path: root/Lib/fontTools/ttLib/tables/TupleVariation.py

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)