| # Licensed to the Apache Software Foundation (ASF) under one or more |
| # contributor license agreements. See the NOTICE file distributed with |
| # this work for additional information regarding copyright ownership. |
| # The ASF licenses this file to You under the Apache License, Version 2.0 |
| # (the "License"); you may not use this file except in compliance with |
| # the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| |
| import unittest |
| import numpy as np |
| from nexustiles.model.nexusmodel import get_approximate_value_for_lat_lon, Tile, BBox |
| |
| |
| class TestApproximateValueMethod(unittest.TestCase): |
| def test_lat_exact_lon_exact(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertAlmostEqual(22.0, get_approximate_value_for_lat_lon([tile], 1.0, 0)) |
| |
| def test_lat_lon_exact_min(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertAlmostEqual(0, get_approximate_value_for_lat_lon([tile], -1.0, -2.0)) |
| |
| def test_lat_approx_lon_exact(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertAlmostEqual(5.0, get_approximate_value_for_lat_lon([tile], -0.4, -2.0)) |
| |
| def test_lat_approx_lon_approx(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertAlmostEqual(7.0, get_approximate_value_for_lat_lon([tile], -0.4, 0.01)) |
| |
| def test_lat_exact_lon_approx(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertAlmostEqual(18.0, get_approximate_value_for_lat_lon([tile], 0.5, 1.01)) |
| |
| def test_lat_greater_than_bounds(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertTrue(np.isnan(get_approximate_value_for_lat_lon([tile], 2.0, 0))) |
| |
| def test_lat_less_than_bounds(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertTrue(np.isnan(get_approximate_value_for_lat_lon([tile], -2.0, 0))) |
| |
| def test_lon_greater_than_bounds(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertTrue(np.isnan(get_approximate_value_for_lat_lon([tile], 0, 3))) |
| |
| def test_lon_less_than_bounds(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertTrue(np.isnan(get_approximate_value_for_lat_lon([tile], 0, -3))) |
| |
| def test_repeated_lats(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, -0.5, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # -0.5 [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| self.assertAlmostEqual(6.0, get_approximate_value_for_lat_lon([tile], -0.4, -1)) |
| |
| def test_multiple_tiles(self): |
| tile1 = Tile() |
| tile1.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile1.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile1.times = np.ma.array([0L]) |
| tile1.data = np.ma.arange(12).reshape((1, 4, 3)) |
| |
| tile2 = Tile() |
| tile2.latitudes = np.ma.array([4.0, 5.0, 6.0, 7.0]) |
| tile2.longitudes = np.ma.array([-3.0, -4.0, -5.0]) |
| tile2.times = np.ma.array([0L]) |
| tile2.data = np.ma.arange(12, 24).reshape((1, 4, 3)) |
| |
| self.assertAlmostEqual(1, get_approximate_value_for_lat_lon([tile1, tile2], 0.4, -1)) |
| |
| def test_multiple_tiles_same_long(self): |
| tile1 = Tile() |
| tile1.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile1.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile1.times = np.ma.array([0L]) |
| tile1.data = np.ma.arange(12).reshape((1, 4, 3)) |
| |
| tile2 = Tile() |
| tile2.latitudes = np.ma.array([4.0, 5.0, 6.0, 7.0]) |
| tile2.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile2.times = np.ma.array([0L]) |
| tile2.data = np.ma.arange(12, 24).reshape((1, 4, 3)) |
| |
| self.assertAlmostEqual(1, get_approximate_value_for_lat_lon([tile1, tile2], 0.4, -1)) |
| |
| |
| class TestTileContainsMethod(unittest.TestCase): |
| def test_masked_tile(self): |
| tile = Tile() |
| tile.bbox = BBox(30.5, 37.5, -51.5, -36.5) |
| tile.latitudes = np.ma.arange(30.5, 38.5, 1.0) |
| tile.longitudes = np.ma.arange(-51.5, -35.5, 1.0) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(128.0).reshape((1, 8, 16)) |
| |
| # tile.latitudes [ 30.5 31.5 32.5 33.5 34.5 35.5 36.5 37.5] |
| tile.latitudes = np.ma.masked_outside(tile.latitudes, 35, 45) |
| # tile.latitudes [-- -- -- -- -- 35.5 36.5 37.5] |
| |
| # tile.longitudes [-51.5 -50.5 -49.5 -48.5 -47.5 -46.5 -45.5 -44.5 -43.5 -42.5 -41.5 -40.5 -39.5 -38.5 -37.5 -36.5] |
| tile.longitudes = np.ma.masked_outside(tile.longitudes, -50, -40) |
| # tile.longitudes [-- -- -49.5 -48.5 -47.5 -46.5 -45.5 -44.5 -43.5 -42.5 -41.5 -40.5 -- -- -- --] |
| |
| # Tile no longer contains 35, -50 |
| self.assertFalse(tile.contains_point(35, -50)) |
| |
| |
| class TestTileUpdateStats(unittest.TestCase): |
| def test_update_tile_stats(self): |
| tile = Tile() |
| tile.bbox = BBox(-1.0, 1.0, -2.0, 2.0) |
| tile.latitudes = np.ma.array([-1.0, -0.5, 0, .5, 1.0]) |
| tile.longitudes = np.ma.array([-2.0, -1.0, 0, 1.0, 2.0]) |
| tile.times = np.ma.array([0L]) |
| tile.data = np.ma.arange(25.0).reshape((1, 5, 5)) |
| |
| # -2 -1 0 1 2 |
| # -1.0 [[[0. 1. 2. 3. 4. ] |
| # -0.5 [5. 6. 7. 8. 9. ] |
| # 0. [10. 11. 12. 13. 14.] |
| # 0.5 [15. 16. 17. 18. 19.] |
| # 1.0 [20. 21. 22. 23. 24.]]] |
| |
| tile.update_stats() |
| |
| self.assertAlmostEqual(0.0, tile.tile_stats.min) |
| self.assertAlmostEqual(24.0, tile.tile_stats.max) |
| self.assertAlmostEqual(12.0, tile.tile_stats.mean) |
| self.assertEqual(25, tile.tile_stats.count) |
| |
| |
| class TestMergeTilesMethod(unittest.TestCase): |
| def test_merge_tiles(self): |
| tile1 = Tile() |
| tile1.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile1.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile1.times = np.ma.array([0L]) |
| tile1.data = np.ma.arange(12).reshape((1, 4, 3)) |
| |
| tile2 = Tile() |
| tile2.latitudes = np.ma.array([4.0, 5.0, 6.0, 7.0]) |
| tile2.longitudes = np.ma.array([-3.0, -4.0, -5.0]) |
| tile2.times = np.ma.array([0L]) |
| tile2.data = np.ma.arange(12, 24).reshape((1, 4, 3)) |
| |
| from nexustiles.model.nexusmodel import merge_tiles |
| |
| times, lats, longs, data = merge_tiles([tile1, tile2]) |
| |
| self.assertTrue(np.ma.allequal(times, np.array([0L]))) |
| self.assertTrue(np.ma.allequal(lats, np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0]))) |
| self.assertTrue(np.ma.allequal(longs, np.array([-5.0, -4.0, -3.0, -2.0, -1.0, 0.0]))) |
| expected = np.ma.array([[[0, 0, 0, 2, 1, 0], |
| [0, 0, 0, 5, 4, 3], |
| [0, 0, 0, 8, 7, 6], |
| [0, 0, 0, 11, 10, 9], |
| [14, 13, 12, 0, 0, 0], |
| [17, 16, 15, 0, 0, 0], |
| [20, 19, 18, 0, 0, 0], |
| [23, 22, 21, 0, 0, 0]]], mask=np.array([[[True, True, True, False, False, False], |
| [True, True, True, False, False, False], |
| [True, True, True, False, False, False], |
| [True, True, True, False, False, False], |
| [False, False, False, True, True, True], |
| [False, False, False, True, True, True], |
| [False, False, False, True, True, True], |
| [False, False, False, True, True, True]]])) |
| self.assertTrue(np.ma.allequal(np.ma.getmaskarray(data), np.ma.getmaskarray(expected))) |
| self.assertTrue(np.ma.allequal(data, expected)) |
| |
| def test_merge_tiles_vertical(self): |
| tile1 = Tile() |
| tile1.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile1.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile1.times = np.ma.array([0L]) |
| tile1.data = np.ma.arange(12).reshape((1, 4, 3)) |
| |
| tile2 = Tile() |
| tile2.latitudes = np.ma.array([4.0, 5.0, 6.0, 7.0]) |
| tile2.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile2.times = np.ma.array([0L]) |
| tile2.data = np.ma.arange(12, 24).reshape((1, 4, 3)) |
| |
| from nexustiles.model.nexusmodel import merge_tiles |
| |
| times, lats, longs, data = merge_tiles([tile1, tile2]) |
| |
| self.assertTrue(np.ma.allequal(times, np.array([0L]))) |
| self.assertTrue(np.ma.allequal(lats, np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0]))) |
| self.assertTrue(np.ma.allequal(longs, np.array([-2.0, -1.0, 0.0]))) |
| expected = np.ma.array([[[2, 1, 0], |
| [5, 4, 3], |
| [8, 7, 6], |
| [11, 10, 9], |
| [14, 13, 12], |
| [17, 16, 15], |
| [20, 19, 18], |
| [23, 22, 21]]], mask=False) |
| self.assertTrue(np.ma.allequal(np.ma.getmaskarray(data), np.ma.getmaskarray(expected))) |
| self.assertTrue(np.ma.allequal(data, expected)) |
| |
| def test_merge_tiles_horizontal(self): |
| tile1 = Tile() |
| tile1.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile1.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile1.times = np.ma.array([0L]) |
| tile1.data = np.ma.arange(12).reshape((1, 4, 3)) |
| |
| tile2 = Tile() |
| tile2.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile2.longitudes = np.ma.array([-3.0, -4.0, -5.0]) |
| tile2.times = np.ma.array([0L]) |
| tile2.data = np.ma.arange(12, 24).reshape((1, 4, 3)) |
| |
| from nexustiles.model.nexusmodel import merge_tiles |
| |
| times, lats, longs, data = merge_tiles([tile1, tile2]) |
| |
| self.assertTrue(np.ma.allequal(times, np.array([0L]))) |
| self.assertTrue(np.ma.allequal(lats, np.array([0.0, 1.0, 2.0, 3.0]))) |
| self.assertTrue(np.ma.allequal(longs, np.array([-5.0, -4.0, -3.0, -2.0, -1.0, 0.0]))) |
| expected = np.ma.array([[[14, 13, 12, 2, 1, 0], |
| [17, 16, 15, 5, 4, 3], |
| [20, 19, 18, 8, 7, 6], |
| [23, 22, 21, 11, 10, 9]]], mask=False) |
| self.assertTrue(np.ma.allequal(np.ma.getmaskarray(data), np.ma.getmaskarray(expected))) |
| self.assertTrue(np.ma.allequal(data, expected)) |
| |
| def test_merge_tiles_overlapping(self): |
| tile1 = Tile() |
| tile1.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile1.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile1.times = np.ma.array([0L]) |
| tile1.data = np.ma.arange(12).reshape((1, 4, 3)) |
| |
| tile2 = Tile() |
| tile2.latitudes = np.ma.array([0.0, 1.0, 2.0, 3.0]) |
| tile2.longitudes = np.ma.array([0.0, -1.0, -2.0]) |
| tile2.times = np.ma.array([0L]) |
| tile2.data = np.ma.arange(12, 24).reshape((1, 4, 3)) |
| |
| from nexustiles.model.nexusmodel import merge_tiles |
| |
| self.assertRaises(Exception, lambda _: merge_tiles([tile1, tile2])) |
