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70 lines
2.1 KiB
70 lines
2.1 KiB
5 years ago
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# Copyright (c) 2019 Project Nayuki. (MIT License)
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# https://www.nayuki.io/page/free-small-fft-in-multiple-languages
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import math, cmath
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def transform_radix2(vector, inverse):
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# Returns the integer whose value is the reverse of the lowest 'bits' bits of the integer 'x'.
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def reverse(x, bits):
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y = 0
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for i in range(bits):
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y = (y << 1) | (x & 1)
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x >>= 1
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return y
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# Initialization
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n = len(vector)
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levels = int(math.log2(n))
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coef = (2 if inverse else -2) * cmath.pi / n
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exptable = [cmath.rect(1, i * coef) for i in range(n // 2)]
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vector = [vector[reverse(i, levels)] for i in range(n)] # Copy with bit-reversed permutation
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# Radix-2 decimation-in-time FFT
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size = 2
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while size <= n:
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halfsize = size // 2
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tablestep = n // size
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for i in range(0, n, size):
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k = 0
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for j in range(i, i + halfsize):
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temp = vector[j + halfsize] * exptable[k]
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vector[j + halfsize] = vector[j] - temp
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vector[j] += temp
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k += tablestep
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size *= 2
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return vector
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###########################################################################
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# Benchmark interface
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bm_params = {
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(50, 25): (2, 128),
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(100, 100): (3, 256),
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(1000, 1000): (20, 512),
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(5000, 1000): (100, 512),
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}
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def bm_setup(params):
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state = None
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signal = [math.cos(2 * math.pi * i / params[1]) + 0j for i in range(params[1])]
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fft = None
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fft_inv = None
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def run():
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nonlocal fft, fft_inv
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for _ in range(params[0]):
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fft = transform_radix2(signal, False)
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fft_inv = transform_radix2(fft, True)
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def result():
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nonlocal fft, fft_inv
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fft[1] -= 0.5 * params[1]
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fft[-1] -= 0.5 * params[1]
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fft_ok = all(abs(f) < 1e-3 for f in fft)
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for i in range(len(fft_inv)):
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fft_inv[i] -= params[1] * signal[i]
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fft_inv_ok = all(abs(f) < 1e-3 for f in fft_inv)
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return params[0] * params[1], (fft_ok, fft_inv_ok)
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return run, result
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