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Split off box-splitting/support code to separate function

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This commit is contained in:
Simon Cozens 2021-03-03 10:33:50 +00:00
parent 8c8522560a
commit e9b35d0318
1 changed files with 30 additions and 24 deletions
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54
Lib/fontTools/varLib/models.py
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@ -281,34 +281,18 @@ class VariationModel(object):
def _computeMasterSupports(self, axisPoints):
supports = []
locations = self.locations
# Compute min/max across each axis, use it as total range.
# TODO Take this as input from outside?
minV = {}
maxV = {}
for l in locations:
for k,v in l.items():
minV[k] = min(v, minV.get(k, v))
maxV[k] = max(v, maxV.get(k, v))
for i,loc in enumerate(locations):
box = {}
for axis,locV in loc.items():
if locV > 0:
box[axis] = (0, locV, maxV[axis])
else:
box[axis] = (minV[axis], locV, 0)
locAxes = set(loc.keys())
boxes = self._locationsToBoxes()
for i,box in enumerate(boxes):
locAxes = set(box.keys())
# Walk over previous masters now
for j,m in enumerate(locations[:i]):
for j,prev_box in enumerate(boxes[:i]):
# Master with extra axes do not participte
if not set(m.keys()).issubset(locAxes):
if not set(prev_box.keys()).issubset(locAxes):
continue
# If it's NOT in the current box, it does not participate
relevant = True
for axis, (lower,peak,upper) in box.items():
if axis not in m or not (m[axis] == peak or lower < m[axis] < upper):
if axis not in prev_box or not (prev_box[axis][1] == peak or lower < prev_box[axis][1] < upper):
relevant = False
break
if not relevant:
@ -323,8 +307,8 @@ class VariationModel(object):
bestAxes = {}
bestRatio = -1
for axis in m.keys():
val = m[axis]
for axis in prev_box.keys():
val = prev_box[axis][1]
assert axis in box
lower,locV,upper = box[axis]
newLower, newUpper = lower, upper
@ -349,6 +333,28 @@ class VariationModel(object):
self.supports = supports
self._computeDeltaWeights()
def _locationsToBoxes(self):
locations = self.locations
# Compute min/max across each axis, use it as total range.
# TODO Take this as input from outside?
minV = {}
maxV = {}
for l in locations:
for k,v in l.items():
minV[k] = min(v, minV.get(k, v))
maxV[k] = max(v, maxV.get(k, v))
boxes = []
for i,loc in enumerate(locations):
box = {}
for axis,locV in loc.items():
if locV > 0:
box[axis] = (0, locV, maxV[axis])
else:
box[axis] = (minV[axis], locV, 0)
boxes.append(box)
return boxes
def _computeDeltaWeights(self):
deltaWeights = []
for i,loc in enumerate(self.locations):