1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
|
from dtcwt.sampling import rescale
import numpy as np
def test_rescale_lanczos():
# Create random 100x120 image
X = np.random.rand(100,120)
# Re size up
Xrs = rescale(X, (300, 210), 'lanczos')
assert Xrs.shape == (300, 210)
# And down
Xrecon = rescale(Xrs, X.shape, 'lanczos')
assert Xrecon.shape == X.shape
# Got back roughly the same thing to within 5%?
assert np.all(np.abs(X-Xrecon) < 5e-2)
def test_rescale_bilinear():
# Create random 100x120 image
X = np.random.rand(100,120)
# Re size up
Xrs = rescale(X, (300, 210), 'bilinear')
assert Xrs.shape == (300, 210)
# And down
Xrecon = rescale(Xrs, X.shape, 'bilinear')
assert Xrecon.shape == X.shape
# Got back roughly the same thing to within 30% (bilinear sucks)
assert np.all(np.abs(X-Xrecon) < 3e-1)
def test_rescale_nearest():
# Create random 100x120 image
X = np.random.rand(100,120)
# Re size up
Xrs = rescale(X, (200, 240), 'nearest')
assert Xrs.shape == (200, 240)
# And down
Xrecon = rescale(Xrs, X.shape, 'nearest')
assert Xrecon.shape == X.shape
# Got back roughly the same thing to within 1% (nearest neighbour should be exact)
assert np.all(np.abs(X-Xrecon) < 1e-2)
|
