Preparing the data to instantiate¶
Sub-Directory Structure¶
The sub-directory structure followed for storing and processing of static data source used for instantiations is outlined as follows.
|- staticInst/
|- data/
|- base/ # Raw data for each city
|- bangalore/ # Data for Bangalore City
|- demographics.csv # demographic data about each ward
|- households.csv # number of households in each ward
|- ODMatrix.csv # origin-destination matrix for employed
|- city.geojson # geographic boundaries of wards
|- employment.csv # census data on employed people
|- cityProfile.json # age, household size and school size distributions
|- mumbai/ # Data for Mumbai City, with each of the 24 wards split into non-HD areas and HD-areas
|- demographics.csv # demographic data about each ward division (48 total)
|- households.json # number of households in each ward
|- ODMatrix.csv # origin-destination matrix for employed
|- city.geojson # geographic boundaries of wards (24 total)
|- employment.csv # census data on employed people
|- cityProfile.json # age, household size and school size distributions
|- presampled-points/ # presampled latitude-longitudes for 48 ward subdivisions
|- 0.csv # presampled points for ward index 0
...
|- 47.csv # presampled points for ward index 47
|- PresamplePoints.ipynb # python notebook for presampling points from wards subdivisions
|- slumClusters.geojson # geographic boundaries of slum clusters