SantasSledges_CostVector.mos

model "SantasSledges Clustering At Scale"

uses "r", "mmsystem", "mmsheet"

parameters
  CLUSTER=1

  SLEDGECAPACITY=1000
  SLEDGEWEIGHT=10

  r = 100
  Pi = 3.14159265359
end-parameters

function arcsin(r:real): real
  if abs(r)<1 then
    returned:=2*arctan((r/(1+(1-r^2)^0.5)))
  else
    writeln("Math error")
  end-if 
end-function

! A haversine function
function haversine( latitude1 : real, longitude1 : real, 
                    latitude2 : real, longitude2 : real ) : real
  returned := 2*r*arcsin( sqrt( sin((Pi*latitude2/180-Pi*latitude1/180)/2)^2 + 
    cos(Pi*latitude1/180)*cos(Pi*latitude2/180)*sin((Pi*longitude2/180-Pi*longitude1/180)/2)^2 ) )  
end-function

writeln("Making Cost Vector for Cluster: ", CLUSTER)
writeln
writeln

declarations
  POLE_LATITUDE = 90
  POLE_LONGITUDE = 0

  Locations : set of integer
  Distances : array(Locations, Locations) of real

  GiftIDs   : set of integer
  Latitude  : array(GiftIDs) of real
  Longitude : array(GiftIDs) of real
  Weight    : array(GiftIDs) of real
  
end-declarations

!!!!!! ENTERS DIFFERENT CWD
setparam('workdir','./'+CLUSTER)

initializations from "mmsheet.csv:cluster_" + CLUSTER + ".csv"
  [Latitude, Longitude, Weight] as "skiph;[B:E]"
end-initializations

Locations := {0} + GiftIDs;
forall(c in Locations, d in Locations) do
  ! If between two gift locations
  if (c <> 0 and d <> 0) then
    Distance(c,d) := haversine( Latitude(c), Longitude(c), Latitude(d), Longitude(d) )
  elif (c = 0 and d <> 0) then
    ! Going from the Pole
    Distance(0,d) := haversine( POLE_LATITUDE, POLE_LONGITUDE, Latitude(d), Longitude(d) )
  elif (c <> 0) then
    ! Going to the Pole
    Distance(c,0) := haversine( Latitude(c), Longitude(c), POLE_LATITUDE, POLE_LONGITUDE )
  else
    ! Stay put at the Pole
    Distance(0,0) := 0
  end-if
end-do

writeln("Total gift count: ", getsize(GiftIDs))

! For calculating costs
costs := 0.0
weight := 0.0
start := 0
  
declarations
  Index         : set of integer
  sortedGiftIDs : array(Index) of integer  
  sortedWeights : array(Index) of real
  TripIDs       : array(Index) of integer
  TripSet       : dynamic array(set of integer) of set of integer
  TripList      : list of integer
  
  CostVector    : dynamic array(set of integer) of real
end-declarations

initializations from "mmsheet.csv:subcluster_"+CLUSTER+"_costs.csv"
  [sortedGiftIDs, TripIDs, sortedWeights] as "skiph;[A:D]"
end-initializations

maxTrip := 0
forall( i in Index ) do
  TripSet(TripIDs(i)) += {i}
  if TripIDs(i) > maxTrip then
    maxTrip := TripIDs(i)
  end-if
end-do

writeln("Starting...")
forall( t in 1..maxTrip ) do
  weight := sum( i in TripSet(t) ) sortedWeights(i)
  weight += 10

  forall( i in TripSet(t) ) do
    costs  += weight*Distance(start, sortedGiftIDs(i))
    weight -= sortedWeights(i)
    start  := sortedGiftIDs(i)
  end-do
  costs += weight*Distance(start,0)
  CostVector(t) := costs
  start := 0
  costs := 0
  weight := 0
  TripList := []
end-do

fopen("cost_"+CLUSTER+".csv",F_OUTPUT)
writeln("TripID,Cost")
forall( t in 1..maxTrip ) do
  writeln(t,",",CostVector(t))
end-do
fclose(F_OUTPUT)
!!!!!!! GOES BACK OUT OF CHANGED CWD
setparam('workdir','../')
writeln
writeln

end-model