rgeoda: R Library for Spatial Data Analysis

# 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, 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, 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, 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, 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, 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, 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, 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, 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, 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) {
    .Call('_rgeoda_p_spatialvalidation', PACKAGE = 'rgeoda', xp_geoda, clusters, xp_w)
}

p_joincount_ratio <- function(clusters, xp_w) {
    .Call('_rgeoda_p_joincount_ratio', PACKAGE = 'rgeoda', clusters, xp_w)
}

p_make_spatial <- function(clusters, xp_w) {
    .Call('_rgeoda_p_make_spatial', PACKAGE = 'rgeoda', clusters, xp_w)
}

p_LISA__Run <- function(xp) {
    invisible(.Call('_rgeoda_p_LISA__Run', PACKAGE = 'rgeoda', xp))
}

p_LISA__SetNumPermutations <- function(xp, num_perm) {
    invisible(.Call('_rgeoda_p_LISA__SetNumPermutations', PACKAGE = 'rgeoda', xp, num_perm))
}

p_LISA__SetNumThreads <- function(xp, num_threads) {
    invisible(.Call('_rgeoda_p_LISA__SetNumThreads', PACKAGE = 'rgeoda', xp, num_threads))
}

p_LISA__GetLISAValues <- function(xp) {
    .Call('_rgeoda_p_LISA__GetLISAValues', PACKAGE = 'rgeoda', xp)
}

p_LISA__GetLocalSignificanceValues <- function(xp) {
    .Call('_rgeoda_p_LISA__GetLocalSignificanceValues', PACKAGE = 'rgeoda', xp)
}

p_LISA__GetClusterIndicators <- function(xp) {
    .Call('_rgeoda_p_LISA__GetClusterIndicators', PACKAGE = 'rgeoda', xp)
}

p_LISA__GetNumNeighbors <- function(xp) {
    .Call('_rgeoda_p_LISA__GetNumNeighbors', PACKAGE = 'rgeoda', xp)
}

p_LISA__SetSignificanceCutoff <- function(xp, cutoff) {
    invisible(.Call('_rgeoda_p_LISA__SetSignificanceCutoff', PACKAGE = 'rgeoda', xp, cutoff))
}

p_LISA__GetLabels <- function(xp) {
    .Call('_rgeoda_p_LISA__GetLabels', PACKAGE = 'rgeoda', xp)
}

p_LISA__GetColors <- function(xp) {
    .Call('_rgeoda_p_LISA__GetColors', PACKAGE = 'rgeoda', xp)
}

p_LISA__GetBO <- function(xp, pval) {
    .Call('_rgeoda_p_LISA__GetBO', PACKAGE = 'rgeoda', xp, pval)
}

p_LISA__GetFDR <- function(xp, pval) {
    .Call('_rgeoda_p_LISA__GetFDR', PACKAGE = 'rgeoda', xp, pval)
}

p_localmoran <- function(xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localmoran', PACKAGE = 'rgeoda', xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_bi_localmoran <- function(xp_w, data1, data2, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_bi_localmoran', PACKAGE = 'rgeoda', xp_w, data1, data2, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_eb_rate <- function(event_data, base_data) {
    .Call('_rgeoda_p_eb_rate', PACKAGE = 'rgeoda', event_data, base_data)
}

p_localmoran_eb <- function(xp_w, event_data, base_data, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localmoran_eb', PACKAGE = 'rgeoda', xp_w, event_data, base_data, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_localgeary <- function(xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localgeary', PACKAGE = 'rgeoda', xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_localmultigeary <- function(xp_w, data, n_vars, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localmultigeary', PACKAGE = 'rgeoda', xp_w, data, n_vars, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_localg <- function(xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localg', PACKAGE = 'rgeoda', xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_localgstar <- function(xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localgstar', PACKAGE = 'rgeoda', xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_localjoincount <- function(xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localjoincount', PACKAGE = 'rgeoda', xp_w, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_localmultijoincount <- function(xp_w, data, n_vars, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_localmultijoincount', PACKAGE = 'rgeoda', xp_w, data, n_vars, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_quantilelisa <- function(xp_w, k, quantile, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_quantilelisa', PACKAGE = 'rgeoda', xp_w, k, quantile, data, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_multiquantilelisa <- function(xp_w, k_s, q_s, data_s, permutations, permutation_method, significance_cutoff, cpu_threads, seed) {
    .Call('_rgeoda_p_multiquantilelisa', PACKAGE = 'rgeoda', xp_w, k_s, q_s, data_s, permutations, permutation_method, significance_cutoff, cpu_threads, seed)
}

p_neighbor_match_test <- function(xp_geoda, k, power, is_inverse, is_arc, is_mile, data_s, n_vars, scale_method, dist_type) {
    .Call('_rgeoda_p_neighbor_match_test', PACKAGE = 'rgeoda', xp_geoda, k, power, is_inverse, is_arc, is_mile, data_s, n_vars, scale_method, dist_type)
}

p_GeoDa__new <- function(file_path) {
    .Call('_rgeoda_p_GeoDa__new', PACKAGE = 'rgeoda', file_path)
}

p_GeoDa__new1 <- function(xp, layer_name, map_type, num_features, wkbs, wkb_bytes_len) {
    .Call('_rgeoda_p_GeoDa__new1', PACKAGE = 'rgeoda', xp, layer_name, map_type, num_features, wkbs, wkb_bytes_len)
}

p_GeoDa__GetNumObs <- function(xp) {
    .Call('_rgeoda_p_GeoDa__GetNumObs', PACKAGE = 'rgeoda', xp)
}

p_GeoDa__GetNumCols <- function(xp) {
    .Call('_rgeoda_p_GeoDa__GetNumCols', PACKAGE = 'rgeoda', xp)
}

p_GeoDa__GetMapType <- function(xp) {
    .Call('_rgeoda_p_GeoDa__GetMapType', PACKAGE = 'rgeoda', xp)
}

p_GeoDa__GetFieldNames <- function(xp) {
    .Call('_rgeoda_p_GeoDa__GetFieldNames', PACKAGE = 'rgeoda', xp)
}

p_GeoDa__GetFieldTypes <- function(xp) {
    .Call('_rgeoda_p_GeoDa__GetFieldTypes', PACKAGE = 'rgeoda', xp)
}

p_GeoDa__GetNumericCol <- function(xp, col_name) {
    .Call('_rgeoda_p_GeoDa__GetNumericCol', PACKAGE = 'rgeoda', xp, col_name)
}

p_GeoDa__GetIntegerCol <- function(xp, col_name) {
    .Call('_rgeoda_p_GeoDa__GetIntegerCol', PACKAGE = 'rgeoda', xp, col_name)
}

p_GeoDa__GetStringCol <- function(xp, col_name) {
    .Call('_rgeoda_p_GeoDa__GetStringCol', PACKAGE = 'rgeoda', xp, col_name)
}

p_GeoDa__GetNullValues <- function(xp, col_name) {
    .Call('_rgeoda_p_GeoDa__GetNullValues', PACKAGE = 'rgeoda', xp, col_name)
}

p_GeoDa__GetPointer <- function(xp) {
    .Call('_rgeoda_p_GeoDa__GetPointer', PACKAGE = 'rgeoda', xp)
}

p_GeoDaTable__new <- function() {
    .Call('_rgeoda_p_GeoDaTable__new', PACKAGE = 'rgeoda')
}

p_GeoDaTable__AddIntColumn <- function(xp, col_name, vals) {
    invisible(.Call('_rgeoda_p_GeoDaTable__AddIntColumn', PACKAGE = 'rgeoda', xp, col_name, vals))
}

p_GeoDaTable__AddStringColumn <- function(xp, col_name, vals) {
    invisible(.Call('_rgeoda_p_GeoDaTable__AddStringColumn', PACKAGE = 'rgeoda', xp, col_name, vals))
}

p_GeoDaTable__AddRealColumn <- function(xp, col_name, vals) {
    invisible(.Call('_rgeoda_p_GeoDaTable__AddRealColumn', PACKAGE = 'rgeoda', xp, col_name, vals))
}

p_GeoDaTable__GetPointer <- function(xp) {
    .Call('_rgeoda_p_GeoDaTable__GetPointer', PACKAGE = 'rgeoda', xp)
}

p_gda_isbinary <- function(values) {
    .Call('_rgeoda_p_gda_isbinary', PACKAGE = 'rgeoda', values)
}

p_naturalbreaks <- function(k, data) {
    .Call('_rgeoda_p_naturalbreaks', PACKAGE = 'rgeoda', k, data)
}

p_quantilebreaks <- function(k, data) {
    .Call('_rgeoda_p_quantilebreaks', PACKAGE = 'rgeoda', k, data)
}

p_hinge15breaks <- function(data) {
    .Call('_rgeoda_p_hinge15breaks', PACKAGE = 'rgeoda', data)
}

p_hinge30breaks <- function(data) {
    .Call('_rgeoda_p_hinge30breaks', PACKAGE = 'rgeoda', data)
}

p_percentilebreaks <- function(data) {
    .Call('_rgeoda_p_percentilebreaks', PACKAGE = 'rgeoda', data)
}

p_stddevbreaks <- function(data) {
    .Call('_rgeoda_p_stddevbreaks', PACKAGE = 'rgeoda', data)
}

p_GeoDaWeight__new <- function(num_obs) {
    .Call('_rgeoda_p_GeoDaWeight__new', PACKAGE = 'rgeoda', num_obs)
}

p_GeoDaWeight__GetPointer <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__GetPointer', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__SetNeighbors <- function(xp, idx, v_nbr_ids) {
    invisible(.Call('_rgeoda_p_GeoDaWeight__SetNeighbors', PACKAGE = 'rgeoda', xp, idx, v_nbr_ids))
}

p_GeoDaWeight__SetNeighborsAndWeights <- function(xp, idx, v_nbr_ids, v_nbr_w) {
    invisible(.Call('_rgeoda_p_GeoDaWeight__SetNeighborsAndWeights', PACKAGE = 'rgeoda', xp, idx, v_nbr_ids, v_nbr_w))
}

p_GeoDaWeight__GetNbrStats <- function(xp) {
    invisible(.Call('_rgeoda_p_GeoDaWeight__GetNbrStats', PACKAGE = 'rgeoda', xp))
}

p_GeoDaWeight__GetNumObs <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__GetNumObs', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__IsSymmetric <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__IsSymmetric', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__HasIsolates <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__HasIsolates', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__GetSparsity <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__GetSparsity', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__GetMinNeighbors <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__GetMinNeighbors', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__GetMaxNeighbors <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__GetMaxNeighbors', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__GetMeanNeighbors <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__GetMeanNeighbors', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__GetMedianNeighbors <- function(xp) {
    .Call('_rgeoda_p_GeoDaWeight__GetMedianNeighbors', PACKAGE = 'rgeoda', xp)
}

p_GeoDaWeight__SpatialLag <- function(xp, vals) {
    .Call('_rgeoda_p_GeoDaWeight__SpatialLag', PACKAGE = 'rgeoda', xp, vals)
}

p_GeoDaWeight__GetNeighborSize <- function(xp, obs_idx) {
    .Call('_rgeoda_p_GeoDaWeight__GetNeighborSize', PACKAGE = 'rgeoda', xp, obs_idx)
}

p_GeoDaWeight__SaveToFile <- function(xp, out_path, layer_name, id_name, id_vec) {
    .Call('_rgeoda_p_GeoDaWeight__SaveToFile', PACKAGE = 'rgeoda', xp, out_path, layer_name, id_name, id_vec)
}

p_GeoDaWeight__GetNeighbors <- function(xp, obs_idx) {
    .Call('_rgeoda_p_GeoDaWeight__GetNeighbors', PACKAGE = 'rgeoda', xp, obs_idx)
}

p_GeoDaWeight__GetNeighborWeights <- function(xp, obs_idx) {
    .Call('_rgeoda_p_GeoDaWeight__GetNeighborWeights', PACKAGE = 'rgeoda', xp, obs_idx)
}

p_gda_min_distthreshold <- function(xp_geoda, is_arc, is_mile) {
    .Call('_rgeoda_p_gda_min_distthreshold', PACKAGE = 'rgeoda', xp_geoda, is_arc, is_mile)
}

p_gda_queen_weights <- function(xp_geoda, order, include_lower_order, precision_threshold) {
    .Call('_rgeoda_p_gda_queen_weights', PACKAGE = 'rgeoda', xp_geoda, order, include_lower_order, precision_threshold)
}

p_gda_rook_weights <- function(xp_geoda, order, include_lower_order, precision_threshold) {
    .Call('_rgeoda_p_gda_rook_weights', PACKAGE = 'rgeoda', xp_geoda, order, include_lower_order, precision_threshold)
}

p_gda_distance_weights <- function(xp_geoda, dist_thres, power, is_inverse, is_arc, is_mile) {
    .Call('_rgeoda_p_gda_distance_weights', PACKAGE = 'rgeoda', xp_geoda, dist_thres, power, is_inverse, is_arc, is_mile)
}

p_gda_kernel_weights <- function(xp_geoda, bandwidth, kernel_method, use_kernel_diagonals, power, is_inverse, is_arc, is_mile) {
    .Call('_rgeoda_p_gda_kernel_weights', PACKAGE = 'rgeoda', xp_geoda, bandwidth, kernel_method, use_kernel_diagonals, power, is_inverse, is_arc, is_mile)
}

p_gda_knn_weights <- function(xp_geoda, k, power, is_inverse, is_arc, is_mile) {
    .Call('_rgeoda_p_gda_knn_weights', PACKAGE = 'rgeoda', xp_geoda, k, power, is_inverse, is_arc, is_mile)
}

p_gda_kernel_knn_weights <- function(xp_geoda, k, power, is_inverse, is_arc, is_mile, kernel_method, bandwidth, adaptive_bandwidth, use_kernel_diagonals) {
    .Call('_rgeoda_p_gda_kernel_knn_weights', PACKAGE = 'rgeoda', xp_geoda, k, power, is_inverse, is_arc, is_mile, kernel_method, bandwidth, adaptive_bandwidth, use_kernel_diagonals)
}

p_gda_load_gal <- function(weights_path, v_id_vec) {
    .Call('_rgeoda_p_gda_load_gal', PACKAGE = 'rgeoda', weights_path, v_id_vec)
}

p_gda_load_gwt <- function(weights_path, v_id_vec) {
    .Call('_rgeoda_p_gda_load_gwt', PACKAGE = 'rgeoda', weights_path, v_id_vec)
}

p_gda_load_swm <- function(weights_path, v_id_vec) {
    .Call('_rgeoda_p_gda_load_swm', PACKAGE = 'rgeoda', weights_path, v_id_vec)
}