2 # Fast discrete cosine transform algorithms (Python)
4 # Copyright (c) 2020 Project Nayuki. (MIT License)
5 # https://www.nayuki.io/page/fast-discrete-cosine-transform-algorithms
7 # Permission is hereby granted, free of charge, to any person obtaining a copy of
8 # this software and associated documentation files (the "Software"), to deal in
9 # the Software without restriction, including without limitation the rights to
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11 # copies of the Software, and to permit persons to whom the Software is
12 # furnished to do so, subject to the following conditions:
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15 # - The Software is provided "as is", without warranty of any kind, express or
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24 import math
, random
, unittest
25 import fastdctlee
, naivedct
28 class FastDctTest(unittest
.TestCase
):
30 def test_fast_dct_lee_vs_naive(self
):
33 vector
= FastDctTest
.nonrandom_vector(n
)
34 expect
= naivedct
.transform(vector
)
35 original
= fastdctlee
.transform(vector
)
36 actual
= fastdctlee
.transform2(vector
)
37 self
.assertListAlmostEqual(actual
, expect
)
38 expect
= naivedct
.inverse_transform(vector
)
39 actual
= fastdctlee
.inverse_transform(vector
)
40 self
.assertListAlmostEqual(actual
, expect
)
42 def notest_fast_dct_lee_invertibility(self
):
43 for i
in range(1, 10):
45 vector
= FastDctTest
.random_vector(n
)
46 temp
= fastdctlee
.transform2(vector
)
47 temp
= fastdctlee
.inverse_transform(temp
)
48 temp
= [(val
* 2.0 / n
) for val
in temp
]
49 self
.assertListAlmostEqual(vector
, temp
)
51 def assertListAlmostEqual(self
, actual
, expect
):
52 self
.assertEqual(len(actual
), len(expect
))
53 for (x
, y
) in zip(actual
, expect
):
54 self
.assertAlmostEqual(x
, y
, delta
=FastDctTest
._EPSILON
)
58 return [random
.uniform(-1.0, 1.0) for _
in range(n
)]
61 def nonrandom_vector(n
):
62 return [(i
-n
/2.0) for i
in range(n
)]
68 if __name__
== "__main__":