# Testing GeoPandas and SpatialPandas import dask.dataframe as dd import datashader as ds from datashader.tests.test_pandas import assert_eq_ndarray import numpy as np from numpy import nan import pytest try: import dask_geopandas except ImportError: dask_geopandas = None try: import geodatasets except ImportError: geodatasets = None try: import geopandas except ImportError: geopandas = None try: # Import to register extension arrays import spatialpandas # noqa (register EAs) except ImportError: spatialpandas = None nybb_lines_sol = np.array([ [ 0., 0., 0., nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], # noqa: E501 [ 0., nan, 0., 0., 0., nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], # noqa: E501 [ 0., 0., nan, nan, 0., 0., nan, nan, nan, nan, nan, 1., 1., 1., nan, nan, nan, nan, nan, nan], # noqa: E501 [nan, 0., nan, nan, nan, 0., 0., 0., 2., 2., 2., 2., 2., 2., 1., 1., nan, nan, nan, nan], # noqa: E501 [nan, 0., 0., nan, nan, nan, 0., 0., 2., 2., 2., 2., 2., 2., 2., 1., 1., 1., 1., nan], # noqa: E501 [nan, 0., 0., nan, nan, nan, 0., 2., 2., nan, nan, 2., 2., 2., 2., 2., 1., 1., 1., nan], # noqa: E501 [nan, 0., 0., 0., 0., 0., 0., 2., nan, nan, nan, nan, 2., 2., 2., 2., 1., 1., 1., nan], # noqa: E501 [nan, nan, 0., 0., nan, 0., 0., 2., 2., 2., nan, nan, nan, 2., 2., 1., 1., nan, 1., 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, 3., 2., nan, nan, 2., 2., 2., nan, nan, nan, 1., 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, 3., 3., 3., 2., nan, 2., 2., 2., nan, nan, nan, nan, 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 3., 2., 2., nan, nan, nan, nan, nan, 1., 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, 3., nan, 3., 2., nan, nan, nan, nan, nan, nan, nan, 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 3., 3., nan, nan, 1., nan, nan, 1., 1., 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., nan, 3., 3., 4., 1., 1., 1., 1., 1., nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 4., 4., 4., 4., 4., 4., 1., nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 4., nan, 4., 4., 4., 4., nan, nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 4., nan, nan, 4., 4., 4., 4., nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 4., 4., nan, nan, 4., 4., 4., nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 4., 4., nan, nan, 4., 4., 4., nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 4., 4., 4., nan, nan, nan, nan, nan], # noqa: E501 ]) nybb_points_sol = np.array([ [2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 3, 1, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 3, 7, 6, 2, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 4, 3, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 2, 4, 2, 8, 3, 0, 1, 2, 2, 0, 3, 1, 0, 0, 0, 2, 1], [0, 0, 1, 0, 5, 2, 3, 0, 0, 2, 4, 2, 3, 1, 0, 0, 0, 0, 0, 0], [0, 0, 2, 2, 3, 8, 3, 0, 1, 5, 2, 7, 5, 0, 3, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 1, 5, 5, 3, 4, 3, 3, 1, 2, 0, 2, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 5, 2, 4, 3, 3, 2, 3, 1], [0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 1, 2, 5, 4, 1, 3, 1, 0, 4], [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 5, 2, 2, 5, 2, 3, 1, 1, 2, 4], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 6, 1, 2, 2, 3, 2, 1, 2, 1, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 8, 7, 1, 2, 2, 1, 2, 1, 1, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 9, 6, 3, 3, 1, 4, 1, 3, 5, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 6, 6, 1, 0, 0, 2, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 4, 7, 4, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 6, 8, 9, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 4, 4, 5, 5, 5, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 4, 2, 2, 5, 7, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 5, 0, 0, 0], ], dtype=np.uint32) nybb_polygons_sol = np.array([ [ 0., 0., nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], # noqa: E501 [ 0., 0., 0., nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], # noqa: E501 [nan, 0., 0., 0., 0., nan, nan, nan, nan, nan, nan, 1., nan, nan, nan, nan, nan, nan, nan, nan], # noqa: E501 [nan, nan, 0., 0., 0., 0., nan, 0., nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], # noqa: E501 [nan, nan, 0., 0., 0., 0., 0., 0., nan, 2., 2., 2., 2., 2., 2., 1., 1., nan, nan, nan], # noqa: E501 [nan, nan, 0., 0., 0., 0., 0., nan, 2., 2., 2., 2., 2., 2., 2., 2., 1., 1., nan, nan], # noqa: E501 [nan, nan, 0., 0., 0., 0., 0., nan, 2., 2., 2., 2., 2., 2., 2., 2., 1., 1., nan, nan], # noqa: E501 [nan, nan, nan, 0., nan, nan, nan, nan, 2., 2., 2., 2., 2., 2., 1., 1., 1., 1., 1., nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, 2., 2., 2., 2., 2., 1., 1., 1., 1., 1., nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, 3., 3., 3., 2., 2., 2., 1., 1., 1., 1., 1., 1., nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 2., 1., 1., 1., 1., 1., 1., 1., nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 1., 1., 1., 1., 1., 1., 1., 1., 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 1., 1., 1., 1., 1., 1., 1., 1., 1.], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 1., 1., nan, 1., 1., 1., nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 3., 4., 4., nan, nan, nan, nan, nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 4., 4., 4., 4., nan, nan, nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 4., 4., 4., 4., 4., nan, nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 4., 4., 4., 4., 4., 4., nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 3., 4., 4., 4., 4., 4., 4., nan, nan], # noqa: E501 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 4., 4., 4., nan, nan, nan, nan, nan], # noqa: E501 ]) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not geopandas, reason="geopandas not installed") @pytest.mark.parametrize("geom_type, explode, use_boundary", [ ("multipolygon", False, False), ("polygon", True, False), ("multilinestring", False, True), ("linestring", True, True), ], ) def test_lines_geopandas(geom_type, explode, use_boundary): df = geopandas.read_file(geodatasets.get_path("nybb")) df["col"] = np.arange(len(df)) # Extra column for aggregation. geometry = "boundary" if use_boundary else "geometry" if explode: df = df.explode(index_parts=False) # Multipolygon -> polygon. if use_boundary: df["boundary"] = df.boundary unique_geom_type = df[geometry].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.line(source=df, geometry=geometry, agg=ds.max("col")) assert_eq_ndarray(agg.data, nybb_lines_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not dask_geopandas, reason="dask_geopandas not installed") @pytest.mark.skipif(not geopandas, reason="geopandas not installed") @pytest.mark.parametrize('npartitions', [1, 2, 5]) @pytest.mark.parametrize("geom_type, explode, use_boundary", [ ("multipolygon", False, False), ("polygon", True, False), ("multilinestring", False, True), ("linestring", True, True), ], ) def test_lines_dask_geopandas(geom_type, explode, use_boundary, npartitions): df = geopandas.read_file(geodatasets.get_path("nybb")) df["col"] = np.arange(len(df)) # Extra column for aggregation. geometry = "boundary" if use_boundary else "geometry" if explode: df = df.explode(index_parts=False) # Multipolygon -> polygon. if use_boundary: df["boundary"] = df.boundary unique_geom_type = df[geometry].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type df = dd.from_pandas(df, npartitions=npartitions) assert df.npartitions == npartitions df.calculate_spatial_partitions() canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.line(source=df, geometry=geometry, agg=ds.max("col")) assert_eq_ndarray(agg.data, nybb_lines_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('npartitions', [1, 2, 5]) @pytest.mark.parametrize("geom_type, explode, use_boundary", [ ("multipolygon", False, False), ("polygon", True, False), ("multilinestring", False, True), ("linestring", True, True), ], ) def test_lines_spatialpandas(geom_type, explode, use_boundary, npartitions): df = geopandas.read_file(geodatasets.get_path("nybb")) df["col"] = np.arange(len(df)) # Extra column for aggregation. geometry = "boundary" if use_boundary else "geometry" if explode: df = df.explode(index_parts=False) # Multipolygon -> polygon. if use_boundary: df["boundary"] = df.boundary unique_geom_type = df[geometry].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type df = spatialpandas.GeoDataFrame(df) if npartitions > 0: df = dd.from_pandas(df, npartitions=npartitions) assert df.npartitions == npartitions canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.line(source=df, geometry=geometry, agg=ds.max("col")) assert_eq_ndarray(agg.data, nybb_lines_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not geopandas, reason="geopandas not installed") @pytest.mark.parametrize("geom_type", ["multipoint", "point"]) def test_points_geopandas(geom_type): df = geopandas.read_file(geodatasets.get_path("nybb")) df["geometry"] = df["geometry"].sample_points(100, seed=93814) # multipoint if geom_type == "point": df = df.explode(index_parts=False) # Multipoint -> point. unique_geom_type = df["geometry"].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.points(source=df, geometry="geometry", agg=ds.count()) assert_eq_ndarray(agg.data, nybb_points_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not geopandas, reason="geopandas not installed") @pytest.mark.parametrize('npartitions', [1, 2, 5]) @pytest.mark.parametrize("geom_type", ["multipoint", "point"]) def test_points_dask_geopandas(geom_type, npartitions): df = geopandas.read_file(geodatasets.get_path("nybb")) df["geometry"] = df["geometry"].sample_points(100, seed=93814) # multipoint if geom_type == "point": df = df.explode(index_parts=False) # Multipoint -> point. unique_geom_type = df["geometry"].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type df = dd.from_pandas(df, npartitions=npartitions) assert df.npartitions == npartitions df.calculate_spatial_partitions() canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.points(source=df, geometry="geometry", agg=ds.count()) assert_eq_ndarray(agg.data, nybb_points_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('npartitions', [0, 1, 2, 5]) @pytest.mark.parametrize("geom_type", ["multipoint", "point"]) def test_points_spatialpandas(geom_type, npartitions): df = geopandas.read_file(geodatasets.get_path("nybb")) df["geometry"] = df["geometry"].sample_points(100, seed=93814) # multipoint if geom_type == "point": df = df.explode(index_parts=False) # Multipoint -> point. unique_geom_type = df["geometry"].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type df = spatialpandas.GeoDataFrame(df) if npartitions > 0: df = dd.from_pandas(df, npartitions=npartitions) assert df.npartitions == npartitions canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.points(source=df, geometry="geometry", agg=ds.count()) assert_eq_ndarray(agg.data, nybb_points_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not geopandas, reason="geopandas not installed") @pytest.mark.parametrize("geom_type", ["multipolygon", "polygon"]) def test_polygons_geopandas(geom_type): df = geopandas.read_file(geodatasets.get_path("nybb")) df["col"] = np.arange(len(df)) # Extra column for aggregation. if geom_type == "polygon": df = df.explode(index_parts=False) # Multipolygon -> polygon. unique_geom_type = df["geometry"].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.polygons(source=df, geometry="geometry", agg=ds.max("col")) assert_eq_ndarray(agg.data, nybb_polygons_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not dask_geopandas, reason="dask_geopandas not installed") @pytest.mark.skipif(not geopandas, reason="geopandas not installed") @pytest.mark.parametrize('npartitions', [1, 2, 5]) @pytest.mark.parametrize("geom_type", ["multipolygon", "polygon"]) def test_polygons_dask_geopandas(geom_type, npartitions): df = geopandas.read_file(geodatasets.get_path("nybb")) df["col"] = np.arange(len(df)) if geom_type == "polygon": df = df.explode(index_parts=False) # Multipolygon -> polygon. unique_geom_type = df["geometry"].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type df = dd.from_pandas(df, npartitions=npartitions) assert df.npartitions == npartitions df.calculate_spatial_partitions() canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.polygons(source=df, geometry="geometry", agg=ds.max("col")) assert_eq_ndarray(agg.data, nybb_polygons_sol) @pytest.mark.skipif(not geodatasets, reason="geodatasets not installed") @pytest.mark.skipif(not geopandas, reason="geopandas not installed") @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('npartitions', [0, 1, 2, 5]) @pytest.mark.parametrize("geom_type", ["multipolygon", "polygon"]) def test_polygons_spatialpandas(geom_type, npartitions): df = geopandas.read_file(geodatasets.get_path("nybb")) df["col"] = np.arange(len(df)) if geom_type == "polygon": df = df.explode(index_parts=False) # Multipolygon -> polygon. unique_geom_type = df["geometry"].geom_type.unique() assert len(unique_geom_type) == 1 and unique_geom_type[0].lower() == geom_type df = spatialpandas.GeoDataFrame(df) if npartitions > 0: df = dd.from_pandas(df, npartitions=npartitions) assert df.npartitions == npartitions canvas = ds.Canvas(plot_height=20, plot_width=20) agg = canvas.polygons(source=df, geometry="geometry", agg=ds.max("col")) assert_eq_ndarray(agg.data, nybb_polygons_sol)