[pyproj][] is a Python wrapper around [PROJ.4][].  Here's a quick
walkthrough.

Initialize a [geodetic][] converter:

    >>> from pyproj import Geod
    >>> g = Geod(ellps='clrk66')

where `ellps='clrk66'` selects [Clarke's 1866][clrk66] [reference
ellipsoid][rell].  `help(Geod.__new__)` gives a list of possible
ellipsoids.

Calculate the distance between two points, as well as the local
heading, try

    >>> lat1,lng1 = (40.7143528, -74.0059731)  # New York, NY
    >>> lat2,lng2 = (49.261226, -123.1139268)   # Vancouver, Canada
    >>> az12,az21,dist = g.inv(lng1,lat1,lng2,lat2)
    >>> az12,az21,dist
    (-59.10918706123901, 84.99453463527395, 3914198.2912370963)

which gives forward and back [azimuths][] as well as the geodesic
distance in meters.  Not that longitude comes *before* latitude in the
these pyproj argument lists.

Calculate the terminus of a geodesic from an initial point, azimuth,
and distance with:

    >>> lng3,lat3,az3 = g.fwd(lng1,lat1,az12, dist)
    >>> lat3,lng3,az3
    (49.26122600306212, -123.11392684861474, 84.99453467574762)

Plan your trip with:

    >>> pts = g.npts(lng1,lat1,lng2,lat2,npts=5)
    >>> pts.insert(0, (lng1, lat1))
    >>> pts.append((lng2, lat2))
    >>> import numpy
    >>> npts = numpy.array(pts)
    >>> npts
    array([[ -74.0059731 ,   40.7143528 ],
           [ -80.93566289,   43.52686057],
           [ -88.48167748,   45.87969433],
           [ -96.61187851,   47.6930911 ],
           [-105.22271807,   48.89347605],
           [-114.13503215,   49.42510006],
           [-123.1139268 ,   49.261226  ]])

To plot the above New York to Vancouver route on a flat map, we need a
`Proj` instance:

    >>> from pyproj import Proj
    >>> awips221 = Proj(proj='lcc', R=6371200, lat_1=50, lat_2=50,
    ...     lon_0=-107, ellps='clrk66')
    >>> awips218 = Proj(proj='lcc', R=6371200, lat_1=25, lat_2=25,
    ...     lon_0=-95, ellps='clrk66')  #x_0=-llcrnrx,y_0=-llcrnry)

    #llcrnrlon,llcrnrlat are lon and lat (in degrees) of lower
    #    left hand corner of projection region.

where `proj='lcc'` selects the [Lambert conformal conic][lcc]
projection for the x/y points, and `ellps='clrk66'` selects the
reference ellipsoid for the lat/lng coordinates.  The other
coordinates are LCC parameters that select the [AWIPS 221][awips221]
and [AWIPS 226][awips226] projections respectively (`lat_1`
corresponds to `Latin1`, `lat_2` corresponds to `Latin2`, and `lon_0`
corresponds to `Lov`; see [this description][lcc-param] of the
two-standard-parallel LCC and its PROJ.4 parameters).

Convert our lat/lng pairs into grid points:

    >>> awips221(lng1, lat1)
    (2725283.842678774, 5823260.730665273)
    >>> x221,y221 = awips221(npts[:,0], npts[:,1])
    >>> # xy221 = numpy.concatenate((a1, a2, ...), axis=0)  # numpy-2.0
    >>> xy221 = numpy.ndarray(shape=npts.shape, dtype=npts.dtype)
    >>> xy221[:,0] = x221
    >>> xy221[:,1] = y221
    >>> xy221
    array([[ 2725283.84267877,  5823260.73066527],
           [ 2071820.3526011 ,  5892518.49630526],
           [ 1422529.71760395,  5967565.49899035],
           [  775650.03731228,  6046475.43928965],
           [  129946.46495299,  6127609.80532071],
           [ -515306.57275941,  6209785.69230076],
           [-1160447.80254759,  6292455.41884832]])

Finally, you can convert points from one projection to another.

    >>> from pyproj import transform
    >>> x218,y218 = transform(awips221, awips218, x221, y221)
    >>> xy218 = numpy.ndarray(shape=npts.shape, dtype=npts.dtype)
    >>> xy218[:,0] = x218
    >>> xy218[:,1] = y218
    >>> xy218
    array([[ 1834251.59591561,  4780900.70184736],
           [ 1197541.13209718,  5028862.9881648 ],
           [  542391.04388716,  5258740.71523961],
           [ -131577.34942316,  5464828.45934687],
           [ -822685.42269932,  5641393.59760613],
           [-1527077.85176048,  5783597.16169582],
           [-2239159.34620498,  5888495.91009021]])

Another useful coordinate system is the [Universal Transverse
Mercator][UTM] projection which slices the world into [zones][].

    >>> p = Proj(proj='utm', zone=10, ellps='clrk66')

Putting everything together, here's a route map based on digital
lat/lng pairs stored in a text file:

    >>> from numpy import array
    >>> from pylab import plot, show
    >>> from pyproj import Geod, Proj
    >>> latlng = array([[float(x) for x in ln.split()]
    ...                for ln in open('coords', 'r')
    ...                if not ln.startswith('#')])
    >>> g = Geod(ellps='WGS84')
    >>> az12s,az21s,dists = g.inv(latlng[:-1,1], latlng[:-1,0],
    ...                           latlng[1:,1], latlng[1:,0])
    >>> print('total distance: %g m' % dists.sum())
    total distance: 2078.93 m
    >>> mlng = latlng[:,1].mean()
    >>> zone = int(round((mlng + 180) / 6.))
    >>> p = Proj(proj='utm', zone=zone, ellps='WGS84')
    >>> xs,ys = p(latlng[:,1], latlng[:,0])
    >>> lines = plot(xs, ys, 'r.-')
    >>> show()

I've written up a simple script using this approach:
[[geoscript/maproute.py]].  I've also written up a simple script to
draw a map with labeled points: [[geoscript/maplabel.py]].

Note that you can easily get lat/lng pairs using [geopy][] (ebuild in
my [[Gentoo overlay]]):

    >>> import geopy
    >>> g = geopy.geocoders.Google()
    >>> place1,(lat1,lng1) = g.geocode("New York, NY")
    >>> place2,(lat2,lng2) = g.geocode("Vancouver, Canada")
    >>> place1,(lat1,lng1)
    (u'New York, NY, USA', (40.7143528, -74.0059731))
    >>> place2,(lat2,lng2)
    (u'Vancouver, BC, Canada', (49.261226, -123.1139268))

If you're looking for a more compact [[C++]] package for geographic
conversions, [GeographicLib][] looks promising.

[pyproj]: http://code.google.com/p/pyproj/
[PROJ.4]: http://trac.osgeo.org/proj/
[geodetic]: http://en.wikipedia.org/wiki/Geodesy
[clrk66]: http://en.wikipedia.org/wiki/Alexander_Ross_Clarke
[rell]: http://en.wikipedia.org/wiki/Reference_ellipsoid
[azimuths]: http://en.wikipedia.org/wiki/Azimuth
[LCC]: http://en.wikipedia.org/wiki/Lambert_conformal_conic_projection
[awips221]: http://www.nco.ncep.noaa.gov/pmb/docs/on388/tableb.html#GRID221
[awips226]: http://www.nco.ncep.noaa.gov/pmb/docs/on388/tableb.html#GRID218
[lcc-param]: http://www.remotesensing.org/geotiff/proj_list/lambert_conic_conformal_2sp.html
[UTM]: http://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system
[zones]: http://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system#UTM_zone
[geopy]: http://code.google.com/p/geopy/
[GeographicLib]: http://geographiclib.sourceforge.net/html/

[[!tag tags/fun]]
[[!tag tags/linux]]
[[!tag tags/python]]
[[!tag tags/tools]]