fix index error if input gdf has own index [issue #8]

`xa.get_pixel_overlaps()` creates a `poly_idx` column in the `gdf` that takes as its value the index of the input `gdf`. However, if there is a pre-existing index, this can lead to bad behavior, since `poly_idx` is used as an `.iloc` indexer in the `gdf`. This update instead makes `poly_idx` `np.arange(0,len(gdf))`, which will avoid this indexing issue (and hopefully not cause any more? I figured there would've been a reason I used the existing index if not a new one... fingers crossed).

tests/test_core.py

@@ -303,6 +303,28 @@ def test_get_pixel_overlaps_passthru_weights(pix_agg=pix_agg):
 
 # Should probably test multiple polygons just to be sure... 
 
+
+###### get_pixel_overlaps() and aggregate() coupling tests #####
+def test_get_pixel_overlaps_gdf_wpreexisting_index(pix_agg=pix_agg):
+	# Test to make sure it works with pre-existing indices in the gdf
+	# Create polygon covering multiple pixels
+	gdf_test = {'name':['test'],
+				'geometry':[Polygon([(0,0),(0,1),(1,1),(1,0),(0,0)])]}
+	gdf_test = gpd.GeoDataFrame(gdf_test,crs="EPSG:4326",index=np.arange(10,11))
+
+	# Get pixel overlaps
+	wm_out = get_pixel_overlaps(gdf_test,pix_agg)
+
+	# The index error for an incorrectly-indexed gdf is thrown in aggregate()
+	agg = aggregate(ds,wm_out)
+
+	# this assert uses 2.1666 because of the weighting that creates 
+	# the pix_agg variable that this whole section has used. Doesn't really 
+	# matter, since this is testing an index error that would've 
+	# happened during aggregate() above. 
+	assert np.allclose([v for v in agg.agg.test.values],2.1666,rtol=1e-4)
+
+
 ##### aggregate() tests #####
 
 

xagg/core.py

@@ -283,8 +283,9 @@ def get_pixel_overlaps(gdf_in,pix_agg):
 
 
     # Add an index for each polygon as a column to make indexing easier
-    if 'poly_idx' not in gdf_in.columns:
-        gdf_in['poly_idx'] = gdf_in.index.values
+    #if 'poly_idx' not in gdf_in.columns:
+    #    gdf_in['poly_idx'] = gdf_in.index.values
+    gdf_in['poly_idx'] = np.arange(0,len(gdf_in))
 
     # Match up CRSes
     pix_agg['gdf_pixels'] = pix_agg['gdf_pixels'].to_crs(gdf_in.crs)