create_mapper_object function

Create a mapper object

Run the mapper algorithm on a data frame.

create_mapper_object(
  data,
  dists,
  filtered_data,
  cover_element_tests,
  clusterer = NULL
)

Arguments

• data: A data frame.
• dists: A distance matrix for the data frame.
• filtered_data: The result of a function applied to the data frame; there should be one filter value per observation in the original data frame.
• cover_element_tests: A list of membership test functions for a set of cover elements. In other words, each element of cover_element_tests is a function that returns TRUE or FALSE when given a filter value.
• clusterer: A function which accepts a list of distance matrices as input, and returns the results of clustering done on each distance matrix. Defaults to NULL, meaning no all data in each bin will be lumped into a single cluster.

Returns

A list of two dataframes, one with node data and one with edge data.

Examples

data = data.frame(x = sapply(1:100, function(x) cos(x)), y = sapply(1:100, function(x) sin(x)))
projx = data$x

num_bins = 10
percent_overlap = 25
xcover = create_width_balanced_cover(min(projx), max(projx), num_bins, percent_overlap)

check_in_interval <- function(endpoints) {
 return(function(x) (endpoints[1] - x <= 0) & (endpoints[2] - x >= 0))
}

# each of the "cover" elements will really be a function that checks if a data point lives in it
xcovercheck = apply(xcover, 1, check_in_interval)

# build the mapper object
xmapper = create_mapper_object(
  data = data,
  dists = dist(data),
  filtered_data = projx,
  cover_element_tests = xcovercheck
)