distance = math.sqrt(
(curX - preX)**2 + (curY - preY)**2
) # distance between an observation in current data and each points in previous one
# add observation satisfying the neighborhood condition
if distance < bandwidth: # 1. bandwidth condition
if distance > mindist: # 2. minimum distance condition
if nCount <= knn: # 3. number of maximum neighborhoods
distDic[preOID] = [distance, preUnitPrice]
nCount += 1
distDicsorted = collections.OrderedDict(
sorted(distDic.items(), key=lambda t: t[1][0]))
# print distDicsorted.values()[0][0]
## calculating Wij & Wij*UnitPricej for current year observations
sumWij = 0 # initialize sigma Wij
sumWijP = 0 # initialize sigma Wij*UnitP
for dist, UnitP in distDicsorted.values():
wij = (1 - (dist / bandwidth)**2)**2
wijP = wij * UnitP
sumWij += wij
sumWijP += wijP
lag = sumWijP / sumWij
lagVar.append(lag)
excel.excelWriteOnExistingFile3(filepath2, sheetname2, 'X', lagVar)
print(lagVar)
resultEMD = excel.excelRead(filenameEMD, sheetnameEMD)
emdMatList = []
for addrMat in matResult[1:]:
tempEMD = '-1'
addrStrip = str(addrMat[0].value).strip()
for rowEMD in resultEMD:
rowEMDStr = str(rowEMD[1].value)
if addrStrip == rowEMDStr:
tempEMD = str(int(rowEMD[0].value))
break
emdMatList.append(tempEMD)
excel.excelWriteOnExistingFile3(filenameMat, sheetnameMat, 'k', emdMatList)
print('saved successfully in ' + filenameMat)
#4-2 - Matching excel file and dictionary
filenameDicRe = 'Dictionary_result.xlsx'
sheetnameDicRe = 'Sheet2'
resultDicRe = excel.excelRead(filenameDicRe, sheetnameDicRe)
matResult2 = excel.excelRead(filenameMat, sheetnameMat)
snList = []
for addrMat1 in matResult2[1:]:
tempBd_SN = '-1'
tempeqb_SN = '-1'
resultEMD = excel.excelRead(filenameEMD, sheetnameEMD)
emdMatList = []
for addrMat in matResult[1:]:
tempEMD = '-1'
addrStrip = str(addrMat[0].value).strip()
for rowEMD in resultEMD:
rowEMDStr = str(rowEMD[1].value)
if addrStrip == rowEMDStr:
tempEMD = str(int(rowEMD[0].value))
break
emdMatList.append(tempEMD)
excel.excelWriteOnExistingFile3(filenameMat, sheetnameMat, 'k', emdMatList)
print('saved successfully in '+ filenameMat)
#4-2 - Matching excel file and dictionary
filenameDicRe = 'Dictionary_result.xlsx'
sheetnameDicRe = 'Sheet2'
resultDicRe = excel.excelRead(filenameDicRe, sheetnameDicRe)
matResult2 = excel.excelRead(filenameMat, sheetnameMat)
snList = []
for addrMat1 in matResult2[1:]:
tempBd_SN = '-1'
tempeqb_SN = '-1'
preOID = int(preValue[2].value) # OBJECT ID of previous year data
preUnitPrice = float(preValue[22].value) # Unit Price of previous year data
distance = math.sqrt((curX - preX)**2+(curY - preY)**2) # distance between an observation in current data and each points in previous one
# add observation satisfying the neighborhood condition
if distance < bandwidth : # 1. bandwidth condition
if distance > mindist: # 2. minimum distance condition
if nCount <= knn: # 3. number of maximum neighborhoods
distDic[preOID] = [distance, preUnitPrice]
nCount+=1
distDicsorted = collections.OrderedDict(sorted(distDic.items(), key=lambda t:t[1][0]))
# print distDicsorted.values()[0][0]
## calculating Wij & Wij*UnitPricej for current year observations
sumWij = 0 # initialize sigma Wij
sumWijP = 0 # initialize sigma Wij*UnitP
for dist, UnitP in distDicsorted.values():
wij = (1-(dist/bandwidth)**2)**2
wijP = wij*UnitP
sumWij += wij
sumWijP += wijP
lag = sumWijP / sumWij
lagVar.append(lag)
excel.excelWriteOnExistingFile3(filepath2, sheetname2, 'X', lagVar)
print(lagVar)
