xypattern
Description
A simple small library to handle x-y patterns, such as are collected with x-ray diffraction or Raman spectroscopy.
Installation
pip install xypattern
Features
- Load and save patterns from/to various file formats (.xy, .chi, .fxye)
- Apply scaling, offset, and smoothing to patterns
- Background subtraction (manual or automatic)
- Pattern manipulation (limiting, extending, deleting ranges)
- Mathematical operations (addition, subtraction, multiplication)
- Pattern transformation (x-axis transformation)
- Pattern rebinning
- Pattern serialization to/from dictionaries
Usage Examples
Reading a file
from xypattern import Pattern
import matplotlib.pyplot as plt
p1 = Pattern.from_file('path/to/file')
p1.scaling = 0.5
p1.offset = 0.1
plt.plot(p1.x, p1.y)
plt.show()
Use a background pattern
p2 = Pattern.from_file('path/to/file')
p2.scaling = 0.9
p1.background_pattern = p2
Automatic background subtraction
from xypattern.auto_background import SmoothBrucknerBackground
p1 = Pattern.from_file('path/to/file')
p1.auto_bkg = SmoothBrucknerBackground(smooth_width=0.2, iterations=30, cheb_order=20)
p1.auto_bkg_roi = [10.0, 60.0] # Optional region of interest for background calculation
Pattern manipulation
# Limit pattern to a specific x-range
limited_pattern = p1.limit(10.0, 60.0)
# Extend pattern to a specific x-value
extended_pattern = p1.extend_to(5.0, 0.0)
# Delete specific x-ranges
cleaned_pattern = p1.delete_ranges([[10.0, 15.0], [40.0, 45.0]])
# Transform x-axis (e.g., convert from 2theta to q-space)
from math import pi, sin
wavelength = 0.3344 # Å
transformed_pattern = p1.transform_x(lambda x: 4 * pi * sin(x * pi / 360) / wavelength)
Scale and stitch multiple patterns
p1 = Pattern.from_file('path/to/file1')
p2 = Pattern.from_file('path/to/file2')
p3 = Pattern.from_file('path/to/file3')
from xypattern.combine import scale_patterns, stitch_patterns
patterns = [p1, p2, p3]
scale_patterns(patterns)
stitched_pattern = stitch_patterns(patterns)
Pattern serialization
# Save pattern to dictionary (useful for JSON serialization)
pattern_dict = p1.to_dict()
# Create pattern from dictionary
p2 = Pattern.from_dict(pattern_dict)
# Create a deep copy of a pattern
p2 = p1.copy()
API Documentation
For detailed API documentation, please visit https://xypattern.readthedocs.io/ or https://cprescher.github.io/xypattern/.
Building Documentation
The project documentation is built using Sphinx. To build the documentation locally:
# Install development dependencies
poetry install --with dev
# Navigate to the docs directory
cd docs
# Build the documentation
make html
The built documentation will be available in the docs/_build/html directory. Open index.html in your web browser to view it.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
1 maintainer
Release files for xypattern 1.2.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| xypattern-1.2.3.tar.gz | 21.5 kB | Details |
Built distributions (wheels)
Total release size:4.4 MB
Release files / xypattern-1.2.3.tar.gz
| Download URL | xypattern-1.2.3.tar.gz |
|---|---|
| Size | 21.5 kB |
| Tags | Source |
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| Tags | CPython 3.8 macOS 15.0+ ARM64 |
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SHA-256 checksum How to use checksums |
20642fa28e71aaf71d82651ff257b2e36003d49fd4cf108ec5e7d1f932c29c85
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BLAKE2b-256 checksum How to use checksums |
73b34311d6d02b09fc1e1c18bf9d8e6c43e4f9ca2d4c485da69dce697706e681
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
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Signed by GitHub Actions, verified by PyPI on Sep 26, 2025.
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