Code for the paper "Evolution of residential segregation patterns in the Netherlands between 2015 and 2020"

This code is used for computing the results of the paper "Evolution of residential segregation patterns in the Netherlands between 2015 and 2020". <br>This code identifies and characterizes residential segregation patterns from demographic data. It is applied in a Dutch case study. It is written in python, using notebooks.<br>This source code should be stored in a folder named code. The folder code and the folder data (see https://doi.org/10.4121/78ca3d23-2846-499d-8448-d0a1812bc378) should be located in the same directory.<br>FORMAT*.mkd;*.ipynb;*.txt;*.csv<br>RECOMMENDED HARDWARE1. Processor: Intel® Core™ i5-10210U CPU2. RAM: 32GiB of RAM (DDR4)3. GPU: Intel® UHD Graphics GPU<br>RECOMMENDED OPERATING SYSTEMUbuntu 21.10, 64-bit<br>REQUIRED VERSION OF PYTHON3.9.7<br>REQUIRED LIBRARIES USEDsee requirements.txt<br>EXTRA FILEparameter.csv specifies some parameters used in the analysis.<br>SEQUENCE OF SCRIPTSThe scripts should be run in the following order:<br>1. demographics_preprocess.ipynb2. extract_city_boundary.ipynb3. extract_street_network.ipynb4. extract_zones_in_gemeente.ipynb5. shortest_path.ipynb6. adjacency_matrix.ipynb7. covariance_matrix.ipynb8. mean_var_city_Bernoulli.ipynb7. exposure.ipynb8. regionalization.ipynb9. indicators_city.ipynb10. data_analytics.ipynb

本代码用于复现论文《2015至2020年荷兰居民居住隔离格局的演变》（Evolution of residential segregation patterns in the Netherlands between 2015 and 2020）的计算结果。
本代码可从人口统计数据中识别并刻画居住隔离格局，并应用于荷兰的案例研究。本代码采用Python语言编写，依托Jupyter Notebook实现。
本源代码需存储于名为code的文件夹中。该code文件夹与data文件夹（详见https://doi.org/10.4121/78ca3d23-2846-499d-8448-d0a1812bc378）需位于同一目录下。
支持文件格式：*.mkd、*.ipynb、*.txt、*.csv
推荐硬件配置：
1. 处理器：Intel® Core™ i5-10210U中央处理器
2. 内存：32GiB DDR4内存
3. 图形处理器：Intel® UHD Graphics图形处理器
推荐操作系统：Ubuntu 21.10 64位版本
所需Python版本：3.9.7
所需依赖库：详见requirements.txt文件
额外文件：parameter.csv用于指定分析过程中使用的部分参数
脚本运行顺序：需按照以下次序运行脚本：
1. demographics_preprocess.ipynb
2. extract_city_boundary.ipynb
3. extract_street_network.ipynb
4. extract_zones_in_gemeente.ipynb
5. shortest_path.ipynb
6. adjacency_matrix.ipynb
7. covariance_matrix.ipynb
8. mean_var_city_Bernoulli.ipynb
9. exposure.ipynb
10. regionalization.ipynb
11. indicators_city.ipynb
12. data_analytics.ipynb