def _generic_convert_dem_from_ascii2netcdf(name_in,
name_out=None,
quantity_name=None,
verbose=False):
"""Read raster from the following ASCII format (.asc)
Internal function. See public function convert_dem_from_ascii2netcdf
for details.
"""
import os
from anuga.file.netcdf import NetCDFFile
root = name_in[:-4]
# Read Meta data
if verbose: log.critical('Reading METADATA from %s' % (root + '.prj'))
metadatafile = open(root + '.prj')
metalines = metadatafile.readlines()
metadatafile.close()
L = metalines[0].strip().split()
assert L[0].strip().lower() == 'projection'
projection = L[1].strip() #TEXT
L = metalines[1].strip().split()
assert L[0].strip().lower() == 'zone'
zone = int(L[1].strip())
L = metalines[2].strip().split()
assert L[0].strip().lower() == 'datum'
datum = L[1].strip() #TEXT
L = metalines[3].strip().split()
assert L[0].strip().lower() == 'zunits' #IGNORE
zunits = L[1].strip() #TEXT
L = metalines[4].strip().split()
assert L[0].strip().lower() == 'units'
units = L[1].strip() #TEXT
L = metalines[5].strip().split()
assert L[0].strip().lower() == 'spheroid' #IGNORE
spheroid = L[1].strip() #TEXT
L = metalines[6].strip().split()
assert L[0].strip().lower() == 'xshift'
false_easting = float(L[1].strip())
L = metalines[7].strip().split()
assert L[0].strip().lower() == 'yshift'
false_northing = float(L[1].strip())
if name_in[-4:] != '.asc':
raise IOError('Input file %s should be of type .asc.' % name_in)
#Read DEM data
datafile = open(name_in)
if verbose: log.critical('Reading raster from %s' % (name_in))
lines = datafile.readlines()
datafile.close()
if verbose: log.critical('Got %d lines' % len(lines))
ncols = int(lines[0].split()[1].strip())
nrows = int(lines[1].split()[1].strip())
# Do cellsize (line 4) before line 2 and 3
cellsize = float(lines[4].split()[1].strip())
# Checks suggested by Joaquim Luis
# Our internal representation of xllcorner
# and yllcorner is non-standard.
xref = lines[2].split()
if xref[0].strip() == 'xllcorner':
xllcorner = float(xref[1].strip()) # + 0.5*cellsize # Correct offset
elif xref[0].strip() == 'xllcenter':
xllcorner = float(xref[1].strip())
else:
msg = 'Unknown keyword: %s' % xref[0].strip()
raise Exception, msg
yref = lines[3].split()
if yref[0].strip() == 'yllcorner':
yllcorner = float(yref[1].strip()) # + 0.5*cellsize # Correct offset
elif yref[0].strip() == 'yllcenter':
yllcorner = float(yref[1].strip())
else:
msg = 'Unknown keyword: %s' % yref[0].strip()
raise Exception, msg
NODATA_value = int(float(lines[5].split()[1].strip()))
assert len(lines) == nrows + 6
if name_out == None:
netcdfname = name_in[:-4] + '.dem'
else:
netcdfname = name_out + '.dem'
if verbose: log.critical('Store to NetCDF file %s' % netcdfname)
# NetCDF file definition
fid = NetCDFFile(netcdfname, netcdf_mode_w)
#Create new file
fid.institution = 'Geoscience Australia'
fid.description = 'NetCDF DEM format for compact and portable storage ' \
'of spatial point data'
fid.ncols = ncols
fid.nrows = nrows
fid.xllcorner = xllcorner
fid.yllcorner = yllcorner
fid.cellsize = cellsize
fid.NODATA_value = NODATA_value
fid.zone = zone
fid.false_easting = false_easting
fid.false_northing = false_northing
fid.projection = projection
fid.datum = datum
fid.units = units
# dimension definitions
fid.createDimension('number_of_rows', nrows)
fid.createDimension('number_of_columns', ncols)
# variable definitions
fid.createVariable(quantity_name, netcdf_float,
('number_of_rows', 'number_of_columns'))
# Get handles to the variables
elevation = fid.variables[quantity_name]
#Store data
import numpy
datafile = open(name_in)
elevation[:, :] = numpy.loadtxt(datafile, skiprows=6)
datafile.close()
# n = len(lines[6:])
# for i, line in enumerate(lines[6:]):
# fields = line.split()
# if verbose and i % ((n+10)/10) == 0:
# log.critical('Processing row %d of %d' % (i, nrows))
#
# if len(fields) != ncols:
# msg = 'Wrong number of columns in file "%s" line %d\n' % (name_in, i)
# msg += 'I got %d elements, but there should have been %d\n' % (len(fields), ncols)
# raise Exception, msg
#
# elevation[i, :] = num.array([float(x) for x in fields])
fid.close()
def _convert_dem_from_ascii2netcdf(name_in, name_out = None,
verbose = False):
"""Read Digital Elevation model from the following ASCII format (.asc)
Internal function. See public function convert_dem_from_ascii2netcdf
for details.
"""
import os
from anuga.file.netcdf import NetCDFFile
root = name_in[:-4]
# Read Meta data
if verbose: log.critical('Reading METADATA from %s' % (root + '.prj'))
metadatafile = open(root + '.prj')
metalines = metadatafile.readlines()
metadatafile.close()
L = metalines[0].strip().split()
assert L[0].strip().lower() == 'projection'
projection = L[1].strip() #TEXT
L = metalines[1].strip().split()
assert L[0].strip().lower() == 'zone'
zone = int(L[1].strip())
L = metalines[2].strip().split()
assert L[0].strip().lower() == 'datum'
datum = L[1].strip() #TEXT
L = metalines[3].strip().split()
assert L[0].strip().lower() == 'zunits' #IGNORE
zunits = L[1].strip() #TEXT
L = metalines[4].strip().split()
assert L[0].strip().lower() == 'units'
units = L[1].strip() #TEXT
L = metalines[5].strip().split()
assert L[0].strip().lower() == 'spheroid' #IGNORE
spheroid = L[1].strip() #TEXT
L = metalines[6].strip().split()
assert L[0].strip().lower() == 'xshift'
false_easting = float(L[1].strip())
L = metalines[7].strip().split()
assert L[0].strip().lower() == 'yshift'
false_northing = float(L[1].strip())
if name_in[-4:] != '.asc':
raise IOError('Input file %s should be of type .asc.' % name_in)
#Read DEM data
datafile = open(name_in)
if verbose: log.critical('Reading DEM from %s' % (name_in))
lines = datafile.readlines()
datafile.close()
if verbose: log.critical('Got %d lines' % len(lines))
ncols = int(lines[0].split()[1].strip())
nrows = int(lines[1].split()[1].strip())
# Do cellsize (line 4) before line 2 and 3
cellsize = float(lines[4].split()[1].strip())
# Checks suggested by Joaquim Luis
# Our internal representation of xllcorner
# and yllcorner is non-standard.
xref = lines[2].split()
if xref[0].strip() == 'xllcorner':
xllcorner = float(xref[1].strip()) # + 0.5*cellsize # Correct offset
elif xref[0].strip() == 'xllcenter':
xllcorner = float(xref[1].strip())
else:
msg = 'Unknown keyword: %s' % xref[0].strip()
raise Exception, msg
yref = lines[3].split()
if yref[0].strip() == 'yllcorner':
yllcorner = float(yref[1].strip()) # + 0.5*cellsize # Correct offset
elif yref[0].strip() == 'yllcenter':
yllcorner = float(yref[1].strip())
else:
msg = 'Unknown keyword: %s' % yref[0].strip()
raise Exception, msg
NODATA_value = int(float(lines[5].split()[1].strip()))
assert len(lines) == nrows + 6
if name_out == None:
netcdfname = name_in[:-4]+'.dem'
else:
netcdfname = name_out + '.dem'
if verbose: log.critical('Store to NetCDF file %s' % netcdfname)
# NetCDF file definition
fid = NetCDFFile(netcdfname, netcdf_mode_w)
#Create new file
fid.institution = 'Geoscience Australia'
fid.description = 'NetCDF DEM format for compact and portable storage ' \
'of spatial point data'
fid.ncols = ncols
fid.nrows = nrows
fid.xllcorner = xllcorner
fid.yllcorner = yllcorner
fid.cellsize = cellsize
fid.NODATA_value = NODATA_value
fid.zone = zone
fid.false_easting = false_easting
fid.false_northing = false_northing
fid.projection = projection
fid.datum = datum
fid.units = units
# dimension definitions
fid.createDimension('number_of_rows', nrows)
fid.createDimension('number_of_columns', ncols)
# variable definitions
fid.createVariable('elevation', netcdf_float, ('number_of_rows',
'number_of_columns'))
# Get handles to the variables
elevation = fid.variables['elevation']
#Store data
import numpy
datafile = open(name_in)
elevation[:,:] = numpy.loadtxt(datafile, skiprows=6)
datafile.close()
# n = len(lines[6:])
# for i, line in enumerate(lines[6:]):
# fields = line.split()
# if verbose and i % ((n+10)/10) == 0:
# log.critical('Processing row %d of %d' % (i, nrows))
#
# if len(fields) != ncols:
# msg = 'Wrong number of columns in file "%s" line %d\n' % (name_in, i)
# msg += 'I got %d elements, but there should have been %d\n' % (len(fields), ncols)
# raise Exception, msg
#
# elevation[i, :] = num.array([float(x) for x in fields])
fid.close()
def dem2dem(name_in, stencil, cellsize_new, name_out=None,
verbose=False):
"""Read Digitial Elevation model from the following NetCDF format (.dem)
Example:
ncols 3121
nrows 1800
xllcorner 722000
yllcorner 5893000
cellsize 25
NODATA_value -9999
138.3698 137.4194 136.5062 135.5558 ..........
Decimate data to cellsize_new using stencil and write to NetCDF dem format.
"""
import os
from anuga.file.netcdf import NetCDFFile
if name_in[-4:] != '.dem':
raise IOError('Input file %s should be of type .dem.' % name_in)
if name_out != None and basename_out[-4:] != '.dem':
raise IOError('Input file %s should be of type .dem.' % name_out)
#Open existing netcdf file to read
infile = NetCDFFile(name_in, netcdf_mode_r)
if verbose: log.critical('Reading DEM from %s' % inname)
# Read metadata (convert from numpy.int32 to int where appropriate)
ncols = int(infile.ncols)
nrows = int(infile.nrows)
xllcorner = infile.xllcorner
yllcorner = infile.yllcorner
cellsize = int(infile.cellsize)
NODATA_value = int(infile.NODATA_value)
zone = int(infile.zone)
false_easting = infile.false_easting
false_northing = infile.false_northing
projection = infile.projection
datum = infile.datum
units = infile.units
dem_elevation = infile.variables['elevation']
#Get output file name
if name_out == None:
outname = name_in[:-4] + '_' + repr(cellsize_new) + '.dem'
else:
outname = name_out
if verbose: log.critical('Write decimated NetCDF file to %s' % outname)
#Determine some dimensions for decimated grid
(nrows_stencil, ncols_stencil) = stencil.shape
x_offset = ncols_stencil / 2
y_offset = nrows_stencil / 2
cellsize_ratio = int(cellsize_new / cellsize)
ncols_new = 1 + (ncols - ncols_stencil) / cellsize_ratio
nrows_new = 1 + (nrows - nrows_stencil) / cellsize_ratio
#print type(ncols_new), ncols_new
#Open netcdf file for output
outfile = NetCDFFile(outname, netcdf_mode_w)
#Create new file
outfile.institution = 'Geoscience Australia'
outfile.description = 'NetCDF DEM format for compact and portable ' \
'storage of spatial point data'
#Georeferencing
outfile.zone = zone
outfile.projection = projection
outfile.datum = datum
outfile.units = units
outfile.cellsize = cellsize_new
outfile.NODATA_value = NODATA_value
outfile.false_easting = false_easting
outfile.false_northing = false_northing
outfile.xllcorner = xllcorner + (x_offset * cellsize)
outfile.yllcorner = yllcorner + (y_offset * cellsize)
outfile.ncols = ncols_new
outfile.nrows = nrows_new
# dimension definition
#print nrows_new, ncols_new, nrows_new*ncols_new
#print type(nrows_new), type(ncols_new), type(nrows_new*ncols_new)
outfile.createDimension('number_of_points', nrows_new*ncols_new)
# variable definition
outfile.createVariable('elevation', netcdf_float, ('number_of_points',))
# Get handle to the variable
elevation = outfile.variables['elevation']
dem_elevation_r = num.reshape(dem_elevation, (nrows, ncols))
#Store data
global_index = 0
for i in range(nrows_new):
if verbose: log.critical('Processing row %d of %d' % (i, nrows_new))
lower_index = global_index
telev = num.zeros(ncols_new, num.float)
local_index = 0
trow = i * cellsize_ratio
for j in range(ncols_new):
tcol = j * cellsize_ratio
tmp = dem_elevation_r[trow:trow+nrows_stencil,
tcol:tcol+ncols_stencil]
#if dem contains 1 or more NODATA_values set value in
#decimated dem to NODATA_value, else compute decimated
#value using stencil
if num.sum(num.sum(num.equal(tmp, NODATA_value))) > 0:
telev[local_index] = NODATA_value
else:
telev[local_index] = num.sum(num.sum(tmp * stencil))
global_index += 1
local_index += 1
upper_index = global_index
elevation[lower_index:upper_index] = telev
assert global_index == nrows_new*ncols_new, \
'index not equal to number of points'
infile.close()
outfile.close()
def test_decimate_dem(self):
"""Test decimation of dem file
"""
import os
from anuga.file.netcdf import NetCDFFile
#Write test dem file
root = 'decdemtest'
filename = root + '.dem'
fid = NetCDFFile(filename, netcdf_mode_w)
fid.institution = 'Geoscience Australia'
fid.description = 'NetCDF DEM format for compact and portable ' +\
'storage of spatial point data'
nrows = 15
ncols = 18
fid.ncols = ncols
fid.nrows = nrows
fid.xllcorner = 2000.5
fid.yllcorner = 3000.5
fid.cellsize = 25
fid.NODATA_value = -9999
fid.zone = 56
fid.false_easting = 0.0
fid.false_northing = 0.0
fid.projection = 'UTM'
fid.datum = 'WGS84'
fid.units = 'METERS'
fid.createDimension('number_of_points', nrows * ncols)
fid.createVariable('elevation', netcdf_float, ('number_of_points', ))
elevation = fid.variables['elevation']
elevation[:] = (num.arange(nrows * ncols))
fid.close()
#generate the elevation values expected in the decimated file
ref_elevation = [
(0 + 1 + 2 + 18 + 19 + 20 + 36 + 37 + 38) / 9.0,
(4 + 5 + 6 + 22 + 23 + 24 + 40 + 41 + 42) / 9.0,
(8 + 9 + 10 + 26 + 27 + 28 + 44 + 45 + 46) / 9.0,
(12 + 13 + 14 + 30 + 31 + 32 + 48 + 49 + 50) / 9.0,
(72 + 73 + 74 + 90 + 91 + 92 + 108 + 109 + 110) / 9.0,
(76 + 77 + 78 + 94 + 95 + 96 + 112 + 113 + 114) / 9.0,
(80 + 81 + 82 + 98 + 99 + 100 + 116 + 117 + 118) / 9.0,
(84 + 85 + 86 + 102 + 103 + 104 + 120 + 121 + 122) / 9.0,
(144 + 145 + 146 + 162 + 163 + 164 + 180 + 181 + 182) / 9.0,
(148 + 149 + 150 + 166 + 167 + 168 + 184 + 185 + 186) / 9.0,
(152 + 153 + 154 + 170 + 171 + 172 + 188 + 189 + 190) / 9.0,
(156 + 157 + 158 + 174 + 175 + 176 + 192 + 193 + 194) / 9.0,
(216 + 217 + 218 + 234 + 235 + 236 + 252 + 253 + 254) / 9.0,
(220 + 221 + 222 + 238 + 239 + 240 + 256 + 257 + 258) / 9.0,
(224 + 225 + 226 + 242 + 243 + 244 + 260 + 261 + 262) / 9.0,
(228 + 229 + 230 + 246 + 247 + 248 + 264 + 265 + 266) / 9.0
]
# generate a stencil for computing the decimated values
stencil = num.ones((3, 3), num.float) / 9.0
dem2dem(filename, stencil=stencil, cellsize_new=100)
# Open decimated NetCDF file
fid = NetCDFFile(root + '_100.dem', netcdf_mode_r)
# Get decimated elevation
elevation = fid.variables['elevation']
# Check values
assert num.allclose(elevation, ref_elevation)
# Cleanup
fid.close()
os.remove(root + '.dem')
os.remove(root + '_100.dem')
def dem2dem(name_in, stencil, cellsize_new, name_out=None, verbose=False):
"""Read Digitial Elevation model from the following NetCDF format (.dem)
Example:
ncols 3121
nrows 1800
xllcorner 722000
yllcorner 5893000
cellsize 25
NODATA_value -9999
138.3698 137.4194 136.5062 135.5558 ..........
Decimate data to cellsize_new using stencil and write to NetCDF dem format.
"""
import os
from anuga.file.netcdf import NetCDFFile
if name_in[-4:] != '.dem':
raise IOError('Input file %s should be of type .dem.' % name_in)
if name_out != None and basename_out[-4:] != '.dem':
raise IOError('Input file %s should be of type .dem.' % name_out)
#Open existing netcdf file to read
infile = NetCDFFile(name_in, netcdf_mode_r)
if verbose: log.critical('Reading DEM from %s' % inname)
# Read metadata (convert from numpy.int32 to int where appropriate)
ncols = int(infile.ncols)
nrows = int(infile.nrows)
xllcorner = infile.xllcorner
yllcorner = infile.yllcorner
cellsize = int(infile.cellsize)
NODATA_value = int(infile.NODATA_value)
zone = int(infile.zone)
false_easting = infile.false_easting
false_northing = infile.false_northing
projection = infile.projection
datum = infile.datum
units = infile.units
dem_elevation = infile.variables['elevation']
#Get output file name
if name_out == None:
outname = name_in[:-4] + '_' + repr(cellsize_new) + '.dem'
else:
outname = name_out
if verbose: log.critical('Write decimated NetCDF file to %s' % outname)
#Determine some dimensions for decimated grid
(nrows_stencil, ncols_stencil) = stencil.shape
x_offset = ncols_stencil / 2
y_offset = nrows_stencil / 2
cellsize_ratio = int(cellsize_new / cellsize)
ncols_new = 1 + (ncols - ncols_stencil) / cellsize_ratio
nrows_new = 1 + (nrows - nrows_stencil) / cellsize_ratio
#print type(ncols_new), ncols_new
#Open netcdf file for output
outfile = NetCDFFile(outname, netcdf_mode_w)
#Create new file
outfile.institution = 'Geoscience Australia'
outfile.description = 'NetCDF DEM format for compact and portable ' \
'storage of spatial point data'
#Georeferencing
outfile.zone = zone
outfile.projection = projection
outfile.datum = datum
outfile.units = units
outfile.cellsize = cellsize_new
outfile.NODATA_value = NODATA_value
outfile.false_easting = false_easting
outfile.false_northing = false_northing
outfile.xllcorner = xllcorner + (x_offset * cellsize)
outfile.yllcorner = yllcorner + (y_offset * cellsize)
outfile.ncols = ncols_new
outfile.nrows = nrows_new
# dimension definition
#print nrows_new, ncols_new, nrows_new*ncols_new
#print type(nrows_new), type(ncols_new), type(nrows_new*ncols_new)
outfile.createDimension('number_of_points', nrows_new * ncols_new)
# variable definition
outfile.createVariable('elevation', netcdf_float, ('number_of_points', ))
# Get handle to the variable
elevation = outfile.variables['elevation']
dem_elevation_r = num.reshape(dem_elevation, (nrows, ncols))
#Store data
global_index = 0
for i in range(nrows_new):
if verbose: log.critical('Processing row %d of %d' % (i, nrows_new))
lower_index = global_index
telev = num.zeros(ncols_new, num.float)
local_index = 0
trow = i * cellsize_ratio
for j in range(ncols_new):
tcol = j * cellsize_ratio
tmp = dem_elevation_r[trow:trow + nrows_stencil,
tcol:tcol + ncols_stencil]
#if dem contains 1 or more NODATA_values set value in
#decimated dem to NODATA_value, else compute decimated
#value using stencil
if num.sum(num.sum(num.equal(tmp, NODATA_value))) > 0:
telev[local_index] = NODATA_value
else:
telev[local_index] = num.sum(num.sum(tmp * stencil))
global_index += 1
local_index += 1
upper_index = global_index
elevation[lower_index:upper_index] = telev
assert global_index == nrows_new*ncols_new, \
'index not equal to number of points'
infile.close()
outfile.close()
def test_decimate_dem(self):
"""Test decimation of dem file
"""
import os
from anuga.file.netcdf import NetCDFFile
# Write test dem file
root = "decdemtest"
filename = root + ".dem"
fid = NetCDFFile(filename, netcdf_mode_w)
fid.institution = "Geoscience Australia"
fid.description = "NetCDF DEM format for compact and portable " + "storage of spatial point data"
nrows = 15
ncols = 18
fid.ncols = ncols
fid.nrows = nrows
fid.xllcorner = 2000.5
fid.yllcorner = 3000.5
fid.cellsize = 25
fid.NODATA_value = -9999
fid.zone = 56
fid.false_easting = 0.0
fid.false_northing = 0.0
fid.projection = "UTM"
fid.datum = "WGS84"
fid.units = "METERS"
fid.createDimension("number_of_points", nrows * ncols)
fid.createVariable("elevation", netcdf_float, ("number_of_points",))
elevation = fid.variables["elevation"]
elevation[:] = num.arange(nrows * ncols)
fid.close()
# generate the elevation values expected in the decimated file
ref_elevation = [
(0 + 1 + 2 + 18 + 19 + 20 + 36 + 37 + 38) / 9.0,
(4 + 5 + 6 + 22 + 23 + 24 + 40 + 41 + 42) / 9.0,
(8 + 9 + 10 + 26 + 27 + 28 + 44 + 45 + 46) / 9.0,
(12 + 13 + 14 + 30 + 31 + 32 + 48 + 49 + 50) / 9.0,
(72 + 73 + 74 + 90 + 91 + 92 + 108 + 109 + 110) / 9.0,
(76 + 77 + 78 + 94 + 95 + 96 + 112 + 113 + 114) / 9.0,
(80 + 81 + 82 + 98 + 99 + 100 + 116 + 117 + 118) / 9.0,
(84 + 85 + 86 + 102 + 103 + 104 + 120 + 121 + 122) / 9.0,
(144 + 145 + 146 + 162 + 163 + 164 + 180 + 181 + 182) / 9.0,
(148 + 149 + 150 + 166 + 167 + 168 + 184 + 185 + 186) / 9.0,
(152 + 153 + 154 + 170 + 171 + 172 + 188 + 189 + 190) / 9.0,
(156 + 157 + 158 + 174 + 175 + 176 + 192 + 193 + 194) / 9.0,
(216 + 217 + 218 + 234 + 235 + 236 + 252 + 253 + 254) / 9.0,
(220 + 221 + 222 + 238 + 239 + 240 + 256 + 257 + 258) / 9.0,
(224 + 225 + 226 + 242 + 243 + 244 + 260 + 261 + 262) / 9.0,
(228 + 229 + 230 + 246 + 247 + 248 + 264 + 265 + 266) / 9.0,
]
# generate a stencil for computing the decimated values
stencil = num.ones((3, 3), num.float) / 9.0
dem2dem(filename, stencil=stencil, cellsize_new=100)
# Open decimated NetCDF file
fid = NetCDFFile(root + "_100.dem", netcdf_mode_r)
# Get decimated elevation
elevation = fid.variables["elevation"]
# Check values
assert num.allclose(elevation, ref_elevation)
# Cleanup
fid.close()
os.remove(root + ".dem")
os.remove(root + "_100.dem")