def groupingAnalysis():
groupDiet = dietActInfoRetrv.getGroups(labelsDietType)
groupAct = dietActInfoRetrv.getGroups(labelsActType)
print groupAct
print groupDiet
dd = {}
for key1 in groupDiet:
dd[key1] = {}
for key2 in groupAct:
dd[key1][key2] = 0
for item in groupDiet[key1]:
if item in groupAct[key2]:
dd[key1][key2] += 1
print dd
dd = {}
for key1 in groupAct:
dd[key1] = {}
for key2 in groupDiet:
dd[key1][key2] = 0
for item in groupAct[key1]:
if item in groupDiet[key2]:
dd[key1][key2] += 1
print dd
def buildSubAveInfo():
workbookW = xlwt.Workbook()
ws = workbookW.add_sheet('AveInfo')
groupAct = dietActInfoRetrv.getGroups(labelsActType)
groupDiet = dietActInfoRetrv.getGroups(labelsDietType)
Age, Gender, Height, Weight, BMI, FatFree, FatMass, PercFat, Vo2max = slpInfoRetrv.getDemoGInfo(
)
SlpHours = slpInfoRetrv.getSlpHours()
MedianHR = slpInfoRetrv.getMedianHR()
MedianHRBefore = slpInfoRetrv.getMedianHRBefore()
MedianHRAfter = slpInfoRetrv.getMedianHRAfter()
titles = [
'SubjId', 'ActGroup', 'DietGroup', 'HoursSleep', 'MedianHR',
'MedianHRBefore', 'MedianHRAfter', 'age', 'gender', 'height', 'weight',
'BMI', 'FatFreeMass', 'FatMass', 'PercFat', 'vo2max'
]
for i in range(len(titles)):
ws.write(0, i, titles[i])
rowW = 1
for index in range(len(sleep_list)):
ws.write(rowW, 0, sleep_list[index])
for key in groupAct:
if sleep_list[index] in groupAct[key]:
ws.write(rowW, 1, key)
break
for key in groupDiet:
if sleep_list[index] in groupDiet[key]:
ws.write(rowW, 2, key)
break
ws.write(rowW, 1 + 2, SlpHours[index])
ws.write(rowW, 2 + 2, MedianHR[index])
ws.write(rowW, 3 + 2, MedianHRBefore[index])
ws.write(rowW, 4 + 2, MedianHRAfter[index])
ws.write(rowW, 5 + 2, Age[index])
ws.write(rowW, 6 + 2, Gender[index])
ws.write(rowW, 7 + 2, Height[index])
ws.write(rowW, 8 + 2, Weight[index])
ws.write(rowW, 9 + 2, BMI[index])
ws.write(rowW, 10 + 2, FatFree[index])
ws.write(rowW, 11 + 2, FatMass[index])
ws.write(rowW, 12 + 2, PercFat[index])
ws.write(rowW, 13 + 2, Vo2max[index])
rowW += 1
ws2 = workbookW.add_sheet('DietTF')
row_labels = utilise.itemDict2list(dataGen4DietAct.genDietTypeDict())
X = utilise.normArray(dataGen4DietAct.genDietTypeTFArray())
ws2.write(0, 0, 'SubjId')
ws2.write(0, 1, 'DietGroup')
for i in range(len(row_labels)):
ws2.write(0, i + 2, row_labels[i])
rowW = 1
for index in range(len(available_list)):
ws2.write(rowW, 0, available_list[index])
for key in groupDiet:
if available_list[index] in groupDiet[key]:
ws2.write(rowW, 1, key)
break
for i in range(len(row_labels)):
ws2.write(rowW, i + 2, X[index][i])
rowW += 1
ws3 = workbookW.add_sheet('ActTF')
row_labels = utilise.itemDict2list(dataGen4DietAct.genActTypeDict())
X = utilise.normArray(dataGen4DietAct.genActTypeTFArray())
ws3.write(0, 0, 'SubjId')
ws3.write(0, 1, 'ActGroup')
for i in range(len(row_labels)):
ws3.write(0, i + 2, row_labels[i])
rowW = 1
for index in range(len(available_list)):
ws3.write(rowW, 0, available_list[index])
for key in groupAct:
if available_list[index] in groupAct[key]:
ws3.write(rowW, 1, key)
break
for i in range(len(row_labels)):
ws3.write(rowW, i + 2, X[index][i])
rowW += 1
workbookW.save('SubAveInfo.xls')
def genDemoInfoDietGroups():
groupDiet = dietActInfoRetrv.getGroups(labelsDietType)
Age, Gender, Height, Weight, BMI, FatFree, FatMass, PercFat, Vo2max = slpInfoRetrv.getDemoGInfo(
)
SlpHours = slpInfoRetrv.getSlpHours()
MedianHR = slpInfoRetrv.getMedianHR()
MedianHRBefore = slpInfoRetrv.getMedianHRBefore()
MedianHRAfter = slpInfoRetrv.getMedianHRAfter()
# write the info to excel file
workbookW = xlwt.Workbook()
ws = workbookW.add_sheet('sheet1')
rowW = 0
titles = [
'age', 'men', 'women', 'height', 'weight', 'BMI', 'fat_free',
'fat_mass', 'perc_fat', 'vo2max', 'slpHours', 'medianHR',
'medianHRBefore', 'medianHRAfter'
]
col = 0
for item in titles:
ws.write(rowW, col, item)
col += 1
rowW += 1
demoDict = {}
for key in groupDiet:
demoDict[key] = {}
temp_Age = []
temp_Gender = []
temp_Height = []
temp_Weight = []
temp_BMI = []
temp_FatFree = []
temp_FatMass = []
temp_PercFat = []
temp_Vo2max = []
temp_slpHours = []
temp_MedianHR = []
temp_MedianHRBefore = []
temp_MedianHRAfter = []
for index in range(len(sleep_list)):
if sleep_list[index] in groupDiet[key]:
temp_Age.append(Age[index])
temp_Gender.append(Gender[index])
temp_Height.append(Height[index])
temp_Weight.append(Weight[index])
temp_BMI.append(BMI[index])
temp_FatFree.append(FatFree[index])
temp_FatMass.append(FatMass[index])
temp_PercFat.append(PercFat[index])
temp_Vo2max.append(Vo2max[index])
temp_slpHours.append(SlpHours[index])
temp_MedianHR.append(MedianHR[index])
temp_MedianHRBefore.append(MedianHRBefore[index])
temp_MedianHRAfter.append(MedianHRAfter[index])
demoDict[key]['age'] = sum(temp_Age) / float(len(temp_Age))
demoDict[key]['men'] = temp_Gender.count(1.0)
demoDict[key]['women'] = temp_Gender.count(0.0)
demoDict[key]['height'] = sum(temp_Height) / float(len(temp_Height))
demoDict[key]['weight'] = sum(temp_Weight) / float(len(temp_Weight))
demoDict[key]['BMI'] = sum(temp_BMI) / float(len(temp_BMI))
demoDict[key]['fat_free'] = sum(temp_FatFree) / float(
len(temp_FatFree))
demoDict[key]['fat_mass'] = sum(temp_FatMass) / float(
len(temp_FatMass))
demoDict[key]['perc_fat'] = sum(temp_PercFat) / float(
len(temp_PercFat))
demoDict[key]['vo2max'] = sum(temp_Vo2max) / float(len(temp_Vo2max))
demoDict[key]['slpHours'] = sum(temp_slpHours) / float(
len(temp_slpHours))
demoDict[key]['medianHR'] = sum(temp_MedianHR) / float(
len(temp_MedianHR))
demoDict[key]['medianHRBefore'] = sum(temp_MedianHRBefore) / float(
len(temp_MedianHRBefore))
demoDict[key]['medianHRAfter'] = sum(temp_MedianHRAfter) / float(
len(temp_MedianHRAfter))
col = 0
for item in titles:
if item in demoDict[key]:
ws.write(rowW, col, demoDict[key][item])
col += 1
rowW += 1
workbookW.save('tempDietGroupDemo.xls')
print demoDict