R/RcppExports.R

In mattdneal/gaussianProcess: Gaussian Process Fitting and Prediction

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

getCovarianceMatrixCpp <- function(x, k, sigma_n, hyperParams) {
    .Call('_gaussianProcess_getCovarianceMatrixCpp', PACKAGE = 'gaussianProcess', x, k, sigma_n, hyperParams)
}

getCovarianceMatrixBuiltInCpp <- function(x, k, sigma_n, hyperParams, additionalParams) {
    .Call('_gaussianProcess_getCovarianceMatrixBuiltInCpp', PACKAGE = 'gaussianProcess', x, k, sigma_n, hyperParams, additionalParams)
}

getCovarianceMatrixGradArray <- function(x, k, sigma_n, hyperParams, additionalParams) {
    .Call('_gaussianProcess_getCovarianceMatrixGradArray', PACKAGE = 'gaussianProcess', x, k, sigma_n, hyperParams, additionalParams)
}

getCovarianceMatrixHessianArray <- function(x, k, sigma_n, hyperParams, additionalParams) {
    .Call('_gaussianProcess_getCovarianceMatrixHessianArray', PACKAGE = 'gaussianProcess', x, k, sigma_n, hyperParams, additionalParams)
}

#' Select Built-in C++ Kernels by Name
#'
#' Built in kernels include:
#' \itemize{
#'   \item squaredExponential
#'   \item rationalQuadratic
#'   \item periodic
#'   \item constant
#'   \item generalisedLinear
#'   \item oneDLinear
#'   \item changepoint
#'   \item randomForest
#'   \item neuralNetwork
#'   \item generalisedPolynomial
#'   \item polynomial
#'   \item homogeneousPolynomial
#' }
#'
#' @param kernelName the kernel's name (as a string)
#' @param a the first data point
#' @param b the second data point
#' @param hyperParams the kernel's hyperparameters as a named numeric vector
#' @param additionalParams a list of any additional parameters
#'
#' @export
callKernelByString <- function(kernelName, a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_callKernelByString', PACKAGE = 'gaussianProcess', kernelName, a, b, hyperParams, additionalParams)
}

callKernelGradByString <- function(kernelName, a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_callKernelGradByString', PACKAGE = 'gaussianProcess', kernelName, a, b, hyperParams, additionalParams)
}

callKernelHessByString <- function(kernelName, a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_callKernelHessByString', PACKAGE = 'gaussianProcess', kernelName, a, b, hyperParams, additionalParams)
}

getKernelHyperparamNames <- function(kernelName, additionalParams) {
    .Call('_gaussianProcess_getKernelHyperparamNames', PACKAGE = 'gaussianProcess', kernelName, additionalParams)
}

squaredExponentialKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_squaredExponentialKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

squaredExponentialKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_squaredExponentialKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

squaredExponentialKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_squaredExponentialKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

ARDKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_ARDKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

ARDKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_ARDKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

ARDKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_ARDKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

inverseARDKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_inverseARDKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

inverseARDKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_inverseARDKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

inverseARDKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_inverseARDKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

shiftedLog <- function(x) {
    .Call('_gaussianProcess_shiftedLog', PACKAGE = 'gaussianProcess', x)
}

stablePow <- function(x, a) {
    .Call('_gaussianProcess_stablePow', PACKAGE = 'gaussianProcess', x, a)
}

rationalQuadraticKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_rationalQuadraticKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

rationalQuadraticKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_rationalQuadraticKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

rationalQuadraticKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_rationalQuadraticKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

periodicKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_periodicKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

periodicKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_periodicKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

periodicKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_periodicKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

constantKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_constantKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

constantKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_constantKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

constantKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_constantKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

generalisedPolynomialKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_generalisedPolynomialKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

generalisedPolynomialKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_generalisedPolynomialKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

generalisedPolynomialKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_generalisedPolynomialKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

polynomialKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_polynomialKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

polynomialKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_polynomialKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

polynomialKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_polynomialKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

homogeneousPolynomialKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_homogeneousPolynomialKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

homogeneousPolynomialKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_homogeneousPolynomialKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

homogeneousPolynomialKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_homogeneousPolynomialKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

randomForestKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_randomForestKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

randomForestKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_randomForestKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

randomForestKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_randomForestKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

neuralNetworkKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_neuralNetworkKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

neuralNetworkKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_neuralNetworkKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

neuralNetworkKernelHess <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_neuralNetworkKernelHess', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

generalNeuralNetworkKernel <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_generalNeuralNetworkKernel', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

generalNeuralNetworkKernelGrad <- function(a, b, hyperParams, additionalParams) {
    .Call('_gaussianProcess_generalNeuralNetworkKernelGrad', PACKAGE = 'gaussianProcess', a, b, hyperParams, additionalParams)
}

getTreeHeight <- function(tree) {
    .Call('_gaussianProcess_getTreeHeight', PACKAGE = 'gaussianProcess', tree)
}

navigateRFTree <- function(tree, data, isFactor, inputHeight) {
    .Call('_gaussianProcess_navigateRFTree', PACKAGE = 'gaussianProcess', tree, data, isFactor, inputHeight)
}

kahanSum <- function(summands) {
    .Call('_gaussianProcess_kahanSum', PACKAGE = 'gaussianProcess', summands)
}

sumSQuaredDiffs <- function(a, b) {
    .Call('_gaussianProcess_sumSQuaredDiffs', PACKAGE = 'gaussianProcess', a, b)
}

sumSQuaredDiffsPartial <- function(a, b, additionalParams) {
    .Call('_gaussianProcess_sumSQuaredDiffsPartial', PACKAGE = 'gaussianProcess', a, b, additionalParams)
}

bitWiseAnd <- function(a, b) {
    .Call('_gaussianProcess_bitWiseAnd', PACKAGE = 'gaussianProcess', a, b)
}