| | from fontTools.misc.fixedTools import ( |
| | fixedToFloat as fi2fl, |
| | floatToFixed as fl2fi, |
| | floatToFixedToStr as fl2str, |
| | strToFixedToFloat as str2fl, |
| | otRound, |
| | ) |
| | from fontTools.misc.textTools import safeEval |
| | import array |
| | from collections import Counter, defaultdict |
| | import io |
| | import logging |
| | import struct |
| | import sys |
| |
|
| |
|
| | |
| |
|
| | EMBEDDED_PEAK_TUPLE = 0x8000 |
| | INTERMEDIATE_REGION = 0x4000 |
| | PRIVATE_POINT_NUMBERS = 0x2000 |
| |
|
| | DELTAS_ARE_ZERO = 0x80 |
| | DELTAS_ARE_WORDS = 0x40 |
| | DELTAS_ARE_LONGS = 0xC0 |
| | DELTAS_SIZE_MASK = 0xC0 |
| | DELTA_RUN_COUNT_MASK = 0x3F |
| |
|
| | POINTS_ARE_WORDS = 0x80 |
| | POINT_RUN_COUNT_MASK = 0x7F |
| |
|
| | TUPLES_SHARE_POINT_NUMBERS = 0x8000 |
| | TUPLE_COUNT_MASK = 0x0FFF |
| | TUPLE_INDEX_MASK = 0x0FFF |
| |
|
| | log = logging.getLogger(__name__) |
| |
|
| |
|
| | class TupleVariation(object): |
| | def __init__(self, axes, coordinates): |
| | self.axes = axes.copy() |
| | self.coordinates = list(coordinates) |
| |
|
| | def __repr__(self): |
| | axes = ",".join( |
| | sorted(["%s=%s" % (name, value) for (name, value) in self.axes.items()]) |
| | ) |
| | return "<TupleVariation %s %s>" % (axes, self.coordinates) |
| |
|
| | def __eq__(self, other): |
| | return self.coordinates == other.coordinates and self.axes == other.axes |
| |
|
| | def getUsedPoints(self): |
| | |
| | if None not in self.coordinates: |
| | return frozenset() |
| | used = frozenset([i for i, p in enumerate(self.coordinates) if p is not None]) |
| | |
| | return used if used else None |
| |
|
| | def hasImpact(self): |
| | """Returns True if this TupleVariation has any visible impact. |
| | |
| | If the result is False, the TupleVariation can be omitted from the font |
| | without making any visible difference. |
| | """ |
| | return any(c is not None for c in self.coordinates) |
| |
|
| | def toXML(self, writer, axisTags): |
| | writer.begintag("tuple") |
| | writer.newline() |
| | for axis in axisTags: |
| | value = self.axes.get(axis) |
| | if value is not None: |
| | minValue, value, maxValue = value |
| | defaultMinValue = min(value, 0.0) |
| | defaultMaxValue = max(value, 0.0) |
| | if minValue == defaultMinValue and maxValue == defaultMaxValue: |
| | writer.simpletag("coord", axis=axis, value=fl2str(value, 14)) |
| | else: |
| | attrs = [ |
| | ("axis", axis), |
| | ("min", fl2str(minValue, 14)), |
| | ("value", fl2str(value, 14)), |
| | ("max", fl2str(maxValue, 14)), |
| | ] |
| | writer.simpletag("coord", attrs) |
| | writer.newline() |
| | wrote_any_deltas = False |
| | for i, delta in enumerate(self.coordinates): |
| | if type(delta) == tuple and len(delta) == 2: |
| | writer.simpletag("delta", pt=i, x=delta[0], y=delta[1]) |
| | writer.newline() |
| | wrote_any_deltas = True |
| | elif type(delta) == int: |
| | writer.simpletag("delta", cvt=i, value=delta) |
| | writer.newline() |
| | wrote_any_deltas = True |
| | elif delta is not None: |
| | log.error("bad delta format") |
| | writer.comment("bad delta #%d" % i) |
| | writer.newline() |
| | wrote_any_deltas = True |
| | if not wrote_any_deltas: |
| | writer.comment("no deltas") |
| | writer.newline() |
| | writer.endtag("tuple") |
| | writer.newline() |
| |
|
| | def fromXML(self, name, attrs, _content): |
| | if name == "coord": |
| | axis = attrs["axis"] |
| | value = str2fl(attrs["value"], 14) |
| | defaultMinValue = min(value, 0.0) |
| | defaultMaxValue = max(value, 0.0) |
| | minValue = str2fl(attrs.get("min", defaultMinValue), 14) |
| | maxValue = str2fl(attrs.get("max", defaultMaxValue), 14) |
| | self.axes[axis] = (minValue, value, maxValue) |
| | elif name == "delta": |
| | if "pt" in attrs: |
| | point = safeEval(attrs["pt"]) |
| | x = safeEval(attrs["x"]) |
| | y = safeEval(attrs["y"]) |
| | self.coordinates[point] = (x, y) |
| | elif "cvt" in attrs: |
| | cvt = safeEval(attrs["cvt"]) |
| | value = safeEval(attrs["value"]) |
| | self.coordinates[cvt] = value |
| | else: |
| | log.warning("bad delta format: %s" % ", ".join(sorted(attrs.keys()))) |
| |
|
| | def compile(self, axisTags, sharedCoordIndices={}, pointData=None): |
| | assert set(self.axes.keys()) <= set(axisTags), ( |
| | "Unknown axis tag found.", |
| | self.axes.keys(), |
| | axisTags, |
| | ) |
| |
|
| | tupleData = [] |
| | auxData = [] |
| |
|
| | if pointData is None: |
| | usedPoints = self.getUsedPoints() |
| | if usedPoints is None: |
| | return b"", b"" |
| | pointData = self.compilePoints(usedPoints) |
| |
|
| | coord = self.compileCoord(axisTags) |
| | flags = sharedCoordIndices.get(coord) |
| | if flags is None: |
| | flags = EMBEDDED_PEAK_TUPLE |
| | tupleData.append(coord) |
| |
|
| | intermediateCoord = self.compileIntermediateCoord(axisTags) |
| | if intermediateCoord is not None: |
| | flags |= INTERMEDIATE_REGION |
| | tupleData.append(intermediateCoord) |
| |
|
| | |
| | if pointData: |
| | flags |= PRIVATE_POINT_NUMBERS |
| | auxData.append(pointData) |
| |
|
| | auxData.append(self.compileDeltas()) |
| | auxData = b"".join(auxData) |
| |
|
| | tupleData.insert(0, struct.pack(">HH", len(auxData), flags)) |
| | return b"".join(tupleData), auxData |
| |
|
| | def compileCoord(self, axisTags): |
| | result = [] |
| | axes = self.axes |
| | for axis in axisTags: |
| | triple = axes.get(axis) |
| | if triple is None: |
| | result.append(b"\0\0") |
| | else: |
| | result.append(struct.pack(">h", fl2fi(triple[1], 14))) |
| | return b"".join(result) |
| |
|
| | def compileIntermediateCoord(self, axisTags): |
| | needed = False |
| | for axis in axisTags: |
| | minValue, value, maxValue = self.axes.get(axis, (0.0, 0.0, 0.0)) |
| | defaultMinValue = min(value, 0.0) |
| | defaultMaxValue = max(value, 0.0) |
| | if (minValue != defaultMinValue) or (maxValue != defaultMaxValue): |
| | needed = True |
| | break |
| | if not needed: |
| | return None |
| | minCoords = [] |
| | maxCoords = [] |
| | for axis in axisTags: |
| | minValue, value, maxValue = self.axes.get(axis, (0.0, 0.0, 0.0)) |
| | minCoords.append(struct.pack(">h", fl2fi(minValue, 14))) |
| | maxCoords.append(struct.pack(">h", fl2fi(maxValue, 14))) |
| | return b"".join(minCoords + maxCoords) |
| |
|
| | @staticmethod |
| | def decompileCoord_(axisTags, data, offset): |
| | coord = {} |
| | pos = offset |
| | for axis in axisTags: |
| | coord[axis] = fi2fl(struct.unpack(">h", data[pos : pos + 2])[0], 14) |
| | pos += 2 |
| | return coord, pos |
| |
|
| | @staticmethod |
| | def compilePoints(points): |
| | |
| | |
| | |
| | |
| | |
| | |
| | if not points: |
| | return b"\0" |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | points = list(points) |
| | points.sort() |
| | numPoints = len(points) |
| |
|
| | result = bytearray() |
| | |
| | |
| | if numPoints < 0x80: |
| | result.append(numPoints) |
| | else: |
| | result.append((numPoints >> 8) | 0x80) |
| | result.append(numPoints & 0xFF) |
| |
|
| | MAX_RUN_LENGTH = 127 |
| | pos = 0 |
| | lastValue = 0 |
| | while pos < numPoints: |
| | runLength = 0 |
| |
|
| | headerPos = len(result) |
| | result.append(0) |
| |
|
| | useByteEncoding = None |
| | while pos < numPoints and runLength <= MAX_RUN_LENGTH: |
| | curValue = points[pos] |
| | delta = curValue - lastValue |
| | if useByteEncoding is None: |
| | useByteEncoding = 0 <= delta <= 0xFF |
| | if useByteEncoding and (delta > 0xFF or delta < 0): |
| | |
| | break |
| | |
| | |
| | if useByteEncoding: |
| | result.append(delta) |
| | else: |
| | result.append(delta >> 8) |
| | result.append(delta & 0xFF) |
| | lastValue = curValue |
| | pos += 1 |
| | runLength += 1 |
| | if useByteEncoding: |
| | result[headerPos] = runLength - 1 |
| | else: |
| | result[headerPos] = (runLength - 1) | POINTS_ARE_WORDS |
| |
|
| | return result |
| |
|
| | @staticmethod |
| | def decompilePoints_(numPoints, data, offset, tableTag): |
| | """(numPoints, data, offset, tableTag) --> ([point1, point2, ...], newOffset)""" |
| | assert tableTag in ("cvar", "gvar") |
| | pos = offset |
| | numPointsInData = data[pos] |
| | pos += 1 |
| | if (numPointsInData & POINTS_ARE_WORDS) != 0: |
| | numPointsInData = (numPointsInData & POINT_RUN_COUNT_MASK) << 8 | data[pos] |
| | pos += 1 |
| | if numPointsInData == 0: |
| | return (range(numPoints), pos) |
| |
|
| | result = [] |
| | while len(result) < numPointsInData: |
| | runHeader = data[pos] |
| | pos += 1 |
| | numPointsInRun = (runHeader & POINT_RUN_COUNT_MASK) + 1 |
| | point = 0 |
| | if (runHeader & POINTS_ARE_WORDS) != 0: |
| | points = array.array("H") |
| | pointsSize = numPointsInRun * 2 |
| | else: |
| | points = array.array("B") |
| | pointsSize = numPointsInRun |
| | points.frombytes(data[pos : pos + pointsSize]) |
| | if sys.byteorder != "big": |
| | points.byteswap() |
| |
|
| | assert len(points) == numPointsInRun |
| | pos += pointsSize |
| |
|
| | result.extend(points) |
| |
|
| | |
| | absolute = [] |
| | current = 0 |
| | for delta in result: |
| | current += delta |
| | absolute.append(current) |
| | result = absolute |
| | del absolute |
| |
|
| | badPoints = {str(p) for p in result if p < 0 or p >= numPoints} |
| | if badPoints: |
| | log.warning( |
| | "point %s out of range in '%s' table" |
| | % (",".join(sorted(badPoints)), tableTag) |
| | ) |
| | return (result, pos) |
| |
|
| | def compileDeltas(self): |
| | deltaX = [] |
| | deltaY = [] |
| | if self.getCoordWidth() == 2: |
| | for c in self.coordinates: |
| | if c is None: |
| | continue |
| | deltaX.append(c[0]) |
| | deltaY.append(c[1]) |
| | else: |
| | for c in self.coordinates: |
| | if c is None: |
| | continue |
| | deltaX.append(c) |
| | bytearr = bytearray() |
| | self.compileDeltaValues_(deltaX, bytearr) |
| | self.compileDeltaValues_(deltaY, bytearr) |
| | return bytearr |
| |
|
| | @staticmethod |
| | def compileDeltaValues_(deltas, bytearr=None): |
| | """[value1, value2, value3, ...] --> bytearray |
| | |
| | Emits a sequence of runs. Each run starts with a |
| | byte-sized header whose 6 least significant bits |
| | (header & 0x3F) indicate how many values are encoded |
| | in this run. The stored length is the actual length |
| | minus one; run lengths are thus in the range [1..64]. |
| | If the header byte has its most significant bit (0x80) |
| | set, all values in this run are zero, and no data |
| | follows. Otherwise, the header byte is followed by |
| | ((header & 0x3F) + 1) signed values. If (header & |
| | 0x40) is clear, the delta values are stored as signed |
| | bytes; if (header & 0x40) is set, the delta values are |
| | signed 16-bit integers. |
| | """ |
| | if bytearr is None: |
| | bytearr = bytearray() |
| | pos = 0 |
| | numDeltas = len(deltas) |
| | while pos < numDeltas: |
| | value = deltas[pos] |
| | if value == 0: |
| | pos = TupleVariation.encodeDeltaRunAsZeroes_(deltas, pos, bytearr) |
| | elif -128 <= value <= 127: |
| | pos = TupleVariation.encodeDeltaRunAsBytes_(deltas, pos, bytearr) |
| | elif -32768 <= value <= 32767: |
| | pos = TupleVariation.encodeDeltaRunAsWords_(deltas, pos, bytearr) |
| | else: |
| | pos = TupleVariation.encodeDeltaRunAsLongs_(deltas, pos, bytearr) |
| | return bytearr |
| |
|
| | @staticmethod |
| | def encodeDeltaRunAsZeroes_(deltas, offset, bytearr): |
| | pos = offset |
| | numDeltas = len(deltas) |
| | while pos < numDeltas and deltas[pos] == 0: |
| | pos += 1 |
| | runLength = pos - offset |
| | while runLength >= 64: |
| | bytearr.append(DELTAS_ARE_ZERO | 63) |
| | runLength -= 64 |
| | if runLength: |
| | bytearr.append(DELTAS_ARE_ZERO | (runLength - 1)) |
| | return pos |
| |
|
| | @staticmethod |
| | def encodeDeltaRunAsBytes_(deltas, offset, bytearr): |
| | pos = offset |
| | numDeltas = len(deltas) |
| | while pos < numDeltas: |
| | value = deltas[pos] |
| | if not (-128 <= value <= 127): |
| | break |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | if value == 0 and pos + 1 < numDeltas and deltas[pos + 1] == 0: |
| | break |
| | pos += 1 |
| | runLength = pos - offset |
| | while runLength >= 64: |
| | bytearr.append(63) |
| | bytearr.extend(array.array("b", deltas[offset : offset + 64])) |
| | offset += 64 |
| | runLength -= 64 |
| | if runLength: |
| | bytearr.append(runLength - 1) |
| | bytearr.extend(array.array("b", deltas[offset:pos])) |
| | return pos |
| |
|
| | @staticmethod |
| | def encodeDeltaRunAsWords_(deltas, offset, bytearr): |
| | pos = offset |
| | numDeltas = len(deltas) |
| | while pos < numDeltas: |
| | value = deltas[pos] |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | if value == 0: |
| | break |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | if ( |
| | (-128 <= value <= 127) |
| | and pos + 1 < numDeltas |
| | and (-128 <= deltas[pos + 1] <= 127) |
| | ): |
| | break |
| |
|
| | if not (-32768 <= value <= 32767): |
| | break |
| |
|
| | pos += 1 |
| | runLength = pos - offset |
| | while runLength >= 64: |
| | bytearr.append(DELTAS_ARE_WORDS | 63) |
| | a = array.array("h", deltas[offset : offset + 64]) |
| | if sys.byteorder != "big": |
| | a.byteswap() |
| | bytearr.extend(a) |
| | offset += 64 |
| | runLength -= 64 |
| | if runLength: |
| | bytearr.append(DELTAS_ARE_WORDS | (runLength - 1)) |
| | a = array.array("h", deltas[offset:pos]) |
| | if sys.byteorder != "big": |
| | a.byteswap() |
| | bytearr.extend(a) |
| | return pos |
| |
|
| | @staticmethod |
| | def encodeDeltaRunAsLongs_(deltas, offset, bytearr): |
| | pos = offset |
| | numDeltas = len(deltas) |
| | while pos < numDeltas: |
| | value = deltas[pos] |
| | if -32768 <= value <= 32767: |
| | break |
| | pos += 1 |
| | runLength = pos - offset |
| | while runLength >= 64: |
| | bytearr.append(DELTAS_ARE_LONGS | 63) |
| | a = array.array("i", deltas[offset : offset + 64]) |
| | if sys.byteorder != "big": |
| | a.byteswap() |
| | bytearr.extend(a) |
| | offset += 64 |
| | runLength -= 64 |
| | if runLength: |
| | bytearr.append(DELTAS_ARE_LONGS | (runLength - 1)) |
| | a = array.array("i", deltas[offset:pos]) |
| | if sys.byteorder != "big": |
| | a.byteswap() |
| | bytearr.extend(a) |
| | return pos |
| |
|
| | @staticmethod |
| | def decompileDeltas_(numDeltas, data, offset=0): |
| | """(numDeltas, data, offset) --> ([delta, delta, ...], newOffset)""" |
| | result = [] |
| | pos = offset |
| | while len(result) < numDeltas if numDeltas is not None else pos < len(data): |
| | runHeader = data[pos] |
| | pos += 1 |
| | numDeltasInRun = (runHeader & DELTA_RUN_COUNT_MASK) + 1 |
| | if (runHeader & DELTAS_SIZE_MASK) == DELTAS_ARE_ZERO: |
| | result.extend([0] * numDeltasInRun) |
| | else: |
| | if (runHeader & DELTAS_SIZE_MASK) == DELTAS_ARE_LONGS: |
| | deltas = array.array("i") |
| | deltasSize = numDeltasInRun * 4 |
| | elif (runHeader & DELTAS_SIZE_MASK) == DELTAS_ARE_WORDS: |
| | deltas = array.array("h") |
| | deltasSize = numDeltasInRun * 2 |
| | else: |
| | deltas = array.array("b") |
| | deltasSize = numDeltasInRun |
| | deltas.frombytes(data[pos : pos + deltasSize]) |
| | if sys.byteorder != "big": |
| | deltas.byteswap() |
| | assert len(deltas) == numDeltasInRun, (len(deltas), numDeltasInRun) |
| | pos += deltasSize |
| | result.extend(deltas) |
| | assert numDeltas is None or len(result) == numDeltas |
| | return (result, pos) |
| |
|
| | @staticmethod |
| | def getTupleSize_(flags, axisCount): |
| | size = 4 |
| | if (flags & EMBEDDED_PEAK_TUPLE) != 0: |
| | size += axisCount * 2 |
| | if (flags & INTERMEDIATE_REGION) != 0: |
| | size += axisCount * 4 |
| | return size |
| |
|
| | def getCoordWidth(self): |
| | """Return 2 if coordinates are (x, y) as in gvar, 1 if single values |
| | as in cvar, or 0 if empty. |
| | """ |
| | firstDelta = next((c for c in self.coordinates if c is not None), None) |
| | if firstDelta is None: |
| | return 0 |
| | if type(firstDelta) in (int, float): |
| | return 1 |
| | if type(firstDelta) is tuple and len(firstDelta) == 2: |
| | return 2 |
| | raise TypeError( |
| | "invalid type of delta; expected (int or float) number, or " |
| | "Tuple[number, number]: %r" % firstDelta |
| | ) |
| |
|
| | def scaleDeltas(self, scalar): |
| | if scalar == 1.0: |
| | return |
| | coordWidth = self.getCoordWidth() |
| | self.coordinates = [ |
| | ( |
| | None |
| | if d is None |
| | else d * scalar if coordWidth == 1 else (d[0] * scalar, d[1] * scalar) |
| | ) |
| | for d in self.coordinates |
| | ] |
| |
|
| | def roundDeltas(self): |
| | coordWidth = self.getCoordWidth() |
| | self.coordinates = [ |
| | ( |
| | None |
| | if d is None |
| | else otRound(d) if coordWidth == 1 else (otRound(d[0]), otRound(d[1])) |
| | ) |
| | for d in self.coordinates |
| | ] |
| |
|
| | def calcInferredDeltas(self, origCoords, endPts): |
| | from fontTools.varLib.iup import iup_delta |
| |
|
| | if self.getCoordWidth() == 1: |
| | raise TypeError("Only 'gvar' TupleVariation can have inferred deltas") |
| | if None in self.coordinates: |
| | if len(self.coordinates) != len(origCoords): |
| | raise ValueError( |
| | "Expected len(origCoords) == %d; found %d" |
| | % (len(self.coordinates), len(origCoords)) |
| | ) |
| | self.coordinates = iup_delta(self.coordinates, origCoords, endPts) |
| |
|
| | def optimize(self, origCoords, endPts, tolerance=0.5, isComposite=False): |
| | from fontTools.varLib.iup import iup_delta_optimize |
| |
|
| | if None in self.coordinates: |
| | return |
| |
|
| | deltaOpt = iup_delta_optimize( |
| | self.coordinates, origCoords, endPts, tolerance=tolerance |
| | ) |
| | if None in deltaOpt: |
| | if isComposite and all(d is None for d in deltaOpt): |
| | |
| | |
| | deltaOpt = [(0, 0)] + [None] * (len(deltaOpt) - 1) |
| | |
| | varOpt = TupleVariation(self.axes, deltaOpt) |
| |
|
| | |
| | axisTags = sorted(self.axes.keys()) |
| | tupleData, auxData = self.compile(axisTags) |
| | unoptimizedLength = len(tupleData) + len(auxData) |
| | tupleData, auxData = varOpt.compile(axisTags) |
| | optimizedLength = len(tupleData) + len(auxData) |
| |
|
| | if optimizedLength < unoptimizedLength: |
| | self.coordinates = varOpt.coordinates |
| |
|
| | def __imul__(self, scalar): |
| | self.scaleDeltas(scalar) |
| | return self |
| |
|
| | def __iadd__(self, other): |
| | if not isinstance(other, TupleVariation): |
| | return NotImplemented |
| | deltas1 = self.coordinates |
| | length = len(deltas1) |
| | deltas2 = other.coordinates |
| | if len(deltas2) != length: |
| | raise ValueError("cannot sum TupleVariation deltas with different lengths") |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | if self.getCoordWidth() == 2: |
| | for i, d2 in zip(range(length), deltas2): |
| | d1 = deltas1[i] |
| | try: |
| | deltas1[i] = (d1[0] + d2[0], d1[1] + d2[1]) |
| | except TypeError: |
| | raise ValueError("cannot sum gvar deltas with inferred points") |
| | else: |
| | for i, d2 in zip(range(length), deltas2): |
| | d1 = deltas1[i] |
| | if d1 is not None and d2 is not None: |
| | deltas1[i] = d1 + d2 |
| | elif d1 is None and d2 is not None: |
| | deltas1[i] = d2 |
| | |
| | return self |
| |
|
| |
|
| | def decompileSharedTuples(axisTags, sharedTupleCount, data, offset): |
| | result = [] |
| | for _ in range(sharedTupleCount): |
| | t, offset = TupleVariation.decompileCoord_(axisTags, data, offset) |
| | result.append(t) |
| | return result |
| |
|
| |
|
| | def compileSharedTuples( |
| | axisTags, variations, MAX_NUM_SHARED_COORDS=TUPLE_INDEX_MASK + 1 |
| | ): |
| | coordCount = Counter() |
| | for var in variations: |
| | coord = var.compileCoord(axisTags) |
| | coordCount[coord] += 1 |
| | |
| | |
| | sharedCoords = sorted( |
| | coordCount.most_common(MAX_NUM_SHARED_COORDS), |
| | key=lambda item: (-item[1], item[0]), |
| | ) |
| | return [c[0] for c in sharedCoords if c[1] > 1] |
| |
|
| |
|
| | def compileTupleVariationStore( |
| | variations, pointCount, axisTags, sharedTupleIndices, useSharedPoints=True |
| | ): |
| | |
| | del pointCount |
| | newVariations = [] |
| | pointDatas = [] |
| | |
| | sharedPoints = None |
| |
|
| | |
| | pointSetCount = defaultdict(int) |
| | for v in variations: |
| | points = v.getUsedPoints() |
| | if points is None: |
| | continue |
| | pointSetCount[points] += 1 |
| | newVariations.append(v) |
| | pointDatas.append(points) |
| | variations = newVariations |
| | del newVariations |
| |
|
| | if not variations: |
| | return (0, b"", b"") |
| |
|
| | n = len(variations[0].coordinates) |
| | assert all( |
| | len(v.coordinates) == n for v in variations |
| | ), "Variation sets have different sizes" |
| |
|
| | compiledPoints = { |
| | pointSet: TupleVariation.compilePoints(pointSet) for pointSet in pointSetCount |
| | } |
| |
|
| | tupleVariationCount = len(variations) |
| | tuples = [] |
| | data = [] |
| |
|
| | if useSharedPoints: |
| | |
| | def key(pn): |
| | pointSet = pn[0] |
| | count = pn[1] |
| | return len(compiledPoints[pointSet]) * (count - 1) |
| |
|
| | sharedPoints = max(pointSetCount.items(), key=key)[0] |
| |
|
| | data.append(compiledPoints[sharedPoints]) |
| | tupleVariationCount |= TUPLES_SHARE_POINT_NUMBERS |
| |
|
| | |
| | pointDatas = [ |
| | compiledPoints[points] if points != sharedPoints else b"" |
| | for points in pointDatas |
| | ] |
| |
|
| | for v, p in zip(variations, pointDatas): |
| | thisTuple, thisData = v.compile(axisTags, sharedTupleIndices, pointData=p) |
| |
|
| | tuples.append(thisTuple) |
| | data.append(thisData) |
| |
|
| | tuples = b"".join(tuples) |
| | data = b"".join(data) |
| | return tupleVariationCount, tuples, data |
| |
|
| |
|
| | def decompileTupleVariationStore( |
| | tableTag, |
| | axisTags, |
| | tupleVariationCount, |
| | pointCount, |
| | sharedTuples, |
| | data, |
| | pos, |
| | dataPos, |
| | ): |
| | numAxes = len(axisTags) |
| | result = [] |
| | if (tupleVariationCount & TUPLES_SHARE_POINT_NUMBERS) != 0: |
| | sharedPoints, dataPos = TupleVariation.decompilePoints_( |
| | pointCount, data, dataPos, tableTag |
| | ) |
| | else: |
| | sharedPoints = [] |
| | for _ in range(tupleVariationCount & TUPLE_COUNT_MASK): |
| | dataSize, flags = struct.unpack(">HH", data[pos : pos + 4]) |
| | tupleSize = TupleVariation.getTupleSize_(flags, numAxes) |
| | tupleData = data[pos : pos + tupleSize] |
| | pointDeltaData = data[dataPos : dataPos + dataSize] |
| | result.append( |
| | decompileTupleVariation_( |
| | pointCount, |
| | sharedTuples, |
| | sharedPoints, |
| | tableTag, |
| | axisTags, |
| | tupleData, |
| | pointDeltaData, |
| | ) |
| | ) |
| | pos += tupleSize |
| | dataPos += dataSize |
| | return result |
| |
|
| |
|
| | def decompileTupleVariation_( |
| | pointCount, sharedTuples, sharedPoints, tableTag, axisTags, data, tupleData |
| | ): |
| | assert tableTag in ("cvar", "gvar"), tableTag |
| | flags = struct.unpack(">H", data[2:4])[0] |
| | pos = 4 |
| | if (flags & EMBEDDED_PEAK_TUPLE) == 0: |
| | peak = sharedTuples[flags & TUPLE_INDEX_MASK] |
| | else: |
| | peak, pos = TupleVariation.decompileCoord_(axisTags, data, pos) |
| | if (flags & INTERMEDIATE_REGION) != 0: |
| | start, pos = TupleVariation.decompileCoord_(axisTags, data, pos) |
| | end, pos = TupleVariation.decompileCoord_(axisTags, data, pos) |
| | else: |
| | start, end = inferRegion_(peak) |
| | axes = {} |
| | for axis in axisTags: |
| | region = start[axis], peak[axis], end[axis] |
| | if region != (0.0, 0.0, 0.0): |
| | axes[axis] = region |
| | pos = 0 |
| | if (flags & PRIVATE_POINT_NUMBERS) != 0: |
| | points, pos = TupleVariation.decompilePoints_( |
| | pointCount, tupleData, pos, tableTag |
| | ) |
| | else: |
| | points = sharedPoints |
| |
|
| | deltas = [None] * pointCount |
| |
|
| | if tableTag == "cvar": |
| | deltas_cvt, pos = TupleVariation.decompileDeltas_(len(points), tupleData, pos) |
| | for p, delta in zip(points, deltas_cvt): |
| | if 0 <= p < pointCount: |
| | deltas[p] = delta |
| |
|
| | elif tableTag == "gvar": |
| | deltas_x, pos = TupleVariation.decompileDeltas_(len(points), tupleData, pos) |
| | deltas_y, pos = TupleVariation.decompileDeltas_(len(points), tupleData, pos) |
| | for p, x, y in zip(points, deltas_x, deltas_y): |
| | if 0 <= p < pointCount: |
| | deltas[p] = (x, y) |
| |
|
| | return TupleVariation(axes, deltas) |
| |
|
| |
|
| | def inferRegion_(peak): |
| | """Infer start and end for a (non-intermediate) region |
| | |
| | This helper function computes the applicability region for |
| | variation tuples whose INTERMEDIATE_REGION flag is not set in the |
| | TupleVariationHeader structure. Variation tuples apply only to |
| | certain regions of the variation space; outside that region, the |
| | tuple has no effect. To make the binary encoding more compact, |
| | TupleVariationHeaders can omit the intermediateStartTuple and |
| | intermediateEndTuple fields. |
| | """ |
| | start, end = {}, {} |
| | for axis, value in peak.items(): |
| | start[axis] = min(value, 0.0) |
| | end[axis] = max(value, 0.0) |
| | return (start, end) |
| |
|