在Matplotlib中的插圖中使用twiny（）

Question

我試圖將第二個x軸添加到我從mpl_toolkits.axes_grid1.inset_locator用InsetPosition創建的插圖中（例如https://scipython.com/blog/inset-plots-in-matplotlib/ ），但是第二個x軸似乎沒有顯示，我也不知道為什么。

這是我正在使用的代碼：

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.gca()

from mpl_toolkits.axes_grid1.inset_locator import InsetPosition
zoom_ax = fig.add_axes([0,0,1,1])
zoom_ax.set_axes_locator(InsetPosition(ax, [0.6, 0.6, 0.3, 0.3]))

def expansion(z):
    return 1.0 / (1.0 + z)

def redshift(a):
    return 1.0 / a - 1.0

def tick_function(a):
    return ["%.1f" % z for z in redshift(a)]

z_ticks = np.array([0.0, 0.5, 1.0, 2.0, 5.0, 100.0])
a_ticks = expansion(z_ticks)

twin_ax = zoom_ax.twiny()
twin_ax.set_xticks(a_ticks)
twin_ax.set_xticklabels(tick_function(a_ticks))
twin_ax.set_xlim(zoom_ax.get_xlim())

xmin, xmax = 0.0, 1.0
x = np.linspace(xmin, xmax)
zoom_ax.plot(x, np.sin(x))
zoom_ax.set_xlim(xmin, xmax)

plt.show()

這將產生以下繪圖-沒有任何twiny()軸：

Answer 1

顯然axes_locator twiny()對於axes_locator使用的zoom_ax有問題（不知道這是否是錯誤）。 如果重復set_axes_locator()命令twin_ax ，得到的情節看起來像我期望（我離開了軸蜱命令，使我的例子情節更容易理解）：

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.gca()

from mpl_toolkits.axes_grid1.inset_locator import InsetPosition
zoom_ax = fig.add_axes([0,0,1,1])
zoom_ax.set_axes_locator(InsetPosition(ax, [0.6, 0.6, 0.3, 0.3]))

def expansion(z):
    return 1.0 / (1.0 + z)

def redshift(a):
    return 1.0 / a - 1.0

def tick_function(a):
    return ["%.1f" % z for z in redshift(a)]

z_ticks = np.array([0.0, 0.5, 1.0, 2.0, 5.0, 100.0])
a_ticks = expansion(z_ticks)

twin_ax = zoom_ax.twiny()
##twin_ax.set_xticks(a_ticks)
##twin_ax.set_xticklabels(tick_function(a_ticks))
twin_ax.set_xlim(zoom_ax.get_xlim())

xmin, xmax = 0.0, 1.0
x = np.linspace(xmin, xmax)
zoom_ax.plot(x, np.sin(x))
zoom_ax.set_xlim(xmin, xmax)

##the extra lines
twin_ax.set_axes_locator(InsetPosition(ax, [0.6, 0.6, 0.3, 0.3]))
x2 = np.linspace(xmin, 2*xmax)
twin_ax.plot(x2,np.cos(x2),'r')
twin_ax.set_xlim(xmin, 2*xmax)

plt.show()

這將產生以下圖：

Answer 2

也許您想使用通常的mpl_toolkits.axes_grid1.inset_locator.inset_axes ，即使使用孿生也可以正常工作。

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.gca()

from mpl_toolkits.axes_grid1.inset_locator import inset_axes
zoom_ax = inset_axes(ax, "100%", "100%", bbox_to_anchor=[0.6, 0.6, 0.3, 0.3], 
                     bbox_transform=ax.transAxes)

def expansion(z):
    return 1.0 / (1.0 + z)

def redshift(a):
    return 1.0 / a - 1.0

def tick_function(a):
    return ["%.1f" % z for z in redshift(a)]

z_ticks = np.array([0.0, 0.5, 1.0, 2.0, 5.0, 100.0])
a_ticks = expansion(z_ticks)

twin_ax = zoom_ax.twiny()
twin_ax.set_xticks(a_ticks)
twin_ax.set_xticklabels(tick_function(a_ticks))
twin_ax.set_xlim(zoom_ax.get_xlim())

xmin, xmax = 0.0, 1.0
x = np.linspace(xmin, xmax)
zoom_ax.plot(x, np.sin(x))
zoom_ax.set_xlim(xmin, xmax)

plt.show()

從matplotlib 3.0開始，您可以使用Axes.inset_axes進一步簡化此Axes.inset_axes ：

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.gca()

zoom_ax = ax.inset_axes([0.6, 0.6, 0.3, 0.3])

def expansion(z):
    return 1.0 / (1.0 + z)

def redshift(a):
    return 1.0 / a - 1.0

def tick_function(a):
    return ["%.1f" % z for z in redshift(a)]

z_ticks = np.array([0.0, 0.5, 1.0, 2.0, 5.0, 100.0])
a_ticks = expansion(z_ticks)

twin_ax = zoom_ax.twiny()
twin_ax.set_xticks(a_ticks)
twin_ax.set_xticklabels(tick_function(a_ticks))
twin_ax.set_xlim(zoom_ax.get_xlim())

xmin, xmax = 0.0, 1.0
x = np.linspace(xmin, xmax)
zoom_ax.plot(x, np.sin(x))
zoom_ax.set_xlim(xmin, xmax)

plt.show()

結果在視覺上是相同的：