generate_averaged_ROC_with_coned_directions: Generates ROC curve averaged over multiple runs.

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

Generates ROC curve averaged over multiple runs.

Description

Generates ROC curve averaged over multiple runs. We specify in the function what shapes to simulate, paramters for the about the EC comptutation, as well as assessment scheme.

Usage

generate_averaged_ROC_with_coned_directions(
  runs = 5,
  nsim = 50,
  curve_length = 10,
  grid_size = 25,
  distance_to_causal_point = 0.1,
  causal_points = 10,
  shared_points = 3,
  num_cones = 5,
  eta = 0.1,
  truncated = FALSE,
  two_curves = FALSE,
  ball_radius = 2,
  ball = TRUE,
  type = "vertex",
  min_points = 2,
  directions_per_cone = 5,
  cap_radius = 0.15,
  radius = 0,
  mode = "sphere",
  num_cusps = 10,
  subdivision = 3,
  num_causal_region = 5,
  num_shared_region = 5,
  ec_type = "ECT",
  alpha = 0.5,
  reduce = max,
  write = FALSE
)

Arguments

runs	(int): Number of runs to average the curves over
curve_length	(int) : Number of sub-level sets in each EC computation.
grid_size	(int) : The fine-ness/granularity of the interpolated shapes.
distance_to_causal_point	(float) : For interpolated shapes, the distance from a vertex to the causal points to be considered a "causal vertex"
causal_points	(int) : The number of causal points in each causal cusp, or number of causal points used for interpolations.
shared_points	(int) : The number of shared points in the shared cusps, or the number of shared points in the interpolations.
num_cones	(int): The number of cones to compute the (S/D) EC curves for the generated shapes over.
eta	(float) : The kernel shape parameter.
truncated	(int) : The number of "cuts" to compute TPR/FPR for the ROC curve over. Used to speed up ROC computations.
two_curves	(boolean) : Whether or not to compute ROC curves using class specific causal points, or the set of all causal points. Setting two_curves = TRUE will provide two curves, for each class.
ball_radius	(float) : The radius of the bounding ball used if we compute the balled EC curve.
ball	(boolean) : Denotes whether or not to compute the EC curves over a ball for uniform measurements
type	(string) : The assessment scheme. We currently support 'vertex' (finding causal vertices), 'feature' (finding causal sub-level sets), 'cusp' (finding causal cusps for spheres).
min_points	(int) : Used when type = 'feature'. The mininum number of causal vertices for a sub-level set to be associated with to be considered a causal 'feature'.
directions_per_cone	(int): The number of directions we want generated within each cone.
cap_radius	(float): The radius of the cones we generate (determines the size of each cone).
radius	(int) : The number of sub-level sets "before" and "after" the selected sub-level sets we want to include (during reconstruction).
mode	(string) : The data generation scheme. We currently support 'sphere', 'gaussian_grid", or rbf interpolations (default).
subdivision	(int) : The fineness of the sphere meshes (if mode == 'sphere'). We currently use subdivision = 3.
num_causal_region	(int) : The number of causal cusps (for when mode == 'sphere').
num_shared_region	(int) : The number of shared cusps (for when mode == 'sphere').
ec_type	(string) : The type of EC we are computing. We currently support ECT, DECT and SECT.
num_sim	(int) : The number of replicates of data.

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