def rastervals_in_unit(unit, lon_min, lat_min, cellsize, data, view='y-x+'):
# For some reason it is MUCH faster to do it this way.
if isinstance(unit, geometry.multipolygon.MultiPolygon):
return np.hstack([rastervals_in_unit(g,lon_min,lat_min,cellsize,data,view) for g in unit.geoms])
llc = unit.bounds[:2]
urc = unit.bounds[2:]
lon_min_in = int((llc[0]-lon_min)/cellsize)
lon_max_in = int((urc[0]-lon_min)/cellsize)+1
lat_min_in = int((llc[1]-lat_min)/cellsize)
lat_max_in = int((urc[1]-lat_min)/cellsize)+1
data_boxed_ = grid_convert(data,view,'x+y+')[lon_min_in:lon_max_in+1,lat_min_in:lat_max_in+1]
flat_shape = (-1,)+data_boxed_.shape[2:]
data_boxed = data_boxed_.reshape(flat_shape)
lon_boxed = np.arange(lon_min_in, lon_max_in+1)*cellsize + lon_min
lat_boxed = np.arange(lat_min_in, lat_max_in+1)*cellsize + lat_min
mlon_boxed, mlat_boxed = np.meshgrid(lon_boxed, lat_boxed)
mlon_boxed = grid_convert(mlon_boxed,'y+x+','x+y+')
mlat_boxed = grid_convert(mlat_boxed,'y+x+','x+y+')
p=[geom.Point(*pair) for pair in zip(mlon_boxed.ravel(), mlat_boxed.ravel())]
if isinstance(unit, geometry.polygon.Polygon):
p_in = set(iterops.contains(geometry.polygon.Polygon(unit.exterior.coords), p, True))
for hole in unit.interiors:
p_in -= set(iterops.contains(geometry.polygon.Polygon(hole.coords), p, True))
else:
p_in = iterops.contains(unit, p, True)
i_in = [p.index(p_in_) for p_in_ in p_in]
out = data_boxed[i_in]
return out
def exportAscii2(lon, lat, data, filename, view="y-x+"):
"Exports longitude and latitude vectors and a data masked array to ascii."
data = grid_convert(data, view, "y-x+")
if data.shape != (len(lat), len(lon)):
raise ValueError, "Data is wrong shape"
data.fill_value = np.asscalar(np.array(-9999).astype(data.dtype))
header = {
"ncols": len(lon),
"nrows": len(lat),
"cellsize": lon[1] - lon[0],
"xllcorner": lon.min(),
"yllcorner": lat.min(),
"NODATA_value": data.fill_value,
}
exportAscii(data.filled(), filename, header, True - data.mask)
def export_flt(lon, lat, data, filename, view="y-x+"):
"filename should have no extension; the '.hdr' and '.flt' extensions will be added automatically."
data = grid_convert(data, view, "y-x+")
if data.shape != (len(lat), len(lon)):
raise ValueError, "Data is wrong shape"
data.fill_value = np.asscalar(np.array(-9999).astype(data.dtype))
header = {
"ncols": len(lon),
"nrows": len(lat),
"cellsize": lon[1] - lon[0],
"xllcorner": lon.min(),
"yllcorner": lat.min(),
"NODATA_value": data.fill_value,
"byteorder": "LSBFIRST",
}
hfile = file(filename + ".hdr", "w")
for k, v in header.iteritems():
hfile.write("%s\t%s\r\n" % (k, v))
hfile.close()
dfile = npfile(filename + ".flt", order="C", endian="<", permission="w")
dfile.write_array(data.filled().astype("float32"))
dfile.close()
