(* Title: HOL/Matrix/cplex/fspmlp.ML
ID: $Id$
Author: Steven Obua
*)
signature FSPMLP =
sig
type linprog
type vector = FloatSparseMatrixBuilder.vector
type matrix = FloatSparseMatrixBuilder.matrix
val y : linprog -> term
val A : linprog -> term * term
val b : linprog -> term
val c : linprog -> term * term
val r : linprog -> term
val r12 : linprog -> term * term
exception Load of string
val load : string -> int -> bool -> linprog
end
structure Fspmlp : FSPMLP =
struct
type vector = FloatSparseMatrixBuilder.vector
type matrix = FloatSparseMatrixBuilder.matrix
type linprog = term * (term * term) * term * (term * term) * term * (term * term)
fun y (c1, c2, c3, c4, c5, _) = c1
fun A (c1, c2, c3, c4, c5, _) = c2
fun b (c1, c2, c3, c4, c5, _) = c3
fun c (c1, c2, c3, c4, c5, _) = c4
fun r (c1, c2, c3, c4, c5, _) = c5
fun r12 (c1, c2, c3, c4, c5, c6) = c6
structure CplexFloatSparseMatrixConverter =
MAKE_CPLEX_MATRIX_CONVERTER(structure cplex = Cplex and matrix_builder = FloatSparseMatrixBuilder);
datatype bound_type = LOWER | UPPER
fun intbound_ord ((i1, b1),(i2,b2)) =
if i1 < i2 then LESS
else if i1 = i2 then
(if b1 = b2 then EQUAL else if b1=LOWER then LESS else GREATER)
else GREATER
structure Inttab = TableFun(type key = int val ord = (rev_order o int_ord));
structure VarGraph = TableFun(type key = int*bound_type val ord = intbound_ord);
(* key -> (float option) * (int -> (float * (((float * float) * key) list)))) *)
(* dest_key -> (sure_bound * (row_index -> (row_bound * (((coeff_lower * coeff_upper) * src_key) list)))) *)
exception Internal of string;
fun add_row_bound g dest_key row_index row_bound =
let
val x =
case VarGraph.lookup g dest_key of
NONE => (NONE, Inttab.update (row_index, (row_bound, [])) Inttab.empty)
| SOME (sure_bound, f) =>
(sure_bound,
case Inttab.lookup f row_index of
NONE => Inttab.update (row_index, (row_bound, [])) f
| SOME _ => raise (Internal "add_row_bound"))
in
VarGraph.update (dest_key, x) g
end
fun update_sure_bound g (key as (_, btype)) bound =
let
val x =
case VarGraph.lookup g key of
NONE => (SOME bound, Inttab.empty)
| SOME (NONE, f) => (SOME bound, f)
| SOME (SOME old_bound, f) =>
(SOME ((case btype of
UPPER => Float.min
| LOWER => Float.max)
old_bound bound), f)
in
VarGraph.update (key, x) g
end
fun get_sure_bound g key =
case VarGraph.lookup g key of
NONE => NONE
| SOME (sure_bound, _) => sure_bound
(*fun get_row_bound g key row_index =
case VarGraph.lookup g key of
NONE => NONE
| SOME (sure_bound, f) =>
(case Inttab.lookup f row_index of
NONE => NONE
| SOME (row_bound, _) => (sure_bound, row_bound))*)
fun add_edge g src_key dest_key row_index coeff =
case VarGraph.lookup g dest_key of
NONE => raise (Internal "add_edge: dest_key not found")
| SOME (sure_bound, f) =>
(case Inttab.lookup f row_index of
NONE => raise (Internal "add_edge: row_index not found")
| SOME (row_bound, sources) =>
VarGraph.update (dest_key, (sure_bound, Inttab.update (row_index, (row_bound, (coeff, src_key) :: sources)) f)) g)
fun split_graph g =
let
fun split (key, (sure_bound, _)) (r1, r2) = case sure_bound
of NONE => (r1, r2)
| SOME bound => (case key
of (u, UPPER) => (r1, Inttab.update (u, bound) r2)
| (u, LOWER) => (Inttab.update (u, bound) r1, r2))
in VarGraph.fold split g (Inttab.empty, Inttab.empty) end
fun it2list t = Inttab.fold cons t [];
(* If safe is true, termination is guaranteed, but the sure bounds may be not optimal (relative to the algorithm).
If safe is false, termination is not guaranteed, but on termination the sure bounds are optimal (relative to the algorithm) *)
fun propagate_sure_bounds safe names g =
let
(* returns NONE if no new sure bound could be calculated, otherwise the new sure bound is returned *)
fun calc_sure_bound_from_sources g (key as (_, btype)) =
let
fun mult_upper x (lower, upper) =
if Float.cmp_zero x = LESS then
Float.mult x lower
else
Float.mult x upper
fun mult_lower x (lower, upper) =
if Float.cmp_zero x = LESS then
Float.mult x upper
else
Float.mult x lower
val mult_btype = case btype of UPPER => mult_upper | LOWER => mult_lower
fun calc_sure_bound (row_index, (row_bound, sources)) sure_bound =
let
fun add_src_bound (coeff, src_key) sum =
case sum of
NONE => NONE
| SOME x =>
(case get_sure_bound g src_key of
NONE => NONE
| SOME src_sure_bound => SOME (Float.add x (mult_btype src_sure_bound coeff)))
in
case fold add_src_bound sources (SOME row_bound) of
NONE => sure_bound
| new_sure_bound as (SOME new_bound) =>
(case sure_bound of
NONE => new_sure_bound
| SOME old_bound =>
SOME (case btype of
UPPER => Float.min old_bound new_bound
| LOWER => Float.max old_bound new_bound))
end
in
case VarGraph.lookup g key of
NONE => NONE
| SOME (sure_bound, f) =>
let
val x = Inttab.fold calc_sure_bound f sure_bound
in
if x = sure_bound then NONE else x
end
end
fun propagate (key, _) (g, b) =
case calc_sure_bound_from_sources g key of
NONE => (g,b)
| SOME bound => (update_sure_bound g key bound,
if safe then
case get_sure_bound g key of
NONE => true
| _ => b
else
true)
val (g, b) = VarGraph.fold propagate g (g, false)
in
if b then propagate_sure_bounds safe names g else g
end
exception Load of string;
(*val empty_spvec = @ {term "Nil :: (nat * real) list"};
fun cons_spvec x xs = @ {term "Cons :: nat * real => nat * real => (nat * real) list"} $ x $ xs;
val empty_spmat = @ {term "Nil :: (nat * (nat * real) list) list"};
fun cons_spmat x xs = @ {term "Cons :: nat * (nat * real) list => (nat * (nat * real) list) list => (nat * (nat * real) list) list"} $ x $ xs;*)
val empty_spvec = Bound 0
fun cons_spvec x xs = Bound 0
val empty_spmat = Bound 0
fun cons_spmat x xs = Bound 0
fun calcr safe_propagation xlen names prec A b =
let
val empty = Inttab.empty
fun instab t i x = Inttab.update (i, x) t
fun isnegstr x = String.isPrefix "-" x
fun negstr x = if isnegstr x then String.extract (x, 1, NONE) else "-"^x
fun test_1 (lower, upper) =
if lower = upper then
(if Float.eq (lower, (Integer.int ~1, Integer.zero)) then ~1
else if Float.eq (lower, (Integer.int 1, Integer.zero)) then 1
else 0)
else 0
fun calcr (row_index, a) g =
let
val b = FloatSparseMatrixBuilder.v_elem_at b row_index
val (_, b2) = FloatArith.approx_decstr_by_bin prec (case b of NONE => "0" | SOME b => b)
val approx_a = FloatSparseMatrixBuilder.v_fold (fn (i, s) => fn l =>
(i, FloatArith.approx_decstr_by_bin prec s)::l) a []
fun fold_dest_nodes (dest_index, dest_value) g =
let
val dest_test = test_1 dest_value
in
if dest_test = 0 then
g
else let
val (dest_key as (_, dest_btype), row_bound) =
if dest_test = ~1 then
((dest_index, LOWER), Float.neg b2)
else
((dest_index, UPPER), b2)
fun fold_src_nodes (src_index, src_value as (src_lower, src_upper)) g =
if src_index = dest_index then g
else
let
val coeff = case dest_btype of
UPPER => (Float.neg src_upper, Float.neg src_lower)
| LOWER => src_value
in
if Float.cmp_zero src_lower = LESS then
add_edge g (src_index, UPPER) dest_key row_index coeff
else
add_edge g (src_index, LOWER) dest_key row_index coeff
end
in
fold fold_src_nodes approx_a (add_row_bound g dest_key row_index row_bound)
end
end
in
case approx_a of
[] => g
| [(u, a)] =>
let
val atest = test_1 a
in
if atest = ~1 then
update_sure_bound g (u, LOWER) (Float.neg b2)
else if atest = 1 then
update_sure_bound g (u, UPPER) b2
else
g
end
| _ => fold fold_dest_nodes approx_a g
end
val g = FloatSparseMatrixBuilder.m_fold calcr A VarGraph.empty
val g = propagate_sure_bounds safe_propagation names g
val (r1, r2) = split_graph g
fun add_row_entry m index value =
let
val vec = cons_spvec (FloatSparseMatrixBuilder.mk_spvec_entry 0 value) empty_spvec
in
cons_spmat (FloatSparseMatrixBuilder.mk_spmat_entry index vec) m
end
fun abs_estimate i r1 r2 =
if i = 0 then
let val e = empty_spmat in (e, (e, e)) end
else
let
val index = xlen-i
val (r, (r12_1, r12_2)) = abs_estimate (i-1) r1 r2
val b1 = case Inttab.lookup r1 index of NONE => raise (Load ("x-value not bounded from below: "^(names index))) | SOME x => x
val b2 = case Inttab.lookup r2 index of NONE => raise (Load ("x-value not bounded from above: "^(names index))) | SOME x => x
val abs_max = Float.max (Float.neg (Float.negative_part b1)) (Float.positive_part b2)
val i' = Integer.int index
in
(add_row_entry r i' abs_max, (add_row_entry r12_1 i' b1, add_row_entry r12_2 i' b2))
end
val (r, (r1, r2)) = abs_estimate xlen r1 r2
in
(r, (r1, r2))
end
fun load filename prec safe_propagation =
let
val prog = Cplex.load_cplexFile filename
val prog = Cplex.elim_nonfree_bounds prog
val prog = Cplex.relax_strict_ineqs prog
val (maximize, c, A, b, (xlen, names, _)) = CplexFloatSparseMatrixConverter.convert_prog prog
val (r, (r1, r2)) = calcr safe_propagation xlen names prec A b
val _ = if maximize then () else raise Load "sorry, cannot handle minimization problems"
val (dualprog, indexof) = FloatSparseMatrixBuilder.dual_cplexProg c A b
val results = Cplex.solve dualprog
val (optimal,v) = CplexFloatSparseMatrixConverter.convert_results results indexof
val A = FloatSparseMatrixBuilder.cut_matrix v NONE A
fun id x = x
val v = FloatSparseMatrixBuilder.set_vector FloatSparseMatrixBuilder.empty_matrix 0 v
val b = FloatSparseMatrixBuilder.transpose_matrix (FloatSparseMatrixBuilder.set_vector FloatSparseMatrixBuilder.empty_matrix 0 b)
val c = FloatSparseMatrixBuilder.set_vector FloatSparseMatrixBuilder.empty_matrix 0 c
val (y1, _) = FloatSparseMatrixBuilder.approx_matrix prec Float.positive_part v
val A = FloatSparseMatrixBuilder.approx_matrix prec id A
val (_,b2) = FloatSparseMatrixBuilder.approx_matrix prec id b
val c = FloatSparseMatrixBuilder.approx_matrix prec id c
in
(y1, A, b2, c, r, (r1, r2))
end handle CplexFloatSparseMatrixConverter.Converter s => (raise (Load ("Converter: "^s)))
end