import os, array, numarray, math, tempfile
_rad2dg = 180./math.pi
_dg2rad = math.pi/180.
class Proj:
"""
peforms cartographic transformations (converts from longitude,latitude
to native map projection x,y coordinates and vice versa) using proj
(http://www.remotesensing.org/proj/).
__init__ method sets up projection information.
__call__ method compute transformations.
See docstrings for __init__ and __call__ for details.
Jeff Whitaker <jeffrey.s.whitaker@noaa.gov>
20040711
"""
def __init__(self,params,projcmd='proj'):
"""
initialize a Proj class instance.
Input 'params' is a dictionary containing proj map
projection control parameter key/value pairs.
See the proj documentation (http://www.remotesensing.org/proj/)
for details.
Optional keyword 'projcmd' is the full path to the proj exectuable.
Default will work if proj is in the unix PATH.
"""
# make sure proj parameter specified.
# (no other checking done in proj parameters)
if 'proj' not in params.keys():
raise KeyError, "need to specify proj parameter"
# build proj command.
for key,value in map(None,params.keys(),params.values()):
if key == 'x_0' or key == 'y_0':
value=10*value # convert false easting, northing to cm.
projcmd = projcmd + " +"+key+"="+str(value)
self.projcmd = projcmd + ' -b'
def __call__(self,lon,lat,inverse=False):
"""
Calling a Proj class instance with the arguments lon, lat will
convert lon/lat (in degrees) to x/y native map projection
coordinates (in meters). If optional keyword 'inverse' is
True (default is False), the inverse transformation from x/y
to lon/lat is performed.
Example usage:
>>> from proj import Proj
>>> params = {}
>>> params['proj'] = 'lcc' # lambert conformal conic
>>> params['lat_1'] = 30. # standard parallel 1
>>> params['lat_2'] = 50. # standard parallel 2
>>> params['lon_0'] = -96 # central meridian
>>> map = Proj(params)
>>> x,y = map(-107,40) # find x,y coords of lon=-107,lat=40
>>> print x,y
-92272.1004461 477477.890988
lon,lat can be either scalar floats or numarray arrays.
"""
npts = 1
# if inputs are numarray arrays, get shape and total number of pts.
try:
shapein = lon.shape
npts = reduce(lambda x, y: x*y, shapein)
lontypein = lon.typecode()
lattypein = lat.typecode()
except:
shapein = False
# make sure inputs have same shape.
if shapein and lat.shape != shapein:
raise ValueError, 'lon, lat must be scalars or numarray arrays with the same shape'
# make a rank 1 array with x/y (or lon/lat) pairs.
xy = numarray.zeros(2*npts,'d')
xy[::2] = numarray.ravel(lon)
xy[1::2] = numarray.ravel(lat)
# convert degrees to radians, meters to cm.
if not inverse:
xy = _dg2rad*xy
else:
xy = 10.*xy
# write input data to binary file.
xyout = array.array('d')
xyout.fromlist(xy.tolist())
# set up cmd string, scale factor for output.
if inverse:
cmd = self.projcmd+' -I'
scale = _rad2dg
else:
cmd = self.projcmd
scale = 0.1
# use pipes for input and output if amount of
# data less than default buffer size (usually 8192).
# otherwise use pipe for input, tempfile for output
if 2*npts*8 > 8192:
fd, fn=tempfile.mkstemp(); os.close(fd); stdout=open(fn,'rb')
cmd = cmd+' > '+fn
stdin=os.popen(cmd,'w')
xyout.tofile(stdin)
stdin.close()
outxy = scale*numarray.fromstring(stdout.read(),'d')
stdout.close()
os.remove(fn)
else:
stdin,stdout=os.popen2(cmd,mode='b')
xyout.tofile(stdin)
stdin.close()
outxy = scale*numarray.fromstring(stdout.read(),'d')
stdout.close()
# return numarray arrays or scalars, depending on type of input.
if shapein:
outx = numarray.reshape(outxy[::2],shapein).astype(lontypein)
outy = numarray.reshape(outxy[1::2],shapein).astype(lattypein)
else:
outx = outxy[0]; outy = outxy[1]
return outx,outy
if __name__ == "__main__":
params = {}
params['proj'] = 'lcc'
params['R'] = 63712000
params['lat_1'] = 50
params['lat_2'] = 50
params['lon_0'] = -107
awips221 = Proj(params)
# AWIPS grid 221 parameters
# (from http://www.nco.ncep.noaa.gov/pmb/docs/on388/tableb.html)
nx = 349; ny = 277; dx = 32463.41; dy = dx
llcornerx, llcornery = awips221(-145.5,1.)
params['x_0'] = -llcornerx # add cartesian offset so llcorner = (0,0)
params['y_0'] = -llcornery
awips221 = Proj(params)
# find 4 lon/lat corners of AWIPS grid 221.
llcornerx = 0.; llcornery = 0.
lrcornerx = dx*(nx-1); lrcornery = 0.
ulcornerx = 0.,; ulcornery = dy*(ny-1)
urcornerx = dx*(nx-1); urcornery = dy*(ny-1)
llcornerlon, llcornerlat = awips221(llcornerx, llcornery, inverse=True)
lrcornerlon, lrcornerlat = awips221(lrcornerx, lrcornery, inverse=True)
urcornerlon, urcornerlat = awips221(urcornerx, urcornery, inverse=True)
ulcornerlon, ulcornerlat = awips221(ulcornerx, ulcornery, inverse=True)
print '4 corners of AWIPS grid 221:'
print llcornerlon, llcornerlat
print lrcornerlon, lrcornerlat
print urcornerlon, urcornerlat
print ulcornerlon, ulcornerlat
print 'from GRIB docs'
print '(see http://www.nco.ncep.noaa.gov/pmb/docs/on388/tableb.html)'
print ' -145.5 1.0'
print ' -68.318 0.897'
print ' -2.566 46.352'
print ' 148.639 46.635'
# compute lons and lats for the whole AWIPS grid 221 (377x249).
x = numarray.zeros((nx,ny),'d')
y = numarray.zeros((nx,ny),'d')
x = dx*numarray.indices(x.shape)[0,:,:]
y = dy*numarray.indices(y.shape)[1,:,:]
import time; t1 = time.clock()
lons, lats = awips221(x, y, inverse=True)
t2 = time.clock()
print 'compute lats/lons for all points on AWIPS 221 grid (%sx%s)' %(nx,ny)
print 'max/min lons'
print min(numarray.ravel(lons)),max(numarray.ravel(lons))
print 'max/min lats'
print min(numarray.ravel(lats)),max(numarray.ravel(lats))
print 'took',t2-t1,'secs'
