在matplot lib中创建插入

Yot*_*tam 5 python matplotlib insets

我在matplot lib中创建了一个图,我希望在该图中添加一个插图.我希望绘制的数据保存在我在其他图中使用的字典中.我在循环中找到了这个数据,然后我再次为子图运行这个循环.以下是相关部分:

leg = []     
colors=['red','blue']
count = 0                     
for key in Xpr: #Xpr holds my data
    #skipping over what I don't want to plot
    if not key[0] == '5': continue 
    if key[1] == '0': continue
    if key[1] == 'a': continue
    leg.append(key)
    x = Xpr[key]
    y = Ypr[key] #Ypr holds the Y axis and is created when Xpr is created
    plt.scatter(x,y,color=colors[count],marker='.')
    count += 1

plt.xlabel(r'$z/\mu$')
plt.ylabel(r'$\rho(z)$')
plt.legend(leg)
plt.xlim(0,10)
#Now I wish to create the inset
a=plt.axes([0.7,0.7,0.8,0.8])
count = 0
for key in Xpr:
    break
    if not key[0] == '5': continue
    if key[1] == '0': continue
    if key[1] == 'a': continue
    leg.append(key)
    x = Xpr[key]
    y = Ypr[key]
    a.plot(x,y,color=colors[count])
    count += 1
plt.savefig('ion density 5per Un.pdf',format='pdf')

plt.cla()
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奇怪的是,当我试图移动插入位置时,我仍然得到之前的插入(来自上一代代码的插件).我甚至试图在a=axes([])没有任何明显的情况下评论这条线.我附上了示例文件.为什么它以这种方式行事?弯曲输出的数字

tac*_*ell 5

简单的答案是您应该使用plt.clf()它来清除图形,而不是当前轴。break插入循环中还有一个,表示该代码都不会运行。

当您开始执行比使用单个轴更复杂的操作时,值得切换为使用OO接口matplotlib。乍一看似乎比较复杂,但是您不必再担心的隐藏状态pyplot。您的代码可以重写为

fig = plt.figure()
ax = fig.add_axes([.1,.1,.8,.8]) # main axes
colors=['red','blue']
for key  in Xpr: #Xpr holds my data
    #skipping over what I don't want to plot
    if not key[0] == '5': continue 
    if key[1] == '0': continue
    if key[1] == 'a': continue
    x = Xpr[key]
    y = Ypr[key] #Ypr holds the Y axis and is created when Xpr is created
    ax.scatter(x,y,color=colors[count],marker='.',label=key)
    count += 1

ax.set_xlabel(r'$z/\mu$')
ax.set_ylabel(r'$\rho(z)$')
ax.set_xlim(0,10)
leg = ax.legend()

#Now I wish to create the inset
ax_inset=fig.add_axes([0.7,0.7,0.3,0.3])
count =0
for key  in Xpr: #Xpr holds my data
    if not key[0] == '5': continue
    if key[1] == '0': continue
    if key[1] == 'a': continue
    x = Xpr[key]
    y = Ypr[key]
    ax_inset.plot(x,y,color=colors[count],label=key)
    count +=1

ax_inset.legend()
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