create_data_normal_fixed: Generate (S/D) EC curves for a collection of interpolations...

In lcrawlab/SINATRA: Sub Image Analysis using Topological Summary Statistics (SINATRA)

Generate (S/D) EC curves for a collection of interpolations on the plane

Description

Given a set of input parameters, create_data_normal_fixed generates replicates of interpolations on the plane. These interpolations are then converted to simplicial complexes, and have the (S/D) EC curve computed over them.

Usage

create_data_normal_fixed(
  num_sim = 25,
  dir,
  curve_length = 10,
  shared_points = 5,
  causal_points = 5,
  grid_size = 25,
  func = rbf_gauss,
  eta = 5,
  ball = TRUE,
  ball_radius = 1,
  ec_type = "ECT"
)

Arguments

num_sim	(int) : The number of replicates of data.
dir	(matrix) : The matrix of directions we compute the EC curves over.
curve_length	(int) : Number of sub-level sets in each EC computation.
shared_points	(int) : The number of shared points across both classes of shapes.
causal_points	(int) : The number of class specific causal points in each class.
grid_size	(int) : The fine-ness/granularity of the interpolated shapes.
func	(function) : The function used to compute the interpolations.
eta	(float) : The kernel shape parameter.
ball	(boolean) : Denotes whether or not to compute the EC curves over a ball for uniform measurements
ball_radius	(float) : The radius of the bounding ball used if we compute the balled EC curve.
ec_type	(string) : The type of EC we are computing. We currently support ECT, DECT and SECT.

Value

data_list (list) : List of procedure specific data : The associated (S/D) EC matrix, coordinates of causal & shared points, and the vertex coordinates of all the shapes.

lcrawlab/SINATRA documentation built on Sept. 13, 2023, 2 p.m.