/usr/share/axiom-20170501/src/algebra/E04MBFA.spad is in axiom-source 20170501-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | )abbrev domain E04MBFA e04mbfAnnaType
++ Author: Brian Dupee
++ Date Created: February 1996
++ Date Last Updated: February 1996
++ References:
++ Dupe95 Using Computer Algebra to Choose and Apply Numerical Routines
++ Dewa92 Using Computer Algebra to Select Numerical Algorithms
++ Description:
++ \axiomType{e04mbfAnnaType} is a domain of \axiomType{NumericalOptimization}
++ for the NAG routine E04MBF, an optimization routine for Linear functions.
++ The function
++ \axiomFun{measure} measures the usefulness of the routine E04MBF
++ for the given problem. The function \axiomFun{numericalOptimization}
++ performs the optimization by using \axiomType{NagOptimisationPackage}.
e04mbfAnnaType() : SIG == CODE where
DF ==> DoubleFloat
EF ==> Expression Float
EDF ==> Expression DoubleFloat
PDF ==> Polynomial DoubleFloat
VPDF ==> Vector Polynomial DoubleFloat
LDF ==> List DoubleFloat
LOCDF ==> List OrderedCompletion DoubleFloat
MDF ==> Matrix DoubleFloat
MPDF ==> Matrix Polynomial DoubleFloat
MF ==> Matrix Float
MEF ==> Matrix Expression Float
LEDF ==> List Expression DoubleFloat
VEF ==> Vector Expression Float
NOA ==> Record(fn:EDF, init:LDF, lb:LOCDF, cf:LEDF, ub:LOCDF)
LSA ==> Record(lfn:LEDF, init:LDF)
EF2 ==> ExpressionFunctions2
MI ==> Matrix Integer
INT ==> Integer
F ==> Float
NNI ==> NonNegativeInteger
S ==> Symbol
LS ==> List Symbol
MVCF ==> MultiVariableCalculusFunctions
ESTOOLS2 ==> ExpertSystemToolsPackage2
SDF ==> Stream DoubleFloat
LSDF ==> List Stream DoubleFloat
SOCDF ==> Segment OrderedCompletion DoubleFloat
OCDF ==> OrderedCompletion DoubleFloat
SIG ==> NumericalOptimizationCategory
CODE ==> Result add
Rep:=Result
import Rep, NagOptimisationPackage
import e04AgentsPackage,ExpertSystemToolsPackage
measure(R:RoutinesTable,args:NOA) ==
(not linear?([args.fn])) or (not linear?(args.cf)) =>
[0.0,"e04mbf is for a linear objective function and constraints only."]
[getMeasure(R,e04mbf@Symbol)$RoutinesTable,"e04mbf is recommended" ]
numericalOptimization(args:NOA) ==
argsFn:EDF := args.fn
c := args.cf
listVars:List LS := _
concat(variables(argsFn)$EDF,[variables(z)$EDF for z in c])
n:NNI := #(v := removeDuplicates(concat(listVars)$LS)$LS)
A:MDF := linearMatrix(args.cf,n)
nclin:NNI := # linearPart(c)
nrowa:NNI := max(1,nclin)
bl:MDF := mat(finiteBound(args.lb,float(1,21,10)$DF),n)
bu:MDF := mat(finiteBound(args.ub,float(1,21,10)$DF),n)
cvec:MDF := mat(coefficients(retract(argsFn)@PDF)$PDF,n)
x := mat(args.init,n)
lwork:INT :=
nclin < n => 2*nclin*(nclin+4)+2+6*n+nrowa
2*(n+3)*n+4*nclin+nrowa
out:Result := _
e04mbf(20,1,n,nclin,n+nclin,nrowa,A,bl,bu,cvec,true,2*n,lwork,x,-1)
changeNameToObjf(objlp@Symbol,out)
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