[Git][debian-gis-team/pyresample][upstream] New upstream version 1.8.1
Antonio Valentino
gitlab at salsa.debian.org
Sun Feb 25 12:06:50 UTC 2018
Antonio Valentino pushed to branch upstream at Debian GIS Project / pyresample
Commits:
b72681d2 by Antonio Valentino at 2018-02-25T10:08:11+00:00
New upstream version 1.8.1
- - - - -
10 changed files:
- .bumpversion.cfg
- README.md
- changelog.rst
- pyresample/data_reduce.py
- pyresample/geometry.py
- pyresample/kd_tree.py
- pyresample/test/__init__.py
- + pyresample/test/test_data_reduce.py
- pyresample/test/test_kd_tree.py
- pyresample/version.py
Changes:
=====================================
.bumpversion.cfg
=====================================
--- 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
=====================================
README.md
=====================================
--- 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
=====================================
changelog.rst
=====================================
--- 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]
=====================================
pyresample/data_reduce.py
=====================================
--- 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:
=====================================
pyresample/geometry.py
=====================================
--- 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`.
=====================================
pyresample/kd_tree.py
=====================================
--- 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,
=====================================
pyresample/test/__init__.py
=====================================
--- 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
=====================================
pyresample/test/test_data_reduce.py
=====================================
--- /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()
=====================================
pyresample/test/test_kd_tree.py
=====================================
--- 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()
=====================================
pyresample/version.py
=====================================
--- 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'
View it on GitLab: https://salsa.debian.org/debian-gis-team/pyresample/commit/b72681d2de72de3fba9edd4c7cbed9ba9e43709d
---
View it on GitLab: https://salsa.debian.org/debian-gis-team/pyresample/commit/b72681d2de72de3fba9edd4c7cbed9ba9e43709d
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