Merge pull request #1876 from greglucas/deps-scipy-mpl

MNT: Update imports for dependencies

INSTALL

@@ -79,6 +79,10 @@ Further information about the required dependencies can be found here:
 **Python** 3.7 or later (https://www.python.org/)
     Python 2 support was removed in v0.19.
 
+**Matplotlib** 3.1 or later (https://matplotlib.org/)
+    Python package for 2D plotting. Python package required for any
+    graphical capabilities.
+
 **GEOS** 3.7.2 or later (https://trac.osgeo.org/geos/)
     GEOS is an API of spatial predicates and functions for processing geometry
     written in C++.
@@ -102,10 +106,6 @@ Optional Dependencies
 To make the most of Cartopy by enabling additional functionality, you may want
 to install these optional dependencies.
 
-**Matplotlib** 3.1 or later (https://matplotlib.org/)
-    Python package for 2D plotting. Python package required for any
-    graphical capabilities.
-
 **GDAL** version 2.3.2 (https://gdal.org/)
     GDAL is a translator library for raster and vector geospatial data formats,
     which has powerful data transformation and processing capabilities.

lib/cartopy/img_transform.py

@@ -14,7 +14,11 @@
     import pykdtree.kdtree
     _is_pykdtree = True
 except ImportError:
-    import scipy.spatial
+    try:
+        import scipy.spatial
+    except ImportError as e:
+        raise ImportError("Using image transforms requires either "
+                          "pykdtree or scipy.") from e
     _is_pykdtree = False
 
 import cartopy.crs as ccrs

lib/cartopy/mpl/geoaxes.py

@@ -34,13 +34,11 @@
 from cartopy import config
 import cartopy.crs as ccrs
 import cartopy.feature
-import cartopy.img_transform
 import cartopy.mpl.contour
 import cartopy.mpl.geocollection
 import cartopy.mpl.feature_artist as feature_artist
 import cartopy.mpl.patch as cpatch
 from cartopy.mpl.slippy_image_artist import SlippyImageArtist
-from cartopy.vector_transform import vector_scalar_to_grid
 
 
 assert mpl.__version__ >= '3.1', \
@@ -1371,7 +1369,9 @@ def imshow(self, img, *args, **kwargs):
             regrid_shape = kwargs.pop('regrid_shape', 750)
             regrid_shape = self._regrid_shape_aspect(regrid_shape,
                                                      target_extent)
-            warp_array = cartopy.img_transform.warp_array
+            # Lazy import because scipy/pykdtree in img_transform are only
+            # optional dependencies
+            from cartopy.img_transform import warp_array
             original_extent = extent
             img, extent = warp_array(img,
                                      source_proj=transform,
@@ -2073,6 +2073,9 @@ def quiver(self, x, y, u, v, *args, **kwargs):
             # manually and plotting in native coordinates.
             regrid_shape = self._regrid_shape_aspect(regrid_shape,
                                                      target_extent)
+            # Lazy load vector_scalar_to_grid due to the optional
+            # scipy dependency
+            from cartopy.vector_transform import vector_scalar_to_grid
             if args:
                 # Interpolate color array as well as vector components.
                 x, y, u, v, c = vector_scalar_to_grid(
@@ -2145,6 +2148,9 @@ def barbs(self, x, y, u, v, *args, **kwargs):
             # manually and plotting in native coordinates.
             regrid_shape = self._regrid_shape_aspect(regrid_shape,
                                                      target_extent)
+            # Lazy load vector_scalar_to_grid due to the optional
+            # scipy dependency
+            from cartopy.vector_transform import vector_scalar_to_grid
             if args:
                 # Interpolate color array as well as vector components.
                 x, y, u, v, c = vector_scalar_to_grid(
@@ -2218,6 +2224,9 @@ def streamplot(self, x, y, u, v, **kwargs):
             scalars.append(lw)
         # Do the regridding including any scalar fields.
         target_extent = self.get_extent(self.projection)
+        # Lazy load vector_scalar_to_grid due to the optional
+        # scipy dependency
+        from cartopy.vector_transform import vector_scalar_to_grid
         gridded = vector_scalar_to_grid(t, self.projection, regrid_shape,
                                         x, y, u, v, *scalars,
                                         target_extent=target_extent)

lib/cartopy/vector_transform.py

@@ -10,7 +10,10 @@
 """
 
 import numpy as np
-from scipy.interpolate import griddata
+try:
+    from scipy.interpolate import griddata
+except ImportError as e:
+    raise ImportError("Regridding vectors requires scipy.") from e
 
 
 def _interpolate_to_grid(nx, ny, x, y, *scalars, **kwargs):

requirements/default.txt

@@ -1,4 +1,5 @@
 numpy>=1.18
+matplotlib>=3.1
 shapely>=1.6.4
 pyshp>=2.1
 pyproj>=3.0.0

requirements/plotting.txt

@@ -1,4 +1,3 @@
-matplotlib>=3.1
 GDAL>=2.3.2
 pillow>=6.1.0
 scipy>=1.3.1