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Default habitat clustering function using adespatial::constr.hclust.

Source: R/constrained_hclust.R
constrained_hclust_mst.Rd

Take a dataframe of points containing additional_variable_cols values, create a minimum spanning tree using prepare_mst_edges() and then cluster points using point data and edges with constrained_hclust(). Any additional arguments for prepare_mst_edges() or constrained_hclust() (excluding distance_alpha) can be included.

Usage

constrained_hclust_mst(
  points,
  distance_alpha = 0.5,
  n_points = 204,
  x_col = "X_standard",
  y_col = "Y_standard",
  interpolation_threshold = 30000,
  ...
)

Arguments

points

data.frame. Contains values for X and Y coordinates, as well as additional_variable_cols.

distance_alpha

float numeric. Weighting applied to the additional variable distance values when creating the distance matrix for clustering. This argument is not included in ... for discoverability.

n_points

numeric. Desired number of points per cluster. Default = 204 ( which equates to site sizes of 62,500m^2 when using H3 cells of resolution 12).

x_col

character. Name of column holding X coordinate values. Default = "X_standard".

y_col

character. Name of column holding Y coordinates. Default = "Y_standard".

interpolation_threshold

numeric. Threshold from where to sample random points and interpolate clusters for remaining points. This value should be scaled with reef area for larger reefs. Default value is 30,000, setting a higher threshold may result in long computation times and high RAM usage.

...

additional arguments. Additional arguments can be used here and will be passed onto prepare_mst_edges() and constrained_hclust() functions. These arguments must be named. distance_alpha argument is not included in these additional arguments. For information on arguments available in these functions and default values when arguments are not used, see prepare_mst_edges() and constrained_hclust().

Value

data.frame of points with allocated site_ids based on cluster outputs from constrained_hclust() using prepare_mst_edges to create a minimum spanning tree for input. site_id values are a combination of the id_col value, habitat_col value and the cluster allocation.