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