def test_nearest_interpolation_1d_variants():
"""Test nearest neighbor interpolation variants in 1d."""
intv = odl.IntervalProd(0, 1)
part = odl.uniform_partition_fromintv(intv, 5, nodes_on_bdry=False)
# Coordinate vectors are:
# [0.1, 0.3, 0.5, 0.7, 0.9]
fspace = odl.FunctionSpace(intv)
tspace = odl.rn(part.shape)
# 'left' variant
interp_op = NearestInterpolation(fspace, part, tspace, variant='left')
assert repr(interp_op) != ''
function = interp_op([0, 1, 2, 3, 4])
# Testing two midpoints and the extreme values
pts = np.array([0.4, 0.8, 0.0, 1.0])
true_arr = [1, 3, 0, 4]
assert all_equal(function(pts), true_arr)
# 'right' variant
interp_op = NearestInterpolation(fspace, part, tspace, variant='right')
assert repr(interp_op) != ''
function = interp_op([0, 1, 2, 3, 4])
# Testing two midpoints and the extreme values
pts = np.array([0.4, 0.8, 0.0, 1.0])
true_arr = [2, 4, 0, 4]
assert all_equal(function(pts), true_arr)
def test_nearest_interpolation_1d_variants():
intv = odl.Interval(0, 1)
part = odl.uniform_partition_fromintv(intv, 5, nodes_on_bdry=False)
# Coordinate vectors are:
# [0.1, 0.3, 0.5, 0.7, 0.9]
space = odl.FunctionSpace(intv)
dspace = odl.Rn(part.size)
# 'left' variant
interp_op = NearestInterpolation(space, part, dspace, variant='left')
function = interp_op([0, 1, 2, 3, 4])
# Testing two midpoints and the extreme values
pts = np.array([0.4, 0.8, 0.0, 1.0])
true_arr = [1, 3, 0, 4]
assert all_equal(function(pts), true_arr)
# 'right' variant
interp_op = NearestInterpolation(space, part, dspace, variant='right')
function = interp_op([0, 1, 2, 3, 4])
# Testing two midpoints and the extreme values
pts = np.array([0.4, 0.8, 0.0, 1.0])
true_arr = [2, 4, 0, 4]
assert all_equal(function(pts), true_arr)
def test_collocation_interpolation_identity():
"""Check if collocation is left-inverse to interpolation."""
# Interpolation followed by collocation on the same grid should be
# the identity
rect = odl.IntervalProd([0, 0], [1, 1])
part = odl.uniform_partition_fromintv(rect, [4, 2])
space = odl.FunctionSpace(rect)
tspace = odl.rn(part.shape)
coll_op = PointCollocation(space, part, tspace)
interp_ops = [
NearestInterpolation(space, part, tspace, variant='left'),
NearestInterpolation(space, part, tspace, variant='right'),
LinearInterpolation(space, part, tspace),
PerAxisInterpolation(space,
part,
tspace,
schemes=['linear', 'nearest'])
]
values = np.arange(1, 9, dtype='float64').reshape(tspace.shape)
for interp_op in interp_ops:
ident_values = coll_op(interp_op(values))
assert all_almost_equal(ident_values, values)
def test_collocation_interpolation_identity():
# Check if interpolation followed by collocation on the same grid
# is the identity
rect = odl.IntervalProd([0, 0], [1, 1])
part = odl.uniform_partition_fromintv(rect, [4, 2])
space = odl.FunctionSpace(rect)
dspace = odl.rn(part.size)
coll_op_c = PointCollocation(space, part, dspace, order='C')
coll_op_f = PointCollocation(space, part, dspace, order='F')
interp_ops_c = [
NearestInterpolation(space, part, dspace, variant='left', order='C'),
NearestInterpolation(space, part, dspace, variant='right', order='C'),
LinearInterpolation(space, part, dspace, order='C'),
PerAxisInterpolation(space, part, dspace, order='C',
schemes=['linear', 'nearest'])]
interp_ops_f = [
NearestInterpolation(space, part, dspace, variant='left', order='F'),
NearestInterpolation(space, part, dspace, variant='right', order='F'),
LinearInterpolation(space, part, dspace, order='F'),
PerAxisInterpolation(space, part, dspace, order='F',
schemes=['linear', 'nearest'])]
values = np.arange(1, 9, dtype='float64')
for interp_op_c in interp_ops_c:
ident_values = coll_op_c(interp_op_c(values))
assert all_almost_equal(ident_values, values)
for interp_op_f in interp_ops_f:
ident_values = coll_op_f(interp_op_f(values))
assert all_almost_equal(ident_values, values)
def test_nearest_interpolation_2d_float():
"""Test nearest neighbor interpolation in 2d."""
rect = odl.IntervalProd([0, 0], [1, 1])
part = odl.uniform_partition_fromintv(rect, [4, 2], nodes_on_bdry=False)
# Coordinate vectors are:
# [0.125, 0.375, 0.625, 0.875], [0.25, 0.75]
fspace = odl.FunctionSpace(rect)
tspace = odl.rn(part.shape)
interp_op = NearestInterpolation(fspace, part, tspace)
function = interp_op(np.reshape([0, 1, 2, 3, 4, 5, 6, 7], part.shape))
# Evaluate at single point
val = function([0.3, 0.6]) # closest to index (1, 1) -> 3
assert val == 3.0
# Input array, with and without output array
pts = np.array([[0.3, 0.6], [1.0, 1.0]])
true_arr = [3, 7]
assert all_equal(function(pts.T), true_arr)
out = np.empty(2, dtype='float64')
function(pts.T, out=out)
assert all_equal(out, true_arr)
# Input meshgrid, with and without output array
mg = sparse_meshgrid([0.3, 1.0], [0.4, 1.0])
# Indices: (1, 3) x (0, 1)
true_mg = [[2, 3], [6, 7]]
assert all_equal(function(mg), true_mg)
out = np.empty((2, 2), dtype='float64')
function(mg, out=out)
assert all_equal(out, true_mg)
assert repr(interp_op) != ''
def test_nearest_interpolation_1d_complex(odl_tspace_impl):
"""Test nearest neighbor interpolation in 1d with complex values."""
impl = odl_tspace_impl # TODO: not used!
intv = odl.IntervalProd(0, 1)
part = odl.uniform_partition_fromintv(intv, 5, nodes_on_bdry=False)
# Coordinate vectors are:
# [0.1, 0.3, 0.5, 0.7, 0.9]
fspace = odl.FunctionSpace(intv, out_dtype=complex)
tspace = odl.cn(part.shape)
interp_op = NearestInterpolation(fspace, part, tspace)
function = interp_op([0 + 1j, 1 + 2j, 2 + 3j, 3 + 4j, 4 + 5j])
# Evaluate at single point
val = function(0.35) # closest to index 1 -> 1 + 2j
assert val == 1.0 + 2.0j
# Input array, with and without output array
pts = np.array([0.4, 0.0, 0.65, 0.95])
true_arr = [1 + 2j, 0 + 1j, 3 + 4j, 4 + 5j]
assert all_equal(function(pts), true_arr)
# Should also work with a (1, N) array
pts = pts[None, :]
assert all_equal(function(pts), true_arr)
out = np.empty(4, dtype='complex128')
function(pts, out=out)
assert all_equal(out, true_arr)
# Input meshgrid, with and without output array
# Same as array for 1d
mg = sparse_meshgrid([0.4, 0.0, 0.65, 0.95])
true_mg = [1 + 2j, 0 + 1j, 3 + 4j, 4 + 5j]
assert all_equal(function(mg), true_mg)
function(mg, out=out)
assert all_equal(out, true_mg)
assert repr(interp_op) != ''
def test_nearest_interpolation_2d_string():
"""Test nearest neighbor interpolation in 2d with string values."""
rect = odl.IntervalProd([0, 0], [1, 1])
part = odl.uniform_partition_fromintv(rect, [4, 2], nodes_on_bdry=False)
# Coordinate vectors are:
# [0.125, 0.375, 0.625, 0.875], [0.25, 0.75]
fspace = odl.FunctionSpace(rect, out_dtype='U1')
tspace = odl.tensor_space(part.shape, dtype='U1')
interp_op = NearestInterpolation(fspace, part, tspace)
values = np.array([c for c in 'mystring']).reshape(tspace.shape)
function = interp_op(values)
# Evaluate at single point
val = function([0.3, 0.6]) # closest to index (1, 1) -> 3
assert val == 't'
# Input array, with and without output array
pts = np.array([[0.3, 0.6], [1.0, 1.0]])
true_arr = ['t', 'g']
assert all_equal(function(pts.T), true_arr)
out = np.empty(2, dtype='U1')
function(pts.T, out=out)
assert all_equal(out, true_arr)
# Input meshgrid, with and without output array
mg = sparse_meshgrid([0.3, 1.0], [0.4, 1.0])
# Indices: (1, 3) x (0, 1)
true_mg = [['s', 't'], ['n', 'g']]
assert all_equal(function(mg), true_mg)
out = np.empty((2, 2), dtype='U1')
function(mg, out=out)
assert all_equal(out, true_mg)
assert repr(interp_op) != ''
def test_nearest_interpolation_1d_complex(fn_impl):
intv = odl.IntervalProd(0, 1)
part = odl.uniform_partition_fromintv(intv, 5, nodes_on_bdry=False)
# Coordinate vectors are:
# [0.1, 0.3, 0.5, 0.7, 0.9]
space = odl.FunctionSpace(intv, field=odl.ComplexNumbers())
dspace = odl.cn(part.size)
interp_op = NearestInterpolation(space, part, dspace)
function = interp_op([0 + 1j, 1 + 2j, 2 + 3j, 3 + 4j, 4 + 5j])
# Evaluate at single point
val = function(0.35) # closest to index 1 -> 1 + 2j
assert val == 1.0 + 2.0j
# Input array, with and without output array
pts = np.array([0.4, 0.0, 0.65, 0.95])
true_arr = [1 + 2j, 0 + 1j, 3 + 4j, 4 + 5j]
assert all_equal(function(pts), true_arr)
# Should also work with a (1, N) array
pts = pts[None, :]
assert all_equal(function(pts), true_arr)
out = np.empty(4, dtype='complex128')
function(pts, out=out)
assert all_equal(out, true_arr)
# Input meshgrid, with and without output array
# Same as array for 1d
mg = sparse_meshgrid([0.4, 0.0, 0.65, 0.95])
true_mg = [1 + 2j, 0 + 1j, 3 + 4j, 4 + 5j]
assert all_equal(function(mg), true_mg)
function(mg, out=out)
assert all_equal(out, true_mg)
def test_nearest_interpolation_2d_string():
rect = odl.Rectangle([0, 0], [1, 1])
part = odl.uniform_partition_fromintv(rect, [4, 2], nodes_on_bdry=False)
# Coordinate vectors are:
# [0.125, 0.375, 0.625, 0.875], [0.25, 0.75]
space = odl.FunctionSet(rect, odl.Strings(1))
dspace = odl.Ntuples(part.size, dtype='U1')
interp_op = NearestInterpolation(space, part, dspace)
values = np.array([c for c in 'mystring'])
function = interp_op(values)
# Evaluate at single point
val = function([0.3, 0.6]) # closest to index (1, 1) -> 3
assert val == 't'
# Input array, with and without output array
pts = np.array([[0.3, 0.6], [1.0, 1.0]])
true_arr = ['t', 'g']
assert all_equal(function(pts.T), true_arr)
out = np.empty(2, dtype='U1')
function(pts.T, out=out)
assert all_equal(out, true_arr)
# Input meshgrid, with and without output array
mg = sparse_meshgrid([0.3, 1.0], [0.4, 1.0])
# Indices: (1, 3) x (0, 1)
true_mg = [['s', 't'], ['n', 'g']]
assert all_equal(function(mg), true_mg)
out = np.empty((2, 2), dtype='U1')
function(mg, out=out)
assert all_equal(out, true_mg)
