def z_integrate(
azimuthal_integrator: AzimuthalIntegrator,
data: np.ndarray,
mask: np.ndarray,
dark: np.ndarray,
flat: np.ndarray,
normalization_factor: float = 1) -> Tuple[np.ndarray, np.ndarray]:
if dark is None: dark = np.zeros_like(data)
if flat is None: flat = np.ones_like(data)
if mask is None: mask = np.zeros_like(data)
I = np.sum((data - dark) * np.average(flat - dark) / (flat - dark) /
normalization_factor * np.logical_not(mask),
axis=1)[::-1]
centerx = azimuthal_integrator.getFit2D()['centerX']
centerz = azimuthal_integrator.getFit2D()['centerY']
q_z = azimuthal_integrator.qFunction(np.arange(
0, data.shape[0]), np.array([centerx] * data.shape[0])) / 10
q_z[np.arange(0, data.shape[0]) < centerz] *= -1.
return q_z, I
