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commit b72681d2de72de3fba9edd4c7cbed9ba9e43709d Author: Antonio Valentino <[email protected]> Date: Sun Feb 25 10:08:11 2018 +0000 New upstream version 1.8.1 --- .bumpversion.cfg | 2 +- README.md | 2 +- changelog.rst | 35 ++++++++ pyresample/data_reduce.py | 8 +- pyresample/geometry.py | 15 +++- pyresample/kd_tree.py | 9 +- pyresample/test/__init__.py | 3 +- pyresample/test/test_data_reduce.py | 172 ++++++++++++++++++++++++++++++++++++ pyresample/test/test_kd_tree.py | 79 +---------------- pyresample/version.py | 2 +- 10 files changed, 235 insertions(+), 92 deletions(-) diff --git a/.bumpversion.cfg b/.bumpversion.cfg index e10021a..d50a490 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.8.0 +current_version = 1.8.1 commit = True tag = True diff --git a/README.md b/README.md index d1e5fed..5158019 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ Pyresample works with Numpy arrays including support for masked arrays. Support for parallel resampling using multiple processor cores. Plotting capablity using Basemap. As of v0.8.0 [pykdtree](https://github.com/storpipfugl/pykdtree) can be used to speed up processing. -Pyresample is tested with Python 2.6, 2.7, 3.2, 3.3, and 3.4. +Pyresample is tested with Python 2.7, 3.4, 3.5, and 3.6. Note: For numpy >= 1.6.2 use pyresample >= 0.7.13 diff --git a/changelog.rst b/changelog.rst index 4906438..a159ed6 100644 --- a/changelog.rst +++ b/changelog.rst @@ -2,6 +2,41 @@ Changelog ========= +v1.8.1 (2018-02-22) +------------------- +- update changelog. [Martin Raspaud] +- Bump version: 1.8.0 → 1.8.1. [Martin Raspaud] +- Merge pull request #101 from floriankrb/master. [Martin Raspaud] + + Update README to include correct versions of python tested +- Update README.md. [Florian] +- Update README.md. [Florian] +- Merge pull request #99 from pytroll/feature-dynamic-projs. [Martin + Raspaud] + + Add support for dynamic resampling for most projections +- Do not overwrite provided lon_0 and lat_0. [Martin Raspaud] +- Add support for dynamic resampling for most projections. [Martin + Raspaud] +- Merge pull request #98 from pytroll/bugfix-data-reduce. [Martin + Raspaud] + + Revert "Fix data reduction when poles are within area" +- Add test for data reduction over the poles. [Martin Raspaud] +- Make pep8 happy. [Martin Raspaud] +- Revert "Fix data reduction when poles are within area" [Martin + Raspaud] + + This reverts commit 1c9ac493aea549a354f384059e9aa6ad41558fd8. + +- Merge pull request #96 from pytroll/bugfix-partially-invalid-source- + data. [David Hoese] + + Fix xarray resampling for partially invalid source datasets +- Fix xarray resampling for partially invalid source datasets. [Martin + Raspaud] + + v1.8.0 (2018-02-02) ------------------- - update changelog. [Martin Raspaud] diff --git a/pyresample/data_reduce.py b/pyresample/data_reduce.py index 76e488a..3d25885 100644 --- a/pyresample/data_reduce.py +++ b/pyresample/data_reduce.py @@ -289,14 +289,14 @@ def _get_valid_index(lons_side1, lons_side2, lons_side3, lons_side4, # From the winding number theorem follows: # angle_sum possiblilities: - # 360: area covers north pole - #-360: area covers south pole + # -360: area covers north pole + # 360: area covers south pole # 0: area covers no poles # else: area covers both poles - if round(angle_sum) == 360: + if round(angle_sum) == -360: # Covers NP valid_index = (lats >= lat_min_buffered) - elif round(angle_sum) == -360: + elif round(angle_sum) == 360: # Covers SP valid_index = (lats <= lat_max_buffered) elif round(angle_sum) == 0: diff --git a/pyresample/geometry.py b/pyresample/geometry.py index 2e7f8be..8efa8f6 100644 --- a/pyresample/geometry.py +++ b/pyresample/geometry.py @@ -186,7 +186,8 @@ class BaseDefinition(object): side2 = self.get_lonlats(data_slice=(slice(None), -1)) side3 = self.get_lonlats(data_slice=(-1, slice(None))) side4 = self.get_lonlats(data_slice=(slice(None), 0)) - return Boundary(side1[0], side2[0], side3[0][::-1], side4[0][::-1]), Boundary(side1[1], side2[1], side3[1][::-1], side4[1][::-1]) + return (Boundary(side1[0], side2[0], side3[0][::-1], side4[0][::-1]), + Boundary(side1[1], side2[1], side3[1][::-1], side4[1][::-1])) def get_cartesian_coords(self, nprocs=None, data_slice=None, cache=False): """Retrieve cartesian coordinates of geometry definition @@ -528,6 +529,14 @@ class SwathDefinition(CoordinateDefinition): 'lat_0': float(lat0), 'lonc': float(lonc), 'no_rot': True, 'ellps': ellipsoid} + def _compute_generic_parameters(self, projection, ellipsoid): + """Compute the projection bb parameters for most projections.""" + lines, cols = self.lons.shape + lat_0 = self.lats[int(lines / 2), int(cols / 2)] + lon_0 = self.lons[int(lines / 2), int(cols / 2)] + return {'proj': projection, 'ellps': ellipsoid, + 'lat_0': lat_0, 'lon_0': lon_0} + def get_edge_lonlats(self): """Get the concatenated boundary of the current swath.""" lons, lats = self.get_boundary_lonlats() @@ -543,7 +552,9 @@ class SwathDefinition(CoordinateDefinition): if projection == 'omerc': return self._compute_omerc_parameters(ellipsoid) else: - raise NotImplementedError('Only omerc supported for now.') + new_proj = self._compute_generic_parameters(projection, ellipsoid) + new_proj.update(proj_dict) + return new_proj def compute_optimal_bb_area(self, proj_dict=None): """Compute the "best" bounding box area for this swath with `proj_dict`. diff --git a/pyresample/kd_tree.py b/pyresample/kd_tree.py index 8c89d79..fe27a53 100644 --- a/pyresample/kd_tree.py +++ b/pyresample/kd_tree.py @@ -1012,13 +1012,10 @@ class XArrayResamplerNN(object): # which is an invalid index, we mask those out so -1 represents # invalid values # voi is 2D, index_array is 1D - bad_mask = index_array >= resample_kdtree.n - voi[bad_mask.reshape(shape)] = False + good_pixels = index_array < resample_kdtree.n + voi[voi] = good_pixels res_ia = np.full(shape, fill_value=-1, dtype=np.int) - res_ia[voi] = index_array[~bad_mask] - # res_ia[voi >= resample_kdtree.n] = -1 - # res_ia[voi] = index_array - # res_ia[voi >= resample_kdtree.n] = -1 + res_ia[voi] = index_array[good_pixels] return res_ia res = da.map_blocks(query_no_distance, target_lons, target_lats, diff --git a/pyresample/test/__init__.py b/pyresample/test/__init__.py index baccb3c..364b132 100644 --- a/pyresample/test/__init__.py +++ b/pyresample/test/__init__.py @@ -36,6 +36,7 @@ from pyresample.test import ( test_ewa_ll2cr, test_ewa_fornav, test_bilinear, + test_data_reduce, ) import unittest @@ -57,7 +58,7 @@ def suite(): mysuite.addTests(test_ewa_ll2cr.suite()) mysuite.addTests(test_ewa_fornav.suite()) mysuite.addTests(test_bilinear.suite()) - + mysuite.addTests(test_data_reduce.suite()) return mysuite diff --git a/pyresample/test/test_data_reduce.py b/pyresample/test/test_data_reduce.py new file mode 100644 index 0000000..34be384 --- /dev/null +++ b/pyresample/test/test_data_reduce.py @@ -0,0 +1,172 @@ +# pyresample, Resampling of remote sensing image data in python +# +# Copyright (C) 2018 Pytroll Developers +# +# This program is free software: you can redistribute it and/or modify it under +# the terms of the GNU Lesser General Public License as published by the Free +# Software Foundation, either version 3 of the License, or (at your option) any +# later version. +# +# This program is distributed in the hope that it will be useful, but WITHOUT +# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more +# details. +# +# You should have received a copy of the GNU Lesser General Public License +# along with this program. If not, see <http://www.gnu.org/licenses/>. +"""Testing the data_reduce module.""" + +import unittest +import numpy as np +from pyresample import geometry +from pyresample.data_reduce import (get_valid_index_from_cartesian_grid, + swath_from_lonlat_grid, + swath_from_lonlat_boundaries, + swath_from_cartesian_grid, + get_valid_index_from_lonlat_grid) + + +class Test(unittest.TestCase): + """Unit testing the data_reduce module.""" + + @classmethod + def setUpClass(cls): + """Get ready for testing.""" + cls.area_def = geometry.AreaDefinition('areaD', + 'Europe (3km, HRV, VTC)', + 'areaD', + {'a': '6378144.0', + 'b': '6356759.0', + 'lat_0': '50.00', + 'lat_ts': '50.00', + 'lon_0': '8.00', + 'proj': 'stere'}, + 800, + 800, + [-1370912.72, + -909968.64000000001, + 1029087.28, + 1490031.3600000001]) + + def test_reduce(self): + data = np.fromfunction(lambda y, x: (y + x), (1000, 1000)) + lons = np.fromfunction( + lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) + lats = np.fromfunction( + lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) + grid_lons, grid_lats = self.area_def.get_lonlats() + lons, lats, data = swath_from_lonlat_grid(grid_lons, grid_lats, + lons, lats, data, + 7000) + cross_sum = data.sum() + expected = 20514375.0 + self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') + + def test_reduce_boundary(self): + data = np.fromfunction(lambda y, x: (y + x), (1000, 1000)) + lons = np.fromfunction( + lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) + lats = np.fromfunction( + lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) + boundary_lonlats = self.area_def.get_boundary_lonlats() + lons, lats, data = swath_from_lonlat_boundaries(boundary_lonlats[0], + boundary_lonlats[1], + lons, lats, data, 7000) + cross_sum = data.sum() + expected = 20514375.0 + self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') + + def test_cartesian_reduce(self): + data = np.fromfunction(lambda y, x: (y + x), (1000, 1000)) + lons = np.fromfunction( + lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) + lats = np.fromfunction( + lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) + grid = self.area_def.get_cartesian_coords() + lons, lats, data = swath_from_cartesian_grid(grid, lons, lats, data, + 7000) + cross_sum = data.sum() + expected = 20514375.0 + self.assertAlmostEqual( + cross_sum, expected, msg='Cartesian reduce data failed') + + def test_area_con_reduce(self): + data = np.fromfunction(lambda y, x: (y + x), (1000, 1000)) + lons = np.fromfunction( + lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) + lats = np.fromfunction( + lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) + grid_lons, grid_lats = self.area_def.get_lonlats() + valid_index = get_valid_index_from_lonlat_grid(grid_lons, grid_lats, + lons, lats, 7000) + data = data[valid_index] + cross_sum = data.sum() + expected = 20514375.0 + self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') + + def test_area_con_cartesian_reduce(self): + data = np.fromfunction(lambda y, x: (y + x), (1000, 1000)) + lons = np.fromfunction( + lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) + lats = np.fromfunction( + lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) + cart_grid = self.area_def.get_cartesian_coords() + valid_index = get_valid_index_from_cartesian_grid(cart_grid, + lons, lats, 7000) + data = data[valid_index] + cross_sum = data.sum() + expected = 20514375.0 + self.assertAlmostEqual( + cross_sum, expected, msg='Cartesian reduce data failed') + + def test_reduce_north_pole(self): + """Test reducing around the poles.""" + + from pyresample import utils + area_id = 'ease_sh' + description = 'Antarctic EASE grid' + proj_id = 'ease_sh' + projection = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' + x_size = 425 + y_size = 425 + area_extent = (-5326849.0625, -5326849.0625, + 5326849.0625, 5326849.0625) + area_def = utils.get_area_def(area_id, description, proj_id, + projection, x_size, y_size, area_extent) + + grid_lons, grid_lats = area_def.get_lonlats() + + area_id = 'ease_sh' + description = 'Antarctic EASE grid' + proj_id = 'ease_sh' + projection = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' + x_size = 1000 + y_size = 1000 + area_extent = (-532684.0625, -532684.0625, 532684.0625, 532684.0625) + smaller_area_def = utils.get_area_def(area_id, description, proj_id, + projection, x_size, y_size, + area_extent) + + data = np.fromfunction(lambda y, x: (y + x), (1000, 1000)) + lons, lats = smaller_area_def.get_lonlats() + + lons, lats, data = swath_from_lonlat_grid(grid_lons, grid_lats, + lons, lats, data, 7000) + + cross_sum = data.sum() + expected = 999000000.0 + self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') + + +def suite(): + """The test suite. + """ + loader = unittest.TestLoader() + mysuite = unittest.TestSuite() + mysuite.addTest(loader.loadTestsFromTestCase(Test)) + + return mysuite + + +if __name__ == '__main__': + unittest.main() diff --git a/pyresample/test/test_kd_tree.py b/pyresample/test/test_kd_tree.py index d1cadd2..755be24 100644 --- a/pyresample/test/test_kd_tree.py +++ b/pyresample/test/test_kd_tree.py @@ -5,7 +5,7 @@ import sys import numpy -from pyresample import data_reduce, geometry, kd_tree, utils +from pyresample import geometry, kd_tree, utils from pyresample.test.utils import catch_warnings if sys.version_info < (2, 7): @@ -135,7 +135,7 @@ class Test(unittest.TestCase): mask = numpy.ones_like(lons, dtype=numpy.bool) mask[::2, ::2] = False swath_def = geometry.SwathDefinition( - lons=numpy.ma.masked_array(lons, mask=mask), # numpy.ones_like(lons, dtype=numpy.bool)), + lons=numpy.ma.masked_array(lons, mask=mask), lats=numpy.ma.masked_array(lats, mask=False) ) res = kd_tree.resample_nearest(swath_def, data.ravel(), @@ -501,80 +501,6 @@ class Test(unittest.TestCase): self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel custom resampling failed') - def test_reduce(self): - data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) - lons = numpy.fromfunction( - lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) - lats = numpy.fromfunction( - lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) - grid_lons, grid_lats = self.area_def.get_lonlats() - lons, lats, data = data_reduce.swath_from_lonlat_grid(grid_lons, grid_lats, - lons, lats, data, - 7000) - cross_sum = data.sum() - expected = 20514375.0 - self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') - - def test_reduce_boundary(self): - data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) - lons = numpy.fromfunction( - lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) - lats = numpy.fromfunction( - lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) - boundary_lonlats = self.area_def.get_boundary_lonlats() - lons, lats, data = data_reduce.swath_from_lonlat_boundaries(boundary_lonlats[0], - boundary_lonlats[ - 1], - lons, lats, data, - 7000) - cross_sum = data.sum() - expected = 20514375.0 - self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') - - def test_cartesian_reduce(self): - data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) - lons = numpy.fromfunction( - lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) - lats = numpy.fromfunction( - lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) - #grid = utils.generate_cartesian_grid(self.area_def) - grid = self.area_def.get_cartesian_coords() - lons, lats, data = data_reduce.swath_from_cartesian_grid(grid, lons, lats, data, - 7000) - cross_sum = data.sum() - expected = 20514375.0 - self.assertAlmostEqual( - cross_sum, expected, msg='Cartesian reduce data failed') - - def test_area_con_reduce(self): - data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) - lons = numpy.fromfunction( - lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) - lats = numpy.fromfunction( - lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) - grid_lons, grid_lats = self.area_def.get_lonlats() - valid_index = data_reduce.get_valid_index_from_lonlat_grid(grid_lons, grid_lats, - lons, lats, 7000) - data = data[valid_index] - cross_sum = data.sum() - expected = 20514375.0 - self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') - - def test_area_con_cartesian_reduce(self): - data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) - lons = numpy.fromfunction( - lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) - lats = numpy.fromfunction( - lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) - cart_grid = self.area_def.get_cartesian_coords() - valid_index = data_reduce.get_valid_index_from_cartesian_grid(cart_grid, - lons, lats, 7000) - data = data[valid_index] - cross_sum = data.sum() - expected = 20514375.0 - self.assertAlmostEqual( - cross_sum, expected, msg='Cartesian reduce data failed') - def test_masked_nearest(self): data = numpy.ones((50, 10)) data[:, 5:] = 2 @@ -849,5 +775,6 @@ def suite(): return mysuite + if __name__ == '__main__': unittest.main() diff --git a/pyresample/version.py b/pyresample/version.py index a77942a..052f1f5 100644 --- a/pyresample/version.py +++ b/pyresample/version.py @@ -15,4 +15,4 @@ # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see <http://www.gnu.org/licenses/>. -__version__ = '1.8.0' +__version__ = '1.8.1' -- Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/pkg-grass/pyresample.git _______________________________________________ Pkg-grass-devel mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-grass-devel
