---
# System prepended metadata

title: Meeting Note 11/13
tags: [meeting note]

---

# Meeting Note 11/13
###### tags: `meeting note`

[TOC]

## TODO list
- github
    - public or private
    - 目錄架構
        - python專案
- initialize module
    - worker flow detail?
    -
- simulation
    - 不能建邊啊，2300萬個點再建要爆炸了
        - 不能建，也不用建
        - networkX
    - 需要$O(1)$
        - node to group list
            - `group_list(u)`
        - iterate elements in a given group list
            - `group_members(g)`
        - $p_{max,u}$ of a contact group $g$
            - $u$ is a age group
            - $p_{max,u}=\max\{p_{u,v}\mid v\in (S\cup F)\cap g\}$ 
        - $N$ of a contact group
            - $|(S\cup F)\cap g|$
    - 機率的
        - 所以可能要repeat幾次取平均?
    - 不同community的contact probability不一樣

## 內容
- raw
- worker flow format
    - $A$ to $B$ 工作人數的list (matrix)
        - $A,B$是鄉鎮市區
- data processing
    - use worker flow data(from [US](https://www.census.gov/data/tables/2015/demo/metro-micro/commuting-flows-2015.html)) to build **probability of commuting from A to B daily** where A and B are census tract.
    - convert all necessary data to JSON or CSV format
    
- contact group 
    - period
        - day only
        - night only
        - both
    - age dependent
        - 0-5
        - elementary school
        - ...
        - 19-64
        - 64-
    - if $u$ and $v$ are 屬於多個共同community
        - 就會判定多次
        - 加乘效果，合理
- day night不同
    - dynamic community(X
        - 兩個static community
        - 但幾乎一樣，只差在某些worker加入或離開

- data format
    - 規定 input data
        - Geographics
            - census_tract.csv
        - Demographics
            - age_population.csv
        - Worker Flow
            - ratio_commute_worker.csv
            - worker_flow.csv
        - Contact Matrix
            - contact_prob.csv
        - COVID-19 configuration
            - R0.csv [(Next-generation Matrix)](https://eehh-stanford.github.io/gceid/sens.html)
            - age_dependent_mortality.csv
            - latent_period.csv
            - Infectious period.csv
            - natural immunity
            - initial_adopter.csv ($\{\{地區_0, 人數_0\}, \{地區_1, 人數_1\}, ... \}$)
        - input data to init_module.data
            - graph.txt
        - init_module to simulation_module

## graph.txt 格式細節

- first line
    - number of node $n$
    - number of group class $m$
    - number of age group $a$
- second line 
    - each group class $0\leq i<m$, the number of that group class $m_i$
- followed by $m$ blocks
    - each block contains $a$ line, $a$ doubles each line
        - $c_{i,j,m_i}$ indecates contact probability of contact group $m_i$ from age group $i$ to age group $j$
- the following $n$ line, for line $i$
    - indicate information of node $i$
    - first the age group it belongs
    - then the number of day group 
        - and followed by group class $m_i$ and group id $0\leq idx_{m_i}<m_i$
    - then the number of night group 
        - and followed by group class $m_i$ and group id $0\leq idx_{m_i}<m_i$

```
2 3 2
1 2 3
0.6 0.4
0.2 0.3
0.5 0.2
0.2 0.4
0.9 0.4
0.4 0.2
0 1 0 0 2 0 0 2 1
1 2 0 0 1 0 0
```

## 禮拜三前須完成事項
- 郭庭佑
    - ML
    - data format from init_module to simulation_module
    - SI module
        - naive?
        - Sieve?
- 廖廷恩
    - Data processing
- 沈家駿
- 廖晊程
    - define data format to load in init_module
    - process data in init_module and output graph.txt