from unittest import SkipTest import numpy as np from holoviews.element import RGB, Image, ImageStack, Raster from holoviews.plotting.bokeh.raster import ImageStackPlot from .test_plot import TestBokehPlot, bokeh_renderer class TestRasterPlot(TestBokehPlot): def test_image_colormapping(self): img = Image(np.random.rand(10, 10)).opts(logz=True) self._test_colormapping(img, 2, True) def test_image_boolean_array(self): img = Image(np.array([[True, False], [False, True]])) plot = bokeh_renderer.get_plot(img) cmapper = plot.handles["color_mapper"] source = plot.handles["source"] assert cmapper.low == 0 assert cmapper.high == 1 np.testing.assert_equal(source.data["image"][0], np.array([[0, 1], [1, 0]])) def test_nodata_array(self): img = Image(np.array([[0, 1], [2, 0]])).opts(nodata=0) plot = bokeh_renderer.get_plot(img) cmapper = plot.handles["color_mapper"] source = plot.handles["source"] assert cmapper.low == 1 assert cmapper.high == 2 np.testing.assert_equal( source.data["image"][0], np.array([[2, np.nan], [np.nan, 1]]) ) def test_nodata_array_uint(self): img = Image(np.array([[0, 1], [2, 0]], dtype="uint32")).opts(nodata=0) plot = bokeh_renderer.get_plot(img) cmapper = plot.handles["color_mapper"] source = plot.handles["source"] assert cmapper.low == 1 assert cmapper.high == 2 np.testing.assert_equal( source.data["image"][0], np.array([[2, np.nan], [np.nan, 1]]) ) def test_nodata_rgb(self): N = 2 rgb_d = np.linspace(0, 1, N * N * 3).reshape(N, N, 3) rgb = RGB(rgb_d).redim.nodata(R=0) plot = bokeh_renderer.get_plot(rgb) image_data = plot.handles["source"].data["image"][0] assert (image_data == 0).sum() == 1 def test_raster_invert_axes(self): arr = np.array([[0, 1, 2], [3, 4, 5]]) raster = Raster(arr).opts(invert_axes=True) plot = bokeh_renderer.get_plot(raster) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0], arr.T) assert source.data["x"][0] == 0 assert source.data["y"][0] == 0 assert source.data["dw"][0] == 2 assert source.data["dh"][0] == 3 def test_image_invert_axes(self): arr = np.array([[0, 1, 2], [3, 4, 5]]) raster = Image(arr).opts(invert_axes=True) plot = bokeh_renderer.get_plot(raster) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0], np.rot90(arr)[::-1, ::-1]) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == -0.5 assert source.data["dw"][0] == 1 assert source.data["dh"][0] == 1 def test_image_invert_xaxis(self): arr = np.random.rand(10, 10) img = Image(arr).opts(invert_xaxis=True) plot = bokeh_renderer.get_plot(img) x_range = plot.handles["x_range"] assert x_range.start == 0.5 assert x_range.end == -0.5 cdata = plot.handles["source"].data assert cdata["y"] == [-0.5] assert cdata["dh"] == [1.0] assert cdata["dw"] == [1.0] assert cdata["x"] == [-0.5] np.testing.assert_equal(cdata["image"][0], arr[::-1]) def test_image_invert_yaxis(self): arr = np.random.rand(10, 10) img = Image(arr).opts(invert_yaxis=True) plot = bokeh_renderer.get_plot(img) y_range = plot.handles["y_range"] assert y_range.start == 0.5 assert y_range.end == -0.5 cdata = plot.handles["source"].data assert cdata["x"] == [-0.5] assert cdata["dh"] == [1.0] assert cdata["dw"] == [1.0] assert cdata["y"] == [-0.5] np.testing.assert_equal(cdata["image"][0], arr[::-1]) def test_rgb_invert_xaxis(self): rgb = RGB(np.random.rand(10, 10, 3)).opts(invert_xaxis=True) plot = bokeh_renderer.get_plot(rgb) x_range = plot.handles["x_range"] assert x_range.start == 0.5 assert x_range.end == -0.5 cdata = plot.handles["source"].data assert cdata["y"] == [-0.5] assert cdata["dh"] == [1.0] assert cdata["dw"] == [1.0] assert cdata["x"] == [-0.5] def test_rgb_invert_yaxis(self): rgb = RGB(np.random.rand(10, 10, 3)).opts(invert_yaxis=True) plot = bokeh_renderer.get_plot(rgb) y_range = plot.handles["y_range"] assert y_range.start == 0.5 assert y_range.end == -0.5 cdata = plot.handles["source"].data assert cdata["x"] == [-0.5] assert cdata["dh"] == [1.0] assert cdata["dw"] == [1.0] assert cdata["y"] == [-0.5] class _ImageStackBase(TestRasterPlot): __test__ = False def test_image_stack_tuple(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c img_stack = ImageStack((x, y, a, b, c), kdims=["x", "y"], vdims=["a", "b", "c"]) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_tuple_unspecified_dims(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c img_stack = ImageStack((x, y, a, b, c), kdims=["x", "y"]) assert img_stack.vdims == ["level_0", "level_1", "level_2"] plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_dict(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c ds = {"x": x, "y": y, "a": a, "b": b, "c": c} img_stack = ImageStack(ds, kdims=["x", "y"], vdims=["a", "b", "c"]) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_dict_unspecified_dims(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c ds = {"x": x, "y": y, "a": a, "b": b, "c": c} img_stack = ImageStack(ds) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_dict_no_kdims(self): a, b, c = self.a, self.b, self.c ds = {"a": a, "b": b, "c": c} img_stack = ImageStack(ds) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == -0.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_list(self): a, b, c = self.a, self.b, self.c ds = [a, b, c] img_stack = ImageStack(ds) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == -0.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_xarray_dataset(self): try: import xarray as xr except ImportError: raise SkipTest("xarray not available for core tests") x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c ds = xr.Dataset( {"a": (["y", "x"], a), "b": (["y", "x"], b), "c": (["y", "x"], c)}, coords={"x": x, "y": y}, ) img_stack = ImageStack(ds, kdims=["x", "y"]) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_xarray_dataarray(self): try: import xarray as xr except ImportError: raise SkipTest("xarray not available for core tests") x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c da = xr.Dataset( {"a": (["y", "x"], a), "b": (["y", "x"], b), "c": (["y", "x"], c)}, coords={"x": x, "y": y}, ).to_array("level") img_stack = ImageStack(da, vdims=["level"]) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_invert_xaxis(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c img_stack = ImageStack((x, y, a, b, c), kdims=["x", "y"], vdims=["a", "b", "c"]) plot = bokeh_renderer.get_plot(img_stack.opts(invert_xaxis=True)) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize def test_image_stack_invert_yaxis(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c img_stack = ImageStack((x, y, a, b, c), kdims=["x", "y"], vdims=["a", "b", "c"]) plot = bokeh_renderer.get_plot(img_stack.opts(invert_yaxis=True)) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize def test_image_stack_invert_axes(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c img_stack = ImageStack((x, y, a, b, c), kdims=["x", "y"], vdims=["a", "b", "c"]) plot = bokeh_renderer.get_plot(img_stack.opts(invert_axes=True)) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0].T, a) np.testing.assert_equal(source.data["image"][0][:, :, 1].T, b) np.testing.assert_equal(source.data["image"][0][:, :, 2].T, c) assert source.data["x"][0] == 4.5 assert source.data["y"][0] == -0.5 assert source.data["dw"][0] == self.ysize assert source.data["dh"][0] == self.xsize def test_image_stack_array(self): a, b, c = self.a, self.b, self.c data = np.dstack((a, b, c)) img_stack = ImageStack(data, kdims=["x", "y"], vdims=["a", "b", "c"]) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == -0.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) def test_image_stack_tuple_single_3darray(self): x = np.arange(self.xsize) y = np.arange(self.ysize) + 5 a, b, c = self.a, self.b, self.c data = (x, y, np.dstack((a, b, c))) img_stack = ImageStack(data, kdims=["x", "y"], vdims=["a", "b", "c"]) plot = bokeh_renderer.get_plot(img_stack) source = plot.handles["source"] np.testing.assert_equal(source.data["image"][0][:, :, 0], a) np.testing.assert_equal(source.data["image"][0][:, :, 1], b) np.testing.assert_equal(source.data["image"][0][:, :, 2], c) assert source.data["x"][0] == -0.5 assert source.data["y"][0] == 4.5 assert source.data["dw"][0] == self.xsize assert source.data["dh"][0] == self.ysize assert isinstance(plot, ImageStackPlot) class TestImageStackEven(_ImageStackBase): __test__ = True def setUp(self): self.a = np.array([[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3]) self.b = np.array([[np.nan] * 3, [1, 1, np.nan], [np.nan] * 3]) self.c = np.array([[np.nan] * 3, [np.nan] * 3, [1, 1, 1]]) self.ysize = 3 self.xsize = 3 super().setUp() class TestImageStackUneven1(_ImageStackBase): __test__ = True def setUp(self): self.a = np.array( [[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3, [np.nan] * 3] ) self.b = np.array([[np.nan] * 3, [1, 1, np.nan], [np.nan] * 3, [np.nan] * 3]) self.c = np.array([[np.nan] * 3, [np.nan] * 3, [1, 1, 1], [np.nan] * 3]) self.ysize = 4 self.xsize = 3 super().setUp() class TestImageStackUneven2(_ImageStackBase): __test__ = True def setUp(self): self.a = np.array([[np.nan, np.nan, 1, np.nan], [np.nan] * 4, [np.nan] * 4]) self.b = np.array([[np.nan] * 4, [1, 1, np.nan, np.nan], [np.nan] * 4]) self.c = np.array([[np.nan] * 4, [np.nan] * 4, [1, 1, 1, 1]]) self.ysize = 3 self.xsize = 4 super().setUp()