def test_riab_interpolation(self):
"""Interpolation using Raster and Vector objects
"""
# Create test data
lon_ul = 100 # Longitude of upper left corner
lat_ul = 10 # Latitude of upper left corner
numlon = 8 # Number of longitudes
numlat = 5 # Number of latitudes
dlon = 1
dlat = -1
# Define array where latitudes are rows and longitude columns
A = numpy.zeros((numlat, numlon))
# Establish coordinates for lower left corner
lat_ll = lat_ul - numlat
lon_ll = lon_ul
# Define pixel centers along each direction
longitudes = numpy.linspace(lon_ll + 0.5,
lon_ll + numlon - 0.5,
numlon)
latitudes = numpy.linspace(lat_ll + 0.5,
lat_ll + numlat - 0.5,
numlat)
# Define raster with latitudes going bottom-up (south to north).
# Longitudes go left-right (west to east)
for i in range(numlat):
for j in range(numlon):
A[numlat - 1 - i, j] = linear_function(longitudes[j],
latitudes[i])
# Write array to a raster file
geotransform = (lon_ul, dlon, 0, lat_ul, 0, dlat)
projection = ('GEOGCS["GCS_WGS_1984",'
'DATUM["WGS_1984",'
'SPHEROID["WGS_1984",6378137.0,298.257223563]],'
'PRIMEM["Greenwich",0.0],'
'UNIT["Degree",0.0174532925199433]]')
raster_filename = unique_filename(suffix='.tif')
write_raster_data(A,
projection,
geotransform,
raster_filename)
# Write test interpolation point to a vector file
coordinates = []
for xi in longitudes:
for eta in latitudes:
coordinates.append((xi, eta))
vector_filename = unique_filename(suffix='.shp')
write_vector_data(data=None,
projection=projection,
geometry=coordinates,
filename=vector_filename)
# Read both datasets back in
R = read_layer(raster_filename)
V = read_layer(vector_filename)
# Then test that axes and data returned by R are correct
x, y = R.get_geometry()
msg = 'X axes was %s, should have been %s' % (longitudes, x)
assert numpy.allclose(longitudes, x), msg
msg = 'Y axes was %s, should have been %s' % (latitudes, y)
assert numpy.allclose(latitudes, y), msg
AA = R.get_data()
msg = 'Raster data was %s, should have been %s' % (AA, A)
assert numpy.allclose(AA, A), msg
# Test riab's interpolation function
I = R.interpolate(V, name='value')
Icoordinates = I.get_geometry()
Iattributes = I.get_data()
assert numpy.allclose(Icoordinates, coordinates)
# Test that interpolated points are correct
for i, (xi, eta) in enumerate(Icoordinates):
z = Iattributes[i]['value']
#print xi, eta, z, linear_function(xi, eta)
assert numpy.allclose(z, linear_function(xi, eta),
rtol=1e-12)
# FIXME (Ole): Need test for values outside grid.
# They should be NaN or something
# Cleanup
# FIXME (Ole): Shape files are a collection of files. How to remove?
os.remove(vector_filename)
def test_riab_interpolation(self):
"""Interpolation using Raster and Vector objects
"""
# Create test data
lon_ul = 100 # Longitude of upper left corner
lat_ul = 10 # Latitude of upper left corner
numlon = 8 # Number of longitudes
numlat = 5 # Number of latitudes
dlon = 1
dlat = -1
# Define array where latitudes are rows and longitude columns
A = numpy.zeros((numlat, numlon))
# Establish coordinates for lower left corner
lat_ll = lat_ul - numlat
lon_ll = lon_ul
# Define pixel centers along each direction
longitudes = numpy.linspace(lon_ll + 0.5,
lon_ll + numlon - 0.5,
numlon)
latitudes = numpy.linspace(lat_ll + 0.5,
lat_ll + numlat - 0.5,
numlat)
# Define raster with latitudes going bottom-up (south to north).
# Longitudes go left-right (west to east)
for i in range(numlat):
for j in range(numlon):
A[numlat - 1 - i, j] = linear_function(longitudes[j],
latitudes[i])
# Create bilinear interpolation function
F = raster_spline(longitudes, latitudes, A)
# Write array to a raster file
geotransform = (lon_ul, dlon, 0, lat_ul, 0, dlat)
projection = ('GEOGCS["GCS_WGS_1984",'
'DATUM["WGS_1984",'
'SPHEROID["WGS_1984",6378137.0,298.257223563]],'
'PRIMEM["Greenwich",0.0],'
'UNIT["Degree",0.0174532925199433]]')
raster_filename = unique_filename(suffix='.tif')
write_raster_data(A,
projection,
geotransform,
raster_filename)
# Write test interpolation point to a vector file
coordinates = []
for xi in longitudes:
for eta in latitudes:
coordinates.append((xi, eta))
vector_filename = unique_filename(suffix='.shp')
write_point_data(data=None,
projection=projection,
geometry=coordinates,
filename=vector_filename)
# Read both datasets back in
R = read_layer(raster_filename)
V = read_layer(vector_filename)
# Then test that axes and data returned by R are correct
x, y = R.get_geometry()
msg = 'X axes was %s, should have been %s' % (longitudes, x)
assert numpy.allclose(longitudes, x), msg
msg = 'Y axes was %s, should have been %s' % (latitudes, y)
assert numpy.allclose(latitudes, y), msg
AA = R.get_data()
msg = 'Raster data was %s, should have been %s' % (AA, A)
assert numpy.allclose(AA, A), msg
# Test riab's interpolation function
I = R.interpolate(V, name='value')
Icoordinates = I.get_geometry()
Iattributes = I.get_data()
assert numpy.allclose(Icoordinates, coordinates)
# Test that interpolated points are correct
for i, (xi, eta) in enumerate(Icoordinates):
z = Iattributes[i]['value']
#print xi, eta, z, linear_function(xi, eta)
assert numpy.allclose(z, linear_function(xi, eta),
rtol=1e-12)
# FIXME (Ole): Need test for values outside grid.
# They should be NaN or something
# Cleanup
# FIXME (Ole): Shape files are a collection of files. How to remove?
os.remove(vector_filename)
def test_reading_and_writing_of_real_rasters(self):
"""Rasters can be read and written correctly
"""
for rastername in ['Earthquake_Ground_Shaking_clip.tif',
'Population_2010_clip.tif',
'shakemap_padang_20090930.asc',
'population_padang_1.asc',
'population_padang_2.asc']:
filename = '%s/%s' % (TESTDATA, rastername)
R1 = read_layer(filename)
# Check consistency of raster
A1 = R1.get_data()
M, N = A1.shape
msg = ('Dimensions of raster array do not match those of '
'raster file %s' % R1.filename)
assert M == R1.rows, msg
assert N == R1.columns, msg
# Write back to new (tif) file
out_filename = unique_filename(suffix='.tif')
write_raster_data(A1,
R1.get_projection(),
R1.get_geotransform(),
out_filename)
# Read again and check consistency
R2 = read_layer(out_filename)
msg = ('Dimensions of written raster array do not match those '
'of input raster file\n')
msg += (' Dimensions of input file '
'%s: (%s, %s)\n' % (R1.filename, M, N))
msg += (' Dimensions of output file %s: '
'(%s, %s)' % (R2.filename, R2.rows, R2.columns))
assert M == R2.rows, msg
assert N == R2.columns, msg
A2 = R2.get_data()
assert numpy.allclose(numpy.min(A1), numpy.min(A2))
assert numpy.allclose(numpy.max(A1), numpy.max(A2))
msg = 'Array values of written raster array were not as expected'
assert numpy.allclose(A1, A2), msg
msg = 'Geotransforms were different'
assert R1.get_geotransform() == R2.get_geotransform(), msg
p1 = R1.get_projection(proj4=True)
p2 = R2.get_projection(proj4=True)
msg = 'Projections were different: %s != %s' % (p1, p2)
assert p1 == p1, msg
# Use overridden == and != to verify
assert R1 == R2
assert not R1 != R2
# Check that equality raises exception when type is wrong
try:
R1 == Vector()
except TypeError:
pass
else:
msg = 'Should have raised TypeError'
raise Exception(msg)
