blob: f9465ae5d6f4632c588efa84017ed994bfa83390 [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.
#
#-------------------------------------------------------------
# Returns the means absolute error between the two inputs
#
# INPUT:
# --------------------------------------------------------------------------------
# X First Matrix to compare
# Y Second Matrix to compare
# P Quantiles to extract as well if empty matrix not calculated
# --------------------------------------------------------------------------------
#
# OUTPUT:
# -----------------------------------------------------------------------------------------------
# Z Mean absolute error
# Q Quantiles calculated
# -----------------------------------------------------------------------------------------------
m_mae = function(Matrix[Double] X, Matrix[Double] Y, Matrix[Double] P = matrix(0, rows=0, cols=0))
return (Matrix[Double] Z, Matrix[Double] Q) {
AE = abs(X - Y)
Z = as.matrix(mean(AE))
Q = flattenQuantile(AE, P)
}