处理文本
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
matplotlib 对文本的支持十分完善，包括数学公式，Unicode 文字，栅格和向量化输出，文字换行，文字旋转等一系列操作。
基础文本函数
在 matplotlib.pyplot 中，基础的文本函数如下：
text()在Axes对象的任意位置添加文本xlabel()添加 x 轴标题ylabel()添加 y 轴标题title()给Axes对象添加标题figtext()在Figure对象的任意位置添加文本suptitle()给Figure对象添加标题anotate()给Axes对象添加注释（可选择是否添加箭头标记）
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
%matplotlib inline# plt.figure() 返回一个 Figure() 对象
fig = plt.figure(figsize=(12, 9))# 设置这个 Figure 对象的标题
# 事实上，如果我们直接调用 plt.suptitle() 函数，它会自动找到当前的 Figure 对象
fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')# Axes 对象表示 Figure 对象中的子图
# 这里只有一幅图像，所以使用 add_subplot(111)
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)# 可以直接使用 set_xxx 的方法来设置标题
ax.set_title('axes title')
# 也可以直接调用 title()，因为会自动定位到当前的 Axes 对象
# plt.title('axes title')ax.set_xlabel('xlabel')
ax.set_ylabel('ylabel')# 添加文本，斜体加文本框
ax.text(3, 8, 'boxed italics text in data coords', style='italic',bbox={'facecolor':'red', 'alpha':0.5, 'pad':10})# 数学公式，用 $$ 输入 Tex 公式
ax.text(2, 6, r'an equation: $E=mc^2$', fontsize=15)# Unicode 支持
ax.text(3, 2, u'unicode: Institut für Festkörperphysik')# 颜色，对齐方式
ax.text(0.95, 0.01, 'colored text in axes coords',verticalalignment='bottom', horizontalalignment='right',transform=ax.transAxes,color='green', fontsize=15)# 注释文本和箭头
ax.plot([2], [1], 'o')
ax.annotate('annotate', xy=(2, 1), xytext=(3, 4),arrowprops=dict(facecolor='black', shrink=0.05))# 设置显示范围
ax.axis([0, 10, 0, 10])plt.show()
文本属性和布局
我们可以通过下列关键词，在文本函数中设置文本的属性：
| 关键词 | 值 |
|---|---|
| alpha | float |
| backgroundcolor | any matplotlib color |
| bbox | rectangle prop dict plus key 'pad' which is a pad in points |
| clip_box | a matplotlib.transform.Bbox instance |
| clip_on | [True ， False] |
| clip_path | a Path instance and a Transform instance, a Patch |
| color | any matplotlib color |
| family | [ 'serif' , 'sans-serif' , 'cursive' , 'fantasy' , 'monospace' ] |
| fontproperties | a matplotlib.font_manager.FontProperties instance |
| horizontalalignment or ha | [ 'center' , 'right' , 'left' ] |
| label | any string |
| linespacing | float |
| multialignment | ['left' , 'right' , 'center' ] |
| name or fontname | string e.g., ['Sans' , 'Courier' , 'Helvetica' …] |
| picker | [None,float,boolean,callable] |
| position | (x,y) |
| rotation | [ angle in degrees 'vertical' , 'horizontal' |
| size or fontsize | [ size in points , relative size, e.g., 'smaller', 'x-large' ] |
| style or fontstyle | [ 'normal' , 'italic' , 'oblique'] |
| text | string or anything printable with ‘%s’ conversion |
| transform | a matplotlib.transform transformation instance |
| variant | [ 'normal' , 'small-caps' ] |
| verticalalignment or va | [ 'center' , 'top' , 'bottom' , 'baseline' ] |
| visible | [True , False] |
| weight or fontweight | [ 'normal' , 'bold' , 'heavy' , 'light' , 'ultrabold' , 'ultralight'] |
| x | float |
| y | float |
| zorder | any number |
其中 va, ha, multialignment 可以用来控制布局。
horizontalalignmentorha：x 位置参数表示的位置verticalalignmentorva：y 位置参数表示的位置multialignment：多行位置控制
import matplotlib.pyplot as plt
import matplotlib.patches as patches# build a rectangle in axes coords
left, width = .25, .5
bottom, height = .25, .5
right = left + width
top = bottom + heightfig = plt.figure(figsize=(10,7))
ax = fig.add_axes([0,0,1,1])# axes coordinates are 0,0 is bottom left and 1,1 is upper right
p = patches.Rectangle((left, bottom), width, height,fill=False, transform=ax.transAxes, clip_on=False)ax.add_patch(p)ax.text(left, bottom, 'left top',horizontalalignment='left',verticalalignment='top',transform=ax.transAxes,size='xx-large')ax.text(left, bottom, 'left bottom',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes,size='xx-large')ax.text(right, top, 'right bottom',horizontalalignment='right',verticalalignment='bottom',transform=ax.transAxes,size='xx-large')ax.text(right, top, 'right top',horizontalalignment='right',verticalalignment='top',transform=ax.transAxes,size='xx-large')ax.text(right, bottom, 'center top',horizontalalignment='center',verticalalignment='top',transform=ax.transAxes,size='xx-large')ax.text(left, 0.5*(bottom+top), 'right center',horizontalalignment='right',verticalalignment='center',rotation='vertical',transform=ax.transAxes,size='xx-large')ax.text(left, 0.5*(bottom+top), 'left center',horizontalalignment='left',verticalalignment='center',rotation='vertical',transform=ax.transAxes,size='xx-large')ax.text(0.5*(left+right), 0.5*(bottom+top), 'middle',horizontalalignment='center',verticalalignment='center',fontsize=20, color='red',transform=ax.transAxes)ax.text(right, 0.5*(bottom+top), 'centered',horizontalalignment='center',verticalalignment='center',rotation='vertical',transform=ax.transAxes,size='xx-large')ax.text(left, top, 'rotated\nwith newlines',horizontalalignment='center',verticalalignment='center',rotation=45,transform=ax.transAxes,size='xx-large')ax.set_axis_off()
plt.show()
注释文本
text() 函数在 Axes 对象的指定位置添加文本，而 annotate() 则是对某一点添加注释文本，需要考虑两个位置：一是注释点的坐标 xy ，二是注释文本的位置坐标 xytext：
fig = plt.figure()
ax = fig.add_subplot(111)t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2*np.pi*t)
line, = ax.plot(t, s, lw=2)ax.annotate('local max', xy=(2, 1), xytext=(3, 1.5),arrowprops=dict(facecolor='black', shrink=0.05),)ax.set_ylim(-2,2)
plt.show()
在上面的例子中，两个左边使用的都是原始数据的坐标系，不过我们还可以通过 xycoords 和 textcoords 来设置坐标系（默认是 'data'）：
| 参数 | 坐标系 |
|---|---|
| ‘figure points’ | points from the lower left corner of the figure |
| ‘figure pixels’ | pixels from the lower left corner of the figure |
| ‘figure fraction’ | 0,0 is lower left of figure and 1,1 is upper right |
| ‘axes points’ | points from lower left corner of axes |
| ‘axes pixels’ | pixels from lower left corner of axes |
| ‘axes fraction’ | 0,0 is lower left of axes and 1,1 is upper right |
| ‘data’ | use the axes data coordinate system |
使用一个不同的坐标系：
fig = plt.figure()
ax = fig.add_subplot(111)t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2*np.pi*t)
line, = ax.plot(t, s, lw=2)ax.annotate('local max', xy=(3, 1), xycoords='data',xytext=(0.8, 0.95), textcoords='axes fraction',arrowprops=dict(facecolor='black', shrink=0.05),horizontalalignment='right', verticalalignment='top',)ax.set_ylim(-2,2)
plt.show()
极坐标系注释文本
产生极坐标系需要在 subplot 的参数中设置 polar=True：
fig = plt.figure()
ax = fig.add_subplot(111, polar=True)
r = np.arange(0,1,0.001)
theta = 2*2*np.pi*r
line, = ax.plot(theta, r, color='#ee8d18', lw=3)ind = 800
thisr, thistheta = r[ind], theta[ind]
ax.plot([thistheta], [thisr], 'o')
ax.annotate('a polar annotation',xy=(thistheta, thisr), # theta, radiusxytext=(0.05, 0.05), # fraction, fractiontextcoords='figure fraction',arrowprops=dict(facecolor='black', shrink=0.05),horizontalalignment='left',verticalalignment='bottom',)
plt.show()
