# LocalCartesian
Fast GPS to local Cartesian coordinate conversion using [GeographicLib](https://github.com/geographiclib/geographiclib).
## Description
This package provides efficient conversion between GPS coordinates (latitude, longitude) and local Cartesian coordinates (x, y). It uses the GeographicLib C++ library through Python bindings created with pybind11.
The package exists because GeographicLib's Python bindings don't include the equivalent of the C++ `LocalCartesian` class, which is essential for many geospatial applications.
## Installation
Install from PyPI using [uv](https://docs.astral.sh/uv/):
```bash
uv add localcartesian
```
or via pip globally, or inside any Python environment like virtualenv or conda:
```bash
pip install localcartesian
```
## Usage
```python
from localcartesian import gps2xy, xy2gps
# Define some GPS coordinates (lat, lon pairs)
gps_coords = [
[40.7128, -74.0060], # New York City
[40.7589, -73.9851], # Times Square
[40.6892, -74.0445], # Statue of Liberty
]
# Define origin point (lat, lon, altitude)
origin = [40.7128, -74.0060, 0.0] # NYC as origin
# Convert GPS to local Cartesian coordinates
local_coords = gps2xy(gps_coords, origin)
print("Local coordinates:", local_coords)
# Convert back to GPS coordinates
gps_back = xy2gps(local_coords, origin)
print("GPS coordinates:", gps_back)
```
## API Reference
### `gps2xy(latlon, origin_latlonalt)`
Convert GPS coordinates to local Cartesian coordinates.
**Parameters:**
- `latlon`: List of [latitude, longitude] pairs
- `origin_latlonalt`: Origin point as [latitude, longitude, altitude]
**Returns:**
- List of [x, y] coordinate pairs in meters
### `xy2gps(xy, origin_latlonalt)`
Convert local Cartesian coordinates to GPS coordinates.
**Parameters:**
- `xy`: List of [x, y] coordinate pairs in meters
- `origin_latlonalt`: Origin point as [latitude, longitude, altitude]
**Returns:**
- List of [latitude, longitude] pairs
## Development
### Building from Source Locally
Clone the repository and navigate to the project directory:
```bash
git clone https://github.com/PastorD/localcartesian.git
cd localcartesian
uv sync --dev
```
It will fetch the GeographicLib binaries, build the C++ extension, and install the package in editable mode. You can now import and use `localcartesian` in your Python environment. See `examples/basic_usage.py` for example usage.
### Generate multiple wheels locally
For Linux
```bash
uvx cibuildwheel --platform linux \
--only "cp39-manylinux_x86_64 cp310-manylinux_x86_64 \
cp311-manylinux_x86_64 cp312-manylinux_x86_64 cp313-manylinux_x86_64"
```
For MacOS
```bash
uvx cibuildwheel --platform macos \
--only "cp39-macosx_x86_64 cp310-macosx_x86_64 cp311-macosx_x86_64 cp312-macosx_x86_64 \
cp39-macosx_arm64 cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64"
```
### Running Tests
```bash
uv sync --extra test
uv run pytest
```
## License
This project is licensed under the MIT License.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Raw data
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"description": "# LocalCartesian\n\nFast GPS to local Cartesian coordinate conversion using [GeographicLib](https://github.com/geographiclib/geographiclib).\n\n## Description\n\nThis package provides efficient conversion between GPS coordinates (latitude, longitude) and local Cartesian coordinates (x, y). It uses the GeographicLib C++ library through Python bindings created with pybind11.\n\nThe package exists because GeographicLib's Python bindings don't include the equivalent of the C++ `LocalCartesian` class, which is essential for many geospatial applications.\n\n## Installation\n\nInstall from PyPI using [uv](https://docs.astral.sh/uv/):\n```bash\nuv add localcartesian\n```\nor via pip globally, or inside any Python environment like virtualenv or conda:\n```bash\npip install localcartesian\n```\n\n## Usage\n\n```python\nfrom localcartesian import gps2xy, xy2gps\n\n# Define some GPS coordinates (lat, lon pairs)\ngps_coords = [\n [40.7128, -74.0060], # New York City\n [40.7589, -73.9851], # Times Square\n [40.6892, -74.0445], # Statue of Liberty\n]\n\n# Define origin point (lat, lon, altitude)\norigin = [40.7128, -74.0060, 0.0] # NYC as origin\n\n# Convert GPS to local Cartesian coordinates\nlocal_coords = gps2xy(gps_coords, origin)\nprint(\"Local coordinates:\", local_coords)\n\n# Convert back to GPS coordinates\ngps_back = xy2gps(local_coords, origin)\nprint(\"GPS coordinates:\", gps_back)\n```\n\n## API Reference\n\n### `gps2xy(latlon, origin_latlonalt)`\n\nConvert GPS coordinates to local Cartesian coordinates.\n\n**Parameters:**\n- `latlon`: List of [latitude, longitude] pairs\n- `origin_latlonalt`: Origin point as [latitude, longitude, altitude]\n\n**Returns:**\n- List of [x, y] coordinate pairs in meters\n\n### `xy2gps(xy, origin_latlonalt)`\n\nConvert local Cartesian coordinates to GPS coordinates.\n\n**Parameters:**\n- `xy`: List of [x, y] coordinate pairs in meters\n- `origin_latlonalt`: Origin point as [latitude, longitude, altitude]\n\n**Returns:**\n- List of [latitude, longitude] pairs\n\n## Development\n\n### Building from Source Locally\n\nClone the repository and navigate to the project directory: \n```bash\ngit clone https://github.com/PastorD/localcartesian.git\ncd localcartesian\nuv sync --dev\n```\nIt will fetch the GeographicLib binaries, build the C++ extension, and install the package in editable mode. You can now import and use `localcartesian` in your Python environment. See `examples/basic_usage.py` for example usage.\n\n### Generate multiple wheels locally\n\nFor Linux\n```bash\nuvx cibuildwheel --platform linux \\\n --only \"cp39-manylinux_x86_64 cp310-manylinux_x86_64 \\\n cp311-manylinux_x86_64 cp312-manylinux_x86_64 cp313-manylinux_x86_64\"\n```\n\nFor MacOS\n```bash\nuvx cibuildwheel --platform macos \\\n --only \"cp39-macosx_x86_64 cp310-macosx_x86_64 cp311-macosx_x86_64 cp312-macosx_x86_64 \\\n cp39-macosx_arm64 cp310-macosx_arm64 cp311-macosx_arm64 cp312-macosx_arm64\"\n```\n\n### Running Tests\n\n```bash\nuv sync --extra test\nuv run pytest\n```\n\n## License\n\nThis project is licensed under the MIT License.\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.",
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