Nicholas Tierney

Wow this is great! In particular, the point that: > 1. straight-line distances are quite a poor substitute for street network distances; and > 2. relationships between the two are...

OK that is rather neat! Am I correct in that we are looking for something like this to identify say x and y cols: * https://github.com/ATFutures/dodgr/blob/master/R/graph-functions-misc.R#L84 and * https://github.com/ATFutures/dodgr/blob/master/R/graph-functions.R#L43

Just to be clear, the input would be this ```r max_coverage(existing_facility = wifi, proposed_facility = property, user = stops, distance_cutoff = 92, n_added = c(100, 200, 300)) ```

Have a look at the [tidy tools manifesto](https://cran.r-project.org/web/packages/tidyverse/vignettes/manifesto.html) for inspiration about this. Also make sure to re-read these sections on writing R functions: - http://adv-r.had.co.nz/Functions.html - http://r4ds.had.co.nz/program-intro.html (all of the...

Yes! This is something that I've been meaning to get back to @richardbeare about, I would love to collaborate to work on this article - do we have a specific...

Add a print method for this that shows what the results are doing. Specifically, state something like "Coverage df1 on df2 ", that clearly explains what the method did.

I also repeat the same sort of code here: ```r proposed_facility_cpp % dplyr::select(lat, long) %>% as.matrix() user_cpp % dplyr::select(lat, long) %>% as.matrix() A

I have written a wrapper function for `max_coverage` that handles creating the appropriate matrix and finding users not covered: ```r user_not_covered

This should form a vignette in version 0.2.0, that might also describe how to use others solvers

Paper on the significance of the maximal covering location problem http://journals.sagepub.com/doi/pdf/10.1177/0160017615600222 From #44