b9bca702f6
* Try a set of used points instead of all points when testing whether to share points. * Amend comment, remove unused variable
623 lines
21 KiB
Python
623 lines
21 KiB
Python
from __future__ import print_function, division, absolute_import
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from fontTools.misc.py23 import *
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from fontTools.misc.fixedTools import fixedToFloat, floatToFixed
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from fontTools.misc.textTools import safeEval
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import array
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import io
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import logging
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import struct
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import sys
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# https://www.microsoft.com/typography/otspec/otvarcommonformats.htm
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EMBEDDED_PEAK_TUPLE = 0x8000
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INTERMEDIATE_REGION = 0x4000
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PRIVATE_POINT_NUMBERS = 0x2000
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DELTAS_ARE_ZERO = 0x80
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DELTAS_ARE_WORDS = 0x40
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DELTA_RUN_COUNT_MASK = 0x3f
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POINTS_ARE_WORDS = 0x80
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POINT_RUN_COUNT_MASK = 0x7f
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TUPLES_SHARE_POINT_NUMBERS = 0x8000
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TUPLE_COUNT_MASK = 0x0fff
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TUPLE_INDEX_MASK = 0x0fff
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log = logging.getLogger(__name__)
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class TupleVariation(object):
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def __init__(self, axes, coordinates):
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self.axes = axes.copy()
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self.coordinates = coordinates[:]
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def __repr__(self):
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axes = ",".join(sorted(["%s=%s" % (name, value) for (name, value) in self.axes.items()]))
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return "<TupleVariation %s %s>" % (axes, self.coordinates)
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def __eq__(self, other):
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return self.coordinates == other.coordinates and self.axes == other.axes
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def getUsedPoints(self):
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result = set()
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for i, point in enumerate(self.coordinates):
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if point is not None:
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result.add(i)
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return result
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def hasImpact(self):
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"""Returns True if this TupleVariation has any visible impact.
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If the result is False, the TupleVariation can be omitted from the font
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without making any visible difference.
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"""
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for c in self.coordinates:
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if c is not None:
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return True
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return False
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def toXML(self, writer, axisTags):
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writer.begintag("tuple")
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writer.newline()
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for axis in axisTags:
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value = self.axes.get(axis)
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if value is not None:
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minValue, value, maxValue = (float(v) for v in value)
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defaultMinValue = min(value, 0.0) # -0.3 --> -0.3; 0.7 --> 0.0
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defaultMaxValue = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
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if minValue == defaultMinValue and maxValue == defaultMaxValue:
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writer.simpletag("coord", axis=axis, value=value)
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else:
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writer.simpletag("coord", axis=axis, value=value, min=minValue, max=maxValue)
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writer.newline()
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wrote_any_deltas = False
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for i, delta in enumerate(self.coordinates):
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if type(delta) == tuple and len(delta) == 2:
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writer.simpletag("delta", pt=i, x=delta[0], y=delta[1])
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writer.newline()
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wrote_any_deltas = True
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elif type(delta) == int:
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writer.simpletag("delta", cvt=i, value=delta)
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writer.newline()
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wrote_any_deltas = True
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elif delta is not None:
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log.error("bad delta format")
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writer.comment("bad delta #%d" % i)
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writer.newline()
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wrote_any_deltas = True
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if not wrote_any_deltas:
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writer.comment("no deltas")
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writer.newline()
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writer.endtag("tuple")
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writer.newline()
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def fromXML(self, name, attrs, _content):
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if name == "coord":
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axis = attrs["axis"]
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value = float(attrs["value"])
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defaultMinValue = min(value, 0.0) # -0.3 --> -0.3; 0.7 --> 0.0
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defaultMaxValue = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
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minValue = float(attrs.get("min", defaultMinValue))
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maxValue = float(attrs.get("max", defaultMaxValue))
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self.axes[axis] = (minValue, value, maxValue)
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elif name == "delta":
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if "pt" in attrs:
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point = safeEval(attrs["pt"])
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x = safeEval(attrs["x"])
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y = safeEval(attrs["y"])
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self.coordinates[point] = (x, y)
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elif "cvt" in attrs:
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cvt = safeEval(attrs["cvt"])
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value = safeEval(attrs["value"])
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self.coordinates[cvt] = value
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else:
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log.warning("bad delta format: %s" %
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", ".join(sorted(attrs.keys())))
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def compile(self, axisTags, sharedCoordIndices, sharedPoints):
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tupleData = []
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assert all(tag in axisTags for tag in self.axes.keys()), ("Unknown axis tag found.", self.axes.keys(), axisTags)
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coord = self.compileCoord(axisTags)
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if coord in sharedCoordIndices:
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flags = sharedCoordIndices[coord]
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else:
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flags = EMBEDDED_PEAK_TUPLE
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tupleData.append(coord)
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intermediateCoord = self.compileIntermediateCoord(axisTags)
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if intermediateCoord is not None:
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flags |= INTERMEDIATE_REGION
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tupleData.append(intermediateCoord)
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points = self.getUsedPoints()
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if sharedPoints == points:
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# Only use the shared points if they are identical to the actually used points
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auxData = self.compileDeltas(sharedPoints)
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usesSharedPoints = True
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else:
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flags |= PRIVATE_POINT_NUMBERS
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numPointsInGlyph = len(self.coordinates)
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auxData = self.compilePoints(points, numPointsInGlyph) + self.compileDeltas(points)
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usesSharedPoints = False
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tupleData = struct.pack('>HH', len(auxData), flags) + bytesjoin(tupleData)
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return (tupleData, auxData, usesSharedPoints)
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def compileCoord(self, axisTags):
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result = []
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for axis in axisTags:
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_minValue, value, _maxValue = self.axes.get(axis, (0.0, 0.0, 0.0))
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result.append(struct.pack(">h", floatToFixed(value, 14)))
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return bytesjoin(result)
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def compileIntermediateCoord(self, axisTags):
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needed = False
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for axis in axisTags:
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minValue, value, maxValue = self.axes.get(axis, (0.0, 0.0, 0.0))
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defaultMinValue = min(value, 0.0) # -0.3 --> -0.3; 0.7 --> 0.0
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defaultMaxValue = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
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if (minValue != defaultMinValue) or (maxValue != defaultMaxValue):
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needed = True
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break
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if not needed:
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return None
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minCoords = []
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maxCoords = []
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for axis in axisTags:
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minValue, value, maxValue = self.axes.get(axis, (0.0, 0.0, 0.0))
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minCoords.append(struct.pack(">h", floatToFixed(minValue, 14)))
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maxCoords.append(struct.pack(">h", floatToFixed(maxValue, 14)))
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return bytesjoin(minCoords + maxCoords)
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@staticmethod
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def decompileCoord_(axisTags, data, offset):
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coord = {}
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pos = offset
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for axis in axisTags:
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coord[axis] = fixedToFloat(struct.unpack(">h", data[pos:pos+2])[0], 14)
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pos += 2
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return coord, pos
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@staticmethod
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def compilePoints(points, numPointsInGlyph):
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# If the set consists of all points in the glyph, it gets encoded with
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# a special encoding: a single zero byte.
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if len(points) == numPointsInGlyph:
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return b"\0"
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# In the 'gvar' table, the packing of point numbers is a little surprising.
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# It consists of multiple runs, each being a delta-encoded list of integers.
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# For example, the point set {17, 18, 19, 20, 21, 22, 23} gets encoded as
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# [6, 17, 1, 1, 1, 1, 1, 1]. The first value (6) is the run length minus 1.
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# There are two types of runs, with values being either 8 or 16 bit unsigned
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# integers.
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points = list(points)
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points.sort()
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numPoints = len(points)
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# The binary representation starts with the total number of points in the set,
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# encoded into one or two bytes depending on the value.
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if numPoints < 0x80:
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result = [bytechr(numPoints)]
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else:
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result = [bytechr((numPoints >> 8) | 0x80) + bytechr(numPoints & 0xff)]
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MAX_RUN_LENGTH = 127
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pos = 0
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lastValue = 0
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while pos < numPoints:
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run = io.BytesIO()
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runLength = 0
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useByteEncoding = None
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while pos < numPoints and runLength <= MAX_RUN_LENGTH:
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curValue = points[pos]
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delta = curValue - lastValue
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if useByteEncoding is None:
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useByteEncoding = 0 <= delta <= 0xff
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if useByteEncoding and (delta > 0xff or delta < 0):
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# we need to start a new run (which will not use byte encoding)
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break
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# TODO This never switches back to a byte-encoding from a short-encoding.
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# That's suboptimal.
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if useByteEncoding:
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run.write(bytechr(delta))
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else:
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run.write(bytechr(delta >> 8))
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run.write(bytechr(delta & 0xff))
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lastValue = curValue
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pos += 1
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runLength += 1
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if useByteEncoding:
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runHeader = bytechr(runLength - 1)
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else:
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runHeader = bytechr((runLength - 1) | POINTS_ARE_WORDS)
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result.append(runHeader)
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result.append(run.getvalue())
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return bytesjoin(result)
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@staticmethod
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def decompilePoints_(numPoints, data, offset, tableTag):
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"""(numPoints, data, offset, tableTag) --> ([point1, point2, ...], newOffset)"""
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assert tableTag in ('cvar', 'gvar')
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pos = offset
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numPointsInData = byteord(data[pos])
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pos += 1
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if (numPointsInData & POINTS_ARE_WORDS) != 0:
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numPointsInData = (numPointsInData & POINT_RUN_COUNT_MASK) << 8 | byteord(data[pos])
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pos += 1
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if numPointsInData == 0:
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return (range(numPoints), pos)
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result = []
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while len(result) < numPointsInData:
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runHeader = byteord(data[pos])
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pos += 1
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numPointsInRun = (runHeader & POINT_RUN_COUNT_MASK) + 1
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point = 0
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if (runHeader & POINTS_ARE_WORDS) != 0:
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points = array.array("H")
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pointsSize = numPointsInRun * 2
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else:
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points = array.array("B")
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pointsSize = numPointsInRun
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points.fromstring(data[pos:pos+pointsSize])
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if sys.byteorder != "big":
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points.byteswap()
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assert len(points) == numPointsInRun
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pos += pointsSize
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result.extend(points)
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# Convert relative to absolute
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absolute = []
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current = 0
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for delta in result:
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current += delta
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absolute.append(current)
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result = absolute
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del absolute
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badPoints = {str(p) for p in result if p < 0 or p >= numPoints}
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if badPoints:
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log.warning("point %s out of range in '%s' table" %
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(",".join(sorted(badPoints)), tableTag))
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return (result, pos)
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def compileDeltas(self, points):
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deltaX = []
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deltaY = []
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for p in sorted(list(points)):
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c = self.coordinates[p]
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if type(c) is tuple and len(c) == 2:
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deltaX.append(c[0])
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deltaY.append(c[1])
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elif type(c) is int:
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deltaX.append(c)
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elif c is not None:
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raise ValueError("invalid type of delta: %s" % type(c))
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return self.compileDeltaValues_(deltaX) + self.compileDeltaValues_(deltaY)
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@staticmethod
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def compileDeltaValues_(deltas):
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"""[value1, value2, value3, ...] --> bytestring
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Emits a sequence of runs. Each run starts with a
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byte-sized header whose 6 least significant bits
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(header & 0x3F) indicate how many values are encoded
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in this run. The stored length is the actual length
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minus one; run lengths are thus in the range [1..64].
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If the header byte has its most significant bit (0x80)
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set, all values in this run are zero, and no data
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follows. Otherwise, the header byte is followed by
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((header & 0x3F) + 1) signed values. If (header &
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0x40) is clear, the delta values are stored as signed
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bytes; if (header & 0x40) is set, the delta values are
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signed 16-bit integers.
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""" # Explaining the format because the 'gvar' spec is hard to understand.
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stream = io.BytesIO()
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pos = 0
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while pos < len(deltas):
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value = deltas[pos]
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if value == 0:
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pos = TupleVariation.encodeDeltaRunAsZeroes_(deltas, pos, stream)
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elif value >= -128 and value <= 127:
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pos = TupleVariation.encodeDeltaRunAsBytes_(deltas, pos, stream)
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else:
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pos = TupleVariation.encodeDeltaRunAsWords_(deltas, pos, stream)
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return stream.getvalue()
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@staticmethod
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def encodeDeltaRunAsZeroes_(deltas, offset, stream):
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runLength = 0
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pos = offset
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numDeltas = len(deltas)
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while pos < numDeltas and runLength < 64 and deltas[pos] == 0:
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pos += 1
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runLength += 1
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assert runLength >= 1 and runLength <= 64
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stream.write(bytechr(DELTAS_ARE_ZERO | (runLength - 1)))
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return pos
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@staticmethod
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def encodeDeltaRunAsBytes_(deltas, offset, stream):
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runLength = 0
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pos = offset
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numDeltas = len(deltas)
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while pos < numDeltas and runLength < 64:
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value = deltas[pos]
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if value < -128 or value > 127:
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break
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# Within a byte-encoded run of deltas, a single zero
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# is best stored literally as 0x00 value. However,
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# if are two or more zeroes in a sequence, it is
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# better to start a new run. For example, the sequence
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# of deltas [15, 15, 0, 15, 15] becomes 6 bytes
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# (04 0F 0F 00 0F 0F) when storing the zero value
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# literally, but 7 bytes (01 0F 0F 80 01 0F 0F)
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# when starting a new run.
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if value == 0 and pos+1 < numDeltas and deltas[pos+1] == 0:
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break
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pos += 1
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runLength += 1
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assert runLength >= 1 and runLength <= 64
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stream.write(bytechr(runLength - 1))
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for i in range(offset, pos):
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stream.write(struct.pack('b', round(deltas[i])))
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return pos
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@staticmethod
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def encodeDeltaRunAsWords_(deltas, offset, stream):
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runLength = 0
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pos = offset
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numDeltas = len(deltas)
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while pos < numDeltas and runLength < 64:
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value = deltas[pos]
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# Within a word-encoded run of deltas, it is easiest
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# to start a new run (with a different encoding)
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# whenever we encounter a zero value. For example,
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# the sequence [0x6666, 0, 0x7777] needs 7 bytes when
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# storing the zero literally (42 66 66 00 00 77 77),
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# and equally 7 bytes when starting a new run
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# (40 66 66 80 40 77 77).
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if value == 0:
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break
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# Within a word-encoded run of deltas, a single value
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# in the range (-128..127) should be encoded literally
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# because it is more compact. For example, the sequence
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# [0x6666, 2, 0x7777] becomes 7 bytes when storing
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# the value literally (42 66 66 00 02 77 77), but 8 bytes
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# when starting a new run (40 66 66 00 02 40 77 77).
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isByteEncodable = lambda value: value >= -128 and value <= 127
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if isByteEncodable(value) and pos+1 < numDeltas and isByteEncodable(deltas[pos+1]):
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break
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pos += 1
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runLength += 1
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assert runLength >= 1 and runLength <= 64
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stream.write(bytechr(DELTAS_ARE_WORDS | (runLength - 1)))
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for i in range(offset, pos):
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stream.write(struct.pack('>h', round(deltas[i])))
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return pos
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@staticmethod
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def decompileDeltas_(numDeltas, data, offset):
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"""(numDeltas, data, offset) --> ([delta, delta, ...], newOffset)"""
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result = []
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pos = offset
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while len(result) < numDeltas:
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runHeader = byteord(data[pos])
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pos += 1
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numDeltasInRun = (runHeader & DELTA_RUN_COUNT_MASK) + 1
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if (runHeader & DELTAS_ARE_ZERO) != 0:
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result.extend([0] * numDeltasInRun)
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else:
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if (runHeader & DELTAS_ARE_WORDS) != 0:
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deltas = array.array("h")
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deltasSize = numDeltasInRun * 2
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else:
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deltas = array.array("b")
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deltasSize = numDeltasInRun
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deltas.fromstring(data[pos:pos+deltasSize])
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if sys.byteorder != "big":
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deltas.byteswap()
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assert len(deltas) == numDeltasInRun
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pos += deltasSize
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result.extend(deltas)
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assert len(result) == numDeltas
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return (result, pos)
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@staticmethod
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def getTupleSize_(flags, axisCount):
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size = 4
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if (flags & EMBEDDED_PEAK_TUPLE) != 0:
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size += axisCount * 2
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if (flags & INTERMEDIATE_REGION) != 0:
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size += axisCount * 4
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return size
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def decompileSharedTuples(axisTags, sharedTupleCount, data, offset):
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result = []
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for _ in range(sharedTupleCount):
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t, offset = TupleVariation.decompileCoord_(axisTags, data, offset)
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result.append(t)
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return result
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def compileSharedTuples(axisTags, variations):
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coordCount = {}
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for var in variations:
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coord = var.compileCoord(axisTags)
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coordCount[coord] = coordCount.get(coord, 0) + 1
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sharedCoords = [(count, coord)
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for (coord, count) in coordCount.items() if count > 1]
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sharedCoords.sort(reverse=True)
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MAX_NUM_SHARED_COORDS = TUPLE_INDEX_MASK + 1
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sharedCoords = sharedCoords[:MAX_NUM_SHARED_COORDS]
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return [c[1] for c in sharedCoords] # Strip off counts.
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def compileTupleVariationStore(variations, pointCount,
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axisTags, sharedTupleIndices):
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variations = [v for v in variations if v.hasImpact()]
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if len(variations) == 0:
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return (0, b"", b"")
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# Each glyph variation tuples modifies a set of control points. To
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# indicate which exact points are getting modified, a single tuple
|
|
# can either refer to a shared set of points, or the tuple can
|
|
# supply its private point numbers. Because the impact of sharing
|
|
# can be positive (no need for a private point list) or negative
|
|
# (need to supply 0,0 deltas for unused points), it is not obvious
|
|
# how to determine which tuples should take their points from the
|
|
# shared pool versus have their own. Perhaps we should resort to
|
|
# brute force, and try all combinations? However, if a glyph has n
|
|
# variation tuples, we would need to try 2^n combinations (because
|
|
# each tuple may or may not be part of the shared set). How many
|
|
# variations tuples do glyphs have?
|
|
#
|
|
# Skia.ttf: {3: 1, 5: 11, 6: 41, 7: 62, 8: 387, 13: 1, 14: 3}
|
|
# JamRegular.ttf: {3: 13, 4: 122, 5: 1, 7: 4, 8: 1, 9: 1, 10: 1}
|
|
# BuffaloGalRegular.ttf: {1: 16, 2: 13, 4: 2, 5: 4, 6: 19, 7: 1, 8: 3, 9: 8}
|
|
# (Reading example: In Skia.ttf, 41 glyphs have 6 variation tuples).
|
|
#
|
|
|
|
# Is this even worth optimizing? If we never use a shared point
|
|
# list, the private lists will consume 112K for Skia, 5K for
|
|
# BuffaloGalRegular, and 15K for JamRegular. If we always use a
|
|
# shared point list, the shared lists will consume 16K for Skia,
|
|
# 3K for BuffaloGalRegular, and 10K for JamRegular. However, in
|
|
# the latter case the delta arrays will become larger, but I
|
|
# haven't yet measured by how much. From gut feeling (which may be
|
|
# wrong), the optimum is to share some but not all points;
|
|
# however, then we would need to try all combinations.
|
|
#
|
|
# For the time being, we try two variants and then pick the better one:
|
|
# (a) each tuple supplies its own private set of points;
|
|
# (b) all tuples refer to a shared set of points, which consists of
|
|
# "every control point in the glyph that has explicit deltas".
|
|
usedPoints = set()
|
|
for v in variations:
|
|
usedPoints |= v.getUsedPoints()
|
|
tuples = []
|
|
data = []
|
|
someTuplesSharePoints = False
|
|
sharedPointVariation = None # To keep track of a variation that uses shared points
|
|
for v in variations:
|
|
privateTuple, privateData, _ = v.compile(
|
|
axisTags, sharedTupleIndices, sharedPoints=None)
|
|
sharedTuple, sharedData, usesSharedPoints = v.compile(
|
|
axisTags, sharedTupleIndices, sharedPoints=usedPoints)
|
|
if (len(sharedTuple) + len(sharedData)) < (len(privateTuple) + len(privateData)):
|
|
tuples.append(sharedTuple)
|
|
data.append(sharedData)
|
|
someTuplesSharePoints |= usesSharedPoints
|
|
sharedPointVariation = v
|
|
else:
|
|
tuples.append(privateTuple)
|
|
data.append(privateData)
|
|
if someTuplesSharePoints:
|
|
# Use the last of the variations that share points for compiling the packed point data
|
|
data = sharedPointVariation.compilePoints(usedPoints, len(sharedPointVariation.coordinates)) + bytesjoin(data)
|
|
tupleVariationCount = TUPLES_SHARE_POINT_NUMBERS | len(tuples)
|
|
else:
|
|
data = bytesjoin(data)
|
|
tupleVariationCount = len(tuples)
|
|
tuples = bytesjoin(tuples)
|
|
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) # -0.3 --> -0.3; 0.7 --> 0.0
|
|
end[axis] = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
|
|
return (start, end)
|