def test_nan_threshold_alt():
# test threshold on odd numbers
data = ones((3, 6))
data[0] = nan
data[1, 2:5] = nan
expected = [(0.4, [nan, nan]), (0.5, [1, nan]), (0.7, [1, 1])]
for thresh, exp in expected:
res = _resample(data, xscale=3, yscale=3, thresh=thresh)
assert_array_equal(res, reshape(exp, res.shape))
def test_nan_threshold():
# test threshold based on number of NaNs per averaging tile
data = ones((2, 10))
data[0, 3:] = nan
data[1, 7:] = nan
# key: NaN threshold as a % of pixels, expected result
expected = [(0.0, [1, nan, nan, nan, nan]),
(0.25, [1, nan, nan, nan, nan]),
(0.5, [1, 1, nan, nan, nan]), (0.75, [1, 1, 1, nan, nan]),
(1.0, [1, 1, 1, 1, nan])]
for thresh, exp in expected:
res = _resample(data, xscale=2, yscale=2, thresh=thresh)
assert_array_equal(res, reshape(exp, res.shape))
