Extract lon_lat_to_easting_northing and easting_northing_to_lon_lat

as utility functions

holoviews/element/tiles.py

@@ -8,6 +8,7 @@
 from ..core import util
 from ..core.dimension import Dimension
 from ..core.element import Element2D
+from ..util.transform import lon_lat_to_easting_northing, easting_northing_to_lon_lat
 
 
 class Tiles(Element2D):
@@ -60,70 +61,21 @@ def lon_lat_to_easting_northing(longitude, latitude):
         Projects the given longitude, latitude values into Web Mercator
         (aka Pseudo-Mercator or EPSG:3857) coordinates.
 
-        Longitude and latitude can be provided as scalars, Pandas columns,
-        or Numpy arrays, and will be returned in the same form.  Lists
-        or tuples will be converted to Numpy arrays.
-
-        Args:
-            longitude
-            latitude
-
-        Returns:
-            (easting, northing)
-
-        Examples:
-           easting, northing = lon_lat_to_easting_northing(-74,40.71)
-
-           easting, northing = lon_lat_to_easting_northing(
-               np.array([-74]),np.array([40.71])
-           )
-
-           df=pandas.DataFrame(dict(longitude=np.array([-74]),latitude=np.array([40.71])))
-           df.loc[:, 'longitude'], df.loc[:, 'latitude'] = lon_lat_to_easting_northing(
-               df.longitude,df.latitude
-           )
+        See docstring for holoviews.util.transform.lon_lat_to_easting_northing
+        for more information
         """
-        if isinstance(longitude, (list, tuple)):
-            longitude = np.array(longitude)
-        if isinstance(latitude, (list, tuple)):
-            latitude = np.array(latitude)
-
-        origin_shift = np.pi * 6378137
-        easting = longitude * origin_shift / 180.0
-        with np.errstate(divide='ignore', invalid='ignore'):
-            northing = np.log(
-                np.tan((90 + latitude) * np.pi / 360.0)
-            ) * origin_shift / np.pi
-        return easting, northing
+        return lon_lat_to_easting_northing(longitude, latitude)
 
     @staticmethod
     def easting_northing_to_lon_lat(easting, northing):
         """
         Projects the given easting, northing values into
         longitude, latitude coordinates.
 
-        easting and northing values are assumed to be in Web Mercator
-        (aka Pseudo-Mercator or EPSG:3857) coordinates.
-
-        Args:
-            easting
-            northing
-
-        Returns:
-            (longitude, latitude)
+        See docstring for holoviews.util.transform.easting_northing_to_lon_lat
+        for more information
         """
-        if isinstance(easting, (list, tuple)):
-            easting = np.array(easting)
-        if isinstance(northing, (list, tuple)):
-            northing = np.array(northing)
-
-        origin_shift = np.pi * 6378137
-        longitude = easting * 180.0 / origin_shift
-        with np.errstate(divide='ignore'):
-            latitude = np.arctan(
-                np.exp(northing * np.pi / origin_shift)
-            ) * 360.0 / np.pi - 90
-        return longitude, latitude
+        return easting_northing_to_lon_lat(easting, northing)
 
 
 # Mapping between patterns to match specified as tuples and tuples containing attributions

holoviews/util/transform.py

@@ -859,3 +859,74 @@ def _coerce(self, dataset):
         if self.interface_applies(dataset, coerce=False):
             return dataset
         return dataset.clone(datatype=['xarray'])
+
+
+def lon_lat_to_easting_northing(longitude, latitude):
+    """
+    Projects the given longitude, latitude values into Web Mercator
+    (aka Pseudo-Mercator or EPSG:3857) coordinates.
+
+    Longitude and latitude can be provided as scalars, Pandas columns,
+    or Numpy arrays, and will be returned in the same form.  Lists
+    or tuples will be converted to Numpy arrays.
+
+    Args:
+        longitude
+        latitude
+
+    Returns:
+        (easting, northing)
+
+    Examples:
+       easting, northing = lon_lat_to_easting_northing(-74,40.71)
+
+       easting, northing = lon_lat_to_easting_northing(
+           np.array([-74]),np.array([40.71])
+       )
+
+       df=pandas.DataFrame(dict(longitude=np.array([-74]),latitude=np.array([40.71])))
+       df.loc[:, 'longitude'], df.loc[:, 'latitude'] = lon_lat_to_easting_northing(
+           df.longitude,df.latitude
+       )
+    """
+    if isinstance(longitude, (list, tuple)):
+        longitude = np.array(longitude)
+    if isinstance(latitude, (list, tuple)):
+        latitude = np.array(latitude)
+
+    origin_shift = np.pi * 6378137
+    easting = longitude * origin_shift / 180.0
+    with np.errstate(divide='ignore', invalid='ignore'):
+        northing = np.log(
+            np.tan((90 + latitude) * np.pi / 360.0)
+        ) * origin_shift / np.pi
+    return easting, northing
+
+
+def easting_northing_to_lon_lat(easting, northing):
+    """
+    Projects the given easting, northing values into
+    longitude, latitude coordinates.
+
+    easting and northing values are assumed to be in Web Mercator
+    (aka Pseudo-Mercator or EPSG:3857) coordinates.
+
+    Args:
+        easting
+        northing
+
+    Returns:
+        (longitude, latitude)
+    """
+    if isinstance(easting, (list, tuple)):
+        easting = np.array(easting)
+    if isinstance(northing, (list, tuple)):
+        northing = np.array(northing)
+
+    origin_shift = np.pi * 6378137
+    longitude = easting * 180.0 / origin_shift
+    with np.errstate(divide='ignore'):
+        latitude = np.arctan(
+            np.exp(northing * np.pi / origin_shift)
+        ) * 360.0 / np.pi - 90
+    return longitude, latitude