lib = Library()
top = Pattern()
top.shapes[(1, 0)].append(RectCollection(rects=[[0, 0, 10, 10], [20, 0, 30, 10], [40, 0, 50, 10], [60, 0, 70, 10]]))
top.polygon((1, 0), vertices=[[80, 0], [85, 10], [90, 0]])
top.polygon((1, 0), vertices=[[100, 0], [105, 10], [110, 0]])
lib['top'] = top
gds_file = tmp_path / 'arrow_rect_batches.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
libarr = gdsii_arrow._read_to_arrow(gds_file)[0]
cells = libarr['cells'].values
cell_ids = cells.field('id').to_numpy()
cell_names = libarr['cell_names'].as_py()
layer_table = [
((int(layer) >> 16) & 0xFFFF, int(layer) & 0xFFFF)
for layer in libarr['layers'].values.to_numpy()
]
top_index = next(ii for ii, cell_id in enumerate(cell_ids) if cell_names[cell_id] == 'top')
rect_batches = cells.field('rect_batches')[top_index].as_py()
boundary_batches = cells.field('boundary_batches')[top_index].as_py()
assert len(rect_batches) == 1
assert tuple(layer_table[rect_batches[0]['layer']]) == (1, 0)
assert rect_batches[0]['rects'] == [
0, 0, 10, 10,
20, 0, 30, 10,
40, 0, 50, 10,
60, 0, 70, 10,
]
assert len(boundary_batches) == 1
assert tuple(layer_table[boundary_batches[0]['layer']]) == (1, 0)
assert boundary_batches[0]['vertex_offsets'] == [0, 3]
def test_gdsii_arrow_ref_schema(tmp_path: Path) -> None:
lib = _make_arrow_test_library()
gds_file = tmp_path / 'arrow_ref_batches.gds'
gdsii.writefile(lib, gds_file, meters_per_unit=1e-9)
libarr = gdsii_arrow._read_to_arrow(gds_file)[0]
cells = libarr['cells'].values
cell_ids = cells.field('id').to_numpy()
cell_names = libarr['cell_names'].as_py()
fanout_index = next(ii for ii, cell_id in enumerate(cell_ids) if cell_names[cell_id] == 'fanout')
srefs = cells.field('srefs')[fanout_index].as_py()
arefs = cells.field('arefs')[fanout_index].as_py()
sref_props = cells.field('sref_props')[fanout_index].as_py()
aref_props = cells.field('aref_props')[fanout_index].as_py()
sref_target_ids = [entry['target'] for entry in srefs]
sref_targets = [cell_names[target] for target in sref_target_ids]
assert sorted(sref_targets) == ['child', 'leaf', 'leaf']
assert sref_target_ids == sorted(sref_target_ids)
sref_by_target = {}
for entry in srefs:
sref_by_target.setdefault(cell_names[entry['target']], []).append(entry)
assert [entry['invert_y'] for entry in sref_by_target['child']] == [True]
assert [entry['scale'] for entry in sref_by_target['child']] == pytest.approx([1.1])
assert len(sref_by_target['leaf']) == 2
aref_target_ids = [entry['target'] for entry in arefs]
aref_targets = [cell_names[target] for target in aref_target_ids]
assert sorted(aref_targets) == ['child', 'leaf', 'leaf']
assert aref_target_ids == sorted(aref_target_ids)
aref_by_target = {}
for entry in arefs:
aref_by_target.setdefault(cell_names[entry['target']], []).append(entry)
assert [entry['invert_y'] for entry in aref_by_target['child']] == [True]
assert [entry['scale'] for entry in aref_by_target['child']] == pytest.approx([1.2])
assert len(aref_by_target['leaf']) == 2
assert len(sref_props) == 1
assert cell_names[sref_props[0]['target']] == 'leaf'
assert sref_props[0]['properties'][0]['value'] == 'fanout-sref'
assert len(aref_props) == 1
assert cell_names[aref_props[0]['target']] == 'child'
assert aref_props[0]['properties'][0]['value'] == 'fanout-aref'
def test_gdsii_arrow_invalid_path_type_matches_gdsii(tmp_path: Path) -> None:
gds_file = tmp_path / 'invalid_path_type.gds'
_write_invalid_path_type_fixture(gds_file)
with pytest.raises(PatternError, match='Unrecognized path type: 3'):
gdsii.readfile(gds_file)
with pytest.raises(PatternError, match='Unrecognized path type: 3'):
gdsii_arrow.readfile(gds_file)
def test_raw_ref_grid_label_constructors_match_public() -> None:
raw_grid = Grid._from_raw(
a_vector=numpy.array([20, 0]),
a_count=3,
b_vector=numpy.array([0, 30]),
b_count=2,
)
public_grid = Grid(a_vector=(20, 0), a_count=3, b_vector=(0, 30), b_count=2)
assert raw_grid == public_grid
raw_poly = Polygon._from_raw(
vertices=numpy.array([[0.0, 0.0], [5.0, 0.0], [5.0, 5.0], [0.0, 5.0]]),
annotations={'1': ['poly']},
)
public_poly = Polygon(
vertices=[[0, 0], [5, 0], [5, 5], [0, 5]],
annotations={'1': ['poly']},
)
assert raw_poly == public_poly
raw_poly_collection = PolyCollection._from_raw(
vertex_lists=numpy.array([
[0.0, 0.0], [2.0, 0.0], [2.0, 2.0],
[10.0, 10.0], [12.0, 10.0], [12.0, 12.0],
]),
vertex_offsets=numpy.array([0, 3], dtype=numpy.uint32),
annotations={'2': ['pc']},
)
public_poly_collection = PolyCollection(
vertex_lists=[[0, 0], [2, 0], [2, 2], [10, 10], [12, 10], [12, 12]],
vertex_offsets=[0, 3],
annotations={'2': ['pc']},
)
assert raw_poly_collection == public_poly_collection
assert [tuple(s.indices(len(raw_poly_collection.vertex_lists))) for s in raw_poly_collection.vertex_slices] == [(0, 3, 1), (3, 6, 1)]
raw_rect_collection = RectCollection._from_raw(
rects=numpy.array([[10.0, 10.0, 12.0, 12.0], [0.0, 0.0, 5.0, 5.0]]),
annotations={'3': ['rects']},
)
public_rect_collection = RectCollection(
rects=[[0, 0, 5, 5], [10, 10, 12, 12]],
annotations={'3': ['rects']},
)
assert raw_rect_collection == public_rect_collection
raw_ref_empty = Ref._from_raw(
offset=numpy.array([100, 200]),
rotation=numpy.pi / 2,
mirrored=False,
scale=1.0,
repetition=None,
annotations=None,
)
public_ref_empty = Ref(
offset=(100, 200),
rotation=numpy.pi / 2,
mirrored=False,
scale=1.0,
repetition=None,
annotations=None,
)
assert raw_ref_empty.annotations is None
assert raw_ref_empty == public_ref_empty
raw_ref = Ref._from_raw(
offset=numpy.array([100, 200]),
rotation=numpy.pi / 2,
mirrored=True,
scale=1.25,
repetition=raw_grid,
annotations={'12': ['child-ref']},
)
public_ref = Ref(
offset=(100, 200),
rotation=numpy.pi / 2,
mirrored=True,
scale=1.25,
repetition=public_grid,
annotations={'12': ['child-ref']},
)
assert raw_ref == public_ref
assert numpy.array_equal(raw_ref.as_transforms(), public_ref.as_transforms())
raw_label_empty = Label._from_raw(
'LEAF',
offset=numpy.array([3, 4]),
annotations=None,
)
public_label_empty = Label(
'LEAF',
offset=(3, 4),
annotations=None,
)
assert raw_label_empty.annotations is None
assert raw_label_empty == public_label_empty
raw_label = Label._from_raw(
'LEAF',
offset=numpy.array([3, 4]),
annotations={'10': ['leaf-label']},
)
public_label = Label(
'LEAF',
offset=(3, 4),
annotations={'10': ['leaf-label']},
)
assert raw_label == public_label
assert numpy.array_equal(raw_label.get_bounds_single(), public_label.get_bounds_single())

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from pathlib import Path
import numpy
from numpy.testing import assert_allclose
from ..file import gdsii, gdsii_lazy
from ..pattern import Pattern
from ..library import Library
def _make_lazy_port_library() -> Library:
lib = Library()
leaf = Pattern()
leaf.label(layer=(10, 0), string='A:type1 0', offset=(5, 0))
lib['leaf'] = leaf
child = Pattern()
child.ref('leaf', offset=(10, 20), rotation=numpy.pi / 2)
lib['child'] = child
top = Pattern()
top.ref('child', offset=(100, 200))
lib['top'] = top
return lib
def test_gdsii_lazy_source_exposes_order_and_graph_without_materializing(tmp_path: Path) -> None:
gds_file = tmp_path / 'lazy_source.gds'
src = _make_lazy_port_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='classic-lazy')
lib, info = gdsii_lazy.readfile(gds_file)
assert info['name'] == 'classic-lazy'
assert lib.source_order() == ('leaf', 'child', 'top')
assert lib.child_graph(dangling='ignore') == {
'leaf': set(),
'child': {'leaf'},
'top': {'child'},
}
assert not lib._cache
child = lib['child']
assert list(child.refs.keys()) == ['leaf']
assert set(lib._cache) == {'child'}
def test_gdsii_lazy_ports_view_keeps_raw_source_unmodified(tmp_path: Path) -> None:
gds_file = tmp_path / 'lazy_ports.gds'
src = _make_lazy_port_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='classic-ports')
raw, _ = gdsii_lazy.readfile(gds_file)
processed = raw.with_ports_from_data(layers=[(10, 0)], max_depth=2)
top = processed['top']
assert set(top.ports) == {'A'}
assert_allclose(top.ports['A'].offset, [110, 225], atol=1e-10)
assert not raw._cache
raw_top = raw['top']
assert not raw_top.ports
def test_gdsii_lazy_overlay_add_source_stays_lazy_for_processed_view(tmp_path: Path) -> None:
gds_file = tmp_path / 'lazy_overlay.gds'
src = _make_lazy_port_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='classic-overlay')
raw, _ = gdsii_lazy.readfile(gds_file)
processed = raw.with_ports_from_data(layers=[(10, 0)], max_depth=2)
overlay = gdsii_lazy.OverlayLibrary()
overlay.add_source(processed)
assert not raw._cache
assert not processed._cache
abstract = overlay.abstract('top')
assert set(abstract.ports) == {'A'}
def test_gdsii_lazy_processed_write_roundtrips_without_explicit_units(tmp_path: Path) -> None:
gds_file = tmp_path / 'lazy_roundtrip.gds'
src = _make_lazy_port_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='classic-roundtrip')
raw, _ = gdsii_lazy.readfile(gds_file)
processed = raw.with_ports_from_data(layers=[(10, 0)], max_depth=2)
out_file = tmp_path / 'lazy_roundtrip_out.gds'
gdsii_lazy.writefile(processed, out_file)
assert out_file.read_bytes() == gds_file.read_bytes()
def test_gdsii_removed_closure_based_lazy_loader() -> None:
assert not hasattr(gdsii, 'load_library')
assert not hasattr(gdsii, 'load_libraryfile')

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from pathlib import Path
import subprocess
import sys
import textwrap
import klamath
import numpy
import pytest
pytest.importorskip('pyarrow')
from .. import PatternError
from ..library import Library
from ..pattern import Pattern
from ..repetition import Grid
from ..file import gdsii, gdsii_lazy_arrow
from ..file.gdsii_perf import write_fixture
if not gdsii_lazy_arrow.is_available():
pytest.skip('klamath_rs_ext shared library is not available', allow_module_level=True)
def _make_small_library() -> Library:
lib = Library()
leaf = Pattern()
leaf.polygon((1, 0), vertices=[[0, 0], [10, 0], [10, 5], [0, 5]])
lib['leaf'] = leaf
mid = Pattern()
mid.ref('leaf', offset=(10, 20))
mid.ref('leaf', offset=(40, 0), repetition=Grid(a_vector=(12, 0), a_count=2, b_vector=(0, 9), b_count=2))
lib['mid'] = mid
top = Pattern()
top.ref('mid', offset=(100, 200))
lib['top'] = top
return lib
def _make_complex_ref_library() -> Library:
lib = Library()
leaf = Pattern()
leaf.polygon((1, 0), vertices=[[0, 0], [10, 0], [10, 10], [0, 10]])
lib['leaf'] = leaf
child = Pattern()
child.ref('leaf', offset=(100, 200), rotation=numpy.pi / 2, mirrored=True, scale=1.25)
lib['child'] = child
sibling = Pattern()
sibling.ref(
'leaf',
offset=(-50, 60),
repetition=Grid(a_vector=(20, 0), a_count=3, b_vector=(0, 30), b_count=2),
)
lib['sibling'] = sibling
fanout = Pattern()
fanout.ref('leaf', offset=(0, 0))
fanout.ref('child', offset=(10, 0), mirrored=True, rotation=numpy.pi / 6, scale=1.1)
fanout.ref('leaf', offset=(30, 0), repetition=Grid(a_vector=(5, 0), a_count=2, b_vector=(0, 7), b_count=3))
fanout.ref(
'child',
offset=(40, 0),
mirrored=True,
rotation=numpy.pi / 4,
scale=1.2,
repetition=Grid(a_vector=(9, 0), a_count=2, b_vector=(0, 11), b_count=2),
)
lib['fanout'] = fanout
top = Pattern()
top.ref('child', offset=(500, 600))
top.ref('sibling', offset=(-100, 50), rotation=numpy.pi)
top.ref('fanout', offset=(250, -75))
lib['top'] = top
return lib
def _write_invalid_path_type_fixture(path: Path) -> None:
with path.open('wb') as stream:
header = klamath.library.FileHeader(
name=b'test',
user_units_per_db_unit=1.0,
meters_per_db_unit=1e-9,
)
header.write(stream)
elem = klamath.elements.Path(
layer=(1, 0),
path_type=3,
width=10,
extension=(0, 0),
xy=numpy.array([[0, 0], [10, 0]], dtype=numpy.int32),
properties={},
)
klamath.library.write_struct(stream, name=b'top', elements=[elem])
klamath.records.ENDLIB.write(stream, None)
def _transform_rows_key(values: numpy.ndarray) -> tuple[tuple[object, ...], ...]:
arr = numpy.asarray(values, dtype=float)
arr = numpy.atleast_2d(arr)
rows = [
(
round(float(row[0]), 8),
round(float(row[1]), 8),
round(float(row[2]), 8),
bool(int(round(float(row[3])))),
round(float(row[4]), 8),
)
for row in arr
]
return tuple(sorted(rows))
def _local_refs_key(refs: dict[str, list[numpy.ndarray]]) -> dict[str, tuple[tuple[object, ...], ...]]:
return {
parent: _transform_rows_key(numpy.concatenate(transforms))
for parent, transforms in refs.items()
}
def _global_refs_key(refs: dict[tuple[str, ...], numpy.ndarray]) -> dict[tuple[str, ...], tuple[tuple[object, ...], ...]]:
return {
path: _transform_rows_key(transforms)
for path, transforms in refs.items()
}
def test_gdsii_lazy_arrow_loads_perf_fixture(tmp_path: Path) -> None:
gds_file = tmp_path / 'many_cells_lazy.gds'
manifest = write_fixture(gds_file, preset='many_cells', scale=0.001)
lib, info = gdsii_lazy_arrow.readfile(gds_file)
assert info['name'] == manifest.library_name
assert len(lib) == manifest.cells
assert lib.top() == 'TOP'
assert 'TOP' in lib.child_graph(dangling='ignore')
def test_gdsii_lazy_arrow_local_and_global_refs(tmp_path: Path) -> None:
gds_file = tmp_path / 'refs.gds'
src = _make_small_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='lazy-refs')
lib, _ = gdsii_lazy_arrow.readfile(gds_file)
local = lib.find_refs_local('leaf')
assert set(local) == {'mid'}
assert sum(arr.shape[0] for arr in local['mid']) == 5
global_refs = lib.find_refs_global('leaf')
assert {path for path in global_refs} == {('top', 'mid', 'leaf')}
assert global_refs[('top', 'mid', 'leaf')].shape[0] == 5
def test_gdsii_lazy_arrow_ref_queries_match_eager_reader(tmp_path: Path) -> None:
gds_file = tmp_path / 'complex_refs.gds'
src = _make_complex_ref_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='lazy-complex-refs')
eager, _ = gdsii.readfile(gds_file)
lazy, _ = gdsii_lazy_arrow.readfile(gds_file)
for name in ('leaf', 'child'):
assert _local_refs_key(lazy.find_refs_local(name)) == _local_refs_key(eager.find_refs_local(name))
assert _global_refs_key(lazy.find_refs_global(name)) == _global_refs_key(eager.find_refs_global(name))
def test_gdsii_lazy_arrow_invalid_input_raises_klamath_error(tmp_path: Path) -> None:
gds_file = tmp_path / 'invalid.gds'
gds_file.write_bytes(b'not-a-gds')
script = textwrap.dedent(f"""
from masque.file import gdsii_lazy_arrow
try:
gdsii_lazy_arrow.readfile({str(gds_file)!r})
except Exception as exc:
print(type(exc).__module__)
print(type(exc).__qualname__)
print(exc)
else:
raise SystemExit('expected gdsii_lazy_arrow.readfile() to fail')
""")
result = subprocess.run([sys.executable, '-c', script], capture_output=True, text=True, check=False)
assert result.returncode == 0, result.stderr
assert 'klamath.basic' in result.stdout
assert 'KlamathError' in result.stdout
def test_gdsii_lazy_arrow_invalid_path_type_raises_pattern_error(tmp_path: Path) -> None:
gds_file = tmp_path / 'invalid_path_type.gds'
_write_invalid_path_type_fixture(gds_file)
lib, _ = gdsii_lazy_arrow.readfile(gds_file)
with pytest.raises(PatternError, match='Unrecognized path type: 3'):
lib['top']
def test_gdsii_lazy_arrow_untouched_write_is_copy_through(tmp_path: Path) -> None:
gds_file = tmp_path / 'copy_source.gds'
src = _make_small_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='copy-through')
lib, info = gdsii_lazy_arrow.readfile(gds_file)
out_file = tmp_path / 'copy_out.gds'
gdsii_lazy_arrow.writefile(
lib,
out_file,
meters_per_unit=info['meters_per_unit'],
logical_units_per_unit=info['logical_units_per_unit'],
library_name=info['name'],
)
assert out_file.read_bytes() == gds_file.read_bytes()
def test_gdsii_lazy_arrow_gzipped_copy_through(tmp_path: Path) -> None:
gds_file = tmp_path / 'copy_source.gds.gz'
src = _make_small_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='copy-through-gz')
lib, info = gdsii_lazy_arrow.readfile(gds_file)
out_file = tmp_path / 'copy_out.gds.gz'
gdsii_lazy_arrow.writefile(
lib,
out_file,
meters_per_unit=info['meters_per_unit'],
logical_units_per_unit=info['logical_units_per_unit'],
library_name=info['name'],
)
assert out_file.read_bytes() == gds_file.read_bytes()
def test_gdsii_lazy_overlay_merge_and_write(tmp_path: Path) -> None:
base_a = Library()
leaf_a = Pattern()
leaf_a.polygon((1, 0), vertices=[[0, 0], [8, 0], [8, 8], [0, 8]])
base_a['leaf'] = leaf_a
top_a = Pattern()
top_a.ref('leaf', offset=(0, 0))
base_a['top_a'] = top_a
base_b = Library()
leaf_b = Pattern()
leaf_b.polygon((2, 0), vertices=[[0, 0], [5, 0], [5, 5], [0, 5]])
base_b['leaf'] = leaf_b
top_b = Pattern()
top_b.ref('leaf', offset=(20, 30))
base_b['top_b'] = top_b
gds_a = tmp_path / 'a.gds'
gds_b = tmp_path / 'b.gds'
gdsii.writefile(base_a, gds_a, meters_per_unit=1e-9, library_name='overlay')
gdsii.writefile(base_b, gds_b, meters_per_unit=1e-9, library_name='overlay')
lib_a, _ = gdsii_lazy_arrow.readfile(gds_a)
lib_b, _ = gdsii_lazy_arrow.readfile(gds_b)
overlay = gdsii_lazy_arrow.OverlayLibrary()
overlay.add_source(lib_a)
rename_map = overlay.add_source(lib_b, rename_theirs=lambda lib, name: lib.get_name(name))
renamed_leaf = rename_map['leaf']
assert rename_map == {'leaf': renamed_leaf}
assert renamed_leaf != 'leaf'
assert len(lib_a._cache) == 0
assert len(lib_b._cache) == 0
overlay.move_references('leaf', renamed_leaf)
out_file = tmp_path / 'overlay_out.gds'
gdsii_lazy_arrow.writefile(overlay, out_file)
roundtrip, _ = gdsii.readfile(out_file)
assert set(roundtrip.keys()) == {'leaf', renamed_leaf, 'top_a', 'top_b'}
assert 'top_b' in roundtrip
assert list(roundtrip['top_b'].refs.keys()) == [renamed_leaf]
def test_gdsii_writer_accepts_overlay_library(tmp_path: Path) -> None:
gds_file = tmp_path / 'overlay_source.gds'
src = _make_small_library()
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='overlay-src')
lib, info = gdsii_lazy_arrow.readfile(gds_file)
overlay = gdsii_lazy_arrow.OverlayLibrary()
overlay.add_source(lib)
overlay.rename('leaf', 'leaf_copy', move_references=True)
out_file = tmp_path / 'overlay_via_eager_writer.gds'
gdsii.writefile(
overlay,
out_file,
meters_per_unit=info['meters_per_unit'],
logical_units_per_unit=info['logical_units_per_unit'],
library_name=info['name'],
)
roundtrip, _ = gdsii.readfile(out_file)
assert set(roundtrip.keys()) == {'leaf_copy', 'mid', 'top'}
assert list(roundtrip['mid'].refs.keys()) == ['leaf_copy']
def test_svg_writer_uses_detached_materialized_copy(tmp_path: Path) -> None:
pytest.importorskip('svgwrite')
from ..file import svg
from ..shapes import Path as MPath
gds_file = tmp_path / 'svg_source.gds'
src = _make_small_library()
src['top'].path((3, 0), vertices=[[0, 0], [0, 20]], width=4)
gdsii.writefile(src, gds_file, meters_per_unit=1e-9, library_name='svg-src')
lib, _ = gdsii_lazy_arrow.readfile(gds_file)
top_pat = lib['top']
assert list(top_pat.refs.keys()) == ['mid']
assert any(isinstance(shape, MPath) for shape in top_pat.shapes[(3, 0)])
svg_path = tmp_path / 'lazy.svg'
svg.writefile(lib, 'top', str(svg_path))
assert svg_path.exists()
assert list(top_pat.refs.keys()) == ['mid']
assert any(isinstance(shape, MPath) for shape in top_pat.shapes[(3, 0)])

View file

@ -0,0 +1,24 @@
from dataclasses import asdict
import json
from pathlib import Path
from ..file import gdsii
from ..file.gdsii_perf import fixture_manifest, write_fixture
def test_gdsii_perf_fixture_smoke(tmp_path: Path) -> None:
output = tmp_path / 'many_cells.gds'
manifest = write_fixture(output, preset='many_cells', scale=0.002)
expected = fixture_manifest(output, preset='many_cells', scale=0.002)
assert output.exists()
assert manifest == expected
sidecar = json.loads(output.with_suffix('.gds.json').read_text())
assert sidecar == asdict(manifest)
read_lib, info = gdsii.readfile(output)
assert info['name'] == manifest.library_name
assert len(read_lib) == manifest.cells
assert 'TOP' in read_lib
assert len(read_lib['TOP'].refs) > 0

View file

@ -0,0 +1,97 @@
import numpy
from numpy import pi
from numpy.testing import assert_allclose
from ..shapes import Arc, Circle, Ellipse, Path, Text
def test_circle_raw_constructor_matches_public() -> None:
raw = Circle._from_raw(
radius=5.0,
offset=numpy.array([1.0, 2.0]),
annotations={'1': ['circle']},
)
public = Circle(
radius=5.0,
offset=(1.0, 2.0),
annotations={'1': ['circle']},
)
assert raw == public
def test_ellipse_raw_constructor_matches_public() -> None:
raw = Ellipse._from_raw(
radii=numpy.array([3.0, 5.0]),
offset=numpy.array([1.0, 2.0]),
rotation=5 * pi / 2,
annotations={'2': ['ellipse']},
)
public = Ellipse(
radii=(3.0, 5.0),
offset=(1.0, 2.0),
rotation=5 * pi / 2,
annotations={'2': ['ellipse']},
)
assert raw == public
def test_arc_raw_constructor_matches_public() -> None:
raw = Arc._from_raw(
radii=numpy.array([10.0, 6.0]),
angles=numpy.array([0.0, pi / 2]),
width=2.0,
offset=numpy.array([1.0, 2.0]),
rotation=5 * pi / 2,
annotations={'3': ['arc']},
)
public = Arc(
radii=(10.0, 6.0),
angles=(0.0, pi / 2),
width=2.0,
offset=(1.0, 2.0),
rotation=5 * pi / 2,
annotations={'3': ['arc']},
)
assert raw == public
def test_path_raw_constructor_matches_public() -> None:
raw = Path._from_raw(
vertices=numpy.array([[0.0, 0.0], [10.0, 0.0], [10.0, 5.0]]),
width=2.0,
cap=Path.Cap.SquareCustom,
cap_extensions=numpy.array([1.0, 3.0]),
annotations={'4': ['path']},
)
public = Path(
vertices=((0.0, 0.0), (10.0, 0.0), (10.0, 5.0)),
width=2.0,
cap=Path.Cap.SquareCustom,
cap_extensions=(1.0, 3.0),
annotations={'4': ['path']},
)
assert raw == public
assert raw.cap_extensions is not None
assert_allclose(raw.cap_extensions, [1.0, 3.0])
def test_text_raw_constructor_matches_public() -> None:
raw = Text._from_raw(
string='RAW',
height=12.0,
font_path='font.otf',
offset=numpy.array([1.0, 2.0]),
rotation=5 * pi / 2,
mirrored=True,
annotations={'5': ['text']},
)
public = Text(
string='RAW',
height=12.0,
font_path='font.otf',
offset=(1.0, 2.0),
rotation=5 * pi / 2,
mirrored=True,
annotations={'5': ['text']},
)
assert raw == public

View file

@ -0,0 +1,70 @@
import copy
import numpy
import pytest
from numpy.testing import assert_allclose, assert_equal
from ..error import PatternError
from ..shapes import Polygon, RectCollection
def test_rect_collection_init_and_to_polygons() -> None:
rects = RectCollection([[10, 10, 12, 12], [0, 0, 5, 5]])
assert_equal(rects.rects, [[0, 0, 5, 5], [10, 10, 12, 12]])
polys = rects.to_polygons()
assert len(polys) == 2
assert all(isinstance(poly, Polygon) for poly in polys)
assert_equal(polys[0].vertices, [[0, 0], [0, 5], [5, 5], [5, 0]])
def test_rect_collection_rejects_invalid_rects() -> None:
with pytest.raises(PatternError):
RectCollection([[0, 0, 1]])
with pytest.raises(PatternError):
RectCollection([[5, 0, 1, 2]])
with pytest.raises(PatternError):
RectCollection([[0, 5, 1, 2]])
def test_rect_collection_raw_constructor_matches_public() -> None:
raw = RectCollection._from_raw(
rects=numpy.array([[10.0, 10.0, 12.0, 12.0], [0.0, 0.0, 5.0, 5.0]]),
annotations={'1': ['rects']},
)
public = RectCollection(
[[0, 0, 5, 5], [10, 10, 12, 12]],
annotations={'1': ['rects']},
)
assert raw == public
assert_equal(raw.get_bounds_single(), [[0, 0], [12, 12]])
def test_rect_collection_manhattan_transforms() -> None:
rects = RectCollection([[0, 0, 2, 4], [10, 20, 12, 22]])
mirrored = copy.deepcopy(rects).mirror(1)
assert_equal(mirrored.rects, [[-2, 0, 0, 4], [-12, 20, -10, 22]])
scaled = copy.deepcopy(rects).scale_by(-2)
assert_equal(scaled.rects, [[-4, -8, 0, 0], [-24, -44, -20, -40]])
rotated = copy.deepcopy(rects).rotate(numpy.pi / 2)
assert_equal(rotated.rects, [[-4, 0, 0, 2], [-22, 10, -20, 12]])
def test_rect_collection_non_manhattan_rotation_raises() -> None:
rects = RectCollection([[0, 0, 2, 4]])
with pytest.raises(PatternError, match='Manhattan rotations'):
rects.rotate(numpy.pi / 4)
def test_rect_collection_normalized_form_rebuild_is_independent() -> None:
rects = RectCollection([[0, 0, 2, 4], [10, 20, 12, 22]])
_intrinsic, extrinsic, rebuild = rects.normalized_form(2)
clone = rebuild()
clone.rects[:] = [[1, 1, 2, 2], [3, 3, 4, 4]]
assert_allclose(extrinsic[0], [6, 11.5])
assert_equal(rects.rects, [[0, 0, 2, 4], [10, 20, 12, 22]])

View file

@ -5,9 +5,17 @@ from numpy.testing import assert_equal, assert_allclose
from numpy import pi
import pytest
from ..utils import remove_duplicate_vertices, remove_colinear_vertices, poly_contains_points, rotation_matrix_2d, apply_transforms, normalize_mirror, DeferredDict
from ..utils import (
DeferredDict,
apply_transforms,
normalize_mirror,
poly_contains_points,
remove_colinear_vertices,
remove_duplicate_vertices,
rotation_matrix_2d,
)
from ..file.utils import tmpfile
from ..utils.curves import bezier
from ..utils.curves import bezier, circular_arc, euler_bend, euler_spiral
from ..error import PatternError
@ -23,6 +31,23 @@ def test_remove_duplicate_vertices() -> None:
assert_equal(v_clean_open, [[0, 0], [1, 1], [2, 2], [0, 0]])
def test_remove_duplicate_vertices_tolerance_defaults_to_exact_match() -> None:
v = [[0, 0], [1, 1], [1 + 1e-13, 1], [2, 2], [1e-13, 0]]
assert_allclose(remove_duplicate_vertices(v, closed_path=True), v, atol=0, rtol=0)
assert_allclose(
remove_duplicate_vertices(v, closed_path=True, tolerance=1e-12),
[[0, 0], [1 + 1e-13, 1], [2, 2]],
atol=0,
rtol=0,
)
def test_remove_duplicate_vertices_rejects_negative_tolerance() -> None:
with pytest.raises(ValueError, match='non-negative'):
remove_duplicate_vertices([[0, 0]], tolerance=-1)
def test_remove_colinear_vertices() -> None:
v = [[0, 0], [1, 0], [2, 0], [2, 1], [2, 2], [1, 1], [0, 0]]
v_clean = remove_colinear_vertices(v, closed_path=True)
@ -123,6 +148,53 @@ def test_bezier_accepts_exact_weight_count() -> None:
assert_allclose(samples, [[0, 0], [2 / 3, 2 / 3], [1, 1]], atol=1e-10)
def _endpoint_tangent(xy: numpy.ndarray) -> float:
dxy = xy[-1] - xy[-2]
return numpy.arctan2(dxy[1], dxy[0])
@pytest.mark.parametrize(
('switchover_angle', 'total_angle'),
[
(pi / 8, pi / 4),
(pi / 8, pi / 2),
(pi / 4, pi),
],
)
def test_euler_bend_supports_total_angle(switchover_angle: float, total_angle: float) -> None:
xy = euler_bend(switchover_angle, num_points=2000, total_angle=total_angle)
assert_allclose(xy[0], [0, 0], atol=1e-12)
assert_allclose(_endpoint_tangent(xy), -total_angle, atol=1e-3)
def test_euler_bend_180_degrees_with_90_degree_circular_middle() -> None:
xy = euler_bend(pi / 4, num_points=2000, total_angle=pi)
assert_allclose(_endpoint_tangent(xy), -pi, atol=1e-3)
assert abs(xy[-1][0]) < 1e-3
assert xy[-1][1] < 0
def test_euler_bend_rejects_too_large_switchover_angle() -> None:
with pytest.raises(PatternError, match='total_angle / 2'):
euler_bend(pi / 2, total_angle=pi / 2)
def test_euler_spiral_and_circular_arc_helpers_match_endpoint_tangent() -> None:
xy_spiral = euler_spiral(pi / 4, num_points=1000)
assert_allclose(_endpoint_tangent(xy_spiral), -pi / 4, atol=1e-3)
xy_arc = circular_arc(
10,
pi / 2,
num_points=1000,
start_angle=_endpoint_tangent(xy_spiral),
start=xy_spiral[-1],
)
assert_allclose(_endpoint_tangent(xy_arc), -3 * pi / 4, atol=2e-3)
def test_deferred_dict_accessors_resolve_values_once() -> None:
calls = 0

View file

@ -9,7 +9,15 @@ def annotation2key(aaa: int | float | str) -> tuple[bool, Any]:
return (isinstance(aaa, str), aaa)
def _normalized_annotations(annotations: annotations_t) -> annotations_t:
if not annotations:
return None
return annotations
def annotations_lt(aa: annotations_t, bb: annotations_t) -> bool:
aa = _normalized_annotations(aa)
bb = _normalized_annotations(bb)
if aa is None:
return bb is not None
elif bb is None: # noqa: RET505
@ -36,6 +44,8 @@ def annotations_lt(aa: annotations_t, bb: annotations_t) -> bool:
def annotations_eq(aa: annotations_t, bb: annotations_t) -> bool:
aa = _normalized_annotations(aa)
bb = _normalized_annotations(bb)
if aa is None:
return bb is None
elif bb is None: # noqa: RET505

View file

@ -3,11 +3,7 @@ from numpy.typing import ArrayLike, NDArray
from numpy import pi
from ..error import PatternError
try:
from numpy import trapezoid
except ImportError:
from numpy import trapz as trapezoid # type:ignore
from .vertices import remove_duplicate_vertices
def bezier(
@ -53,70 +49,196 @@ def bezier(
return qq
def _integrate_tangent(
qq: NDArray[numpy.float64],
theta: NDArray[numpy.float64],
num_points: int,
) -> NDArray[numpy.float64]:
dx = numpy.cos(theta)
dy = numpy.sin(theta)
dq = qq[-1] / (qq.size - 1)
ix = numpy.zeros(qq.size)
iy = numpy.zeros(qq.size)
ix[1:] = numpy.cumsum((dx[:-1] + dx[1:]) / 2) * dq
iy[1:] = numpy.cumsum((dy[:-1] + dy[1:]) / 2) * dq
qq_target = numpy.linspace(0, qq[-1], num_points)
x_target = numpy.interp(qq_target, qq, ix)
y_target = numpy.interp(qq_target, qq, iy)
return numpy.stack((x_target, y_target), axis=1)
def euler_spiral(
switchover_angle: float,
num_points: int = 200,
*,
start_angle: float = 0.0,
start: ArrayLike = (0.0, 0.0),
reverse: bool = False,
) -> NDArray[numpy.float64]:
"""
Generate one Euler bend transition segment.
Positive angles bend clockwise, matching `euler_bend()`. When `reverse` is
`False`, curvature ramps from zero to the switchover curvature. When
`reverse` is `True`, curvature ramps from the switchover curvature to zero.
Args:
switchover_angle: Tangent angle change across the Euler segment, in radians.
num_points: Number of points in the curve.
start_angle: Tangent angle at the first point.
start: First point of the segment.
reverse: If `True`, generate the exit segment of an Euler bend.
Returns:
`[[x0, y0], ...]` for the curve.
"""
if num_points < 0:
raise PatternError(f'num_points must be non-negative, got {num_points}')
if switchover_angle < 0:
raise PatternError(f'switchover_angle must be non-negative, got {switchover_angle}')
if num_points == 0:
return numpy.empty((0, 2))
start = numpy.asarray(start, dtype=float)
if start.shape != (2,):
raise PatternError(f'start must be a 2D point; got shape {start.shape}')
if switchover_angle == 0:
return numpy.tile(start, (num_points, 1))
resolution = 100000
ll_max = numpy.sqrt(2 * switchover_angle)
qq = numpy.linspace(0, ll_max, resolution)
if reverse:
theta = start_angle - (ll_max * qq - qq * qq / 2)
else:
theta = start_angle - qq * qq / 2
return _integrate_tangent(qq, theta, num_points) + start
def circular_arc(
radius: float,
arc_angle: float,
num_points: int = 200,
*,
start_angle: float = 0.0,
start: ArrayLike = (0.0, 0.0),
) -> NDArray[numpy.float64]:
"""
Generate a clockwise circular arc.
Args:
radius: Arc radius.
arc_angle: Clockwise tangent angle change across the arc, in radians.
num_points: Number of points in the curve, excluding the start point.
start_angle: Tangent angle at the start point.
start: Point where the arc starts.
Returns:
`[[x0, y0], ...]` for the arc, excluding `start`.
"""
if num_points < 0:
raise PatternError(f'num_points must be non-negative, got {num_points}')
if radius <= 0:
raise PatternError(f'radius must be positive, got {radius}')
if arc_angle < 0:
raise PatternError(f'arc_angle must be non-negative, got {arc_angle}')
if num_points == 0:
return numpy.empty((0, 2))
start = numpy.asarray(start, dtype=float)
if start.shape != (2,):
raise PatternError(f'start must be a 2D point; got shape {start.shape}')
if arc_angle == 0:
return numpy.tile(start, (num_points, 1))
angles = numpy.linspace(0, arc_angle, num_points + 1)[1:]
right_normal = numpy.array([numpy.sin(start_angle), -numpy.cos(start_angle)])
center = start + radius * right_normal
radial = start - center
cos_t = numpy.cos(-angles)
sin_t = numpy.sin(-angles)
xx = center[0] + cos_t * radial[0] - sin_t * radial[1]
yy = center[1] + sin_t * radial[0] + cos_t * radial[1]
return numpy.stack((xx, yy), axis=1)
def euler_bend(
switchover_angle: float,
num_points: int = 200,
*,
total_angle: float = pi / 2,
) -> NDArray[numpy.float64]:
"""
Generate a 90 degree Euler bend (AKA Clothoid bend or Cornu spiral).
Generate an Euler bend (AKA Clothoid bend or Cornu spiral).
Positive angles bend clockwise. By default, this generates the historical
90 degree bend.
Args:
switchover_angle: After this angle, the bend will transition into a circular arc
(and transition back to an Euler spiral on the far side). If this is set to
`>= pi / 4`, no circular arc will be added.
num_points: Number of points in the curve
`total_angle / 2`, no circular arc will be added.
num_points: Number of points in the curve.
total_angle: Total tangent angle change across the bend, in radians.
Returns:
`[[x0, y0], ...]` for the curve
"""
if switchover_angle <= 0:
raise PatternError(f'switchover_angle must be positive, got {switchover_angle}')
if total_angle <= 0:
raise PatternError(f'total_angle must be positive, got {total_angle}')
if switchover_angle > total_angle / 2:
raise PatternError(
f'switchover_angle must be <= total_angle / 2; '
f'got {switchover_angle} for total_angle {total_angle}'
)
if num_points < 2:
raise PatternError(f'num_points must be at least 2, got {num_points}')
arc_angle = total_angle - 2 * switchover_angle
ll_max = numpy.sqrt(2 * switchover_angle) # total length of (one) spiral portion
ll_tot = 2 * ll_max + (pi / 2 - 2 * switchover_angle)
num_points_spiral = numpy.floor(ll_max / ll_tot * num_points).astype(int)
num_points_arc = num_points - 2 * num_points_spiral
ll_tot = 2 * ll_max + arc_angle
num_points_spiral = max(2, numpy.floor(ll_max / ll_tot * num_points).astype(int))
num_points_arc = max(0, num_points - 2 * num_points_spiral)
if arc_angle > 0:
num_points_arc = max(1, num_points_arc)
def gen_spiral(ll_max: float) -> NDArray[numpy.float64]:
if ll_max == 0:
return numpy.zeros((num_points_spiral, 2))
resolution = 100000
qq = numpy.linspace(0, ll_max, resolution)
dx = numpy.cos(qq * qq / 2)
dy = -numpy.sin(qq * qq / 2)
dq = ll_max / (resolution - 1)
ix = numpy.zeros(resolution)
iy = numpy.zeros(resolution)
ix[1:] = numpy.cumsum((dx[:-1] + dx[1:]) / 2) * dq
iy[1:] = numpy.cumsum((dy[:-1] + dy[1:]) / 2) * dq
ll_target = numpy.linspace(0, ll_max, num_points_spiral)
x_target = numpy.interp(ll_target, qq, ix)
y_target = numpy.interp(ll_target, qq, iy)
return numpy.stack((x_target, y_target), axis=1)
xy_spiral = gen_spiral(ll_max)
xy_spiral = euler_spiral(switchover_angle, num_points_spiral)
xy_parts = [xy_spiral]
if switchover_angle < pi / 4:
if arc_angle > 0:
# Build a circular segment to join the two euler portions
rmin = 1.0 / ll_max
half_angle = pi / 4 - switchover_angle
qq = numpy.linspace(half_angle * 2, 0, num_points_arc + 1) + switchover_angle
xc = rmin * numpy.cos(qq)
yc = rmin * numpy.sin(qq) + xy_spiral[-1, 1]
xc += xy_spiral[-1, 0] - xc[0]
yc += xy_spiral[-1, 1] - yc[0]
xy_parts.append(numpy.stack((xc[1:], yc[1:]), axis=1))
xy_arc = circular_arc(
rmin,
arc_angle,
num_points_arc,
start_angle=-switchover_angle,
start=xy_spiral[-1],
)
xy_parts.append(xy_arc)
endpoint_xy = xy_parts[-1][-1, :]
second_spiral = xy_spiral[::-1, ::-1] + endpoint_xy - xy_spiral[-1, ::-1]
second_spiral = euler_spiral(
switchover_angle,
num_points_spiral,
start_angle=-(total_angle - switchover_angle),
start=endpoint_xy,
reverse=True,
)
xy_parts.append(second_spiral)
xy_parts.append(second_spiral[1:])
xy = numpy.concatenate(xy_parts)
# Remove any 2x-duplicate points
xy = xy[(numpy.roll(xy, 1, axis=0) - xy > 1e-12).any(axis=1)]
xy = remove_duplicate_vertices(xy, closed_path=False, tolerance=1e-12)
return xy

View file

@ -5,7 +5,11 @@ import numpy
from numpy.typing import NDArray, ArrayLike
def remove_duplicate_vertices(vertices: ArrayLike, closed_path: bool = True) -> NDArray[numpy.float64]:
def remove_duplicate_vertices(
vertices: ArrayLike,
closed_path: bool = True,
tolerance: float = 0.0,
) -> NDArray[numpy.float64]:
"""
Given a list of vertices, remove any consecutive duplicates.
@ -13,14 +17,22 @@ def remove_duplicate_vertices(vertices: ArrayLike, closed_path: bool = True) ->
vertices: `[[x0, y0], [x1, y1], ...]`
closed_path: If True, `vertices` is interpreted as an implicity-closed path
(i.e. the last vertex will be removed if it is the same as the first)
tolerance: Maximum coordinate-wise absolute difference for two vertices to
be considered duplicates. Default `0` requires exact equality.
Returns:
`vertices` with no consecutive duplicates. This may be a view into the original array.
"""
if tolerance < 0:
raise ValueError(f'tolerance must be non-negative, got {tolerance}')
vertices = numpy.asarray(vertices)
if vertices.shape[0] <= 1:
return vertices
if tolerance == 0:
duplicates = (vertices == numpy.roll(vertices, -1, axis=0)).all(axis=1)
else:
duplicates = (numpy.abs(vertices - numpy.roll(vertices, -1, axis=0)) <= tolerance).all(axis=1)
if not closed_path:
duplicates[-1] = False

View file

@ -44,7 +44,7 @@ dependencies = [
[dependency-groups]
dev = [
"pytest",
"masque[arrow]",
"masque[oasis]",
"masque[dxf]",
"masque[svg]",
@ -52,6 +52,7 @@ dev = [
"masque[text]",
"masque[manhattanize]",
"masque[manhattanize_slow]",
"masque[boolean]",
"matplotlib>=3.10.8",
"pytest>=9.0.2",
"ruff>=0.15.5",
@ -66,6 +67,7 @@ build-backend = "hatchling.build"
path = "masque/__init__.py"
[project.optional-dependencies]
arrow = ["pyarrow", "cffi"]
oasis = ["fatamorgana~=0.11"]
dxf = ["ezdxf~=1.4"]
svg = ["svgwrite"]
@ -121,4 +123,3 @@ mypy_path = "stubs"
python_version = "3.11"
strict = false
check_untyped_defs = true