0811834b3c
not only base should be at 0, but min/max respectively at -1.0 and +1.0. that's how varLib constructs models internally, so update test case to reflect that
157 lines
5.5 KiB
Python
157 lines
5.5 KiB
Python
from __future__ import print_function, division, absolute_import
|
|
from fontTools.misc.py23 import *
|
|
from fontTools.varLib.models import (
|
|
normalizeLocation, supportScalar, VariationModel)
|
|
import pytest
|
|
|
|
|
|
def test_normalizeLocation():
|
|
axes = {"wght": (100, 400, 900)}
|
|
assert normalizeLocation({"wght": 400}, axes) == {'wght': 0.0}
|
|
assert normalizeLocation({"wght": 100}, axes) == {'wght': -1.0}
|
|
assert normalizeLocation({"wght": 900}, axes) == {'wght': 1.0}
|
|
assert normalizeLocation({"wght": 650}, axes) == {'wght': 0.5}
|
|
assert normalizeLocation({"wght": 1000}, axes) == {'wght': 1.0}
|
|
assert normalizeLocation({"wght": 0}, axes) == {'wght': -1.0}
|
|
|
|
axes = {"wght": (0, 0, 1000)}
|
|
assert normalizeLocation({"wght": 0}, axes) == {'wght': 0.0}
|
|
assert normalizeLocation({"wght": -1}, axes) == {'wght': 0.0}
|
|
assert normalizeLocation({"wght": 1000}, axes) == {'wght': 1.0}
|
|
assert normalizeLocation({"wght": 500}, axes) == {'wght': 0.5}
|
|
assert normalizeLocation({"wght": 1001}, axes) == {'wght': 1.0}
|
|
|
|
axes = {"wght": (0, 1000, 1000)}
|
|
assert normalizeLocation({"wght": 0}, axes) == {'wght': -1.0}
|
|
assert normalizeLocation({"wght": -1}, axes) == {'wght': -1.0}
|
|
assert normalizeLocation({"wght": 500}, axes) == {'wght': -0.5}
|
|
assert normalizeLocation({"wght": 1000}, axes) == {'wght': 0.0}
|
|
assert normalizeLocation({"wght": 1001}, axes) == {'wght': 0.0}
|
|
|
|
|
|
def test_supportScalar():
|
|
assert supportScalar({}, {}) == 1.0
|
|
assert supportScalar({'wght':.2}, {}) == 1.0
|
|
assert supportScalar({'wght':.2}, {'wght':(0,2,3)}) == 0.1
|
|
assert supportScalar({'wght':2.5}, {'wght':(0,2,4)}) == 0.75
|
|
|
|
|
|
class VariationModelTest(object):
|
|
|
|
@pytest.mark.parametrize(
|
|
"locations, axisOrder, sortedLocs, supports, deltaWeights",
|
|
[
|
|
(
|
|
[
|
|
{'wght': 0.55},
|
|
{'wght': -0.55},
|
|
{'wght': -1.0},
|
|
{'wdth': 1.0},
|
|
{'wght': 0.66, 'wdth': 1.0},
|
|
{'wght': 0.66, 'wdth': 0.66},
|
|
{},
|
|
{'wght': 1.0, 'wdth': 1.0},
|
|
{'wght': 1.0},
|
|
],
|
|
["wght"],
|
|
[
|
|
{},
|
|
{'wght': -0.55},
|
|
{'wght': -1.0},
|
|
{'wght': 0.55},
|
|
{'wght': 1.0},
|
|
{'wdth': 1.0},
|
|
{'wdth': 1.0, 'wght': 1.0},
|
|
{'wdth': 1.0, 'wght': 0.66},
|
|
{'wdth': 0.66, 'wght': 0.66}
|
|
],
|
|
[
|
|
{},
|
|
{'wght': (-1.0, -0.55, 0)},
|
|
{'wght': (-1.0, -1.0, -0.55)},
|
|
{'wght': (0, 0.55, 1.0)},
|
|
{'wght': (0.55, 1.0, 1.0)},
|
|
{'wdth': (0, 1.0, 1.0)},
|
|
{'wdth': (0, 1.0, 1.0), 'wght': (0, 1.0, 1.0)},
|
|
{'wdth': (0, 1.0, 1.0), 'wght': (0, 0.66, 1.0)},
|
|
{'wdth': (0, 0.66, 1.0), 'wght': (0, 0.66, 1.0)}
|
|
],
|
|
[
|
|
{},
|
|
{0: 1.0},
|
|
{0: 1.0},
|
|
{0: 1.0},
|
|
{0: 1.0},
|
|
{0: 1.0},
|
|
{0: 1.0,
|
|
4: 1.0,
|
|
5: 1.0},
|
|
{0: 1.0,
|
|
3: 0.7555555555555555,
|
|
4: 0.24444444444444444,
|
|
5: 1.0,
|
|
6: 0.66},
|
|
{0: 1.0,
|
|
3: 0.7555555555555555,
|
|
4: 0.24444444444444444,
|
|
5: 0.66,
|
|
6: 0.43560000000000006,
|
|
7: 0.66}
|
|
]
|
|
),
|
|
(
|
|
[
|
|
{},
|
|
{'bar': 0.5},
|
|
{'bar': 1.0},
|
|
{'foo': 1.0},
|
|
{'bar': 0.5, 'foo': 1.0},
|
|
{'bar': 1.0, 'foo': 1.0},
|
|
],
|
|
None,
|
|
[
|
|
{},
|
|
{'bar': 0.5},
|
|
{'bar': 1.0},
|
|
{'foo': 1.0},
|
|
{'bar': 0.5, 'foo': 1.0},
|
|
{'bar': 1.0, 'foo': 1.0},
|
|
],
|
|
[
|
|
{},
|
|
{'bar': (0, 0.5, 1.0)},
|
|
{'bar': (0.5, 1.0, 1.0)},
|
|
{'foo': (0, 1.0, 1.0)},
|
|
{'bar': (0, 0.5, 1.0), 'foo': (0, 1.0, 1.0)},
|
|
{'bar': (0.5, 1.0, 1.0), 'foo': (0, 1.0, 1.0)},
|
|
],
|
|
[
|
|
{},
|
|
{0: 1.0},
|
|
{0: 1.0},
|
|
{0: 1.0},
|
|
{0: 1.0, 1: 1.0, 3: 1.0},
|
|
{0: 1.0, 2: 1.0, 3: 1.0},
|
|
],
|
|
)
|
|
]
|
|
)
|
|
def test_init(
|
|
self, locations, axisOrder, sortedLocs, supports, deltaWeights
|
|
):
|
|
model = VariationModel(locations, axisOrder=axisOrder)
|
|
|
|
assert model.locations == sortedLocs
|
|
assert model.supports == supports
|
|
assert model.deltaWeights == deltaWeights
|
|
|
|
def test_init_duplicate_locations(self):
|
|
with pytest.raises(ValueError, match="locations must be unique"):
|
|
VariationModel(
|
|
[
|
|
{"foo": 0.0, "bar": 0.0},
|
|
{"foo": 1.0, "bar": 1.0},
|
|
{"bar": 1.0, "foo": 1.0},
|
|
]
|
|
)
|