绘图：Matplotlib

用于绘制一些数据图，同学推荐的，挺好用。非常好的官网文档：http://matplotlib.org/contents.html

0. 安装

可以直接pip install，还有一些依赖就按照提示来吧，具体也忘了。

1. 基本画图

import matplotlib.pyplot as plt
xs = [1,2,3,4]
ys = [1,2,3,4]
plt.plot(xs, ys)
plt.show()

xs表示点的x坐标，ys表示点的y坐标，所画的点就是(xs[i], ys[i])，默认情况下会依次用直线把点连起来。此时可以看到弹出一张过原点斜率为1的直线。注意show过后，不能再次show了，需要再plot画一次。说明这个plot模块是有状态的。

2. 散点

可以设置画图点的模式（markers），不使用直线将点连起来，而就是画个散点即可：

import matplotlib.pyplot as plt
xs = [1,2,3,4]
ys = [1,2,3,4]
plt.plot(xs, ys, "ob");
plt.show()

此时看到的就是几个离散的点。这里"ob"表示使用圆形的marker并且颜色是蓝色（blue），其中filled_markers可以是：

'o' - 圆点, 'v' - 倒三角, '^' - 正三角,  '<' - 左三角, '>' - 右三角, '8', 's' - 正方形, 'p' - 凸五边形, '*' - 五角星, 'h', 'H', 'D' - 菱形, 'd' - 扁菱形

All possible markers are defined here:

marker	description
”.”	point
”,”	pixel
“o”	circle
“v”	triangle_down
“^”	triangle_up
“<”	triangle_left
“>”	triangle_right
“1”	tri_down
“2”	tri_up
“3”	tri_left
“4”	tri_right
“8”	octagon
“s”	square
“p”	pentagon
“*”	star
“h”	hexagon1
“H”	hexagon2
“+”	plus
“x”	x
“D”	diamond
“d”	thin_diamond
“|”	vline
“_”	hline
TICKLEFT	tickleft
TICKRIGHT	tickright
TICKUP	tickup
TICKDOWN	tickdown
CARETLEFT	caretleft
CARETRIGHT	caretright
CARETUP	caretup
CARETDOWN	caretdown
“None”	nothing
None	nothing
” “	nothing
“”	nothing
'$...$'	render the string using mathtext.
verts	a list of (x, y) pairs used for Path vertices. The center of the marker is located at (0,0) and the size is normalized.
path	a Path instance.
(numsides, style, angle)	see below

 http://matplotlib.org/api/markers_api.html#module-matplotlib.markers

3. 填充数据

可以结合numpy来快速的填充数据，画出图形

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> x=np.arange(0, 4, 0.05)
>>> x
array([ 0.  ,  0.05,  0.1 ,  0.15,  0.2 ,  0.25,  0.3 ,  0.35,  0.4 ,
        0.45,  0.5 ,  0.55,  0.6 ,  0.65,  0.7 ,  0.75,  0.8 ,  0.85,
        0.9 ,  0.95,  1.  ,  1.05,  1.1 ,  1.15,  1.2 ,  1.25,  1.3 ,
        1.35,  1.4 ,  1.45,  1.5 ,  1.55,  1.6 ,  1.65,  1.7 ,  1.75,
        1.8 ,  1.85,  1.9 ,  1.95,  2.  ,  2.05,  2.1 ,  2.15,  2.2 ,
        2.25,  2.3 ,  2.35,  2.4 ,  2.45,  2.5 ,  2.55,  2.6 ,  2.65,
        2.7 ,  2.75,  2.8 ,  2.85,  2.9 ,  2.95,  3.  ,  3.05,  3.1 ,
        3.15,  3.2 ,  3.25,  3.3 ,  3.35,  3.4 ,  3.45,  3.5 ,  3.55,
        3.6 ,  3.65,  3.7 ,  3.75,  3.8 ,  3.85,  3.9 ,  3.95])
>>> plt.plot(x, np.sin(0.5 * np.pi * x))
[<matplotlib.lines.Line2D object at 0x11314a810>]
>>> plt.show()

 4. 线条样式

Controlling line properties

Lines have many attributes that you can set: linewidth, dash style, antialiased, etc; see matplotlib.lines.Line2D. There are several ways to set line properties

• Use keyword args:

  plt.plot(x, y, linewidth=2.0)
  

• Use the setter methods of the Line2D instance. plot returns a list of lines; e.g., line1, line2 = plot(x1,y1,x2,y2). Below I have only one line so it is a list of length 1. I use tuple unpacking in the line, = plot(x, y, 'o') to get the first element of the list:

  line, = plt.plot(x, y, '-')
  line.set_antialiased(False) # turn off antialising
  

• Use the setp() command. The example below uses a MATLAB-style command to set multiple properties on a list of lines. setpworks transparently with a list of objects or a single object. You can either use python keyword arguments or MATLAB-style string/value pairs:

  lines = plt.plot(x1, y1, x2, y2)
  # use keyword args
  plt.setp(lines, color='r', linewidth=2.0)
  # or MATLAB style string value pairs
  plt.setp(lines, 'color', 'r', 'linewidth', 2.0)
  

Here are the available Line2D properties.

Property	Value Type
alpha	float
animated	[True | False]
antialiased or aa	[True | False]
clip_box	a matplotlib.transform.Bbox instance
clip_on	[True | False]
clip_path	a Path instance and a Transform instance, a Patch
color or c	any matplotlib color
contains	the hit testing function
dash_capstyle	['butt' | 'round' | 'projecting']
dash_joinstyle	['miter' | 'round' | 'bevel']
dashes	sequence of on/off ink in points
data	(np.array xdata, np.array ydata)
figure	a matplotlib.figure.Figure instance
label	any string
linestyle or ls	[ '-' | '--' | '-.' | ':' | 'steps' | ...]
linewidth or lw	float value in points
lod	[True | False]
marker	[ '+' | ',' | '.' | '1' | '2' | '3' | '4' ]
markeredgecolor or mec	any matplotlib color
markeredgewidth or mew	float value in points
markerfacecolor or mfc	any matplotlib color
markersize or ms	float
markevery	[ None | integer | (startind, stride) ]
picker	used in interactive line selection
pickradius	the line pick selection radius
solid_capstyle	['butt' | 'round' | 'projecting']
solid_joinstyle	['miter' | 'round' | 'bevel']
transform	a matplotlib.transforms.Transform instance
visible	[True | False]
xdata	np.array
ydata	np.array
zorder	any number