125 lines
3.8 KiB
R
125 lines
3.8 KiB
R
# Generated by using Rcpp::compileAttributes() -> do not edit by hand
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# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
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#' Human Crafted Evaluation
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HCE <- function(positions) {
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.Call(`_Rchess_HCE`, positions)
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}
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#' Given a FEN (position) determines if its whites turn
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isWhiteTurn <- function(positions) {
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.Call(`_Rchess_isWhiteTurn`, positions)
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}
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#' Check if current side to move is in check
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isCheck <- function(positions) {
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.Call(`_Rchess_isCheck`, positions)
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}
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#' Check if the current position is a quiet position (no piece is attacked)
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isQuiet <- function(positions) {
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.Call(`_Rchess_isQuiet`, positions)
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}
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#' Check if position is terminal
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#'
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#' Checks if the position is a terminal position, meaning if the game ended
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#' by mate, stale mate or the 50 modes rule. Three-Fold repetition is NOT
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#' checked, therefore a seperate game history is required which the board
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#' does NOT track.
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#'
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isTerminal <- function(positions) {
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.Call(`_Rchess_isTerminal`, positions)
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}
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#' Check if checkmate is possible by material on the board
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#'
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#' Checks if there is sufficient mating material on the board, meaning if it
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#' possible for any side to deliver a check mate. More specifically, it
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#' checks if the pieces on the board are KK, KNK or KBK.
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#'
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isInsufficient <- function(positions) {
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.Call(`_Rchess_isInsufficient`, positions)
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}
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#' Specialized version of `read_cyclic.cpp` taylored to work in conjunction with
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#' `gmlm_chess()` as data generator to provide random draws from a FEN data set
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#' with scores filtered to be in in the range `score_min` to `score_max`.
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#'
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data.gen <- function(file, sample_size, score_min = -5.0, score_max = +5.0, quiet = FALSE, min_ply_count = 10L, white_only = TRUE) {
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.Call(`_Rchess_data_gen`, file, sample_size, score_min, score_max, quiet, min_ply_count, white_only)
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}
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#' Human Crafted Evaluation
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eval.psqt <- function(positions, psqt, pawn_structure = FALSE, eval_rooks = FALSE, eval_king = FALSE) {
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.Call(`_Rchess_eval_psqt`, positions, psqt, pawn_structure, eval_rooks, eval_king)
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}
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#' Convert a legal FEN string to a 3D binary (integer with 0-1 entries) array
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fen2int <- function(boards) {
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.Call(`_Rchess_fen2int`, boards)
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}
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#' Reads lines from a text file with recycling.
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#'
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read.cyclic <- function(file, nrows = 1000L, skip = 100L, start = 1L, line_len = 64L) {
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.Call(`_Rchess_read_cyclic`, file, nrows, skip, start, line_len)
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}
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#' Samples a legal move from a given position
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sample.move <- function(pos) {
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.Call(`_Rchess_sample_move`, pos)
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}
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#' Samples a random FEN (position) by applying `ply` random moves to the start
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#' position.
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#'
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#' @param nr number of positions to sample
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#' @param min_depth minimum number of random ply's to generate random positions
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#' @param max_depth maximum number of random ply's to generate random positions
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sample.fen <- function(nr, min_depth = 4L, max_depth = 20L) {
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.Call(`_Rchess_sample_fen`, nr, min_depth, max_depth)
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}
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#' Converts a FEN string to a Board (position) or return the current internal state
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board <- function(fen = "") {
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.Call(`_Rchess_board`, fen)
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}
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print.board <- function(fen = "") {
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invisible(.Call(`_Rchess_print_board`, fen))
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}
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print.moves <- function(fen = "") {
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invisible(.Call(`_Rchess_print_moves`, fen))
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}
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print.bitboards <- function(fen = "") {
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invisible(.Call(`_Rchess_print_bitboards`, fen))
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}
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position <- function(pos, moves, san = FALSE) {
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.Call(`_Rchess_position`, pos, moves, san)
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}
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perft <- function(depth = 6L) {
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invisible(.Call(`_Rchess_perft`, depth))
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}
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go <- function(depth = 6L) {
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.Call(`_Rchess_go`, depth)
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}
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ucinewgame <- function() {
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invisible(.Call(`_Rchess_ucinewgame`))
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}
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.onLoad <- function(libname, pkgname) {
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invisible(.Call(`_Rchess_onLoad`, libname, pkgname))
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}
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.onUnload <- function(libpath) {
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invisible(.Call(`_Rchess_onUnload`, libpath))
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}
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