Metadata-Version: 2.4
Name: rodhypix
Version: 0.1.1
Summary: Standalone reader for Rigaku .rodhypix detector images
Author-email: Robert Buecker <robert.buecker@rigaku.com>
License: BSD-3-Clause
Project-URL: Homepage, https://github.com/robertbuecker/rodhypix
Project-URL: Repository, https://github.com/robertbuecker/rodhypix
Project-URL: Issues, https://github.com/robertbuecker/rodhypix/issues
Keywords: rodhypix,hypix,rigaku,crystallography,microed,3ded,crysalispro
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Chemistry
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.20.0
Provides-Extra: viz
Requires-Dist: matplotlib>=3.3.0; extra == "viz"
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Requires-Dist: black>=22.0.0; extra == "dev"
Requires-Dist: flake8>=4.0.0; extra == "dev"
Dynamic: license-file

# rodhypix

Standalone reader for Rigaku `.rodhypix` detector images.

## Features

- Read native `.rodhypix` images without CrysAlisPro
- Access detector and experiment metadata
- Native C++ TY6 backend
- Pure Python fallback

## Installation

```bash
pip install rodhypix
```

On Windows, this will install native decompression from wheels without compilation.

Plotting support (only required for example notebooks):

```bash
pip install "rodhypix[viz]"
```

## Quick Start

```python
from rodhypix import RODImageReader, get_rod_info, read_rod_image

image = read_rod_image("snapshot.rodhypix")
info = get_rod_info("snapshot.rodhypix")

reader = RODImageReader("snapshot.rodhypix")
print(reader.get_decompression_method())
print(info["exposure_time_sec"])
```

## Public API

- `RODImageReader`
- `read_rod_image`
- `get_rod_info`
- `HAS_NATIVE_CPP`

## Included Material

- `rodhypix/rod_image_reader.py`: main reader implementation
- `rodhypix/ty6_backend_tools.py`: backend comparison and benchmark helpers
- `scripts/benchmark_ty6_backends.py`: CLI benchmark
- `examples/01_image_visualization.ipynb`: image visualization notebook

## Example Data

The extracted example dataset is stored in `example_data/exp_11317.zip`.
