import os import tempfile from unittest import SkipTest from collections import OrderedDict import numpy as np from holoviews import Store from holoviews.element import RGB, Image from holoviews.element.comparison import ComparisonTestCase try: import xarray as xr except ImportError: raise SkipTest('XArray not available') else: import hvplot.xarray # noqa class TestGridPlots(ComparisonTestCase): def setUp(self): coords = OrderedDict([('band', [1, 2, 3]), ('y', [0, 1]), ('x', [0, 1])]) self.da_rgb = xr.DataArray(np.arange(12).reshape((3, 2, 2)), coords, ['band', 'y', 'x']) coords = OrderedDict([('time', [0, 1]), ('band', [1, 2, 3]), ('y', [0, 1]), ('x', [0, 1])]) self.da_rgb_by_time = xr.DataArray( np.arange(24).reshape((2, 3, 2, 2)), coords, ['time', 'band', 'y', 'x'] ) coords = OrderedDict([('time', [0, 1]), ('lat', [0, 1]), ('lon', [0, 1])]) self.da_img_by_time = xr.DataArray( np.arange(8).reshape((2, 2, 2)), coords, ['time', 'lat', 'lon'] ).assign_coords(lat1=xr.DataArray([2, 3], dims=['lat'])) self.xarr_with_attrs = xr.DataArray( np.random.rand(10, 10), coords=[('x', range(10)), ('y', range(10))], dims=['y', 'x'], attrs={'long_name': 'luminosity', 'units': 'lm'}, ) self.xarr_with_attrs.x.attrs['long_name'] = 'Declination' self.xarr_with_attrs.y.attrs['long_name'] = 'Right Ascension' self.xds_with_attrs = xr.Dataset({'light': self.xarr_with_attrs}) self.da_img = xr.DataArray(np.arange(-2, 2).reshape((2, 2)), name='foo') self.big_img = xr.DataArray(np.arange(-1e6, 1e6).reshape(1000, 2000)) self.ds = xr.Dataset( { 'temp': (('lon', 'lat'), 15 + 8 * np.random.randn(2, 2)), 'precip': (('lon', 'lat'), 10 * np.random.rand(2, 2)), }, coords={'lon': [-99.83, -99.32], 'lat': [42.25, 42.21]}, ) xs = np.linspace(0, 10, 5) lon = xs * xs[np.newaxis, :].T lat = xs + xs[:, np.newaxis] coords = { 'lon': (('ny', 'nx'), lon), 'lat': (('ny', 'nx'), lat), 'time': [1, 2, 3], 'samples': ('nsamples', [0, 1, 2, 3]), } self.ds_unindexed = xr.DataArray( np.random.rand(5, 5, 3, 4), coords=coords, dims=('nx', 'ny', 'time', 'nsamples') ) def test_rgb_dataarray_no_args(self): rgb = self.da_rgb.hvplot() self.assertEqual(rgb, RGB(([0, 1], [0, 1]) + tuple(self.da_rgb.values))) def test_rgb_dataarray_explicit_args(self): rgb = self.da_rgb.hvplot('x', 'y') self.assertEqual(rgb, RGB(([0, 1], [0, 1]) + tuple(self.da_rgb.values))) def test_rgb_dataarray_explicit_args_and_kind(self): rgb = self.da_rgb.hvplot.rgb('x', 'y') self.assertEqual(rgb, RGB(([0, 1], [0, 1]) + tuple(self.da_rgb.values))) def test_rgb_dataset(self): rgb = self.da_rgb.to_dataset(name='z').hvplot.rgb() self.assertEqual(rgb, RGB(([0, 1], [0, 1]) + tuple(self.da_rgb.values))) def test_rgb_dataset_explicit_z(self): rgb = self.da_rgb.to_dataset(name='z').hvplot.rgb(z='z') self.assertEqual(rgb, RGB(([0, 1], [0, 1]) + tuple(self.da_rgb.values))) def test_rgb_dataset_robust(self): rgb = self.da_rgb.to_dataset(name='z').hvplot.rgb(robust=True) self.assertNotEqual(rgb, RGB(([0, 1], [0, 1]) + tuple(self.da_rgb.values))) def test_rgb_dataarray_groupby_explicit(self): rgb = self.da_rgb_by_time.hvplot.rgb('x', 'y', groupby='time') self.assertEqual(rgb[0], RGB(([0, 1], [0, 1]) + tuple(self.da_rgb_by_time.values[0]))) self.assertEqual(rgb[1], RGB(([0, 1], [0, 1]) + tuple(self.da_rgb_by_time.values[1]))) def test_rgb_dataarray_groupby_infer(self): rgb = self.da_rgb_by_time.hvplot.rgb('x', 'y', bands='band') self.assertEqual(rgb[0], RGB(([0, 1], [0, 1]) + tuple(self.da_rgb_by_time.values[0]))) self.assertEqual(rgb[1], RGB(([0, 1], [0, 1]) + tuple(self.da_rgb_by_time.values[1]))) def test_img_dataarray_infers_correct_other_dims(self): img = self.da_img_by_time[0].hvplot() self.assertEqual(img, Image(self.da_img_by_time[0], ['lon', 'lat'], ['value'])) def test_img_dataarray_robust_to_clim_percentile(self): img = self.da_img_by_time[0].hvplot(robust=True) assert img.opts['clim_percentile'] is True def test_img_dataarray_groupby_infers_correct_other_dims(self): img = self.da_img_by_time.hvplot(groupby='time') self.assertEqual(img[0], Image(self.da_img_by_time[0], ['lon', 'lat'], ['value'])) self.assertEqual(img[1], Image(self.da_img_by_time[1], ['lon', 'lat'], ['value'])) def test_line_infer_dimension_params_from_xarray_attrs(self): hmap = self.xarr_with_attrs.hvplot.line(groupby='x', dynamic=False) self.assertEqual(hmap.kdims[0].label, 'Declination') self.assertEqual(hmap.last.kdims[0].label, 'Right Ascension') self.assertEqual(hmap.last.vdims[0].label, 'luminosity') self.assertEqual(hmap.last.vdims[0].unit, 'lm') def test_img_infer_dimension_params_from_xarray_attrs(self): img = self.xarr_with_attrs.hvplot.image(clim=(0, 2)) self.assertEqual(img.kdims[0].label, 'Declination') self.assertEqual(img.kdims[1].label, 'Right Ascension') self.assertEqual(img.vdims[0].label, 'luminosity') self.assertEqual(img.vdims[0].unit, 'lm') self.assertEqual(img.vdims[0].range, (0, 2)) def test_table_infer_dimension_params_from_xarray_ds_attrs(self): table = self.xds_with_attrs.hvplot.dataset() self.assertEqual(table.kdims[0].label, 'Declination') self.assertEqual(table.kdims[1].label, 'Right Ascension') self.assertEqual(table.vdims[0].label, 'luminosity') self.assertEqual(table.vdims[0].unit, 'lm') def test_points_infer_dimension_params_from_xarray_attrs(self): points = self.xarr_with_attrs.hvplot.points(c='value', clim=(0, 2)) self.assertEqual(points.kdims[0].label, 'Declination') self.assertEqual(points.kdims[1].label, 'Right Ascension') self.assertEqual(points.vdims[0].label, 'luminosity') self.assertEqual(points.vdims[0].unit, 'lm') self.assertEqual(points.vdims[0].range, (0, 2)) def test_dataset_infer_dimension_params_from_xarray_attrs(self): ds = self.xarr_with_attrs.hvplot.dataset() self.assertEqual(ds.kdims[0].label, 'Declination') self.assertEqual(ds.kdims[1].label, 'Right Ascension') self.assertEqual(ds.vdims[0].label, 'luminosity') self.assertEqual(ds.vdims[0].unit, 'lm') def test_table_infer_dimension_params_from_xarray_attrs(self): table = self.xarr_with_attrs.hvplot.dataset() self.assertEqual(table.kdims[0].label, 'Declination') self.assertEqual(table.kdims[1].label, 'Right Ascension') self.assertEqual(table.vdims[0].label, 'luminosity') self.assertEqual(table.vdims[0].unit, 'lm') def test_symmetric_img_deduces_symmetric(self): plot = self.da_img.hvplot.image() plot_opts = Store.lookup_options('bokeh', plot, 'plot') self.assertEqual(plot_opts.kwargs.get('symmetric'), True) style_opts = Store.lookup_options('bokeh', plot, 'style') self.assertEqual(style_opts.kwargs['cmap'], 'coolwarm') def test_symmetric_img_with_symmetric_set_to_false(self): plot = self.da_img.hvplot.image(symmetric=False) plot_opts = Store.lookup_options('bokeh', plot, 'plot') self.assertEqual(plot_opts.kwargs.get('symmetric'), False) style_opts = Store.lookup_options('bokeh', plot, 'style') self.assertEqual(style_opts.kwargs['cmap'], 'kbc_r') def test_symmetric_img_with_cmap_set(self): plot = self.da_img.hvplot.image(cmap='fire') plot_opts = Store.lookup_options('bokeh', plot, 'plot') self.assertEqual(plot_opts.kwargs.get('symmetric'), True) style_opts = Store.lookup_options('bokeh', plot, 'style') self.assertEqual(style_opts.kwargs['cmap'], 'fire') def test_symmetric_with_big_img_sets_symmetric_to_false_without_calculating(self): plot = self.big_img.hvplot.image() plot_opts = Store.lookup_options('bokeh', plot, 'plot') self.assertEqual(plot_opts.kwargs.get('symmetric'), False) style_opts = Store.lookup_options('bokeh', plot, 'style') self.assertEqual(style_opts.kwargs['cmap'], 'kbc_r') def test_symmetric_with_big_img_and_check_symmetric_max_calculates_symmetric(self): plot = self.big_img.hvplot.image(check_symmetric_max=int(1e7)) plot_opts = Store.lookup_options('bokeh', plot, 'plot') self.assertEqual(plot_opts.kwargs.get('symmetric'), True) style_opts = Store.lookup_options('bokeh', plot, 'style') self.assertEqual(style_opts.kwargs['cmap'], 'coolwarm') def test_multiple_zs(self): plot = self.ds.hvplot(x='lat', y='lon', z=['temp', 'precip'], dynamic=False) assert 'temp' in plot.keys() assert 'precip' in plot.keys() assert plot['temp'].kdims == ['lat', 'lon'] assert plot['precip'].kdims == ['lat', 'lon'] def test_unindexed_quadmesh(self): plot = self.ds_unindexed.hvplot.quadmesh(x='lon', y='lat') assert len(plot.kdims) == 2 assert plot.kdims[0].name == 'time' assert plot.kdims[1].name == 'nsamples' p = plot[1, 0] assert len(p.kdims) == 2 assert p.kdims[0].name == 'lon' assert p.kdims[1].name == 'lat' def test_symmetric_dataset_not_in_memory(self): # Creating a netcdf file and loading it as to get an non in memory # DataArray. da = xr.DataArray( data=np.arange(-100, 100).reshape(10, 10, 2), dims=['x', 'y', 'z'], coords={'x': np.arange(10), 'y': np.arange(10), 'z': np.arange(2)}, ) ds = xr.Dataset(data_vars={'value': da}) with tempfile.TemporaryDirectory() as tempdir: fpath = os.path.join(tempdir, 'data.nc') ds.to_netcdf(fpath) ds = xr.open_dataset(fpath) plot = ds.value.hvplot(x='x', y='y', check_symmetric_max=ds.value.size + 1) plot[(0)] plot_opts = Store.lookup_options('bokeh', plot.last, 'plot') # If a DataArray is not in memory, computing whether it's symmetric should # not be done and return False. assert not plot_opts.kwargs['symmetric'] ds.close() def test_symmetric_dataset_in_memory(self): da = xr.DataArray( data=np.arange(-100, 100).reshape(10, 10, 2), dims=['x', 'y', 'z'], coords={'x': np.arange(10), 'y': np.arange(10), 'z': np.arange(2)}, ) ds = xr.Dataset(data_vars={'value': da}) plot = ds.value.hvplot(x='x', y='y', check_symmetric_max=ds.value.size + 1) plot[(0)] plot_opts = Store.lookup_options('bokeh', plot.last, 'plot') # This DataArray happens to be symmetric. assert plot_opts.kwargs['symmetric'] def test_dataarray_unnamed_label(self): plot = self.da_rgb.sel(band=1).hvplot.image(label='test') assert plot.vdims[0].name == 'test' def test_dataarray_unnamed_value_label(self): plot = self.da_rgb.sel(band=1).hvplot.image(value_label='test') assert plot.vdims[0].name == 'test' def test_dataarray_label_precedence(self): # name > label > value_label plot = self.da_rgb.sel(band=1).rename('a').hvplot.image(label='b') assert plot.vdims[0].name == 'a' plot = self.da_rgb.sel(band=1).hvplot.image(label='b', value_label='c') assert plot.vdims[0].name == 'b' def test_tiles_without_gv(self): plot = self.ds.hvplot('lon', 'lat', tiles=True) assert len(plot) == 2 assert isinstance(plot.get(1), Image) assert 'x' in plot.get(1).data assert 'y' in plot.get(1).data