How to use capped method in hypothesis

Best Python code snippet using hypothesis

baseline_functions.py

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1from helper_functions import *2from error_functions import *3from data_get import *4from calendar_date import *5import global_vars6from datetime import datetime7# runBaseline(interval_df, DRDays, temp_df, interval, date, storage_list)8# runs baseline functions for an SAID for given day using passed in data9# input10# interval_df, pandas.Dataframe, contains all interval data relevant to SAID11# DRdays, list, contains list of DR event dates in datetime form12# temp_df, pandas.Dataframe, contains all temperature data13# interval, int, 15 or 60, data collection interval used to find correct sql table14# date, pandas.datetime, date to run baselines on 15# storage_list, list, starter list for new row16# output17# row_data, list, all data including baseline for specific SAID 18def runBaseline(interval_df, DRDays, temp_df, interval, date, storage_list):19 try:20 maxTemp = getMaxTemp(temp_df, date)21 if(global_vars.PRINTFLAG >= 2):22 print("Max Temp is",maxTemp,"F")23 except:24 # print("Failed MaxTemp")25 return 'NA'26 maxTemp = str(maxTemp)27 # used for time inputs28 twoPM = pd.to_datetime(('14:00').strip(),format='%H:%M').time()29 eightPM = pd.to_datetime(('20:00').strip(),format='%H:%M').time()30 31 try:32 errorsTTN = getTenTenNonAdjustment(interval_df, DRDays, date)33 except:34 return 'NA'35 if errorsTTN == 'NA':36 return 'NA'37 try:38 errorsTTA, cappedAdjustmentsErrorsTTA = getTenTenWithAdjustment(interval_df, DRDays, date, twoPM, interval)39 except:40 return 'NA'41 if errorsTTA == 'NA':42 return 'NA'43 errorsThTN = getThreeTenNonAdjustment(interval_df, DRDays, date, twoPM, eightPM)44 if errorsThTN == 'NA':45 return 'NA'46 try:47 errorsThTA, cappedAdjustmentsErrorsThTA = getThreeTenWithAdjustment(interval_df, DRDays, date, twoPM, eightPM, interval)48 except:49 return 'NA'50 if errorsThTA == 'NA':51 return 'NA'52 try:53 errorsFN, cappedAdjustmentsErrorsFN = getFourNintyWeather(interval_df, DRDays, temp_df, date)54 except:55 return 'NA'56 if errorsFN == 'NA':57 return 'NA'58 if isHoliday(date):59 try:60 errorsF, cappedAdjustmentsErrorsF = getThreeFiveWeather(interval_df, DRDays, temp_df, date)61 except:62 return 'NA'63 if errorsF == 'NA':64 return 'NA'65 if(global_vars.PRINTFLAG >= 2):66 print("errors", errorsF)67 print("cappedAdjustmentsErrors", cappedAdjustmentsErrorsF)68 try:69 errorsT, cappedAdjustmentsErrorsT = getFourFourWeather(interval_df, DRDays, temp_df, date)70 except:71 return 'NA'72 if errorsT == 'NA':73 return 'NA'74 75 #bussinessday76 else:77 try:78 errorsF, cappedAdjustmentsErrorsF = getFiveTenWeather(interval_df, DRDays, temp_df, date)79 except:80 return 'NA'81 if errorsF == 'NA':82 return 'NA'83 try: 84 errorsT, cappedAdjustmentsErrorsT = getTenTenWeather(interval_df, DRDays, temp_df, date)85 except:86 return 'NA'87 if errorsT == 'NA':88 return 'NA'89 today = str(datetime.now().date())90 row_data = [errorsTTN[0], errorsTTN[1], errorsTTN[2], errorsTTA[0], errorsTTA[1], errorsTTA[2], cappedAdjustmentsErrorsTTA[0][0], cappedAdjustmentsErrorsTTA[0][1], cappedAdjustmentsErrorsTTA[0][2], cappedAdjustmentsErrorsTTA[1][0], cappedAdjustmentsErrorsTTA[1][1], cappedAdjustmentsErrorsTTA[1][2], cappedAdjustmentsErrorsTTA[2][0], cappedAdjustmentsErrorsTTA[2][1], cappedAdjustmentsErrorsTTA[2][2], cappedAdjustmentsErrorsTTA[3][0], cappedAdjustmentsErrorsTTA[3][1], cappedAdjustmentsErrorsTTA[3][2], cappedAdjustmentsErrorsTTA[4][0], cappedAdjustmentsErrorsTTA[4][1], cappedAdjustmentsErrorsTTA[4][2], cappedAdjustmentsErrorsTTA[5][0], cappedAdjustmentsErrorsTTA[5][1], cappedAdjustmentsErrorsTTA[5][2], cappedAdjustmentsErrorsTTA[6][0], cappedAdjustmentsErrorsTTA[6][1], cappedAdjustmentsErrorsTTA[6][2], cappedAdjustmentsErrorsTTA[7][0], cappedAdjustmentsErrorsTTA[7][1], cappedAdjustmentsErrorsTTA[7][2], cappedAdjustmentsErrorsTTA[8][0], cappedAdjustmentsErrorsTTA[8][1], cappedAdjustmentsErrorsTTA[8][2], cappedAdjustmentsErrorsTTA[9][0], cappedAdjustmentsErrorsTTA[9][1], cappedAdjustmentsErrorsTTA[9][2], cappedAdjustmentsErrorsTTA[10][0], cappedAdjustmentsErrorsTTA[10][1], cappedAdjustmentsErrorsTTA[10][2], errorsThTN[0], errorsThTN[1], errorsThTN[2], errorsThTA[0], errorsThTA[1], errorsThTA[2], cappedAdjustmentsErrorsThTA[0][0], cappedAdjustmentsErrorsThTA[0][1], cappedAdjustmentsErrorsThTA[0][2], cappedAdjustmentsErrorsThTA[1][0], cappedAdjustmentsErrorsThTA[1][1], cappedAdjustmentsErrorsThTA[1][2], cappedAdjustmentsErrorsThTA[2][0], cappedAdjustmentsErrorsThTA[2][1], cappedAdjustmentsErrorsThTA[2][2], cappedAdjustmentsErrorsThTA[3][0], cappedAdjustmentsErrorsThTA[3][1], cappedAdjustmentsErrorsThTA[3][2], cappedAdjustmentsErrorsThTA[4][0], cappedAdjustmentsErrorsThTA[4][1], cappedAdjustmentsErrorsThTA[4][2], cappedAdjustmentsErrorsThTA[5][0], cappedAdjustmentsErrorsThTA[5][1], cappedAdjustmentsErrorsThTA[5][2], cappedAdjustmentsErrorsThTA[6][0], cappedAdjustmentsErrorsThTA[6][1], cappedAdjustmentsErrorsThTA[6][2], cappedAdjustmentsErrorsThTA[7][0], cappedAdjustmentsErrorsThTA[7][1], cappedAdjustmentsErrorsThTA[7][2], cappedAdjustmentsErrorsThTA[8][0], cappedAdjustmentsErrorsThTA[8][1], cappedAdjustmentsErrorsThTA[8][2], cappedAdjustmentsErrorsThTA[9][0], cappedAdjustmentsErrorsThTA[9][1], cappedAdjustmentsErrorsThTA[9][2], cappedAdjustmentsErrorsThTA[10][0], cappedAdjustmentsErrorsThTA[10][1], cappedAdjustmentsErrorsThTA[10][2], errorsFN[0], errorsFN[1], errorsFN[2], cappedAdjustmentsErrorsFN[0][0], cappedAdjustmentsErrorsFN[0][1], cappedAdjustmentsErrorsFN[0][2], cappedAdjustmentsErrorsFN[1][0], cappedAdjustmentsErrorsFN[1][1], cappedAdjustmentsErrorsFN[1][2], cappedAdjustmentsErrorsFN[2][0], cappedAdjustmentsErrorsFN[2][1], cappedAdjustmentsErrorsFN[2][2], cappedAdjustmentsErrorsFN[3][0], cappedAdjustmentsErrorsFN[3][1], cappedAdjustmentsErrorsFN[3][2], cappedAdjustmentsErrorsFN[4][0], cappedAdjustmentsErrorsFN[4][1], cappedAdjustmentsErrorsFN[4][2], cappedAdjustmentsErrorsFN[5][0], cappedAdjustmentsErrorsFN[5][1], cappedAdjustmentsErrorsFN[5][2], cappedAdjustmentsErrorsFN[6][0], cappedAdjustmentsErrorsFN[6][1], cappedAdjustmentsErrorsFN[6][2], cappedAdjustmentsErrorsFN[7][0], cappedAdjustmentsErrorsFN[7][1], cappedAdjustmentsErrorsFN[7][2], cappedAdjustmentsErrorsFN[8][0], cappedAdjustmentsErrorsFN[8][1], cappedAdjustmentsErrorsFN[8][2], cappedAdjustmentsErrorsFN[9][0], cappedAdjustmentsErrorsFN[9][1], cappedAdjustmentsErrorsFN[9][2], cappedAdjustmentsErrorsFN[10][0], cappedAdjustmentsErrorsFN[10][1], cappedAdjustmentsErrorsFN[10][2], errorsF[0], errorsF[1], errorsF[2], cappedAdjustmentsErrorsF[0][0], cappedAdjustmentsErrorsF[0][1], cappedAdjustmentsErrorsF[0][2], cappedAdjustmentsErrorsF[1][0], cappedAdjustmentsErrorsF[1][1], cappedAdjustmentsErrorsF[1][2], cappedAdjustmentsErrorsF[2][0], cappedAdjustmentsErrorsF[2][1], cappedAdjustmentsErrorsF[2][2], cappedAdjustmentsErrorsF[3][0], cappedAdjustmentsErrorsF[3][1], cappedAdjustmentsErrorsF[3][2], cappedAdjustmentsErrorsF[4][0], cappedAdjustmentsErrorsF[4][1], cappedAdjustmentsErrorsF[4][2], cappedAdjustmentsErrorsF[5][0], cappedAdjustmentsErrorsF[5][1], cappedAdjustmentsErrorsF[5][2], cappedAdjustmentsErrorsF[6][0], cappedAdjustmentsErrorsF[6][1], cappedAdjustmentsErrorsF[6][2], cappedAdjustmentsErrorsF[7][0], cappedAdjustmentsErrorsF[7][1], cappedAdjustmentsErrorsF[7][2], cappedAdjustmentsErrorsF[8][0], cappedAdjustmentsErrorsF[8][1], cappedAdjustmentsErrorsF[8][2], cappedAdjustmentsErrorsF[9][0], cappedAdjustmentsErrorsF[9][1], cappedAdjustmentsErrorsF[9][2], cappedAdjustmentsErrorsF[10][0], cappedAdjustmentsErrorsF[10][1], cappedAdjustmentsErrorsF[10][2], errorsT[0], errorsT[1], errorsT[2], cappedAdjustmentsErrorsT[0][0], cappedAdjustmentsErrorsT[0][1], cappedAdjustmentsErrorsT[0][2], cappedAdjustmentsErrorsT[1][0], cappedAdjustmentsErrorsT[1][1], cappedAdjustmentsErrorsT[1][2], cappedAdjustmentsErrorsT[2][0], cappedAdjustmentsErrorsT[2][1], cappedAdjustmentsErrorsT[2][2], cappedAdjustmentsErrorsT[3][0], cappedAdjustmentsErrorsT[3][1], cappedAdjustmentsErrorsT[3][2], cappedAdjustmentsErrorsT[4][0], cappedAdjustmentsErrorsT[4][1], cappedAdjustmentsErrorsT[4][2], cappedAdjustmentsErrorsT[5][0], cappedAdjustmentsErrorsT[5][1], cappedAdjustmentsErrorsT[5][2], cappedAdjustmentsErrorsT[6][0], cappedAdjustmentsErrorsT[6][1], cappedAdjustmentsErrorsT[6][2], cappedAdjustmentsErrorsT[7][0], cappedAdjustmentsErrorsT[7][1], cappedAdjustmentsErrorsT[7][2], cappedAdjustmentsErrorsT[8][0], cappedAdjustmentsErrorsT[8][1], cappedAdjustmentsErrorsT[8][2], cappedAdjustmentsErrorsT[9][0], cappedAdjustmentsErrorsT[9][1], cappedAdjustmentsErrorsT[9][2], cappedAdjustmentsErrorsT[10][0], cappedAdjustmentsErrorsT[10][1], cappedAdjustmentsErrorsT[10][2]]91 row_data.append(today)92 row_data.insert(0, maxTemp)93 # Holiday is H, Bussiness is B94 if isHoliday(date):95 row_data.insert(0, 'H')96 else:97 row_data.insert(0, 'B')98 row_data.insert(0, date)99 row_data.insert(0, storage_list[2])100 row_data.insert(0, storage_list[1])101 row_data.insert(0, storage_list[0])102 if(global_vars.PRINTFLAG >= 2):103 print("returning row")104 return row_data105def runBaseline2(interval_df, DRDays, temp_df, interval, date, storage_list):106 try:107 maxTemp = getMaxTemp(temp_df, date)108 if(global_vars.PRINTFLAG >= 2):109 print("Max Temp is",maxTemp,"F")110 except:111 # print("Failed MaxTemp")112 return 'NA'113 maxTemp = str(maxTemp)114 # used for time inputs115 twoPM = pd.to_datetime(('14:00').strip(),format='%H:%M').time()116 eightPM = pd.to_datetime(('20:00').strip(),format='%H:%M').time()117 118 try:119 errorsTTN = getTenTenNonAdjustment(interval_df, DRDays, date)120 except:121 return 'NA'122 if errorsTTN == 'NA':123 return 'NA'124 try:125 errorsTTA, cappedAdjustmentsErrorsTTA = getTenTenWithAdjustment(interval_df, DRDays, date, twoPM, interval)126 except:127 return 'NA'128 if errorsTTA == 'NA':129 return 'NA'130 errorsThTN = getThreeTenNonAdjustment(interval_df, DRDays, date, twoPM, eightPM)131 if errorsThTN == 'NA':132 return 'NA'133 try:134 errorsThTA, cappedAdjustmentsErrorsThTA = getThreeTenWithAdjustment(interval_df, DRDays, date, twoPM, eightPM, interval)135 except:136 return 'NA'137 if errorsThTA == 'NA':138 return 'NA'139 errorsFiveTN = getFiveTenNonAdjustment(interval_df, DRDays, date, twoPM, eightPM)140 if errorsThTN == 'NA':141 return 'NA'142 try:143 errorsFiveTA, cappedAdjustmentsErrorsFiveTA = getFiveTenWithAdjustment(interval_df, DRDays, date, twoPM, eightPM, interval)144 except:145 return 'NA'146 if errorsThTA == 'NA':147 return 'NA'148 try:149 errorsFN, cappedAdjustmentsErrorsFN = getFourNintyWeather(interval_df, DRDays, temp_df, date)150 except:151 return 'NA'152 if errorsFN == 'NA':153 return 'NA'154 if isHoliday(date):155 try:156 errorsF, cappedAdjustmentsErrorsF = getThreeFiveWeather(interval_df, DRDays, temp_df, date)157 except:158 return 'NA'159 if errorsF == 'NA':160 return 'NA'161 if(global_vars.PRINTFLAG >= 2):162 print("errors", errorsF)163 print("cappedAdjustmentsErrors", cappedAdjustmentsErrorsF)164 try:165 errorsT, cappedAdjustmentsErrorsT = getFourFourWeather(interval_df, DRDays, temp_df, date)166 except:167 return 'NA'168 if errorsT == 'NA':169 return 'NA'170 171 #bussinessday172 else:173 try:174 errorsF, cappedAdjustmentsErrorsF = getFiveTenWeather(interval_df, DRDays, temp_df, date)175 except:176 return 'NA'177 if errorsF == 'NA':178 return 'NA'179 try: 180 errorsT, cappedAdjustmentsErrorsT = getTenTenWeather(interval_df, DRDays, temp_df, date)181 except:182 return 'NA'183 if errorsT == 'NA':184 return 'NA'185 today = str(datetime.now().date())186 row_data = [errorsTTN[0], errorsTTN[1], errorsTTN[2], errorsTTA[0], errorsTTA[1], errorsTTA[2], cappedAdjustmentsErrorsTTA[0][0], cappedAdjustmentsErrorsTTA[0][1], cappedAdjustmentsErrorsTTA[0][2], cappedAdjustmentsErrorsTTA[1][0], cappedAdjustmentsErrorsTTA[1][1], cappedAdjustmentsErrorsTTA[1][2], cappedAdjustmentsErrorsTTA[2][0], cappedAdjustmentsErrorsTTA[2][1], cappedAdjustmentsErrorsTTA[2][2], cappedAdjustmentsErrorsTTA[3][0], cappedAdjustmentsErrorsTTA[3][1], cappedAdjustmentsErrorsTTA[3][2], cappedAdjustmentsErrorsTTA[4][0], cappedAdjustmentsErrorsTTA[4][1], cappedAdjustmentsErrorsTTA[4][2], cappedAdjustmentsErrorsTTA[5][0], cappedAdjustmentsErrorsTTA[5][1], cappedAdjustmentsErrorsTTA[5][2], cappedAdjustmentsErrorsTTA[6][0], cappedAdjustmentsErrorsTTA[6][1], cappedAdjustmentsErrorsTTA[6][2], cappedAdjustmentsErrorsTTA[7][0], cappedAdjustmentsErrorsTTA[7][1], cappedAdjustmentsErrorsTTA[7][2], cappedAdjustmentsErrorsTTA[8][0], cappedAdjustmentsErrorsTTA[8][1], cappedAdjustmentsErrorsTTA[8][2], cappedAdjustmentsErrorsTTA[9][0], cappedAdjustmentsErrorsTTA[9][1], cappedAdjustmentsErrorsTTA[9][2], cappedAdjustmentsErrorsTTA[10][0], cappedAdjustmentsErrorsTTA[10][1], cappedAdjustmentsErrorsTTA[10][2], errorsThTN[0], errorsThTN[1], errorsThTN[2], errorsThTA[0], errorsThTA[1], errorsThTA[2], cappedAdjustmentsErrorsThTA[0][0], cappedAdjustmentsErrorsThTA[0][1], cappedAdjustmentsErrorsThTA[0][2], cappedAdjustmentsErrorsThTA[1][0], cappedAdjustmentsErrorsThTA[1][1], cappedAdjustmentsErrorsThTA[1][2], cappedAdjustmentsErrorsThTA[2][0], cappedAdjustmentsErrorsThTA[2][1], cappedAdjustmentsErrorsThTA[2][2], cappedAdjustmentsErrorsThTA[3][0], cappedAdjustmentsErrorsThTA[3][1], cappedAdjustmentsErrorsThTA[3][2], cappedAdjustmentsErrorsThTA[4][0], cappedAdjustmentsErrorsThTA[4][1], cappedAdjustmentsErrorsThTA[4][2], cappedAdjustmentsErrorsThTA[5][0], cappedAdjustmentsErrorsThTA[5][1], cappedAdjustmentsErrorsThTA[5][2], cappedAdjustmentsErrorsThTA[6][0], cappedAdjustmentsErrorsThTA[6][1], cappedAdjustmentsErrorsThTA[6][2], cappedAdjustmentsErrorsThTA[7][0], cappedAdjustmentsErrorsThTA[7][1], cappedAdjustmentsErrorsThTA[7][2], cappedAdjustmentsErrorsThTA[8][0], cappedAdjustmentsErrorsThTA[8][1], cappedAdjustmentsErrorsThTA[8][2], cappedAdjustmentsErrorsThTA[9][0], cappedAdjustmentsErrorsThTA[9][1], cappedAdjustmentsErrorsThTA[9][2], cappedAdjustmentsErrorsThTA[10][0], cappedAdjustmentsErrorsThTA[10][1], cappedAdjustmentsErrorsThTA[10][2], errorsFiveTN[0], errorsFiveTN[1], errorsFiveTN[2], errorsFiveTA[0], errorsFiveTA[1], errorsFiveTA[2], cappedAdjustmentsErrorsFiveTA[0][0], cappedAdjustmentsErrorsFiveTA[0][1], cappedAdjustmentsErrorsFiveTA[0][2], cappedAdjustmentsErrorsFiveTA[1][0], cappedAdjustmentsErrorsFiveTA[1][1], cappedAdjustmentsErrorsFiveTA[1][2], cappedAdjustmentsErrorsFiveTA[2][0], cappedAdjustmentsErrorsFiveTA[2][1], cappedAdjustmentsErrorsFiveTA[2][2], cappedAdjustmentsErrorsFiveTA[3][0], cappedAdjustmentsErrorsFiveTA[3][1], cappedAdjustmentsErrorsFiveTA[3][2], cappedAdjustmentsErrorsFiveTA[4][0], cappedAdjustmentsErrorsFiveTA[4][1], cappedAdjustmentsErrorsFiveTA[4][2], cappedAdjustmentsErrorsFiveTA[5][0], cappedAdjustmentsErrorsFiveTA[5][1], cappedAdjustmentsErrorsFiveTA[5][2], cappedAdjustmentsErrorsFiveTA[6][0], cappedAdjustmentsErrorsFiveTA[6][1], cappedAdjustmentsErrorsFiveTA[6][2], cappedAdjustmentsErrorsFiveTA[7][0], cappedAdjustmentsErrorsFiveTA[7][1], cappedAdjustmentsErrorsFiveTA[7][2], cappedAdjustmentsErrorsFiveTA[8][0], cappedAdjustmentsErrorsFiveTA[8][1], cappedAdjustmentsErrorsFiveTA[8][2], cappedAdjustmentsErrorsFiveTA[9][0], cappedAdjustmentsErrorsFiveTA[9][1], cappedAdjustmentsErrorsFiveTA[9][2], cappedAdjustmentsErrorsFiveTA[10][0], cappedAdjustmentsErrorsFiveTA[10][1], cappedAdjustmentsErrorsFiveTA[10][2], errorsFN[0], errorsFN[1], errorsFN[2], cappedAdjustmentsErrorsFN[0][0], cappedAdjustmentsErrorsFN[0][1], cappedAdjustmentsErrorsFN[0][2], cappedAdjustmentsErrorsFN[1][0], cappedAdjustmentsErrorsFN[1][1], cappedAdjustmentsErrorsFN[1][2], cappedAdjustmentsErrorsFN[2][0], cappedAdjustmentsErrorsFN[2][1], cappedAdjustmentsErrorsFN[2][2], cappedAdjustmentsErrorsFN[3][0], cappedAdjustmentsErrorsFN[3][1], cappedAdjustmentsErrorsFN[3][2], cappedAdjustmentsErrorsFN[4][0], cappedAdjustmentsErrorsFN[4][1], cappedAdjustmentsErrorsFN[4][2], cappedAdjustmentsErrorsFN[5][0], cappedAdjustmentsErrorsFN[5][1], cappedAdjustmentsErrorsFN[5][2], cappedAdjustmentsErrorsFN[6][0], cappedAdjustmentsErrorsFN[6][1], cappedAdjustmentsErrorsFN[6][2], cappedAdjustmentsErrorsFN[7][0], cappedAdjustmentsErrorsFN[7][1], cappedAdjustmentsErrorsFN[7][2], cappedAdjustmentsErrorsFN[8][0], cappedAdjustmentsErrorsFN[8][1], cappedAdjustmentsErrorsFN[8][2], cappedAdjustmentsErrorsFN[9][0], cappedAdjustmentsErrorsFN[9][1], cappedAdjustmentsErrorsFN[9][2], cappedAdjustmentsErrorsFN[10][0], cappedAdjustmentsErrorsFN[10][1], cappedAdjustmentsErrorsFN[10][2], errorsF[0], errorsF[1], errorsF[2], cappedAdjustmentsErrorsF[0][0], cappedAdjustmentsErrorsF[0][1], cappedAdjustmentsErrorsF[0][2], cappedAdjustmentsErrorsF[1][0], cappedAdjustmentsErrorsF[1][1], cappedAdjustmentsErrorsF[1][2], cappedAdjustmentsErrorsF[2][0], cappedAdjustmentsErrorsF[2][1], cappedAdjustmentsErrorsF[2][2], cappedAdjustmentsErrorsF[3][0], cappedAdjustmentsErrorsF[3][1], cappedAdjustmentsErrorsF[3][2], cappedAdjustmentsErrorsF[4][0], cappedAdjustmentsErrorsF[4][1], cappedAdjustmentsErrorsF[4][2], cappedAdjustmentsErrorsF[5][0], cappedAdjustmentsErrorsF[5][1], cappedAdjustmentsErrorsF[5][2], cappedAdjustmentsErrorsF[6][0], cappedAdjustmentsErrorsF[6][1], cappedAdjustmentsErrorsF[6][2], cappedAdjustmentsErrorsF[7][0], cappedAdjustmentsErrorsF[7][1], cappedAdjustmentsErrorsF[7][2], cappedAdjustmentsErrorsF[8][0], cappedAdjustmentsErrorsF[8][1], cappedAdjustmentsErrorsF[8][2], cappedAdjustmentsErrorsF[9][0], cappedAdjustmentsErrorsF[9][1], cappedAdjustmentsErrorsF[9][2], cappedAdjustmentsErrorsF[10][0], cappedAdjustmentsErrorsF[10][1], cappedAdjustmentsErrorsF[10][2], errorsT[0], errorsT[1], errorsT[2], cappedAdjustmentsErrorsT[0][0], cappedAdjustmentsErrorsT[0][1], cappedAdjustmentsErrorsT[0][2], cappedAdjustmentsErrorsT[1][0], cappedAdjustmentsErrorsT[1][1], cappedAdjustmentsErrorsT[1][2], cappedAdjustmentsErrorsT[2][0], cappedAdjustmentsErrorsT[2][1], cappedAdjustmentsErrorsT[2][2], cappedAdjustmentsErrorsT[3][0], cappedAdjustmentsErrorsT[3][1], cappedAdjustmentsErrorsT[3][2], cappedAdjustmentsErrorsT[4][0], cappedAdjustmentsErrorsT[4][1], cappedAdjustmentsErrorsT[4][2], cappedAdjustmentsErrorsT[5][0], cappedAdjustmentsErrorsT[5][1], cappedAdjustmentsErrorsT[5][2], cappedAdjustmentsErrorsT[6][0], cappedAdjustmentsErrorsT[6][1], cappedAdjustmentsErrorsT[6][2], cappedAdjustmentsErrorsT[7][0], cappedAdjustmentsErrorsT[7][1], cappedAdjustmentsErrorsT[7][2], cappedAdjustmentsErrorsT[8][0], cappedAdjustmentsErrorsT[8][1], cappedAdjustmentsErrorsT[8][2], cappedAdjustmentsErrorsT[9][0], cappedAdjustmentsErrorsT[9][1], cappedAdjustmentsErrorsT[9][2], cappedAdjustmentsErrorsT[10][0], cappedAdjustmentsErrorsT[10][1], cappedAdjustmentsErrorsT[10][2]]187 # errorsFiveTN[0], errorsFiveTN[1], errorsFiveTN[2], errorsFiveTA[0], errorsFiveTA[1], errorsFiveTA[2], cappedAdjustmentsErrorsFiveTA[0][0], cappedAdjustmentsErrorsFiveTA[0][1], cappedAdjustmentsErrorsFiveTA[0][2], cappedAdjustmentsErrorsFiveTA[1][0], cappedAdjustmentsErrorsFiveTA[1][1], cappedAdjustmentsErrorsFiveTA[1][2], cappedAdjustmentsErrorsFiveTA[2][0], cappedAdjustmentsErrorsFiveTA[2][1], cappedAdjustmentsErrorsFiveTA[2][2], cappedAdjustmentsErrorsFiveTA[3][0], cappedAdjustmentsErrorsFiveTA[3][1], cappedAdjustmentsErrorsFiveTA[3][2], cappedAdjustmentsErrorsFiveTA[4][0], cappedAdjustmentsErrorsFiveTA[4][1], cappedAdjustmentsErrorsFiveTA[4][2], cappedAdjustmentsErrorsFiveTA[5][0], cappedAdjustmentsErrorsFiveTA[5][1], cappedAdjustmentsErrorsFiveTA[5][2], cappedAdjustmentsErrorsFiveTA[6][0], cappedAdjustmentsErrorsFiveTA[6][1], cappedAdjustmentsErrorsFiveTA[6][2], cappedAdjustmentsErrorsFiveTA[7][0], cappedAdjustmentsErrorsFiveTA[7][1], cappedAdjustmentsErrorsFiveTA[7][2], cappedAdjustmentsErrorsFiveTA[8][0], cappedAdjustmentsErrorsFiveTA[8][1], cappedAdjustmentsErrorsFiveTA[8][2], cappedAdjustmentsErrorsFiveTA[9][0], cappedAdjustmentsErrorsFiveTA[9][1], cappedAdjustmentsErrorsFiveTA[9][2], cappedAdjustmentsErrorsFiveTA[10][0], cappedAdjustmentsErrorsFiveTA[10][1], cappedAdjustmentsErrorsFiveTA[10][2],188 row_data.append(today)189 row_data.insert(0, maxTemp)190 # Holiday is H, Bussiness is B191 if isHoliday(date):192 row_data.insert(0, 'H')193 else:194 row_data.insert(0, 'B')195 row_data.insert(0, date)196 row_data.insert(0, storage_list[2])197 row_data.insert(0, storage_list[1])198 row_data.insert(0, storage_list[0])199 if(global_vars.PRINTFLAG >= 2):200 print("returning row")201 return row_data202# runFrequentBaseline(interval_df, DRDays, temp_df, interval, date, storage_list)203# runs baseline functions for an SAID for given day using passed in data204# input205# interval_df, pandas.Dataframe, contains all interval data relevant to SAID206# DRdays, list, contains list of DR event dates in datetime form207# temp_df, pandas.Dataframe, contains all temperature data208# interval, int, 15 or 60, data collection interval used to find correct sql table209# date, pandas.datetime, date to run baselines on 210# storage_list, list, starter list for new row211# output212# row_data, list, all data including baseline for specific SAID 213def runFrequentBaseline(interval_df, DRDays, temp_df, interval, date, storage_list):214 try:215 maxTemp = getMaxTemp(temp_df, date)216 if(global_vars.PRINTFLAG >= 2):217 print("Max Temp is",maxTemp,"F")218 except:219 print("Might be error with python version if this prints many times, try Python 3.5.5")220 return 'NA'221 maxTemp = str(maxTemp)222 # used for time inputs223 twoAM = pd.to_datetime(('02:00').strip(),format='%H:%M').time() 224 fourAM = pd.to_datetime(('04:00').strip(),format='%H:%M').time() 225 eightAM = pd.to_datetime(('08:00').strip(),format='%H:%M').time()226 tenAM = pd.to_datetime(('10:00').strip(),format='%H:%M').time()227 twoPM = pd.to_datetime(('14:00').strip(),format='%H:%M').time()228 fourPM = pd.to_datetime(('16:00').strip(),format='%H:%M').time() 229 eightPM = pd.to_datetime(('20:00').strip(),format='%H:%M').time()230 tenPM = pd.to_datetime(('22:00').strip(),format='%H:%M').time() 231 event_times = [fourAM, eightAM, tenAM, twoPM, fourPM, eightPM, tenPM]232 event_tuples = [(eightAM, tenAM), (twoPM, fourPM), (eightPM, tenPM), 233 (fourAM, eightAM), (tenAM, twoPM), (fourPM, eightPM),234 (fourAM, tenAM), (tenAM, fourPM), (fourPM, tenPM), 235 (eightAM, fourPM), (twoPM, tenPM)]236 # all data that will be returned for that date237 row_data = []238 try:239 for start_time in event_times:240 errorsTTA, cappedAdjustmentsErrorsTTA = getTenTenWithAdjustment(interval_df, DRDays, date, start_time, interval)241 if errorsTTA == 'NA':242 return 'NA'243 row_data.append(errorsTTA[0])244 row_data.append(errorsTTA[1])245 row_data.append(errorsTTA[2]) 246 except:247 return 'NA'248 try:249 for (start_time, end_time) in event_tuples:250 errorsThTN = getThreeTenNonAdjustment(interval_df, DRDays, date, start_time, end_time)251 if errorsThTN == 'NA':252 return 'NA'253 row_data.append(errorsThTN[0])254 row_data.append(errorsThTN[1])255 row_data.append(errorsThTN[2]) 256 except:257 return 'NA'258 try:259 for (start_time, end_time) in event_tuples:260 errorsThTA, cappedAdjustmentsErrorsThTA = getThreeTenWithAdjustment(interval_df, DRDays, date, start_time, end_time, interval)261 if errorsTTA == 'NA':262 return 'NA'263 row_data.append(errorsThTA[0])264 row_data.append(errorsThTA[1])265 row_data.append(errorsThTA[2]) 266 except:267 return 'NA'268 today = str(datetime.now().date())269 row_data.append(today)270 row_data.insert(0, maxTemp)271 # Holiday is H, Bussiness is B272 if isHoliday(date):273 row_data.insert(0, 'H')274 else:275 row_data.insert(0, 'B')276 row_data.insert(0, date)277 row_data.insert(0, storage_list[2])278 row_data.insert(0, storage_list[1])279 row_data.insert(0, storage_list[0])280 if(global_vars.PRINTFLAG >= 2):281 print("returning row")282 return row_data283def runXSPBaseline(interval_df, DRDays, temp_df, interval, date, storage_list):284 # used for time inputs285 twoPM = pd.to_datetime(('14:00').strip(),format='%H:%M').time()286 eightPM = pd.to_datetime(('20:00').strip(),format='%H:%M').time()287 288 try:289 errorsTTN = getTenTenNonAdjustment(interval_df, DRDays, date)290 except:291 errorsTTN = ['NA','NA','NA']292 try:293 errorsTTA, cappedAdjustmentsErrorsTTA = getTenTenWithAdjustment(interval_df, DRDays, date, twoPM, interval)294 except:295 errorsTTA = ['NA','NA','NA']296 try:297 errorsThTN = getThreeTenNonAdjustment(interval_df, DRDays, date, twoPM, eightPM)298 except:299 errorsThTN = ['NA','NA','NA']300 try:301 errorsThTA, cappedAdjustmentsErrorsThTA = getThreeTenWithAdjustment(interval_df, DRDays, date, twoPM, eightPM, interval)302 except:303 errorsThTA = ['NA','NA','NA'] 304 row_data = [errorsTTN[0], errorsTTN[1], errorsTTN[2], errorsTTA[0], errorsTTA[1], errorsTTA[2], errorsThTN[0], errorsThTN[1], errorsThTN[2], errorsThTA[0], errorsThTA[1], errorsThTA[2]]305 return row_data306# getTenTenNonAdjustment(interval_df, DRdays, date)307# gets error rates for 10-in-10 Baseline with no adjustment308# input309# interval_df, pandas.Dataframe, contains all interval data relevant to SAID310# DRdays, list, contains list of DR event dates in datetime form311# date, pandas.datetime, date to run baselines on 312# output313# error, triple, (cv, rmse, mape)314def getTenTenNonAdjustment(interval_df, DRDays, date):315 # get numpy array interval data for past 10 days and current date (11 rows)316 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)317 if numberData.shape[0] <= 10:318 if(global_vars.PRINTFLAG >= 2):319 print("Dataframe has only",numberData.shape[0], "days")320 return 'NA'321 prediction = np.mean(numberData[0:numberData.shape[0]-1], axis=0)322 actual = numberData[numberData.shape[0]-1,:]323 if(global_vars.PRINTFLAG >= 2):324 print("10-in-10 With No Adjustment:")325 errors = getErrors(prediction, actual)326 return errors327# getTenTenWithAdjustment(interval_df, DRdays, date, timeInitial, timeFinal)328# gets error rates for 10-in-10 Baseline with adjustment based on the start and end time329# input330# interval_df, pandas.Dataframe, contains all interval data relevant to SAID331# DRdays, list, contains list of DR event dates in datetime form332# date, pandas.datetime, date to run baselines on 333# eventTime, datetime.time, time of start of event334# interval, int, period between each interval measurement335# output336# error, triple, (cv, rmse, mape)337# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form338def getTenTenWithAdjustment(interval_df, DRDays, date, eventTime, interval):339 # get numpy array interval data for past 10 days and current date (11 rows)340 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)341 if numberData.shape[0] <= 10:342 if(global_vars.PRINTFLAG >= 2):343 print("Dataframe has only",numberData.shape[0], "days")344 return 'NA','NA'345 prediction = np.mean(numberData[0:numberData.shape[0]-1], axis=0)346 actual = numberData[numberData.shape[0]-1,:]347 adjustment = getAdjustment(numberData, time_indexes, eventTime, interval)348 if(global_vars.PRINTFLAG >= 2):349 print("10-10 With Adjustment Capped:")350 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)351 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, adjustment)352 prediction = [data * adjustment for data in prediction]353 # print("10pred", prediction)354 if(global_vars.PRINTFLAG >= 2):355 print("10-in-10 With Adjustment:")356 errors = getErrors(prediction, actual)357 return errors, cappedAdjustmentsErrors358# getThreeTenNonAdjustment(interval_df, DRdays, date)359# gets error rates for 3-in-10 Baseline (top three days of the last 10) with no adjustment360# input361# interval_df, pandas.Dataframe, contains all interval data relevant to SAID362# DRdays, list, contains list of DR event dates in datetime form363# date, pandas.datetime, date to run baselines on 364# eventStart, datetime.time, event start time365# eventEnd, datetime.time, event end time366# output367# error, triple, (cv, rmse, mape)368def getThreeTenNonAdjustment(interval_df, DRDays, date, eventStart, eventEnd):369 # get numpy array interval data for past 10 days and current date (11 rows)370 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)371 if numberData.shape[0] <=10:372 if(global_vars.PRINTFLAG >= 2):373 print("Dataframe has only",numberData.shape[0], "days")374 return 'NA','NA'375 numberData = np.asarray(numberData)376 eventStartTimeIndex = time_indexes.index(eventStart)377 eventEndTimeIndex = time_indexes.index(eventEnd)378 numberData_row_part_totals = np.sum(numberData[0:numberData.shape[0]-1, eventStartTimeIndex:eventEndTimeIndex], axis=1)379 max_rows = numberData_row_part_totals.argsort()[-3:][::-1]380 381 prediction = np.mean(numberData[max_rows], axis=0)382 actual = numberData[numberData.shape[0]-1,:]383 if(global_vars.PRINTFLAG >= 2):384 print("3-in-10 With No Adjustment:")385 errors = getErrors(prediction, actual)386 return errors387# getThreeTenWithAdjustment(interval_df, DRdays, date, eventTime, interval)388# gets error rates for 3-in-10 Baseline (top three days of the last 10) with adjustment389# input390# interval_df, pandas.Dataframe, contains all interval data relevant to SAID391# DRdays, list, contains list of DR event dates in datetime form392# date, pandas.datetime, date to run baselines on 393# eventTime, datetime.time, time of start of event394# eventEnd, datetime.time, event end time395# interval, int, period between each interval measurement396# output397# error, triple, (cv, rmse, mape)398# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form399def getThreeTenWithAdjustment(interval_df, DRDays, date, eventTime, eventEnd, interval):400 # get numpy array interval data for past 10 days and current date (11 rows)401 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)402 if numberData.shape[0] <=10:403 if(global_vars.PRINTFLAG >= 2):404 print("Dataframe has only",numberData.shape[0], "days")405 return 'NA','NA'406 numberData = np.asarray(numberData)407 eventStartTimeIndex = time_indexes.index(eventTime)408 eventEndTimeIndex = time_indexes.index(eventEnd)409 numberData_row_part_totals = np.sum(numberData[0:numberData.shape[0]-1, eventStartTimeIndex:eventEndTimeIndex], axis=1)410 max_rows = numberData_row_part_totals.argsort()[-3:][::-1]411 prediction = np.mean(numberData[max_rows], axis=0)412 actual = numberData[numberData.shape[0]-1,:]413 414 max_rows = max_rows.tolist()415 max_rows.append(numberData.shape[0]-1)416 # max_rows = np.vstack([max_rows, newrow])417 adjustment = getAdjustment(numberData[max_rows], time_indexes, eventTime, interval)418 419 # print("ey\n",numberData[max_rows])420 # print("adjustment",adjustment)421 if(global_vars.PRINTFLAG >= 2):422 print("3-10 With Adjustment Capped:")423 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)424 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, adjustment)425 if(global_vars.PRINTFLAG >= 2):426 print("adjustment", adjustment)427 prediction = [data * adjustment for data in prediction]428 # print("3pred", prediction)429 if(global_vars.PRINTFLAG >= 2):430 print("3-in-10 With Adjustment:")431 errors = getErrors(prediction, actual)432 return errors, cappedAdjustmentsErrors433# getThreeTenNonAdjustment(interval_df, DRdays, date)434# gets error rates for 3-in-10 Baseline (top three days of the last 10) with no adjustment435# input436# interval_df, pandas.Dataframe, contains all interval data relevant to SAID437# DRdays, list, contains list of DR event dates in datetime form438# date, pandas.datetime, date to run baselines on 439# eventStart, datetime.time, event start time440# eventEnd, datetime.time, event end time441# output442# error, triple, (cv, rmse, mape)443def getFiveTenNonAdjustment(interval_df, DRDays, date, eventStart, eventEnd):444 # get numpy array interval data for past 10 days and current date (11 rows)445 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)446 if numberData.shape[0] <=10:447 if(global_vars.PRINTFLAG >= 2):448 print("Dataframe has only",numberData.shape[0], "days")449 return 'NA','NA'450 numberData = np.asarray(numberData)451 eventStartTimeIndex = time_indexes.index(eventStart)452 eventEndTimeIndex = time_indexes.index(eventEnd)453 numberData_row_part_totals = np.sum(numberData[0:numberData.shape[0]-1, eventStartTimeIndex:eventEndTimeIndex], axis=1)454 max_rows = numberData_row_part_totals.argsort()[-5:][::-1]455 456 prediction = np.mean(numberData[max_rows], axis=0)457 actual = numberData[numberData.shape[0]-1,:]458 if(global_vars.PRINTFLAG >= 2):459 print("3-in-10 With No Adjustment:")460 errors = getErrors(prediction, actual)461 return errors462# getThreeTenWithAdjustment(interval_df, DRdays, date, eventTime, interval)463# gets error rates for 3-in-10 Baseline (top three days of the last 10) with adjustment464# input465# interval_df, pandas.Dataframe, contains all interval data relevant to SAID466# DRdays, list, contains list of DR event dates in datetime form467# date, pandas.datetime, date to run baselines on 468# eventTime, datetime.time, time of start of event469# eventEnd, datetime.time, event end time470# interval, int, period between each interval measurement471# output472# error, triple, (cv, rmse, mape)473# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form474def getFiveTenWithAdjustment(interval_df, DRDays, date, eventTime, eventEnd, interval):475 # get numpy array interval data for past 10 days and current date (11 rows)476 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)477 if numberData.shape[0] <=10:478 if(global_vars.PRINTFLAG >= 2):479 print("Dataframe has only",numberData.shape[0], "days")480 return 'NA','NA'481 numberData = np.asarray(numberData)482 eventStartTimeIndex = time_indexes.index(eventTime)483 eventEndTimeIndex = time_indexes.index(eventEnd)484 numberData_row_part_totals = np.sum(numberData[0:numberData.shape[0]-1, eventStartTimeIndex:eventEndTimeIndex], axis=1)485 max_rows = numberData_row_part_totals.argsort()[-5:][::-1]486 prediction = np.mean(numberData[max_rows], axis=0)487 actual = numberData[numberData.shape[0]-1,:]488 489 max_rows = max_rows.tolist()490 max_rows.append(numberData.shape[0]-1)491 # max_rows = np.vstack([max_rows, newrow])492 adjustment = getAdjustment(numberData[max_rows], time_indexes, eventTime, interval)493 494 # print("ey\n",numberData[max_rows])495 # print("adjustment",adjustment)496 if(global_vars.PRINTFLAG >= 2):497 print("3-10 With Adjustment Capped:")498 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)499 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, adjustment)500 if(global_vars.PRINTFLAG >= 2):501 print("adjustment", adjustment)502 prediction = [data * adjustment for data in prediction]503 # print("3pred", prediction)504 if(global_vars.PRINTFLAG >= 2):505 print("3-in-10 With Adjustment:")506 errors = getErrors(prediction, actual)507 return errors, cappedAdjustmentsErrors508# getFourNintyWeather(interval_df, DRDays, temp_df, date)509# runs 4-90 baseline function and return error. Top 4 weather days of any error510# input511# interval_df, pandas.Dataframe, contains all interval data relevant to SAID512# DRdays, list, contains list of DR event dates in datetime form513# temp_df, pandas.Dataframe, contains all temperature data514# date, pandas.datetime, date to run baselines on 515# output516# error, triple, (cv, rmse, mape)517# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form518def getFourNintyWeather(interval_df, DRDays, temp_df, date):519 tempHours, tempData = getPastDaysTemp(temp_df, DRDays, date, 90, False)520 # print("td",len(tempData))521 # print(tempData)522 # Make all tempDatas in the same hour the same523 tempData = adjustTimeTemp(tempHours, tempData)524 # print("td",len(tempData))525 # print(tempData)526 # Temp measurements per day527 chunksize = 48528 # to split days into seperate rows529 max_days_temp = []530 try:531 for i in range(90):532 newRow = max(tempData[(i*chunksize):(i+1)*chunksize])533 max_days_temp.append(newRow)534 except:535 return 'NA','NA'536 # get index of max temps from high to low537 max_days_temp = np.asarray(max_days_temp)538 indexList = list(max_days_temp.argsort())539 indexList.reverse()540 # get numpy array interval data for past 90 days and current date (91 rows)541 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 90, False)542 if numberData.shape[0] <= 90:543 if(global_vars.PRINTFLAG >= 2):544 print("Dataframe has only",numberData.shape[0], "days")545 return 'NA','NA'546 prediction = np.mean(numberData[indexList[:4]], axis=0)547 actual = numberData[numberData.shape[0]-1,:]548 if(global_vars.PRINTFLAG >= 2):549 print("4-90 Weather Capped:")550 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)551 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, 1.51)552 if(global_vars.PRINTFLAG >= 2):553 print("4-90 Weather:")554 errors = getErrors(prediction, actual)555 return errors, cappedAdjustmentsErrors556# getFiveTenWeather(interval_df, DRDays, temp_df, date)557# runs 5-10 baseline function and return error. Top 5 weather days of any error558# input559# interval_df, pandas.Dataframe, contains all interval data relevant to SAID560# DRdays, list, contains list of DR event dates in datetime form561# temp_df, pandas.Dataframe, contains all temperature data562# date, pandas.datetime, date to run baselines on 563# output564# error, triple, (cv, rmse, mape)565# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form566def getFiveTenWeather(interval_df, DRDays, temp_df, date):567 tempHours, tempData = getPastDaysTemp(temp_df, DRDays, date, 10, True)568 # Make all tempDatas in the same hour the same569 tempData = adjustTimeTemp(tempHours, tempData)570 # print("td 5-10",len(tempData),date)571 # print(tempData)572 # Temp measurements per day573 chunksize = 48574 # to split days into seperate rows575 max_days_temp = []576 try:577 for i in range(10):578 newRow = max(tempData[(i*chunksize):(i+1)*chunksize])579 max_days_temp.append(newRow)580 except:581 return 'NA','NA'582 # get index of max temps from high to low583 max_days_temp = np.asarray(max_days_temp)584 indexList = list(max_days_temp.argsort())585 indexList.reverse()586 # get numpy array interval data for past 90 days and current date (91 rows)587 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)588 # print("5-10", numberData)589 if numberData.shape[0] <= 10:590 if(global_vars.PRINTFLAG >= 2):591 print("Dataframe has only",numberData.shape[0], "days")592 return 'NA','NA'593 prediction = np.mean(numberData[indexList[:5]], axis=0)594 actual = numberData[numberData.shape[0]-1,:]595 596 # print("5-10", prediction)597 if(global_vars.PRINTFLAG >= 2):598 print("5-10 Weather Capped:")599 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)600 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, 1.51)601 if(global_vars.PRINTFLAG >= 2):602 print("5-10 Weather:")603 errors = getErrors(prediction, actual)604 return errors, cappedAdjustmentsErrors605# getTenTenWeather(interval_df, DRDays, temp_df, date)606# runs 10-10 baseline function and return error. Top 5 weather days of any error607# input608# interval_df, pandas.Dataframe, contains all interval data relevant to SAID609# DRdays, list, contains list of DR event dates in datetime form610# temp_df, pandas.Dataframe, contains all temperature data611# date, pandas.datetime, date to run baselines on 612# output613# error, triple, (cv, rmse, mape)614# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form615def getTenTenWeather(interval_df, DRDays, temp_df, date):616 tempHours, tempData = getPastDaysTemp(temp_df, DRDays, date, 10, True)617 # Make all tempDatas in the same hour the same618 tempData = adjustTimeTemp(tempHours, tempData)619 # Temp measurements per day620 chunksize = 48621 # to split days into seperate rows622 max_days_temp = []623 try:624 for i in range(10):625 newRow = max(tempData[(i*chunksize):(i+1)*chunksize])626 max_days_temp.append(newRow)627 except:628 return 'NA','NA'629 # get index of max temps from high to low630 max_days_temp = np.asarray(max_days_temp)631 indexList = list(max_days_temp.argsort())632 indexList.reverse()633 # get numpy array interval data for past 90 days and current date (91 rows)634 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 10, True)635 if numberData.shape[0] <= 10:636 if(global_vars.PRINTFLAG >= 2):637 print("Dataframe has only",numberData.shape[0], "days")638 return 'NA','NA'639 prediction = np.mean(numberData[indexList[:10]], axis=0)640 actual = numberData[numberData.shape[0]-1,:]641 if(global_vars.PRINTFLAG >= 2):642 print("10-10 Weather Capped:")643 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)644 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, 1.51)645 if(global_vars.PRINTFLAG >= 2):646 print("10-10 Weather:")647 errors = getErrors(prediction, actual)648 return errors, cappedAdjustmentsErrors649# getThreeFiveWeather(interval_df, DRDays, temp_df, date)650# runs 3-5 baseline function and return error. Top 5 weather days of any error651# input652# interval_df, pandas.Dataframe, contains all interval data relevant to SAID653# DRdays, list, contains list of DR event dates in datetime form654# temp_df, pandas.Dataframe, contains all temperature data655# date, pandas.datetime, date to run baselines on 656# output657# error, triple, (cv, rmse, mape)658# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form659def getThreeFiveWeather(interval_df, DRDays, temp_df, date):660 tempHours, tempData = getPastDaysTemp(temp_df, DRDays, date, 5, True)661 # print("td",len(tempData))662 # print(tempData)663 # Make all tempDatas in the same hour the same664 tempData = adjustTimeTemp(tempHours, tempData)665 # print("td 3-5",len(tempData), date)666 # print(tempData)667 # Temp measurements per day668 chunksize = 48669 # to split days into seperate rows670 max_days_temp = []671 # try:672 # for i in range(5):673 # newRow = max(tempData[(i*chunksize):(i+1)*chunksize])674 # max_days_temp.append(newRow)675 # print(max_days_temp)676 # except:677 # print("Oh No")678 # return 'NA','NA'679 for i in range(5):680 newRow = max(tempData[(i*chunksize):(i+1)*chunksize])681 max_days_temp.append(newRow)682 # print(max_days_temp)683 # get index of max temps from high to low684 max_days_temp = np.asarray(max_days_temp)685 indexList = list(max_days_temp.argsort())686 indexList.reverse()687 # get numpy array interval data for past 90 days and current date (91 rows)688 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 5, True)689 # print("3-5", numberData)690 if numberData.shape[0] <= 5:691 if(global_vars.PRINTFLAG >= 2):692 print("Dataframe has only",numberData.shape[0], "days")693 return 'NA','NA'694 prediction = (numberData[indexList[0]]*0.5)+(numberData[indexList[1]]*0.3)+(numberData[indexList[2]]*0.2)695 actual = numberData[numberData.shape[0]-1,:]696 # print("3-5", prediction)697 # print("3-5 a", actual)698 if(global_vars.PRINTFLAG >= 2):699 print("3-5 Weather Capped:")700 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)701 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, 1.51)702 if(global_vars.PRINTFLAG >= 2):703 print("3-5 Weather:")704 errors = getErrors(prediction, actual)705 return errors, cappedAdjustmentsErrors706# getFourFourWeather(interval_df, DRDays, temp_df, date)707# runs 4-4 baseline function and return error. Top 5 weather days of any error708# input709# interval_df, pandas.Dataframe, contains all interval data relevant to SAID710# DRdays, list, contains list of DR event dates in datetime form711# temp_df, pandas.Dataframe, contains all temperature data712# date, pandas.datetime, date to run baselines on 713# output714# error, triple, (cv, rmse, mape)715# cappedAdjustmentsErrors,list of triples, error rates for each capped adjustment in list form716def getFourFourWeather(interval_df, DRDays, temp_df, date):717 tempHours, tempData = getPastDaysTemp(temp_df, DRDays, date, 4, True)718 # Make all tempDatas in the same hour the same719 tempData = adjustTimeTemp(tempHours, tempData)720 # Temp measurements per day721 chunksize = 48722 # to split days into seperate rows723 max_days_temp = []724 try:725 for i in range(4):726 newRow = max(tempData[(i*chunksize):(i+1)*chunksize])727 max_days_temp.append(newRow)728 except:729 return 'NA','NA'730 # get index of max temps from high to low731 max_days_temp = np.asarray(max_days_temp)732 indexList = list(max_days_temp.argsort())733 indexList.reverse()734 # get numpy array interval data for past 90 days and current date (91 rows)735 numberData, time_indexes = getNeededDates(interval_df, DRDays, date, 4, True)736 if numberData.shape[0] <= 4:737 return 'NA','NA'738 prediction = np.mean(numberData[indexList[:4]], axis=0)739 actual = numberData[numberData.shape[0]-1,:]740 if(global_vars.PRINTFLAG >= 2):741 print("4-4 Weather Capped:")742 # -50,-40,-30,-20,-10,0 ,10,20,30,40,50 adjustment list (no)743 cappedAdjustmentsErrors = getCappedAdjustments(prediction, actual, 1.51)744 if(global_vars.PRINTFLAG >= 2):745 print("4-4 Weather:")746 errors = getErrors(prediction, actual)747 return errors, cappedAdjustmentsErrors748 ...

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test_capping_wang.py

Source:test_capping_wang.py Github

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1from sys import stderr2import unittest3from fragment_capping.helpers.types_helpers import Atom4from fragment_capping.helpers.molecule import Molecule, molecule_from_pdb_str5CAPPING_FUNCTION_NAME = 'get_best_capped_molecule_with_ILP'6class Test_Capping(unittest.TestCase):7 def test_example_0(self) -> None:8 molecule = Molecule(9 [10 Atom(index=1, element='C', valence=3, capped=True, coordinates=None),11 Atom(index=2, element='O', valence=1, capped=True, coordinates=None),12 Atom(index=3, element='O', valence=2, capped=True, coordinates=None),13 Atom(index=4, element='H', valence=1, capped=True, coordinates=None),14 Atom(index=5, element='H', valence=1, capped=True, coordinates=None),15 ],16 [17 (1, 2),18 (1, 3),19 (3, 4),20 (1, 5),21 ],22 name='methoanoic acid',23 )24 molecule.write_graph('raw_molecule')25 molecule.assign_bond_orders_and_charges_with_ILP()26 molecule.write_graph('molecule_with_electrons')27 def test_example_1(self) -> None:28 uncapped_molecule = Molecule(29 {30 1: Atom(index=1, element='C', valence=3, capped=False, coordinates=None),31 2: Atom(index=2, element='C', valence=3, capped=False, coordinates=None),32 },33 [34 (1, 2),35 ],36 name='example_1',37 )38 uncapped_molecule.write_graph('uncapped_molecule')39 for use_ILP in (True,):40 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)41 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))42 assert capped_molecule.formula(charge=True) == 'C2H4', capped_molecule.formula(charge=True)43 def test_example_2(self) -> None:44 uncapped_molecule = Molecule(45 {46 1: Atom(index=1, element='C', valence=3, capped=False, coordinates=None),47 2: Atom(index=2, element='O', valence=1, capped=False, coordinates=None),48 },49 [50 (1, 2),51 ],52 name='example_2',53 )54 uncapped_molecule.write_graph('uncapped_molecule')55 for use_ILP in (True,):56 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)57 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))58 assert capped_molecule.formula(charge=True) == 'CH2O', capped_molecule.formula(charge=True)59 def test_example_3(self) -> None:60 uncapped_molecule = Molecule(61 {62 1: Atom(index=1, element='C', valence=3, capped=False, coordinates=None),63 2: Atom(index=2, element='C', valence=3, capped=False, coordinates=None),64 3: Atom(index=3, element='C', valence=3, capped=False, coordinates=None),65 4: Atom(index=4, element='C', valence=3, capped=False, coordinates=None),66 5: Atom(index=5, element='C', valence=3, capped=False, coordinates=None),67 6: Atom(index=6, element='C', valence=3, capped=False, coordinates=None),68 },69 [70 (1, 2),71 (2, 3),72 (3, 4),73 (4, 5),74 (5, 6),75 (6, 1),76 ]77 )78 uncapped_molecule.write_graph('uncapped_molecule')79 for use_ILP in (True, False):80 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)81 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))82 assert capped_molecule.formula(charge=True) == 'C6H6', capped_molecule.formula(charge=True)83 def test_example_4(self) -> None:84 uncapped_molecule = Molecule(85 {86 1: Atom(index=1, element='C', valence=4, capped=False, coordinates=None),87 },88 [89 ],90 name='example_4',91 )92 uncapped_molecule.write_graph('uncapped_molecule')93 for use_ILP in (True, False):94 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)95 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))96 assert capped_molecule.formula(charge=True) == 'CH4', capped_molecule.formula(charge=True)97 def test_example_5(self) -> None:98 uncapped_molecule = Molecule(99 {100 1: Atom(index=1, element='C', valence=2, capped=True, coordinates=None),101 2: Atom(index=2, element='O', valence=1, capped=True, coordinates=None),102 3: Atom(index=3, element='O', valence=1, capped=True, coordinates=None),103 },104 [105 (1, 2),106 (1, 3),107 ],108 name='example_5',109 )110 uncapped_molecule.write_graph('uncapped_molecule')111 for use_ILP in (True, False):112 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)113 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))114 assert capped_molecule.formula(charge=True) == 'CO2', capped_molecule.formula(charge=True)115 def test_example_6(self) -> None:116 uncapped_molecule = Molecule(117 {118 1: Atom(index=1, element='C', valence=4, capped=False, coordinates=None),119 },120 [121 ],122 name='example_6',123 )124 uncapped_molecule.write_graph('uncapped_molecule')125 for use_ILP in (True, False):126 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)127 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))128 assert capped_molecule.formula(charge=True) == 'CH4', capped_molecule.formula(charge=True)129 def test_example_7(self) -> None:130 uncapped_molecule = Molecule(131 {132 1: Atom(index=1, element='C', valence=3, capped=False, coordinates=None),133 2: Atom(index=2, element='O', valence=2, capped=True, coordinates=None),134 3: Atom(index=3, element='O', valence=1, capped=True, coordinates=None),135 4: Atom(index=4, element='H', valence=1, capped=True, coordinates=None),136 },137 [138 (1, 2),139 (1, 3),140 (2, 4),141 ],142 name='example_7',143 )144 uncapped_molecule.write_graph('uncapped_molecule')145 for use_ILP in (True, False):146 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)147 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))148 assert capped_molecule.formula(charge=True) == 'CH2O2', capped_molecule.formula(charge=True)149 def test_example_8(self) -> None:150 uncapped_molecule = Molecule(151 {152 1: Atom(index=1, element='N', valence=None, capped=False, coordinates=None),153 2: Atom(index=2, element='H', valence=1, capped=True, coordinates=None),154 },155 [156 (1, 2),157 ],158 name='example_0',159 )160 uncapped_molecule.write_graph('uncapped_molecule')161 for use_ILP in (True,):162 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)163 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))164 assert capped_molecule.formula(charge=True) == 'H3N', capped_molecule.formula(charge=True)165 def test_example_9(self) -> None:166 uncapped_molecule = Molecule(167 {168 1: Atom(index=1, element='N', valence=None, capped=False, coordinates=None),169 2: Atom(index=2, element='H', valence=1, capped=True, coordinates=None),170 },171 [172 (1, 2),173 ],174 name='example_0',175 )176 uncapped_molecule.write_graph('uncapped_molecule')177 for use_ILP in (True,):178 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)179 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))180 assert capped_molecule.formula(charge=True) == 'H3N', capped_molecule.formula(charge=True)181 # Source: https://doi.org/10.1016/j.jmgm.2005.12.005182 def test_example_wang_1(self) -> None:183 uncapped_molecule = Molecule(184 {185 1: Atom(index=1, element='C', valence=3, capped=True, coordinates=None),186 2: Atom(index=2, element='C', valence=3, capped=True, coordinates=None),187 3: Atom(index=3, element='C', valence=3, capped=True, coordinates=None),188 4: Atom(index=4, element='C', valence=3, capped=True, coordinates=None),189 5: Atom(index=5, element='C', valence=3, capped=True, coordinates=None),190 6: Atom(index=6, element='C', valence=3, capped=True, coordinates=None),191 7: Atom(index=7, element='H', valence=1, capped=True, coordinates=None),192 8: Atom(index=8, element='H', valence=1, capped=True, coordinates=None),193 9: Atom(index=9, element='H', valence=1, capped=True, coordinates=None),194 10: Atom(index=10, element='H', valence=1, capped=True, coordinates=None),195 11: Atom(index=11, element='H', valence=1, capped=True, coordinates=None),196 12: Atom(index=12, element='O', valence=1, capped=True, coordinates=None),197 },198 [199 (1, 2),200 (2, 3),201 (3, 4),202 (4, 5),203 (5, 6),204 (6, 1),205 (7, 1),206 (8, 2),207 (9, 3),208 (10, 4),209 (11, 5),210 (12, 6),211 ],212 name='example_wang_1',213 )214 uncapped_molecule.write_graph('uncapped_molecule')215 for use_ILP in (True, False):216 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)217 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))218 assert capped_molecule.formula(charge=True) == 'C6H5O 1-', capped_molecule.formula(charge=True)219 def test_example_wang_2(self) -> None:220 uncapped_molecule = Molecule(221 {222 1: Atom(index=1, element='O', valence=1, capped=True, coordinates=None),223 2: Atom(index=2, element='C', valence=2, capped=True, coordinates=None),224 3: Atom(index=3, element='S', valence=3, capped=True, coordinates=None),225 4: Atom(index=4, element='C', valence=4, capped=False, coordinates=None),226 5: Atom(index=5, element='C', valence=4, capped=False, coordinates=None),227 },228 [229 (1, 2),230 (2, 3),231 (3, 4),232 (3, 5),233 ],234 name='example_wang_2',235 )236 uncapped_molecule.write_graph('uncapped_molecule')237 for use_ILP in (True, False):238 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)239 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))240 assert capped_molecule.formula(charge=True) == 'C3H6OS', capped_molecule.formula(charge=True)241 def test_example_wang_3(self) -> None:242 uncapped_molecule = Molecule(243 {244 1: Atom(index=1, element='C', valence=4, capped=False, coordinates=None),245 2: Atom(index=2, element='C', valence=4, capped=False, coordinates=None),246 3: Atom(index=3, element='C', valence=4, capped=False, coordinates=None),247 4: Atom(index=4, element='P', valence=4, capped=True, coordinates=None),248 5: Atom(index=5, element='O', valence=1, capped=True, coordinates=None),249 6: Atom(index=6, element='O', valence=2, capped=True, coordinates=None),250 7: Atom(index=7, element='O', valence=2, capped=True, coordinates=None),251 8: Atom(index=8, element='C', valence=4, capped=False, coordinates=None),252 9: Atom(index=9, element='C', valence=4, capped=False, coordinates=None),253 },254 [255 (1, 2),256 (2, 3),257 (2, 4),258 (4, 5),259 (4, 6),260 (4, 7),261 (6, 8),262 (7, 9),263 ],264 name='example_wang_3',265 )266 uncapped_molecule.write_graph('uncapped_molecule')267 for use_ILP in (True, False):268 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)269 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))270 assert capped_molecule.formula(charge=True) == 'C5H13O3P', capped_molecule.formula(charge=True)271 def test_example_wang_4(self) -> None:272 uncapped_molecule = Molecule(273 {274 1: Atom(index=1, element='O', valence=1, capped=True, coordinates=None),275 2: Atom(index=2, element='C', valence=3, capped=True, coordinates=None),276 3: Atom(index=3, element='C', valence=3, capped=False, coordinates=None),277 4: Atom(index=4, element='C', valence=3, capped=False, coordinates=None),278 5: Atom(index=5, element='C', valence=3, capped=False, coordinates=None),279 6: Atom(index=6, element='N', valence=2, capped=True, coordinates=None),280 },281 [282 (1, 2),283 (2, 3),284 (3, 4),285 (4, 5),286 (5, 6),287 (6, 2),288 ],289 name='example_wang_4',290 )291 uncapped_molecule.write_graph('uncapped_molecule')292 for use_ILP in (True, False):293 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)294 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))295 assert capped_molecule.formula(charge=True) == 'C4H3NO', capped_molecule.formula(charge=True)296 def test_example_wang_5(self) -> None:297 uncapped_molecule = Molecule(298 {299 1: Atom(index=1, element='C', valence=4, capped=False, coordinates=None),300 2: Atom(index=2, element='C', valence=4, capped=False, coordinates=None),301 3: Atom(index=3, element='C', valence=4, capped=False, coordinates=None),302 4: Atom(index=4, element='C', valence=2, capped=True, coordinates=None),303 5: Atom(index=5, element='N', valence=2, capped=True, coordinates=None),304 6: Atom(index=6, element='C', valence=4, capped=False, coordinates=None),305 },306 [307 (1, 2),308 (2, 3),309 (2, 4),310 (4, 5),311 (5, 6),312 ],313 name='example_wang_5',314 )315 uncapped_molecule.write_graph('uncapped_molecule')316 for use_ILP in (True, False):317 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)318 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))319 #assert capped_molecule.formula(charge=True) == 'C5H10N 1+', capped_molecule.formula(charge=True)320 def test_example_wang_6(self) -> None:321 uncapped_molecule = Molecule(322 {323 1: Atom(index=1, element='C', valence=3, capped=False, coordinates=None),324 2: Atom(index=2, element='C', valence=3, capped=False, coordinates=None),325 3: Atom(index=3, element='C', valence=3, capped=False, coordinates=None),326 4: Atom(index=4, element='C', valence=3, capped=False, coordinates=None),327 5: Atom(index=5, element='C', valence=3, capped=True, coordinates=None),328 6: Atom(index=6, element='C', valence=3, capped=False, coordinates=None),329 7: Atom(index=7, element='C', valence=3, capped=False, coordinates=None),330 8: Atom(index=8, element='C', valence=3, capped=False, coordinates=None),331 9: Atom(index=9, element='C', valence=3, capped=False, coordinates=None),332 10: Atom(index=10, element='C', valence=3, capped=True, coordinates=None),333 },334 [335 (1, 2),336 (2, 3),337 (3, 4),338 (4, 5),339 (5, 6),340 (6, 7),341 (7, 8),342 (8, 9),343 (9, 10),344 (10, 1),345 (10, 5),346 ],347 name='example_wang_6',348 )349 uncapped_molecule.write_graph('uncapped_molecule')350 for use_ILP in (True, False):351 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)352 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))353 assert capped_molecule.formula(charge=True) == 'C10H8', capped_molecule.formula(charge=True)354 def test_example_wang_7(self) -> None:355 uncapped_molecule = Molecule(356 {357 1: Atom(index=1, element='C', valence=4, capped=False, coordinates=None),358 2: Atom(index=2, element='C', valence=2, capped=True, coordinates=None),359 3: Atom(index=3, element='N', valence=2, capped=True, coordinates=None),360 4: Atom(index=4, element='S', valence=1, capped=True, coordinates=None),361 },362 [363 (1, 2),364 (2, 3),365 (3, 4),366 ],367 name='example_wang_7',368 )369 uncapped_molecule.write_graph('uncapped_molecule')370 for use_ILP in (True, False):371 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)372 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))373 assert capped_molecule.formula(charge=True) == 'C2H3NS', capped_molecule.formula(charge=True)374 def test_example_wang_8(self) -> None:375 uncapped_molecule = Molecule(376 {377 1: Atom(index=1, element='N', valence=1, capped=True, coordinates=None),378 2: Atom(index=2, element='N', valence=2, capped=True, coordinates=None),379 3: Atom(index=3, element='C', valence=3, capped=True, coordinates=None),380 4: Atom(index=4, element='C', valence=3, capped=False, coordinates=None),381 5: Atom(index=5, element='P', valence=2, capped=True, coordinates=None),382 6: Atom(index=6, element='N', valence=2, capped=True, coordinates=None),383 7: Atom(index=7, element='C', valence=3, capped=False, coordinates=None),384 },385 [386 (1, 2),387 (2, 3),388 (3, 4),389 (4, 5),390 (5, 6),391 (6, 7),392 (7, 3),393 ],394 name='example_wang_8',395 )396 uncapped_molecule.write_graph('uncapped_molecule')397 for use_ILP in (True, False):398 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)399 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))400 assert capped_molecule.formula(charge=True) == 'C3H2N3P', capped_molecule.formula(charge=True)401 def test_example_wang_9(self) -> None:402 uncapped_molecule = Molecule(403 {404 1: Atom(index=1, element='H', valence=1, capped=True, coordinates=None),405 2: Atom(index=2, element='N', valence=2, capped=True, coordinates=None),406 3: Atom(index=3, element='C', valence=3, capped=False, coordinates=None),407 4: Atom(index=4, element='C', valence=3, capped=True, coordinates=None),408 5: Atom(index=5, element='C', valence=3, capped=False, coordinates=None),409 6: Atom(index=6, element='P', valence=2, capped=True, coordinates=None),410 7: Atom(index=7, element='H', valence=1, capped=True, coordinates=None),411 8: Atom(index=8, element='N', valence=2, capped=True, coordinates=None),412 9: Atom(index=9, element='N', valence=1, capped=True, coordinates=None),413 },414 [415 (1, 2),416 (2, 3),417 (3, 4),418 (4, 5),419 (5, 6),420 (6, 7),421 (4, 8),422 (8, 9),423 ],424 name='example_wang_9',425 )426 uncapped_molecule.write_graph('uncapped_molecule')427 for use_ILP in (True, False):428 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)429 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))430 assert capped_molecule.formula(charge=True) == 'C3H4N3P', capped_molecule.formula(charge=True)431 def test_example_wang_10(self) -> None:432 uncapped_molecule = Molecule(433 {434 1: Atom(index=1, element='C', valence=3, capped=True, coordinates=None),435 2: Atom(index=2, element='C', valence=3, capped=True, coordinates=None),436 3: Atom(index=3, element='C', valence=3, capped=True, coordinates=None),437 4: Atom(index=4, element='C', valence=3, capped=True, coordinates=None),438 5: Atom(index=5, element='C', valence=3, capped=True, coordinates=None),439 6: Atom(index=6, element='C', valence=3, capped=True, coordinates=None),440 7: Atom(index=7, element='O', valence=1, capped=True, coordinates=None),441 8: Atom(index=8, element='H', valence=1, capped=True, coordinates=None),442 9: Atom(index=9, element='H', valence=1, capped=True, coordinates=None),443 10: Atom(index=10, element='O', valence=1, capped=True, coordinates=None),444 11: Atom(index=11, element='H', valence=1, capped=True, coordinates=None),445 12: Atom(index=12, element='H', valence=1, capped=True, coordinates=None),446 },447 [448 (1, 2),449 (2, 3),450 (3, 4),451 (4, 5),452 (5, 6),453 (6, 1),454 (7, 1),455 (8, 2),456 (9, 3),457 (10, 4),458 (11, 5),459 (12, 6),460 ],461 name='example_wang_10',462 )463 uncapped_molecule.write_graph('uncapped_molecule')464 for use_ILP in (True, False):465 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)466 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))467 assert capped_molecule.formula(charge=True) == 'C6H4O2', capped_molecule.formula(charge=True)468 def test_example_wang_11(self) -> None:469 uncapped_molecule = Molecule(470 {471 1: Atom(index=1, element='C', valence=3, capped=False, coordinates=None),472 2: Atom(index=2, element='N', valence=3, capped=True, coordinates=None),473 3: Atom(index=3, element='H', valence=1, capped=True, coordinates=None),474 4: Atom(index=4, element='C', valence=3, capped=True, coordinates=None),475 5: Atom(index=5, element='C', valence=3, capped=False, coordinates=None),476 6: Atom(index=6, element='N', valence=2, capped=True, coordinates=None),477 7: Atom(index=7, element='S', valence=2, capped=True, coordinates=None),478 8: Atom(index=8, element='C', valence=3, capped=True, coordinates=None),479 9: Atom(index=9, element='N', valence=3, capped=True, coordinates=None),480 10: Atom(index=10, element='H', valence=1, capped=True, coordinates=None),481 },482 [483 (1, 2),484 (2, 3),485 (2, 4),486 (4, 5),487 (5, 6),488 (6, 7),489 (7, 8),490 (8, 9),491 (9, 10),492 (9, 1),493 (4, 8),494 ],495 name='example_wang_11',496 )497 uncapped_molecule.write_graph('uncapped_molecule')498 for use_ILP in (True, False):499 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)500 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))501 assert capped_molecule.formula(charge=True) == 'C4H4N3S 1+', capped_molecule.formula(charge=True)502 def test_example_wang_12(self) -> None:503 uncapped_molecule = Molecule(504 {505 1: Atom(index=1, element='C', valence=3, capped=True, coordinates=None),506 2: Atom(index=2, element='C', valence=3, capped=False, coordinates=None),507 3: Atom(index=3, element='C', valence=3, capped=False, coordinates=None),508 4: Atom(index=4, element='C', valence=3, capped=False, coordinates=None),509 5: Atom(index=5, element='C', valence=3, capped=False, coordinates=None),510 6: Atom(index=6, element='P', valence=4, capped=True, coordinates=None),511 7: Atom(index=7, element='O', valence=2, capped=True, coordinates=None),512 8: Atom(index=8, element='H', valence=1, capped=True, coordinates=None),513 9: Atom(index=9, element='O', valence=2, capped=True, coordinates=None),514 10: Atom(index=10, element='H', valence=1, capped=True, coordinates=None),515 11: Atom(index=11, element='O', valence=1, capped=True, coordinates=None),516 },517 [518 (1, 2),519 (2, 3),520 (3, 4),521 (4, 5),522 (5, 1),523 (1, 6),524 (6, 7),525 (7, 8),526 (6, 9),527 (9, 10),528 (6, 11),529 ],530 name='example_wang_12',531 )532 uncapped_molecule.write_graph('uncapped_molecule')533 for use_ILP in (True, False):534 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)535 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'))536 assert capped_molecule.formula(charge=True) == 'C5H6O3P 1-', capped_molecule.formula(charge=True)537 def test_example_taxol_core(self) -> None:538 uncapped_molecule = Molecule(539 {5: Atom(index=5, element="C", valence=3, capped=False, coordinates=(0.746, 3.138, 0.794)), 7: Atom(index=7, element="O", valence=2, capped=True, coordinates=(1.175, 1.853, 0.61)), 8: Atom(index=8, element="C", valence=4, capped=True, coordinates=(1.672, 1.0, 1.641)), 9: Atom(index=9, element="C", valence=4, capped=True, coordinates=(2.696, 1.617, 2.644)), 10: Atom(index=10, element="H", valence=1, capped=True, coordinates=(2.871, 2.705, 2.545)), 11: Atom(index=11, element="H", valence=1, capped=True, coordinates=(3.667, 1.113, 2.766)), 12: Atom(index=12, element="O", valence=2, capped=True, coordinates=(1.805, 1.347, 3.756)), 13: Atom(index=13, element="C", valence=4, capped=True, coordinates=(0.741, 0.845, 2.897)), 14: Atom(index=14, element="H", valence=1, capped=True, coordinates=(-0.111, 1.567, 2.942)), 15: Atom(index=15, element="C", valence=4, capped=False, coordinates=(0.262, -0.558, 3.171)), 18: Atom(index=18, element="C", valence=4, capped=False, coordinates=(1.353, -1.632, 3.131)), 20: Atom(index=20, element="O", valence=2, capped=True, coordinates=(1.998, -1.605, 4.383)), 21: Atom(index=21, element="H", valence=1, capped=True, coordinates=(2.798, -2.116, 4.304)), 22: Atom(index=22, element="C", valence=4, capped=False, coordinates=(2.315, -1.541, 1.879)), 29: Atom(index=29, element="C", valence=4, capped=True, coordinates=(1.951, -0.352, 0.936)), 30: Atom(index=30, element="H", valence=1, capped=True, coordinates=(0.931, -0.608, 0.548)), 31: Atom(index=31, element="C", valence=4, capped=True, coordinates=(2.911, -0.285, -0.293)), 32: Atom(index=32, element="H", valence=1, capped=True, coordinates=(3.702, -1.082, -0.163)), 33: Atom(index=33, element="O", valence=2, capped=False, coordinates=(3.52, 1.006, -0.367)), 101: Atom(index=101, element="C", valence=4, capped=False, coordinates=(0.908, -3.278, 0.308)), 47: Atom(index=47, element="C", valence=4, capped=True, coordinates=(2.191, -0.548, -1.701)), 48: Atom(index=48, element="O", valence=2, capped=True, coordinates=(3.132, -0.275, -2.729)), 49: Atom(index=49, element="H", valence=1, capped=True, coordinates=(3.241, 0.668, -2.768)), 50: Atom(index=50, element="C", valence=4, capped=False, coordinates=(0.937, 0.345, -1.879)), 53: Atom(index=53, element="C", valence=4, capped=False, coordinates=(1.845, -2.08, -1.847)), 54: Atom(index=54, element="C", valence=3, capped=True, coordinates=(0.733, -2.32, -0.843)), 59: Atom(index=59, element="C", valence=3, capped=False, coordinates=(-0.388, -1.56, -0.899))},540 {frozenset({5, 7}), frozenset({13, 15}), frozenset({18, 20}), frozenset({18, 15}), frozenset({50, 47}), frozenset({18, 22}), frozenset({8, 29}), frozenset({8, 9}), frozenset({32, 31}), frozenset({48, 47}), frozenset({9, 10}), frozenset({29, 30}), frozenset({29, 31}), frozenset({9, 11}), frozenset({53, 54}), frozenset({9, 12}), frozenset({20, 21}), frozenset({48, 49}), frozenset({29, 22}), frozenset({33, 31}), frozenset({31, 47}), frozenset({12, 13}), frozenset({13, 14}), frozenset({59, 54}), frozenset({8, 7}), frozenset({53, 47}), frozenset({101, 54}), frozenset({8, 13})},541 name='example_taxol_core',542 )543 uncapped_molecule.write_graph('uncapped_molecule', output_size=(1200, 1200))544 for use_ILP in (True,):545 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)546 capped_molecule.write_graph('capped_molecule_with_{0}'.format('ILP' if use_ILP else 'bruteforce'), output_size=(1200, 1200))547 assert capped_molecule.formula(charge=True) == 'C16H26O5', capped_molecule.formula(charge=True)548 def test_example_porphyrin(self, use_ILP: bool = True) -> None:549 with open('pdbs/tetraphenylporphyrin.pdb') as fh:550 uncapped_molecule = molecule_from_pdb_str(551 fh.read(),552 name='porphyrin',553 )554 _, _, pos = uncapped_molecule.write_graph(555 'input',556 output_size=(1200, 1200),557 graph_kwargs={'include_atom_index': False},558 )559 capped_molecule = getattr(uncapped_molecule, CAPPING_FUNCTION_NAME)(debug=None)560 capped_molecule.write_graph(561 'output',562 output_size=(1200, 1200),563 graph_kwargs={'include_atom_index': False},564 pos=None,565 )566if __name__ == '__main__':...

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LennardJonesCapped.py

Source:LennardJonesCapped.py Github

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1# Copyright (C) 2012,20132# Max Planck Institute for Polymer Research3# Copyright (C) 2008,2009,2010,20114# Max-Planck-Institute for Polymer Research & Fraunhofer SCAI5# 6# This file is part of ESPResSo++.7# 8# ESPResSo++ is free software: you can redistribute it and/or modify9# it under the terms of the GNU General Public License as published by10# the Free Software Foundation, either version 3 of the License, or11# (at your option) any later version.12# 13# ESPResSo++ is distributed in the hope that it will be useful,14# but WITHOUT ANY WARRANTY; without even the implied warranty of15# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the16# GNU General Public License for more details.17# 18# You should have received a copy of the GNU General Public License19# along with this program. If not, see <http://www.gnu.org/licenses/>. 20r"""21*****************************************22espressopp.interaction.LennardJonesCapped23*****************************************24.. math::25 V(r) = 4 \varepsilon \left[ \left( \frac{\sigma}{r} \right)^{12} -26 \left( \frac{\sigma}{r} \right)^{6} \right]27where `r` is either the distance or the capped distance, depending on which is28greater.29.. function:: espressopp.interaction.LennardJonesCapped(epsilon, sigma, cutoff, caprad, shift)30 :param epsilon: (default: 1.0)31 :param sigma: (default: 1.0)32 :param cutoff: (default: infinity)33 :param caprad: (default: 0.0)34 :param shift: (default: "auto")35 :type epsilon: real36 :type sigma: real37 :type cutoff: 38 :type caprad: real39 :type shift: 40.. function:: espressopp.interaction.VerletListLennardJonesCapped(vl)41 :param vl: 42 :type vl: 43.. function:: espressopp.interaction.VerletListLennardJonesCapped.getPotential(type1, type2)44 :param type1: 45 :param type2: 46 :type type1: 47 :type type2: 48 :rtype: 49.. function:: espressopp.interaction.VerletListLennardJonesCapped.setPotential(type1, type2, potential)50 :param type1: 51 :param type2: 52 :param potential: 53 :type type1: 54 :type type2: 55 :type potential: 56.. function:: espressopp.interaction.VerletListAdressLennardJonesCapped(vl, fixedtupleList)57 :param vl: 58 :param fixedtupleList: 59 :type vl: 60 :type fixedtupleList: 61.. function:: espressopp.interaction.VerletListAdressLennardJonesCapped.getPotentialAT(type1, type2)62 :param type1: 63 :param type2: 64 :type type1: 65 :type type2: 66 :rtype: 67.. function:: espressopp.interaction.VerletListAdressLennardJonesCapped.getPotentialCG(type1, type2)68 :param type1: 69 :param type2: 70 :type type1: 71 :type type2: 72 :rtype: 73.. function:: espressopp.interaction.VerletListAdressLennardJonesCapped.setPotentialAT(type1, type2, potential)74 :param type1: 75 :param type2: 76 :param potential: 77 :type type1: 78 :type type2: 79 :type potential: 80.. function:: espressopp.interaction.VerletListAdressLennardJonesCapped.setPotentialCG(type1, type2, potential)81 :param type1: 82 :param type2: 83 :param potential: 84 :type type1: 85 :type type2: 86 :type potential: 87.. function:: espressopp.interaction.VerletListHadressLennardJonesCapped(vl, fixedtupleList)88 :param vl: 89 :param fixedtupleList: 90 :type vl: 91 :type fixedtupleList: 92.. function:: espressopp.interaction.VerletListHadressLennardJonesCapped.getPotentialAT(type1, type2)93 :param type1: 94 :param type2: 95 :type type1: 96 :type type2: 97 :rtype: 98.. function:: espressopp.interaction.VerletListHadressLennardJonesCapped.getPotentialCG(type1, type2)99 :param type1: 100 :param type2: 101 :type type1: 102 :type type2: 103 :rtype: 104.. function:: espressopp.interaction.VerletListHadressLennardJonesCapped.setPotentialAT(type1, type2, potential)105 :param type1: 106 :param type2: 107 :param potential: 108 :type type1: 109 :type type2: 110 :type potential: 111.. function:: espressopp.interaction.VerletListHadressLennardJonesCapped.setPotentialCG(type1, type2, potential)112 :param type1: 113 :param type2: 114 :param potential: 115 :type type1: 116 :type type2: 117 :type potential: 118.. function:: espressopp.interaction.CellListLennardJonesCapped(stor)119 :param stor: 120 :type stor: 121.. function:: espressopp.interaction.CellListLennardJonesCapped.getPotential(type1, type2)122 :param type1: 123 :param type2: 124 :type type1: 125 :type type2: 126 :rtype: 127.. function:: espressopp.interaction.CellListLennardJonesCapped.setPotential(type1, type2, potential)128 :param type1: 129 :param type2: 130 :param potential: 131 :type type1: 132 :type type2: 133 :type potential: 134.. function:: espressopp.interaction.FixedPairListLennardJonesCapped(system, vl, potential)135 :param system: 136 :param vl: 137 :param potential: 138 :type system: 139 :type vl: 140 :type potential: 141.. function:: espressopp.interaction.FixedPairListLennardJonesCapped.getPotential()142 :rtype: 143.. function:: espressopp.interaction.FixedPairListLennardJonesCapped.setPotential(potential)144 :param potential: 145 :type potential: 146"""147from espressopp import pmi, infinity148from espressopp.esutil import *149from espressopp.interaction.Potential import *150from espressopp.interaction.Interaction import *151from _espressopp import interaction_LennardJonesCapped, \152 interaction_VerletListLennardJonesCapped, \153 interaction_VerletListAdressLennardJonesCapped, \154 interaction_VerletListHadressLennardJonesCapped, \155 interaction_CellListLennardJonesCapped, \156 interaction_FixedPairListLennardJonesCapped157class LennardJonesCappedLocal(PotentialLocal, interaction_LennardJonesCapped):158 def __init__(self, epsilon=1.0, sigma=1.0, 159 cutoff=infinity, caprad=0.0, shift="auto"):160 """Initialize the local Lennard Jones object."""161 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():162 if shift =="auto":163 cxxinit(self, interaction_LennardJonesCapped, 164 epsilon, sigma, cutoff, caprad)165 else:166 cxxinit(self, interaction_LennardJonesCapped, 167 epsilon, sigma, cutoff, caprad, shift)168class VerletListLennardJonesCappedLocal(InteractionLocal, interaction_VerletListLennardJonesCapped):169 def __init__(self, vl):170 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():171 cxxinit(self, interaction_VerletListLennardJonesCapped, vl)172 def setPotential(self, type1, type2, potential):173 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():174 self.cxxclass.setPotential(self, type1, type2, potential)175 def getPotential(self, type1, type2):176 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():177 return self.cxxclass.getPotential(self, type1, type2)178class VerletListAdressLennardJonesCappedLocal(InteractionLocal, interaction_VerletListAdressLennardJonesCapped):179 def __init__(self, vl, fixedtupleList):180 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():181 cxxinit(self, interaction_VerletListAdressLennardJonesCapped, vl, fixedtupleList)182 def setPotentialAT(self, type1, type2, potential):183 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():184 self.cxxclass.setPotentialAT(self, type1, type2, potential)185 def setPotentialCG(self, type1, type2, potential):186 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():187 self.cxxclass.setPotentialCG(self, type1, type2, potential)188 def getPotentialAT(self, type1, type2):189 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():190 return self.cxxclass.getPotentialAT(self, type1, type2)191 def getPotentialCG(self, type1, type2):192 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():193 return self.cxxclass.getPotentialCG(self, type1, type2)194 195class VerletListHadressLennardJonesCappedLocal(InteractionLocal, interaction_VerletListHadressLennardJonesCapped):196 def __init__(self, vl, fixedtupleList):197 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():198 cxxinit(self, interaction_VerletListHadressLennardJonesCapped, vl, fixedtupleList)199 def setPotentialAT(self, type1, type2, potential):200 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():201 self.cxxclass.setPotentialAT(self, type1, type2, potential)202 def setPotentialCG(self, type1, type2, potential):203 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():204 self.cxxclass.setPotentialCG(self, type1, type2, potential)205 def getPotentialAT(self, type1, type2):206 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():207 return self.cxxclass.getPotentialAT(self, type1, type2)208 def getPotentialCG(self, type1, type2):209 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():210 return self.cxxclass.getPotentialCG(self, type1, type2)211class CellListLennardJonesCappedLocal(InteractionLocal, interaction_CellListLennardJonesCapped):212 def __init__(self, stor):213 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():214 cxxinit(self, interaction_CellListLennardJonesCapped, stor)215 216 def setPotential(self, type1, type2, potential):217 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():218 self.cxxclass.setPotential(self, type1, type2, potential)219 def getPotential(self, type1, type2):220 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():221 return self.cxxclass.getPotential(self, type1, type2)222class FixedPairListLennardJonesCappedLocal(InteractionLocal, interaction_FixedPairListLennardJonesCapped):223 def __init__(self, system, vl, potential):224 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():225 cxxinit(self, interaction_FixedPairListLennardJonesCapped, system, vl, potential)226 227 def setPotential(self, potential):228 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():229 self.cxxclass.setPotential(self, potential)230 def getPotential(self):231 if not (pmi._PMIComm and pmi._PMIComm.isActive()) or pmi._MPIcomm.rank in pmi._PMIComm.getMPIcpugroup():232 return self.cxxclass.getPotential(self)233if pmi.isController:234 class LennardJonesCapped(Potential):235 'The Lennard-Jones potential.'236 pmiproxydefs = dict(237 cls = 'espressopp.interaction.LennardJonesCappedLocal',238 pmiproperty = ['epsilon', 'sigma', 'cutoff', 'caprad']239 )240 class VerletListLennardJonesCapped(Interaction):241 __metaclass__ = pmi.Proxy242 pmiproxydefs = dict(243 cls = 'espressopp.interaction.VerletListLennardJonesCappedLocal',244 pmicall = ['setPotential', 'getPotential']245 )246 class VerletListAdressLennardJonesCapped(Interaction):247 __metaclass__ = pmi.Proxy248 pmiproxydefs = dict(249 cls = 'espressopp.interaction.VerletListAdressLennardJonesCappedLocal',250 pmicall = ['setPotentialAT', 'setPotentialCG', 'getPotentialAT', 'getPotentialCG']251 )252 253 class VerletListHadressLennardJonesCapped(Interaction):254 __metaclass__ = pmi.Proxy255 pmiproxydefs = dict(256 cls = 'espressopp.interaction.VerletListHadressLennardJonesCappedLocal',257 pmicall = ['setPotentialAT', 'setPotentialCG', 'getPotentialAT', 'getPotentialCG']258 )259 class CellListLennardJonesCapped(Interaction):260 __metaclass__ = pmi.Proxy261 pmiproxydefs = dict(262 cls = 'espressopp.interaction.CellListLennardJonesCappedLocal',263 pmicall = ['setPotential', 'getPotential']264 )265 266 class FixedPairListLennardJonesCapped(Interaction):267 __metaclass__ = pmi.Proxy268 pmiproxydefs = dict(269 cls = 'espressopp.interaction.FixedPairListLennardJonesCappedLocal',270 pmicall = ['setPotential']...

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