pyplot - 复制轴内容并以新图形显示

Question

假设我有这个代码:

num_rows = 10
num_cols = 1
fig, axs = plt.subplots(num_rows, num_cols, sharex=True)
for i in xrange(num_rows):
     ax = axs[i]
     ax.plot(np.arange(10), np.arange(10)**i)
plt.show()

结果图有太多信息,现在我想选择1个轴并在新图中单独绘制它

我尝试过做这样的事情

def on_click(event):
    axes = event.inaxes.get_axes()
    fig2 = plt.figure(15)
    fig2.axes.append(axes)
    fig2.show()

fig.canvas.mpl_connect('button_press_event', on_click)

但它没有奏效.这样做的正确方法是什么？搜索文档并抛出SE几乎没有任何有用的结果

编辑:

我不介意重新绘制所选择的轴,但我不知道如何判断哪个轴被选中,所以如果该信息以某种方式可用,那么它对我来说是一个有效的解决方案

编辑#2:

所以我设法做了这样的事情:

def on_click(event):
    fig2 = plt.figure(15)
    fig2.clf()
    for line in event.inaxes.axes.get_lines():
         xydata = line.get_xydata()
         plt.plot(xydata[:, 0], xydata[:, 1])
    fig2.show()

这似乎是"工作"(所有其他信息丢失 - 标签,线条颜色,线条样式,线条宽度,xlim,ylim等...)但我觉得必须有一个更好的方法来做到这一点

谢谢

Answer 1

复制轴

这里的初步答案不起作用,我们将其保留以备将来参考,并了解为什么需要更复杂的方法.

#There are some pitfalls on the way with the initial approach. 
#Adding an `axes` to a figure can be done via `fig.add_axes(axes)`. However, at this point, 
#the axes' figure needs to be the figure the axes should be added to. 
#This may sound a bit like running in circles but we can actually set the axes' 
#figure as `axes.figure = fig2` and hence break out of this.

#One might then also position the axes in the new figure to take the usual dimensions. 
#For this a dummy axes can be added first, the axes can change its position to the position 
#of the dummy axes and then the dummy axes is removed again. In total, this would look as follows.

import matplotlib.pyplot as plt
import numpy as np

num_rows = 10
num_cols = 1
fig, axs = plt.subplots(num_rows, num_cols, sharex=True)
for i in xrange(num_rows):
     ax = axs[i]
     ax.plot(np.arange(10), np.arange(10)**i)
     
     
def on_click(event):
    axes = event.inaxes
    if not axes: return   
    fig2 = plt.figure()
    axes.figure=fig2
    fig2.axes.append(axes)
    fig2.add_axes(axes)
    
    dummy = fig2.add_subplot(111)
    axes.set_position(dummy.get_position())
    dummy.remove()
    fig2.show()

fig.canvas.mpl_connect('button_press_event', on_click)


plt.show()

#So far so good, however, be aware that now after a click the axes is somehow 
#residing in both figures, which can cause all sorts of problems, e.g. if you
# want to resize or save the initial figure.

相反,以下内容将起作用:

腌制这个数字

问题是轴无法复制(甚至deepcopy会失败).因此,要获得轴的真实副本,您可能需要使用pickle.以下将有效.它会腌制完整的图形并移除除了一个轴之外的所有图形.

import matplotlib.pyplot as plt
import numpy as np
import pickle
import io

num_rows = 10
num_cols = 1
fig, axs = plt.subplots(num_rows, num_cols, sharex=True)
for i in range(num_rows):
     ax = axs[i]
     ax.plot(np.arange(10), np.arange(10)**i)

def on_click(event):

    if not event.inaxes: return
    inx = list(fig.axes).index(event.inaxes)
    buf = io.BytesIO()
    pickle.dump(fig, buf)
    buf.seek(0)
    fig2 = pickle.load(buf) 

    for i, ax in enumerate(fig2.axes):
        if i != inx:
            fig2.delaxes(ax)
        else:
            axes=ax

    axes.change_geometry(1,1,1)
    fig2.show()

fig.canvas.mpl_connect('button_press_event', on_click)

plt.show()

重新创建情节

上述的替代方案当然是每次单击轴时在新图中重新创建绘图.为此,可以使用在指定轴上创建绘图并使用指定索引作为输入的函数.在图形创建过程中以及稍后在另一个图形中复制图形时使用此功能可确保在所有情况下都具有相同的图形.

import matplotlib.pyplot as plt
import numpy as np

num_rows = 10
num_cols = 1
colors = plt.rcParams["axes.prop_cycle"].by_key()["color"]
labels = ["Label {}".format(i+1) for i in range(num_rows)]

def myplot(i, ax):
    ax.plot(np.arange(10), np.arange(10)**i, color=colors[i])
    ax.set_ylabel(labels[i])


fig, axs = plt.subplots(num_rows, num_cols, sharex=True)
for i in xrange(num_rows):
     myplot(i, axs[i])


def on_click(event):
    axes = event.inaxes
    if not axes: return
    inx = list(fig.axes).index(axes)
    fig2 = plt.figure()
    ax = fig2.add_subplot(111)
    myplot(inx, ax)
    fig2.show()

fig.canvas.mpl_connect('button_press_event', on_click)

plt.show()