Shafaq-Siddiqi commented on a change in pull request #1306: URL: https://github.com/apache/systemds/pull/1306#discussion_r648261772
########## File path: scripts/builtin/residencyMatchMain.dml ########## @@ -0,0 +1,194 @@ +#------------------------------------------------------------- +## 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. +##------------------------------------------------------------- +# THIS SCRIPT COMPUTES A SOLUTION FOR THE HOSPITAL RESIDENCY MATCH PROBLEM +# +# INPUT PARAMETERS: +# -------------------------------------------------------------------------------------------- +# NAME TYPE DEFAULT MEANING +# -------------------------------------------------------------------------------------------- +# R Matrix --- Residents matrix R. +# It must be an ORDERED matrix. +# +# H Matrix --- Hospitals matrix H. +# It must be an UnORDERED matrix. +# +# C Matrix --- Capacity of Hospitals matrix C. +# It must be a [c,1] matrix with non zero values. +# i.e. the leftmost value in a row is the most preferred partner's index. +# i.e. the leftmost value in a row in P is the preference value for the acceptor with index 1 and vice-versa (higher is better). +# OUTPUT PARAMETERS: +# -------------------------------------------------------------------------------------------- +# NAME TYPE DEFAULT MEANING +# -------------------------------------------------------------------------------------------- +# ResidencyMatch Matrix --- Result Matrix +# If cell [i,j] is non-zero, it means that Resident i has matched with Hospital j. +# Further, if cell [i,j] is non-zero, it holds the preference value that led to the match. +# +# +# HospitalMatch Matrix --- Result Matrix +# If cell [i,j] is non-zero, it means that Resident i has matched with Hospital j. +# Further, if cell [i,j] is non-zero, it holds the preference value that led to the match. +# +# +# Residents.mtx: +# 2.0,1.0,3.0 +# 1.0,2.0,3.0 +# 1.0,2.0,0.0 +# +# Since it is an ORDERED matrix, this means that Resident 1 (row 1) likes acceptor 2 the most, followed by acceptor 1 and acceptor 3. +# If it was UNORDERED, this would mean that proposer 1 (row 1) likes acceptor 3 the most (since the value at [1,3] is the row max), +# followed by acceptor 1 (2.0 preference value) and acceptor 2 (1.0 preference value). +# +# Hospitals.mtx: +# 2.0,1.0,0.0 +# 0.0,1.0,2.0 +# 1.0,2.0,0.0 +# +# Since it is an UNORDERED matrix this means that Hospital 1 (row 1) likes Resident 1 the most (since the value at [1,1] is the row max). +# +# Capacity.mtx +# 1.0 +# 1.0 +# 1.0 +# +# ResidencyMatch.mtx +# 0.0,0.0,3.0 +# 1.0,0.0,0.0 +# 0.0,2.0,0.0 +# +# HospitalMatch.mtx +# 0.0,1.0,0.0 +# 0.0,0.0,2.0 +# 1.0,0.0,0.0 +# +# Resident 1 has matched with Hospital 3 (since [1,3] is non-zero) at a preference level of 3.0. +# Resident 2 has matched with Hospital 1 (since [2,1] is non-zero) at a preference level of 1.0. +# Resident 3 has matched with Hospital 2 (since [3,2] is non-zero) at a preference level of 2.0. +# -------------------------------------------------------------------------------------------- +m_residencyMatchMain = function(Matrix[Double] R, Matrix[Double] H,Matrix[Double] C ) + return (Matrix[Double] ResidencyMatch) +{ +#TODO PLEASE PAY ATTENTION +# in this step we consider that Residents Matrix is ORDERED !!!! +# in this step we consider that Hospital Matrix is UNORDERED !!!! + +print("STARTING Resident Hospital Match"); +#TODO set a finite number of maximum iterations so that the execution termiates after maximum iterations. + +print("\n") +print("STARTING RESIDENCY MATCH ALGORITHM"); +print("READING R as residents AND H as Hospitals and also C as capacity..."); + +m = nrow(R) +n = ncol (R) +Capacityrows = nrow(C) +####################################################################################################### +Capacity = matrix(0.0, rows=Capacityrows , cols=1) +Capacity = C; +max_position = colMaxs(Capacity) +####################################################################################################### +# we can consider number of choices for every resident # +####################################################################################################### +ResidencyMatch = matrix(0.0, rows=m, cols=n) +HospitalMatch = matrix(0.0, rows=n, cols=m) +Result_matrix = matrix(0.0, rows=nrow(R), cols=ncol(R)) +######################################################################################################## +if(nrow(Capacity) != nrow(H)) { + print("ERROR: Wrong Input !Capacity indexes is not match with the Number of hospitals ") + #it means that some hospitals' capacity is not defined. +}# end of if + +StarM = matrix(1.0, rows=m, cols=1) ### for checking while + +HIndex =matrix(1.0, rows=m, cols=1) +proposer_pointers = matrix(1.0, rows=m, cols=1) +prev_Residents_vector = matrix(1.0, rows=n, cols=1) +prevIndex_Residents_vector = matrix(1.0, rows=n, cols=1) + +prev_Residents_vector = rowMins(HospitalMatch) +prevIndex_Residents_vector = rowIndexMin(HospitalMatch) + +while(sum(StarM) > 0) { + + for(i in 1:m) { + + while (as.scalar (StarM[i]) == 1) { + SecondIndex = as.scalar (proposer_pointers[i]) + HIndex[i] = as.scalar (R[i,SecondIndex]) + prev_Residents_vector = rowMaxs(HospitalMatch) # we consider if the preference value is 1 it means it is the first selection of that hospital, the minimum value means most preference. + prevIndex_Residents_vector = rowIndexMax(HospitalMatch) + if (as.scalar(HIndex[i]) != 0 ){ + + HosValue = as.scalar (H[as.scalar (HIndex[i]),i]) Review comment: remove unnecessary space after as.scalar -- This is an automated message from the Apache Git Service. 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