View source: R/baskin_robbins.R
create_clusterball_mapper_object | R Documentation |
Run Ball Mapper, but non-trivially cluster within the balls. You can use two different distance matrices to for the balling and clustering.
create_clusterball_mapper_object(
data,
dist1,
dist2,
eps,
clusterer = local_hierarchical_clusterer("single")
)
data |
A data frame. |
dist1 |
A distance matrix for the data frame; this will be used to ball the data. It can be a |
dist2 |
Another distance matrix for the data frame; this will be used to cluster the data after balling. It can be a |
eps |
A positive real number for the desired ball radius. |
clusterer |
A function which accepts a list of distance matrices as input, and returns the results of clustering done on each distance matrix; that is, it should return a list of named vectors, whose name are the names of data points and whose values are cluster assignments (integers). If this value is omitted, then single-linkage clustering will be done (and a cutting height will be decided for you). |
A list
of two data frames, nodes
and edges
, which contain information about the Mapper graph constructed from the given parameters.
The node data frame consists of:
id
: vertex ID
cluster_size
: number of data points in vertex
mean_dist_to_medoid
: mean distance to medoid of vertex
data
: names of data points in cluster
patch
: level set ID
The edge
data frame contains consists of:
source
: vertex ID of edge source
target
: vertex ID of edge target
weight
: Jaccard index of edge; this is the size of the intersection between the vertices divided by the union
overlap_data
: names of data points in overlap
overlap_size
: number of data points overlap
# Create noisy circle data set
data = data.frame(x = sapply(1:100, function(x) cos(x)), y = sapply(1:100, function(x) sin(x)))
data.dists = dist(data)
# Set ball radius
eps = 1
# Do single-linkage clustering in the balls to produce Mapper graph
create_clusterball_mapper_object(data, data.dists, data.dists, eps)
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