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feature: add distmatrix argument for clustering functions (#32)
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@lixun910
lixun910 authored Apr 5, 2022
1 parent 4f97d13 commit 0b50ded
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3 changes: 3 additions & 0 deletions .Rbuildignore
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^src/libgeoda/README.md
^src/libgeoda/.git
^\.github$
^_pkgdown\.yml$
^docs$
^pkgdown$
1 change: 1 addition & 0 deletions .gitignore
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*.so
.DS_Store
.DS_Store
docs
4 changes: 2 additions & 2 deletions DESCRIPTION
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Package: rgeoda
Type: Package
Title: R Library for Spatial Data Analysis
Version: 0.0.8-6
Date: 2021-09-07
Version: 0.0.9
Date: 2022-04-04
Authors@R:
c(person(given = "Xun", family = "Li", email="lixun910@gmail.com", role=c("aut","cre")),
person(given = "Luc", family = "Anselin", email="anselin@uchicago.edu", role="aut"))
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36 changes: 18 additions & 18 deletions R/RcppExports.R
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# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

p_skater <- function(k, xp_w, data, n_vars, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads) {
.Call('_rgeoda_p_skater', PACKAGE = 'rgeoda', k, xp_w, data, n_vars, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads)
p_skater <- function(k, xp_w, data, n_vars, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads, rdist) {
.Call('_rgeoda_p_skater', PACKAGE = 'rgeoda', k, xp_w, data, n_vars, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads, rdist)
}

p_redcap <- function(k, xp_w, data, n_vars, redcap_method, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads) {
.Call('_rgeoda_p_redcap', PACKAGE = 'rgeoda', k, xp_w, data, n_vars, redcap_method, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads)
p_redcap <- function(k, xp_w, data, n_vars, redcap_method, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads, rdist) {
.Call('_rgeoda_p_redcap', PACKAGE = 'rgeoda', k, xp_w, data, n_vars, redcap_method, scale_method, distance_method, bound_vals, min_bound, seed, cpu_threads, rdist)
}

p_schc <- function(k, xp_w, data, n_vars, linkage_method, scale_method, distance_method, bound_vals, min_bound) {
.Call('_rgeoda_p_schc', PACKAGE = 'rgeoda', k, xp_w, data, n_vars, linkage_method, scale_method, distance_method, bound_vals, min_bound)
p_schc <- function(k, xp_w, data, n_vars, linkage_method, scale_method, distance_method, bound_vals, min_bound, rdist) {
.Call('_rgeoda_p_schc', PACKAGE = 'rgeoda', k, xp_w, data, n_vars, linkage_method, scale_method, distance_method, bound_vals, min_bound, rdist)
}

p_maxp_greedy <- function(xp_w, data, n_vars, bound_vals, min_bound, iterations, init_regions, scale_method, distance_method, seed, cpu_threads) {
.Call('_rgeoda_p_maxp_greedy', PACKAGE = 'rgeoda', xp_w, data, n_vars, bound_vals, min_bound, iterations, init_regions, scale_method, distance_method, seed, cpu_threads)
p_maxp_greedy <- function(xp_w, data, n_vars, bound_vals, min_bound, iterations, init_regions, scale_method, distance_method, seed, cpu_threads, rdist) {
.Call('_rgeoda_p_maxp_greedy', PACKAGE = 'rgeoda', xp_w, data, n_vars, bound_vals, min_bound, iterations, init_regions, scale_method, distance_method, seed, cpu_threads, rdist)
}

p_maxp_sa <- function(xp_w, data, n_vars, bound_vals, min_bound, iterations, cooling_rate, sa_maxit, init_regions, scale_method, distance_method, seed, cpu_threads) {
.Call('_rgeoda_p_maxp_sa', PACKAGE = 'rgeoda', xp_w, data, n_vars, bound_vals, min_bound, iterations, cooling_rate, sa_maxit, init_regions, scale_method, distance_method, seed, cpu_threads)
p_maxp_sa <- function(xp_w, data, n_vars, bound_vals, min_bound, iterations, cooling_rate, sa_maxit, init_regions, scale_method, distance_method, seed, cpu_threads, rdist) {
.Call('_rgeoda_p_maxp_sa', PACKAGE = 'rgeoda', xp_w, data, n_vars, bound_vals, min_bound, iterations, cooling_rate, sa_maxit, init_regions, scale_method, distance_method, seed, cpu_threads, rdist)
}

p_maxp_tabu <- function(xp_w, data, n_vars, bound_vals, min_bound, iterations, tabu_length, conv_tabu, init_regions, scale_method, distance_method, seed, cpu_threads) {
.Call('_rgeoda_p_maxp_tabu', PACKAGE = 'rgeoda', xp_w, data, n_vars, bound_vals, min_bound, iterations, tabu_length, conv_tabu, init_regions, scale_method, distance_method, seed, cpu_threads)
p_maxp_tabu <- function(xp_w, data, n_vars, bound_vals, min_bound, iterations, tabu_length, conv_tabu, init_regions, scale_method, distance_method, seed, cpu_threads, rdist) {
.Call('_rgeoda_p_maxp_tabu', PACKAGE = 'rgeoda', xp_w, data, n_vars, bound_vals, min_bound, iterations, tabu_length, conv_tabu, init_regions, scale_method, distance_method, seed, cpu_threads, rdist)
}

p_azp_greedy <- function(p, xp_w, data, n_vars, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed) {
.Call('_rgeoda_p_azp_greedy', PACKAGE = 'rgeoda', p, xp_w, data, n_vars, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed)
p_azp_greedy <- function(p, xp_w, data, n_vars, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed, rdist) {
.Call('_rgeoda_p_azp_greedy', PACKAGE = 'rgeoda', p, xp_w, data, n_vars, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed, rdist)
}

p_azp_sa <- function(p, xp_w, data, n_vars, cooling_rate, sa_maxit, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed) {
.Call('_rgeoda_p_azp_sa', PACKAGE = 'rgeoda', p, xp_w, data, n_vars, cooling_rate, sa_maxit, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed)
p_azp_sa <- function(p, xp_w, data, n_vars, cooling_rate, sa_maxit, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed, rdist) {
.Call('_rgeoda_p_azp_sa', PACKAGE = 'rgeoda', p, xp_w, data, n_vars, cooling_rate, sa_maxit, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed, rdist)
}

p_azp_tabu <- function(p, xp_w, data, n_vars, tabu_length, conv_tabu, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed) {
.Call('_rgeoda_p_azp_tabu', PACKAGE = 'rgeoda', p, xp_w, data, n_vars, tabu_length, conv_tabu, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed)
p_azp_tabu <- function(p, xp_w, data, n_vars, tabu_length, conv_tabu, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed, rdist) {
.Call('_rgeoda_p_azp_tabu', PACKAGE = 'rgeoda', p, xp_w, data, n_vars, tabu_length, conv_tabu, bound_vals, min_bound, inits, init_regions, scale_method, distance_method, seed, rdist)
}

p_spatialvalidation <- function(xp_geoda, clusters, xp_w) {
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