blob: b94cfd4b4741653a0f875c48a90aa869f0910ac7 [file] [log] [blame]
from __future__ import print_function, division, absolute_import
from fontTools.misc.py23 import *
from fontTools.misc.fixedTools import fixedToFloat, floatToFixed
from fontTools.misc.textTools import safeEval
import array
import io
import logging
import struct
import sys
# https://www.microsoft.com/typography/otspec/otvarcommonformats.htm
EMBEDDED_PEAK_TUPLE = 0x8000
INTERMEDIATE_REGION = 0x4000
PRIVATE_POINT_NUMBERS = 0x2000
DELTAS_ARE_ZERO = 0x80
DELTAS_ARE_WORDS = 0x40
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 = 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):
result = set()
for i, point in enumerate(self.coordinates):
if point is not None:
result.add(i)
return result
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.
"""
for c in self.coordinates:
if c is not None:
return True
return False
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 = (float(v) for v in value)
defaultMinValue = min(value, 0.0) # -0.3 --> -0.3; 0.7 --> 0.0
defaultMaxValue = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
if minValue == defaultMinValue and maxValue == defaultMaxValue:
writer.simpletag("coord", axis=axis, value=value)
else:
writer.simpletag("coord", axis=axis, value=value, min=minValue, max=maxValue)
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 = float(attrs["value"])
defaultMinValue = min(value, 0.0) # -0.3 --> -0.3; 0.7 --> 0.0
defaultMaxValue = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
minValue = float(attrs.get("min", defaultMinValue))
maxValue = float(attrs.get("max", defaultMaxValue))
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, sharedPoints):
tupleData = []
assert all(tag in axisTags for tag in self.axes.keys()), ("Unknown axis tag found.", self.axes.keys(), axisTags)
coord = self.compileCoord(axisTags)
if coord in sharedCoordIndices:
flags = sharedCoordIndices[coord]
else:
flags = EMBEDDED_PEAK_TUPLE
tupleData.append(coord)
intermediateCoord = self.compileIntermediateCoord(axisTags)
if intermediateCoord is not None:
flags |= INTERMEDIATE_REGION
tupleData.append(intermediateCoord)
points = self.getUsedPoints()
if sharedPoints == points:
# Only use the shared points if they are identical to the actually used points
auxData = self.compileDeltas(sharedPoints)
usesSharedPoints = True
else:
flags |= PRIVATE_POINT_NUMBERS
numPointsInGlyph = len(self.coordinates)
auxData = self.compilePoints(points, numPointsInGlyph) + self.compileDeltas(points)
usesSharedPoints = False
tupleData = struct.pack('>HH', len(auxData), flags) + bytesjoin(tupleData)
return (tupleData, auxData, usesSharedPoints)
def compileCoord(self, axisTags):
result = []
for axis in axisTags:
_minValue, value, _maxValue = self.axes.get(axis, (0.0, 0.0, 0.0))
result.append(struct.pack(">h", floatToFixed(value, 14)))
return bytesjoin(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) # -0.3 --> -0.3; 0.7 --> 0.0
defaultMaxValue = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
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", floatToFixed(minValue, 14)))
maxCoords.append(struct.pack(">h", floatToFixed(maxValue, 14)))
return bytesjoin(minCoords + maxCoords)
@staticmethod
def decompileCoord_(axisTags, data, offset):
coord = {}
pos = offset
for axis in axisTags:
coord[axis] = fixedToFloat(struct.unpack(">h", data[pos:pos+2])[0], 14)
pos += 2
return coord, pos
@staticmethod
def compilePoints(points, numPointsInGlyph):
# If the set consists of all points in the glyph, it gets encoded with
# a special encoding: a single zero byte.
if len(points) == numPointsInGlyph:
return b"\0"
# In the 'gvar' table, the packing of point numbers is a little surprising.
# It consists of multiple runs, each being a delta-encoded list of integers.
# For example, the point set {17, 18, 19, 20, 21, 22, 23} gets encoded as
# [6, 17, 1, 1, 1, 1, 1, 1]. The first value (6) is the run length minus 1.
# There are two types of runs, with values being either 8 or 16 bit unsigned
# integers.
points = list(points)
points.sort()
numPoints = len(points)
# The binary representation starts with the total number of points in the set,
# encoded into one or two bytes depending on the value.
if numPoints < 0x80:
result = [bytechr(numPoints)]
else:
result = [bytechr((numPoints >> 8) | 0x80) + bytechr(numPoints & 0xff)]
MAX_RUN_LENGTH = 127
pos = 0
lastValue = 0
while pos < numPoints:
run = io.BytesIO()
runLength = 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):
# we need to start a new run (which will not use byte encoding)
break
# TODO This never switches back to a byte-encoding from a short-encoding.
# That's suboptimal.
if useByteEncoding:
run.write(bytechr(delta))
else:
run.write(bytechr(delta >> 8))
run.write(bytechr(delta & 0xff))
lastValue = curValue
pos += 1
runLength += 1
if useByteEncoding:
runHeader = bytechr(runLength - 1)
else:
runHeader = bytechr((runLength - 1) | POINTS_ARE_WORDS)
result.append(runHeader)
result.append(run.getvalue())
return bytesjoin(result)
@staticmethod
def decompilePoints_(numPoints, data, offset, tableTag):
"""(numPoints, data, offset, tableTag) --> ([point1, point2, ...], newOffset)"""
assert tableTag in ('cvar', 'gvar')
pos = offset
numPointsInData = byteord(data[pos])
pos += 1
if (numPointsInData & POINTS_ARE_WORDS) != 0:
numPointsInData = (numPointsInData & POINT_RUN_COUNT_MASK) << 8 | byteord(data[pos])
pos += 1
if numPointsInData == 0:
return (range(numPoints), pos)
result = []
while len(result) < numPointsInData:
runHeader = byteord(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.fromstring(data[pos:pos+pointsSize])
if sys.byteorder != "big":
points.byteswap()
assert len(points) == numPointsInRun
pos += pointsSize
result.extend(points)
# Convert relative to absolute
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, points):
deltaX = []
deltaY = []
for p in sorted(list(points)):
c = self.coordinates[p]
if type(c) is tuple and len(c) == 2:
deltaX.append(c[0])
deltaY.append(c[1])
elif type(c) is int:
deltaX.append(c)
elif c is not None:
raise ValueError("invalid type of delta: %s" % type(c))
return self.compileDeltaValues_(deltaX) + self.compileDeltaValues_(deltaY)
@staticmethod
def compileDeltaValues_(deltas):
"""[value1, value2, value3, ...] --> bytestring
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.
""" # Explaining the format because the 'gvar' spec is hard to understand.
stream = io.BytesIO()
pos = 0
while pos < len(deltas):
value = deltas[pos]
if value == 0:
pos = TupleVariation.encodeDeltaRunAsZeroes_(deltas, pos, stream)
elif value >= -128 and value <= 127:
pos = TupleVariation.encodeDeltaRunAsBytes_(deltas, pos, stream)
else:
pos = TupleVariation.encodeDeltaRunAsWords_(deltas, pos, stream)
return stream.getvalue()
@staticmethod
def encodeDeltaRunAsZeroes_(deltas, offset, stream):
runLength = 0
pos = offset
numDeltas = len(deltas)
while pos < numDeltas and runLength < 64 and deltas[pos] == 0:
pos += 1
runLength += 1
assert runLength >= 1 and runLength <= 64
stream.write(bytechr(DELTAS_ARE_ZERO | (runLength - 1)))
return pos
@staticmethod
def encodeDeltaRunAsBytes_(deltas, offset, stream):
runLength = 0
pos = offset
numDeltas = len(deltas)
while pos < numDeltas and runLength < 64:
value = deltas[pos]
if value < -128 or value > 127:
break
# Within a byte-encoded run of deltas, a single zero
# is best stored literally as 0x00 value. However,
# if are two or more zeroes in a sequence, it is
# better to start a new run. For example, the sequence
# of deltas [15, 15, 0, 15, 15] becomes 6 bytes
# (04 0F 0F 00 0F 0F) when storing the zero value
# literally, but 7 bytes (01 0F 0F 80 01 0F 0F)
# when starting a new run.
if value == 0 and pos+1 < numDeltas and deltas[pos+1] == 0:
break
pos += 1
runLength += 1
assert runLength >= 1 and runLength <= 64
stream.write(bytechr(runLength - 1))
for i in range(offset, pos):
stream.write(struct.pack('b', round(deltas[i])))
return pos
@staticmethod
def encodeDeltaRunAsWords_(deltas, offset, stream):
runLength = 0
pos = offset
numDeltas = len(deltas)
while pos < numDeltas and runLength < 64:
value = deltas[pos]
# Within a word-encoded run of deltas, it is easiest
# to start a new run (with a different encoding)
# whenever we encounter a zero value. For example,
# the sequence [0x6666, 0, 0x7777] needs 7 bytes when
# storing the zero literally (42 66 66 00 00 77 77),
# and equally 7 bytes when starting a new run
# (40 66 66 80 40 77 77).
if value == 0:
break
# Within a word-encoded run of deltas, a single value
# in the range (-128..127) should be encoded literally
# because it is more compact. For example, the sequence
# [0x6666, 2, 0x7777] becomes 7 bytes when storing
# the value literally (42 66 66 00 02 77 77), but 8 bytes
# when starting a new run (40 66 66 00 02 40 77 77).
isByteEncodable = lambda value: value >= -128 and value <= 127
if isByteEncodable(value) and pos+1 < numDeltas and isByteEncodable(deltas[pos+1]):
break
pos += 1
runLength += 1
assert runLength >= 1 and runLength <= 64
stream.write(bytechr(DELTAS_ARE_WORDS | (runLength - 1)))
for i in range(offset, pos):
stream.write(struct.pack('>h', round(deltas[i])))
return pos
@staticmethod
def decompileDeltas_(numDeltas, data, offset):
"""(numDeltas, data, offset) --> ([delta, delta, ...], newOffset)"""
result = []
pos = offset
while len(result) < numDeltas:
runHeader = byteord(data[pos])
pos += 1
numDeltasInRun = (runHeader & DELTA_RUN_COUNT_MASK) + 1
if (runHeader & DELTAS_ARE_ZERO) != 0:
result.extend([0] * numDeltasInRun)
else:
if (runHeader & DELTAS_ARE_WORDS) != 0:
deltas = array.array("h")
deltasSize = numDeltasInRun * 2
else:
deltas = array.array("b")
deltasSize = numDeltasInRun
deltas.fromstring(data[pos:pos+deltasSize])
if sys.byteorder != "big":
deltas.byteswap()
assert len(deltas) == numDeltasInRun
pos += deltasSize
result.extend(deltas)
assert 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 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):
coordCount = {}
for var in variations:
coord = var.compileCoord(axisTags)
coordCount[coord] = coordCount.get(coord, 0) + 1
sharedCoords = [(count, coord)
for (coord, count) in coordCount.items() if count > 1]
sharedCoords.sort(reverse=True)
MAX_NUM_SHARED_COORDS = TUPLE_INDEX_MASK + 1
sharedCoords = sharedCoords[:MAX_NUM_SHARED_COORDS]
return [c[1] for c in sharedCoords] # Strip off counts.
def compileTupleVariationStore(variations, pointCount,
axisTags, sharedTupleIndices,
useSharedPoints=True):
variations = [v for v in variations if v.hasImpact()]
if len(variations) == 0:
return (0, b"", b"")
# Each glyph variation tuples modifies a set of control points. To
# 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 useSharedPoints and (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)