matplotlib的一个小例子

一个例子：

---

#-*-coding:utf-8-*-
#文件名: ch.py
def set_ch():
	from pylab import mpl
	mpl.rcParams['font.sans-serif'] = ['STFangsong'] # 指定默认字体
	mpl.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题

"""
1-导入Excel文档
2-获得每一列数据
3-第一列作为X轴
4-2~17列作为Y的数据
"""


import ch
ch.set_ch()
from collections import OrderedDict
import xlrd
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import scipy
from scipy.interpolate import spline
from matplotlib import ticker

font = {
        'family':'STFangsong',
        'size':12
        }
mpl.rc('font',**font)
mpl.rc('figure',autolayout = True,facecolor = 'white')#figure自动使所有内容全部自适应出现在整个图像内
mpl.rc('axes',facecolor = 'white',grid = True)

#导入表格，获取sheet
path = "/Volumes/大白菜/研究生研究课题工作/国网报告整理/20170902严主任数据/实验数据/16路微水变化对比.xlsx"
book_temp = xlrd.open_workbook(path)
sheetName = book_temp.sheet_names()

#建立每一列的数组，数组的元素是1~17列的数据
sheet1 = book_temp.sheet_by_name(sheetName[0])
col_name = []
for i in range(16):
    col_name.append('col_data_'+str(i))
    col_name[i] = sheet1.col_values(i)[1::15]

#列出X轴的数据
x = np.array([x for x in range(len(col_name[0]))])
xnew = np.linspace(x.min(),x.max(),3000)

#Y轴的数据，使用有序字典
y = OrderedDict()
for i in range(15):
    y[i] = col_name[i+1]

ynew = OrderedDict()
for i in range(15):
    ynew[i] = spline(x,y[i],xnew)#曲线平滑处理

#进行绘图
fig,ax = plt.subplots(1,1)
for i in range(15):
    ax.plot(xnew,ynew[i],label = str(i+1)+"号")

# plt.xlabel("时间")
plt.ylabel("微水($\mu L/L$)")
plt.legend(loc = 0,framealpha = 0.5,fontsize = 8,frameon = False)#修改legend的大小
plt.title("16路微水变化对比图")
#改变X轴坐标的显示
import matplotlib.ticker as ticker
tick_spacing = 15
plt.xticks(x, col_name[0], rotation=15)#改变X轴显示的内容
ax.xaxis.set_major_locator(ticker.MultipleLocator(tick_spacing))#改变X轴显示的密度
fig.set_size_inches(6.3,3.5)
plt.savefig('./images/%s.pdf'%(ax.get_title()),dpi = 300,bbox_inches=None, pad_inches=0.1)
plt.savefig('./images/%s.png'%(ax.get_title()),dpi = 300,bbox_inches=None, pad_inches=0.1)
plt.show()