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diff --git a/impetusModel/Fig4_5_DroughtPlotKey.pdf b/impetusModel/Fig4_5_DroughtPlotKey.pdf
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diff --git a/impetusModel/Fig4_Compare_sum_model_v1_3.pdf b/impetusModel/Fig4_Compare_sum_model_v1_3.pdf
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diff --git a/impetusModel/Fig5_Chart_savings_v1_3_by_month.pdf b/impetusModel/Fig5_Chart_savings_v1_3_by_month.pdf
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diff --git a/impetusModel/impetusModel.html b/impetusModel/impetusModel.html
index 9198f002421d1e220a66ad9eec08e366ebb77604..2891b05741b81f0d6487ea49c6917d9b2efb9924 100644
--- a/impetusModel/impetusModel.html
+++ b/impetusModel/impetusModel.html
@@ -24,8 +24,8 @@
<link href="impetusModel_files/tocify-1.9.1/jquery.tocify.css" rel="stylesheet" />
<script src="impetusModel_files/tocify-1.9.1/jquery.tocify.js"></script>
<script src="impetusModel_files/navigation-1.1/tabsets.js"></script>
-<link href="impetusModel_files/highlightjs-1.1/default.css" rel="stylesheet" />
-<script src="impetusModel_files/highlightjs-1.1/highlight.js"></script>
+<link href="impetusModel_files/highlightjs-9.12.0/default.css" rel="stylesheet" />
+<script src="impetusModel_files/highlightjs-9.12.0/highlight.js"></script>
<style type="text/css">code{white-space: pre;}</style>
<style type="text/css">
@@ -34,10 +34,12 @@
}
</style>
<script type="text/javascript">
-if (window.hljs && document.readyState && document.readyState === "complete") {
- window.setTimeout(function() {
- hljs.initHighlighting();
- }, 0);
+if (window.hljs) {
+ hljs.configure({languages: []});
+ hljs.initHighlightingOnLoad();
+ if (document.readyState && document.readyState === "complete") {
+ window.setTimeout(function() { hljs.initHighlighting(); }, 0);
+ }
}
</script>
@@ -216,7 +218,7 @@ div.tocify {
<h1 class="title toc-ignore">A household level daily consumption estimation microsimulation model</h1>
<h4 class="author"><em>Ben Anderson (<a href="mailto:b.anderson@soton.ac.uk">b.anderson@soton.ac.uk</a>, <code>@dataknut</code>), Despoina Manouseli (<a href="mailto:d.manouseli@soton.ac.uk">d.manouseli@soton.ac.uk</a>) & Magesh Nagarajan (<a href="mailto:m.nagarajan@soton.ac.uk">m.nagarajan@soton.ac.uk</a>)</em></h4>
-<h4 class="date"><em>Last run at: 2017-11-08 19:39:55</em></h4>
+<h4 class="date"><em>Last run at: 2018-03-19 03:26:43</em></h4>
</div>
@@ -2152,21 +2154,21 @@ kable(caption = "Check % metered distribution", 100 * round(prop.table
<tbody>
<tr class="odd">
<td>Metered</td>
-<td align="right">37</td>
-<td align="right">40.1</td>
-<td align="right">42.7</td>
-<td align="right">41.7</td>
+<td align="right">41</td>
+<td align="right">41</td>
+<td align="right">36.1</td>
+<td align="right">38.1</td>
<td align="right">45.7</td>
-<td align="right">38.6</td>
+<td align="right">37.3</td>
</tr>
<tr class="even">
<td>Not metered</td>
-<td align="right">63</td>
-<td align="right">59.9</td>
-<td align="right">57.3</td>
-<td align="right">58.3</td>
+<td align="right">59</td>
+<td align="right">59</td>
+<td align="right">63.9</td>
+<td align="right">61.9</td>
<td align="right">54.3</td>
-<td align="right">61.4</td>
+<td align="right">62.7</td>
</tr>
</tbody>
</table>
@@ -2692,69 +2694,69 @@ kable(caption = "Test Basin & Bath l/day as modelled using rsnorm()&quo
<tbody>
<tr class="odd">
<td></td>
-<td align="center">Min. :12.01</td>
-<td align="center">Min. : 32.90</td>
-<td align="left">Min. :19.88</td>
+<td align="center">Min. :12.14</td>
+<td align="center">Min. : 37.30</td>
+<td align="left">Min. :19.66</td>
<td align="left">Min. : 0.00</td>
-<td align="left">Min. :27.20</td>
-<td align="left">Min. :21.10</td>
-<td align="center">Min. : 46.38</td>
-<td align="left">Min. : 57.26</td>
+<td align="left">Min. :27.29</td>
+<td align="left">Min. :21.84</td>
+<td align="center">Min. : 49.72</td>
+<td align="left">Min. : 57.32</td>
</tr>
<tr class="even">
<td></td>
-<td align="center">1st Qu.:17.48</td>
-<td align="center">1st Qu.: 57.03</td>
-<td align="left">1st Qu.:22.65</td>
-<td align="left">1st Qu.:10.72</td>
-<td align="left">1st Qu.:32.52</td>
-<td align="left">1st Qu.:32.11</td>
-<td align="center">1st Qu.: 79.78</td>
-<td align="left">1st Qu.: 73.16</td>
+<td align="center">1st Qu.:17.37</td>
+<td align="center">1st Qu.: 57.19</td>
+<td align="left">1st Qu.:22.63</td>
+<td align="left">1st Qu.:10.77</td>
+<td align="left">1st Qu.:32.63</td>
+<td align="left">1st Qu.:31.69</td>
+<td align="center">1st Qu.: 80.63</td>
+<td align="left">1st Qu.: 73.40</td>
</tr>
<tr class="odd">
<td></td>
-<td align="center">Median :24.22</td>
-<td align="center">Median : 74.01</td>
-<td align="left">Median :23.95</td>
-<td align="left">Median :15.27</td>
-<td align="left">Median :43.10</td>
-<td align="left">Median :36.58</td>
-<td align="center">Median :100.25</td>
-<td align="left">Median : 81.94</td>
+<td align="center">Median :24.12</td>
+<td align="center">Median : 73.61</td>
+<td align="left">Median :23.85</td>
+<td align="left">Median :15.95</td>
+<td align="left">Median :43.07</td>
+<td align="left">Median :36.48</td>
+<td align="center">Median :100.75</td>
+<td align="left">Median : 82.27</td>
</tr>
<tr class="even">
<td></td>
-<td align="center">Mean :22.94</td>
-<td align="center">Mean : 71.87</td>
-<td align="left">Mean :24.25</td>
-<td align="left">Mean :15.37</td>
-<td align="left">Mean :40.47</td>
-<td align="left">Mean :36.54</td>
-<td align="center">Mean : 98.71</td>
-<td align="left">Mean : 84.19</td>
+<td align="center">Mean :22.91</td>
+<td align="center">Mean : 71.71</td>
+<td align="left">Mean :24.11</td>
+<td align="left">Mean :15.61</td>
+<td align="left">Mean :40.42</td>
+<td align="left">Mean :36.45</td>
+<td align="center">Mean : 99.15</td>
+<td align="left">Mean : 83.96</td>
</tr>
<tr class="odd">
<td></td>
-<td align="center">3rd Qu.:27.11</td>
-<td align="center">3rd Qu.: 83.16</td>
-<td align="left">3rd Qu.:25.66</td>
-<td align="left">3rd Qu.:22.26</td>
-<td align="left">3rd Qu.:46.29</td>
-<td align="left">3rd Qu.:40.95</td>
-<td align="center">3rd Qu.:114.20</td>
-<td align="left">3rd Qu.: 92.89</td>
+<td align="center">3rd Qu.:27.05</td>
+<td align="center">3rd Qu.: 83.83</td>
+<td align="left">3rd Qu.:25.41</td>
+<td align="left">3rd Qu.:22.24</td>
+<td align="left">3rd Qu.:46.19</td>
+<td align="left">3rd Qu.:40.76</td>
+<td align="center">3rd Qu.:114.97</td>
+<td align="left">3rd Qu.: 92.40</td>
</tr>
<tr class="even">
<td></td>
-<td align="center">Max. :38.29</td>
-<td align="center">Max. :137.50</td>
-<td align="left">Max. :32.84</td>
-<td align="left">Max. :53.46</td>
-<td align="left">Max. :57.41</td>
-<td align="left">Max. :61.11</td>
-<td align="center">Max. :174.28</td>
-<td align="left">Max. :153.25</td>
+<td align="center">Max. :40.37</td>
+<td align="center">Max. :128.19</td>
+<td align="left">Max. :32.28</td>
+<td align="left">Max. :65.47</td>
+<td align="left">Max. :59.49</td>
+<td align="left">Max. :61.65</td>
+<td align="center">Max. :181.27</td>
+<td align="left">Max. :150.64</td>
</tr>
</tbody>
</table>
@@ -2784,31 +2786,31 @@ kable(caption = "Metered vs un-metered estimates (mean)", t)</code></p
<tbody>
<tr class="odd">
<td align="left">Metered</td>
-<td align="right">16.87288</td>
-<td align="right">55.51313</td>
-<td align="right">23.03054</td>
-<td align="right">9.97072</td>
-<td align="right">32.02423</td>
-<td align="right">31.45315</td>
-<td align="right">77.60751</td>
-<td align="right">78.05961</td>
+<td align="right">16.83207</td>
+<td align="right">55.02204</td>
+<td align="right">22.94178</td>
+<td align="right">10.12150</td>
+<td align="right">32.02371</td>
+<td align="right">31.03535</td>
+<td align="right">77.43587</td>
+<td align="right">77.26493</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
-<td align="right">26.97718</td>
-<td align="right">82.78251</td>
-<td align="right">25.06828</td>
-<td align="right">18.96585</td>
-<td align="right">46.10112</td>
-<td align="right">39.92801</td>
-<td align="right">112.77722</td>
-<td align="right">88.27885</td>
+<td align="right">26.96571</td>
+<td align="right">82.84065</td>
+<td align="right">24.88585</td>
+<td align="right">19.26286</td>
+<td align="right">46.01007</td>
+<td align="right">40.05337</td>
+<td align="right">113.62444</td>
+<td align="right">88.42468</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: 31.19.</p>
+<p>% difference between means for washing machine: 31.85.</p>
</div>
<div id="occupancy-based-adjustment" class="section level3">
<h3><span class="header-section-number">8.4.3</span> Occupancy based adjustment</h3>
@@ -3041,98 +3043,98 @@ 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">16.85</td>
-<td align="right">3.20</td>
-<td align="right">57.14</td>
-<td align="right">11.35</td>
+<td align="right">17.04</td>
+<td align="right">3.03</td>
+<td align="right">56.28</td>
+<td align="right">9.87</td>
</tr>
<tr class="even">
<td align="left">Metered</td>
<td align="right">2</td>
-<td align="right">18.56</td>
-<td align="right">3.04</td>
-<td align="right">55.67</td>
-<td align="right">9.39</td>
+<td align="right">18.47</td>
+<td align="right">2.94</td>
+<td align="right">55.90</td>
+<td align="right">9.26</td>
</tr>
<tr class="odd">
<td align="left">Metered</td>
<td align="right">3</td>
-<td align="right">18.78</td>
-<td align="right">3.00</td>
-<td align="right">57.87</td>
-<td align="right">10.96</td>
+<td align="right">18.63</td>
+<td align="right">2.59</td>
+<td align="right">56.17</td>
+<td align="right">9.40</td>
</tr>
<tr class="even">
<td align="left">Metered</td>
<td align="right">4</td>
-<td align="right">19.60</td>
-<td align="right">2.93</td>
-<td align="right">58.31</td>
-<td align="right">8.49</td>
+<td align="right">19.56</td>
+<td align="right">2.83</td>
+<td align="right">57.51</td>
+<td align="right">11.62</td>
</tr>
<tr class="odd">
<td align="left">Metered</td>
<td align="right">5</td>
-<td align="right">18.61</td>
-<td align="right">2.28</td>
-<td align="right">53.79</td>
-<td align="right">7.36</td>
+<td align="right">18.73</td>
+<td align="right">2.89</td>
+<td align="right">52.10</td>
+<td align="right">8.53</td>
</tr>
<tr class="even">
<td align="left">Metered</td>
<td align="right">6</td>
-<td align="right">18.41</td>
-<td align="right">3.24</td>
-<td align="right">56.51</td>
-<td align="right">8.02</td>
+<td align="right">17.30</td>
+<td align="right">3.05</td>
+<td align="right">58.35</td>
+<td align="right">11.77</td>
</tr>
<tr class="odd">
<td align="left">Not metered</td>
<td align="right">1</td>
-<td align="right">27.06</td>
-<td align="right">2.93</td>
-<td align="right">82.44</td>
-<td align="right">10.01</td>
+<td align="right">27.00</td>
+<td align="right">2.94</td>
+<td align="right">82.45</td>
+<td align="right">10.20</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
<td align="right">2</td>
-<td align="right">28.18</td>
-<td align="right">2.91</td>
-<td align="right">84.31</td>
-<td align="right">9.99</td>
+<td align="right">28.33</td>
+<td align="right">3.04</td>
+<td align="right">83.95</td>
+<td align="right">10.24</td>
</tr>
<tr class="odd">
<td align="left">Not metered</td>
<td align="right">3</td>
-<td align="right">29.46</td>
-<td align="right">2.89</td>
-<td align="right">85.94</td>
-<td align="right">9.98</td>
+<td align="right">29.52</td>
+<td align="right">2.78</td>
+<td align="right">85.42</td>
+<td align="right">9.10</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
<td align="right">4</td>
-<td align="right">29.50</td>
-<td align="right">2.76</td>
-<td align="right">82.77</td>
-<td align="right">10.55</td>
+<td align="right">29.73</td>
+<td align="right">3.33</td>
+<td align="right">85.02</td>
+<td align="right">10.44</td>
</tr>
<tr class="odd">
<td align="left">Not metered</td>
<td align="right">5</td>
-<td align="right">30.14</td>
-<td align="right">3.03</td>
-<td align="right">86.43</td>
-<td align="right">10.46</td>
+<td align="right">28.77</td>
+<td align="right">2.95</td>
+<td align="right">85.91</td>
+<td align="right">8.69</td>
</tr>
<tr class="even">
<td align="left">Not metered</td>
<td align="right">6</td>
-<td align="right">31.08</td>
-<td align="right">2.63</td>
-<td align="right">86.53</td>
-<td align="right">9.01</td>
+<td align="right">30.87</td>
+<td align="right">3.07</td>
+<td align="right">88.35</td>
+<td align="right">9.10</td>
</tr>
</tbody>
</table>
@@ -3321,55 +3323,50 @@ ggplot(est2013dataFig2DT[modelDT], aes(x = factor(occupancy))) + geom_point(aes(
</tbody>
</table>
<p>Comparing these values with the IMPETUS model is not straightforward as not all of the usages match to the microcomonents modelled. However, the following chart attempts to show all values on the sae graphs as far as possible. Wider bars indicate values which cannot be matched.</p>
-<pre class="r"><code># change labels to match EST
-mt <- hhDataFinalDaily_v1_3DT[, .(vol = "vol", Basin = round(mean(Basin.baseline),
+<pre class="r"><code>myCap <- "IMPETUS model: synthetic households (n = 1800)\n Model v1" # simple for
+# change labels to match EST
+modelDT <- hhDataFinalDaily_v1_3DT[, .(vol = "vol", Basin = round(mean(Basin.baseline),
2), Dishwasher = round(mean(Dishwasher.baseline), 2), External = round(mean(External.baseline),
2), `Kitchen Sink` = round(mean(KitchenSink.baseline), 2), Bath = round(mean(Bath.baseline),
2), Shower = round(mean(Shower.baseline), 2), Toilet = round(mean(WC.baseline),
2), `Washing machine` = round(mean(WashingMachine.baseline), 2), Total = round(mean(sumDaily.baseline),
2))]
# recast
-mt <- dcast(melt(mt, id.vars = "vol"), variable ~ vol)
-mt <- mt[, `:=`(Usage, variable)]
-mt <- mt[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
-
-pct <- hhDataFinalDaily_v1_3DT[, .(pc = "pc", Basin = 100 * round(mean(Basin.baseline/sumDaily.baseline),
- 4), Dishwasher = 100 * round(mean(Dishwasher.baseline/sumDaily.baseline),
- 4), External = 100 * round(mean(External.baseline/sumDaily.baseline), 4),
- `Kitchen Sink` = 100 * round(mean(KitchenSink.baseline/sumDaily.baseline),
- 4), Bath = 100 * round(mean(Bath.baseline/sumDaily.baseline), 4), Shower = 100 *
- round(mean(Shower.baseline/sumDaily.baseline), 4), Toilet = 100 * round(mean(WC.baseline/sumDaily.baseline),
- 4), `Washing machine` = 100 * round(mean(WashingMachine.baseline/sumDaily.baseline),
- 4))]
-# recast
-pct <- dcast(melt(pct, id.vars = "pc"), variable ~ pc)
-pct <- pct[, `:=`(Usage, variable)]
-pct <- pct[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
+modelDT <- dcast(melt(modelDT, id.vars = "vol"), variable ~ vol)
+modelDT <- modelDT[, `:=`(Usage, variable)]
+modelDT <- modelDT[, `:=`(source, paste0("IMPETUS Model"))]
+modelTot <- modelDT[Usage == "Total", vol]
+modelDT <- modelDT[, `:=`(pcTot, 100 * (vol/modelTot))]
-setkey(mt, Usage, variable, source) # simplest way to remove vars!
-setkey(pct, Usage, variable, source)
-mt <- merge(mt, pct, all = TRUE)
+setkey(modelDT, Usage, variable, source) # simplest way to remove vars!
-est2013dataFig1DT <- est2013dataFig1DT[, `:=`(pc, percentOfTotalDaily)]
-est2013dataFig1DT <- est2013dataFig1DT[, `:=`(vol, imputed.l.hh.day)]
-est2013dataFig1DT <- est2013dataFig1DT[, `:=`(source, "EST (2013)")]
+estDT <- est2013dataFig1DT
+estDT <- estDT[, `:=`(pcTot, percentOfTotalDaily)]
+estDT <- estDT[, `:=`(vol, imputed.l.hh.day)]
+estDT <- estDT[, `:=`(source, "EST (2013)")]
-mt$variable <- NULL # remove
-est2013dataFig1DT$percentOfTotalDaily <- NULL
-est2013dataFig1DT$imputed.l.hh.day <- NULL
+modelDT$variable <- NULL # remove
+estDT$percentOfTotalDaily <- NULL
+estDT$imputed.l.hh.day <- NULL
-plotDT <- rbind(est2013dataFig1DT, mt)
+plotDT <- rbind(estDT, modelDT)
plotDT <- plotDT[, `:=`(Usage, as.factor(Usage))]
plotDT <- plotDT[, `:=`(UsageRo, relevel(Usage, "Total"))] # put usage at the end
ggplot(plotDT, aes(x = UsageRo, fill = source)) + geom_col(aes(y = vol), position = "dodge") +
- labs(title = "Total use (l/day)", y = "Mean l/day", x = "Usage") + coord_flip() # rotate for legibility</code></pre>
+ labs(y = "Mean l/day", x = "Usage", caption = myCap) + coord_flip() # rotate for legibility</code></pre>
<p><img src="impetusModel_files/figure-html/compareESTmcm%20v1-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(plotDT[Usage != "Total"], aes(x = UsageRo, fill = source)) + geom_col(aes(y = pc),
- position = "dodge") + labs(title = "% of total (l/day)", y = "%", x = "Usage") +
- coord_flip() # rotate for legibility</code></pre>
+<pre class="r"><code>estPlot <- ggplot(plotDT[Usage != "Total"], aes(x = UsageRo, fill = source)) +
+ geom_col(aes(y = pcTot), position = "dodge") + labs(y = "% household total",
+ x = "Usage", caption = myCap) + coord_flip() # rotate for legibility
+
+estPlot</code></pre>
<p><img src="impetusModel_files/figure-html/compareESTmcm%20v1-2.png" /><!-- --></p>
+<pre class="r"><code># Grey scale version if required
+estPlot <- estPlot + theme_bw()
+
+ggsave("Fig2_CompareModelv1_3withEST2013.pdf", dpi = 400)</code></pre>
<p>These charts suggest that compared to the EST (2013) estimates our model underestimates Shower use and over-estimates Bath use. However, given that the EST estimates used a self-selecting sample who may have been more likely to be ‘careful’ water users, it may be that respondents to their survey were more likely to use showers than baths. Of the other usages that can be directly compared, our model also slighty overestimates external, dishwasher, toilet and (especially) washing machine use, perhaps for similar reasons. Overall, accounting for the usages that are not directly comparable (basin, taps, kitchen sink etc) the mean ‘Total’ usage figures were broadly comparable.</p>
<blockquote>
<p>They are both models of course… How could we validate with measured data? Artesia?</p>
@@ -3400,7 +3397,7 @@ write.csv(keepDT, oFile)
# compress it now gzip new one
print(paste0("gzipping file to: ", oFile, ".gz"))</code></pre>
-<pre><code>## [1] "gzipping file to: ~/Data/IMPETUS/outputs/model_v1/output-hh-baseline-mcm-consumption_2017-11-08_v1_3.csv.gz"</code></pre>
+<pre><code>## [1] "gzipping file to: ~/Data/IMPETUS/outputs/model_v1/output-hh-baseline-mcm-consumption_2018-03-19_v1_3.csv.gz"</code></pre>
<pre class="r"><code>cmd <- paste0("gzip -f ", oFile) # forces over-write
try(system(cmd)) # in case it fails (it will on windows - you will be left with a .csv file)</code></pre>
<p>Data written to:</p>
@@ -6060,22 +6057,33 @@ mt <- hhDataFinalDaily_v2_0DT[, .(vol = "vol", Basin = round(mean(d
na.rm = TRUE), 2), Total = round(mean(totalDailyHouseDemandFinal, na.rm = TRUE),
2))]
# recast
-mt <- dcast(melt(mt, id.vars = "vol"), variable ~ vol)
-mt <- mt[, `:=`(Usage, variable)]
-mt <- mt[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
+mtDT <- as.data.table(dcast(melt(mt, id.vars = "vol"), variable ~ vol))
+mtDT <- mtDT[, `:=`(Usage, variable)]
+mtDT <- mtDT[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
+# calculate % of total column for chart
+tot <- mtDT[Usage == "Total", vol]
+mtDT <- mtDT[, `:=`(pcTot, 100 * (vol/tot))]
+setkey(mtDT, Usage, variable, source) # simplest way to remove vars!
-setkey(mt, Usage, variable, source) # simplest way to remove vars!
+mtDT$variable <- NULL # remove
-mt$variable <- NULL # remove
-est2013dataFig1DT$pc <- NULL
-plotDT <- rbind(est2013dataFig1DT, mt)
+# re-use from model 1 - may break if model 1 not run
+plotDT <- rbind(estDT, mtDT)
plotDT <- plotDT[, `:=`(Usage, as.factor(Usage))]
plotDT <- plotDT[, `:=`(UsageRo, relevel(Usage, "Total"))] # put usage at the end
-ggplot(plotDT, aes(x = UsageRo, fill = source)) + geom_col(aes(y = vol), position = "dodge") +
- labs(title = "Total use (l/day)", y = "Mean l/day", x = "Usage") + coord_flip() # rotate for legibility</code></pre>
+myPlot <- ggplot(plotDT, aes(x = UsageRo, fill = source)) + geom_col(aes(y = vol),
+ position = "dodge") + labs(y = "Mean l/day", x = "Usage") + coord_flip() # rotate for legibility
+
+myPlot</code></pre>
<p><img src="impetusModel_files/figure-html/compareESTmcm%20v2-1.png" /><!-- --></p>
+<pre class="r"><code>myPlot <- ggplot(plotDT[Usage != "Total"], aes(x = UsageRo, fill = source)) +
+ geom_col(aes(y = pcTot), position = "dodge") + labs(y = "% total", x = "Usage") +
+ coord_flip() # rotate for legibility
+
+myPlot</code></pre>
+<p><img src="impetusModel_files/figure-html/compareESTmcm%20v2-2.png" /><!-- --></p>
</div>
<div id="save-data" class="section level2">
<h2><span class="header-section-number">9.9</span> Save data</h2>
@@ -6094,7 +6102,7 @@ oFile <- paste0(m2oPath, "output-SPRG-1800hh-consumption_", format(
write.csv(hhDataFinalDaily_v2_0DT, oFile)</code></pre>
<p>Data written to:</p>
<blockquote>
-<p>~/Data/IMPETUS/outputs/model_v2/output-SPRG-1800hh-consumption_2017-11-08_v2_0.csv and (possibly) gzipped</p>
+<p>~/Data/IMPETUS/outputs/model_v2/output-SPRG-1800hh-consumption_2018-03-19_v2_0.csv and (possibly) gzipped</p>
</blockquote>
</div>
</div>
@@ -6124,17 +6132,17 @@ 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 28 29 30 52 65 66 84 85 90 96 ...
+## $ hhid : int 8 16 22 28 29 30 40 43 52 58 ...
## $ occupancy : int 1 1 1 1 1 1 1 1 1 1 ...
## $ metered : chr "Metered" "Metered" "Metered" "Metered" ...
-## $ Basin.baseline : num 15.1 14.8 14.9 16.6 14.8 ...
-## $ Bath.baseline : num 46.3 48.3 54.4 78.8 64.2 ...
-## $ Dishwasher.baseline : num 22.8 21.3 23.5 20.5 20.9 ...
-## $ KitchenSink.baseline : num 30.5 29.2 32.3 28 32.9 ...
-## $ Shower.baseline : num 25.9 33.5 29.8 30.4 31.2 ...
-## $ WC.baseline : num 70.6 59 71.4 68.4 80.7 ...
-## $ WashingMachine.baseline: num 64.6 67.7 65.6 71.3 87.4 ...
-## $ External.baseline : num 13.7 0 0 15.1 0 ...
+## $ Basin.baseline : num 14.5 14 14.1 16.6 18.5 ...
+## $ Bath.baseline : num 46.7 47.8 49.5 48.3 53.3 ...
+## $ Dishwasher.baseline : num 23 20.5 25.6 22.5 22 ...
+## $ KitchenSink.baseline : num 30.8 33.9 30 27.3 29.3 ...
+## $ Shower.baseline : num 30.1 39.4 23.6 29.3 28.8 ...
+## $ WC.baseline : num 67.3 108 58.4 64.2 54.5 ...
+## $ WashingMachine.baseline: num 81.9 94.5 60.3 84.1 85.8 ...
+## $ External.baseline : num 0 12.9 13.1 11.2 0 ...
## $ model : chr "v1_3" "v1_3" "v1_3" "v1_3" ...
## - attr(*, ".internal.selfref")=<externalptr>
## - attr(*, "sorted")= chr "metered" "occupancy"</code></pre>
@@ -6498,15 +6506,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="center">Min. : 1.000</td>
<td align="center">Length:433800</td>
<td align="center">Min. :1.000</td>
-<td align="left">Min. :272.6</td>
-<td align="left">Min. :11.91</td>
-<td align="left">Min. : 33.34</td>
-<td align="left">Min. :14.08</td>
+<td align="left">Min. :245.8</td>
+<td align="left">Min. :12.59</td>
+<td align="left">Min. : 37.18</td>
+<td align="left">Min. :13.80</td>
<td align="left">Min. :-2.511</td>
-<td align="left">Min. :27.70</td>
-<td align="left">Min. :20.85</td>
-<td align="left">Min. : 48.18</td>
-<td align="left">Min. : 56.27</td>
+<td align="left">Min. :27.22</td>
+<td align="left">Min. :22.41</td>
+<td align="left">Min. : 49.10</td>
+<td align="left">Min. : 57.64</td>
</tr>
<tr class="even">
<td></td>
@@ -6514,15 +6522,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="center">1st Qu.: 4.000</td>
<td align="center">Class :character</td>
<td align="center">1st Qu.:1.000</td>
-<td align="left">1st Qu.:349.2</td>
-<td align="left">1st Qu.:19.09</td>
-<td align="left">1st Qu.: 57.94</td>
-<td align="left">1st Qu.:20.89</td>
-<td align="left">1st Qu.:11.063</td>
-<td align="left">1st Qu.:35.01</td>
-<td align="left">1st Qu.:33.41</td>
-<td align="left">1st Qu.: 86.87</td>
-<td align="left">1st Qu.: 75.04</td>
+<td align="left">1st Qu.:346.2</td>
+<td align="left">1st Qu.:18.77</td>
+<td align="left">1st Qu.: 57.92</td>
+<td align="left">1st Qu.:20.87</td>
+<td align="left">1st Qu.:11.194</td>
+<td align="left">1st Qu.:35.06</td>
+<td align="left">1st Qu.:33.09</td>
+<td align="left">1st Qu.: 85.82</td>
+<td align="left">1st Qu.: 75.12</td>
</tr>
<tr class="odd">
<td></td>
@@ -6530,15 +6538,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="center">Median : 7.000</td>
<td align="center">Mode :character</td>
<td align="center">Median :2.000</td>
-<td align="left">Median :425.6</td>
-<td align="left">Median :25.68</td>
-<td align="left">Median : 73.56</td>
-<td align="left">Median :22.42</td>
-<td align="left">Median :15.800</td>
-<td align="left">Median :44.60</td>
-<td align="left">Median :37.55</td>
-<td align="left">Median :110.38</td>
-<td align="left">Median : 83.66</td>
+<td align="left">Median :427.6</td>
+<td align="left">Median :25.61</td>
+<td align="left">Median : 73.34</td>
+<td align="left">Median :22.29</td>
+<td align="left">Median :16.403</td>
+<td align="left">Median :44.82</td>
+<td align="left">Median :37.25</td>
+<td align="left">Median :110.61</td>
+<td align="left">Median : 83.88</td>
</tr>
<tr class="even">
<td></td>
@@ -6546,15 +6554,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="center">Mean : 6.523</td>
<td align="center">NA</td>
<td align="center">Mean :2.407</td>
-<td align="left">Mean :408.6</td>
-<td align="left">Mean :24.46</td>
-<td align="left">Mean : 71.86</td>
-<td align="left">Mean :22.69</td>
-<td align="left">Mean :15.789</td>
-<td align="left">Mean :42.33</td>
-<td align="left">Mean :37.53</td>
-<td align="left">Mean :107.99</td>
-<td align="left">Mean : 86.01</td>
+<td align="left">Mean :408.8</td>
+<td align="left">Mean :24.45</td>
+<td align="left">Mean : 71.71</td>
+<td align="left">Mean :22.52</td>
+<td align="left">Mean :16.037</td>
+<td align="left">Mean :42.27</td>
+<td align="left">Mean :37.42</td>
+<td align="left">Mean :108.61</td>
+<td align="left">Mean : 85.78</td>
</tr>
<tr class="odd">
<td></td>
@@ -6562,15 +6570,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="center">3rd Qu.:10.000</td>
<td align="center">NA</td>
<td align="center">3rd Qu.:3.000</td>
-<td align="left">3rd Qu.:458.7</td>
-<td align="left">3rd Qu.:28.79</td>
-<td align="left">3rd Qu.: 82.83</td>
-<td align="left">3rd Qu.:24.30</td>
-<td align="left">3rd Qu.:22.694</td>
-<td align="left">3rd Qu.:47.99</td>
-<td align="left">3rd Qu.:41.76</td>
-<td align="left">3rd Qu.:126.22</td>
-<td align="left">3rd Qu.: 94.54</td>
+<td align="left">3rd Qu.:460.5</td>
+<td align="left">3rd Qu.:28.77</td>
+<td align="left">3rd Qu.: 83.58</td>
+<td align="left">3rd Qu.:24.05</td>
+<td align="left">3rd Qu.:22.734</td>
+<td align="left">3rd Qu.:47.93</td>
+<td align="left">3rd Qu.:41.45</td>
+<td align="left">3rd Qu.:128.10</td>
+<td align="left">3rd Qu.: 93.69</td>
</tr>
<tr class="even">
<td></td>
@@ -6578,15 +6586,15 @@ kable(caption = "Summary of final household data (litres/day) - model v1_3&
<td align="center">Max. :12.000</td>
<td align="center">NA</td>
<td align="center">Max. :6.000</td>
-<td align="left">Max. :554.1</td>
-<td align="left">Max. :39.79</td>
-<td align="left">Max. :138.75</td>
-<td align="left">Max. :32.93</td>
-<td align="left">Max. :55.837</td>
-<td align="left">Max. :59.02</td>
-<td align="left">Max. :62.59</td>
-<td align="left">Max. :186.97</td>
-<td align="left">Max. :154.86</td>
+<td align="left">Max. :555.7</td>
+<td align="left">Max. :43.10</td>
+<td align="left">Max. :128.28</td>
+<td align="left">Max. :35.07</td>
+<td align="left">Max. :67.849</td>
+<td align="left">Max. :61.66</td>
+<td align="left">Max. :62.86</td>
+<td align="left">Max. :184.94</td>
+<td align="left">Max. :155.90</td>
</tr>
</tbody>
</table>
@@ -6873,14 +6881,14 @@ kable(caption = "Summary statistics", t)</code></pre>
<tr class="odd">
<td align="left">v1_3</td>
<td align="left">Not metered</td>
-<td align="right">453.7999</td>
-<td align="right">255.3888</td>
+<td align="right">455.7314</td>
+<td align="right">250.3137</td>
</tr>
<tr class="even">
<td align="left">v1_3</td>
<td align="left">Metered</td>
-<td align="right">340.9167</td>
-<td align="right">183.7912</td>
+<td align="right">338.3823</td>
+<td align="right">189.7024</td>
</tr>
<tr class="odd">
<td align="left">v2_0</td>
@@ -6979,6 +6987,9 @@ myPlot</code></pre>
<li>as for WC but stratified by top & bottom 50% shower litres/day within household size</li>
</ul></li>
</ul>
+<blockquote>
+<p>somehow this process needs to take account of the ‘existing’ uptake levels in 2011 in model v2 (based on SPRG survey data)</p>
+</blockquote>
<pre class="r"><code># start with a collapsed year/month spine
hhFinalDataComboExpandedDT <- hhFinalDataComboExpandedDT[, `:=`(obsDate, ymd(paste0(currYear,
@@ -7195,18 +7206,31 @@ dt <- hhFinalDataComboExpandedDT[currYear == 2012 & model == "v1_3&q
Dishwasher = mean(Dishwasher.baseline.madj), External = mean(External.baseline.madj),
Shower = mean(Shower.baseline.madj.we), WC = mean(WC.baseline.madj.we),
WashingMachine = mean(WashingMachine.baseline.madj)), by = .(metered, currMon)]
+# recast dt to make plotting easier
+plotDT <- melt(dt, id.vars = c("currMon", "metered"))
+plotDT <- plotDT[, `:=`(Usage, variable)]
-myPlot <- ggplot(dt, aes(x = factor(currMon), group = metered)) + # geom_boxplot() +
-geom_line(aes(y = Basin, colour = "Basin")) + geom_line(aes(y = Bath, colour = "Bath")) +
- geom_line(aes(y = KitchenSink, colour = "Kitchen Sink")) + geom_line(aes(y = Dishwasher,
- colour = "Dishwasher")) + geom_line(aes(y = External, colour = "External")) +
- geom_line(aes(y = Shower, colour = "Shower")) + geom_line(aes(y = WC, colour = "WC")) +
- geom_line(aes(y = WashingMachine, colour = "Washing Machine")) + facet_grid(. ~
- metered, scales = "free") + theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+myPlot <- ggplot(plotDT, aes(x = factor(currMon), y = value, group = Usage)) +
+ geom_line(aes(colour = Usage)) + facet_grid(. ~ metered, scales = "free") +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
labs(y = "Mean litres/day", x = "Month", title = myTitle, caption = myCaption)
myPlot</code></pre>
<p><img src="impetusModel_files/figure-html/final%20model%20v1_3%202012%20by%20month-1.png" /><!-- --></p>
+<pre class="r"><code># version with linetype for use in bw fig
+myPlot <- ggplot(plotDT, aes(x = factor(currMon), y = value, group = Usage)) +
+ geom_line(aes(linetype = Usage)) + facet_grid(. ~ metered, scales = "free") +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+ labs(y = "Mean litres/day", x = "Month", caption = myCaption)
+
+myPlot</code></pre>
+<p><img src="impetusModel_files/figure-html/final%20model%20v1_3%202012%20by%20month-2.png" /><!-- --></p>
+<pre class="r"><code># Grey scale version if required
+myPlot <- myPlot + theme_bw()
+
+# Figure for IWA Bath final paper
+# (http://ws.iwaponline.com/content/early/2018/02/13/ws.2018.035)
+ggsave("Fig3_Final_model_v1_3_2012_by_month.pdf", plot = myPlot, dpi = 400)</code></pre>
<pre class="r"><code>myTitle <- "All uses (all years)"
myCaption <- "IMPETUS model: synthetic households (n = 1800 per month)\nModel v1\nBaseline water efficiency uptake"
@@ -7299,27 +7323,27 @@ myPlot</code></pre>
##
## Basin.baseline Bath.baseline Dishwasher.baseline
## Min. : 10.40 Min. : 0.00 Min. : 0.00
-## 1st Qu.: 21.30 1st Qu.: 26.40 1st Qu.: 0.00
-## Median : 26.69 Median : 56.91 Median :19.83
-## Mean : 39.67 Mean : 54.96 Mean :13.40
-## 3rd Qu.: 39.72 3rd Qu.: 76.67 3rd Qu.:23.27
-## Max. :463.20 Max. :138.66 Max. :32.93
+## 1st Qu.: 20.94 1st Qu.: 26.40 1st Qu.: 0.00
+## Median : 26.64 Median : 56.91 Median :19.80
+## Mean : 39.66 Mean : 54.88 Mean :13.31
+## 3rd Qu.: 39.72 3rd Qu.: 76.50 3rd Qu.:23.13
+## Max. :463.20 Max. :128.19 Max. :35.07
## NA's :12050
-## KitchenSink.baseline Shower.baseline WC.baseline
-## Min. : 7.57 Min. : 0.00 Min. : 25.00
-## 1st Qu.:15.14 1st Qu.: 34.55 1st Qu.: 75.00
-## Median :32.31 Median : 41.32 Median :100.00
-## Mean :31.51 Mean : 69.10 Mean : 99.92
-## 3rd Qu.:45.05 3rd Qu.: 93.60 3rd Qu.:125.00
-## Max. :75.70 Max. :513.83 Max. :262.50
-## NA's :11568 NA's :12773
+## KitchenSink.baseline Shower.baseline WC.baseline
+## Min. : 7.57 Min. : 0.00 Min. : 25.0
+## 1st Qu.:15.14 1st Qu.: 34.23 1st Qu.: 75.0
+## Median :32.10 Median : 41.06 Median :100.0
+## Mean :31.48 Mean : 69.04 Mean :100.2
+## 3rd Qu.:45.14 3rd Qu.: 93.60 3rd Qu.:127.0
+## Max. :75.70 Max. :513.83 Max. :262.5
+## NA's :11568 NA's :12773
## WashingMachine.baseline External.baseline Basin
## Min. : 0.00 Min. :-1.23 Min. :-0.0908
-## 1st Qu.: 16.67 1st Qu.: 1.13 1st Qu.: 0.0570
-## Median : 67.78 Median :16.43 Median : 0.1315
-## Mean : 56.86 Mean :17.92 Mean : 0.1300
-## 3rd Qu.: 85.26 3rd Qu.:26.01 3rd Qu.: 0.1740
-## Max. :154.90 Max. :97.50 Max. : 0.4506
+## 1st Qu.: 16.67 1st Qu.: 1.32 1st Qu.: 0.0570
+## Median : 67.23 Median :16.88 Median : 0.1315
+## Mean : 56.74 Mean :18.06 Mean : 0.1300
+## 3rd Qu.: 85.36 3rd Qu.:25.76 3rd Qu.: 0.1740
+## Max. :155.94 Max. :97.50 Max. : 0.4506
## NA's :8435 NA's :40247
## Bath Dishwasher External KitchenSink
## Min. :-3.9549 Min. :-2.1795 Min. :-1.28218 Min. :-0.10074
@@ -7339,27 +7363,27 @@ myPlot</code></pre>
##
## Basin.baseline.madj Bath.baseline.madj Dishwasher.baseline.madj
## Min. : 10.33 Min. : -3.955 Min. :-2.17945
-## 1st Qu.: 21.45 1st Qu.: 26.202 1st Qu.:-0.04467
-## Median : 26.86 Median : 55.730 Median :18.98319
-## Mean : 39.80 Mean : 53.771 Mean :12.73835
-## 3rd Qu.: 39.81 3rd Qu.: 74.870 3rd Qu.:22.56947
-## Max. :463.65 Max. :138.755 Max. :32.93016
+## 1st Qu.: 21.11 1st Qu.: 26.202 1st Qu.:-0.04467
+## Median : 26.85 Median : 55.606 Median :18.88683
+## Mean : 39.79 Mean : 53.693 Mean :12.65217
+## 3rd Qu.: 39.82 3rd Qu.: 74.710 3rd Qu.:22.41976
+## Max. :463.65 Max. :128.283 Max. :35.07312
## NA's :12050
## External.baseline.madj KitchenSink.baseline.madj Shower.baseline.madj
## Min. :-2.51 Min. : 7.469 Min. : -0.244
-## 1st Qu.: 1.63 1st Qu.:15.468 1st Qu.: 35.026
-## Median :16.60 Median :32.471 Median : 41.929
-## Mean :18.04 Mean :31.663 Mean : 69.528
-## 3rd Qu.:26.11 3rd Qu.:45.198 3rd Qu.: 93.587
+## 1st Qu.: 1.85 1st Qu.:15.468 1st Qu.: 34.704
+## Median :17.06 Median :32.264 Median : 41.658
+## Mean :18.18 Mean :31.634 Mean : 69.469
+## 3rd Qu.:25.88 3rd Qu.:45.291 3rd Qu.: 93.587
## Max. :98.17 Max. :76.121 Max. :515.302
## NA's :40247 NA's :11568
## WC.baseline.madj WashingMachine.baseline.madj sumDaily.baseline.madj
## Min. : 20.64 Min. : -3.245 Min. : 53.53
-## 1st Qu.: 73.50 1st Qu.: 18.342 1st Qu.: 310.28
-## Median : 98.95 Median : 68.550 Median : 387.12
-## Mean : 98.78 Mean : 56.589 Mean : 382.56
-## 3rd Qu.:123.89 3rd Qu.: 84.742 3rd Qu.: 460.74
-## Max. :262.81 Max. :154.862 Max. :1153.15
+## 1st Qu.: 73.00 1st Qu.: 18.342 1st Qu.: 307.77
+## Median : 99.57 Median : 68.052 Median : 386.97
+## Mean : 99.11 Mean : 56.469 Mean : 382.64
+## 3rd Qu.:125.24 3rd Qu.: 84.807 3rd Qu.: 462.31
+## Max. :262.81 Max. :155.901 Max. :1153.15
## NA's :12773 NA's :8435 NA's :40247
## currMonS occRed loWC loSh
## Length:827353 Min. :1.0 Min. :0 Min. :0
@@ -7371,18 +7395,18 @@ myPlot</code></pre>
##
## dualFlushWC loFlowShower WC.baseline.madj.we
## Length:827353 Length:827353 Min. : 9.814
-## Class :character Class :character 1st Qu.: 55.055
-## Mode :character Mode :character Median : 79.842
-## Mean : 87.819
-## 3rd Qu.:116.706
+## Class :character Class :character 1st Qu.: 55.517
+## Mode :character Mode :character Median : 79.470
+## Mean : 88.086
+## 3rd Qu.:118.059
## Max. :262.811
## NA's :12773
## Shower.baseline.madj.we sumDaily.baseline.madj.we
-## Min. : -0.244 Min. : 35.99
-## 1st Qu.: 32.402 1st Qu.: 292.81
-## Median : 40.788 Median : 368.34
-## Mean : 65.454 Mean : 367.56
-## 3rd Qu.: 85.459 3rd Qu.: 449.20
+## Min. : -0.244 Min. : 35.59
+## 1st Qu.: 32.004 1st Qu.: 291.23
+## Median : 40.509 Median : 369.12
+## Mean : 65.392 Mean : 367.59
+## 3rd Qu.: 85.431 3rd Qu.: 451.23
## Max. :515.302 Max. :1152.91
## NA's :11568 NA's :40247</code></pre>
</div>
@@ -7561,10 +7585,10 @@ Basin.baseline
815,303
</td>
<td>
-39.670
+39.663
</td>
<td>
-39.837
+39.844
</td>
<td>
10.400
@@ -7581,16 +7605,16 @@ Bath.baseline
827,353
</td>
<td>
-54.960
+54.882
</td>
<td>
-26.245
+26.253
</td>
<td>
0.000
</td>
<td>
-138.664
+128.192
</td>
</tr>
<tr>
@@ -7601,16 +7625,16 @@ Dishwasher.baseline
827,353
</td>
<td>
-13.396
+13.310
</td>
<td>
-10.848
+10.759
</td>
<td>
0.000
</td>
<td>
-32.930
+35.073
</td>
</tr>
<tr>
@@ -7621,10 +7645,10 @@ KitchenSink.baseline
827,353
</td>
<td>
-31.506
+31.477
</td>
<td>
-14.239
+14.212
</td>
<td>
7.570
@@ -7641,10 +7665,10 @@ Shower.baseline
815,785
</td>
<td>
-69.102
+69.042
</td>
<td>
-62.510
+62.550
</td>
<td>
0.000
@@ -7661,10 +7685,10 @@ WC.baseline
814,580
</td>
<td>
-99.921
+100.249
</td>
<td>
-38.938
+39.418
</td>
<td>
25.000
@@ -7681,16 +7705,16 @@ WashingMachine.baseline
818,918
</td>
<td>
-56.862
+56.743
</td>
<td>
-35.164
+35.021
</td>
<td>
0.000
</td>
<td>
-154.898
+155.937
</td>
</tr>
<tr>
@@ -7701,10 +7725,10 @@ External.baseline
787,106
</td>
<td>
-17.922
+18.059
</td>
<td>
-15.079
+15.069
</td>
<td>
-1.229
@@ -7881,10 +7905,10 @@ Basin.baseline.madj
815,303
</td>
<td>
-39.800
+39.792
</td>
<td>
-39.834
+39.841
</td>
<td>
10.328
@@ -7901,16 +7925,16 @@ Bath.baseline.madj
827,353
</td>
<td>
-53.771
+53.693
</td>
<td>
-25.997
+26.000
</td>
<td>
-3.955
</td>
<td>
-138.755
+128.283
</td>
</tr>
<tr>
@@ -7921,16 +7945,16 @@ Dishwasher.baseline.madj
827,353
</td>
<td>
-12.738
+12.652
</td>
<td>
-10.827
+10.739
</td>
<td>
-2.179
</td>
<td>
-32.930
+35.073
</td>
</tr>
<tr>
@@ -7941,10 +7965,10 @@ External.baseline.madj
787,106
</td>
<td>
-18.044
+18.181
</td>
<td>
-15.119
+15.110
</td>
<td>
-2.511
@@ -7961,10 +7985,10 @@ KitchenSink.baseline.madj
827,353
</td>
<td>
-31.663
+31.634
</td>
<td>
-14.237
+14.210
</td>
<td>
7.469
@@ -7981,10 +8005,10 @@ Shower.baseline.madj
815,785
</td>
<td>
-69.528
+69.469
</td>
<td>
-62.516
+62.556
</td>
<td>
-0.244
@@ -8001,10 +8025,10 @@ WC.baseline.madj
814,580
</td>
<td>
-98.778
+99.107
</td>
<td>
-38.647
+39.121
</td>
<td>
20.638
@@ -8021,16 +8045,16 @@ WashingMachine.baseline.madj
818,918
</td>
<td>
-56.589
+56.469
</td>
<td>
-34.985
+34.828
</td>
<td>
-3.245
</td>
<td>
-154.862
+155.901
</td>
</tr>
<tr>
@@ -8041,10 +8065,10 @@ sumDaily.baseline.madj
787,106
</td>
<td>
-382.559
+382.639
</td>
<td>
-133.745
+134.330
</td>
<td>
53.528
@@ -8121,10 +8145,10 @@ WC.baseline.madj.we
814,580
</td>
<td>
-87.819
+88.086
</td>
<td>
-41.289
+41.660
</td>
<td>
9.814
@@ -8141,10 +8165,10 @@ Shower.baseline.madj.we
815,785
</td>
<td>
-65.454
+65.392
</td>
<td>
-60.249
+60.272
</td>
<td>
-0.244
@@ -8161,13 +8185,13 @@ sumDaily.baseline.madj.we
787,106
</td>
<td>
-367.555
+367.586
</td>
<td>
-131.067
+131.572
</td>
<td>
-35.986
+35.586
</td>
<td>
1,152.909
@@ -9076,7 +9100,7 @@ for(y in minYear:maxYear){
<pre><code>##
## Dual flush Single flush
## Dual flush 139980 0
-## Single flush 109341 492207</code></pre>
+## Single flush 109667 491881</code></pre>
<pre class="r"><code># > test ----
plotOrigDT <- hhFinalDataComboExpandedCEHDT[model == "v1_3", .(nHHs = .N,
pcHHs = .N/1800), by = .(obsDate, flush = dualFlushWC)]
@@ -9183,235 +9207,235 @@ for (y in minYear:maxYear) {
## [1] "Updating low flow shower uptake for year: 1995 & month 3 (2. Developing)"
## [1] "N cases selected: 3254"
## [1] "Updating low flow shower uptake for year: 1995 & month 4 (2. Developing)"
-## [1] "N cases selected: 3246"
+## [1] "N cases selected: 3248"
## [1] "Updating low flow shower uptake for year: 1995 & month 5 (2. Developing)"
-## [1] "N cases selected: 3240"
+## [1] "N cases selected: 3238"
## [1] "Updating low flow shower uptake for year: 1995 & month 6 (2. Developing)"
-## [1] "N cases selected: 3232"
+## [1] "N cases selected: 3231"
## [1] "Updating low flow shower uptake for year: 1995 & month 7 (2. Developing)"
-## [1] "N cases selected: 3223"
+## [1] "N cases selected: 3225"
## [1] "Updating low flow shower uptake for year: 1995 & month 8 (2. Developing)"
-## [1] "N cases selected: 3217"
+## [1] "N cases selected: 3215"
## [1] "Updating low flow shower uptake for year: 1995 & month 9 (3. Drought)"
-## [1] "N cases selected: 3209"
+## [1] "N cases selected: 3207"
## [1] "Updating low flow shower uptake for year: 1995 & month 10 (3. Drought)"
-## [1] "N cases selected: 3197"
+## [1] "N cases selected: 3198"
## [1] "Updating low flow shower uptake for year: 1995 & month 11 (3. Drought)"
-## [1] "N cases selected: 3186"
+## [1] "N cases selected: 3190"
## [1] "Updating low flow shower uptake for year: 1995 & month 12 (2. Developing)"
-## [1] "N cases selected: 3179"
+## [1] "N cases selected: 3180"
## [1] "Year: 1996"
## [1] "Updating low flow shower uptake for year: 1996 & month 1 (2. Developing)"
-## [1] "N cases selected: 3173"
+## [1] "N cases selected: 3170"
## [1] "Updating low flow shower uptake for year: 1996 & month 2 (2. Developing)"
-## [1] "N cases selected: 3166"
+## [1] "N cases selected: 3163"
## [1] "Updating low flow shower uptake for year: 1996 & month 3 (3. Drought)"
-## [1] "N cases selected: 3161"
+## [1] "N cases selected: 3154"
## [1] "Updating low flow shower uptake for year: 1996 & month 4 (3. Drought)"
-## [1] "N cases selected: 3147"
+## [1] "N cases selected: 3149"
## [1] "Updating low flow shower uptake for year: 1996 & month 5 (3. Drought)"
-## [1] "N cases selected: 3138"
+## [1] "N cases selected: 3135"
## [1] "Updating low flow shower uptake for year: 1996 & month 6 (3. Drought)"
-## [1] "N cases selected: 3130"
+## [1] "N cases selected: 3132"
## [1] "Updating low flow shower uptake for year: 1996 & month 7 (3. Drought)"
## [1] "N cases selected: 3117"
## [1] "Updating low flow shower uptake for year: 1996 & month 8 (3. Drought)"
-## [1] "N cases selected: 3116"
+## [1] "N cases selected: 3110"
## [1] "Updating low flow shower uptake for year: 1996 & month 9 (3. Drought)"
## [1] "N cases selected: 3100"
## [1] "Updating low flow shower uptake for year: 1996 & month 10 (3. Drought)"
-## [1] "N cases selected: 3087"
+## [1] "N cases selected: 3092"
## [1] "Updating low flow shower uptake for year: 1996 & month 11 (3. Drought)"
-## [1] "N cases selected: 3085"
+## [1] "N cases selected: 3078"
## [1] "Updating low flow shower uptake for year: 1996 & month 12 (4. Severe Drought)"
-## [1] "N cases selected: 3075"
+## [1] "N cases selected: 3078"
## [1] "Year: 1997"
## [1] "Updating low flow shower uptake for year: 1997 & month 1 (4. Severe Drought)"
-## [1] "N cases selected: 3057"
+## [1] "N cases selected: 3058"
## [1] "Updating low flow shower uptake for year: 1997 & month 2 (4. Severe Drought)"
-## [1] "N cases selected: 3050"
+## [1] "N cases selected: 3047"
## [1] "Updating low flow shower uptake for year: 1997 & month 3 (4. Severe Drought)"
## [1] "N cases selected: 3039"
## [1] "Updating low flow shower uptake for year: 1997 & month 4 (4. Severe Drought)"
-## [1] "N cases selected: 3023"
+## [1] "N cases selected: 3026"
## [1] "Updating low flow shower uptake for year: 1997 & month 5 (4. Severe Drought)"
-## [1] "N cases selected: 3017"
+## [1] "N cases selected: 3012"
## [1] "Updating low flow shower uptake for year: 1997 & month 6 (5. Recovering)"
-## [1] "N cases selected: 3001"
+## [1] "N cases selected: 3003"
## [1] "Updating low flow shower uptake for year: 1997 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2991"
+## [1] "N cases selected: 2998"
## [1] "Updating low flow shower uptake for year: 1997 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2977"
+## [1] "N cases selected: 2980"
## [1] "Updating low flow shower uptake for year: 1997 & month 9 (4. Severe Drought)"
-## [1] "N cases selected: 2987"
+## [1] "N cases selected: 2978"
## [1] "Updating low flow shower uptake for year: 1997 & month 10 (4. Severe Drought)"
-## [1] "N cases selected: 2971"
+## [1] "N cases selected: 2966"
## [1] "Updating low flow shower uptake for year: 1997 & month 11 (4. Severe Drought)"
-## [1] "N cases selected: 2956"
+## [1] "N cases selected: 2959"
## [1] "Updating low flow shower uptake for year: 1997 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2951"
+## [1] "N cases selected: 2952"
## [1] "Year: 1998"
## [1] "Updating low flow shower uptake for year: 1998 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2942"
+## [1] "N cases selected: 2946"
## [1] "Updating low flow shower uptake for year: 1998 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2930"
+## [1] "N cases selected: 2932"
## [1] "Updating low flow shower uptake for year: 1998 & month 3 (5. Recovering)"
-## [1] "N cases selected: 2931"
+## [1] "N cases selected: 2924"
## [1] "Updating low flow shower uptake for year: 1998 & month 4 (5. Recovering)"
-## [1] "N cases selected: 2926"
+## [1] "N cases selected: 2927"
## [1] "Updating low flow shower uptake for year: 1998 & month 5 (5. Recovering)"
-## [1] "N cases selected: 2915"
+## [1] "N cases selected: 2917"
## [1] "Updating low flow shower uptake for year: 1998 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2912"
+## [1] "N cases selected: 2904"
## [1] "Updating low flow shower uptake for year: 1998 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2905"
+## [1] "N cases selected: 2898"
## [1] "Updating low flow shower uptake for year: 1998 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2904"
+## [1] "N cases selected: 2894"
## [1] "Updating low flow shower uptake for year: 1998 & month 9 (5. Recovering)"
-## [1] "N cases selected: 2896"
+## [1] "N cases selected: 2893"
## [1] "Updating low flow shower uptake for year: 1998 & month 10 (5. Recovering)"
-## [1] "N cases selected: 2888"
+## [1] "N cases selected: 2893"
## [1] "Updating low flow shower uptake for year: 1998 & month 11 (5. Recovering)"
-## [1] "N cases selected: 2879"
+## [1] "N cases selected: 2889"
## [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: 2734"
+## [1] "N cases selected: 2736"
## [1] "Updating low flow shower uptake for year: 2003 & month 4 (2. Developing)"
-## [1] "N cases selected: 2734"
-## [1] "Updating low flow shower uptake for year: 2003 & month 5 (2. Developing)"
## [1] "N cases selected: 2736"
+## [1] "Updating low flow shower uptake for year: 2003 & month 5 (2. Developing)"
+## [1] "N cases selected: 2720"
## [1] "Updating low flow shower uptake for year: 2003 & month 6 (2. Developing)"
-## [1] "N cases selected: 2723"
+## [1] "N cases selected: 2721"
## [1] "Updating low flow shower uptake for year: 2003 & month 7 (2. Developing)"
-## [1] "N cases selected: 2707"
+## [1] "N cases selected: 2712"
## [1] "Updating low flow shower uptake for year: 2003 & month 8 (2. Developing)"
-## [1] "N cases selected: 2711"
+## [1] "N cases selected: 2715"
## [1] "Updating low flow shower uptake for year: 2003 & month 9 (3. Drought)"
-## [1] "N cases selected: 2701"
+## [1] "N cases selected: 2711"
## [1] "Updating low flow shower uptake for year: 2003 & month 10 (3. Drought)"
-## [1] "N cases selected: 2694"
+## [1] "N cases selected: 2693"
## [1] "Updating low flow shower uptake for year: 2003 & month 11 (3. Drought)"
-## [1] "N cases selected: 2678"
+## [1] "N cases selected: 2689"
## [1] "Updating low flow shower uptake for year: 2003 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2687"
+## [1] "N cases selected: 2671"
## [1] "Year: 2004"
## [1] "Updating low flow shower uptake for year: 2004 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2660"
+## [1] "N cases selected: 2668"
## [1] "Updating low flow shower uptake for year: 2004 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2670"
+## [1] "N cases selected: 2655"
## [1] "Updating low flow shower uptake for year: 2004 & month 12 (2. Developing)"
-## [1] "N cases selected: 2639"
+## [1] "N cases selected: 2629"
## [1] "Year: 2005"
## [1] "Updating low flow shower uptake for year: 2005 & month 1 (2. Developing)"
-## [1] "N cases selected: 2633"
+## [1] "N cases selected: 2630"
## [1] "Updating low flow shower uptake for year: 2005 & month 2 (2. Developing)"
-## [1] "N cases selected: 2609"
+## [1] "N cases selected: 2618"
## [1] "Updating low flow shower uptake for year: 2005 & month 3 (2. Developing)"
-## [1] "N cases selected: 2623"
+## [1] "N cases selected: 2613"
## [1] "Updating low flow shower uptake for year: 2005 & month 4 (2. Developing)"
-## [1] "N cases selected: 2619"
+## [1] "N cases selected: 2604"
## [1] "Updating low flow shower uptake for year: 2005 & month 5 (2. Developing)"
-## [1] "N cases selected: 2601"
+## [1] "N cases selected: 2619"
## [1] "Updating low flow shower uptake for year: 2005 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2600"
+## [1] "N cases selected: 2605"
## [1] "Updating low flow shower uptake for year: 2005 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2593"
+## [1] "N cases selected: 2600"
## [1] "Updating low flow shower uptake for year: 2005 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2584"
+## [1] "N cases selected: 2604"
## [1] "Updating low flow shower uptake for year: 2005 & month 9 (2. Developing)"
-## [1] "N cases selected: 2582"
+## [1] "N cases selected: 2574"
## [1] "Updating low flow shower uptake for year: 2005 & month 10 (2. Developing)"
-## [1] "N cases selected: 2581"
+## [1] "N cases selected: 2573"
## [1] "Updating low flow shower uptake for year: 2005 & month 11 (2. Developing)"
-## [1] "N cases selected: 2574"
+## [1] "N cases selected: 2559"
## [1] "Updating low flow shower uptake for year: 2005 & month 12 (3. Drought)"
-## [1] "N cases selected: 2560"
+## [1] "N cases selected: 2557"
## [1] "Year: 2006"
## [1] "Updating low flow shower uptake for year: 2006 & month 1 (3. Drought)"
-## [1] "N cases selected: 2569"
+## [1] "N cases selected: 2552"
## [1] "Updating low flow shower uptake for year: 2006 & month 2 (3. Drought)"
-## [1] "N cases selected: 2546"
+## [1] "N cases selected: 2552"
## [1] "Updating low flow shower uptake for year: 2006 & month 3 (3. Drought)"
-## [1] "N cases selected: 2531"
+## [1] "N cases selected: 2555"
## [1] "Updating low flow shower uptake for year: 2006 & month 4 (3. Drought)"
-## [1] "N cases selected: 2536"
+## [1] "N cases selected: 2535"
## [1] "Updating low flow shower uptake for year: 2006 & month 5 (3. Drought)"
-## [1] "N cases selected: 2522"
+## [1] "N cases selected: 2535"
## [1] "Updating low flow shower uptake for year: 2006 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2529"
+## [1] "N cases selected: 2513"
## [1] "Updating low flow shower uptake for year: 2006 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2518"
+## [1] "N cases selected: 2513"
## [1] "Updating low flow shower uptake for year: 2006 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2516"
+## [1] "N cases selected: 2508"
## [1] "Updating low flow shower uptake for year: 2006 & month 9 (5. Recovering)"
-## [1] "N cases selected: 2502"
+## [1] "N cases selected: 2499"
## [1] "Updating low flow shower uptake for year: 2006 & month 10 (5. Recovering)"
-## [1] "N cases selected: 2505"
+## [1] "N cases selected: 2496"
## [1] "Updating low flow shower uptake for year: 2006 & month 11 (5. Recovering)"
-## [1] "N cases selected: 2500"
+## [1] "N cases selected: 2494"
## [1] "Updating low flow shower uptake for year: 2006 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2474"
+## [1] "N cases selected: 2483"
## [1] "Year: 2007"
## [1] "Updating low flow shower uptake for year: 2007 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2482"
+## [1] "N cases selected: 2478"
## [1] "Updating low flow shower uptake for year: 2007 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2476"
+## [1] "N cases selected: 2463"
## [1] "Year: 2008"
## [1] "Year: 2009"
## [1] "Updating low flow shower uptake for year: 2009 & month 3 (2. Developing)"
-## [1] "N cases selected: 2400"
+## [1] "N cases selected: 2409"
## [1] "Updating low flow shower uptake for year: 2009 & month 4 (2. Developing)"
-## [1] "N cases selected: 2399"
+## [1] "N cases selected: 2380"
## [1] "Updating low flow shower uptake for year: 2009 & month 5 (2. Developing)"
-## [1] "N cases selected: 2405"
+## [1] "N cases selected: 2382"
## [1] "Updating low flow shower uptake for year: 2009 & month 6 (2. Developing)"
-## [1] "N cases selected: 2400"
+## [1] "N cases selected: 2399"
## [1] "Updating low flow shower uptake for year: 2009 & month 7 (2. Developing)"
-## [1] "N cases selected: 2397"
+## [1] "N cases selected: 2388"
## [1] "Updating low flow shower uptake for year: 2009 & month 8 (2. Developing)"
-## [1] "N cases selected: 2380"
+## [1] "N cases selected: 2387"
## [1] "Updating low flow shower uptake for year: 2009 & month 9 (3. Drought)"
-## [1] "N cases selected: 2377"
+## [1] "N cases selected: 2384"
## [1] "Updating low flow shower uptake for year: 2009 & month 10 (3. Drought)"
-## [1] "N cases selected: 2368"
+## [1] "N cases selected: 2377"
## [1] "Updating low flow shower uptake for year: 2009 & month 11 (3. Drought)"
-## [1] "N cases selected: 2359"
+## [1] "N cases selected: 2372"
## [1] "Updating low flow shower uptake for year: 2009 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2363"
+## [1] "N cases selected: 2349"
## [1] "Year: 2010"
## [1] "Updating low flow shower uptake for year: 2010 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2352"
+## [1] "N cases selected: 2349"
## [1] "Updating low flow shower uptake for year: 2010 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2359"
+## [1] "N cases selected: 2337"
## [1] "Updating low flow shower uptake for year: 2010 & month 9 (2. Developing)"
-## [1] "N cases selected: 2335"
+## [1] "N cases selected: 2325"
## [1] "Updating low flow shower uptake for year: 2010 & month 10 (2. Developing)"
## [1] "N cases selected: 2327"
## [1] "Updating low flow shower uptake for year: 2010 & month 11 (2. Developing)"
-## [1] "N cases selected: 2321"
+## [1] "N cases selected: 2315"
## [1] "Updating low flow shower uptake for year: 2010 & month 12 (2. Developing)"
-## [1] "N cases selected: 2316"
+## [1] "N cases selected: 2299"
## [1] "Year: 2011"
## [1] "Updating low flow shower uptake for year: 2011 & month 1 (2. Developing)"
-## [1] "N cases selected: 2300"
+## [1] "N cases selected: 2326"
## [1] "Updating low flow shower uptake for year: 2011 & month 2 (2. Developing)"
-## [1] "N cases selected: 2299"
+## [1] "N cases selected: 2305"
## [1] "Updating low flow shower uptake for year: 2011 & month 3 (3. Drought)"
-## [1] "N cases selected: 2297"
+## [1] "N cases selected: 2291"
## [1] "Updating low flow shower uptake for year: 2011 & month 4 (3. Drought)"
-## [1] "N cases selected: 2301"
+## [1] "N cases selected: 2280"
## [1] "Updating low flow shower uptake for year: 2011 & month 5 (3. Drought)"
-## [1] "N cases selected: 2290"
+## [1] "N cases selected: 2308"
## [1] "Updating low flow shower uptake for year: 2011 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2286"
+## [1] "N cases selected: 2287"
## [1] "Updating low flow shower uptake for year: 2011 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2273"
+## [1] "N cases selected: 2257"
## [1] "Updating low flow shower uptake for year: 2011 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2270"
+## [1] "N cases selected: 2281"
## [1] "Year: 2012"</code></pre>
<pre class="r"><code>print("After model applied")</code></pre>
<pre><code>## [1] "After model applied"</code></pre>
@@ -9419,7 +9443,7 @@ for (y in minYear:maxYear) {
<pre><code>##
## Low flow Normal flow
## Low flow 103304 0
-## Normal flow 60316 577908</code></pre>
+## Normal flow 60567 577657</code></pre>
<pre class="r"><code># > test ----
plotOrigDT <- hhFinalDataComboExpandedCEHDT[model == "v1_3", .(nHHs = .N, pcHHs = .N/1800),
by = .(obsDate, flow = loFlowShower)]
@@ -9442,6 +9466,9 @@ ggplot(plotDT, aes(x = obsDate, y = pcHHs, colour = flow)) + geom_line() + facet
<div id="temporary-use-ban" class="section level3">
<h3><span class="header-section-number">11.4.3</span> Temporary Use Ban</h3>
<p>Now apply the TUB. This one does need to be done by model as it uses a cut point in external consumption which will differ.</p>
+<blockquote>
+<p>We also shoud use the ‘no garden to water’ data in the SPRG survey in the process for v2?</p>
+</blockquote>
<pre class="r"><code># as above but with some variations no need to update forwards as we assume
# people revert to 'normal' after TUB we only do something if we have
# drought or severe drought
@@ -9515,8 +9542,8 @@ 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: 26.7029814730589"
-## [1] "Top 28% cut: 21.2574514397221"
+## [1] "Top 14% cut: 26.5848437091723"
+## [1] "Top 28% cut: 21.5288841242727"
## [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)"
@@ -9525,8 +9552,8 @@ 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: 26.8200355433548"
-## [1] "Top 28% cut: 21.3558054166805"
+## [1] "Top 14% cut: 26.6507521149996"
+## [1] "Top 28% cut: 21.5911132257507"
## [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)"
@@ -9535,8 +9562,8 @@ 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: 26.7032988766881"
-## [1] "Top 28% cut: 21.2813951500138"
+## [1] "Top 14% cut: 26.534015448333"
+## [1] "Top 28% cut: 21.4916495060354"
## [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)"
@@ -9546,8 +9573,8 @@ 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: 27.1150651990317"
-## [1] "Top 28% cut: 21.6257803225655"
+## [1] "Top 14% cut: 26.9271598198798"
+## [1] "Top 28% cut: 21.8801573315507"
## [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)"
@@ -9556,8 +9583,8 @@ 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: 27.3162147990317"
-## [1] "Top 28% cut: 21.8051872812671"
+## [1] "Top 14% cut: 27.0892998198798"
+## [1] "Top 28% cut: 22.0422973315507"
## [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)"
@@ -9566,8 +9593,8 @@ 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: 27.4064154728594"
-## [1] "Top 28% cut: 22.0049088214481"
+## [1] "Top 14% cut: 27.287840375839"
+## [1] "Top 28% cut: 22.2357769049278"
## [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)"
@@ -9576,8 +9603,8 @@ 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: 28.0140954728594"
-## [1] "Top 28% cut: 22.6125888214481"
+## [1] "Top 14% cut: 27.895520375839"
+## [1] "Top 28% cut: 22.874616748026"
## [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)"
@@ -9586,8 +9613,8 @@ 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: 27.8746721395261"
-## [1] "Top 28% cut: 22.4671471912724"
+## [1] "Top 14% cut: 27.7560970425057"
+## [1] "Top 28% cut: 22.7040335715945"
## [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)"
@@ -9596,8 +9623,8 @@ 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: 27.2972596200058"
-## [1] "Top 28% cut: 21.8389114229238"
+## [1] "Top 14% cut: 27.2393508100736"
+## [1] "Top 28% cut: 22.0825818423683"
## [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)"
@@ -9606,8 +9633,8 @@ 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: 27.2149632183101"
-## [1] "Top 28% cut: 21.7230068029683"
+## [1] "Top 14% cut: 27.0323464865465"
+## [1] "Top 28% cut: 21.9853439982174"
## [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)"
@@ -9616,8 +9643,8 @@ 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: 26.6505522100214"
-## [1] "Top 28% cut: 21.1598938762707"
+## [1] "Top 14% cut: 26.4606684316816"
+## [1] "Top 28% cut: 21.3845785513219"
## [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)"
@@ -9626,8 +9653,8 @@ 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: 26.4345055022416"
-## [1] "Top 28% cut: 20.9404768029683"
+## [1] "Top 14% cut: 26.2498164865465"
+## [1] "Top 28% cut: 21.2028139982174"
## [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)"
@@ -9636,8 +9663,8 @@ 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: 26.8804788766881"
-## [1] "Top 28% cut: 21.3853097429373"
+## [1] "Top 14% cut: 26.6847106909446"
+## [1] "Top 28% cut: 21.6029060179886"
## [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)"
@@ -9647,8 +9674,8 @@ 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: 26.9625555433548"
-## [1] "Top 28% cut: 21.4875350166805"
+## [1] "Top 14% cut: 26.7932721149996"
+## [1] "Top 28% cut: 21.7277578904882"
## [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)"
@@ -9657,8 +9684,8 @@ 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: 27.1202793402119"
-## [1] "Top 28% cut: 21.6028649990715"
+## [1] "Top 14% cut: 26.8785364865465"
+## [1] "Top 28% cut: 21.8315339982174"
## [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)"
@@ -9667,8 +9694,8 @@ 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: 27.3628833924386"
-## [1] "Top 28% cut: 21.8951144221809"
+## [1] "Top 14% cut: 27.2050511069816"
+## [1] "Top 28% cut: 22.1588506648841"
## [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)"
@@ -9677,8 +9704,8 @@ 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: 27.2991325990317"
-## [1] "Top 28% cut: 21.8095317892321"
+## [1] "Top 14% cut: 27.1092864865465"
+## [1] "Top 28% cut: 22.0622839982174"
## [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)"
@@ -9687,8 +9714,8 @@ 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: 27.5139492184224"
-## [1] "Top 28% cut: 22.0415126728919"
+## [1] "Top 14% cut: 27.419060375839"
+## [1] "Top 28% cut: 22.3098809287109"
## [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)"
@@ -9697,8 +9724,8 @@ 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: 27.3456800849767"
-## [1] "Top 28% cut: 21.8591934696349"
+## [1] "Top 14% cut: 27.1685331532132"
+## [1] "Top 28% cut: 22.1215306648841"
## [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)"
@@ -9707,8 +9734,8 @@ 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: 26.6380855433548"
-## [1] "Top 28% cut: 21.133903209604"
+## [1] "Top 14% cut: 26.4146339576112"
+## [1] "Top 28% cut: 21.3488673315507"
## [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)"
@@ -9717,8 +9744,8 @@ 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: 26.5840555433548"
-## [1] "Top 28% cut: 21.0995208038063"
+## [1] "Top 14% cut: 26.4147721149996"
+## [1] "Top 28% cut: 21.3395076729654"
## [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)"
@@ -9733,8 +9760,8 @@ 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: 27.327116725772"
-## [1] "Top 28% cut: 21.9034788214481"
+## [1] "Top 14% cut: 27.2170325491869"
+## [1] "Top 28% cut: 22.1773133709197"
## [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)"
@@ -9743,8 +9770,8 @@ 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: 26.6846222100214"
-## [1] "Top 28% cut: 21.1989189429373"
+## [1] "Top 14% cut: 26.4955441279114"
+## [1] "Top 28% cut: 21.4281370749833"
## [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)"
@@ -9753,8 +9780,8 @@ 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: 26.5034188766881"
-## [1] "Top 28% cut: 20.9953398762707"
+## [1] "Top 14% cut: 26.2679989576112"
+## [1] "Top 28% cut: 21.2142006648841"
## [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)"
@@ -9765,8 +9792,8 @@ 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: 26.9356722100214"
-## [1] "Top 28% cut: 21.4466509429373"
+## [1] "Top 14% cut: 26.7465941279114"
+## [1] "Top 28% cut: 21.6739081513219"
## [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)"
@@ -9776,8 +9803,8 @@ 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: 26.9673688766881"
-## [1] "Top 28% cut: 21.4971987500138"
+## [1] "Top 14% cut: 26.798085448333"
+## [1] "Top 28% cut: 21.7360177175557"
## [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)"
@@ -9786,8 +9813,8 @@ 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: 27.1562022100214"
-## [1] "Top 28% cut: 21.6601305429373"
+## [1] "Top 14% cut: 26.9576619576112"
+## [1] "Top 28% cut: 21.8763085513219"
## [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)"
@@ -9796,8 +9823,8 @@ 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: 27.1094333924386"
-## [1] "Top 28% cut: 21.66765920539"
+## [1] "Top 14% cut: 26.9874573736483"
+## [1] "Top 28% cut: 21.9387394682108"
## [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)"
@@ -9806,8 +9833,8 @@ 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: 27.1536166849767"
-## [1] "Top 28% cut: 21.6612701363016"
+## [1] "Top 14% cut: 26.9706098198798"
+## [1] "Top 28% cut: 21.9236073315507"
## [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)"
@@ -9816,8 +9843,8 @@ 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: 27.1068958850891"
-## [1] "Top 28% cut: 21.648203243011"
+## [1] "Top 14% cut: 27.0120070425057"
+## [1] "Top 28% cut: 21.9128499953775"
## [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)"
@@ -9829,8 +9856,8 @@ 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: 27.3143155022416"
-## [1] "Top 28% cut: 21.8202868029683"
+## [1] "Top 14% cut: 27.1296264865465"
+## [1] "Top 28% cut: 22.0826239982174"
## [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)"
@@ -9839,8 +9866,8 @@ 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: 26.5195455433548"
-## [1] "Top 28% cut: 21.0678002166805"
+## [1] "Top 14% cut: 26.3502621149996"
+## [1] "Top 28% cut: 21.2931053218941"
## [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)"
@@ -9849,8 +9876,8 @@ 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: 26.4039103990317"
-## [1] "Top 28% cut: 20.9133207225655"
+## [1] "Top 14% cut: 26.2079898198798"
+## [1] "Top 28% cut: 21.1609873315507"
## [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)"
@@ -9861,8 +9888,8 @@ 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: 27.3679585323651"
-## [1] "Top 28% cut: 21.8735742147611"
+## [1] "Top 14% cut: 27.1591264865465"
+## [1] "Top 28% cut: 22.1121239982174"
## [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)"
@@ -9871,8 +9898,8 @@ 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: 27.5169211990317"
-## [1] "Top 28% cut: 22.0268756558988"
+## [1] "Top 14% cut: 27.3243431532132"
+## [1] "Top 28% cut: 22.2773406648841"
## [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)"
@@ -9881,8 +9908,8 @@ 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: 27.6515988061927"
-## [1] "Top 28% cut: 22.244073857939"
+## [1] "Top 14% cut: 27.5330237091723"
+## [1] "Top 28% cut: 22.4809602382611"
## [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)"
@@ -10083,7 +10110,30 @@ minY <- min(plotTotalDT[model == "v1_3"]$yminDr)
myDrPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
myDrPlot</code></pre>
<p><img src="impetusModel_files/figure-html/Compare%20sum-1.png" /><!-- --></p>
-<pre class="r"><code># 2.0 ----
+<pre class="r"><code># Figure for IWA Bath final paper
+# (http://ws.iwaponline.com/content/early/2018/02/13/ws.2018.035) take the
+# mean of the baseline & WE models (i.e. ignore metering as not mentioned in
+# the text & caption etc) also do not display drought phases (too complex to
+# create key!)
+myCap <- "IMPETUS Model: synthetic households (n = 1800)\n Model v1"
+paperPlotDT <- plotTotalDT[model == "v1_3", .(meanBaselineWeSum = mean(meanBaselineWeSum),
+ meanBaselineDrSum = mean(meanBaselineDrSum)), keyby = obsDate]
+paperPlot <- ggplot(paperPlotDT, aes(x = obsDate)) + geom_line(aes(y = meanBaselineWeSum,
+ colour = "Baseline")) + geom_line(aes(y = meanBaselineDrSum, colour = "Drought model")) +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+ labs(y = "Mean l/hh/day", x = "Date", caption = myCap)
+maxY <- max(paperPlotDT$meanBaselineDrSum)
+minY <- min(paperPlotDT$meanBaselineDrSum)
+
+paperPlot <- ba_IMPETUSaddDroughtPhases(paperPlot, minY, maxY)
+paperPlot</code></pre>
+<p><img src="impetusModel_files/figure-html/Compare%20sum-2.png" /><!-- --></p>
+<pre class="r"><code>ggsave("Fig4_Compare_sum_model_v1_3.pdf", dpi = 400)
+
+# Grey scale version if required myDrPlot <- myDrPlot + theme_bw()
+# ggsave('Fig4_Compare_sum_model_v1_3_gs.pdf', plot = myDrPlot, dpi = 400)
+
+# 2.0 ----
myPlot <- ggplot(plotTotalDT[model == "v2_0"], aes(x = obsDate)) + geom_ribbon(aes(ymin = yminWE,
ymax = ymaxWE, fill = "Baseline 95% CI", group = metered), alpha = 0.5) +
geom_line(aes(y = meanBaselineWeSum, colour = "Baseline", linetype = metered,
@@ -10100,7 +10150,7 @@ maxY <- max(plotTotalDT[model == "v2_0"]$ymaxWE)
minY <- min(plotTotalDT[model == "v2_0"]$yminDr)
myDrPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
myDrPlot</code></pre>
-<p><img src="impetusModel_files/figure-html/Compare%20sum-2.png" /><!-- --></p>
+<p><img src="impetusModel_files/figure-html/Compare%20sum-3.png" /><!-- --></p>
<pre class="r"><code>myPlot <- ggplot(plotTotalDT, aes(x = obsDate)) + geom_ribbon(aes(ymin = yminWE,
ymax = ymaxWE, fill = "Baseline 95% CI", group = metered), alpha = 0.5) +
geom_line(aes(y = meanBaselineWeSum, colour = "Baseline", linetype = metered,
@@ -10117,7 +10167,7 @@ maxY <- max(plotTotalDT$ymaxWE)
minY <- min(plotTotalDT$yminDr)
myDrPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
myDrPlot</code></pre>
-<p><img src="impetusModel_files/figure-html/Compare%20sum-3.png" /><!-- --></p>
+<p><img src="impetusModel_files/figure-html/Compare%20sum-4.png" /><!-- --></p>
<pre class="r"><code>plotTotalDT <- plotTotalDT[, `:=`(pcSaved, 100 * ((meanBaselineWeSum - meanBaselineDrSum)/meanBaselineWeSum))]</code></pre>
<p>The table below shows the mean and maximum savings over the period for each model.</p>
<pre class="r"><code>t <- plotTotalDT[, .(`Min reduction` = round(min(pcSaved), 2), `Mean reduction` = round(mean(pcSaved),
@@ -10139,29 +10189,29 @@ kable(caption = "Model affects (% total reduced)", t)</code></pre>
<td align="left">v1_3</td>
<td align="left">Not metered</td>
<td align="right">0</td>
-<td align="right">2.72</td>
-<td align="right">4.36</td>
+<td align="right">2.70</td>
+<td align="right">4.14</td>
</tr>
<tr class="even">
<td align="left">v1_3</td>
<td align="left">Metered</td>
<td align="right">0</td>
-<td align="right">2.42</td>
-<td align="right">3.53</td>
+<td align="right">2.36</td>
+<td align="right">3.43</td>
</tr>
<tr class="odd">
<td align="left">v2_0</td>
<td align="left">Not metered</td>
<td align="right">0</td>
-<td align="right">3.14</td>
-<td align="right">5.18</td>
+<td align="right">3.46</td>
+<td align="right">5.17</td>
</tr>
<tr class="even">
<td align="left">v2_0</td>
<td align="left">Metered</td>
<td align="right">0</td>
-<td align="right">3.27</td>
-<td align="right">5.40</td>
+<td align="right">2.98</td>
+<td align="right">5.47</td>
</tr>
</tbody>
</table>
@@ -10178,9 +10228,9 @@ model2Red <- plotTotalDT[model == "v2_0" & obsDate == min(obsDa
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 5.92, 5.89%</li>
-<li>model v1_3 showed a reduction of 8.99, 8.79%</li>
-<li>model v2_0 showed a reduction of 8.21, 12.04%</li>
+<li>the baseline model showed a reduction of 5.85, 6.06%</li>
+<li>model v1_3 showed a reduction of 8.59, 9.23%</li>
+<li>model v2_0 showed a reduction of 10.73, 9.45%</li>
</ul>
<p>This is clearly shown in the chart below where:</p>
<ul>
@@ -10197,9 +10247,31 @@ model2Red <- plotTotalDT[model == "v2_0" & obsDate == min(obsDa
maxY <- max(plotTotalDT[model == "v1_3"]$pcSaved)
minY <- 0
-ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)</code></pre>
+myPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
+myPlot</code></pre>
<p><img src="impetusModel_files/figure-html/Chart%20savings-1.png" /><!-- --></p>
-<pre class="r"><code>myPlot <- ggplot(plotTotalDT[model == "v2_0"], aes(x = obsDate, y = pcSaved,
+<pre class="r"><code># Figure for IWA Bath final paper
+# (http://ws.iwaponline.com/content/early/2018/02/13/ws.2018.035) just
+# baseline - WE (ignore metering) re-use previous paper DT
+paperPlotDT <- paperPlotDT[, `:=`(pcSaved, 100 * ((meanBaselineWeSum - meanBaselineDrSum)/meanBaselineWeSum))]
+myCap <- "IMPETUS model: synthetic households (n = 1800)\n Model v1"
+myPlot <- ggplot(paperPlotDT, aes(x = obsDate, y = pcSaved)) + geom_point() +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+ labs(y = "% saving", x = "Date", caption = myCap)
+
+maxY <- max(paperPlotDT$pcSaved)
+minY <- 0
+
+myPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
+myPlot</code></pre>
+<p><img src="impetusModel_files/figure-html/Chart%20savings-2.png" /><!-- --></p>
+<pre class="r"><code>ggsave("Fig5_Chart_savings_v1_3_by_month.pdf", plot = myPlot, dpi = 400)
+
+# Grey scale version if required myPlot <- myPlot + theme_bw()
+# ggsave('Fig5_Chart_savings_v1_3_by_month_gs.pdf', plot = myPlot, dpi =
+# 400)
+
+myPlot <- ggplot(plotTotalDT[model == "v2_0"], aes(x = obsDate, y = pcSaved,
colour = metered)) + geom_point() + theme(legend.title = element_blank()) +
theme(legend.position = "bottom") + facet_grid(model ~ .) + labs(title = "% saving in total l/hh/day",
y = "%", x = "Date")
@@ -10207,7 +10279,7 @@ ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)</code></pre>
maxY <- max(plotTotalDT$pcSaved)
minY <- 0
ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)</code></pre>
-<p><img src="impetusModel_files/figure-html/Chart%20savings-2.png" /><!-- --></p>
+<p><img src="impetusModel_files/figure-html/Chart%20savings-3.png" /><!-- --></p>
<pre class="r"><code>myPlot <- ggplot(plotTotalDT, aes(x = obsDate, y = pcSaved, colour = metered)) +
geom_point() + theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
facet_grid(model ~ .) + labs(title = "% saving in total l/hh/day", y = "%",
@@ -10217,7 +10289,7 @@ maxY <- max(plotTotalDT$pcSaved)
minY <- 0
ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)</code></pre>
-<p><img src="impetusModel_files/figure-html/Chart%20savings-3.png" /><!-- --></p>
+<p><img src="impetusModel_files/figure-html/Chart%20savings-4.png" /><!-- --></p>
<p>Interesting - savings under model v2 are larger. Why?</p>
<p>Create a fake chart so we get a coloured drought phase key for use in the paper/presentations.</p>
<pre class="r"><code>droughtPhaseDT <- as.data.table(rep(2:5))
@@ -10235,6 +10307,7 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
scale_fill_manual(values = c(develCol, droughtCol, sevDroughtCol, recoveringCol))</code></pre>
<p><img src="impetusModel_files/figure-html/Drought%20phase%20key-1.png" /><!-- --></p>
+<pre class="r"><code>ggsave("Fig4_5_DroughtPlotKey.pdf", dpi = 400)</code></pre>
</div>
</div>
<div id="extract-drought-we-adjusted-hot-water-volumes-for-becc-2017-paper" class="section level2">
@@ -10259,27 +10332,27 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
##
## Basin.baseline Bath.baseline Dishwasher.baseline
## Min. : 10.40 Min. : 0.00 Min. : 0.00
-## 1st Qu.: 21.30 1st Qu.: 26.40 1st Qu.: 0.00
-## Median : 26.69 Median : 56.91 Median :19.83
-## Mean : 39.67 Mean : 54.96 Mean :13.40
-## 3rd Qu.: 39.72 3rd Qu.: 76.67 3rd Qu.:23.27
-## Max. :463.20 Max. :138.66 Max. :32.93
+## 1st Qu.: 20.94 1st Qu.: 26.40 1st Qu.: 0.00
+## Median : 26.64 Median : 56.91 Median :19.80
+## Mean : 39.66 Mean : 54.88 Mean :13.31
+## 3rd Qu.: 39.72 3rd Qu.: 76.50 3rd Qu.:23.13
+## Max. :463.20 Max. :128.19 Max. :35.07
## NA's :10800
-## KitchenSink.baseline Shower.baseline WC.baseline
-## Min. : 7.57 Min. : 0.00 Min. : 25.00
-## 1st Qu.:15.14 1st Qu.: 34.55 1st Qu.: 75.00
-## Median :32.31 Median : 41.32 Median :100.00
-## Mean :31.51 Mean : 69.10 Mean : 99.92
-## 3rd Qu.:45.05 3rd Qu.: 93.60 3rd Qu.:125.00
-## Max. :75.70 Max. :513.83 Max. :262.50
-## NA's :10368 NA's :11448
+## KitchenSink.baseline Shower.baseline WC.baseline
+## Min. : 7.57 Min. : 0.00 Min. : 25.0
+## 1st Qu.:15.14 1st Qu.: 34.23 1st Qu.: 75.0
+## Median :32.10 Median : 41.06 Median :100.0
+## Mean :31.48 Mean : 69.04 Mean :100.2
+## 3rd Qu.:45.14 3rd Qu.: 93.60 3rd Qu.:127.0
+## Max. :75.70 Max. :513.83 Max. :262.5
+## NA's :10368 NA's :11448
## WashingMachine.baseline External.baseline Basin
## Min. : 0.00 Min. :-1.23 Min. :-0.0908
-## 1st Qu.: 16.67 1st Qu.: 1.13 1st Qu.: 0.0569
-## Median : 67.78 Median :16.43 Median : 0.1282
-## Mean : 56.86 Mean :17.92 Mean : 0.1280
-## 3rd Qu.: 85.26 3rd Qu.:26.01 3rd Qu.: 0.1720
-## Max. :154.90 Max. :97.50 Max. : 0.4506
+## 1st Qu.: 16.67 1st Qu.: 1.32 1st Qu.: 0.0569
+## Median : 67.23 Median :16.88 Median : 0.1282
+## Mean : 56.74 Mean :18.06 Mean : 0.1280
+## 3rd Qu.: 85.36 3rd Qu.:25.76 3rd Qu.: 0.1720
+## Max. :155.94 Max. :97.50 Max. : 0.4506
## NA's :7560 NA's :36072
## Bath Dishwasher External KitchenSink
## Min. :-3.9549 Min. :-2.1795 Min. :-1.2822 Min. :-0.1007
@@ -10299,27 +10372,27 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
##
## Basin.baseline.madj Bath.baseline.madj Dishwasher.baseline.madj
## Min. : 10.33 Min. : -3.955 Min. :-2.17945
-## 1st Qu.: 21.44 1st Qu.: 26.196 1st Qu.:-0.04467
-## Median : 26.86 Median : 55.722 Median :18.99479
-## Mean : 39.80 Mean : 53.761 Mean :12.74892
-## 3rd Qu.: 39.81 3rd Qu.: 74.857 3rd Qu.:22.58034
-## Max. :463.65 Max. :138.755 Max. :32.93016
+## 1st Qu.: 21.11 1st Qu.: 26.196 1st Qu.:-0.04467
+## Median : 26.85 Median : 55.598 Median :18.89711
+## Mean : 39.79 Mean : 53.683 Mean :12.66274
+## 3rd Qu.: 39.82 3rd Qu.: 74.699 3rd Qu.:22.43016
+## Max. :463.65 Max. :128.283 Max. :35.07312
## NA's :10800
## External.baseline.madj KitchenSink.baseline.madj Shower.baseline.madj
## Min. :-2.51 Min. : 7.469 Min. : -0.244
-## 1st Qu.: 1.63 1st Qu.:15.466 1st Qu.: 35.014
-## Median :16.60 Median :32.469 Median : 41.918
-## Mean :18.04 Mean :31.660 Mean : 69.518
-## 3rd Qu.:26.11 3rd Qu.:45.196 3rd Qu.: 93.573
+## 1st Qu.: 1.85 1st Qu.:15.466 1st Qu.: 34.694
+## Median :17.06 Median :32.262 Median : 41.646
+## Mean :18.18 Mean :31.632 Mean : 69.458
+## 3rd Qu.:25.88 3rd Qu.:45.289 3rd Qu.: 93.573
## Max. :98.17 Max. :76.121 Max. :515.287
## NA's :36072 NA's :10368
## WC.baseline.madj WashingMachine.baseline.madj sumDaily.baseline.madj
## Min. : 20.64 Min. : -3.245 Min. : 53.53
-## 1st Qu.: 73.44 1st Qu.: 18.377 1st Qu.: 310.29
-## Median : 98.95 Median : 68.592 Median : 387.13
-## Mean : 98.77 Mean : 56.630 Mean : 382.58
-## 3rd Qu.:123.88 3rd Qu.: 84.787 3rd Qu.: 460.76
-## Max. :262.79 Max. :154.862 Max. :1153.15
+## 1st Qu.: 72.99 1st Qu.: 18.377 1st Qu.: 307.77
+## Median : 99.56 Median : 68.092 Median : 386.98
+## Mean : 99.10 Mean : 56.511 Mean : 382.66
+## 3rd Qu.:125.22 3rd Qu.: 84.852 3rd Qu.: 462.33
+## Max. :262.79 Max. :155.901 Max. :1153.15
## NA's :11448 NA's :7560 NA's :36072
## currMonS occRed loWC loSh
## Length:741528 Min. :1.0 Min. :0 Min. :0
@@ -10331,19 +10404,19 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
##
## dualFlushWC loFlowShower WC.baseline.madj.we
## Length:741528 Length:741528 Min. : 9.814
-## Class :character Class :character 1st Qu.: 57.833
-## Mode :character Mode :character Median : 82.439
-## Mean : 88.902
-## 3rd Qu.:117.557
+## Class :character Class :character 1st Qu.: 58.230
+## Mode :character Mode :character Median : 81.400
+## Mean : 89.174
+## 3rd Qu.:118.995
## Max. :262.787
## NA's :11448
## Shower.baseline.madj.we sumDaily.baseline.madj.we yearOrig
-## Min. : -0.244 Min. : 36.45 Min. :1994
-## 1st Qu.: 32.630 1st Qu.: 294.21 1st Qu.:1999
-## Median : 40.862 Median : 369.57 Median :2003
-## Mean : 65.726 Mean : 368.95 Mean :2003
-## 3rd Qu.: 85.698 3rd Qu.: 450.49 3rd Qu.:2008
-## Max. :515.287 Max. :1152.91 Max. :2012
+## Min. : -0.244 Min. : 35.59 Min. :1994
+## 1st Qu.: 32.315 1st Qu.: 292.77 1st Qu.:1999
+## Median : 40.591 Median : 370.52 Median :2003
+## Mean : 65.663 Mean : 368.98 Mean :2003
+## 3rd Qu.: 85.671 3rd Qu.: 452.59 3rd Qu.:2008
+## Max. :515.262 Max. :1152.91 Max. :2012
## NA's :10368 NA's :36072
## currSeason yrStr seasonStr Colne
## Spring:185382 Length:741528 Length:741528 Length:741528
@@ -10362,27 +10435,27 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
##
##
## dualFlushWCupdated loFlowShowerDr loFlowShowerUpdated
-## Min. :0.0000 Length:741528 Min. :0.00000
-## 1st Qu.:0.0000 Class :character 1st Qu.:0.00000
-## Median :0.0000 Mode :character Median :0.00000
-## Mean :0.1909 Mean :0.09709
-## 3rd Qu.:0.0000 3rd Qu.:0.00000
-## Max. :1.0000 Max. :1.00000
+## Min. :0.000 Length:741528 Min. :0.00000
+## 1st Qu.:0.000 Class :character 1st Qu.:0.00000
+## Median :0.000 Mode :character Median :0.00000
+## Mean :0.191 Mean :0.09698
+## 3rd Qu.:0.000 3rd Qu.:0.00000
+## Max. :1.000 Max. :1.00000
##
## applyTUB WC.baseline.madj.we.dr Shower.baseline.madj.we.dr
-## Min. :0.00000 Min. : 9.814 Min. : -0.244
-## 1st Qu.:0.00000 1st Qu.: 47.992 1st Qu.: 29.887
-## Median :0.00000 Median : 73.991 Median : 40.298
-## Mean :0.01215 Mean : 81.002 Mean : 63.514
-## 3rd Qu.:0.00000 3rd Qu.:111.965 3rd Qu.: 80.808
-## Max. :1.00000 Max. :262.739 Max. :515.287
+## Min. :0.00000 Min. : 9.70 Min. : -0.244
+## 1st Qu.:0.00000 1st Qu.: 48.42 1st Qu.: 30.051
+## Median :0.00000 Median : 73.98 Median : 39.807
+## Mean :0.01215 Mean : 81.42 Mean : 63.342
+## 3rd Qu.:0.00000 3rd Qu.:112.16 3rd Qu.: 80.702
+## Max. :1.00000 Max. :262.79 Max. :515.262
## NA's :11448 NA's :10368
## External.baseline.madj.we.dr sumDaily.baseline.madj.we.dr
-## Min. :-2.51 Min. : 36.45
-## 1st Qu.: 1.63 1st Qu.: 284.01
-## Median :16.20 Median : 360.61
-## Mean :17.61 Mean : 358.46
-## 3rd Qu.:25.58 3rd Qu.: 439.11
+## Min. :-2.51 Min. : 35.59
+## 1st Qu.: 1.85 1st Qu.: 283.35
+## Median :16.67 Median : 361.62
+## Mean :17.74 Mean : 358.50
+## 3rd Qu.:25.36 3rd Qu.: 441.08
## Max. :98.17 Max. :1152.91
## NA's :36072 NA's :36072</code></pre>
</div>
@@ -10428,7 +10501,7 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
<h2><span class="header-section-number">12.3</span> Citation</h2>
<p>If you wish to refer to any of the material from this report please cite as:</p>
<ul>
-<li>Anderson, B., Manouseli, D. & Nagarajan, M. (2017) <em>A household level daily consumption estimation microsimulation model</em>, University of Southampton: Southampton, UK.</li>
+<li>Anderson, B., Manouseli, D. & Nagarajan, M. (2018) <em>A household level daily consumption estimation microsimulation model</em>, University of Southampton: Southampton, UK.</li>
</ul>
</div>
</div>
@@ -10437,7 +10510,7 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
<pre class="r"><code>t <- proc.time() - startTime
elapsed <- t[[3]]</code></pre>
-<p>Analysis completed in 519.826 seconds ( 8.66 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 3.4.2 (2017-09-28) running on x86_64-apple-darwin15.6.0.</p>
+<p>Analysis completed in 670.059 seconds ( 11.17 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 3.4.2 (2017-09-28) running on x86_64-apple-darwin15.6.0.</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 3721cedca94beca034987c3ffdea24a69f3f77ea..92a4fd00995a0f05aa08b17527b0766f00a5fdbf 100644
--- a/impetusModel/impetusModel.md
+++ b/impetusModel/impetusModel.md
@@ -1,6 +1,28 @@
-# A household level daily consumption estimation microsimulation model
-Ben Anderson (b.anderson@soton.ac.uk, `@dataknut`), Despoina Manouseli (d.manouseli@soton.ac.uk) & Magesh Nagarajan (m.nagarajan@soton.ac.uk)
-Last run at: `r Sys.time()`
+---
+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: 2018-03-19 03:26:43'
+output:
+ html_document:
+ keep_md: yes
+ number_sections: yes
+ self_contained: no
+ toc: yes
+ toc_depth: 4
+ toc_float: yes
+ pdf_document:
+ number_sections: yes
+ toc: yes
+ toc_depth: 4
+ toc_float: yes
+ word_document:
+ fig_caption: yes
+ keep_md: yes
+ toc: yes
+ toc_depth: 4
+bibliography: ../bibliography.bib
+---
@@ -607,10 +629,10 @@ kable(caption = "Check % metered distribution", 100 * round(prop.table(table(hhP
Table: Check % metered distribution
- 1 2 3 4 5 6
------------- --- ----- ----- ----- ----- -----
-Metered 37 40.1 42.7 41.7 45.7 38.6
-Not metered 63 59.9 57.3 58.3 54.3 61.4
+ 1 2 3 4 5 6
+------------ --- --- ----- ----- ----- -----
+Metered 41 41 36.1 38.1 45.7 37.3
+Not metered 59 59 63.9 61.9 54.3 62.7
## Baseline consumption estimation
@@ -852,12 +874,12 @@ 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. :12.01 Min. : 32.90 Min. :19.88 Min. : 0.00 Min. :27.20 Min. :21.10 Min. : 46.38 Min. : 57.26
- 1st Qu.:17.48 1st Qu.: 57.03 1st Qu.:22.65 1st Qu.:10.72 1st Qu.:32.52 1st Qu.:32.11 1st Qu.: 79.78 1st Qu.: 73.16
- Median :24.22 Median : 74.01 Median :23.95 Median :15.27 Median :43.10 Median :36.58 Median :100.25 Median : 81.94
- Mean :22.94 Mean : 71.87 Mean :24.25 Mean :15.37 Mean :40.47 Mean :36.54 Mean : 98.71 Mean : 84.19
- 3rd Qu.:27.11 3rd Qu.: 83.16 3rd Qu.:25.66 3rd Qu.:22.26 3rd Qu.:46.29 3rd Qu.:40.95 3rd Qu.:114.20 3rd Qu.: 92.89
- Max. :38.29 Max. :137.50 Max. :32.84 Max. :53.46 Max. :57.41 Max. :61.11 Max. :174.28 Max. :153.25
+ Min. :12.14 Min. : 37.30 Min. :19.66 Min. : 0.00 Min. :27.29 Min. :21.84 Min. : 49.72 Min. : 57.32
+ 1st Qu.:17.37 1st Qu.: 57.19 1st Qu.:22.63 1st Qu.:10.77 1st Qu.:32.63 1st Qu.:31.69 1st Qu.: 80.63 1st Qu.: 73.40
+ Median :24.12 Median : 73.61 Median :23.85 Median :15.95 Median :43.07 Median :36.48 Median :100.75 Median : 82.27
+ Mean :22.91 Mean : 71.71 Mean :24.11 Mean :15.61 Mean :40.42 Mean :36.45 Mean : 99.15 Mean : 83.96
+ 3rd Qu.:27.05 3rd Qu.: 83.83 3rd Qu.:25.41 3rd Qu.:22.24 3rd Qu.:46.19 3rd Qu.:40.76 3rd Qu.:114.97 3rd Qu.: 92.40
+ Max. :40.37 Max. :128.19 Max. :32.28 Max. :65.47 Max. :59.49 Max. :61.65 Max. :181.27 Max. :150.64
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.
@@ -879,15 +901,15 @@ Table: Metered vs un-metered estimates (mean)
metered Basin Bath Dishwasher External KitchenSink Shower WC WashingMachine
------------ --------- --------- ----------- --------- ------------ --------- ---------- ---------------
-Metered 16.87288 55.51313 23.03054 9.97072 32.02423 31.45315 77.60751 78.05961
-Not metered 26.97718 82.78251 25.06828 18.96585 46.10112 39.92801 112.77722 88.27885
+Metered 16.83207 55.02204 22.94178 10.12150 32.02371 31.03535 77.43587 77.26493
+Not metered 26.96571 82.84065 24.88585 19.26286 46.01007 40.05337 113.62444 88.42468
```r
wmMetered <- t[metered == "Metered", WC]
wmNonMetered <- t[metered == "Not metered", WC]
```
-% difference between means for washing machine: 31.19.
+% difference between means for washing machine: 31.85.
### Occupancy based adjustment
@@ -963,18 +985,18 @@ Table: Test monthly fixed and occupancy adjusted l/day
metered occupancy meanBasin.baseline sdBasin.baseline meanBath.baseline sdBath.baseline
------------ ---------- ------------------- ----------------- ------------------ ----------------
-Metered 1 16.85 3.20 57.14 11.35
-Metered 2 18.56 3.04 55.67 9.39
-Metered 3 18.78 3.00 57.87 10.96
-Metered 4 19.60 2.93 58.31 8.49
-Metered 5 18.61 2.28 53.79 7.36
-Metered 6 18.41 3.24 56.51 8.02
-Not metered 1 27.06 2.93 82.44 10.01
-Not metered 2 28.18 2.91 84.31 9.99
-Not metered 3 29.46 2.89 85.94 9.98
-Not metered 4 29.50 2.76 82.77 10.55
-Not metered 5 30.14 3.03 86.43 10.46
-Not metered 6 31.08 2.63 86.53 9.01
+Metered 1 17.04 3.03 56.28 9.87
+Metered 2 18.47 2.94 55.90 9.26
+Metered 3 18.63 2.59 56.17 9.40
+Metered 4 19.56 2.83 57.51 11.62
+Metered 5 18.73 2.89 52.10 8.53
+Metered 6 17.30 3.05 58.35 11.77
+Not metered 1 27.00 2.94 82.45 10.20
+Not metered 2 28.33 3.04 83.95 10.24
+Not metered 3 29.52 2.78 85.42 9.10
+Not metered 4 29.73 3.33 85.02 10.44
+Not metered 5 28.77 2.95 85.91 8.69
+Not metered 6 30.87 3.07 88.35 9.10
The table above shows the effect on the median consumption values for Basin and Bath by occupancy group and metered/un-metered.
@@ -1135,62 +1157,60 @@ Comparing these values with the IMPETUS model is not straightforward as not all
```r
+myCap <- "IMPETUS model: synthetic households (n = 1800)\n Model v1" # simple for
# change labels to match EST
-mt <- hhDataFinalDaily_v1_3DT[, .(vol = "vol", Basin = round(mean(Basin.baseline),
+modelDT <- hhDataFinalDaily_v1_3DT[, .(vol = "vol", Basin = round(mean(Basin.baseline),
2), Dishwasher = round(mean(Dishwasher.baseline), 2), External = round(mean(External.baseline),
2), `Kitchen Sink` = round(mean(KitchenSink.baseline), 2), Bath = round(mean(Bath.baseline),
2), Shower = round(mean(Shower.baseline), 2), Toilet = round(mean(WC.baseline),
2), `Washing machine` = round(mean(WashingMachine.baseline), 2), Total = round(mean(sumDaily.baseline),
2))]
# recast
-mt <- dcast(melt(mt, id.vars = "vol"), variable ~ vol)
-mt <- mt[, `:=`(Usage, variable)]
-mt <- mt[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
-
-pct <- hhDataFinalDaily_v1_3DT[, .(pc = "pc", Basin = 100 * round(mean(Basin.baseline/sumDaily.baseline),
- 4), Dishwasher = 100 * round(mean(Dishwasher.baseline/sumDaily.baseline),
- 4), External = 100 * round(mean(External.baseline/sumDaily.baseline), 4),
- `Kitchen Sink` = 100 * round(mean(KitchenSink.baseline/sumDaily.baseline),
- 4), Bath = 100 * round(mean(Bath.baseline/sumDaily.baseline), 4), Shower = 100 *
- round(mean(Shower.baseline/sumDaily.baseline), 4), Toilet = 100 * round(mean(WC.baseline/sumDaily.baseline),
- 4), `Washing machine` = 100 * round(mean(WashingMachine.baseline/sumDaily.baseline),
- 4))]
-# recast
-pct <- dcast(melt(pct, id.vars = "pc"), variable ~ pc)
-pct <- pct[, `:=`(Usage, variable)]
-pct <- pct[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
+modelDT <- dcast(melt(modelDT, id.vars = "vol"), variable ~ vol)
+modelDT <- modelDT[, `:=`(Usage, variable)]
+modelDT <- modelDT[, `:=`(source, paste0("IMPETUS Model"))]
+modelTot <- modelDT[Usage == "Total", vol]
+modelDT <- modelDT[, `:=`(pcTot, 100 * (vol/modelTot))]
-setkey(mt, Usage, variable, source) # simplest way to remove vars!
-setkey(pct, Usage, variable, source)
-mt <- merge(mt, pct, all = TRUE)
+setkey(modelDT, Usage, variable, source) # simplest way to remove vars!
-est2013dataFig1DT <- est2013dataFig1DT[, `:=`(pc, percentOfTotalDaily)]
-est2013dataFig1DT <- est2013dataFig1DT[, `:=`(vol, imputed.l.hh.day)]
-est2013dataFig1DT <- est2013dataFig1DT[, `:=`(source, "EST (2013)")]
+estDT <- est2013dataFig1DT
+estDT <- estDT[, `:=`(pcTot, percentOfTotalDaily)]
+estDT <- estDT[, `:=`(vol, imputed.l.hh.day)]
+estDT <- estDT[, `:=`(source, "EST (2013)")]
-mt$variable <- NULL # remove
-est2013dataFig1DT$percentOfTotalDaily <- NULL
-est2013dataFig1DT$imputed.l.hh.day <- NULL
+modelDT$variable <- NULL # remove
+estDT$percentOfTotalDaily <- NULL
+estDT$imputed.l.hh.day <- NULL
-plotDT <- rbind(est2013dataFig1DT, mt)
+plotDT <- rbind(estDT, modelDT)
plotDT <- plotDT[, `:=`(Usage, as.factor(Usage))]
plotDT <- plotDT[, `:=`(UsageRo, relevel(Usage, "Total"))] # put usage at the end
ggplot(plotDT, aes(x = UsageRo, fill = source)) + geom_col(aes(y = vol), position = "dodge") +
- labs(title = "Total use (l/day)", y = "Mean l/day", x = "Usage") + coord_flip() # rotate for legibility
+ labs(y = "Mean l/day", x = "Usage", caption = myCap) + coord_flip() # rotate for legibility
```
<!-- -->
```r
-ggplot(plotDT[Usage != "Total"], aes(x = UsageRo, fill = source)) + geom_col(aes(y = pc),
- position = "dodge") + labs(title = "% of total (l/day)", y = "%", x = "Usage") +
- coord_flip() # rotate for legibility
+estPlot <- ggplot(plotDT[Usage != "Total"], aes(x = UsageRo, fill = source)) +
+ geom_col(aes(y = pcTot), position = "dodge") + labs(y = "% household total",
+ x = "Usage", caption = myCap) + coord_flip() # rotate for legibility
+
+estPlot
```
<!-- -->
+```r
+# Grey scale version if required
+estPlot <- estPlot + theme_bw()
+
+ggsave("Fig2_CompareModelv1_3withEST2013.pdf", dpi = 400)
+```
+
These charts suggest that compared to the EST (2013) estimates our model underestimates Shower use and over-estimates Bath use. However, given that the EST estimates used a self-selecting sample who may have been more likely to be 'careful' water users, it may be that respondents to their survey were more likely to use showers than baths. Of the other usages that can be directly compared, our model also slighty overestimates external, dishwasher, toilet and (especially) washing machine use, perhaps for similar reasons. Overall, accounting for the usages that are not directly comparable (basin, taps, kitchen sink etc) the mean 'Total' usage figures were broadly comparable.
> They are both models of course... How could we validate with measured data? Artesia?
@@ -1226,7 +1246,7 @@ print(paste0("gzipping file to: ", oFile, ".gz"))
```
```
-## [1] "gzipping file to: ~/Data/IMPETUS/outputs/model_v1/output-hh-baseline-mcm-consumption_2017-11-08_v1_3.csv.gz"
+## [1] "gzipping file to: ~/Data/IMPETUS/outputs/model_v1/output-hh-baseline-mcm-consumption_2018-03-19_v1_3.csv.gz"
```
```r
@@ -3059,25 +3079,40 @@ mt <- hhDataFinalDaily_v2_0DT[, .(vol = "vol", Basin = round(mean(dailyBathroomS
na.rm = TRUE), 2), Total = round(mean(totalDailyHouseDemandFinal, na.rm = TRUE),
2))]
# recast
-mt <- dcast(melt(mt, id.vars = "vol"), variable ~ vol)
-mt <- mt[, `:=`(Usage, variable)]
-mt <- mt[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
+mtDT <- as.data.table(dcast(melt(mt, id.vars = "vol"), variable ~ vol))
+mtDT <- mtDT[, `:=`(Usage, variable)]
+mtDT <- mtDT[, `:=`(source, paste0("IMPETUS Model ", modelVersion))]
+# calculate % of total column for chart
+tot <- mtDT[Usage == "Total", vol]
+mtDT <- mtDT[, `:=`(pcTot, 100 * (vol/tot))]
+setkey(mtDT, Usage, variable, source) # simplest way to remove vars!
-setkey(mt, Usage, variable, source) # simplest way to remove vars!
+mtDT$variable <- NULL # remove
-mt$variable <- NULL # remove
-est2013dataFig1DT$pc <- NULL
-plotDT <- rbind(est2013dataFig1DT, mt)
+# re-use from model 1 - may break if model 1 not run
+plotDT <- rbind(estDT, mtDT)
plotDT <- plotDT[, `:=`(Usage, as.factor(Usage))]
plotDT <- plotDT[, `:=`(UsageRo, relevel(Usage, "Total"))] # put usage at the end
-ggplot(plotDT, aes(x = UsageRo, fill = source)) + geom_col(aes(y = vol), position = "dodge") +
- labs(title = "Total use (l/day)", y = "Mean l/day", x = "Usage") + coord_flip() # rotate for legibility
+myPlot <- ggplot(plotDT, aes(x = UsageRo, fill = source)) + geom_col(aes(y = vol),
+ position = "dodge") + labs(y = "Mean l/day", x = "Usage") + coord_flip() # rotate for legibility
+
+myPlot
```
<!-- -->
+```r
+myPlot <- ggplot(plotDT[Usage != "Total"], aes(x = UsageRo, fill = source)) +
+ geom_col(aes(y = pcTot), position = "dodge") + labs(y = "% total", x = "Usage") +
+ coord_flip() # rotate for legibility
+
+myPlot
+```
+
+<!-- -->
+
## Save data
Now write out the monthly values
@@ -3099,7 +3134,7 @@ write.csv(hhDataFinalDaily_v2_0DT, oFile)
Data written to:
-> ~/Data/IMPETUS/outputs/model_v2/output-SPRG-1800hh-consumption_2017-11-08_v2_0.csv and (possibly) gzipped
+> ~/Data/IMPETUS/outputs/model_v2/output-SPRG-1800hh-consumption_2018-03-19_v2_0.csv and (possibly) gzipped
@@ -3138,17 +3173,17 @@ st <- str(hhDataFinalDaily_v1_3fDT)
```
## Classes 'data.table' and 'data.frame': 1800 obs. of 12 variables:
-## $ hhid : int 28 29 30 52 65 66 84 85 90 96 ...
+## $ hhid : int 8 16 22 28 29 30 40 43 52 58 ...
## $ occupancy : int 1 1 1 1 1 1 1 1 1 1 ...
## $ metered : chr "Metered" "Metered" "Metered" "Metered" ...
-## $ Basin.baseline : num 15.1 14.8 14.9 16.6 14.8 ...
-## $ Bath.baseline : num 46.3 48.3 54.4 78.8 64.2 ...
-## $ Dishwasher.baseline : num 22.8 21.3 23.5 20.5 20.9 ...
-## $ KitchenSink.baseline : num 30.5 29.2 32.3 28 32.9 ...
-## $ Shower.baseline : num 25.9 33.5 29.8 30.4 31.2 ...
-## $ WC.baseline : num 70.6 59 71.4 68.4 80.7 ...
-## $ WashingMachine.baseline: num 64.6 67.7 65.6 71.3 87.4 ...
-## $ External.baseline : num 13.7 0 0 15.1 0 ...
+## $ Basin.baseline : num 14.5 14 14.1 16.6 18.5 ...
+## $ Bath.baseline : num 46.7 47.8 49.5 48.3 53.3 ...
+## $ Dishwasher.baseline : num 23 20.5 25.6 22.5 22 ...
+## $ KitchenSink.baseline : num 30.8 33.9 30 27.3 29.3 ...
+## $ Shower.baseline : num 30.1 39.4 23.6 29.3 28.8 ...
+## $ WC.baseline : num 67.3 108 58.4 64.2 54.5 ...
+## $ WashingMachine.baseline: num 81.9 94.5 60.3 84.1 85.8 ...
+## $ External.baseline : num 0 12.9 13.1 11.2 0 ...
## $ model : chr "v1_3" "v1_3" "v1_3" "v1_3" ...
## - attr(*, ".internal.selfref")=<externalptr>
## - attr(*, "sorted")= chr "metered" "occupancy"
@@ -3524,12 +3559,12 @@ 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. :272.6 Min. :11.91 Min. : 33.34 Min. :14.08 Min. :-2.511 Min. :27.70 Min. :20.85 Min. : 48.18 Min. : 56.27
- 1st Qu.:1999 1st Qu.: 4.000 Class :character 1st Qu.:1.000 1st Qu.:349.2 1st Qu.:19.09 1st Qu.: 57.94 1st Qu.:20.89 1st Qu.:11.063 1st Qu.:35.01 1st Qu.:33.41 1st Qu.: 86.87 1st Qu.: 75.04
- Median :2004 Median : 7.000 Mode :character Median :2.000 Median :425.6 Median :25.68 Median : 73.56 Median :22.42 Median :15.800 Median :44.60 Median :37.55 Median :110.38 Median : 83.66
- Mean :2004 Mean : 6.523 NA Mean :2.407 Mean :408.6 Mean :24.46 Mean : 71.86 Mean :22.69 Mean :15.789 Mean :42.33 Mean :37.53 Mean :107.99 Mean : 86.01
- 3rd Qu.:2009 3rd Qu.:10.000 NA 3rd Qu.:3.000 3rd Qu.:458.7 3rd Qu.:28.79 3rd Qu.: 82.83 3rd Qu.:24.30 3rd Qu.:22.694 3rd Qu.:47.99 3rd Qu.:41.76 3rd Qu.:126.22 3rd Qu.: 94.54
- Max. :2014 Max. :12.000 NA Max. :6.000 Max. :554.1 Max. :39.79 Max. :138.75 Max. :32.93 Max. :55.837 Max. :59.02 Max. :62.59 Max. :186.97 Max. :154.86
+ Min. :1994 Min. : 1.000 Length:433800 Min. :1.000 Min. :245.8 Min. :12.59 Min. : 37.18 Min. :13.80 Min. :-2.511 Min. :27.22 Min. :22.41 Min. : 49.10 Min. : 57.64
+ 1st Qu.:1999 1st Qu.: 4.000 Class :character 1st Qu.:1.000 1st Qu.:346.2 1st Qu.:18.77 1st Qu.: 57.92 1st Qu.:20.87 1st Qu.:11.194 1st Qu.:35.06 1st Qu.:33.09 1st Qu.: 85.82 1st Qu.: 75.12
+ Median :2004 Median : 7.000 Mode :character Median :2.000 Median :427.6 Median :25.61 Median : 73.34 Median :22.29 Median :16.403 Median :44.82 Median :37.25 Median :110.61 Median : 83.88
+ Mean :2004 Mean : 6.523 NA Mean :2.407 Mean :408.8 Mean :24.45 Mean : 71.71 Mean :22.52 Mean :16.037 Mean :42.27 Mean :37.42 Mean :108.61 Mean : 85.78
+ 3rd Qu.:2009 3rd Qu.:10.000 NA 3rd Qu.:3.000 3rd Qu.:460.5 3rd Qu.:28.77 3rd Qu.: 83.58 3rd Qu.:24.05 3rd Qu.:22.734 3rd Qu.:47.93 3rd Qu.:41.45 3rd Qu.:128.10 3rd Qu.: 93.69
+ Max. :2014 Max. :12.000 NA Max. :6.000 Max. :555.7 Max. :43.10 Max. :128.28 Max. :35.07 Max. :67.849 Max. :61.66 Max. :62.86 Max. :184.94 Max. :155.90
```r
kable(caption = "Summary of final household data (litres/day) - model v2_0",
@@ -3763,8 +3798,8 @@ Table: Summary statistics
model metered Daily mean litres/day Daily mean litres/day per capita
------ ------------ ---------------------- ---------------------------------
-v1_3 Not metered 453.7999 255.3888
-v1_3 Metered 340.9167 183.7912
+v1_3 Not metered 455.7314 250.3137
+v1_3 Metered 338.3823 189.7024
v2_0 Not metered 362.7737 133.9713
v2_0 Metered 336.4506 139.7480
@@ -3883,6 +3918,7 @@ The first step is to allocate households to dual-flush/no dual-flush status and
* low-flow/normal flow shower head:
* as for WC but stratified by top & bottom 50% shower litres/day within household size
+> somehow this process needs to take account of the 'existing' uptake levels in 2011 in model v2 (based on SPRG survey data)
```r
@@ -4150,14 +4186,13 @@ dt <- hhFinalDataComboExpandedDT[currYear == 2012 & model == "v1_3", .(Basin = m
Dishwasher = mean(Dishwasher.baseline.madj), External = mean(External.baseline.madj),
Shower = mean(Shower.baseline.madj.we), WC = mean(WC.baseline.madj.we),
WashingMachine = mean(WashingMachine.baseline.madj)), by = .(metered, currMon)]
+# recast dt to make plotting easier
+plotDT <- melt(dt, id.vars = c("currMon", "metered"))
+plotDT <- plotDT[, `:=`(Usage, variable)]
-myPlot <- ggplot(dt, aes(x = factor(currMon), group = metered)) + # geom_boxplot() +
-geom_line(aes(y = Basin, colour = "Basin")) + geom_line(aes(y = Bath, colour = "Bath")) +
- geom_line(aes(y = KitchenSink, colour = "Kitchen Sink")) + geom_line(aes(y = Dishwasher,
- colour = "Dishwasher")) + geom_line(aes(y = External, colour = "External")) +
- geom_line(aes(y = Shower, colour = "Shower")) + geom_line(aes(y = WC, colour = "WC")) +
- geom_line(aes(y = WashingMachine, colour = "Washing Machine")) + facet_grid(. ~
- metered, scales = "free") + theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+myPlot <- ggplot(plotDT, aes(x = factor(currMon), y = value, group = Usage)) +
+ geom_line(aes(colour = Usage)) + facet_grid(. ~ metered, scales = "free") +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
labs(y = "Mean litres/day", x = "Month", title = myTitle, caption = myCaption)
myPlot
@@ -4165,6 +4200,27 @@ myPlot
<!-- -->
+```r
+# version with linetype for use in bw fig
+myPlot <- ggplot(plotDT, aes(x = factor(currMon), y = value, group = Usage)) +
+ geom_line(aes(linetype = Usage)) + facet_grid(. ~ metered, scales = "free") +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+ labs(y = "Mean litres/day", x = "Month", caption = myCaption)
+
+myPlot
+```
+
+<!-- -->
+
+```r
+# Grey scale version if required
+myPlot <- myPlot + theme_bw()
+
+# Figure for IWA Bath final paper
+# (http://ws.iwaponline.com/content/early/2018/02/13/ws.2018.035)
+ggsave("Fig3_Final_model_v1_3_2012_by_month.pdf", plot = myPlot, dpi = 400)
+```
+
```r
myTitle <- "All uses (all years)"
@@ -4304,27 +4360,27 @@ summary(hhFinalDataComboExpandedDT)
##
## Basin.baseline Bath.baseline Dishwasher.baseline
## Min. : 10.40 Min. : 0.00 Min. : 0.00
-## 1st Qu.: 21.30 1st Qu.: 26.40 1st Qu.: 0.00
-## Median : 26.69 Median : 56.91 Median :19.83
-## Mean : 39.67 Mean : 54.96 Mean :13.40
-## 3rd Qu.: 39.72 3rd Qu.: 76.67 3rd Qu.:23.27
-## Max. :463.20 Max. :138.66 Max. :32.93
+## 1st Qu.: 20.94 1st Qu.: 26.40 1st Qu.: 0.00
+## Median : 26.64 Median : 56.91 Median :19.80
+## Mean : 39.66 Mean : 54.88 Mean :13.31
+## 3rd Qu.: 39.72 3rd Qu.: 76.50 3rd Qu.:23.13
+## Max. :463.20 Max. :128.19 Max. :35.07
## NA's :12050
-## KitchenSink.baseline Shower.baseline WC.baseline
-## Min. : 7.57 Min. : 0.00 Min. : 25.00
-## 1st Qu.:15.14 1st Qu.: 34.55 1st Qu.: 75.00
-## Median :32.31 Median : 41.32 Median :100.00
-## Mean :31.51 Mean : 69.10 Mean : 99.92
-## 3rd Qu.:45.05 3rd Qu.: 93.60 3rd Qu.:125.00
-## Max. :75.70 Max. :513.83 Max. :262.50
-## NA's :11568 NA's :12773
+## KitchenSink.baseline Shower.baseline WC.baseline
+## Min. : 7.57 Min. : 0.00 Min. : 25.0
+## 1st Qu.:15.14 1st Qu.: 34.23 1st Qu.: 75.0
+## Median :32.10 Median : 41.06 Median :100.0
+## Mean :31.48 Mean : 69.04 Mean :100.2
+## 3rd Qu.:45.14 3rd Qu.: 93.60 3rd Qu.:127.0
+## Max. :75.70 Max. :513.83 Max. :262.5
+## NA's :11568 NA's :12773
## WashingMachine.baseline External.baseline Basin
## Min. : 0.00 Min. :-1.23 Min. :-0.0908
-## 1st Qu.: 16.67 1st Qu.: 1.13 1st Qu.: 0.0570
-## Median : 67.78 Median :16.43 Median : 0.1315
-## Mean : 56.86 Mean :17.92 Mean : 0.1300
-## 3rd Qu.: 85.26 3rd Qu.:26.01 3rd Qu.: 0.1740
-## Max. :154.90 Max. :97.50 Max. : 0.4506
+## 1st Qu.: 16.67 1st Qu.: 1.32 1st Qu.: 0.0570
+## Median : 67.23 Median :16.88 Median : 0.1315
+## Mean : 56.74 Mean :18.06 Mean : 0.1300
+## 3rd Qu.: 85.36 3rd Qu.:25.76 3rd Qu.: 0.1740
+## Max. :155.94 Max. :97.50 Max. : 0.4506
## NA's :8435 NA's :40247
## Bath Dishwasher External KitchenSink
## Min. :-3.9549 Min. :-2.1795 Min. :-1.28218 Min. :-0.10074
@@ -4344,27 +4400,27 @@ summary(hhFinalDataComboExpandedDT)
##
## Basin.baseline.madj Bath.baseline.madj Dishwasher.baseline.madj
## Min. : 10.33 Min. : -3.955 Min. :-2.17945
-## 1st Qu.: 21.45 1st Qu.: 26.202 1st Qu.:-0.04467
-## Median : 26.86 Median : 55.730 Median :18.98319
-## Mean : 39.80 Mean : 53.771 Mean :12.73835
-## 3rd Qu.: 39.81 3rd Qu.: 74.870 3rd Qu.:22.56947
-## Max. :463.65 Max. :138.755 Max. :32.93016
+## 1st Qu.: 21.11 1st Qu.: 26.202 1st Qu.:-0.04467
+## Median : 26.85 Median : 55.606 Median :18.88683
+## Mean : 39.79 Mean : 53.693 Mean :12.65217
+## 3rd Qu.: 39.82 3rd Qu.: 74.710 3rd Qu.:22.41976
+## Max. :463.65 Max. :128.283 Max. :35.07312
## NA's :12050
## External.baseline.madj KitchenSink.baseline.madj Shower.baseline.madj
## Min. :-2.51 Min. : 7.469 Min. : -0.244
-## 1st Qu.: 1.63 1st Qu.:15.468 1st Qu.: 35.026
-## Median :16.60 Median :32.471 Median : 41.929
-## Mean :18.04 Mean :31.663 Mean : 69.528
-## 3rd Qu.:26.11 3rd Qu.:45.198 3rd Qu.: 93.587
+## 1st Qu.: 1.85 1st Qu.:15.468 1st Qu.: 34.704
+## Median :17.06 Median :32.264 Median : 41.658
+## Mean :18.18 Mean :31.634 Mean : 69.469
+## 3rd Qu.:25.88 3rd Qu.:45.291 3rd Qu.: 93.587
## Max. :98.17 Max. :76.121 Max. :515.302
## NA's :40247 NA's :11568
## WC.baseline.madj WashingMachine.baseline.madj sumDaily.baseline.madj
## Min. : 20.64 Min. : -3.245 Min. : 53.53
-## 1st Qu.: 73.50 1st Qu.: 18.342 1st Qu.: 310.28
-## Median : 98.95 Median : 68.550 Median : 387.12
-## Mean : 98.78 Mean : 56.589 Mean : 382.56
-## 3rd Qu.:123.89 3rd Qu.: 84.742 3rd Qu.: 460.74
-## Max. :262.81 Max. :154.862 Max. :1153.15
+## 1st Qu.: 73.00 1st Qu.: 18.342 1st Qu.: 307.77
+## Median : 99.57 Median : 68.052 Median : 386.97
+## Mean : 99.11 Mean : 56.469 Mean : 382.64
+## 3rd Qu.:125.24 3rd Qu.: 84.807 3rd Qu.: 462.31
+## Max. :262.81 Max. :155.901 Max. :1153.15
## NA's :12773 NA's :8435 NA's :40247
## currMonS occRed loWC loSh
## Length:827353 Min. :1.0 Min. :0 Min. :0
@@ -4376,18 +4432,18 @@ summary(hhFinalDataComboExpandedDT)
##
## dualFlushWC loFlowShower WC.baseline.madj.we
## Length:827353 Length:827353 Min. : 9.814
-## Class :character Class :character 1st Qu.: 55.055
-## Mode :character Mode :character Median : 79.842
-## Mean : 87.819
-## 3rd Qu.:116.706
+## Class :character Class :character 1st Qu.: 55.517
+## Mode :character Mode :character Median : 79.470
+## Mean : 88.086
+## 3rd Qu.:118.059
## Max. :262.811
## NA's :12773
## Shower.baseline.madj.we sumDaily.baseline.madj.we
-## Min. : -0.244 Min. : 35.99
-## 1st Qu.: 32.402 1st Qu.: 292.81
-## Median : 40.788 Median : 368.34
-## Mean : 65.454 Mean : 367.56
-## 3rd Qu.: 85.459 3rd Qu.: 449.20
+## Min. : -0.244 Min. : 35.59
+## 1st Qu.: 32.004 1st Qu.: 291.23
+## Median : 40.509 Median : 369.12
+## Mean : 65.392 Mean : 367.59
+## 3rd Qu.: 85.431 3rd Qu.: 451.23
## Max. :515.302 Max. :1152.91
## NA's :11568 NA's :40247
```
@@ -4502,14 +4558,14 @@ stargazer(hhFinalDataComboExpandedDT, type = "html")
<tr><td style="text-align:left">currMon</td><td>827,353</td><td>6.523</td><td>3.463</td><td>1</td><td>12</td></tr>
<tr><td style="text-align:left">hhid</td><td>827,353</td><td>398,103,841.000</td><td>417,963,933.000</td><td>1</td><td>836,965,495</td></tr>
<tr><td style="text-align:left">occupancy</td><td>827,353</td><td>2.503</td><td>1.359</td><td>1</td><td>10</td></tr>
-<tr><td style="text-align:left">Basin.baseline</td><td>815,303</td><td>39.670</td><td>39.837</td><td>10.400</td><td>463.200</td></tr>
-<tr><td style="text-align:left">Bath.baseline</td><td>827,353</td><td>54.960</td><td>26.245</td><td>0.000</td><td>138.664</td></tr>
-<tr><td style="text-align:left">Dishwasher.baseline</td><td>827,353</td><td>13.396</td><td>10.848</td><td>0.000</td><td>32.930</td></tr>
-<tr><td style="text-align:left">KitchenSink.baseline</td><td>827,353</td><td>31.506</td><td>14.239</td><td>7.570</td><td>75.700</td></tr>
-<tr><td style="text-align:left">Shower.baseline</td><td>815,785</td><td>69.102</td><td>62.510</td><td>0.000</td><td>513.825</td></tr>
-<tr><td style="text-align:left">WC.baseline</td><td>814,580</td><td>99.921</td><td>38.938</td><td>25.000</td><td>262.500</td></tr>
-<tr><td style="text-align:left">WashingMachine.baseline</td><td>818,918</td><td>56.862</td><td>35.164</td><td>0.000</td><td>154.898</td></tr>
-<tr><td style="text-align:left">External.baseline</td><td>787,106</td><td>17.922</td><td>15.079</td><td>-1.229</td><td>97.504</td></tr>
+<tr><td style="text-align:left">Basin.baseline</td><td>815,303</td><td>39.663</td><td>39.844</td><td>10.400</td><td>463.200</td></tr>
+<tr><td style="text-align:left">Bath.baseline</td><td>827,353</td><td>54.882</td><td>26.253</td><td>0.000</td><td>128.192</td></tr>
+<tr><td style="text-align:left">Dishwasher.baseline</td><td>827,353</td><td>13.310</td><td>10.759</td><td>0.000</td><td>35.073</td></tr>
+<tr><td style="text-align:left">KitchenSink.baseline</td><td>827,353</td><td>31.477</td><td>14.212</td><td>7.570</td><td>75.700</td></tr>
+<tr><td style="text-align:left">Shower.baseline</td><td>815,785</td><td>69.042</td><td>62.550</td><td>0.000</td><td>513.825</td></tr>
+<tr><td style="text-align:left">WC.baseline</td><td>814,580</td><td>100.249</td><td>39.418</td><td>25.000</td><td>262.500</td></tr>
+<tr><td style="text-align:left">WashingMachine.baseline</td><td>818,918</td><td>56.743</td><td>35.021</td><td>0.000</td><td>155.937</td></tr>
+<tr><td style="text-align:left">External.baseline</td><td>787,106</td><td>18.059</td><td>15.069</td><td>-1.229</td><td>97.504</td></tr>
<tr><td style="text-align:left">Basin</td><td>827,353</td><td>0.130</td><td>0.114</td><td>-0.091</td><td>0.451</td></tr>
<tr><td style="text-align:left">Bath</td><td>827,353</td><td>-1.189</td><td>1.015</td><td>-3.955</td><td>0.091</td></tr>
<tr><td style="text-align:left">Dishwasher</td><td>827,353</td><td>-0.658</td><td>0.590</td><td>-2.179</td><td>0.000</td></tr>
@@ -4518,21 +4574,21 @@ stargazer(hhFinalDataComboExpandedDT, type = "html")
<tr><td style="text-align:left">Shower</td><td>827,353</td><td>0.426</td><td>0.480</td><td>-0.244</td><td>1.477</td></tr>
<tr><td style="text-align:left">WC</td><td>827,353</td><td>-1.140</td><td>1.097</td><td>-4.362</td><td>0.311</td></tr>
<tr><td style="text-align:left">WashingMachine</td><td>827,353</td><td>-0.270</td><td>1.698</td><td>-3.245</td><td>3.439</td></tr>
-<tr><td style="text-align:left">Basin.baseline.madj</td><td>815,303</td><td>39.800</td><td>39.834</td><td>10.328</td><td>463.651</td></tr>
-<tr><td style="text-align:left">Bath.baseline.madj</td><td>827,353</td><td>53.771</td><td>25.997</td><td>-3.955</td><td>138.755</td></tr>
-<tr><td style="text-align:left">Dishwasher.baseline.madj</td><td>827,353</td><td>12.738</td><td>10.827</td><td>-2.179</td><td>32.930</td></tr>
-<tr><td style="text-align:left">External.baseline.madj</td><td>787,106</td><td>18.044</td><td>15.119</td><td>-2.511</td><td>98.172</td></tr>
-<tr><td style="text-align:left">KitchenSink.baseline.madj</td><td>827,353</td><td>31.663</td><td>14.237</td><td>7.469</td><td>76.121</td></tr>
-<tr><td style="text-align:left">Shower.baseline.madj</td><td>815,785</td><td>69.528</td><td>62.516</td><td>-0.244</td><td>515.302</td></tr>
-<tr><td style="text-align:left">WC.baseline.madj</td><td>814,580</td><td>98.778</td><td>38.647</td><td>20.638</td><td>262.811</td></tr>
-<tr><td style="text-align:left">WashingMachine.baseline.madj</td><td>818,918</td><td>56.589</td><td>34.985</td><td>-3.245</td><td>154.862</td></tr>
-<tr><td style="text-align:left">sumDaily.baseline.madj</td><td>787,106</td><td>382.559</td><td>133.745</td><td>53.528</td><td>1,153.147</td></tr>
+<tr><td style="text-align:left">Basin.baseline.madj</td><td>815,303</td><td>39.792</td><td>39.841</td><td>10.328</td><td>463.651</td></tr>
+<tr><td style="text-align:left">Bath.baseline.madj</td><td>827,353</td><td>53.693</td><td>26.000</td><td>-3.955</td><td>128.283</td></tr>
+<tr><td style="text-align:left">Dishwasher.baseline.madj</td><td>827,353</td><td>12.652</td><td>10.739</td><td>-2.179</td><td>35.073</td></tr>
+<tr><td style="text-align:left">External.baseline.madj</td><td>787,106</td><td>18.181</td><td>15.110</td><td>-2.511</td><td>98.172</td></tr>
+<tr><td style="text-align:left">KitchenSink.baseline.madj</td><td>827,353</td><td>31.634</td><td>14.210</td><td>7.469</td><td>76.121</td></tr>
+<tr><td style="text-align:left">Shower.baseline.madj</td><td>815,785</td><td>69.469</td><td>62.556</td><td>-0.244</td><td>515.302</td></tr>
+<tr><td style="text-align:left">WC.baseline.madj</td><td>814,580</td><td>99.107</td><td>39.121</td><td>20.638</td><td>262.811</td></tr>
+<tr><td style="text-align:left">WashingMachine.baseline.madj</td><td>818,918</td><td>56.469</td><td>34.828</td><td>-3.245</td><td>155.901</td></tr>
+<tr><td style="text-align:left">sumDaily.baseline.madj</td><td>787,106</td><td>382.639</td><td>134.330</td><td>53.528</td><td>1,153.147</td></tr>
<tr><td style="text-align:left">occRed</td><td>827,353</td><td>2.500</td><td>1.347</td><td>1</td><td>6</td></tr>
<tr><td style="text-align:left">loWC</td><td>827,353</td><td>0.000</td><td>0.000</td><td>0</td><td>0</td></tr>
<tr><td style="text-align:left">loSh</td><td>827,353</td><td>0.000</td><td>0.000</td><td>0</td><td>0</td></tr>
-<tr><td style="text-align:left">WC.baseline.madj.we</td><td>814,580</td><td>87.819</td><td>41.289</td><td>9.814</td><td>262.811</td></tr>
-<tr><td style="text-align:left">Shower.baseline.madj.we</td><td>815,785</td><td>65.454</td><td>60.249</td><td>-0.244</td><td>515.302</td></tr>
-<tr><td style="text-align:left">sumDaily.baseline.madj.we</td><td>787,106</td><td>367.555</td><td>131.067</td><td>35.986</td><td>1,152.909</td></tr>
+<tr><td style="text-align:left">WC.baseline.madj.we</td><td>814,580</td><td>88.086</td><td>41.660</td><td>9.814</td><td>262.811</td></tr>
+<tr><td style="text-align:left">Shower.baseline.madj.we</td><td>815,785</td><td>65.392</td><td>60.272</td><td>-0.244</td><td>515.302</td></tr>
+<tr><td style="text-align:left">sumDaily.baseline.madj.we</td><td>787,106</td><td>367.586</td><td>131.572</td><td>35.586</td><td>1,152.909</td></tr>
<tr><td colspan="6" style="border-bottom: 1px solid black"></td></tr></table>
Import the CEH drought histories.
@@ -5206,7 +5262,7 @@ table(hhFinalDataComboExpandedCEHDT$dualFlushWC, hhFinalDataComboExpandedCEHDT$d
##
## Dual flush Single flush
## Dual flush 139980 0
-## Single flush 109341 492207
+## Single flush 109667 491881
```
```r
@@ -5336,235 +5392,235 @@ for (y in minYear:maxYear) {
## [1] "Updating low flow shower uptake for year: 1995 & month 3 (2. Developing)"
## [1] "N cases selected: 3254"
## [1] "Updating low flow shower uptake for year: 1995 & month 4 (2. Developing)"
-## [1] "N cases selected: 3246"
+## [1] "N cases selected: 3248"
## [1] "Updating low flow shower uptake for year: 1995 & month 5 (2. Developing)"
-## [1] "N cases selected: 3240"
+## [1] "N cases selected: 3238"
## [1] "Updating low flow shower uptake for year: 1995 & month 6 (2. Developing)"
-## [1] "N cases selected: 3232"
+## [1] "N cases selected: 3231"
## [1] "Updating low flow shower uptake for year: 1995 & month 7 (2. Developing)"
-## [1] "N cases selected: 3223"
+## [1] "N cases selected: 3225"
## [1] "Updating low flow shower uptake for year: 1995 & month 8 (2. Developing)"
-## [1] "N cases selected: 3217"
+## [1] "N cases selected: 3215"
## [1] "Updating low flow shower uptake for year: 1995 & month 9 (3. Drought)"
-## [1] "N cases selected: 3209"
+## [1] "N cases selected: 3207"
## [1] "Updating low flow shower uptake for year: 1995 & month 10 (3. Drought)"
-## [1] "N cases selected: 3197"
+## [1] "N cases selected: 3198"
## [1] "Updating low flow shower uptake for year: 1995 & month 11 (3. Drought)"
-## [1] "N cases selected: 3186"
+## [1] "N cases selected: 3190"
## [1] "Updating low flow shower uptake for year: 1995 & month 12 (2. Developing)"
-## [1] "N cases selected: 3179"
+## [1] "N cases selected: 3180"
## [1] "Year: 1996"
## [1] "Updating low flow shower uptake for year: 1996 & month 1 (2. Developing)"
-## [1] "N cases selected: 3173"
+## [1] "N cases selected: 3170"
## [1] "Updating low flow shower uptake for year: 1996 & month 2 (2. Developing)"
-## [1] "N cases selected: 3166"
+## [1] "N cases selected: 3163"
## [1] "Updating low flow shower uptake for year: 1996 & month 3 (3. Drought)"
-## [1] "N cases selected: 3161"
+## [1] "N cases selected: 3154"
## [1] "Updating low flow shower uptake for year: 1996 & month 4 (3. Drought)"
-## [1] "N cases selected: 3147"
+## [1] "N cases selected: 3149"
## [1] "Updating low flow shower uptake for year: 1996 & month 5 (3. Drought)"
-## [1] "N cases selected: 3138"
+## [1] "N cases selected: 3135"
## [1] "Updating low flow shower uptake for year: 1996 & month 6 (3. Drought)"
-## [1] "N cases selected: 3130"
+## [1] "N cases selected: 3132"
## [1] "Updating low flow shower uptake for year: 1996 & month 7 (3. Drought)"
## [1] "N cases selected: 3117"
## [1] "Updating low flow shower uptake for year: 1996 & month 8 (3. Drought)"
-## [1] "N cases selected: 3116"
+## [1] "N cases selected: 3110"
## [1] "Updating low flow shower uptake for year: 1996 & month 9 (3. Drought)"
## [1] "N cases selected: 3100"
## [1] "Updating low flow shower uptake for year: 1996 & month 10 (3. Drought)"
-## [1] "N cases selected: 3087"
+## [1] "N cases selected: 3092"
## [1] "Updating low flow shower uptake for year: 1996 & month 11 (3. Drought)"
-## [1] "N cases selected: 3085"
+## [1] "N cases selected: 3078"
## [1] "Updating low flow shower uptake for year: 1996 & month 12 (4. Severe Drought)"
-## [1] "N cases selected: 3075"
+## [1] "N cases selected: 3078"
## [1] "Year: 1997"
## [1] "Updating low flow shower uptake for year: 1997 & month 1 (4. Severe Drought)"
-## [1] "N cases selected: 3057"
+## [1] "N cases selected: 3058"
## [1] "Updating low flow shower uptake for year: 1997 & month 2 (4. Severe Drought)"
-## [1] "N cases selected: 3050"
+## [1] "N cases selected: 3047"
## [1] "Updating low flow shower uptake for year: 1997 & month 3 (4. Severe Drought)"
## [1] "N cases selected: 3039"
## [1] "Updating low flow shower uptake for year: 1997 & month 4 (4. Severe Drought)"
-## [1] "N cases selected: 3023"
+## [1] "N cases selected: 3026"
## [1] "Updating low flow shower uptake for year: 1997 & month 5 (4. Severe Drought)"
-## [1] "N cases selected: 3017"
+## [1] "N cases selected: 3012"
## [1] "Updating low flow shower uptake for year: 1997 & month 6 (5. Recovering)"
-## [1] "N cases selected: 3001"
+## [1] "N cases selected: 3003"
## [1] "Updating low flow shower uptake for year: 1997 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2991"
+## [1] "N cases selected: 2998"
## [1] "Updating low flow shower uptake for year: 1997 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2977"
+## [1] "N cases selected: 2980"
## [1] "Updating low flow shower uptake for year: 1997 & month 9 (4. Severe Drought)"
-## [1] "N cases selected: 2987"
+## [1] "N cases selected: 2978"
## [1] "Updating low flow shower uptake for year: 1997 & month 10 (4. Severe Drought)"
-## [1] "N cases selected: 2971"
+## [1] "N cases selected: 2966"
## [1] "Updating low flow shower uptake for year: 1997 & month 11 (4. Severe Drought)"
-## [1] "N cases selected: 2956"
+## [1] "N cases selected: 2959"
## [1] "Updating low flow shower uptake for year: 1997 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2951"
+## [1] "N cases selected: 2952"
## [1] "Year: 1998"
## [1] "Updating low flow shower uptake for year: 1998 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2942"
+## [1] "N cases selected: 2946"
## [1] "Updating low flow shower uptake for year: 1998 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2930"
+## [1] "N cases selected: 2932"
## [1] "Updating low flow shower uptake for year: 1998 & month 3 (5. Recovering)"
-## [1] "N cases selected: 2931"
+## [1] "N cases selected: 2924"
## [1] "Updating low flow shower uptake for year: 1998 & month 4 (5. Recovering)"
-## [1] "N cases selected: 2926"
+## [1] "N cases selected: 2927"
## [1] "Updating low flow shower uptake for year: 1998 & month 5 (5. Recovering)"
-## [1] "N cases selected: 2915"
+## [1] "N cases selected: 2917"
## [1] "Updating low flow shower uptake for year: 1998 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2912"
+## [1] "N cases selected: 2904"
## [1] "Updating low flow shower uptake for year: 1998 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2905"
+## [1] "N cases selected: 2898"
## [1] "Updating low flow shower uptake for year: 1998 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2904"
+## [1] "N cases selected: 2894"
## [1] "Updating low flow shower uptake for year: 1998 & month 9 (5. Recovering)"
-## [1] "N cases selected: 2896"
+## [1] "N cases selected: 2893"
## [1] "Updating low flow shower uptake for year: 1998 & month 10 (5. Recovering)"
-## [1] "N cases selected: 2888"
+## [1] "N cases selected: 2893"
## [1] "Updating low flow shower uptake for year: 1998 & month 11 (5. Recovering)"
-## [1] "N cases selected: 2879"
+## [1] "N cases selected: 2889"
## [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: 2734"
+## [1] "N cases selected: 2736"
## [1] "Updating low flow shower uptake for year: 2003 & month 4 (2. Developing)"
-## [1] "N cases selected: 2734"
-## [1] "Updating low flow shower uptake for year: 2003 & month 5 (2. Developing)"
## [1] "N cases selected: 2736"
+## [1] "Updating low flow shower uptake for year: 2003 & month 5 (2. Developing)"
+## [1] "N cases selected: 2720"
## [1] "Updating low flow shower uptake for year: 2003 & month 6 (2. Developing)"
-## [1] "N cases selected: 2723"
+## [1] "N cases selected: 2721"
## [1] "Updating low flow shower uptake for year: 2003 & month 7 (2. Developing)"
-## [1] "N cases selected: 2707"
+## [1] "N cases selected: 2712"
## [1] "Updating low flow shower uptake for year: 2003 & month 8 (2. Developing)"
-## [1] "N cases selected: 2711"
+## [1] "N cases selected: 2715"
## [1] "Updating low flow shower uptake for year: 2003 & month 9 (3. Drought)"
-## [1] "N cases selected: 2701"
+## [1] "N cases selected: 2711"
## [1] "Updating low flow shower uptake for year: 2003 & month 10 (3. Drought)"
-## [1] "N cases selected: 2694"
+## [1] "N cases selected: 2693"
## [1] "Updating low flow shower uptake for year: 2003 & month 11 (3. Drought)"
-## [1] "N cases selected: 2678"
+## [1] "N cases selected: 2689"
## [1] "Updating low flow shower uptake for year: 2003 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2687"
+## [1] "N cases selected: 2671"
## [1] "Year: 2004"
## [1] "Updating low flow shower uptake for year: 2004 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2660"
+## [1] "N cases selected: 2668"
## [1] "Updating low flow shower uptake for year: 2004 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2670"
+## [1] "N cases selected: 2655"
## [1] "Updating low flow shower uptake for year: 2004 & month 12 (2. Developing)"
-## [1] "N cases selected: 2639"
+## [1] "N cases selected: 2629"
## [1] "Year: 2005"
## [1] "Updating low flow shower uptake for year: 2005 & month 1 (2. Developing)"
-## [1] "N cases selected: 2633"
+## [1] "N cases selected: 2630"
## [1] "Updating low flow shower uptake for year: 2005 & month 2 (2. Developing)"
-## [1] "N cases selected: 2609"
+## [1] "N cases selected: 2618"
## [1] "Updating low flow shower uptake for year: 2005 & month 3 (2. Developing)"
-## [1] "N cases selected: 2623"
+## [1] "N cases selected: 2613"
## [1] "Updating low flow shower uptake for year: 2005 & month 4 (2. Developing)"
-## [1] "N cases selected: 2619"
+## [1] "N cases selected: 2604"
## [1] "Updating low flow shower uptake for year: 2005 & month 5 (2. Developing)"
-## [1] "N cases selected: 2601"
+## [1] "N cases selected: 2619"
## [1] "Updating low flow shower uptake for year: 2005 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2600"
+## [1] "N cases selected: 2605"
## [1] "Updating low flow shower uptake for year: 2005 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2593"
+## [1] "N cases selected: 2600"
## [1] "Updating low flow shower uptake for year: 2005 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2584"
+## [1] "N cases selected: 2604"
## [1] "Updating low flow shower uptake for year: 2005 & month 9 (2. Developing)"
-## [1] "N cases selected: 2582"
+## [1] "N cases selected: 2574"
## [1] "Updating low flow shower uptake for year: 2005 & month 10 (2. Developing)"
-## [1] "N cases selected: 2581"
+## [1] "N cases selected: 2573"
## [1] "Updating low flow shower uptake for year: 2005 & month 11 (2. Developing)"
-## [1] "N cases selected: 2574"
+## [1] "N cases selected: 2559"
## [1] "Updating low flow shower uptake for year: 2005 & month 12 (3. Drought)"
-## [1] "N cases selected: 2560"
+## [1] "N cases selected: 2557"
## [1] "Year: 2006"
## [1] "Updating low flow shower uptake for year: 2006 & month 1 (3. Drought)"
-## [1] "N cases selected: 2569"
+## [1] "N cases selected: 2552"
## [1] "Updating low flow shower uptake for year: 2006 & month 2 (3. Drought)"
-## [1] "N cases selected: 2546"
+## [1] "N cases selected: 2552"
## [1] "Updating low flow shower uptake for year: 2006 & month 3 (3. Drought)"
-## [1] "N cases selected: 2531"
+## [1] "N cases selected: 2555"
## [1] "Updating low flow shower uptake for year: 2006 & month 4 (3. Drought)"
-## [1] "N cases selected: 2536"
+## [1] "N cases selected: 2535"
## [1] "Updating low flow shower uptake for year: 2006 & month 5 (3. Drought)"
-## [1] "N cases selected: 2522"
+## [1] "N cases selected: 2535"
## [1] "Updating low flow shower uptake for year: 2006 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2529"
+## [1] "N cases selected: 2513"
## [1] "Updating low flow shower uptake for year: 2006 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2518"
+## [1] "N cases selected: 2513"
## [1] "Updating low flow shower uptake for year: 2006 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2516"
+## [1] "N cases selected: 2508"
## [1] "Updating low flow shower uptake for year: 2006 & month 9 (5. Recovering)"
-## [1] "N cases selected: 2502"
+## [1] "N cases selected: 2499"
## [1] "Updating low flow shower uptake for year: 2006 & month 10 (5. Recovering)"
-## [1] "N cases selected: 2505"
+## [1] "N cases selected: 2496"
## [1] "Updating low flow shower uptake for year: 2006 & month 11 (5. Recovering)"
-## [1] "N cases selected: 2500"
+## [1] "N cases selected: 2494"
## [1] "Updating low flow shower uptake for year: 2006 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2474"
+## [1] "N cases selected: 2483"
## [1] "Year: 2007"
## [1] "Updating low flow shower uptake for year: 2007 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2482"
+## [1] "N cases selected: 2478"
## [1] "Updating low flow shower uptake for year: 2007 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2476"
+## [1] "N cases selected: 2463"
## [1] "Year: 2008"
## [1] "Year: 2009"
## [1] "Updating low flow shower uptake for year: 2009 & month 3 (2. Developing)"
-## [1] "N cases selected: 2400"
+## [1] "N cases selected: 2409"
## [1] "Updating low flow shower uptake for year: 2009 & month 4 (2. Developing)"
-## [1] "N cases selected: 2399"
+## [1] "N cases selected: 2380"
## [1] "Updating low flow shower uptake for year: 2009 & month 5 (2. Developing)"
-## [1] "N cases selected: 2405"
+## [1] "N cases selected: 2382"
## [1] "Updating low flow shower uptake for year: 2009 & month 6 (2. Developing)"
-## [1] "N cases selected: 2400"
+## [1] "N cases selected: 2399"
## [1] "Updating low flow shower uptake for year: 2009 & month 7 (2. Developing)"
-## [1] "N cases selected: 2397"
+## [1] "N cases selected: 2388"
## [1] "Updating low flow shower uptake for year: 2009 & month 8 (2. Developing)"
-## [1] "N cases selected: 2380"
+## [1] "N cases selected: 2387"
## [1] "Updating low flow shower uptake for year: 2009 & month 9 (3. Drought)"
-## [1] "N cases selected: 2377"
+## [1] "N cases selected: 2384"
## [1] "Updating low flow shower uptake for year: 2009 & month 10 (3. Drought)"
-## [1] "N cases selected: 2368"
+## [1] "N cases selected: 2377"
## [1] "Updating low flow shower uptake for year: 2009 & month 11 (3. Drought)"
-## [1] "N cases selected: 2359"
+## [1] "N cases selected: 2372"
## [1] "Updating low flow shower uptake for year: 2009 & month 12 (5. Recovering)"
-## [1] "N cases selected: 2363"
+## [1] "N cases selected: 2349"
## [1] "Year: 2010"
## [1] "Updating low flow shower uptake for year: 2010 & month 1 (5. Recovering)"
-## [1] "N cases selected: 2352"
+## [1] "N cases selected: 2349"
## [1] "Updating low flow shower uptake for year: 2010 & month 2 (5. Recovering)"
-## [1] "N cases selected: 2359"
+## [1] "N cases selected: 2337"
## [1] "Updating low flow shower uptake for year: 2010 & month 9 (2. Developing)"
-## [1] "N cases selected: 2335"
+## [1] "N cases selected: 2325"
## [1] "Updating low flow shower uptake for year: 2010 & month 10 (2. Developing)"
## [1] "N cases selected: 2327"
## [1] "Updating low flow shower uptake for year: 2010 & month 11 (2. Developing)"
-## [1] "N cases selected: 2321"
+## [1] "N cases selected: 2315"
## [1] "Updating low flow shower uptake for year: 2010 & month 12 (2. Developing)"
-## [1] "N cases selected: 2316"
+## [1] "N cases selected: 2299"
## [1] "Year: 2011"
## [1] "Updating low flow shower uptake for year: 2011 & month 1 (2. Developing)"
-## [1] "N cases selected: 2300"
+## [1] "N cases selected: 2326"
## [1] "Updating low flow shower uptake for year: 2011 & month 2 (2. Developing)"
-## [1] "N cases selected: 2299"
+## [1] "N cases selected: 2305"
## [1] "Updating low flow shower uptake for year: 2011 & month 3 (3. Drought)"
-## [1] "N cases selected: 2297"
+## [1] "N cases selected: 2291"
## [1] "Updating low flow shower uptake for year: 2011 & month 4 (3. Drought)"
-## [1] "N cases selected: 2301"
+## [1] "N cases selected: 2280"
## [1] "Updating low flow shower uptake for year: 2011 & month 5 (3. Drought)"
-## [1] "N cases selected: 2290"
+## [1] "N cases selected: 2308"
## [1] "Updating low flow shower uptake for year: 2011 & month 6 (5. Recovering)"
-## [1] "N cases selected: 2286"
+## [1] "N cases selected: 2287"
## [1] "Updating low flow shower uptake for year: 2011 & month 7 (5. Recovering)"
-## [1] "N cases selected: 2273"
+## [1] "N cases selected: 2257"
## [1] "Updating low flow shower uptake for year: 2011 & month 8 (5. Recovering)"
-## [1] "N cases selected: 2270"
+## [1] "N cases selected: 2281"
## [1] "Year: 2012"
```
@@ -5584,7 +5640,7 @@ table(hhFinalDataComboExpandedCEHDT$loFlowShower, hhFinalDataComboExpandedCEHDT$
##
## Low flow Normal flow
## Low flow 103304 0
-## Normal flow 60316 577908
+## Normal flow 60567 577657
```
```r
@@ -5612,6 +5668,8 @@ ggplot(plotDT, aes(x = obsDate, y = pcHHs, colour = flow)) + geom_line() + facet
### Temporary Use Ban
Now apply the TUB. This one does need to be done by model as it uses a cut point in external consumption which will differ.
+> We also shoud use the 'no garden to water' data in the SPRG survey in the process for v2?
+
```r
# as above but with some variations no need to update forwards as we assume
@@ -5690,8 +5748,8 @@ 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: 26.7029814730589"
-## [1] "Top 28% cut: 21.2574514397221"
+## [1] "Top 14% cut: 26.5848437091723"
+## [1] "Top 28% cut: 21.5288841242727"
## [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)"
@@ -5700,8 +5758,8 @@ 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: 26.8200355433548"
-## [1] "Top 28% cut: 21.3558054166805"
+## [1] "Top 14% cut: 26.6507521149996"
+## [1] "Top 28% cut: 21.5911132257507"
## [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)"
@@ -5710,8 +5768,8 @@ 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: 26.7032988766881"
-## [1] "Top 28% cut: 21.2813951500138"
+## [1] "Top 14% cut: 26.534015448333"
+## [1] "Top 28% cut: 21.4916495060354"
## [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)"
@@ -5721,8 +5779,8 @@ 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: 27.1150651990317"
-## [1] "Top 28% cut: 21.6257803225655"
+## [1] "Top 14% cut: 26.9271598198798"
+## [1] "Top 28% cut: 21.8801573315507"
## [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)"
@@ -5731,8 +5789,8 @@ 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: 27.3162147990317"
-## [1] "Top 28% cut: 21.8051872812671"
+## [1] "Top 14% cut: 27.0892998198798"
+## [1] "Top 28% cut: 22.0422973315507"
## [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)"
@@ -5741,8 +5799,8 @@ 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: 27.4064154728594"
-## [1] "Top 28% cut: 22.0049088214481"
+## [1] "Top 14% cut: 27.287840375839"
+## [1] "Top 28% cut: 22.2357769049278"
## [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)"
@@ -5751,8 +5809,8 @@ 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: 28.0140954728594"
-## [1] "Top 28% cut: 22.6125888214481"
+## [1] "Top 14% cut: 27.895520375839"
+## [1] "Top 28% cut: 22.874616748026"
## [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)"
@@ -5761,8 +5819,8 @@ 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: 27.8746721395261"
-## [1] "Top 28% cut: 22.4671471912724"
+## [1] "Top 14% cut: 27.7560970425057"
+## [1] "Top 28% cut: 22.7040335715945"
## [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)"
@@ -5771,8 +5829,8 @@ 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: 27.2972596200058"
-## [1] "Top 28% cut: 21.8389114229238"
+## [1] "Top 14% cut: 27.2393508100736"
+## [1] "Top 28% cut: 22.0825818423683"
## [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)"
@@ -5781,8 +5839,8 @@ 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: 27.2149632183101"
-## [1] "Top 28% cut: 21.7230068029683"
+## [1] "Top 14% cut: 27.0323464865465"
+## [1] "Top 28% cut: 21.9853439982174"
## [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)"
@@ -5791,8 +5849,8 @@ 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: 26.6505522100214"
-## [1] "Top 28% cut: 21.1598938762707"
+## [1] "Top 14% cut: 26.4606684316816"
+## [1] "Top 28% cut: 21.3845785513219"
## [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)"
@@ -5801,8 +5859,8 @@ 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: 26.4345055022416"
-## [1] "Top 28% cut: 20.9404768029683"
+## [1] "Top 14% cut: 26.2498164865465"
+## [1] "Top 28% cut: 21.2028139982174"
## [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)"
@@ -5811,8 +5869,8 @@ 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: 26.8804788766881"
-## [1] "Top 28% cut: 21.3853097429373"
+## [1] "Top 14% cut: 26.6847106909446"
+## [1] "Top 28% cut: 21.6029060179886"
## [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)"
@@ -5822,8 +5880,8 @@ 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: 26.9625555433548"
-## [1] "Top 28% cut: 21.4875350166805"
+## [1] "Top 14% cut: 26.7932721149996"
+## [1] "Top 28% cut: 21.7277578904882"
## [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)"
@@ -5832,8 +5890,8 @@ 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: 27.1202793402119"
-## [1] "Top 28% cut: 21.6028649990715"
+## [1] "Top 14% cut: 26.8785364865465"
+## [1] "Top 28% cut: 21.8315339982174"
## [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)"
@@ -5842,8 +5900,8 @@ 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: 27.3628833924386"
-## [1] "Top 28% cut: 21.8951144221809"
+## [1] "Top 14% cut: 27.2050511069816"
+## [1] "Top 28% cut: 22.1588506648841"
## [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)"
@@ -5852,8 +5910,8 @@ 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: 27.2991325990317"
-## [1] "Top 28% cut: 21.8095317892321"
+## [1] "Top 14% cut: 27.1092864865465"
+## [1] "Top 28% cut: 22.0622839982174"
## [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)"
@@ -5862,8 +5920,8 @@ 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: 27.5139492184224"
-## [1] "Top 28% cut: 22.0415126728919"
+## [1] "Top 14% cut: 27.419060375839"
+## [1] "Top 28% cut: 22.3098809287109"
## [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)"
@@ -5872,8 +5930,8 @@ 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: 27.3456800849767"
-## [1] "Top 28% cut: 21.8591934696349"
+## [1] "Top 14% cut: 27.1685331532132"
+## [1] "Top 28% cut: 22.1215306648841"
## [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)"
@@ -5882,8 +5940,8 @@ 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: 26.6380855433548"
-## [1] "Top 28% cut: 21.133903209604"
+## [1] "Top 14% cut: 26.4146339576112"
+## [1] "Top 28% cut: 21.3488673315507"
## [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)"
@@ -5892,8 +5950,8 @@ 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: 26.5840555433548"
-## [1] "Top 28% cut: 21.0995208038063"
+## [1] "Top 14% cut: 26.4147721149996"
+## [1] "Top 28% cut: 21.3395076729654"
## [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)"
@@ -5908,8 +5966,8 @@ 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: 27.327116725772"
-## [1] "Top 28% cut: 21.9034788214481"
+## [1] "Top 14% cut: 27.2170325491869"
+## [1] "Top 28% cut: 22.1773133709197"
## [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)"
@@ -5918,8 +5976,8 @@ 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: 26.6846222100214"
-## [1] "Top 28% cut: 21.1989189429373"
+## [1] "Top 14% cut: 26.4955441279114"
+## [1] "Top 28% cut: 21.4281370749833"
## [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)"
@@ -5928,8 +5986,8 @@ 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: 26.5034188766881"
-## [1] "Top 28% cut: 20.9953398762707"
+## [1] "Top 14% cut: 26.2679989576112"
+## [1] "Top 28% cut: 21.2142006648841"
## [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)"
@@ -5940,8 +5998,8 @@ 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: 26.9356722100214"
-## [1] "Top 28% cut: 21.4466509429373"
+## [1] "Top 14% cut: 26.7465941279114"
+## [1] "Top 28% cut: 21.6739081513219"
## [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)"
@@ -5951,8 +6009,8 @@ 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: 26.9673688766881"
-## [1] "Top 28% cut: 21.4971987500138"
+## [1] "Top 14% cut: 26.798085448333"
+## [1] "Top 28% cut: 21.7360177175557"
## [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)"
@@ -5961,8 +6019,8 @@ 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: 27.1562022100214"
-## [1] "Top 28% cut: 21.6601305429373"
+## [1] "Top 14% cut: 26.9576619576112"
+## [1] "Top 28% cut: 21.8763085513219"
## [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)"
@@ -5971,8 +6029,8 @@ 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: 27.1094333924386"
-## [1] "Top 28% cut: 21.66765920539"
+## [1] "Top 14% cut: 26.9874573736483"
+## [1] "Top 28% cut: 21.9387394682108"
## [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)"
@@ -5981,8 +6039,8 @@ 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: 27.1536166849767"
-## [1] "Top 28% cut: 21.6612701363016"
+## [1] "Top 14% cut: 26.9706098198798"
+## [1] "Top 28% cut: 21.9236073315507"
## [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)"
@@ -5991,8 +6049,8 @@ 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: 27.1068958850891"
-## [1] "Top 28% cut: 21.648203243011"
+## [1] "Top 14% cut: 27.0120070425057"
+## [1] "Top 28% cut: 21.9128499953775"
## [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)"
@@ -6004,8 +6062,8 @@ 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: 27.3143155022416"
-## [1] "Top 28% cut: 21.8202868029683"
+## [1] "Top 14% cut: 27.1296264865465"
+## [1] "Top 28% cut: 22.0826239982174"
## [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)"
@@ -6014,8 +6072,8 @@ 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: 26.5195455433548"
-## [1] "Top 28% cut: 21.0678002166805"
+## [1] "Top 14% cut: 26.3502621149996"
+## [1] "Top 28% cut: 21.2931053218941"
## [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)"
@@ -6024,8 +6082,8 @@ 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: 26.4039103990317"
-## [1] "Top 28% cut: 20.9133207225655"
+## [1] "Top 14% cut: 26.2079898198798"
+## [1] "Top 28% cut: 21.1609873315507"
## [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)"
@@ -6036,8 +6094,8 @@ 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: 27.3679585323651"
-## [1] "Top 28% cut: 21.8735742147611"
+## [1] "Top 14% cut: 27.1591264865465"
+## [1] "Top 28% cut: 22.1121239982174"
## [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)"
@@ -6046,8 +6104,8 @@ 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: 27.5169211990317"
-## [1] "Top 28% cut: 22.0268756558988"
+## [1] "Top 14% cut: 27.3243431532132"
+## [1] "Top 28% cut: 22.2773406648841"
## [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)"
@@ -6056,8 +6114,8 @@ 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: 27.6515988061927"
-## [1] "Top 28% cut: 22.244073857939"
+## [1] "Top 14% cut: 27.5330237091723"
+## [1] "Top 28% cut: 22.4809602382611"
## [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)"
@@ -6315,6 +6373,33 @@ myDrPlot
<!-- -->
```r
+# Figure for IWA Bath final paper
+# (http://ws.iwaponline.com/content/early/2018/02/13/ws.2018.035) take the
+# mean of the baseline & WE models (i.e. ignore metering as not mentioned in
+# the text & caption etc) also do not display drought phases (too complex to
+# create key!)
+myCap <- "IMPETUS Model: synthetic households (n = 1800)\n Model v1"
+paperPlotDT <- plotTotalDT[model == "v1_3", .(meanBaselineWeSum = mean(meanBaselineWeSum),
+ meanBaselineDrSum = mean(meanBaselineDrSum)), keyby = obsDate]
+paperPlot <- ggplot(paperPlotDT, aes(x = obsDate)) + geom_line(aes(y = meanBaselineWeSum,
+ colour = "Baseline")) + geom_line(aes(y = meanBaselineDrSum, colour = "Drought model")) +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+ labs(y = "Mean l/hh/day", x = "Date", caption = myCap)
+maxY <- max(paperPlotDT$meanBaselineDrSum)
+minY <- min(paperPlotDT$meanBaselineDrSum)
+
+paperPlot <- ba_IMPETUSaddDroughtPhases(paperPlot, minY, maxY)
+paperPlot
+```
+
+<!-- -->
+
+```r
+ggsave("Fig4_Compare_sum_model_v1_3.pdf", dpi = 400)
+
+# Grey scale version if required myDrPlot <- myDrPlot + theme_bw()
+# ggsave('Fig4_Compare_sum_model_v1_3_gs.pdf', plot = myDrPlot, dpi = 400)
+
# 2.0 ----
myPlot <- ggplot(plotTotalDT[model == "v2_0"], aes(x = obsDate)) + geom_ribbon(aes(ymin = yminWE,
ymax = ymaxWE, fill = "Baseline 95% CI", group = metered), alpha = 0.5) +
@@ -6334,7 +6419,7 @@ myDrPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
myDrPlot
```
-<!-- -->
+<!-- -->
```r
myPlot <- ggplot(plotTotalDT, aes(x = obsDate)) + geom_ribbon(aes(ymin = yminWE,
@@ -6355,7 +6440,7 @@ myDrPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
myDrPlot
```
-<!-- -->
+<!-- -->
```r
plotTotalDT <- plotTotalDT[, `:=`(pcSaved, 100 * ((meanBaselineWeSum - meanBaselineDrSum)/meanBaselineWeSum))]
@@ -6376,10 +6461,10 @@ Table: Model affects (% total reduced)
model metered Min reduction Mean reduction Max reduction
------ ------------ -------------- --------------- --------------
-v1_3 Not metered 0 2.72 4.36
-v1_3 Metered 0 2.42 3.53
-v2_0 Not metered 0 3.14 5.18
-v2_0 Metered 0 3.27 5.40
+v1_3 Not metered 0 2.70 4.14
+v1_3 Metered 0 2.36 3.43
+v2_0 Not metered 0 3.46 5.17
+v2_0 Metered 0 2.98 5.47
```r
baseline1Start <- plotTotalDT[model == "v1_3" & obsDate == min(obsDate), meanBaselineWeSum]
@@ -6397,9 +6482,9 @@ 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 5.92, 5.89%
- * model v1_3 showed a reduction of 8.99, 8.79%
- * model v2_0 showed a reduction of 8.21, 12.04%
+ * the baseline model showed a reduction of 5.85, 6.06%
+ * model v1_3 showed a reduction of 8.59, 9.23%
+ * model v2_0 showed a reduction of 10.73, 9.45%
This is clearly shown in the chart below where:
@@ -6418,12 +6503,38 @@ myPlot <- ggplot(plotTotalDT[model == "v1_3"], aes(x = obsDate, y = pcSaved,
maxY <- max(plotTotalDT[model == "v1_3"]$pcSaved)
minY <- 0
-ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
+myPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
+myPlot
```
<!-- -->
```r
+# Figure for IWA Bath final paper
+# (http://ws.iwaponline.com/content/early/2018/02/13/ws.2018.035) just
+# baseline - WE (ignore metering) re-use previous paper DT
+paperPlotDT <- paperPlotDT[, `:=`(pcSaved, 100 * ((meanBaselineWeSum - meanBaselineDrSum)/meanBaselineWeSum))]
+myCap <- "IMPETUS model: synthetic households (n = 1800)\n Model v1"
+myPlot <- ggplot(paperPlotDT, aes(x = obsDate, y = pcSaved)) + geom_point() +
+ theme(legend.title = element_blank()) + theme(legend.position = "bottom") +
+ labs(y = "% saving", x = "Date", caption = myCap)
+
+maxY <- max(paperPlotDT$pcSaved)
+minY <- 0
+
+myPlot <- ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
+myPlot
+```
+
+<!-- -->
+
+```r
+ggsave("Fig5_Chart_savings_v1_3_by_month.pdf", plot = myPlot, dpi = 400)
+
+# Grey scale version if required myPlot <- myPlot + theme_bw()
+# ggsave('Fig5_Chart_savings_v1_3_by_month_gs.pdf', plot = myPlot, dpi =
+# 400)
+
myPlot <- ggplot(plotTotalDT[model == "v2_0"], aes(x = obsDate, y = pcSaved,
colour = metered)) + geom_point() + theme(legend.title = element_blank()) +
theme(legend.position = "bottom") + facet_grid(model ~ .) + labs(title = "% saving in total l/hh/day",
@@ -6434,7 +6545,7 @@ minY <- 0
ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
```
-<!-- -->
+<!-- -->
```r
myPlot <- ggplot(plotTotalDT, aes(x = obsDate, y = pcSaved, colour = metered)) +
@@ -6448,7 +6559,7 @@ minY <- 0
ba_IMPETUSaddDroughtPhases(myPlot, minY, maxY)
```
-<!-- -->
+<!-- -->
Interesting - savings under model v2 are larger. Why?
@@ -6474,6 +6585,10 @@ ggplot(droughtPhaseDT, aes(x = phase, y = V1, fill = phase)) + geom_col() +
<!-- -->
+```r
+ggsave("Fig4_5_DroughtPlotKey.pdf", dpi = 400)
+```
+
## Extract drought & WE-adjusted hot water volumes (for BECC 2017 paper)
Use: hhFinalDataComboExpandedCEHDT
@@ -6502,27 +6617,27 @@ summary(hhFinalDataComboExpandedCEHDT)
##
## Basin.baseline Bath.baseline Dishwasher.baseline
## Min. : 10.40 Min. : 0.00 Min. : 0.00
-## 1st Qu.: 21.30 1st Qu.: 26.40 1st Qu.: 0.00
-## Median : 26.69 Median : 56.91 Median :19.83
-## Mean : 39.67 Mean : 54.96 Mean :13.40
-## 3rd Qu.: 39.72 3rd Qu.: 76.67 3rd Qu.:23.27
-## Max. :463.20 Max. :138.66 Max. :32.93
+## 1st Qu.: 20.94 1st Qu.: 26.40 1st Qu.: 0.00
+## Median : 26.64 Median : 56.91 Median :19.80
+## Mean : 39.66 Mean : 54.88 Mean :13.31
+## 3rd Qu.: 39.72 3rd Qu.: 76.50 3rd Qu.:23.13
+## Max. :463.20 Max. :128.19 Max. :35.07
## NA's :10800
-## KitchenSink.baseline Shower.baseline WC.baseline
-## Min. : 7.57 Min. : 0.00 Min. : 25.00
-## 1st Qu.:15.14 1st Qu.: 34.55 1st Qu.: 75.00
-## Median :32.31 Median : 41.32 Median :100.00
-## Mean :31.51 Mean : 69.10 Mean : 99.92
-## 3rd Qu.:45.05 3rd Qu.: 93.60 3rd Qu.:125.00
-## Max. :75.70 Max. :513.83 Max. :262.50
-## NA's :10368 NA's :11448
+## KitchenSink.baseline Shower.baseline WC.baseline
+## Min. : 7.57 Min. : 0.00 Min. : 25.0
+## 1st Qu.:15.14 1st Qu.: 34.23 1st Qu.: 75.0
+## Median :32.10 Median : 41.06 Median :100.0
+## Mean :31.48 Mean : 69.04 Mean :100.2
+## 3rd Qu.:45.14 3rd Qu.: 93.60 3rd Qu.:127.0
+## Max. :75.70 Max. :513.83 Max. :262.5
+## NA's :10368 NA's :11448
## WashingMachine.baseline External.baseline Basin
## Min. : 0.00 Min. :-1.23 Min. :-0.0908
-## 1st Qu.: 16.67 1st Qu.: 1.13 1st Qu.: 0.0569
-## Median : 67.78 Median :16.43 Median : 0.1282
-## Mean : 56.86 Mean :17.92 Mean : 0.1280
-## 3rd Qu.: 85.26 3rd Qu.:26.01 3rd Qu.: 0.1720
-## Max. :154.90 Max. :97.50 Max. : 0.4506
+## 1st Qu.: 16.67 1st Qu.: 1.32 1st Qu.: 0.0569
+## Median : 67.23 Median :16.88 Median : 0.1282
+## Mean : 56.74 Mean :18.06 Mean : 0.1280
+## 3rd Qu.: 85.36 3rd Qu.:25.76 3rd Qu.: 0.1720
+## Max. :155.94 Max. :97.50 Max. : 0.4506
## NA's :7560 NA's :36072
## Bath Dishwasher External KitchenSink
## Min. :-3.9549 Min. :-2.1795 Min. :-1.2822 Min. :-0.1007
@@ -6542,27 +6657,27 @@ summary(hhFinalDataComboExpandedCEHDT)
##
## Basin.baseline.madj Bath.baseline.madj Dishwasher.baseline.madj
## Min. : 10.33 Min. : -3.955 Min. :-2.17945
-## 1st Qu.: 21.44 1st Qu.: 26.196 1st Qu.:-0.04467
-## Median : 26.86 Median : 55.722 Median :18.99479
-## Mean : 39.80 Mean : 53.761 Mean :12.74892
-## 3rd Qu.: 39.81 3rd Qu.: 74.857 3rd Qu.:22.58034
-## Max. :463.65 Max. :138.755 Max. :32.93016
+## 1st Qu.: 21.11 1st Qu.: 26.196 1st Qu.:-0.04467
+## Median : 26.85 Median : 55.598 Median :18.89711
+## Mean : 39.79 Mean : 53.683 Mean :12.66274
+## 3rd Qu.: 39.82 3rd Qu.: 74.699 3rd Qu.:22.43016
+## Max. :463.65 Max. :128.283 Max. :35.07312
## NA's :10800
## External.baseline.madj KitchenSink.baseline.madj Shower.baseline.madj
## Min. :-2.51 Min. : 7.469 Min. : -0.244
-## 1st Qu.: 1.63 1st Qu.:15.466 1st Qu.: 35.014
-## Median :16.60 Median :32.469 Median : 41.918
-## Mean :18.04 Mean :31.660 Mean : 69.518
-## 3rd Qu.:26.11 3rd Qu.:45.196 3rd Qu.: 93.573
+## 1st Qu.: 1.85 1st Qu.:15.466 1st Qu.: 34.694
+## Median :17.06 Median :32.262 Median : 41.646
+## Mean :18.18 Mean :31.632 Mean : 69.458
+## 3rd Qu.:25.88 3rd Qu.:45.289 3rd Qu.: 93.573
## Max. :98.17 Max. :76.121 Max. :515.287
## NA's :36072 NA's :10368
## WC.baseline.madj WashingMachine.baseline.madj sumDaily.baseline.madj
## Min. : 20.64 Min. : -3.245 Min. : 53.53
-## 1st Qu.: 73.44 1st Qu.: 18.377 1st Qu.: 310.29
-## Median : 98.95 Median : 68.592 Median : 387.13
-## Mean : 98.77 Mean : 56.630 Mean : 382.58
-## 3rd Qu.:123.88 3rd Qu.: 84.787 3rd Qu.: 460.76
-## Max. :262.79 Max. :154.862 Max. :1153.15
+## 1st Qu.: 72.99 1st Qu.: 18.377 1st Qu.: 307.77
+## Median : 99.56 Median : 68.092 Median : 386.98
+## Mean : 99.10 Mean : 56.511 Mean : 382.66
+## 3rd Qu.:125.22 3rd Qu.: 84.852 3rd Qu.: 462.33
+## Max. :262.79 Max. :155.901 Max. :1153.15
## NA's :11448 NA's :7560 NA's :36072
## currMonS occRed loWC loSh
## Length:741528 Min. :1.0 Min. :0 Min. :0
@@ -6574,19 +6689,19 @@ summary(hhFinalDataComboExpandedCEHDT)
##
## dualFlushWC loFlowShower WC.baseline.madj.we
## Length:741528 Length:741528 Min. : 9.814
-## Class :character Class :character 1st Qu.: 57.833
-## Mode :character Mode :character Median : 82.439
-## Mean : 88.902
-## 3rd Qu.:117.557
+## Class :character Class :character 1st Qu.: 58.230
+## Mode :character Mode :character Median : 81.400
+## Mean : 89.174
+## 3rd Qu.:118.995
## Max. :262.787
## NA's :11448
## Shower.baseline.madj.we sumDaily.baseline.madj.we yearOrig
-## Min. : -0.244 Min. : 36.45 Min. :1994
-## 1st Qu.: 32.630 1st Qu.: 294.21 1st Qu.:1999
-## Median : 40.862 Median : 369.57 Median :2003
-## Mean : 65.726 Mean : 368.95 Mean :2003
-## 3rd Qu.: 85.698 3rd Qu.: 450.49 3rd Qu.:2008
-## Max. :515.287 Max. :1152.91 Max. :2012
+## Min. : -0.244 Min. : 35.59 Min. :1994
+## 1st Qu.: 32.315 1st Qu.: 292.77 1st Qu.:1999
+## Median : 40.591 Median : 370.52 Median :2003
+## Mean : 65.663 Mean : 368.98 Mean :2003
+## 3rd Qu.: 85.671 3rd Qu.: 452.59 3rd Qu.:2008
+## Max. :515.262 Max. :1152.91 Max. :2012
## NA's :10368 NA's :36072
## currSeason yrStr seasonStr Colne
## Spring:185382 Length:741528 Length:741528 Length:741528
@@ -6605,27 +6720,27 @@ summary(hhFinalDataComboExpandedCEHDT)
##
##
## dualFlushWCupdated loFlowShowerDr loFlowShowerUpdated
-## Min. :0.0000 Length:741528 Min. :0.00000
-## 1st Qu.:0.0000 Class :character 1st Qu.:0.00000
-## Median :0.0000 Mode :character Median :0.00000
-## Mean :0.1909 Mean :0.09709
-## 3rd Qu.:0.0000 3rd Qu.:0.00000
-## Max. :1.0000 Max. :1.00000
+## Min. :0.000 Length:741528 Min. :0.00000
+## 1st Qu.:0.000 Class :character 1st Qu.:0.00000
+## Median :0.000 Mode :character Median :0.00000
+## Mean :0.191 Mean :0.09698
+## 3rd Qu.:0.000 3rd Qu.:0.00000
+## Max. :1.000 Max. :1.00000
##
## applyTUB WC.baseline.madj.we.dr Shower.baseline.madj.we.dr
-## Min. :0.00000 Min. : 9.814 Min. : -0.244
-## 1st Qu.:0.00000 1st Qu.: 47.992 1st Qu.: 29.887
-## Median :0.00000 Median : 73.991 Median : 40.298
-## Mean :0.01215 Mean : 81.002 Mean : 63.514
-## 3rd Qu.:0.00000 3rd Qu.:111.965 3rd Qu.: 80.808
-## Max. :1.00000 Max. :262.739 Max. :515.287
+## Min. :0.00000 Min. : 9.70 Min. : -0.244
+## 1st Qu.:0.00000 1st Qu.: 48.42 1st Qu.: 30.051
+## Median :0.00000 Median : 73.98 Median : 39.807
+## Mean :0.01215 Mean : 81.42 Mean : 63.342
+## 3rd Qu.:0.00000 3rd Qu.:112.16 3rd Qu.: 80.702
+## Max. :1.00000 Max. :262.79 Max. :515.262
## NA's :11448 NA's :10368
## External.baseline.madj.we.dr sumDaily.baseline.madj.we.dr
-## Min. :-2.51 Min. : 36.45
-## 1st Qu.: 1.63 1st Qu.: 284.01
-## Median :16.20 Median : 360.61
-## Mean :17.61 Mean : 358.46
-## 3rd Qu.:25.58 3rd Qu.: 439.11
+## Min. :-2.51 Min. : 35.59
+## 1st Qu.: 1.85 1st Qu.: 283.35
+## Median :16.67 Median : 361.62
+## Mean :17.74 Mean : 358.50
+## 3rd Qu.:25.36 3rd Qu.: 441.08
## Max. :98.17 Max. :1152.91
## NA's :36072 NA's :36072
```
@@ -6672,7 +6787,7 @@ Magesh Nagarajan (m.nagarajan@soton.ac.uk)
If you wish to refer to any of the material from this report please cite as:
- * Anderson, B., Manouseli, D. & Nagarajan, M. (2017) _A household level daily consumption estimation microsimulation model_, University of Southampton: Southampton, UK.
+ * Anderson, B., Manouseli, D. & Nagarajan, M. (2018) _A household level daily consumption estimation microsimulation model_, University of Southampton: Southampton, UK.
# Runtime
@@ -6684,7 +6799,7 @@ t <- proc.time() - startTime
elapsed <- t[[3]]
```
-Analysis completed in 519.826 seconds ( 8.66 minutes) using [knitr](https://cran.r-project.org/package=knitr) in [RStudio](http://www.rstudio.com) with R version 3.4.2 (2017-09-28) running on x86_64-apple-darwin15.6.0.
+Analysis completed in 670.059 seconds ( 11.17 minutes) using [knitr](https://cran.r-project.org/package=knitr) in [RStudio](http://www.rstudio.com) with R version 3.4.2 (2017-09-28) running on x86_64-apple-darwin15.6.0.
R packages used:
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