| Name | karney JSON |
| Version |
1.0.10
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| home_page | None |
| Summary | Solves the direct and inverse geodesic problem. |
| upload_time | 2024-09-30 12:13:40 |
| maintainer | None |
| docs_url | None |
| author | Per A. Brodtkorb |
| requires_python | >=3.8.0 |
| license | MIT |
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# Introduction to Karney
[](https://badge.fury.io/py/karney)
[](https://karney.readthedocs.io/en/latest/)
[](https://github.com/pbrod/karney/actions/workflows/CI-CD.yml)
The `karney` library provides native Python implementations of a subset of the C++ library, GeographicLib.
Currently the following operations are implemented:
* Calculate the surface distance between two geographical positions.
* Find the destination point given start point, azimuth/bearing and distance.
All the functions are vectorized and offer speeds comparable to compiled C++ code when operating on arrays.
Some common features of these functions:
Angles (latitude, longitude, azimuth) are measured in degrees or radians.
Distances are measured in meters.
The ellipsoid is specified as [a, f], where a = equatorial radius and f = flattening.
Keep |f| <= 1/50 for full double precision accuracy.
## Installation
```bash
$ pip install karney
```
## Usage
Below the solution to two geodesic problems are given.
### Surface distance
Find the surface distance sAB (i.e. great circle distance) between two
positions A and B. The heights of A and B are ignored, i.e. if they don't have
zero height, we seek the distance between the points that are at the surface of
the Earth, directly above/below A and B. Use Earth radius 6371e3 m.
Compare the results with exact calculations for the WGS-84 ellipsoid.
In geodesy this is known as "The second geodetic problem" or
"The inverse geodetic problem" for a sphere/ellipsoid.
Solution for a sphere:
>>> import numpy as np
>>> from karney.geodesic import rad, sphere_distance_rad, distance
>>> latlon_a = (88, 0)
>>> latlon_b = (89, -170)
>>> latlons = latlon_a + latlon_b
>>> r_Earth = 6371e3 # m, mean Earth radius
>>> s_AB = sphere_distance_rad(*rad(latlons))[0]*r_Earth
>>> s_AB = distance(*latlons, a=r_Earth, f=0, degrees=True)[0] # or alternatively
>>> 'Ex5: Great circle = {:5.2f} km'.format(s_AB / 1000)
'Ex5: Great circle = 332.46 km'
Exact solution for the WGS84 ellipsoid:
>>> s_12, azi1, azi2 = distance(*latlons, degrees=True)
>>> 'Ellipsoidal distance = {:5.2f} km'.format(s_12 / 1000)
'Ellipsoidal distance = 333.95 km'
See also
[Example 5 at www.navlab.net](http://www.navlab.net/nvector/#example_5)
### A and azimuth/distance to B
We have an initial position A, direction of travel given as an azimuth
(bearing) relative to north (clockwise), and finally the
distance to travel along a great circle given as sAB.
Use Earth radius 6371e3 m to find the destination point B.
In geodesy this is known as "The first geodetic problem" or
"The direct geodetic problem" for a sphere.
>>> import numpy as np
>>> from karney.geodesic import reckon
>>> lat, lon = 80, -90
>>> msg = 'Ex8, Destination: lat, lon = {:4.4f} deg, {:4.4f} deg'
Greatcircle solution:
>>> lat2, lon2, azi_b = reckon(lat, lon, distance=1000, azimuth=200, a=6371e3, f=0, degrees=True)
>>> msg.format(lat2, lon2)
'Ex8, Destination: lat, lon = 79.9915 deg, -90.0177 deg'
>>> np.allclose(azi_b, -160.0174292682187)
True
Exact solution:
>>> lat_b, lon_b, azi_b = reckon(lat, lon, distance=1000, azimuth=200, degrees=True)
>>> msg.format(lat_b, lon_b)
'Ex8, Destination: lat, lon = 79.9916 deg, -90.0176 deg'
>>> np.allclose(azi_b, -160.01742926820506)
True
See also
[Example 8 at www.navlab.net](http://www.navlab.net/nvector/#example_8)
## Contributing
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
## License
`karney` was created by Per A. Brodtkorb and is licensed under the terms of the MIT/X11 license.
## Acknowledgements
The [`karney` package](http://pypi.python.org/pypi/karney/) for
[Python](https://www.python.org/) was written by Per A. Brodtkorb at
[FFI (The Norwegian Defence Research Establishment)](http://www.ffi.no/en>)
based on the [Geographic toolbox](https://github.com/geographiclib/geographiclib-octave)
written by Charles Karney for [Matlab](http://www.mathworks.com) and [GNU Octave](https://octave.org>).
The karney.geodesic module is a vectorized reimplementation of the Matlab/Octave GeographicLib toolbox.
The content is based on the article by [Karney, 2013](https://doi.org/10.1007/s00190-012-0578-z).
Thus this article should be cited in publications using the software.
The `karney` package structure was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
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"description": "# Introduction to Karney\n\n[](https://badge.fury.io/py/karney)\n[![Documentation](https://readthedocs.org/projects/karney/badge/?svg=true \"documentation\")](https://karney.readthedocs.io/en/latest/)\n[](https://github.com/pbrod/karney/actions/workflows/CI-CD.yml)\n\n\nThe `karney` library provides native Python implementations of a subset of the C++ library, GeographicLib.\nCurrently the following operations are implemented:\n\n* Calculate the surface distance between two geographical positions.\n\n* Find the destination point given start point, azimuth/bearing and distance.\n\n\nAll the functions are vectorized and offer speeds comparable to compiled C++ code when operating on arrays.\n\nSome common features of these functions:\n\nAngles (latitude, longitude, azimuth) are measured in degrees or radians.\nDistances are measured in meters.\nThe ellipsoid is specified as [a, f], where a = equatorial radius and f = flattening.\nKeep |f| <= 1/50 for full double precision accuracy.\n\n\n## Installation\n\n```bash\n$ pip install karney\n```\n\n\n## Usage\n\nBelow the solution to two geodesic problems are given.\n\n### Surface distance\nFind the surface distance sAB (i.e. great circle distance) between two\npositions A and B. The heights of A and B are ignored, i.e. if they don't have\nzero height, we seek the distance between the points that are at the surface of\nthe Earth, directly above/below A and B. Use Earth radius 6371e3 m.\nCompare the results with exact calculations for the WGS-84 ellipsoid.\n\nIn geodesy this is known as \"The second geodetic problem\" or\n\"The inverse geodetic problem\" for a sphere/ellipsoid.\n\n\nSolution for a sphere:\n\n >>> import numpy as np\n >>> from karney.geodesic import rad, sphere_distance_rad, distance\n\n >>> latlon_a = (88, 0)\n >>> latlon_b = (89, -170)\n >>> latlons = latlon_a + latlon_b\n >>> r_Earth = 6371e3 # m, mean Earth radius\n >>> s_AB = sphere_distance_rad(*rad(latlons))[0]*r_Earth\n >>> s_AB = distance(*latlons, a=r_Earth, f=0, degrees=True)[0] # or alternatively\n\n >>> 'Ex5: Great circle = {:5.2f} km'.format(s_AB / 1000)\n 'Ex5: Great circle = 332.46 km'\n\nExact solution for the WGS84 ellipsoid:\n\n >>> s_12, azi1, azi2 = distance(*latlons, degrees=True)\n >>> 'Ellipsoidal distance = {:5.2f} km'.format(s_12 / 1000)\n 'Ellipsoidal distance = 333.95 km'\n\nSee also\n [Example 5 at www.navlab.net](http://www.navlab.net/nvector/#example_5)\n\n\n### A and azimuth/distance to B\n\nWe have an initial position A, direction of travel given as an azimuth\n(bearing) relative to north (clockwise), and finally the\ndistance to travel along a great circle given as sAB.\nUse Earth radius 6371e3 m to find the destination point B.\n\nIn geodesy this is known as \"The first geodetic problem\" or\n\"The direct geodetic problem\" for a sphere.\n\n\n >>> import numpy as np\n >>> from karney.geodesic import reckon\n >>> lat, lon = 80, -90\n >>> msg = 'Ex8, Destination: lat, lon = {:4.4f} deg, {:4.4f} deg'\n\nGreatcircle solution:\n\n >>> lat2, lon2, azi_b = reckon(lat, lon, distance=1000, azimuth=200, a=6371e3, f=0, degrees=True)\n\n >>> msg.format(lat2, lon2)\n 'Ex8, Destination: lat, lon = 79.9915 deg, -90.0177 deg'\n\n >>> np.allclose(azi_b, -160.0174292682187)\n True\n\nExact solution:\n\n >>> lat_b, lon_b, azi_b = reckon(lat, lon, distance=1000, azimuth=200, degrees=True)\n >>> msg.format(lat_b, lon_b)\n 'Ex8, Destination: lat, lon = 79.9916 deg, -90.0176 deg'\n\n >>> np.allclose(azi_b, -160.01742926820506)\n True\n\n\nSee also\n [Example 8 at www.navlab.net](http://www.navlab.net/nvector/#example_8)\n\n\t\n\n## Contributing\n\nInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.\n\n## License\n\n`karney` was created by Per A. Brodtkorb and is licensed under the terms of the MIT/X11 license.\n\n\n## Acknowledgements\n\nThe [`karney` package](http://pypi.python.org/pypi/karney/) for\n[Python](https://www.python.org/) was written by Per A. Brodtkorb at\n[FFI (The Norwegian Defence Research Establishment)](http://www.ffi.no/en>)\nbased on the [Geographic toolbox](https://github.com/geographiclib/geographiclib-octave)\nwritten by Charles Karney for [Matlab](http://www.mathworks.com) and [GNU Octave](https://octave.org>).\nThe karney.geodesic module is a vectorized reimplementation of the Matlab/Octave GeographicLib toolbox.\n\nThe content is based on the article by [Karney, 2013](https://doi.org/10.1007/s00190-012-0578-z).\nThus this article should be cited in publications using the software.\n\n\n\nThe `karney` package structure was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).\n\n",
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