scikit-learn：matplotlib.pyplot经常使用绘图功能总结（1）

參考：http://matplotlib.org/api/pyplot_api.html

绘图功能总结（2）：http://blog.csdn.net/mmc2015/article/details/48222611

1、matplotlib.pyplot.plot(*args, **kwargs)。最简单的沿坐标轴划线函数：

以下四种格式都合法：

plot(x, y)        # plot x and y using default line style and color

plot(x, y, 'bo')  # plot x and y using blue circle markers

plot(y)           # plot y using x as index array 0..N-1

plot(y, 'r+')     # ditto, but with red plusses

<pre name="code" class="python">import numpy as np

import matplotlib.pyplot as plt

x1=np.arange(0,5,0.1)

y1=np.sin(x1)

x2=np.linspace(1,10,20,True)

y2=np.cos(x2)

plt.plot(x1,y1,'b^')

watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQv/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70/gravity/Center" alt="">

也能够同一时候画一组图：

plt.plot(x1, y1, 'go', x2, y2, 'r-')

假设颜色不显示指出，则默认循环使用不同的颜色，支持的颜色有：

character	color
‘b’	blue
‘g’	green
‘r’	red
‘c’	cyan
‘m’	magenta
‘y’	yellow
‘k’	black
‘w’	white

支持的line style有：

character	description
'-'	solid line style
'--'	dashed line style
'-.'	dash-dot line style
':'	dotted line style
'.'	point marker
','	pixel marker
'o'	circle marker
'v'	triangle_down marker
'^'	triangle_up marker
'<'	triangle_left marker
'>'	triangle_right marker
'1'	tri_down marker
'2'	tri_up marker
'3'	tri_left marker
'4'	tri_right marker
's'	square marker
'p'	pentagon marker
'*'	star marker
'h'	hexagon1 marker
'H'	hexagon2 marker
'+'	plus marker
'x'	x marker
'D'	diamond marker
'd'	thin_diamond marker
'|'	vline marker
'_'	hline marker

加入图例：

plt.plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)

plt.plot([1,2,3], [1,4,9], 'rs',  label='line 2')

plt.legend()

指定坐标范围：

plt.plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)

plt.plot([1,2,3], [1,4,9], 'rs',  label='line 2')

plt.<strong>axis(</strong>[0, 4, 0, 10])

plt.legend()

watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQv/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70/gravity/Center" alt="">

加入坐标轴说明和标题说明：

plt.plot([1,2,3], [1,2,3], 'go-', <strong>label=</strong>'line 1', linewidth=2)

plt.plot([1,2,3], [1,4,9], 'rs',  label='line 2')

plt.axis([0, 4, 0, 10])

plt.<strong>xlabel</strong>('data x')

plt.ylabel('target y')

plt.<strong>title</strong>('test plot')

plt.<strong>legend()</strong>

加入网格：

plt.grid()

plt.legend(['3','4','5'], loc='upper right')

plt.show()

上面全部的格式都能够通过关键词来控制（格式，即參数kwargs）：

plot(x, y, color='green', linestyle='dashed', marker='o', markerfacecolor='blue', markersize=12).

The kwargs are Line2D properties：

Property	Description
agg_filter	unknown
alpha	float (0.0 transparent through 1.0 opaque)
animated	[True | False]
antialiased or aa	[True | False]
axes	an Axes instance
clip_box	a matplotlib.transforms.Bbox instance
clip_on	[True | False]
clip_path	[ (Path, Transform) | Patch | None ]
color or c	any matplotlib color
contains	a callable function
dash_capstyle	[‘butt’ | ‘round’ | ‘projecting’]
dash_joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
dashes	sequence of on/off ink in points
drawstyle	[‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’]
figure	a matplotlib.figure.Figure instance
fillstyle	[‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’ | ‘none’]
gid	an id string
label	string or anything printable with ‘%s’ conversion.
linestyle or ls	['-' | '--' | '-.' | ':' | 'None' | ' ' | '']
linewidth or lw	float value in points
lod	[True | False]
marker	A valid marker style
markeredgecolor or mec	any matplotlib color
markeredgewidth or mew	float value in points
markerfacecolor or mfc	any matplotlib color
markerfacecoloralt or mfcalt	any matplotlib color
markersize or ms	float
markevery	[None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float]
path_effects	unknown
picker	float distance in points or callable pick function fn(artist, event)
pickradius	float distance in points
rasterized	[True | False | None]
sketch_params	unknown
snap	unknown
solid_capstyle	[‘butt’ | ‘round’ | ‘projecting’]
solid_joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
transform	a matplotlib.transforms.Transform instance
url	a url string
visible	[True | False]
xdata	1D array
ydata	1D array
zorder	any number

2、matplotlib.pyplot.scatter(x, y, s=20, c=u'b', marker=u'o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None,verts=None, hold=None, **kwargs)散点图：

本质上和plot没甚差别。但要注意：

1）不能同一时候画多个曲线，plt.scatter(x1, y1, c='b', marker='o', x2, y2, c='r', marker='^', s=5)不合法。

2）color、marker等不能同一时候作为一个參数，plt.scatter(x1, y1, 'bo', s=5)不合法。

3）给个样例：

plt.scatter(x1, y1, c='b', marker='o', s=5)

4）我们看到，scatter会自己主动在坐标的头尾加上“延长”的部分，但plot假设不指定axis，则不会延长。

5）为了同一时候在一个图上画多条曲线。能够使用holdkeyword：

（When hold is True,
subsequent plot commands will be added to the current axes. When hold is False,
the current axes and figure will be cleared on the next plot command.）

plt.scatter(x1, y1, s=10, c='b', marker='o', label='test plot 1')

plt.<strong>hold(True)</strong>

plt.scatter(x2, y2, s=5, c='r', marker='^', label='test plot 2')

plt.legend()

watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQv/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70/gravity/Center" alt="">

假设不使用hold，效果例如以下：

plt.scatter(x1, y1, s=10, c='b', marker='o', label='test plot 1')

plt.hold(<strong>False)</strong>

plt.scatter(x2, y2, s=5, c='r', marker='^', label='test plot 2')

plt.legend()

待续。。。。

scikit-learn：matplotlib.pyplot经常使用绘图功能总结（1）的相关教程结束。