下面的代码 sn-p 是一个例子,使用 text 函数在左侧标注负值,右侧标注正值,gcalmettes 和zhenya 都提到过。
from pylab import setp
import numpy as np
import matplotlib.pyplot as plt
import math
# creation of the data
name_list = ['day1', 'day2', 'day3', 'day4']
data = {name: 3+10*np.random.rand(5) for name in name_list}
for name in name_list:
data[name][0] = data[name][0]*-1
data[name][2] = data[name][2]*-1
colors_list = ['0.5', 'r', 'b', 'g'] #optional
def customize_barh(data, width_bar=1, width_space=0.5, colors=None):
n_measure = len(data) #number of measure per people
n_people = data[data.keys()[0]].size # number of people
#some calculation to determine the position of Y ticks labels
total_space = n_people*(n_measure*width_bar)+(n_people-1)*width_space
ind_space = n_measure*width_bar
step = ind_space/2.
pos = np.arange(step, total_space+width_space, ind_space+width_space)
# create the figure and the axes to plot the data
fig = plt.figure(figsize=(8,6))
ax = fig.add_axes([0.15, 0.15, 0.65, 0.7])
# remove top and right spines and turn ticks off if no spine
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('default') # ticks position on the right
# postition of tick out
ax.tick_params(axis='both', direction='out', width=3, length=6,
labelsize=24, pad=8)
ax.spines['left'].set_linewidth(3)
ax.spines['bottom'].set_linewidth(3)
# plot the data
for i,day in enumerate(data.keys()):
if colors == None:
ax.barh(pos-step+i*width_bar, data[day], width_bar, #facecolor='0.4',
edgecolor='k', linewidth=3)
else:
ax.barh(pos-step+i*width_bar, data[day], width_bar, facecolor=colors[i],
edgecolor='k', linewidth=3)
ax.set_yticks(pos)
# you may want to use the list of name as argument of the function to be more
# flexible (if you have to add a people)
setp(ax.get_yticklabels(), visible=False)
ax.set_ylim((-width_space, total_space+width_space))
ax.set_xlabel('Performance', size=26, labelpad=10)
labels_list = ['Tom', 'Dick', 'Harry', 'Slim','Jim']
# creation of an array of positive/negative values (based on the values
# of the data) that will be used as x values for adding text as side labels
side_list = []
for index in range(len(labels_list)):
sum = 0
for name in name_list:
sum+= data[name][index]
if math.copysign(1,sum) > 0:
side_list.append(16)
else:
side_list.append(-21)
for label in labels_list:
plt.text(side_list[labels_list.index(label)], pos[labels_list.index(label)]-0.5, label,fontsize=26)
customize_barh(data, colors=colors_list)
plt.savefig('perf.png')
plt.show()
它的工作原理是,给定人的所有条都需要是负数或正数,才能在正确的一侧注释文本。要更改此行为,只需更改 side_list 的生成即可。
例如,如果您想要某个条形阈值来确定标签的位置,则计算超过该阈值的数据值,而不是对给定名称的值求和。
例如,对于 3 条的阈值,无论多少条,for 循环都变为
for index in range(len(labels_list)):
count = 0
for name in name_list:
if data[name][index] > 0:
count+= 1
if count > 3:
side_list.append(16)
else:
side_list.append(-21)
side_list 的生成也需要更改以适应您的数据范围,因为给出的示例使用指定范围内的随机数据。
例如,您需要调整 side_list.append(16) 和 side_list.append(-21) 的标签偏移量以适合您的数据。