def setUp(self): # Set up plot component containing xs = np.arange(0, 5) ys = np.arange(0, 5) # Add some fake 2D data for the box's component index = GridDataSource(xdata=xs, ydata=ys, sort_order=('ascending', 'ascending')) index_mapper = GridMapper(range=DataRange2D(index)) color_source = ImageData(data=np.ones(shape=(5, 5)), depth=1) self.plot = CMapImagePlot( index=index, index_mapper=index_mapper, value=color_source, ) self.databox = DataBox( component=self.plot, data_position=[0, 0], ) self.plot.overlays.append(self.databox)
def test_redraw_on_color_mapper_update(self): # regression check for https://github.com/enthought/chaco/issues/220 npoints = 200 xs = numpy.linspace(-2 * numpy.pi, +2 * numpy.pi, npoints) ys = numpy.linspace(-1.5 * numpy.pi, +1.5 * numpy.pi, npoints) x, y = numpy.meshgrid(xs, ys) z = y * x index = GridDataSource(xdata=xs, ydata=ys) index_mapper = GridMapper(range=DataRange2D(index)) color_source = ImageData(data=z, value_depth=1) color_mapper = Spectral(DataRange1D(color_source)) cmap_plot = CMapImagePlot( index=index, index_mapper=index_mapper, value=color_source, value_mapper=color_mapper, ) cmap_plot._window = window = mock.Mock(spec=AbstractWindow) #when cmap_plot.color_mapper.updated = True # Then window.redraw.assert_called_once_with()
def rendered_image_result(image, filename=None, **plot_kwargs): data_source = ImageData(data=image) index, index_mapper = get_image_index_and_mapper(image) renderer = ImagePlot(value=data_source, index=index, index_mapper=index_mapper, **plot_kwargs) orientation = plot_kwargs.get('orientation', 'h') return image_from_renderer(renderer, orientation)
def create_plot(self): # Create the mapper, etc self._image_index = GridDataSource(array([]), array([]), sort_order=("ascending", "ascending")) image_index_range = DataRange2D(self._image_index) # self._image_index.on_trait_change(self._metadata_changed, # "metadata_changed") self._image_value = ImageData(data=array([]), value_depth=1) image_value_range = DataRange1D(self._image_value) # Create the colormapped scalar plot self.plot = CMapImagePlot( index=self._image_index, index_mapper=GridMapper(range=image_index_range), value=self._image_value, value_mapper=self._cmap(image_value_range)) # Add a left axis to the plot left = PlotAxis(orientation='left', title="y", mapper=self.plot.index_mapper._ymapper, component=self.plot) self.plot.overlays.append(left) # Add a bottom axis to the plot bottom = PlotAxis(orientation='bottom', title="x", mapper=self.plot.index_mapper._xmapper, component=self.plot) self.plot.overlays.append(bottom) # Add some tools to the plot self.plot.tools.append(PanTool(self.plot, constrain_key="shift")) self.plot.overlays.append( ZoomTool(component=self.plot, tool_mode="box", always_on=False)) # Create a colorbar cbar_index_mapper = LinearMapper(range=image_value_range) self.colorbar = ColorBar(index_mapper=cbar_index_mapper, plot=self.plot, padding_top=self.plot.padding_top, padding_bottom=self.plot.padding_bottom, padding_right=40, resizable='v', width=10) # Create a container and add components self.container = HPlotContainer(padding=40, fill_padding=True, bgcolor="white", use_backbuffer=False) self.container.add(self.colorbar) self.container.add(self.plot)
def set_pict(self): pd = self.plot_data if not pd: return try: imgd = ImageData.fromfile(self.pict)._data[::-1] except: imgd = ImageData() imgd.set_data(255 * ones((2, 2, 3), dtype='uint8')) imgd = imgd._data pd.set_data("image", imgd)
def _corr_plot_default(self): diag = self.covar.diagonal() corr = self.covar / np.sqrt(np.outer(diag, diag)) N = len(diag) value_range = DataRange1D(low=-1, high=1) color_mapper = cmap(range=value_range) index = GridDataSource() value = ImageData() mapper = GridMapper(range=DataRange2D(index), y_low_pos=1.0, y_high_pos=0.0) index.set_data(xdata=np.arange(-0.5, N), ydata=np.arange(-0.5, N)) value.set_data(np.flipud(corr)) self.corr_data = value cmap_plot = CMapImagePlot(index=index, index_mapper=mapper, value=value, value_mapper=color_mapper, padding=(40, 40, 100, 40)) yaxis = PlotAxis( cmap_plot, orientation='left', tick_interval=1, tick_label_formatter=lambda x: self.header[int(N - 1 - x)], tick_generator=ShowAllTickGenerator(positions=np.arange(N))) xaxis = PlotAxis( cmap_plot, orientation='top', tick_interval=1, tick_label_formatter=lambda x: self.header[int(x)], tick_label_alignment='edge', tick_generator=ShowAllTickGenerator(positions=np.arange(N))) cmap_plot.overlays.append(yaxis) cmap_plot.overlays.append(xaxis) colorbar = ColorBar( index_mapper=LinearMapper(range=cmap_plot.value_range), plot=cmap_plot, orientation='v', resizable='v', width=10, padding=(40, 5, 100, 40)) container = HPlotContainer(bgcolor='transparent') container.add(cmap_plot) container.add(colorbar) return container
def image_histogram_plot_component(self): xs = np.arange(0, len(self.im)) ys = np.arange(0, len(self.im[0])) index = GridDataSource(xdata=xs, ydata=ys, sort_order=('ascending', 'ascending')) index_mapper = GridMapper(range=DataRange2D(index)) color_source = ImageData(data=np.flipud(self.im), value_depth=1) reversed_grays = reverse(Greys) color_mapper = reversed_grays(DataRange1D(color_source)) plot = CMapImagePlot( index=index, index_mapper=index_mapper, value=color_source, value_mapper=color_mapper, ) #: Add overlay for zoom data_box_overlay = MyDataBox( component=plot, data_position=[0, 0], data_bounds=self.data_bounds, ) move_tool = MoveTool(component=data_box_overlay) resize_tool = ResizeTool(component=data_box_overlay) data_box_overlay.tools.append(move_tool) data_box_overlay.tools.append(resize_tool) data_box_overlay.on_trait_change(self.update_position, 'position') data_box_overlay.on_trait_change(self.update_data_bounds, 'bounds') #: Add to plot plot.overlays.append(data_box_overlay) return plot
def image_histogram_plot_component(self): xs = np.arange(0, len(self.im)) ys = np.arange(0, len(self.im[0])) index = GridDataSource(xdata=xs, ydata=ys, sort_order=('ascending', 'ascending')) index_mapper = GridMapper(range=DataRange2D(index)) color_source = ImageData(data=self.im, value_depth=1) reversed_grays = reverse(Greys) color_mapper = reversed_grays(DataRange1D(color_source)) plot = CMapImagePlot( index=index, index_mapper=index_mapper, value=color_source, value_mapper=color_mapper, orientation='h', origin='top left', ) self.data_box_overlay = DataBox( component=plot, data_position=[0, 0], data_bounds=[self.my_data_bounds, self.my_data_bounds], ) move_tool = MoveTool(component=self.data_box_overlay) self.data_box_overlay.tools.append(move_tool) self.data_box_overlay.on_trait_change(self.update_my_position, 'position') #: Add to plot plot.overlays.append(self.data_box_overlay) return plot
def test_get_width_transposed(self): myarray = arange(15).reshape(5, 3) data_source = ImageData(data=myarray, transposed=True) self.assertEqual(5, data_source.get_width())
def test_data_size_no_data(self): data_source = ImageData() self.assertEqual(0, data_source.get_size())
def test_bounds_empty(self): data_source = ImageData() bounds = data_source.get_bounds() self.assertEqual(bounds, (0, 0))
def test_get_data_mask_no_data(self): data_source = ImageData() # XXX this is probably not the right thing with self.assertRaises(NotImplementedError): data, mask = data_source.get_data_mask()
def test_get_data_transposed(self): myarray = arange(15).reshape(5, 3, 1) data_source = ImageData(data=myarray, transposed=True) assert_array_equal(swapaxes(myarray, 0, 1), data_source.get_data())
def test_get_data_no_data(self): data_source = ImageData() self.assertIsNone(data_source.get_data())
def __init__(self, x, y, z): super(ImagePlot, self).__init__() self.pd_all = ArrayPlotData(imagedata=z) #self.pd_horiz = ArrayPlotData(x=x, horiz=z[4, :]) #self.pd_vert = ArrayPlotData(y=y, vert=z[:,5]) self._imag_index = GridDataSource(xdata=x, ydata=y, sort_order=("ascending", "ascending")) index_mapper = GridMapper(range=DataRange2D(self._imag_index)) self._imag_index.on_trait_change(self._metadata_changed, "metadata_changed") self._image_value = ImageData(data=z, value_depth=1) color_mapper = jet(DataRange1D(self._image_value)) self.color_plot = CMapImagePlot(index=self._imag_index, index_mapper=index_mapper, value=self._image_value, value_mapper=color_mapper, padding=20, use_backbuffer=True, unified_draw=True) #Add axes to image plot left = PlotAxis(orientation='left', title="Frequency (GHz)", mapper=self.color_plot.index_mapper._ymapper, component=self.color_plot) self.color_plot.overlays.append(left) bottom = PlotAxis(orientation='bottom', title="Time (us)", mapper=self.color_plot.index_mapper._xmapper, component=self.color_plot) self.color_plot.overlays.append(bottom) self.color_plot.tools.append( PanTool(self.color_plot, constrain_key="shift")) self.color_plot.overlays.append( ZoomTool(component=self.color_plot, tool_mode="box", always_on=False)) #Add line inspector tool for horizontal and vertical self.color_plot.overlays.append( LineInspector(component=self.color_plot, axis='index_x', inspect_mode="indexed", write_metadata=True, is_listener=True, color="white")) self.color_plot.overlays.append( LineInspector(component=self.color_plot, axis='index_y', inspect_mode="indexed", write_metadata=True, color="white", is_listener=True)) myrange = DataRange1D(low=amin(z), high=amax(z)) cmap = jet self.colormap = cmap(myrange) # Create a colorbar cbar_index_mapper = LinearMapper(range=myrange) self.colorbar = ColorBar(index_mapper=cbar_index_mapper, plot=self.color_plot, padding_top=self.color_plot.padding_top, padding_bottom=self.color_plot.padding_bottom, padding_right=40, resizable='v', width=30) #, ytitle="Magvec (mV)") #create horizontal line plot self.horiz_cross_plot = Plot(self.pd_horiz, resizable="h") self.horiz_cross_plot.height = 100 self.horiz_cross_plot.padding = 20 self.horiz_cross_plot.plot(("x", "horiz")) #, #line_style="dot") # self.cross_plot.plot(("scatter_index","scatter_value","scatter_color"), # type="cmap_scatter", # name="dot", # color_mapper=self._cmap(image_value_range), # marker="circle", # marker_size=8) self.horiz_cross_plot.index_range = self.color_plot.index_range.x_range #create vertical line plot self.vert_cross_plot = Plot(self.pd_vert, width=140, orientation="v", resizable="v", padding=20, padding_bottom=160) self.vert_cross_plot.plot(("y", "vert")) #, # line_style="dot") # self.vert_cross_plot.xtitle="Magvec (mV)" # self.vertica_cross_plot.plot(("vertical_scatter_index", # "vertical_scatter_value", # "vertical_scatter_color"), # type="cmap_scatter", # name="dot", # color_mapper=self._cmap(image_value_range), # marker="circle", # marker_size=8) self.vert_cross_plot.index_range = self.color_plot.index_range.y_range # Create a container and add components self.container = HPlotContainer(padding=40, fill_padding=True, bgcolor="white", use_backbuffer=False) inner_cont = VPlotContainer(padding=0, use_backbuffer=True) inner_cont.add(self.horiz_cross_plot) inner_cont.add(self.color_plot) self.container.add(self.colorbar) self.container.add(inner_cont) self.container.add(self.vert_cross_plot)
def setUp(self): self.myarray = arange(15).reshape(5, 3, 1) self.data_source = ImageData(data=self.myarray)
def test_array_bounds_transposed(self): myarray = arange(15).reshape(5, 3, 1) data_source = ImageData(data=myarray, transposed=True) self.assertEqual(((0, 5), (0, 3)), data_source.get_array_bounds())
def _plot2(self): print"...plotting line scans" title = str(self.plotE['plot']) + str(self.plotE["notes"]["start"]) self.plotdata5 = ArrayPlotData(imagedata = self.plotE['data']) self._image_index = GridDataSource(array([]), array([]), sort_order=("ascending","ascending")) self.xs = linspace(self.plotE["range"][0][0], self.plotE["range"][0][1], self.plotE["shape"][0]) self.ys = linspace(self.plotE["range"][1][0], self.plotE["range"][1][1], self.plotE["shape"][1]) self._image_index.set_data(self.xs, self.ys) image_index_range = DataRange2D(self._image_index) self._image_value = ImageData(data=array([]), value_depth=1) self._image_value.data = self.plotE['data'] image_value_range = DataRange1D(self._image_value) s = "" f = "" if self.x_s: s = "X" if self.y_s: s = "Y" if self.z_s: s = "Z" if self.x_f: f = "X" if self.y_f: f = "Y" if self.z_f: f = "Z" self.plot1lines = Plot(self.plotdata5, title = title) self.plot1lines.img_plot("imagedata", xbounds = (self.plotE["range"][0][0],self.plotE["range"][0][1]), ybounds = (self.plotE["range"][1][0],self.plotE["range"][1][1]), colormap=jet) img_plot = self.plot1lines.img_plot("imagedata")[0] imgtool = ImageInspectorTool(img_plot) img_plot.tools.append(imgtool) overlay = ImageInspectorOverlay(component=img_plot, image_inspector=imgtool, bgcolor="white", border_visible=True) self.plot1lines.overlays.append(overlay) ##ADD TOOLS self.plot1lines.tools.append(PanTool(self.plot1lines)) zoom1 = ZoomTool(component=self.plot1lines, tool_mode="box", always_on=False) self.plot1lines.overlays.append(zoom1) self.plot1lines.overlays.append(LineInspector(component=self.plot1lines, axis='index_x', inspect_mode="indexed", write_metadata=True, is_listener=False, #constrain_key="right", color="white")) self.plot1lines.overlays.append(LineInspector(component=self.plot1lines, axis='index_y', inspect_mode="indexed", write_metadata=True, color="white", is_listener=False)) ##ADD COLORBAR self.colorbar5 = ColorBar(index_mapper=LinearMapper(range=self.plot1lines.color_mapper.range), color_mapper=self.plot1lines.color_mapper, orientation='v', resizable='v', width=20, padding=5) self.colorbar5.plot = self.plot1lines self.colorbar5.tools.append(PanTool(self.colorbar5, constrain_direction="y", constrain=True)) self.zoom_overlay5 = ZoomTool(self.colorbar5, axis="index", tool_mode="range", always_on=True, drag_button="right") self.colorbar5.overlays.append(self.zoom_overlay5) self.pd = ArrayPlotData(line_index = array([]), line_value = array([])) self.slow_plot = Plot(self.pd, title = "Slowline : " + self.slowline) self.slow_plot.plot(("line_index", "line_value"), line_style='solid') self.pd.set_data("line_index2", array([])) self.pd.set_data("line_value2", array([])) self.fast_plot = Plot(self.pd, title = "Fastline : " + self.fastline) self.fast_plot.plot(("line_index2", "line_value2"), line_style='solid') self.pd.set_data("line_index", self.xs) self.pd.set_data("line_index2", self.ys) self.pd.set_data("line_value", self._image_value.data[self.fastscanline,:]) self.pd.set_data("line_value2", self._image_value.data[:,self.slowscanline]) self.colorbar5.padding= 0 self.colorbar5.padding_left = 15 #self.colorbar5.height = 400 self.colorbar5.padding_top =50 self.colorbar5.padding_bottom = 0 self.colorbar5.padding_right = 25 self.colorbar5.padding_left = 50 self.plot1lines.width = 300 self.plot1lines.padding_top = 50 self.plot1lines.index_axis.title = 'fast axis (um)' self.plot1lines.value_axis.title = 'slow axis (um)' self.slow_plot.width = 100 self.slow_plot.padding_right = 20 self.fast_plot.width = 100 self.fast_plot.padding_right = 20 self.container2 = GridPlotContainer(shape = (1,2), spacing = ((0,0)), use_backbuffer=True, valign = 'top', halign = 'center', bgcolor = 'white') self.container3 = GridPlotContainer(shape = (2,1), spacing = (0,0), use_backbuffer=True, valign = 'top', halign = 'center', bgcolor = 'grey') self.container4 = GridPlotContainer(shape = (1,2), spacing = (0,0), use_backbuffer=True, valign = 'top', halign = 'center', bgcolor = 'grey') self.container2.add(self.colorbar5) self.container3.add(self.fast_plot) self.container3.add(self.slow_plot) self.container4.add(self.container3) self.container4.add(self.plot1lines) self.container2.add(self.container4) self.LineScans = self.container2 self._readline_fired() self._scale_set_fired()
def create_plot(self): # Create the mapper, etc self._image_index = GridDataSource(array([]), array([]), sort_order=("ascending","ascending")) image_index_range = DataRange2D(self._image_index) self._image_index.on_trait_change(self._metadata_changed, "metadata_changed") self._image_value = ImageData(data=array([]), value_depth=1) image_value_range = DataRange1D(self._image_value) # Create the contour plots self.polyplot = ContourPolyPlot(index=self._image_index, value=self._image_value, index_mapper=GridMapper(range= image_index_range), color_mapper=\ self._cmap(image_value_range), levels=self.num_levels) self.lineplot = ContourLinePlot(index=self._image_index, value=self._image_value, index_mapper=GridMapper(range= self.polyplot.index_mapper.range), levels=self.num_levels) # Add a left axis to the plot left = PlotAxis(orientation='left', title= "y", mapper=self.polyplot.index_mapper._ymapper, component=self.polyplot) self.polyplot.overlays.append(left) # Add a bottom axis to the plot bottom = PlotAxis(orientation='bottom', title= "x", mapper=self.polyplot.index_mapper._xmapper, component=self.polyplot) self.polyplot.overlays.append(bottom) # Add some tools to the plot self.polyplot.tools.append(PanTool(self.polyplot, constrain_key="shift")) self.polyplot.overlays.append(ZoomTool(component=self.polyplot, tool_mode="box", always_on=False)) self.polyplot.overlays.append(LineInspector(component=self.polyplot, axis='index_x', inspect_mode="indexed", write_metadata=True, is_listener=True, color="white")) self.polyplot.overlays.append(LineInspector(component=self.polyplot, axis='index_y', inspect_mode="indexed", write_metadata=True, color="white", is_listener=True)) # Add these two plots to one container contour_container = OverlayPlotContainer(padding=20, use_backbuffer=True, unified_draw=True) contour_container.add(self.polyplot) contour_container.add(self.lineplot) # Create a colorbar cbar_index_mapper = LinearMapper(range=image_value_range) self.colorbar = ColorBar(index_mapper=cbar_index_mapper, plot=self.polyplot, padding_top=self.polyplot.padding_top, padding_bottom=self.polyplot.padding_bottom, padding_right=40, resizable='v', width=30) self.pd = ArrayPlotData(line_index = array([]), line_value = array([]), scatter_index = array([]), scatter_value = array([]), scatter_color = array([])) self.cross_plot = Plot(self.pd, resizable="h") self.cross_plot.height = 100 self.cross_plot.padding = 20 self.cross_plot.plot(("line_index", "line_value"), line_style="dot") self.cross_plot.plot(("scatter_index","scatter_value","scatter_color"), type="cmap_scatter", name="dot", color_mapper=self._cmap(image_value_range), marker="circle", marker_size=8) self.cross_plot.index_range = self.polyplot.index_range.x_range self.pd.set_data("line_index2", array([])) self.pd.set_data("line_value2", array([])) self.pd.set_data("scatter_index2", array([])) self.pd.set_data("scatter_value2", array([])) self.pd.set_data("scatter_color2", array([])) self.cross_plot2 = Plot(self.pd, width = 140, orientation="v", resizable="v", padding=20, padding_bottom=160) self.cross_plot2.plot(("line_index2", "line_value2"), line_style="dot") self.cross_plot2.plot(("scatter_index2","scatter_value2","scatter_color2"), type="cmap_scatter", name="dot", color_mapper=self._cmap(image_value_range), marker="circle", marker_size=8) self.cross_plot2.index_range = self.polyplot.index_range.y_range # Create a container and add components self.container = HPlotContainer(padding=40, fill_padding=True, bgcolor = "white", use_backbuffer=False) inner_cont = VPlotContainer(padding=0, use_backbuffer=True) inner_cont.add(self.cross_plot) inner_cont.add(contour_container) self.container.add(self.colorbar) self.container.add(inner_cont) self.container.add(self.cross_plot2)
def _plot_data_default(self): return ImageData(data=BLANK_IMG)
def test_init_defaults(self): data_source = ImageData() assert_array_equal(data_source.data, [])
def test_get_height_transposed(self): myarray = arange(15).reshape(5, 3, 1) data_source = ImageData(data=myarray, transposed=True) self.assertEqual(3, data_source.get_height())
def create_plot_component(self): if not self.data.size: return self.pd = ArrayPlotData() self.shape = self.data.shape self.pd.set_data("imagedata", self.data) self.pd.set_data("left_line", self.data[:, self.shape[0]//2]) self.pd.set_data("top_line", self.data[self.shape[1]//2,:]) plot = Plot(self.pd) cmap = default_colormaps.color_map_name_dict[self.colormap] if self.rev_cmap: cmap = default_colormaps.reverse(cmap) drange = DataRange1D(ImageData(data=self.data, value_depth=1)) self.ccmap = cmap_constant_range(cmap, drange)(drange) #from copy import copy self.img_plot = plot.img_plot("imagedata", colormap=cmap, #xbounds=self.xbounds, #ybounds=self.ybounds, )[0] self.cmap = self.img_plot.value_mapper if not self.autoscale: self.img_plot.value_mapper = self.ccmap # Tweak some of the plot properties plot.title = self.title plot.padding = 10 # Attach some tools to the plot plot.tools.append(PanTool(plot)) zoom = ZoomTool(component=plot, tool_mode="box", always_on=False) plot.overlays.append(zoom) csr = CursorTool(self.img_plot, drag_button='right', color='white', line_width=2.0 ) self.cursor = csr csr.current_index = self.shape[0]//2, self.shape[1]//2 self.img_plot.overlays.append(csr) imgtool = ImageInspectorTool(self.img_plot) self.img_plot.tools.append(imgtool) overlay = ImageInspectorOverlay(component=self.img_plot, image_inspector=imgtool, bgcolor="white", border_visible=True) self.img_plot.overlays.append(overlay) self.plot = plot self.cross_plot = Plot(self.pd,resizable='h') self.cross_plot.height = 40 self.cross_plot.padding = 15 self.cross_plot.plot("top_line", line_style="dot") self.cross_plot.index_range = self.img_plot.index_range.x_range self.cross_plot2 = Plot(self.pd, width=40, orientation="v", padding=15, padding_bottom=10, resizable='v') self.cross_plot2.plot("left_line", line_style="dot") self.cross_plot2.index_range = self.img_plot.index_range.y_range # Create a container and add components #self.container = HPlotContainer(padding=10, fill_padding=False, # bgcolor="none", use_backbuffer=False) #inner_cont = VPlotContainer(padding=0, use_backbuffer=True, bgcolor="none") #inner_cont.add(self.plot) #inner_cont.add(self.cross_plot) self.container = GridPlotContainer(padding=20, fill_padding=False, bgcolor="none", use_backbuffer=True, shape=(2, 2), spacing=(12, 20)) #self.container.add(self.colorbar) self.container.add(self.plot) self.container.add(self.cross_plot2) self.container.add(self.cross_plot)