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[CFF] Fixups for width module

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This commit is contained in:
Behdad Esfahbod 2018-02-08 22:15:03 -06:00
parent a70bca61fe
commit 0394016ba9
1 changed files with 9 additions and 7 deletions
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16
Lib/fontTools/cffLib/width.py
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@ -90,8 +90,10 @@ def optimizeWidthsBruteforce(widths):
def optimizeWidths(widths): def optimizeWidths(widths):
"""Given a list of glyph widths, or dictionary mapping glyph width to number of glyphs having that, """Given a list of glyph widths, or dictionary mapping glyph width to number of
returns a tuple of best CFF default and nominal glyph widths.""" glyphs having that, returns a tuple of best CFF default and nominal glyph widths.
This algorithm is linear in UPEM+numGlyphs."""
if not hasattr(widths, 'items'): if not hasattr(widths, 'items'):
d = defaultdict(int) d = defaultdict(int)
@ -110,13 +112,13 @@ def optimizeWidths(widths):
cumMaxD = cumSum(widths, op=max, decreasing=True) cumMaxD = cumSum(widths, op=max, decreasing=True)
# Cost per nominal choice, without default consideration. # Cost per nominal choice, without default consideration.
nomnCostU = missingdict(lambda x: cumFrqU[x] + cumFrqU[x-108] + cumFrqU[x-1131]*3) nomnCostU = missingdict(lambda x: cumFrqU[x] + cumFrqU[x-108] + cumFrqU[x-1132]*3)
nomnCostD = missingdict(lambda x: cumFrqD[x] + cumFrqD[x+108] + cumFrqD[x+1131]*3) nomnCostD = missingdict(lambda x: cumFrqD[x] + cumFrqD[x+108] + cumFrqD[x+1132]*3)
nomnCost = missingdict(lambda x: nomnCostU[x] + nomnCostD[x]) nomnCost = missingdict(lambda x: nomnCostU[x] + nomnCostD[x] - widths[x])
# Cost-saving per nominal choice, by best default choice. # Cost-saving per nominal choice, by best default choice.
dfltCostU = missingdict(lambda x: max(cumMaxU[x], cumMaxU[x-108]*2, cumMaxU[x-1131]*5)) dfltCostU = missingdict(lambda x: max(cumMaxU[x], cumMaxU[x-108]*2, cumMaxU[x-1132]*5))
dfltCostD = missingdict(lambda x: max(cumMaxD[x], cumMaxD[x+108]*2, cumMaxD[x+1131]*5)) dfltCostD = missingdict(lambda x: max(cumMaxD[x], cumMaxD[x+108]*2, cumMaxD[x+1132]*5))
dfltCost = missingdict(lambda x: max(dfltCostU[x], dfltCostD[x])) dfltCost = missingdict(lambda x: max(dfltCostU[x], dfltCostD[x]))
# Combined cost per nominal choice. # Combined cost per nominal choice.