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[interpolatable] Remove the empirical high-cost error

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This was very empirical and has no theoretical background. Experiment
shows that this is mostly false-positive.
This commit is contained in:
Behdad Esfahbod 2022-03-31 19:37:00 -06:00
parent d0d8039bd3
commit 3a846a5389
1 changed files with 0 additions and 28 deletions
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28
Lib/fontTools/varLib/interpolatable.py
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@ -213,7 +213,6 @@ def test(glyphsets, glyphs=None, names=None):
# points.value is a list of pt,bool where bool is true if on-curve and false if off-curve;
# now check all rotations and mirror-rotations of the contour and build list of isomorphic
# possible starting points.
#print(points.value)
bits = 0
for pt,b in points.value:
bits = (bits << 1) | b
@ -294,23 +293,6 @@ def test(glyphsets, glyphs=None, names=None):
},
)
break
upem = 2048
item_cost = round(
(matching_cost / len(m0) / len(m0[0])) ** 0.5 / upem * 100
)
hist.append(item_cost)
threshold = 7
if item_cost >= threshold:
add_problem(
glyph_name,
{
"type": "high_cost",
"master_1": names[i],
"master_2": names[i + 1],
"value_1": item_cost,
"value_2": threshold,
},
)
for i, (m0, m1) in enumerate(zip(allContourIsomorphisms[:-1], allContourIsomorphisms[1:])):
if not m0:
@ -437,16 +419,6 @@ def main(args=None):
p["master_2"],
)
)
if p["type"] == "high_cost":
print(
" Interpolation has high cost: cost of %s to %s = %i, threshold %i"
% (
p["master_1"],
p["master_2"],
p["value_1"],
p["value_2"],
)
)
if problems:
return problems