插入定位器演示

inset_locator 的 inset_axes 允许通过指定宽度和高度以及可选地将位置(Loc)接受位置作为代码(类似于图例)，轻松地在轴的角中放置插入。默认情况下，通过“边界板”(BorderPad)参数控制的内嵌与轴之间的某些点偏移。

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes


fig, (ax, ax2) = plt.subplots(1, 2, figsize=[5.5, 2.8])

# Create inset of width 1.3 inches and height 0.9 inches
# at the default upper right location
axins = inset_axes(ax, width=1.3, height=0.9)

# Create inset of width 30% and height 40% of the parent axes' bounding box
# at the lower left corner (loc=3)
axins2 = inset_axes(ax, width="30%", height="40%", loc=3)

# Create inset of mixed specifications in the second subplot;
# width is 30% of parent axes' bounding box and
# height is 1 inch at the upper left corner (loc=2)
axins3 = inset_axes(ax2, width="30%", height=1., loc=2)

# Create an inset in the lower right corner (loc=4) with borderpad=1, i.e.
# 10 points padding (as 10pt is the default fontsize) to the parent axes
axins4 = inset_axes(ax2, width="20%", height="20%", loc=4, borderpad=1)

# Turn ticklabels of insets off
for axi in [axins, axins2, axins3, axins4]:
    axi.tick_params(labelleft=False, labelbottom=False)

plt.show()

插入定位器演示

参数bbox_to_anchor 和 bbox_transfrom 可用于对插入位置和大小进行更细粒度的控制，甚至可以将插入位置置于完全任意位置。bbox_to_anchor 根据 bbox_transform 设置坐标中的边界框。

fig = plt.figure(figsize=[5.5, 2.8])
ax = fig.add_subplot(121)

# We use the axes transform as bbox_transform. Therefore the bounding box
# needs to be specified in axes coordinates ((0,0) is the lower left corner
# of the axes, (1,1) is the upper right corner).
# The bounding box (.2, .4, .6, .5) starts at (.2,.4) and ranges to (.8,.9)
# in those coordinates.
# Inside of this bounding box an inset of half the bounding box' width and
# three quarters of the bounding box' height is created. The lower left corner
# of the inset is aligned to the lower left corner of the bounding box (loc=3).
# The inset is then offset by the default 0.5 in units of the font size.

axins = inset_axes(ax, width="50%", height="75%",
                   bbox_to_anchor=(.2, .4, .6, .5),
                   bbox_transform=ax.transAxes, loc=3)

# For visualization purposes we mark the bounding box by a rectangle
ax.add_patch(plt.Rectangle((.2, .4), .6, .5, ls="--", ec="c", fc="None",
                           transform=ax.transAxes))

# We set the axis limits to something other than the default, in order to not
# distract from the fact that axes coodinates are used here.
ax.axis([0, 10, 0, 10])


# Note how the two following insets are created at the same positions, one by
# use of the default parent axes' bbox and the other via a bbox in axes
# coordinates and the respective transform.
ax2 = fig.add_subplot(222)
axins2 = inset_axes(ax2, width="30%", height="50%")

ax3 = fig.add_subplot(224)
axins3 = inset_axes(ax3, width="100%", height="100%",
                    bbox_to_anchor=(.7, .5, .3, .5),
                    bbox_transform=ax3.transAxes)

# For visualization purposes we mark the bounding box by a rectangle
ax2.add_patch(plt.Rectangle((0, 0), 1, 1, ls="--", lw=2, ec="c", fc="None"))
ax3.add_patch(plt.Rectangle((.7, .5), .3, .5, ls="--", lw=2,
                            ec="c", fc="None"))

# Turn ticklabels off
for axi in [axins2, axins3, ax2, ax3]:
    axi.tick_params(labelleft=False, labelbottom=False)

plt.show()

插入定位器演示2

在上述方法中，使用了轴变换和4元组边界框，因为它主要用于指定相对于其所插入的轴的插入值。但是，其他用例也是可能的。下面的示例检查其中一些。

fig = plt.figure(figsize=[5.5, 2.8])
ax = fig.add_subplot(131)

# Create an inset outside the axes
axins = inset_axes(ax, width="100%", height="100%",
                   bbox_to_anchor=(1.05, .6, .5, .4),
                   bbox_transform=ax.transAxes, loc=2, borderpad=0)
axins.tick_params(left=False, right=True, labelleft=False, labelright=True)

# Create an inset with a 2-tuple bounding box. Note that this creates a
# bbox without extent. This hence only makes sense when specifying
# width and height in absolute units (inches).
axins2 = inset_axes(ax, width=0.5, height=0.4,
                    bbox_to_anchor=(0.33, 0.25),
                    bbox_transform=ax.transAxes, loc=3, borderpad=0)


ax2 = fig.add_subplot(133)
ax2.set_xscale("log")
ax2.axis([1e-6, 1e6, -2, 6])

# Create inset in data coordinates using ax.transData as transform
axins3 = inset_axes(ax2, width="100%", height="100%",
                    bbox_to_anchor=(1e-2, 2, 1e3, 3),
                    bbox_transform=ax2.transData, loc=2, borderpad=0)

# Create an inset horizontally centered in figure coordinates and vertically
# bound to line up with the axes.
from matplotlib.transforms import blended_transform_factory
transform = blended_transform_factory(fig.transFigure, ax2.transAxes)
axins4 = inset_axes(ax2, width="16%", height="34%",
                    bbox_to_anchor=(0, 0, 1, 1),
                    bbox_transform=transform, loc=8, borderpad=0)

plt.show()