Revert "[varLib.models] Generate narrower tents"
This reverts commit 688939394b8cae3b2a0d5747e435cbd828a14531.
This commit is contained in:
Cosimo Lupo
parent
5284ac3c58
commit
f5933c1cfa
@ -9,7 +9,6 @@ __all__ = [
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from fontTools.misc.roundTools import noRound
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from fontTools.misc.roundTools import noRound
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from .errors import VariationModelError
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from .errors import VariationModelError
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from collections import defaultdict
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def nonNone(lst):
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def nonNone(lst):
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@ -225,8 +224,13 @@ class VariationModel(object):
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0, 4: 1.0, 5: 1.0},
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{0: 1.0, 4: 1.0, 5: 1.0},
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{0: 1.0, 3: 0.75, 4: 0.25, 5: 1.0},
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{0: 1.0, 3: 0.75, 4: 0.25, 5: 1.0, 6: 0.6666666666666666},
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{0: 1.0, 3: 0.75, 4: 0.25, 5: 0.6666666666666667}]
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{0: 1.0,
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3: 0.75,
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4: 0.25,
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5: 0.6666666666666667,
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6: 0.4444444444444445,
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7: 0.6666666666666667}]
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"""
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"""
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def __init__(self, locations, axisOrder=None, extrapolate=False):
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def __init__(self, locations, axisOrder=None, extrapolate=False):
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@ -385,48 +389,23 @@ class VariationModel(object):
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def _locationsToRegions(self):
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def _locationsToRegions(self):
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locations = self.locations
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locations = self.locations
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# Compute min/max across each axis, use it as total range.
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# Compute min/max across each axis, use it as total range.
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# TODO Take this as input from outside?
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minV = {}
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minV = {}
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maxV = {}
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maxV = {}
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axes = set()
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for l in locations:
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for l in locations:
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for axis in l.keys():
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for k, v in l.items():
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axes.add(axis)
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minV[k] = min(v, minV.get(k, v))
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for axis in axes:
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maxV[k] = max(v, maxV.get(k, v))
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minV[axis] = 0.0
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maxV[axis] = 0.0
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for l in locations:
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for axis, v in l.items():
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minV[axis] = min(v, minV.get(axis, v))
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maxV[axis] = max(v, maxV.get(axis, v))
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axisPoints = defaultdict(lambda: defaultdict(lambda: {0.0}))
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for loc in locations:
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for axis, value in loc.items():
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offAxisLoc = loc.copy()
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offAxisLoc.pop(axis)
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offAxisLoc = tuple(sorted(offAxisLoc.items()))
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axisPoints[axis][offAxisLoc].add(value)
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regions = []
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regions = []
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for loc in locations:
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for loc in locations:
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region = {}
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region = {}
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for axis, peak in loc.items():
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for axis, locV in loc.items():
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assert peak != 0
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if locV > 0:
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region[axis] = (0, locV, maxV[axis])
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offAxisLoc = loc.copy()
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else:
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offAxisLoc.pop(axis)
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region[axis] = (minV[axis], locV, 0)
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offAxisLoc = tuple(sorted(offAxisLoc.items()))
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points = axisPoints[axis][offAxisLoc]
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points.add(minV[axis])
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points.add(maxV[axis])
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points = sorted(points)
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peakIndex = points.index(peak)
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lower = peak if peakIndex == 0 else points[peakIndex - 1]
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upper = peak if peakIndex == len(points) - 1 else points[peakIndex + 1]
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region[axis] = (lower, peak, upper)
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regions.append(region)
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regions.append(region)
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return regions
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return regions
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File diff suppressed because it is too large
Load Diff
@ -39,7 +39,7 @@ def test_supportScalar():
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assert supportScalar({"wght": 4}, {"wght": (0, 2, 2)}) == 0.0
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assert supportScalar({"wght": 4}, {"wght": (0, 2, 2)}) == 0.0
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assert supportScalar({"wght": 4}, {"wght": (0, 2, 2)}, extrapolate=True) == 2.0
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assert supportScalar({"wght": 4}, {"wght": (0, 2, 2)}, extrapolate=True) == 2.0
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assert supportScalar({"wght": 4}, {"wght": (0, 2, 3)}, extrapolate=True) == 2.0
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assert supportScalar({"wght": 4}, {"wght": (0, 2, 3)}, extrapolate=True) == 2.0
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assert supportScalar({"wght": 2}, {"wght": (0, .75, 1)}, extrapolate=True) == -4.0
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assert supportScalar({"wght": 2}, {"wght": (0, 0.75, 1)}, extrapolate=True) == -4.0
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@pytest.mark.parametrize(
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@pytest.mark.parametrize(
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@ -112,8 +112,8 @@ class VariationModelTest(object):
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{"wght": (0, 0.55, 1.0)},
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{"wght": (0, 0.55, 1.0)},
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{"wght": (0.55, 1.0, 1.0)},
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{"wght": (0.55, 1.0, 1.0)},
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{"wdth": (0, 1.0, 1.0)},
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{"wdth": (0, 1.0, 1.0)},
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{"wdth": (0, 1.0, 1.0), "wght": (0.66, 1.0, 1.0)},
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{"wdth": (0, 1.0, 1.0), "wght": (0, 1.0, 1.0)},
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{"wdth": (0.66, 1.0, 1.0), "wght": (0, 0.66, 1.0)},
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{"wdth": (0, 1.0, 1.0), "wght": (0, 0.66, 1.0)},
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{"wdth": (0, 0.66, 1.0), "wght": (0, 0.66, 1.0)},
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{"wdth": (0, 0.66, 1.0), "wght": (0, 0.66, 1.0)},
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],
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],
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[
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[
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@ -124,8 +124,21 @@ class VariationModelTest(object):
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0, 4: 1.0, 5: 1.0},
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{0: 1.0, 4: 1.0, 5: 1.0},
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{0: 1.0, 3: 0.7555555555555555, 4: 0.24444444444444444, 5: 1.0},
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{
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{0: 1.0, 3: 0.7555555555555555, 4: 0.24444444444444444, 5: 0.66},
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0: 1.0,
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3: 0.7555555555555555,
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4: 0.24444444444444444,
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5: 1.0,
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6: 0.66,
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},
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{
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0: 1.0,
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3: 0.7555555555555555,
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4: 0.24444444444444444,
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5: 0.66,
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6: 0.43560000000000004,
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7: 0.66,
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},
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],
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],
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),
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),
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(
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(
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@ -187,22 +200,22 @@ class VariationModelTest(object):
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],
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],
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[
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[
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{},
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{},
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{"bar": (0.0, 0.25, 0.75)},
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{"bar": (0.0, 0.25, 1.0)},
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{"bar": (0.25, 0.75, 1.0)},
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{"bar": (0.25, 0.75, 1.0)},
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{"bar": (0.75, 1.0, 1.0)},
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{"bar": (0.75, 1.0, 1.0)},
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{"foo": (0.0, 0.25, 0.5)},
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{"foo": (0.0, 0.25, 1.0)},
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{"foo": (0.25, 0.5, 0.75)},
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{"foo": (0.25, 0.5, 1.0)},
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{"foo": (0.5, 0.75, 1.0)},
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{"foo": (0.5, 0.75, 1.0)},
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{"foo": (0.75, 1.0, 1.0)},
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{"foo": (0.75, 1.0, 1.0)},
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],
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],
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[
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[
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{},
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{},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0, 1: 0.3333333333333333},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0, 4: 0.6666666666666666},
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{0: 1.0},
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{0: 1.0, 4: 0.3333333333333333, 5: 0.5},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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],
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],
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),
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),
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@ -230,22 +243,22 @@ class VariationModelTest(object):
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],
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],
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[
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[
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{},
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{},
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{"bar": (0, 0.25, 0.75)},
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{"bar": (0, 0.25, 1.0)},
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{"bar": (0.25, 0.75, 1.0)},
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{"bar": (0.25, 0.75, 1.0)},
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{"bar": (0.75, 1.0, 1.0)},
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{"bar": (0.75, 1.0, 1.0)},
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{"foo": (0, 0.25, 0.5)},
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{"foo": (0, 0.25, 1.0)},
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{"foo": (0.25, 0.5, 0.75)},
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{"foo": (0.25, 0.5, 1.0)},
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{"foo": (0.5, 0.75, 1.0)},
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{"foo": (0.5, 0.75, 1.0)},
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{"foo": (0.75, 1.0, 1.0)},
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{"foo": (0.75, 1.0, 1.0)},
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],
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],
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[
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[
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{},
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{},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0, 1: 0.3333333333333333},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0, 4: 0.6666666666666666},
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{0: 1.0},
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{0: 1.0, 4: 0.3333333333333333, 5: 0.5},
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{0: 1.0},
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{0: 1.0},
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{0: 1.0},
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],
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],
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),
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),
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