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 |