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https://github.com/mborgerding/kissfft.git
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7c9a5586a9
Fixes test run with -DKISSFFT_TOOLS=OFF Signed-off-by: Vasyl Gello <vasek.gello@gmail.com>
144 lines
3.4 KiB
Python
Executable File
144 lines
3.4 KiB
Python
Executable File
#!/usr/bin/env python
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# Copyright (c) 2003-2019, Mark Borgerding. All rights reserved.
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# This file is part of KISS FFT - https://github.com/mborgerding/kissfft
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#
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# SPDX-License-Identifier: BSD-3-Clause
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# See COPYING file for more information.
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from __future__ import absolute_import, division, print_function
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import math
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import sys
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import os
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import random
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import struct
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import getopt
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import numpy as np
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po = math.pi
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e = math.e
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do_real = False
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datatype = os.environ.get('KISSFFT_DATATYPE', 'float')
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openmp = os.environ.get('KISSFFT_OPENMP', 'float')
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util = './fastfilt-' + datatype
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if openmp == '1' or openmp == 'ON':
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util = util + '-openmp'
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minsnr = 90
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if datatype == 'double':
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dtype = np.float64
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elif datatype == 'float':
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dtype = np.float32
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elif datatype == 'int16_t':
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dtype = np.int16
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minsnr = 10
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elif datatype == 'int32_t':
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dtype = np.int32
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elif datatype == 'simd':
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sys.stderr.write('testkiss.py does not yet test simd')
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sys.exit(0)
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else:
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sys.stderr.write('unrecognized datatype {0}\n'.format(datatype))
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sys.exit(1)
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def dopack(x):
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if np.iscomplexobj(x):
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x = x.astype(np.complex128).view(np.float64)
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else:
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x = x.astype(np.float64)
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return x.astype(dtype).tobytes()
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def dounpack(x, cpx):
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x = np.frombuffer(x, dtype).astype(np.float64)
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if cpx:
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x = x[::2] + 1j * x[1::2]
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return x
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def make_random(shape):
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'create random uniform (-1,1) data of the given shape'
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if do_real:
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return np.random.uniform(-1, 1, shape)
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else:
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return (np.random.uniform(-1, 1, shape) + 1j * np.random.uniform(-1, 1, shape))
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def randmat(ndim):
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'create a random multidimensional array in range (-1,1)'
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dims = np.random.randint(2, 5, ndim)
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if do_real:
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dims[-1] = (dims[-1] // 2) * 2 # force even last dimension if real
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return make_random(dims)
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def test_fft(ndim):
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x = randmat(ndim)
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if do_real:
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xver = np.fft.rfftn(x)
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else:
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xver = np.fft.fftn(x)
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x2 = dofft(x, do_real)
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err = xver - x2
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errf = err.ravel()
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xverf = xver.ravel()
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errpow = np.vdot(errf, errf) + 1e-10
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sigpow = np.vdot(xverf, xverf) + 1e-10
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snr = 10 * math.log10(abs(sigpow / errpow))
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print('SNR (compared to NumPy) : {0:.1f}dB'.format(float(snr)))
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if snr < minsnr:
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print('xver=', xver)
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print('x2=', x2)
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print('err', err)
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sys.exit(1)
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def dofft(x, isreal):
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dims = list(np.shape(x))
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x = x.ravel()
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scale = 1
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if datatype == 'int16_t':
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x = 32767 * x
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scale = len(x) / 32767.0
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elif datatype == 'int32_t':
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x = 2147483647.0 * x
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scale = len(x) / 2147483647.0
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cmd = util + ' -n '
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cmd += ','.join([str(d) for d in dims])
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if do_real:
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cmd += ' -R '
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print(cmd)
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from subprocess import Popen, PIPE
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p = Popen(cmd, shell=True, stdin=PIPE, stdout=PIPE)
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p.stdin.write(dopack(x))
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p.stdin.close()
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res = dounpack(p.stdout.read(), 1)
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if do_real:
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dims[-1] = (dims[-1] // 2) + 1
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res = scale * res
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p.wait()
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return np.reshape(res, dims)
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def main():
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opts, args = getopt.getopt(sys.argv[1:], 'r')
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opts = dict(opts)
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global do_real
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do_real = '-r' in opts
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if do_real:
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print('Testing multi-dimensional real FFTs')
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else:
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print('Testing multi-dimensional FFTs')
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for dim in range(1, 4):
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test_fft(dim)
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if __name__ == "__main__":
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main()
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