Chaco-获取多个数据系列以使用相同的轴和贴图 [英] Chaco - Getting multiple data series to use the same axes and maps

问题描述

我正在尝试在一个图上绘制多个数据集合.

I am trying to plot several collections of data on a single plot.

每个数据集都可以表示为x系列(索引)和几个y系列(值).每个数据集中x和y数据序列的范围可能不同.我想在一个绘图上显示多个这些数据集.但是，当我简单地将第二个绘图对象添加到第一个绘图对象(见下文)时，它为它创建了第二个轴，该轴嵌套在绘图内.

Each dataset can be represented as an x-series (index) and several y-series (values). The ranges of x and y data series may be different in each data set. I want to have several of these data sets display on one plot. However, when I simply add the second plot object to the first (see below) it makes a second axis for it that is nested inside the plot.

我希望两个图共享相同的轴，并希望更新轴范围以适合所有数据.实现此目标的最佳方法是什么?我正在努力在文档中找到与此相关的主题.

I want both plots to share the same axis and for the axis bounds to be updated to fit all the data. What is the best way to achieve this? I am struggling to find topics on this in the documentation.

感谢您的帮助.下面的代码突出了我的问题.

Thanks for your help. The code below highlights my problem.

# Major library imports
from numpy import linspace
from scipy.special import jn

from chaco.example_support import COLOR_PALETTE
# Enthought library imports
from enable.api import Component, ComponentEditor
from traits.api import HasTraits, Instance
from traitsui.api import Item, Group, View

# Chaco imports
from chaco.api import ArrayPlotData, Plot
from chaco.tools.api import BroadcasterTool, PanTool, ZoomTool
from chaco.api import create_line_plot, add_default_axes

def _create_plot_component():    
    # Create some x-y data series to plot
    x = linspace(-2.0, 10.0, 100)
    x2 =linspace(-5.0, 10.0, 100)

    pd = ArrayPlotData(index = x)
    for i in range(5):
        pd.set_data("y" + str(i), jn(i,x))

    #slightly different plot data
    pd2 =  ArrayPlotData(index = x2)
    for i in range(5):
        pd2.set_data("y" + str(i), 2*jn(i,x2))

    # 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

    plot2 = Plot(pd2)
    plot2.plot(("index", "y0", "y1"), name="j_n, n<3", color="green")

    plot1.add(plot2)
    # Attach some tools to the plot
    broadcaster = BroadcasterTool()
    broadcaster.tools.append(PanTool(plot1))
    broadcaster.tools.append(PanTool(plot2))

    for c in (plot1, plot2):
        zoom = ZoomTool(component=c, tool_mode="box", always_on=False)
        broadcaster.tools.append(zoom)

    plot1.tools.append(broadcaster)

    return plot1

# Attributes to use for the plot view.
size=(900,500)
title="Multi-Y plot"

# # Demo class that is used by the demo.py application.
#===============================================================================
class Demo(HasTraits):
    plot = Instance(Component)

    traits_view = View(
                    Group(
                        Item('plot', editor=ComponentEditor(size=size),
                             show_label=False),
                        orientation = "vertical"),
                    resizable=True, title=title,
                    width=size[0], height=size[1]
                    )

    def _plot_default(self):
         return _create_plot_component()

demo = Demo()
if __name__ == "__main__":
    demo.configure_traits()

推荐答案

Chaco(实际上还有很多绘图库)的缺点之一是术语的重载-尤其是"plot"一词.

One of the warts in Chaco (and indeed many plotting libraries) is the overloading of terms---especially the word "plot".

您要创建两个不同的(大写字母"P")Plot，但是(我相信)您实际上只想要一个. Plot是保存所有单独行... umm ...绘图的容器. Plot.plot方法返回一个LinePlot实例列表(有时也将此绘图"也称为渲染器").该渲染器就是您要添加到(大写"P")绘图"容器中的对象. plot方法实际上创建了LinePlot实例，并将其添加到了Plot容器中. (是的，这是绘图"的三种不同用法:容器，渲染器以及添加/返回渲染器的容器上的方法.)

You're creating two different (capital-"P") Plots, but (I believe) you really only want one. Plot is the container that holds all of your individual line ... umm ... plots. The Plot.plot method returns a list of LinePlot instances (this "plot" is also called a "renderer" sometimes). That renderer is what you want to add to your (capital-"P") Plot container. The plot method actually creates the LinePlot instance and adds it to the Plot container for you. (Yup, that's three different uses of "plot": The container, the renderer, and the method on the container that adds/returns the renderer.)

这是_create_plot_component的简单版本，可以满足您的需求.请注意，仅创建了一个(大写字母"P")Plot容器.

Here's a simpler version of _create_plot_component that does roughly what you want. Note that only a single (capital-"P") Plot container is created.

def _create_plot_component():
    # Create some x-y data series to plot
    x = linspace(-2.0, 10.0, 100)
    x2 =linspace(-5.0, 10.0, 100)

    pd = ArrayPlotData(x=x, x2=x2)
    for i in range(3):
        pd.set_data("y" + str(i), jn(i,x))

    # slightly different plot data
    for i in range(3, 5):
        pd.set_data("y" + str(i), 2*jn(i,x2))

    # Create some line plots of some of the data
    canvas = Plot(pd)
    canvas.plot(("x", "y0", "y1", "y2"), name="plot 1", color="red")
    canvas.plot(("x2", "y3", "y4"), name="plot 2", color="green")
    return canvas

先前的答复通过两行修改解决了该问题，但这不是解决问题的理想方法.

An earlier response fixed the issue with a two-line modification, but it wasn't the ideal way to solve the problem.

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