Chaco: Get Index and Value out of a chaco plot

Question

I'm working on a program that has two plots next to each other. The first plot has a ZoomTool, a PanTool and a RangeSelection tool. The second plot should be modified according to the changes (zooming, etc.) made in the left plot.

Is there a possibility to get the new index and value after zooming? And how do I get the new index range after doing a rangeselection? This index schould also be the new index of the right plot until the selected part is no longer selected.

I will post my code below this text but you can also see it here

Here is my code:

#=================================================
# Code
#=================================================

# Enthought library imports
from traits.api import HasTraits, Int, Instance
from traits.api import *
from traitsui.api import Item, View, Group, HGroup, VGroup
from enable.api import Component
from enable.component_editor import ComponentEditor
from traitsui.menu import OKButton, CancelButton
# Chaco imports
from chaco.tools.api import RangeSelection, RangeSelectionOverlay
from chaco.chaco_plot_editor import ChacoPlotEditor, ChacoPlotItem
from chaco.api import Plot, ArrayPlotData, OverlayPlotContainer, create_line_plot, create_scatter_plot, add_default_axes, add_default_grids, PlotAxis, PlotLabel
from chaco.tools.api import PanTool, BroadcasterTool, ZoomTool
# Numpy imports
from numpy import linspace, pi, sin, tan

def main():
    # normally this function gets its values out of other files
    x1 = -2*pi
    x2 = pi
    y1 = 0
    y2 = 2
    uebergabe = {"xlim":[x1,x2], "ylim":[y1,y2], "ranges":[x1,x2]}
    return uebergabe


class Trait(HasTraits):
    plot = Instance(Component)    

    #creates the container
    container = OverlayPlotContainer(padding = 50, fill_padding = True,
                        bgcolor = "lightgray", use_backbuffer=True)
    container2 = OverlayPlotContainer(padding = 50, fill_padding = True,
                        bgcolor = "lightgray", use_backbuffer=True)

    # Traits
    xmin = Float
    xmax = Float
    ymin = Float
    ymax = Float
    rangeXMin = Float
    rangeXMax = Float

    # TraitsUI view
    traits_view = View(Group(
        HGroup(
            VGroup(Item("container", editor = ComponentEditor(), show_label = False)),
            VGroup(Item("container2", editor = ComponentEditor(), show_label = False))),        
        HGroup(Item("xmin"), Item("xmax"), Item("ymin"), Item("ymax"), show_border = True, label = "Plotborders"),
        HGroup(Item("rangeXMin", label="x_min"), Item("rangeXMax", label="x_max"), show_border = True, label="Range of right plot")), 
        buttons = [OKButton, CancelButton], resizable = True, width = 1000, height = 800)

    # Constructor
    def __init__(self):
        super(Trait, self).__init__()

        uebergabe = main()

        # initialize traits
        self.xmin = uebergabe["xlim"][0]
        self.xmax = uebergabe["xlim"][1]
        self.ymin = uebergabe["ylim"][0]
        self.ymax = uebergabe["ylim"][1]
        self.rangeXMin = uebergabe["ranges"][0]
        self.rangeXMin = uebergabe["ranges"][1]


        self._create_Container()


    def _create_Container(self):

        #creating dict of plots and the broadcaster
        plots = {}
        broadcaster = BroadcasterTool()

        #=====================first container===========================

        #first plot
        index = linspace(-2*pi,2*pi,1000)
        plot = create_line_plot((index, sin(index)+0.5), color = "blue", index_bounds=(self.xmin, self.xmax), value_bounds = (self.ymin, self.ymax))
        plot.bgcolor = "white"
        plot.border_visible = True
        value_mapper = plot.value_mapper
        index_mapper = plot.index_mapper
        add_default_grids(plot)
        add_default_axes(plot)

        # range selection
        self.rangeselect = RangeSelection(plot, left_button_selects = False, auto_handle_event = False)
        plot.active_tool = self.rangeselect
        plot.overlays.append(RangeSelectionOverlay(component=plot))

        #adds plot to the container
        self.container.add(plot)

        # second plot
        index2 = linspace(-5*pi,4*pi,1000)
        plot = create_line_plot((index2, tan(index2)), color = "black", index_bounds=(self.xmin, self.xmax), value_bounds = (self.ymin, self.ymax))
        plot.value_mapper = value_mapper
        value_mapper.range.add(plot.value)
        plot.index_mapper = index_mapper
        index_mapper.range.add(plot.index)

        # Create a pan tool and give it a reference to the plot
        pan = PanTool(plot, drag_button="left")
        broadcaster.tools.append(pan)

        # allows to zoom
        zoom = ZoomTool(plot, tool_mode="box", always_on = False, visible = True)
        plot.overlays.append(zoom)


        #adds plot to the container
        self.container.add(plot)

        # appends broadcaster to the container
        self.container.tools.append(broadcaster)

        # title of the container
        self.container.overlays.append(PlotLabel("left plot", component=self.container, overlay_position = "top"))

        #==============end of first container===========================

        #====================second container===========================

        #first plot2
        index3 = linspace(-10*pi,10*pi,500)
        plot2 = create_scatter_plot((index3, sin(index3)), color = "blue", index_bounds=(self.rangeXMin, self.rangeXMax), value_bounds = (self.ymin, self.ymax))
        plot2.bgcolor = "white"
        plot2.border_visible = True
        plot2.value_mapper = value_mapper # the plot uses the same index and
        plot2.index_mapper = index_mapper # value like the plots of container1
        #value_mapper.range.add(plot2.value)
        #index_mapper.range.add(plot2.index)
        add_default_grids(plot2)
        add_default_axes(plot2)

        #adds plot to the container
        self.container2.add(plot2)

        # title of the container
        self.container2.overlays.append(PlotLabel("right plot", component=self.container, overlay_position = "top"))

        #=============end of second container===========================
gui = Trait()
gui.configure_traits()

Answer 1

You can use sync_trait() to Synchronizes value between two traits:

self.sync_trait("xmin", index_mapper.range, "_low_value")
self.sync_trait("xmax", index_mapper.range, "_high_value")
self.sync_trait("ymin", value_mapper.range, "_low_value")
self.sync_trait("ymax", value_mapper.range, "_high_value")

self.sync_trait("rangeXMin", plot2.index_mapper.range, "low", False)
self.sync_trait("rangeXMax", plot2.index_mapper.range, "high", False)

To catch range selection changes:

self.rangeselect.on_trait_change(self.on_selection_changed, "selection")

def on_selection_changed(self, selection):
    if selection != None:
        self.rangeXMin, self.rangeXMax = selection

To catch axis range changes:

index_mapper.on_trait_change(self.on_mapper_updated, "updated")

def on_mapper_updated(self, mapper, name, value):
    if not self.rangeselect.selection:
        self.rangeXMin = mapper.range.low
        self.rangeXMax = mapper.range.high

Here is the full code:

# -*- coding: utf-8 -*-
#=================================================
# Code
#=================================================

# Enthought library imports
from traits.api import HasTraits, Int, Instance
from traits.api import *
from traitsui.api import Item, View, Group, HGroup, VGroup
from enable.api import Component
from enable.component_editor import ComponentEditor
from traitsui.menu import OKButton, CancelButton
# Chaco imports
from chaco.tools.api import RangeSelection, RangeSelectionOverlay
from chaco.chaco_plot_editor import ChacoPlotEditor, ChacoPlotItem
from chaco.api import Plot, ArrayPlotData, OverlayPlotContainer, create_line_plot, create_scatter_plot, add_default_axes, add_default_grids, PlotAxis, PlotLabel
from chaco.tools.api import PanTool, BroadcasterTool, ZoomTool
# Numpy imports
from numpy import linspace, pi, sin, tan

def main():
    # normally this function gets its values out of other files
    x1 = -2*pi
    x2 = pi
    y1 = 0
    y2 = 2
    uebergabe = {"xlim":[x1,x2], "ylim":[y1,y2], "ranges":[x1,x2]}
    return uebergabe


class Trait(HasTraits):
    plot = Instance(Component)    

    #creates the container
    container = OverlayPlotContainer(padding = 50, fill_padding = True,
                        bgcolor = "lightgray", use_backbuffer=True)
    container2 = OverlayPlotContainer(padding = 50, fill_padding = True,
                        bgcolor = "lightgray", use_backbuffer=True)

    # Traits
    xmin = Float
    xmax = Float
    ymin = Float
    ymax = Float
    rangeXMin = Float
    rangeXMax = Float

    # TraitsUI view
    traits_view = View(Group(
        HGroup(
            VGroup(Item("container", editor = ComponentEditor(), show_label = False)),
            VGroup(Item("container2", editor = ComponentEditor(), show_label = False))),        
        HGroup(Item("xmin"), Item("xmax"), Item("ymin"), Item("ymax"), show_border = True, label = "Plotborders"),
        HGroup(Item("rangeXMin", label="x_min"), Item("rangeXMax", label="x_max"), show_border = True, label="Range of right plot")), 
        buttons = [OKButton, CancelButton], resizable = True, width = 1000, height = 500)

    # Constructor
    def __init__(self):
        super(Trait, self).__init__()

        uebergabe = main()

        # initialize traits
        self.xmin = uebergabe["xlim"][0]
        self.xmax = uebergabe["xlim"][1]
        self.ymin = uebergabe["ylim"][0]
        self.ymax = uebergabe["ylim"][1]
        self.rangeXMin = uebergabe["ranges"][0]
        self.rangeXMin = uebergabe["ranges"][1]


        self._create_Container()


    def _create_Container(self):

        #creating dict of plots and the broadcaster
        plots = {}
        broadcaster = BroadcasterTool()

        #=====================first container===========================

        #first plot
        index = linspace(-2*pi,2*pi,1000)
        plot = create_line_plot((index, sin(index)+0.5), color = "blue", index_bounds=(self.xmin, self.xmax), value_bounds = (self.ymin, self.ymax))
        plot.bgcolor = "white"
        plot.border_visible = True
        value_mapper = plot.value_mapper
        index_mapper = plot.index_mapper
        add_default_grids(plot)
        add_default_axes(plot)

        self.sync_trait("xmin", index_mapper.range, "_low_value")
        self.sync_trait("xmax", index_mapper.range, "_high_value")
        self.sync_trait("ymin", value_mapper.range, "_low_value")
        self.sync_trait("ymax", value_mapper.range, "_high_value")

        # range selection
        self.rangeselect = RangeSelection(plot, left_button_selects = False, auto_handle_event = False)
        plot.active_tool = self.rangeselect
        plot.overlays.append(RangeSelectionOverlay(component=plot))
        self.rangeselect.on_trait_change(self.on_selection_changed, "selection")

        #adds plot to the container
        self.container.add(plot)

        # second plot
        index2 = linspace(-5*pi,4*pi,1000)
        plot = create_line_plot((index2, tan(index2)), color = "black", index_bounds=(self.xmin, self.xmax), value_bounds = (self.ymin, self.ymax))
        plot.value_mapper = value_mapper
        value_mapper.range.add(plot.value)
        plot.index_mapper = index_mapper
        index_mapper.range.add(plot.index)

        # Create a pan tool and give it a reference to the plot
        pan = PanTool(plot, drag_button="left")
        broadcaster.tools.append(pan)

        # allows to zoom
        zoom = ZoomTool(plot, tool_mode="box", always_on = False, visible = True)
        plot.overlays.append(zoom)


        #adds plot to the container
        self.container.add(plot)

        # appends broadcaster to the container
        self.container.tools.append(broadcaster)

        # title of the container
        self.container.overlays.append(PlotLabel("left plot", component=self.container, overlay_position = "top"))

        #==============end of first container===========================

        #====================second container===========================

        #first plot2
        index3 = linspace(-10*pi,10*pi,500)
        plot2 = create_scatter_plot((index3, sin(index3)), color = "blue", index_bounds=(self.rangeXMin, self.rangeXMax), value_bounds = (self.ymin, self.ymax))
        plot2.bgcolor = "white"
        plot2.border_visible = True
        plot2.value_mapper = value_mapper # the plot uses the same index and
        #plot2.index_mapper = index_mapper # value like the plots of container1
        self.sync_trait("rangeXMin", plot2.index_mapper.range, "low", False)
        self.sync_trait("rangeXMax", plot2.index_mapper.range, "high", False)


        plot2.index_mapper.range.low = 0
        plot2.index_mapper.range.high = 2        
        #value_mapper.range.add(plot2.value)
        #index_mapper.range.add(plot2.index)
        add_default_grids(plot2)
        add_default_axes(plot2)

        #adds plot to the container
        self.container2.add(plot2)

        # title of the container
        self.container2.overlays.append(PlotLabel("right plot", component=self.container, overlay_position = "top"))

        index_mapper.on_trait_change(self.on_mapper_updated, "updated")

        #=============end of second container===========================

    def on_mapper_updated(self, mapper, name, value):
        if not self.rangeselect.selection:
            self.rangeXMin = mapper.range.low
            self.rangeXMax = mapper.range.high

    def on_selection_changed(self, selection):
        if selection != None:
            self.rangeXMin, self.rangeXMax = selection

gui = Trait()
gui.configure_traits()

Answer 2

I believe there is a simpler way to do what you want: each Plot object has a range2d attribute. If the set the second range2d to be pointing to the range2d of the first plot, you have done the job with half a line. Here is a complete example:

class ConnectedRange(HasTraits):
    container = Instance(HPlotContainer)
    traits_view = View(Item('container', editor=ComponentEditor(),
                       show_label=False),
                      width=1000, height=600, resizable=True, title="Connected Range")

    def _container_default(self):
        x = linspace(-14, 14, 100)
        y = sin(x) * x**3
        plotdata = ArrayPlotData(x = x, y = y)
        scatter = Plot(plotdata)
        scatter.plot(("x", "y"), type="scatter", color="blue") 
        line = Plot(plotdata)
        line.plot(("x", "y"), type="line", color="blue")

        scatter.tools.append(PanTool(scatter)) 
        scatter.tools.append(ZoomTool(scatter))
        line.tools.append(PanTool(line)) 
        line.tools.append(ZoomTool(line))

        # connect the ranges so that zooming in one zooms in the other
        scatter.range2d = line.range2d
        return HPlotContainer(scatter, line)