mappeR will assume the output of the filter
is in the same order as the original data points.create_mapper_object function should
correctly handle non 1D lens functions.names(filtered_data) = row.names(data) or similar before
making a call to generate a mapper object. The Ball Mapper flavored
versions should still work fine.igraph dependency; see shinymappeR
for an example of how to use igraph with
mappeR.tightness to mean_dist_to_medoid and
bin to patch.weight to use Jaccard index.clusterer, which is a
function that can handle a list of distance matrices (one for each
bin/level set) and output clustering results for each one. The
hierarchical clustering included previously is now available as a
clusterer called hierarchical_clusterer because I am very
creative.clusterer should look like a list of calls to
cutree from the hclust package. Look to the
clusterer farm for more examples in the future.compute_tightness to no longer normalize by the
maximum distance from the medoid (easier to see behavior in a single
mapper graph, may add options in future)fastcluster)mapply simplificationsNA
inputs, etc)igraph
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