PR rtl-optimization/79386
[official-gcc.git] / gcc / ada / a-ngrear.adb
blobc3b954ab5126c4848436f64fe3a66c58c64c68f8
1 ------------------------------------------------------------------------------
2 -- --
3 -- GNAT RUN-TIME COMPONENTS --
4 -- --
5 -- ADA.NUMERICS.GENERIC_REAL_ARRAYS --
6 -- --
7 -- B o d y --
8 -- --
9 -- Copyright (C) 2006-2016, Free Software Foundation, Inc. --
10 -- --
11 -- GNAT is free software; you can redistribute it and/or modify it under --
12 -- terms of the GNU General Public License as published by the Free Soft- --
13 -- ware Foundation; either version 3, or (at your option) any later ver- --
14 -- sion. GNAT is distributed in the hope that it will be useful, but WITH- --
15 -- OUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY --
16 -- or FITNESS FOR A PARTICULAR PURPOSE. --
17 -- --
18 -- As a special exception under Section 7 of GPL version 3, you are granted --
19 -- additional permissions described in the GCC Runtime Library Exception, --
20 -- version 3.1, as published by the Free Software Foundation. --
21 -- --
22 -- You should have received a copy of the GNU General Public License and --
23 -- a copy of the GCC Runtime Library Exception along with this program; --
24 -- see the files COPYING3 and COPYING.RUNTIME respectively. If not, see --
25 -- <http://www.gnu.org/licenses/>. --
26 -- --
27 -- GNAT was originally developed by the GNAT team at New York University. --
28 -- Extensive contributions were provided by Ada Core Technologies Inc. --
29 -- --
30 ------------------------------------------------------------------------------
32 -- This version of Generic_Real_Arrays avoids the use of BLAS and LAPACK. One
33 -- reason for this is new Ada 2012 requirements that prohibit algorithms such
34 -- as Strassen's algorithm, which may be used by some BLAS implementations. In
35 -- addition, some platforms lacked suitable compilers to compile the reference
36 -- BLAS/LAPACK implementation. Finally, on some platforms there are more
37 -- floating point types than supported by BLAS/LAPACK.
39 with Ada.Containers.Generic_Anonymous_Array_Sort; use Ada.Containers;
41 with System; use System;
42 with System.Generic_Array_Operations; use System.Generic_Array_Operations;
44 package body Ada.Numerics.Generic_Real_Arrays is
46 package Ops renames System.Generic_Array_Operations;
48 function Is_Non_Zero (X : Real'Base) return Boolean is (X /= 0.0);
50 procedure Back_Substitute is new Ops.Back_Substitute
51 (Scalar => Real'Base,
52 Matrix => Real_Matrix,
53 Is_Non_Zero => Is_Non_Zero);
55 function Diagonal is new Ops.Diagonal
56 (Scalar => Real'Base,
57 Vector => Real_Vector,
58 Matrix => Real_Matrix);
60 procedure Forward_Eliminate is new Ops.Forward_Eliminate
61 (Scalar => Real'Base,
62 Real => Real'Base,
63 Matrix => Real_Matrix,
64 Zero => 0.0,
65 One => 1.0);
67 procedure Swap_Column is new Ops.Swap_Column
68 (Scalar => Real'Base,
69 Matrix => Real_Matrix);
71 procedure Transpose is new Ops.Transpose
72 (Scalar => Real'Base,
73 Matrix => Real_Matrix);
75 function Is_Symmetric (A : Real_Matrix) return Boolean is
76 (Transpose (A) = A);
77 -- Return True iff A is symmetric, see RM G.3.1 (90).
79 function Is_Tiny (Value, Compared_To : Real) return Boolean is
80 (abs Compared_To + 100.0 * abs (Value) = abs Compared_To);
81 -- Return True iff the Value is much smaller in magnitude than the least
82 -- significant digit of Compared_To.
84 procedure Jacobi
85 (A : Real_Matrix;
86 Values : out Real_Vector;
87 Vectors : out Real_Matrix;
88 Compute_Vectors : Boolean := True);
89 -- Perform Jacobi's eigensystem algorithm on real symmetric matrix A
91 function Length is new Square_Matrix_Length (Real'Base, Real_Matrix);
92 -- Helper function that raises a Constraint_Error is the argument is
93 -- not a square matrix, and otherwise returns its length.
95 procedure Rotate (X, Y : in out Real; Sin, Tau : Real);
96 -- Perform a Givens rotation
98 procedure Sort_Eigensystem
99 (Values : in out Real_Vector;
100 Vectors : in out Real_Matrix);
101 -- Sort Values and associated Vectors by decreasing absolute value
103 procedure Swap (Left, Right : in out Real);
104 -- Exchange Left and Right
106 function Sqrt is new Ops.Sqrt (Real);
107 -- Instant a generic square root implementation here, in order to avoid
108 -- instantiating a complete copy of Generic_Elementary_Functions.
109 -- Speed of the square root is not a big concern here.
111 ------------
112 -- Rotate --
113 ------------
115 procedure Rotate (X, Y : in out Real; Sin, Tau : Real) is
116 Old_X : constant Real := X;
117 Old_Y : constant Real := Y;
118 begin
119 X := Old_X - Sin * (Old_Y + Old_X * Tau);
120 Y := Old_Y + Sin * (Old_X - Old_Y * Tau);
121 end Rotate;
123 ----------
124 -- Swap --
125 ----------
127 procedure Swap (Left, Right : in out Real) is
128 Temp : constant Real := Left;
129 begin
130 Left := Right;
131 Right := Temp;
132 end Swap;
134 -- Instantiating the following subprograms directly would lead to
135 -- name clashes, so use a local package.
137 package Instantiations is
139 function "+" is new
140 Vector_Elementwise_Operation
141 (X_Scalar => Real'Base,
142 Result_Scalar => Real'Base,
143 X_Vector => Real_Vector,
144 Result_Vector => Real_Vector,
145 Operation => "+");
147 function "+" is new
148 Matrix_Elementwise_Operation
149 (X_Scalar => Real'Base,
150 Result_Scalar => Real'Base,
151 X_Matrix => Real_Matrix,
152 Result_Matrix => Real_Matrix,
153 Operation => "+");
155 function "+" is new
156 Vector_Vector_Elementwise_Operation
157 (Left_Scalar => Real'Base,
158 Right_Scalar => Real'Base,
159 Result_Scalar => Real'Base,
160 Left_Vector => Real_Vector,
161 Right_Vector => Real_Vector,
162 Result_Vector => Real_Vector,
163 Operation => "+");
165 function "+" is new
166 Matrix_Matrix_Elementwise_Operation
167 (Left_Scalar => Real'Base,
168 Right_Scalar => Real'Base,
169 Result_Scalar => Real'Base,
170 Left_Matrix => Real_Matrix,
171 Right_Matrix => Real_Matrix,
172 Result_Matrix => Real_Matrix,
173 Operation => "+");
175 function "-" is new
176 Vector_Elementwise_Operation
177 (X_Scalar => Real'Base,
178 Result_Scalar => Real'Base,
179 X_Vector => Real_Vector,
180 Result_Vector => Real_Vector,
181 Operation => "-");
183 function "-" is new
184 Matrix_Elementwise_Operation
185 (X_Scalar => Real'Base,
186 Result_Scalar => Real'Base,
187 X_Matrix => Real_Matrix,
188 Result_Matrix => Real_Matrix,
189 Operation => "-");
191 function "-" is new
192 Vector_Vector_Elementwise_Operation
193 (Left_Scalar => Real'Base,
194 Right_Scalar => Real'Base,
195 Result_Scalar => Real'Base,
196 Left_Vector => Real_Vector,
197 Right_Vector => Real_Vector,
198 Result_Vector => Real_Vector,
199 Operation => "-");
201 function "-" is new
202 Matrix_Matrix_Elementwise_Operation
203 (Left_Scalar => Real'Base,
204 Right_Scalar => Real'Base,
205 Result_Scalar => Real'Base,
206 Left_Matrix => Real_Matrix,
207 Right_Matrix => Real_Matrix,
208 Result_Matrix => Real_Matrix,
209 Operation => "-");
211 function "*" is new
212 Scalar_Vector_Elementwise_Operation
213 (Left_Scalar => Real'Base,
214 Right_Scalar => Real'Base,
215 Result_Scalar => Real'Base,
216 Right_Vector => Real_Vector,
217 Result_Vector => Real_Vector,
218 Operation => "*");
220 function "*" is new
221 Scalar_Matrix_Elementwise_Operation
222 (Left_Scalar => Real'Base,
223 Right_Scalar => Real'Base,
224 Result_Scalar => Real'Base,
225 Right_Matrix => Real_Matrix,
226 Result_Matrix => Real_Matrix,
227 Operation => "*");
229 function "*" is new
230 Vector_Scalar_Elementwise_Operation
231 (Left_Scalar => Real'Base,
232 Right_Scalar => Real'Base,
233 Result_Scalar => Real'Base,
234 Left_Vector => Real_Vector,
235 Result_Vector => Real_Vector,
236 Operation => "*");
238 function "*" is new
239 Matrix_Scalar_Elementwise_Operation
240 (Left_Scalar => Real'Base,
241 Right_Scalar => Real'Base,
242 Result_Scalar => Real'Base,
243 Left_Matrix => Real_Matrix,
244 Result_Matrix => Real_Matrix,
245 Operation => "*");
247 function "*" is new
248 Outer_Product
249 (Left_Scalar => Real'Base,
250 Right_Scalar => Real'Base,
251 Result_Scalar => Real'Base,
252 Left_Vector => Real_Vector,
253 Right_Vector => Real_Vector,
254 Matrix => Real_Matrix);
256 function "*" is new
257 Inner_Product
258 (Left_Scalar => Real'Base,
259 Right_Scalar => Real'Base,
260 Result_Scalar => Real'Base,
261 Left_Vector => Real_Vector,
262 Right_Vector => Real_Vector,
263 Zero => 0.0);
265 function "*" is new
266 Matrix_Vector_Product
267 (Left_Scalar => Real'Base,
268 Right_Scalar => Real'Base,
269 Result_Scalar => Real'Base,
270 Matrix => Real_Matrix,
271 Right_Vector => Real_Vector,
272 Result_Vector => Real_Vector,
273 Zero => 0.0);
275 function "*" is new
276 Vector_Matrix_Product
277 (Left_Scalar => Real'Base,
278 Right_Scalar => Real'Base,
279 Result_Scalar => Real'Base,
280 Left_Vector => Real_Vector,
281 Matrix => Real_Matrix,
282 Result_Vector => Real_Vector,
283 Zero => 0.0);
285 function "*" is new
286 Matrix_Matrix_Product
287 (Left_Scalar => Real'Base,
288 Right_Scalar => Real'Base,
289 Result_Scalar => Real'Base,
290 Left_Matrix => Real_Matrix,
291 Right_Matrix => Real_Matrix,
292 Result_Matrix => Real_Matrix,
293 Zero => 0.0);
295 function "/" is new
296 Vector_Scalar_Elementwise_Operation
297 (Left_Scalar => Real'Base,
298 Right_Scalar => Real'Base,
299 Result_Scalar => Real'Base,
300 Left_Vector => Real_Vector,
301 Result_Vector => Real_Vector,
302 Operation => "/");
304 function "/" is new
305 Matrix_Scalar_Elementwise_Operation
306 (Left_Scalar => Real'Base,
307 Right_Scalar => Real'Base,
308 Result_Scalar => Real'Base,
309 Left_Matrix => Real_Matrix,
310 Result_Matrix => Real_Matrix,
311 Operation => "/");
313 function "abs" is new
314 L2_Norm
315 (X_Scalar => Real'Base,
316 Result_Real => Real'Base,
317 X_Vector => Real_Vector,
318 "abs" => "+");
319 -- While the L2_Norm by definition uses the absolute values of the
320 -- elements of X_Vector, for real values the subsequent squaring
321 -- makes this unnecessary, so we substitute the "+" identity function
322 -- instead.
324 function "abs" is new
325 Vector_Elementwise_Operation
326 (X_Scalar => Real'Base,
327 Result_Scalar => Real'Base,
328 X_Vector => Real_Vector,
329 Result_Vector => Real_Vector,
330 Operation => "abs");
332 function "abs" is new
333 Matrix_Elementwise_Operation
334 (X_Scalar => Real'Base,
335 Result_Scalar => Real'Base,
336 X_Matrix => Real_Matrix,
337 Result_Matrix => Real_Matrix,
338 Operation => "abs");
340 function Solve is new
341 Matrix_Vector_Solution (Real'Base, 0.0, Real_Vector, Real_Matrix);
343 function Solve is new
344 Matrix_Matrix_Solution (Real'Base, 0.0, Real_Matrix);
346 function Unit_Matrix is new
347 Generic_Array_Operations.Unit_Matrix
348 (Scalar => Real'Base,
349 Matrix => Real_Matrix,
350 Zero => 0.0,
351 One => 1.0);
353 function Unit_Vector is new
354 Generic_Array_Operations.Unit_Vector
355 (Scalar => Real'Base,
356 Vector => Real_Vector,
357 Zero => 0.0,
358 One => 1.0);
360 end Instantiations;
362 ---------
363 -- "+" --
364 ---------
366 function "+" (Right : Real_Vector) return Real_Vector
367 renames Instantiations."+";
369 function "+" (Right : Real_Matrix) return Real_Matrix
370 renames Instantiations."+";
372 function "+" (Left, Right : Real_Vector) return Real_Vector
373 renames Instantiations."+";
375 function "+" (Left, Right : Real_Matrix) return Real_Matrix
376 renames Instantiations."+";
378 ---------
379 -- "-" --
380 ---------
382 function "-" (Right : Real_Vector) return Real_Vector
383 renames Instantiations."-";
385 function "-" (Right : Real_Matrix) return Real_Matrix
386 renames Instantiations."-";
388 function "-" (Left, Right : Real_Vector) return Real_Vector
389 renames Instantiations."-";
391 function "-" (Left, Right : Real_Matrix) return Real_Matrix
392 renames Instantiations."-";
394 ---------
395 -- "*" --
396 ---------
398 -- Scalar multiplication
400 function "*" (Left : Real'Base; Right : Real_Vector) return Real_Vector
401 renames Instantiations."*";
403 function "*" (Left : Real_Vector; Right : Real'Base) return Real_Vector
404 renames Instantiations."*";
406 function "*" (Left : Real'Base; Right : Real_Matrix) return Real_Matrix
407 renames Instantiations."*";
409 function "*" (Left : Real_Matrix; Right : Real'Base) return Real_Matrix
410 renames Instantiations."*";
412 -- Vector multiplication
414 function "*" (Left, Right : Real_Vector) return Real'Base
415 renames Instantiations."*";
417 function "*" (Left, Right : Real_Vector) return Real_Matrix
418 renames Instantiations."*";
420 function "*" (Left : Real_Vector; Right : Real_Matrix) return Real_Vector
421 renames Instantiations."*";
423 function "*" (Left : Real_Matrix; Right : Real_Vector) return Real_Vector
424 renames Instantiations."*";
426 -- Matrix Multiplication
428 function "*" (Left, Right : Real_Matrix) return Real_Matrix
429 renames Instantiations."*";
431 ---------
432 -- "/" --
433 ---------
435 function "/" (Left : Real_Vector; Right : Real'Base) return Real_Vector
436 renames Instantiations."/";
438 function "/" (Left : Real_Matrix; Right : Real'Base) return Real_Matrix
439 renames Instantiations."/";
441 -----------
442 -- "abs" --
443 -----------
445 function "abs" (Right : Real_Vector) return Real'Base
446 renames Instantiations."abs";
448 function "abs" (Right : Real_Vector) return Real_Vector
449 renames Instantiations."abs";
451 function "abs" (Right : Real_Matrix) return Real_Matrix
452 renames Instantiations."abs";
454 -----------------
455 -- Determinant --
456 -----------------
458 function Determinant (A : Real_Matrix) return Real'Base is
459 M : Real_Matrix := A;
460 B : Real_Matrix (A'Range (1), 1 .. 0);
461 R : Real'Base;
462 begin
463 Forward_Eliminate (M, B, R);
464 return R;
465 end Determinant;
467 -----------------
468 -- Eigensystem --
469 -----------------
471 procedure Eigensystem
472 (A : Real_Matrix;
473 Values : out Real_Vector;
474 Vectors : out Real_Matrix)
476 begin
477 Jacobi (A, Values, Vectors, Compute_Vectors => True);
478 Sort_Eigensystem (Values, Vectors);
479 end Eigensystem;
481 -----------------
482 -- Eigenvalues --
483 -----------------
485 function Eigenvalues (A : Real_Matrix) return Real_Vector is
486 begin
487 return Values : Real_Vector (A'Range (1)) do
488 declare
489 Vectors : Real_Matrix (1 .. 0, 1 .. 0);
490 begin
491 Jacobi (A, Values, Vectors, Compute_Vectors => False);
492 Sort_Eigensystem (Values, Vectors);
493 end;
494 end return;
495 end Eigenvalues;
497 -------------
498 -- Inverse --
499 -------------
501 function Inverse (A : Real_Matrix) return Real_Matrix is
502 (Solve (A, Unit_Matrix (Length (A))));
504 ------------
505 -- Jacobi --
506 ------------
508 procedure Jacobi
509 (A : Real_Matrix;
510 Values : out Real_Vector;
511 Vectors : out Real_Matrix;
512 Compute_Vectors : Boolean := True)
514 -- This subprogram uses Carl Gustav Jacob Jacobi's iterative method
515 -- for computing eigenvalues and eigenvectors and is based on
516 -- Rutishauser's implementation.
518 -- The given real symmetric matrix is transformed iteratively to
519 -- diagonal form through a sequence of appropriately chosen elementary
520 -- orthogonal transformations, called Jacobi rotations here.
522 -- The Jacobi method produces a systematic decrease of the sum of the
523 -- squares of off-diagonal elements. Convergence to zero is quadratic,
524 -- both for this implementation, as for the classic method that doesn't
525 -- use row-wise scanning for pivot selection.
527 -- The numerical stability and accuracy of Jacobi's method make it the
528 -- best choice here, even though for large matrices other methods will
529 -- be significantly more efficient in both time and space.
531 -- While the eigensystem computations are absolutely foolproof for all
532 -- real symmetric matrices, in presence of invalid values, or similar
533 -- exceptional situations it might not. In such cases the results cannot
534 -- be trusted and Constraint_Error is raised.
536 -- Note: this implementation needs temporary storage for 2 * N + N**2
537 -- values of type Real.
539 Max_Iterations : constant := 50;
540 N : constant Natural := Length (A);
542 subtype Square_Matrix is Real_Matrix (1 .. N, 1 .. N);
544 -- In order to annihilate the M (Row, Col) element, the
545 -- rotation parameters Cos and Sin are computed as
546 -- follows:
548 -- Theta = Cot (2.0 * Phi)
549 -- = (Diag (Col) - Diag (Row)) / (2.0 * M (Row, Col))
551 -- Then Tan (Phi) as the smaller root (in modulus) of
553 -- T**2 + 2 * T * Theta = 1 (or 0.5 / Theta, if Theta is large)
555 function Compute_Tan (Theta : Real) return Real is
556 (Real'Copy_Sign (1.0 / (abs Theta + Sqrt (1.0 + Theta**2)), Theta));
558 function Compute_Tan (P, H : Real) return Real is
559 (if Is_Tiny (P, Compared_To => H) then P / H
560 else Compute_Tan (Theta => H / (2.0 * P)));
562 function Sum_Strict_Upper (M : Square_Matrix) return Real;
563 -- Return the sum of all elements in the strict upper triangle of M
565 ----------------------
566 -- Sum_Strict_Upper --
567 ----------------------
569 function Sum_Strict_Upper (M : Square_Matrix) return Real is
570 Sum : Real := 0.0;
572 begin
573 for Row in 1 .. N - 1 loop
574 for Col in Row + 1 .. N loop
575 Sum := Sum + abs M (Row, Col);
576 end loop;
577 end loop;
579 return Sum;
580 end Sum_Strict_Upper;
582 M : Square_Matrix := A; -- Work space for solving eigensystem
583 Threshold : Real;
584 Sum : Real;
585 Diag : Real_Vector (1 .. N);
586 Diag_Adj : Real_Vector (1 .. N);
588 -- The vector Diag_Adj indicates the amount of change in each value,
589 -- while Diag tracks the value itself and Values holds the values as
590 -- they were at the beginning. As the changes typically will be small
591 -- compared to the absolute value of Diag, at the end of each iteration
592 -- Diag is computed as Diag + Diag_Adj thus avoiding accumulating
593 -- rounding errors. This technique is due to Rutishauser.
595 begin
596 if Compute_Vectors
597 and then (Vectors'Length (1) /= N or else Vectors'Length (2) /= N)
598 then
599 raise Constraint_Error with "incompatible matrix dimensions";
601 elsif Values'Length /= N then
602 raise Constraint_Error with "incompatible vector length";
604 elsif not Is_Symmetric (M) then
605 raise Constraint_Error with "matrix not symmetric";
606 end if;
608 -- Note: Only the locally declared matrix M and vectors (Diag, Diag_Adj)
609 -- have lower bound equal to 1. The Vectors matrix may have
610 -- different bounds, so take care indexing elements. Assignment
611 -- as a whole is fine as sliding is automatic in that case.
613 Vectors := (if not Compute_Vectors then (1 .. 0 => (1 .. 0 => 0.0))
614 else Unit_Matrix (Vectors'Length (1), Vectors'Length (2)));
615 Values := Diagonal (M);
617 Sweep : for Iteration in 1 .. Max_Iterations loop
619 -- The first three iterations, perform rotation for any non-zero
620 -- element. After this, rotate only for those that are not much
621 -- smaller than the average off-diagnal element. After the fifth
622 -- iteration, additionally zero out off-diagonal elements that are
623 -- very small compared to elements on the diagonal with the same
624 -- column or row index.
626 Sum := Sum_Strict_Upper (M);
628 exit Sweep when Sum = 0.0;
630 Threshold := (if Iteration < 4 then 0.2 * Sum / Real (N**2) else 0.0);
632 -- Iterate over all off-diagonal elements, rotating any that have
633 -- an absolute value that exceeds the threshold.
635 Diag := Values;
636 Diag_Adj := (others => 0.0); -- Accumulates adjustments to Diag
638 for Row in 1 .. N - 1 loop
639 for Col in Row + 1 .. N loop
641 -- If, before the rotation M (Row, Col) is tiny compared to
642 -- Diag (Row) and Diag (Col), rotation is skipped. This is
643 -- meaningful, as it produces no larger error than would be
644 -- produced anyhow if the rotation had been performed.
645 -- Suppress this optimization in the first four sweeps, so
646 -- that this procedure can be used for computing eigenvectors
647 -- of perturbed diagonal matrices.
649 if Iteration > 4
650 and then Is_Tiny (M (Row, Col), Compared_To => Diag (Row))
651 and then Is_Tiny (M (Row, Col), Compared_To => Diag (Col))
652 then
653 M (Row, Col) := 0.0;
655 elsif abs M (Row, Col) > Threshold then
656 Perform_Rotation : declare
657 Tan : constant Real := Compute_Tan (M (Row, Col),
658 Diag (Col) - Diag (Row));
659 Cos : constant Real := 1.0 / Sqrt (1.0 + Tan**2);
660 Sin : constant Real := Tan * Cos;
661 Tau : constant Real := Sin / (1.0 + Cos);
662 Adj : constant Real := Tan * M (Row, Col);
664 begin
665 Diag_Adj (Row) := Diag_Adj (Row) - Adj;
666 Diag_Adj (Col) := Diag_Adj (Col) + Adj;
667 Diag (Row) := Diag (Row) - Adj;
668 Diag (Col) := Diag (Col) + Adj;
670 M (Row, Col) := 0.0;
672 for J in 1 .. Row - 1 loop -- 1 <= J < Row
673 Rotate (M (J, Row), M (J, Col), Sin, Tau);
674 end loop;
676 for J in Row + 1 .. Col - 1 loop -- Row < J < Col
677 Rotate (M (Row, J), M (J, Col), Sin, Tau);
678 end loop;
680 for J in Col + 1 .. N loop -- Col < J <= N
681 Rotate (M (Row, J), M (Col, J), Sin, Tau);
682 end loop;
684 for J in Vectors'Range (1) loop
685 Rotate (Vectors (J, Row - 1 + Vectors'First (2)),
686 Vectors (J, Col - 1 + Vectors'First (2)),
687 Sin, Tau);
688 end loop;
689 end Perform_Rotation;
690 end if;
691 end loop;
692 end loop;
694 Values := Values + Diag_Adj;
695 end loop Sweep;
697 -- All normal matrices with valid values should converge perfectly.
699 if Sum /= 0.0 then
700 raise Constraint_Error with "eigensystem solution does not converge";
701 end if;
702 end Jacobi;
704 -----------
705 -- Solve --
706 -----------
708 function Solve (A : Real_Matrix; X : Real_Vector) return Real_Vector
709 renames Instantiations.Solve;
711 function Solve (A, X : Real_Matrix) return Real_Matrix
712 renames Instantiations.Solve;
714 ----------------------
715 -- Sort_Eigensystem --
716 ----------------------
718 procedure Sort_Eigensystem
719 (Values : in out Real_Vector;
720 Vectors : in out Real_Matrix)
722 procedure Swap (Left, Right : Integer);
723 -- Swap Values (Left) with Values (Right), and also swap the
724 -- corresponding eigenvectors. Note that lowerbounds may differ.
726 function Less (Left, Right : Integer) return Boolean is
727 (Values (Left) > Values (Right));
728 -- Sort by decreasing eigenvalue, see RM G.3.1 (76).
730 procedure Sort is new Generic_Anonymous_Array_Sort (Integer);
731 -- Sorts eigenvalues and eigenvectors by decreasing value
733 procedure Swap (Left, Right : Integer) is
734 begin
735 Swap (Values (Left), Values (Right));
736 Swap_Column (Vectors, Left - Values'First + Vectors'First (2),
737 Right - Values'First + Vectors'First (2));
738 end Swap;
740 begin
741 Sort (Values'First, Values'Last);
742 end Sort_Eigensystem;
744 ---------------
745 -- Transpose --
746 ---------------
748 function Transpose (X : Real_Matrix) return Real_Matrix is
749 begin
750 return R : Real_Matrix (X'Range (2), X'Range (1)) do
751 Transpose (X, R);
752 end return;
753 end Transpose;
755 -----------------
756 -- Unit_Matrix --
757 -----------------
759 function Unit_Matrix
760 (Order : Positive;
761 First_1 : Integer := 1;
762 First_2 : Integer := 1) return Real_Matrix
763 renames Instantiations.Unit_Matrix;
765 -----------------
766 -- Unit_Vector --
767 -----------------
769 function Unit_Vector
770 (Index : Integer;
771 Order : Positive;
772 First : Integer := 1) return Real_Vector
773 renames Instantiations.Unit_Vector;
775 end Ada.Numerics.Generic_Real_Arrays;