import pytest import pandas as pd import numpy as np import xarray as xr import datashader as ds from datashader.tests.test_pandas import assert_eq_ndarray, assert_eq_xr from datashader.tests.utils import dask_switcher try: import dask.dataframe as dd except ImportError: dd = None @pytest.fixture(autouse=True) def _classic_dd(): with dask_switcher(query=False, extras=["spatialpandas.dask"]): ... try: # Import to register extension arrays import spatialpandas # noqa (register EAs) from spatialpandas import GeoDataFrame from spatialpandas.geometry import MultiPolygonArray except ImportError: spatialpandas = None GeoDataFrame = None MultiPolygonArray = None def dask_GeoDataFrame(*args, **kwargs): return dd.from_pandas(GeoDataFrame(*args, **kwargs), npartitions=3) DataFrames = [GeoDataFrame, dask_GeoDataFrame] @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('DataFrame', DataFrames) def test_multipolygon_manual_range(DataFrame): df = DataFrame({ 'polygons': pd.Series([[ [ [0, 0, 2, 0, 2, 2, 1, 3, 0, 0], [1, 0.25, 1, 2, 1.75, .25, 0.25, 0.25] ], [ [2.5, 1, 4, 1, 4, 2, 2.5, 2, 2.5, 1] ], ]], dtype='MultiPolygon[float64]'), 'v': [1] }) cvs = ds.Canvas(plot_width=16, plot_height=16) agg = cvs.polygons(df, geometry='polygons', agg=ds.count()) axis = ds.core.LinearAxis() lincoords_x = axis.compute_index( axis.compute_scale_and_translate((0., 4.), 16), 16) lincoords_y = axis.compute_index( axis.compute_scale_and_translate((0., 3.), 16), 16) sol = np.array([ [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] ], dtype='i4') out = xr.DataArray(sol, coords=[lincoords_y, lincoords_x], dims=['y', 'x']) assert_eq_xr(agg, out) assert_eq_ndarray(agg.x_range, (0, 4), close=True) assert_eq_ndarray(agg.y_range, (0, 3), close=True) @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('DataFrame', DataFrames) def test_multiple_polygons_auto_range(DataFrame): df = DataFrame({ 'polygons': pd.Series([[ [ [0, 0, 2, 0, 2, 2, 1, 3, 0, 0], [1, 0.25, 1, 2, 1.75, .25, 0.25, 0.25] ], [ [2.5, 1, 4, 1, 4, 2, 2.5, 2, 2.5, 1] ], ]], dtype='MultiPolygon[float64]'), 'v': [1] }) cvs = ds.Canvas(plot_width=16, plot_height=16, x_range=[-1, 3.5], y_range=[0.1, 2]) agg = cvs.polygons(df, geometry='polygons', agg=ds.count()) axis = ds.core.LinearAxis() lincoords_x = axis.compute_index( axis.compute_scale_and_translate((-1, 3.5), 16), 16) lincoords_y = axis.compute_index( axis.compute_scale_and_translate((0.1, 2), 16), 16) sol = np.array([ [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1] ], dtype='i4') out = xr.DataArray(sol, coords=[lincoords_y, lincoords_x], dims=['y', 'x']) assert_eq_xr(agg, out) assert_eq_ndarray(agg.x_range, (-1, 3.5), close=True) assert_eq_ndarray(agg.y_range, (0.1, 2), close=True) @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('DataFrame', DataFrames) def test_no_overlap(DataFrame): df = DataFrame({ 'polygons': pd.Series([ [ [1, 1, 2, 2, 1, 3, 0, 2, 1, 1], [0.5, 1.5, 0.5, 2.5, 1.5, 2.5, 1.5, 1.5, 0.5, 1.5] ], [ [0.5, 1.5, 1.5, 1.5, 1.5, 2.5, 0.5, 2.5, 0.5, 1.5] ], [ [0, 1, 2, 1, 2, 3, 0, 3, 0, 1, 1, 1, 0, 2, 1, 3, 2, 2, 1, 1] ] ], dtype='Polygon[float64]'), }) cvs = ds.Canvas(plot_width=16, plot_height=16) agg = cvs.polygons(df, geometry='polygons', agg=ds.count()) axis = ds.core.LinearAxis() lincoords_x = axis.compute_index( axis.compute_scale_and_translate((0, 2), 16), 16) lincoords_y = axis.compute_index( axis.compute_scale_and_translate((1, 3), 16), 16) sol = np.array([ [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] ], dtype='i4') out = xr.DataArray(sol, coords=[lincoords_y, lincoords_x], dims=['y', 'x']) assert_eq_xr(agg, out) @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('DataFrame', DataFrames) def test_no_overlap_agg(DataFrame): df = DataFrame({ 'polygons': pd.Series([ [[1, 1, 2, 2, 1, 3, 0, 2, 1, 1], [0.5, 1.5, 0.5, 2.5, 1.5, 2.5, 1.5, 1.5, 0.5, 1.5]], [[0.5, 1.5, 1.5, 1.5, 1.5, 2.5, 0.5, 2.5, 0.5, 1.5]], [[0, 1, 2, 1, 2, 3, 0, 3, 0, 1, 1, 1, 0, 2, 1, 3, 2, 2, 1, 1]] ], dtype='Polygon[float64]'), 'v': range(3) }) cvs = ds.Canvas(plot_width=16, plot_height=16) agg = cvs.polygons(df, geometry='polygons', agg=ds.sum('v')) axis = ds.core.LinearAxis() lincoords_x = axis.compute_index( axis.compute_scale_and_translate((0, 2), 16), 16) lincoords_y = axis.compute_index( axis.compute_scale_and_translate((1, 3), 16), 16) sol = np.array([ [2., 2., 2., 2., 2., 2., 2., 2., 0., 2., 2., 2., 2., 2., 2., 2.], [2., 2., 2., 2., 2., 2., 2., 0., 0., 0., 2., 2., 2., 2., 2., 2.], [2., 2., 2., 2., 2., 2., 0., 0., 0., 0., 0., 2., 2., 2., 2., 2.], [2., 2., 2., 2., 2., 0., 0., 0., 0., 0., 0., 0., 2., 2., 2., 2.], [2., 2., 2., 2., 1., 1., 1., 1., 1., 1., 1., 1., 0., 2., 2., 2.], [2., 2., 2., 0., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0., 2., 2.], [2., 2., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0., 0., 2.], [2., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0., 0., 0.], [2., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0., 0., 0.], [2., 2., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0., 0., 2.], [2., 2., 2., 0., 1., 1., 1., 1., 1., 1., 1., 1., 0., 0., 2., 2.], [2., 2., 2., 2., 1., 1., 1., 1., 1., 1., 1., 1., 0., 2., 2., 2.], [2., 2., 2., 2., 2., 0., 0., 0., 0., 0., 0., 0., 2., 2., 2., 2.], [2., 2., 2., 2., 2., 2., 0., 0., 0., 0., 0., 2., 2., 2., 2., 2.], [2., 2., 2., 2., 2., 2., 2., 0., 0., 0., 2., 2., 2., 2., 2., 2.], [2., 2., 2., 2., 2., 2., 2., 2., 0., 2., 2., 2., 2., 2., 2., 2.] ]) out = xr.DataArray(sol, coords=[lincoords_y, lincoords_x], dims=['y', 'x']) assert_eq_xr(agg, out) @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('DataFrame', DataFrames) @pytest.mark.parametrize('scale', [4, 100]) def test_multipolygon_subpixel_vertical(DataFrame, scale): df = GeoDataFrame({ 'geometry': MultiPolygonArray([[ [[0, 0, 1, 0, 1, 1, 0, 1, 0, 0]], [[2, 0, 3, 0, 3, 1, 2, 1, 2, 0]], ]]) }) cvs = ds.Canvas( plot_height=8, plot_width=8, x_range=(0, 4), y_range=(-2 * scale, 2 * scale) ) agg = cvs.polygons(df, 'geometry', agg=ds.count()) sol = np.array([ [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0] ], dtype=np.int32) axis = ds.core.LinearAxis() lincoords_x = axis.compute_index( axis.compute_scale_and_translate((0, 4), 8), 8) lincoords_y = axis.compute_index( axis.compute_scale_and_translate((-2 * scale, 2 * scale), 8), 8) out = xr.DataArray(sol, coords=[lincoords_y, lincoords_x], dims=['y', 'x']) assert_eq_xr(agg, out) @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") @pytest.mark.parametrize('DataFrame', DataFrames) @pytest.mark.parametrize('scale', [4, 100]) def test_multipolygon_subpixel_horizontal(DataFrame, scale): df = GeoDataFrame({ 'geometry': MultiPolygonArray([[ [[0, 0, 1, 0, 1, 1, 0, 1, 0, 0]], [[0, 2, 1, 2, 1, 3, 0, 3, 0, 2]], ]]) }) cvs = ds.Canvas( plot_height=8, plot_width=8, x_range=(-2 * scale, 2 * scale), y_range=(0, 4) ) agg = cvs.polygons(df, 'geometry', agg=ds.count()) sol = np.array([ [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0] ], dtype=np.int32) axis = ds.core.LinearAxis() lincoords_x = axis.compute_index( axis.compute_scale_and_translate((-2 * scale, 2 * scale), 8), 8) lincoords_y = axis.compute_index( axis.compute_scale_and_translate((0, 4), 8), 8) out = xr.DataArray(sol, coords=[lincoords_y, lincoords_x], dims=['y', 'x']) assert_eq_xr(agg, out) @pytest.mark.skipif(not spatialpandas, reason="spatialpandas not installed") def test_spatial_index_not_dropped(): # Issue 1121 df = GeoDataFrame({ 'some_geom': MultiPolygonArray([ [[[0, 0, 1, 0, 1, 1, 0, 1, 0, 0]]], [[[0, 2, 1, 2, 1, 3, 0, 3, 0, 2]]], ]), 'other': [23, 45], # This column is not used and will be dropped. }) assert df.some_geom.array._sindex is None sindex = df.some_geom.array.sindex assert sindex is not None glyph = ds.glyphs.polygon.PolygonGeom('some_geom') agg = ds.count() df2, _ = ds.core._bypixel_sanitise(df, glyph, agg) assert df2.columns == ['some_geom'] assert df2.some_geom.array._sindex == df.some_geom.array._sindex