NEWS

maxcovr 0.1.3.9200

This release is created to assist in replicating previous journal articles that used this software. The API of maxcovr is likely to change from here.

max_coverage_relocation now works for different data, thanks to a bug fix.
prototype solver engines added. maxcovr now works with glpk, and gurobi, in addition to lpSolve. Testing still to be conducted.
summary function coverage added as a one liner to take two dataframes and from the coverage of one dataframe on another. Documentation and tests still need work
summary_mc_cv_relocate added for relocation methods. This will eventially be an S3 method, I think?
rewrote the extraction functions for results from max_coverage, replacing them with key functions. This will make things easier to debug and extend in the future. These functions start with extract_. There will likely be some updates to this in the future
started work on refactoring the max_coverage functions to work with vectors, this fule is called maxcovr-refactor-vectors. This provides some more efficient computation of preparation of matrices for optimisation, and will provide substantial speedups for larger N, and for when multiple n_added's are needed.
max_coverage now returns the entire solution from lpSolve, except for the constraints, because they are too large (can easily be over 1Gb)

summary.maxcovr and summary.maxcovr_relocation method now return information about the previous distances.
Improvements have been made to the overall returning API of max_coverage_relocation so that it plays better with extracting summary information.

Removed the scraggly test dataset that was lurking in the shadows and making my model not work.

new function, max_coverage_relocation, takes a arguments for total cost, installation cost, and relocation costs and then works out how many facilities it can place, and potentially remove and replace to obtain optimum coverage. The function is currently Under development. In the future it will be absorted into max_coverage.
added a results extraction method for max_coverage_relocation, extract_mc_result_relocation. Eventually this will be be absorbed into the extract_mc_result function, through some kind of S3 method.
added print and summary S3 method for max_coverage and max_coverage_relocation, and an is.maxcovr_relocation and is.maxcovr, which should be handy for testing.

Changed the specification of m_under_i and m_over_i to more clearly reflect "The gain of removing an AED from position i"
Removed the scraggly test dataset that was lurking in the shadows and making my model not work.

added a vignette that describes how to perform cross validation on the maxcovr problem using modelr and purrr
maxcovr now returns a tibble of lists. This makes it easier to perform other tasks, and more consistent and easier to work with.

Added a NEWS.md file to track changes to the package.
Added a helper function to assist with extracting the results from the model
This will eventually be broken up into smaller functions, so that you can be really specific about what function you want to run to get what result. Ideally, each function, except for the one that runs the model, should return one, or maybe two arguments.

added c++ functions to calculate the distance matrices and binary matrices
added wrapper function nearest to find the nearest lat/long points from one dataframe to another and then calculate the distance between the two. This is at least 10 times faster than the previous method using joins and dplyr.
changed API for max_coverage, it now takes 3 dataframes, but it does more of the behind the scenes work, at the cost of taking slightly longer as it calculates the A matrix. Speedups are definitely still available though, as the c++ functions are yet to be parallelised.
max_coverage now also calculates a summary, which can be retrieved as mc_model$summary.

fixed bug in spherical_distance to return metres. Before this is was assuming there were 100m in a kilometer!
added parameters to facility_user_distance - coverage_distance, which allows you to specify the coverage you are interested in, and nearest, where you specify nearest to be "facility" if you want the nearest facility to each user, "user" if you want the nearest user to each facility, and NULL if you just want the complete pairwise distances.

added summarise_coverage() function, which calculates coverage based upon a distance dataframe created from facility_user_dist().
added york_crime data containing crime locations around the city of york.

improved README to include examples of usage (again)
removed artifacts relating to previous work; maxcovr now works for other kinds of data

added draft cpp code for spherical_distance and distance_matrix
updated max_coverage to include the extract_mc_result inside the function, rather than needing a separate function call. This was to save space, as the A matrix and friends can be rather large, especially if you are running the coverage multiple times under different conditions.