matplotlib学习笔记--Legend
转载于：
http://blog.sina.com.cn/s/blog_b09d460201019c10.html
legend 显示图例
1 legend基础
函数原型 legend(*args, **kwargs)
当len(args) == 2
args 是[artist]和[label]的集合
当len(args) == 0
args会自动调用get_legend_handles_labels()生成
等价于
handles, labels = ax.get_legend_handles_labels()
ax.legend(handles, labels)
ax.get_legend_handles_labels()的作用在于返回ax.lines, ax.patch所有对象以及ax.collection中的LineCollection or RegularPolyCollection对象
注意：这里只提供有限支持, 并不是所有的artist都可以被用作图例，比如errorbar支持不完善
1.1 调整顺序
ax = subplot(1,1,1)
p1, = ax.plot([1,2,3], label="line 1")
p2, = ax.plot([3,2,1], label="line 2")
p3, = ax.plot([2,3,1], label="line 3")
handles, labels = ax.get_legend_handles_labels()
# reverse the order
ax.legend(handles[::-1], labels[::-1])
# or sort them by labels
import operatorhl = sorted(zip(handles, labels), key=operator.itemgetter(1))
handles2, labels2 = zip(*hl)
ax.legend(handles2, labels2)
1.2 使用代理artist
当需要使用legend不支持的artist时，可以使用另一个被legend支持的artist作为代理
比如以下示例中使用不在axe上的一个artist
p = Rectangle((0, 0), 1, 1, fc="r")
legend([p], ["Red Rectangle"])
2 多列图例
ax1 = plt.subplot(3,1,1)
ax1.plot([1], label="multi\nline")
ax1.plot([1], label="$2^{2^2}$")
ax1.plot([1], label=r"$\frac{1}{2}\pi$")
ax1.legend(loc=1, ncol=3, shadow=True)
ax2 = plt.subplot(3,1,2)
myplot(ax2)
ax2.legend(loc="center left", bbox_to_anchor=[0.5, 0.5],
ncol=2, shadow=True, title="Legend")
ax2.get_legend().get_title().set_color("red")
3 图例位置
ax.legend(…., loc=3) 具体对应位置如下图
绘制在图上是这样的，（具体没有分清 5和7的区别）
4 多个图例
如果不采取措施，连续调用两个legend会使得后面的legend覆盖前面的
from matplotlib.pyplot import * p1, = plot([1,2,3], label="test1")
p2, = plot([3,2,1], label="test2")
l1 = legend([p1], ["Label 1"], loc=1)l2 = legend([p2], ["Label 2"], loc=4) # this removes l1 from the axes.
gca().add_artist(l1) # add l1 as a separate artist to the axes
5. API
class matplotlib.legend.Legend(parent, handles, labels,**args)
三个最重要的必要参数
parent --- legend的父artist， 包含legend的对象
比如用ax.legend()调用之后
>>> print ax.get_legend().parent
Axes(0.125,0.1;0.775x0.8)
handles --- 图例上面画出的各个artist（lines, patches）
labels --- artist 对应的标签
其他参数
KeywordDescription
loca location code
propthe font property (matplotlib.font_manager.FontProperties 对象)
eg
song_font = matplotlib.font_manager.FontProperties(fname='simsun.ttc', size=8)
fontsizethe font size (和prop互斥，不可同时使用)
markerscalethe relative size of legend markers vs. original
numpointsthe number of points in the legend for line
scatterpointsthe number of points in the legend for scatter plot
scatteryoffsetsa list of yoffsets for scatter symbols in legend
frameonif True, draw a frame around the legend. If None, use rc
fancyboxif True, draw a frame with a round fancybox. If None, use rc
shadowif True, draw a shadow behind legend
ncolnumber of columns
borderpadthe fractional whitespace inside the legend border
labelspacingthe vertical space between the legend entries
handlelengththe length of the legend handles
handleheightthe length of the legend handles
handletextpadthe pad between the legend handle and text
borderaxespadthe pad between the axes and legend border
columnspacingthe spacing between columns
titlethe legend title
bbox_to_anchorthe bbox that the legend will be anchored.
bbox_transformthe transform for the bbox. transAxes if None.
主要函数
get_frame() --- 返回legend所在的方形对象
get_lines()
get_patches()
get_texts()
get_title() --- 上面几个比较简单，不解释了
set_bbox_to_anchor(bbox, transform=None)
(…本函数待续…之后写axes的时候会加入，目前我没有看懂他的这个长宽和figure以及axes的关系)
6. 样例
leg = ax.legend(('Model length', 'Data length', 'Total message length'),
'upper center', shadow=True)
# the matplotlib.patches.Rectangle instance surrounding the legend 即外框
frame = leg.get_frame()
frame.set_facecolor('0.80')# set the frame face color to light gray
# matplotlib.text.Text instances 即legend中文本
for t in leg.get_texts():
t.set_fontsize('small')# the legend text fontsize
# matplotlib.lines.Line2D instances 即legend中所表示的artist
for l in leg.get_lines():
l.set_linewidth(1.5) # the legend line width
fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.1, 0.4, 0.7])
ax2 = fig.add_axes([0.55, 0.1, 0.4, 0.7])
x = np.arange(0.0, 2.0, 0.02)
y1 = np.sin(2*np.pi*x)
y2 = np.exp(-x)
l1, l2 = ax1.plot(x, y1, 'rs-', x, y2, 'go')
y3 = np.sin(4*np.pi*x)
y4 = np.exp(-2*x)
l3, l4 = ax2.plot(x, y3, 'yd-', x, y3, 'k^')
fig.legend((l1, l2), ('Line 1', 'Line 2'), 'upper left')
fig.legend((l3, l4), ('Line 3', 'Line 4'), 'upper right')