trxrdpy 2.1.1

Python toolkit for time-resolved X-ray diffraction simulation and beamline-dependent analysis workflows.

XRDpy

XRDpy is a Python toolkit for X-ray diffraction (XRD) simulation and analysis, with a particular focus on time-resolved / pump–probe diffraction workflows.

The project name on GitHub and Zenodo is XRDpy. The package is distributed on PyPI as trxrdpy and should be imported in Python as trxrdpy.

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Repository

Source code: https://github.com/julioguzmanb/XRDpy

DOI (Zenodo)

• Project concept DOI (all versions): https://doi.org/10.5281/zenodo.18634909

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Main capabilities

Simulation

• Polycrystalline XRD simulation
• Single-crystal diffraction simulation
• CIF-based crystallographic helpers
• Plotting utilities for simulated diffraction data
• A GUI for simulation workflows

Analysis

• Beamline/facility-specific data handling
• 2D image reduction and azimuthal integration
• Standardized generation of 1D xy diffraction patterns
• Peak fitting workflows
• Differential analysis workflows
• Shared utilities for plotting, path handling, and common analysis operations

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Package structure

XRDpy/
├── pyproject.toml
├── README.md
├── LICENSE
└── src/
    └── trxrdpy/
        ├── __init__.py
        ├── utils.py
        ├── detector.py
        ├── experiment.py
        ├── plot.py
        ├── sample.py
        ├── cif.py
        ├── simulation/
        │   ├── __init__.py
        │   ├── polycrystalline.py
        │   ├── single_crystal.py
        │   └── gui.py
        └── analysis/
            ├── common/
            │   ├── __init__.py
            │   ├── paths.py
            │   ├── plot_utils.py
            │   ├── general_utils.py
            │   ├── azimint_utils.py
            │   ├── differential_analysis_utils.py
            │   ├── fitting_utils.py
            │   └── calibration_utils.py
            ├── _shared_2d/
            │   ├── __init__.py
            │   └── azimint.py
            ├── ESRF_ID09/
            │   ├── __init__.py
            │   ├── datared.py
            │   └── azimint.py
            ├── MaxIV_FemtoMAX/
            │   ├── __init__.py
            │   ├── datared_utils.py
            │   ├── datared.py
            │   └── azimint.py
            ├── Spring8_SACLA/
            │   ├── __init__.py
            │   ├── datared.py
            │   ├── azimint.py
            │   └── pbs/
            │       └── parallel_job_sender.sh
            ├── differential_analysis.py
            ├── fitting.py
            ├── calibration.py
            └── gui.py

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Installation

From PyPI

pip install trxrdpy

Optional extras:

pip install "trxrdpy[analysis]"
pip install "trxrdpy[gui]"

From source

Clone the repository and install in editable mode:

git clone https://github.com/julioguzmanb/XRDpy.git
cd XRDpy
pip install -e .

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Import

import trxrdpy
from trxrdpy import simulation
from trxrdpy import analysis
from trxrdpy.analysis import calibration

More specific imports:

from trxrdpy.analysis import fitting
from trxrdpy.analysis import differential_analysis
from trxrdpy.analysis.MaxIV_FemtoMAX import azimint
from trxrdpy.analysis.Spring8_SACLA import datared

The package currently exposes the following top-level modules through trxrdpy.__init__:

from . import utils
from . import experiment
from . import plot
from . import sample
from . import cif
from . import simulation
from . import analysis

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Analysis organization

The analysis section is organized into shared utilities, facility-specific workflows, and user-facing APIs.

analysis.common

Facility-independent shared utilities:

• path handling
• plotting helpers
• general helper functions
• common azimuthal-integration helpers
• fitting utilities
• differential-analysis utilities

analysis._shared_2d

Shared 2D-image-based azimuthal-integration workflow.

This layer is currently used by:

• Max IV FemtoMAX
• SPring-8 SACLA

analysis.ESRF_ID09

ID09-specific azimuthal-integration workflow.

At ESRF ID09, the route to generate xy files differs from the homogenized 2D-image workflow used elsewhere. The beamline-provided tools and data structure are handled through a dedicated facility-specific implementation.

analysis.MaxIV_FemtoMAX

FemtoMAX-specific analysis entry points.

This section contains:

• beamline-specific data reduction
• azimuthal-integration entry points
• wrappers that preserve the facility-facing public API

analysis.Spring8_SACLA

SACLA-specific analysis entry points.

This section contains:

• beamline-specific data reduction
• azimuthal-integration entry points
• PBS job-submission helper scripts for HPC workflows

User-facing analysis APIs

These modules provide the user-facing analysis layer after xy files are available:

• analysis.fitting
• analysis.differential_analysis

Once xy files are created, the downstream fitting and differential-analysis pipeline is shared across facilities.

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Facility-specific workflow overview

The analysis pipeline is intentionally split because raw-data handling differs across facilities.

Max IV FemtoMAX

• Uses facility-specific data reduction
• Produces homogenized 2D images
• Reuses the shared 2D azimuthal-integration workflow
• Then uses the shared downstream analysis pipeline

SPring-8 SACLA

• Uses facility-specific data reduction
• Some reduction steps may depend on beamline-specific software, legacy Python environments, VPN access, or HPC job submission
• Produces homogenized 2D images
• Reuses the shared 2D azimuthal-integration workflow
• Then uses the shared downstream analysis pipeline

ESRF ID09

• Does not use the same 2D homogenization route as FemtoMAX/SACLA
• Uses a different beamline-specific azimuthal-integration workflow to generate xy files
• Then uses the same downstream fitting and differential-analysis pipeline

In other words:

• data reduction differs across facilities
• xy generation differs for ID09 vs the shared 2D workflow
• the downstream analysis after xy creation is shared

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Notes

• Some analysis workflows may require facility-specific dependencies that are not part of a standard Python installation.
• Some SACLA workflows may rely on legacy Python environments and external HPC job submission.
• The simulation and analysis sections are developed within the same package but target different use cases.
• The project is published on PyPI as trxrdpy because the xrdpy name is already taken on PyPI.

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Citation

If you use XRDpy in academic work, please cite the Zenodo record corresponding to the version you used.

• Project concept DOI (all versions): https://doi.org/10.5281/zenodo.18634909

Version-specific citation metadata is available on the Zenodo release page.

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License

Creative Commons Attribution 4.0 International (CC BY 4.0). See LICENSE for details.

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Author

Julio Guzman-Brambila