axis（'；square'；）和set#xlim之间的python交互作用

对于相关图，我希望有一个光学正方形的图（x和y的像素长度相同），但在x和y上也有一定的轴限制。我可以分别获得这两个，但不能同时获得：

import matplotlib.pyplot as plt

f, (ax1, ax2) = plt.subplots(1, 2)
x = [1 , 4 , 6]
y1 = [4, 7, 9]
y2 = [20, 89, 99]

ax1.plot(x, y1, 'o')
ax2.plot(x, y2, 'o')

myXlim = [0, 8]
ax1.set_xlim(myXlim)
ax2.set_xlim(myXlim)

ax1.axis('square')
ax2.axis('square')
# limit is gone here

ax1.set_xlim(myXlim)
ax2.set_xlim(myXlim)
# square is gone here

plt.show()

---

如果我只使用

ax1.setxlim（myXlim）

（而不是

square

），那么我可以手动调整窗口大小以获得所需的内容，但如何自动执行此操作？

获取方形子地块的一个选项是设置子地块参数，以便生成的子地块自动调整为方形。这有点复杂，因为需要考虑所有的边距和间距

import matplotlib.pyplot as plt

f, (ax1, ax2) = plt.subplots(1, 2)
x = [1 , 4 , 6]
y1 = [4, 7, 9]
y2 = [20, 89, 99]

def square_subplots(fig):
    rows, cols = ax1.get_subplotspec().get_gridspec().get_geometry()
    l = fig.subplotpars.left
    r = fig.subplotpars.right
    t = fig.subplotpars.top
    b = fig.subplotpars.bottom
    wspace = fig.subplotpars.wspace
    hspace = fig.subplotpars.hspace
    figw,figh = fig.get_size_inches()

    axw = figw*(r-l)/(cols+(cols-1)*wspace)
    axh = figh*(t-b)/(rows+(rows-1)*hspace)
    axs = min(axw,axh)
    w = (1-axs/figw*(cols+(cols-1)*wspace))/2.
    h = (1-axs/figh*(rows+(rows-1)*hspace))/2.
    fig.subplots_adjust(bottom=h, top=1-h, left=w, right=1-w)

ax1.plot(x, y1, 'o')
ax2.plot(x, y2, 'o')

#f.tight_layout() # optionally call tight_layout first
square_subplots(f)

plt.show()

这里的好处是能够自由缩放和自动缩放。缺点是一旦图形大小改变，子地块大小就不再是正方形了。为了克服这个缺点，还可以注册图形大小更改的回调

import matplotlib.pyplot as plt

f, (ax1, ax2) = plt.subplots(1, 2)
x = [1 , 4 , 6]
y1 = [4, 7, 9]
y2 = [20, 89, 99]

class SquareSubplots():
    def __init__(self, fig):
        self.fig = fig
        self.ax = self.fig.axes[0]
        self.figw,self.figh = 0,0
        self.params = [self.fig.subplotpars.left,
                       self.fig.subplotpars.right,
                       self.fig.subplotpars.top,
                       self.fig.subplotpars.bottom,
                       self.fig.subplotpars.wspace,
                       self.fig.subplotpars.hspace]
        self.rows, self.cols = self.ax.get_subplotspec().get_gridspec().get_geometry()
        self.update(None)
        self.cid = self.fig.canvas.mpl_connect('resize_event', self.update)


    def update(self, evt):
        figw,figh = self.fig.get_size_inches()
        if self.figw != figw or self.figh != figh:
            self.figw = figw; self.figh = figh
            l,r,t,b,wspace,hspace = self.params
            axw = figw*(r-l)/(self.cols+(self.cols-1)*wspace)
            axh = figh*(t-b)/(self.rows+(self.rows-1)*hspace)
            axs = min(axw,axh)
            w = (1-axs/figw*(self.cols+(self.cols-1)*wspace))/2.
            h = (1-axs/figh*(self.rows+(self.rows-1)*hspace))/2.
            self.fig.subplots_adjust(bottom=h, top=1-h, left=w, right=1-w)
            self.fig.canvas.draw_idle()

s = SquareSubplots(f)

ax1.plot(x, y1, 'o')
ax2.plot(x, y2, 'o')

plt.show()

---

上述解决方案通过限制子地块在其网格内的空间来工作。另一种相反的方法是，子地块的大小在某种程度上是固定的，它将显示在问题的答案中