mlgidBASE Documentation

Welcome to the mlgidBASE documentation!

mlgidBASE is a Python package for machine learning–driven analysis of grazing-incidence wide-angle X-ray scattering (GIWAXS) data. It provides a full workflow from peak detection to matching with known crystal structures.

The package builds on the following components:

• mlgidDETECT — for peak detection

• pygidFIT — for two-dimensional peak fitting

• mlgidMATCH — for matching experimental peaks to known structures

Key Features

Initialization

Can be created from a pygid.Conversion object or loaded directly from a NeXus file.

Methods

Provides functions for:

• Peak detection: Tutorial 2: Peak Detection

• Peak fitting: Tutorial 3: Peak Fitting

• Peak matching: Tutorial 4: Peak Matching

Visualization

Supports visualization at all stages of the analysis pipeline: Tutorial 6: Visualization.

Peak Adjustment

Includes functions to add or delete peaks, either interactively or programmatically: Tutorial 7: Operations with peaks.

Data Access

Enables retrieving analysis results from the NeXus file for further processing: Tutorial 8: Operations with saved data.

Outline

• Quick Start
  • How to use
• Tutorials
  • Tutorial 1: mlgidBASE Initialization
  • Tutorial 2: Peak Detection
  • Tutorial 3: Peak Fitting
  • Tutorial 4: Peak Matching
  • Tutorial 5: Analysis from memory
  • Tutorial 6: Visualization
  • Tutorial 7: Operations with peaks
  • Tutorial 8: Operations with saved data
• File Format
  • Data Format