def interpolate_raster_vector_points(source,
target,
layer_name=None,
attribute_name=None,
mode='linear'):
"""Interpolate from raster layer to point data
Args:
* source: Raster data set (grid)
* target: Vector data set (points)
* layer_name: Optional name of returned interpolated layer.
If None the name of target is used for the returned layer.
* attribute_name: Name for new attribute.
If None (default) the name of layer source is used
* mode: 'linear' or 'constant' - determines whether interpolation
from grid to points should be bilinear or piecewise constant
Output
I: Vector data set; points located as target with values
interpolated from source
"""
msg = ('There are no data points to interpolate to. Perhaps zoom out '
'and try again')
verify(len(target) > 0, msg)
# Input checks
verify(source.is_raster)
verify(target.is_vector)
verify(target.is_point_data)
# Get raster data and corresponding x and y axes
A = source.get_data(nan=True)
longitudes, latitudes = source.get_geometry()
verify(len(longitudes) == A.shape[1])
verify(len(latitudes) == A.shape[0])
# Get vector point geometry as Nx2 array
coordinates = numpy.array(target.get_geometry(), dtype='d', copy=False)
# Get original attributes
attributes = target.get_data()
# Create new attribute and interpolate
try:
values = interpolate_raster(longitudes,
latitudes,
A,
coordinates,
mode=mode)
except (BoundsError, InaSAFEError), e:
msg = (tr('Could not interpolate from raster layer %(raster)s to '
'vector layer %(vector)s. Error message: %(error)s') % {
'raster': source.get_name(),
'vector': target.get_name(),
'error': str(e)
})
raise InaSAFEError(msg)
def interpolate_raster_vector_points(source, target,
layer_name=None,
attribute_name=None,
mode='linear'):
"""Interpolate from raster layer to point data
Args:
* source: Raster data set (grid)
* target: Vector data set (points)
* layer_name: Optional name of returned interpolated layer.
If None the name of target is used for the returned layer.
* attribute_name: Name for new attribute.
If None (default) the name of layer source is used
* mode: 'linear' or 'constant' - determines whether interpolation
from grid to points should be bilinear or piecewise constant
Output
I: Vector data set; points located as target with values
interpolated from source
"""
msg = ('There are no data points to interpolate to. Perhaps zoom out '
'and try again')
verify(len(target) > 0, msg)
# Input checks
verify(source.is_raster)
verify(target.is_vector)
verify(target.is_point_data)
# Get raster data and corresponding x and y axes
A = source.get_data(nan=True)
longitudes, latitudes = source.get_geometry()
verify(len(longitudes) == A.shape[1])
verify(len(latitudes) == A.shape[0])
# Get vector point geometry as Nx2 array
coordinates = numpy.array(target.get_geometry(),
dtype='d',
copy=False)
# Get original attributes
attributes = target.get_data()
# Create new attribute and interpolate
try:
values = interpolate_raster(longitudes, latitudes, A,
coordinates, mode=mode)
except (BoundsError, InaSAFEError), e:
msg = (
tr(
'Could not interpolate from raster layer %(raster)s to '
'vector layer %(vector)s. Error message: %(error)s'
) % {
'raster': source.get_name(),
'vector': target.get_name(),
'error': str(e)})
raise InaSAFEError(msg)
def test_interpolation_raster_data(self):
"""Interpolation library works for raster data
This shows interpolation of data arranged with
latitudes bottom - up and
longitudes left - right
"""
# 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
# 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])
# Then test that interpolated points are correct
xis = numpy.linspace(lon_ll + 1, lon_ll + numlon - 1, 100)
etas = numpy.linspace(lat_ll + 1, lat_ll + numlat - 1, 100)
points = combine_coordinates(xis, etas)
vals = interpolate_raster(longitudes,
latitudes,
A,
points,
mode='linear')
refs = linear_function(points[:, 0], points[:, 1])
assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)
def test_interpolation_raster_data(self):
"""Interpolation library works for raster data
This shows interpolation of data arranged with
latitudes bottom - up and
longitudes left - right
"""
# 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
# 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])
# Then test that interpolated points are correct
xis = numpy.linspace(lon_ll + 1, lon_ll + numlon - 1, 100)
etas = numpy.linspace(lat_ll + 1, lat_ll + numlat - 1, 100)
points = combine_coordinates(xis, etas)
vals = interpolate_raster(longitudes, latitudes, A, points,
mode='linear')
refs = linear_function(points[:, 0], points[:, 1])
assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)
