Add GridRepetition: a SubPattern-like object which implements regular spatial arrays.
Also rework masque.file.gdsii to consolidate write() and write_dose2dtype()
This commit is contained in:
parent
539198435c
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c50bd8e148
@ -27,6 +27,7 @@ from .error import PatternError
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from .shapes import Shape
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from .shapes import Shape
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from .label import Label
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from .label import Label
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from .subpattern import SubPattern
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from .subpattern import SubPattern
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from .repetition import GridRepetition
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from .pattern import Pattern
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from .pattern import Pattern
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@ -6,12 +6,12 @@ import gdsii.library
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import gdsii.structure
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import gdsii.structure
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import gdsii.elements
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import gdsii.elements
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from typing import List, Any, Dict
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from typing import List, Any, Dict, Tuple
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import re
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import re
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import numpy
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import numpy
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from .utils import mangle_name, make_dose_table
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from .utils import mangle_name, make_dose_table
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from .. import Pattern, SubPattern, PatternError, Label
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from .. import Pattern, SubPattern, GridRepetition, PatternError, Label, Shape
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from ..shapes import Polygon
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from ..shapes import Polygon
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from ..utils import rotation_matrix_2d, get_bit, set_bit, vector2, is_scalar
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from ..utils import rotation_matrix_2d, get_bit, set_bit, vector2, is_scalar
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@ -74,45 +74,13 @@ def write(patterns: Pattern or List[Pattern],
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structure = gdsii.structure.Structure(name=encoded_name)
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structure = gdsii.structure.Structure(name=encoded_name)
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lib.append(structure)
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lib.append(structure)
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# Add a Boundary element for each shape
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# Add a Boundary element for each shape
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for shape in pat.shapes:
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structure += _shapes_to_boundaries(pat.shapes)
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layer, data_type = _mlayer2gds(shape.layer)
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for polygon in shape.to_polygons():
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xy_open = numpy.round(polygon.vertices + polygon.offset).astype(int)
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xy_closed = numpy.vstack((xy_open, xy_open[0, :]))
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structure.append(gdsii.elements.Boundary(layer=layer,
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data_type=data_type,
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xy=xy_closed))
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for label in pat.labels:
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layer, text_type = _mlayer2gds(label.layer)
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xy = numpy.round([label.offset]).astype(int)
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structure.append(gdsii.elements.Text(layer=layer,
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text_type=text_type,
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xy=xy,
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string=label.string.encode('ASCII')))
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# Add an SREF for each subpattern entry
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structure += _labels_to_texts(pat.labels)
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# strans must be set for angle and mag to take effect
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for subpat in pat.subpatterns:
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# Add an SREF / AREF for each subpattern entry
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sanitized_name = re.compile('[^A-Za-z0-9_\?\$]').sub('_', subpat.pattern.name)
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structure += _subpatterns_to_refs(pat.subpatterns)
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encoded_name = sanitized_name.encode('ASCII')
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if len(encoded_name) == 0:
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raise PatternError('Zero-length name after sanitize+encode, originally "{}"'.format(subpat.pattern.name))
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sref = gdsii.elements.SRef(struct_name=encoded_name,
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xy=numpy.round([subpat.offset]).astype(int))
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sref.strans = 0
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sref.angle = subpat.rotation * 180 / numpy.pi
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mirror_x, mirror_y = subpat.mirrored
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if mirror_y and mirror_y:
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sref.angle += 180
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elif mirror_x:
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sref.strans = set_bit(sref.strans, 15 - 0, True)
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elif mirror_y:
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sref.angle += 180
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sref.strans = set_bit(sref.strans, 15 - 0, True)
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sref.mag = subpat.scale
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structure.append(sref)
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with open(filename, mode='wb') as stream:
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with open(filename, mode='wb') as stream:
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lib.save(stream)
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lib.save(stream)
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@ -155,12 +123,31 @@ def write_dose2dtype(patterns: Pattern or List[Pattern],
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:returns: A list of doses, providing a mapping between datatype (int, list index)
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:returns: A list of doses, providing a mapping between datatype (int, list index)
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and dose (float, list entry).
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and dose (float, list entry).
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"""
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"""
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# Create library
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patterns, dose_vals = dose2dtype(patterns)
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lib = gdsii.library.Library(version=600,
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write(patterns, filename, meters_per_unit, logical_units_per_unit)
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name='masque-write_dose2dtype'.encode('ASCII'),
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return dose_vals
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logical_unit=logical_units_per_unit,
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physical_unit=meters_per_unit)
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def dose2dtype(patterns: Pattern or List[Pattern],
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) -> Tuple[List[Pattern], List[float]]:
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"""
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For each shape in each pattern, set shape.layer to the tuple
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(base_layer, datatype), where:
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layer is chosen to be equal to the original shape.layer if it is an int,
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or shape.layer[0] if it is a tuple
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datatype is chosen arbitrarily, based on calcualted dose for each shape.
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Shapes with equal calcualted dose will have the same datatype.
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A list of doses is retured, providing a mapping between datatype
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(list index) and dose (list entry).
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Note that this function modifies the input Pattern(s).
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:param patterns: A Pattern or list of patterns to write to file. Modified by this function.
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:returns: (patterns, dose_list)
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patterns: modified input patterns
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dose_list: A list of doses, providing a mapping between datatype (int, list index)
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and dose (float, list entry).
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"""
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if isinstance(patterns, Pattern):
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if isinstance(patterns, Pattern):
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patterns = [patterns]
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patterns = [patterns]
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@ -183,66 +170,36 @@ def write_dose2dtype(patterns: Pattern or List[Pattern],
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if len(dose_vals) > 256:
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if len(dose_vals) > 256:
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raise PatternError('Too many dose values: {}, maximum 256 when using dtypes.'.format(len(dose_vals)))
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raise PatternError('Too many dose values: {}, maximum 256 when using dtypes.'.format(len(dose_vals)))
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dose_vals_list = list(dose_vals)
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# Create a new pattern for each non-1-dose entry in the dose table
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# and update the shapes to reflect their new dose
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# Now create a structure for each row in sd_table (ie, each pattern + dose combination)
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new_pats = {} # (id, dose) -> new_pattern mapping
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# and add in any Boundary and SREF elements
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for pat_id, pat_dose in sd_table:
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for pat_id, pat_dose in sd_table:
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pat = patterns_by_id[pat_id]
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if pat_dose == 1:
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new_pats[(pat_id, pat_dose)] = patterns_by_id[pat_id]
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continue
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pat = patterns_by_id[pat_id].deepcopy()
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encoded_name = mangle_name(pat, pat_dose).encode('ASCII')
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encoded_name = mangle_name(pat, pat_dose).encode('ASCII')
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if len(encoded_name) == 0:
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if len(encoded_name) == 0:
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raise PatternError('Zero-length name after mangle+encode, originally "{}"'.format(pat.name))
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raise PatternError('Zero-length name after mangle+encode, originally "{}"'.format(pat.name))
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structure = gdsii.structure.Structure(name=encoded_name)
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lib.append(structure)
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# Add a Boundary element for each shape
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for shape in pat.shapes:
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for shape in pat.shapes:
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for polygon in shape.to_polygons():
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data_type = dose_vals_list.index(shape.dose * pat_dose)
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data_type = dose_vals_list.index(polygon.dose * pat_dose)
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if is_scalar(shape.layer):
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xy_open = numpy.round(polygon.vertices + polygon.offset).astype(int)
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layer = (shape.layer, data_type)
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xy_closed = numpy.vstack((xy_open, xy_open[0, :]))
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if is_scalar(polygon.layer):
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layer = polygon.layer
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else:
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else:
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layer = polygon.layer[0]
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layer = (shape.layer[0], data_type)
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structure.append(gdsii.elements.Boundary(layer=layer,
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data_type=data_type,
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xy=xy_closed))
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for label in pat.labels:
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layer, text_type = _mlayer2gds(label.layer)
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xy = numpy.round([label.offset]).astype(int)
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structure.append(gdsii.elements.Text(layer=layer,
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text_type=text_type,
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xy=xy,
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string=label.string.encode('ASCII')))
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# Add an SREF for each subpattern entry
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new_pats[(pat_id, pat_dose)] = pat
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# strans must be set for angle and mag to take effect
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# Go back through all the dose-specific patterns and fix up their subpattern entries
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for (pat_id, pat_dose), pat in new_pats.items():
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for subpat in pat.subpatterns:
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for subpat in pat.subpatterns:
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dose_mult = subpat.dose * pat_dose
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dose_mult = subpat.dose * pat_dose
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encoded_name = mangle_name(subpat.pattern, dose_mult).encode('ASCII')
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subpat.pattern = new_pats[(id(subpat.pattern), dose_mult)]
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if len(encoded_name) == 0:
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raise PatternError('Zero-length name after mangle+encode, originally "{}"'.format(subpat.pattern.name))
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sref = gdsii.elements.SRef(struct_name=encoded_name,
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xy=numpy.round([subpat.offset]).astype(int))
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sref.strans = 0
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sref.angle = subpat.rotation * 180 / numpy.pi
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sref.mag = subpat.scale
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mirror_x, mirror_y = subpat.mirrored
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if mirror_y and mirror_y:
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sref.angle += 180
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elif mirror_x:
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sref.strans = set_bit(sref.strans, 15 - 0, True)
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elif mirror_y:
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sref.angle += 180
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sref.strans = set_bit(sref.strans, 15 - 0, True)
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structure.append(sref)
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with open(filename, mode='wb') as stream:
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return patterns, list(dose_vals)
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lib.save(stream)
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return dose_vals_list
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def read_dtype2dose(filename: str) -> (List[Pattern], Dict[str, Any]):
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def read_dtype2dose(filename: str) -> (List[Pattern], Dict[str, Any]):
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@ -285,34 +242,6 @@ def read(filename: str,
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'logical_units_per_unit': lib.logical_unit,
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'logical_units_per_unit': lib.logical_unit,
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}
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}
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def ref_element_to_subpat(element, offset: vector2) -> SubPattern:
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# Helper function to create a SubPattern from an SREF or AREF. Sets subpat.pattern to None
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# and sets the instance attribute .ref_name to the struct_name.
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#
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# BUG: "Absolute" means not affected by parent elements.
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# That's not currently supported by masque at all, so need to either tag it and
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# undo the parent transformations, or implement it in masque.
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subpat = SubPattern(pattern=None, offset=offset)
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subpat.ref_name = element.struct_name
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if element.strans is not None:
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if element.mag is not None:
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subpat.scale = element.mag
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# Bit 13 means absolute scale
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if get_bit(element.strans, 15 - 13):
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#subpat.offset *= subpat.scale
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raise PatternError('Absolute scale is not implemented yet!')
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if element.angle is not None:
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subpat.rotation = element.angle * numpy.pi / 180
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# Bit 14 means absolute rotation
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if get_bit(element.strans, 15 - 14):
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#subpat.offset = numpy.dot(rotation_matrix_2d(subpat.rotation), subpat.offset)
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raise PatternError('Absolute rotation is not implemented yet!')
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# Bit 0 means mirror x-axis
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if get_bit(element.strans, 15 - 0):
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subpat.mirror(axis=0)
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return subpat
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patterns = []
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patterns = []
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for structure in lib:
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for structure in lib:
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pat = Pattern(name=structure.name.decode('ASCII'))
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pat = Pattern(name=structure.name.decode('ASCII'))
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@ -341,18 +270,10 @@ def read(filename: str,
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pat.labels.append(label)
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pat.labels.append(label)
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elif isinstance(element, gdsii.elements.SRef):
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elif isinstance(element, gdsii.elements.SRef):
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pat.subpatterns.append(ref_element_to_subpat(element, element.xy))
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pat.subpatterns.append(_sref_to_subpat(element))
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elif isinstance(element, gdsii.elements.ARef):
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elif isinstance(element, gdsii.elements.ARef):
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xy = numpy.array(element.xy)
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pat.subpatterns.append(_aref_to_gridrep(element))
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origin = xy[0]
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col_spacing = (xy[1] - origin) / element.cols
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row_spacing = (xy[2] - origin) / element.rows
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for c in range(element.cols):
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for r in range(element.rows):
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offset = origin + c * col_spacing + r * row_spacing
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pat.subpatterns.append(ref_element_to_subpat(element, offset))
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patterns.append(pat)
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patterns.append(pat)
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@ -378,3 +299,149 @@ def _mlayer2gds(mlayer):
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else:
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else:
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data_type = 0
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data_type = 0
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return layer, data_type
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return layer, data_type
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def _sref_to_subpat(element: gdsii.elements.SRef) -> SubPattern:
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# Helper function to create a SubPattern from an SREF. Sets subpat.pattern to None
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# and sets the instance attribute .ref_name to the struct_name.
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#
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# BUG: "Absolute" means not affected by parent elements.
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# That's not currently supported by masque at all, so need to either tag it and
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# undo the parent transformations, or implement it in masque.
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subpat = SubPattern(pattern=None, offset=element.xy)
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subpat.ref_name = element.struct_name
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if element.strans is not None:
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if element.mag is not None:
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subpat.scale = element.mag
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# Bit 13 means absolute scale
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if get_bit(element.strans, 15 - 13):
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#subpat.offset *= subpat.scale
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raise PatternError('Absolute scale is not implemented yet!')
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if element.angle is not None:
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subpat.rotation = element.angle * numpy.pi / 180
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# Bit 14 means absolute rotation
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if get_bit(element.strans, 15 - 14):
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#subpat.offset = numpy.dot(rotation_matrix_2d(subpat.rotation), subpat.offset)
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raise PatternError('Absolute rotation is not implemented yet!')
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# Bit 0 means mirror x-axis
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if get_bit(element.strans, 15 - 0):
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subpat.mirror(axis=0)
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return subpat
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def _aref_to_gridrep(element: gdsii.elements.ARef) -> GridRepetition:
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# Helper function to create a GridRepetition from an AREF. Sets gridrep.pattern to None
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# and sets the instance attribute .ref_name to the struct_name.
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#
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# BUG: "Absolute" means not affected by parent elements.
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# That's not currently supported by masque at all, so need to either tag it and
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# undo the parent transformations, or implement it in masque.i
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rotation = 0
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offset = numpy.array(element.xy[0])
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scale = 1
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mirror_signs = numpy.ones(2)
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if element.strans is not None:
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if element.mag is not None:
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scale = element.mag
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# Bit 13 means absolute scale
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if get_bit(element.strans, 15 - 13):
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raise PatternError('Absolute scale is not implemented yet!')
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if element.angle is not None:
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rotation = element.angle * numpy.pi / 180
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# Bit 14 means absolute rotation
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if get_bit(element.strans, 15 - 14):
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raise PatternError('Absolute rotation is not implemented yet!')
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# Bit 0 means mirror x-axis
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if get_bit(element.strans, 15 - 0):
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mirror_signs[0] = -1
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counts = [element.cols, element.rows]
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vec_a0 = element.xy[1] - offset
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vec_b0 = element.xy[2] - offset
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a_vector = numpy.dot(rotation_matrix_2d(-rotation), vec_a0 / scale / counts[0]) * mirror_signs[0]
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b_vector = numpy.dot(rotation_matrix_2d(-rotation), vec_b0 / scale / counts[1]) * mirror_signs[1]
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gridrep = GridRepetition(pattern=None,
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a_vector=a_vector,
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b_vector=b_vector,
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a_count=counts[0],
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b_count=counts[1],
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offset=offset,
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rotation=rotation,
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scale=scale,
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mirrored=(mirror_signs == -1))
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gridrep.ref_name = element.struct_name
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return gridrep
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||||||
|
def _subpatterns_to_refs(subpatterns: List[SubPattern or GridRepetition]
|
||||||
|
) -> List[gdsii.elements.ARef or gdsii.elements.SRef]:
|
||||||
|
# strans must be set for angle and mag to take effect
|
||||||
|
refs = []
|
||||||
|
for subpat in subpatterns:
|
||||||
|
sanitized_name = re.compile('[^A-Za-z0-9_\?\$]').sub('_', subpat.pattern.name)
|
||||||
|
encoded_name = sanitized_name.encode('ASCII')
|
||||||
|
if len(encoded_name) == 0:
|
||||||
|
raise PatternError('Zero-length name after sanitize+encode, originally "{}"'.format(subpat.pattern.name))
|
||||||
|
|
||||||
|
if isinstance(subpat, GridRepetition):
|
||||||
|
mirror_signs = (-1) ** numpy.array(subpat.mirrored)
|
||||||
|
xy = numpy.array(subpat.offset) + [
|
||||||
|
[0, 0],
|
||||||
|
numpy.dot(rotation_matrix_2d(subpat.rotation), subpat.a_vector * mirror_signs) * subpat.scale * subpat.a_count,
|
||||||
|
numpy.dot(rotation_matrix_2d(subpat.rotation), subpat.b_vector * mirror_signs) * subpat.scale * subpat.b_count,
|
||||||
|
]
|
||||||
|
ref = gdsii.elements.ARef(struct_name=encoded_name,
|
||||||
|
xy=numpy.round(xy).astype(int),
|
||||||
|
cols=subpat.a_count,
|
||||||
|
rows=subpat.b_count)
|
||||||
|
else:
|
||||||
|
ref = gdsii.elements.SRef(struct_name=encoded_name,
|
||||||
|
xy=numpy.round([subpat.offset]).astype(int))
|
||||||
|
|
||||||
|
ref.strans = 0
|
||||||
|
ref.angle = subpat.rotation * 180 / numpy.pi
|
||||||
|
mirror_x, mirror_y = subpat.mirrored
|
||||||
|
if mirror_y and mirror_y:
|
||||||
|
ref.angle += 180
|
||||||
|
elif mirror_x:
|
||||||
|
ref.strans = set_bit(ref.strans, 15 - 0, True)
|
||||||
|
elif mirror_y:
|
||||||
|
ref.angle += 180
|
||||||
|
ref.strans = set_bit(ref.strans, 15 - 0, True)
|
||||||
|
ref.mag = subpat.scale
|
||||||
|
|
||||||
|
refs.append(ref)
|
||||||
|
return refs
|
||||||
|
|
||||||
|
|
||||||
|
def _shapes_to_boundaries(shapes: List[Shape]
|
||||||
|
) -> List[gdsii.elements.Boundary]:
|
||||||
|
# Add a Boundary element for each shape
|
||||||
|
boundaries = []
|
||||||
|
for shape in shapes:
|
||||||
|
layer, data_type = _mlayer2gds(shape.layer)
|
||||||
|
for polygon in shape.to_polygons():
|
||||||
|
xy_open = numpy.round(polygon.vertices + polygon.offset).astype(int)
|
||||||
|
xy_closed = numpy.vstack((xy_open, xy_open[0, :]))
|
||||||
|
boundaries.append(gdsii.elements.Boundary(layer=layer,
|
||||||
|
data_type=data_type,
|
||||||
|
xy=xy_closed))
|
||||||
|
return boundaries
|
||||||
|
|
||||||
|
|
||||||
|
def _labels_to_texts(labels: List[Label]) -> List[gdsii.elements.Text]:
|
||||||
|
texts = []
|
||||||
|
for label in labels:
|
||||||
|
layer, text_type = _mlayer2gds(label.layer)
|
||||||
|
xy = numpy.round([label.offset]).astype(int)
|
||||||
|
texts.append(gdsii.elements.Text(layer=layer,
|
||||||
|
text_type=text_type,
|
||||||
|
xy=xy,
|
||||||
|
string=label.string.encode('ASCII')))
|
||||||
|
return texts
|
||||||
|
@ -12,6 +12,7 @@ import numpy
|
|||||||
# .visualize imports matplotlib and matplotlib.collections
|
# .visualize imports matplotlib and matplotlib.collections
|
||||||
|
|
||||||
from .subpattern import SubPattern
|
from .subpattern import SubPattern
|
||||||
|
from .repetition import GridRepetition
|
||||||
from .shapes import Shape, Polygon
|
from .shapes import Shape, Polygon
|
||||||
from .label import Label
|
from .label import Label
|
||||||
from .utils import rotation_matrix_2d, vector2
|
from .utils import rotation_matrix_2d, vector2
|
||||||
@ -34,7 +35,7 @@ class Pattern:
|
|||||||
"""
|
"""
|
||||||
shapes = None # type: List[Shape]
|
shapes = None # type: List[Shape]
|
||||||
labels = None # type: List[Labels]
|
labels = None # type: List[Labels]
|
||||||
subpatterns = None # type: List[SubPattern]
|
subpatterns = None # type: List[SubPattern or GridRepetition]
|
||||||
name = None # type: str
|
name = None # type: str
|
||||||
|
|
||||||
def __init__(self,
|
def __init__(self,
|
||||||
|
291
masque/repetition.py
Normal file
291
masque/repetition.py
Normal file
@ -0,0 +1,291 @@
|
|||||||
|
"""
|
||||||
|
Repetitions provides support for efficiently nesting multiple identical
|
||||||
|
instances of a Pattern in the same parent Pattern.
|
||||||
|
"""
|
||||||
|
|
||||||
|
from typing import Union, List
|
||||||
|
import copy
|
||||||
|
|
||||||
|
import numpy
|
||||||
|
from numpy import pi
|
||||||
|
|
||||||
|
from .error import PatternError
|
||||||
|
from .utils import is_scalar, rotation_matrix_2d, vector2
|
||||||
|
|
||||||
|
|
||||||
|
__author__ = 'Jan Petykiewicz'
|
||||||
|
|
||||||
|
|
||||||
|
# TODO need top-level comment about what order rotation/scale/offset/mirror/array are applied
|
||||||
|
|
||||||
|
class GridRepetition:
|
||||||
|
"""
|
||||||
|
GridRepetition provides support for efficiently embedding multiple copies of a Pattern
|
||||||
|
into another Pattern at regularly-spaced offsets.
|
||||||
|
"""
|
||||||
|
|
||||||
|
pattern = None # type: Pattern
|
||||||
|
|
||||||
|
_offset = (0.0, 0.0) # type: numpy.ndarray
|
||||||
|
_rotation = 0.0 # type: float
|
||||||
|
_dose = 1.0 # type: float
|
||||||
|
_scale = 1.0 # type: float
|
||||||
|
_mirrored = None # type: List[bool]
|
||||||
|
|
||||||
|
_a_vector = None # type: numpy.ndarray
|
||||||
|
_b_vector = None # type: numpy.ndarray
|
||||||
|
a_count = None # type: int
|
||||||
|
b_count = 1 # type: int
|
||||||
|
|
||||||
|
def __init__(self,
|
||||||
|
pattern: 'Pattern',
|
||||||
|
a_vector: numpy.ndarray,
|
||||||
|
a_count: int,
|
||||||
|
b_vector: numpy.ndarray = None,
|
||||||
|
b_count: int = 1,
|
||||||
|
offset: vector2 = (0.0, 0.0),
|
||||||
|
rotation: float = 0.0,
|
||||||
|
mirrored: List[bool] = None,
|
||||||
|
dose: float = 1.0,
|
||||||
|
scale: float = 1.0):
|
||||||
|
"""
|
||||||
|
:param a_vector: First lattice vector, of the form [x, y].
|
||||||
|
Specifies center-to-center spacing between adjacent elements.
|
||||||
|
:param a_count: Number of elements in the a_vector direction.
|
||||||
|
:param b_vector: Second lattice vector, of the form [x, y].
|
||||||
|
Specifies center-to-center spacing between adjacent elements.
|
||||||
|
Can be omitted when specifying a 1D array.
|
||||||
|
:param b_count: Number of elements in the b_vector direction.
|
||||||
|
Should be omitted if b_vector was omitted.
|
||||||
|
:raises: InvalidDataError if b_* inputs conflict with each other
|
||||||
|
or a_count < 1.
|
||||||
|
"""
|
||||||
|
if b_vector is None:
|
||||||
|
if b_count > 1:
|
||||||
|
raise PatternError('Repetition has b_count > 1 but no b_vector')
|
||||||
|
else:
|
||||||
|
b_vector = numpy.array([0.0, 0.0])
|
||||||
|
|
||||||
|
if a_count < 1:
|
||||||
|
raise InvalidDataError('Repetition has too-small a_count: '
|
||||||
|
'{}'.format(a_count))
|
||||||
|
if b_count < 1:
|
||||||
|
raise InvalidDataError('Repetition has too-small b_count: '
|
||||||
|
'{}'.format(b_count))
|
||||||
|
self.a_vector = a_vector
|
||||||
|
self.b_vector = b_vector
|
||||||
|
self.a_count = a_count
|
||||||
|
self.b_count = b_count
|
||||||
|
|
||||||
|
self.pattern = pattern
|
||||||
|
self.offset = offset
|
||||||
|
self.rotation = rotation
|
||||||
|
self.dose = dose
|
||||||
|
self.scale = scale
|
||||||
|
if mirrored is None:
|
||||||
|
mirrored = [False, False]
|
||||||
|
self.mirrored = mirrored
|
||||||
|
|
||||||
|
# offset property
|
||||||
|
@property
|
||||||
|
def offset(self) -> numpy.ndarray:
|
||||||
|
return self._offset
|
||||||
|
|
||||||
|
@offset.setter
|
||||||
|
def offset(self, val: vector2):
|
||||||
|
if not isinstance(val, numpy.ndarray):
|
||||||
|
val = numpy.array(val, dtype=float)
|
||||||
|
|
||||||
|
if val.size != 2:
|
||||||
|
raise PatternError('Offset must be convertible to size-2 ndarray')
|
||||||
|
self._offset = val.flatten()
|
||||||
|
|
||||||
|
# dose property
|
||||||
|
@property
|
||||||
|
def dose(self) -> float:
|
||||||
|
return self._dose
|
||||||
|
|
||||||
|
@dose.setter
|
||||||
|
def dose(self, val: float):
|
||||||
|
if not is_scalar(val):
|
||||||
|
raise PatternError('Dose must be a scalar')
|
||||||
|
if not val >= 0:
|
||||||
|
raise PatternError('Dose must be non-negative')
|
||||||
|
self._dose = val
|
||||||
|
|
||||||
|
# scale property
|
||||||
|
@property
|
||||||
|
def scale(self) -> float:
|
||||||
|
return self._scale
|
||||||
|
|
||||||
|
@scale.setter
|
||||||
|
def scale(self, val: float):
|
||||||
|
if not is_scalar(val):
|
||||||
|
raise PatternError('Scale must be a scalar')
|
||||||
|
if not val > 0:
|
||||||
|
raise PatternError('Scale must be positive')
|
||||||
|
self._scale = val
|
||||||
|
|
||||||
|
# Rotation property [ccw]
|
||||||
|
@property
|
||||||
|
def rotation(self) -> float:
|
||||||
|
return self._rotation
|
||||||
|
|
||||||
|
@rotation.setter
|
||||||
|
def rotation(self, val: float):
|
||||||
|
if not is_scalar(val):
|
||||||
|
raise PatternError('Rotation must be a scalar')
|
||||||
|
self._rotation = val % (2 * pi)
|
||||||
|
|
||||||
|
# Mirrored property
|
||||||
|
@property
|
||||||
|
def mirrored(self) -> List[bool]:
|
||||||
|
return self._mirrored
|
||||||
|
|
||||||
|
@mirrored.setter
|
||||||
|
def mirrored(self, val: List[bool]):
|
||||||
|
if is_scalar(val):
|
||||||
|
raise PatternError('Mirrored must be a 2-element list of booleans')
|
||||||
|
self._mirrored = val
|
||||||
|
|
||||||
|
# a_vector property
|
||||||
|
@property
|
||||||
|
def a_vector(self) -> numpy.ndarray:
|
||||||
|
return self._a_vector
|
||||||
|
|
||||||
|
@a_vector.setter
|
||||||
|
def a_vector(self, val: vector2):
|
||||||
|
if not isinstance(val, numpy.ndarray):
|
||||||
|
val = numpy.array(val, dtype=float)
|
||||||
|
|
||||||
|
if val.size != 2:
|
||||||
|
raise PatternError('a_vector must be convertible to size-2 ndarray')
|
||||||
|
self._a_vector = val.flatten()
|
||||||
|
|
||||||
|
# b_vector property
|
||||||
|
@property
|
||||||
|
def b_vector(self) -> numpy.ndarray:
|
||||||
|
return self._b_vector
|
||||||
|
|
||||||
|
@b_vector.setter
|
||||||
|
def b_vector(self, val: vector2):
|
||||||
|
if not isinstance(val, numpy.ndarray):
|
||||||
|
val = numpy.array(val, dtype=float)
|
||||||
|
|
||||||
|
if val.size != 2:
|
||||||
|
raise PatternError('b_vector must be convertible to size-2 ndarray')
|
||||||
|
self._b_vector = val.flatten()
|
||||||
|
|
||||||
|
|
||||||
|
def as_pattern(self) -> 'Pattern':
|
||||||
|
"""
|
||||||
|
Returns a copy of self.pattern which has been scaled, rotated, etc. according to this
|
||||||
|
SubPattern's properties.
|
||||||
|
:return: Copy of self.pattern that has been altered to reflect the SubPattern's properties.
|
||||||
|
"""
|
||||||
|
#xy = numpy.array(element.xy)
|
||||||
|
#origin = xy[0]
|
||||||
|
#col_spacing = (xy[1] - origin) / element.cols
|
||||||
|
#row_spacing = (xy[2] - origin) / element.rows
|
||||||
|
|
||||||
|
patterns = []
|
||||||
|
|
||||||
|
for a in range(self.a_count):
|
||||||
|
for b in range(self.b_count):
|
||||||
|
offset = a * self.a_vector + b * self.b_vector
|
||||||
|
newPat = self.pattern.deepcopy()
|
||||||
|
newPat.translate_elements(offset)
|
||||||
|
patterns.append(newPat)
|
||||||
|
|
||||||
|
combined = patterns[0]
|
||||||
|
for p in patterns[1:]:
|
||||||
|
combined.append(p)
|
||||||
|
|
||||||
|
combined.scale_by(self.scale)
|
||||||
|
[combined.mirror(ax) for ax, do in enumerate(self.mirrored) if do]
|
||||||
|
combined.rotate_around((0.0, 0.0), self.rotation)
|
||||||
|
combined.translate_elements(self.offset)
|
||||||
|
combined.scale_element_doses(self.dose)
|
||||||
|
|
||||||
|
return combined
|
||||||
|
|
||||||
|
def translate(self, offset: vector2) -> 'GridRepetition':
|
||||||
|
"""
|
||||||
|
Translate by the given offset
|
||||||
|
|
||||||
|
:param offset: Translate by this offset
|
||||||
|
:return: self
|
||||||
|
"""
|
||||||
|
self.offset += offset
|
||||||
|
return self
|
||||||
|
|
||||||
|
def rotate_around(self, pivot: vector2, rotation: float) -> 'GridRepetition':
|
||||||
|
"""
|
||||||
|
Rotate around a point
|
||||||
|
|
||||||
|
:param pivot: Point to rotate around
|
||||||
|
:param rotation: Angle to rotate by (counterclockwise, radians)
|
||||||
|
:return: self
|
||||||
|
"""
|
||||||
|
pivot = numpy.array(pivot, dtype=float)
|
||||||
|
self.translate(-pivot)
|
||||||
|
self.offset = numpy.dot(rotation_matrix_2d(rotation), self.offset)
|
||||||
|
self.rotate(rotation)
|
||||||
|
self.translate(+pivot)
|
||||||
|
return self
|
||||||
|
|
||||||
|
def rotate(self, rotation: float) -> 'GridRepetition':
|
||||||
|
"""
|
||||||
|
Rotate around (0, 0)
|
||||||
|
|
||||||
|
:param rotation: Angle to rotate by (counterclockwise, radians)
|
||||||
|
:return: self
|
||||||
|
"""
|
||||||
|
self.rotation += rotation
|
||||||
|
return self
|
||||||
|
|
||||||
|
def mirror(self, axis: int) -> 'GridRepetition':
|
||||||
|
"""
|
||||||
|
Mirror the subpattern across an axis.
|
||||||
|
|
||||||
|
:param axis: Axis to mirror across.
|
||||||
|
:return: self
|
||||||
|
"""
|
||||||
|
self.mirrored[axis] = not self.mirrored[axis]
|
||||||
|
return self
|
||||||
|
|
||||||
|
def get_bounds(self) -> numpy.ndarray or None:
|
||||||
|
"""
|
||||||
|
Return a numpy.ndarray containing [[x_min, y_min], [x_max, y_max]], corresponding to the
|
||||||
|
extent of the SubPattern in each dimension.
|
||||||
|
Returns None if the contained Pattern is empty.
|
||||||
|
|
||||||
|
:return: [[x_min, y_min], [x_max, y_max]] or None
|
||||||
|
"""
|
||||||
|
return self.as_pattern().get_bounds()
|
||||||
|
|
||||||
|
def scale_by(self, c: float) -> 'GridRepetition':
|
||||||
|
"""
|
||||||
|
Scale the subpattern by a factor
|
||||||
|
|
||||||
|
:param c: scaling factor
|
||||||
|
"""
|
||||||
|
self.scale *= c
|
||||||
|
return self
|
||||||
|
|
||||||
|
def copy(self) -> 'GridRepetition':
|
||||||
|
"""
|
||||||
|
Return a shallow copy of the repetition.
|
||||||
|
|
||||||
|
:return: copy.copy(self)
|
||||||
|
"""
|
||||||
|
return copy.copy(self)
|
||||||
|
|
||||||
|
def deepcopy(self) -> 'SubPattern':
|
||||||
|
"""
|
||||||
|
Return a deep copy of the repetition.
|
||||||
|
|
||||||
|
:return: copy.copy(self)
|
||||||
|
"""
|
||||||
|
return copy.deepcopy(self)
|
||||||
|
|
Loading…
Reference in New Issue
Block a user