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二次指數平滑預測法 Python實現

日期:2017/3/1 9:20:36   编辑:Linux編程

從以往的時間序列值,進行指數平滑,做兩次預測出下一個時間的估計值。

目錄結構如下:

Python代碼如下:

forecast.py

# -*-coding:utf-8 -*-
# Time:2015.11.25 sangjin
__author__ = 'hunterhug'
import matplotlib
#matplotlib.use("Agg")
#matplotlib.use("TkAgg")
#matplotlib.use("gtk")
import matplotlib.pyplot as plt
from matplotlib.pyplot import savefig
from matplotlib.font_manager import FontProperties
from operator import itemgetter
#讀取execel使用(支持07)
from openpyxl import Workbook
#寫入excel使用(支持07)
from openpyxl import load_workbook
import os


def judgefile():
path = input("請輸入該目錄下的excel文件名:") # file path
if os.path.isfile(path):
return path.lower()
else:
print("文件不存在")
return judgefile()

def writeexcel07(path, content, name='Sheet1', sheetnum=0):
wb=Workbook()
#sheet=wb.add_sheet("xlwt3數據測試表")
sheet=wb.create_sheet(sheetnum,name)
# values = [["名稱", "Hadoop編程實戰", "hbase編程實戰", "lucene編程實戰"], ["價格", "52.3", "45", "36"], ["出版社", "機械工業出版社", "人民郵電出版社", "華夏人民出版社"], ["中文版式", "中", "英", "英"]]
for i in range(0,len(content)):
for j in range(0,len(content[i])):
sheet.cell(row = i+1,column= j+1).value = content[i][j]

# sheet.cell(row = 1,column= 2).value="溫度"
wb.save(path)
print("寫入數據成功!")

def read07excel(path):
excelcontent = []
wb2=load_workbook(path)
sheetnames = wb2.get_sheet_names()
ws=wb2.get_sheet_by_name(sheetnames[0])
row=ws.get_highest_row()
col=ws.get_highest_column()
# print("列數: ",ws.get_highest_column())
# print("行數: ",ws.get_highest_row())

for i in range(0,row):
rowcontent = []
for j in range(0,col):
if ws.rows[i][j].value:
rowcontent.append(ws.rows[i][j].value)
excelcontent.append(rowcontent)
print("讀取數據成功!")
return excelcontent


def calvalue(excel, a):
date = [] # x label date
data = [] # y label data

for i in range(2,len(excel)-1):
data.append(float(excel[i][1]))
date.append(excel[i][0])

e1 = [data[0]] # one time forecast

for i in range(0,len(data)):
next = data[i] * a + e1[i] * (1 - a)
e1.append(next)

e1e = [] # one time absoultion error
for i in range(0,len(data)):
e1e.append(abs(data[i]-e1[i]))

e1e2 = sum(e1e)

e2 = [data[0]] # second time forecast
for i in range(0,len(data)):
next = e1[i] * a + e2[i] * (1 - a)
e2.append(next)

e2e = [] # second time absoultion error
for i in range(0,len(data)):
e2e.append(abs(data[i]-e2[i]))

e2e2 = sum(e2e)

e1y = e1[len(e1)-1] # one time forecast value
e2y = e2[len(e2)-1] # two time forecast value
return [a, e1y, e2y, e1e2, e2e2]

def calvaluetop5(excel, step = 0.01):
initvalue = 1.0
all = []
top5 =[]
while initvalue <= 1.0 and initvalue >= 0:
all.append(calvalue(excel, initvalue))
initvalue = initvalue -step
d = {}
for i in range(0, len(all)):
d.setdefault(i, all[i][3])
d1 = sorted(d.items(), key=itemgetter(1))
#print(d1)
topnum = len(d1)
if topnum>=5:
topnum = 5
else:
pass
for i in range(0,topnum):
pos = d1[i][0]
top5.append(all[pos])
return top5

def judgestep():
try:
a = float(input("請選擇系數變化步長(范圍0~1):")) # change var
except:
print("請輸入數字好麼...")
return judgestep()
while a > 1 or a < 0:
print('輸入的步長范圍在0-1之間')
return judgestep()
return a

def judge():
try:
a = float(input("請輸入變化系數a:")) # change var
except:
print("請輸入數字好麼...")
return judge()
while a > 1 or a < 0:
print('輸入的變化系數范圍在0-1之間')
return judge()
return a


def single(a,path):
excel = read07excel(path)
title1 = excel[0][0]
title2 = excel[1]
# print(excel)

title = ':'.join(excel[0])
date = [] # x label date
data = [] # y label data

for i in range(2,len(excel)-1):
data.append(float(excel[i][1]))
date.append(excel[i][0])
# print('/n',data)
# print(title,data,date)

e1 = [data[0]] # one time forecast

for i in range(0,len(data)):
next = data[i] * a + e1[i] * (1 - a)
e1.append(next)
# print('/n',e1)

e1e = [] # one time absoultion error
for i in range(0,len(data)):
e1e.append(abs(data[i]-e1[i]))
# print('/n',e1e)

ele2 = sum(e1e)
# print(ele2)

e2 = [data[0]] # second time forecast
for i in range(0,len(data)):
next = e1[i] * a + e2[i] * (1 - a)
e2.append(next)
# print('/n',e2)

e2e = [] # second time absoultion error
for i in range(0,len(data)):
e2e.append(abs(data[i]-e2[i]))
# print('/n',e2e)

e2e2 = sum(e2e)
# print(e2e2)

e1y = e1[len(e1)-1] # one time forecast value
e2y = e2[len(e2)-1] # two time forecast value

content = [[title1,'可變系數a=',a]]
content.append([title2[0],title2[1],'一次指數平滑預測值','絕對誤差','二次指數平滑','絕對誤差'])

datas = [date, data, e1[:len(e1)-1], e1e, e2[:len(e2)-1], e2e]

datast = [[r[col] for r in datas] for col in range(len(datas[0]))]
content[len(content):] = datast

yu1 = ['', e2y, e1y, ele2, e2y, e2e2]
yu2 = ['', '最終預測值', '一次指數平滑預測值', '一次指數平滑絕對誤差累加', '二次指數平滑預測值', '一次指數平滑絕對誤差累加']
content.append(yu1)
content.append(yu2)
content.append(['說明:請手動插入走勢圖。此文件為自動計算生成'])
# print(content)

path1 =path.replace('.xlsx', '(結果生成).xlsx')
writeexcel07(path1, content, '生成表')
print("請打開所在目錄生成的excel文件(結果生成)")
plt.close('all')
font = FontProperties(fname=r"c:\windows\fonts\simsun.ttc", size=14)
plt.figure(figsize=(10,7))
num = range(0,len(date))
plt.plot(num, data, 'b-*', label='原始數據')
plt.plot(num, e1[:len(e1)-1], 'r*-', label='一次指數預測')
plt.plot(num, e2[:len(e2)-1], 'g*-', label='二次指數預測')
bottomtitle1 = '\n一次預測值:'+str(e1y)+"\t誤差和:"+str(ele2)
bottomtitle = bottomtitle1 + '\n二次預測值:'+str(e2y)+"\t誤差和:"+str(e2e2)
plt.title('指數平滑法預測走勢圖(時間序列)變化系數a={0:3f}'.format(a)+bottomtitle, fontproperties=font) # simfang.ttf
# plt.text(0, 0, bottomtitle, fontproperties=font)
plt.xlabel('時間間隔', fontproperties=font)
plt.ylabel('成交額', fontproperties=font)
legend = plt.legend(loc='upper right', prop=font)
# legend = plt.legend(loc='upper right', shadow=True, prop=font)
legend.get_frame().set_facecolor('white')
plt.grid(True)

# Tweak spacing to prevent clipping of ylabel
plt.subplots_adjust(left=0.15)
plt.show()
savefig('Fig.png')


def begin():
sangjin = '''
-----------------------------------------
| 歡迎使用二次指數平滑法預測未來值 |
| |
| 使用方法: |
| 1.根據提示進行操作 |
| 2.輸出為預測走勢圖,以及處理後的excel |
-----------------------------------------
| ��木公司花名:桑槿 |
| 新浪微博:一只尼瑪 |
| 微信/QQ:569929309 |
-----------------------------------------
'''
print(sangjin)

def loop(path):
choice1 = input("自動計算變化系數請選擇y,手動請選擇n\n")
if choice1 == 'y':
step = judgestep()
p5 = calvaluetop5(read07excel(path), step)
print('總誤差最小的前五個是')
for i in p5:
print('變化系數:{0:3f}\t預測值:{1:3f}\t總誤差值:{2:3f}'.format(i[0],i[2],i[4]))
single(p5[0][0],path)
else:
a = judge()
single(a,path)


def loop3(path):
choice2 = input("如果想操作其他文件請選擇y,退出選擇n,其他操作按任意鍵\n")
if choice2 == 'y':
loop1()
elif choice2 == 'n':
print("正在退出中...\n"*6)
print("正在退出中...謝謝")
exit(1)
else:
loop(path)
loop3(path)

def loop1():
path = judgefile()
loop(path)
loop3(path)

begin()
loop1()

輸入excel格式如下:

輸出結果:

代碼參考:

下載

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具體下載目錄在 /2015年資料/11月/27日/二次指數平滑預測法 Python實現/

下載方法見 http://www.linuxidc.com/Linux/2013-07/87684.htm

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