R/RcppExports.R

Defines functions row_var_dgcmatrix row_mean_dgcmatrix row_sum_dgcmatrix SNN_SmallestNonzero_Dist DirectSNNToFile WriteEdgeFile ComputeSNN ScoreHelper IntegrateDataC FindWeightsC fast_dist GraphToNeighborHelper ReplaceColsC SparseRowVar RowVar FastLogVMR SparseRowVarStd SparseRowVar2 FastExpMean FastRBind FastCovMats FastCov FastSparseRowScaleWithKnownStats FastSparseRowScale Standardize LogNorm RowMergeMatrices RunUMISamplingPerCell RunUMISampling RunModularityClusteringCpp

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

RunModularityClusteringCpp <- function(SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename) {
    .Call('_Seurat_RunModularityClusteringCpp', PACKAGE = 'Seurat', SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename)
}

RunUMISampling <- function(data, sample_val, upsample = FALSE, display_progress = TRUE) {
    .Call('_Seurat_RunUMISampling', PACKAGE = 'Seurat', data, sample_val, upsample, display_progress)
}

RunUMISamplingPerCell <- function(data, sample_val, upsample = FALSE, display_progress = TRUE) {
    .Call('_Seurat_RunUMISamplingPerCell', PACKAGE = 'Seurat', data, sample_val, upsample, display_progress)
}

RowMergeMatrices <- function(mat1, mat2, mat1_rownames, mat2_rownames, all_rownames) {
    .Call('_Seurat_RowMergeMatrices', PACKAGE = 'Seurat', mat1, mat2, mat1_rownames, mat2_rownames, all_rownames)
}

LogNorm <- function(data, scale_factor, display_progress = TRUE) {
    .Call('_Seurat_LogNorm', PACKAGE = 'Seurat', data, scale_factor, display_progress)
}

Standardize <- function(mat, display_progress = TRUE) {
    .Call('_Seurat_Standardize', PACKAGE = 'Seurat', mat, display_progress)
}

FastSparseRowScale <- function(mat, scale = TRUE, center = TRUE, scale_max = 10, display_progress = TRUE) {
    .Call('_Seurat_FastSparseRowScale', PACKAGE = 'Seurat', mat, scale, center, scale_max, display_progress)
}

FastSparseRowScaleWithKnownStats <- function(mat, mu, sigma, scale = TRUE, center = TRUE, scale_max = 10, display_progress = TRUE) {
    .Call('_Seurat_FastSparseRowScaleWithKnownStats', PACKAGE = 'Seurat', mat, mu, sigma, scale, center, scale_max, display_progress)
}

FastCov <- function(mat, center = TRUE) {
    .Call('_Seurat_FastCov', PACKAGE = 'Seurat', mat, center)
}

FastCovMats <- function(mat1, mat2, center = TRUE) {
    .Call('_Seurat_FastCovMats', PACKAGE = 'Seurat', mat1, mat2, center)
}

FastRBind <- function(mat1, mat2) {
    .Call('_Seurat_FastRBind', PACKAGE = 'Seurat', mat1, mat2)
}

FastExpMean <- function(mat, display_progress) {
    .Call('_Seurat_FastExpMean', PACKAGE = 'Seurat', mat, display_progress)
}

SparseRowVar2 <- function(mat, mu, display_progress) {
    .Call('_Seurat_SparseRowVar2', PACKAGE = 'Seurat', mat, mu, display_progress)
}

SparseRowVarStd <- function(mat, mu, sd, vmax, display_progress) {
    .Call('_Seurat_SparseRowVarStd', PACKAGE = 'Seurat', mat, mu, sd, vmax, display_progress)
}

FastLogVMR <- function(mat, display_progress) {
    .Call('_Seurat_FastLogVMR', PACKAGE = 'Seurat', mat, display_progress)
}

RowVar <- function(x) {
    .Call('_Seurat_RowVar', PACKAGE = 'Seurat', x)
}

SparseRowVar <- function(mat, display_progress) {
    .Call('_Seurat_SparseRowVar', PACKAGE = 'Seurat', mat, display_progress)
}

ReplaceColsC <- function(mat, col_idx, replacement) {
    .Call('_Seurat_ReplaceColsC', PACKAGE = 'Seurat', mat, col_idx, replacement)
}

GraphToNeighborHelper <- function(mat) {
    .Call('_Seurat_GraphToNeighborHelper', PACKAGE = 'Seurat', mat)
}

fast_dist <- function(x, y, n) {
    .Call('_Seurat_fast_dist', PACKAGE = 'Seurat', x, y, n)
}

FindWeightsC <- function(cells2, distances, anchor_cells2, integration_matrix_rownames, cell_index, anchor_score, min_dist, sd, display_progress) {
    .Call('_Seurat_FindWeightsC', PACKAGE = 'Seurat', cells2, distances, anchor_cells2, integration_matrix_rownames, cell_index, anchor_score, min_dist, sd, display_progress)
}

IntegrateDataC <- function(integration_matrix, weights, expression_cells2) {
    .Call('_Seurat_IntegrateDataC', PACKAGE = 'Seurat', integration_matrix, weights, expression_cells2)
}

ScoreHelper <- function(snn, query_pca, query_dists, corrected_nns, k_snn, subtract_first_nn, display_progress) {
    .Call('_Seurat_ScoreHelper', PACKAGE = 'Seurat', snn, query_pca, query_dists, corrected_nns, k_snn, subtract_first_nn, display_progress)
}

ComputeSNN <- function(nn_ranked, prune) {
    .Call('_Seurat_ComputeSNN', PACKAGE = 'Seurat', nn_ranked, prune)
}

WriteEdgeFile <- function(snn, filename, display_progress) {
    invisible(.Call('_Seurat_WriteEdgeFile', PACKAGE = 'Seurat', snn, filename, display_progress))
}

DirectSNNToFile <- function(nn_ranked, prune, display_progress, filename) {
    .Call('_Seurat_DirectSNNToFile', PACKAGE = 'Seurat', nn_ranked, prune, display_progress, filename)
}

SNN_SmallestNonzero_Dist <- function(snn, mat, n, nearest_dist) {
    .Call('_Seurat_SNN_SmallestNonzero_Dist', PACKAGE = 'Seurat', snn, mat, n, nearest_dist)
}

row_sum_dgcmatrix <- function(x, i, rows, cols) {
    .Call('_Seurat_row_sum_dgcmatrix', PACKAGE = 'Seurat', x, i, rows, cols)
}

row_mean_dgcmatrix <- function(x, i, rows, cols) {
    .Call('_Seurat_row_mean_dgcmatrix', PACKAGE = 'Seurat', x, i, rows, cols)
}

row_var_dgcmatrix <- function(x, i, rows, cols) {
    .Call('_Seurat_row_var_dgcmatrix', PACKAGE = 'Seurat', x, i, rows, cols)
}
satijalab/seurat documentation built on May 11, 2024, 4:04 a.m.