def test_fft(self):
for libname in ("numpy","scipy"):
set_fftlib(libname)
a = np.random.randn(4)
fft = np.fft.fft(a)
out = _fft(a)
self.assertTrue(np.allclose(fft, out))
def _cross_corr_fft(x, y, t1, t2, length, dummy, out):
out_length = len(dummy)
tmp1 = np.zeros((length * 2), x.dtype)
_fill_data(x, t1, tmp1)
#tmp1[list(t1)] = x
tmp2 = np.zeros((length * 2), y.dtype)
_fill_data(y, t2, tmp2)
#tmp2[list(t2)] = y
x = _fft(tmp1, overwrite_x=True)
y = _fft(tmp2, overwrite_x=True)
np.conj(y, out=y)
np.multiply(x, y, out=x)
_out = _ifft(x, overwrite_x=True)
out[:] += _out[:out_length].real
out[1:] += _out[-1:-out_length:-1].real
def _cross_sum_rfft(x, y, t, length, dummy, out):
out_length = len(dummy)
tmp1 = np.zeros((length * 2), y.dtype)
_fill_data(x, t, tmp1)
x = _fft(tmp1, overwrite_x=True)
np.multiply(x, y, out=x)
_out = _ifft(x, overwrite_x=True)
out[:] += _out[:out_length].real
out[1:] = out[1:] + _out[-1:-out_length:-1].real
def _cross_corr_fft_regular(x, y, dummy, out):
out_length = len(dummy)
length = len(x)
tmp1 = np.empty((length * 2), x.dtype)
tmp1[0:length] = x
tmp1[length:] = 0.
tmp2 = np.empty((length * 2), y.dtype)
tmp2[0:length] = y
tmp2[length:] = 0.
x = _fft(tmp1, overwrite_x=True)
y = _fft(tmp2, overwrite_x=True)
x = x * np.conj(y)
_out = _ifft(x, overwrite_x=True)
out[:] += _out[:out_length].real
out[1:] += _out[-1:-out_length:-1].real
def _auto_corr_fft(x, t, length, dummy, out):
out_length = len(dummy)
tmp = np.zeros((length * 2), x.dtype)
_fill_data(x, t, tmp)
#tmp[list(t)] = x
x = _fft(tmp, overwrite_x=True)
y = np.conj(x)
np.multiply(x, y, out=x)
_out = _ifft(x, overwrite_x=True)
out[:] += _out[:out_length].real
def _auto_corr_fft_regular(x, dummy, out):
out_length = len(dummy)
length = len(x)
tmp = np.empty((length * 2), x.dtype)
tmp[0:length] = x
tmp[length:] = 0.
x = _fft(tmp, overwrite_x=True)
x = x * np.conj(x)
_out = _ifft(x, overwrite_x=True)
out[:] += _out[:out_length].real