WIP Improve function docstrings

mapshader/core.py

@@ -525,7 +525,13 @@ def render_map(source: MapSource,  # noqa: C901
         Height of the output aggregate in pixels.
     width : int
         Width of the output aggregate in pixels.
+
+    Returns
+    -------
+    img : xarray.DataArray
+        A DataArray representing an image.
     """
+
     if x is not None and y is not None and z is not None:
         xmin, ymin, xmax, ymax = tile_def.get_tile_meters(x, y, z)
 
@@ -587,10 +593,12 @@ def tile_to_disk(img, output_location, z=0, x=0, y=0, tile_format='png'):
     ----------
     img: xarray.DataArray
         aggregation data array of the tile to write to image
-    x, y, z : float
-        The coordinates to be used to get the bounds inclusive space along the axis.
     output_location: str
         Path to write tile image
+    x, y, z : float
+        The coordinates to be used to get the bounds inclusive space along the axis.
+    tile_format: str
+        Format of output image
 
     Returns
     -------
@@ -616,18 +624,22 @@ def tile_to_disk(img, output_location, z=0, x=0, y=0, tile_format='png'):
 
 def tile_to_s3(img, output_location, z=0, x=0, y=0, tile_format='png'):
     """
+    Write a tile image to a S3 bucket
 
     Parameters
     ----------
-    img
-    output_location
-    z
-    x
-    y
-    tile_format
+    img: xarray.DataArray
+        aggregation data array of the tile to write to image
+    output_location: str
+        Path to write tile image
+    x, y, z : float
+        The coordinates to be used to get the bounds inclusive space along the axis.
+    tile_format: str
+        Format of output image
 
     Returns
     -------
+        None
 
     """
 
@@ -655,6 +667,25 @@ def tile_to_s3(img, output_location, z=0, x=0, y=0, tile_format='png'):
 
 
 def render_tile(source, output_location, z=0, x=0, y=0, tile_format='png'):
+    """
+    Create a tile from a source and save as an image to a output location.
+
+    Parameters
+    ----------
+    source: MapSource
+        MapSource object to define the map.
+    output_location: str
+        Path to write tile image. Can be a path to local disk or a S3 bucket.
+    x, y, z : float
+        The coordinates to be used to get the bounds inclusive space along the axis.
+    tile_format: str (default='png')
+        Format of output image
+
+    Returns
+    -------
+        None
+    """
+
     agg = render_map(source, x=int(x), y=int(y), z=int(z), height=256, width=256)
 
     if 0 in agg.shape:
@@ -692,6 +723,7 @@ def get_source_data(source: MapSource, simplify=None):
     gdf : GeoDataFrame or dict
         The Mapsource data
     """
+
     if isinstance(source.data, spd.GeoDataFrame):
         gdf = source.data.to_geopandas()
 

mapshader/io.py

@@ -14,12 +14,18 @@ def load_raster(file_path, transforms, force_recreate_overviews,
                 xmin=None, ymin=None, xmax=None, ymax=None, chunks=None,
                 layername='data'):
     """
-    Load raster data.
+    Load raster data from a path into a xarray DataArray. The input data can be in one of following
+    extensions: .tif, .nc, or .vrt. If a NetCDF file (.nc) is provided, a layer name must be
+    specified. Transforms can be applied while loading.
 
     Parameters
     ----------
     file_path : str
         Relative path to the file.
+    transforms: List
+        List of transforms to apply to the raster data.
+    force_recreate_overviews: bool
+        Whether to force recreate overview data.
     xmin : float
         X-axis minimum range.
     ymin : float
@@ -80,12 +86,20 @@ def load_vector(
     region_of_interest,
 ):
     """
-    Load vector data.
+    Load vector data from a file path to a geopandas or dask-geopandas DataFrame. If the data is
+    from a S3 bucket, storage options with access key ID and secret access key must be provided.
 
     Parameters
     ----------
     filepath : str
         Relative path to the file.
+    storage_options: Dict
+        Dictionary that contains user information including access key ID and secret access key
+    geometry: str
+        Geometry column in the data frame
+    region_of_interest: list-like object
+        Only select data that lies within, or intersects with this region.
+        The region is a list-like object with 4 values of minx, miny, maxx, maxy
 
     Returns
     -------