bloodmoon

Name	bloodmoon JSON
Version	0.1.0 JSON
	download
home_page	None
Summary	A library for analyzing data and simulations from the WFM coded mask instrument.
upload_time	2025-01-08 14:42:16
maintainer	None
docs_url	None
author	None
requires_python	>=3.11
license	MIT License Copyright (c) 2025 Giuseppe Dilillo Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
keywords	astrophysics coded masks
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # Bloodmoon

A Python library for analyzing data from the Wide Field Monitor (WFM) coded mask instrument. Bloodmoon provides tools for:
- Image reconstruction
- Source detection and parameter estimation
- Detector effects modeling (vignetting, PSF)
- Dual-camera source localization

> ⚠️ **Note**: Bloodmoon is under active development. APIs may change between versions.


## Installation

### PyPI

```bash
pip install bloodmoon
```

### From Source

Installing from source is necessary when doing development work. The exact process depends on your platform but will generally require:
- Git
- Python 3.11 or later
- pip
- venv or conda (for environment management)

#### Using venv
```bash
# Clone repository
git clone https://github.com/peppedilillo/bloodmoon.git
cd bloodmoon

# Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate

# Install package in editable mode with development dependencies
pip install -e ".[dev]"
```

#### Using Conda
```bash
# Clone repository
git clone https://github.com/peppedilillo/bloodmoon.git
cd bloodmoon

# Create and activate conda environment
conda create -n "bloodmoon" python=3.11
conda activate bloodmoon

# Install package in editable mode with development dependencies
pip install -e ".[dev]"
```

## Quick Start

```python
import bloodmoon as bm

# Load camera configuration
wfm = bm.codedmask("wfm_mask.fits")

# Load simulation data
filepaths = bm.simulation_files("simdir/")
sdl1a = bm.simulation(filepaths["cam1a"]["reconstructed"])
sdl1b = bm.simulation(filepaths["cam1b"]["reconstructed"])

# Create detector images
detector, bins = bm.count(wfm, sdl1a.data)

# Reconstruct sky image
sky = bm.decode(wfm, detector)

# Run iterative source detection
for sources, residuals in bm.iros(wfm, sdl1a, sdl1b, max_iterations=10):
    # Process detected sources...
    pass
```

For more take a look at our [demo](demo/demo.ipynb).

## Development

### Running Tests

Assuming you installed from sources, and your source living into `bloodmon` directory.

```bash
cd bloodmoon
python -m unittest
```

## Contributing

Contributions are welcome! Before submitting a pull request:

1. Ensure all tests pass: `python -m unittest`
2. Format code with black: `black -l 120 .`
3. Sort imports with isort: `isort --profile=google .`

For bug reports and feature requests, please open an issue.
            

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    "description": "# Bloodmoon\n\nA Python library for analyzing data from the Wide Field Monitor (WFM) coded mask instrument. Bloodmoon provides tools for:\n- Image reconstruction\n- Source detection and parameter estimation\n- Detector effects modeling (vignetting, PSF)\n- Dual-camera source localization\n\n> \u26a0\ufe0f **Note**: Bloodmoon is under active development. APIs may change between versions.\n\n\n## Installation\n\n### PyPI\n\n```bash\npip install bloodmoon\n```\n\n### From Source\n\nInstalling from source is necessary when doing development work. The exact process depends on your platform but will generally require:\n- Git\n- Python 3.11 or later\n- pip\n- venv or conda (for environment management)\n\n#### Using venv\n```bash\n# Clone repository\ngit clone https://github.com/peppedilillo/bloodmoon.git\ncd bloodmoon\n\n# Create and activate virtual environment\npython3 -m venv venv\nsource venv/bin/activate  # On Windows: .\\venv\\Scripts\\activate\n\n# Install package in editable mode with development dependencies\npip install -e \".[dev]\"\n```\n\n#### Using Conda\n```bash\n# Clone repository\ngit clone https://github.com/peppedilillo/bloodmoon.git\ncd bloodmoon\n\n# Create and activate conda environment\nconda create -n \"bloodmoon\" python=3.11\nconda activate bloodmoon\n\n# Install package in editable mode with development dependencies\npip install -e \".[dev]\"\n```\n\n## Quick Start\n\n```python\nimport bloodmoon as bm\n\n# Load camera configuration\nwfm = bm.codedmask(\"wfm_mask.fits\")\n\n# Load simulation data\nfilepaths = bm.simulation_files(\"simdir/\")\nsdl1a = bm.simulation(filepaths[\"cam1a\"][\"reconstructed\"])\nsdl1b = bm.simulation(filepaths[\"cam1b\"][\"reconstructed\"])\n\n# Create detector images\ndetector, bins = bm.count(wfm, sdl1a.data)\n\n# Reconstruct sky image\nsky = bm.decode(wfm, detector)\n\n# Run iterative source detection\nfor sources, residuals in bm.iros(wfm, sdl1a, sdl1b, max_iterations=10):\n    # Process detected sources...\n    pass\n```\n\nFor more take a look at our [demo](demo/demo.ipynb).\n\n## Development\n\n### Running Tests\n\nAssuming you installed from sources, and your source living into `bloodmon` directory.\n\n```bash\ncd bloodmoon\npython -m unittest\n```\n\n## Contributing\n\nContributions are welcome! Before submitting a pull request:\n\n1. Ensure all tests pass: `python -m unittest`\n2. Format code with black: `black -l 120 .`\n3. Sort imports with isort: `isort --profile=google .`\n\nFor bug reports and feature requests, please open an issue.",
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