diff --git a/impetusModel/impetusModel.html b/impetusModel/impetusModel.html
index e4a8c74189b12e2ced4a9637def7d248adb8f76f..e3494cd33bf95ac2dfe430035075ae0ed1e44713 100644
--- a/impetusModel/impetusModel.html
+++ b/impetusModel/impetusModel.html
@@ -266,7 +266,7 @@ div.tocify {
<h1 class="title toc-ignore">A household level daily consumption estimation microsimulation model</h1>
<h4 class="author">Ben Anderson (<a href="mailto:b.anderson@soton.ac.uk" class="email">b.anderson@soton.ac.uk</a>, <code>@dataknut</code>), Despoina Manouseli (<a href="mailto:d.manouseli@soton.ac.uk" class="email">d.manouseli@soton.ac.uk</a>) & Magesh Nagarajan (<a href="mailto:m.nagarajan@soton.ac.uk" class="email">m.nagarajan@soton.ac.uk</a>)</h4>
-<h4 class="date">Last run at: 2021-03-24 10:53:45</h4>
+<h4 class="date">Last run at: 2021-03-29 17:00:42</h4>
</div>
@@ -377,23 +377,129 @@ metDataMeanSunshineDT <- data.table(read.csv(paste0(iPath,"totalSunshine
kable(caption = "Summary of Met Office tables",
tables()
)</code></pre>
-<pre><code>## NAME NROW NCOL MB
-## 1: metDataMeanRainfallDT 107 14 0
-## 2: metDataMeanSunshineDT 88 14 0
-## 3: metDataMeanTempDT 107 14 0
-## COLS KEY
-## 1: year,obs_total_rainfall_jan,obs_total_rainfall_feb,obs_total_rainfall_mar,obs_total_rainfall_apr,obs_total_rainfall_may,...
-## 2: year,obs_total_sunshine_jan,obs_total_sunshine_feb,obs_total_sunshine_mar,obs_total_sunshine_apr,obs_total_sunshine_may,...
-## 3: year,obs_mean_temp_jan,obs_mean_temp_feb,obs_mean_temp_mar,obs_mean_temp_apr,obs_mean_temp_may,...
-## Total: 0MB</code></pre>
+<pre><code>## NAME NROW NCOL MB
+## 1: climAdjCoeffDT 10 10 0
+## 2: est2013dataFig1DT 10 6 0
+## 3: est2013dataFig2DT 6 5 0
+## 4: estDT 10 4 0
+## 5: hhDataFinalDaily_v1_3DT 1,800 14 0
+## 6: hhDataFinalDaily_v2_0DT 1,800 24 0
+## 7: hhMcDataDT 1,800 21 0
+## 8: hhPropsDT 1,800 5 0
+## 9: keepDT 1,800 12 0
+## 10: mcMedianDT 2 9 0
+## 11: metDataDT 276 12 0
+## 12: metDataMeanRainfallDT 107 14 0
+## 13: metDataMeanSunshineDT 88 14 0
+## 14: metDataMeanTempDT 107 14 0
+## 15: mlmDataDT 70 12 0
+## 16: mlmDataMeteredDT 35 12 0
+## 17: mlmDataSummaryDT 18 11 0
+## 18: mlmDataUnmeteredDT 35 12 0
+## 19: modelDT 9 4 0
+## 20: monthAdjCoeffDT 24 11 0
+## 21: mt 1 10 0
+## 22: mtDT 9 4 0
+## 23: occAdjValuesDT 1,800 38 1
+## 24: occupancyAdjCoeffDT 12 11 0
+## 25: plotDT 19 5 0
+## 26: rainfallDT 276 6 0
+## 27: relevantMetDataDT 252 8 0
+## 28: relMetDataMeanRainfallDT 23 14 0
+## 29: relMetDataMeanSunshineDT 23 14 0
+## 30: relMetDataMeanTempDT 23 14 0
+## 31: summaryDT 12 10 0
+## 32: sumt 12 6 0
+## 33: sunshineDT 276 6 0
+## 34: temperatureDT 276 6 0
+## 35: testDT 1,800 8 0
+## 36: yoyAdjCoeffDT 2 10 0
+## NAME NROW NCOL MB
+## COLS
+## 1: var,metered,Basin,Bath,Dishwasher,External,...
+## 2: Usage,percentOfTotalDaily,imputed.l.hh.day,pcTot,vol,source
+## 3: N.people,AverageLitresPerDayPerHousehold,AverageLitresPerDayPerCapita,source,occupancy
+## 4: Usage,pcTot,vol,source
+## 5: metered,occupancy,hhid,lsoaarea,dtype,Basin.baseline,...
+## 6: id,hhsize,meter,monthlyBathUse,monthlyShowerUse,monthlyDishwasherUse,...
+## 7: metered,hhid,lsoaarea,occupancy,dtype,Basin.parkerMedian,...
+## 8: hhid,lsoaarea,occupancy,dtype,metered
+## 9: hhid,occupancy,metered,Basin.baseline,Bath.baseline,Dishwasher.baseline,...
+## 10: metered,Basin.parkerMedian,Bath.parkerMedian,Dishwasher.parkerMedian,External.parkerMedian,KitchenSink.parkerMedian,...
+## 11: year,mon,place,time.x,meanTemp,id.x,...
+## 12: year,obs_total_rainfall_jan,obs_total_rainfall_feb,obs_total_rainfall_mar,obs_total_rainfall_apr,obs_total_rainfall_may,...
+## 13: year,obs_total_sunshine_jan,obs_total_sunshine_feb,obs_total_sunshine_mar,obs_total_sunshine_apr,obs_total_sunshine_may,...
+## 14: year,obs_mean_temp_jan,obs_mean_temp_feb,obs_mean_temp_mar,obs_mean_temp_apr,obs_mean_temp_may,...
+## 15: var,Basin,Bath,Dishwasher,External,Kitchen.sink,...
+## 16: var,Basin,Bath,Dishwasher,External,Kitchen.sink,...
+## 17: type,var,Basin.parkerMedian,Bath.parkerMedian,Dishwasher.parkerMedian,External.parkerMedian,...
+## 18: var,Basin,Bath,Dishwasher,External,Kitchen.sink,...
+## 19: vol,Usage,source,pcTot
+## 20: var,metered,month,Basin,Bath,Dishwasher,...
+## 21: vol,Basin,Dishwasher,External,Kitchen Sink,Bath,...
+## 22: vol,Usage,source,pcTot
+## 23: metered,occupancy,hhid,lsoaarea,dtype,Basin.parkerMedian,...
+## 24: var,metered,occupancy,Basin,Bath,Dishwasher,...
+## 25: Usage,pcTot,vol,source,UsageRo
+## 26: year,place,time,totalRainfall,id,mon
+## 27: year,mon,place,meanTemp,id.x,totalSunshine,...
+## 28: year,obs_total_rainfall_jan,obs_total_rainfall_feb,obs_total_rainfall_mar,obs_total_rainfall_apr,obs_total_rainfall_may,...
+## 29: year,obs_total_sunshine_jan,obs_total_sunshine_feb,obs_total_sunshine_mar,obs_total_sunshine_apr,obs_total_sunshine_may,...
+## 30: year,obs_mean_temp_jan,obs_mean_temp_feb,obs_mean_temp_mar,obs_mean_temp_apr,obs_mean_temp_may,...
+## 31: occupancy,metered,meanBasin,meanBath,meanDishwasher,meanExternal,...
+## 32: metered,occupancy,meanBasin.baseline,sdBasin.baseline,meanBath.baseline,sdBath.baseline
+## 33: year,place,time,totalSunshine,id,mon
+## 34: year,place,time,meanTemp,id,mon
+## 35: Basin.rsnorm,Bath.rsnorm,Dishwasher.rsnorm,External.rsnorm,KitchenSink.rsnorm,Shower.rsnorm,...
+## 36: var,metered,Basin,Bath,Dishwasher,External,...
+## COLS
+## KEY
+## 1: metered
+## 2:
+## 3: occupancy
+## 4:
+## 5: metered,occupancy
+## 6:
+## 7: metered,occupancy
+## 8: metered
+## 9: metered,occupancy
+## 10: metered
+## 11: year,mon,place
+## 12:
+## 13:
+## 14:
+## 15:
+## 16:
+## 17:
+## 18:
+## 19: Usage
+## 20: metered
+## 21:
+## 22: Usage
+## 23: metered,occupancy
+## 24: metered,occupancy
+## 25:
+## 26: year,mon,place
+## 27: year,mon,place
+## 28:
+## 29:
+## 30:
+## 31:
+## 32: metered,occupancy
+## 33: year,mon,place
+## 34: year,mon,place
+## 35:
+## 36: metered
+## KEY
+## Total: 1MB</code></pre>
<table>
<caption>Summary of Met Office tables</caption>
<colgroup>
-<col width="6%" />
-<col width="1%" />
-<col width="1%" />
+<col width="2%" />
<col width="0%" />
-<col width="88%" />
+<col width="0%" />
+<col width="0%" />
+<col width="94%" />
<col width="1%" />
</colgroup>
<thead>
@@ -408,6 +514,94 @@ kable(caption = "Summary of Met Office tables",
</thead>
<tbody>
<tr class="odd">
+<td align="left">climAdjCoeffDT</td>
+<td align="right">10</td>
+<td align="right">10</td>
+<td align="right">0</td>
+<td align="left">var , metered , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine</td>
+<td align="left">metered</td>
+</tr>
+<tr class="even">
+<td align="left">est2013dataFig1DT</td>
+<td align="right">10</td>
+<td align="right">6</td>
+<td align="right">0</td>
+<td align="left">Usage , percentOfTotalDaily, imputed.l.hh.day , pcTot , vol , source</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="odd">
+<td align="left">est2013dataFig2DT</td>
+<td align="right">6</td>
+<td align="right">5</td>
+<td align="right">0</td>
+<td align="left">N.people , AverageLitresPerDayPerHousehold, AverageLitresPerDayPerCapita , source , occupancy</td>
+<td align="left">occupancy</td>
+</tr>
+<tr class="even">
+<td align="left">estDT</td>
+<td align="right">10</td>
+<td align="right">4</td>
+<td align="right">0</td>
+<td align="left">Usage , pcTot , vol , source</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="odd">
+<td align="left">hhDataFinalDaily_v1_3DT</td>
+<td align="right">1800</td>
+<td align="right">14</td>
+<td align="right">0</td>
+<td align="left">metered , occupancy , hhid , lsoaarea , dtype , Basin.baseline , Bath.baseline , Dishwasher.baseline , External.baseline , KitchenSink.baseline , Shower.baseline , WC.baseline , WashingMachine.baseline, sumDaily.baseline</td>
+<td align="left">metered , occupancy</td>
+</tr>
+<tr class="even">
+<td align="left">hhDataFinalDaily_v2_0DT</td>
+<td align="right">1800</td>
+<td align="right">24</td>
+<td align="right">0</td>
+<td align="left">id , hhsize , meter , monthlyBathUse , monthlyShowerUse , monthlyDishwasherUse , monthlyKitchenSinkUse , monthlyWCUse , monthlyWashingMachineUse , monthlyBathroomSinkUse , totalMonthlyInHouseDemand , monthlyGardenUse , dailyGardenUse , monthlyCarWashUse , dailyCarWashUse , totalMonthlyHouseDemandFinal, totalDailyHouseDemandFinal , dailyBathUse , dailyShowerUse , dailyDishwasherUse , dailyKitchenSinkUse , dailyWCUse , dailyWashingMachineUse , dailyBathroomSinkUse</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="odd">
+<td align="left">hhMcDataDT</td>
+<td align="right">1800</td>
+<td align="right">21</td>
+<td align="right">0</td>
+<td align="left">metered , hhid , lsoaarea , occupancy , dtype , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian, Basin.rsnorm , Bath.rsnorm , Dishwasher.rsnorm , External.rsnorm , KitchenSink.rsnorm , Shower.rsnorm , WC.rsnorm , WashingMachine.rsnorm</td>
+<td align="left">metered , occupancy</td>
+</tr>
+<tr class="even">
+<td align="left">hhPropsDT</td>
+<td align="right">1800</td>
+<td align="right">5</td>
+<td align="right">0</td>
+<td align="left">hhid , lsoaarea , occupancy, dtype , metered</td>
+<td align="left">metered</td>
+</tr>
+<tr class="odd">
+<td align="left">keepDT</td>
+<td align="right">1800</td>
+<td align="right">12</td>
+<td align="right">0</td>
+<td align="left">hhid , occupancy , metered , Basin.baseline , Bath.baseline , Dishwasher.baseline , KitchenSink.baseline , Shower.baseline , WC.baseline , WashingMachine.baseline, External.baseline , sumDaily.baseline</td>
+<td align="left">metered , occupancy</td>
+</tr>
+<tr class="even">
+<td align="left">mcMedianDT</td>
+<td align="right">2</td>
+<td align="right">9</td>
+<td align="right">0</td>
+<td align="left">metered , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian</td>
+<td align="left">metered</td>
+</tr>
+<tr class="odd">
+<td align="left">metDataDT</td>
+<td align="right">276</td>
+<td align="right">12</td>
+<td align="right">0</td>
+<td align="left">year , mon , place , time.x , meanTemp , id.x , time.y , totalSunshine, id.y , time , totalRainfall, id</td>
+<td align="left">year , mon , place</td>
+</tr>
+<tr class="even">
<td align="left">metDataMeanRainfallDT</td>
<td align="right">107</td>
<td align="right">14</td>
@@ -415,7 +609,7 @@ kable(caption = "Summary of Met Office tables",
<td align="left">year , obs_total_rainfall_jan, obs_total_rainfall_feb, obs_total_rainfall_mar, obs_total_rainfall_apr, obs_total_rainfall_may, obs_total_rainfall_jun, obs_total_rainfall_jul, obs_total_rainfall_aug, obs_total_rainfall_sep, obs_total_rainfall_oct, obs_total_rainfall_nov, obs_total_rainfall_dec, place</td>
<td align="left">NULL</td>
</tr>
-<tr class="even">
+<tr class="odd">
<td align="left">metDataMeanSunshineDT</td>
<td align="right">88</td>
<td align="right">14</td>
@@ -423,7 +617,7 @@ kable(caption = "Summary of Met Office tables",
<td align="left">year , obs_total_sunshine_jan, obs_total_sunshine_feb, obs_total_sunshine_mar, obs_total_sunshine_apr, obs_total_sunshine_may, obs_total_sunshine_jun, obs_total_sunshine_jul, obs_total_sunshine_aug, obs_total_sunshine_sep, obs_total_sunshine_oct, obs_total_sunshine_nov, obs_total_sunshine_dec, place</td>
<td align="left">NULL</td>
</tr>
-<tr class="odd">
+<tr class="even">
<td align="left">metDataMeanTempDT</td>
<td align="right">107</td>
<td align="right">14</td>
@@ -431,6 +625,182 @@ kable(caption = "Summary of Met Office tables",
<td align="left">year , obs_mean_temp_jan, obs_mean_temp_feb, obs_mean_temp_mar, obs_mean_temp_apr, obs_mean_temp_may, obs_mean_temp_jun, obs_mean_temp_jul, obs_mean_temp_aug, obs_mean_temp_sep, obs_mean_temp_oct, obs_mean_temp_nov, obs_mean_temp_dec, place</td>
<td align="left">NULL</td>
</tr>
+<tr class="odd">
+<td align="left">mlmDataDT</td>
+<td align="right">70</td>
+<td align="right">12</td>
+<td align="right">0</td>
+<td align="left">var , Basin , Bath , Dishwasher , External , Kitchen.sink , Shower , WC , Washing.machine, addldetails , note , metered</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="even">
+<td align="left">mlmDataMeteredDT</td>
+<td align="right">35</td>
+<td align="right">12</td>
+<td align="right">0</td>
+<td align="left">var , Basin , Bath , Dishwasher , External , Kitchen.sink , Shower , WC , Washing.machine, addldetails , note , metered</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="odd">
+<td align="left">mlmDataSummaryDT</td>
+<td align="right">18</td>
+<td align="right">11</td>
+<td align="right">0</td>
+<td align="left">type , var , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian, Source</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="even">
+<td align="left">mlmDataUnmeteredDT</td>
+<td align="right">35</td>
+<td align="right">12</td>
+<td align="right">0</td>
+<td align="left">var , Basin , Bath , Dishwasher , External , Kitchen.sink , Shower , WC , Washing.machine, addldetails , note , metered</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="odd">
+<td align="left">modelDT</td>
+<td align="right">9</td>
+<td align="right">4</td>
+<td align="right">0</td>
+<td align="left">vol , Usage , source, pcTot</td>
+<td align="left">Usage</td>
+</tr>
+<tr class="even">
+<td align="left">monthAdjCoeffDT</td>
+<td align="right">24</td>
+<td align="right">11</td>
+<td align="right">0</td>
+<td align="left">var , metered , month , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine</td>
+<td align="left">metered</td>
+</tr>
+<tr class="odd">
+<td align="left">mt</td>
+<td align="right">1</td>
+<td align="right">10</td>
+<td align="right">0</td>
+<td align="left">vol , Basin , Dishwasher , External , Kitchen Sink , Bath , Shower , Toilet , Washing machine, Total</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="even">
+<td align="left">mtDT</td>
+<td align="right">9</td>
+<td align="right">4</td>
+<td align="right">0</td>
+<td align="left">vol , Usage , source, pcTot</td>
+<td align="left">Usage</td>
+</tr>
+<tr class="odd">
+<td align="left">occAdjValuesDT</td>
+<td align="right">1800</td>
+<td align="right">38</td>
+<td align="right">1</td>
+<td align="left">metered , occupancy , hhid , lsoaarea , dtype , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian, Basin.rsnorm , Bath.rsnorm , Dishwasher.rsnorm , External.rsnorm , KitchenSink.rsnorm , Shower.rsnorm , WC.rsnorm , WashingMachine.rsnorm , var , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine , Basin.baseline , Bath.baseline , Dishwasher.baseline , External.baseline , KitchenSink.baseline , Shower.baseline , WC.baseline , WashingMachine.baseline</td>
+<td align="left">metered , occupancy</td>
+</tr>
+<tr class="even">
+<td align="left">occupancyAdjCoeffDT</td>
+<td align="right">12</td>
+<td align="right">11</td>
+<td align="right">0</td>
+<td align="left">var , metered , occupancy , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine</td>
+<td align="left">metered , occupancy</td>
+</tr>
+<tr class="odd">
+<td align="left">plotDT</td>
+<td align="right">19</td>
+<td align="right">5</td>
+<td align="right">0</td>
+<td align="left">Usage , pcTot , vol , source , UsageRo</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="even">
+<td align="left">rainfallDT</td>
+<td align="right">276</td>
+<td align="right">6</td>
+<td align="right">0</td>
+<td align="left">year , place , time , totalRainfall, id , mon</td>
+<td align="left">year , mon , place</td>
+</tr>
+<tr class="odd">
+<td align="left">relevantMetDataDT</td>
+<td align="right">252</td>
+<td align="right">8</td>
+<td align="right">0</td>
+<td align="left">year , mon , place , meanTemp , id.x , totalSunshine, totalRainfall, slno</td>
+<td align="left">year , mon , place</td>
+</tr>
+<tr class="even">
+<td align="left">relMetDataMeanRainfallDT</td>
+<td align="right">23</td>
+<td align="right">14</td>
+<td align="right">0</td>
+<td align="left">year , obs_total_rainfall_jan, obs_total_rainfall_feb, obs_total_rainfall_mar, obs_total_rainfall_apr, obs_total_rainfall_may, obs_total_rainfall_jun, obs_total_rainfall_jul, obs_total_rainfall_aug, obs_total_rainfall_sep, obs_total_rainfall_oct, obs_total_rainfall_nov, obs_total_rainfall_dec, place</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="odd">
+<td align="left">relMetDataMeanSunshineDT</td>
+<td align="right">23</td>
+<td align="right">14</td>
+<td align="right">0</td>
+<td align="left">year , obs_total_sunshine_jan, obs_total_sunshine_feb, obs_total_sunshine_mar, obs_total_sunshine_apr, obs_total_sunshine_may, obs_total_sunshine_jun, obs_total_sunshine_jul, obs_total_sunshine_aug, obs_total_sunshine_sep, obs_total_sunshine_oct, obs_total_sunshine_nov, obs_total_sunshine_dec, place</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="even">
+<td align="left">relMetDataMeanTempDT</td>
+<td align="right">23</td>
+<td align="right">14</td>
+<td align="right">0</td>
+<td align="left">year , obs_mean_temp_jan, obs_mean_temp_feb, obs_mean_temp_mar, obs_mean_temp_apr, obs_mean_temp_may, obs_mean_temp_jun, obs_mean_temp_jul, obs_mean_temp_aug, obs_mean_temp_sep, obs_mean_temp_oct, obs_mean_temp_nov, obs_mean_temp_dec, place</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="odd">
+<td align="left">summaryDT</td>
+<td align="right">12</td>
+<td align="right">10</td>
+<td align="right">0</td>
+<td align="left">occupancy , metered , meanBasin , meanBath , meanDishwasher , meanExternal , meanKitchenSink , meanShower , meanWC , meanWashingMachine</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="even">
+<td align="left">sumt</td>
+<td align="right">12</td>
+<td align="right">6</td>
+<td align="right">0</td>
+<td align="left">metered , occupancy , meanBasin.baseline, sdBasin.baseline , meanBath.baseline , sdBath.baseline</td>
+<td align="left">metered , occupancy</td>
+</tr>
+<tr class="odd">
+<td align="left">sunshineDT</td>
+<td align="right">276</td>
+<td align="right">6</td>
+<td align="right">0</td>
+<td align="left">year , place , time , totalSunshine, id , mon</td>
+<td align="left">year , mon , place</td>
+</tr>
+<tr class="even">
+<td align="left">temperatureDT</td>
+<td align="right">276</td>
+<td align="right">6</td>
+<td align="right">0</td>
+<td align="left">year , place , time , meanTemp, id , mon</td>
+<td align="left">year , mon , place</td>
+</tr>
+<tr class="odd">
+<td align="left">testDT</td>
+<td align="right">1800</td>
+<td align="right">8</td>
+<td align="right">0</td>
+<td align="left">Basin.rsnorm , Bath.rsnorm , Dishwasher.rsnorm , External.rsnorm , KitchenSink.rsnorm , Shower.rsnorm , WC.rsnorm , WashingMachine.rsnorm</td>
+<td align="left">NULL</td>
+</tr>
+<tr class="even">
+<td align="left">yoyAdjCoeffDT</td>
+<td align="right">2</td>
+<td align="right">10</td>
+<td align="right">0</td>
+<td align="left">var , metered , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine</td>
+<td align="left">metered</td>
+</tr>
</tbody>
</table>
<p>Sunshine only starts in 1929 so the sunshine table has fewer rows.</p>
@@ -2247,21 +2617,21 @@ kable(caption = "Check % metered distribution",
<tbody>
<tr class="odd">
<td align="left">Metered</td>
-<td align="right">42</td>
+<td align="right">40.8</td>
+<td align="right">39.6</td>
+<td align="right">40.7</td>
+<td align="right">41.7</td>
<td align="right">38.3</td>
-<td align="right">40.4</td>
-<td align="right">37.5</td>
-<td align="right">43.6</td>
-<td align="right">39.8</td>
+<td align="right">33.7</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
-<td align="right">58</td>
+<td align="right">59.2</td>
+<td align="right">60.4</td>
+<td align="right">59.3</td>
+<td align="right">58.3</td>
<td align="right">61.7</td>
-<td align="right">59.6</td>
-<td align="right">62.5</td>
-<td align="right">56.4</td>
-<td align="right">60.2</td>
+<td align="right">66.3</td>
</tr>
</tbody>
</table>
@@ -2807,69 +3177,69 @@ kable(caption = "Test Basin & Bath l/day as modelled using rsnorm()&quo
<tbody>
<tr class="odd">
<td align="left"></td>
-<td align="left">Min. :12.11</td>
-<td align="left">Min. : 32.95</td>
-<td align="left">Min. :19.95</td>
+<td align="left">Min. :11.77</td>
+<td align="left">Min. : 37.10</td>
+<td align="left">Min. :19.79</td>
<td align="left">Min. : 0.00</td>
-<td align="left">Min. :27.22</td>
-<td align="left">Min. :21.44</td>
-<td align="left">Min. : 49.50</td>
-<td align="left">Min. : 55.51</td>
+<td align="left">Min. :26.99</td>
+<td align="left">Min. :20.83</td>
+<td align="left">Min. : 48.72</td>
+<td align="left">Min. : 55.09</td>
</tr>
<tr class="even">
<td align="left"></td>
-<td align="left">1st Qu.:17.58</td>
-<td align="left">1st Qu.: 57.10</td>
+<td align="left">1st Qu.:17.53</td>
+<td align="left">1st Qu.: 56.57</td>
<td align="left">1st Qu.:22.63</td>
-<td align="left">1st Qu.:10.72</td>
+<td align="left">1st Qu.:10.71</td>
<td align="left">1st Qu.:32.46</td>
-<td align="left">1st Qu.:31.65</td>
-<td align="left">1st Qu.: 80.84</td>
-<td align="left">1st Qu.: 72.84</td>
+<td align="left">1st Qu.:31.58</td>
+<td align="left">1st Qu.: 80.31</td>
+<td align="left">1st Qu.: 73.04</td>
</tr>
<tr class="odd">
<td align="left"></td>
-<td align="left">Median :24.09</td>
-<td align="left">Median : 74.08</td>
-<td align="left">Median :23.99</td>
-<td align="left">Median :15.72</td>
-<td align="left">Median :43.03</td>
-<td align="left">Median :36.15</td>
-<td align="left">Median :100.80</td>
-<td align="left">Median : 81.24</td>
+<td align="left">Median :24.17</td>
+<td align="left">Median : 74.12</td>
+<td align="left">Median :23.93</td>
+<td align="left">Median :15.86</td>
+<td align="left">Median :43.08</td>
+<td align="left">Median :36.35</td>
+<td align="left">Median :100.25</td>
+<td align="left">Median : 82.15</td>
</tr>
<tr class="even">
<td align="left"></td>
-<td align="left">Mean :22.94</td>
-<td align="left">Mean : 72.13</td>
-<td align="left">Mean :24.25</td>
-<td align="left">Mean :15.84</td>
-<td align="left">Mean :40.34</td>
-<td align="left">Mean :36.31</td>
-<td align="left">Mean : 98.89</td>
-<td align="left">Mean : 83.70</td>
+<td align="left">Mean :23.09</td>
+<td align="left">Mean : 71.54</td>
+<td align="left">Mean :24.22</td>
+<td align="left">Mean :15.65</td>
+<td align="left">Mean :40.31</td>
+<td align="left">Mean :36.41</td>
+<td align="left">Mean : 98.59</td>
+<td align="left">Mean : 84.17</td>
</tr>
<tr class="odd">
<td align="left"></td>
-<td align="left">3rd Qu.:26.95</td>
-<td align="left">3rd Qu.: 84.26</td>
-<td align="left">3rd Qu.:25.63</td>
-<td align="left">3rd Qu.:22.56</td>
-<td align="left">3rd Qu.:46.05</td>
-<td align="left">3rd Qu.:40.79</td>
-<td align="left">3rd Qu.:114.68</td>
-<td align="left">3rd Qu.: 92.47</td>
+<td align="left">3rd Qu.:27.40</td>
+<td align="left">3rd Qu.: 83.65</td>
+<td align="left">3rd Qu.:25.57</td>
+<td align="left">3rd Qu.:22.24</td>
+<td align="left">3rd Qu.:46.02</td>
+<td align="left">3rd Qu.:41.01</td>
+<td align="left">3rd Qu.:114.34</td>
+<td align="left">3rd Qu.: 93.32</td>
</tr>
<tr class="even">
<td align="left"></td>
-<td align="left">Max. :39.56</td>
-<td align="left">Max. :123.99</td>
-<td align="left">Max. :32.54</td>
-<td align="left">Max. :56.10</td>
-<td align="left">Max. :59.52</td>
-<td align="left">Max. :59.02</td>
-<td align="left">Max. :168.86</td>
-<td align="left">Max. :170.78</td>
+<td align="left">Max. :41.99</td>
+<td align="left">Max. :125.42</td>
+<td align="left">Max. :34.79</td>
+<td align="left">Max. :52.46</td>
+<td align="left">Max. :58.59</td>
+<td align="left">Max. :59.47</td>
+<td align="left">Max. :178.98</td>
+<td align="left">Max. :143.85</td>
</tr>
</tbody>
</table>
@@ -2890,14 +3260,14 @@ kable(caption = "Test Basin & Bath l/day as modelled using rsnorm()&quo
kable(caption = "Metered vs un-metered estimates (mean)",
t
)</code></pre>
-<table style="width:100%;">
+<table>
<caption>Metered vs un-metered estimates (mean)</caption>
<colgroup>
<col width="12%" />
<col width="9%" />
-<col width="9%" />
+<col width="7%" />
<col width="11%" />
-<col width="9%" />
+<col width="10%" />
<col width="12%" />
<col width="9%" />
<col width="10%" />
@@ -2919,31 +3289,31 @@ kable(caption = "Metered vs un-metered estimates (mean)",
<tbody>
<tr class="odd">
<td align="left">Metered</td>
-<td align="right">17.05667</td>
-<td align="right">55.07805</td>
-<td align="right">23.08817</td>
-<td align="right">10.72518</td>
-<td align="right">31.99094</td>
-<td align="right">30.83176</td>
-<td align="right">78.46629</td>
-<td align="right">77.96451</td>
+<td align="right">17.06715</td>
+<td align="right">54.868</td>
+<td align="right">23.00139</td>
+<td align="right">9.943501</td>
+<td align="right">31.91475</td>
+<td align="right">30.82813</td>
+<td align="right">76.90131</td>
+<td align="right">78.18723</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
-<td align="right">26.86254</td>
-<td align="right">83.49025</td>
-<td align="right">25.02250</td>
-<td align="right">19.25489</td>
-<td align="right">45.90234</td>
-<td align="right">39.96394</td>
-<td align="right">112.51120</td>
-<td align="right">87.52588</td>
+<td align="right">27.09918</td>
+<td align="right">82.660</td>
+<td align="right">25.03293</td>
+<td align="right">19.455593</td>
+<td align="right">45.90567</td>
+<td align="right">40.12686</td>
+<td align="right">113.05406</td>
+<td align="right">88.16084</td>
</tr>
</tbody>
</table>
<pre class="r"><code>wmMetered <- t[metered == "Metered", WC]
wmNonMetered <- t[metered == "Not metered", WC]</code></pre>
-<p>% difference between means for washing machine: 30.26.</p>
+<p>% difference between means for washing machine: 31.98.</p>
</div>
<div id="occupancy-based-adjustment" class="section level3">
<h3><span class="header-section-number">8.4.3</span> Occupancy based adjustment</h3>
@@ -3203,98 +3573,98 @@ kable(caption = "Test monthly fixed and occupancy adjusted l/day", sum
<tr class="odd">
<td align="left">Metered</td>
<td align="right">1</td>
-<td align="right">17.26</td>
-<td align="right">3.11</td>
-<td align="right">55.42</td>
-<td align="right">9.90</td>
+<td align="right">16.93</td>
+<td align="right">2.96</td>
+<td align="right">54.29</td>
+<td align="right">9.48</td>
</tr>
<tr class="even">
<td align="left">Metered</td>
<td align="right">2</td>
-<td align="right">18.34</td>
-<td align="right">3.00</td>
-<td align="right">55.48</td>
-<td align="right">10.31</td>
+<td align="right">18.81</td>
+<td align="right">3.25</td>
+<td align="right">56.08</td>
+<td align="right">10.48</td>
</tr>
<tr class="odd">
<td align="left">Metered</td>
<td align="right">3</td>
-<td align="right">19.21</td>
-<td align="right">3.04</td>
-<td align="right">57.35</td>
-<td align="right">11.08</td>
+<td align="right">19.47</td>
+<td align="right">3.42</td>
+<td align="right">57.96</td>
+<td align="right">10.81</td>
</tr>
<tr class="even">
<td align="left">Metered</td>
<td align="right">4</td>
-<td align="right">20.05</td>
-<td align="right">3.49</td>
-<td align="right">57.37</td>
-<td align="right">8.50</td>
+<td align="right">19.18</td>
+<td align="right">2.22</td>
+<td align="right">57.09</td>
+<td align="right">8.12</td>
</tr>
<tr class="odd">
<td align="left">Metered</td>
<td align="right">5</td>
-<td align="right">19.14</td>
-<td align="right">2.88</td>
-<td align="right">52.19</td>
-<td align="right">9.61</td>
+<td align="right">18.86</td>
+<td align="right">2.49</td>
+<td align="right">53.95</td>
+<td align="right">10.34</td>
</tr>
<tr class="even">
<td align="left">Metered</td>
<td align="right">6</td>
-<td align="right">18.21</td>
-<td align="right">2.62</td>
-<td align="right">64.09</td>
-<td align="right">10.04</td>
+<td align="right">18.19</td>
+<td align="right">1.72</td>
+<td align="right">58.55</td>
+<td align="right">10.43</td>
</tr>
<tr class="odd">
<td align="left">Not metered</td>
<td align="right">1</td>
-<td align="right">26.92</td>
-<td align="right">3.10</td>
-<td align="right">83.74</td>
-<td align="right">10.88</td>
+<td align="right">27.19</td>
+<td align="right">2.96</td>
+<td align="right">83.50</td>
+<td align="right">10.21</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
<td align="right">2</td>
-<td align="right">28.13</td>
-<td align="right">3.03</td>
-<td align="right">83.81</td>
-<td align="right">9.94</td>
+<td align="right">28.38</td>
+<td align="right">2.93</td>
+<td align="right">83.46</td>
+<td align="right">9.73</td>
</tr>
<tr class="odd">
<td align="left">Not metered</td>
<td align="right">3</td>
-<td align="right">29.50</td>
-<td align="right">2.87</td>
-<td align="right">87.07</td>
-<td align="right">10.82</td>
+<td align="right">29.17</td>
+<td align="right">2.73</td>
+<td align="right">85.03</td>
+<td align="right">8.70</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
<td align="right">4</td>
-<td align="right">29.62</td>
-<td align="right">3.16</td>
-<td align="right">85.64</td>
-<td align="right">10.14</td>
+<td align="right">30.52</td>
+<td align="right">3.71</td>
+<td align="right">83.89</td>
+<td align="right">10.78</td>
</tr>
<tr class="odd">
<td align="left">Not metered</td>
<td align="right">5</td>
-<td align="right">29.05</td>
-<td align="right">2.65</td>
-<td align="right">86.24</td>
-<td align="right">9.54</td>
+<td align="right">29.47</td>
+<td align="right">2.71</td>
+<td align="right">84.93</td>
+<td align="right">8.17</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
<td align="right">6</td>
-<td align="right">30.64</td>
-<td align="right">3.04</td>
-<td align="right">87.82</td>
-<td align="right">9.63</td>
+<td align="right">31.13</td>
+<td align="right">3.42</td>
+<td align="right">86.53</td>
+<td align="right">9.42</td>
</tr>
</tbody>
</table>
@@ -4256,14 +4626,22 @@ teethdemand1[,6]<- ifelse(teethdemand1[,6] == "at a sink with a cup of w
teethdemand_hh<-mutate(teethdemand1,teethbrush_hh= (wash_freq*hhsize*teeth_where*30))
summary(teethdemand_hh)</code></pre>
-<pre><code>## obs id hhsize meter wash_freq teeth_where teethbrush_hh
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000 Min. : 0.0
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :2.000 Median : 1.420 Median : 255.6
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :1.996 Mean : 5.699 Mean : 915.7
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700 3rd Qu.: 1002.0
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :4.000 Max. :16.700 Max. :12024.0
-## NA's :22 NA's :42 NA's :53</code></pre>
+<pre><code>## obs id hhsize meter wash_freq teeth_where
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :2.000 Median : 1.420
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :1.996 Mean : 5.699
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :4.000 Max. :16.700
+## NA's :22 NA's :42
+## teethbrush_hh
+## Min. : 0.0
+## 1st Qu.: 170.4
+## Median : 255.6
+## Mean : 915.7
+## 3rd Qu.: 1002.0
+## Max. :12024.0
+## NA's :53</code></pre>
<pre class="r"><code>kable(caption = "Summary of demand for teeth brushing",
teethdemand_hh [1:5,]
)</code></pre>
@@ -4338,22 +4716,22 @@ bathsink_hh<-mutate(bathsink_hh,monthlyBathroomSinkUse= (teethbrush_hh+hands)
bathsink_hh<-bathsink_hh[,-(8:10),drop=FALSE]#droping columns I dont need
bathsink_hh<-mutate(bathsink_hh,dailyBathroomSinkUse= (monthlyBathroomSinkUse/30))
summary(bathsink_hh)</code></pre>
-<pre><code>## id obs.x hhsize.x meter.x wash_freq teeth_where teethbrush_hh
-## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000 Min. : 0.0
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4
-## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median :2.000 Median : 1.420 Median : 255.6
-## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1.996 Mean : 5.699 Mean : 915.7
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700 3rd Qu.: 1002.0
-## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :4.000 Max. :16.700 Max. :12024.0
-## NA's :22 NA's :42 NA's :53
-## hands monthlyBathroomSinkUse dailyBathroomSinkUse
-## Min. : 312.0 Min. : 312.0 Min. : 10.40
-## 1st Qu.: 624.0 1st Qu.: 794.4 1st Qu.: 26.48
-## Median : 624.0 Median : 1191.6 Median : 39.72
-## Mean : 828.4 Mean : 1748.0 Mean : 58.27
-## 3rd Qu.:1248.0 3rd Qu.: 1986.0 3rd Qu.: 66.20
-## Max. :3120.0 Max. :13896.0 Max. :463.20
-## NA's :53 NA's :53</code></pre>
+<pre><code>## id obs.x hhsize.x meter.x wash_freq teeth_where
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median :2.000 Median : 1.420
+## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1.996 Mean : 5.699
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700
+## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :4.000 Max. :16.700
+## NA's :22 NA's :42
+## teethbrush_hh hands monthlyBathroomSinkUse dailyBathroomSinkUse
+## Min. : 0.0 Min. : 312.0 Min. : 312.0 Min. : 10.40
+## 1st Qu.: 170.4 1st Qu.: 624.0 1st Qu.: 794.4 1st Qu.: 26.48
+## Median : 255.6 Median : 624.0 Median : 1191.6 Median : 39.72
+## Mean : 915.7 Mean : 828.4 Mean : 1748.0 Mean : 58.27
+## 3rd Qu.: 1002.0 3rd Qu.:1248.0 3rd Qu.: 1986.0 3rd Qu.: 66.20
+## Max. :12024.0 Max. :3120.0 Max. :13896.0 Max. :463.20
+## NA's :53 NA's :53 NA's :53</code></pre>
<pre class="r"><code>kable(caption = "Summary of demand for washing of hands",
bathsink_hh [1:5,]
)</code></pre>
@@ -4488,22 +4866,22 @@ bathdemand_hh$dailyBathUse<-bathdemand_hh$monthlyBathUse/30 #'At home wit
# households that had no baths in their bathrooms, were assumed as not taking any baths
summary(bathdemand_hh) </code></pre>
-<pre><code>## hhsize obs id meter bath_freq baths housefreq
-## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.000 Min. :0.0000 Min. : 0.000
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.000 1st Qu.:1.0000 1st Qu.: 0.000
-## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.000 Median :1.0000 Median : 0.000
-## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :1.881 Mean :0.9717 Mean : 5.099
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:3.000 3rd Qu.:1.0000 3rd Qu.: 7.000
-## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :9.000 Max. :4.0000 Max. :63.000
-## NA's :51 NA's :51
-## baths_freq_EST showers_freq_EST monthlyBathUse dailyBathUse
-## Min. :1.700 Min. : 5.20 Min. : 0.0 Min. : 0.00
-## 1st Qu.:2.250 1st Qu.: 9.40 1st Qu.: 598.4 1st Qu.:19.95
-## Median :2.250 Median : 9.40 Median : 792.0 Median :26.40
-## Mean :3.264 Mean :10.56 Mean :1065.9 Mean :35.53
-## 3rd Qu.:4.850 3rd Qu.:14.65 3rd Qu.:1707.2 3rd Qu.:56.91
-## Max. :6.600 Max. :16.05 Max. :2323.2 Max. :77.44
-## </code></pre>
+<pre><code>## hhsize obs id meter bath_freq baths
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.000 Min. :0.0000
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.000 1st Qu.:1.0000
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.000 Median :1.0000
+## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :1.881 Mean :0.9717
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:3.000 3rd Qu.:1.0000
+## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :9.000 Max. :4.0000
+## NA's :51
+## housefreq baths_freq_EST showers_freq_EST monthlyBathUse dailyBathUse
+## Min. : 0.000 Min. :1.700 Min. : 5.20 Min. : 0.0 Min. : 0.00
+## 1st Qu.: 0.000 1st Qu.:2.250 1st Qu.: 9.40 1st Qu.: 598.4 1st Qu.:19.95
+## Median : 0.000 Median :2.250 Median : 9.40 Median : 792.0 Median :26.40
+## Mean : 5.099 Mean :3.264 Mean :10.56 Mean :1065.9 Mean :35.53
+## 3rd Qu.: 7.000 3rd Qu.:4.850 3rd Qu.:14.65 3rd Qu.:1707.2 3rd Qu.:56.91
+## Max. :63.000 Max. :6.600 Max. :16.05 Max. :2323.2 Max. :77.44
+## NA's :51</code></pre>
<pre class="r"><code>kable(caption = "Summary of bath demand",
bathdemand_hh [1:5,]
)</code></pre>
@@ -4674,20 +5052,20 @@ monthlyDishwasherUse$monthlyDishwasherUse <- ifelse(monthlyDishwasherUse$dish
monthlyDishwasherUse$dailyDishwasherUse <- monthlyDishwasherUse$monthlyDishwasherUse/30
summary(monthlyDishwasherUse)#'At home with water2' reports 10 l/hh/day for their sample for taps. Our mean is 2.4 l/hh/d. Reasonable but much lower than theirs. This is probably because zero values are included in the mean calculation).</code></pre>
-<pre><code>## hhsize obs id meter dishwashers dish_freq weeklyDish_freq
-## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.0000 Length:1800 Min. :0.900
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.0000 Class :character 1st Qu.:2.300
-## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.0000 Mode :character Median :2.300
-## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :0.4233 Mean :2.737
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:1.0000 3rd Qu.:4.300
-## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :2.0000 Max. :4.800
-## monthlyDishwasherUse dailyDishwasherUse
-## Min. : 0.00 Min. :0.000
-## 1st Qu.: 0.00 1st Qu.:0.000
-## Median : 0.00 Median :0.000
-## Mean : 71.18 Mean :2.373
-## 3rd Qu.:128.80 3rd Qu.:4.293
-## Max. :268.80 Max. :8.960</code></pre>
+<pre><code>## hhsize obs id meter dishwashers dish_freq
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.0000 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.0000 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.0000 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :0.4233
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:1.0000
+## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :2.0000
+## weeklyDish_freq monthlyDishwasherUse dailyDishwasherUse
+## Min. :0.900 Min. : 0.00 Min. :0.000
+## 1st Qu.:2.300 1st Qu.: 0.00 1st Qu.:0.000
+## Median :2.300 Median : 0.00 Median :0.000
+## Mean :2.737 Mean : 71.18 Mean :2.373
+## 3rd Qu.:4.300 3rd Qu.:128.80 3rd Qu.:4.293
+## Max. :4.800 Max. :268.80 Max. :8.960</code></pre>
<pre class="r"><code>kable(caption = "Summary of demand for dishwashers",
monthlyDishwasherUse [1:5,]
)</code></pre>
@@ -4795,13 +5173,20 @@ kitchen_sink<-rename(kitchen_sink, obs =iobs, id=bmg_id, hhsize=q2, meter=q4)
kitchen_sink_hh<-mutate(kitchen_sink,monthlyKitchenSinkUse = hhsize*7.57*30)
kitchen_sink_hh<-mutate(kitchen_sink_hh,dailyKitchenSinkUse = monthlyKitchenSinkUse/30)
summary(kitchen_sink_hh)</code></pre>
-<pre><code>## obs id hhsize meter monthlyKitchenSinkUse dailyKitchenSinkUse
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 227.1 Min. : 7.57
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 454.2 1st Qu.:15.14
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 454.2 Median :15.14
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 603.0 Mean :20.10
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 908.4 3rd Qu.:30.28
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2271.0 Max. :75.70</code></pre>
+<pre><code>## obs id hhsize meter monthlyKitchenSinkUse
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 227.1
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 454.2
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 454.2
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 603.0
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 908.4
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2271.0
+## dailyKitchenSinkUse
+## Min. : 7.57
+## 1st Qu.:15.14
+## Median :15.14
+## Mean :20.10
+## 3rd Qu.:30.28
+## Max. :75.70</code></pre>
<pre class="r"><code>kable(caption = "Summary of demand for kitchen sink uses",
kitchen_sink_hh [1:5,]
)</code></pre>
@@ -5106,22 +5491,22 @@ toiletdemand_hh<-mutate (toiletdemand2, monthlyWCUse=flushvolume*hhsize*30*5)
toiletdemand_hh<-mutate (toiletdemand_hh, dailyWCUse=monthlyWCUse/30) #'At home with water2' reports 74 l/hh/day for their sample for lavatories. Our mean is 91.3 l/hh/d. Our results make sense.
summary (toiletdemand_hh)</code></pre>
-<pre><code>## obs id hhsize meter singleflush_wc dualflush_wc effective_flush
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 0.000 Min. :0.0000 Length:1800
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 1.000 1st Qu.:0.0000 Class :character
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 1.000 Median :0.0000 Mode :character
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 1.169 Mean :0.4233
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 2.000 3rd Qu.:1.0000
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :97.000 Max. :5.0000
-##
-## flushvolume monthlyWCUse dailyWCUse
-## Min. :5.000 Min. : 750 Min. : 25.00
-## 1st Qu.:6.250 1st Qu.:1500 1st Qu.: 50.00
-## Median :7.500 Median :2250 Median : 75.00
-## Mean :6.918 Mean :2739 Mean : 91.31
-## 3rd Qu.:7.500 3rd Qu.:3375 3rd Qu.:112.50
-## Max. :7.500 Max. :7875 Max. :262.50
-## NA's :59 NA's :59 NA's :59</code></pre>
+<pre><code>## obs id hhsize meter singleflush_wc dualflush_wc
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 0.000 Min. :0.0000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 1.000 1st Qu.:0.0000
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 1.000 Median :0.0000
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 1.169 Mean :0.4233
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 2.000 3rd Qu.:1.0000
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :97.000 Max. :5.0000
+##
+## effective_flush flushvolume monthlyWCUse dailyWCUse
+## Length:1800 Min. :5.000 Min. : 750 Min. : 25.00
+## Class :character 1st Qu.:6.250 1st Qu.:1500 1st Qu.: 50.00
+## Mode :character Median :7.500 Median :2250 Median : 75.00
+## Mean :6.918 Mean :2739 Mean : 91.31
+## 3rd Qu.:7.500 3rd Qu.:3375 3rd Qu.:112.50
+## Max. :7.500 Max. :7875 Max. :262.50
+## NA's :59 NA's :59 NA's :59</code></pre>
<pre class="r"><code>sapply(split(toiletdemand_hh$monthlyWCUse, toiletdemand_hh$hhsize), mean, na.rm=TRUE) </code></pre>
<pre><code>## 1 2 3 4 5 6 7 10
## 1063.670 2067.707 3075.615 4104.235 5189.438 6286.765 7109.375 7500.000</code></pre>
@@ -5217,22 +5602,22 @@ summary(washingmachinedemand1[,6]) #47 NA's</code></pre>
washingmachine_hh<-mutate(washingmachine_hh,dailyWashingMachineUse=monthlyWashingMachineUse/30) #'At home with water2' reports 33 l/hh/day for their sample for washing machines. Our mean is 25. Our results make sense.
summary(washingmachine_hh)</code></pre>
-<pre><code>## obs id hhsize meter washingmachine weeklyloads combinedwash
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. : 0.000 Min. :1
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:1.0000 1st Qu.: 2.500 1st Qu.:1
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :1.0000 Median : 2.500 Median :1
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.9472 Mean : 3.542 Mean :1
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.: 4.500 3rd Qu.:1
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2.0000 Max. :12.000 Max. :1
-## NA's :47 NA's :98
-## monthlyWashingMachineUse dailyWashingMachineUse
-## Min. : 0.0 Min. : 0.00
-## 1st Qu.: 500.0 1st Qu.:16.67
-## Median : 500.0 Median :16.67
-## Mean : 708.3 Mean :23.61
-## 3rd Qu.: 900.0 3rd Qu.:30.00
-## Max. :2400.0 Max. :80.00
-## NA's :47 NA's :47</code></pre>
+<pre><code>## obs id hhsize meter washingmachine weeklyloads
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. : 0.000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:1.0000 1st Qu.: 2.500
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :1.0000 Median : 2.500
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.9472 Mean : 3.542
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.: 4.500
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2.0000 Max. :12.000
+## NA's :47
+## combinedwash monthlyWashingMachineUse dailyWashingMachineUse
+## Min. :1 Min. : 0.0 Min. : 0.00
+## 1st Qu.:1 1st Qu.: 500.0 1st Qu.:16.67
+## Median :1 Median : 500.0 Median :16.67
+## Mean :1 Mean : 708.3 Mean :23.61
+## 3rd Qu.:1 3rd Qu.: 900.0 3rd Qu.:30.00
+## Max. :1 Max. :2400.0 Max. :80.00
+## NA's :98 NA's :47 NA's :47</code></pre>
<pre class="r"><code>washingmachine_hh<-washingmachine_hh[,-(5:7),drop=FALSE]
kable(caption = "Summary of washing machine demand data table",
@@ -5333,22 +5718,30 @@ str(totalIntDemand_hh)</code></pre>
monthlyWCUse + monthlyWashingMachineUse + monthlyBathroomSinkUse) )
summary(totalIntDemand_hh)</code></pre>
-<pre><code>## id obs.y hhsize.x.x meter.x.x monthlyBathUse monthlyShowerUse monthlyDishwasherUse
-## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. : 0.0 Min. : 0 Min. : 0.00
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.: 598.4 1st Qu.: 1464 1st Qu.: 0.00
-## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median : 792.0 Median : 2808 Median : 0.00
-## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1065.9 Mean : 3210 Mean : 71.18
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:1707.2 3rd Qu.: 4638 3rd Qu.:128.80
-## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :2323.2 Max. :15415 Max. :268.80
-## NA's :53
-## monthlyKitchenSinkUse monthlyWCUse monthlyWashingMachineUse monthlyBathroomSinkUse totalMonthlyInHouseDemand
-## Min. : 227.1 Min. : 750 Min. : 0.0 Min. : 312.0 Min. : 1907
-## 1st Qu.: 454.2 1st Qu.:1500 1st Qu.: 500.0 1st Qu.: 794.4 1st Qu.: 6043
-## Median : 454.2 Median :2250 Median : 500.0 Median : 1191.6 Median : 9167
-## Mean : 603.0 Mean :2739 Mean : 708.3 Mean : 1748.0 Mean :10140
-## 3rd Qu.: 908.4 3rd Qu.:3375 3rd Qu.: 900.0 3rd Qu.: 1986.0 3rd Qu.:13821
-## Max. :2271.0 Max. :7875 Max. :2400.0 Max. :13896.0 Max. :34171
-## NA's :59 NA's :47 NA's :53 NA's :186</code></pre>
+<pre><code>## id obs.y hhsize.x.x meter.x.x monthlyBathUse monthlyShowerUse
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. : 0.0 Min. : 0
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.: 598.4 1st Qu.: 1464
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median : 792.0 Median : 2808
+## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1065.9 Mean : 3210
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:1707.2 3rd Qu.: 4638
+## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :2323.2 Max. :15415
+## NA's :53
+## monthlyDishwasherUse monthlyKitchenSinkUse monthlyWCUse monthlyWashingMachineUse monthlyBathroomSinkUse
+## Min. : 0.00 Min. : 227.1 Min. : 750 Min. : 0.0 Min. : 312.0
+## 1st Qu.: 0.00 1st Qu.: 454.2 1st Qu.:1500 1st Qu.: 500.0 1st Qu.: 794.4
+## Median : 0.00 Median : 454.2 Median :2250 Median : 500.0 Median : 1191.6
+## Mean : 71.18 Mean : 603.0 Mean :2739 Mean : 708.3 Mean : 1748.0
+## 3rd Qu.:128.80 3rd Qu.: 908.4 3rd Qu.:3375 3rd Qu.: 900.0 3rd Qu.: 1986.0
+## Max. :268.80 Max. :2271.0 Max. :7875 Max. :2400.0 Max. :13896.0
+## NA's :59 NA's :47 NA's :53
+## totalMonthlyInHouseDemand
+## Min. : 1907
+## 1st Qu.: 6043
+## Median : 9167
+## Mean :10140
+## 3rd Qu.:13821
+## Max. :34171
+## NA's :186</code></pre>
</div>
</div>
<div id="estimate-external-consumption" class="section level2">
@@ -5459,22 +5852,30 @@ size7mean_wash<-filter(CarDemand_hh, hhsize == 7 &CarSum>=1)
mean7<-mean (size7mean_wash$Mean_wash,na.rm=TRUE)
summary(CarDemand_hh)</code></pre>
-<pre><code>## obs id hhsize meter onecar twocars threecars
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. :0.0000 Min. :0.0000
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :0.0000 Median :0.0000 Median :0.0000
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.4567 Mean :0.4956 Mean :0.1717
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :1.0000 Max. :2.0000 Max. :3.0000
-##
-## carwash_freq bucket_wash hose_wash pres_wash CarSum Mean_wash
-## Min. :0.0000 Min. : 0.000 Min. : 0.00 Min. : 0.000 Min. :0.000 Min. : 10.00
-## 1st Qu.:0.0000 1st Qu.: 0.000 1st Qu.: 0.00 1st Qu.: 0.000 1st Qu.:1.000 1st Qu.: 10.00
-## Median :0.2500 Median : 0.000 Median : 0.00 Median : 0.000 Median :1.000 Median : 10.00
-## Mean :0.4543 Mean : 7.567 Mean : 17.22 Mean : 1.467 Mean :1.124 Mean : 31.26
-## 3rd Qu.:0.3300 3rd Qu.:30.000 3rd Qu.: 0.00 3rd Qu.: 0.000 3rd Qu.:2.000 3rd Qu.: 54.00
-## Max. :4.0000 Max. :30.000 Max. :250.00 Max. :132.000 Max. :3.000 Max. :137.33
-## NA's :41 NA's :1296</code></pre>
+<pre><code>## obs id hhsize meter onecar twocars
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. :0.0000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:0.0000 1st Qu.:0.0000
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :0.0000 Median :0.0000
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.4567 Mean :0.4956
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.:0.0000
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :1.0000 Max. :2.0000
+##
+## threecars carwash_freq bucket_wash hose_wash pres_wash CarSum
+## Min. :0.0000 Min. :0.0000 Min. : 0.000 Min. : 0.00 Min. : 0.000 Min. :0.000
+## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 0.000 1st Qu.: 0.00 1st Qu.: 0.000 1st Qu.:1.000
+## Median :0.0000 Median :0.2500 Median : 0.000 Median : 0.00 Median : 0.000 Median :1.000
+## Mean :0.1717 Mean :0.4543 Mean : 7.567 Mean : 17.22 Mean : 1.467 Mean :1.124
+## 3rd Qu.:0.0000 3rd Qu.:0.3300 3rd Qu.:30.000 3rd Qu.: 0.00 3rd Qu.: 0.000 3rd Qu.:2.000
+## Max. :3.0000 Max. :4.0000 Max. :30.000 Max. :250.00 Max. :132.000 Max. :3.000
+## NA's :41
+## Mean_wash
+## Min. : 10.00
+## 1st Qu.: 10.00
+## Median : 10.00
+## Mean : 31.26
+## 3rd Qu.: 54.00
+## Max. :137.33
+## NA's :1296</code></pre>
<pre class="r"><code>CarDemand_hh$Mean_wash <- ifelse(is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 1, mean1, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 2, mean2, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 3, mean3, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 4, mean4,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 5, mean5,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 6, mean6,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 7, mean7,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum<1 ,0, CarDemand_hh$Mean_wash ))))))))
# Now, only households with no cars have a zero value for mean_wash (429).
@@ -5806,20 +6207,20 @@ kable(caption = "Summary of bath and shower demand",
kitchen_dish_hh<-merge(x = monthlyDishwasherUse, y = kitchen_sink_hh, by = "id", all = TRUE)
kitchen_dish_hh<-kitchen_dish_hh[,-(2:7),drop=FALSE]#dropping columns i dont need
summary(kitchen_dish_hh)</code></pre>
-<pre><code>## id monthlyDishwasherUse dailyDishwasherUse obs.y hhsize.y meter.y monthlyKitchenSinkUse
-## Min. :836900048 Min. : 0.00 Min. :0.000 Min. : 2.0 Min. : 1.000 Length:1800 Min. : 227.1
-## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.: 454.2
-## Median :836920637 Median : 0.00 Median :0.000 Median : 905.5 Median : 2.000 Mode :character Median : 454.2
-## Mean :836919052 Mean : 71.18 Mean :2.373 Mean : 906.0 Mean : 2.655 Mean : 603.0
-## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.: 908.4
-## Max. :836965495 Max. :268.80 Max. :8.960 Max. :1810.0 Max. :10.000 Max. :2271.0
-## dailyKitchenSinkUse
-## Min. : 7.57
-## 1st Qu.:15.14
-## Median :15.14
-## Mean :20.10
-## 3rd Qu.:30.28
-## Max. :75.70</code></pre>
+<pre><code>## id monthlyDishwasherUse dailyDishwasherUse obs.y hhsize.y meter.y
+## Min. :836900048 Min. : 0.00 Min. :0.000 Min. : 2.0 Min. : 1.000 Length:1800
+## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000 1st Qu.: 454.8 1st Qu.: 2.000 Class :character
+## Median :836920637 Median : 0.00 Median :0.000 Median : 905.5 Median : 2.000 Mode :character
+## Mean :836919052 Mean : 71.18 Mean :2.373 Mean : 906.0 Mean : 2.655
+## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293 3rd Qu.:1356.2 3rd Qu.: 4.000
+## Max. :836965495 Max. :268.80 Max. :8.960 Max. :1810.0 Max. :10.000
+## monthlyKitchenSinkUse dailyKitchenSinkUse
+## Min. : 227.1 Min. : 7.57
+## 1st Qu.: 454.2 1st Qu.:15.14
+## Median : 454.2 Median :15.14
+## Mean : 603.0 Mean :20.10
+## 3rd Qu.: 908.4 3rd Qu.:30.28
+## Max. :2271.0 Max. :75.70</code></pre>
<pre class="r"><code>kable(caption = "Summary of demand for dishwashers and kitchen uses",
kitchen_dish_hh [1:5,]
)</code></pre>
@@ -6042,16 +6443,17 @@ kable(caption = "Summary of daily total household demand values",
<pre class="r"><code>ggplot(data = totalDemand_hh) +
geom_bar(mapping = aes(x = factor(meter)))+xlab('metered or not')</code></pre>
<p><img src="impetusModel_files/figure-html/Number%20metered-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize)) +
+<pre class="r"><code>ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize), colour = meter) +
geom_boxplot() +
labs(title = "total use (l/month)")+labs(title = " total demand (l/household/month)")+ xlab('household size')+ylab('total household demand (l/hh/month)')</code></pre>
-<p><img src="impetusModel_files/figure-html/Total%20monthly%20demand%20by%20household%20size-1.png" /><!-- --></p>
+<p><img src="impetusModel_files/figure-html/Total%20monthly%20demand%20by%20household%20size%20and%20metering-1.png" /><!-- --></p>
<pre class="r"><code>ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(meter)) +
geom_boxplot() +labs(title = "Total demand (l/household/month)")+ xlab('metered or not')+ylab('Total household demand (l/hh/month)')</code></pre>
<p><img src="impetusModel_files/figure-html/Total%20monthly%20demand%20by%20metering-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(data=totalDemand_hh)+ aes(y = totalDailyHouseDemandFinal, x = factor(hhsize)) +
- geom_boxplot() +labs(title = " Total demand (l/household/day)")+ xlab('metered or not')+ylab('Total household demand (l/hh/day)')</code></pre>
-<p><img src="impetusModel_files/figure-html/Total%20monthly%20external%20demand%20by%20household%20size-1.png" /><!-- --></p>
+<pre class="r"><code>totalDemand_hh$totalMonthlyExtHouseDemand <- totalDemand_hh$monthlyCarWashUse + totalDemand_hh$monthlyGardenUse
+ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyExtHouseDemand, x = meter) +
+ geom_boxplot() +labs(title = " Total demand (l/household/month)")+ xlab('Metered')+ylab('Total external monthly household demand (l/hh/month)')</code></pre>
+<p><img src="impetusModel_files/figure-html/Total%20monthly%20external%20demand%20by%20metering-1.png" /><!-- --></p>
<pre class="r"><code>ggplot(totalDemand_hh[totalDemand_hh$meter == "yes"|totalDemand_hh$meter == "no",], aes(factor(hhsize), totalDailyHouseDemandFinal)) + geom_boxplot(aes(fill = meter))+labs(title = " total demand (l/household/day)")+ xlab('household size')+ylab('total demand (l/hh/day)')</code></pre>
<p><img src="impetusModel_files/figure-html/Total%20daily%20demand%20by%20household%20size%20&%20metering-1.png" /><!-- --></p>
<pre class="r"><code>#delete columns I dont need
@@ -6123,7 +6525,7 @@ oFile <- paste0(m2oPath,"output-SPRG-1800hh-consumption_",format(Sy
data.table::fwrite(hhDataFinalDaily_v2_0DT, file = oFile)</code></pre>
<p>Data written to:</p>
<blockquote>
-<p>~/University of Southampton/IMPETUS - Documents/data/model_outputs/model_v2/output-SPRG-1800hh-consumption_2021-03-24_v2_0.csv and (possibly) gzipped</p>
+<p>~/University of Southampton/IMPETUS - Documents/data/model_outputs/model_v2/output-SPRG-1800hh-consumption_2021-03-29_v2_0.csv and (possibly) gzipped</p>
</blockquote>
</div>
</div>
@@ -6155,17 +6557,17 @@ hhDataFinalDaily_v1_3fDT <- hhDataFinalDaily_v1_3DT[, .(hhid, occupancy, mete
hhDataFinalDaily_v1_3fDT <- hhDataFinalDaily_v1_3fDT[, model := "v1_3"]
st <- str(hhDataFinalDaily_v1_3fDT)</code></pre>
<pre><code>## Classes 'data.table' and 'data.frame': 1800 obs. of 12 variables:
-## $ hhid : int 8 28 30 40 41 59 64 66 67 76 ...
+## $ hhid : int 8 16 21 28 30 52 59 64 73 84 ...
## $ occupancy : int 1 1 1 1 1 1 1 1 1 1 ...
## $ metered : chr "Metered" "Metered" "Metered" "Metered" ...
-## $ Basin.baseline : num 20.4 18 18.6 13.5 19.3 ...
-## $ Bath.baseline : num 44.2 56.2 66.9 63.2 65.3 ...
-## $ Dishwasher.baseline : num 21.3 21.3 25.7 20.6 21.8 ...
-## $ KitchenSink.baseline : num 28.9 29.9 29.6 32 28.7 ...
-## $ Shower.baseline : num 27.1 27.9 29.6 31.3 30.9 ...
-## $ WC.baseline : num 77.4 69.5 63.6 83.9 78.3 ...
-## $ WashingMachine.baseline: num 92.1 92.3 73 77.5 98 ...
-## $ External.baseline : num 0 0 0 0 0 ...
+## $ Basin.baseline : num 19.5 15 18.1 13.3 17.5 ...
+## $ Bath.baseline : num 59.4 55.5 51.9 41.7 56.8 ...
+## $ Dishwasher.baseline : num 23.1 21.3 22.3 24.8 23.8 ...
+## $ KitchenSink.baseline : num 30 33.8 31.3 30.4 31.5 ...
+## $ Shower.baseline : num 27 29.1 30.5 26.7 26.8 ...
+## $ WC.baseline : num 88 85.6 94 65.7 68.5 ...
+## $ WashingMachine.baseline: num 77.7 67.3 69.8 73.3 62.2 ...
+## $ External.baseline : num 0 21.8 30.5 11.5 19.7 ...
## $ model : chr "v1_3" "v1_3" "v1_3" "v1_3" ...
## - attr(*, ".internal.selfref")=<externalptr>
## - attr(*, "sorted")= chr [1:2] "metered" "occupancy"</code></pre>
@@ -6520,15 +6922,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="left">Min. : 1.000</td>
<td align="left">Length:433800</td>
<td align="left">Min. :1.000</td>
-<td align="left">Min. :254.8</td>
-<td align="left">Min. :12.55</td>
-<td align="left">Min. : 34.87</td>
-<td align="left">Min. :13.79</td>
+<td align="left">Min. :272.7</td>
+<td align="left">Min. :11.68</td>
+<td align="left">Min. : 37.54</td>
+<td align="left">Min. :13.74</td>
<td align="left">Min. :-2.511</td>
-<td align="left">Min. :27.42</td>
-<td align="left">Min. :21.20</td>
-<td align="left">Min. : 48.88</td>
-<td align="left">Min. : 57.80</td>
+<td align="left">Min. :27.57</td>
+<td align="left">Min. :20.83</td>
+<td align="left">Min. : 48.10</td>
+<td align="left">Min. : 56.70</td>
</tr>
<tr class="even">
<td align="left"></td>
@@ -6536,15 +6938,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="left">1st Qu.: 4.000</td>
<td align="left">Class :character</td>
<td align="left">1st Qu.:1.000</td>
-<td align="left">1st Qu.:346.5</td>
-<td align="left">1st Qu.:19.00</td>
-<td align="left">1st Qu.: 57.95</td>
-<td align="left">1st Qu.:20.96</td>
-<td align="left">1st Qu.:11.227</td>
-<td align="left">1st Qu.:35.05</td>
-<td align="left">1st Qu.:32.88</td>
-<td align="left">1st Qu.: 86.84</td>
-<td align="left">1st Qu.: 74.58</td>
+<td align="left">1st Qu.:345.8</td>
+<td align="left">1st Qu.:18.96</td>
+<td align="left">1st Qu.: 57.52</td>
+<td align="left">1st Qu.:20.94</td>
+<td align="left">1st Qu.:11.104</td>
+<td align="left">1st Qu.:34.77</td>
+<td align="left">1st Qu.:32.91</td>
+<td align="left">1st Qu.: 86.44</td>
+<td align="left">1st Qu.: 74.97</td>
</tr>
<tr class="odd">
<td align="left"></td>
@@ -6552,15 +6954,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="left">Median : 7.000</td>
<td align="left">Mode :character</td>
<td align="left">Median :2.000</td>
-<td align="left">Median :425.8</td>
-<td align="left">Median :25.59</td>
-<td align="left">Median : 73.64</td>
-<td align="left">Median :22.45</td>
-<td align="left">Median :16.254</td>
+<td align="left">Median :427.9</td>
+<td align="left">Median :25.71</td>
+<td align="left">Median : 73.73</td>
+<td align="left">Median :22.36</td>
+<td align="left">Median :16.435</td>
<td align="left">Median :44.61</td>
-<td align="left">Median :36.96</td>
-<td align="left">Median :110.90</td>
-<td align="left">Median : 82.89</td>
+<td align="left">Median :37.13</td>
+<td align="left">Median :110.16</td>
+<td align="left">Median : 83.60</td>
</tr>
<tr class="even">
<td align="left"></td>
@@ -6568,15 +6970,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="left">Mean : 6.523</td>
<td align="left">NA</td>
<td align="left">Mean :2.407</td>
-<td align="left">Mean :408.8</td>
-<td align="left">Mean :24.46</td>
-<td align="left">Mean : 72.11</td>
-<td align="left">Mean :22.65</td>
-<td align="left">Mean :16.273</td>
-<td align="left">Mean :42.18</td>
-<td align="left">Mean :37.28</td>
-<td align="left">Mean :108.33</td>
-<td align="left">Mean : 85.52</td>
+<td align="left">Mean :408.4</td>
+<td align="left">Mean :24.62</td>
+<td align="left">Mean : 71.55</td>
+<td align="left">Mean :22.63</td>
+<td align="left">Mean :16.077</td>
+<td align="left">Mean :42.15</td>
+<td align="left">Mean :37.39</td>
+<td align="left">Mean :108.00</td>
+<td align="left">Mean : 85.99</td>
</tr>
<tr class="odd">
<td align="left"></td>
@@ -6584,15 +6986,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="left">3rd Qu.:10.000</td>
<td align="left">NA</td>
<td align="left">3rd Qu.:3.000</td>
-<td align="left">3rd Qu.:460.3</td>
-<td align="left">3rd Qu.:28.60</td>
-<td align="left">3rd Qu.: 83.97</td>
-<td align="left">3rd Qu.:24.19</td>
-<td align="left">3rd Qu.:23.079</td>
-<td align="left">3rd Qu.:47.60</td>
-<td align="left">3rd Qu.:41.48</td>
-<td align="left">3rd Qu.:127.33</td>
-<td align="left">3rd Qu.: 94.03</td>
+<td align="left">3rd Qu.:459.8</td>
+<td align="left">3rd Qu.:29.06</td>
+<td align="left">3rd Qu.: 83.16</td>
+<td align="left">3rd Qu.:24.16</td>
+<td align="left">3rd Qu.:22.796</td>
+<td align="left">3rd Qu.:47.69</td>
+<td align="left">3rd Qu.:41.75</td>
+<td align="left">3rd Qu.:127.37</td>
+<td align="left">3rd Qu.: 94.77</td>
</tr>
<tr class="even">
<td align="left"></td>
@@ -6600,15 +7002,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="left">Max. :12.000</td>
<td align="left">NA</td>
<td align="left">Max. :6.000</td>
-<td align="left">Max. :560.8</td>
-<td align="left">Max. :40.25</td>
-<td align="left">Max. :124.08</td>
-<td align="left">Max. :32.27</td>
-<td align="left">Max. :58.004</td>
-<td align="left">Max. :61.69</td>
-<td align="left">Max. :60.49</td>
-<td align="left">Max. :188.81</td>
-<td align="left">Max. :170.75</td>
+<td align="left">Max. :561.1</td>
+<td align="left">Max. :44.91</td>
+<td align="left">Max. :125.70</td>
+<td align="left">Max. :33.99</td>
+<td align="left">Max. :54.834</td>
+<td align="left">Max. :60.77</td>
+<td align="left">Max. :60.52</td>
+<td align="left">Max. :189.84</td>
+<td align="left">Max. :145.57</td>
</tr>
</tbody>
</table>
@@ -6935,14 +7337,14 @@ kable(caption = "Summary of results", t)</code></pre>
<tr class="odd">
<td align="left">v1_3</td>
<td align="left">Not metered</td>
-<td align="right">454.1061</td>
-<td align="right">249.1422</td>
+<td align="right">454.9823</td>
+<td align="right">250.5077</td>
</tr>
<tr class="even">
<td align="left">v1_3</td>
<td align="left">Metered</td>
-<td align="right">340.8619</td>
-<td align="right">191.8263</td>
+<td align="right">338.5436</td>
+<td align="right">189.4032</td>
</tr>
<tr class="odd">
<td align="left">v2_0</td>
@@ -7350,12 +7752,13 @@ baselineWE_DT <- baselineWE_DT[, loFlowShower := ifelse(is.na(loFlowShower),
#summary(yearMonthSpineDT)
names(baselineWE_DT)</code></pre>
-<pre><code>## [1] "currYear" "currMon" "hhid" "model"
-## [5] "obsDate" "occupancy" "metered" "Basin.baseline.madj"
-## [9] "Bath.baseline.madj" "Dishwasher.baseline.madj" "External.baseline.madj" "KitchenSink.baseline.madj"
-## [13] "Shower.baseline.madj" "WC.baseline.madj" "WashingMachine.baseline.madj" "sumDaily.baseline.madj"
-## [17] "occRed" "loWC" "loSh" "dualFlushWC"
-## [21] "loFlowShower"</code></pre>
+<pre><code>## [1] "currYear" "currMon" "hhid"
+## [4] "model" "obsDate" "occupancy"
+## [7] "metered" "Basin.baseline.madj" "Bath.baseline.madj"
+## [10] "Dishwasher.baseline.madj" "External.baseline.madj" "KitchenSink.baseline.madj"
+## [13] "Shower.baseline.madj" "WC.baseline.madj" "WashingMachine.baseline.madj"
+## [16] "sumDaily.baseline.madj" "occRed" "loWC"
+## [19] "loSh" "dualFlushWC" "loFlowShower"</code></pre>
<pre class="r"><code># check imputed update rates
ggplot(yearMonthSpineDT, aes(x=obsDate)) +
geom_line(aes(y = 100*dfWCRateCum, colour = "Dual flush WC")) +
@@ -7407,8 +7810,8 @@ baselineWE_DT[, .(mean_sumDaily = mean(sumDaily.baseline.madj, na.rm = TRUE),
), keyby = .(model, metered)
]</code></pre>
<pre><code>## model metered mean_sumDaily mean_WC mean_shower
-## 1: v1_3 Metered 340.8619 84.54052 32.31327
-## 2: v1_3 Not metered 454.1061 124.18930 40.58952
+## 1: v1_3 Metered 338.5436 83.03458 32.35519
+## 2: v1_3 Not metered 454.9823 124.63944 40.75476
## 3: v2_0 Metered 336.4506 83.91561 102.24988
## 4: v2_0 Not metered 362.7737 92.13191 109.05040
## 5: v2_1 Metered 336.4506 83.91561 102.24988
@@ -7438,12 +7841,12 @@ baselineWE_DT[, .(mean_sumDaily = mean(sumDaily.baseline.madj.we, na.rm = TRUE),
), keyby = .(model, metered)
]</code></pre>
<pre><code>## model metered mean_sumDaily mean_WC mean_shower
-## 1: v1_3 Metered 330.3141 75.26894 31.03697
-## 2: v1_3 Not metered 438.9518 110.62445 39.00004
-## 3: v2_0 Metered 323.3260 74.72015 98.26638
-## 4: v2_0 Not metered 348.3528 82.03014 104.77559
-## 5: v2_1 Metered 312.4606 63.74666 98.26616
-## 6: v2_1 Not metered 336.2035 69.96383 104.71251</code></pre>
+## 1: v1_3 Metered 328.1783 73.94774 31.07670
+## 2: v1_3 Not metered 439.7477 111.00402 39.15561
+## 3: v2_0 Metered 323.2413 74.73259 98.17426
+## 4: v2_0 Not metered 348.3415 82.03952 104.75750
+## 5: v2_1 Metered 312.3911 63.70172 98.24216
+## 6: v2_1 Not metered 336.2510 69.96768 104.77145</code></pre>
</div>
<div id="compare-effects-by-model" class="section level2">
<h2><span class="header-section-number">13.3</span> Compare effects by model</h2>
@@ -8271,11 +8674,11 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">Basin.baseline.madj</td>
<td align="right">24100</td>
<td align="right">0.98</td>
-<td align="right">45.36</td>
-<td align="right">45.09</td>
+<td align="right">45.42</td>
+<td align="right">45.07</td>
<td align="right">10.33</td>
-<td align="right">23.90</td>
-<td align="right">27.53</td>
+<td align="right">23.85</td>
+<td align="right">27.92</td>
<td align="right">52.93</td>
<td align="right">463.65</td>
<td align="left">▇▁▁▁▁</td>
@@ -8284,38 +8687,38 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">Bath.baseline.madj</td>
<td align="right">0</td>
<td align="right">1.00</td>
-<td align="right">47.44</td>
-<td align="right">26.02</td>
+<td align="right">47.24</td>
+<td align="right">25.71</td>
<td align="right">-3.95</td>
<td align="right">25.23</td>
-<td align="right">46.80</td>
-<td align="right">65.84</td>
-<td align="right">124.08</td>
+<td align="right">46.81</td>
+<td align="right">65.67</td>
+<td align="right">125.70</td>
<td align="left">▅▇▇▅▁</td>
</tr>
<tr class="odd">
<td align="left">Dishwasher.baseline.madj</td>
<td align="right">0</td>
<td align="right">1.00</td>
-<td align="right">9.19</td>
-<td align="right">10.42</td>
+<td align="right">9.18</td>
+<td align="right">10.41</td>
<td align="right">-2.18</td>
<td align="right">-0.17</td>
<td align="right">4.26</td>
-<td align="right">21.24</td>
-<td align="right">32.27</td>
+<td align="right">21.21</td>
+<td align="right">33.99</td>
<td align="left">▇▂▁▅▁</td>
</tr>
<tr class="even">
<td align="left">External.baseline.madj</td>
<td align="right">80494</td>
<td align="right">0.93</td>
-<td align="right">19.09</td>
-<td align="right">16.43</td>
+<td align="right">19.01</td>
+<td align="right">16.45</td>
<td align="right">-2.51</td>
-<td align="right">1.42</td>
-<td align="right">17.45</td>
-<td align="right">27.90</td>
+<td align="right">1.34</td>
+<td align="right">17.47</td>
+<td align="right">27.73</td>
<td align="right">98.17</td>
<td align="left">▇▆▂▁▁</td>
</tr>
@@ -8323,12 +8726,12 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">KitchenSink.baseline.madj</td>
<td align="right">0</td>
<td align="right">1.00</td>
-<td align="right">27.82</td>
-<td align="right">14.11</td>
+<td align="right">27.81</td>
+<td align="right">14.10</td>
<td align="right">7.47</td>
<td align="right">15.28</td>
<td align="right">30.27</td>
-<td align="right">38.21</td>
+<td align="right">38.20</td>
<td align="right">76.12</td>
<td align="left">▇▇▆▂▁</td>
</tr>
@@ -8336,11 +8739,11 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">Shower.baseline.madj</td>
<td align="right">23136</td>
<td align="right">0.98</td>
-<td align="right">81.02</td>
-<td align="right">69.38</td>
+<td align="right">81.07</td>
+<td align="right">69.35</td>
<td align="right">-0.24</td>
-<td align="right">35.74</td>
-<td align="right">48.82</td>
+<td align="right">35.99</td>
+<td align="right">48.84</td>
<td align="right">114.49</td>
<td align="right">515.30</td>
<td align="left">▇▂▁▁▁</td>
@@ -8349,38 +8752,38 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">WC.baseline.madj</td>
<td align="right">25546</td>
<td align="right">0.98</td>
-<td align="right">95.56</td>
-<td align="right">41.94</td>
+<td align="right">95.44</td>
+<td align="right">42.02</td>
<td align="right">20.64</td>
-<td align="right">71.64</td>
-<td align="right">92.52</td>
-<td align="right">123.20</td>
+<td align="right">71.54</td>
+<td align="right">91.89</td>
+<td align="right">123.33</td>
<td align="right">262.81</td>
-<td align="left">▃▇▅▁▁</td>
+<td align="left">▃▇▃▁▁</td>
</tr>
<tr class="even">
<td align="left">WashingMachine.baseline.madj</td>
<td align="right">16870</td>
<td align="right">0.99</td>
-<td align="right">45.81</td>
-<td align="right">33.90</td>
+<td align="right">45.98</td>
+<td align="right">34.14</td>
<td align="right">-3.24</td>
<td align="right">15.90</td>
<td align="right">31.04</td>
-<td align="right">77.68</td>
-<td align="right">170.75</td>
-<td align="left">▇▂▅▁▁</td>
+<td align="right">78.16</td>
+<td align="right">145.57</td>
+<td align="left">▇▅▅▃▁</td>
</tr>
<tr class="odd">
<td align="left">sumDaily.baseline.madj</td>
<td align="right">80494</td>
<td align="right">0.93</td>
-<td align="right">372.70</td>
-<td align="right">151.37</td>
+<td align="right">372.54</td>
+<td align="right">151.48</td>
<td align="right">53.53</td>
-<td align="right">272.66</td>
-<td align="right">367.46</td>
-<td align="right">463.51</td>
+<td align="right">272.85</td>
+<td align="right">366.08</td>
+<td align="right">463.13</td>
<td align="right">1153.15</td>
<td align="left">▃▇▂▁▁</td>
</tr>
@@ -8427,12 +8830,12 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">WC.baseline.madj.we</td>
<td align="right">25546</td>
<td align="right">0.98</td>
-<td align="right">81.41</td>
-<td align="right">43.51</td>
-<td align="right">9.81</td>
-<td align="right">45.45</td>
-<td align="right">74.06</td>
-<td align="right">112.14</td>
+<td align="right">81.30</td>
+<td align="right">43.54</td>
+<td align="right">9.70</td>
+<td align="right">45.43</td>
+<td align="right">74.05</td>
+<td align="right">112.04</td>
<td align="right">262.81</td>
<td align="left">▇▇▅▁▁</td>
</tr>
@@ -8440,11 +8843,11 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">Shower.baseline.madj.we</td>
<td align="right">23136</td>
<td align="right">0.98</td>
-<td align="right">77.84</td>
-<td align="right">67.82</td>
+<td align="right">77.87</td>
+<td align="right">67.76</td>
<td align="right">-0.24</td>
-<td align="right">34.33</td>
-<td align="right">48.49</td>
+<td align="right">34.48</td>
+<td align="right">48.54</td>
<td align="right">109.47</td>
<td align="right">515.30</td>
<td align="left">▇▂▁▁▁</td>
@@ -8453,13 +8856,13 @@ skimr::skim(baselineWE_DT)</code></pre>
<td align="left">sumDaily.baseline.madj.we</td>
<td align="right">80494</td>
<td align="right">0.93</td>
-<td align="right">355.49</td>
-<td align="right">147.28</td>
-<td align="right">35.59</td>
-<td align="right">255.98</td>
-<td align="right">351.39</td>
-<td align="right">448.97</td>
-<td align="right">1153.15</td>
+<td align="right">355.33</td>
+<td align="right">147.33</td>
+<td align="right">36.05</td>
+<td align="right">255.76</td>
+<td align="right">350.95</td>
+<td align="right">449.75</td>
+<td align="right">1152.91</td>
<td align="left">▃▇▂▁▁</td>
</tr>
</tbody>
@@ -9625,21 +10028,21 @@ for(model in models){
<pre><code>## dualFlushWCdr
## dualFlushWC Dual flush Single flush
## Dual flush 71958 0
-## Single flush 11 316831</code></pre>
+## Single flush 51 316791</code></pre>
<pre class="r"><code>print("After model v2_0 applied")</code></pre>
<pre><code>## [1] "After model v2_0 applied"</code></pre>
<pre class="r"><code>with(baselineWE_DR_DT[model == "v2_0"], table(dualFlushWC,dualFlushWCdr))</code></pre>
<pre><code>## dualFlushWCdr
## dualFlushWC Dual flush Single flush
## Dual flush 65271 0
-## Single flush 43 287414</code></pre>
+## Single flush 39 287418</code></pre>
<pre class="r"><code>print("After model v2_1 applied")</code></pre>
<pre><code>## [1] "After model v2_1 applied"</code></pre>
<pre class="r"><code>with(baselineWE_DR_DT[model == "v2_1"], table(dualFlushWC,dualFlushWCdr))</code></pre>
<pre><code>## dualFlushWCdr
## dualFlushWC Dual flush Single flush
## Dual flush 143408 0
-## Single flush 19 209301</code></pre>
+## Single flush 0 209320</code></pre>
<p>Test the results</p>
<pre class="r"><code># > test ----
plotOrigDT <- baselineWE_DR_DT[model == "v1_3", .(nHHs = .N,
@@ -9753,233 +10156,233 @@ for(y in minYear:maxYear){
## [1] "Updating low flow shower uptake for year: 1995 & month 4 (2. Developing)"
## [1] "N cases selected: 5039"
## [1] "Updating low flow shower uptake for year: 1995 & month 5 (2. Developing)"
-## [1] "N cases selected: 5026"
+## [1] "N cases selected: 5025"
## [1] "Updating low flow shower uptake for year: 1995 & month 6 (2. Developing)"
-## [1] "N cases selected: 5015"
+## [1] "N cases selected: 5014"
## [1] "Updating low flow shower uptake for year: 1995 & month 7 (2. Developing)"
## [1] "N cases selected: 5002"
## [1] "Updating low flow shower uptake for year: 1995 & month 8 (2. Developing)"
-## [1] "N cases selected: 4989"
+## [1] "N cases selected: 4990"
## [1] "Updating low flow shower uptake for year: 1995 & month 9 (3. Drought)"
-## [1] "N cases selected: 4978"
+## [1] "N cases selected: 4977"
## [1] "Updating low flow shower uptake for year: 1995 & month 10 (3. Drought)"
## [1] "N cases selected: 4962"
## [1] "Updating low flow shower uptake for year: 1995 & month 11 (3. Drought)"
## [1] "N cases selected: 4946"
## [1] "Updating low flow shower uptake for year: 1995 & month 12 (2. Developing)"
-## [1] "N cases selected: 4931"
+## [1] "N cases selected: 4930"
## [1] "Year: 1996"
## [1] "Updating low flow shower uptake for year: 1996 & month 1 (2. Developing)"
## [1] "N cases selected: 4917"
## [1] "Updating low flow shower uptake for year: 1996 & month 2 (2. Developing)"
-## [1] "N cases selected: 4906"
+## [1] "N cases selected: 4904"
## [1] "Updating low flow shower uptake for year: 1996 & month 3 (3. Drought)"
-## [1] "N cases selected: 4895"
+## [1] "N cases selected: 4892"
## [1] "Updating low flow shower uptake for year: 1996 & month 4 (3. Drought)"
-## [1] "N cases selected: 4878"
+## [1] "N cases selected: 4875"
## [1] "Updating low flow shower uptake for year: 1996 & month 5 (3. Drought)"
-## [1] "N cases selected: 4861"
+## [1] "N cases selected: 4863"
## [1] "Updating low flow shower uptake for year: 1996 & month 6 (3. Drought)"
## [1] "N cases selected: 4848"
## [1] "Updating low flow shower uptake for year: 1996 & month 7 (3. Drought)"
-## [1] "N cases selected: 4831"
+## [1] "N cases selected: 4829"
## [1] "Updating low flow shower uptake for year: 1996 & month 8 (3. Drought)"
-## [1] "N cases selected: 4813"
+## [1] "N cases selected: 4812"
## [1] "Updating low flow shower uptake for year: 1996 & month 9 (3. Drought)"
-## [1] "N cases selected: 4799"
+## [1] "N cases selected: 4800"
## [1] "Updating low flow shower uptake for year: 1996 & month 10 (3. Drought)"
## [1] "N cases selected: 4783"
## [1] "Updating low flow shower uptake for year: 1996 & month 11 (3. Drought)"
-## [1] "N cases selected: 4767"
+## [1] "N cases selected: 4766"
## [1] "Updating low flow shower uptake for year: 1996 & month 12 (4. Severe Drought)"
-## [1] "N cases selected: 4754"
+## [1] "N cases selected: 4751"
## [1] "Year: 1997"
## [1] "Updating low flow shower uptake for year: 1997 & month 1 (4. Severe Drought)"
-## [1] "N cases selected: 4732"
+## [1] "N cases selected: 4734"
## [1] "Updating low flow shower uptake for year: 1997 & month 2 (4. Severe Drought)"
-## [1] "N cases selected: 4715"
+## [1] "N cases selected: 4716"
## [1] "Updating low flow shower uptake for year: 1997 & month 3 (4. Severe Drought)"
-## [1] "N cases selected: 4695"
+## [1] "N cases selected: 4699"
## [1] "Updating low flow shower uptake for year: 1997 & month 4 (4. Severe Drought)"
-## [1] "N cases selected: 4682"
+## [1] "N cases selected: 4675"
## [1] "Updating low flow shower uptake for year: 1997 & month 5 (4. Severe Drought)"
-## [1] "N cases selected: 4661"
+## [1] "N cases selected: 4658"
## [1] "Updating low flow shower uptake for year: 1997 & month 6 (5. Recovering)"
-## [1] "N cases selected: 4640"
+## [1] "N cases selected: 4639"
## [1] "Updating low flow shower uptake for year: 1997 & month 7 (5. Recovering)"
-## [1] "N cases selected: 4633"
+## [1] "N cases selected: 4630"
## [1] "Updating low flow shower uptake for year: 1997 & month 8 (5. Recovering)"
-## [1] "N cases selected: 4624"
+## [1] "N cases selected: 4619"
## [1] "Updating low flow shower uptake for year: 1997 & month 9 (4. Severe Drought)"
-## [1] "N cases selected: 4605"
+## [1] "N cases selected: 4606"
## [1] "Updating low flow shower uptake for year: 1997 & month 10 (4. Severe Drought)"
-## [1] "N cases selected: 4595"
+## [1] "N cases selected: 4592"
## [1] "Updating low flow shower uptake for year: 1997 & month 11 (4. Severe Drought)"
-## [1] "N cases selected: 4569"
+## [1] "N cases selected: 4577"
## [1] "Updating low flow shower uptake for year: 1997 & month 12 (5. Recovering)"
-## [1] "N cases selected: 4551"
+## [1] "N cases selected: 4554"
## [1] "Year: 1998"
## [1] "Updating low flow shower uptake for year: 1998 & month 1 (5. Recovering)"
-## [1] "N cases selected: 4543"
+## [1] "N cases selected: 4547"
## [1] "Updating low flow shower uptake for year: 1998 & month 2 (5. Recovering)"
## [1] "N cases selected: 4528"
## [1] "Updating low flow shower uptake for year: 1998 & month 3 (5. Recovering)"
-## [1] "N cases selected: 4522"
+## [1] "N cases selected: 4517"
## [1] "Updating low flow shower uptake for year: 1998 & month 4 (5. Recovering)"
-## [1] "N cases selected: 4510"
+## [1] "N cases selected: 4519"
## [1] "Updating low flow shower uptake for year: 1998 & month 5 (5. Recovering)"
-## [1] "N cases selected: 4503"
+## [1] "N cases selected: 4498"
## [1] "Updating low flow shower uptake for year: 1998 & month 6 (5. Recovering)"
-## [1] "N cases selected: 4488"
+## [1] "N cases selected: 4486"
## [1] "Updating low flow shower uptake for year: 1998 & month 7 (5. Recovering)"
-## [1] "N cases selected: 4479"
+## [1] "N cases selected: 4481"
## [1] "Updating low flow shower uptake for year: 1998 & month 8 (5. Recovering)"
-## [1] "N cases selected: 4475"
+## [1] "N cases selected: 4464"
## [1] "Updating low flow shower uptake for year: 1998 & month 9 (5. Recovering)"
-## [1] "N cases selected: 4456"
+## [1] "N cases selected: 4451"
## [1] "Updating low flow shower uptake for year: 1998 & month 10 (5. Recovering)"
-## [1] "N cases selected: 4444"
+## [1] "N cases selected: 4455"
## [1] "Updating low flow shower uptake for year: 1998 & month 11 (5. Recovering)"
-## [1] "N cases selected: 4445"
+## [1] "N cases selected: 4436"
## [1] "Year: 1999"
## [1] "Year: 2000"
## [1] "Year: 2001"
## [1] "Year: 2002"
## [1] "Year: 2003"
## [1] "Updating low flow shower uptake for year: 2003 & month 3 (2. Developing)"
-## [1] "N cases selected: 4225"
+## [1] "N cases selected: 4216"
## [1] "Updating low flow shower uptake for year: 2003 & month 4 (2. Developing)"
-## [1] "N cases selected: 4217"
+## [1] "N cases selected: 4222"
## [1] "Updating low flow shower uptake for year: 2003 & month 5 (2. Developing)"
-## [1] "N cases selected: 4212"
+## [1] "N cases selected: 4201"
## [1] "Updating low flow shower uptake for year: 2003 & month 6 (2. Developing)"
-## [1] "N cases selected: 4210"
+## [1] "N cases selected: 4200"
## [1] "Updating low flow shower uptake for year: 2003 & month 7 (2. Developing)"
-## [1] "N cases selected: 4192"
+## [1] "N cases selected: 4186"
## [1] "Updating low flow shower uptake for year: 2003 & month 8 (2. Developing)"
-## [1] "N cases selected: 4180"
+## [1] "N cases selected: 4178"
## [1] "Updating low flow shower uptake for year: 2003 & month 9 (3. Drought)"
-## [1] "N cases selected: 4180"
+## [1] "N cases selected: 4160"
## [1] "Updating low flow shower uptake for year: 2003 & month 10 (3. Drought)"
-## [1] "N cases selected: 4154"
+## [1] "N cases selected: 4159"
## [1] "Updating low flow shower uptake for year: 2003 & month 11 (3. Drought)"
-## [1] "N cases selected: 4147"
+## [1] "N cases selected: 4152"
## [1] "Updating low flow shower uptake for year: 2003 & month 12 (5. Recovering)"
-## [1] "N cases selected: 4132"
+## [1] "N cases selected: 4135"
## [1] "Year: 2004"
## [1] "Updating low flow shower uptake for year: 2004 & month 1 (5. Recovering)"
-## [1] "N cases selected: 4126"
+## [1] "N cases selected: 4124"
## [1] "Updating low flow shower uptake for year: 2004 & month 2 (5. Recovering)"
-## [1] "N cases selected: 4110"
+## [1] "N cases selected: 4116"
## [1] "Updating low flow shower uptake for year: 2004 & month 12 (2. Developing)"
-## [1] "N cases selected: 4080"
+## [1] "N cases selected: 4068"
## [1] "Year: 2005"
## [1] "Updating low flow shower uptake for year: 2005 & month 1 (2. Developing)"
-## [1] "N cases selected: 4070"
-## [1] "Updating low flow shower uptake for year: 2005 & month 2 (2. Developing)"
## [1] "N cases selected: 4052"
+## [1] "Updating low flow shower uptake for year: 2005 & month 2 (2. Developing)"
+## [1] "N cases selected: 4058"
## [1] "Updating low flow shower uptake for year: 2005 & month 3 (2. Developing)"
-## [1] "N cases selected: 4045"
+## [1] "N cases selected: 4044"
## [1] "Updating low flow shower uptake for year: 2005 & month 4 (2. Developing)"
-## [1] "N cases selected: 4030"
+## [1] "N cases selected: 4034"
## [1] "Updating low flow shower uptake for year: 2005 & month 5 (2. Developing)"
-## [1] "N cases selected: 4028"
+## [1] "N cases selected: 4016"
## [1] "Updating low flow shower uptake for year: 2005 & month 6 (5. Recovering)"
-## [1] "N cases selected: 4021"
+## [1] "N cases selected: 4012"
## [1] "Updating low flow shower uptake for year: 2005 & month 7 (5. Recovering)"
-## [1] "N cases selected: 4006"
+## [1] "N cases selected: 4002"
## [1] "Updating low flow shower uptake for year: 2005 & month 8 (5. Recovering)"
-## [1] "N cases selected: 3998"
+## [1] "N cases selected: 4009"
## [1] "Updating low flow shower uptake for year: 2005 & month 9 (2. Developing)"
-## [1] "N cases selected: 3989"
+## [1] "N cases selected: 3984"
## [1] "Updating low flow shower uptake for year: 2005 & month 10 (2. Developing)"
-## [1] "N cases selected: 3977"
+## [1] "N cases selected: 3971"
## [1] "Updating low flow shower uptake for year: 2005 & month 11 (2. Developing)"
-## [1] "N cases selected: 3968"
+## [1] "N cases selected: 3969"
## [1] "Updating low flow shower uptake for year: 2005 & month 12 (3. Drought)"
-## [1] "N cases selected: 3970"
+## [1] "N cases selected: 3963"
## [1] "Year: 2006"
## [1] "Updating low flow shower uptake for year: 2006 & month 1 (3. Drought)"
-## [1] "N cases selected: 3944"
+## [1] "N cases selected: 3949"
## [1] "Updating low flow shower uptake for year: 2006 & month 2 (3. Drought)"
-## [1] "N cases selected: 3946"
+## [1] "N cases selected: 3940"
## [1] "Updating low flow shower uptake for year: 2006 & month 3 (3. Drought)"
-## [1] "N cases selected: 3927"
+## [1] "N cases selected: 3908"
## [1] "Updating low flow shower uptake for year: 2006 & month 4 (3. Drought)"
-## [1] "N cases selected: 3923"
+## [1] "N cases selected: 3914"
## [1] "Updating low flow shower uptake for year: 2006 & month 5 (3. Drought)"
-## [1] "N cases selected: 3896"
+## [1] "N cases selected: 3891"
## [1] "Updating low flow shower uptake for year: 2006 & month 6 (5. Recovering)"
-## [1] "N cases selected: 3894"
+## [1] "N cases selected: 3896"
## [1] "Updating low flow shower uptake for year: 2006 & month 7 (5. Recovering)"
-## [1] "N cases selected: 3884"
+## [1] "N cases selected: 3873"
## [1] "Updating low flow shower uptake for year: 2006 & month 8 (5. Recovering)"
-## [1] "N cases selected: 3876"
+## [1] "N cases selected: 3872"
## [1] "Updating low flow shower uptake for year: 2006 & month 9 (5. Recovering)"
-## [1] "N cases selected: 3873"
+## [1] "N cases selected: 3859"
## [1] "Updating low flow shower uptake for year: 2006 & month 10 (5. Recovering)"
-## [1] "N cases selected: 3850"
+## [1] "N cases selected: 3869"
## [1] "Updating low flow shower uptake for year: 2006 & month 11 (5. Recovering)"
-## [1] "N cases selected: 3843"
+## [1] "N cases selected: 3848"
## [1] "Updating low flow shower uptake for year: 2006 & month 12 (5. Recovering)"
-## [1] "N cases selected: 3839"
+## [1] "N cases selected: 3849"
## [1] "Year: 2007"
## [1] "Updating low flow shower uptake for year: 2007 & month 1 (5. Recovering)"
-## [1] "N cases selected: 3830"
+## [1] "N cases selected: 3837"
## [1] "Updating low flow shower uptake for year: 2007 & month 2 (5. Recovering)"
-## [1] "N cases selected: 3812"
+## [1] "N cases selected: 3827"
## [1] "Year: 2008"
## [1] "Year: 2009"
## [1] "Updating low flow shower uptake for year: 2009 & month 3 (2. Developing)"
-## [1] "N cases selected: 3729"
+## [1] "N cases selected: 3706"
## [1] "Updating low flow shower uptake for year: 2009 & month 4 (2. Developing)"
-## [1] "N cases selected: 3721"
-## [1] "Updating low flow shower uptake for year: 2009 & month 5 (2. Developing)"
## [1] "N cases selected: 3706"
+## [1] "Updating low flow shower uptake for year: 2009 & month 5 (2. Developing)"
+## [1] "N cases selected: 3703"
## [1] "Updating low flow shower uptake for year: 2009 & month 6 (2. Developing)"
-## [1] "N cases selected: 3688"
+## [1] "N cases selected: 3709"
## [1] "Updating low flow shower uptake for year: 2009 & month 7 (2. Developing)"
-## [1] "N cases selected: 3674"
+## [1] "N cases selected: 3684"
## [1] "Updating low flow shower uptake for year: 2009 & month 8 (2. Developing)"
-## [1] "N cases selected: 3679"
+## [1] "N cases selected: 3657"
## [1] "Updating low flow shower uptake for year: 2009 & month 9 (3. Drought)"
-## [1] "N cases selected: 3676"
+## [1] "N cases selected: 3677"
## [1] "Updating low flow shower uptake for year: 2009 & month 10 (3. Drought)"
-## [1] "N cases selected: 3665"
+## [1] "N cases selected: 3675"
## [1] "Updating low flow shower uptake for year: 2009 & month 11 (3. Drought)"
-## [1] "N cases selected: 3649"
+## [1] "N cases selected: 3652"
## [1] "Updating low flow shower uptake for year: 2009 & month 12 (5. Recovering)"
-## [1] "N cases selected: 3647"
+## [1] "N cases selected: 3627"
## [1] "Year: 2010"
## [1] "Updating low flow shower uptake for year: 2010 & month 1 (5. Recovering)"
-## [1] "N cases selected: 3635"
+## [1] "N cases selected: 3623"
## [1] "Updating low flow shower uptake for year: 2010 & month 2 (5. Recovering)"
-## [1] "N cases selected: 3631"
+## [1] "N cases selected: 3624"
## [1] "Updating low flow shower uptake for year: 2010 & month 9 (2. Developing)"
-## [1] "N cases selected: 3591"
+## [1] "N cases selected: 3584"
## [1] "Updating low flow shower uptake for year: 2010 & month 10 (2. Developing)"
-## [1] "N cases selected: 3590"
+## [1] "N cases selected: 3602"
## [1] "Updating low flow shower uptake for year: 2010 & month 11 (2. Developing)"
-## [1] "N cases selected: 3578"
+## [1] "N cases selected: 3579"
## [1] "Updating low flow shower uptake for year: 2010 & month 12 (2. Developing)"
-## [1] "N cases selected: 3575"
+## [1] "N cases selected: 3570"
## [1] "Year: 2011"
## [1] "Updating low flow shower uptake for year: 2011 & month 1 (2. Developing)"
-## [1] "N cases selected: 3569"
+## [1] "N cases selected: 3563"
## [1] "Updating low flow shower uptake for year: 2011 & month 2 (2. Developing)"
## [1] "N cases selected: 3549"
## [1] "Updating low flow shower uptake for year: 2011 & month 3 (3. Drought)"
-## [1] "N cases selected: 3545"
+## [1] "N cases selected: 3547"
## [1] "Updating low flow shower uptake for year: 2011 & month 4 (3. Drought)"
-## [1] "N cases selected: 3537"
+## [1] "N cases selected: 3530"
## [1] "Updating low flow shower uptake for year: 2011 & month 5 (3. Drought)"
-## [1] "N cases selected: 3509"
+## [1] "N cases selected: 3524"
## [1] "Updating low flow shower uptake for year: 2011 & month 6 (5. Recovering)"
-## [1] "N cases selected: 3519"
+## [1] "N cases selected: 3520"
## [1] "Updating low flow shower uptake for year: 2011 & month 7 (5. Recovering)"
-## [1] "N cases selected: 3501"
+## [1] "N cases selected: 3509"
## [1] "Updating low flow shower uptake for year: 2011 & month 8 (5. Recovering)"
-## [1] "N cases selected: 3507"
+## [1] "N cases selected: 3505"
## [1] "Year: 2012"</code></pre>
<pre class="r"><code>print("After model applied")</code></pre>
<pre><code>## [1] "After model applied"</code></pre>
@@ -9987,7 +10390,7 @@ for(y in minYear:maxYear){
<pre><code>##
## Low flow Normal flow
## Low flow 98670 0
-## Normal flow 103091 892495</code></pre>
+## Normal flow 103447 892139</code></pre>
<pre class="r"><code># > test ----
plotOrigDT <- baselineWE_DR_DT[model == "v1_3", .(nHHs = .N,
pcHHs = .N/1800), by = .(obsDate, flow = loFlowShower)]
@@ -10085,8 +10488,8 @@ for(y in minYear:maxYear){
<pre><code>## [1] "Year: 1994"
## [1] "Year: 1995"
## [1] "Applying TUB for year: 1995, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.0209782834374"
-## [1] "Top 28% cut: 21.7793992685707"
+## [1] "Top 14% cut: 26.5860413287535"
+## [1] "Top 28% cut: 21.3731258984767"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1995, month 9 & model v2_0 (3. Drought)"
@@ -10100,8 +10503,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1995, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.089484491569"
-## [1] "Top 28% cut: 21.9900915298826"
+## [1] "Top 14% cut: 26.713836335934"
+## [1] "Top 28% cut: 21.5699235514826"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1995, month 10 & model v2_0 (3. Drought)"
@@ -10115,8 +10518,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1995, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.012933780435"
-## [1] "Top 28% cut: 21.879648944339"
+## [1] "Top 14% cut: 26.5970996692674"
+## [1] "Top 28% cut: 21.4717305754455"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1995, month 11 & model v2_0 (3. Drought)"
@@ -10131,8 +10534,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected for TUB: 90"
## [1] "Year: 1996"
## [1] "Applying TUB for year: 1996, month 3 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.3633951045177"
-## [1] "Top 28% cut: 22.1426556025845"
+## [1] "Top 14% cut: 26.9898609721129"
+## [1] "Top 28% cut: 21.7926184896391"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 3 & model v2_0 (3. Drought)"
@@ -10146,8 +10549,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 4 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.5439852307267"
-## [1] "Top 28% cut: 22.3501556025845"
+## [1] "Top 14% cut: 27.1700893334081"
+## [1] "Top 28% cut: 21.9642305656103"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 4 & model v2_0 (3. Drought)"
@@ -10161,8 +10564,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 5 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.7348698194874"
-## [1] "Top 28% cut: 22.4823959352374"
+## [1] "Top 14% cut: 27.3704168798647"
+## [1] "Top 28% cut: 22.1151145311506"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 5 & model v2_0 (3. Drought)"
@@ -10176,8 +10579,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 6 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 28.3425498194874"
-## [1] "Top 28% cut: 23.10822969399"
+## [1] "Top 14% cut: 27.9788182485187"
+## [1] "Top 28% cut: 22.752683829755"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 6 & model v2_0 (3. Drought)"
@@ -10191,8 +10594,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 7 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 28.1922316167708"
-## [1] "Top 28% cut: 22.9506526019041"
+## [1] "Top 14% cut: 27.7989795092292"
+## [1] "Top 28% cut: 22.54437923181"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 7 & model v2_0 (3. Drought)"
@@ -10206,8 +10609,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 8 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.6771148680466"
-## [1] "Top 28% cut: 22.3882254096416"
+## [1] "Top 14% cut: 27.2538043917333"
+## [1] "Top 28% cut: 22.0052891216358"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 8 & model v2_0 (3. Drought)"
@@ -10221,8 +10624,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.4429066641819"
-## [1] "Top 28% cut: 22.2202523638809"
+## [1] "Top 14% cut: 27.0950476387795"
+## [1] "Top 28% cut: 21.8813090801927"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 9 & model v2_0 (3. Drought)"
@@ -10236,8 +10639,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.9173933293586"
-## [1] "Top 28% cut: 21.725384033293"
+## [1] "Top 14% cut: 26.5317552342067"
+## [1] "Top 28% cut: 21.3683384501934"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 10 & model v2_0 (3. Drought)"
@@ -10251,8 +10654,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.6773444641819"
-## [1] "Top 28% cut: 21.4536222692512"
+## [1] "Top 14% cut: 26.3125176387795"
+## [1] "Top 28% cut: 21.1120019563058"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 11 & model v2_0 (3. Drought)"
@@ -10266,8 +10669,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 12 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.1450645960253"
-## [1] "Top 28% cut: 21.9527024229792"
+## [1] "Top 14% cut: 26.7616819008734"
+## [1] "Top 28% cut: 21.5866659168601"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1996, month 12 & model v2_0 (4. Severe Drought)"
@@ -10282,8 +10685,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected for TUB: 180"
## [1] "Year: 1997"
## [1] "Applying TUB for year: 1997, month 1 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.232004491569"
-## [1] "Top 28% cut: 22.1206184817447"
+## [1] "Top 14% cut: 26.856356335934"
+## [1] "Top 28% cut: 21.7124435514826"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 1 & model v2_0 (4. Severe Drought)"
@@ -10297,8 +10700,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 2 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.3545393159083"
-## [1] "Top 28% cut: 22.1612213775857"
+## [1] "Top 14% cut: 26.9624218667413"
+## [1] "Top 28% cut: 21.7639938825689"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 2 & model v2_0 (4. Severe Drought)"
@@ -10312,8 +10715,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 3 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.6023664861541"
-## [1] "Top 28% cut: 22.3816997761577"
+## [1] "Top 14% cut: 27.2685543054462"
+## [1] "Top 28% cut: 22.0396828041461"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 3 & model v2_0 (4. Severe Drought)"
@@ -10327,8 +10730,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 4 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.5458377045177"
-## [1] "Top 28% cut: 22.3270389359179"
+## [1] "Top 14% cut: 27.1719876387795"
+## [1] "Top 28% cut: 21.9753770229725"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 4 & model v2_0 (4. Severe Drought)"
@@ -10342,8 +10745,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 5 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.8551949501041"
-## [1] "Top 28% cut: 22.6136159352374"
+## [1] "Top 14% cut: 27.4185926708734"
+## [1] "Top 28% cut: 22.1907226815871"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 5 & model v2_0 (4. Severe Drought)"
@@ -10357,8 +10760,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 9 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.5650464861541"
-## [1] "Top 28% cut: 22.3443797761577"
+## [1] "Top 14% cut: 27.2312343054462"
+## [1] "Top 28% cut: 22.0023628041461"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 9 & model v2_0 (4. Severe Drought)"
@@ -10372,8 +10775,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 10 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 26.898164662692"
-## [1] "Top 28% cut: 21.7030367398966"
+## [1] "Top 14% cut: 26.5091309153317"
+## [1] "Top 28% cut: 21.3148186446808"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 10 & model v2_0 (4. Severe Drought)"
@@ -10387,8 +10790,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 11 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 26.853504491569"
-## [1] "Top 28% cut: 21.7246543059845"
+## [1] "Top 14% cut: 26.477856335934"
+## [1] "Top 28% cut: 21.3339435514826"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 11 & model v2_0 (4. Severe Drought)"
@@ -10408,8 +10811,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2002"
## [1] "Year: 2003"
## [1] "Applying TUB for year: 2003, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.6334398194874"
-## [1] "Top 28% cut: 22.4034984212959"
+## [1] "Top 14% cut: 27.2996276387795"
+## [1] "Top 28% cut: 22.0707561374794"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2003, month 9 & model v2_0 (3. Drought)"
@@ -10423,8 +10826,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2003, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.953940862692"
-## [1] "Top 28% cut: 21.7694910477533"
+## [1] "Top 14% cut: 26.5711605265454"
+## [1] "Top 28% cut: 21.4076742641864"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2003, month 10 & model v2_0 (3. Drought)"
@@ -10438,8 +10841,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2003, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.761549662692"
-## [1] "Top 28% cut: 21.5683700732299"
+## [1] "Top 14% cut: 26.3624959153317"
+## [1] "Top 28% cut: 21.1662353113474"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2003, month 11 & model v2_0 (3. Drought)"
@@ -10455,8 +10858,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2004"
## [1] "Year: 2005"
## [1] "Applying TUB for year: 2005, month 12 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.203331862692"
-## [1] "Top 28% cut: 22.0120090477533"
+## [1] "Top 14% cut: 26.8168752342067"
+## [1] "Top 28% cut: 21.6570522243108"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2005, month 12 & model v2_0 (3. Drought)"
@@ -10471,8 +10874,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected for TUB: 90"
## [1] "Year: 2006"
## [1] "Applying TUB for year: 2006, month 1 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.2368178249024"
-## [1] "Top 28% cut: 22.131484863216"
+## [1] "Top 14% cut: 26.8611696692674"
+## [1] "Top 28% cut: 21.717256884816"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 1 & model v2_0 (3. Drought)"
@@ -10486,8 +10889,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 2 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.420336662692"
-## [1] "Top 28% cut: 22.2275232229792"
+## [1] "Top 14% cut: 27.0374052342067"
+## [1] "Top 28% cut: 21.8600684501934"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 2 & model v2_0 (3. Drought)"
@@ -10501,8 +10904,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 3 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.3906098194874"
-## [1] "Top 28% cut: 22.1694938836202"
+## [1] "Top 14% cut: 27.0567976387795"
+## [1] "Top 28% cut: 21.8279261374794"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 3 & model v2_0 (3. Drought)"
@@ -10516,8 +10919,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 4 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.3835665308486"
-## [1] "Top 28% cut: 22.1605220972142"
+## [1] "Top 14% cut: 27.0333109721129"
+## [1] "Top 28% cut: 21.821578813526"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 4 & model v2_0 (3. Drought)"
@@ -10531,8 +10934,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 5 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.4481416167708"
-## [1] "Top 28% cut: 22.2065626019041"
+## [1] "Top 14% cut: 27.0115393375401"
+## [1] "Top 28% cut: 21.7913341139886"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 5 & model v2_0 (3. Drought)"
@@ -10549,8 +10952,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2008"
## [1] "Year: 2009"
## [1] "Applying TUB for year: 2009, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.5531755308486"
-## [1] "Top 28% cut: 22.3288056025845"
+## [1] "Top 14% cut: 27.1923276387795"
+## [1] "Top 28% cut: 21.9894634801926"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2009, month 9 & model v2_0 (3. Drought)"
@@ -10564,8 +10967,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2009, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.7935363137684"
-## [1] "Top 28% cut: 21.6958956110057"
+## [1] "Top 14% cut: 26.413346335934"
+## [1] "Top 28% cut: 21.2728793309876"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2009, month 10 & model v2_0 (3. Drought)"
@@ -10579,8 +10982,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2009, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.6455299045177"
-## [1] "Top 28% cut: 21.4328056025845"
+## [1] "Top 14% cut: 26.2706909721129"
+## [1] "Top 28% cut: 21.0752798808276"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2009, month 11 & model v2_0 (3. Drought)"
@@ -10596,8 +10999,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2010"
## [1] "Year: 2011"
## [1] "Applying TUB for year: 2011, month 3 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.598768437851"
-## [1] "Top 28% cut: 22.3989556025845"
+## [1] "Top 14% cut: 27.224007982274"
+## [1] "Top 28% cut: 22.0264165474943"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2011, month 3 & model v2_0 (3. Drought)"
@@ -10611,8 +11014,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2011, month 4 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.7613391045177"
-## [1] "Top 28% cut: 22.5452722692512"
+## [1] "Top 14% cut: 27.3870443054462"
+## [1] "Top 28% cut: 22.1913231563059"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2011, month 4 & model v2_0 (3. Drought)"
@@ -10626,8 +11029,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2011, month 5 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.9749046615565"
-## [1] "Top 28% cut: 22.7275792685707"
+## [1] "Top 14% cut: 27.615600213198"
+## [1] "Top 28% cut: 22.3261962999714"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2011, month 5 & model v2_0 (3. Drought)"
@@ -10845,27 +11248,27 @@ kable(dcast(t, component ~ model), caption = "Mean of meanBaseline.madj&quo
<tr class="odd">
<td align="left">Basin</td>
<td align="right">NA</td>
-<td align="right">24.46239</td>
+<td align="right">24.61785</td>
<td align="right">57.240433</td>
<td align="right">57.240433</td>
</tr>
<tr class="even">
<td align="left">Bath</td>
<td align="right">NA</td>
-<td align="right">72.09866</td>
+<td align="right">71.53676</td>
<td align="right">33.827889</td>
<td align="right">33.827889</td>
</tr>
<tr class="odd">
<td align="left">Dishwasher</td>
<td align="right">NA</td>
-<td align="right">22.66048</td>
+<td align="right">22.63672</td>
<td align="right">1.784999</td>
<td align="right">1.784999</td>
</tr>
<tr class="even">
<td align="left">External</td>
-<td align="right">19.29923</td>
+<td align="right">19.23379</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
@@ -10873,20 +11276,20 @@ kable(dcast(t, component ~ model), caption = "Mean of meanBaseline.madj&quo
<tr class="odd">
<td align="left">KitchenSink</td>
<td align="right">NA</td>
-<td align="right">42.17928</td>
+<td align="right">42.14794</td>
<td align="right">19.907452</td>
<td align="right">19.907452</td>
</tr>
<tr class="even">
<td align="left">Shower</td>
-<td align="right">82.99050</td>
+<td align="right">83.02914</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
</tr>
<tr class="odd">
<td align="left">WC</td>
-<td align="right">94.95473</td>
+<td align="right">94.84397</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
@@ -10894,7 +11297,7 @@ kable(dcast(t, component ~ model), caption = "Mean of meanBaseline.madj&quo
<tr class="even">
<td align="left">WashingMachine</td>
<td align="right">NA</td>
-<td align="right">85.56456</td>
+<td align="right">86.03717</td>
<td align="right">23.492576</td>
<td align="right">23.492576</td>
</tr>
@@ -10939,7 +11342,7 @@ kable(dcast(t, component ~ model), caption = "Mean of meanBaseline.madj.we&
</tr>
<tr class="even">
<td align="left">External</td>
-<td align="right">19.29923</td>
+<td align="right">19.23379</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
@@ -10953,14 +11356,14 @@ kable(dcast(t, component ~ model), caption = "Mean of meanBaseline.madj.we&
</tr>
<tr class="even">
<td align="left">Shower</td>
-<td align="right">80.06890</td>
+<td align="right">80.09981</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
</tr>
<tr class="odd">
<td align="left">WC</td>
-<td align="right">82.18122</td>
+<td align="right">82.07265</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
@@ -11013,7 +11416,7 @@ kable(dcast(t, component ~ model), caption = "Mean of meanBaseline.madj.we.
</tr>
<tr class="even">
<td align="left">External</td>
-<td align="right">18.80957</td>
+<td align="right">18.74593</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
@@ -11027,14 +11430,14 @@ kable(dcast(t, component ~ model), caption = "Mean of meanBaseline.madj.we.
</tr>
<tr class="even">
<td align="left">Shower</td>
-<td align="right">77.10207</td>
+<td align="right">77.03659</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
</tr>
<tr class="odd">
<td align="left">WC</td>
-<td align="right">82.17814</td>
+<td align="right">82.06912</td>
<td align="right">NA</td>
<td align="right">NA</td>
<td align="right">NA</td>
@@ -11124,49 +11527,49 @@ kable(startDT, caption = "Mean values 1994", digits = 2)</code></pre>
<td align="left">v1_3</td>
<td align="left">Metered</td>
<td align="right">1994</td>
-<td align="right">340.06</td>
-<td align="right">340.00</td>
-<td align="right">340.00</td>
+<td align="right">337.74</td>
+<td align="right">337.63</td>
+<td align="right">337.63</td>
</tr>
<tr class="even">
<td align="left">v1_3</td>
<td align="left">Not metered</td>
<td align="right">1994</td>
-<td align="right">455.30</td>
-<td align="right">455.15</td>
-<td align="right">455.15</td>
+<td align="right">456.17</td>
+<td align="right">456.09</td>
+<td align="right">456.09</td>
</tr>
<tr class="odd">
<td align="left">v2_0</td>
<td align="left">Metered</td>
<td align="right">1994</td>
<td align="right">335.65</td>
-<td align="right">335.54</td>
-<td align="right">335.54</td>
+<td align="right">335.65</td>
+<td align="right">335.65</td>
</tr>
<tr class="even">
<td align="left">v2_0</td>
<td align="left">Not metered</td>
<td align="right">1994</td>
<td align="right">363.96</td>
-<td align="right">363.96</td>
-<td align="right">363.96</td>
+<td align="right">363.83</td>
+<td align="right">363.83</td>
</tr>
<tr class="odd">
<td align="left">v2_1</td>
<td align="left">Metered</td>
<td align="right">1994</td>
<td align="right">335.65</td>
-<td align="right">335.53</td>
-<td align="right">335.53</td>
+<td align="right">335.49</td>
+<td align="right">335.49</td>
</tr>
<tr class="even">
<td align="left">v2_1</td>
<td align="left">Not metered</td>
<td align="right">1994</td>
<td align="right">363.96</td>
-<td align="right">363.79</td>
-<td align="right">363.79</td>
+<td align="right">363.78</td>
+<td align="right">363.78</td>
</tr>
</tbody>
</table>
@@ -11188,49 +11591,49 @@ kable(startDT, caption = "Mean values 1994", digits = 2)</code></pre>
<td align="left">v1_3</td>
<td align="left">Metered</td>
<td align="right">2012</td>
-<td align="right">340.73</td>
-<td align="right">322.18</td>
-<td align="right">320.23</td>
+<td align="right">338.41</td>
+<td align="right">320.56</td>
+<td align="right">318.91</td>
</tr>
<tr class="even">
<td align="left">v1_3</td>
<td align="left">Not metered</td>
<td align="right">2012</td>
-<td align="right">453.79</td>
-<td align="right">427.39</td>
-<td align="right">425.17</td>
+<td align="right">454.66</td>
+<td align="right">427.77</td>
+<td align="right">425.47</td>
</tr>
<tr class="odd">
<td align="left">v2_0</td>
<td align="left">Metered</td>
<td align="right">2012</td>
<td align="right">336.32</td>
-<td align="right">313.63</td>
-<td align="right">307.16</td>
+<td align="right">313.27</td>
+<td align="right">306.69</td>
</tr>
<tr class="even">
<td align="left">v2_0</td>
<td align="left">Not metered</td>
<td align="right">2012</td>
<td align="right">362.45</td>
-<td align="right">337.15</td>
-<td align="right">331.68</td>
+<td align="right">337.16</td>
+<td align="right">331.16</td>
</tr>
<tr class="odd">
<td align="left">v2_1</td>
<td align="left">Metered</td>
<td align="right">2012</td>
<td align="right">336.32</td>
-<td align="right">294.47</td>
-<td align="right">289.18</td>
+<td align="right">294.43</td>
+<td align="right">288.54</td>
</tr>
<tr class="even">
<td align="left">v2_1</td>
<td align="left">Not metered</td>
<td align="right">2012</td>
<td align="right">362.45</td>
-<td align="right">316.00</td>
-<td align="right">309.97</td>
+<td align="right">315.80</td>
+<td align="right">310.48</td>
</tr>
</tbody>
</table>
@@ -11370,70 +11773,73 @@ kable(t, caption = "Summary of Model v2 by drought stage", digits = 3)
<tr class="odd">
<td align="left">1. Normal</td>
<td align="left">Metered</td>
-<td align="right">335.536</td>
-<td align="right">312.521</td>
+<td align="right">335.648</td>
+<td align="right">312.337</td>
</tr>
<tr class="even">
<td align="left">1. Normal</td>
<td align="left">Not metered</td>
-<td align="right">363.964</td>
-<td align="right">334.338</td>
+<td align="right">363.825</td>
+<td align="right">334.672</td>
</tr>
<tr class="odd">
<td align="left">2. Developing</td>
<td align="left">Metered</td>
-<td align="right">338.820</td>
-<td align="right">313.733</td>
+<td align="right">338.515</td>
+<td align="right">312.648</td>
</tr>
<tr class="even">
<td align="left">2. Developing</td>
<td align="left">Not metered</td>
-<td align="right">365.086</td>
-<td align="right">337.673</td>
+<td align="right">365.371</td>
+<td align="right">338.413</td>
</tr>
<tr class="odd">
<td align="left">3. Drought</td>
<td align="left">Metered</td>
-<td align="right">337.376</td>
-<td align="right">315.384</td>
+<td align="right">336.862</td>
+<td align="right">313.515</td>
</tr>
<tr class="even">
<td align="left">3. Drought</td>
<td align="left">Not metered</td>
-<td align="right">364.676</td>
-<td align="right">338.916</td>
+<td align="right">364.735</td>
+<td align="right">338.054</td>
</tr>
<tr class="odd">
<td align="left">4. Severe Drought</td>
<td align="left">Metered</td>
-<td align="right">334.582</td>
-<td align="right">330.395</td>
+<td align="right">334.784</td>
+<td align="right">330.699</td>
</tr>
<tr class="even">
<td align="left">4. Severe Drought</td>
<td align="left">Not metered</td>
-<td align="right">363.363</td>
-<td align="right">357.655</td>
+<td align="right">363.340</td>
+<td align="right">356.910</td>
</tr>
<tr class="odd">
<td align="left">5. Recovering</td>
<td align="left">Metered</td>
-<td align="right">335.631</td>
-<td align="right">312.821</td>
+<td align="right">335.162</td>
+<td align="right">313.141</td>
</tr>
<tr class="even">
<td align="left">5. Recovering</td>
<td align="left">Not metered</td>
-<td align="right">359.370</td>
-<td align="right">337.568</td>
+<td align="right">359.824</td>
+<td align="right">336.548</td>
</tr>
</tbody>
</table>
<pre class="r"><code>min <- min(dt$pc_diff)
head(dt[pc_diff < -2.9, .(obsDate, droughtStage, metered, pc = round(pc_diff,2))])</code></pre>
<pre><code>## obsDate droughtStage metered pc
-## 1: 2011-04-15 3. Drought Metered -3.08
-## 2: 2011-05-15 3. Drought Metered -3.20</code></pre>
+## 1: 2009-10-15 3. Drought Metered -3.01
+## 2: 2009-11-15 3. Drought Metered -3.02
+## 3: 2011-03-15 3. Drought Metered -3.13
+## 4: 2011-04-15 3. Drought Metered -3.25
+## 5: 2011-05-15 3. Drought Metered -3.17</code></pre>
<pre class="r"><code>twe <- dt[, .(maxL = max(meanBaselineWeSum),
minL = min(meanBaselineWeSum)), keyby = .(metered)]
twe[, Model := "water efficiency"]
@@ -11461,30 +11867,30 @@ kable(t[, .(Model, metered, maxL, minL, pc_reduction)], digits = 2)</code></pre>
<tr class="odd">
<td align="left">water efficiency</td>
<td align="left">Metered</td>
-<td align="right">338.82</td>
-<td align="right">312.52</td>
-<td align="right">7.76</td>
+<td align="right">338.52</td>
+<td align="right">312.34</td>
+<td align="right">7.73</td>
</tr>
<tr class="even">
<td align="left">water efficiency</td>
<td align="left">Not metered</td>
-<td align="right">365.09</td>
-<td align="right">334.34</td>
-<td align="right">8.42</td>
+<td align="right">365.37</td>
+<td align="right">334.67</td>
+<td align="right">8.40</td>
</tr>
<tr class="odd">
<td align="left">water efficiency + drought</td>
<td align="left">Metered</td>
-<td align="right">338.44</td>
-<td align="right">305.43</td>
-<td align="right">9.75</td>
+<td align="right">338.32</td>
+<td align="right">303.69</td>
+<td align="right">10.23</td>
</tr>
<tr class="even">
<td align="left">water efficiency + drought</td>
<td align="left">Not metered</td>
-<td align="right">364.97</td>
-<td align="right">328.49</td>
-<td align="right">9.99</td>
+<td align="right">365.37</td>
+<td align="right">328.62</td>
+<td align="right">10.06</td>
</tr>
</tbody>
</table>
@@ -11521,7 +11927,12 @@ dt[, pc_diff := 100*(meanBaselineDrSum - meanBaselineWeSum)/meanBaselineWeSum]
min <- min(dt$pc_diff)
head(dt[pc_diff < -3, .(obsDate, droughtStage, metered, pc = round(pc_diff,2))])</code></pre>
-<pre><code>## Empty data.table (0 rows and 4 cols): obsDate,droughtStage,metered,pc</code></pre>
+<pre><code>## obsDate droughtStage metered pc
+## 1: 2009-09-15 3. Drought Metered -3.09
+## 2: 2009-10-15 3. Drought Metered -3.02
+## 3: 2011-03-15 3. Drought Metered -3.24
+## 4: 2011-04-15 3. Drought Metered -3.01
+## 5: 2011-05-15 3. Drought Metered -3.36</code></pre>
<pre class="r"><code>twe <- dt[, .(maxL = max(meanBaselineWeSum),
minL = min(meanBaselineWeSum)), keyby = .(metered)]
twe[, Model := "water efficiency"]
@@ -11549,30 +11960,30 @@ kable(t[, .(Model, metered, maxL, minL, pc_reduction)], digits = 2)</code></pre>
<tr class="odd">
<td align="left">water efficiency</td>
<td align="left">Metered</td>
-<td align="right">337.95</td>
-<td align="right">292.58</td>
-<td align="right">13.43</td>
+<td align="right">337.78</td>
+<td align="right">291.77</td>
+<td align="right">13.62</td>
</tr>
<tr class="even">
<td align="left">water efficiency</td>
<td align="left">Not metered</td>
-<td align="right">365.00</td>
-<td align="right">313.39</td>
-<td align="right">14.14</td>
+<td align="right">364.49</td>
+<td align="right">312.82</td>
+<td align="right">14.18</td>
</tr>
<tr class="odd">
<td align="left">water efficiency + drought</td>
<td align="left">Metered</td>
-<td align="right">337.41</td>
-<td align="right">287.21</td>
-<td align="right">14.88</td>
+<td align="right">337.54</td>
+<td align="right">285.82</td>
+<td align="right">15.32</td>
</tr>
<tr class="even">
<td align="left">water efficiency + drought</td>
<td align="left">Not metered</td>
-<td align="right">364.88</td>
-<td align="right">307.20</td>
-<td align="right">15.81</td>
+<td align="right">364.42</td>
+<td align="right">307.53</td>
+<td align="right">15.61</td>
</tr>
</tbody>
</table>
@@ -11604,43 +12015,43 @@ kable(caption = "Model affects (% reduced by drought model compared to WE b
<td align="left">v1_3</td>
<td align="left">Metered</td>
<td align="right">0</td>
-<td align="right">0.47</td>
-<td align="right">0.86</td>
+<td align="right">0.36</td>
+<td align="right">0.75</td>
</tr>
<tr class="even">
<td align="left">v1_3</td>
<td align="left">Not metered</td>
<td align="right">0</td>
<td align="right">0.45</td>
-<td align="right">1.18</td>
+<td align="right">1.16</td>
</tr>
<tr class="odd">
<td align="left">v2_0</td>
<td align="left">Metered</td>
<td align="right">0</td>
-<td align="right">1.43</td>
-<td align="right">3.20</td>
+<td align="right">1.60</td>
+<td align="right">3.25</td>
</tr>
<tr class="even">
<td align="left">v2_0</td>
<td align="left">Not metered</td>
<td align="right">0</td>
-<td align="right">1.09</td>
-<td align="right">2.35</td>
+<td align="right">1.22</td>
+<td align="right">2.36</td>
</tr>
<tr class="odd">
<td align="left">v2_1</td>
<td align="left">Metered</td>
<td align="right">0</td>
-<td align="right">1.35</td>
-<td align="right">2.87</td>
+<td align="right">1.48</td>
+<td align="right">3.36</td>
</tr>
<tr class="even">
<td align="left">v2_1</td>
<td align="left">Not metered</td>
<td align="right">0</td>
-<td align="right">1.31</td>
-<td align="right">2.87</td>
+<td align="right">1.24</td>
+<td align="right">2.46</td>
</tr>
</tbody>
</table>
@@ -11653,9 +12064,9 @@ baseline2Red <- baseline2Start - plotTotalDT[model == "v2_0" &
model2Red <- plotTotalDT[model == "v2_0" & obsDate == min(obsDate), meanBaselineDrSum] - plotTotalDT[model == "v2_0" & obsDate == max(obsDate), meanBaselineDrSum]</code></pre>
<p>Overall from 1994-12-15 to 2012-11-15:</p>
<ul>
-<li>the baseline model showed a reduction of 6.32, 5.59%</li>
-<li>model v1_3 showed a reduction of 6.83, 6.17%</li>
-<li>model v2_0 showed a reduction of 6.5, 9.92%</li>
+<li>the baseline model showed a reduction of 6.56, 5.32%</li>
+<li>model v1_3 showed a reduction of 7.02, 5.84%</li>
+<li>model v2_0 showed a reduction of 6.58, 9.98%</li>
</ul>
<p>This is clearly shown in the chart below where:</p>
<ul>
@@ -11775,33 +12186,33 @@ ba_IMPETUSaddDroughtPhases(p, minY, maxY)</code></pre>
<p><img src="impetusModel_files/figure-html/compare%202.0%20and%202.1-1.png" /><!-- --></p>
<pre class="r"><code>ggsave(paste0("plots_v2.1/compareWeModelsDroughtModelPcSavings.png"), dpi = 400)</code></pre>
<p>Maximum difference between the models:</p>
-<p>-7.0894933%</p>
+<p>-6.6711833%</p>
<pre class="r"><code>models[, year := lubridate::year(obsDate)]
models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<pre><code>## year meanDiff
-## 1: 1994 -0.0002471496
-## 2: 1995 -0.0021739863
-## 3: 1996 -0.0059149769
-## 4: 1997 -0.0094824771
-## 5: 1998 -0.0129025234
-## 6: 1999 -0.0156782048
-## 7: 2000 -0.0197760291
-## 8: 2001 -0.0229966071
-## 9: 2002 -0.0255450971
-## 10: 2003 -0.0284372229
-## 11: 2004 -0.0315994224
-## 12: 2005 -0.0364115290
-## 13: 2006 -0.0399777683
-## 14: 2007 -0.0456209855
-## 15: 2008 -0.0488367859
-## 16: 2009 -0.0529726764
-## 17: 2010 -0.0551458005
-## 18: 2011 -0.0591128139
-## 19: 2012 -0.0620001064</code></pre>
+## 1: 1994 -0.0003020146
+## 2: 1995 -0.0019597824
+## 3: 1996 -0.0057953029
+## 4: 1997 -0.0095076175
+## 5: 1998 -0.0120261810
+## 6: 1999 -0.0141479024
+## 7: 2000 -0.0185785848
+## 8: 2001 -0.0214190234
+## 9: 2002 -0.0258597365
+## 10: 2003 -0.0282442826
+## 11: 2004 -0.0312990726
+## 12: 2005 -0.0354045521
+## 13: 2006 -0.0385268285
+## 14: 2007 -0.0418210190
+## 15: 2008 -0.0463683116
+## 16: 2009 -0.0497234286
+## 17: 2010 -0.0527518851
+## 18: 2011 -0.0573650391
+## 19: 2012 -0.0608181857</code></pre>
<p>% reduction for 2_0</p>
-<p>-19.4941623%</p>
+<p>-20.3095536%</p>
<p>% reduction for 2_1</p>
-<p>-27.0433781%</p>
+<p>-27.4997985%</p>
</div>
</div>
</div>
@@ -12119,11 +12530,11 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">Basin.baseline.madj</td>
<td align="right">21600</td>
<td align="right">0.98</td>
-<td align="right">45.36</td>
-<td align="right">45.09</td>
+<td align="right">45.42</td>
+<td align="right">45.07</td>
<td align="right">10.33</td>
-<td align="right">23.90</td>
-<td align="right">27.53</td>
+<td align="right">23.85</td>
+<td align="right">27.92</td>
<td align="right">52.92</td>
<td align="right">463.65</td>
<td align="left">▇▁▁▁▁</td>
@@ -12132,38 +12543,38 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">Bath.baseline.madj</td>
<td align="right">0</td>
<td align="right">1.00</td>
-<td align="right">47.43</td>
-<td align="right">26.02</td>
+<td align="right">47.23</td>
+<td align="right">25.71</td>
<td align="right">-3.95</td>
<td align="right">25.22</td>
<td align="right">46.80</td>
-<td align="right">65.84</td>
-<td align="right">124.08</td>
+<td align="right">65.67</td>
+<td align="right">125.70</td>
<td align="left">▅▇▇▅▁</td>
</tr>
<tr class="odd">
<td align="left">Dishwasher.baseline.madj</td>
<td align="right">0</td>
<td align="right">1.00</td>
-<td align="right">9.20</td>
-<td align="right">10.42</td>
+<td align="right">9.19</td>
+<td align="right">10.41</td>
<td align="right">-2.18</td>
<td align="right">-0.15</td>
<td align="right">4.26</td>
-<td align="right">21.25</td>
-<td align="right">32.27</td>
+<td align="right">21.22</td>
+<td align="right">33.99</td>
<td align="left">▇▂▁▅▁</td>
</tr>
<tr class="even">
<td align="left">External.baseline.madj</td>
<td align="right">72144</td>
<td align="right">0.93</td>
-<td align="right">19.09</td>
-<td align="right">16.43</td>
+<td align="right">19.01</td>
+<td align="right">16.45</td>
<td align="right">-2.51</td>
-<td align="right">1.42</td>
-<td align="right">17.46</td>
-<td align="right">27.91</td>
+<td align="right">1.33</td>
+<td align="right">17.47</td>
+<td align="right">27.73</td>
<td align="right">98.17</td>
<td align="left">▇▆▂▁▁</td>
</tr>
@@ -12171,12 +12582,12 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">KitchenSink.baseline.madj</td>
<td align="right">0</td>
<td align="right">1.00</td>
-<td align="right">27.82</td>
-<td align="right">14.11</td>
+<td align="right">27.81</td>
+<td align="right">14.10</td>
<td align="right">7.47</td>
<td align="right">15.28</td>
<td align="right">30.27</td>
-<td align="right">38.21</td>
+<td align="right">38.20</td>
<td align="right">76.12</td>
<td align="left">▇▇▆▂▁</td>
</tr>
@@ -12184,11 +12595,11 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">Shower.baseline.madj</td>
<td align="right">20736</td>
<td align="right">0.98</td>
-<td align="right">81.01</td>
-<td align="right">69.38</td>
+<td align="right">81.05</td>
+<td align="right">69.35</td>
<td align="right">-0.24</td>
-<td align="right">35.73</td>
-<td align="right">48.80</td>
+<td align="right">35.98</td>
+<td align="right">48.83</td>
<td align="right">114.46</td>
<td align="right">515.29</td>
<td align="left">▇▂▁▁▁</td>
@@ -12197,38 +12608,38 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">WC.baseline.madj</td>
<td align="right">22896</td>
<td align="right">0.98</td>
-<td align="right">95.55</td>
-<td align="right">41.94</td>
+<td align="right">95.43</td>
+<td align="right">42.02</td>
<td align="right">20.64</td>
-<td align="right">71.66</td>
-<td align="right">92.51</td>
-<td align="right">123.19</td>
+<td align="right">71.51</td>
+<td align="right">91.88</td>
+<td align="right">123.32</td>
<td align="right">262.79</td>
-<td align="left">▃▇▅▁▁</td>
+<td align="left">▃▇▃▁▁</td>
</tr>
<tr class="even">
<td align="left">WashingMachine.baseline.madj</td>
<td align="right">15120</td>
<td align="right">0.99</td>
-<td align="right">45.86</td>
-<td align="right">33.90</td>
+<td align="right">46.03</td>
+<td align="right">34.14</td>
<td align="right">-3.24</td>
<td align="right">15.92</td>
<td align="right">31.07</td>
-<td align="right">77.73</td>
-<td align="right">170.75</td>
-<td align="left">▇▂▅▁▁</td>
+<td align="right">78.20</td>
+<td align="right">145.57</td>
+<td align="left">▇▅▅▃▁</td>
</tr>
<tr class="odd">
<td align="left">sumDaily.baseline.madj</td>
<td align="right">72144</td>
<td align="right">0.93</td>
-<td align="right">372.71</td>
-<td align="right">151.38</td>
+<td align="right">372.56</td>
+<td align="right">151.48</td>
<td align="right">53.53</td>
-<td align="right">272.68</td>
-<td align="right">367.47</td>
-<td align="right">463.54</td>
+<td align="right">272.86</td>
+<td align="right">366.09</td>
+<td align="right">463.15</td>
<td align="right">1153.15</td>
<td align="left">▃▇▂▁▁</td>
</tr>
@@ -12275,12 +12686,12 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">WC.baseline.madj.we</td>
<td align="right">22896</td>
<td align="right">0.98</td>
-<td align="right">82.87</td>
-<td align="right">43.57</td>
-<td align="right">9.81</td>
-<td align="right">47.17</td>
+<td align="right">82.75</td>
+<td align="right">43.58</td>
+<td align="right">9.70</td>
+<td align="right">47.31</td>
<td align="right">74.48</td>
-<td align="right">112.50</td>
+<td align="right">112.41</td>
<td align="right">262.79</td>
<td align="left">▇▇▅▁▁</td>
</tr>
@@ -12288,12 +12699,12 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">Shower.baseline.madj.we</td>
<td align="right">20736</td>
<td align="right">0.98</td>
-<td align="right">78.16</td>
-<td align="right">67.99</td>
+<td align="right">78.19</td>
+<td align="right">67.93</td>
<td align="right">-0.24</td>
-<td align="right">34.51</td>
-<td align="right">48.57</td>
-<td align="right">109.59</td>
+<td align="right">34.66</td>
+<td align="right">48.59</td>
+<td align="right">109.60</td>
<td align="right">515.29</td>
<td align="left">▇▂▁▁▁</td>
</tr>
@@ -12301,13 +12712,13 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">sumDaily.baseline.madj.we</td>
<td align="right">72144</td>
<td align="right">0.93</td>
-<td align="right">357.29</td>
-<td align="right">147.75</td>
-<td align="right">35.59</td>
-<td align="right">257.46</td>
-<td align="right">352.63</td>
-<td align="right">450.72</td>
-<td align="right">1153.15</td>
+<td align="right">357.13</td>
+<td align="right">147.80</td>
+<td align="right">36.05</td>
+<td align="right">257.28</td>
+<td align="right">352.07</td>
+<td align="right">451.25</td>
+<td align="right">1152.91</td>
<td align="left">▃▇▂▁▁</td>
</tr>
<tr class="even">
@@ -12366,12 +12777,12 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">WC.baseline.madj.we.dr</td>
<td align="right">22896</td>
<td align="right">0.98</td>
-<td align="right">82.87</td>
-<td align="right">43.57</td>
-<td align="right">9.81</td>
-<td align="right">47.15</td>
+<td align="right">82.75</td>
+<td align="right">43.59</td>
+<td align="right">9.70</td>
+<td align="right">47.31</td>
<td align="right">74.48</td>
-<td align="right">112.50</td>
+<td align="right">112.41</td>
<td align="right">262.79</td>
<td align="left">▇▇▅▁▁</td>
</tr>
@@ -12379,25 +12790,25 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">Shower.baseline.madj.we.dr</td>
<td align="right">20736</td>
<td align="right">0.98</td>
-<td align="right">75.26</td>
-<td align="right">66.66</td>
+<td align="right">75.21</td>
+<td align="right">66.41</td>
<td align="right">-0.24</td>
-<td align="right">32.79</td>
-<td align="right">47.41</td>
-<td align="right">104.04</td>
-<td align="right">515.29</td>
+<td align="right">32.90</td>
+<td align="right">47.36</td>
+<td align="right">103.24</td>
+<td align="right">515.26</td>
<td align="left">▇▂▁▁▁</td>
</tr>
<tr class="even">
<td align="left">External.baseline.madj.we.dr</td>
<td align="right">72144</td>
<td align="right">0.93</td>
-<td align="right">18.61</td>
-<td align="right">16.18</td>
+<td align="right">18.53</td>
+<td align="right">16.20</td>
<td align="right">-2.51</td>
-<td align="right">1.42</td>
-<td align="right">16.95</td>
-<td align="right">27.25</td>
+<td align="right">1.33</td>
+<td align="right">17.03</td>
+<td align="right">27.11</td>
<td align="right">98.17</td>
<td align="left">▇▆▂▁▁</td>
</tr>
@@ -12405,13 +12816,13 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<td align="left">sumDaily.baseline.madj.we.dr</td>
<td align="right">72144</td>
<td align="right">0.93</td>
-<td align="right">353.98</td>
-<td align="right">146.34</td>
-<td align="right">35.59</td>
-<td align="right">254.93</td>
-<td align="right">350.73</td>
-<td align="right">447.94</td>
-<td align="right">1153.15</td>
+<td align="right">353.70</td>
+<td align="right">146.42</td>
+<td align="right">36.05</td>
+<td align="right">254.27</td>
+<td align="right">350.09</td>
+<td align="right">448.81</td>
+<td align="right">1152.91</td>
<td align="left">▃▇▂▁▁</td>
</tr>
</tbody>
@@ -12467,7 +12878,7 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]</code></pre>
<pre class="r"><code>t <- proc.time() - startTime
elapsed <- t[[3]]</code></pre>
-<p>Analysis completed in 718.816 seconds ( 11.98 minutes) using <a href="https://cran.r-project.org/package=knitr">knitr</a> in <a href="http://www.rstudio.com">RStudio</a> with R version 4.0.2 (2020-06-22) running on x86_64-apple-darwin17.0.</p>
+<p>Analysis completed in 660.067 seconds ( 11 minutes) using <a href="https://cran.r-project.org/package=knitr">knitr</a> in <a href="http://www.rstudio.com">RStudio</a> with R version 4.0.2 (2020-06-22) running on x86_64-apple-darwin17.0.</p>
<p>R packages used:</p>
<ul>
<li>base R - for the basics <span class="citation">(R Core Team 2016)</span></li>
diff --git a/impetusModel/impetusModel.md b/impetusModel/impetusModel.md
index b43bf4edb53ed3012641cfc7b38077a0e746fbb8..b7d42f7ca8ec13f9fa7c78b75f8632c10ca71244 100644
--- a/impetusModel/impetusModel.md
+++ b/impetusModel/impetusModel.md
@@ -2,7 +2,7 @@
title: "A household level daily consumption estimation microsimulation model"
author: Ben Anderson (b.anderson@soton.ac.uk, `@dataknut`), Despoina Manouseli (d.manouseli@soton.ac.uk)
& Magesh Nagarajan (m.nagarajan@soton.ac.uk)
-date: 'Last run at: 2021-03-24 10:53:45'
+date: 'Last run at: 2021-03-29 17:00:42'
output:
html_document:
keep_md: yes
@@ -128,26 +128,165 @@ kable(caption = "Summary of Met Office tables",
```
```
-## NAME NROW NCOL MB
-## 1: metDataMeanRainfallDT 107 14 0
-## 2: metDataMeanSunshineDT 88 14 0
-## 3: metDataMeanTempDT 107 14 0
-## COLS KEY
-## 1: year,obs_total_rainfall_jan,obs_total_rainfall_feb,obs_total_rainfall_mar,obs_total_rainfall_apr,obs_total_rainfall_may,...
-## 2: year,obs_total_sunshine_jan,obs_total_sunshine_feb,obs_total_sunshine_mar,obs_total_sunshine_apr,obs_total_sunshine_may,...
-## 3: year,obs_mean_temp_jan,obs_mean_temp_feb,obs_mean_temp_mar,obs_mean_temp_apr,obs_mean_temp_may,...
-## Total: 0MB
+## NAME NROW NCOL MB
+## 1: climAdjCoeffDT 10 10 0
+## 2: est2013dataFig1DT 10 6 0
+## 3: est2013dataFig2DT 6 5 0
+## 4: estDT 10 4 0
+## 5: hhDataFinalDaily_v1_3DT 1,800 14 0
+## 6: hhDataFinalDaily_v2_0DT 1,800 24 0
+## 7: hhMcDataDT 1,800 21 0
+## 8: hhPropsDT 1,800 5 0
+## 9: keepDT 1,800 12 0
+## 10: mcMedianDT 2 9 0
+## 11: metDataDT 276 12 0
+## 12: metDataMeanRainfallDT 107 14 0
+## 13: metDataMeanSunshineDT 88 14 0
+## 14: metDataMeanTempDT 107 14 0
+## 15: mlmDataDT 70 12 0
+## 16: mlmDataMeteredDT 35 12 0
+## 17: mlmDataSummaryDT 18 11 0
+## 18: mlmDataUnmeteredDT 35 12 0
+## 19: modelDT 9 4 0
+## 20: monthAdjCoeffDT 24 11 0
+## 21: mt 1 10 0
+## 22: mtDT 9 4 0
+## 23: occAdjValuesDT 1,800 38 1
+## 24: occupancyAdjCoeffDT 12 11 0
+## 25: plotDT 19 5 0
+## 26: rainfallDT 276 6 0
+## 27: relevantMetDataDT 252 8 0
+## 28: relMetDataMeanRainfallDT 23 14 0
+## 29: relMetDataMeanSunshineDT 23 14 0
+## 30: relMetDataMeanTempDT 23 14 0
+## 31: summaryDT 12 10 0
+## 32: sumt 12 6 0
+## 33: sunshineDT 276 6 0
+## 34: temperatureDT 276 6 0
+## 35: testDT 1,800 8 0
+## 36: yoyAdjCoeffDT 2 10 0
+## NAME NROW NCOL MB
+## COLS
+## 1: var,metered,Basin,Bath,Dishwasher,External,...
+## 2: Usage,percentOfTotalDaily,imputed.l.hh.day,pcTot,vol,source
+## 3: N.people,AverageLitresPerDayPerHousehold,AverageLitresPerDayPerCapita,source,occupancy
+## 4: Usage,pcTot,vol,source
+## 5: metered,occupancy,hhid,lsoaarea,dtype,Basin.baseline,...
+## 6: id,hhsize,meter,monthlyBathUse,monthlyShowerUse,monthlyDishwasherUse,...
+## 7: metered,hhid,lsoaarea,occupancy,dtype,Basin.parkerMedian,...
+## 8: hhid,lsoaarea,occupancy,dtype,metered
+## 9: hhid,occupancy,metered,Basin.baseline,Bath.baseline,Dishwasher.baseline,...
+## 10: metered,Basin.parkerMedian,Bath.parkerMedian,Dishwasher.parkerMedian,External.parkerMedian,KitchenSink.parkerMedian,...
+## 11: year,mon,place,time.x,meanTemp,id.x,...
+## 12: year,obs_total_rainfall_jan,obs_total_rainfall_feb,obs_total_rainfall_mar,obs_total_rainfall_apr,obs_total_rainfall_may,...
+## 13: year,obs_total_sunshine_jan,obs_total_sunshine_feb,obs_total_sunshine_mar,obs_total_sunshine_apr,obs_total_sunshine_may,...
+## 14: year,obs_mean_temp_jan,obs_mean_temp_feb,obs_mean_temp_mar,obs_mean_temp_apr,obs_mean_temp_may,...
+## 15: var,Basin,Bath,Dishwasher,External,Kitchen.sink,...
+## 16: var,Basin,Bath,Dishwasher,External,Kitchen.sink,...
+## 17: type,var,Basin.parkerMedian,Bath.parkerMedian,Dishwasher.parkerMedian,External.parkerMedian,...
+## 18: var,Basin,Bath,Dishwasher,External,Kitchen.sink,...
+## 19: vol,Usage,source,pcTot
+## 20: var,metered,month,Basin,Bath,Dishwasher,...
+## 21: vol,Basin,Dishwasher,External,Kitchen Sink,Bath,...
+## 22: vol,Usage,source,pcTot
+## 23: metered,occupancy,hhid,lsoaarea,dtype,Basin.parkerMedian,...
+## 24: var,metered,occupancy,Basin,Bath,Dishwasher,...
+## 25: Usage,pcTot,vol,source,UsageRo
+## 26: year,place,time,totalRainfall,id,mon
+## 27: year,mon,place,meanTemp,id.x,totalSunshine,...
+## 28: year,obs_total_rainfall_jan,obs_total_rainfall_feb,obs_total_rainfall_mar,obs_total_rainfall_apr,obs_total_rainfall_may,...
+## 29: year,obs_total_sunshine_jan,obs_total_sunshine_feb,obs_total_sunshine_mar,obs_total_sunshine_apr,obs_total_sunshine_may,...
+## 30: year,obs_mean_temp_jan,obs_mean_temp_feb,obs_mean_temp_mar,obs_mean_temp_apr,obs_mean_temp_may,...
+## 31: occupancy,metered,meanBasin,meanBath,meanDishwasher,meanExternal,...
+## 32: metered,occupancy,meanBasin.baseline,sdBasin.baseline,meanBath.baseline,sdBath.baseline
+## 33: year,place,time,totalSunshine,id,mon
+## 34: year,place,time,meanTemp,id,mon
+## 35: Basin.rsnorm,Bath.rsnorm,Dishwasher.rsnorm,External.rsnorm,KitchenSink.rsnorm,Shower.rsnorm,...
+## 36: var,metered,Basin,Bath,Dishwasher,External,...
+## COLS
+## KEY
+## 1: metered
+## 2:
+## 3: occupancy
+## 4:
+## 5: metered,occupancy
+## 6:
+## 7: metered,occupancy
+## 8: metered
+## 9: metered,occupancy
+## 10: metered
+## 11: year,mon,place
+## 12:
+## 13:
+## 14:
+## 15:
+## 16:
+## 17:
+## 18:
+## 19: Usage
+## 20: metered
+## 21:
+## 22: Usage
+## 23: metered,occupancy
+## 24: metered,occupancy
+## 25:
+## 26: year,mon,place
+## 27: year,mon,place
+## 28:
+## 29:
+## 30:
+## 31:
+## 32: metered,occupancy
+## 33: year,mon,place
+## 34: year,mon,place
+## 35:
+## 36: metered
+## KEY
+## Total: 1MB
```
Table: Summary of Met Office tables
-|NAME | NROW| NCOL| MB|COLS |KEY |
-|:---------------------|----:|----:|--:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----|
-|metDataMeanRainfallDT | 107| 14| 0|year , obs_total_rainfall_jan, obs_total_rainfall_feb, obs_total_rainfall_mar, obs_total_rainfall_apr, obs_total_rainfall_may, obs_total_rainfall_jun, obs_total_rainfall_jul, obs_total_rainfall_aug, obs_total_rainfall_sep, obs_total_rainfall_oct, obs_total_rainfall_nov, obs_total_rainfall_dec, place |NULL |
-|metDataMeanSunshineDT | 88| 14| 0|year , obs_total_sunshine_jan, obs_total_sunshine_feb, obs_total_sunshine_mar, obs_total_sunshine_apr, obs_total_sunshine_may, obs_total_sunshine_jun, obs_total_sunshine_jul, obs_total_sunshine_aug, obs_total_sunshine_sep, obs_total_sunshine_oct, obs_total_sunshine_nov, obs_total_sunshine_dec, place |NULL |
-|metDataMeanTempDT | 107| 14| 0|year , obs_mean_temp_jan, obs_mean_temp_feb, obs_mean_temp_mar, obs_mean_temp_apr, obs_mean_temp_may, obs_mean_temp_jun, obs_mean_temp_jul, obs_mean_temp_aug, obs_mean_temp_sep, obs_mean_temp_oct, obs_mean_temp_nov, obs_mean_temp_dec, place |NULL |
+|NAME | NROW| NCOL| MB|COLS |KEY |
+|:------------------------|----:|----:|--:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------|
+|climAdjCoeffDT | 10| 10| 0|var , metered , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine |metered |
+|est2013dataFig1DT | 10| 6| 0|Usage , percentOfTotalDaily, imputed.l.hh.day , pcTot , vol , source |NULL |
+|est2013dataFig2DT | 6| 5| 0|N.people , AverageLitresPerDayPerHousehold, AverageLitresPerDayPerCapita , source , occupancy |occupancy |
+|estDT | 10| 4| 0|Usage , pcTot , vol , source |NULL |
+|hhDataFinalDaily_v1_3DT | 1800| 14| 0|metered , occupancy , hhid , lsoaarea , dtype , Basin.baseline , Bath.baseline , Dishwasher.baseline , External.baseline , KitchenSink.baseline , Shower.baseline , WC.baseline , WashingMachine.baseline, sumDaily.baseline |metered , occupancy |
+|hhDataFinalDaily_v2_0DT | 1800| 24| 0|id , hhsize , meter , monthlyBathUse , monthlyShowerUse , monthlyDishwasherUse , monthlyKitchenSinkUse , monthlyWCUse , monthlyWashingMachineUse , monthlyBathroomSinkUse , totalMonthlyInHouseDemand , monthlyGardenUse , dailyGardenUse , monthlyCarWashUse , dailyCarWashUse , totalMonthlyHouseDemandFinal, totalDailyHouseDemandFinal , dailyBathUse , dailyShowerUse , dailyDishwasherUse , dailyKitchenSinkUse , dailyWCUse , dailyWashingMachineUse , dailyBathroomSinkUse |NULL |
+|hhMcDataDT | 1800| 21| 0|metered , hhid , lsoaarea , occupancy , dtype , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian, Basin.rsnorm , Bath.rsnorm , Dishwasher.rsnorm , External.rsnorm , KitchenSink.rsnorm , Shower.rsnorm , WC.rsnorm , WashingMachine.rsnorm |metered , occupancy |
+|hhPropsDT | 1800| 5| 0|hhid , lsoaarea , occupancy, dtype , metered |metered |
+|keepDT | 1800| 12| 0|hhid , occupancy , metered , Basin.baseline , Bath.baseline , Dishwasher.baseline , KitchenSink.baseline , Shower.baseline , WC.baseline , WashingMachine.baseline, External.baseline , sumDaily.baseline |metered , occupancy |
+|mcMedianDT | 2| 9| 0|metered , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian |metered |
+|metDataDT | 276| 12| 0|year , mon , place , time.x , meanTemp , id.x , time.y , totalSunshine, id.y , time , totalRainfall, id |year , mon , place |
+|metDataMeanRainfallDT | 107| 14| 0|year , obs_total_rainfall_jan, obs_total_rainfall_feb, obs_total_rainfall_mar, obs_total_rainfall_apr, obs_total_rainfall_may, obs_total_rainfall_jun, obs_total_rainfall_jul, obs_total_rainfall_aug, obs_total_rainfall_sep, obs_total_rainfall_oct, obs_total_rainfall_nov, obs_total_rainfall_dec, place |NULL |
+|metDataMeanSunshineDT | 88| 14| 0|year , obs_total_sunshine_jan, obs_total_sunshine_feb, obs_total_sunshine_mar, obs_total_sunshine_apr, obs_total_sunshine_may, obs_total_sunshine_jun, obs_total_sunshine_jul, obs_total_sunshine_aug, obs_total_sunshine_sep, obs_total_sunshine_oct, obs_total_sunshine_nov, obs_total_sunshine_dec, place |NULL |
+|metDataMeanTempDT | 107| 14| 0|year , obs_mean_temp_jan, obs_mean_temp_feb, obs_mean_temp_mar, obs_mean_temp_apr, obs_mean_temp_may, obs_mean_temp_jun, obs_mean_temp_jul, obs_mean_temp_aug, obs_mean_temp_sep, obs_mean_temp_oct, obs_mean_temp_nov, obs_mean_temp_dec, place |NULL |
+|mlmDataDT | 70| 12| 0|var , Basin , Bath , Dishwasher , External , Kitchen.sink , Shower , WC , Washing.machine, addldetails , note , metered |NULL |
+|mlmDataMeteredDT | 35| 12| 0|var , Basin , Bath , Dishwasher , External , Kitchen.sink , Shower , WC , Washing.machine, addldetails , note , metered |NULL |
+|mlmDataSummaryDT | 18| 11| 0|type , var , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian, Source |NULL |
+|mlmDataUnmeteredDT | 35| 12| 0|var , Basin , Bath , Dishwasher , External , Kitchen.sink , Shower , WC , Washing.machine, addldetails , note , metered |NULL |
+|modelDT | 9| 4| 0|vol , Usage , source, pcTot |Usage |
+|monthAdjCoeffDT | 24| 11| 0|var , metered , month , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine |metered |
+|mt | 1| 10| 0|vol , Basin , Dishwasher , External , Kitchen Sink , Bath , Shower , Toilet , Washing machine, Total |NULL |
+|mtDT | 9| 4| 0|vol , Usage , source, pcTot |Usage |
+|occAdjValuesDT | 1800| 38| 1|metered , occupancy , hhid , lsoaarea , dtype , Basin.parkerMedian , Bath.parkerMedian , Dishwasher.parkerMedian , External.parkerMedian , KitchenSink.parkerMedian , Shower.parkerMedian , WC.parkerMedian , WashingMachine.parkerMedian, Basin.rsnorm , Bath.rsnorm , Dishwasher.rsnorm , External.rsnorm , KitchenSink.rsnorm , Shower.rsnorm , WC.rsnorm , WashingMachine.rsnorm , var , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine , Basin.baseline , Bath.baseline , Dishwasher.baseline , External.baseline , KitchenSink.baseline , Shower.baseline , WC.baseline , WashingMachine.baseline |metered , occupancy |
+|occupancyAdjCoeffDT | 12| 11| 0|var , metered , occupancy , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine |metered , occupancy |
+|plotDT | 19| 5| 0|Usage , pcTot , vol , source , UsageRo |NULL |
+|rainfallDT | 276| 6| 0|year , place , time , totalRainfall, id , mon |year , mon , place |
+|relevantMetDataDT | 252| 8| 0|year , mon , place , meanTemp , id.x , totalSunshine, totalRainfall, slno |year , mon , place |
+|relMetDataMeanRainfallDT | 23| 14| 0|year , obs_total_rainfall_jan, obs_total_rainfall_feb, obs_total_rainfall_mar, obs_total_rainfall_apr, obs_total_rainfall_may, obs_total_rainfall_jun, obs_total_rainfall_jul, obs_total_rainfall_aug, obs_total_rainfall_sep, obs_total_rainfall_oct, obs_total_rainfall_nov, obs_total_rainfall_dec, place |NULL |
+|relMetDataMeanSunshineDT | 23| 14| 0|year , obs_total_sunshine_jan, obs_total_sunshine_feb, obs_total_sunshine_mar, obs_total_sunshine_apr, obs_total_sunshine_may, obs_total_sunshine_jun, obs_total_sunshine_jul, obs_total_sunshine_aug, obs_total_sunshine_sep, obs_total_sunshine_oct, obs_total_sunshine_nov, obs_total_sunshine_dec, place |NULL |
+|relMetDataMeanTempDT | 23| 14| 0|year , obs_mean_temp_jan, obs_mean_temp_feb, obs_mean_temp_mar, obs_mean_temp_apr, obs_mean_temp_may, obs_mean_temp_jun, obs_mean_temp_jul, obs_mean_temp_aug, obs_mean_temp_sep, obs_mean_temp_oct, obs_mean_temp_nov, obs_mean_temp_dec, place |NULL |
+|summaryDT | 12| 10| 0|occupancy , metered , meanBasin , meanBath , meanDishwasher , meanExternal , meanKitchenSink , meanShower , meanWC , meanWashingMachine |NULL |
+|sumt | 12| 6| 0|metered , occupancy , meanBasin.baseline, sdBasin.baseline , meanBath.baseline , sdBath.baseline |metered , occupancy |
+|sunshineDT | 276| 6| 0|year , place , time , totalSunshine, id , mon |year , mon , place |
+|temperatureDT | 276| 6| 0|year , place , time , meanTemp, id , mon |year , mon , place |
+|testDT | 1800| 8| 0|Basin.rsnorm , Bath.rsnorm , Dishwasher.rsnorm , External.rsnorm , KitchenSink.rsnorm , Shower.rsnorm , WC.rsnorm , WashingMachine.rsnorm |NULL |
+|yoyAdjCoeffDT | 2| 10| 0|var , metered , Basin , Bath , Dishwasher , External , KitchenSink , Shower , WC , WashingMachine |metered |
Sunshine only starts in 1929 so the sunshine table has fewer rows.
@@ -643,10 +782,10 @@ kable(caption = "Check % metered distribution",
Table: Check % metered distribution
-| | 1| 2| 3| 4| 5| 6|
-|:-----------|--:|----:|----:|----:|----:|----:|
-|Metered | 42| 38.3| 40.4| 37.5| 43.6| 39.8|
-|Not metered | 58| 61.7| 59.6| 62.5| 56.4| 60.2|
+| | 1| 2| 3| 4| 5| 6|
+|:-----------|----:|----:|----:|----:|----:|----:|
+|Metered | 40.8| 39.6| 40.7| 41.7| 38.3| 33.7|
+|Not metered | 59.2| 60.4| 59.3| 58.3| 61.7| 66.3|
## Baseline consumption estimation
@@ -884,12 +1023,12 @@ Table: Test Basin & Bath l/day as modelled using rsnorm()
| | Basin.rsnorm | Bath.rsnorm |Dishwasher.rsnorm |External.rsnorm |KitchenSink.rsnorm |Shower.rsnorm | WC.rsnorm |WashingMachine.rsnorm |
|:--|:-------------|:--------------|:-----------------|:---------------|:------------------|:-------------|:--------------|:---------------------|
-| |Min. :12.11 |Min. : 32.95 |Min. :19.95 |Min. : 0.00 |Min. :27.22 |Min. :21.44 |Min. : 49.50 |Min. : 55.51 |
-| |1st Qu.:17.58 |1st Qu.: 57.10 |1st Qu.:22.63 |1st Qu.:10.72 |1st Qu.:32.46 |1st Qu.:31.65 |1st Qu.: 80.84 |1st Qu.: 72.84 |
-| |Median :24.09 |Median : 74.08 |Median :23.99 |Median :15.72 |Median :43.03 |Median :36.15 |Median :100.80 |Median : 81.24 |
-| |Mean :22.94 |Mean : 72.13 |Mean :24.25 |Mean :15.84 |Mean :40.34 |Mean :36.31 |Mean : 98.89 |Mean : 83.70 |
-| |3rd Qu.:26.95 |3rd Qu.: 84.26 |3rd Qu.:25.63 |3rd Qu.:22.56 |3rd Qu.:46.05 |3rd Qu.:40.79 |3rd Qu.:114.68 |3rd Qu.: 92.47 |
-| |Max. :39.56 |Max. :123.99 |Max. :32.54 |Max. :56.10 |Max. :59.52 |Max. :59.02 |Max. :168.86 |Max. :170.78 |
+| |Min. :11.77 |Min. : 37.10 |Min. :19.79 |Min. : 0.00 |Min. :26.99 |Min. :20.83 |Min. : 48.72 |Min. : 55.09 |
+| |1st Qu.:17.53 |1st Qu.: 56.57 |1st Qu.:22.63 |1st Qu.:10.71 |1st Qu.:32.46 |1st Qu.:31.58 |1st Qu.: 80.31 |1st Qu.: 73.04 |
+| |Median :24.17 |Median : 74.12 |Median :23.93 |Median :15.86 |Median :43.08 |Median :36.35 |Median :100.25 |Median : 82.15 |
+| |Mean :23.09 |Mean : 71.54 |Mean :24.22 |Mean :15.65 |Mean :40.31 |Mean :36.41 |Mean : 98.59 |Mean : 84.17 |
+| |3rd Qu.:27.40 |3rd Qu.: 83.65 |3rd Qu.:25.57 |3rd Qu.:22.24 |3rd Qu.:46.02 |3rd Qu.:41.01 |3rd Qu.:114.34 |3rd Qu.: 93.32 |
+| |Max. :41.99 |Max. :125.42 |Max. :34.79 |Max. :52.46 |Max. :58.59 |Max. :59.47 |Max. :178.98 |Max. :143.85 |
The table above shows the effect on the mean consumption values for Basin and Bath by occupancy group and metered/un-metered. Note that there is still no correction for occupancy levels.
@@ -918,17 +1057,17 @@ kable(caption = "Metered vs un-metered estimates (mean)",
Table: Metered vs un-metered estimates (mean)
-|metered | Basin| Bath| Dishwasher| External| KitchenSink| Shower| WC| WashingMachine|
-|:-----------|--------:|--------:|----------:|--------:|-----------:|--------:|---------:|--------------:|
-|Metered | 17.05667| 55.07805| 23.08817| 10.72518| 31.99094| 30.83176| 78.46629| 77.96451|
-|Not metered | 26.86254| 83.49025| 25.02250| 19.25489| 45.90234| 39.96394| 112.51120| 87.52588|
+|metered | Basin| Bath| Dishwasher| External| KitchenSink| Shower| WC| WashingMachine|
+|:-----------|--------:|------:|----------:|---------:|-----------:|--------:|---------:|--------------:|
+|Metered | 17.06715| 54.868| 23.00139| 9.943501| 31.91475| 30.82813| 76.90131| 78.18723|
+|Not metered | 27.09918| 82.660| 25.03293| 19.455593| 45.90567| 40.12686| 113.05406| 88.16084|
```r
wmMetered <- t[metered == "Metered", WC]
wmNonMetered <- t[metered == "Not metered", WC]
```
-% difference between means for washing machine: 30.26.
+% difference between means for washing machine: 31.98.
### Occupancy based adjustment
@@ -1010,18 +1149,18 @@ Table: Test monthly fixed and occupancy adjusted l/day
|metered | occupancy| meanBasin.baseline| sdBasin.baseline| meanBath.baseline| sdBath.baseline|
|:-----------|---------:|------------------:|----------------:|-----------------:|---------------:|
-|Metered | 1| 17.26| 3.11| 55.42| 9.90|
-|Metered | 2| 18.34| 3.00| 55.48| 10.31|
-|Metered | 3| 19.21| 3.04| 57.35| 11.08|
-|Metered | 4| 20.05| 3.49| 57.37| 8.50|
-|Metered | 5| 19.14| 2.88| 52.19| 9.61|
-|Metered | 6| 18.21| 2.62| 64.09| 10.04|
-|Not metered | 1| 26.92| 3.10| 83.74| 10.88|
-|Not metered | 2| 28.13| 3.03| 83.81| 9.94|
-|Not metered | 3| 29.50| 2.87| 87.07| 10.82|
-|Not metered | 4| 29.62| 3.16| 85.64| 10.14|
-|Not metered | 5| 29.05| 2.65| 86.24| 9.54|
-|Not metered | 6| 30.64| 3.04| 87.82| 9.63|
+|Metered | 1| 16.93| 2.96| 54.29| 9.48|
+|Metered | 2| 18.81| 3.25| 56.08| 10.48|
+|Metered | 3| 19.47| 3.42| 57.96| 10.81|
+|Metered | 4| 19.18| 2.22| 57.09| 8.12|
+|Metered | 5| 18.86| 2.49| 53.95| 10.34|
+|Metered | 6| 18.19| 1.72| 58.55| 10.43|
+|Not metered | 1| 27.19| 2.96| 83.50| 10.21|
+|Not metered | 2| 28.38| 2.93| 83.46| 9.73|
+|Not metered | 3| 29.17| 2.73| 85.03| 8.70|
+|Not metered | 4| 30.52| 3.71| 83.89| 10.78|
+|Not metered | 5| 29.47| 2.71| 84.93| 8.17|
+|Not metered | 6| 31.13| 3.42| 86.53| 9.42|
The table above shows the effect on the median consumption values for Basin and Bath by occupancy group and metered/un-metered.
@@ -1590,14 +1729,22 @@ summary(teethdemand_hh)
```
```
-## obs id hhsize meter wash_freq teeth_where teethbrush_hh
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000 Min. : 0.0
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :2.000 Median : 1.420 Median : 255.6
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :1.996 Mean : 5.699 Mean : 915.7
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700 3rd Qu.: 1002.0
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :4.000 Max. :16.700 Max. :12024.0
-## NA's :22 NA's :42 NA's :53
+## obs id hhsize meter wash_freq teeth_where
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :2.000 Median : 1.420
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :1.996 Mean : 5.699
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :4.000 Max. :16.700
+## NA's :22 NA's :42
+## teethbrush_hh
+## Min. : 0.0
+## 1st Qu.: 170.4
+## Median : 255.6
+## Mean : 915.7
+## 3rd Qu.: 1002.0
+## Max. :12024.0
+## NA's :53
```
```r
@@ -1632,22 +1779,22 @@ summary(bathsink_hh)
```
```
-## id obs.x hhsize.x meter.x wash_freq teeth_where teethbrush_hh
-## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000 Min. : 0.0
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4
-## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median :2.000 Median : 1.420 Median : 255.6
-## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1.996 Mean : 5.699 Mean : 915.7
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700 3rd Qu.: 1002.0
-## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :4.000 Max. :16.700 Max. :12024.0
-## NA's :22 NA's :42 NA's :53
-## hands monthlyBathroomSinkUse dailyBathroomSinkUse
-## Min. : 312.0 Min. : 312.0 Min. : 10.40
-## 1st Qu.: 624.0 1st Qu.: 794.4 1st Qu.: 26.48
-## Median : 624.0 Median : 1191.6 Median : 39.72
-## Mean : 828.4 Mean : 1748.0 Mean : 58.27
-## 3rd Qu.:1248.0 3rd Qu.: 1986.0 3rd Qu.: 66.20
-## Max. :3120.0 Max. :13896.0 Max. :463.20
-## NA's :53 NA's :53
+## id obs.x hhsize.x meter.x wash_freq teeth_where
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. :0.000 Min. : 0.000
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.:2.000 1st Qu.: 1.420
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median :2.000 Median : 1.420
+## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1.996 Mean : 5.699
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:2.000 3rd Qu.:16.700
+## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :4.000 Max. :16.700
+## NA's :22 NA's :42
+## teethbrush_hh hands monthlyBathroomSinkUse dailyBathroomSinkUse
+## Min. : 0.0 Min. : 312.0 Min. : 312.0 Min. : 10.40
+## 1st Qu.: 170.4 1st Qu.: 624.0 1st Qu.: 794.4 1st Qu.: 26.48
+## Median : 255.6 Median : 624.0 Median : 1191.6 Median : 39.72
+## Mean : 915.7 Mean : 828.4 Mean : 1748.0 Mean : 58.27
+## 3rd Qu.: 1002.0 3rd Qu.:1248.0 3rd Qu.: 1986.0 3rd Qu.: 66.20
+## Max. :12024.0 Max. :3120.0 Max. :13896.0 Max. :463.20
+## NA's :53 NA's :53 NA's :53
```
```r
@@ -1732,22 +1879,22 @@ summary(bathdemand_hh)
```
```
-## hhsize obs id meter bath_freq baths housefreq
-## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.000 Min. :0.0000 Min. : 0.000
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.000 1st Qu.:1.0000 1st Qu.: 0.000
-## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.000 Median :1.0000 Median : 0.000
-## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :1.881 Mean :0.9717 Mean : 5.099
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:3.000 3rd Qu.:1.0000 3rd Qu.: 7.000
-## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :9.000 Max. :4.0000 Max. :63.000
-## NA's :51 NA's :51
-## baths_freq_EST showers_freq_EST monthlyBathUse dailyBathUse
-## Min. :1.700 Min. : 5.20 Min. : 0.0 Min. : 0.00
-## 1st Qu.:2.250 1st Qu.: 9.40 1st Qu.: 598.4 1st Qu.:19.95
-## Median :2.250 Median : 9.40 Median : 792.0 Median :26.40
-## Mean :3.264 Mean :10.56 Mean :1065.9 Mean :35.53
-## 3rd Qu.:4.850 3rd Qu.:14.65 3rd Qu.:1707.2 3rd Qu.:56.91
-## Max. :6.600 Max. :16.05 Max. :2323.2 Max. :77.44
-##
+## hhsize obs id meter bath_freq baths
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.000 Min. :0.0000
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.000 1st Qu.:1.0000
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.000 Median :1.0000
+## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :1.881 Mean :0.9717
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:3.000 3rd Qu.:1.0000
+## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :9.000 Max. :4.0000
+## NA's :51
+## housefreq baths_freq_EST showers_freq_EST monthlyBathUse dailyBathUse
+## Min. : 0.000 Min. :1.700 Min. : 5.20 Min. : 0.0 Min. : 0.00
+## 1st Qu.: 0.000 1st Qu.:2.250 1st Qu.: 9.40 1st Qu.: 598.4 1st Qu.:19.95
+## Median : 0.000 Median :2.250 Median : 9.40 Median : 792.0 Median :26.40
+## Mean : 5.099 Mean :3.264 Mean :10.56 Mean :1065.9 Mean :35.53
+## 3rd Qu.: 7.000 3rd Qu.:4.850 3rd Qu.:14.65 3rd Qu.:1707.2 3rd Qu.:56.91
+## Max. :63.000 Max. :6.600 Max. :16.05 Max. :2323.2 Max. :77.44
+## NA's :51
```
```r
@@ -1847,20 +1994,20 @@ summary(monthlyDishwasherUse)#'At home with water2' reports 10 l/hh/day for thei
```
```
-## hhsize obs id meter dishwashers dish_freq weeklyDish_freq
-## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.0000 Length:1800 Min. :0.900
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.0000 Class :character 1st Qu.:2.300
-## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.0000 Mode :character Median :2.300
-## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :0.4233 Mean :2.737
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:1.0000 3rd Qu.:4.300
-## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :2.0000 Max. :4.800
-## monthlyDishwasherUse dailyDishwasherUse
-## Min. : 0.00 Min. :0.000
-## 1st Qu.: 0.00 1st Qu.:0.000
-## Median : 0.00 Median :0.000
-## Mean : 71.18 Mean :2.373
-## 3rd Qu.:128.80 3rd Qu.:4.293
-## Max. :268.80 Max. :8.960
+## hhsize obs id meter dishwashers dish_freq
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800 Min. :0.0000 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character 1st Qu.:0.0000 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character Median :0.0000 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052 Mean :0.4233
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.:1.0000
+## Max. :10.000 Max. :1810.0 Max. :836965495 Max. :2.0000
+## weeklyDish_freq monthlyDishwasherUse dailyDishwasherUse
+## Min. :0.900 Min. : 0.00 Min. :0.000
+## 1st Qu.:2.300 1st Qu.: 0.00 1st Qu.:0.000
+## Median :2.300 Median : 0.00 Median :0.000
+## Mean :2.737 Mean : 71.18 Mean :2.373
+## 3rd Qu.:4.300 3rd Qu.:128.80 3rd Qu.:4.293
+## Max. :4.800 Max. :268.80 Max. :8.960
```
```r
@@ -1921,13 +2068,20 @@ summary(kitchen_sink_hh)
```
```
-## obs id hhsize meter monthlyKitchenSinkUse dailyKitchenSinkUse
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 227.1 Min. : 7.57
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 454.2 1st Qu.:15.14
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 454.2 Median :15.14
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 603.0 Mean :20.10
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 908.4 3rd Qu.:30.28
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2271.0 Max. :75.70
+## obs id hhsize meter monthlyKitchenSinkUse
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 227.1
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 454.2
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 454.2
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 603.0
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 908.4
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2271.0
+## dailyKitchenSinkUse
+## Min. : 7.57
+## 1st Qu.:15.14
+## Median :15.14
+## Mean :20.10
+## 3rd Qu.:30.28
+## Max. :75.70
```
```r
@@ -2131,22 +2285,22 @@ summary (toiletdemand_hh)
```
```
-## obs id hhsize meter singleflush_wc dualflush_wc effective_flush
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 0.000 Min. :0.0000 Length:1800
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 1.000 1st Qu.:0.0000 Class :character
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 1.000 Median :0.0000 Mode :character
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 1.169 Mean :0.4233
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 2.000 3rd Qu.:1.0000
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :97.000 Max. :5.0000
-##
-## flushvolume monthlyWCUse dailyWCUse
-## Min. :5.000 Min. : 750 Min. : 25.00
-## 1st Qu.:6.250 1st Qu.:1500 1st Qu.: 50.00
-## Median :7.500 Median :2250 Median : 75.00
-## Mean :6.918 Mean :2739 Mean : 91.31
-## 3rd Qu.:7.500 3rd Qu.:3375 3rd Qu.:112.50
-## Max. :7.500 Max. :7875 Max. :262.50
-## NA's :59 NA's :59 NA's :59
+## obs id hhsize meter singleflush_wc dualflush_wc
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. : 0.000 Min. :0.0000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.: 1.000 1st Qu.:0.0000
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median : 1.000 Median :0.0000
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean : 1.169 Mean :0.4233
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.: 2.000 3rd Qu.:1.0000
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :97.000 Max. :5.0000
+##
+## effective_flush flushvolume monthlyWCUse dailyWCUse
+## Length:1800 Min. :5.000 Min. : 750 Min. : 25.00
+## Class :character 1st Qu.:6.250 1st Qu.:1500 1st Qu.: 50.00
+## Mode :character Median :7.500 Median :2250 Median : 75.00
+## Mean :6.918 Mean :2739 Mean : 91.31
+## 3rd Qu.:7.500 3rd Qu.:3375 3rd Qu.:112.50
+## Max. :7.500 Max. :7875 Max. :262.50
+## NA's :59 NA's :59 NA's :59
```
```r
@@ -2236,22 +2390,22 @@ summary(washingmachine_hh)
```
```
-## obs id hhsize meter washingmachine weeklyloads combinedwash
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. : 0.000 Min. :1
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:1.0000 1st Qu.: 2.500 1st Qu.:1
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :1.0000 Median : 2.500 Median :1
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.9472 Mean : 3.542 Mean :1
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.: 4.500 3rd Qu.:1
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2.0000 Max. :12.000 Max. :1
-## NA's :47 NA's :98
-## monthlyWashingMachineUse dailyWashingMachineUse
-## Min. : 0.0 Min. : 0.00
-## 1st Qu.: 500.0 1st Qu.:16.67
-## Median : 500.0 Median :16.67
-## Mean : 708.3 Mean :23.61
-## 3rd Qu.: 900.0 3rd Qu.:30.00
-## Max. :2400.0 Max. :80.00
-## NA's :47 NA's :47
+## obs id hhsize meter washingmachine weeklyloads
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. : 0.000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:1.0000 1st Qu.: 2.500
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :1.0000 Median : 2.500
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.9472 Mean : 3.542
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.: 4.500
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :2.0000 Max. :12.000
+## NA's :47
+## combinedwash monthlyWashingMachineUse dailyWashingMachineUse
+## Min. :1 Min. : 0.0 Min. : 0.00
+## 1st Qu.:1 1st Qu.: 500.0 1st Qu.:16.67
+## Median :1 Median : 500.0 Median :16.67
+## Mean :1 Mean : 708.3 Mean :23.61
+## 3rd Qu.:1 3rd Qu.: 900.0 3rd Qu.:30.00
+## Max. :1 Max. :2400.0 Max. :80.00
+## NA's :98 NA's :47 NA's :47
```
```r
@@ -2338,22 +2492,30 @@ summary(totalIntDemand_hh)
```
```
-## id obs.y hhsize.x.x meter.x.x monthlyBathUse monthlyShowerUse monthlyDishwasherUse
-## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. : 0.0 Min. : 0 Min. : 0.00
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.: 598.4 1st Qu.: 1464 1st Qu.: 0.00
-## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median : 792.0 Median : 2808 Median : 0.00
-## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1065.9 Mean : 3210 Mean : 71.18
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:1707.2 3rd Qu.: 4638 3rd Qu.:128.80
-## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :2323.2 Max. :15415 Max. :268.80
-## NA's :53
-## monthlyKitchenSinkUse monthlyWCUse monthlyWashingMachineUse monthlyBathroomSinkUse totalMonthlyInHouseDemand
-## Min. : 227.1 Min. : 750 Min. : 0.0 Min. : 312.0 Min. : 1907
-## 1st Qu.: 454.2 1st Qu.:1500 1st Qu.: 500.0 1st Qu.: 794.4 1st Qu.: 6043
-## Median : 454.2 Median :2250 Median : 500.0 Median : 1191.6 Median : 9167
-## Mean : 603.0 Mean :2739 Mean : 708.3 Mean : 1748.0 Mean :10140
-## 3rd Qu.: 908.4 3rd Qu.:3375 3rd Qu.: 900.0 3rd Qu.: 1986.0 3rd Qu.:13821
-## Max. :2271.0 Max. :7875 Max. :2400.0 Max. :13896.0 Max. :34171
-## NA's :59 NA's :47 NA's :53 NA's :186
+## id obs.y hhsize.x.x meter.x.x monthlyBathUse monthlyShowerUse
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800 Min. : 0.0 Min. : 0
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.: 598.4 1st Qu.: 1464
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character Median : 792.0 Median : 2808
+## Mean :836919052 Mean : 906.0 Mean : 2.655 Mean :1065.9 Mean : 3210
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.:1707.2 3rd Qu.: 4638
+## Max. :836965495 Max. :1810.0 Max. :10.000 Max. :2323.2 Max. :15415
+## NA's :53
+## monthlyDishwasherUse monthlyKitchenSinkUse monthlyWCUse monthlyWashingMachineUse monthlyBathroomSinkUse
+## Min. : 0.00 Min. : 227.1 Min. : 750 Min. : 0.0 Min. : 312.0
+## 1st Qu.: 0.00 1st Qu.: 454.2 1st Qu.:1500 1st Qu.: 500.0 1st Qu.: 794.4
+## Median : 0.00 Median : 454.2 Median :2250 Median : 500.0 Median : 1191.6
+## Mean : 71.18 Mean : 603.0 Mean :2739 Mean : 708.3 Mean : 1748.0
+## 3rd Qu.:128.80 3rd Qu.: 908.4 3rd Qu.:3375 3rd Qu.: 900.0 3rd Qu.: 1986.0
+## Max. :268.80 Max. :2271.0 Max. :7875 Max. :2400.0 Max. :13896.0
+## NA's :59 NA's :47 NA's :53
+## totalMonthlyInHouseDemand
+## Min. : 1907
+## 1st Qu.: 6043
+## Median : 9167
+## Mean :10140
+## 3rd Qu.:13821
+## Max. :34171
+## NA's :186
```
## Estimate External Consumption
@@ -2518,22 +2680,30 @@ summary(CarDemand_hh)
```
```
-## obs id hhsize meter onecar twocars threecars
-## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. :0.0000 Min. :0.0000
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
-## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :0.0000 Median :0.0000 Median :0.0000
-## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.4567 Mean :0.4956 Mean :0.1717
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
-## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :1.0000 Max. :2.0000 Max. :3.0000
-##
-## carwash_freq bucket_wash hose_wash pres_wash CarSum Mean_wash
-## Min. :0.0000 Min. : 0.000 Min. : 0.00 Min. : 0.000 Min. :0.000 Min. : 10.00
-## 1st Qu.:0.0000 1st Qu.: 0.000 1st Qu.: 0.00 1st Qu.: 0.000 1st Qu.:1.000 1st Qu.: 10.00
-## Median :0.2500 Median : 0.000 Median : 0.00 Median : 0.000 Median :1.000 Median : 10.00
-## Mean :0.4543 Mean : 7.567 Mean : 17.22 Mean : 1.467 Mean :1.124 Mean : 31.26
-## 3rd Qu.:0.3300 3rd Qu.:30.000 3rd Qu.: 0.00 3rd Qu.: 0.000 3rd Qu.:2.000 3rd Qu.: 54.00
-## Max. :4.0000 Max. :30.000 Max. :250.00 Max. :132.000 Max. :3.000 Max. :137.33
-## NA's :41 NA's :1296
+## obs id hhsize meter onecar twocars
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800 Min. :0.0000 Min. :0.0000
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character 1st Qu.:0.0000 1st Qu.:0.0000
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character Median :0.0000 Median :0.0000
+## Mean : 906.0 Mean :836919052 Mean : 2.655 Mean :0.4567 Mean :0.4956
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000 3rd Qu.:1.0000 3rd Qu.:0.0000
+## Max. :1810.0 Max. :836965495 Max. :10.000 Max. :1.0000 Max. :2.0000
+##
+## threecars carwash_freq bucket_wash hose_wash pres_wash CarSum
+## Min. :0.0000 Min. :0.0000 Min. : 0.000 Min. : 0.00 Min. : 0.000 Min. :0.000
+## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 0.000 1st Qu.: 0.00 1st Qu.: 0.000 1st Qu.:1.000
+## Median :0.0000 Median :0.2500 Median : 0.000 Median : 0.00 Median : 0.000 Median :1.000
+## Mean :0.1717 Mean :0.4543 Mean : 7.567 Mean : 17.22 Mean : 1.467 Mean :1.124
+## 3rd Qu.:0.0000 3rd Qu.:0.3300 3rd Qu.:30.000 3rd Qu.: 0.00 3rd Qu.: 0.000 3rd Qu.:2.000
+## Max. :3.0000 Max. :4.0000 Max. :30.000 Max. :250.00 Max. :132.000 Max. :3.000
+## NA's :41
+## Mean_wash
+## Min. : 10.00
+## 1st Qu.: 10.00
+## Median : 10.00
+## Mean : 31.26
+## 3rd Qu.: 54.00
+## Max. :137.33
+## NA's :1296
```
```r
@@ -2723,20 +2893,20 @@ summary(kitchen_dish_hh)
```
```
-## id monthlyDishwasherUse dailyDishwasherUse obs.y hhsize.y meter.y monthlyKitchenSinkUse
-## Min. :836900048 Min. : 0.00 Min. :0.000 Min. : 2.0 Min. : 1.000 Length:1800 Min. : 227.1
-## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000 1st Qu.: 454.8 1st Qu.: 2.000 Class :character 1st Qu.: 454.2
-## Median :836920637 Median : 0.00 Median :0.000 Median : 905.5 Median : 2.000 Mode :character Median : 454.2
-## Mean :836919052 Mean : 71.18 Mean :2.373 Mean : 906.0 Mean : 2.655 Mean : 603.0
-## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.: 908.4
-## Max. :836965495 Max. :268.80 Max. :8.960 Max. :1810.0 Max. :10.000 Max. :2271.0
-## dailyKitchenSinkUse
-## Min. : 7.57
-## 1st Qu.:15.14
-## Median :15.14
-## Mean :20.10
-## 3rd Qu.:30.28
-## Max. :75.70
+## id monthlyDishwasherUse dailyDishwasherUse obs.y hhsize.y meter.y
+## Min. :836900048 Min. : 0.00 Min. :0.000 Min. : 2.0 Min. : 1.000 Length:1800
+## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000 1st Qu.: 454.8 1st Qu.: 2.000 Class :character
+## Median :836920637 Median : 0.00 Median :0.000 Median : 905.5 Median : 2.000 Mode :character
+## Mean :836919052 Mean : 71.18 Mean :2.373 Mean : 906.0 Mean : 2.655
+## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293 3rd Qu.:1356.2 3rd Qu.: 4.000
+## Max. :836965495 Max. :268.80 Max. :8.960 Max. :1810.0 Max. :10.000
+## monthlyKitchenSinkUse dailyKitchenSinkUse
+## Min. : 227.1 Min. : 7.57
+## 1st Qu.: 454.2 1st Qu.:15.14
+## Median : 454.2 Median :15.14
+## Mean : 603.0 Mean :20.10
+## 3rd Qu.: 908.4 3rd Qu.:30.28
+## Max. :2271.0 Max. :75.70
```
```r
@@ -2807,12 +2977,12 @@ ggplot(data = totalDemand_hh) +
```r
-ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize)) +
+ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize), colour = meter) +
geom_boxplot() +
labs(title = "total use (l/month)")+labs(title = " total demand (l/household/month)")+ xlab('household size')+ylab('total household demand (l/hh/month)')
```
-<!-- -->
+<!-- -->
```r
@@ -2824,11 +2994,12 @@ ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(me
```r
-ggplot(data=totalDemand_hh)+ aes(y = totalDailyHouseDemandFinal, x = factor(hhsize)) +
- geom_boxplot() +labs(title = " Total demand (l/household/day)")+ xlab('metered or not')+ylab('Total household demand (l/hh/day)')
+totalDemand_hh$totalMonthlyExtHouseDemand <- totalDemand_hh$monthlyCarWashUse + totalDemand_hh$monthlyGardenUse
+ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyExtHouseDemand, x = meter) +
+ geom_boxplot() +labs(title = " Total demand (l/household/month)")+ xlab('Metered')+ylab('Total external monthly household demand (l/hh/month)')
```
-<!-- -->
+<!-- -->
```r
@@ -2921,7 +3092,7 @@ data.table::fwrite(hhDataFinalDaily_v2_0DT, file = oFile)
Data written to:
-> ~/University of Southampton/IMPETUS - Documents/data/model_outputs/model_v2/output-SPRG-1800hh-consumption_2021-03-24_v2_0.csv and (possibly) gzipped
+> ~/University of Southampton/IMPETUS - Documents/data/model_outputs/model_v2/output-SPRG-1800hh-consumption_2021-03-29_v2_0.csv and (possibly) gzipped
@@ -2962,17 +3133,17 @@ st <- str(hhDataFinalDaily_v1_3fDT)
```
## Classes 'data.table' and 'data.frame': 1800 obs. of 12 variables:
-## $ hhid : int 8 28 30 40 41 59 64 66 67 76 ...
+## $ hhid : int 8 16 21 28 30 52 59 64 73 84 ...
## $ occupancy : int 1 1 1 1 1 1 1 1 1 1 ...
## $ metered : chr "Metered" "Metered" "Metered" "Metered" ...
-## $ Basin.baseline : num 20.4 18 18.6 13.5 19.3 ...
-## $ Bath.baseline : num 44.2 56.2 66.9 63.2 65.3 ...
-## $ Dishwasher.baseline : num 21.3 21.3 25.7 20.6 21.8 ...
-## $ KitchenSink.baseline : num 28.9 29.9 29.6 32 28.7 ...
-## $ Shower.baseline : num 27.1 27.9 29.6 31.3 30.9 ...
-## $ WC.baseline : num 77.4 69.5 63.6 83.9 78.3 ...
-## $ WashingMachine.baseline: num 92.1 92.3 73 77.5 98 ...
-## $ External.baseline : num 0 0 0 0 0 ...
+## $ Basin.baseline : num 19.5 15 18.1 13.3 17.5 ...
+## $ Bath.baseline : num 59.4 55.5 51.9 41.7 56.8 ...
+## $ Dishwasher.baseline : num 23.1 21.3 22.3 24.8 23.8 ...
+## $ KitchenSink.baseline : num 30 33.8 31.3 30.4 31.5 ...
+## $ Shower.baseline : num 27 29.1 30.5 26.7 26.8 ...
+## $ WC.baseline : num 88 85.6 94 65.7 68.5 ...
+## $ WashingMachine.baseline: num 77.7 67.3 69.8 73.3 62.2 ...
+## $ External.baseline : num 0 21.8 30.5 11.5 19.7 ...
## $ model : chr "v1_3" "v1_3" "v1_3" "v1_3" ...
## - attr(*, ".internal.selfref")=<externalptr>
## - attr(*, "sorted")= chr [1:2] "metered" "occupancy"
@@ -3321,12 +3492,12 @@ Table: Summary of final household data (litres/day) - model v1_3
| | currYear | currMon | metered | occupancy |sumDaily.baseline.madj |Basin.baseline.madj |Bath.baseline.madj |Dishwasher.baseline.madj |External.baseline.madj |KitchenSink.baseline.madj |Shower.baseline.madj |WC.baseline.madj |WashingMachine.baseline.madj |
|:--|:------------|:--------------|:----------------|:-------------|:----------------------|:-------------------|:------------------|:------------------------|:----------------------|:-------------------------|:--------------------|:----------------|:----------------------------|
-| |Min. :1994 |Min. : 1.000 |Length:433800 |Min. :1.000 |Min. :254.8 |Min. :12.55 |Min. : 34.87 |Min. :13.79 |Min. :-2.511 |Min. :27.42 |Min. :21.20 |Min. : 48.88 |Min. : 57.80 |
-| |1st Qu.:1999 |1st Qu.: 4.000 |Class :character |1st Qu.:1.000 |1st Qu.:346.5 |1st Qu.:19.00 |1st Qu.: 57.95 |1st Qu.:20.96 |1st Qu.:11.227 |1st Qu.:35.05 |1st Qu.:32.88 |1st Qu.: 86.84 |1st Qu.: 74.58 |
-| |Median :2004 |Median : 7.000 |Mode :character |Median :2.000 |Median :425.8 |Median :25.59 |Median : 73.64 |Median :22.45 |Median :16.254 |Median :44.61 |Median :36.96 |Median :110.90 |Median : 82.89 |
-| |Mean :2004 |Mean : 6.523 |NA |Mean :2.407 |Mean :408.8 |Mean :24.46 |Mean : 72.11 |Mean :22.65 |Mean :16.273 |Mean :42.18 |Mean :37.28 |Mean :108.33 |Mean : 85.52 |
-| |3rd Qu.:2009 |3rd Qu.:10.000 |NA |3rd Qu.:3.000 |3rd Qu.:460.3 |3rd Qu.:28.60 |3rd Qu.: 83.97 |3rd Qu.:24.19 |3rd Qu.:23.079 |3rd Qu.:47.60 |3rd Qu.:41.48 |3rd Qu.:127.33 |3rd Qu.: 94.03 |
-| |Max. :2014 |Max. :12.000 |NA |Max. :6.000 |Max. :560.8 |Max. :40.25 |Max. :124.08 |Max. :32.27 |Max. :58.004 |Max. :61.69 |Max. :60.49 |Max. :188.81 |Max. :170.75 |
+| |Min. :1994 |Min. : 1.000 |Length:433800 |Min. :1.000 |Min. :272.7 |Min. :11.68 |Min. : 37.54 |Min. :13.74 |Min. :-2.511 |Min. :27.57 |Min. :20.83 |Min. : 48.10 |Min. : 56.70 |
+| |1st Qu.:1999 |1st Qu.: 4.000 |Class :character |1st Qu.:1.000 |1st Qu.:345.8 |1st Qu.:18.96 |1st Qu.: 57.52 |1st Qu.:20.94 |1st Qu.:11.104 |1st Qu.:34.77 |1st Qu.:32.91 |1st Qu.: 86.44 |1st Qu.: 74.97 |
+| |Median :2004 |Median : 7.000 |Mode :character |Median :2.000 |Median :427.9 |Median :25.71 |Median : 73.73 |Median :22.36 |Median :16.435 |Median :44.61 |Median :37.13 |Median :110.16 |Median : 83.60 |
+| |Mean :2004 |Mean : 6.523 |NA |Mean :2.407 |Mean :408.4 |Mean :24.62 |Mean : 71.55 |Mean :22.63 |Mean :16.077 |Mean :42.15 |Mean :37.39 |Mean :108.00 |Mean : 85.99 |
+| |3rd Qu.:2009 |3rd Qu.:10.000 |NA |3rd Qu.:3.000 |3rd Qu.:459.8 |3rd Qu.:29.06 |3rd Qu.: 83.16 |3rd Qu.:24.16 |3rd Qu.:22.796 |3rd Qu.:47.69 |3rd Qu.:41.75 |3rd Qu.:127.37 |3rd Qu.: 94.77 |
+| |Max. :2014 |Max. :12.000 |NA |Max. :6.000 |Max. :561.1 |Max. :44.91 |Max. :125.70 |Max. :33.99 |Max. :54.834 |Max. :60.77 |Max. :60.52 |Max. :189.84 |Max. :145.57 |
```r
kable(caption = "Summary of final household data (litres/day) - model v2_0",
@@ -3584,8 +3755,8 @@ Table: Summary of results
|model |metered | dailyMean| dailyMeanPcc|
|:-----|:-----------|---------:|------------:|
-|v1_3 |Not metered | 454.1061| 249.1422|
-|v1_3 |Metered | 340.8619| 191.8263|
+|v1_3 |Not metered | 454.9823| 250.5077|
+|v1_3 |Metered | 338.5436| 189.4032|
|v2_0 |Not metered | 362.7737| 133.9713|
|v2_0 |Metered | 336.4506| 139.7480|
@@ -4020,12 +4191,13 @@ names(baselineWE_DT)
```
```
-## [1] "currYear" "currMon" "hhid" "model"
-## [5] "obsDate" "occupancy" "metered" "Basin.baseline.madj"
-## [9] "Bath.baseline.madj" "Dishwasher.baseline.madj" "External.baseline.madj" "KitchenSink.baseline.madj"
-## [13] "Shower.baseline.madj" "WC.baseline.madj" "WashingMachine.baseline.madj" "sumDaily.baseline.madj"
-## [17] "occRed" "loWC" "loSh" "dualFlushWC"
-## [21] "loFlowShower"
+## [1] "currYear" "currMon" "hhid"
+## [4] "model" "obsDate" "occupancy"
+## [7] "metered" "Basin.baseline.madj" "Bath.baseline.madj"
+## [10] "Dishwasher.baseline.madj" "External.baseline.madj" "KitchenSink.baseline.madj"
+## [13] "Shower.baseline.madj" "WC.baseline.madj" "WashingMachine.baseline.madj"
+## [16] "sumDaily.baseline.madj" "occRed" "loWC"
+## [19] "loSh" "dualFlushWC" "loFlowShower"
```
@@ -4098,8 +4270,8 @@ baselineWE_DT[, .(mean_sumDaily = mean(sumDaily.baseline.madj, na.rm = TRUE),
```
## model metered mean_sumDaily mean_WC mean_shower
-## 1: v1_3 Metered 340.8619 84.54052 32.31327
-## 2: v1_3 Not metered 454.1061 124.18930 40.58952
+## 1: v1_3 Metered 338.5436 83.03458 32.35519
+## 2: v1_3 Not metered 454.9823 124.63944 40.75476
## 3: v2_0 Metered 336.4506 83.91561 102.24988
## 4: v2_0 Not metered 362.7737 92.13191 109.05040
## 5: v2_1 Metered 336.4506 83.91561 102.24988
@@ -4135,12 +4307,12 @@ baselineWE_DT[, .(mean_sumDaily = mean(sumDaily.baseline.madj.we, na.rm = TRUE),
```
## model metered mean_sumDaily mean_WC mean_shower
-## 1: v1_3 Metered 330.3141 75.26894 31.03697
-## 2: v1_3 Not metered 438.9518 110.62445 39.00004
-## 3: v2_0 Metered 323.3260 74.72015 98.26638
-## 4: v2_0 Not metered 348.3528 82.03014 104.77559
-## 5: v2_1 Metered 312.4606 63.74666 98.26616
-## 6: v2_1 Not metered 336.2035 69.96383 104.71251
+## 1: v1_3 Metered 328.1783 73.94774 31.07670
+## 2: v1_3 Not metered 439.7477 111.00402 39.15561
+## 3: v2_0 Metered 323.2413 74.73259 98.17426
+## 4: v2_0 Not metered 348.3415 82.03952 104.75750
+## 5: v2_1 Metered 312.3911 63.70172 98.24216
+## 6: v2_1 Not metered 336.2510 69.96768 104.77145
```
@@ -5063,21 +5235,21 @@ Table: Data summary
|currMon | 0| 1.00| 6.52| 3.46| 1.00| 4.00| 7.00| 10.00| 12.00|▇▅▅▅▇ |
|hhid | 0| 1.00| 539553760.00| 400555167.51| 1.00| 1267.00| 836910431.00| 836921421.00| 836965495.00|▅▁▁▁▇ |
|occupancy | 0| 1.00| 2.54| 1.35| 1.00| 2.00| 2.00| 3.00| 10.00|▇▅▁▁▁ |
-|Basin.baseline.madj | 24100| 0.98| 45.36| 45.09| 10.33| 23.90| 27.53| 52.93| 463.65|▇▁▁▁▁ |
-|Bath.baseline.madj | 0| 1.00| 47.44| 26.02| -3.95| 25.23| 46.80| 65.84| 124.08|▅▇▇▅▁ |
-|Dishwasher.baseline.madj | 0| 1.00| 9.19| 10.42| -2.18| -0.17| 4.26| 21.24| 32.27|▇▂▁▅▁ |
-|External.baseline.madj | 80494| 0.93| 19.09| 16.43| -2.51| 1.42| 17.45| 27.90| 98.17|▇▆▂▁▁ |
-|KitchenSink.baseline.madj | 0| 1.00| 27.82| 14.11| 7.47| 15.28| 30.27| 38.21| 76.12|▇▇▆▂▁ |
-|Shower.baseline.madj | 23136| 0.98| 81.02| 69.38| -0.24| 35.74| 48.82| 114.49| 515.30|▇▂▁▁▁ |
-|WC.baseline.madj | 25546| 0.98| 95.56| 41.94| 20.64| 71.64| 92.52| 123.20| 262.81|▃▇▅▁▁ |
-|WashingMachine.baseline.madj | 16870| 0.99| 45.81| 33.90| -3.24| 15.90| 31.04| 77.68| 170.75|▇▂▅▁▁ |
-|sumDaily.baseline.madj | 80494| 0.93| 372.70| 151.37| 53.53| 272.66| 367.46| 463.51| 1153.15|▃▇▂▁▁ |
+|Basin.baseline.madj | 24100| 0.98| 45.42| 45.07| 10.33| 23.85| 27.92| 52.93| 463.65|▇▁▁▁▁ |
+|Bath.baseline.madj | 0| 1.00| 47.24| 25.71| -3.95| 25.23| 46.81| 65.67| 125.70|▅▇▇▅▁ |
+|Dishwasher.baseline.madj | 0| 1.00| 9.18| 10.41| -2.18| -0.17| 4.26| 21.21| 33.99|▇▂▁▅▁ |
+|External.baseline.madj | 80494| 0.93| 19.01| 16.45| -2.51| 1.34| 17.47| 27.73| 98.17|▇▆▂▁▁ |
+|KitchenSink.baseline.madj | 0| 1.00| 27.81| 14.10| 7.47| 15.28| 30.27| 38.20| 76.12|▇▇▆▂▁ |
+|Shower.baseline.madj | 23136| 0.98| 81.07| 69.35| -0.24| 35.99| 48.84| 114.49| 515.30|▇▂▁▁▁ |
+|WC.baseline.madj | 25546| 0.98| 95.44| 42.02| 20.64| 71.54| 91.89| 123.33| 262.81|▃▇▃▁▁ |
+|WashingMachine.baseline.madj | 16870| 0.99| 45.98| 34.14| -3.24| 15.90| 31.04| 78.16| 145.57|▇▅▅▃▁ |
+|sumDaily.baseline.madj | 80494| 0.93| 372.54| 151.48| 53.53| 272.85| 366.08| 463.13| 1153.15|▃▇▂▁▁ |
|occRed | 0| 1.00| 2.53| 1.34| 1.00| 2.00| 2.00| 3.00| 6.00|▇▂▂▁▁ |
|loWC | 0| 1.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00|▁▁▇▁▁ |
|loSh | 0| 1.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00|▁▁▇▁▁ |
-|WC.baseline.madj.we | 25546| 0.98| 81.41| 43.51| 9.81| 45.45| 74.06| 112.14| 262.81|▇▇▅▁▁ |
-|Shower.baseline.madj.we | 23136| 0.98| 77.84| 67.82| -0.24| 34.33| 48.49| 109.47| 515.30|▇▂▁▁▁ |
-|sumDaily.baseline.madj.we | 80494| 0.93| 355.49| 147.28| 35.59| 255.98| 351.39| 448.97| 1153.15|▃▇▂▁▁ |
+|WC.baseline.madj.we | 25546| 0.98| 81.30| 43.54| 9.70| 45.43| 74.05| 112.04| 262.81|▇▇▅▁▁ |
+|Shower.baseline.madj.we | 23136| 0.98| 77.87| 67.76| -0.24| 34.48| 48.54| 109.47| 515.30|▇▂▁▁▁ |
+|sumDaily.baseline.madj.we | 80494| 0.93| 355.33| 147.33| 36.05| 255.76| 350.95| 449.75| 1152.91|▃▇▂▁▁ |
Import the CEH drought histories.
@@ -6013,7 +6185,7 @@ with(baselineWE_DR_DT[model == "v1_3"], table(dualFlushWC,dualFlushWCdr))
## dualFlushWCdr
## dualFlushWC Dual flush Single flush
## Dual flush 71958 0
-## Single flush 11 316831
+## Single flush 51 316791
```
```r
@@ -6032,7 +6204,7 @@ with(baselineWE_DR_DT[model == "v2_0"], table(dualFlushWC,dualFlushWCdr))
## dualFlushWCdr
## dualFlushWC Dual flush Single flush
## Dual flush 65271 0
-## Single flush 43 287414
+## Single flush 39 287418
```
```r
@@ -6051,7 +6223,7 @@ with(baselineWE_DR_DT[model == "v2_1"], table(dualFlushWC,dualFlushWCdr))
## dualFlushWCdr
## dualFlushWC Dual flush Single flush
## Dual flush 143408 0
-## Single flush 19 209301
+## Single flush 0 209320
```
Test the results
@@ -6190,233 +6362,233 @@ for(y in minYear:maxYear){
## [1] "Updating low flow shower uptake for year: 1995 & month 4 (2. Developing)"
## [1] "N cases selected: 5039"
## [1] "Updating low flow shower uptake for year: 1995 & month 5 (2. Developing)"
-## [1] "N cases selected: 5026"
+## [1] "N cases selected: 5025"
## [1] "Updating low flow shower uptake for year: 1995 & month 6 (2. Developing)"
-## [1] "N cases selected: 5015"
+## [1] "N cases selected: 5014"
## [1] "Updating low flow shower uptake for year: 1995 & month 7 (2. Developing)"
## [1] "N cases selected: 5002"
## [1] "Updating low flow shower uptake for year: 1995 & month 8 (2. Developing)"
-## [1] "N cases selected: 4989"
+## [1] "N cases selected: 4990"
## [1] "Updating low flow shower uptake for year: 1995 & month 9 (3. Drought)"
-## [1] "N cases selected: 4978"
+## [1] "N cases selected: 4977"
## [1] "Updating low flow shower uptake for year: 1995 & month 10 (3. Drought)"
## [1] "N cases selected: 4962"
## [1] "Updating low flow shower uptake for year: 1995 & month 11 (3. Drought)"
## [1] "N cases selected: 4946"
## [1] "Updating low flow shower uptake for year: 1995 & month 12 (2. Developing)"
-## [1] "N cases selected: 4931"
+## [1] "N cases selected: 4930"
## [1] "Year: 1996"
## [1] "Updating low flow shower uptake for year: 1996 & month 1 (2. Developing)"
## [1] "N cases selected: 4917"
## [1] "Updating low flow shower uptake for year: 1996 & month 2 (2. Developing)"
-## [1] "N cases selected: 4906"
+## [1] "N cases selected: 4904"
## [1] "Updating low flow shower uptake for year: 1996 & month 3 (3. Drought)"
-## [1] "N cases selected: 4895"
+## [1] "N cases selected: 4892"
## [1] "Updating low flow shower uptake for year: 1996 & month 4 (3. Drought)"
-## [1] "N cases selected: 4878"
+## [1] "N cases selected: 4875"
## [1] "Updating low flow shower uptake for year: 1996 & month 5 (3. Drought)"
-## [1] "N cases selected: 4861"
+## [1] "N cases selected: 4863"
## [1] "Updating low flow shower uptake for year: 1996 & month 6 (3. Drought)"
## [1] "N cases selected: 4848"
## [1] "Updating low flow shower uptake for year: 1996 & month 7 (3. Drought)"
-## [1] "N cases selected: 4831"
+## [1] "N cases selected: 4829"
## [1] "Updating low flow shower uptake for year: 1996 & month 8 (3. Drought)"
-## [1] "N cases selected: 4813"
+## [1] "N cases selected: 4812"
## [1] "Updating low flow shower uptake for year: 1996 & month 9 (3. Drought)"
-## [1] "N cases selected: 4799"
+## [1] "N cases selected: 4800"
## [1] "Updating low flow shower uptake for year: 1996 & month 10 (3. Drought)"
## [1] "N cases selected: 4783"
## [1] "Updating low flow shower uptake for year: 1996 & month 11 (3. Drought)"
-## [1] "N cases selected: 4767"
+## [1] "N cases selected: 4766"
## [1] "Updating low flow shower uptake for year: 1996 & month 12 (4. Severe Drought)"
-## [1] "N cases selected: 4754"
+## [1] "N cases selected: 4751"
## [1] "Year: 1997"
## [1] "Updating low flow shower uptake for year: 1997 & month 1 (4. Severe Drought)"
-## [1] "N cases selected: 4732"
+## [1] "N cases selected: 4734"
## [1] "Updating low flow shower uptake for year: 1997 & month 2 (4. Severe Drought)"
-## [1] "N cases selected: 4715"
+## [1] "N cases selected: 4716"
## [1] "Updating low flow shower uptake for year: 1997 & month 3 (4. Severe Drought)"
-## [1] "N cases selected: 4695"
+## [1] "N cases selected: 4699"
## [1] "Updating low flow shower uptake for year: 1997 & month 4 (4. Severe Drought)"
-## [1] "N cases selected: 4682"
+## [1] "N cases selected: 4675"
## [1] "Updating low flow shower uptake for year: 1997 & month 5 (4. Severe Drought)"
-## [1] "N cases selected: 4661"
+## [1] "N cases selected: 4658"
## [1] "Updating low flow shower uptake for year: 1997 & month 6 (5. Recovering)"
-## [1] "N cases selected: 4640"
+## [1] "N cases selected: 4639"
## [1] "Updating low flow shower uptake for year: 1997 & month 7 (5. Recovering)"
-## [1] "N cases selected: 4633"
+## [1] "N cases selected: 4630"
## [1] "Updating low flow shower uptake for year: 1997 & month 8 (5. Recovering)"
-## [1] "N cases selected: 4624"
+## [1] "N cases selected: 4619"
## [1] "Updating low flow shower uptake for year: 1997 & month 9 (4. Severe Drought)"
-## [1] "N cases selected: 4605"
+## [1] "N cases selected: 4606"
## [1] "Updating low flow shower uptake for year: 1997 & month 10 (4. Severe Drought)"
-## [1] "N cases selected: 4595"
+## [1] "N cases selected: 4592"
## [1] "Updating low flow shower uptake for year: 1997 & month 11 (4. Severe Drought)"
-## [1] "N cases selected: 4569"
+## [1] "N cases selected: 4577"
## [1] "Updating low flow shower uptake for year: 1997 & month 12 (5. Recovering)"
-## [1] "N cases selected: 4551"
+## [1] "N cases selected: 4554"
## [1] "Year: 1998"
## [1] "Updating low flow shower uptake for year: 1998 & month 1 (5. Recovering)"
-## [1] "N cases selected: 4543"
+## [1] "N cases selected: 4547"
## [1] "Updating low flow shower uptake for year: 1998 & month 2 (5. Recovering)"
## [1] "N cases selected: 4528"
## [1] "Updating low flow shower uptake for year: 1998 & month 3 (5. Recovering)"
-## [1] "N cases selected: 4522"
+## [1] "N cases selected: 4517"
## [1] "Updating low flow shower uptake for year: 1998 & month 4 (5. Recovering)"
-## [1] "N cases selected: 4510"
+## [1] "N cases selected: 4519"
## [1] "Updating low flow shower uptake for year: 1998 & month 5 (5. Recovering)"
-## [1] "N cases selected: 4503"
+## [1] "N cases selected: 4498"
## [1] "Updating low flow shower uptake for year: 1998 & month 6 (5. Recovering)"
-## [1] "N cases selected: 4488"
+## [1] "N cases selected: 4486"
## [1] "Updating low flow shower uptake for year: 1998 & month 7 (5. Recovering)"
-## [1] "N cases selected: 4479"
+## [1] "N cases selected: 4481"
## [1] "Updating low flow shower uptake for year: 1998 & month 8 (5. Recovering)"
-## [1] "N cases selected: 4475"
+## [1] "N cases selected: 4464"
## [1] "Updating low flow shower uptake for year: 1998 & month 9 (5. Recovering)"
-## [1] "N cases selected: 4456"
+## [1] "N cases selected: 4451"
## [1] "Updating low flow shower uptake for year: 1998 & month 10 (5. Recovering)"
-## [1] "N cases selected: 4444"
+## [1] "N cases selected: 4455"
## [1] "Updating low flow shower uptake for year: 1998 & month 11 (5. Recovering)"
-## [1] "N cases selected: 4445"
+## [1] "N cases selected: 4436"
## [1] "Year: 1999"
## [1] "Year: 2000"
## [1] "Year: 2001"
## [1] "Year: 2002"
## [1] "Year: 2003"
## [1] "Updating low flow shower uptake for year: 2003 & month 3 (2. Developing)"
-## [1] "N cases selected: 4225"
+## [1] "N cases selected: 4216"
## [1] "Updating low flow shower uptake for year: 2003 & month 4 (2. Developing)"
-## [1] "N cases selected: 4217"
+## [1] "N cases selected: 4222"
## [1] "Updating low flow shower uptake for year: 2003 & month 5 (2. Developing)"
-## [1] "N cases selected: 4212"
+## [1] "N cases selected: 4201"
## [1] "Updating low flow shower uptake for year: 2003 & month 6 (2. Developing)"
-## [1] "N cases selected: 4210"
+## [1] "N cases selected: 4200"
## [1] "Updating low flow shower uptake for year: 2003 & month 7 (2. Developing)"
-## [1] "N cases selected: 4192"
+## [1] "N cases selected: 4186"
## [1] "Updating low flow shower uptake for year: 2003 & month 8 (2. Developing)"
-## [1] "N cases selected: 4180"
+## [1] "N cases selected: 4178"
## [1] "Updating low flow shower uptake for year: 2003 & month 9 (3. Drought)"
-## [1] "N cases selected: 4180"
+## [1] "N cases selected: 4160"
## [1] "Updating low flow shower uptake for year: 2003 & month 10 (3. Drought)"
-## [1] "N cases selected: 4154"
+## [1] "N cases selected: 4159"
## [1] "Updating low flow shower uptake for year: 2003 & month 11 (3. Drought)"
-## [1] "N cases selected: 4147"
+## [1] "N cases selected: 4152"
## [1] "Updating low flow shower uptake for year: 2003 & month 12 (5. Recovering)"
-## [1] "N cases selected: 4132"
+## [1] "N cases selected: 4135"
## [1] "Year: 2004"
## [1] "Updating low flow shower uptake for year: 2004 & month 1 (5. Recovering)"
-## [1] "N cases selected: 4126"
+## [1] "N cases selected: 4124"
## [1] "Updating low flow shower uptake for year: 2004 & month 2 (5. Recovering)"
-## [1] "N cases selected: 4110"
+## [1] "N cases selected: 4116"
## [1] "Updating low flow shower uptake for year: 2004 & month 12 (2. Developing)"
-## [1] "N cases selected: 4080"
+## [1] "N cases selected: 4068"
## [1] "Year: 2005"
## [1] "Updating low flow shower uptake for year: 2005 & month 1 (2. Developing)"
-## [1] "N cases selected: 4070"
-## [1] "Updating low flow shower uptake for year: 2005 & month 2 (2. Developing)"
## [1] "N cases selected: 4052"
+## [1] "Updating low flow shower uptake for year: 2005 & month 2 (2. Developing)"
+## [1] "N cases selected: 4058"
## [1] "Updating low flow shower uptake for year: 2005 & month 3 (2. Developing)"
-## [1] "N cases selected: 4045"
+## [1] "N cases selected: 4044"
## [1] "Updating low flow shower uptake for year: 2005 & month 4 (2. Developing)"
-## [1] "N cases selected: 4030"
+## [1] "N cases selected: 4034"
## [1] "Updating low flow shower uptake for year: 2005 & month 5 (2. Developing)"
-## [1] "N cases selected: 4028"
+## [1] "N cases selected: 4016"
## [1] "Updating low flow shower uptake for year: 2005 & month 6 (5. Recovering)"
-## [1] "N cases selected: 4021"
+## [1] "N cases selected: 4012"
## [1] "Updating low flow shower uptake for year: 2005 & month 7 (5. Recovering)"
-## [1] "N cases selected: 4006"
+## [1] "N cases selected: 4002"
## [1] "Updating low flow shower uptake for year: 2005 & month 8 (5. Recovering)"
-## [1] "N cases selected: 3998"
+## [1] "N cases selected: 4009"
## [1] "Updating low flow shower uptake for year: 2005 & month 9 (2. Developing)"
-## [1] "N cases selected: 3989"
+## [1] "N cases selected: 3984"
## [1] "Updating low flow shower uptake for year: 2005 & month 10 (2. Developing)"
-## [1] "N cases selected: 3977"
+## [1] "N cases selected: 3971"
## [1] "Updating low flow shower uptake for year: 2005 & month 11 (2. Developing)"
-## [1] "N cases selected: 3968"
+## [1] "N cases selected: 3969"
## [1] "Updating low flow shower uptake for year: 2005 & month 12 (3. Drought)"
-## [1] "N cases selected: 3970"
+## [1] "N cases selected: 3963"
## [1] "Year: 2006"
## [1] "Updating low flow shower uptake for year: 2006 & month 1 (3. Drought)"
-## [1] "N cases selected: 3944"
+## [1] "N cases selected: 3949"
## [1] "Updating low flow shower uptake for year: 2006 & month 2 (3. Drought)"
-## [1] "N cases selected: 3946"
+## [1] "N cases selected: 3940"
## [1] "Updating low flow shower uptake for year: 2006 & month 3 (3. Drought)"
-## [1] "N cases selected: 3927"
+## [1] "N cases selected: 3908"
## [1] "Updating low flow shower uptake for year: 2006 & month 4 (3. Drought)"
-## [1] "N cases selected: 3923"
+## [1] "N cases selected: 3914"
## [1] "Updating low flow shower uptake for year: 2006 & month 5 (3. Drought)"
-## [1] "N cases selected: 3896"
+## [1] "N cases selected: 3891"
## [1] "Updating low flow shower uptake for year: 2006 & month 6 (5. Recovering)"
-## [1] "N cases selected: 3894"
+## [1] "N cases selected: 3896"
## [1] "Updating low flow shower uptake for year: 2006 & month 7 (5. Recovering)"
-## [1] "N cases selected: 3884"
+## [1] "N cases selected: 3873"
## [1] "Updating low flow shower uptake for year: 2006 & month 8 (5. Recovering)"
-## [1] "N cases selected: 3876"
+## [1] "N cases selected: 3872"
## [1] "Updating low flow shower uptake for year: 2006 & month 9 (5. Recovering)"
-## [1] "N cases selected: 3873"
+## [1] "N cases selected: 3859"
## [1] "Updating low flow shower uptake for year: 2006 & month 10 (5. Recovering)"
-## [1] "N cases selected: 3850"
+## [1] "N cases selected: 3869"
## [1] "Updating low flow shower uptake for year: 2006 & month 11 (5. Recovering)"
-## [1] "N cases selected: 3843"
+## [1] "N cases selected: 3848"
## [1] "Updating low flow shower uptake for year: 2006 & month 12 (5. Recovering)"
-## [1] "N cases selected: 3839"
+## [1] "N cases selected: 3849"
## [1] "Year: 2007"
## [1] "Updating low flow shower uptake for year: 2007 & month 1 (5. Recovering)"
-## [1] "N cases selected: 3830"
+## [1] "N cases selected: 3837"
## [1] "Updating low flow shower uptake for year: 2007 & month 2 (5. Recovering)"
-## [1] "N cases selected: 3812"
+## [1] "N cases selected: 3827"
## [1] "Year: 2008"
## [1] "Year: 2009"
## [1] "Updating low flow shower uptake for year: 2009 & month 3 (2. Developing)"
-## [1] "N cases selected: 3729"
+## [1] "N cases selected: 3706"
## [1] "Updating low flow shower uptake for year: 2009 & month 4 (2. Developing)"
-## [1] "N cases selected: 3721"
-## [1] "Updating low flow shower uptake for year: 2009 & month 5 (2. Developing)"
## [1] "N cases selected: 3706"
+## [1] "Updating low flow shower uptake for year: 2009 & month 5 (2. Developing)"
+## [1] "N cases selected: 3703"
## [1] "Updating low flow shower uptake for year: 2009 & month 6 (2. Developing)"
-## [1] "N cases selected: 3688"
+## [1] "N cases selected: 3709"
## [1] "Updating low flow shower uptake for year: 2009 & month 7 (2. Developing)"
-## [1] "N cases selected: 3674"
+## [1] "N cases selected: 3684"
## [1] "Updating low flow shower uptake for year: 2009 & month 8 (2. Developing)"
-## [1] "N cases selected: 3679"
+## [1] "N cases selected: 3657"
## [1] "Updating low flow shower uptake for year: 2009 & month 9 (3. Drought)"
-## [1] "N cases selected: 3676"
+## [1] "N cases selected: 3677"
## [1] "Updating low flow shower uptake for year: 2009 & month 10 (3. Drought)"
-## [1] "N cases selected: 3665"
+## [1] "N cases selected: 3675"
## [1] "Updating low flow shower uptake for year: 2009 & month 11 (3. Drought)"
-## [1] "N cases selected: 3649"
+## [1] "N cases selected: 3652"
## [1] "Updating low flow shower uptake for year: 2009 & month 12 (5. Recovering)"
-## [1] "N cases selected: 3647"
+## [1] "N cases selected: 3627"
## [1] "Year: 2010"
## [1] "Updating low flow shower uptake for year: 2010 & month 1 (5. Recovering)"
-## [1] "N cases selected: 3635"
+## [1] "N cases selected: 3623"
## [1] "Updating low flow shower uptake for year: 2010 & month 2 (5. Recovering)"
-## [1] "N cases selected: 3631"
+## [1] "N cases selected: 3624"
## [1] "Updating low flow shower uptake for year: 2010 & month 9 (2. Developing)"
-## [1] "N cases selected: 3591"
+## [1] "N cases selected: 3584"
## [1] "Updating low flow shower uptake for year: 2010 & month 10 (2. Developing)"
-## [1] "N cases selected: 3590"
+## [1] "N cases selected: 3602"
## [1] "Updating low flow shower uptake for year: 2010 & month 11 (2. Developing)"
-## [1] "N cases selected: 3578"
+## [1] "N cases selected: 3579"
## [1] "Updating low flow shower uptake for year: 2010 & month 12 (2. Developing)"
-## [1] "N cases selected: 3575"
+## [1] "N cases selected: 3570"
## [1] "Year: 2011"
## [1] "Updating low flow shower uptake for year: 2011 & month 1 (2. Developing)"
-## [1] "N cases selected: 3569"
+## [1] "N cases selected: 3563"
## [1] "Updating low flow shower uptake for year: 2011 & month 2 (2. Developing)"
## [1] "N cases selected: 3549"
## [1] "Updating low flow shower uptake for year: 2011 & month 3 (3. Drought)"
-## [1] "N cases selected: 3545"
+## [1] "N cases selected: 3547"
## [1] "Updating low flow shower uptake for year: 2011 & month 4 (3. Drought)"
-## [1] "N cases selected: 3537"
+## [1] "N cases selected: 3530"
## [1] "Updating low flow shower uptake for year: 2011 & month 5 (3. Drought)"
-## [1] "N cases selected: 3509"
+## [1] "N cases selected: 3524"
## [1] "Updating low flow shower uptake for year: 2011 & month 6 (5. Recovering)"
-## [1] "N cases selected: 3519"
+## [1] "N cases selected: 3520"
## [1] "Updating low flow shower uptake for year: 2011 & month 7 (5. Recovering)"
-## [1] "N cases selected: 3501"
+## [1] "N cases selected: 3509"
## [1] "Updating low flow shower uptake for year: 2011 & month 8 (5. Recovering)"
-## [1] "N cases selected: 3507"
+## [1] "N cases selected: 3505"
## [1] "Year: 2012"
```
@@ -6436,7 +6608,7 @@ table(baselineWE_DR_DT$loFlowShower, baselineWE_DR_DT$loFlowShowerDr)
##
## Low flow Normal flow
## Low flow 98670 0
-## Normal flow 103091 892495
+## Normal flow 103447 892139
```
@@ -6544,8 +6716,8 @@ for(y in minYear:maxYear){
## [1] "Year: 1994"
## [1] "Year: 1995"
## [1] "Applying TUB for year: 1995, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.0209782834374"
-## [1] "Top 28% cut: 21.7793992685707"
+## [1] "Top 14% cut: 26.5860413287535"
+## [1] "Top 28% cut: 21.3731258984767"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1995, month 9 & model v2_0 (3. Drought)"
@@ -6559,8 +6731,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1995, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.089484491569"
-## [1] "Top 28% cut: 21.9900915298826"
+## [1] "Top 14% cut: 26.713836335934"
+## [1] "Top 28% cut: 21.5699235514826"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1995, month 10 & model v2_0 (3. Drought)"
@@ -6574,8 +6746,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1995, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.012933780435"
-## [1] "Top 28% cut: 21.879648944339"
+## [1] "Top 14% cut: 26.5970996692674"
+## [1] "Top 28% cut: 21.4717305754455"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1995, month 11 & model v2_0 (3. Drought)"
@@ -6590,8 +6762,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected for TUB: 90"
## [1] "Year: 1996"
## [1] "Applying TUB for year: 1996, month 3 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.3633951045177"
-## [1] "Top 28% cut: 22.1426556025845"
+## [1] "Top 14% cut: 26.9898609721129"
+## [1] "Top 28% cut: 21.7926184896391"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 3 & model v2_0 (3. Drought)"
@@ -6605,8 +6777,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 4 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.5439852307267"
-## [1] "Top 28% cut: 22.3501556025845"
+## [1] "Top 14% cut: 27.1700893334081"
+## [1] "Top 28% cut: 21.9642305656103"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 4 & model v2_0 (3. Drought)"
@@ -6620,8 +6792,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 5 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.7348698194874"
-## [1] "Top 28% cut: 22.4823959352374"
+## [1] "Top 14% cut: 27.3704168798647"
+## [1] "Top 28% cut: 22.1151145311506"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 5 & model v2_0 (3. Drought)"
@@ -6635,8 +6807,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 6 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 28.3425498194874"
-## [1] "Top 28% cut: 23.10822969399"
+## [1] "Top 14% cut: 27.9788182485187"
+## [1] "Top 28% cut: 22.752683829755"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 6 & model v2_0 (3. Drought)"
@@ -6650,8 +6822,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 7 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 28.1922316167708"
-## [1] "Top 28% cut: 22.9506526019041"
+## [1] "Top 14% cut: 27.7989795092292"
+## [1] "Top 28% cut: 22.54437923181"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 7 & model v2_0 (3. Drought)"
@@ -6665,8 +6837,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 8 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.6771148680466"
-## [1] "Top 28% cut: 22.3882254096416"
+## [1] "Top 14% cut: 27.2538043917333"
+## [1] "Top 28% cut: 22.0052891216358"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 8 & model v2_0 (3. Drought)"
@@ -6680,8 +6852,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.4429066641819"
-## [1] "Top 28% cut: 22.2202523638809"
+## [1] "Top 14% cut: 27.0950476387795"
+## [1] "Top 28% cut: 21.8813090801927"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 9 & model v2_0 (3. Drought)"
@@ -6695,8 +6867,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.9173933293586"
-## [1] "Top 28% cut: 21.725384033293"
+## [1] "Top 14% cut: 26.5317552342067"
+## [1] "Top 28% cut: 21.3683384501934"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 10 & model v2_0 (3. Drought)"
@@ -6710,8 +6882,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.6773444641819"
-## [1] "Top 28% cut: 21.4536222692512"
+## [1] "Top 14% cut: 26.3125176387795"
+## [1] "Top 28% cut: 21.1120019563058"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 1996, month 11 & model v2_0 (3. Drought)"
@@ -6725,8 +6897,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 1996, month 12 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.1450645960253"
-## [1] "Top 28% cut: 21.9527024229792"
+## [1] "Top 14% cut: 26.7616819008734"
+## [1] "Top 28% cut: 21.5866659168601"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1996, month 12 & model v2_0 (4. Severe Drought)"
@@ -6741,8 +6913,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected for TUB: 180"
## [1] "Year: 1997"
## [1] "Applying TUB for year: 1997, month 1 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.232004491569"
-## [1] "Top 28% cut: 22.1206184817447"
+## [1] "Top 14% cut: 26.856356335934"
+## [1] "Top 28% cut: 21.7124435514826"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 1 & model v2_0 (4. Severe Drought)"
@@ -6756,8 +6928,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 2 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.3545393159083"
-## [1] "Top 28% cut: 22.1612213775857"
+## [1] "Top 14% cut: 26.9624218667413"
+## [1] "Top 28% cut: 21.7639938825689"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 2 & model v2_0 (4. Severe Drought)"
@@ -6771,8 +6943,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 3 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.6023664861541"
-## [1] "Top 28% cut: 22.3816997761577"
+## [1] "Top 14% cut: 27.2685543054462"
+## [1] "Top 28% cut: 22.0396828041461"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 3 & model v2_0 (4. Severe Drought)"
@@ -6786,8 +6958,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 4 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.5458377045177"
-## [1] "Top 28% cut: 22.3270389359179"
+## [1] "Top 14% cut: 27.1719876387795"
+## [1] "Top 28% cut: 21.9753770229725"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 4 & model v2_0 (4. Severe Drought)"
@@ -6801,8 +6973,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 5 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.8551949501041"
-## [1] "Top 28% cut: 22.6136159352374"
+## [1] "Top 14% cut: 27.4185926708734"
+## [1] "Top 28% cut: 22.1907226815871"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 5 & model v2_0 (4. Severe Drought)"
@@ -6816,8 +6988,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 9 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 27.5650464861541"
-## [1] "Top 28% cut: 22.3443797761577"
+## [1] "Top 14% cut: 27.2312343054462"
+## [1] "Top 28% cut: 22.0023628041461"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 9 & model v2_0 (4. Severe Drought)"
@@ -6831,8 +7003,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 10 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 26.898164662692"
-## [1] "Top 28% cut: 21.7030367398966"
+## [1] "Top 14% cut: 26.5091309153317"
+## [1] "Top 28% cut: 21.3148186446808"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 10 & model v2_0 (4. Severe Drought)"
@@ -6846,8 +7018,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 411"
## [1] "N cases selected for TUB: 180"
## [1] "Applying TUB for year: 1997, month 11 & model v1_3 (4. Severe Drought)"
-## [1] "Top 14% cut: 26.853504491569"
-## [1] "Top 28% cut: 21.7246543059845"
+## [1] "Top 14% cut: 26.477856335934"
+## [1] "Top 28% cut: 21.3339435514826"
## [1] "N cases selected: 504"
## [1] "N cases selected for TUB: 221"
## [1] "Applying TUB for year: 1997, month 11 & model v2_0 (4. Severe Drought)"
@@ -6867,8 +7039,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2002"
## [1] "Year: 2003"
## [1] "Applying TUB for year: 2003, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.6334398194874"
-## [1] "Top 28% cut: 22.4034984212959"
+## [1] "Top 14% cut: 27.2996276387795"
+## [1] "Top 28% cut: 22.0707561374794"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2003, month 9 & model v2_0 (3. Drought)"
@@ -6882,8 +7054,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2003, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.953940862692"
-## [1] "Top 28% cut: 21.7694910477533"
+## [1] "Top 14% cut: 26.5711605265454"
+## [1] "Top 28% cut: 21.4076742641864"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2003, month 10 & model v2_0 (3. Drought)"
@@ -6897,8 +7069,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2003, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.761549662692"
-## [1] "Top 28% cut: 21.5683700732299"
+## [1] "Top 14% cut: 26.3624959153317"
+## [1] "Top 28% cut: 21.1662353113474"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2003, month 11 & model v2_0 (3. Drought)"
@@ -6914,8 +7086,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2004"
## [1] "Year: 2005"
## [1] "Applying TUB for year: 2005, month 12 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.203331862692"
-## [1] "Top 28% cut: 22.0120090477533"
+## [1] "Top 14% cut: 26.8168752342067"
+## [1] "Top 28% cut: 21.6570522243108"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2005, month 12 & model v2_0 (3. Drought)"
@@ -6930,8 +7102,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected for TUB: 90"
## [1] "Year: 2006"
## [1] "Applying TUB for year: 2006, month 1 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.2368178249024"
-## [1] "Top 28% cut: 22.131484863216"
+## [1] "Top 14% cut: 26.8611696692674"
+## [1] "Top 28% cut: 21.717256884816"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 1 & model v2_0 (3. Drought)"
@@ -6945,8 +7117,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 2 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.420336662692"
-## [1] "Top 28% cut: 22.2275232229792"
+## [1] "Top 14% cut: 27.0374052342067"
+## [1] "Top 28% cut: 21.8600684501934"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 2 & model v2_0 (3. Drought)"
@@ -6960,8 +7132,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 3 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.3906098194874"
-## [1] "Top 28% cut: 22.1694938836202"
+## [1] "Top 14% cut: 27.0567976387795"
+## [1] "Top 28% cut: 21.8279261374794"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 3 & model v2_0 (3. Drought)"
@@ -6975,8 +7147,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 4 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.3835665308486"
-## [1] "Top 28% cut: 22.1605220972142"
+## [1] "Top 14% cut: 27.0333109721129"
+## [1] "Top 28% cut: 21.821578813526"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 4 & model v2_0 (3. Drought)"
@@ -6990,8 +7162,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2006, month 5 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.4481416167708"
-## [1] "Top 28% cut: 22.2065626019041"
+## [1] "Top 14% cut: 27.0115393375401"
+## [1] "Top 28% cut: 21.7913341139886"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2006, month 5 & model v2_0 (3. Drought)"
@@ -7008,8 +7180,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2008"
## [1] "Year: 2009"
## [1] "Applying TUB for year: 2009, month 9 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.5531755308486"
-## [1] "Top 28% cut: 22.3288056025845"
+## [1] "Top 14% cut: 27.1923276387795"
+## [1] "Top 28% cut: 21.9894634801926"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2009, month 9 & model v2_0 (3. Drought)"
@@ -7023,8 +7195,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2009, month 10 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.7935363137684"
-## [1] "Top 28% cut: 21.6958956110057"
+## [1] "Top 14% cut: 26.413346335934"
+## [1] "Top 28% cut: 21.2728793309876"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2009, month 10 & model v2_0 (3. Drought)"
@@ -7038,8 +7210,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2009, month 11 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 26.6455299045177"
-## [1] "Top 28% cut: 21.4328056025845"
+## [1] "Top 14% cut: 26.2706909721129"
+## [1] "Top 28% cut: 21.0752798808276"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2009, month 11 & model v2_0 (3. Drought)"
@@ -7055,8 +7227,8 @@ for(y in minYear:maxYear){
## [1] "Year: 2010"
## [1] "Year: 2011"
## [1] "Applying TUB for year: 2011, month 3 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.598768437851"
-## [1] "Top 28% cut: 22.3989556025845"
+## [1] "Top 14% cut: 27.224007982274"
+## [1] "Top 28% cut: 22.0264165474943"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2011, month 3 & model v2_0 (3. Drought)"
@@ -7070,8 +7242,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2011, month 4 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.7613391045177"
-## [1] "Top 28% cut: 22.5452722692512"
+## [1] "Top 14% cut: 27.3870443054462"
+## [1] "Top 28% cut: 22.1913231563059"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2011, month 4 & model v2_0 (3. Drought)"
@@ -7085,8 +7257,8 @@ for(y in minYear:maxYear){
## [1] "N cases selected: 206"
## [1] "N cases selected for TUB: 90"
## [1] "Applying TUB for year: 2011, month 5 & model v1_3 (3. Drought)"
-## [1] "Top 14% cut: 27.9749046615565"
-## [1] "Top 28% cut: 22.7275792685707"
+## [1] "Top 14% cut: 27.615600213198"
+## [1] "Top 28% cut: 22.3261962999714"
## [1] "N cases selected: 252"
## [1] "N cases selected for TUB: 110"
## [1] "Applying TUB for year: 2011, month 5 & model v2_0 (3. Drought)"
@@ -7356,14 +7528,14 @@ Table: Mean of meanBaseline.madj
|component | NA| v1_3| v2_0| v2_1|
|:--------------|--------:|--------:|---------:|---------:|
-|Basin | NA| 24.46239| 57.240433| 57.240433|
-|Bath | NA| 72.09866| 33.827889| 33.827889|
-|Dishwasher | NA| 22.66048| 1.784999| 1.784999|
-|External | 19.29923| NA| NA| NA|
-|KitchenSink | NA| 42.17928| 19.907452| 19.907452|
-|Shower | 82.99050| NA| NA| NA|
-|WC | 94.95473| NA| NA| NA|
-|WashingMachine | NA| 85.56456| 23.492576| 23.492576|
+|Basin | NA| 24.61785| 57.240433| 57.240433|
+|Bath | NA| 71.53676| 33.827889| 33.827889|
+|Dishwasher | NA| 22.63672| 1.784999| 1.784999|
+|External | 19.23379| NA| NA| NA|
+|KitchenSink | NA| 42.14794| 19.907452| 19.907452|
+|Shower | 83.02914| NA| NA| NA|
+|WC | 94.84397| NA| NA| NA|
+|WashingMachine | NA| 86.03717| 23.492576| 23.492576|
```r
t <- componentsDT[, .(mean = mean(meanBaseline.madj.we, na.rm = TRUE)),
@@ -7381,10 +7553,10 @@ Table: Mean of meanBaseline.madj.we
|Basin | NA| NaN| NaN| NaN|
|Bath | NA| NaN| NaN| NaN|
|Dishwasher | NA| NaN| NaN| NaN|
-|External | 19.29923| NA| NA| NA|
+|External | 19.23379| NA| NA| NA|
|KitchenSink | NA| NaN| NaN| NaN|
-|Shower | 80.06890| NA| NA| NA|
-|WC | 82.18122| NA| NA| NA|
+|Shower | 80.09981| NA| NA| NA|
+|WC | 82.07265| NA| NA| NA|
|WashingMachine | NA| NaN| NaN| NaN|
```r
@@ -7403,10 +7575,10 @@ Table: Mean of meanBaseline.madj.we.dr
|Basin | NA| NaN| NaN| NaN|
|Bath | NA| NaN| NaN| NaN|
|Dishwasher | NA| NaN| NaN| NaN|
-|External | 18.80957| NA| NA| NA|
+|External | 18.74593| NA| NA| NA|
|KitchenSink | NA| NaN| NaN| NaN|
-|Shower | 77.10207| NA| NA| NA|
-|WC | 82.17814| NA| NA| NA|
+|Shower | 77.03659| NA| NA| NA|
+|WC | 82.06912| NA| NA| NA|
|WashingMachine | NA| NaN| NaN| NaN|
#### Model 1_3
@@ -7516,12 +7688,12 @@ Table: Mean values 1994
|model |metered | currYear| mean.madj| mean.madj.we| mean.madj.we.dr|
|:-----|:-----------|--------:|---------:|------------:|---------------:|
-|v1_3 |Metered | 1994| 340.06| 340.00| 340.00|
-|v1_3 |Not metered | 1994| 455.30| 455.15| 455.15|
-|v2_0 |Metered | 1994| 335.65| 335.54| 335.54|
-|v2_0 |Not metered | 1994| 363.96| 363.96| 363.96|
-|v2_1 |Metered | 1994| 335.65| 335.53| 335.53|
-|v2_1 |Not metered | 1994| 363.96| 363.79| 363.79|
+|v1_3 |Metered | 1994| 337.74| 337.63| 337.63|
+|v1_3 |Not metered | 1994| 456.17| 456.09| 456.09|
+|v2_0 |Metered | 1994| 335.65| 335.65| 335.65|
+|v2_0 |Not metered | 1994| 363.96| 363.83| 363.83|
+|v2_1 |Metered | 1994| 335.65| 335.49| 335.49|
+|v2_1 |Not metered | 1994| 363.96| 363.78| 363.78|
```r
kable(endDT, caption = "Mean values 2012", digits = 2)
@@ -7533,12 +7705,12 @@ Table: Mean values 2012
|model |metered | currYear| mean.madj| mean.madj.we| mean.madj.we.dr|
|:-----|:-----------|--------:|---------:|------------:|---------------:|
-|v1_3 |Metered | 2012| 340.73| 322.18| 320.23|
-|v1_3 |Not metered | 2012| 453.79| 427.39| 425.17|
-|v2_0 |Metered | 2012| 336.32| 313.63| 307.16|
-|v2_0 |Not metered | 2012| 362.45| 337.15| 331.68|
-|v2_1 |Metered | 2012| 336.32| 294.47| 289.18|
-|v2_1 |Not metered | 2012| 362.45| 316.00| 309.97|
+|v1_3 |Metered | 2012| 338.41| 320.56| 318.91|
+|v1_3 |Not metered | 2012| 454.66| 427.77| 425.47|
+|v2_0 |Metered | 2012| 336.32| 313.27| 306.69|
+|v2_0 |Not metered | 2012| 362.45| 337.16| 331.16|
+|v2_1 |Metered | 2012| 336.32| 294.43| 288.54|
+|v2_1 |Not metered | 2012| 362.45| 315.80| 310.48|
```r
@@ -7708,16 +7880,16 @@ Table: Summary of Model v2 by drought stage
|droughtStage |metered | maxLitres_per_day_we| minLitres_per_day_we|
|:-----------------|:-----------|--------------------:|--------------------:|
-|1. Normal |Metered | 335.536| 312.521|
-|1. Normal |Not metered | 363.964| 334.338|
-|2. Developing |Metered | 338.820| 313.733|
-|2. Developing |Not metered | 365.086| 337.673|
-|3. Drought |Metered | 337.376| 315.384|
-|3. Drought |Not metered | 364.676| 338.916|
-|4. Severe Drought |Metered | 334.582| 330.395|
-|4. Severe Drought |Not metered | 363.363| 357.655|
-|5. Recovering |Metered | 335.631| 312.821|
-|5. Recovering |Not metered | 359.370| 337.568|
+|1. Normal |Metered | 335.648| 312.337|
+|1. Normal |Not metered | 363.825| 334.672|
+|2. Developing |Metered | 338.515| 312.648|
+|2. Developing |Not metered | 365.371| 338.413|
+|3. Drought |Metered | 336.862| 313.515|
+|3. Drought |Not metered | 364.735| 338.054|
+|4. Severe Drought |Metered | 334.784| 330.699|
+|4. Severe Drought |Not metered | 363.340| 356.910|
+|5. Recovering |Metered | 335.162| 313.141|
+|5. Recovering |Not metered | 359.824| 336.548|
```r
min <- min(dt$pc_diff)
@@ -7726,8 +7898,11 @@ head(dt[pc_diff < -2.9, .(obsDate, droughtStage, metered, pc = round(pc_diff,2))
```
## obsDate droughtStage metered pc
-## 1: 2011-04-15 3. Drought Metered -3.08
-## 2: 2011-05-15 3. Drought Metered -3.20
+## 1: 2009-10-15 3. Drought Metered -3.01
+## 2: 2009-11-15 3. Drought Metered -3.02
+## 3: 2011-03-15 3. Drought Metered -3.13
+## 4: 2011-04-15 3. Drought Metered -3.25
+## 5: 2011-05-15 3. Drought Metered -3.17
```
```r
@@ -7750,10 +7925,10 @@ kable(t[, .(Model, metered, maxL, minL, pc_reduction)], digits = 2)
|Model |metered | maxL| minL| pc_reduction|
|:--------------------------|:-----------|------:|------:|------------:|
-|water efficiency |Metered | 338.82| 312.52| 7.76|
-|water efficiency |Not metered | 365.09| 334.34| 8.42|
-|water efficiency + drought |Metered | 338.44| 305.43| 9.75|
-|water efficiency + drought |Not metered | 364.97| 328.49| 9.99|
+|water efficiency |Metered | 338.52| 312.34| 7.73|
+|water efficiency |Not metered | 365.37| 334.67| 8.40|
+|water efficiency + drought |Metered | 338.32| 303.69| 10.23|
+|water efficiency + drought |Not metered | 365.37| 328.62| 10.06|
@@ -7799,7 +7974,12 @@ head(dt[pc_diff < -3, .(obsDate, droughtStage, metered, pc = round(pc_diff,2))])
```
```
-## Empty data.table (0 rows and 4 cols): obsDate,droughtStage,metered,pc
+## obsDate droughtStage metered pc
+## 1: 2009-09-15 3. Drought Metered -3.09
+## 2: 2009-10-15 3. Drought Metered -3.02
+## 3: 2011-03-15 3. Drought Metered -3.24
+## 4: 2011-04-15 3. Drought Metered -3.01
+## 5: 2011-05-15 3. Drought Metered -3.36
```
```r
@@ -7822,10 +8002,10 @@ kable(t[, .(Model, metered, maxL, minL, pc_reduction)], digits = 2)
|Model |metered | maxL| minL| pc_reduction|
|:--------------------------|:-----------|------:|------:|------------:|
-|water efficiency |Metered | 337.95| 292.58| 13.43|
-|water efficiency |Not metered | 365.00| 313.39| 14.14|
-|water efficiency + drought |Metered | 337.41| 287.21| 14.88|
-|water efficiency + drought |Not metered | 364.88| 307.20| 15.81|
+|water efficiency |Metered | 337.78| 291.77| 13.62|
+|water efficiency |Not metered | 364.49| 312.82| 14.18|
+|water efficiency + drought |Metered | 337.54| 285.82| 15.32|
+|water efficiency + drought |Not metered | 364.42| 307.53| 15.61|
@@ -7850,12 +8030,12 @@ Table: Model affects (% reduced by drought model compared to WE baseline)
|model |metered | Min reduction| Mean reduction| Max reduction|
|:-----|:-----------|-------------:|--------------:|-------------:|
-|v1_3 |Metered | 0| 0.47| 0.86|
-|v1_3 |Not metered | 0| 0.45| 1.18|
-|v2_0 |Metered | 0| 1.43| 3.20|
-|v2_0 |Not metered | 0| 1.09| 2.35|
-|v2_1 |Metered | 0| 1.35| 2.87|
-|v2_1 |Not metered | 0| 1.31| 2.87|
+|v1_3 |Metered | 0| 0.36| 0.75|
+|v1_3 |Not metered | 0| 0.45| 1.16|
+|v2_0 |Metered | 0| 1.60| 3.25|
+|v2_0 |Not metered | 0| 1.22| 2.36|
+|v2_1 |Metered | 0| 1.48| 3.36|
+|v2_1 |Not metered | 0| 1.24| 2.46|
```r
baseline1Start <- plotTotalDT[model == "v1_3" & obsDate == min(obsDate), meanBaselineWeSum]
@@ -7869,9 +8049,9 @@ model2Red <- plotTotalDT[model == "v2_0" & obsDate == min(obsDate), meanBaseline
Overall from 1994-12-15 to 2012-11-15:
- * the baseline model showed a reduction of 6.32, 5.59%
- * model v1_3 showed a reduction of 6.83, 6.17%
- * model v2_0 showed a reduction of 6.5, 9.92%
+ * the baseline model showed a reduction of 6.56, 5.32%
+ * model v1_3 showed a reduction of 7.02, 5.84%
+ * model v2_0 showed a reduction of 6.58, 9.98%
This is clearly shown in the chart below where:
@@ -8039,7 +8219,7 @@ ggsave(paste0("plots_v2.1/compareWeModelsDroughtModelPcSavings.png"), dpi = 400)
Maximum difference between the models:
--7.0894933%
+-6.6711833%
```r
@@ -8049,34 +8229,34 @@ models[,.(meanDiff = mean(drDiff)), keyby = year]
```
## year meanDiff
-## 1: 1994 -0.0002471496
-## 2: 1995 -0.0021739863
-## 3: 1996 -0.0059149769
-## 4: 1997 -0.0094824771
-## 5: 1998 -0.0129025234
-## 6: 1999 -0.0156782048
-## 7: 2000 -0.0197760291
-## 8: 2001 -0.0229966071
-## 9: 2002 -0.0255450971
-## 10: 2003 -0.0284372229
-## 11: 2004 -0.0315994224
-## 12: 2005 -0.0364115290
-## 13: 2006 -0.0399777683
-## 14: 2007 -0.0456209855
-## 15: 2008 -0.0488367859
-## 16: 2009 -0.0529726764
-## 17: 2010 -0.0551458005
-## 18: 2011 -0.0591128139
-## 19: 2012 -0.0620001064
+## 1: 1994 -0.0003020146
+## 2: 1995 -0.0019597824
+## 3: 1996 -0.0057953029
+## 4: 1997 -0.0095076175
+## 5: 1998 -0.0120261810
+## 6: 1999 -0.0141479024
+## 7: 2000 -0.0185785848
+## 8: 2001 -0.0214190234
+## 9: 2002 -0.0258597365
+## 10: 2003 -0.0282442826
+## 11: 2004 -0.0312990726
+## 12: 2005 -0.0354045521
+## 13: 2006 -0.0385268285
+## 14: 2007 -0.0418210190
+## 15: 2008 -0.0463683116
+## 16: 2009 -0.0497234286
+## 17: 2010 -0.0527518851
+## 18: 2011 -0.0573650391
+## 19: 2012 -0.0608181857
```
% reduction for 2_0
--19.4941623%
+-20.3095536%
% reduction for 2_1
--27.0433781%
+-27.4997985%
# Summary of final data
@@ -8142,29 +8322,29 @@ Table: Data summary
|currYear | 0| 1.00| 2003.42| 5.20| 1994.00| 1999.00| 2003.00| 2008.00| 2012.00|▆▇▆▇▇ |
|currMon | 0| 1.00| 6.50| 3.45| 1.00| 3.75| 6.50| 9.25| 12.00|▇▅▅▅▇ |
|occupancy | 0| 1.00| 2.54| 1.35| 1.00| 2.00| 2.00| 3.00| 10.00|▇▅▁▁▁ |
-|Basin.baseline.madj | 21600| 0.98| 45.36| 45.09| 10.33| 23.90| 27.53| 52.92| 463.65|▇▁▁▁▁ |
-|Bath.baseline.madj | 0| 1.00| 47.43| 26.02| -3.95| 25.22| 46.80| 65.84| 124.08|▅▇▇▅▁ |
-|Dishwasher.baseline.madj | 0| 1.00| 9.20| 10.42| -2.18| -0.15| 4.26| 21.25| 32.27|▇▂▁▅▁ |
-|External.baseline.madj | 72144| 0.93| 19.09| 16.43| -2.51| 1.42| 17.46| 27.91| 98.17|▇▆▂▁▁ |
-|KitchenSink.baseline.madj | 0| 1.00| 27.82| 14.11| 7.47| 15.28| 30.27| 38.21| 76.12|▇▇▆▂▁ |
-|Shower.baseline.madj | 20736| 0.98| 81.01| 69.38| -0.24| 35.73| 48.80| 114.46| 515.29|▇▂▁▁▁ |
-|WC.baseline.madj | 22896| 0.98| 95.55| 41.94| 20.64| 71.66| 92.51| 123.19| 262.79|▃▇▅▁▁ |
-|WashingMachine.baseline.madj | 15120| 0.99| 45.86| 33.90| -3.24| 15.92| 31.07| 77.73| 170.75|▇▂▅▁▁ |
-|sumDaily.baseline.madj | 72144| 0.93| 372.71| 151.38| 53.53| 272.68| 367.47| 463.54| 1153.15|▃▇▂▁▁ |
+|Basin.baseline.madj | 21600| 0.98| 45.42| 45.07| 10.33| 23.85| 27.92| 52.92| 463.65|▇▁▁▁▁ |
+|Bath.baseline.madj | 0| 1.00| 47.23| 25.71| -3.95| 25.22| 46.80| 65.67| 125.70|▅▇▇▅▁ |
+|Dishwasher.baseline.madj | 0| 1.00| 9.19| 10.41| -2.18| -0.15| 4.26| 21.22| 33.99|▇▂▁▅▁ |
+|External.baseline.madj | 72144| 0.93| 19.01| 16.45| -2.51| 1.33| 17.47| 27.73| 98.17|▇▆▂▁▁ |
+|KitchenSink.baseline.madj | 0| 1.00| 27.81| 14.10| 7.47| 15.28| 30.27| 38.20| 76.12|▇▇▆▂▁ |
+|Shower.baseline.madj | 20736| 0.98| 81.05| 69.35| -0.24| 35.98| 48.83| 114.46| 515.29|▇▂▁▁▁ |
+|WC.baseline.madj | 22896| 0.98| 95.43| 42.02| 20.64| 71.51| 91.88| 123.32| 262.79|▃▇▃▁▁ |
+|WashingMachine.baseline.madj | 15120| 0.99| 46.03| 34.14| -3.24| 15.92| 31.07| 78.20| 145.57|▇▅▅▃▁ |
+|sumDaily.baseline.madj | 72144| 0.93| 372.56| 151.48| 53.53| 272.86| 366.09| 463.15| 1153.15|▃▇▂▁▁ |
|occRed | 0| 1.00| 2.53| 1.34| 1.00| 2.00| 2.00| 3.00| 6.00|▇▂▂▁▁ |
|loWC | 0| 1.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00|▁▁▇▁▁ |
|loSh | 0| 1.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00| 0.00|▁▁▇▁▁ |
-|WC.baseline.madj.we | 22896| 0.98| 82.87| 43.57| 9.81| 47.17| 74.48| 112.50| 262.79|▇▇▅▁▁ |
-|Shower.baseline.madj.we | 20736| 0.98| 78.16| 67.99| -0.24| 34.51| 48.57| 109.59| 515.29|▇▂▁▁▁ |
-|sumDaily.baseline.madj.we | 72144| 0.93| 357.29| 147.75| 35.59| 257.46| 352.63| 450.72| 1153.15|▃▇▂▁▁ |
+|WC.baseline.madj.we | 22896| 0.98| 82.75| 43.58| 9.70| 47.31| 74.48| 112.41| 262.79|▇▇▅▁▁ |
+|Shower.baseline.madj.we | 20736| 0.98| 78.19| 67.93| -0.24| 34.66| 48.59| 109.60| 515.29|▇▂▁▁▁ |
+|sumDaily.baseline.madj.we | 72144| 0.93| 357.13| 147.80| 36.05| 257.28| 352.07| 451.25| 1152.91|▃▇▂▁▁ |
|yearOrig | 0| 1.00| 2003.42| 5.20| 1994.00| 1999.00| 2003.00| 2008.00| 2012.00|▆▇▆▇▇ |
|dualFlushWCupdated | 0| 1.00| 0.00| 0.01| 0.00| 0.00| 0.00| 0.00| 1.00|▇▁▁▁▁ |
|loFlowShowerUpdated | 0| 1.00| 0.11| 0.31| 0.00| 0.00| 0.00| 0.00| 1.00|▇▁▁▁▁ |
|applyTUB | 0| 1.00| 0.01| 0.11| 0.00| 0.00| 0.00| 0.00| 1.00|▇▁▁▁▁ |
-|WC.baseline.madj.we.dr | 22896| 0.98| 82.87| 43.57| 9.81| 47.15| 74.48| 112.50| 262.79|▇▇▅▁▁ |
-|Shower.baseline.madj.we.dr | 20736| 0.98| 75.26| 66.66| -0.24| 32.79| 47.41| 104.04| 515.29|▇▂▁▁▁ |
-|External.baseline.madj.we.dr | 72144| 0.93| 18.61| 16.18| -2.51| 1.42| 16.95| 27.25| 98.17|▇▆▂▁▁ |
-|sumDaily.baseline.madj.we.dr | 72144| 0.93| 353.98| 146.34| 35.59| 254.93| 350.73| 447.94| 1153.15|▃▇▂▁▁ |
+|WC.baseline.madj.we.dr | 22896| 0.98| 82.75| 43.59| 9.70| 47.31| 74.48| 112.41| 262.79|▇▇▅▁▁ |
+|Shower.baseline.madj.we.dr | 20736| 0.98| 75.21| 66.41| -0.24| 32.90| 47.36| 103.24| 515.26|▇▂▁▁▁ |
+|External.baseline.madj.we.dr | 72144| 0.93| 18.53| 16.20| -2.51| 1.33| 17.03| 27.11| 98.17|▇▆▂▁▁ |
+|sumDaily.baseline.madj.we.dr | 72144| 0.93| 353.70| 146.42| 36.05| 254.27| 350.09| 448.81| 1152.91|▃▇▂▁▁ |
@@ -8220,7 +8400,7 @@ t <- proc.time() - startTime
elapsed <- t[[3]]
```
-Analysis completed in 718.816 seconds ( 11.98 minutes) using [knitr](https://cran.r-project.org/package=knitr) in [RStudio](http://www.rstudio.com) with R version 4.0.2 (2020-06-22) running on x86_64-apple-darwin17.0.
+Analysis completed in 660.067 seconds ( 11 minutes) using [knitr](https://cran.r-project.org/package=knitr) in [RStudio](http://www.rstudio.com) with R version 4.0.2 (2020-06-22) running on x86_64-apple-darwin17.0.
R packages used:
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