在matplotlib动画中将2D数组更新为y数据

Question

我有一组N随机路径，它们从一个点X开始。我有一个滑块，它改变初始点X，从而生成新的N路径。我希望能够更新路径，但是set_ydata只接受1D数组。目前我正在清理坐标轴并在每次更新时进行绘图，这不是很有效。在matplotlib中是否有任何内置的方法来完成它？在

xJ = arange(-10,10,0.1)
psinaive = zeros((xJ.shape[0]))
uapprox = zeros((xJ.shape[0],Nt))

wplot = []
wcondplot = []

for i,x in enumerate(xJ):
    WJ = sqrt(dt)*np.random.randn(Ntraj,Nt)
    WJ[:,0] = x
    WJ = np.cumsum(WJ,1)
    wplot.append(WJ)
    cond = V(WJ,limits)[0]
    wcondplot.append(WJ[cond,:])
    wa = 1.0/WJ.shape[0]*exp(-phi(WJ[:,-1],alpha)/lmbda)
    psinaive[i] = sum(wa[cond])
    uapprox[i,:] = 1.0/psinaive[i]*np.dot(wa[cond],WJ[cond,:]).flatten()
    if i % 10 == 0:
        print '..%.1f'%x,



J = -lmbda*log(psinaive)

#plot results

ax1=subplot(221)
plot(xJ,J)
plot(xJ,Jl(xJ,ti,tf,alpha,R,v,t1,limits))
title('$J(x,t)$')
plt.axvline(x=-10)

subplot(222)
plot(xJ,uapprox[:,0])

ax3 = subplot(223)
plot(t,wplot[0].T,alpha=0.2)
title('%d paths'%Ntraj)
ylim((-15,15))
ymin,ymax = ylim()
plt.axvline(x=t1, ymin=(d-ymin)/(ymax-ymin), linewidth=2, color='k')
plt.axvline(x=t1, ymin=(b-ymin)/(ymax-ymin), ymax = (c-ymin)/(ymax-ymin), linewidth=2, color='k')
plt.axvline(x=t1, ymax=(a-ymin)/(ymax-ymin), linewidth=2, color='k')

ax4 = subplot(224)
ax4.set_title('No alive paths')
if len(wcondplot[0])>0:
    ax4.plot(t,wcondplot[0].T,alpha=0.2)
    ax4.set_title('%d alive from %d paths'%(len(wcondplot[0]),Ntraj))
ylim((-15,15))
ymin,ymax = ylim()
plt.axvline(x=t1, ymin=(d-ymin)/(ymax-ymin), linewidth=2, color='k')
plt.axvline(x=t1, ymin=(b-ymin)/(ymax-ymin), ymax = (c-ymin)/(ymax-ymin), linewidth=2, color='k')
plt.axvline(x=t1, ymax=(a-ymin)/(ymax-ymin), linewidth=2, color='k')
subplots_adjust(0.15,0.25)


axsx = axes([0.15,0.1,0.75,0.1])
slx = Slider(axsx,'x',0,len(xJ),0,valfmt='%.0f')



def updatex(val):
    x = int(val)

    ax1.cla()
    ax1.plot(xJ,J)
    ax1.plot(xJ,Jl(xJ,ti,tf,alpha,R,v,t1,limits))
    ax1.set_title('$J(x,t)$')
    ax1.axvline(x=xJ[x])

    ax3.cla()
    ax3.plot(t,wplot[x].T,alpha=0.2)
    ax3.set_title('%d paths'%Ntraj)
    ax3.set_ylim((-15,15))
    ymin,ymax = ax3.get_ylim()
    ax3.axvline(x=t1, ymin=(d-ymin)/(ymax-ymin), linewidth=2, color='k')
    ax3.axvline(x=t1, ymin=(b-ymin)/(ymax-ymin), ymax = (c-ymin)/(ymax-ymin), linewidth=2, color='k')
    ax3.axvline(x=t1, ymax=(a-ymin)/(ymax-ymin), linewidth=2, color='k')

    ax4.cla()
    ax4.set_title('No alive paths')
    if len(wcondplot[x])>0:
        ax4.plot(t,wcondplot[x].T,alpha=0.4)
        ax4.set_title('%d alive from %d paths'%(len(wcondplot[x]),Ntraj))
    ax4.set_ylim((-15,15))
    ymin,ymax = ax4.get_ylim()
    ax4.axvline(x=t1, ymin=(d-ymin)/(ymax-ymin), linewidth=2, color='k')
    ax4.axvline(x=t1, ymin=(b-ymin)/(ymax-ymin), ymax = (c-ymin)/(ymax-ymin), linewidth=2, color='k')
    ax4.axvline(x=t1, ymax=(a-ymin)/(ymax-ymin), linewidth=2, color='k')
    draw()

slx.on_changed(updatex)

结果是：

Answer 1

您可以使用这样一个事实：如果数组包含nan，matplotlib将创建不同的段，尽管数组是一维的

x = (np.arange(5 * 4) % 4).reshape(5, 4) * 1.
x[x==3] = np.nan
y = x + (np.arange(5 * 4)/4).reshape(5,4)*1.
line2d = plt.plot(x.flatten(),y.flatten()) [0]
print x,y
> [[  0.,   1.,   2.,  nan],
> [  0.,   1.,   2.,  nan],
> [  0.,   1.,   2.,  nan],
> [  0.,   1.,   2.,  nan],
> [  0.,   1.,   2.,  nan]]
> [[  0.   1.   2.  nan]
> [  1.   2.   3.  nan]
> [  2.   3.   4.  nan]
> [  3.   4.   5.  nan]
> [  4.   5.   6.  nan]]

如果没有问题，可以使用U（）方法，例如：

^{pr2}$

Answer 2

尝试使用set_data，因为这样可以省去清除和回复（你已经意识到这是非常慢的）。使用示例：

fig = figure()
ax = fig.add_subplot(111)
p = ax.plot(x, y)

# you do something to your data and want to replot

p.set_data(x, y)

如果你可以发布你的代码，那么我们可以帮助你找到确切的解决方案。在