python - matplotlib：多个箱线图的插入轴

Question

我在 matplotlib 中有一些箱线图，我想使用插入轴放大特定的 y 范围（[0,0.1]）。从文档中的示例中我不清楚我应该如何为同一图中的多个箱线图执行此操作。我试图修改此示例提供的代码，但有太多不必要的复杂性。我的代码很简单：

# dataToPlot is a list of lists, containing some data. 
plt.figure()
plt.boxplot(dataToPlot)
plt.savefig( 'image.jpeg', bbox_inches=0)

如何添加插入轴并放大两者的第一个箱线图？我怎样才能为两者做到这一点？

编辑：我尝试了下面的代码，但这是我得到的：

什么地方出了错？

# what's the meaning of these two parameters?
fig = plt.figure(1, [5,4])
# what does 111 mean?
ax = fig.add_subplot(111)
ax.boxplot(data)
# ax.set_xlim(0,21)  # done automatically based on the no. of samples, right?
# ax.set_ylim(0,300) # done automatically based on max value in my samples, right?
# Create the zoomed axes
axins = zoomed_inset_axes(ax, 6, loc=1) # zoom = 6, location = 1 (upper right)
axins.boxplot(data)
# sub region of the original image
#here I am selecting the first boxplot by choosing appropriate values for x1 and x2 
# on the y-axis, I'm selecting the range which I want to zoom in, right?
x1, x2, y1, y2 = 0.9, 1.1, 0.0, 0.01
axins.set_xlim(x1, x2)
axins.set_ylim(y1, y2)
# even though it's false, I still see all numbers on both axes, how do I remove them?
plt.xticks(visible=False)
plt.yticks(visible=False)
# draw a bbox of the region of the inset axes in the parent axes and
# connecting lines between the bbox and the inset axes area
# what are fc and ec here? where do loc1 and loc2 come from?
mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
plt.savefig( 'img.jpeg', bbox_inches=0)

Answer 1

loc确定缩放轴的位置，1 代表，upper right2 代表upper left以此类推。我稍微修改了示例代码以生成多个缩放轴。

import matplotlib.pyplot as plt

from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
from mpl_toolkits.axes_grid1.inset_locator import mark_inset

import numpy as np

def get_demo_image():
    from matplotlib.cbook import get_sample_data
    import numpy as np
    f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
    z = np.load(f)
    # z is a numpy array of 15x15
    return z, (-3,4,-4,3)


fig = plt.figure(1, [5,4])
ax = fig.add_subplot(111)

# prepare the demo image
Z, extent = get_demo_image()
Z2 = np.zeros([150, 150], dtype="d")
ny, nx = Z.shape
Z2[30:30+ny, 30:30+nx] = Z

# extent = [-3, 4, -4, 3]
ax.imshow(Z2, extent=extent, interpolation="nearest",
          origin="lower")

axins = zoomed_inset_axes(ax, 6, loc=1) # zoom = 6
axins.imshow(Z2, extent=extent, interpolation="nearest",
             origin="lower")

# sub region of the original image
x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
axins.set_xlim(x1, x2)
axins.set_ylim(y1, y2)

axins1 = zoomed_inset_axes(ax, 8, loc=2) # zoom = 8
axins1.imshow(Z2, extent=extent, interpolation="nearest",
             origin="lower")

# sub region of the original image
x1, x2, y1, y2 = -1.2, -0.9, -2.2, -1.9
axins1.set_xlim(x1, x2)
axins1.set_ylim(y1, y2)

plt.xticks(visible=False)
plt.yticks(visible=False)

# draw a bbox of the region of the inset axes in the parent axes and
# connecting lines between the bbox and the inset axes area
mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
mark_inset(ax, axins1, loc1=2, loc2=4, fc="none", ec="0.5")

plt.draw()
plt.show()

编辑1：

同样，您也可以在箱线图中添加缩放轴。这是一个例子

from pylab import *
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
from mpl_toolkits.axes_grid1.inset_locator import mark_inset

# fake up some data
spread = rand(50) * 100 
center = ones(25) * 50
flier_high = rand(10) * 100 + 100
flier_low = rand(10) * -100
data = concatenate((spread, center, flier_high, flier_low), 0)

# fake up some more data
spread= rand(50) * 100
center = ones(25) * 40
flier_high = rand(10) * 100 + 100
flier_low = rand(10) * -100
d2 = concatenate( (spread, center, flier_high, flier_low), 0 )
data.shape = (-1, 1)
d2.shape = (-1, 1)
data = [data, d2, d2[::2,0]]

# multiple box plots on one figure
fig = plt.figure(1, [5,4])
ax = fig.add_subplot(111)
ax.boxplot(data)
ax.set_xlim(0.5,5)
ax.set_ylim(0,300)

# Create the zoomed axes
axins = zoomed_inset_axes(ax, 3, loc=1) # zoom = 3, location = 1 (upper right)
axins.boxplot(data)

# sub region of the original image
x1, x2, y1, y2 = 0.9, 1.1, 125, 175
axins.set_xlim(x1, x2)
axins.set_ylim(y1, y2)
plt.xticks(visible=False)
plt.yticks(visible=False)

# draw bboxes of the two regions of the inset axes in the parent axes and
# connect lines between the bbox and the inset axes area
mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")

show() 

编辑2

如果分布是异质的，即大多数值很小而很少有非常大的值，上述缩放过程可能不起作用，因为它会缩放轴x和y轴。在这种情况下，最好将 的比例更改y-axis为log。

from pylab import *

# fake up some data
spread = rand(50) * 1
center = ones(25) * .5
flier_high = rand(10) * 100 + 100
flier_low = rand(10) * -100
data = concatenate((spread, center, flier_high, flier_low), 0)

# fake up some more data
spread = rand(50) * 1
center = ones(25) * .4
flier_high = rand(10) * 100 + 100
flier_low = rand(10) * -100
d2 = concatenate( (spread, center, flier_high, flier_low), 0 )
data.shape = (-1, 1)
d2.shape = (-1, 1)
data = [data, d2, d2[::2,0]]

# multiple box plots on one figure
fig = plt.figure(1, [5,4]) # Figure Size
ax = fig.add_subplot(111)  # Only 1 subplot 
ax.boxplot(data)
ax.set_xlim(0.5,5)
ax.set_ylim(.1,300)
ax.set_yscale('log')

show()