如何修复长时间计算中的Tkinter GUI冻结

Question

我在GUI中有我的按钮和功能，如下所示。运行函数计算X和Y坐标以及颜色值，然后使用matplotlib打印它们。由于计算和绘图需要时间，Tkinter会冻结直到完成。我见过有人使用线程，但我不能真正将其应用到我自己的代码中。我怎样才能阻止特金特冻僵

RUNButton = Button(RUNFrame, text="RUN", width = 10, style='RUN.TButton', command = lambda: RUN(voidORinc.get()))
RUNButton.grid(row=0,column=0,padx=10,ipady=15,pady=5,columnspan=2)

def RUN(inclusion):
    global deformationType
    global NL
    global EL
    global ENL
    global cEntry
    global dEntry
    global dropElementType
    global axstress_xx
    global axstress_xy
    global axstress_yx
    global axstress_yy
    global axstrain_xx
    global axstrain_xy
    global axstrain_yx
    global axstrain_yy
    global axdisp_x
    global axdisp_y
    global analysisType

    (ENL,DOFs,DOCs) = assign_BCs(NL,deformationType.get())
    
    K = assemble_stiffness( ENL ,EL , NL , int(cEntry.get()) , int(dEntry.get()) , inclusion )
    
    Fp = assemble_forces(ENL,NL)
    
    Up = assemble_displacements(ENL,NL)
    
    K_reduced = K[0:DOFs, 0:DOFs] #K_UU
    K_UP = K[0:DOFs, DOFs:DOCs+DOFs]
    K_PU = K_PU= K[DOFs:DOCs+DOFs, 0:DOFs]
    K_PP= K[DOFs:DOCs+DOFs, DOFs:DOCs+DOFs]

    F = Fp - (K_UP @ Up)
    
    Uu = np.linalg.solve( K_reduced, F)
    
    Fu = (K_PU @ Uu)  +  (K_PP @ Up)
    
    ENL = update_nodes(ENL,Uu,Fu,NL)
    
    (stress_xx,stress_xy,stress_yx,stress_yy,strain_xx,strain_xy,strain_yx,strain_yy,disp_x,disp_y,X,Y) = post_process(NL, EL, ENL, int(cEntry.get()), int(dEntry.get()), inclusion)
    
    
    option = analysisType.get()
    
    """
    
    POLYGONAL PLOTS
    
    
    """
            
    axstress_xx.cla()
    axstress_xy.cla()
    axstress_yx.cla()
    axstress_yy.cla()
    axstrain_xx.cla()
    axstrain_xy.cla()
    axstrain_yx.cla()
    axstrain_yy.cla()
    axdisp_x.cla()
    axdisp_y.cla()
    
    
    if option == 'Polygonal':
        stress_xxNormalized = (np.mean(stress_xx, axis=0) - np.mean(stress_xx, axis=0).min()) / (np.mean(stress_xx, axis=0).max() - np.mean(stress_xx, axis=0).min())
        stress_xyNormalized = (np.mean(stress_xy, axis=0) - np.mean(stress_xy, axis=0).min()) / (np.mean(stress_xy, axis=0).max() - np.mean(stress_xy, axis=0).min())
        stress_yxNormalized = (np.mean(stress_yx, axis=0) - np.mean(stress_yx, axis=0).min()) / (np.mean(stress_yx, axis=0).max() - np.mean(stress_yx, axis=0).min())
        stress_yyNormalized = (np.mean(stress_yy, axis=0) - np.mean(stress_yy, axis=0).min()) / (np.mean(stress_yy, axis=0).max() - np.mean(stress_yy, axis=0).min())
        strain_xxNormalized = (np.mean(strain_xx, axis=0) - np.mean(strain_xx, axis=0).min()) / (np.mean(strain_xx, axis=0).max() - np.mean(strain_xx, axis=0).min())
        strain_xyNormalized = (np.mean(strain_xy, axis=0) - np.mean(strain_xy, axis=0).min()) / (np.mean(strain_xy, axis=0).max() - np.mean(strain_xy, axis=0).min())
        strain_yxNormalized = (np.mean(strain_yx, axis=0) - np.mean(strain_yx, axis=0).min()) / (np.mean(strain_yx, axis=0).max() - np.mean(strain_yx, axis=0).min())
        strain_yyNormalized = (np.mean(strain_yy, axis=0) - np.mean(strain_yy, axis=0).min()) / (np.mean(strain_yy, axis=0).max() - np.mean(strain_yy, axis=0).min())
        disp_xNormalized = (np.mean(abs(disp_x), axis=0) - np.mean(abs(disp_x), axis=0).min()) / (np.mean(abs(disp_x), axis=0).max() - np.mean(abs(disp_x), axis=0).min())
        disp_yNormalized = (np.mean(abs(disp_y), axis=0) - np.mean(abs(disp_y), axis=0).min()) / (np.mean(abs(disp_y), axis=0).max() - np.mean(abs(disp_y), axis=0).min())
      
        patches = []
    
        for i in range(len(stress_xxNormalized)):
            verts = np.hstack([np.array([X[:,i]]).T,np.array([Y[:,i]]).T])
            polygon = Polygon(verts)
            patches.append(polygon)
            polygon.set_edgecolor('black')
    
        
        cmap = plt.get_cmap('jet')
        
        colors1 = cmap(stress_xxNormalized)
        colors2 = cmap(stress_xyNormalized)
        colors3 = cmap(stress_yxNormalized)
        colors4 = cmap(stress_yyNormalized)
        colors5 = cmap(strain_xxNormalized)
        colors6 = cmap(strain_xyNormalized)
        colors7 = cmap(strain_yxNormalized)
        colors8 = cmap(strain_yyNormalized)
        colors9 = cmap(disp_xNormalized)
        colors10 = cmap(disp_yNormalized)
        
        
        
        collection1 = PatchCollection(patches)
        collection2 = PatchCollection(patches)
        collection3 = PatchCollection(patches)
        collection4 = PatchCollection(patches)
        collection5 = PatchCollection(patches)
        collection6 = PatchCollection(patches)
        collection7 = PatchCollection(patches)
        collection8 = PatchCollection(patches)
        collection9 = PatchCollection(patches)
        collection10 = PatchCollection(patches)
        
        axstress_xx.add_collection(collection1)
        axstress_xy.add_collection(collection2)
        axstress_yx.add_collection(collection3)
        axstress_yy.add_collection(collection4)
        axstrain_xx.add_collection(collection5)
        axstrain_xy.add_collection(collection6)
        axstrain_yx.add_collection(collection7)
        axstrain_yy.add_collection(collection8)
        axdisp_x.add_collection(collection9)
        axdisp_y.add_collection(collection10)
        
        collection1.set_facecolor(colors1)
        collection2.set_facecolor(colors2)
        collection3.set_facecolor(colors3)
        collection4.set_facecolor(colors4)
        collection5.set_facecolor(colors5)
        collection6.set_facecolor(colors6)
        collection7.set_facecolor(colors7)
        collection8.set_facecolor(colors8)
        collection9.set_facecolor(colors9)
        collection10.set_facecolor(colors10)
        
        collection1.set_edgecolor('black')
        collection2.set_edgecolor('black')
        collection3.set_edgecolor('black')
        collection4.set_edgecolor('black')
        collection5.set_edgecolor('black')
        collection6.set_edgecolor('black')
        collection7.set_edgecolor('black')
        collection8.set_edgecolor('black')
        collection9.set_edgecolor('black')
        collection10.set_edgecolor('black')
        
        axstress_xx.autoscale_view()
        axstress_xy.autoscale_view()
        axstress_yx.autoscale_view()
        axstress_yy.autoscale_view()
        axstrain_xx.autoscale_view()
        axstrain_xy.autoscale_view()
        axstrain_yx.autoscale_view()
        axstrain_yy.autoscale_view()
        axdisp_x.autoscale_view()
        axdisp_y.autoscale_view()
    
    """
    
    TRICONTOURF PLOTS
    
    """

    if option == 'Contour':
        stress_xxNormalized = (stress_xx - stress_xx.min()) / (stress_xx.max() - stress_xx.min())
        stress_xyNormalized = (stress_xy - stress_xy.min()) / (stress_xy.max() - stress_xy.min())
        stress_yxNormalized = (stress_yx - stress_yx.min()) / (stress_yx.max() - stress_yx.min())
        stress_yyNormalized = (stress_yy - stress_yy.min()) / (stress_yy.max() - stress_yy.min())
        strain_xxNormalized = (strain_xx - strain_xx.min()) / (strain_xx.max() - strain_xx.min())
        strain_xyNormalized = (strain_xy - strain_xy.min()) / (strain_xy.max() - strain_xy.min())
        strain_yxNormalized = (strain_yx - strain_yx.min()) / (strain_yx.max() - strain_yx.min())
        strain_yyNormalized = (strain_yy - strain_yy.min()) / (strain_yy.max() - strain_yy.min())
        disp_xNormalized = (disp_x - disp_x.min()) / (disp_x.max() - disp_x.min())
        disp_yNormalized = (disp_y - disp_y.min()) / (disp_y.max() - disp_y.min())
        
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = stress_xxNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstress_xx.tricontourf(x,y,c ,cmap = cmap,levels=1)
        
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = stress_xyNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstress_xy.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = stress_yxNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstress_yx.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = stress_yyNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstress_yy.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = strain_xxNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstrain_xx.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = strain_xyNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstrain_xy.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = strain_yxNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstrain_yx.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = strain_yyNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axstrain_yy.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = disp_xNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axdisp_x.tricontourf(x,y,c, cmap = cmap,levels=1)
        for i in range(np.size(X,1)):
            x = X[:,i]
            y = Y[:,i]
            c = disp_yNormalized[:,i]
            cmap = truncate_colormap(plt.get_cmap('jet'), c.min(), c.max())
            axdisp_y.tricontourf(x,y,c, cmap = cmap,levels=1)
    
    canvasAnalysis.draw()

编辑：这是我到目前为止尝试的：

def RUN(inclusion):
    ... function content above

RUNFrame = LabelFrame(processFrame)
RUNFrame.grid(row=1,column=2,padx=10)

RUNButton = Button(RUNFrame, text="RUN", width = 10, style='RUN.TButton', command = threading.Thread(target=RUN, args=(voidORinc.get(), )))
RUNButton.grid(row=0,column=0,padx=10,ipady=15,pady=5,columnspan=2)

我收到错误“未定义名称RUNFrame”

Answer 1

Button应该运行创建thread的函数并启动它

如果在RUN中使用小部件中的一些值，那么可以将它们作为参数发送，因为大多数GUI不喜欢在单独的线程中使用小部件

Button(..., command=run_calculations)

def run_calculations():
    
    t = threading.Thread(taget=RUN, args=(voidORinc.get(), cEntry.get()) , int(dEntry.get(), ...))
    t.start()
    

---

最后，在RUN中，您应该定期使用root.update()（其中root是主窗口）强制tkinter从系统获取键/鼠标事件，将它们发送到小部件，并重新绘制小部件。这样它就不会结冰。这不需要thread

 def RUN(inclusion):

     # ... some part of code ...

     root.update()

     # ... some part of code ...

     root.update()

     # ... some part of code ...

     root.update()