Merge remote-tracking branch 'upstream/master' into new_labelling

Conflicts:
	lib/cartopy/tests/mpl/test_ticker.py

.appveyor.yml

@@ -5,7 +5,7 @@ environment:
           PACKAGES: "cython numpy matplotlib-base proj4 pykdtree scipy"
         - PYTHON_VERSION: "2.7"
           CONDA_INSTALL_LOCN: "C:\\Miniconda-x64"
-          PACKAGES: "cython=0.17 numpy=1.10.0 matplotlib=1.5.1 nose proj4=4.9.1 scipy=0.16.0 mock msinttypes futures"
+          PACKAGES: "cython=0.28 numpy=1.10.0 matplotlib=1.5.1 nose proj4=4.9.1 scipy=0.16.0 mock msinttypes futures"
 
 install:
   # Install miniconda

.coveragerc

@@ -0,0 +1,19 @@
+#
+# .coveragerc to control coverage.py
+#
+
+[run]
+branch = True
+omit = 
+    lib/cartopy/examples/*
+    lib/cartopy/sphinxext/*
+    lib/cartopy/tests/*
+    lib/cartopy/_version.py
+    *.pxd
+plugins = Cython.Coverage
+
+[report]
+exclude_lines =
+    pragma: no cover
+    def __repr__
+    if __name__ == .__main__.:

.travis.yml

@@ -5,9 +5,9 @@ env:
         # These ancient versions are linked to an old libgfortran, but that version
         # isn't pinned in the package metadata
         - PYTHON_VERSION=2.7
-          PACKAGES="cython=0.17 numpy=1.10.0 matplotlib=1.5.1 nose proj4=4.9.1 scipy=0.16.0 libgfortran=1 mock futures"
+          PACKAGES="cython=0.28 numpy=1.10.0 matplotlib=1.5.1 nose proj4=4.9.1 scipy=0.16.0 libgfortran=1 mock futures"
         - PYTHON_VERSION=3.5
-          PACKAGES="cython=0.23.1 numpy=1.10.0 matplotlib=1.5.1 nose proj4=4.9.1 scipy=0.16.0 libgfortran=1"
+          PACKAGES="cython=0.28 numpy=1.10.0 matplotlib=1.5.1 nose proj4=4.9.1 scipy=0.16.0 libgfortran=1"
           PYTHONHASHSEED=0  # So pytest-xdist works.
         - NAME="Latest everything."
           PYTHON_VERSION=3.6
@@ -47,6 +47,10 @@ install:
   # Customise the testing environment
   # ---------------------------------
   - PACKAGES="$PACKAGES pillow pytest pytest-xdist filelock pep8 pyshp shapely six requests pyepsg owslib"
+  - if [[ "$NAME" == "Latest everything"* ]]; then
+        PACKAGES="$PACKAGES pytest-cov coveralls";
+        export CYTHON_COVERAGE=1;
+    fi
   - conda install --quiet $PACKAGES
 
   # Conda debug
@@ -69,11 +73,17 @@ script:
   - python $TRAVIS_BUILD_DIR/tools/feature_download.py gshhs physical --dry-run
 
   - if [[ "$NAME" == "Latest everything"* ]]; then
-      CARTOPY_GIT_DIR=$TRAVIS_BUILD_DIR pytest -n 4 --doctest-modules --pyargs cartopy;
+      CARTOPY_GIT_DIR=$TRAVIS_BUILD_DIR pytest -n 4 --doctest-modules --pyargs cartopy --cov=cartopy -ra;
     else
       CARTOPY_GIT_DIR=$TRAVIS_BUILD_DIR pytest -n 4 --pyargs cartopy;
     fi
 
+
+after_success:
+  - if [[ "$NAME" == "Latest everything"* ]]; then
+      coveralls;
+    fi
+
 after_failure:
   - source activate $ENV_NAME
   - python -c "from __future__ import print_function; import cartopy.tests.mpl; print(cartopy.tests.mpl.failed_images_html())"

INSTALL

@@ -56,7 +56,7 @@ The recipes for these can be found at https://github.com/conda-forge/feedstocks.
 **Python** 2.7 or later (https://www.python.org/)
     Cartopy requires Python 2.7 or later.
 
-**Cython** 0.17 or later (https://pypi.python.org/pypi/Cython/)
+**Cython** 0.28 or later (https://pypi.python.org/pypi/Cython/)
 
 **NumPy** 1.10 or later (http://www.numpy.org/)
     Python package for scientific computing including a powerful N-dimensional

MANIFEST.in

@@ -3,11 +3,10 @@ include CHANGES
 include COPYING*
 include INSTALL
 include README.rst
-include pyproject.toml
 include requirements/*.txt
 include lib/cartopy/data/*
 include lib/cartopy/io/srtm.npz
 include lib/cartopy/tests/lakes_shapefile/*
 recursive-include lib *.py
-recursive-include lib *.pyx *.pxd *.h
+recursive-include lib *.pyx *.pxd *.h *.c *.cpp
 include versioneer.py

README.md

@@ -82,12 +82,21 @@ Documentation can be found at <http://scitools.org.uk/cartopy/docs/latest/>.
 - To chat with developers and other users you can use the
   [Gitter Chat](https://gitter.im/SciTools/cartopy)
 
-## License and copyright
 
-Cartopy is licensed under GNU Lesser General Public License (LGPLv3).
+## Credits, copyright and license
 
-Development occurs on GitHub at <https://github.com/SciTools/cartopy>, with a
-contributor's license agreement (CLA) that can be found at
-<http://scitools.org.uk/governance.html>.
+Cartopy is developed collaboratively under the SciTools umberella.
 
-(C) British Crown Copyright, Met Office
+A full list of codecontributors ("Cartopy contributors") can be found at
+https://github.com/SciTools/cartopy/graphs/contributors.
+
+Code is just one of many ways of positively contributing to Cartopy, please see
+our [contributing guide](.github/CONTRIBUTING.md) for more details on how
+you can get involved.
+
+Cartopy is released under a LGPL license with a shared copyright model.
+See [LICENSE](LICENSE) for full terms.
+
+The [Met Office](https://metoffice.gov.uk) has made a significant
+contribution to the development, maintenance and support of this library.
+All Met Office contributions are copyright on behalf of the British Crown.

lib/cartopy/__init__.py

@@ -1,19 +1,7 @@
-# (C) British Crown Copyright 2011 - 2018, Met Office
+# Copyright Cartopy Contributors
 #
-# This file is part of cartopy.
-#
-# cartopy 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.
-#
-# cartopy 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 cartopy.  If not, see <https://www.gnu.org/licenses/>.
+# This file is part of Cartopy and is released under the LGPL license.
+# See LICENSE in the root of the repository for full licensing details.
 
 from __future__ import (absolute_import, division, print_function)
 

lib/cartopy/crs.py

@@ -1,4 +1,4 @@
-# (C) British Crown Copyright 2011 - 2018, Met Office
+# (C) British Crown Copyright 2011 - 2019, Met Office
 #
 # This file is part of cartopy.
 #
@@ -1177,7 +1177,7 @@ def __init__(self, central_longitude=-96.0, central_latitude=39.0,
         self.cutoff = cutoff
         n = 91
         lons = np.empty(n + 2)
-        lats = np.full(n + 2, cutoff)
+        lats = np.full(n + 2, float(cutoff))
         lons[0] = lons[-1] = 0
         lats[0] = lats[-1] = plat
         if plat == 90:

lib/cartopy/examples/contour_labels.py

@@ -0,0 +1,54 @@
+"""
+Contour labels
+--------------
+
+An example of adding contour labels to matplotlib contours.
+
+"""
+__tags__ = ['Scalar data']
+
+import cartopy.crs as ccrs
+import matplotlib.pyplot as plt
+
+from cartopy.examples.waves import sample_data
+
+
+def main():
+    # Setup a global EckertIII map with faint coastlines.
+    ax = plt.axes(projection=ccrs.EckertIII())
+    ax.set_global()
+    ax.coastlines('110m', alpha=0.1)
+
+    # Use the waves example to provide some sample data, but make it
+    # more dependent on y for more interesting contours.
+    x, y, z = sample_data((20, 40))
+    z = z * -1.5 * y
+
+    # Add colourful filled contours.
+    filled_c = ax.contourf(x, y, z, transform=ccrs.PlateCarree())
+
+    # And black line contours.
+    line_c = ax.contour(x, y, z, levels=filled_c.levels,
+                        colors=['black'],
+                        transform=ccrs.PlateCarree())
+
+    # Uncomment to make the line contours invisible.
+    # plt.setp(line_c.collections, visible=False)
+
+    # Add a colorbar for the filled contour.
+    plt.colorbar(filled_c, orientation='horizontal')
+
+    # Use the line contours to place contour labels.
+    plt.clabel(
+        line_c,  # Typically best results when labelling line contours.
+        colors=['black'],
+        manual=False,  # Automatic placement vs manual placement.
+        inline=True,  # Cut the line where the label will be placed.
+        fmt=' {:.0f} '.format,  # Labes as integers, with some extra space.
+    )
+
+    plt.show()
+
+
+if __name__ == '__main__':
+    main()

lib/cartopy/mpl/contour.py

@@ -0,0 +1,98 @@
+# (C) British Crown Copyright 2011 - 2019, Met Office
+#
+# This file is part of cartopy.
+#
+# cartopy 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.
+#
+# cartopy 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 cartopy.  If not, see <https://www.gnu.org/licenses/>.
+
+from __future__ import (absolute_import, division, print_function)
+
+from matplotlib.contour import QuadContourSet
+import matplotlib.path as mpath
+import numpy as np
+
+
+class GeoContourSet(QuadContourSet):
+    """
+    A contourset designed to handle things like contour labels.
+
+    """
+    # nb. No __init__ method here - most of the time a GeoContourSet will
+    # come from GeoAxes.contour[f]. These methods morph a ContourSet by
+    # fiddling with instance.__class__.
+
+    def clabel(self, *args, **kwargs):
+        # nb: contour labelling does not work very well for filled
+        # contours - it is recommended to only label line contours.
+        # This is especially true when inline=True.
+
+        # This wrapper exist because mpl does not properly transform
+        # paths. Instead it simply assumes one path represents one polygon
+        # (not necessarily the case), and it assumes that
+        # transform(path.verts) is equivalent to transform_path(path).
+        # Unfortunately there is no way to easily correct this error,
+        # so we are forced to pre-transform the ContourSet's paths from
+        # the source coordinate system to the axes' projection.
+        # The existing mpl code then has a much simpler job of handling
+        # pre-projected paths (which can now effectively be transformed
+        # naively).
+
+        for col in self.collections:
+            # Snaffle the collection's path list. We will change the
+            # list in-place (as the contour label code does in mpl).
+            paths = col.get_paths()
+
+            data_t = self.ax.transData
+            # Define the transform that will take us from collection
+            # coordinates through to axes projection coordinates.
+            col_to_data = col.get_transform() - data_t
+
+            # Now that we have the transform, project all of this
+            # collection's paths.
+            new_paths = [col_to_data.transform_path(path) for path in paths]
+            new_paths = [path for path in new_paths if path.vertices.size >= 1]
+
+            # The collection will now be referenced in axes projection
+            # coordinates.
+            col.set_transform(self.ax.transData)
+
+            # Clear the now incorrectly referenced paths.
+            del paths[:]
+
+            for path in new_paths:
+                if path.vertices.size == 0:
+                    # Don't persist empty paths. Let's get rid of them.
+                    continue
+
+                # Split the path if it has multiple MOVETO statements.
+                codes = np.array(
+                    path.codes if path.codes is not None else [0])
+                moveto = codes == mpath.Path.MOVETO
+                if moveto.sum() <= 1:
+                    # This is only one path, so add it to the collection.
+                    paths.append(path)
+                else:
+                    # The first MOVETO doesn't need cutting-out.
+                    moveto[0] = False
+                    split_locs = np.flatnonzero(moveto)
+
+                    split_verts = np.split(path.vertices, split_locs)
+                    split_codes = np.split(path.codes, split_locs)
+
+                    for verts, codes in zip(split_verts, split_codes):
+                        # Add this path to the collection's list of paths.
+                        paths.append(mpath.Path(verts, codes))
+
+        # Now that we have prepared the collection paths, call on
+        # through to the underlying implementation.
+        super(GeoContourSet, self).clabel(*args, **kwargs)

lib/cartopy/mpl/geoaxes.py

@@ -32,6 +32,7 @@
 import matplotlib as mpl
 import matplotlib.artist
 import matplotlib.axes
+import matplotlib.contour
 from matplotlib.image import imread
 import matplotlib.transforms as mtransforms
 import matplotlib.patches as mpatches
@@ -45,6 +46,7 @@
 import cartopy.crs as ccrs
 import cartopy.feature
 import cartopy.img_transform
+import cartopy.mpl.contour
 import cartopy.mpl.feature_artist as feature_artist
 import cartopy.mpl.patch as cpatch
 from cartopy.mpl.slippy_image_artist import SlippyImageArtist
@@ -1462,6 +1464,10 @@ def contour(self, *args, **kwargs):
         result = matplotlib.axes.Axes.contour(self, *args, **kwargs)
 
         self.autoscale_view()
+
+        # Re-cast the contour as a GeoContourSet.
+        if isinstance(result, matplotlib.contour.QuadContourSet):
+            result.__class__ = cartopy.mpl.contour.GeoContourSet
         return result
 
     def contourf(self, *args, **kwargs):
@@ -1502,6 +1508,11 @@ def contourf(self, *args, **kwargs):
         self.dataLim.update_from_data_xy(extent.get_points())
 
         self.autoscale_view()
+
+        # Re-cast the contour as a GeoContourSet.
+        if isinstance(result, matplotlib.contour.QuadContourSet):
+            result.__class__ = cartopy.mpl.contour.GeoContourSet
+
         return result
 
     def scatter(self, *args, **kwargs):

lib/cartopy/tests/crs/test_lambert_conformal.py

@@ -1,4 +1,4 @@
-# (C) British Crown Copyright 2011 - 2018, Met Office
+# (C) British Crown Copyright 2011 - 2019, Met Office
 #
 # This file is part of cartopy.
 #
@@ -72,11 +72,11 @@ def test_single_value(self):
         check_proj_params('lcc', crs, other_args)
 
     def test_no_parallel(self):
-        with pytest.raises(ValueError, message='1 or 2 standard parallels'):
+        with pytest.raises(ValueError, match='1 or 2 standard parallels'):
             ccrs.LambertConformal(standard_parallels=[])
 
     def test_too_many_parallel(self):
-        with pytest.raises(ValueError, message='1 or 2 standard parallels'):
+        with pytest.raises(ValueError, match='1 or 2 standard parallels'):
             ccrs.LambertConformal(standard_parallels=[1, 2, 3])
 
     def test_single_spole(self):