Integration: raw intensity to I(q)

Raw detector images generally contain two pixel axes. To visualize and analyze scattering patterns these need to be transformed into chi/q or qz/qxy coordinates. PyHyperScattering wraps several integrators to accomplish this, with most implementations relying on pyFAI.

PFGeneralIntegrator provides a thin layer over pyFAI’s azimuthal integrator. Pass in calibration parameters or a .poni file and a mask, then call integrateImageStack to convert an xarray with pix_x/pix_y axes to intensity in q and optionally chi:

from PyHyperScattering.PFGeneralIntegrator import PFGeneralIntegrator
integrator = PFGeneralIntegrator(ponifile="calib.poni",
                                maskmethod="image", maskpath="mask.tif")
iq = integrator.integrateImageStack(raw_data)

For grazing-incidence experiments PGGeneralIntegrator uses pygix to output either reciprocal-space q_xy/q_z data or caked q vs chi. Datasets already in qx/qy coordinates can be integrated with WPIntegrator which relies on skimage.transform.warp_polar (or its GPU version). WPIntegrator is a detector-plane qx/qy to chi/q_perp remesher, so it is the right choice for reciprocal-plane / 2D NRSS outputs.

For NRSS detector-aware 3D outputs use NRSSIntegrator instead. It keeps the same polar remesh approach but relabels the radial axis with detector-corrected |q| so the reduced curve can be compared to geometry-aware analytical form factors.

All integrators return properly labeled xarray objects so the rest of the workflow can use normal xarray indexing and visualization.