From 2f0f3d328a12e95984521ba37154e03f53f267e0 Mon Sep 17 00:00:00 2001 From: Greg Lucas Date: Sun, 31 Oct 2021 16:54:17 -0600 Subject: [PATCH 1/4] FIX: Change PlateCarree vector handling If a PlateCarree projection is used for transforming vectors, users likely have their data in longitude/latitude for the locations and the measurement of the field is in North/South. To handle this situation with PlateCarree requires an additional scaling by the latitude of the point. This also requires some additional care for handling points near the pole when applying this scaling. --- lib/cartopy/crs.py | 63 ++++++++++++++++++---- lib/cartopy/tests/test_vector_transform.py | 8 +-- 2 files changed, 58 insertions(+), 13 deletions(-) diff --git a/lib/cartopy/crs.py b/lib/cartopy/crs.py index ab7e2157b..18da79fcc 100644 --- a/lib/cartopy/crs.py +++ b/lib/cartopy/crs.py @@ -479,14 +479,34 @@ def transform_vectors(self, src_proj, x, y, u, v): raise ValueError('x, y, u and v arrays must be the same shape') if x.ndim not in (1, 2): raise ValueError('x, y, u and v must be 1 or 2 dimensional') - # Transform the coordinates to the target projection. - proj_xyz = self.transform_points(src_proj, x, y) - target_x, target_y = proj_xyz[..., 0], proj_xyz[..., 1] - # Rotate the input vectors to the projection. - # - # 1: Find the magnitude and direction of the input vectors. - vector_magnitudes = (u**2 + v**2)**0.5 + + # 1a: Find the magnitude of the input vectors + vector_magnitudes = np.sqrt(u**2 + v**2) + + # Handle special case of PlateCarree projection + # This assumes we were given lon/lat coordinates and + # east/north vector components (NOT PlateCarree vector components) + # When projecting the components we need to scale the vector + # component for the transformation to maintain the proper angles + if isinstance(src_proj, PlateCarree): + # First handle points close to the pole by cutting off the + # latitude a small distance away + pole_cutoff = 90 - 1e-2 + pole_points = np.abs(y) >= pole_cutoff + if np.any(pole_points): + # Warn for points close to the poles, as these are + # unreliable for vector directions under transformation + warnings.warn('Vector transforms near the pole ' + 'may not have been transformed correctly') + # Move the pole points away from the pole ever so slightly + y[pole_points] = np.sign(y[pole_points]) * pole_cutoff + + scale_factor = np.cos(y / 180 * np.pi) + v = v * scale_factor + + # 1b: Find the direction of the input vectors vector_angles = np.arctan2(v, u) + # 2: Find a point in the direction of the original vector that is # a small distance away from the base point of the vector (near # the poles the point may have to be in the opposite direction @@ -495,6 +515,7 @@ def transform_vectors(self, src_proj, x, y, u, v): delta = (src_proj.x_limits[1] - src_proj.x_limits[0]) / factor x_perturbations = delta * np.cos(vector_angles) y_perturbations = delta * np.sin(vector_angles) + # 3: Handle points that are invalid. These come from picking a new # point that is outside the domain of the CRS. The first step is # to apply the native transform to the input coordinates to make @@ -535,21 +556,45 @@ def transform_vectors(self, src_proj, x, y, u, v): source_x + x_perturbations < src_proj.x_limits[0] - eps, source_x + x_perturbations > src_proj.x_limits[1] + eps) if problem_points.any(): - warnings.warn('Some vectors at source domain corners ' + warnings.warn('Some vectors at the source domain corners ' 'may not have been transformed correctly') + # 4: Transform this set of points to the projection coordinates and # find the angle between the base point and the perturbed point # in the projection coordinates (reversing the direction at any # points where the original was reversed in step 3). + proj_xyz = self.transform_points(src_proj, x, y) + target_x, target_y = proj_xyz[..., 0], proj_xyz[..., 1] + proj_xyz = self.transform_points(src_proj, source_x + x_perturbations, source_y + y_perturbations) target_x_perturbed = proj_xyz[..., 0] target_y_perturbed = proj_xyz[..., 1] + + x_delta = target_x_perturbed - target_x + if isinstance(self, PlateCarree): + # Warn for points close to the poles, as these are + # unreliable for vector directions under transformation + pole_cutoff = 90 - 1e-2 + pole_points = np.abs(target_y) >= pole_cutoff + if np.any(pole_points): + warnings.warn('Vector transforms near the pole ' + 'may not have been transformed correctly') + # Move the pole points away from the pole ever so slightly + target_y[pole_points] = (np.sign(target_y[pole_points]) * + pole_cutoff) + # Account for scaling to the North/South components in the + # opposite manner as the source coordinate handling + # (i.e. inverse scale factor), with target_y being + # the latitudes we are going to + scale_factor = np.cos(target_y / 180 * np.pi) + x_delta = x_delta * scale_factor projected_angles = np.arctan2(target_y_perturbed - target_y, - target_x_perturbed - target_x) + x_delta) if reversed_vectors.any(): projected_angles[reversed_vectors] += np.pi + # 5: Form the projected vector components, preserving the magnitude # of the original vectors. projected_u = vector_magnitudes * np.cos(projected_angles) diff --git a/lib/cartopy/tests/test_vector_transform.py b/lib/cartopy/tests/test_vector_transform.py index 8a790a4c4..dc65755e7 100644 --- a/lib/cartopy/tests/test_vector_transform.py +++ b/lib/cartopy/tests/test_vector_transform.py @@ -144,11 +144,11 @@ def test_with_transform(self): [7.5, 7.5, 7.5, 7.5, 7.5], [10., 10., 10., 10., 10]]) expected_u_grid = np.array([[np.nan, np.nan, np.nan, np.nan, np.nan], - [np.nan, 2.3838, 3.5025, 2.6152, np.nan], - [2, 3.0043, 4, 2.9022, 2]]) + [np.nan, 2.3893, 3.5097, 2.6194, np.nan], + [2, 3.0005, 4, 2.8977, 2]]) expected_v_grid = np.array([[np.nan, np.nan, np.nan, np.nan, np.nan], - [np.nan, 2.6527, 2.1904, 2.4192, np.nan], - [5.5, 4.6483, 4, 4.47, 5.5]]) + [np.nan, 2.6486, 2.1878, 2.4138, np.nan], + [5.5, 4.6497, 4, 4.4702, 5.5]]) x_grid, y_grid, u_grid, v_grid = vec_trans.vector_scalar_to_grid( src_crs, target_crs, (5, 3), x_nps, y_nps, u_nps, v_nps) From 234432cab2f9b2c0eb3b3dfa67331a0b2941e335 Mon Sep 17 00:00:00 2001 From: Greg Lucas Date: Mon, 1 Nov 2021 08:06:34 -0600 Subject: [PATCH 2/4] MNT: Parameterize transform_vectors tests This adds a parameterization for the vector transform tests on the boundary. The previous values were incorrect. They should be at an angle, not all in vertical/horizontal coordinates. This can be thought of by "wrapping" around the pole with a vector pointing up and right at the corner (180, 90) turning into a down and left vector under transform to stereographic. --- .../tests/test_crs_transform_vectors.py | 84 ++++--------------- 1 file changed, 16 insertions(+), 68 deletions(-) diff --git a/lib/cartopy/tests/test_crs_transform_vectors.py b/lib/cartopy/tests/test_crs_transform_vectors.py index 82875f8a3..c2b98d285 100644 --- a/lib/cartopy/tests/test_crs_transform_vectors.py +++ b/lib/cartopy/tests/test_crs_transform_vectors.py @@ -79,76 +79,24 @@ def test_invalid_input_domain(self): assert_array_almost_equal(ut, np.array([0]), decimal=2) assert_array_almost_equal(vt, np.array([-1]), decimal=2) - def test_invalid_x_domain(self): - # If the point we need to calculate the vector angle falls outside the - # source projection x-domain it should be handled correctly as long as - # it is not a corner point. - rlon = np.array([180.]) - rlat = np.array([0.]) - u = np.array([1.]) - v = np.array([0.]) - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - ut, vt = target_proj.transform_vectors(src_proj, rlon, rlat, u, v) - assert_array_almost_equal(ut, np.array([-1]), decimal=2) - assert_array_almost_equal(vt, np.array([0.]), decimal=2) - - def test_invalid_y_domain(self): - # If the point we need to calculate the vector angle falls outside the - # source projection y-domain it should be handled correctly as long as - # it is not a corner point. - rlon = np.array([0.]) - rlat = np.array([90.]) - u = np.array([0.]) - v = np.array([1.]) - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - ut, vt = target_proj.transform_vectors(src_proj, rlon, rlat, u, v) - assert_array_almost_equal(ut, np.array([0.]), decimal=2) - assert_array_almost_equal(vt, np.array([1.]), decimal=2) - - def test_invalid_xy_domain_corner(self): - # If the point we need to calculate the vector angle falls outside the - # source projection x and y-domain it should be handled correctly. - rlon = np.array([180.]) - rlat = np.array([90.]) - u = np.array([1.]) - v = np.array([1.]) + @pytest.mark.parametrize('x, y, u, v, expected', [ + pytest.param(180, 0, 1, 0, [-1, 0], id='x non-corner'), + pytest.param(0, 90, 0, 1, [0, 1], id='y non-corner'), + pytest.param(180, 90, 1, 1, [0, -np.sqrt(2)], id='xy corner'), + pytest.param(180, 90, 1, -1, [0, np.sqrt(2)], id='x corner'), + pytest.param(180, 90, -1, 1, [0, -np.sqrt(2)], id='y corner')]) + def test_transform_on_border(self, x, y, u, v, expected): src_proj = ccrs.PlateCarree() target_proj = ccrs.Stereographic(central_latitude=90, central_longitude=0) - ut, vt = target_proj.transform_vectors(src_proj, rlon, rlat, u, v) - assert_array_almost_equal(ut, np.array([0.]), decimal=2) - assert_array_almost_equal(vt, np.array([-2**.5]), decimal=2) - def test_invalid_x_domain_corner(self): - # If the point we need to calculate the vector angle falls outside the - # source projection x-domain and is a corner point, it may be handled - # incorrectly and a warning should be raised. - rlon = np.array([180.]) - rlat = np.array([90.]) - u = np.array([1.]) - v = np.array([-1.]) - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - with pytest.warns(UserWarning): - warnings.simplefilter('always') - ut, vt = target_proj.transform_vectors(src_proj, rlon, rlat, u, v) + x, y = np.array([x]), np.array([y]) + u, v = np.array([u]), np.array([v]) + # We expect to warn the user only when y is on the pole + if y[0] == 90: + with pytest.warns(UserWarning): + ut, vt = target_proj.transform_vectors(src_proj, x, y, u, v) + else: + ut, vt = target_proj.transform_vectors(src_proj, x, y, u, v) - def test_invalid_y_domain_corner(self): - # If the point we need to calculate the vector angle falls outside the - # source projection y-domain and is a corner point, it may be handled - # incorrectly and a warning should be raised. - rlon = np.array([180.]) - rlat = np.array([90.]) - u = np.array([-1.]) - v = np.array([1.]) - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - with pytest.warns(UserWarning): - warnings.simplefilter('always') - ut, vt = target_proj.transform_vectors(src_proj, rlon, rlat, u, v) + assert_array_almost_equal([ut[0], vt[0]], expected, decimal=2) From ac93213b2b0d3fe2607e5493898aa2b84b4fbeeb Mon Sep 17 00:00:00 2001 From: Greg Lucas Date: Mon, 1 Nov 2021 08:12:25 -0600 Subject: [PATCH 3/4] MNT: Combine vector transform tests into a single file Move crs_transform_vectors tests into the test_vector_transforms file. --- .../tests/test_crs_transform_vectors.py | 102 ------------------ lib/cartopy/tests/test_vector_transform.py | 90 ++++++++++++++++ 2 files changed, 90 insertions(+), 102 deletions(-) delete mode 100644 lib/cartopy/tests/test_crs_transform_vectors.py diff --git a/lib/cartopy/tests/test_crs_transform_vectors.py b/lib/cartopy/tests/test_crs_transform_vectors.py deleted file mode 100644 index c2b98d285..000000000 --- a/lib/cartopy/tests/test_crs_transform_vectors.py +++ /dev/null @@ -1,102 +0,0 @@ -# Copyright Cartopy Contributors -# -# This file is part of Cartopy and is released under the LGPL license. -# See COPYING and COPYING.LESSER in the root of the repository for full -# licensing details. - -import warnings - -import numpy as np -from numpy.testing import assert_array_almost_equal -import pytest - -import cartopy.crs as ccrs - - -class TestTransformVectors: - - def test_transform(self): - # Test some simple vectors to make sure they are transformed - # correctly. - rlons = np.array([-90., 0, 90., 180.]) - rlats = np.array([0., 0., 0., 0.]) - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - # transform grid eastward vectors - ut, vt = target_proj.transform_vectors(src_proj, - rlons, - rlats, - np.ones([4]), - np.zeros([4])) - assert_array_almost_equal(ut, np.array([0, 1, 0, -1]), decimal=2) - assert_array_almost_equal(vt, np.array([-1, 0, 1, 0]), decimal=2) - # transform grid northward vectors - ut, vt = target_proj.transform_vectors(src_proj, - rlons, - rlats, - np.zeros([4]), - np.ones([4])) - assert_array_almost_equal(ut, np.array([1, 0, -1, 0]), decimal=2) - assert_array_almost_equal(vt, np.array([0, 1, 0, -1]), decimal=2) - # transform grid north-eastward vectors - ut, vt = target_proj.transform_vectors(src_proj, - rlons, - rlats, - np.ones([4]), - np.ones([4])) - assert_array_almost_equal(ut, np.array([1, 1, -1, -1]), decimal=2) - assert_array_almost_equal(vt, np.array([-1, 1, 1, -1]), decimal=2) - - def test_transform_and_inverse(self): - # Check a full circle transform back to the native projection. - x = np.arange(-60, 42.5, 2.5) - y = np.arange(30, 72.5, 2.5) - x2d, y2d = np.meshgrid(x, y) - u = np.cos(np.deg2rad(y2d)) - v = np.cos(2. * np.deg2rad(x2d)) - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - proj_xyz = target_proj.transform_points(src_proj, x2d, y2d) - xt, yt = proj_xyz[..., 0], proj_xyz[..., 1] - ut, vt = target_proj.transform_vectors(src_proj, x2d, y2d, u, v) - utt, vtt = src_proj.transform_vectors(target_proj, xt, yt, ut, vt) - assert_array_almost_equal(u, utt, decimal=4) - assert_array_almost_equal(v, vtt, decimal=4) - - def test_invalid_input_domain(self): - # If an input coordinate is outside the input projection domain - # we should be able to handle it correctly. - rlon = np.array([270.]) - rlat = np.array([0.]) - u = np.array([1.]) - v = np.array([0.]) - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - ut, vt = target_proj.transform_vectors(src_proj, rlon, rlat, u, v) - assert_array_almost_equal(ut, np.array([0]), decimal=2) - assert_array_almost_equal(vt, np.array([-1]), decimal=2) - - @pytest.mark.parametrize('x, y, u, v, expected', [ - pytest.param(180, 0, 1, 0, [-1, 0], id='x non-corner'), - pytest.param(0, 90, 0, 1, [0, 1], id='y non-corner'), - pytest.param(180, 90, 1, 1, [0, -np.sqrt(2)], id='xy corner'), - pytest.param(180, 90, 1, -1, [0, np.sqrt(2)], id='x corner'), - pytest.param(180, 90, -1, 1, [0, -np.sqrt(2)], id='y corner')]) - def test_transform_on_border(self, x, y, u, v, expected): - src_proj = ccrs.PlateCarree() - target_proj = ccrs.Stereographic(central_latitude=90, - central_longitude=0) - - x, y = np.array([x]), np.array([y]) - u, v = np.array([u]), np.array([v]) - # We expect to warn the user only when y is on the pole - if y[0] == 90: - with pytest.warns(UserWarning): - ut, vt = target_proj.transform_vectors(src_proj, x, y, u, v) - else: - ut, vt = target_proj.transform_vectors(src_proj, x, y, u, v) - - assert_array_almost_equal([ut[0], vt[0]], expected, decimal=2) diff --git a/lib/cartopy/tests/test_vector_transform.py b/lib/cartopy/tests/test_vector_transform.py index dc65755e7..9b506652c 100644 --- a/lib/cartopy/tests/test_vector_transform.py +++ b/lib/cartopy/tests/test_vector_transform.py @@ -6,6 +6,7 @@ import numpy as np from numpy.testing import assert_array_almost_equal, assert_array_equal +import pytest import cartopy.crs as ccrs import cartopy.vector_transform as vec_trans @@ -222,3 +223,92 @@ def test_with_scalar_field_non_ndarray_data(self): assert_array_almost_equal(u_grid, expected_u_grid) assert_array_almost_equal(v_grid, expected_v_grid) assert_array_almost_equal(s_grid, expected_s_grid) + + +class TestTransformVectors: + + def test_transform(self): + # Test some simple vectors to make sure they are transformed + # correctly. + rlons = np.array([-90., 0, 90., 180.]) + rlats = np.array([0., 0., 0., 0.]) + src_proj = ccrs.PlateCarree() + target_proj = ccrs.Stereographic(central_latitude=90, + central_longitude=0) + # transform grid eastward vectors + ut, vt = target_proj.transform_vectors(src_proj, + rlons, + rlats, + np.ones([4]), + np.zeros([4])) + assert_array_almost_equal(ut, np.array([0, 1, 0, -1]), decimal=2) + assert_array_almost_equal(vt, np.array([-1, 0, 1, 0]), decimal=2) + # transform grid northward vectors + ut, vt = target_proj.transform_vectors(src_proj, + rlons, + rlats, + np.zeros([4]), + np.ones([4])) + assert_array_almost_equal(ut, np.array([1, 0, -1, 0]), decimal=2) + assert_array_almost_equal(vt, np.array([0, 1, 0, -1]), decimal=2) + # transform grid north-eastward vectors + ut, vt = target_proj.transform_vectors(src_proj, + rlons, + rlats, + np.ones([4]), + np.ones([4])) + assert_array_almost_equal(ut, np.array([1, 1, -1, -1]), decimal=2) + assert_array_almost_equal(vt, np.array([-1, 1, 1, -1]), decimal=2) + + def test_transform_and_inverse(self): + # Check a full circle transform back to the native projection. + x = np.arange(-60, 42.5, 2.5) + y = np.arange(30, 72.5, 2.5) + x2d, y2d = np.meshgrid(x, y) + u = np.cos(np.deg2rad(y2d)) + v = np.cos(2. * np.deg2rad(x2d)) + src_proj = ccrs.PlateCarree() + target_proj = ccrs.Stereographic(central_latitude=90, + central_longitude=0) + proj_xyz = target_proj.transform_points(src_proj, x2d, y2d) + xt, yt = proj_xyz[..., 0], proj_xyz[..., 1] + ut, vt = target_proj.transform_vectors(src_proj, x2d, y2d, u, v) + utt, vtt = src_proj.transform_vectors(target_proj, xt, yt, ut, vt) + assert_array_almost_equal(u, utt, decimal=4) + assert_array_almost_equal(v, vtt, decimal=4) + + def test_invalid_input_domain(self): + # If an input coordinate is outside the input projection domain + # we should be able to handle it correctly. + rlon = np.array([270.]) + rlat = np.array([0.]) + u = np.array([1.]) + v = np.array([0.]) + src_proj = ccrs.PlateCarree() + target_proj = ccrs.Stereographic(central_latitude=90, + central_longitude=0) + ut, vt = target_proj.transform_vectors(src_proj, rlon, rlat, u, v) + assert_array_almost_equal(ut, np.array([0]), decimal=2) + assert_array_almost_equal(vt, np.array([-1]), decimal=2) + + @pytest.mark.parametrize('x, y, u, v, expected', [ + pytest.param(180, 0, 1, 0, [-1, 0], id='x non-corner'), + pytest.param(0, 90, 0, 1, [0, 1], id='y non-corner'), + pytest.param(180, 90, 1, 1, [-1, -1], id='xy corner'), + pytest.param(180, 90, 1, -1, [-1, 1], id='x corner'), + pytest.param(180, 90, -1, 1, [1, -1], id='y corner')]) + def test_transform_on_border(self, x, y, u, v, expected): + src_proj = ccrs.PlateCarree() + target_proj = ccrs.Stereographic(central_latitude=90, + central_longitude=0) + + x, y = np.array([x]), np.array([y]) + u, v = np.array([u]), np.array([v]) + # We expect to warn the user only when y is on the pole + if y[0] == 90: + with pytest.warns(UserWarning): + ut, vt = target_proj.transform_vectors(src_proj, x, y, u, v) + else: + ut, vt = target_proj.transform_vectors(src_proj, x, y, u, v) + + assert_array_almost_equal([ut[0], vt[0]], expected, decimal=2) From 4ef0b66850768f1b8b93eb31dea060a77e1c26f1 Mon Sep 17 00:00:00 2001 From: Greg Lucas Date: Mon, 28 Aug 2023 20:00:41 -0600 Subject: [PATCH 4/4] TST: Updating vector test images Contains the updated images based on the updated vector transform routines. --- .../mpl/test_mpl_integration/barbs_1d.png | Bin 34638 -> 34791 bytes .../barbs_1d_transformed.png | Bin 30494 -> 30444 bytes .../barbs_plate_carree.png | Bin 106787 -> 106344 bytes .../mpl/test_mpl_integration/barbs_regrid.png | Bin 86467 -> 86680 bytes .../barbs_regrid_with_extent.png | Bin 54719 -> 54998 bytes .../quiver_plate_carree.png | Bin 170519 -> 170375 bytes .../test_mpl_integration/quiver_regrid.png | Bin 92267 -> 92109 bytes .../quiver_regrid_with_extent.png | Bin 65981 -> 66991 bytes .../quiver_rotated_pole.png | Bin 176716 -> 179411 bytes .../mpl/test_mpl_integration/streamplot.png | Bin 110080 -> 112792 bytes 10 files changed, 0 insertions(+), 0 deletions(-) diff --git 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