Summary of how it works:
— can be unstandardized or standardized (0-100)
-- requires choice of travel range
3 weights (optional):
—Distance: smaller score for more distant services
—Variety: higher score for more of different types of services
—Relative importance: e.g. hospitals could get more weight than small service provider
This should be done, in two different ways.
[ ] For the package: to just create a weighting of columns in the existing dataframe.
[ ] For the website: store a list of all of the access measures that have been calculated. Allow "advanced" users to sum them up, with weights.
Existing Python implementation for comparison:
https://github.com/GeoDaCenter/spatial_access/blob/master/spatial_access/Models.py
Explanation: https://github.com/GeoDaCenter/spatial_access/blob/master/docs/notebooks/notes.ipynb relevant section: Metrics -- Access Model
https://github.com/GeoDaCenter/spatial_access/blob/master/docs/notebooks/access_score.ipynb
Summary of how it works: — can be unstandardized or standardized (0-100) -- requires choice of travel range 3 weights (optional): —Distance: smaller score for more distant services —Variety: higher score for more of different types of services —Relative importance: e.g. hospitals could get more weight than small service provider
This should be done, in two different ways.