[gdsii_arrow] clean unused var in loop

breaking change, but properties are seldom used by anyone afaik

masque/builder/utils.py

@@ -169,11 +169,11 @@ def ell(
                       'emax', 'max_extension',
                       'min_past_furthest',):
         if numpy.size(bound) == 2:
-            bound = cast(Sequence[float], bound)
+            bound = cast('Sequence[float]', bound)
             rot_bound = (rot_matrix @ ((bound[0], 0),
                                        (0, bound[1])))[0, :]
         else:
-            bound = cast(float, bound)
+            bound = cast('float', bound)
             rot_bound = numpy.array(bound)
 
         if rot_bound < 0:
@@ -185,10 +185,10 @@ def ell(
             offsets += rot_bound.min() - offsets.max()
     else:
         if numpy.size(bound) == 2:
-            bound = cast(Sequence[float], bound)
+            bound = cast('Sequence[float]', bound)
             rot_bound = (rot_matrix @ bound)[0]
         else:
-            bound = cast(float, bound)
+            bound = cast('float', bound)
             neg = (direction + pi / 4) % (2 * pi) > pi
             rot_bound = -bound if neg else bound
 

masque/file/dxf.py

@@ -132,7 +132,7 @@ def writefile(
     with tmpfile(path) as base_stream:
         streams: tuple[Any, ...] = (base_stream,)
         if path.suffix == '.gz':
-            gz_stream = cast(IO[bytes], gzip.GzipFile(filename='', mtime=0, fileobj=base_stream, mode='wb'))
+            gz_stream = cast('IO[bytes]', gzip.GzipFile(filename='', mtime=0, fileobj=base_stream, mode='wb'))
             streams = (gz_stream,) + streams
         else:
             gz_stream = base_stream

masque/file/gdsii.py

@@ -21,6 +21,7 @@ Notes:
 """
 from typing import IO, cast, Any
 from collections.abc import Iterable, Mapping, Callable
+from types import MappingProxyType
 import io
 import mmap
 import logging
@@ -52,6 +53,8 @@ path_cap_map = {
     4: Path.Cap.SquareCustom,
     }
 
+RO_EMPTY_DICT: Mapping[int, bytes] = MappingProxyType({})
+
 
 def rint_cast(val: ArrayLike) -> NDArray[numpy.int32]:
     return numpy.rint(val).astype(numpy.int32)
@@ -145,7 +148,7 @@ def writefile(
     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))
+            stream = cast('IO[bytes]', gzip.GzipFile(filename='', mtime=0, fileobj=base_stream, mode='wb', compresslevel=6))
             streams = (stream,) + streams
         else:
             stream = base_stream
@@ -399,11 +402,15 @@ def _mrefs_to_grefs(refs: dict[str | None, list[Ref]]) -> list[klamath.library.R
     return grefs
 
 
-def _properties_to_annotations(properties: dict[int, bytes]) -> annotations_t:
+def _properties_to_annotations(properties: Mapping[int, bytes]) -> annotations_t:
+    if not properties:
+        return None
     return {str(k): [v.decode()] for k, v in properties.items()}
 
 
-def _annotations_to_properties(annotations: annotations_t, max_len: int = 126) -> dict[int, bytes]:
+def _annotations_to_properties(annotations: annotations_t, max_len: int = 126) -> Mapping[int, bytes]:
+    if annotations is None:
+        return RO_EMPTY_DICT
     cum_len = 0
     props = {}
     for key, vals in annotations.items():

masque/file/gdsii_arrow.py

@@ -0,0 +1,426 @@
+"""
+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
+import io
+import mmap
+import logging
+import pathlib
+import gzip
+import string
+from pprint import pformat
+
+import numpy
+from numpy.typing import ArrayLike, NDArray
+from numpy.testing import assert_equal
+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
+from ..repetition import Grid
+from ..utils import layer_t, annotations_t
+from ..library import LazyLibrary, Library, ILibrary, ILibraryView
+
+
+logger = logging.getLogger(__name__)
+
+clib = ffi.dlopen('/home/jan/projects/klamath-rs/target/release/libklamath_rs_ext.so')
+ffi.cdef('void read_path(char* path, struct ArrowArray* array, struct ArrowSchema* schema);')
+
+
+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 _read_to_arrow(
+        filename: str | pathlib.Path,
+        *args,
+        **kwargs,
+        ) -> pyarrow.Array:
+    path = pathlib.Path(filename)
+    path.resolve()
+    ptr_array = ffi.new('struct ArrowArray[]', 1)
+    ptr_schema = ffi.new('struct ArrowSchema[]', 1)
+    clib.read_path(str(path).encode(), ptr_array, ptr_schema)
+
+    iptr_schema = int(ffi.cast('uintptr_t', ptr_schema))
+    iptr_array = int(ffi.cast('uintptr_t', ptr_array))
+    arrow_arr = pyarrow.Array._import_from_c(iptr_array, iptr_schema)
+
+    return arrow_arr
+
+
+def readfile(
+        filename: str | pathlib.Path,
+        *args,
+        **kwargs,
+        ) -> tuple[Library, dict[str, Any]]:
+    """
+    Wrapper for `read()` that takes a filename or path instead of a stream.
+
+    Will automatically decompress gzipped files.
+
+    Args:
+        filename: Filename to save to.
+        *args: passed to `read()`
+        **kwargs: passed to `read()`
+    """
+    arrow_arr = _read_to_arrow(filename)
+    assert len(arrow_arr) == 1
+
+    results = read_arrow(arrow_arr[0])
+
+    return results
+
+
+def read_arrow(
+        libarr: pyarrow.Array,
+        raw_mode: bool = True,
+        ) -> 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:
+        stream: Stream to read from.
+        raw_mode: If True, constructs shapes in raw mode, bypassing most data validation, Default True.
+
+    Returns:
+        - dict of pattern_name:Patterns generated from GDSII structures
+        - dict of GDSII library info
+    """
+    library_info = _read_header(libarr)
+
+    layer_names_np = libarr['layers'].values.to_numpy().view('i2').reshape((-1, 2))
+    layer_tups = [tuple(pair) 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
+
+    rf = libarr['cells'].values.field('refs')
+    refs = dict(
+        offsets = rf.offsets.to_numpy(),
+        targets = rf.values.field('target').to_numpy(),
+        xy = rf.values.field('xy').to_numpy().view('i4').reshape((-1, 2)),
+        invert_y = rf.values.field('invert_y').fill_null(False).to_numpy(zero_copy_only=False),
+        angle_rad = numpy.rad2deg(rf.values.field('angle_deg').fill_null(0).to_numpy()),
+        scale = rf.values.field('mag').fill_null(1).to_numpy(),
+        rep_valid = rf.values.field('repetition').is_valid().to_numpy(zero_copy_only=False),
+        rep_xy0 = rf.values.field('repetition').field('xy0').fill_null(0).to_numpy().view('i4').reshape((-1, 2)),
+        rep_xy1 = rf.values.field('repetition').field('xy1').fill_null(0).to_numpy().view('i4').reshape((-1, 2)),
+        rep_counts = rf.values.field('repetition').field('counts').fill_null(0).to_numpy().view('i2').reshape((-1, 2)),
+        prop_off = rf.values.field('properties').offsets.to_numpy(),
+        prop_key = rf.values.field('properties').values.field('key').to_numpy(),
+        prop_val = rf.values.field('properties').values.field('value').to_pylist(),
+        )
+
+    txt = libarr['cells'].values.field('texts')
+    texts = dict(
+        offsets = txt.offsets.to_numpy(),
+        layer_inds = txt.values.field('layer').to_numpy(),
+        xy = txt.values.field('xy').to_numpy().view('i4').reshape((-1, 2)),
+        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(
+        boundaries = get_geom(libarr, 'boundaries'),
+        paths = get_geom(libarr, 'paths'),
+        boxes = get_geom(libarr, 'boxes'),
+        nodes = get_geom(libarr, 'nodes'),
+        texts = texts,
+        refs = refs,
+        )
+
+    paths = libarr['cells'].values.field('paths')
+    elements['paths'].update(dict(
+        width = paths.values.field('width').to_numpy(),
+        path_type = paths.values.field('path_type').to_numpy(),
+        extensions = numpy.stack((
+            paths.values.field('extension_start').to_numpy(zero_copy_only=False),
+            paths.values.field('extension_end').to_numpy(zero_copy_only=False),
+            ), axis=-1),
+        ))
+
+    global_args = dict(
+        cell_names = cell_names,
+        layer_tups = layer_tups,
+        raw_mode = raw_mode,
+        )
+
+    mlib = Library()
+    for cc in range(len(libarr['cells'])):
+        name = cell_names[cell_ids[cc]]
+        pat = Pattern()
+        _boundaries_to_polygons(pat, global_args, elements['boundaries'], cc)
+        _gpaths_to_mpaths(pat, global_args, elements['paths'], cc)
+        _grefs_to_mrefs(pat, global_args, elements['refs'], 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'],
+        meters_per_unit = libarr['meters_per_db_unit'],
+        logical_units_per_unit = libarr['user_units_per_db_unit'],
+        )
+    return library_info
+
+
+def _grefs_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']      # which elements belong to each cell
+    xy = elem['xy']
+    prop_key = elem['prop_key']
+    prop_val = elem['prop_val']
+    targets = elem['targets']
+
+    rep_valid = elem['rep_valid']
+
+    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_invert_y = elem['invert_y'][elem_slc]
+    elem_angle_rad = elem['angle_rad'][elem_slc]
+    elem_scale = elem['scale'][elem_slc]
+    elem_rep_xy0 = elem['rep_xy0'][elem_slc]
+    elem_rep_xy1 = elem['rep_xy1'][elem_slc]
+    elem_rep_counts = elem['rep_counts'][elem_slc]
+
+    for ee in range(elem_count):
+        target = cell_names[targets[ee]]
+        offset = xy[ee]
+        mirr = elem_invert_y[ee]
+        rot = elem_angle_rad[ee]
+        mag = elem_scale[ee]
+
+        rep: None | Grid = None
+        if rep_valid[ee]:
+            a_vector = elem_rep_xy0[ee]
+            b_vector = elem_rep_xy1[ee]
+            a_count, b_count = elem_rep_counts[ee]
+            rep = Grid(a_vector=a_vector, b_vector=b_vector, a_count=a_count, b_count=b_count)
+
+        annotations: None | dict[int, str] = None
+        prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
+        if prop_ii < prop_ff:
+            annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
+
+        ref = Ref(offset=offset, mirrored=mirr, rotation=rot, scale=mag, repetition=rep, annotations=annotations)
+        pat.refs[target].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_layer_inds = layer_inds[elem_slc]
+    elem_strings = elem['string'][elem_slc]
+
+    for ee in range(elem_count):
+        layer = layer_tups[elem_layer_inds[ee]]
+        offset = xy[ee]
+        string = elem_strings[ee]
+
+        annotations: None | dict[int, str] = None
+        prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
+        if prop_ii < prop_ff:
+            annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
+
+        mlabel = Label(string=string, offset=offset, annotations=annotations)
+        pat.labels[layer].append(mlabel)
+
+
+def _gpaths_to_mpaths(
+        pat: Pattern,
+        global_args: dict[str, Any],
+        elem: dict[str, Any],
+        cc: int,
+        ) -> None:
+    elem_off = elem['offsets']      # which elements belong to each cell
+    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_widths = elem['width'][elem_slc]
+    elem_path_types = elem['path_type'][elem_slc]
+    elem_extensions = elem['extensions'][elem_slc]
+
+    zeros = numpy.zeros((elem_count, 2))
+    raw_mode = global_args['raw_mode']
+    for ee in range(elem_count):
+        layer = layer_tups[elem_layer_inds[ee]]
+        vertices = xy_val[xy_offs[ee]:xy_offs[ee + 1]]
+        width = elem_widths[ee]
+        cap_int = elem_path_types[ee]
+        cap = path_cap_map[cap_int]
+        if cap_int == 4:
+            cap_extensions = elem_extensions[ee]
+        else:
+            cap_extensions = None
+
+        annotations: None | dict[int, str] = None
+        prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
+        if prop_ii < prop_ff:
+            annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
+
+        path = Path(vertices=vertices, offset=zeros[ee], annotations=annotations, raw=raw_mode,
+            width=width, cap=cap,cap_extensions=cap_extensions)
+        pat.shapes[layer].append(path)
+
+
+def _boundaries_to_polygons(
+        pat: Pattern,
+        global_args: dict[str, Any],
+        elem: dict[str, Any],
+        cc: int,
+        ) -> None:
+    elem_off = elem['offsets']      # which elements belong to each cell
+    xy_val = elem['xy_arr']
+    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]
+    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]
+
+    zeros = numpy.zeros((elem_count, 2))
+    raw_mode = global_args['raw_mode']
+    for ee in range(elem_count):
+        layer = layer_tups[elem_layer_inds[ee]]
+        vertices = xy_val[xy_offs[ee]:xy_offs[ee + 1] - 1]    # -1 to drop closing point
+
+        annotations: None | dict[int, str] = None
+        prop_ii, prop_ff = prop_offs[ee], prop_offs[ee + 1]
+        if prop_ii < prop_ff:
+            annotations = {prop_key[off]: prop_val[off] for off in range(prop_ii, prop_ff)}
+
+        poly = Polygon(vertices=vertices, offset=zeros[ee], annotations=annotations, raw=raw_mode)
+        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')

masque/file/oasis.py

@@ -190,7 +190,7 @@ def writefile(
     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'))
+            stream = cast('IO[bytes]', gzip.GzipFile(filename='', mtime=0, fileobj=base_stream, mode='wb'))
             streams += (stream,)
         else:
             stream = base_stream
@@ -551,7 +551,7 @@ def _shapes_to_elements(
                 circle = fatrec.Circle(
                     layer=layer,
                     datatype=datatype,
-                    radius=cast(int, radius),
+                    radius=cast('int', radius),
                     x=offset[0],
                     y=offset[1],
                     properties=properties,
@@ -568,8 +568,8 @@ def _shapes_to_elements(
                 path = fatrec.Path(
                     layer=layer,
                     datatype=datatype,
-                    point_list=cast(Sequence[Sequence[int]], deltas),
+                    point_list=cast('Sequence[Sequence[int]]', deltas),
-                    half_width=cast(int, half_width),
+                    half_width=cast('int', half_width),
                     x=xy[0],
                     y=xy[1],
                     extension_start=extension_start,       # TODO implement multiple cap types?
@@ -587,7 +587,7 @@ def _shapes_to_elements(
                         datatype=datatype,
                         x=xy[0],
                         y=xy[1],
-                        point_list=cast(list[list[int]], points),
+                        point_list=cast('list[list[int]]', points),
                         properties=properties,
                         repetition=repetition,
                         ))
@@ -651,10 +651,10 @@ def repetition_masq2fata(
         a_count = rint_cast(rep.a_count)
         b_count = rint_cast(rep.b_count) if rep.b_count is not None else None
         frep = fatamorgana.GridRepetition(
-            a_vector=cast(list[int], a_vector),
+            a_vector=cast('list[int]', a_vector),
-            b_vector=cast(list[int] | None, b_vector),
+            b_vector=cast('list[int] | None', b_vector),
-            a_count=cast(int, a_count),
+            a_count=cast('int', a_count),
-            b_count=cast(int | None, b_count),
+            b_count=cast('int | None', b_count),
             )
         offset = (0, 0)
     elif isinstance(rep, Arbitrary):
@@ -671,6 +671,8 @@ def repetition_masq2fata(
 
 def annotations_to_properties(annotations: annotations_t) -> list[fatrec.Property]:
     #TODO determine is_standard based on key?
+    if annotations is None:
+        return []
     properties = []
     for key, values in annotations.items():
         vals = [AString(v) if isinstance(v, str) else v

masque/library.py

@@ -211,7 +211,7 @@ class ILibraryView(Mapping[str, 'Pattern'], metaclass=ABCMeta):
         if isinstance(tops, str):
             tops = (tops,)
 
-        keep = cast(set[str], self.referenced_patterns(tops) - {None})
+        keep = cast('set[str]', self.referenced_patterns(tops) - {None})
         keep |= set(tops)
 
         filtered = {kk: vv for kk, vv in self.items() if kk in keep}
@@ -314,7 +314,7 @@ class ILibraryView(Mapping[str, 'Pattern'], metaclass=ABCMeta):
             flatten_single(top)
 
         assert None not in flattened.values()
-        return cast(dict[str, 'Pattern'], flattened)
+        return cast('dict[str, Pattern]', flattened)
 
     def get_name(
             self,
@@ -504,7 +504,7 @@ class ILibraryView(Mapping[str, 'Pattern'], metaclass=ABCMeta):
                 raise LibraryError('visit_* functions returned a new `Pattern` object'
                                    ' but no top-level name was provided in `hierarchy`')
 
-            cast(ILibrary, self)[name] = pattern
+            cast('ILibrary', self)[name] = pattern
 
         return self
 
@@ -542,7 +542,7 @@ class ILibraryView(Mapping[str, 'Pattern'], metaclass=ABCMeta):
         Return:
             Topologically sorted list of pattern names.
         """
-        return cast(list[str], list(TopologicalSorter(self.child_graph()).static_order()))
+        return cast('list[str]', list(TopologicalSorter(self.child_graph()).static_order()))
 
     def find_refs_local(
             self,
@@ -827,7 +827,7 @@ class ILibrary(ILibraryView, MutableMapping[str, 'Pattern'], metaclass=ABCMeta):
         for old_name in temp:
             new_name = rename_map.get(old_name, old_name)
             pat = self[new_name]
-            pat.refs = map_targets(pat.refs, lambda tt: cast(dict[str | None, str | None], rename_map).get(tt, tt))
+            pat.refs = map_targets(pat.refs, lambda tt: cast('dict[str | None, str | None]', rename_map).get(tt, tt))
 
         return rename_map
 
@@ -944,8 +944,8 @@ class ILibrary(ILibraryView, MutableMapping[str, 'Pattern'], metaclass=ABCMeta):
 
             shape_table: dict[tuple, list] = defaultdict(list)
             for layer, sseq in pat.shapes.items():
-                for i, shape in enumerate(sseq):
+                for ii, shape in enumerate(sseq):
-                    if any(isinstance(shape, t) for t in exclude_types):
+                    if any(isinstance(shape, tt) for tt in exclude_types):
                         continue
 
                     base_label, values, _func = shape.normalized_form(norm_value)
@@ -954,16 +954,16 @@ class ILibrary(ILibraryView, MutableMapping[str, 'Pattern'], metaclass=ABCMeta):
                     if label not in shape_pats:
                         continue
 
-                    shape_table[label].append((i, values))
+                    shape_table[label].append((ii, values))
 
             #  For repeated shapes, create a `Pattern` holding a normalized shape object,
             # and add `pat.refs` entries for each occurrence in pat. Also, note down that
             # we should delete the `pat.shapes` entries for which we made `Ref`s.
             shapes_to_remove = []
-            for label in shape_table:
+            for label, shape_entries in shape_table.items():
                 layer = label[-1]
                 target = label2name(label)
-                for ii, values in shape_table[label]:
+                for ii, values in shape_entries:
                     offset, scale, rotation, mirror_x = values
                     pat.ref(target=target, offset=offset, scale=scale,
                             rotation=rotation, mirrored=(mirror_x, False))
@@ -1047,7 +1047,7 @@ class ILibrary(ILibraryView, MutableMapping[str, 'Pattern'], metaclass=ABCMeta):
         if isinstance(tops, str):
             tops = (tops,)
 
-        keep = cast(set[str], self.referenced_patterns(tops) - {None})
+        keep = cast('set[str]', self.referenced_patterns(tops) - {None})
         keep |= set(tops)
 
         new = type(self)()

masque/pattern.py

@@ -332,7 +332,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
             ))
 
         self.ports = dict(sorted(self.ports.items()))
-        self.annotations = dict(sorted(self.annotations.items()))
+        self.annotations = dict(sorted(self.annotations.items())) if self.annotations is not None else None
 
         return self
 
@@ -354,6 +354,9 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
         for layer, lseq in other_pattern.labels.items():
             self.labels[layer].extend(lseq)
 
+        if other_pattern.annotations is not None:
+            if self.annotations is None:
+                self.annotations = {}
             annotation_conflicts = set(self.annotations.keys()) & set(other_pattern.annotations.keys())
             if annotation_conflicts:
                 raise PatternError(f'Annotation keys overlap: {annotation_conflicts}')
@@ -415,7 +418,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
         elif default_keep:
             pat.refs = copy.copy(self.refs)
 
-        if annotations is not None:
+        if annotations is not None and self.annotations is not None:
             pat.annotations = {k: v for k, v in self.annotations.items() if annotations(k, v)}
         elif default_keep:
             pat.annotations = copy.copy(self.annotations)
@@ -491,7 +494,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
         """
         pat = self.deepcopy().polygonize().flatten(library=library)
         polys = [
-            cast(Polygon, shape).vertices + cast(Polygon, shape).offset
+            cast('Polygon', shape).vertices + cast('Polygon', shape).offset
             for shape in chain_elements(pat.shapes)
             ]
         return polys
@@ -533,7 +536,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
         n_elems = sum(1 for _ in chain_elements(self.shapes, self.labels))
         ebounds = numpy.full((n_elems, 2, 2), nan)
         for ee, entry in enumerate(chain_elements(self.shapes, self.labels)):
-            maybe_ebounds = cast(Bounded, entry).get_bounds()
+            maybe_ebounds = cast('Bounded', entry).get_bounds()
             if maybe_ebounds is not None:
                 ebounds[ee] = maybe_ebounds
         mask = ~numpy.isnan(ebounds[:, 0, 0])
@@ -631,7 +634,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
             self
         """
         for entry in chain(chain_elements(self.shapes, self.labels, self.refs), self.ports.values()):
-            cast(Positionable, entry).translate(offset)
+            cast('Positionable', entry).translate(offset)
         return self
 
     def scale_elements(self, c: float) -> Self:
@@ -645,33 +648,37 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
             self
         """
         for entry in chain_elements(self.shapes, self.refs):
-            cast(Scalable, entry).scale_by(c)
+            cast('Scalable', entry).scale_by(c)
         return self
 
-    def scale_by(self, c: float) -> Self:
+    def scale_by(self, c: float, scale_refs: bool = True) -> Self:
         """
         Scale this Pattern by the given value
-         (all shapes and refs and their offsets are scaled,
+        All shapes and (optionally) refs and their offsets are scaled,
-          as are all label and port offsets)
+          as are all label and port offsets.
 
         Args:
             c: factor to scale by
+            scale_refs: Whether to scale refs. Ref offsets are always scaled,
+                but it may be desirable to not scale the ref itself (e.g. if
+                the target cell was also scaled).
 
         Returns:
             self
         """
         for entry in chain_elements(self.shapes, self.refs):
-            cast(Positionable, entry).offset *= c
+            cast('Positionable', entry).offset *= c
-            cast(Scalable, entry).scale_by(c)
+            if scale_refs or not isinstance(entry, Ref):
+                cast('Scalable', entry).scale_by(c)
 
-            rep = cast(Repeatable, entry).repetition
+            rep = cast('Repeatable', entry).repetition
             if rep:
                 rep.scale_by(c)
 
         for label in chain_elements(self.labels):
-            cast(Positionable, label).offset *= c
+            cast('Positionable', label).offset *= c
 
-            rep = cast(Repeatable, label).repetition
+            rep = cast('Repeatable', label).repetition
             if rep:
                 rep.scale_by(c)
 
@@ -708,8 +715,8 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
             self
         """
         for entry in chain(chain_elements(self.shapes, self.refs, self.labels), self.ports.values()):
-            old_offset = cast(Positionable, entry).offset
+            old_offset = cast('Positionable', entry).offset
-            cast(Positionable, entry).offset = numpy.dot(rotation_matrix_2d(rotation), old_offset)
+            cast('Positionable', entry).offset = numpy.dot(rotation_matrix_2d(rotation), old_offset)
         return self
 
     def rotate_elements(self, rotation: float) -> Self:
@@ -723,7 +730,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
             self
         """
         for entry in chain(chain_elements(self.shapes, self.refs), self.ports.values()):
-            cast(Rotatable, entry).rotate(rotation)
+            cast('Rotatable', entry).rotate(rotation)
         return self
 
     def mirror_element_centers(self, across_axis: int = 0) -> Self:
@@ -738,7 +745,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
             self
         """
         for entry in chain(chain_elements(self.shapes, self.refs, self.labels), self.ports.values()):
-            cast(Positionable, entry).offset[across_axis - 1] *= -1
+            cast('Positionable', entry).offset[across_axis - 1] *= -1
         return self
 
     def mirror_elements(self, across_axis: int = 0) -> Self:
@@ -754,7 +761,7 @@ class Pattern(PortList, AnnotatableImpl, Mirrorable):
             self
         """
         for entry in chain(chain_elements(self.shapes, self.refs), self.ports.values()):
-            cast(Mirrorable, entry).mirror(across_axis)
+            cast('Mirrorable', entry).mirror(across_axis)
         return self
 
     def mirror(self, across_axis: int = 0) -> Self:

masque/repetition.py

@@ -294,7 +294,7 @@ class Grid(Repetition):
     def __le__(self, other: Repetition) -> bool:
         if type(self) is not type(other):
             return repr(type(self)) < repr(type(other))
-        other = cast(Grid, other)
+        other = cast('Grid', other)
         if self.a_count != other.a_count:
             return self.a_count < other.a_count
         if self.b_count != other.b_count:
@@ -357,7 +357,7 @@ class Arbitrary(Repetition):
     def __le__(self, other: Repetition) -> bool:
         if type(self) is not type(other):
             return repr(type(self)) < repr(type(other))
-        other = cast(Arbitrary, other)
+        other = cast('Arbitrary', other)
         if self.displacements.size != other.displacements.size:
             return self.displacements.size < other.displacements.size
 

masque/shapes/arc.py

@@ -157,7 +157,7 @@ class Arc(Shape):
             offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0,
             repetition: Repetition | None = None,
-            annotations: annotations_t | None = None,
+            annotations: annotations_t = None,
             raw: bool = False,
             ) -> None:
         if raw:
@@ -170,7 +170,7 @@ class Arc(Shape):
             self._offset = offset
             self._rotation = rotation
             self._repetition = repetition
-            self._annotations = annotations if annotations is not None else {}
+            self._annotations = annotations
         else:
             self.radii = radii
             self.angles = angles
@@ -178,7 +178,7 @@ class Arc(Shape):
             self.offset = offset
             self.rotation = rotation
             self.repetition = repetition
-            self.annotations = annotations if annotations is not None else {}
+            self.annotations = annotations
 
     def __deepcopy__(self, memo: dict | None = None) -> 'Arc':
         memo = {} if memo is None else memo
@@ -206,7 +206,7 @@ class Arc(Shape):
             if repr(type(self)) != repr(type(other)):
                 return repr(type(self)) < repr(type(other))
             return id(type(self)) < id(type(other))
-        other = cast(Arc, other)
+        other = cast('Arc', other)
         if self.width != other.width:
             return self.width < other.width
         if not numpy.array_equal(self.radii, other.radii):
@@ -233,7 +233,7 @@ class Arc(Shape):
         r0, r1 = self.radii
 
         # Convert from polar angle to ellipse parameter (for [rx*cos(t), ry*sin(t)] representation)
-        a_ranges = cast(_array2x2_t, self._angles_to_parameters())
+        a_ranges = cast('_array2x2_t', self._angles_to_parameters())
 
         # Approximate perimeter via numerical integration
 
@@ -321,7 +321,7 @@ class Arc(Shape):
 
         If the extrema are innaccessible due to arc constraints, check the arc endpoints instead.
         """
-        a_ranges = cast(_array2x2_t, self._angles_to_parameters())
+        a_ranges = cast('_array2x2_t', self._angles_to_parameters())
 
         mins = []
         maxs = []
@@ -432,7 +432,7 @@ class Arc(Shape):
              [[x2, y2], [x3, y3]]],    would create this arc from its corresponding ellipse.
             ```
         """
-        a_ranges = cast(_array2x2_t, self._angles_to_parameters())
+        a_ranges = cast('_array2x2_t', self._angles_to_parameters())
 
         mins = []
         maxs = []

masque/shapes/circle.py

@@ -48,7 +48,7 @@ class Circle(Shape):
             *,
             offset: ArrayLike = (0.0, 0.0),
             repetition: Repetition | None = None,
-            annotations: annotations_t | None = None,
+            annotations: annotations_t = None,
             raw: bool = False,
             ) -> None:
         if raw:
@@ -56,12 +56,12 @@ class Circle(Shape):
             self._radius = radius
             self._offset = offset
             self._repetition = repetition
-            self._annotations = annotations if annotations is not None else {}
+            self._annotations = annotations
         else:
             self.radius = radius
             self.offset = offset
             self.repetition = repetition
-            self.annotations = annotations if annotations is not None else {}
+            self.annotations = annotations
 
     def __deepcopy__(self, memo: dict | None = None) -> 'Circle':
         memo = {} if memo is None else memo
@@ -84,7 +84,7 @@ class Circle(Shape):
             if repr(type(self)) != repr(type(other)):
                 return repr(type(self)) < repr(type(other))
             return id(type(self)) < id(type(other))
-        other = cast(Circle, other)
+        other = cast('Circle', other)
         if not self.radius == other.radius:
             return self.radius < other.radius
         if not numpy.array_equal(self.offset, other.offset):

masque/shapes/ellipse.py

@@ -93,7 +93,7 @@ class Ellipse(Shape):
             offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0,
             repetition: Repetition | None = None,
-            annotations: annotations_t | None = None,
+            annotations: annotations_t = None,
             raw: bool = False,
             ) -> None:
         if raw:
@@ -103,13 +103,13 @@ class Ellipse(Shape):
             self._offset = offset
             self._rotation = rotation
             self._repetition = repetition
-            self._annotations = annotations if annotations is not None else {}
+            self._annotations = annotations
         else:
             self.radii = radii
             self.offset = offset
             self.rotation = rotation
             self.repetition = repetition
-            self.annotations = annotations if annotations is not None else {}
+            self.annotations = annotations
 
     def __deepcopy__(self, memo: dict | None = None) -> Self:
         memo = {} if memo is None else memo
@@ -134,7 +134,7 @@ class Ellipse(Shape):
             if repr(type(self)) != repr(type(other)):
                 return repr(type(self)) < repr(type(other))
             return id(type(self)) < id(type(other))
-        other = cast(Ellipse, other)
+        other = cast('Ellipse', other)
         if not numpy.array_equal(self.radii, other.radii):
             return tuple(self.radii) < tuple(other.radii)
         if not numpy.array_equal(self.offset, other.offset):

masque/shapes/path.py

@@ -170,7 +170,7 @@ class Path(Shape):
             offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0,
             repetition: Repetition | None = None,
-            annotations: annotations_t | None = None,
+            annotations: annotations_t = None,
             raw: bool = False,
             ) -> None:
         self._cap_extensions = None     # Since .cap setter might access it
@@ -182,7 +182,7 @@ class Path(Shape):
             self._vertices = vertices
             self._offset = offset
             self._repetition = repetition
-            self._annotations = annotations if annotations is not None else {}
+            self._annotations = annotations
             self._width = width
             self._cap = cap
             self._cap_extensions = cap_extensions
@@ -190,7 +190,7 @@ class Path(Shape):
             self.vertices = vertices
             self.offset = offset
             self.repetition = repetition
-            self.annotations = annotations if annotations is not None else {}
+            self.annotations = annotations
             self.width = width
             self.cap = cap
             self.cap_extensions = cap_extensions
@@ -223,7 +223,7 @@ class Path(Shape):
             if repr(type(self)) != repr(type(other)):
                 return repr(type(self)) < repr(type(other))
             return id(type(self)) < id(type(other))
-        other = cast(Path, other)
+        other = cast('Path', other)
         if self.width != other.width:
             return self.width < other.width
         if self.cap != other.cap:
@@ -405,7 +405,7 @@ class Path(Shape):
         x_min = rotated_vertices[:, 0].argmin()
         if not is_scalar(x_min):
             y_min = rotated_vertices[x_min, 1].argmin()
-            x_min = cast(Sequence, x_min)[y_min]
+            x_min = cast('Sequence', x_min)[y_min]
         reordered_vertices = numpy.roll(rotated_vertices, -x_min, axis=0)
 
         width0 = self.width / norm_value

masque/shapes/poly_collection.py

@@ -1,97 +1,103 @@
-from typing import Any, cast, Iterable
+from typing import Any, cast, Self
-from collections.abc import Sequence
+from collections.abc import Iterator
 import copy
 import functools
+from itertools import chain
 
 import numpy
 from numpy import pi
 from numpy.typing import NDArray, ArrayLike
 
 from . import Shape, normalized_shape_tuple
-from ..error import PatternError
+from .polygon import Polygon
 from ..repetition import Repetition
-from ..utils import is_scalar, rotation_matrix_2d, annotations_lt, annotations_eq, rep2key
+from ..utils import rotation_matrix_2d, annotations_lt, annotations_eq, rep2key, annotations_t
-from ..utils import remove_colinear_vertices, remove_duplicate_vertices, annotations_t
 
 
 @functools.total_ordering
 class PolyCollection(Shape):
     """
-    A collection of polygons, consisting of list of vertex arrays (N_m x 2 ndarrays) which specify
+    A collection of polygons, consisting of concatenated vertex arrays (N_m x 2 ndarray) which specify
-       implicitly-closed boundaries, and an offset.
+       implicitly-closed boundaries, and an array of offets specifying the first vertex of each
+       successive polygon.
 
-    Note that the setter for `PolyCollection.vertex_list` creates a copy of the
+    A `normalized_form(...)` is available, but is untested and probably fairly slow.
-      passed vertex coordinates.
-
-    A `normalized_form(...)` is available, but can be quite slow with lots of vertices.
     """
     __slots__ = (
         '_vertex_lists',
+        '_vertex_offsets',
         # Inherited
         '_offset', '_repetition', '_annotations',
         )
 
-    _vertex_lists: list[NDArray[numpy.float64]]
+    _vertex_lists: NDArray[numpy.float64]
-    """ List of ndarrays (N_m x 2)  of vertices `[ [[x0, y0], [x1, y1], ...] ]` """
+    """ 2D NDArray ((N+M+...) x 2)  of vertices `[[xa0, ya0], [xa1, ya1], ..., [xb0, yb0], [xb1, yb1], ... ]` """
+
+    _vertex_offsets: NDArray[numpy.intp]
+    """ 1D NDArray specifying the starting offset for each polygon """
 
-    # vertex_lists property
     @property
     def vertex_lists(self) -> Any:        # mypy#3004   NDArray[numpy.float64]:
         """
-        Vertices of the polygons (ist of ndarrays (N_m x 2) `[ [[x0, y0], [x1, y1], ...] ]`
+        Vertices of the polygons, ((N+M+...) x 2). Use with `vertex_offsets`.
-
-        When setting, note that a copy will be made,
         """
         return self._vertex_lists
 
-    @vertex_lists.setter
-    def vertex_lists(self, val: ArrayLike) -> None:
-        val = [numpy.array(vv, dtype=float) for vv in val]
-        for ii, vv in enumerate(val):
-            if len(vv.shape) < 2 or vv.shape[1] != 2:
-                raise PatternError(f'vertex_lists contents must be an Nx2 arrays (polygon #{ii} fails)')
-            if vv.shape[0] < 3:
-                raise PatternError(f'vertex_lists contents must have at least 3 vertices (Nx2 where N>2) (polygon ${ii} has shape {vv.shape})')
-        self._vertices = val
-
-    # xs property
     @property
-    def xs(self) -> NDArray[numpy.float64]:
+    def vertex_offsets(self) -> Any:        # mypy#3004   NDArray[numpy.intp]:
         """
-        All vertex x coords as a 1D ndarray
+        Starting offset (in `vertex_lists`) for each polygon
         """
-        return self.vertices[:, 0]
+        return self._vertex_offsets
+
+    @property
+    def vertex_slices(self) -> Iterator[slice]:
+        """
+        Iterator which provides slices which index vertex_lists
+        """
+        for ii, ff in chain(self._vertex_offsets, (self._vertex_lists.shape[0],)):
+            yield slice(ii, ff)
+
+    @property
+    def polygon_vertices(self) -> Iterator[NDArray[numpy.float64]]:
+        for slc in self.vertex_slices:
+            yield self._vertex_lists[slc]
 
     def __init__(
             self,
-            vertex_lists: Iterable[ArrayLike],
+            vertex_lists: ArrayLike,
+            vertex_offsets: ArrayLike,
             *,
             offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0.0,
             repetition: Repetition | None = None,
-            annotations: annotations_t | None = None,
+            annotations: annotations_t = None,
             raw: bool = False,
             ) -> None:
         if raw:
-            assert isinstance(vertex_lists, list)
+            assert isinstance(vertex_lists, numpy.ndarray)
-            assert all(isinstance(vv, numpy.ndarray) for vv in vertex_lists)
+            assert isinstance(vertex_offsets, numpy.ndarray)
             assert isinstance(offset, numpy.ndarray)
             self._vertex_lists = vertex_lists
+            self._vertex_offsets = vertex_offsets
             self._offset = offset
             self._repetition = repetition
-            self._annotations = annotations if annotations is not None else {}
+            self._annotations = annotations
         else:
-            self.vertices = vertices
+            self._vertex_lists = numpy.asarray(vertex_lists, dtype=float)
+            self._vertex_offsets = numpy.asarray(vertex_offsets, dtype=numpy.intp)
             self.offset = offset
             self.repetition = repetition
-            self.annotations = annotations if annotations is not None else {}
+            self.annotations = annotations
+        if rotation:
             self.rotate(rotation)
 
-    def __deepcopy__(self, memo: dict | None = None) -> 'PolyCollection':
+    def __deepcopy__(self, memo: dict | None = None) -> Self:
         memo = {} if memo is None else memo
         new = copy.copy(self)
         new._offset = self._offset.copy()
-        new._vertex_lists = [vv.copy() for vv in self._vertex_lists]
+        new._vertex_lists = self._vertex_lists.copy()
+        new._vertex_offsets = self._vertex_offsets.copy()
         new._annotations = copy.deepcopy(self._annotations)
         return new
 
@@ -99,7 +105,8 @@ class PolyCollection(Shape):
         return (
             type(self) is type(other)
             and numpy.array_equal(self.offset, other.offset)
-            and all(numpy.array_equal(ss, oo) for ss, oo in zip(self.vertices, other.vertices))
+            and numpy.array_equal(self._vertex_lists, other._vertex_lists)
+            and numpy.array_equal(self._vertex_offsets, other._vertex_offsets)
             and self.repetition == other.repetition
             and annotations_eq(self.annotations, other.annotations)
             )
@@ -110,8 +117,9 @@ class PolyCollection(Shape):
                 return repr(type(self)) < repr(type(other))
             return id(type(self)) < id(type(other))
 
-        other = cast(PolyCollection, other)
+        other = cast('PolyCollection', other)
-        for vv, oo in zip(self.vertices, other.vertices):
+
+        for vv, oo in zip(self.polygon_vertices, other.polygon_vertices, strict=False):
             if not numpy.array_equal(vv, oo):
                 min_len = min(vv.shape[0], oo.shape[0])
                 eq_mask = vv[:min_len] != oo[:min_len]
@@ -121,67 +129,48 @@ class PolyCollection(Shape):
                     return eq_lt_masked.flat[0]
                 return vv.shape[0] < oo.shape[0]
         if len(self.vertex_lists) != len(other.vertex_lists):
-            return len(self.vertex_lists) < len(other.vertex_lists):
+            return len(self.vertex_lists) < len(other.vertex_lists)
         if not numpy.array_equal(self.offset, other.offset):
             return tuple(self.offset) < tuple(other.offset)
         if self.repetition != other.repetition:
             return rep2key(self.repetition) < rep2key(other.repetition)
         return annotations_lt(self.annotations, other.annotations)
 
-    def pop_as_polygon(self, index: int) -> 'Polygon':
-        """
-        Remove one polygon from the list, and return it as a `Polygon` object.
-
-        Args:
-            index: which polygon to pop
-        """
-        verts = self.vertex_lists.pop(index)
-        return Polygon(
-            vertices=verts,
-            offset=self.offset,
-            repetition=self.repetition.copy(),
-            annotations=copy.deepcopy(self.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=vv,
+            vertices = vv,
-            offset=self.offset,
+            offset = self.offset,
-            repetition=self.repetition.copy(),
+            repetition = self.repetition.copy(),
-            annotations=copy.deepcopy(self.annotations),
+            annotations = copy.deepcopy(self.annotations),
-            ) for vv in self.vertex_lists]
+            ) for vv in self.polygon_vertices]
 
     def get_bounds_single(self) -> NDArray[numpy.float64]:         # TODO note shape get_bounds doesn't include repetition
-        mins = [numpy.min(vv, axis=0) for vv self.vertex_lists]
+        return numpy.vstack((self.offset + numpy.min(self._vertex_lists, axis=0),
-        maxs = [numpy.max(vv, axis=0) for vv self.vertex_lists]
+                             self.offset + numpy.max(self._vertex_lists, axis=0)))
-        return numpy.vstack((self.offset + numpy.min(self.vertex_lists, axis=0),
-                             self.offset + numpy.max(self.vertex_lists, axis=0)))
 
-    def rotate(self, theta: float) -> 'Polygon':
+    def rotate(self, theta: float) -> Self:
         if theta != 0:
-            for vv in self.vertex_lists:
+            rot = rotation_matrix_2d(theta)
-                vv[:] = numpy.dot(rotation_matrix_2d(theta), vv.T).T
+            self._vertex_lists = numpy.einsum('ij,kj->ki', rot, self._vertex_lists_)
         return self
 
-    def mirror(self, axis: int = 0) -> 'Polygon':
+    def mirror(self, axis: int = 0) -> Self:
-        for vv in self.vertex_lists:
+        self._vertex_lists[:, axis - 1] *= -1
-            vv[:, axis - 1] *= -1
         return self
 
-    def scale_by(self, c: float) -> 'Polygon':
+    def scale_by(self, c: float) -> Self:
-        for vv in self.vertex_lists:
+        self.vertex_lists *= c
-            vv *= c
         return self
 
     def normalized_form(self, norm_value: float) -> normalized_shape_tuple:
         # Note: this function is going to be pretty slow for many-vertexed polygons, relative to
         #   other shapes
-        meanv = numpy.concatenate(self.vertex_lists).mean(axis=0)
+        meanv = self._vertex_lists.mean(axis=0)
-        zeroed_vertices = [vv - meanv for vv in self.vertex_lists]
+        zeroed_vertices = self._vertex_lists - [meanv]
         offset = meanv + self.offset
 
         scale = zeroed_vertices.std()
@@ -189,22 +178,26 @@ class PolyCollection(Shape):
 
         _, _, vertex_axis = numpy.linalg.svd(zeroed_vertices)
         rotation = numpy.arctan2(vertex_axis[0][1], vertex_axis[0][0]) % (2 * pi)
-        rotated_vertices = numpy.vstack([numpy.dot(rotation_matrix_2d(-rotation), v)
+        rotated_vertices = numpy.einsum('ij,kj->ki', rotation_matrix_2d(-rotation), normed_vertices)
-                                        for v in normed_vertices])
 
-        # Reorder the vertices so that the one with lowest x, then y, comes first.
+        # TODO consider how to reorder vertices for polycollection
-        x_min = rotated_vertices[:, 0].argmin()
+        ## Reorder the vertices so that the one with lowest x, then y, comes first.
-        if not is_scalar(x_min):
+        #x_min = rotated_vertices[:, 0].argmin()
-            y_min = rotated_vertices[x_min, 1].argmin()
+        #if not is_scalar(x_min):
-            x_min = cast(Sequence, x_min)[y_min]
+        #    y_min = rotated_vertices[x_min, 1].argmin()
-        reordered_vertices = numpy.roll(rotated_vertices, -x_min, axis=0)
+        #    x_min = cast('Sequence', x_min)[y_min]
+        #reordered_vertices = numpy.roll(rotated_vertices, -x_min, axis=0)
 
         # TODO: normalize mirroring?
 
-        return ((type(self), reordered_vertices.data.tobytes()),
+        return ((type(self), rotated_vertices.data.tobytes() + self._vertex_offsets.tobytes()),
                 (offset, scale / norm_value, rotation, False),
-                lambda: Polygon(reordered_vertices * norm_value))
+                lambda: PolyCollection(
+                    vertex_lists=rotated_vertices * norm_value,
+                    vertex_offsets=self._vertex_offsets,
+                    ),
+                )
 
     def __repr__(self) -> str:
-        centroid = self.offset + numpy.concatenate(self.vertex_lists).mean(axis=0)
+        centroid = self.offset + self.vertex_lists.mean(axis=0)
-        return f'<PolyCollection centroid {centroid} p{len(self.vertex_lists)}>'
+        return f'<PolyCollection centroid {centroid} p{len(self.vertex_offsets)}>'

masque/shapes/polygon.py

@@ -1,5 +1,4 @@
-from typing import Any, cast
+from typing import Any, cast, TYPE_CHECKING
-from collections.abc import Sequence
 import copy
 import functools
 
@@ -13,6 +12,9 @@ from ..repetition import Repetition
 from ..utils import is_scalar, rotation_matrix_2d, annotations_lt, annotations_eq, rep2key
 from ..utils import remove_colinear_vertices, remove_duplicate_vertices, annotations_t
 
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
 
 @functools.total_ordering
 class Polygon(Shape):
@@ -90,7 +92,7 @@ class Polygon(Shape):
             offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0.0,
             repetition: Repetition | None = None,
-            annotations: annotations_t | None = None,
+            annotations: annotations_t = None,
             raw: bool = False,
             ) -> None:
         if raw:
@@ -99,12 +101,13 @@ class Polygon(Shape):
             self._vertices = vertices
             self._offset = offset
             self._repetition = repetition
-            self._annotations = annotations if annotations is not None else {}
+            self._annotations = annotations
         else:
             self.vertices = vertices
             self.offset = offset
             self.repetition = repetition
-            self.annotations = annotations if annotations is not None else {}
+            self.annotations = annotations
+        if rotation:
             self.rotate(rotation)
 
     def __deepcopy__(self, memo: dict | None = None) -> 'Polygon':
@@ -129,7 +132,7 @@ class Polygon(Shape):
             if repr(type(self)) != repr(type(other)):
                 return repr(type(self)) < repr(type(other))
             return id(type(self)) < id(type(other))
-        other = cast(Polygon, other)
+        other = cast('Polygon', other)
         if not numpy.array_equal(self.vertices, other.vertices):
             min_len = min(self.vertices.shape[0], other.vertices.shape[0])
             eq_mask = self.vertices[:min_len] != other.vertices[:min_len]
@@ -395,7 +398,7 @@ class Polygon(Shape):
         x_min = rotated_vertices[:, 0].argmin()
         if not is_scalar(x_min):
             y_min = rotated_vertices[x_min, 1].argmin()
-            x_min = cast(Sequence, x_min)[y_min]
+            x_min = cast('Sequence', x_min)[y_min]
         reordered_vertices = numpy.roll(rotated_vertices, -x_min, axis=0)
 
         # TODO: normalize mirroring?

masque/shapes/text.py

@@ -71,7 +71,7 @@ class Text(RotatableImpl, Shape):
             offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0.0,
             repetition: Repetition | None = None,
-            annotations: annotations_t | None = None,
+            annotations: annotations_t = None,
             raw: bool = False,
             ) -> None:
         if raw:
@@ -81,14 +81,14 @@ class Text(RotatableImpl, Shape):
             self._height = height
             self._rotation = rotation
             self._repetition = repetition
-            self._annotations = annotations if annotations is not None else {}
+            self._annotations = annotations
         else:
             self.offset = offset
             self.string = string
             self.height = height
             self.rotation = rotation
             self.repetition = repetition
-            self.annotations = annotations if annotations is not None else {}
+            self.annotations = annotations
         self.font_path = font_path
 
     def __deepcopy__(self, memo: dict | None = None) -> Self:
@@ -115,7 +115,7 @@ class Text(RotatableImpl, Shape):
             if repr(type(self)) != repr(type(other)):
                 return repr(type(self)) < repr(type(other))
             return id(type(self)) < id(type(other))
-        other = cast(Text, other)
+        other = cast('Text', other)
         if not self.height == other.height:
             return self.height < other.height
         if not self.string == other.string:

masque/traits/rotatable.py

@@ -1,14 +1,15 @@
-from typing import Self, cast, Any
+from typing import Self, cast, Any, TYPE_CHECKING
 from abc import ABCMeta, abstractmethod
 
 import numpy
 from numpy import pi
 from numpy.typing import ArrayLike
 
-from .positionable import Positionable
 from ..error import MasqueError
 from ..utils import rotation_matrix_2d
 
+if TYPE_CHECKING:
+    from .positionable import Positionable
 
 _empty_slots = ()     # Workaround to get mypy to ignore intentionally empty slots for superclass
 
@@ -113,9 +114,9 @@ class PivotableImpl(Pivotable, metaclass=ABCMeta):
 
     def rotate_around(self, pivot: ArrayLike, rotation: float) -> Self:
         pivot = numpy.asarray(pivot, dtype=float)
-        cast(Positionable, self).translate(-pivot)
+        cast('Positionable', self).translate(-pivot)
-        cast(Rotatable, self).rotate(rotation)
+        cast('Rotatable', self).rotate(rotation)
         self.offset = numpy.dot(rotation_matrix_2d(rotation), self.offset)      # type: ignore # mypy#3004
-        cast(Positionable, self).translate(+pivot)
+        cast('Positionable', self).translate(+pivot)
         return self
 

masque/utils/curves.py

@@ -5,7 +5,7 @@ from numpy import pi
 try:
     from numpy import trapezoid
 except ImportError:
-    from numpy import trapz as trapezoid
+    from numpy import trapz as trapezoid        # type:ignore
 
 
 def bezier(

masque/utils/types.py

@@ -5,7 +5,7 @@ from typing import Protocol
 
 
 layer_t = int | tuple[int, int] | str
-annotations_t = dict[str, list[int | float | str]]
+annotations_t = dict[str, list[int | float | str]] | None
 
 
 class SupportsBool(Protocol):

pyproject.toml

@@ -78,7 +78,6 @@ lint.ignore = [
     "ANN002",   # *args
     "ANN003",   # **kwargs
     "ANN401",   # Any
-    "ANN101",   # self: Self
     "SIM108",   # single-line if / else assignment
     "RET504",   # x=y+z; return x
     "PIE790",   # unnecessary pass