class MyPlot(HasTraits): """ Displays a plot with a few buttons to control which overlay to display """ plot = Instance(Plot) traits_view = View(Item('plot', editor=ComponentEditor(), show_label=False), resizable=True) def __init__(self, x_index, y_index, data, **kw): super(MyPlot, self).__init__(**kw) # Create the data source for the MultiLinePlot. ds = MultiArrayDataSource(data=data) xs = ArrayDataSource(x_index, sort_order='ascending') xrange = DataRange1D() xrange.add(xs) ys = ArrayDataSource(y_index, sort_order='ascending') yrange = DataRange1D() yrange.add(ys) mlp = MultiLinePlot( index = xs, yindex = ys, index_mapper = LinearMapper(range=xrange), value_mapper = LinearMapper(range=yrange), value=ds, global_max = data.max(), global_min = data.min(), **kw) self.plot = Plot() self.plot.add(mlp)
def _create_plot_component(obj): # Setup the spectrum plot frequencies = linspace(0.0, float(SAMPLING_RATE)/2, num=NUM_SAMPLES/2) obj.spectrum_data = ArrayPlotData(frequency=frequencies) empty_amplitude = zeros(NUM_SAMPLES/2) obj.spectrum_data.set_data('amplitude', empty_amplitude) obj.spectrum_plot = Plot(obj.spectrum_data) spec_renderer = obj.spectrum_plot.plot(("frequency", "amplitude"), name="Spectrum", color="red")[0] obj.spectrum_plot.padding = 50 obj.spectrum_plot.title = "Spectrum" spec_range = obj.spectrum_plot.plots.values()[0][0].value_mapper.range spec_range.low = 0.0 spec_range.high = 5.0 obj.spectrum_plot.index_axis.title = 'Frequency (hz)' obj.spectrum_plot.value_axis.title = 'Amplitude' # Time Series plot times = linspace(0.0, float(NUM_SAMPLES)/SAMPLING_RATE, num=NUM_SAMPLES) obj.time_data = ArrayPlotData(time=times) empty_amplitude = zeros(NUM_SAMPLES) obj.time_data.set_data('amplitude', empty_amplitude) obj.time_plot = Plot(obj.time_data) obj.time_plot.plot(("time", "amplitude"), name="Time", color="blue") obj.time_plot.padding = 50 obj.time_plot.title = "Time" obj.time_plot.index_axis.title = 'Time (seconds)' obj.time_plot.value_axis.title = 'Amplitude' time_range = obj.time_plot.plots.values()[0][0].value_mapper.range time_range.low = -0.2 time_range.high = 0.2 # Spectrogram plot values = [zeros(NUM_SAMPLES/2) for i in xrange(SPECTROGRAM_LENGTH)] p = WaterfallRenderer(index = spec_renderer.index, values = values, index_mapper = LinearMapper(range = obj.spectrum_plot.index_mapper.range), value_mapper = LinearMapper(range = DataRange1D(low=0, high=SPECTROGRAM_LENGTH)), y2_mapper = LinearMapper(low_pos=0, high_pos=8, range=DataRange1D(low=0, high=15)), ) spectrogram_plot = p obj.spectrogram_plot = p dummy = Plot() dummy.padding = 50 dummy.index_axis.mapper.range = p.index_mapper.range dummy.index_axis.title = "Frequency (hz)" dummy.add(p) container = HPlotContainer() container.add(obj.spectrum_plot) container.add(obj.time_plot) c2 = VPlotContainer() c2.add(dummy) c2.add(container) return c2
def __init__( self, **traits ): super( ParamController, self ).__init__( **traits ) p = self.rate_plot ( "rates" ) container = Plot() container.add( p ) self.plot = container
def _create_plot_component(): # Create some data numpts = 1000 x = numpy.arange(0, numpts) y = numpy.random.random(numpts) marker_size = numpy.random.normal(4.0, 4.0, numpts) # Create a plot data object and give it this data pd = ArrayPlotData() pd.set_data("index", x) pd.set_data("value", y) # Because this is a non-standard renderer, we can't call plot.plot, which # sets up the array data sources, mappers and default index/value ranges. # So, its gotta be done manually for now. index_ds = ArrayDataSource(x) value_ds = ArrayDataSource(y) # Create the plot plot = Plot(pd) plot.index_range.add(index_ds) plot.value_range.add(value_ds) # Create the index and value mappers using the plot data ranges imapper = LinearMapper(range=plot.index_range) vmapper = LinearMapper(range=plot.value_range) # Create the scatter renderer scatter = VariableSizeScatterPlot( index=index_ds, value=value_ds, index_mapper = imapper, value_mapper = vmapper, marker='circle', marker_size=marker_size, color=(1.0,0.0,0.75,0.4)) # Append the renderer to the list of the plot's plots plot.add(scatter) plot.plots['var_size_scatter'] = [scatter] # Tweak some of the plot properties plot.title = "Scatter Plot" plot.line_width = 0.5 plot.padding = 50 # Attach some tools to the plot plot.tools.append(PanTool(plot, constrain_key="shift")) zoom = ZoomTool(component=plot, tool_mode="box", always_on=False) plot.overlays.append(zoom) return plot
def _plot_default(self): """Create the Plot instance.""" plot = Plot(title="MultiLinePlot Demo") plot.add(self.multi_line_plot_renderer) x_axis = PlotAxis(component=plot, mapper=self.multi_line_plot_renderer.index_mapper, orientation='bottom', title='t (seconds)') y_axis = PlotAxis(component=plot, mapper=self.multi_line_plot_renderer.value_mapper, orientation='left', title='channel') plot.overlays.extend([x_axis, y_axis]) return plot
def _create_plot_component(): # Create some x-y data series to plot x = linspace(-2.0, 10.0, 100) pd = ArrayPlotData(index = x) for i in range(5): pd.set_data("y" + str(i), jn(i,x)) # Create some line plots of some of the data plot1 = Plot(pd) plot1.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="red") # Tweak some of the plot properties plot1.title = "My First Line Plot" plot1.padding = 50 plot1.padding_top = 75 plot1.legend.visible = True x = linspace(-5, 15.0, 100) y = jn(5, x) foreign_plot = create_line_plot((x,y), color=tuple(COLOR_PALETTE[0]), width=2.0) left, bottom = add_default_axes(foreign_plot) left.orientation = "right" bottom.orientation = "top" plot1.add(foreign_plot) # Attach some tools to the plot broadcaster = BroadcasterTool() broadcaster.tools.append(PanTool(plot1)) broadcaster.tools.append(PanTool(foreign_plot)) for c in (plot1, foreign_plot): zoom = ZoomTool(component=c, tool_mode="box", always_on=False) broadcaster.tools.append(zoom) plot1.tools.append(broadcaster) return plot1
def clone_plot(clonetool, drop_position): # A little sketchy... canvas = clonetool.component.container.component.component # Create a new Plot object oldplot = clonetool.component newplot = Plot(oldplot.data) basic_traits = ["orientation", "default_origin", "bgcolor", "border_color", "border_width", "border_visible", "draw_layer", "unified_draw", "fit_components", "fill_padding", "visible", "aspect_ratio", "title"] for attr in basic_traits: setattr(newplot, attr, getattr(oldplot, attr)) # copy the ranges dst = newplot.range2d src = oldplot.range2d #for attr in ('_low_setting', '_low_value', '_high_setting', '_high_value'): # setattr(dst, attr, getattr(src, attr)) dst._xrange.sources = copy(src._xrange.sources) dst._yrange.sources = copy(src._yrange.sources) newplot.padding = oldplot.padding newplot.bounds = oldplot.bounds[:] newplot.resizable = "" newplot.position = drop_position newplot.datasources = copy(oldplot.datasources) for name, renderers in oldplot.plots.items(): newrenderers = [] for renderer in renderers: new_r = clone_renderer(renderer) new_r.index_mapper = LinearMapper(range=newplot.index_range) new_r.value_mapper = LinearMapper(range=newplot.value_range) new_r._layout_needed = True new_r.invalidate_draw() new_r.resizable = "hv" newrenderers.append(new_r) newplot.plots[name] = newrenderers #newplot.plots = copy(oldplot.plots) for name, renderers in newplot.plots.items(): newplot.add(*renderers) newplot.index_axis.title = oldplot.index_axis.title newplot.index_axis.unified_draw = True newplot.value_axis.title = oldplot.value_axis.title newplot.value_axis.unified_draw = True # Add new tools to the new plot newplot.tools.append(AxisTool(component=newplot, range_controller=canvas.range_controller)) # Add tools to the new plot pan_traits = ["drag_button", "constrain", "constrain_key", "constrain_direction", "speed"] zoom_traits = ["tool_mode", "always_on", "axis", "enable_wheel", "drag_button", "wheel_zoom_step", "enter_zoom_key", "exit_zoom_key", "pointer", "color", "alpha", "border_color", "border_size", "disable_on_complete", "minimum_screen_delta", "max_zoom_in_factor", "max_zoom_out_factor"] move_traits = ["drag_button", "end_drag_on_leave", "cancel_keys", "capture_mouse", "modifier_key"] if not MULTITOUCH: for tool in oldplot.tools: if isinstance(tool, PanTool): newtool = tool.clone_traits(pan_traits) newtool.component = newplot break else: newtool = PanTool(newplot) # Reconfigure the pan tool to always use the left mouse, because we will # put plot move on the right mouse button newtool.drag_button = "left" newplot.tools.append(newtool) for tool in oldplot.tools: if isinstance(tool, MoveTool): newtool = tool.clone_traits(move_traits) newtool.component = newplot break else: newtool = MoveTool(newplot, drag_button="right") newplot.tools.append(newtool) for tool in oldplot.tools: if isinstance(tool, ZoomTool): newtool = tool.clone_traits(zoom_traits) newtool.component = newplot break else: newtool = ZoomTool(newplot) newplot.tools.append(newtool) else: pz = MPPanZoom(newplot) #pz.pan.constrain = True #pz.pan.constrain_direction = "x" #pz.zoom.mode = "range" #pz.zoom.axis = "index" newplot.tools.append(MPPanZoom(newplot)) #newplot.tools.append(MTMoveTool( newplot._layout_needed = True clonetool.dest.add(newplot) newplot.invalidate_draw() newplot.request_redraw() canvas.request_redraw() return