first pass at using klayout method. Many bugs likely remain

.flake8

@@ -0,0 +1,29 @@
+[flake8]
+ignore =
+    # E501 line too long
+    E501,
+    # W391 newlines at EOF
+    W391,
+    # E241 multiple spaces after comma
+    E241,
+    # E302 expected 2 newlines
+    E302,
+    # W503 line break before binary operator (to be deprecated)
+    W503,
+    # E265 block comment should start with '# '
+    E265,
+    # E123 closing bracket does not match indentation of opening bracket's line
+    E123,
+    # E124 closing bracket does not match visual indentation
+    E124,
+    # E221 multiple spaces before operator
+    E221,
+    # E201 whitespace after '['
+    E201,
+    # E741 ambiguous variable name 'I'
+    E741,
+
+
+per-file-ignores =
+    # F401 import without use
+    */__init__.py: F401,

examples/check.py

@@ -5,10 +5,7 @@ Example code for checking connectivity in a layout by using
 from pprint import pformat
 import logging
 
-from masque.file import gdsii, oasis
-
 import snarled
-import snarled.interfaces.masque
 
 
 logging.basicConfig()
@@ -21,20 +18,14 @@ connectivity = [
     ((2, 0), (2, 3), (3, 0)),   #M2 to M3 (via V23)
     ]
 
+labels_map = {
+    (1, 0): (1, 0),
+    (2, 0): (2, 0),
+    (3, 0): (3, 0),
+    }
 
-#cells, props = gdsii.readfile('connectivity.gds')
+filename = 'connectivity.oas'
-cells, props = oasis.readfile('connectivity.oas')
-topcell = cells['top']
 
-get_layer = snarled.interfaces.masque.prepare_cell(topcell)
+result = snarled.trace_layout(filename, connectivity, topcell='top', labels_map=labels_map)
-nets_info = snarled.trace_connectivity(get_layer, connectivity)
 
-print('\nFinal nets:')
+print('Result:\n', pformat(result))
-print([kk for kk in sorted(nets_info.nets.keys()) if isinstance(kk.name, str)])
-
-print('\nShorted net sets:')
-for short in nets_info.get_shorted_nets():
-    print('(' + ','.join([repr(nn) for nn in sorted(list(short))]) + ')')
-
-print('\nOpen nets:')
-print(pformat(dict(nets_info.get_open_nets())))

examples/connectivity.txt

@@ -0,0 +1,3 @@
+M1, V12, M2
+M1, V13, M3
+M2, V23, M3

examples/layermap.txt

@@ -0,0 +1,6 @@
+1/0:M1
+2/0:M2
+3/0:M3
+1/2:V12
+1/3:V13
+2/3:V23

examples/run.sh

@@ -0,0 +1,5 @@
+#!/usr/bin/env bash
+
+cd $(dirname -- "$0")       # cd to this script's parent directory
+
+snarled connectivity.oas connectivity.txt -l layermap.txt

pyproject.toml

@@ -0,0 +1,53 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "snarled"
+description = "CAD layout electrical connectivity checker"
+readme = "README.md"
+license = { file = "LICENSE.md" }
+authors = [
+    { name="Jan Petykiewicz", email="jan@mpxd.net" },
+    ]
+homepage = "https://mpxd.net/code/jan/snarled"
+repository = "https://mpxd.net/code/jan/snarled"
+keywords = [
+    "layout",
+    "design",
+    "CAD",
+    "EDA",
+    "electronics",
+    "photonics",
+    "IC",
+    "mask",
+    "pattern",
+    "drawing",
+    "lvs",
+    "connectivity",
+    "short",
+    "unintentional",
+    "label",
+    "schematic",
+    "verification",
+    "checking",
+    ]
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
+    "Intended Audience :: Information Technology",
+    "Intended Audience :: Manufacturing",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
+    "Topic :: Scientific/Engineering :: Electronic Design Automation (EDA)",
+    ]
+requires-python = ">=3.10"
+dynamic = ["version"]
+dependencies = [
+    "klayout~=0.28",
+    ]
+
+
+[tool.hatch.version]
+path = "snarled/__init__.py"

setup.py

@@ -1,63 +0,0 @@
-#!/usr/bin/env python3
-
-from setuptools import setup, find_packages
-
-
-with open('README.md', 'rt') as f:
-    long_description = f.read()
-
-with open('snarled/VERSION.py', 'rt') as f:
-    version = f.readlines()[2].strip()
-
-setup(name='snarled',
-      version=version,
-      description='CAD layout electrical connectivity checker',
-      long_description=long_description,
-      long_description_content_type='text/markdown',
-      author='Jan Petykiewicz',
-      author_email='jan@mpxd.net',
-      url='https://mpxd.net/code/jan/snarled',
-      packages=find_packages(),
-      package_data={
-          'snarled': ['py.typed',
-                    ]
-      },
-      install_requires=[
-          'numpy',
-          'pyclipper',
-      ],
-      extras_require={
-          'masque': ['masque'],
-          'oasis': ['fatamorgana>=0.7'],
-          'gdsii': ['klamath>=1.0'],
-      },
-      classifiers=[
-            'Programming Language :: Python :: 3',
-            'Development Status :: 4 - Beta',
-            'Intended Audience :: Developers',
-            'Intended Audience :: Information Technology',
-            'Intended Audience :: Manufacturing',
-            'Intended Audience :: Science/Research',
-            'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
-            'Topic :: Scientific/Engineering :: Electronic Design Automation (EDA)',
-      ],
-      keywords=[
-          'layout',
-          'design',
-          'CAD',
-          'EDA',
-          'electronics',
-          'photonics',
-          'IC',
-          'mask',
-          'pattern',
-          'drawing',
-          'lvs',
-          'connectivity',
-          'short',
-          'unintentional',
-          'label',
-          'schematic',
-      ],
-      )
-

snarled/VERSION.py

@@ -1,4 +0,0 @@
-""" VERSION defintion. THIS FILE IS MANUALLY PARSED BY setup.py and REQUIRES A SPECIFIC FORMAT """
-__version__ = '''
-0.6
-'''.strip()

snarled/__init__.py

@@ -7,17 +7,12 @@ Layout connectivity checker.
 `snarled` is a python package for checking electrical connectivity in multi-layer layouts.
 
 It is intended to be "poor-man's LVS" (layout-versus-schematic), for when poverty
-has deprived the man of both a schematic and a better connectivity tool.
+has deprived the man of a schematic and a better connectivity tool.
 
-The main functionality is in `trace_connectivity`.
+The main functionality is in `trace`.
-Useful classes, namely `NetsInfo` and `NetName`, are in `snarled.tracker`.
+`__main__.py` details the command-line interface.
-`snarled.interfaces` contains helper code for interfacing with other packages.
 """
-from .main import trace_connectivity, trace_connectivity_preloaded
+from .trace import TraceResult, trace_layout
-from .tracker import NetsInfo, NetName
-from  . import interfaces
-
 
 __author__ = 'Jan Petykiewicz'
-
+__version__ = '1.0'
-from .VERSION import __version__

snarled/__main__.py

@@ -0,0 +1,79 @@
+from typing import Any
+import argparse
+import logging
+from pprint import pformat
+
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+parser = argparse.ArgumentParser(
+    prog='snarled',
+    description='layout connectivity checker',
+    )
+
+parser.add_argument('file_path')
+parser.add_argument('connectivity_path')
+parser.add_argument('-m', '--layermap')
+parser.add_argument('-t', '--top')
+parser.add_argument('-p', '--labels-remap')
+
+parser.add_argument('-l', '--lfile-path')
+parser.add_argument('-r', '--lremap')
+parser.add_argument('-n', '--llayermap')
+parser.add_argument('-s', '--ltop')
+
+parser.add_argument('-o', '--output')
+parser.add_argument('-u', '--raw-label-names', action='store_true')
+
+
+args = parser.parse_args()
+
+filepath = args.file_path
+connectivity = utils.read_connectivity(args.connectivity_path)
+
+kwargs: dict[str, Any] = {}
+
+if args.layermap:
+    kwargs['layer_map'] = utils.read_layermap(args.layermap)
+
+if args.top:
+    kwargs['topcell'] = args.top
+
+if args.labels_remap:
+    kwargs['labels_remap'] = utils.read_remap(args.labels_remap)
+
+if args.lfile_path:
+    kwargs['lfile_path'] = args.lfile_path
+    kwargs['lfile_map'] = utils.read_remap(args.lremap)
+
+if args.llayermap:
+    kwargs['lfile_layermap'] = utils.read_layermap(args.llayermap)
+
+if args.ltop:
+    kwargs['lfile_topcell'] = args.ltop
+
+if args.output:
+    kwargs['output_path'] = args.output
+
+if not args.raw_label_names:
+    def parse_label(string: str) -> str:
+        try:
+            parts = string.split('_')
+            _part_id = int(parts[-1])       # must succeed to return here
+            return '_'.join(parts[:-1])
+        except Exception:
+            return string
+
+    kwargs['parse_label'] = parse_label
+
+result = trace_layout(
+        filepath=filepath,
+        connectivity=connectivity,
+        **kwargs,
+        )
+
+print('Nets: ', pformat(result.nets))
+print('Opens: ', pformat(result.opens))
+print('Shorts: ', pformat(result.shorts))

snarled/clipper.py

@@ -1,64 +0,0 @@
-"""
-Wrappers to simplify some pyclipper functions
-"""
-from typing import Sequence, Optional, List
-
-from numpy.typing import ArrayLike
-from pyclipper import (
-    Pyclipper, PT_CLIP, PT_SUBJECT, CT_UNION, CT_INTERSECTION, PFT_NONZERO, PFT_EVENODD,
-    PyPolyNode, CT_DIFFERENCE,
-    )
-
-from .types import contour_t
-
-
-def union_nonzero(shapes: Sequence[ArrayLike]) -> Optional[PyPolyNode]:
-    if not shapes:
-        return None
-    pc = Pyclipper()
-    pc.AddPaths(shapes, PT_CLIP, closed=True)
-    result = pc.Execute2(CT_UNION, PFT_NONZERO, PFT_NONZERO)
-    return result
-
-
-def union_evenodd(shapes: Sequence[ArrayLike]) -> List[contour_t]:
-    if not shapes:
-        return []
-    pc = Pyclipper()
-    pc.AddPaths(shapes, PT_CLIP, closed=True)
-    return pc.Execute(CT_UNION, PFT_EVENODD, PFT_EVENODD)
-
-
-def intersection_evenodd(
-        subject_shapes: Sequence[ArrayLike],
-        clip_shapes: Sequence[ArrayLike],
-        ) -> List[contour_t]:
-    if not subject_shapes or not clip_shapes:
-        return []
-    pc = Pyclipper()
-    pc.AddPaths(subject_shapes, PT_SUBJECT, closed=True)
-    pc.AddPaths(clip_shapes, PT_CLIP, closed=True)
-    return pc.Execute(CT_INTERSECTION, PFT_EVENODD, PFT_EVENODD)
-
-
-def difference_evenodd(
-        subject_shapes: Sequence[ArrayLike],
-        clip_shapes: Sequence[ArrayLike],
-        ) -> List[contour_t]:
-    if not subject_shapes:
-        return []
-    if not clip_shapes:
-        return subject_shapes
-    pc = Pyclipper()
-    pc.AddPaths(subject_shapes, PT_SUBJECT, closed=True)
-    pc.AddPaths(clip_shapes, PT_CLIP, closed=True)
-    return pc.Execute(CT_DIFFERENCE, PFT_EVENODD, PFT_EVENODD)
-
-
-def hier2oriented(polys: Sequence[PyPolyNode]) -> List[ArrayLike]:
-    contours = []
-    for poly in polys:
-        contours.append(poly.Contour)
-        contours += [hole.Contour for hole in poly.Childs]
-
-    return contours

snarled/interfaces/masque.py

@@ -1,127 +0,0 @@
-"""
-Functionality for extracting geometry and label info from `masque` patterns.
-"""
-from typing import Sequence, Dict, List, Any, Tuple, Optional, Mapping, Callable
-from collections import defaultdict
-
-import numpy
-from numpy.typing import NDArray
-from masque import Pattern
-from masque.file import oasis, gdsii
-from masque.shapes import Polygon
-
-from ..types import layer_t
-from ..utils import connectivity2layers
-
-
-def prepare_cell(
-        cell: Pattern,
-        label_mapping: Optional[Mapping[layer_t, layer_t]] = None,
-        ) -> Callable[[layer_t], Tuple[
-            List[NDArray[numpy.float64]],
-            List[Tuple[float, float, str]]
-            ]]:
-    """
-    Generate a function for extracting `polys` and `labels` from a `masque.Pattern`.
-    The returned function can be passed to `snarled.trace_connectivity`.
-
-    Args:
-        cell: A `masque` `Pattern` object. Usually your topcell.
-        label_mapping: A mapping of `{label_layer: metal_layer}`. This allows labels
-            to refer to nets on metal layers without the labels themselves being on
-            that layer.
-            Default `None` reads labels from the same layer as the geometry.
-
-    Returns:
-        `get_layer` function, to be passed to `snarled.trace_connectivity`.
-    """
-
-    def get_layer(
-            layer: layer_t,
-            ) -> Tuple[
-                List[NDArray[numpy.float64]],
-                List[Tuple[float, float, str]]
-                ]:
-
-        if label_mapping is None:
-            label_layers = {layer: layer}
-        else:
-            label_layers = {label_layer for label_layer, metal_layer in label_mapping.items()
-                            if metal_layer == layer}
-
-        subset = cell.deepcopy().subset(          # TODO add single-op subset-and-copy, to avoid copying unwanted stuff
-            shapes_func=lambda ss: ss.layer == layer,
-            labels_func=lambda ll: ll.layer in label_layers,
-            subpatterns_func=lambda ss: True,
-            recursive=True,
-            )
-
-        polygonized = subset.polygonize()       # Polygonize Path shapes
-        flat = polygonized.flatten()
-
-        # load polygons
-        polys = []
-        for ss in flat.shapes:
-            assert(isinstance(ss, Polygon))
-
-            if ss.repetition is None:
-                displacements = [(0, 0)]
-            else:
-                displacements = ss.repetition.displacements
-
-            for displacement in displacements:
-                polys.append(
-                    ss.vertices + ss.offset + displacement
-                    )
-
-        # load metal labels
-        labels = []
-        for ll in flat.labels:
-            if ll.repetition is None:
-                displacements = [(0, 0)]
-            else:
-                displacements = ll.repetition.displacements
-
-            for displacement in displacements:
-                offset = ll.offset + displacement
-                labels.append((*offset, ll.string))
-
-        return polys, labels
-    return get_layer
-
-
-def read_cell(
-        cell: Pattern,
-        connectivity: Sequence[Tuple[layer_t, Optional[layer_t], layer_t]],
-        label_mapping: Optional[Mapping[layer_t, layer_t]] = None,
-        ) -> Tuple[
-                defaultdict[layer_t, List[NDArray[numpy.float64]]],
-                defaultdict[layer_t, List[Tuple[float, float, str]]]]:
-    """
-    Extract `polys` and `labels` from a `masque.Pattern`.
-
-    This function extracts the data needed by `snarled.trace_connectivity`.
-
-    Args:
-        cell: A `masque` `Pattern` object. Usually your topcell.
-        connectivity: A sequence of 3-tuples specifying the layer connectivity.
-            Same as what is provided to `snarled.trace_connectivity`.
-        label_mapping: A mapping of `{label_layer: metal_layer}`. This allows labels
-            to refer to nets on metal layers without the labels themselves being on
-            that layer.
-
-    Returns:
-        `polys` and `labels` data structures, to be passed to `snarled.trace_connectivity`.
-    """
-
-    metal_layers, via_layers = connectivity2layers(connectivity)
-    poly_layers = metal_layers | via_layers
-
-    get_layer = prepare_cell(cell, label_mapping)
-
-    polys = defaultdict(list)
-    labels = defaultdict(list)
-    for layer in poly_layers:
-        polys[layer], labels[layer] = get_layer(layer)
-
-    return polys, labels

snarled/main.py

@@ -1,369 +0,0 @@
-"""
-Main connectivity-checking functionality for `snarled`
-"""
-from typing import Tuple, List, Dict, Set, Optional, Union, Sequence, Mapping, Callable
-from collections import defaultdict
-from pprint import pformat
-from concurrent.futures import ThreadPoolExecutor
-import logging
-
-import numpy
-from numpy.typing import NDArray, ArrayLike
-from pyclipper import scale_to_clipper, scale_from_clipper, PyPolyNode
-
-from .types import connectivity_t, layer_t, contour_t
-from .poly import poly_contains_points, intersects
-from .clipper import union_nonzero, union_evenodd, intersection_evenodd, difference_evenodd, hier2oriented
-from .tracker import NetsInfo, NetName
-from .utils import connectivity2layers
-
-
-logger = logging.getLogger(__name__)
-
-
-def trace_connectivity_preloaded(
-        polys: Mapping[layer_t, Sequence[ArrayLike]],
-        labels: Mapping[layer_t, Sequence[Tuple[float, float, str]]],
-        connectivity: Sequence[Tuple[layer_t, Optional[layer_t], layer_t]],
-        clipper_scale_factor: int = int(2 ** 24),
-        ) -> NetsInfo:
-    """
-    Analyze the electrical connectivity of the provided layout.
-
-    The resulting `NetsInfo` will contain only disjoint `nets`, and its `net_aliases` can be used to
-    understand which nets are shorted (and therefore known by more than one name).
-
-    Args:
-        polys: A full description of all conducting paths in the layout. Consists of lists of polygons
-            (Nx2 arrays of vertices), indexed by layer. The structure looks roughly like
-            `{layer0: [poly0, poly1, ..., [(x0, y0), (x1, y1), ...]], ...}`
-        labels: A list of "named points" which are used to assign names to the nets they touch.
-            A collection of lists of (x, y, name) tuples, indexed *by the layer they target*.
-            `{layer0: [(x0, y0, name0), (x1, y1, name1), ...], ...}`
-        connectivity: A sequence of 3-tuples specifying the electrical connectivity between layers.
-            Each 3-tuple looks like `(top_layer, via_layer, bottom_layer)` and indicates that
-            `top_layer` and `bottom_layer` are electrically connected at any location where
-            shapes are present on all three (top, via, and bottom) layers.
-            `via_layer` may be `None`, in which case any overlap between shapes on `top_layer`
-            and `bottom_layer` is automatically considered a short (with no third shape necessary).
-        clipper_scale_factor: `pyclipper` uses 64-bit integer math, while we accept either floats or ints.
-            The coordinates from `polys` are scaled by this factor to put them roughly in the middle of
-            the range `pyclipper` wants; you may need to adjust this if you are already using coordinates
-            with large integer values.
-
-    Returns:
-        `NetsInfo` object describing the various nets and their connectivities.
-    """
-    def get_layer(layer: layer_t) -> Tuple[Sequence[ArrayLike], Sequence[Tuple[float, float, str]]]:
-        return polys[layer], labels[layer]
-
-    return trace_connectivity(get_layer, connectivity, clipper_scale_factor)
-
-
-def trace_connectivity(
-        get_layer: Callable[[layer_t], Tuple[Sequence[ArrayLike], Sequence[Tuple[float, float, str]]]],
-        connectivity: Sequence[Tuple[layer_t, Optional[layer_t], layer_t]],
-        clipper_scale_factor: int = int(2 ** 24),
-        ) -> NetsInfo:
-    """
-    Analyze the electrical connectivity of a layout.
-
-    The resulting `NetsInfo` will contain only disjoint `nets`, and its `net_aliases` can be used to
-    understand which nets are shorted (and therefore known by more than one name).
-
-    This function attempts to reduce memory usage by lazy-loading layout data (layer-by-layer) and
-    pruning away layers for which all interactions have already been computed.
-    TODO: In the future, this will be extended to cover partial loading of spatial extents in
-          addition to layers.
-
-    Args:
-        get_layer: When called, `polys, labels = get_layer(layer)` should return the geometry and labels
-            on that layer. Returns
-
-            polys, A list of polygons (Nx2 arrays of vertices) on the layer. The structure looks like
-                `[poly0, poly1, ..., [(x0, y0), (x1, y1), ...]]`
-
-            labels, A list of "named points" which are used to assign names to the nets they touch.
-                A list of (x, y, name) tuples targetting this layer.
-                `[(x0, y0, name0), (x1, y1, name1), ...]`
-
-        connectivity: A sequence of 3-tuples specifying the electrical connectivity between layers.
-
-            Each 3-tuple looks like `(top_layer, via_layer, bottom_layer)` and indicates that
-            `top_layer` and `bottom_layer` are electrically connected at any location where
-            shapes are present on all three (top, via, and bottom) layers.
-
-            `via_layer` may be `None`, in which case any overlap between shapes on `top_layer`
-            and `bottom_layer` is automatically considered a short (with no third shape necessary).
-
-            NOTE that the order in which connectivity is specified (i.e. top-level ordering of the
-            tuples) directly sets the order in which the layers are loaded and merged, and thus
-            has a significant impact on memory usage by determining when layers can be pruned away.
-            Try to group entries by the layers they affect!
-
-        clipper_scale_factor: `pyclipper` uses 64-bit integer math, while we accept either floats or ints.
-            The coordinates from `polys` are scaled by this factor to put them roughly in the middle of
-            the range `pyclipper` wants; you may need to adjust this if you are already using coordinates
-            with large integer values.
-
-    Returns:
-        `NetsInfo` object describing the various nets and their connectivities.
-    """
-    loaded_layers = set()
-    nets_info = NetsInfo()
-
-    for ii, (top_layer, via_layer, bot_layer) in enumerate(connectivity):
-        logger.info(f'{ii}, {top_layer}, {via_layer}, {bot_layer}')
-        for metal_layer in (top_layer, bot_layer):
-            if metal_layer in loaded_layers:
-                continue
-            # Load and run initial union on each layer
-            raw_polys, labels = get_layer(metal_layer)
-            polys = union_input_polys(scale_to_clipper(raw_polys, clipper_scale_factor))
-
-            # Check each polygon for labels, and assign it to a net (possibly anonymous).
-            nets_on_layer, merge_groups = label_polys(polys, labels, clipper_scale_factor)
-            for name, net_polys in nets_on_layer.items():
-                nets_info.nets[name][metal_layer] += hier2oriented(net_polys)
-
-            # Merge any nets that were shorted by having their labels on the same polygon
-            for group in merge_groups:
-                net_names = set(nn.name for nn in group)
-                if len(net_names) > 1:
-                    logger.warning(f'Nets {net_names} are shorted on layer {metal_layer}')
-                first_net, *defunct_nets = group
-                for defunct_net in defunct_nets:
-                    nets_info.merge(first_net, defunct_net)
-
-            loaded_layers.add(metal_layer)
-
-        # Load and union vias
-        via_raw_polys, _labels = get_layer(via_layer)
-        via_union = union_input_polys(scale_to_clipper(via_raw_polys, clipper_scale_factor))
-        via_polylists = scale_from_clipper(hier2oriented(via_union), clipper_scale_factor)
-        via_polys = [numpy.array(vv) for vv in via_polylists]
-
-        # Figure out which nets are shorted by vias, then merge them
-        merge_pairs = find_merge_pairs(nets_info.nets, top_layer, bot_layer, via_polys, clipper_scale_factor)
-        for net_a, net_b in merge_pairs:
-            nets_info.merge(net_a, net_b)
-
-
-        remaining_layers = set()
-        for layer_a, _, layer_b in connectivity[ii + 1:]:
-            remaining_layers.add(layer_a)
-            remaining_layers.add(layer_b)
-
-        finished_layers = loaded_layers - remaining_layers
-        for layer in finished_layers:
-            nets_info.prune(layer)
-            loaded_layers.remove(layer)
-
-    return nets_info
-
-
-def union_input_polys(polys: Sequence[ArrayLike]) -> List[PyPolyNode]:
-    """
-    Perform a union operation on the provided sequence of polygons, and return
-    a list of `PyPolyNode`s corresponding to all of the outer (i.e. non-hole)
-    contours.
-
-    Note that while islands are "outer" contours and returned in the list, they
-    also are still available through the `.Childs` property of the "hole" they
-    appear in. Meanwhile, "hole" contours are only accessible through the `.Childs`
-    property of their parent "outer" contour, and are not returned in the list.
-
-    Args:
-        polys: A sequence of polygons, `[[(x0, y0), (x1, y1), ...], poly1, poly2, ...]`
-            Polygons may be implicitly closed.
-
-    Returns:
-        List of PyPolyNodes, representing all "outer" contours (including islands) in
-        the union of `polys`.
-    """
-    for poly in polys:
-        if (numpy.abs(poly) % 1).any():
-            logger.warning('Warning: union_polys got non-integer coordinates; all values will be truncated.')
-            break
-
-    #TODO: check if we need to reverse the order of points in some polygons
-    #       via sum((x2-x1)(y2+y1)) (-ve means ccw)
-
-    poly_tree = union_nonzero(polys)
-    if poly_tree is None:
-        return []
-
-    # Partially flatten the tree, reclassifying all the "outer" (non-hole) nodes as new root nodes
-    unvisited_nodes = [poly_tree]
-    outer_nodes = []
-    while unvisited_nodes:
-        node = unvisited_nodes.pop()    # node will be the tree parent node (a container), or a hole
-        for poly in node.Childs:
-            outer_nodes.append(poly)
-            for hole in poly.Childs:            # type: ignore
-                unvisited_nodes.append(hole)
-
-    return outer_nodes
-
-def label_polys(
-        polys: Sequence[PyPolyNode],
-        labels: Sequence[Tuple[float, float, str]],
-        clipper_scale_factor: int,
-        ) -> Tuple[
-            defaultdict[NetName, List[PyPolyNode]],
-            List[List[NetName]]
-            ]:
-    merge_groups = []
-    point_xys = []
-    point_names = []
-    nets = defaultdict(list)
-
-    for x, y, point_name in labels:
-        point_xys.append((x, y))
-        point_names.append(point_name)
-
-    for poly in polys:
-        found_nets = label_poly(poly, point_xys, point_names, clipper_scale_factor)
-
-        if found_nets:
-            name = NetName(found_nets[0])
-        else:
-            name = NetName()     # Anonymous net
-
-        nets[name].append(poly)
-
-        if len(found_nets) > 1:
-            # Found a short
-            poly = pformat(scale_from_clipper(poly.Contour, clipper_scale_factor))
-            merge_groups.append([name] + [NetName(nn) for nn in found_nets[1:]])
-    return nets, merge_groups
-
-
-def label_poly(
-        poly: PyPolyNode,
-        point_xys: ArrayLike,
-        point_names: Sequence[str],
-        clipper_scale_factor: int,
-        ) -> List[str]:
-    """
-    Given a `PyPolyNode` (a polygon, possibly with holes) and a sequence of named points,
-    return the list of point names contained inside the polygon.
-
-    Args:
-        poly: A polygon, possibly with holes. "Islands" inside the holes (and deeper-nested
-            structures) are not considered (i.e. only one non-hole contour is considered).
-        point_xys: A sequence of point coordinates (Nx2, `[(x0, y0), (x1, y1), ...]`).
-        point_names: A sequence of point names (same length N as point_xys)
-        clipper_scale_factor: The PyPolyNode structure is from `pyclipper` and likely has
-            a scale factor applied in order to use integer arithmetic. Due to precision
-            limitations in `poly_contains_points`, it's prefereable to undo this scaling
-            rather than asking for similarly-scaled `point_xys` coordinates.
-            NOTE: This could be fixed by using `numpy.longdouble` in
-            `poly_contains_points`, but the exact length of long-doubles is platform-
-            dependent and so probably best avoided.
-
-    Result:
-        All the `point_names` which correspond to points inside the polygon (but not in
-        its holes).
-    """
-    if not point_names:
-        return []
-
-    poly_contour = scale_from_clipper(poly.Contour, clipper_scale_factor)
-    inside = poly_contains_points(poly_contour, point_xys)
-    for hole in poly.Childs:
-        hole_contour = scale_from_clipper(hole.Contour, clipper_scale_factor)
-        inside &= ~poly_contains_points(hole_contour, point_xys)
-
-    inside_nets = sorted([net_name for net_name, ii in zip(point_names, inside) if ii])
-
-    if inside.any():
-        return inside_nets
-    else:
-        return []
-
-
-def find_merge_pairs(
-        nets: Mapping[NetName, Mapping[layer_t, Sequence[contour_t]]],
-        top_layer: layer_t,
-        bot_layer: layer_t,
-        via_polys: Optional[Sequence[contour_t]],
-        clipper_scale_factor: int,
-        ) -> Set[Tuple[NetName, NetName]]:
-    """
-    Given a collection of (possibly anonymous) nets, figure out which pairs of
-    nets are shorted through a via (and thus should be merged).
-
-    Args:
-        nets: A collection of all nets (seqences of polygons in mappings indexed by `NetName`
-            and layer). See `NetsInfo.nets`.
-        top_layer: Layer name of first layer
-        bot_layer: Layer name of second layer
-        via_polys: Sequence of via contours. `None` denotes to vias necessary (overlap is sufficent).
-
-    Returns:
-        A set containing pairs of `NetName`s for each pair of nets which are shorted.
-    """
-    merge_pairs = set()
-    if via_polys is not None and not via_polys:
-        logger.warning(f'No vias between layers {top_layer}, {bot_layer}')
-        return merge_pairs
-
-    tested_pairs = set()
-    with ThreadPoolExecutor() as executor:
-        for top_name in nets.keys():
-            top_polys = nets[top_name][top_layer]
-            if not top_polys:
-                continue
-
-            for bot_name in nets.keys():
-                if bot_name == top_name:
-                    continue
-
-                name_pair: Tuple[NetName, NetName] = tuple(sorted((top_name, bot_name)))  #type: ignore
-                if name_pair in tested_pairs:
-                    continue
-                tested_pairs.add(name_pair)
-
-                bot_polys = nets[bot_name][bot_layer]
-                if not bot_polys:
-                    continue
-
-                executor.submit(check_overlap, top_polys, via_polys, bot_polys, clipper_scale_factor,
-                    lambda np=name_pair: merge_pairs.add(np))
-
-    return merge_pairs
-
-
-def check_overlap(
-        top_polys: Sequence[contour_t],
-        via_polys: Optional[Sequence[NDArray[numpy.float64]]],
-        bot_polys: Sequence[contour_t],
-        clipper_scale_factor: int,
-        action: Callable[[], None],
-        ) -> None:
-    """
-    Check for interaction between top and bottom polys, mediated by via polys if present.
-    """
-    if via_polys is not None:
-        top_bot = intersection_evenodd(top_polys, bot_polys)
-        descaled = scale_from_clipper(top_bot, clipper_scale_factor)
-        overlap = check_any_intersection(descaled, via_polys)
-#        overlap = intersection_evenodd(top_bot, via_polys)
-#        via_polys = difference_evenodd(via_polys, overlap)      # reduce set of via polys for future nets
-    else:
-#        overlap = intersection_evenodd(top_polys, bot_polys)  # TODO verify there aren't any suspicious corner cases for this
-        overlap = check_any_intersection(
-            scale_from_clipper(top_polys, clipper_scale_factor),
-            scale_from_clipper(bot_polys, clipper_scale_factor))
-
-    if overlap:
-        action()
-
-
-def check_any_intersection(polys_a, polys_b) -> bool:
-    for poly_a in polys_a:
-        for poly_b in polys_b:
-            if intersects(poly_a, poly_b):
-                return True
-    return False

snarled/poly.py

@@ -1,157 +0,0 @@
-"""
-Utilities for working with polygons
-"""
-import numpy
-from numpy.typing import NDArray, ArrayLike
-
-
-def poly_contains_points(
-        vertices: ArrayLike,
-        points: ArrayLike,
-        include_boundary: bool = True,
-        ) -> NDArray[numpy.int_]:
-    """
-    Tests whether the provided points are inside the implicitly closed polygon
-    described by the provided list of vertices.
-
-    Args:
-        vertices: Nx2 Arraylike of form [[x0, y0], [x1, y1], ...], describing an implicitly-
-            closed polygon. Note that this should include any offsets.
-        points: Nx2 ArrayLike of form [[x0, y0], [x1, y1], ...] containing the points to test.
-        include_boundary: True if points on the boundary should be count as inside the shape.
-            Default True.
-
-    Returns:
-        ndarray of booleans, [point0_is_in_shape, point1_is_in_shape, ...]
-    """
-    points = numpy.array(points, copy=False)
-    vertices = numpy.array(vertices, copy=False)
-
-    if points.size == 0:
-        return numpy.zeros(0)
-
-    min_bounds = numpy.min(vertices, axis=0)[None, :]
-    max_bounds = numpy.max(vertices, axis=0)[None, :]
-
-    trivially_outside = ((points < min_bounds).any(axis=1)
-                       | (points > max_bounds).any(axis=1))
-
-    nontrivial = ~trivially_outside
-    if trivially_outside.all():
-        inside = numpy.zeros_like(trivially_outside, dtype=bool)
-        return inside
-
-    ntpts = points[None, nontrivial, :]     # nontrivial points, along axis 1 of ndarray
-    verts = vertices[:, None, :]            # vertices, along axis 0
-    xydiff = ntpts - verts      # Expands into (n_vertices, n_ntpts, 2)
-
-    y0_le = xydiff[:, :, 1] >= 0                   # y_point >= y_vertex (axes 0, 1 for all points & vertices)
-    y1_le = numpy.roll(y0_le, -1, axis=0)          # same thing for next vertex
-
-    upward = y0_le & ~y1_le         # edge passes point y coord going upwards
-    downward = ~y0_le & y1_le       # edge passes point y coord going downwards
-
-    dv = numpy.roll(verts, -1, axis=0) - verts
-    is_left = (dv[..., 0] * xydiff[..., 1]        # >0 if left of dv, <0 if right, 0 if on the line
-             - dv[..., 1] * xydiff[..., 0])
-
-    winding_number = ((upward & (is_left > 0)).sum(axis=0)
-                  - (downward & (is_left < 0)).sum(axis=0))
-
-    nontrivial_inside = winding_number != 0        # filter nontrivial points based on winding number
-    if include_boundary:
-        nontrivial_inside[(is_left == 0).any(axis=0)] = True        # check if point lies on any edge
-
-    inside = nontrivial.copy()
-    inside[nontrivial] = nontrivial_inside
-    return inside
-
-
-def intersects(poly_a: ArrayLike, poly_b: ArrayLike) -> bool:
-    """
-    Check if two polygons overlap and/or touch.
-
-    Args:
-        poly_a: List of vertices, implicitly closed: `[[x0, y0], [x1, y1], ...]`
-        poly_b: List of vertices, implicitly closed: `[[x0, y0], [x1, y1], ...]`
-
-    Returns:
-        `True` if the polygons overlap and/or touch.
-    """
-    poly_a = numpy.array(poly_a, copy=False)
-    poly_b = numpy.array(poly_b, copy=False)
-
-    # Check bounding boxes
-    min_a = poly_a.min(axis=0)
-    min_b = poly_b.min(axis=0)
-    max_a = poly_a.max(axis=0)
-    max_b = poly_b.max(axis=0)
-
-    if (min_a > max_b).any() or (min_b > max_a).any():
-        return False
-
-    #TODO: Check against sorted coords?
-
-    #Check if edges intersect
-    if poly_edges_intersect(poly_a, poly_b):
-        return True
-
-    # Check if either polygon contains the other
-    if poly_contains_points(poly_b, poly_a).any():
-        return True
-
-    if poly_contains_points(poly_a, poly_b).any():
-        return True
-
-    return False
-
-
-def poly_edges_intersect(
-        poly_a: NDArray[numpy.float64],
-        poly_b: NDArray[numpy.float64],
-        ) -> NDArray[numpy.int_]:
-    """
-    Check if the edges of two polygons intersect.
-
-    Args:
-        poly_a: NDArray of vertices, implicitly closed: `[[x0, y0], [x1, y1], ...]`
-        poly_b: NDArray of vertices, implicitly closed: `[[x0, y0], [x1, y1], ...]`
-
-    Returns:
-        `True` if the polygons' edges intersect.
-    """
-    a_next = numpy.roll(poly_a, -1, axis=0)
-    b_next = numpy.roll(poly_b, -1, axis=0)
-
-    # Lists of initial/final coordinates for polygon segments
-    xi1 = poly_a[:, 0, None]
-    yi1 = poly_a[:, 1, None]
-    xf1 = a_next[:, 0, None]
-    yf1 = a_next[:, 1, None]
-
-    xi2 = poly_b[None, :, 0]
-    yi2 = poly_b[None, :, 1]
-    xf2 = b_next[None, :, 0]
-    yf2 = b_next[None, :, 1]
-
-    # Perform calculation
-    dxi = xi1 - xi2
-    dyi = yi1 - yi2
-    dx1 = xf1 - xi1
-    dx2 = xf2 - xi2
-    dy1 = yf1 - yi1
-    dy2 = yf2 - yi2
-
-    numerator_a = dx2 * dyi - dy2 * dxi
-    numerator_b = dx1 * dyi - dy1 * dxi
-    denominator = dy2 * dx1 - dx2 * dy1
-
-    # Avoid warnings since we may multiply eg. NaN*False
-    with numpy.errstate(invalid='ignore', divide='ignore'):
-        u_a = numerator_a / denominator
-        u_b = numerator_b / denominator
-
-        # Find the adjacency matrix
-        adjacency = numpy.logical_and.reduce((u_a >= 0, u_a <= 1, u_b >= 0, u_b <= 1))
-
-    return adjacency.any()

snarled/trace.py

@@ -0,0 +1,204 @@
+from typing import Sequence, Callable
+import logging
+from collections import Counter
+from dataclasses import dataclass
+from itertools import chain
+
+from klayout import db
+from .types import lnum_t, layer_t
+
+
+logger = logging.getLogger(__name__)
+
+
+def get_topcell(
+        layout: db.Layout,
+        name: str | None = None,
+        ) -> db.Cell:
+    if name is None:
+        return layout.top_cell()
+    else:
+        ind = layout.cell_by_name(name)
+        return layout.cell(ind)
+
+
+def write_net_layout(
+        l2n: db.LayoutToNetlist,
+        filepath: str,
+        layers: Sequence[lnum_t],
+        ) -> None:
+    layout = db.Layout()
+    top = layout.create_cell('top')
+    lmap = {layout.layer(*layer) for layer in layers}
+    l2n.build_all_nets(l2n.cell_mapping_into(ly, top), ly, lmap, 'net_', 'prop_', l2n.BNH_Flatten, 'circuit_')
+    layout.write(filepath)
+
+
+def merge_labels_from(
+        filepath: str,
+        into_layout: db.Layout,
+        lnum_map: dict[lnum_t, lnum_t],
+        topcell: str | None = None,
+        ) -> None:
+    layout = db.Layout()
+    lm = layout.read(filepath)
+
+    topcell_obj = get_topcell(layout, topcell)
+
+    for labels_layer, conductor_layer in lnum_map:
+        layer_ind_src = layout.layer(*labels_layer)
+        layer_ind_dst = into_layout.layer(*conductor_layer)
+
+        shapes_dst = topcell_obj.shapes(layer_ind_dst)
+        shapes_src = topcell_obj.shapes(layer_ind_src)
+        for shape in shapes_dst.each():
+            new_shape = shapes_dst.insert(shape)
+            shapes_dst.replace_prop_id(new_shape, 0)        # clear shape properties
+
+
+@dataclass
+class TraceResult:
+    shorts: list[str]
+    opens: list[str]
+    nets: list[set[str]]
+
+
+def trace_layout(
+        filepath: str,
+        connectivity: list[layer_t, layer_t | None, layer_t],
+        layer_map: dict[str, lnum_t] | None = None,
+        topcell: str | None = None,
+        *,
+        labels_map: dict[layer_t, layer_t] = {},
+        lfile_path: str | None = None,
+        lfile_map: dict[layer_t, layer_t] | None = None,
+        lfile_layer_map: dict[str, lnum_t] | None = None,
+        lfile_topcell: str | None = None,
+        output_path: str | None = None,
+        parse_label: Callable[[str], str] | None = None,
+        ) -> TraceResult:
+    if layer_map is None:
+        layer_map = {}
+
+    if parse_label is None:
+        def parse_label(label: str) -> str:
+            return label
+
+    layout = db.Layout()
+    lm = layout.read(filepath)
+
+    topcell_obj = get_topcell(layout, topcell)
+
+    # Merge labels from a separate layout if asked
+    if lfile_path:
+        if not lfile_map:
+            raise Exception('Asked to load labels from a separate file, but no '
+                            'label layers were specified in lfile_map')
+
+        if lfile_layer_map is None:
+            lfile_layer_map = layer_map
+
+        lnum_map = {}
+        for ltext, lshape in lfile_map.items():
+            if isinstance(ltext, str):
+                ltext = lfile_layer_map[ltext]
+            if isinstance(lshape, str):
+                lshape = layer_map[lshape]
+            lnum_map[ltext] = lshape
+
+        merge_labels_from(lfile_path, layout, lnum_map, lfile_topcell)
+
+    #
+    # Build a netlist from the layout
+    #
+    l2n = db.LayoutToNetlist(db.RecursiveShapeIterator(layout, topcell_obj, []))
+    #l2n.include_floating_subcircuits = True
+
+    # Create l2n polygon layers
+    layer2polys = {}
+    for layer in set(chain(*connectivity)):
+        if isinstance(layer, str):
+            layer = layer_map[layer]
+        klayer = layout.layer(*layer)
+        layer2polys[layer] = l2n.make_polygon_layer(klayer)
+
+    # Create l2n text layers
+    layer2texts = {}
+    for layer in labels_map.keys():
+        if isinstance(layer, str):
+            layer = layer_map[layer]
+        klayer = layout.layer(*layer)
+        texts = l2n.make_text_layer(klayer)
+        texts.flatten()
+        layer2texts[layer] = texts
+
+    # Connect each layer to itself
+    for name, polys in layer2polys.items():
+        logger.info(f'Adding layer {name}')
+        l2n.connect(polys)
+
+    # Connect layers, optionally with vias
+    for top, via, bot in connectivity:
+        if isinstance(top, str):
+            top = layer_map[top]
+        if isinstance(via, str):
+            via = layer_map[via]
+        if isinstance(top, str):
+            bot = layer_map[bot]
+
+        if via is None:
+            l2n.connect(layer2polys[top], layer2polys[bot])
+        else:
+            l2n.connect(layer2polys[top], layer2polys[via])
+            l2n.connect(layer2polys[bot], layer2polys[via])
+
+    # Label nets
+    for label_layer, metal_layer in labels_map.items():
+        if isinstance(label_layer, str):
+            label_layer = layer_map[label_layer]
+        if isinstance(metal_layer, str):
+            metal_layer = layer_map[metal_layer]
+
+        l2n.connect(layer2polys[metal_layer], layer2texts[label_layer])
+
+    # Get netlist
+    nle = l2n.extract_netlist()
+    nl = l2n.netlist()
+    nl.make_top_level_pins()
+
+    if output_path:
+        write_net_layout(l2n, output_path, layer2polys.keys())
+
+    #
+    # Analyze traced nets
+    #
+    top_circuits = [cc for cc, _ in zip(nl.each_circuit_top_down(), range(nl.top_circuit_count()))]
+
+    # Nets with more than one label get their labels joined with a comma
+    nets = [
+        {parse_label(ll) for ll in nn.name.split(',')}
+        for cc in top_circuits
+        for nn in cc.each_net()
+        if nn.name
+        ]
+    nets2 = [
+        nn.name
+        for cc in top_circuits
+        for nn in cc.each_net()
+        ]
+    print(nets2)
+
+    # Shorts contain more than one label
+    shorts = [net for net in nets if len(net) > 1]
+
+    # Check number of times each label appears
+    net_occurences = Counter(chain.from_iterable(nets))
+
+    # If the same label appears on more than one net, warn about an open
+    opens = [
+        (nn, count)
+        for nn, count in net_occurences.items()
+        if count > 1
+        ]
+
+    return TraceResult(shorts=shorts, opens=opens, nets=nets)

snarled/tracker.py

@@ -1,165 +0,0 @@
-from typing import List, Set, ClassVar, Optional, Dict
-from collections import defaultdict
-from dataclasses import dataclass
-
-from .types import layer_t, contour_t
-
-
-class NetName:
-    """
-    Basically just a uniquely-sortable `Optional[str]`.
-
-    A `name` of `None` indicates that the net is anonymous.
-    The `subname` is used to track multiple same-named nets, to allow testing for opens.
-    """
-    name: Optional[str]
-    subname: int
-
-    count: ClassVar[defaultdict[Optional[str], int]] = defaultdict(int)
-    """ Counter for how many classes have been instantiated with each name """
-
-    def __init__(self, name: Optional[str] = None) -> None:
-        self.name = name
-        self.subname = self.count[name]
-        NetName.count[name] += 1
-
-    def __lt__(self, other: 'NetName') -> bool:
-        if self.name == other.name:
-            return self.subname < other.subname
-        elif self.name is None:
-            return False
-        elif other.name is None:
-            return True
-        else:
-            return self.name < other.name
-
-    def __repr__(self) -> str:
-        if self.name is not None:
-            name = self.name
-        else:
-            name = '(None)'
-
-        if NetName.count[self.name] == 1:
-            return name
-        else:
-            return f'{name}__{self.subname}'
-
-
-class NetsInfo:
-    """
-    Container for describing all nets and keeping track of the "canonical" name for each
-    net. Nets which are known to be shorted together should be `merge`d together,
-    combining their geometry under the "canonical" name and adding the other name as an alias.
-    """
-    nets: defaultdict[NetName, defaultdict[layer_t, List]]
-    """
-    Contains all polygons for all nets, in the format
-    `{net_name: {layer: [poly0, poly1, ...]}}`
-
-    Polygons are usually stored in pyclipper-friendly coordinates, but may be either `PyPolyNode`s
-     or simple lists of coordinates (oriented boundaries).
-    """
-
-    net_aliases: Dict[NetName, NetName]
-    """
-    A mapping from alias to underlying name.
-    Note that the underlying name may itself be an alias.
-    `resolve_name` can be used to simplify lookup
-    """
-
-    def __init__(self) -> None:
-        self.nets = defaultdict(lambda: defaultdict(list))
-        self.net_aliases = {}
-
-    def resolve_name(self, net_name: NetName) -> NetName:
-        """
-        Find the canonical name (as used in `self.nets`) for any NetName.
-
-        Args:
-            net_name: The name of the net to look up. May be an alias.
-
-        Returns:
-            The canonical name for the net.
-        """
-        while net_name in self.net_aliases:
-            net_name = self.net_aliases[net_name]
-        return net_name
-
-    def merge(self, net_a: NetName, net_b: NetName) -> None:
-        """
-        Combine two nets into one.
-        Usually used when it is discovered that two nets are shorted.
-
-        The name that is preserved is based on the sort order of `NetName`s,
-        which favors non-anonymous, lexicograpically small names.
-
-        Args:
-            net_a: A net to merge
-            net_b: The other net to merge
-        """
-        net_a = self.resolve_name(net_a)
-        net_b = self.resolve_name(net_b)
-        if net_a is net_b:
-            return
-
-        # Always keep named nets if the other is anonymous
-        keep_net, old_net = sorted((net_a, net_b))
-
-        #logger.info(f'merging {old_net} into {keep_net}')
-        self.net_aliases[old_net] = keep_net
-        if old_net in self.nets:
-            for layer in self.nets[old_net]:
-                self.nets[keep_net][layer] += self.nets[old_net][layer]
-            del self.nets[old_net]
-
-    def prune(self, layer: layer_t) -> None:
-        """
-        Delete all geometry for the given layer.
-
-        Args:
-            layer: The layer to "forget"
-        """
-        for net in self.nets.values():
-            if layer in net:
-                del net[layer]
-
-    def get_shorted_nets(self) -> List[Set[NetName]]:
-        """
-        List groups of non-anonymous nets which were merged.
-
-        Returns:
-            A list of sets of shorted nets.
-        """
-        shorts = defaultdict(list)
-        for kk in self.net_aliases:
-            if kk.name is None:
-                continue
-
-            base_name = self.resolve_name(kk)
-            assert(base_name.name is not None)
-            shorts[base_name].append(kk)
-
-        shorted_sets = [set([kk] + others)
-                        for kk, others in shorts.items()]
-        return shorted_sets
-
-    def get_open_nets(self) -> defaultdict[str, List[NetName]]:
-        """
-        List groups of same-named nets which were *not* merged.
-
-        Returns:
-            A list of sets of same-named, non-shorted nets.
-        """
-        opens = defaultdict(list)
-        seen_names = {}
-        for kk in self.nets:
-            if kk.name is None:
-                continue
-
-            if kk.name in seen_names:
-                if kk.name not in opens:
-                    opens[kk.name].append(seen_names[kk.name])
-                opens[kk.name].append(kk)
-            else:
-                seen_names[kk.name] = kk
-        return opens

snarled/types.py

@@ -1,5 +1,3 @@
-from typing import Union, Tuple, List, Sequence, Optional, Hashable
 
-layer_t = Hashable
+lnum_t = tuple[int, int]
-contour_t = List[Tuple[int, int]]
+layer_t = lnum_t | str
-connectivity_t = Sequence[Tuple[layer_t, Optional[layer_t], layer_t]]

snarled/utils.py

@@ -1,28 +1,173 @@
-"""
+import logging
-Some utility code that gets reused
+from .types import layer_t
-"""
-from typing import Set, Tuple
-
-from .types import connectivity_t, layer_t
 
 
-def connectivity2layers(
+logger = logging.getLogger(__name__)
-        connectivity: connectivity_t,
+
-        ) -> Tuple[Set[layer_t], Set[layer_t]]:
+
+def read_layermap(path: str) -> dict[str, tuple[int, int]]:
     """
-    Extract the set of all metal layers and the set of all via layers
+    Read a klayout-compatible layermap file.
-    from the connectivity description.
+
+    Only the simplest format is supported:
+        layer/dtype:layer_name
+
+    Empty lines are ignored.
+
+    Args:
+        path: filepath for the input file
+
+    Returns:
+        Dict of {name: (layer, dtype)}
     """
-    metal_layers = set()
+    with open(path, 'rt') as ff:
-    via_layers = set()
+        lines = ff.readlines()
-    for top, via, bot in connectivity:
-        metal_layers.add(top)
-        metal_layers.add(bot)
-        if via is not None:
-            via_layers.add(via)
 
-    both = metal_layers.intersection(via_layers)
+    layer_map = {}
-    if both:
+    for nn, line in enumerate(lines):
-        raise Exception(f'The following layers are both vias and metals!? {both}')
+        line = line.strip()
+        if not line:
+            continue
 
-    return metal_layers, via_layers
+        for cc in '*-()':
+            if cc in line:
+                raise Exception(f'Failed to read layermap on line {nn} due to special character "{cc}"')
+
+        for cc in ':/':
+            if cc not in line:
+                raise Exception(f'Failed to read layermap on line {nn}; missing "{cc}"')
+
+        try:
+            layer_part, name = line.split(':')
+            layer_nums = str2lnum(layer_part)
+        except Exception as err:
+            logger.error(f'Layer map read failed on line {nn}')
+            raise err
+
+        layer_map[name.strip()] = (layer, dtype)
+
+    return layer_map
+
+
+def read_connectivity(path: str) -> list[tuple[layer_t, layer_t | None, layer_t]]:
+    """
+    Read a connectivity spec file, which takes the form
+
+        conductor0, via01, conductor1
+        conductor1, via12, conductor2
+        conductor0, via02, conductor2
+        ...
+        conductorX, conductorY
+
+    where each comma-separated entry is a layer name or numerical layer/dtype
+    deisgnation (e.g. 123/45). Empty lines are ignored. Lines with only 2 entries
+    are directly connected without needing a separate via layer.
+
+    Args:
+        path: filepath for the input file
+
+    Returns:
+        List of layer spec tuples (A, viaAB, B); the middle entry will be None
+        if no via is given.
+    """
+    with open(path, 'rt') as ff:
+        lines = ff.readlines()
+
+    connections = []
+    for nn, line in enumerate(lines):
+        line = line.strip()
+        if not line:
+            continue
+
+        parts = line.split(',')
+
+        if len(parts) not in (2, 3):
+            raise Exception(f'Too many commas in connectivity spec on line {nn}')
+
+        layers = []
+        for part in enumerate(parts):
+            if '/' in part:
+                try:
+                    layer = str2lnum(layer_part)
+                except Exception as err:
+                    logger.error(f'Connectivity spec read failed on line {nn}')
+                    raise err
+            else:
+                layer = part.strip()
+                if not layer:
+                   raise Exception(f'Empty layer in connectivity spec on line {nn}')
+            layers.append(layer)
+
+        if len(layers) == 2:
+            connections.append((layers[0], None, layers[1]))
+        else:
+            connections.append(tuple(layers))
+
+    return connections
+
+
+def read_remap(path: str) -> dict[layer_t, layer_t]:
+    """
+    Read a layer remap spec file, which takes the form
+
+        old_layer1 : new_layer1
+        old_layer2 : new_layer2
+        ...
+
+    where each layer entry is a layer name or numerical layer/dtype
+    designation (e.g. 123/45).
+    Empty lines are ignored.
+
+    Args:
+        path: filepath for the input file
+
+    Returns:
+        Dict mapping from left (old) layers to right (new) layers
+    """
+    with open(path, 'rt') as ff:
+        lines = ff.readlines()
+
+    remap = {}
+    for nn, line in enumerate(lines):
+        line = line.strip()
+        if not line:
+            continue
+
+        parts = line.split(':')
+
+        if len(parts) != 2:
+            raise Exception(f'Too many commas in layer remap spec on line {nn}')
+
+        layers = []
+        for part in enumerate(parts):
+            if '/' in part:
+                try:
+                    layer = str2lnum(layer_part)
+                except Exception as err:
+                    logger.error(f'Layer remap spec read failed on line {nn}')
+                    raise err
+            else:
+                layer = part.strip()
+                if not layer:
+                   raise Exception(f'Empty layer in layer remap spec on line {nn}')
+            layers.append(layer)
+
+        remap[layers[0]] = layers[1]
+
+    return remap
+
+
+def str2lnum(string: str) -> tuple[int, int]:
+    """
+    Parse a '123/45'-style layer/dtype spec string.
+
+    Args:
+        string: String specifying the layer/dtype
+
+    Returns:
+        (layer, dtype)
+    """
+    layer_str, dtype_str = string.split('/')
+    layer = int(layer_str)
+    dtype = int(dtype_str)
+    return (layer, dtype)