mirror of
https://github.com/apachecn/ailearning.git
synced 2026-02-10 05:45:40 +08:00
308 lines
142 KiB
Markdown
308 lines
142 KiB
Markdown
# 处理文本（基础）
|
||
|
||
In [1]:
|
||
|
||
```py
|
||
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）
|
||
|
||
In [2]:
|
||
|
||
```py
|
||
# -*- 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, unicode('unicode: Institut f\374r Festk\366rperphysik', 'latin-1'))
|
||
|
||
# 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。
|
||
|
||
* `horizontalalignment` or `ha` ：x 位置参数表示的位置
|
||
* `verticalalignment` or `va`：y 位置参数表示的位置
|
||
* `multialignment`：多行位置控制
|
||
|
||
In [3]:
|
||
|
||
```py
|
||
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 + height
|
||
|
||
fig = 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`：
|
||
|
||
In [4]:
|
||
|
||
```py
|
||
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：
|
||
|
||
In [5]:
|
||
|
||
```py
|
||
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`：
|
||
|
||
In [6]:
|
||
|
||
```py
|
||
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, radius
|
||
xytext=(0.05, 0.05), # fraction, fraction
|
||
textcoords='figure fraction',
|
||
arrowprops=dict(facecolor='black', shrink=0.05),
|
||
horizontalalignment='left',
|
||
verticalalignment='bottom',
|
||
)
|
||
plt.show()
|
||
|
||
```
|
||
|
||
 |