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Declarative Machine Learning
#-------------------------------------------------------------
#
# 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.
#
#-------------------------------------------------------------
# Utility script to project columns from input matrix.
#
# Parameters:
# X : (input) filename of data matrix
# P : (input) filename of 1-column projection matrix containing columnIDs
# o : (output) filename of output matrix with projected columns
# exclude : (default FALSE) TRUE means P contains columnIds to be projected
# FALSE means P contains columnsIDS to be excluded
# ofmt : (default binary) format of output matrix
#
# Example:
# hadoop jar SystemML.jar -f algorithms/utils/project.dml -nvargs X="/tmp/M.mtx" P="/tmp/P.mtx" o="/tmp/PX.mtx"
#
# Assumptions:
# The order of colIDs in P is preserved. Order of columns in result is same as order of columns in P.
# i.e. projecting columns 4 and 2 of X results in a matrix with columns 4 and 2.
# If P specifies the exclude list, then projected columns are order preserved.
exclude = ifdef ($exclude, FALSE);
ofmt = ifdef ($ofmt, "binary");
X = read ($X)
P = read ($P)
# create projection matrix using projection list and sequence matrix, and pad with 0s. The size of
# PP is nbrOfColsInX x nbrOfColsToKeep
if (exclude==FALSE)
{
# create projection matrix using projection list and sequence matrix, and pad with 0s. The size
# of PP is nbrOfColsInX x nbrOfColsToKeep
PP = table(P, seq(1, nrow(P), 1), ncol(X), nrow(P))
} else {
# create new vector P with list of columns to keep using original vector P containing exclude
# columns. These are all small vector operations.
C = table(P, seq(1, nrow(P), 1))
E = rowSums(C);
# Row pad w/ 0s
EE = matrix (0, rows=ncol(X), cols=1)
EE[1:nrow(E),1] = E
# Convert exclude column list to include column list, and create column indices
EE = (EE == 0)
EE = EE * seq(1, ncol(X), 1)
P = removeEmpty(target=EE, margin="rows")
PP = table(P, seq(1, nrow(P), 1), ncol(X), nrow(P))
}
# Perform projection using permutation matrix
PX = X %*% PP
# Write output
write (PX, $o, format=ofmt)