src/openpower/decoder/isa/naivedct.py

   1 #
   2 # Fast discrete cosine transform algorithms (Python)
   3 #
   4 # Copyright (c) 2020 Project Nayuki. (MIT License)
   5 # https://www.nayuki.io/page/fast-discrete-cosine-transform-algorithms
   6 #
   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
  10 # use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
  11 # the Software, and to permit persons to whom the Software is furnished to do so,
  12 # subject to the following conditions:
  13 # - The above copyright notice and this permission notice shall be included in
  14 #   all copies or substantial portions of the Software.
  15 # - The Software is provided "as is", without warranty of any kind, express or
  16 #   implied, including but not limited to the warranties of merchantability,
  17 #   fitness for a particular purpose and noninfringement. In no event shall the
  18 #   authors or copyright holders be liable for any claim, damages or other
  19 #   liability, whether in an action of contract, tort or otherwise, arising from,
  20 #   out of or in connection with the Software or the use or other dealings in the
  21 #   Software.
  22 #
  23
  24 import math
  25
  26
  27 # DCT type II, unscaled.
  28 # See: https://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II
  29 def transform(vector):
  30         result = []
  31         factor = math.pi / len(vector)
  32         for i in range(len(vector)):
  33                 sum = 0.0
  34                 for (j, val) in enumerate(vector):
  35                         sum += val * math.cos((j + 0.5) * i * factor)
  36                 result.append(sum)
  37         return result
  38
  39
  40 # DCT type III, unscaled.
  41 # See: https://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-III
  42 def inverse_transform(vector):
  43         result = []
  44         factor = math.pi / len(vector)
  45         for i in range(len(vector)):
  46                 sum = vector[0] / 2
  47                 for j in range(1, len(vector)):
  48                         sum += vector[j] * math.cos(j * (i + 0.5) * factor)
  49                 result.append(sum)
  50         return result