def test_csd_complex(self, rand_complex_data_gen, num_samps, fs, nperseg):
cpu_x, gpu_x = rand_complex_data_gen(num_samps)
cpu_y, gpu_y = rand_complex_data_gen(num_samps)
cpu_csd = signal.csd(cpu_x, cpu_y, fs, nperseg=nperseg)
gpu_csd = cp.asnumpy(cusignal.csd(gpu_x, gpu_y, fs, nperseg=nperseg))
assert array_equal(cpu_csd, gpu_csd)
def test_csd_complex(num_samps, fs, nperseg):
cpu_x = np.random.rand(num_samps) + 1j * np.random.rand(num_samps)
cpu_y = np.random.rand(num_samps) + 1j * np.random.rand(num_samps)
gpu_x = cp.asarray(cpu_x)
gpu_y = cp.asarray(cpu_y)
cpu_csd = signal.csd(cpu_x, cpu_y, fs, nperseg=nperseg)
gpu_csd = cp.asnumpy(cusignal.csd(gpu_x, gpu_y, fs, nperseg=nperseg))
assert array_equal(cpu_csd, gpu_csd)
def gpu_version(self, x, y, fs, nperseg):
with cp.cuda.Stream.null:
out = cusignal.csd(x, y, fs, nperseg=nperseg)
cp.cuda.Stream.null.synchronize()
return out