rs = get_random_state()
vec_z = rs.randn(n1d) + \
rs.randn(n1d) * 1j
mat_z = rs.randn(*size2d) + \
rs.randn(*size2d) * 1j
arr_z = rs.randn(*size3d) + \
rs.randn(*size3d) * 1j
# stride 10
tmp = vec_z[::10]
perf_times = time_func(np.fft.fft, tmp, dict(), refresh_buffer=False)
print_summary(perf_times, header='np.fft.fft' + arg_signature(tmp))
perf_times = time_func(np.fft.fft, mat_z, dict(axis=0), refresh_buffer=False)
print_summary(perf_times, header='np.fft.fft(axis=0)' + arg_signature(mat_z))
tmp = arr_z.T
perf_times = time_func(np.fft.fft2,
tmp,
dict(),
batch_size=8,
refresh_buffer=False)
print_summary(perf_times, header='np.fft.fft2' + arg_signature(tmp))
tmp = arr_z.transpose((2, 0, 1))
perf_times = time_func(np.fft.fftn,
tmp,
size3d = (273, 274, 275)
rs = get_random_state()
vec_z = rs.randn(n1d) + \
rs.randn(n1d) * 1j
mat_z = rs.randn(*size2d) + \
rs.randn(*size2d) * 1j
arr_z = rs.randn(*size3d) + \
rs.randn(*size3d) * 1j
tmp = vec_z
perf_times = time_func(np.fft.fft, tmp, dict(), refresh_buffer=False)
print_summary(perf_times, header='np.fft.fft' + arg_signature(tmp))
tmp = vec_z
perf_times = time_func(scipy.fftpack.fft,
tmp,
dict(overwrite_x=True),
refresh_buffer=True)
print_summary(perf_times, header='scipy.fftpack.fft' + arg_signature(tmp))
tmp = mat_z
perf_times = time_func(np.fft.fft2, tmp, dict(), refresh_buffer=False)
print_summary(perf_times, header='np.fft.fft2' + arg_signature(tmp))
tmp = mat_z
perf_times = time_func(scipy.fftpack.fft2,
tmp,
buf = np.empty_like(mat_z)
np.copyto(buf, mat_z)
x1 = np.fft.fft2(buf)
del x1
del buf
print("", flush=True)
tf_kw = {'batch_size': 16, 'repetitions': 6}
perf_times = time_func(np.fft.fft,
vec_z,
dict(),
refresh_buffer=False,
**tf_kw)
print_summary(perf_times, header='np.fft.fft' + arg_signature(vec_z))
if run_scipy:
perf_times = time_func(scipy.fftpack.fft, vec_z, dict(overwrite_x=True),
**tf_kw)
print_summary(perf_times,
header='scipy.fftpack.fft, overwrite_x=True' +
arg_signature(vec_z))
perf_times = time_func(np.fft.fft2,
mat_z,
dict(),
refresh_buffer=False,
**tf_kw)
print_summary(perf_times, header='np.fft.fft2' + arg_signature(mat_z))