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""" Test functions for fftpack.basic module
"""
from __future__ import division, print_function, absolute_import
import sys
from numpy.testing import *
from scipy.fftpack import ifft, fft, fftn, irfft, rfft
from numpy import arange, asarray, zeros, dot, exp, pi, double, cdouble
import numpy.fft
from numpy.random import rand
def random(size):
return rand(*size)
def direct_dft(x):
x = asarray(x)
n = len(x)
y = zeros(n,dtype=cdouble)
w = -arange(n)*(2j*pi/n)
for i in range(n):
y[i] = dot(exp(i*w),x)
return y
def direct_idft(x):
x = asarray(x)
n = len(x)
y = zeros(n,dtype=cdouble)
w = arange(n)*(2j*pi/n)
for i in range(n):
y[i] = dot(exp(i*w),x)/n
return y
class TestFft(TestCase):
def bench_random(self):
from numpy.fft import fft as numpy_fft
print()
print(' Fast Fourier Transform')
print('=================================================')
print(' | real input | complex input ')
print('-------------------------------------------------')
print(' size | scipy | numpy | scipy | numpy ')
print('-------------------------------------------------')
for size,repeat in [(100,7000),(1000,2000),
(256,10000),
(512,10000),
(1024,1000),
(2048,1000),
(2048*2,500),
(2048*4,500),
]:
print('%5s' % size, end=' ')
sys.stdout.flush()
for x in [random([size]).astype(double),
random([size]).astype(cdouble)+random([size]).astype(cdouble)*1j
]:
if size > 500:
y = fft(x)
else:
y = direct_dft(x)
assert_array_almost_equal(fft(x),y)
print('|%8.2f' % measure('fft(x)',repeat), end=' ')
sys.stdout.flush()
assert_array_almost_equal(numpy_fft(x),y)
print('|%8.2f' % measure('numpy_fft(x)',repeat), end=' ')
sys.stdout.flush()
print(' (secs for %s calls)' % (repeat))
sys.stdout.flush()
class TestIfft(TestCase):
def bench_random(self):
from numpy.fft import ifft as numpy_ifft
print()
print(' Inverse Fast Fourier Transform')
print('===============================================')
print(' | real input | complex input ')
print('-----------------------------------------------')
print(' size | scipy | numpy | scipy | numpy ')
print('-----------------------------------------------')
for size,repeat in [(100,7000),(1000,2000),
(256,10000),
(512,10000),
(1024,1000),
(2048,1000),
(2048*2,500),
(2048*4,500),
]:
print('%5s' % size, end=' ')
sys.stdout.flush()
for x in [random([size]).astype(double),
random([size]).astype(cdouble)+random([size]).astype(cdouble)*1j
]:
if size > 500:
y = ifft(x)
else:
y = direct_idft(x)
assert_array_almost_equal(ifft(x),y)
print('|%8.2f' % measure('ifft(x)',repeat), end=' ')
sys.stdout.flush()
assert_array_almost_equal(numpy_ifft(x),y)
print('|%8.2f' % measure('numpy_ifft(x)',repeat), end=' ')
sys.stdout.flush()
print(' (secs for %s calls)' % (repeat))
sys.stdout.flush()
class TestRfft(TestCase):
def bench_random(self):
from numpy.fft import rfft as numpy_rfft
print()
print('Fast Fourier Transform (real data)')
print('==================================')
print(' size | scipy | numpy ')
print('----------------------------------')
for size,repeat in [(100,7000),(1000,2000),
(256,10000),
(512,10000),
(1024,1000),
(2048,1000),
(2048*2,500),
(2048*4,500),
]:
print('%5s' % size, end=' ')
sys.stdout.flush()
x = random([size]).astype(double)
print('|%8.2f' % measure('rfft(x)',repeat), end=' ')
sys.stdout.flush()
print('|%8.2f' % measure('numpy_rfft(x)',repeat), end=' ')
sys.stdout.flush()
print(' (secs for %s calls)' % (repeat))
sys.stdout.flush()
class TestIrfft(TestCase):
def bench_random(self):
from numpy.fft import irfft as numpy_irfft
print()
print('Inverse Fast Fourier Transform (real data)')
print('==================================')
print(' size | scipy | numpy ')
print('----------------------------------')
for size,repeat in [(100,7000),(1000,2000),
(256,10000),
(512,10000),
(1024,1000),
(2048,1000),
(2048*2,500),
(2048*4,500),
]:
print('%5s' % size, end=' ')
sys.stdout.flush()
x = random([size]).astype(double)
x1 = zeros(size/2+1,dtype=cdouble)
x1[0] = x[0]
for i in range(1,size/2):
x1[i] = x[2*i-1] + 1j * x[2*i]
if not size % 2:
x1[-1] = x[-1]
y = irfft(x)
print('|%8.2f' % measure('irfft(x)',repeat), end=' ')
sys.stdout.flush()
assert_array_almost_equal(numpy_irfft(x1,size),y)
print('|%8.2f' % measure('numpy_irfft(x1,size)',repeat), end=' ')
sys.stdout.flush()
print(' (secs for %s calls)' % (repeat))
sys.stdout.flush()
class TestFftn(TestCase):
def bench_random(self):
from numpy.fft import fftn as numpy_fftn
print()
print(' Multi-dimensional Fast Fourier Transform')
print('===================================================')
print(' | real input | complex input ')
print('---------------------------------------------------')
print(' size | scipy | numpy | scipy | numpy ')
print('---------------------------------------------------')
for size,repeat in [((100,100),100),((1000,100),7),
((256,256),10),
((512,512),3),
]:
print('%9s' % ('%sx%s' % size), end=' ')
sys.stdout.flush()
for x in [random(size).astype(double),
random(size).astype(cdouble)+random(size).astype(cdouble)*1j
]:
y = fftn(x)
#if size > 500: y = fftn(x)
#else: y = direct_dft(x)
assert_array_almost_equal(fftn(x),y)
print('|%8.2f' % measure('fftn(x)',repeat), end=' ')
sys.stdout.flush()
assert_array_almost_equal(numpy_fftn(x),y)
print('|%8.2f' % measure('numpy_fftn(x)',repeat), end=' ')
sys.stdout.flush()
print(' (secs for %s calls)' % (repeat))
sys.stdout.flush()
if __name__ == "__main__":
run_module_suite()
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