add gdsii_arrow
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masque/file/gdsii_arrow.py
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275
masque/file/gdsii_arrow.py
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"""
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GDSII file format readers and writers using the `klamath` library.
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Note that GDSII references follow the same convention as `masque`,
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with this order of operations:
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1. Mirroring
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2. Rotation
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3. Scaling
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4. Offset and array expansion (no mirroring/rotation/scaling applied to offsets)
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Scaling, rotation, and mirroring apply to individual instances, not grid
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vectors or offsets.
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Notes:
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* absolute positioning is not supported
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* PLEX is not supported
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* ELFLAGS are not supported
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* GDS does not support library- or structure-level annotations
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* GDS creation/modification/access times are set to 1900-01-01 for reproducibility.
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* Gzip modification time is set to 0 (start of current epoch, usually 1970-01-01)
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"""
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from typing import IO, cast, Any
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from collections.abc import Iterable, Mapping, Callable
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import io
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import mmap
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import logging
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import pathlib
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import gzip
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import string
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from pprint import pformat
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import numpy
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from numpy.typing import ArrayLike, NDArray
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import pyarrow
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from pyarrow.cffi import ffi
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from .utils import is_gzipped, tmpfile
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from .. import Pattern, Ref, PatternError, LibraryError, Label, Shape
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from ..shapes import Polygon, Path
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from ..repetition import Grid
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from ..utils import layer_t, annotations_t
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from ..library import LazyLibrary, Library, ILibrary, ILibraryView
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logger = logging.getLogger(__name__)
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clib = ffi.dlopen('/home/jan/projects/klamath-rs/target/debug/libklamath_rs_ext.so')
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ffi.cdef('void read_path(char* path, struct ArrowArray* array, struct ArrowSchema* schema);')
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path_cap_map = {
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0: Path.Cap.Flush,
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1: Path.Cap.Circle,
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2: Path.Cap.Square,
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4: Path.Cap.SquareCustom,
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}
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def rint_cast(val: ArrayLike) -> NDArray[numpy.int32]:
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return numpy.rint(val).astype(numpy.int32)
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def readfile(
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filename: str | pathlib.Path,
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*args,
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**kwargs,
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) -> tuple[Library, dict[str, Any]]:
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"""
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Wrapper for `read()` that takes a filename or path instead of a stream.
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Will automatically decompress gzipped files.
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Args:
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filename: Filename to save to.
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*args: passed to `read()`
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**kwargs: passed to `read()`
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"""
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path = pathlib.Path(filename)
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path.resolve()
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ptr_array = ffi.new('struct ArrowArray[]', 1)
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ptr_schema = ffi.new('struct ArrowSchema[]', 1)
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clib.read_path(str(path).encode(), ptr_array, ptr_schema)
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iptr_schema = int(ffi.cast('uintptr_t', ptr_schema))
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iptr_array = int(ffi.cast('uintptr_t', ptr_array))
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arrow_arr = pyarrow.Array._import_from_c(iptr_array, iptr_schema)
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assert len(arrow_arr) == 1
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results = read_arrow(arrow_arr[0])
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return results
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def read_arrow(
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libarr: pyarrow.Array,
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raw_mode: bool = True,
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) -> tuple[Library, dict[str, Any]]:
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"""
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# TODO check GDSII file for cycles!
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Read a gdsii file and translate it into a dict of Pattern objects. GDSII structures are
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translated into Pattern objects; boundaries are translated into polygons, and srefs and arefs
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are translated into Ref objects.
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Additional library info is returned in a dict, containing:
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'name': name of the library
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'meters_per_unit': number of meters per database unit (all values are in database units)
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'logical_units_per_unit': number of "logical" units displayed by layout tools (typically microns)
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per database unit
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Args:
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stream: Stream to read from.
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raw_mode: If True, constructs shapes in raw mode, bypassing most data validation, Default True.
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Returns:
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- dict of pattern_name:Patterns generated from GDSII structures
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- dict of GDSII library info
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"""
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library_info = _read_header(libarr)
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mlib = Library()
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for cell in libarr['cells']:
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name = libarr['cell_names'][cell['id'].as_py()].as_py()
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pat = read_cell(cell, libarr['cell_names'], raw_mode=raw_mode)
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mlib[name] = pat
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return mlib, library_info
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def _read_header(libarr: pyarrow.Array) -> dict[str, Any]:
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"""
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Read the file header and create the library_info dict.
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"""
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library_info = dict(
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name = libarr['lib_name'],
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meters_per_unit = libarr['meters_per_db_unit'],
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logical_units_per_unit = libarr['user_units_per_db_unit'],
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)
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return library_info
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def read_cell(
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cellarr: pyarrow.Array,
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cell_names: pyarrow.Array,
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raw_mode: bool = True,
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) -> Pattern:
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"""
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TODO
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Read elements from a GDS structure and build a Pattern from them.
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Args:
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stream: Seekable stream, positioned at a record boundary.
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Will be read until an ENDSTR record is consumed.
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name: Name of the resulting Pattern
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raw_mode: If True, bypass per-shape data validation. Default True.
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Returns:
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A pattern containing the elements that were read.
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"""
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pat = Pattern()
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for refarr in cellarr['refs']:
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target = cell_names[refarr['target'].as_py()].as_py()
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args = dict(
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offset = (refarr['x'].as_py(), refarr['y'].as_py()),
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)
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if (mirr := refarr['invert_y']).is_valid:
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args['mirrored'] = mirr.as_py()
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if (rot := refarr['angle_deg']).is_valid:
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args['rotation'] = numpy.deg2rad(rot.as_py())
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if (mag := refarr['mag']).is_valid:
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args['scale'] = mag.as_py()
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if (rep := refarr['repetition']).is_valid:
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repetition = Grid(
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a_vector = (rep['x0'].as_py(), rep['y0'].as_py()),
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b_vector = (rep['x1'].as_py(), rep['y1'].as_py()),
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a_count = rep['count0'].as_py(),
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b_count = rep['count1'].as_py(),
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)
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args['repetition'] = repetition
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ref = Ref(**args)
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pat.refs[target].append(ref)
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for bnd in cellarr['boundaries']:
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layer = (bnd['layer'].as_py(), bnd['dtype'].as_py())
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args = dict(
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vertices = bnd['xy'].values.to_numpy().reshape((-1, 2))[:-1],
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)
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if (props := bnd['properties']).is_valid:
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args['annotations'] = _properties_to_annotations(props)
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poly = Polygon(**args)
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pat.shapes[layer].append(poly)
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for gpath in cellarr['paths']:
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layer = (gpath['layer'].as_py(), gpath['dtype'].as_py())
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args = dict(
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vertices = gpath['xy'].values.to_numpy().reshape((-1, 2)),
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)
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if (gcap := gpath['path_type']).is_valid:
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mcap = path_cap_map[gcap.as_py()]
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args['cap'] = mcap
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if mcap == Path.Cap.SquareCustom:
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extensions = [0, 0]
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if (ext0 := gpath['extension_start']).is_valid:
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extensions[0] = ext0.as_py()
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if (ext1 := gpath['extension_end']).is_valid:
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extensions[1] = ext1.as_py()
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args['extensions'] = extensions
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if (width := gpath['width']).is_valid:
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args['width'] = width.as_py()
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else:
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args['width'] = 0
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if (props := gpath['properties']).is_valid:
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args['annotations'] = _properties_to_annotations(props)
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mpath = Path(**args)
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pat.shapes[layer].append(mpath)
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for gtext in cellarr['texts']:
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layer = (gtext['layer'].as_py(), gtext['dtype'].as_py())
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args = dict(
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offset = (gtext['x'].as_py(), gtext['y'].as_py()),
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string = gtext['string'].as_py(),
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)
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if (props := gtext['properties']).is_valid:
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args['annotations'] = _properties_to_annotations(props)
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mlabel = Label(**args)
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pat.labels[layer].append(mlabel)
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return pat
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def _properties_to_annotations(properties: pyarrow.Array) -> annotations_t:
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return {prop['key'].as_py(): prop['value'].as_py() for prop in properties}
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def check_valid_names(
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names: Iterable[str],
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max_length: int = 32,
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) -> None:
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"""
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Check all provided names to see if they're valid GDSII cell names.
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Args:
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names: Collection of names to check
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max_length: Max allowed length
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"""
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allowed_chars = set(string.ascii_letters + string.digits + '_?$')
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bad_chars = [
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name for name in names
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if not set(name).issubset(allowed_chars)
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]
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bad_lengths = [
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name for name in names
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if len(name) > max_length
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]
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if bad_chars:
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logger.error('Names contain invalid characters:\n' + pformat(bad_chars))
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if bad_lengths:
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logger.error(f'Names too long (>{max_length}:\n' + pformat(bad_chars))
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if bad_chars or bad_lengths:
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raise LibraryError('Library contains invalid names, see log above')
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