blob: 6df5c5a3a33a7ccc0d8bcffab31682776a040d25 [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.
#
#-------------------------------------------------------------
# Built-in LOGSUMEXP
#
# INPUT:
# --------------------------------------------------------------------------------------
# M matrix to perform Log sum exp on.
# margin if the logsumexp of rows is required set margin = "row"
# if the logsumexp of columns is required set margin = "col"
# if set to "none" then a single scalar is returned computing logsumexp of matrix
# --------------------------------------------------------------------------------------
#
# OUTPUT:
# ---------------------------------------------------------------------------------------
# output a 1*1 matrix, row vector or column vector depends on margin value
# ---------------------------------------------------------------------------------------
m_logSumExp = function(Matrix[Double] M, String margin = "none")
return(Matrix[Double] output)
{
if(margin == "rows") {
ds = M - rowMaxs(M)
rSumOfexp = rowSums(exp(ds))
output = rowMaxs(M) + log(rSumOfexp)
}
else if(margin == "cols") {
ds = M - colMaxs(M)
cSumOfexp = colSums(exp(ds))
output = colMaxs(M) + log(cSumOfexp)
}
else if(margin == "none") {
ds = M - max(M)
sumOfexp = sum(exp(ds))
output = as.matrix(max(M) + log(sumOfexp))
}
else
stop("invalid margin value expecting rows, cols or none found: "+margin)
}