60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
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from __future__ import division, print_function, absolute_import
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from subprocess import Popen, PIPE, STDOUT
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import numpy as np
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SZ = [2, 3, 4, 8, 12, 15, 16, 17, 32, 64, 128, 256, 512, 1024]
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def gen_data(dt):
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arrays = {}
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if dt == np.double:
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pg = './fftw_double'
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elif dt == np.float32:
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pg = './fftw_single'
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else:
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raise ValueError("unknown: %s" % dt)
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# Generate test data using FFTW for reference
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for type in [1, 2, 3, 4, 5, 6, 7, 8]:
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arrays[type] = {}
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for sz in SZ:
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a = Popen([pg, str(type), str(sz)], stdout=PIPE, stderr=STDOUT)
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st = [i.strip() for i in a.stdout.readlines()]
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arrays[type][sz] = np.fromstring(",".join(st), sep=',', dtype=dt)
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return arrays
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# generate single precision data
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data = gen_data(np.float32)
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filename = 'fftw_single_ref'
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# Save ref data into npz format
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d = {'sizes': SZ}
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for type in [1, 2, 3, 4]:
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for sz in SZ:
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d['dct_%d_%d' % (type, sz)] = data[type][sz]
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d['sizes'] = SZ
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for type in [5, 6, 7, 8]:
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for sz in SZ:
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d['dst_%d_%d' % (type-4, sz)] = data[type][sz]
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np.savez(filename, **d)
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# generate double precision data
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data = gen_data(np.float64)
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filename = 'fftw_double_ref'
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# Save ref data into npz format
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d = {'sizes': SZ}
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for type in [1, 2, 3, 4]:
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for sz in SZ:
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d['dct_%d_%d' % (type, sz)] = data[type][sz]
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d['sizes'] = SZ
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for type in [5, 6, 7, 8]:
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for sz in SZ:
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d['dst_%d_%d' % (type-4, sz)] = data[type][sz]
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np.savez(filename, **d)
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