我有如下的情节:

import matplotlib.pyplot as plt

fig2 = plt.figure()
ax3 = fig2.add_subplot(2,1,1)
ax4 = fig2.add_subplot(2,1,2)
ax4.loglog(x1, y1)
ax3.loglog(x2, y2)
ax3.set_ylabel('hello')

我希望能够不仅为两个子图创建轴标签和标题,而且还可以为两个子图创建公共标签。例如,由于两个图具有相同的轴,我只需要一组x轴和y轴标签。但我确实希望每个次要情节都有不同的标题。

我尝试了几件事,但没有一件是正确的


当前回答

Plt.setp()将完成工作:

# plot something
fig, axs = plt.subplots(3,3, figsize=(15, 8), sharex=True, sharey=True)
for i, ax in enumerate(axs.flat):
    ax.scatter(*np.random.normal(size=(2,200)))
    ax.set_title(f'Title {i}')

# set labels
plt.setp(axs[-1, :], xlabel='x axis label')
plt.setp(axs[:, 0], ylabel='y axis label')

其他回答

matplotlib 3.4.0新增功能

现在有内置的方法来设置公共轴标签:

supxlabel Fig.supxlabel ('common xlabel ') supylabel fig supylabel('common ylabel ')


要重现OP的日志图(通用标签但独立标题):

x = np.arange(0.01, 10.01, 0.01)
y = 2 ** x

fig, (ax1, ax2) = plt.subplots(2, 1, constrained_layout=True)
ax1.loglog(y, x)
ax2.loglog(x, y)

# separate subplot titles
ax1.set_title('ax1.title')
ax2.set_title('ax2.title')

# common axis labels
fig.supxlabel('fig.supxlabel')
fig.supylabel('fig.supylabel')

# list loss and acc are your data
fig = plt.figure()
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)

ax1.plot(iteration1, loss)
ax2.plot(iteration2, acc)

ax1.set_title('Training Loss')
ax2.set_title('Training Accuracy')

ax1.set_xlabel('Iteration')
ax1.set_ylabel('Loss')

ax2.set_xlabel('Iteration')
ax2.set_ylabel('Accuracy')

下面是一种解决方案,您可以设置其中一个图的ylabel并调整它的位置,使其垂直居中。这样可以避免KYC提到的问题。

import numpy as np
import matplotlib.pyplot as plt

def set_shared_ylabel(a, ylabel, labelpad = 0.01):
    """Set a y label shared by multiple axes
    Parameters
    ----------
    a: list of axes
    ylabel: string
    labelpad: float
        Sets the padding between ticklabels and axis label"""

    f = a[0].get_figure()
    f.canvas.draw() #sets f.canvas.renderer needed below

    # get the center position for all plots
    top = a[0].get_position().y1
    bottom = a[-1].get_position().y0

    # get the coordinates of the left side of the tick labels 
    x0 = 1
    for at in a:
        at.set_ylabel('') # just to make sure we don't and up with multiple labels
        bboxes, _ = at.yaxis.get_ticklabel_extents(f.canvas.renderer)
        bboxes = bboxes.inverse_transformed(f.transFigure)
        xt = bboxes.x0
        if xt < x0:
            x0 = xt
    tick_label_left = x0

    # set position of label
    a[-1].set_ylabel(ylabel)
    a[-1].yaxis.set_label_coords(tick_label_left - labelpad,(bottom + top)/2, transform=f.transFigure)

length = 100
x = np.linspace(0,100, length)
y1 = np.random.random(length) * 1000
y2 = np.random.random(length)

f,a = plt.subplots(2, sharex=True, gridspec_kw={'hspace':0})
a[0].plot(x, y1)
a[1].plot(x, y2)
set_shared_ylabel(a, 'shared y label (a. u.)')

如果你不打算导出矢量图形,或者你已经设置了matplotlib后端来忽略无色轴,Wen-wei Liao的答案是很好的;否则隐藏的轴将显示在导出的图形中。

我的答案suplabel在这里类似于fig.suptitle,它使用fig.text函数。因此,没有斧头艺术家被创造和被制作成无色的。 然而,如果你尝试多次调用它,你会得到文本添加在对方的顶部(fig.suptitle也一样)。Wen-wei Liao的答案不是,因为fig.add_subplot(111)将返回相同的Axes对象,如果它已经创建。

我的函数也可以在创建图之后调用。

def suplabel(axis,label,label_prop=None,
             labelpad=5,
             ha='center',va='center'):
    ''' Add super ylabel or xlabel to the figure
    Similar to matplotlib.suptitle
    axis       - string: "x" or "y"
    label      - string
    label_prop - keyword dictionary for Text
    labelpad   - padding from the axis (default: 5)
    ha         - horizontal alignment (default: "center")
    va         - vertical alignment (default: "center")
    '''
    fig = pylab.gcf()
    xmin = []
    ymin = []
    for ax in fig.axes:
        xmin.append(ax.get_position().xmin)
        ymin.append(ax.get_position().ymin)
    xmin,ymin = min(xmin),min(ymin)
    dpi = fig.dpi
    if axis.lower() == "y":
        rotation=90.
        x = xmin-float(labelpad)/dpi
        y = 0.5
    elif axis.lower() == 'x':
        rotation = 0.
        x = 0.5
        y = ymin - float(labelpad)/dpi
    else:
        raise Exception("Unexpected axis: x or y")
    if label_prop is None: 
        label_prop = dict()
    pylab.text(x,y,label,rotation=rotation,
               transform=fig.transFigure,
               ha=ha,va=va,
               **label_prop)

Plt.setp()将完成工作:

# plot something
fig, axs = plt.subplots(3,3, figsize=(15, 8), sharex=True, sharey=True)
for i, ax in enumerate(axs.flat):
    ax.scatter(*np.random.normal(size=(2,200)))
    ax.set_title(f'Title {i}')

# set labels
plt.setp(axs[-1, :], xlabel='x axis label')
plt.setp(axs[:, 0], ylabel='y axis label')