blob: 6ef3a5f7404b1897c496983258443449298a3c3d [file] [log] [blame]
#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
#-------------------------------------------------------------
# Read command line arguments
args <- commandArgs(TRUE)
# Set options for numeric precision
options(digits=22)
# Load required libraries
library("Matrix")
library("matrixStats")
# Read matrix X from Matrix Market format files
X = as.matrix(readMM(paste(args[1], "X.mtx", sep="")))
# Create a column vector of ones with the same number of rows as X
ones_vector = matrix(1, nrow(X), 1)
# Create a diagonal matrix from the ones_vector
diag_matrix = diag(as.vector(ones_vector))
# Compute the column-wise cumulative sum (matching DML behavior)
cumsum_matrix = apply(diag_matrix, 2, cumsum)
# Perform the element-wise multiplication of X with the cumsum_matrix
R = X * cumsum_matrix
# Write the result R
writeMM(as(R, "CsparseMatrix"), paste(args[2], "R", sep=""))