假设我有以下代码：
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()
结果图包含太多信息，现在我要选择一个轴并将其单独绘制在新图中
我试图做这样的事情
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)
但效果不佳。正确的方法是什么？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的轴，但是我不确定如何知道选择了哪个轴，因此，如果以某种方式可以获得该信息，那么对我来说这是一个有效的解决方案
编辑＃2：
所以我设法做这样的事情：
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“有效的”（所有其他信息都丢失了-标签，线条颜色，线条样式，线条宽度，xlim，ylim等），但是我觉得必须有更好的方法来做到这一点
谢谢
复制轴 此处的初始答案不起作用，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，以下方法将起作用：
腌制图 问题是无法复制轴（甚至deepcopy会失败）。因此，要获得轴的真实副本，可能需要使用pickle。以下将起作用。它会腌制完整的图形，并删除所有要显示的轴。
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()
重新创建图 当然，上述替代方法是每次单击轴时在新图中重新创建图。为此，可以使用一种函数，该函数在指定的轴上以指定的索引为输入创建图。在图形创建期间以及以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()
