pure Python (no prereqs) coordinate conversions, following convention of several popular Matlab routines.
Python 3-D coordinate conversions
Pure Python (no prerequistes beyond Python itself) 3-D geographic coordinate conversions and geodesy. API similar to popular $1000 Matlab Mapping Toolbox routines for Python PyMap3D is intended for non-interactive use on massively parallel (HPC) and embedded systems.
Thanks to our contributors.
Similar toolboxes in other code languages
Pymap3d is compatible with Python ≥ 3.7 including PyPy. Numpy and AstroPy are optional; algorithms from Vallado and Meeus are used if AstroPy is not present.
python3 -m pip install pymap3d
or for the latest development code:
git clone https://github.com/geospace-code/pymap3d pip install -e pymap3d
One can verify Python functionality after installation by:
Where consistent with the definition of the functions, all arguments may be arbitrarily shaped (scalar, N-D array).
import pymap3d as pm x,y,z = pm.geodetic2ecef(lat,lon,alt) az,el,range = pm.geodetic2aer(lat, lon, alt, observer_lat, observer_lon, 0)
aer = (az,el,slantrange) obslla = (obs_lat,obs_lon,obs_alt) lla = pm.aer2geodetic(*aer,*obslla)
lla is comprised of scalar or N-D arrays
Example scripts are in the examples directory.
Native Python float is typically 64 bit. Numpy can select real precision bits: 32, 64, 128, etc.
Popular mapping toolbox functions ported to Python include the following, where the source coordinate system (before the "2") is converted to the desired coordinate system:
aer2ecef aer2enu aer2geodetic aer2ned ecef2aer ecef2enu ecef2enuv ecef2geodetic ecef2ned ecef2nedv ecef2eci eci2ecef eci2aer aer2eci geodetic2eci eci2geodetic enu2aer enu2ecef enu2geodetic geodetic2aer geodetic2ecef geodetic2enu geodetic2ned ned2aer ned2ecef ned2geodetic azel2radec radec2azel lookAtSpheroid track2 departure meanm rcurve rsphere geod2geoc geoc2geod geodetic2spherical spherical2geodetic
Vincenty functions "vincenty.vreckon" and "vincenty.vdist" are accessed like:
import pymap3d.vincenty as pmv lat2, lon2 = pmv.vreckon(lat1, lon1, ground_range_m, azimuth_deg) dist_m, azimuth_deg = pmv.vdist(lat1, lon1, lat2, lon2)
- loxodrome_inverse: rhumb line distance and azimuth between ellipsoid points (lat,lon) akin to Matlab
- geodetic latitude transforms to/from: parametric, authalic, isometric, and more in pymap3d.latitude
- AER: Azimuth, Elevation, Range
- ECEF: Earth-centered, Earth-fixed
- ECI: Earth-centered Inertial using IERS via
- ENU: East North Up
- NED: North East Down
- radec: right ascension, declination
Command line convenience functions provided include:
python -m pymap3d.vdist python -m pymap3d.vreckon
array vs scalar
Use of pymap3d on embedded systems or other streaming data applications often deal with scalar position data. These data are handled efficiently with the Python math stdlib module. Vector data can be handled via list comprehension.
Those needing multidimensional data with SIMD and other Numpy and/or PyPy accelerated performance can do so automatically by installing Numpy. pymap3d seamlessly falls back to Python's math module if Numpy isn't present. To keep the code clean, only scalar data can be used without Numpy. As noted above, use list comprehension if you need vector data without Numpy.
- Atmospheric effects neglected in all functions not invoking AstroPy. Would need to update code to add these input parameters (just start a GitHub Issue to request).
- Planetary perturbations and nutation etc. not fully considered.
As compared to PyProj:
- PyMap3D does not require anything beyond pure Python for most transforms
- Astronomical conversions are done using (optional) AstroPy for established accuracy
- PyMap3D API is similar to Matlab Mapping Toolbox, while PyProj's interface is quite distinct
- PyMap3D intrinsically handles local coordinate systems such as ENU, while PyProj ENU requires some additional effort.
- PyProj is oriented towards points on the planet surface, while PyMap3D handles points on or above the planet surface equally well, particularly important for airborne vehicles and remote sensing.
At this time,
is not supported.
Let us know if this is of interest.
Impacts on performance would have to be considered before making Quantity a first-class citizen.
For now, you can workaround by passing in the
.value of the variable.
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