def test_list_gridded_ungridded_box_moments(self):
data1 = make_from_cube(mock.make_mock_cube())
data1.name = lambda: 'Name1'
data1.var_name = 'var_name1'
data1._standard_name = 'y_wind'
data2 = make_from_cube(mock.make_mock_cube(data_offset=3))
data2.name = lambda: 'Name1'
data2.var_name = 'var_name2'
data2._standard_name = 'x_wind'
data_list = GriddedDataList([data1, data2])
sample = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0, alt=12.0, t=dt.datetime(1984, 8, 29, 8, 34)),
HyperPoint(lat=3.0, lon=3.0, alt=7.0, t=dt.datetime(1984, 8, 29, 8, 34)),
HyperPoint(lat=-1.0, lon=-1.0, alt=5.0, t=dt.datetime(1984, 8, 29, 8, 34))])
constraint = SepConstraintKdtree('500km')
kernel = moments()
col = GeneralUngriddedCollocator()
output = col.collocate(sample, data_list, constraint, kernel)
expected_result = np.array([28.0/3, 10.0, 20.0/3])
expected_stddev = np.array([1.52752523, 1.82574186, 1.52752523])
expected_n = np.array([3, 4, 3])
assert len(output) == 6
assert isinstance(output, UngriddedDataList)
assert np.allclose(output[0].data, expected_result)
assert np.allclose(output[1].data, expected_stddev)
assert np.allclose(output[2].data, expected_n)
assert np.allclose(output[3].data, expected_result + 3)
assert np.allclose(output[4].data, expected_stddev)
assert np.allclose(output[5].data, expected_n)
def test_coordinates_outside_grid_in_col_ungridded_to_ungridded_in_2d(
self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_pressure, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
sample_points = HyperPointList()
sample_points.append(
HyperPoint(lat=0.0,
lon=0.0,
pres=0.1,
t=dt.datetime(1984, 8, 29, 8, 34)))
sample_points.append(
HyperPoint(lat=0.0,
lon=0.0,
pres=91.0,
t=dt.datetime(1984, 9, 2, 1, 23)))
sample_points.append(
HyperPoint(lat=0.0,
lon=0.0,
pres=890.0,
t=dt.datetime(1984, 9, 4, 15, 54)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_pressure())[0]
eq_(new_data.data[0], 1.0)
eq_(new_data.data[1], 46.0)
eq_(new_data.data[2], 46.0)
def test_coordinates_exactly_between_points_in_col_ungridded_to_ungridded_in_2d(
self):
"""
This works out the edge case where the points are exactly in the middle or two or more datapoints.
The nn_horizontal algorithm will start with the first point as the nearest and iterates through the
points finding any points which are closer than the current closest. If two distances were exactly
the same you would expect the first point to be chosen. This doesn't seem to always be the case but is
probably down to floating points errors in the haversine calculation as these test points are pretty
close together. This test is only really for documenting the behaviour for equidistant points.
"""
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_horizontal, SepConstraintKdtree
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array([
HyperPoint(2.5, 2.5),
HyperPoint(-2.5, 2.5),
HyperPoint(2.5, -2.5),
HyperPoint(-2.5, -2.5)
])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_horizontal())[0]
eq_(new_data.data[0], 11.0)
eq_(new_data.data[1], 5.0)
eq_(new_data.data[2], 10.0)
eq_(new_data.data[3], 4.0)
def test_already_collocated_in_col_ungridded_to_ungridded_in_2d(self):
ug_data = mock.make_regular_2d_ungridded_data()
# This point already exists on the cube with value 5 - which shouldn't be a problem
sample_points = UngriddedData.from_points_array([HyperPoint(0.0, 0.0)])
col = GeneralUngriddedCollocator(fill_value=-999)
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_horizontal_only())[0]
eq_(new_data.data[0], 8.0)
def test_list_ungridded_ungridded_box_mean(self):
ug_data_1 = mock.make_regular_2d_ungridded_data()
ug_data_2 = mock.make_regular_2d_ungridded_data(data_offset=3)
ug_data_2.long_name = 'TOTAL SNOWFALL RATE: LS+CONV KG/M2/S'
ug_data_2.standard_name = 'snowfall_rate'
ug_data_2.metadata._name = 'snow'
data_list = UngriddedDataList([ug_data_1, ug_data_2])
sample_points = mock.make_regular_2d_ungridded_data()
constraint = SepConstraintKdtree('500km')
kernel = moments()
col = GeneralUngriddedCollocator()
output = col.collocate(sample_points, data_list, constraint, kernel)
expected_result = np.array(list(range(1, 16)))
expected_stddev = np.array(15 * [float('inf')])
expected_n = np.array(15 * [1])
assert len(output) == 6
assert isinstance(output, UngriddedDataList)
assert output[3].var_name == 'snow'
assert output[4].var_name == 'snow_std_dev'
assert output[5].var_name == 'snow_num_points'
assert np.allclose(output[0].data, expected_result)
assert np.allclose(output[1].data, expected_stddev)
assert np.allclose(output[2].data, expected_n)
assert np.allclose(output[3].data, expected_result + 3)
assert np.allclose(output[4].data, expected_stddev)
assert np.allclose(output[5].data, expected_n)
def test_basic_col_in_4d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_altitude, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
sample_points = HyperPointList()
sample_points.append(
HyperPoint(lat=1.0,
lon=1.0,
alt=12.0,
t=dt.datetime(1984, 8, 29, 8, 34)))
sample_points.append(
HyperPoint(lat=4.0,
lon=4.0,
alt=34.0,
t=dt.datetime(1984, 9, 2, 1, 23)))
sample_points.append(
HyperPoint(lat=-4.0,
lon=-4.0,
alt=89.0,
t=dt.datetime(1984, 9, 4, 15, 54)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_altitude())[0]
eq_(new_data.data[0], 6.0)
eq_(new_data.data[1], 16.0)
eq_(new_data.data[2], 46.0)
def test_list_ungridded_ungridded_box_mean(self):
ug_data_1 = mock.make_regular_2d_ungridded_data()
ug_data_2 = mock.make_regular_2d_ungridded_data(data_offset=3)
ug_data_2.long_name = 'TOTAL SNOWFALL RATE: LS+CONV KG/M2/S'
ug_data_2.standard_name = 'snowfall_flux'
ug_data_2.metadata._name = 'snow'
data_list = UngriddedDataList([ug_data_1, ug_data_2])
sample_points = mock.make_regular_2d_ungridded_data()
constraint = SepConstraintKdtree('500km')
kernel = moments()
col = GeneralUngriddedCollocator()
output = col.collocate(sample_points, data_list, constraint, kernel)
expected_result = np.array(list(range(1, 16)))
expected_n = np.array(15 * [1])
assert len(output) == 6
assert isinstance(output, UngriddedDataList)
assert output[3].var_name == 'snow'
assert output[4].var_name == 'snow_std_dev'
assert output[5].var_name == 'snow_num_points'
assert np.allclose(output[0].data, expected_result)
assert all(output[1].data.mask)
assert np.allclose(output[2].data, expected_n)
assert np.allclose(output[3].data, expected_result + 3)
assert all(output[4].data.mask)
assert np.allclose(output[5].data, expected_n)
def test_already_collocated_in_col_ungridded_to_ungridded_in_2d(self):
ug_data = mock.make_regular_2d_ungridded_data()
# This point already exists on the cube with value 5 - which shouldn't be a problem
sample_points = UngriddedData.from_points_array([HyperPoint(0.0, 0.0)])
col = GeneralUngriddedCollocator(fill_value=-999)
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_horizontal_only())[0]
eq_(new_data.data[0], 8.0)
def test_already_collocated_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_horizontal, DummyConstraint
ug_data = mock.make_regular_2d_ungridded_data()
# This point already exists on the cube with value 5 - which shouldn't be a problem
sample_points = UngriddedData.from_points_array([HyperPoint(0.0, 0.0)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, DummyConstraint(), nn_horizontal())[0]
eq_(new_data.data[0], 8.0)
def test_already_collocated_in_col_gridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_gridded
cube = gridded_data.make_from_cube(mock.make_square_5x3_2d_cube())
# This point already exists on the cube with value 5 - which shouldn't be a problem
sample_points = UngriddedData.from_points_array([HyperPoint(0.0, 0.0)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, nn_gridded())[0]
eq_(new_data.data[0], 8.0)
def test_basic_col_in_2d(self):
# lat: -10 to 10 step 5; lon -5 to 5 step 5
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0), HyperPoint(lat=4.0, lon=4.0), HyperPoint(lat=-4.0, lon=-4.0)])
col = GeneralUngriddedCollocator(fill_value=-999)
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_horizontal_only())[0]
eq_(new_data.data[0], 8.0)
eq_(new_data.data[1], 12.0)
eq_(new_data.data[2], 4.0)
def test_basic_col_with_incompatible_points_throws_a_TypeError(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_pressure, SepConstraintKdtree
ug_data = mock.make_regular_4d_ungridded_data()
# Make sample points with no time dimension specified
sample_points = UngriddedData.from_points_array(
[HyperPoint(1.0, 1.0), HyperPoint(4.0, 4.0), HyperPoint(-4.0, -4.0)])
col = GeneralUngriddedCollocator()
with self.assertRaises(AttributeError):
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_pressure())[0]
def test_already_collocated_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_pressure, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=0.0, lon=0.0, pres=80.0, t=dt.datetime(1984, 9, 4, 15, 54))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_pressure())[0]
eq_(new_data.data[0], 41.0)
def test_basic_col_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_horizontal, SepConstraintKdtree
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0), HyperPoint(lat=4.0, lon=4.0), HyperPoint(lat=-4.0, lon=-4.0)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_horizontal())[0]
eq_(new_data.data[0], 8.0)
eq_(new_data.data[1], 12.0)
eq_(new_data.data[2], 4.0)
def test_basic_col_gridded_to_ungridded_using_li_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
cube = gridded_data.make_from_cube(mock.make_square_5x3_2d_cube())
sample_points = UngriddedData.from_points_array(
[HyperPoint(1.0, 1.0), HyperPoint(4.0, 4.0), HyperPoint(-4.0, -4.0)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, li())[0]
assert_almost_equal(new_data.data[0], 8.8)
assert_almost_equal(new_data.data[1], 11.2)
assert_almost_equal(new_data.data[2], 4.8)
def test_coordinates_outside_grid_in_col_ungridded_to_ungridded_in_2d(self):
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array(
[HyperPoint(5.5, 5.5), HyperPoint(-5.5, 5.5), HyperPoint(5.5, -5.5),
HyperPoint(-5.5, -5.5)])
col = GeneralUngriddedCollocator(fill_value=-999)
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_horizontal_only())[0]
eq_(new_data.data[0], 12.0)
eq_(new_data.data[1], 6.0)
eq_(new_data.data[2], 10.0)
eq_(new_data.data[3], 4.0)
def test_coordinates_outside_grid_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_horizontal, DummyConstraint
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array(
[HyperPoint(5.5, 5.5), HyperPoint(-5.5, 5.5), HyperPoint(5.5, -5.5), HyperPoint(-5.5, -5.5)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, DummyConstraint(), nn_horizontal())[0]
eq_(new_data.data[0], 12.0)
eq_(new_data.data[1], 6.0)
eq_(new_data.data[2], 10.0)
eq_(new_data.data[3], 4.0)
def test_basic_col_in_4d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, mean, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
# Note - This isn't actually used for averaging
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0, alt=12.0, t=dt.datetime(1984, 8, 29, 8, 34))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), mean())[0]
eq_(new_data.data[0], 25.5)
def test_alt_extrapolation(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_ht_len=10))
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=-4.0, lon=-4.0, alt=6382.8, t=dt.datetime(1984, 8, 27))])
col = GeneralUngriddedCollocator(fill_value=np.NAN)
new_data = col.collocate(sample_points, cube, None, li(extrapolate=True))[0]
assert_almost_equal(new_data.data[0], 126.0, decimal=7)
def test_coordinates_outside_grid_in_col_gridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_gridded
cube = gridded_data.make_from_cube(mock.make_square_5x3_2d_cube())
sample_points = UngriddedData.from_points_array(
[HyperPoint(5.5, 5.5), HyperPoint(-5.5, 5.5), HyperPoint(5.5, -5.5), HyperPoint(-5.5, -5.5)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, nn_gridded())[0]
eq_(new_data.data[0], 12.0)
eq_(new_data.data[1], 6.0)
eq_(new_data.data[2], 10.0)
eq_(new_data.data[3], 4.0)
def test_extrapolation_of_pres_points_on_hybrid_pressure_coordinates(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_pr_len=10))
sample_points = UngriddedData.from_points_array(
# Point interpolated in the horizontal and then extrapolated past the top vertical layer (by one layer)
[HyperPoint(lat=-4.0, lon=-4.0, pres=68400050.0, t=dt.datetime(1984, 8, 27))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, li(extrapolate=True))[0]
assert_almost_equal(new_data.data[0], 125.0, decimal=7)
def test_collocation_of_pres_points_on_hybrid_altitude_coordinates(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_ht_len=10))
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=-4.0, lon=-4.0, pres=100.0, t=dt.datetime(1984, 8, 27))])
col = GeneralUngriddedCollocator(fill_value=np.NAN)
new_data = col.collocate(sample_points, cube, None, li())[0]
# The kernel can't return a unique point and so should raise a ValueError - leaving the data point blank
assert_equal(new_data.data[0], np.NAN)
def test_basic_col_gridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_gridded
cube = gridded_data.make_from_cube(mock.make_square_5x3_2d_cube())
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0),
HyperPoint(lat=4.0, lon=4.0),
HyperPoint(lat=-4.0, lon=-4.0)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, nn_gridded())[0]
eq_(new_data.data[0], 8.0) # float(cube[2,1].data))
eq_(new_data.data[1], 12.0) # float(cube[3,2].data))
eq_(new_data.data[2], 4.0) # float(cube[1,0].data))
def test_collocation_of_pres_points_on_hybrid_altitude_coordinates(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_gridded
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_ht_len=10))
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0, pres=5000.0, t=dt.datetime(1984, 8, 28, 8, 34))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, nn_gridded())[0]
# There is no pressure coordinate on the cube so no single value could be returned by the kernel
eq_(new_data.data[0], np.inf)
def test_collocation_of_alt_pres_points_on_hybrid_altitude_and_pressure_coordinates(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li, DummyConstraint
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_pr_len=10))
sample_points = UngriddedData.from_points_array(
# Test point with both pressure and altitude should interpolate over the altitude only (since that is also
# present in the data cube)
[HyperPoint(lat=0.0, lon=0.0, alt=234.5, pres=1000, t=dt.datetime(1984, 8, 28, 0, 0, 0))])
col = GeneralUngriddedCollocator(fill_value=np.NAN)
new_data = col.collocate(sample_points, cube, None, li())[0]
assert_almost_equal(new_data.data[0], 225.5, decimal=7)
def test_negative_lon_points_in_2d_dont_matter(self):
"""
This is exactly the same test as above, except we ommit the point with negative longitude, this makes the
collocator wrap the longitude coordinate and gives a slightly different interpolation result...
"""
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
cube = gridded_data.make_from_cube(mock.make_square_5x3_2d_cube())
sample_points = UngriddedData.from_points_array(
[HyperPoint(1.0, 1.0), HyperPoint(4.0, 4.0)])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, li())[0]
assert_almost_equal(new_data.data[0], 8.8)
assert_almost_equal(new_data.data[1], 11.2)
def test_basic_col_with_incompatible_points_throws_a_TypeError(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_pressure, SepConstraintKdtree
ug_data = mock.make_regular_4d_ungridded_data()
# Make sample points with no time dimension specified
sample_points = UngriddedData.from_points_array([
HyperPoint(1.0, 1.0),
HyperPoint(4.0, 4.0),
HyperPoint(-4.0, -4.0)
])
col = GeneralUngriddedCollocator()
with self.assertRaises(AttributeError):
new_data = col.collocate(sample_points, ug_data,
SepConstraintKdtree(), nn_pressure())[0]
def test_collocation_of_alt_points_on_hybrid_altitude_coordinates_on_0_360_grid(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_gridded
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_ht_len=10, lon_dim_length=36,
lon_range=(0., 350.)))
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=111.0, alt=5000.0, t=dt.datetime(1984, 8, 28, 8, 34)),
HyperPoint(lat=4.0, lon=141.0, alt=12000.0, t=dt.datetime(1984, 8, 28, 8, 34))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, nn_gridded())[0]
eq_(new_data.data[0], 2501.0) # float(cube[2,11,1,0].data))
eq_(new_data.data[1], 3675.0) # float(cube[3,14,1,4].data))
def test_basic_col_in_2d(self):
# lat: -10 to 10 step 5; lon -5 to 5 step 5
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array([
HyperPoint(lat=1.0, lon=1.0),
HyperPoint(lat=4.0, lon=4.0),
HyperPoint(lat=-4.0, lon=-4.0)
])
col = GeneralUngriddedCollocator(fill_value=-999)
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_horizontal_only())[0]
eq_(new_data.data[0], 8.0)
eq_(new_data.data[1], 12.0)
eq_(new_data.data[2], 4.0)
def test_basic_col_in_2d_with_time(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_time, DummyConstraint
import datetime as dt
ug_data = mock.make_regular_2d_with_time_ungridded_data()
sample_points = HyperPointList()
sample_points.append(HyperPoint(lat=1.0, lon=1.0, t=dt.datetime(1984, 8, 29, 8, 34)))
sample_points.append(HyperPoint(lat=4.0, lon=4.0, t=dt.datetime(1984, 9, 2, 1, 23)))
sample_points.append(HyperPoint(lat=-4.0, lon=-4.0, t=dt.datetime(1984, 9, 4, 15, 54)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, DummyConstraint(), nn_time())[0]
eq_(new_data.data[0], 3.0)
eq_(new_data.data[1], 7.0)
eq_(new_data.data[2], 10.0)
def test_negative_lon_points_on_hybrid_pressure_coordinates_dont_matter(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_pr_len=10))
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=0.0, lon=0.0, pres=111100040.5, t=dt.datetime(1984, 8, 28, 0, 0, 0)),
HyperPoint(lat=5.0, lon=2.5, pres=177125044.5, t=dt.datetime(1984, 8, 28, 0, 0, 0))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, li())[0]
# Exactly on the lat, lon, time points, interpolated over pressure
assert_almost_equal(new_data.data[0], 221.5, decimal=5)
# Exactly on the lat, time points, interpolated over latitude and pressure
assert_almost_equal(new_data.data[1], 330.5, decimal=7)
def test_nearest_neighbour_vertical_interpolation_on_hybrid_pressure(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_pr_len=10))
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=0.0, lon=0.0, pres=111100040.5, t=dt.datetime(1984, 8, 28, 0, 0, 0)),
HyperPoint(lat=5.0, lon=2.5, pres=177125044.5, t=dt.datetime(1984, 8, 28, 0, 0, 0)),
HyperPoint(lat=-4.0, lon=-4.0, pres=68400050.0, t=dt.datetime(1984, 8, 27))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, cube, None, li(nn_vertical=True))[0]
assert_almost_equal(new_data.data[0], 221)
assert_almost_equal(new_data.data[1], 330)
assert_almost_equal(new_data.data[2], 124.0)
def test_already_collocated_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_pressure, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
sample_points = UngriddedData.from_points_array([
HyperPoint(lat=0.0,
lon=0.0,
pres=80.0,
t=dt.datetime(1984, 9, 4, 15, 54))
])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_pressure())[0]
eq_(new_data.data[0], 41.0)
def test_coordinates_outside_grid_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_pressure, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
sample_points = HyperPointList()
sample_points.append(HyperPoint(lat=0.0, lon=0.0, pres=0.1, t=dt.datetime(1984, 8, 29, 8, 34)))
sample_points.append(HyperPoint(lat=0.0, lon=0.0, pres=91.0, t=dt.datetime(1984, 9, 2, 1, 23)))
sample_points.append(HyperPoint(lat=0.0, lon=0.0, pres=890.0, t=dt.datetime(1984, 9, 4, 15, 54)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_pressure())[0]
eq_(new_data.data[0], 1.0)
eq_(new_data.data[1], 46.0)
eq_(new_data.data[2], 46.0)
def test_coordinates_outside_grid_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_time, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_2d_with_time_ungridded_data()
sample_points = HyperPointList()
sample_points.append(HyperPoint(lat=0.0, lon=0.0, t=dt.datetime(1984, 8, 26)))
sample_points.append(HyperPoint(lat=0.0, lon=0.0, t=dt.datetime(1884, 8, 26)))
sample_points.append(HyperPoint(lat=0.0, lon=0.0, t=dt.datetime(1994, 8, 27)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_time())[0]
eq_(new_data.data[0], 1.0)
eq_(new_data.data[1], 1.0)
eq_(new_data.data[2], 15.0)
def test_basic_col_in_4d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_altitude, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
sample_points = HyperPointList()
sample_points.append(HyperPoint(lat=1.0, lon=1.0, alt=12.0, t=dt.datetime(1984, 8, 29, 8, 34)))
sample_points.append(HyperPoint(lat=4.0, lon=4.0, alt=34.0, t=dt.datetime(1984, 9, 2, 1, 23)))
sample_points.append(HyperPoint(lat=-4.0, lon=-4.0, alt=89.0, t=dt.datetime(1984, 9, 4, 15, 54)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_altitude())[0]
eq_(new_data.data[0], 6.0)
eq_(new_data.data[1], 16.0)
eq_(new_data.data[2], 46.0)
def test_basic_col_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_horizontal, SepConstraintKdtree
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array([
HyperPoint(lat=1.0, lon=1.0),
HyperPoint(lat=4.0, lon=4.0),
HyperPoint(lat=-4.0, lon=-4.0)
])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_horizontal())[0]
eq_(new_data.data[0], 8.0)
eq_(new_data.data[1], 12.0)
eq_(new_data.data[2], 4.0)
def test_nearest_neighbour_vertical_interpolation_on_hybrid_altitude(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, li
import datetime as dt
cube = gridded_data.make_from_cube(mock.make_mock_cube(time_dim_length=3, hybrid_ht_len=10))
sample_points = UngriddedData.from_points_array(
# This is just past the top of the vertical coordinate slice
[HyperPoint(lat=-4.0, lon=-4.0, alt=6500.0, t=dt.datetime(1984, 8, 27)),
# This is well past the bottom of the vertical coordinate slice
HyperPoint(lat=-4.0, lon=-4.0, alt=0.0, t=dt.datetime(1984, 8, 27))])
col = GeneralUngriddedCollocator(fill_value=np.NAN)
new_data = col.collocate(sample_points, cube, None, li(nn_vertical=True))[0]
assert_almost_equal(new_data.data[0], 124.0, decimal=7)
assert_almost_equal(new_data.data[1], 115.0, decimal=7)
def test_already_collocated_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_time, SepConstraintKdtree
import datetime as dt
import numpy as np
ug_data = mock.make_regular_2d_with_time_ungridded_data()
sample_points = HyperPointList()
t0 = dt.datetime(1984, 8, 27)
for d in range(15):
sample_points.append(HyperPoint(lat=0.0, lon=0.0, t=t0 + dt.timedelta(days=d)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), nn_time())[0]
assert (np.equal(new_data.data, np.arange(15) + 1.0).all())
def test_coordinates_outside_grid_in_col_ungridded_to_ungridded_in_2d(
self):
ug_data = mock.make_regular_2d_ungridded_data()
sample_points = UngriddedData.from_points_array([
HyperPoint(5.5, 5.5),
HyperPoint(-5.5, 5.5),
HyperPoint(5.5, -5.5),
HyperPoint(-5.5, -5.5)
])
col = GeneralUngriddedCollocator(fill_value=-999)
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_horizontal_only())[0]
eq_(new_data.data[0], 12.0)
eq_(new_data.data[1], 6.0)
eq_(new_data.data[2], 10.0)
eq_(new_data.data[3], 4.0)
def test_basic_col_in_4d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, mean, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
# Note - This isn't actually used for averaging
sample_points = UngriddedData.from_points_array([
HyperPoint(lat=1.0,
lon=1.0,
alt=12.0,
t=dt.datetime(1984, 8, 29, 8, 34))
])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
mean())[0]
eq_(new_data.data[0], 25.5)
def test_averaging_basic_col_in_4d(self):
ug_data = mock.make_regular_4d_ungridded_data()
# Note - This isn't actually used for averaging
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0, alt=12.0, t=dt.datetime(1984, 8, 29, 8, 34))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(), moments())
means = new_data[0]
std_dev = new_data[1]
no_points = new_data[2]
eq_(means.name(), 'rainfall_flux')
eq_(std_dev.name(), 'Corrected sample standard deviation of TOTAL RAINFALL RATE: LS+CONV KG/M2/S')
eq_(no_points.name(), 'Number of points used to calculate the mean of TOTAL RAINFALL RATE: LS+CONV KG/M2/S')
assert means.coords()
assert std_dev.coords()
assert no_points.coords()
def test_already_collocated_in_col_ungridded_to_ungridded_in_2d(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_time, SepConstraintKdtree
import datetime as dt
import numpy as np
ug_data = mock.make_regular_2d_with_time_ungridded_data()
sample_points = HyperPointList()
t0 = dt.datetime(1984, 8, 27)
for d in range(15):
sample_points.append(
HyperPoint(lat=0.0, lon=0.0, t=t0 + dt.timedelta(days=d)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_time())[0]
assert (np.equal(new_data.data, np.arange(15) + 1.0).all())
def test_coordinates_exactly_between_points_in_col_ungridded_to_ungridded_in_2d(
self):
"""
This works out the edge case where the points are exactly in the middle or two or more datapoints.
The nn_time algorithm will start with the first point as the nearest and iterates through the
points finding any points which are closer than the current closest. If two distances were exactly
the same the first point to be chosen.
"""
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_time, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_2d_with_time_ungridded_data()
# Choose a time at midday
sample_points = UngriddedData.from_points_array(
[HyperPoint(lat=0.0, lon=0.0, t=dt.datetime(1984, 8, 29, 12))])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_time())[0]
eq_(new_data.data[0], 3.0)
def test_ungridded_ungridded_box_moments(self):
data = mock.make_regular_2d_ungridded_data()
sample = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0, alt=12.0, t=dt.datetime(1984, 8, 29, 8, 34)),
HyperPoint(lat=3.0, lon=3.0, alt=7.0, t=dt.datetime(1984, 8, 29, 8, 34)),
HyperPoint(lat=-1.0, lon=-1.0, alt=5.0, t=dt.datetime(1984, 8, 29, 8, 34))])
constraint = SepConstraintKdtree('500km')
kernel = moments()
col = GeneralUngriddedCollocator()
output = col.collocate(sample, data, constraint, kernel)
expected_result = np.array([28.0/3, 10.0, 20.0/3])
expected_stddev = np.array([1.52752523, 1.82574186, 1.52752523])
expected_n = np.array([3, 4, 3])
assert len(output) == 3
assert isinstance(output, UngriddedDataList)
assert np.allclose(output[0].data, expected_result)
assert np.allclose(output[1].data, expected_stddev)
assert np.allclose(output[2].data, expected_n)
def test_ungridded_ungridded_box_moments_no_missing_data_for_missing_sample(self):
data = mock.make_regular_2d_ungridded_data()
sample = UngriddedData.from_points_array(
[HyperPoint(lat=1.0, lon=1.0, alt=12.0, t=dt.datetime(1984, 8, 29, 8, 34)),
HyperPoint(lat=3.0, lon=3.0, alt=7.0, t=dt.datetime(1984, 8, 29, 8, 34)),
HyperPoint(lat=-1.0, lon=-1.0, alt=5.0, t=dt.datetime(1984, 8, 29, 8, 34))])
constraint = SepConstraintKdtree('500km')
kernel = moments()
sample_mask = [False, True, False]
sample.data = np.ma.array([0, 0, 0], mask=sample_mask)
col = GeneralUngriddedCollocator(missing_data_for_missing_sample=False)
output = col.collocate(sample, data, constraint, kernel)
assert len(output) == 3
assert isinstance(output, UngriddedDataList)
assert not any(output[0].data.mask)
assert not any(output[1].data.mask)
assert not any(output[2].data.mask)
def test_coordinates_outside_grid_in_col_ungridded_to_ungridded_in_2d(
self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_time, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_2d_with_time_ungridded_data()
sample_points = HyperPointList()
sample_points.append(
HyperPoint(lat=0.0, lon=0.0, t=dt.datetime(1984, 8, 26)))
sample_points.append(
HyperPoint(lat=0.0, lon=0.0, t=dt.datetime(1884, 8, 26)))
sample_points.append(
HyperPoint(lat=0.0, lon=0.0, t=dt.datetime(1994, 8, 27)))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_time())[0]
eq_(new_data.data[0], 1.0)
eq_(new_data.data[1], 1.0)
eq_(new_data.data[2], 15.0)
def test_basic_col_with_time(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, nn_time, SepConstraintKdtree
import numpy as np
ug_data = mock.make_MODIS_time_steps()
ref = np.array([0.0, 1.0, 2.0, 3.0])
sample_points = HyperPointList()
sample_points.append(HyperPoint(lat=0.0, lon=0.0, t=149751.369618055))
sample_points.append(HyperPoint(
lat=0.0,
lon=0.0,
t=149759.378055556,
))
sample_points.append(HyperPoint(lat=0.0, lon=0.0, t=149766.373969907))
sample_points.append(HyperPoint(lat=0.0, lon=0.0, t=149776.375995371))
sample_points = UngriddedData.from_points_array(sample_points)
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
nn_time())[0]
assert (np.equal(new_data.data, ref).all())
def test_basic_col_in_4d_with_pressure_not_altitude(self):
from cis.collocation.col_implementations import GeneralUngriddedCollocator, moments, SepConstraintKdtree
import datetime as dt
ug_data = mock.make_regular_4d_ungridded_data()
# Note - This isn't actually used for averaging
sample_points = UngriddedData.from_points_array([
HyperPoint(lat=1.0,
lon=1.0,
pres=12.0,
t=dt.datetime(1984, 8, 29, 8, 34))
])
col = GeneralUngriddedCollocator()
new_data = col.collocate(sample_points, ug_data, SepConstraintKdtree(),
moments())
means = new_data[0]
std_dev = new_data[1]
no_points = new_data[2]
eq_(means.data[0], 25.5)
assert_almost_equal(std_dev.data[0], np.sqrt(212.5))
eq_(no_points.data[0], 50)
