import sys from unittest import SkipTest from parameterized import parameterized import hvplot.pandas # noqa import numpy as np import pandas as pd from holoviews import Store from holoviews.element import Image, QuadMesh from holoviews.element.comparison import ComparisonTestCase from hvplot.converter import HoloViewsConverter class TestDatashader(ComparisonTestCase): def setUp(self): try: import datashader # noqa except: raise SkipTest('Datashader not available') if sys.maxsize < 2**32: raise SkipTest('Datashader does not support 32-bit systems') import hvplot.pandas # noqa self.df = pd.DataFrame([[1, 2, 'A', 0.1], [3, 4, 'B', 0.2], [5, 6, 'C', 0.3]], columns=['x', 'y', 'category', 'number']) def test_rasterize_by_cat(self): from datashader.reductions import count_cat dmap = self.df.hvplot.scatter('x', 'y', by='category', rasterize=True) agg = dmap.callback.inputs[0].callback.operation.p.aggregator self.assertIsInstance(agg, count_cat) self.assertEqual(agg.column, 'category') @parameterized.expand([('rasterize',), ('datashade',)]) def test_color_dim_with_default_agg(self, operation): from datashader.reductions import mean dmap = self.df.hvplot.scatter('x', 'y', c='number', **{operation: True}) agg = dmap.callback.inputs[0].callback.operation.p.aggregator self.assertIsInstance(agg, mean) self.assertEqual(agg.column, 'number') @parameterized.expand([('rasterize',), ('datashade',)]) def test_color_dim_with_string_agg(self, operation): from datashader.reductions import sum dmap = self.df.hvplot.scatter('x', 'y', c='number', aggregator='sum', **{operation: True}) agg = dmap.callback.inputs[0].callback.operation.p.aggregator self.assertIsInstance(agg, sum) self.assertEqual(agg.column, 'number') @parameterized.expand([('rasterize',), ('datashade',)]) def test_color_dim_also_an_axis(self, operation): from datashader.reductions import mean original_data = self.df.copy(deep=True) dmap = self.df.hvplot.scatter('x', 'y', c='y', **{operation: True}) agg = dmap.callback.inputs[0].callback.operation.p.aggregator self.assertIsInstance(agg, mean) self.assertEqual(agg.column, '_color') assert original_data.equals(self.df) def test_rasterize_color_dim_with_new_column_gets_default_cmap(self): plot = self.df.hvplot.scatter('x', 'y', c='y', dynamic=False, rasterize=True) opts = Store.lookup_options('bokeh', plot, 'style').kwargs self.assertEqual(opts.get('cmap'), 'kbc_r') def test_rasterize_default_cmap(self): plot = self.df.hvplot.scatter('x', 'y', dynamic=False, rasterize=True) opts = Store.lookup_options('bokeh', plot, 'style').kwargs self.assertEqual(opts.get('cmap'), 'kbc_r') def test_rasterize_default_colorbar(self): plot = self.df.hvplot.scatter('x', 'y', dynamic=False, rasterize=True) opts = Store.lookup_options('bokeh', plot, 'plot').kwargs self.assertTrue(opts.get('colorbar')) def test_rasterize_default_colorbar_with_cmap(self): cmap = 'Reds' plot = self.df.hvplot.scatter('x', 'y', dynamic=False, rasterize=True, cmap=cmap) opts = Store.lookup_options('bokeh', plot, 'style').kwargs self.assertEqual(opts.get('cmap'), cmap) opts = Store.lookup_options('bokeh', plot, 'plot').kwargs self.assertTrue(opts.get('colorbar')) def test_rasterize_set_clim(self): plot = self.df.hvplot.scatter('x', 'y', dynamic=False, rasterize=True, clim=(1, 4)) opts = Store.lookup_options('bokeh', plot, 'plot').kwargs self.assertEqual(opts.get('clim'), (1, 4)) @parameterized.expand([('aspect',), ('data_aspect',)]) def test_aspect_with_datashade(self, opt): plot = self.df.hvplot(x='x', y='y', datashade=True, **{opt: 2}) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs self.assertEqual(opts[opt], 2) self.assertEqual(opts.get('height'), None) self.assertEqual(opts.get('frame_height'), None) @parameterized.expand([('aspect',), ('data_aspect',)]) def test_aspect_with_datashade_and_dynamic_is_false(self, opt): plot = self.df.hvplot(x='x', y='y', datashade=True, dynamic=False, **{opt: 2}) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs self.assertEqual(opts[opt], 2) self.assertEqual(opts.get('height'), None) self.assertEqual(opts.get('frame_height'), None) @parameterized.expand([('aspect',), ('data_aspect',)]) def test_aspect_and_frame_height_with_datashade(self, opt): plot = self.df.hvplot(x='x', y='y', frame_height=150, datashade=True, **{opt: 2}) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs self.assertEqual(opts[opt], 2) self.assertEqual(opts.get('frame_height'), 150) self.assertEqual(opts.get('height'), None) self.assertEqual(opts.get('frame_width'), None) @parameterized.expand([('aspect',), ('data_aspect',)]) def test_aspect_and_frame_height_with_datashade_and_dynamic_is_false(self, opt): plot = self.df.hvplot(x='x', y='y', frame_height=150, datashade=True, dynamic=False, **{opt: 2}) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs self.assertEqual(opts[opt], 2) self.assertEqual(opts.get('frame_height'), 150) self.assertEqual(opts.get('height'), None) self.assertEqual(opts.get('frame_width'), None) def test_cmap_can_be_color_key(self): color_key = {'A': '#ff0000', 'B': '#00ff00', 'C': '#0000ff'} self.df.hvplot.points(x='x', y='y', by='category', cmap=color_key, datashade=True) with self.assertRaises(TypeError): self.df.hvplot.points(x='x', y='y', by='category', datashade=True, cmap='kbc_r', color_key=color_key) def test_when_datashade_is_true_set_hover_to_false_by_default(self): plot = self.df.hvplot(x='x', y='y', datashade=True) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs assert 'hover' not in opts.get('tools') def test_when_datashade_is_true_hover_can_still_be_true(self): plot = self.df.hvplot(x='x', y='y', datashade=True, hover=True) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs assert 'hover' in opts.get('tools') def test_xlim_affects_x_range(self): data = pd.DataFrame(np.random.randn(100).cumsum()) img = data.hvplot(xlim=(0, 20000), datashade=True, dynamic=False) assert img.range(0) == (0, 20000) @parameterized.expand([('scatter',), ('line',), ('area',)]) def test_wide_charts_categorically_shaded_explicit_ys(self, kind): df = pd._testing.makeTimeDataFrame() plot = pd._testing.makeTimeDataFrame().hvplot(y=list(df.columns), datashade=True, kind=kind) expected_cmap = HoloViewsConverter._default_cmaps['categorical'] assert plot.callback.inputs[0].callback.operation.p.cmap == expected_cmap assert plot.callback.inputs[0].callback.operation.p.aggregator.column == 'Variable' @parameterized.expand([('scatter',), ('line',), ('area',)]) def test_wide_charts_categorically_shaded_implicit_ys(self, kind): plot = pd._testing.makeTimeDataFrame().hvplot(datashade=True, kind=kind) expected_cmap = HoloViewsConverter._default_cmaps['categorical'] assert plot.callback.inputs[0].callback.operation.p.cmap == expected_cmap assert plot.callback.inputs[0].callback.operation.p.aggregator.column == 'Variable' def test_wide_charts_categorically_shaded_by(self): cat_col = 'category' plot = self.df.hvplot.scatter('x', 'y', by=cat_col, datashade=True) expected_cmap = HoloViewsConverter._default_cmaps['categorical'] assert plot.callback.inputs[0].callback.operation.p.cmap == expected_cmap assert plot.callback.inputs[0].callback.operation.p.aggregator.column == cat_col def test_rasterize_cnorm(self): expected = 'eq_hist' plot = self.df.hvplot(x='x', y='y', rasterize=True, cnorm=expected) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs assert opts.get('cnorm') == expected def test_datashade_cnorm(self): expected = 'eq_hist' plot = self.df.hvplot(x='x', y='y', datashade=True, cnorm=expected) actual = plot.callback.inputs[0].callback.operation.p['cnorm'] assert actual == expected def test_rasterize_rescale_discrete_levels(self): expected = False plot = self.df.hvplot(x='x', y='y', rasterize=True, cnorm='eq_hist', rescale_discrete_levels=expected) opts = Store.lookup_options('bokeh', plot[()], 'plot').kwargs assert opts.get('rescale_discrete_levels') is expected def test_datashade_rescale_discrete_levels(self): expected = False plot = self.df.hvplot(x='x', y='y', datashade=True, cnorm='eq_hist', rescale_discrete_levels=expected) actual = plot.callback.inputs[0].callback.operation.p['rescale_discrete_levels'] assert actual is expected def test_datashade_rescale_discrete_levels_default_True(self): expected = True plot = self.df.hvplot(x='x', y='y', datashade=True, cnorm='eq_hist') actual = plot.callback.inputs[0].callback.operation.p['rescale_discrete_levels'] assert actual is expected class TestChart2D(ComparisonTestCase): def setUp(self): try: import xarray as xr import datashader as ds # noqa except: raise SkipTest('xarray or datashader not available') if sys.maxsize < 2**32: raise SkipTest('Datashader does not support 32-bit systems') import hvplot.xarray # noqa data = np.arange(0, 60).reshape(6, 10) x = np.arange(10) y = np.arange(6) self.da = xr.DataArray(data, coords={'y': y, 'x': x}, dims=('y', 'x')) @parameterized.expand([('image', Image), ('quadmesh', QuadMesh)]) def test_plot_resolution(self, kind, element): plot = self.da.hvplot(kind=kind) assert all(plot.data.x.diff('x').round(0) == 1) assert all(plot.data.y.diff('y').round(0) == 1) @parameterized.expand([('image', Image), ('quadmesh', QuadMesh)]) def test_plot_resolution_with_rasterize(self, kind, element): plot = self.da.hvplot(kind=kind, dynamic=False, rasterize=True, x_sampling=5, y_sampling=2) assert all(plot.data.x.diff('x').round(0) == 5) assert all(plot.data.y.diff('y').round(0) == 2)