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------------------------------------------------------------------------------
-- --
-- GNAT RUN-TIME COMPONENTS --
-- --
-- S Y S T E M . G E N E R I C _ A R R A Y _ O P E R A T I O N S --
-- --
-- B o d y --
-- --
-- Copyright (C) 2006-2012, Free Software Foundation, Inc. --
-- --
-- GNAT is free software; you can redistribute it and/or modify it under --
-- terms of the GNU General Public License as published by the Free Soft- --
-- ware Foundation; either version 3, or (at your option) any later ver- --
-- sion. GNAT is distributed in the hope that it will be useful, but WITH- --
-- OUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY --
-- or FITNESS FOR A PARTICULAR PURPOSE. --
-- --
-- As a special exception under Section 7 of GPL version 3, you are granted --
-- additional permissions described in the GCC Runtime Library Exception, --
-- version 3.1, as published by the Free Software Foundation. --
-- --
-- You should have received a copy of the GNU General Public License and --
-- a copy of the GCC Runtime Library Exception along with this program; --
-- see the files COPYING3 and COPYING.RUNTIME respectively. If not, see --
-- <http://www.gnu.org/licenses/>. --
-- --
-- GNAT was originally developed by the GNAT team at New York University. --
-- Extensive contributions were provided by Ada Core Technologies Inc. --
-- --
------------------------------------------------------------------------------
with Ada.Numerics; use Ada.Numerics;
package body System.Generic_Array_Operations is
function Check_Unit_Last
(Index : Integer;
Order : Positive;
First : Integer) return Integer;
pragma Inline_Always (Check_Unit_Last);
-- Compute index of last element returned by Unit_Vector or Unit_Matrix.
-- A separate function is needed to allow raising Constraint_Error before
-- declaring the function result variable. The result variable needs to be
-- declared first, to allow front-end inlining.
--------------
-- Diagonal --
--------------
function Diagonal (A : Matrix) return Vector is
N : constant Natural := Natural'Min (A'Length (1), A'Length (2));
begin
return R : Vector (A'First (1) .. A'First (1) + N - 1) do
for J in 0 .. N - 1 loop
R (R'First + J) := A (A'First (1) + J, A'First (2) + J);
end loop;
end return;
end Diagonal;
--------------------------
-- Square_Matrix_Length --
--------------------------
function Square_Matrix_Length (A : Matrix) return Natural is
begin
if A'Length (1) /= A'Length (2) then
raise Constraint_Error with "matrix is not square";
else
return A'Length (1);
end if;
end Square_Matrix_Length;
---------------------
-- Check_Unit_Last --
---------------------
function Check_Unit_Last
(Index : Integer;
Order : Positive;
First : Integer) return Integer
is
begin
-- Order the tests carefully to avoid overflow
if Index < First
or else First > Integer'Last - Order + 1
or else Index > First + (Order - 1)
then
raise Constraint_Error;
end if;
return First + (Order - 1);
end Check_Unit_Last;
---------------------
-- Back_Substitute --
---------------------
procedure Back_Substitute (M, N : in out Matrix) is
pragma Assert (M'First (1) = N'First (1)
and then
M'Last (1) = N'Last (1));
procedure Sub_Row
(M : in out Matrix;
Target : Integer;
Source : Integer;
Factor : Scalar);
-- Elementary row operation that subtracts Factor * M (Source, <>) from
-- M (Target, <>)
-------------
-- Sub_Row --
-------------
procedure Sub_Row
(M : in out Matrix;
Target : Integer;
Source : Integer;
Factor : Scalar)
is
begin
for J in M'Range (2) loop
M (Target, J) := M (Target, J) - Factor * M (Source, J);
end loop;
end Sub_Row;
-- Local declarations
Max_Col : Integer := M'Last (2);
-- Start of processing for Back_Substitute
begin
Do_Rows : for Row in reverse M'Range (1) loop
Find_Non_Zero : for Col in reverse M'First (2) .. Max_Col loop
if Is_Non_Zero (M (Row, Col)) then
-- Found first non-zero element, so subtract a multiple of this
-- element from all higher rows, to reduce all other elements
-- in this column to zero.
declare
-- We can't use a for loop, as we'd need to iterate to
-- Row - 1, but that expression will overflow if M'First
-- equals Integer'First, which is true for aggregates
-- without explicit bounds..
J : Integer := M'First (1);
begin
while J < Row loop
Sub_Row (N, J, Row, (M (J, Col) / M (Row, Col)));
Sub_Row (M, J, Row, (M (J, Col) / M (Row, Col)));
J := J + 1;
end loop;
end;
-- Avoid potential overflow in the subtraction below
exit Do_Rows when Col = M'First (2);
Max_Col := Col - 1;
exit Find_Non_Zero;
end if;
end loop Find_Non_Zero;
end loop Do_Rows;
end Back_Substitute;
-----------------------
-- Forward_Eliminate --
-----------------------
procedure Forward_Eliminate
(M : in out Matrix;
N : in out Matrix;
Det : out Scalar)
is
pragma Assert (M'First (1) = N'First (1)
and then
M'Last (1) = N'Last (1));
-- The following are variations of the elementary matrix row operations:
-- row switching, row multiplication and row addition. Because in this
-- algorithm the addition factor is always a negated value, we chose to
-- use row subtraction instead. Similarly, instead of multiplying by
-- a reciprocal, we divide.
procedure Sub_Row
(M : in out Matrix;
Target : Integer;
Source : Integer;
Factor : Scalar);
-- Subtrace Factor * M (Source, <>) from M (Target, <>)
procedure Divide_Row
(M, N : in out Matrix;
Row : Integer;
Scale : Scalar);
-- Divide M (Row) and N (Row) by Scale, and update Det
procedure Switch_Row
(M, N : in out Matrix;
Row_1 : Integer;
Row_2 : Integer);
-- Exchange M (Row_1) and N (Row_1) with M (Row_2) and N (Row_2),
-- negating Det in the process.
-------------
-- Sub_Row --
-------------
procedure Sub_Row
(M : in out Matrix;
Target : Integer;
Source : Integer;
Factor : Scalar)
is
begin
for J in M'Range (2) loop
M (Target, J) := M (Target, J) - Factor * M (Source, J);
end loop;
end Sub_Row;
----------------
-- Divide_Row --
----------------
procedure Divide_Row
(M, N : in out Matrix;
Row : Integer;
Scale : Scalar)
is
begin
Det := Det * Scale;
for J in M'Range (2) loop
M (Row, J) := M (Row, J) / Scale;
end loop;
for J in N'Range (2) loop
N (Row - M'First (1) + N'First (1), J) :=
N (Row - M'First (1) + N'First (1), J) / Scale;
end loop;
end Divide_Row;
----------------
-- Switch_Row --
----------------
procedure Switch_Row
(M, N : in out Matrix;
Row_1 : Integer;
Row_2 : Integer)
is
procedure Swap (X, Y : in out Scalar);
-- Exchange the values of X and Y
----------
-- Swap --
----------
procedure Swap (X, Y : in out Scalar) is
T : constant Scalar := X;
begin
X := Y;
Y := T;
end Swap;
-- Start of processing for Switch_Row
begin
if Row_1 /= Row_2 then
Det := Zero - Det;
for J in M'Range (2) loop
Swap (M (Row_1, J), M (Row_2, J));
end loop;
for J in N'Range (2) loop
Swap (N (Row_1 - M'First (1) + N'First (1), J),
N (Row_2 - M'First (1) + N'First (1), J));
end loop;
end if;
end Switch_Row;
-- Local declarations
Row : Integer := M'First (1);
-- Start of processing for Forward_Eliminate
begin
Det := One;
for J in M'Range (2) loop
declare
Max_Row : Integer := Row;
Max_Abs : Real'Base := 0.0;
begin
-- Find best pivot in column J, starting in row Row
for K in Row .. M'Last (1) loop
declare
New_Abs : constant Real'Base := abs M (K, J);
begin
if Max_Abs < New_Abs then
Max_Abs := New_Abs;
Max_Row := K;
end if;
end;
end loop;
if Max_Abs > 0.0 then
Switch_Row (M, N, Row, Max_Row);
-- The temporaries below are necessary to force a copy of the
-- value and avoid improper aliasing.
declare
Scale : constant Scalar := M (Row, J);
begin
Divide_Row (M, N, Row, Scale);
end;
for U in Row + 1 .. M'Last (1) loop
declare
Factor : constant Scalar := M (U, J);
begin
Sub_Row (N, U, Row, Factor);
Sub_Row (M, U, Row, Factor);
end;
end loop;
exit when Row >= M'Last (1);
Row := Row + 1;
else
-- Set zero (note that we do not have literals)
Det := Zero;
end if;
end;
end loop;
end Forward_Eliminate;
-------------------
-- Inner_Product --
-------------------
function Inner_Product
(Left : Left_Vector;
Right : Right_Vector) return Result_Scalar
is
R : Result_Scalar := Zero;
begin
if Left'Length /= Right'Length then
raise Constraint_Error with
"vectors are of different length in inner product";
end if;
for J in Left'Range loop
R := R + Left (J) * Right (J - Left'First + Right'First);
end loop;
return R;
end Inner_Product;
-------------
-- L2_Norm --
-------------
function L2_Norm (X : X_Vector) return Result_Real'Base is
Sum : Result_Real'Base := 0.0;
begin
for J in X'Range loop
Sum := Sum + Result_Real'Base (abs X (J))**2;
end loop;
return Sqrt (Sum);
end L2_Norm;
----------------------------------
-- Matrix_Elementwise_Operation --
----------------------------------
function Matrix_Elementwise_Operation (X : X_Matrix) return Result_Matrix is
begin
return R : Result_Matrix (X'Range (1), X'Range (2)) do
for J in R'Range (1) loop
for K in R'Range (2) loop
R (J, K) := Operation (X (J, K));
end loop;
end loop;
end return;
end Matrix_Elementwise_Operation;
----------------------------------
-- Vector_Elementwise_Operation --
----------------------------------
function Vector_Elementwise_Operation (X : X_Vector) return Result_Vector is
begin
return R : Result_Vector (X'Range) do
for J in R'Range loop
R (J) := Operation (X (J));
end loop;
end return;
end Vector_Elementwise_Operation;
-----------------------------------------
-- Matrix_Matrix_Elementwise_Operation --
-----------------------------------------
function Matrix_Matrix_Elementwise_Operation
(Left : Left_Matrix;
Right : Right_Matrix) return Result_Matrix
is
begin
return R : Result_Matrix (Left'Range (1), Left'Range (2)) do
if Left'Length (1) /= Right'Length (1)
or else
Left'Length (2) /= Right'Length (2)
then
raise Constraint_Error with
"matrices are of different dimension in elementwise operation";
end if;
for J in R'Range (1) loop
for K in R'Range (2) loop
R (J, K) :=
Operation
(Left (J, K),
Right
(J - R'First (1) + Right'First (1),
K - R'First (2) + Right'First (2)));
end loop;
end loop;
end return;
end Matrix_Matrix_Elementwise_Operation;
------------------------------------------------
-- Matrix_Matrix_Scalar_Elementwise_Operation --
------------------------------------------------
function Matrix_Matrix_Scalar_Elementwise_Operation
(X : X_Matrix;
Y : Y_Matrix;
Z : Z_Scalar) return Result_Matrix
is
begin
return R : Result_Matrix (X'Range (1), X'Range (2)) do
if X'Length (1) /= Y'Length (1)
or else
X'Length (2) /= Y'Length (2)
then
raise Constraint_Error with
"matrices are of different dimension in elementwise operation";
end if;
for J in R'Range (1) loop
for K in R'Range (2) loop
R (J, K) :=
Operation
(X (J, K),
Y (J - R'First (1) + Y'First (1),
K - R'First (2) + Y'First (2)),
Z);
end loop;
end loop;
end return;
end Matrix_Matrix_Scalar_Elementwise_Operation;
-----------------------------------------
-- Vector_Vector_Elementwise_Operation --
-----------------------------------------
function Vector_Vector_Elementwise_Operation
(Left : Left_Vector;
Right : Right_Vector) return Result_Vector
is
begin
return R : Result_Vector (Left'Range) do
if Left'Length /= Right'Length then
raise Constraint_Error with
"vectors are of different length in elementwise operation";
end if;
for J in R'Range loop
R (J) := Operation (Left (J), Right (J - R'First + Right'First));
end loop;
end return;
end Vector_Vector_Elementwise_Operation;
------------------------------------------------
-- Vector_Vector_Scalar_Elementwise_Operation --
------------------------------------------------
function Vector_Vector_Scalar_Elementwise_Operation
(X : X_Vector;
Y : Y_Vector;
Z : Z_Scalar) return Result_Vector is
begin
return R : Result_Vector (X'Range) do
if X'Length /= Y'Length then
raise Constraint_Error with
"vectors are of different length in elementwise operation";
end if;
for J in R'Range loop
R (J) := Operation (X (J), Y (J - X'First + Y'First), Z);
end loop;
end return;
end Vector_Vector_Scalar_Elementwise_Operation;
-----------------------------------------
-- Matrix_Scalar_Elementwise_Operation --
-----------------------------------------
function Matrix_Scalar_Elementwise_Operation
(Left : Left_Matrix;
Right : Right_Scalar) return Result_Matrix
is
begin
return R : Result_Matrix (Left'Range (1), Left'Range (2)) do
for J in R'Range (1) loop
for K in R'Range (2) loop
R (J, K) := Operation (Left (J, K), Right);
end loop;
end loop;
end return;
end Matrix_Scalar_Elementwise_Operation;
-----------------------------------------
-- Vector_Scalar_Elementwise_Operation --
-----------------------------------------
function Vector_Scalar_Elementwise_Operation
(Left : Left_Vector;
Right : Right_Scalar) return Result_Vector
is
begin
return R : Result_Vector (Left'Range) do
for J in R'Range loop
R (J) := Operation (Left (J), Right);
end loop;
end return;
end Vector_Scalar_Elementwise_Operation;
-----------------------------------------
-- Scalar_Matrix_Elementwise_Operation --
-----------------------------------------
function Scalar_Matrix_Elementwise_Operation
(Left : Left_Scalar;
Right : Right_Matrix) return Result_Matrix
is
begin
return R : Result_Matrix (Right'Range (1), Right'Range (2)) do
for J in R'Range (1) loop
for K in R'Range (2) loop
R (J, K) := Operation (Left, Right (J, K));
end loop;
end loop;
end return;
end Scalar_Matrix_Elementwise_Operation;
-----------------------------------------
-- Scalar_Vector_Elementwise_Operation --
-----------------------------------------
function Scalar_Vector_Elementwise_Operation
(Left : Left_Scalar;
Right : Right_Vector) return Result_Vector
is
begin
return R : Result_Vector (Right'Range) do
for J in R'Range loop
R (J) := Operation (Left, Right (J));
end loop;
end return;
end Scalar_Vector_Elementwise_Operation;
----------
-- Sqrt --
----------
function Sqrt (X : Real'Base) return Real'Base is
Root, Next : Real'Base;
begin
-- Be defensive: any comparisons with NaN values will yield False.
if not (X > 0.0) then
if X = 0.0 then
return X;
else
raise Argument_Error;
end if;
elsif X > Real'Base'Last then
-- X is infinity, which is its own square root
return X;
end if;
-- Compute an initial estimate based on:
-- X = M * R**E and Sqrt (X) = Sqrt (M) * R**(E / 2.0),
-- where M is the mantissa, R is the radix and E the exponent.
-- By ignoring the mantissa and ignoring the case of an odd
-- exponent, we get a final error that is at most R. In other words,
-- the result has about a single bit precision.
Root := Real'Base (Real'Machine_Radix) ** (Real'Exponent (X) / 2);
-- Because of the poor initial estimate, use the Babylonian method of
-- computing the square root, as it is stable for all inputs. Every step
-- will roughly double the precision of the result. Just a few steps
-- suffice in most cases. Eight iterations should give about 2**8 bits
-- of precision.
for J in 1 .. 8 loop
Next := (Root + X / Root) / 2.0;
exit when Root = Next;
Root := Next;
end loop;
return Root;
end Sqrt;
---------------------------
-- Matrix_Matrix_Product --
---------------------------
function Matrix_Matrix_Product
(Left : Left_Matrix;
Right : Right_Matrix) return Result_Matrix
is
begin
return R : Result_Matrix (Left'Range (1), Right'Range (2)) do
if Left'Length (2) /= Right'Length (1) then
raise Constraint_Error with
"incompatible dimensions in matrix multiplication";
end if;
for J in R'Range (1) loop
for K in R'Range (2) loop
declare
S : Result_Scalar := Zero;
begin
for M in Left'Range (2) loop
S := S + Left (J, M) *
Right
(M - Left'First (2) + Right'First (1), K);
end loop;
R (J, K) := S;
end;
end loop;
end loop;
end return;
end Matrix_Matrix_Product;
----------------------------
-- Matrix_Vector_Solution --
----------------------------
function Matrix_Vector_Solution (A : Matrix; X : Vector) return Vector is
N : constant Natural := A'Length (1);
MA : Matrix := A;
MX : Matrix (A'Range (1), 1 .. 1);
R : Vector (A'Range (2));
Det : Scalar;
begin
if A'Length (2) /= N then
raise Constraint_Error with "matrix is not square";
end if;
if X'Length /= N then
raise Constraint_Error with "incompatible vector length";
end if;
for J in 0 .. MX'Length (1) - 1 loop
MX (MX'First (1) + J, 1) := X (X'First + J);
end loop;
Forward_Eliminate (MA, MX, Det);
Back_Substitute (MA, MX);
for J in 0 .. R'Length - 1 loop
R (R'First + J) := MX (MX'First (1) + J, 1);
end loop;
return R;
end Matrix_Vector_Solution;
----------------------------
-- Matrix_Matrix_Solution --
----------------------------
function Matrix_Matrix_Solution (A, X : Matrix) return Matrix is
N : constant Natural := A'Length (1);
MA : Matrix (A'Range (2), A'Range (2));
MB : Matrix (A'Range (2), X'Range (2));
Det : Scalar;
begin
if A'Length (2) /= N then
raise Constraint_Error with "matrix is not square";
end if;
if X'Length (1) /= N then
raise Constraint_Error with "matrices have unequal number of rows";
end if;
for J in 0 .. A'Length (1) - 1 loop
for K in MA'Range (2) loop
MA (MA'First (1) + J, K) := A (A'First (1) + J, K);
end loop;
for K in MB'Range (2) loop
MB (MB'First (1) + J, K) := X (X'First (1) + J, K);
end loop;
end loop;
Forward_Eliminate (MA, MB, Det);
Back_Substitute (MA, MB);
return MB;
end Matrix_Matrix_Solution;
---------------------------
-- Matrix_Vector_Product --
---------------------------
function Matrix_Vector_Product
(Left : Matrix;
Right : Right_Vector) return Result_Vector
is
begin
return R : Result_Vector (Left'Range (1)) do
if Left'Length (2) /= Right'Length then
raise Constraint_Error with
"incompatible dimensions in matrix-vector multiplication";
end if;
for J in Left'Range (1) loop
declare
S : Result_Scalar := Zero;
begin
for K in Left'Range (2) loop
S := S + Left (J, K)
* Right (K - Left'First (2) + Right'First);
end loop;
R (J) := S;
end;
end loop;
end return;
end Matrix_Vector_Product;
-------------------
-- Outer_Product --
-------------------
function Outer_Product
(Left : Left_Vector;
Right : Right_Vector) return Matrix
is
begin
return R : Matrix (Left'Range, Right'Range) do
for J in R'Range (1) loop
for K in R'Range (2) loop
R (J, K) := Left (J) * Right (K);
end loop;
end loop;
end return;
end Outer_Product;
-----------------
-- Swap_Column --
-----------------
procedure Swap_Column (A : in out Matrix; Left, Right : Integer) is
Temp : Scalar;
begin
for J in A'Range (1) loop
Temp := A (J, Left);
A (J, Left) := A (J, Right);
A (J, Right) := Temp;
end loop;
end Swap_Column;
---------------
-- Transpose --
---------------
procedure Transpose (A : Matrix; R : out Matrix) is
begin
for J in R'Range (1) loop
for K in R'Range (2) loop
R (J, K) := A (K - R'First (2) + A'First (1),
J - R'First (1) + A'First (2));
end loop;
end loop;
end Transpose;
-------------------------------
-- Update_Matrix_With_Matrix --
-------------------------------
procedure Update_Matrix_With_Matrix (X : in out X_Matrix; Y : Y_Matrix) is
begin
if X'Length (1) /= Y'Length (1)
or else
X'Length (2) /= Y'Length (2)
then
raise Constraint_Error with
"matrices are of different dimension in update operation";
end if;
for J in X'Range (1) loop
for K in X'Range (2) loop
Update (X (J, K), Y (J - X'First (1) + Y'First (1),
K - X'First (2) + Y'First (2)));
end loop;
end loop;
end Update_Matrix_With_Matrix;
-------------------------------
-- Update_Vector_With_Vector --
-------------------------------
procedure Update_Vector_With_Vector (X : in out X_Vector; Y : Y_Vector) is
begin
if X'Length /= Y'Length then
raise Constraint_Error with
"vectors are of different length in update operation";
end if;
for J in X'Range loop
Update (X (J), Y (J - X'First + Y'First));
end loop;
end Update_Vector_With_Vector;
-----------------
-- Unit_Matrix --
-----------------
function Unit_Matrix
(Order : Positive;
First_1 : Integer := 1;
First_2 : Integer := 1) return Matrix
is
begin
return R : Matrix (First_1 .. Check_Unit_Last (First_1, Order, First_1),
First_2 .. Check_Unit_Last (First_2, Order, First_2))
do
R := (others => (others => Zero));
for J in 0 .. Order - 1 loop
R (First_1 + J, First_2 + J) := One;
end loop;
end return;
end Unit_Matrix;
-----------------
-- Unit_Vector --
-----------------
function Unit_Vector
(Index : Integer;
Order : Positive;
First : Integer := 1) return Vector
is
begin
return R : Vector (First .. Check_Unit_Last (Index, Order, First)) do
R := (others => Zero);
R (Index) := One;
end return;
end Unit_Vector;
---------------------------
-- Vector_Matrix_Product --
---------------------------
function Vector_Matrix_Product
(Left : Left_Vector;
Right : Matrix) return Result_Vector
is
begin
return R : Result_Vector (Right'Range (2)) do
if Left'Length /= Right'Length (1) then
raise Constraint_Error with
"incompatible dimensions in vector-matrix multiplication";
end if;
for J in Right'Range (2) loop
declare
S : Result_Scalar := Zero;
begin
for K in Right'Range (1) loop
S := S + Left (K - Right'First (1)
+ Left'First) * Right (K, J);
end loop;
R (J) := S;
end;
end loop;
end return;
end Vector_Matrix_Product;
end System.Generic_Array_Operations;