BP overview

class: center, middle, inverse, title-slide

.title[
# BP overview
]
.subtitle[
## Combined PDF
]
.author[
### Orlenko Irina
]
.date[
### 2023/07/04 (updated: 2023-07-04)
]

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# Counts

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A worker is a user who pings at least 2 times a day at least 2 days per week for at leat 2 weeks during working ours.

<table class=" lightable-paper lightable-striped" style='font-family: "Arial Narrow", arial, helvetica, sans-serif; width: auto !important; margin-left: auto; margin-right: auto;'>
 <thead>
  <tr>
   <th style="text-align:left;"> district </th>
   <th style="text-align:right;"> Worker count </th>
   <th style="text-align:right;"> Signal count </th>
   <th style="text-align:right;"> Average signals per worker </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Raffles Place </td>
   <td style="text-align:right;"> 473 </td>
   <td style="text-align:right;"> 88036 </td>
   <td style="text-align:right;"> 186.12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Changi BP </td>
   <td style="text-align:right;"> 294 </td>
   <td style="text-align:right;"> 68497 </td>
   <td style="text-align:right;"> 232.98 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mapletree BP </td>
   <td style="text-align:right;"> 206 </td>
   <td style="text-align:right;"> 37722 </td>
   <td style="text-align:right;"> 183.12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Defu BP </td>
   <td style="text-align:right;"> 200 </td>
   <td style="text-align:right;"> 52384 </td>
   <td style="text-align:right;"> 261.92 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Katong </td>
   <td style="text-align:right;"> 176 </td>
   <td style="text-align:right;"> 62859 </td>
   <td style="text-align:right;"> 357.15 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> International BP </td>
   <td style="text-align:right;"> 99 </td>
   <td style="text-align:right;"> 27750 </td>
   <td style="text-align:right;"> 280.30 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Seletar BP </td>
   <td style="text-align:right;"> 97 </td>
   <td style="text-align:right;"> 26008 </td>
   <td style="text-align:right;"> 268.12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Boat Quay </td>
   <td style="text-align:right;"> 62 </td>
   <td style="text-align:right;"> 15166 </td>
   <td style="text-align:right;"> 244.61 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Duxton Hill </td>
   <td style="text-align:right;"> 46 </td>
   <td style="text-align:right;"> 10766 </td>
   <td style="text-align:right;"> 234.04 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Jurong Innovation BP </td>
   <td style="text-align:right;"> 17 </td>
   <td style="text-align:right;"> 4868 </td>
   <td style="text-align:right;"> 286.35 </td>
  </tr>
</tbody>
</table>

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# User Mobility Index

Here we calculate,

(1) Sum of absolute change at individual builgings

(2) The absolute value of the sum of the change

(3) The difference between the two sums

The first sum (1) is
$$
S_1=|c_1|+|c_2|+\cdots+|c_n|,
$$
Here, `$c_i$` is the change in building `$i$` for `$i=1,\dots,n$`, where `$n$` is the number of buildings.

The second sum (2) is
$$
S_2=|c_1+c_2+\cdots+c_n|
$$

We call `$S_1-S_2$` the _User Mobility Index_.

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# Overlapping index

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# Hotspots

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node size = mean travel distance (raised to power `$0.4$`), 
node color = density of social interactions (signal count her ha (log)).