def buildmaptile(args):
(log, name, tilex, tiley, elxsize, elysize, lcarr, tifgeotrans, elgeoxform, wantCL) = args
(xminarr, xmaxarr, yminarr, ymaxarr) = lcarr
yamlfile = file(os.path.join('Regions', name, 'Region.yaml'))
self = yaml.load(yamlfile)
yamlfile.close()
offsetx = tilex * Region.prepTileSize
offsety = tiley * Region.prepTileSize
sizex = min(Region.prepTileSizeOverlap, elxsize - offsetx)
sizey = min(Region.prepTileSizeOverlap, elysize - offsety)
srs = osr.SpatialReference()
srs.ImportFromProj4(Region.t_srs)
driver = gdal.GetDriverByName("GTiff")
lctif = os.path.join(self.mapsdir, '%s.tif' % (self.lclayer))
lcextentsWhole = self.utmextents['landcover']
elfile = os.path.join(self.mapsdir, '%s-new.tif' % (self.ellayer))
oifile = os.path.join(self.mapsdir, '%s-new.tif' % (self.oilayer))
# GeoTIFF Image Tile
# eight bands: landcover, elevation, bathy, crust, oR, oG, oB, oA
# data type is GDT_Int16 (elevation can be negative)
log.log_debug(1,"Creating output image tile %d, %d with offset " \
"(%d, %d) and size (%d, %d)" % \
(tilex, tiley, offsetx, offsety, sizex, sizey))
tilename = os.path.join(self.regiondir, 'Tile_%04d_%04d.tif' % (tilex, tiley))
mapds = driver.Create(tilename, sizex, sizey, len(Region.rasters), GDT_Int16)
mapds.SetProjection(srs.ExportToWkt())
# overall map transform should match elevation map transform
geoxform = [elgeoxform[0] + offsetx * elgeoxform[1], elgeoxform[1], elgeoxform[2], \
elgeoxform[3] + offsety * elgeoxform[5], elgeoxform[4], elgeoxform[5]]
mapds.SetGeoTransform(geoxform)
# modify elarray and save it as raster band 2
log.log_debug(2,"Adjusting and storing elevation to GeoTIFF...")
elds = gdal.Open(elfile, GA_ReadOnly)
elarray = elds.GetRasterBand(1).ReadAsArray(offsetx, offsety, sizex, sizey)
elds = None
actualel = ((elarray - self.trim)/self.vscale)+self.sealevel
mapds.GetRasterBand(Region.rasters['elevation']).WriteArray(actualel)
elarray = None
actualel = None
# generate crust and save it as raster band 4
log.log_debug(2,"Adjusting and storing crust to GeoTIFF...")
newcrust = Crust(sizex, sizey, wantCL=wantCL)
crustarray = newcrust()
mapds.GetRasterBand(Region.rasters['crust']).WriteArray(crustarray)
crustarray = None
newcrust = None
# Compute new geographic tile extents for landcover
lcextents = {}
border = self.scale * self.maxdepth
lcxsize = elxsize + 2 * border # Total LC region size
lcysize = elysize + 2 * border
lctxsize = sizex + 2 * border # Current LC tile size
lctysize = sizey + 2 * border
lcextents['xmin'] = lcextentsWhole['xmin'] + \
(offsetx / float(lcxsize)) * \
(lcextentsWhole['xmax'] - lcextentsWhole['xmin'])
lcextents['xmax'] = lcextentsWhole['xmin'] + \
((offsetx + lctxsize) / float(lcxsize)) * \
(lcextentsWhole['xmax'] - lcextentsWhole['xmin'])
lcextents['ymax'] = lcextentsWhole['ymax'] - \
(offsety / float(lcysize)) * \
(lcextentsWhole['ymax'] - lcextentsWhole['ymin'])
lcextents['ymin'] = lcextentsWhole['ymax'] - \
((offsety + lctysize) / float(lcysize)) * \
(lcextentsWhole['ymax'] - lcextentsWhole['ymin'])
# Compute new array tile extents for landcover
lcxminarr = int(xminarr + (offsetx / float(lcxsize)) * (xmaxarr - xminarr))
lcxmaxarr = int(xminarr + ((offsetx + lctxsize) / float(lcxsize)) * (xmaxarr - xminarr))
lcyminarr = int(yminarr + (offsety / float(lcysize)) * (ymaxarr - yminarr))
lcymaxarr = int(yminarr + ((offsety + lctysize) / float(lcysize)) * (ymaxarr - yminarr))
# read landcover array
log.log_debug(2,"Warping and storing landcover and bathy data...")
log.log_debug(3,"LC extents: %s" % str(lcextents))
log.log_debug(3,"LC window: %s => %s" % (str([xminarr, xmaxarr, yminarr, ymaxarr]), \
str([lcxminarr, lcyminarr, lcxmaxarr-lcxminarr, lcymaxarr-lcyminarr])))
tifds = gdal.Open(lctif, GA_ReadOnly)
tifband = tifds.GetRasterBand(1)
values = tifband.ReadAsArray(lcxminarr, lcyminarr, lcxmaxarr-lcxminarr, lcymaxarr-lcyminarr)
tifnodata = tifband.GetNoDataValue() #nodata is treated as water, which is 11
if (tifnodata == None):
tifnodata = 0
values[values == tifnodata] = 11
values = values.flatten()
tifband = None
tifds = None
# 2. a new array of original scale coordinates must be created
# The following two lines should work fine still because x and y are offset into the array
tifxrange = [tifgeotrans[0] + tifgeotrans[1] * x for x in xrange(lcxminarr, lcxmaxarr)]
tifyrange = [tifgeotrans[3] + tifgeotrans[5] * y for y in xrange(lcyminarr, lcymaxarr)]
coords = numpy.array([(x, y) for y in tifyrange for x in tifxrange])
# 3. a new array of goal scale coordinates must be made
# landcover extents are used for the bathy depth array
# yes, it's confusing. sorry.
depthxlen = int((lcextents['xmax']-lcextents['xmin'])/self.scale)
depthylen = int((lcextents['ymax']-lcextents['ymin'])/self.scale)
depthxrange = [lcextents['xmin'] + self.scale * x for x in xrange(depthxlen)]
depthyrange = [lcextents['ymax'] - self.scale * y for y in xrange(depthylen)]
depthbase = numpy.array([(x, y) for y in depthyrange for x in depthxrange])
# 4. an inverse distance tree must be built from that
lcCLIDT = CLIDT(coords, values, depthbase, wantCL=wantCL)
# 5. the desired output comes from that inverse distance tree
deptharray = lcCLIDT()
deptharray.resize((depthylen, depthxlen))
lcCLIDT = None
# 6. Finish and store the band
lcarray = deptharray[self.maxdepth:-1*self.maxdepth, self.maxdepth:-1*self.maxdepth]
geotrans = [ lcextents['xmin'], self.scale, 0, lcextents['ymax'], 0, -1 * self.scale ]
projection = srs.ExportToWkt()
bathyarray = getBathy(deptharray, self.maxdepth, geotrans, projection)
mapds.GetRasterBand(Region.rasters['bathy']).WriteArray(bathyarray)
# perform terrain translation
# NB: figure out why this doesn't work up above
lcpid = self.lclayer[:3]
if lcpid in Terrain.translate:
trans = Terrain.translate[lcpid]
for key in trans:
lcarray[lcarray == key] = trans[key]
for value in numpy.unique(lcarray).flat:
if value not in Terrain.terdict:
self.warn("tile has bad value: " + str(value))
mapds.GetRasterBand(Region.rasters['landcover']).WriteArray(lcarray)
# read and store ortho arrays
tifds = gdal.Open(oifile, GA_ReadOnly)
for band in xrange(1,5): # That is, [1 2 3 4]
log.log_debug(2,"Cropping and storing ortho data (%s band)..." % "-rgba"[band])
tifband = tifds.GetRasterBand(band)
#values = tifband.ReadAsArray(oixminarr, oiyminarr, (oixmaxarr - oixminarr), (oiymaxarr - oiyminarr))
values = tifband.ReadAsArray(offsetx, offsety, sizex, sizey)
tifnodata = tifband.GetNoDataValue()
if (tifnodata == None):
tifnodata = 0
values[values == tifnodata] = -1 #Signal missing
tifband = None
mapds.GetRasterBand(band+Region.rasters['orthor']-1).WriteArray(values)
values = None
tifds = None
# close the dataset and append it to the tile list
mapds = None
return tilename
def buildmap(self, wantCL=True):
"""Use downloaded files and other parameters to build multi-raster map."""
# warp elevation data into new format
# NB: can't do this to landcover until mode algorithm is supported
elvrt = os.path.join(self.mapsdir, self.ellayer, '%s.vrt' % (self.ellayer))
elfile = os.path.join(self.mapsdir, self.ellayer, '%s.tif' % (self.ellayer))
elextents = self.albersextents['elevation']
warpcmd = 'gdalwarp -q -multi -t_srs "%s" -tr %d %d -te %d %d %d %d -r cubic %s %s -srcnodata "-340282346638529993179660072199368212480.000" -dstnodata 0' % (Region.t_srs, self.scale, self.scale, elextents['xmin'], elextents['ymin'], elextents['xmax'], elextents['ymax'], elvrt, elfile)
try:
os.remove(elfile)
except OSError:
pass
# NB: make this work on Windows too!
os.system("%s" % warpcmd)
elds = gdal.Open(elfile, GA_ReadOnly)
elgeotrans = elds.GetGeoTransform()
elband = elds.GetRasterBand(1)
elarray = elband.ReadAsArray(0, 0, elds.RasterXSize, elds.RasterYSize)
(elysize, elxsize) = elarray.shape
# update sealevel, trim and vscale
elmin = elband.GetMinimum()
elmax = elband.GetMaximum()
if elmin is None or elmax is None:
(elmin, elmax) = elband.ComputeRasterMinMax(False)
elmin = int(elmin)
elmax = int(elmax)
elband = None
elds = None
# sealevel depends upon elmin
minsealevel = 2
# if minimum elevation is below sea level, add extra space
if (elmin < 0):
minsealevel += int(-1.0*elmin/self.scale)
maxsealevel = Region.tileheight - Region.headroom
oldsealevel = self.sealevel
if (oldsealevel > maxsealevel or oldsealevel < minsealevel):
print "warning: sealevel value %d outside %d-%d range" % (oldsealevel, minsealevel, maxsealevel)
self.sealevel = int(min(max(oldsealevel, minsealevel), maxsealevel))
# maxdepth depends upon sealevel
minmaxdepth = 1
maxmaxdepth = self.sealevel - 1
oldmaxdepth = self.maxdepth
if (oldmaxdepth > maxmaxdepth or oldmaxdepth < minmaxdepth):
print "warning: maxdepth value %d outside %d-%d range" % (oldmaxdepth, minmaxdepth, maxmaxdepth)
self.maxdepth = int(min(max(oldmaxdepth, minmaxdepth), maxmaxdepth))
# trim depends upon elmin (if elmin < 0, trim == 0)
mintrim = Region.trim
maxtrim = max(elmin, mintrim)
oldtrim = self.trim
if (oldtrim > maxtrim or oldtrim < mintrim):
print "warning: trim value %d outside %d-%d range" % (oldtrim, mintrim, maxtrim)
self.trim = int(min(max(oldtrim, mintrim), maxtrim))
# vscale depends on sealevel, trim and elmax
# NB: no maximum vscale, the sky's the limit (hah!)
eltrimmed = elmax - self.trim
elroom = Region.tileheight - Region.headroom - self.sealevel
minvscale = ceil(eltrimmed / elroom)
oldvscale = self.vscale
if (oldvscale < minvscale):
print "warning: vscale value %d smaller than minimum value %d" % (oldvscale, minvscale)
self.vscale = int(max(oldvscale, minvscale))
# GeoTIFF
# four bands: landcover, elevation, bathy, crust
# data type is GDT_Int16 (elevation can be negative)
driver = gdal.GetDriverByName("GTiff")
mapds = driver.Create(self.mapname, elxsize, elysize, len(Region.rasters), GDT_Int16)
# overall map transform should match elevation map transform
mapds.SetGeoTransform(elgeotrans)
srs = osr.SpatialReference()
srs.ImportFromProj4(Region.t_srs)
mapds.SetProjection(srs.ExportToWkt())
# modify elarray and save it as raster band 2
actualel = ((elarray - self.trim)/self.vscale)+self.sealevel
mapds.GetRasterBand(Region.rasters['elevation']).WriteArray(actualel)
elarray = None
actualel = None
# generate crust and save it as raster band 4
newcrust = Crust(mapds.RasterXSize, mapds.RasterYSize, wantCL=wantCL)
crustarray = newcrust()
mapds.GetRasterBand(Region.rasters['crust']).WriteArray(crustarray)
crustarray = None
newcrust = None
# read landcover array
lcvrt = os.path.join(self.mapsdir, self.lclayer, '%s.vrt' % (self.lclayer))
lcfile = os.path.join(self.mapsdir, self.lclayer, '%s.tif' % (self.lclayer))
# here are the things that need to happen
lcextents = self.albersextents['landcover']
# if True, use new code, if False, use gdalwarp
if True:
# 1. the new file must be read into an array and flattened
vrtds = gdal.Open(lcvrt, GA_ReadOnly)
vrtgeotrans = vrtds.GetGeoTransform()
vrtband = vrtds.GetRasterBand(1)
values = vrtband.ReadAsArray(0, 0, vrtds.RasterXSize, vrtds.RasterYSize)
# nodata is treated as water, which is 11
vrtnodata = vrtband.GetNoDataValue()
if (vrtnodata == None):
vrtnodata = 0
values[values == vrtnodata] = 11
values = values.flatten()
vrtband = None
# 2. a new array of original scale coordinates must be created
vrtxrange = [vrtgeotrans[0] + vrtgeotrans[1] * x for x in xrange(vrtds.RasterXSize)]
vrtyrange = [vrtgeotrans[3] + vrtgeotrans[5] * y for y in xrange(vrtds.RasterYSize)]
vrtds = None
coords = numpy.array([(x, y) for y in vrtyrange for x in vrtxrange])
# 3. a new array of goal scale coordinates must be made
# landcover extents are used for the bathy depth array
# yes, it's confusing. sorry.
depthxlen = int((lcextents['xmax']-lcextents['xmin'])/self.scale)
depthylen = int((lcextents['ymax']-lcextents['ymin'])/self.scale)
depthxrange = [lcextents['xmin'] + self.scale * x for x in xrange(depthxlen)]
depthyrange = [lcextents['ymax'] - self.scale * y for y in xrange(depthylen)]
depthbase = numpy.array([(x, y) for y in depthyrange for x in depthxrange])
# 4. an inverse distance tree must be built from that
lcCLIDT = CLIDT(coords, values, depthbase, wantCL=wantCL)
# 5. the desired output comes from that inverse distance tree
deptharray = lcCLIDT()
deptharray.resize((depthylen, depthxlen))
lcCLIDT = None
else:
warpcmd = 'gdalwarp -q -multi -t_srs "%s" -tr %d %d -te %d %d %d %d -r near %s %s' % (Region.t_srs, self.scale, self.scale, lcextents['xmin'], lcextents['ymin'], lcextents['xmax'], lcextents['ymax'], lcvrt, lcfile)
try:
os.remove(lcfile)
except OSError:
pass
# NB: make this work on Windows too!
os.system("%s" % warpcmd)
lcds = gdal.Open(lcfile, GA_ReadOnly)
lcband = lcds.GetRasterBand(1)
# depth array is entire landcover region, landcover array is subset
deptharray = lcband.ReadAsArray(0, 0, lcds.RasterXSize, lcds.RasterYSize)
lcarray = deptharray[self.maxdepth:-1*self.maxdepth, self.maxdepth:-1*self.maxdepth]
geotrans = [ lcextents['xmin'], self.scale, 0, lcextents['ymax'], 0, -1 * self.scale ]
projection = srs.ExportToWkt()
bathyarray = getBathy(deptharray, self.maxdepth, geotrans, projection)
mapds.GetRasterBand(Region.rasters['bathy']).WriteArray(bathyarray)
# perform terrain translation
# NB: figure out why this doesn't work up above
lcpid = self.lclayer[:3]
if lcpid in Terrain.translate:
trans = Terrain.translate[lcpid]
for key in trans:
lcarray[lcarray == key] = 1000+trans[key]
lcarray[lcarray > 1000] -= 1000
for value in numpy.unique(lcarray).flat:
if value not in Terrain.terdict:
print "bad value: ", value
mapds.GetRasterBand(Region.rasters['landcover']).WriteArray(lcarray)
# close the dataset
mapds = None
