Matplotlib入门[05]——注释与标签

参考：

• https://ailearning.apachecn.org/

• Matplotlib官网

• plt.legend参数

使用Jupyter进行练习

注释

使用文本框进行注释

import numpy.random
import matplotlib.pyplot as pltfig = plt.figure(1, figsize=(5,5))
# plt.clf()清除整个当前graphics的所有坐标轴，但会将窗口打开，
# 以便可以重新用于其他graphics。
fig.clf()ax = fig.add_subplot(111)
# y轴的单位刻度显示长度 与 x轴的单位刻度显示长度 的比例
ax.set_aspect(1)x1 = -1 + numpy.random.randn(100)
y1 = -1 + numpy.random.randn(100)
x2 = 1. + numpy.random.randn(100)
y2 = 1. + numpy.random.randn(100)# 散点图
ax.scatter(x1, y1, color="r")
ax.scatter(x2, y2, color="g")# 加上两个文本框
bbox_props = dict(boxstyle="round", fc="w", ec="0.5", alpha=0.9)
ax.text(-2, -2, "Sample A", ha="center", va="center", size=20,bbox=bbox_props)
ax.text(2, 2, "Sample B", ha="center", va="center", size=20,bbox=bbox_props)# 加上一个箭头文本框
bbox_props = dict(boxstyle="rarrow", fc=(0.8,0.9,0.9), ec="b", lw=2)
t = ax.text(0, 0, "Direction", ha="center", va="center", rotation=45,size=15,bbox=bbox_props)bb = t.get_bbox_patch()
bb.set_boxstyle("rarrow", pad=0.6)ax.set_xlim(-4, 4)
ax.set_ylim(-4, 4)plt.show()

​

text() 函数接受 bbox 参数来绘制文本框。

bbox_props = dict(boxstyle="rarrow,pad=0.3", fc="cyan", ec="b", lw=2)
t = ax.text(0, 0, "Direction", ha="center", va="center", rotation=45,size=15,bbox=bbox_props)

可以这样来获取这个文本框，并对其参数进行修改：

bb = t.get_bbox_patch()
bb.set_boxstyle("rarrow", pad=0.6)

可用的文本框风格有：

import matplotlib.patches as mpatch
import matplotlib.pyplot as pltstyles = mpatch.BoxStyle.get_styles()figheight = (len(styles)+.5)
fig1 = plt.figure(figsize=(4/1.5, figheight/1.5))
fontsize = 0.3 * 72
ax = fig1.add_subplot(111)for i, (stylename, styleclass) in enumerate(styles.items()):ax.text(0.5, (float(len(styles)) - 0.5 - i)/figheight, stylename,ha="center",size=fontsize,transform=fig1.transFigure,bbox=dict(boxstyle=stylename, fc="w", ec="k"))# 去掉轴的显示
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.spines['left'].set_color('none')
ax.spines['bottom'].set_color('none')
plt.xticks([])
plt.yticks([])plt.show()

​

各个风格的文本框如上图所示。

使用箭头进行注释

plt.figure(1, figsize=(4,3))
ax = plt.subplot(111)ax.annotate("",xy=(0.2, 0.2), xycoords='data',xytext=(0.8, 0.8), textcoords='data',arrowprops=dict(arrowstyle="->",connectionstyle="arc3"), )plt.show()

​

之前介绍了 annotate 中 xy, xycoords, xytext, textcoords 参数的含义，通常我们把 xy 设在 data 坐标系，把 xytext 设在 offset 即以注释点为原点的参考系。

箭头显示是可选的，用 arrowprops 参数来指定，接受一个字典作为参数。

不同类型的绘制箭头方式

import matplotlib.pyplot as plt
import matplotlib.patches as mpatchesx1, y1 = 0.3, 0.3
x2, y2 = 0.7, 0.7fig = plt.figure(1, figsize=(8,3))
fig.clf()
from mpl_toolkits.axes_grid.axes_grid import AxesGrid
from mpl_toolkits.axes_grid.anchored_artists import AnchoredText#from matplotlib.font_manager import FontPropertiesdef add_at(ax, t, loc=2):fp = dict(size=10)_at = AnchoredText(t, loc=loc, prop=fp)ax.add_artist(_at)return _atgrid = AxesGrid(fig, 111, (1, 4), label_mode="1", share_all=True)grid[0].set_autoscale_on(False)ax = grid[0]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",xy=(x1, y1), xycoords='data',xytext=(x2, y2), textcoords='data',arrowprops=dict(arrowstyle="-", #linestyle="dashed",color="0.5",patchB=None,shrinkB=0,connectionstyle="arc3,rad=0.3",),)add_at(ax, "connect", loc=2)ax = grid[1]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",xy=(x1, y1), xycoords='data',xytext=(x2, y2), textcoords='data',arrowprops=dict(arrowstyle="-", #linestyle="dashed",color="0.5",patchB=el,shrinkB=0,connectionstyle="arc3,rad=0.3",),)add_at(ax, "clip", loc=2)ax = grid[2]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",xy=(x1, y1), xycoords='data',xytext=(x2, y2), textcoords='data',arrowprops=dict(arrowstyle="-", #linestyle="dashed",color="0.5",patchB=el,shrinkB=5,connectionstyle="arc3,rad=0.3",),)add_at(ax, "shrink", loc=2)ax = grid[3]
ax.plot([x1, x2], [y1, y2], ".")
el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
ax.add_artist(el)
ax.annotate("",xy=(x1, y1), xycoords='data',xytext=(x2, y2), textcoords='data',arrowprops=dict(arrowstyle="fancy", #linestyle="dashed",color="0.5",patchB=el,shrinkB=5,connectionstyle="arc3,rad=0.3",),)add_at(ax, "mutate", loc=2)grid[0].set_xlim(0, 1)
grid[0].set_ylim(0, 1)
grid[0].axis["bottom"].toggle(ticklabels=False)
grid[0].axis["left"].toggle(ticklabels=False)
fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95)plt.draw()
plt.show()

C:\Users\26969\AppData\Local\Temp\ipykernel_2156\2823481789.py:9: MatplotlibDeprecationWarning: 
The mpl_toolkits.axes_grid module was deprecated in Matplotlib 2.1 and will be removed two minor releases later. Use mpl_toolkits.axes_grid1 and mpl_toolkits.axisartist, which provide the same functionality instead.from mpl_toolkits.axes_grid.axes_grid import AxesGrid

字典中，connectionstyle 参数控制路径的风格：

import matplotlib.pyplot as plt
import matplotlib.patches as mpatchesfig = plt.figure(1, figsize=(8,5))
fig.clf()
from mpl_toolkits.axes_grid.axes_grid import AxesGrid
from mpl_toolkits.axes_grid.anchored_artists import AnchoredText#from matplotlib.font_manager import FontPropertiesdef add_at(ax, t, loc=2):fp = dict(size=8)_at = AnchoredText(t, loc=loc, prop=fp)ax.add_artist(_at)return _atgrid = AxesGrid(fig, 111, (3, 5), label_mode="1", share_all=True)grid[0].set_autoscale_on(False)x1, y1 = 0.3, 0.3
x2, y2 = 0.7, 0.7def demo_con_style(ax, connectionstyle, label=None):if label is None:label = connectionstylex1, y1 = 0.3, 0.2x2, y2 = 0.8, 0.6ax.plot([x1, x2], [y1, y2], ".")ax.annotate("",xy=(x1, y1), xycoords='data',xytext=(x2, y2), textcoords='data',arrowprops=dict(arrowstyle="->", #linestyle="dashed",color="0.5",shrinkA=5, shrinkB=5,patchA=None,patchB=None,connectionstyle=connectionstyle,),)add_at(ax, label, loc=2)column = grid.axes_column[0]demo_con_style(column[0], "angle3,angleA=90,angleB=0",label="angle3,\nangleA=90,\nangleB=0")
demo_con_style(column[1], "angle3,angleA=0,angleB=90",label="angle3,\nangleA=0,\nangleB=90")column = grid.axes_column[1]demo_con_style(column[0], "arc3,rad=0.")
demo_con_style(column[1], "arc3,rad=0.3")
demo_con_style(column[2], "arc3,rad=-0.3")column = grid.axes_column[2]demo_con_style(column[0], "angle,angleA=-90,angleB=180,rad=0",label="angle,\nangleA=-90,\nangleB=180,\nrad=0")
demo_con_style(column[1], "angle,angleA=-90,angleB=180,rad=5",label="angle,\nangleA=-90,\nangleB=180,\nrad=5")
demo_con_style(column[2], "angle,angleA=-90,angleB=10,rad=5",label="angle,\nangleA=-90,\nangleB=10,\nrad=0")column = grid.axes_column[3]demo_con_style(column[0], "arc,angleA=-90,angleB=0,armA=30,armB=30,rad=0",label="arc,\nangleA=-90,\nangleB=0,\narmA=30,\narmB=30,\nrad=0")
demo_con_style(column[1], "arc,angleA=-90,angleB=0,armA=30,armB=30,rad=5",label="arc,\nangleA=-90,\nangleB=0,\narmA=30,\narmB=30,\nrad=5")
demo_con_style(column[2], "arc,angleA=-90,angleB=0,armA=0,armB=40,rad=0",label="arc,\nangleA=-90,\nangleB=0,\narmA=0,\narmB=40,\nrad=0")column = grid.axes_column[4]demo_con_style(column[0], "bar,fraction=0.3",label="bar,\nfraction=0.3")
demo_con_style(column[1], "bar,fraction=-0.3",label="bar,\nfraction=-0.3")
demo_con_style(column[2], "bar,angle=180,fraction=-0.2",label="bar,\nangle=180,\nfraction=-0.2")#demo_con_style(column[1], "arc3,rad=0.3")
#demo_con_style(column[2], "arc3,rad=-0.3")grid[0].set_xlim(0, 1)
grid[0].set_ylim(0, 1)
grid.axes_llc.axis["bottom"].toggle(ticklabels=False)
grid.axes_llc.axis["left"].toggle(ticklabels=False)
fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95)plt.draw()
plt.show()

​

arrowstyle 参数控制小箭头的风格：

import matplotlib.patches as mpatches
import matplotlib.pyplot as pltstyles = mpatches.ArrowStyle.get_styles()ncol=2
nrow = (len(styles)+1) // ncol
figheight = (nrow+0.5)
fig1 = plt.figure(1, (4.*ncol/1.5, figheight/1.5))
fontsize = 0.2 * 70ax = fig1.add_axes([0, 0, 1, 1], frameon=False, aspect=1.)ax.set_xlim(0, 4*ncol)
ax.set_ylim(0, figheight)def to_texstring(s):s = s.replace("<", r"$<$")s = s.replace(">", r"$>$")s = s.replace("|", r"$|$")return sfor i, (stylename, styleclass) in enumerate(sorted(styles.items())):x = 3.2 + (i//nrow)*4y = (figheight - 0.7 - i%nrow) # /figheightp = mpatches.Circle((x, y), 0.2, fc="w")ax.add_patch(p)ax.annotate(to_texstring(stylename), (x, y),(x-1.2, y),#xycoords="figure fraction", textcoords="figure fraction",ha="right", va="center",size=fontsize,arrowprops=dict(arrowstyle=stylename,patchB=p,shrinkA=5,shrinkB=5,fc="w", ec="k",connectionstyle="arc3,rad=-0.05",),bbox=dict(boxstyle="square", fc="w"))ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)plt.draw()
plt.show()

​

标签

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

legend() 函数被用来添加图像的标签，其主要相关的属性有：

• legend entry - 一个 legend 包含一个或多个 entry，一个 entry 对应一个 key 和一个 label
• legend key - marker 的标记
• legend label - key 的说明
• legend handle - 一个 entry 在图上对应的对象

使用legend

参数：

• loc: 显示位置，若是使用了bbox_to_anchor，则这项就无效了

  • ‘best’ : 0, (only implemented for axes legends)(自适应方式)
  • ‘upper right’ : 1,
  • ‘upper left’ : 2,
  • ‘lower left’ : 3,
  • ‘lower right’ : 4,
  • ‘right’ : 5,
  • ‘center left’ : 6,
  • ‘center right’ : 7,
  • ‘lower center’ : 8,
  • ‘upper center’ : 9,
  • ‘center’ : 10

• fontsize： 字体大小，

• frameon： 是否显示图例边框，

• ncol： 图例的列的数量，一般为1,

• title: 为图例添加标题

• shadow: 为图例边框添加阴影,

• markerfirst: True表示图例标签在句柄右侧，false反之，

• markerscale： 图例标记为原图标记中的多少倍大小，

• numpoints: 表示图例中的句柄上的标记点的个数，一般设为1,

• fancybox: 是否将图例框的边角设为圆形

• framealpha: 控制图例框的透明度

• borderpad: 图例框内边距

• labelspacing: 图例中条目之间的距离

• handlelength: 图例句柄的长度

• bbox_to_anchor: (横向看右，纵向看下),如果要自定义图例位置或者将图例画在坐标外边，用它。

调用 legend() 会自动获取当前的 Axes 对象，并且得到这些 handles 和 labels，相当于：

handles, labels = ax.get_legend_handles_labels()
ax.legend(handles, labels) 

可以在函数中指定 handles 的参数：

line_up, = plt.plot([1,2,3], label='Line 2')
line_down, = plt.plot([3,2,1], label='Line 1')
plt.legend(handles=[line_up, line_down])
plt.show()

​

可以将 labels 作为参数输入 legend 函数：

line_up, = plt.plot([1,2,3])
line_down, = plt.plot([3,2,1])
plt.legend([line_up, line_down], ['Line Up', 'Line Down'])
plt.show()

​

特殊形状的maker key

块状

# 拥有一些比较常用的形状：箭头、正方形、椭圆等
import matplotlib.patches as mpatchesred_patch = mpatches.Patch(color='red', label='The red data')
plt.legend(handles=[red_patch])plt.show()

​

点线组合

import matplotlib.lines as mlines
import matplotlib.pyplot as pltblue_line = mlines.Line2D([1,2,3], [1,2,3], color='blue', marker='*',markersize=15, label='Blue stars')
plt.plot([1,2,3,4,5,6,7],'b*-')
plt.legend(handles=[blue_line])plt.show()

​

指定legend的位置

bbox_to_anchor 关键词可以指定 legend 放置的位置，例如放到图像的右上角：

plt.plot([1,2,3], label="test1")
plt.plot([3,2,1], label="test2")
plt.legend(bbox_to_anchor=(1, 1),bbox_transform=plt.gcf().transFigure)plt.show()

​

plt.subplot(211)
plt.plot([1,2,3], label="test1")
plt.plot([3,2,1], label="test2")
# 将标签放在图像上方，并进行延长
plt.legend(bbox_to_anchor=(0., 1.02, 1., .102),ncol=2, mode="expand", borderaxespad=0.)plt.subplot(223)
plt.plot([1,2,3], label="test1")
plt.plot([3,2,1], label="test2")
# 将标签放在小图形的右方
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)plt.show()

​

同一个 Axes 中的多个 legend

原始效果：

line1, = plt.plot([1,2,3], label="Line 1", linestyle='--')
line2, = plt.plot([3,2,1], label="Line 2", linewidth=4)
plt.legend()
plt.show()

​

添加多个legend:

line1, = plt.plot([1,2,3], label="Line 1", linestyle='--')
line2, = plt.plot([3,2,1], label="Line 2", linewidth=4)
# 为第一条线添加legend
first_legend = plt.legend(handles=[line1], loc=1)# 将legend手动添加到当前的Axes.
ax = plt.gca().add_artist(first_legend)# 为第二条线添加legend
plt.legend(handles=[line2], loc=4)plt.show()

​

更多用法

多个handle可以通过括号组合在一个entry里。

from numpy.random import randnz = randn(10)red_dot, = plt.plot(z, "ro", markersize=15)
# 给数据加上白色十字.
white_cross, = plt.plot(z[:5], "w+", markeredgewidth=3, markersize=15)plt.legend([red_dot, (red_dot, white_cross)], ["Attr A", "Attr A+B"])plt.show()

​

自定义handle：

import matplotlib.pyplot as plt
import matplotlib.patches as mpatchesclass AnyObject(object):passclass AnyObjectHandler(object):def legend_artist(self, legend, orig_handle, fontsize, handlebox):x0, y0 = handlebox.xdescent, handlebox.ydescentwidth, height = handlebox.width, handlebox.heightpatch = mpatches.Rectangle([x0, y0], width, height, facecolor='red',edgecolor='black', hatch='xx', lw=3,transform=handlebox.get_transform())handlebox.add_artist(patch)return patchplt.legend([AnyObject()], ['My first handler'],handler_map={AnyObject: AnyObjectHandler()})plt.show()

椭圆

from matplotlib.legend_handler import HandlerPatch
import matplotlib.pyplot as plt
import matplotlib.patches as mpatchesclass HandlerEllipse(HandlerPatch):def create_artists(self, legend, orig_handle,xdescent, ydescent, width, height, fontsize, trans):center = 0.5 * width - 0.5 * xdescent, 0.5 * height - 0.5 * ydescentp = mpatches.Ellipse(xy=center, width=width + xdescent,height=height + ydescent)self.update_prop(p, orig_handle, legend)p.set_transform(trans)return [p]c = mpatches.Circle((0.5, 0.5), 0.25, facecolor="green",edgecolor="red", linewidth=3)
plt.gca().add_patch(c)plt.legend([c], ["An ellipse, not a rectangle"],handler_map={mpatches.Circle: HandlerEllipse()})plt.show()

​