抽象与抽象；复杂IPython小部件仪表板的设计模式

IPywidgets手册在很大程度上非常有用，但缺少关于如何创建复杂仪表板的说明。特别是，我正试图了解我们如何：

设计抽象以帮助构建易于扩展的仪表板，仪表板包含多个相互依赖的小部件，其中一些小部件隐藏/显示其他小部件

这样做的方式允许我将所有小部件的状态设置为

dict

，这样我就可以随后实现按钮，将仪表板的配置保存并加载到JSON文件中

为了使这个问题更具体，我设计了一个我当前方法的最小示例，它基于我从@jasongrout上收到的；回答时，请通过在其中重新实现此示例来演示您的设计模式，确保明确满足上述两个标准：

from IPython.display import display
import IPython.display as ipd
import ipywidgets as widgets
import matplotlib.pyplot as plt

class ModelUI:

    def __init__(self):

        self.par = dict()
        self.initUI()

    def initUI(self):

        self.funcPars = widgets.VBox()

        self.initLinear()
        self.initQuadratic()
        self.initFunc()
        self.initButton()
        self.initOutput()    

        self.controls = widgets.HBox([
            self.func, 
            self.funcPars, 
            self.plot
        ])
        self.UI = widgets.VBox([
            self.controls, 
            self.output
        ])

    def initFunc(self):

        self.func = widgets.Dropdown(
            description="Function:", 
            options=[
                "Linear", 
                "Quadratic"
            ])
        self.func.observe(self.updateFunc, "value")

        self.updateFunc(None)

    def initButton(self):

        self.plot = widgets.Button(description="Plot")
        self.plot.on_click(self.plotFunction)

    def updateFunc(self, change):

        if self.func.value == "Linear":
            self.funcPars.children = self.linPars
            self.par['func'] = "Linear"
        elif self.func.value == "Quadratic":
            self.funcPars.children = self.quadPars
            self.par['func'] = "Quadratic"
        else:
            pass

    def initLinear(self):

        self.m = widgets.FloatSlider(
            description="m", 
            min=-10, max=10, value=2)
        self.k = widgets.FloatSlider(
            description="k", 
            min=-10, max=10, value=1)
        self.linPars = [self.m, self.k]

        self.m.observe(self.updateLinear, "value")
        self.k.observe(self.updateLinear, "value")

        self.updateLinear(None)

    def updateLinear(self, change):

        self.par['m'] = self.m.value
        self.par['k'] = self.k.value

    def initQuadratic(self):

        self.a = widgets.FloatSlider(
            description="a", 
            min=-10, max=10, value=1)
        self.b = widgets.FloatSlider(
            description="b", 
            min=-10, max=10, value=2)
        self.c = widgets.FloatSlider(
            description="c", 
            min=-10, max=10, value=3)
        self.quadPars = [self.a, self.b, self.c]

        self.a.observe(self.updateQuadratic, "value")
        self.b.observe(self.updateQuadratic, "value")
        self.c.observe(self.updateQuadratic, "value")

        self.updateQuadratic(None)

    def updateQuadratic(self, change):

        self.par['a'] = self.a.value
        self.par['b'] = self.b.value
        self.par['c'] = self.c.value

    def initOutput(self):

        self.output = widgets.Output()
        self.plotFunction(None)    

    def plotFunction(self, change):

        self.function = {
            "Linear": lambda x: self.par['m']*x + self.par['k'],
            "Quadratic": lambda x: self.par['a']*x**2 + self.par['b']*x + self.par['c']
            }
        with self.output:
            ipd.clear_output()
            xvals = [ i/10 for i in range(-100,100)]
            yvals = list(map(self.function[self.par['func']], xvals))
            plt.plot(xvals,yvals)
            plt.show()

    def _ipython_display_(self):

        display(self.UI)

ModelUI()