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from fontTools.misc.py23 import bytechr, byteord, bytesjoin
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
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.
"""
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) # -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=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) # -0.3 --> -0.3; 0.7 --> 0.0
defaultMaxValue = max(value, 0.0) # -0.3 --> 0.0; 0.7 --> 0.7
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, 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", fl2fi(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", fl2fi(minValue, 14)))
maxCoords.append(struct.pack(">h", fl2fi(maxValue, 14)))
return bytesjoin(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, 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.frombytes(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 TypeError("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', otRound(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', otRound(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.frombytes(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 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 # empty or has no impact
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 # no change
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 # already optimized
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):
# Fix for macOS composites
# https://github.com/fonttools/fonttools/issues/1381
deltaOpt = [(0, 0)] + [None] * (len(deltaOpt) - 1)
# Use "optimized" version only if smaller...
varOpt = TupleVariation(self.axes, deltaOpt)
# Shouldn't matter that this is different from fvar...?
axisTags = sorted(self.axes.keys())
tupleData, auxData, _ = self.compile(axisTags, [], None)
unoptimizedLength = len(tupleData) + len(auxData)
tupleData, auxData, _ = varOpt.compile(axisTags, [], None)
optimizedLength = len(tupleData) + len(auxData)
if optimizedLength < unoptimizedLength:
self.coordinates = varOpt.coordinates
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"
)
# 'None' values have different meanings in gvar vs cvar TupleVariations:
# within the gvar, when deltas are not provided explicitly for some points,
# they need to be inferred; whereas for the 'cvar' table, if deltas are not
# provided for some CVT values, then no adjustments are made (i.e. None == 0).
# Thus, we cannot sum deltas for gvar TupleVariations if they contain
# inferred inferred deltas (the latter need to be computed first using
# 'calcInferredDeltas' method), but we can treat 'None' values in cvar
# deltas as if they are zeros.
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
# elif d2 is None do nothing
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):
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)