libvips/test/test-suite/test_histogram.py
John Cupitt 002b2a28e1 fix test suite
for the new jpg sample image
2019-11-27 11:48:50 +00:00

134 lines
3.3 KiB
Python

# vim: set fileencoding=utf-8 :
import pytest
import pyvips
from helpers import JPEG_FILE
class TestHistogram:
def test_hist_cum(self):
im = pyvips.Image.identity()
sum = im.avg() * 256
cum = im.hist_cum()
p = cum(255, 0)
assert p[0] == sum
def test_hist_equal(self):
im = pyvips.Image.new_from_file(JPEG_FILE)
im2 = im.hist_equal()
assert im.width == im2.width
assert im.height == im2.height
assert im.avg() < im2.avg()
assert im.deviate() < im2.deviate()
def test_hist_ismonotonic(self):
im = pyvips.Image.identity()
assert im.hist_ismonotonic()
def test_hist_local(self):
im = pyvips.Image.new_from_file(JPEG_FILE)
im2 = im.hist_local(10, 10)
assert im.width == im2.width
assert im.height == im2.height
assert im.avg() < im2.avg()
assert im.deviate() < im2.deviate()
if pyvips.at_least_libvips(8, 5):
im3 = im.hist_local(10, 10, max_slope=3)
assert im.width == im3.width
assert im.height == im3.height
assert im3.deviate() < im2.deviate()
def test_hist_match(self):
im = pyvips.Image.identity()
im2 = pyvips.Image.identity()
matched = im.hist_match(im2)
assert (im - matched).abs().max() == 0.0
def test_hist_norm(self):
im = pyvips.Image.identity()
im2 = im.hist_norm()
assert (im - im2).abs().max() == 0.0
def test_hist_plot(self):
im = pyvips.Image.identity()
im2 = im.hist_plot()
assert im2.width == 256
assert im2.height == 256
assert im2.format == pyvips.BandFormat.UCHAR
assert im2.bands == 1
def test_hist_map(self):
im = pyvips.Image.identity()
im2 = im.maplut(im)
assert (im - im2).abs().max() == 0.0
def test_percent(self):
im = pyvips.Image.new_from_file(JPEG_FILE).extract_band(1)
pc = im.percent(90)
msk = im <= pc
n_set = (msk.avg() * msk.width * msk.height) / 255.0
pc_set = 100 * n_set / (msk.width * msk.height)
assert pytest.approx(pc_set, 0.5) == 90
def test_hist_entropy(self):
im = pyvips.Image.new_from_file(JPEG_FILE).extract_band(1)
ent = im.hist_find().hist_entropy()
assert pytest.approx(ent, 0.01) == 6.67
def test_stdif(self):
im = pyvips.Image.new_from_file(JPEG_FILE)
im2 = im.stdif(10, 10)
assert im.width == im2.width
assert im.height == im2.height
# new mean should be closer to target mean
assert abs(im.avg() - 128) > abs(im2.avg() - 128)
def test_case(self):
# slice into two at 128, we should get 50% of pixels in each half
x = pyvips.Image.grey(256, 256, uchar=True)
index = pyvips.Image.switch([x < 128, x >= 128])
y = index.case([10, 20])
assert y.avg() == 15
# slice into four
index = pyvips.Image.switch([
x < 64,
x >= 64 and x < 128,
x >= 128 and x < 192,
x >= 192
])
assert index.case([10, 20, 30, 40]).avg() == 25
# values over N should use the last value
assert index.case([10, 20, 30]).avg() == 22.5
if __name__ == '__main__':
pytest.main()