Fix all unexecutable code examples I can find. (#693)

A few old issues that are tasked for `22.10` involve fixing documentation that is incorrect. I worked through the existing nightly docs and executed all of the code samples, fixing and improving anything that had incorrect outputs or inputs.

closes #460
closes #63

Authors:
  - H. Thomson Comer (https://github.com/thomcom)

Approvers:
  - Mark Harris (https://github.com/harrism)
  - Michael Wang (https://github.com/isVoid)

URL: #693

docs/source/api_docs/geopandas_compatibility.rst

@@ -3,8 +3,8 @@ GeoPandas Compatibility
 
 cuSpatial supports any geometry format supported by `GeoPandas`. Load geometry information from a `GeoPandas.GeoSeries` or `GeoPandas.GeoDataFrame`.
 
-    >>> gpdf = geopandas.read_file('arbitrary.txt')
-        cugpdf = cuspatial.from_geopandas(gpdf)
+    >>> host_dataframe = geopandas.read_file(geopandas.datasets.get_path("naturalearth_lowres"))
+        cugpdf = cuspatial.from_geopandas(host_dataframe)
 
 or
 

python/cuspatial/cuspatial/core/geodataframe.py

@@ -133,7 +133,8 @@ def _split_out_geometry_columns(self) -> Tuple:
         """
         columns_mask = pd.Series(self.columns)
         geocolumn_mask = pd.Series(
-            [isinstance(self[col], GeoSeries) for col in self.columns]
+            [isinstance(self[col], GeoSeries) for col in self.columns],
+            dtype="bool",
         )
         geo_columns = self[columns_mask[geocolumn_mask]]
         # Send the rest of the columns to `cudf` to slice.

python/cuspatial/cuspatial/core/geoseries.py

@@ -37,8 +37,11 @@ class GeoSeries(cudf.Series):
     stored in the `GeoArrowBuffers` object, accessible with the `points`,
     `multipoints`, `lines`, and `polygons` accessors.
 
-    >>> cuseries.points
-        xy:
+    >>> from shapely.geometry import Point
+        import geopandas
+        import cuspatial
+        cuseries = cuspatial.GeoSeries(geopandas.GeoSeries(Point(-1, 0)))
+        cuseries.points.xy
         0   -1.0
         1    0.0
         dtype: float64
@@ -422,8 +425,64 @@ def to_shapely(self):
             return results
 
     def to_arrow(self):
-        # Arrow can't view an empty list, so we need to prep the buffers
-        # here.
+        """
+        Convert to a GeoArrow Array.
+
+        Returns
+        -------
+        result: GeoArrow Union containing GeoArrow Arrays
+
+        Examples
+        --------
+        >>> from shapely.geometry import MultiLineString, LineString
+        >>> cugpdf = cuspatial.from_geopandas(geopandas.GeoSeries(
+            MultiLineString(
+                [
+                    [(1, 0), (0, 1)],
+                    [(0, 0), (1, 1)]
+                ]
+            )))
+        >>> cugpdf.to_arrow()
+        <pyarrow.lib.UnionArray object at 0x7f7061c0e0a0>
+        -- is_valid: all not null
+        -- type_ids:   [
+            2
+          ]
+        -- value_offsets:   [
+            0
+          ]
+        -- child 0 type: list<item: null>
+          []
+        -- child 1 type: list<item: null>
+          []
+        -- child 2 type: list<item: list<item: list<item: double>>>
+          [
+            [
+              [
+                [
+                  1,
+                  0
+                ],
+                [
+                  0,
+                  1
+                ]
+              ],
+              [
+                [
+                  0,
+                  0
+                ],
+                [
+                  1,
+                  1
+                ]
+              ]
+            ]
+          ]
+        -- child 3 type: list<item: null>
+          []
+        """
         points = self._column.points
         mpoints = self._column.mpoints
         lines = self._column.lines

python/cuspatial/cuspatial/core/spatial/distance.py

@@ -72,7 +72,7 @@ def directed_hausdorff_distance(xs, ys, space_offsets):
     >>> result = cuspatial.directed_hausdorff_distance(
             [0, 1, 0, 0], # xs
             [0, 0, 1, 2], # ys
-            [0, 2, 4],    # space_offsets
+            [0, 2],    # space_offsets
         )
     >>> print(result)
              0         1

python/cuspatial/cuspatial/core/trajectory.py

@@ -46,20 +46,20 @@ def derive_trajectories(object_ids, xs, ys, timestamps):
     Compute sorted objects and discovered trajectories
 
     >>> objects, traj_offsets = cuspatial.derive_trajectories(
-            [0, 1, 2, 3],  # object_id
+            [0, 1, 0, 1],  # object_id
             [0, 0, 1, 1],  # x
             [0, 0, 1, 1],  # y
-            [0, 10, 0, 10] # timestamp
+            [0, 10000, 0, 10000] # timestamp
         )
     >>> print(traj_offsets)
         0  0
         1  2
     >>> print(objects)
-           object_id       x       y  timestamp
-        0          0       1       0          0
-        1          0       0       0         10
-        2          1       3       1          0
-        3          1       2       1         10
+        object_id    x    y           timestamp
+        0          0  0.0  0.0 1970-01-01 00:00:00
+        1          0  1.0  1.0 1970-01-01 00:00:10
+        2          1  0.0  0.0 1970-01-01 00:00:00
+        3          1  1.0  1.0 1970-01-01 00:00:10
     """
 
     object_ids = as_column(object_ids, dtype=np.int32)
@@ -103,7 +103,7 @@ def trajectory_bounding_boxes(num_trajectories, object_ids, xs, ys):
     --------
     Compute the minimum bounding boxes of derived trajectories
 
-    >>> objects, traj_offsets = trajectory.derive_trajectories(
+    >>> objects, traj_offsets = cuspatial.derive_trajectories(
             [0, 0, 1, 1],  # object_id
             [0, 1, 2, 3],  # x
             [0, 0, 1, 1],  # y
@@ -168,10 +168,10 @@ def trajectory_distances_and_speeds(
             objects['timestamp']
         )
     >>> print(dists_and_speeds)
-                       distance          speed
+                          distance       speed
         trajectory_id
-        0                1000.0  100000.000000
-        1                1000.0  111111.109375
+        0              1414.213562  141.421356
+        1              1414.213562  141.421356
     """
 
     object_ids = as_column(object_ids, dtype=np.int32)