Pseudo XRR

Python package for pseudo X-ray reflectivity

• Free software: 3-clause BSD license

Installation

To install the pxrr package in a local development environment, follow these steps:

1. Clone the repository:

git clone https://github.com/XYangXRay/pxrr.git
cd pxrr

2. Create the pixi environments (default and 'dev'):

pixi install --all

3. That's all!

Features

• TODO

Quick Start (Notebook Flow)

Minimal processing sequence (mirrors pxrr_step_example):

from pxrr.data_io import load_inputs, binning_GIXOS_data, remove_negative_2theta, real_space_2theta, save_pseudo_reflectivity
from pxrr.plots import GIXOS_data_plot_prep, GIXOS_data_plot, R_data_plot, R_pseudo_data_plot
from pxrr.slit import rect_slit_function, conversion_to_reflectivity
from pxrr.dependency import dependency_real_space_2theta, create_dependency_models

metadata_file = "./testing_data/gixos_metadata.yaml"

# Load raw data + metadata
importGIXOSdata, importbkg, metadata = load_inputs(metadata_file)

# Re-bin & trim negative 2θ
importGIXOSdata, importbkg = binning_GIXOS_data(importGIXOSdata, importbkg)
importGIXOSdata, importbkg, tt_step = remove_negative_2theta(importGIXOSdata, importbkg)

# Geometry (single qxy0 workflow)
metadata = real_space_2theta(metadata)

# Prepare GIXOS signal
GIXOS, DSbetaHW = GIXOS_data_plot_prep(importGIXOSdata, importbkg, metadata, tt_step)
GIXOS_data_plot(GIXOS, metadata)

# Fresnel + transmission + DS terms
GIXOS = GIXOS_RF_and_SF(GIXOS, metadata, DSbetaHW)

# Slit + reflectivity conversion
xrr_config = rect_slit_function(GIXOS, metadata)
GIXOS = conversion_to_reflectivity(GIXOS, xrr_config)

# Plots
R_data_plot(GIXOS, metadata, xrr_config)                 # R
R_pseudo_data_plot(GIXOS, metadata, xrr_config)          # (R/R_F)/scale

# Save pseudo reflectivity (qz ref dR dqz)
outfile = save_pseudo_reflectivity(GIXOS, metadata)
print("Saved:", outfile)

Multi‑curve pseudo reflectivity (different scalings + offsets):

R_pseudo_data_plot(
    GIXOS, metadata, xrr_config,
    rf_scalings=[metadata['RFscaling'], metadata['RFscaling']*2, metadata['RFscaling']*5],
    offsets=[0, 1, 2]   # multiply curves by 10^offset (visual separation)
)

Dependency (qz-selected modeling):

metadata = dependency_real_space_2theta(metadata)   # multi-qxy geometry
model, assume_model, CWM_model = create_dependency_models(GIXOS, metadata, DSbetaHW)
dependency_plot(GIXOS, metadata, model, assume_model, CWM_model)

Outputs

• Reflectivity: *_R_PYTHON_TEST.dat
• DS/(R/RF): *_DS2RRF_PYTHON_TEST.dat
• Structure factor: *_SF_PYTHON_TEST.dat
• Pseudo XRR (portable): <sample>_pseudo_qx.txt (qz ref dR dqz)

Tips

• Override Fresnel scaling in plots: R_data_plot(..., rf_scaling=value)
• Provide multiple scalings + offsets for publication layering.
• Set rf_scalings=None to default to metadata['RFscaling'].