/**************************************************************************\

MODULE: mat_ZZ

SUMMARY:

Defines the class mat_ZZ.

\**************************************************************************/


#include <NTL/matrix.h>
#include <NTL/vec_vec_ZZ.h>

NTL_matrix_decl(ZZ,vec_ZZ,vec_vec_ZZ,mat_ZZ)
NTL_io_matrix_decl(ZZ,vec_ZZ,vec_vec_ZZ,mat_ZZ)
NTL_eq_matrix_decl(ZZ,vec_ZZ,vec_vec_ZZ,mat_ZZ)

void add(mat_ZZ& X, const mat_ZZ& A, const mat_ZZ& B); 
// X = A + B

void sub(mat_ZZ& X, const mat_ZZ& A, const mat_ZZ& B); 
// X = A - B

void negate(mat_ZZ& X, const mat_ZZ& A); 
// X = - A

void mul(mat_ZZ& X, const mat_ZZ& A, const mat_ZZ& B); 
// X = A * B

void mul(vec_ZZ& x, const mat_ZZ& A, const vec_ZZ& b); 
// x = A * b

void mul(vec_ZZ& x, const vec_ZZ& a, const mat_ZZ& B); 
// x = a * B

void mul(mat_ZZ& X, const mat_ZZ& A, const ZZ& b);
void mul(mat_ZZ& X, const mat_ZZ& A, long b);
// X = A * b

void mul(mat_ZZ& X, const ZZ& a, const mat_ZZ& B);
void mul(mat_ZZ& X, long a, const mat_ZZ& B);
// X = a * B



void determinant(ZZ& d, const mat_ZZ& A, long deterministic=0);
ZZ determinant(const mat_ZZ& a, long deterministic=0);
// d = determinant(A).  If !deterministic, a randomized strategy may
// be used that errs with probability at most 2^{-80}.



void solve(ZZ& d, vec_ZZ& x,
           const mat_ZZ& A, const vec_ZZ& b,
           long deterministic=0)
// computes d = determinant(A) and solves x*A = b*d if d != 0; A must
// be a square matrix and have compatible dimensions with b.  If
// !deterministic, the computation of d may use a randomized strategy
// that errs with probability 2^{-80}.



void solve1(ZZ& d, vec_ZZ& x, const mat_ZZ& A, const vec_ZZ& b);
// A must be a square matrix.
// If A is singular, this routine sets d = 0 and returns.
// Otherwise, it computes d, x such that x*A == b*d, 
// such that d > 0 and minimal.
// Note that d is a positive divisor of the determinant,
// and is not in general equal to the determinant.
// The routine is deterministic, and uses either a Hensel lifting
// strategy.

// For backward compatability, there is also a routine called
// HenselSolve1 that simply calls solve1.


void inv(ZZ& d, mat_ZZ& X, const mat_ZZ& A, long deterministic=0);
// computes d = determinant(A) and solves X*A = I*d if d != 0; A must
// be a square matrix.  If !deterministic, the computation of d may
// use a randomized strategy that errs with probability 2^{-80}.


// NOTE:  See LLL.txt for routines that compute the kernel and
// image of an integer matrix.

// NOTE: See HNF.txt for a routine that computes Hermite Normal Forms.

void sqr(mat_ZZ& X, const mat_ZZ& A);
mat_ZZ sqr(const mat_ZZ& A);
// X = A*A   

void inv(mat_ZZ& X, const mat_ZZ& A);
mat_ZZ inv(const mat_ZZ& A);
// X = A^{-1}; error is raised if |det(A)| != 1.

void power(mat_ZZ& X, const mat_ZZ& A, const ZZ& e);
mat_ZZ power(const mat_ZZ& A, const ZZ& e);

void power(mat_ZZ& X, const mat_ZZ& A, long e);
mat_ZZ power(const mat_ZZ& A, long e);
// X = A^e; e may be negative (in which case A must be nonsingular).



void ident(mat_ZZ& X, long n); 
mat_ZZ ident_mat_ZZ(long n); 
// X = n x n identity matrix

long IsIdent(const mat_ZZ& A, long n);
// test if A is the n x n identity matrix

void diag(mat_ZZ& X, long n, const ZZ& d);
mat_ZZ diag(long n, const ZZ& d);
// X = n x n diagonal matrix with d on diagonal

long IsDiag(const mat_ZZ& A, long n, const ZZ& d);
// test if X is an  n x n diagonal matrix with d on diagonal


void transpose(mat_ZZ& X, const mat_ZZ& A);
mat_ZZ transpose(const mat_ZZ& A);
// X = transpose of A


long CRT(mat_ZZ& a, ZZ& prod, const mat_zz_p& A);
// Incremental Chinese Remaindering: If p is the current zz_p modulus with
// (p, prod) = 1; Computes a' such that a' = a mod prod and a' = A mod p,
// with coefficients in the interval (-p*prod/2, p*prod/2]; 
// Sets a := a', prod := p*prod, and returns 1 if a's value changed.



// miscellaneous:

void clear(mat_ZZ& a);
// x = 0 (dimension unchanged)

long IsZero(const mat_ZZ& a);
// test if a is the zero matrix (any dimension)


// operator notation:

mat_ZZ operator+(const mat_ZZ& a, const mat_ZZ& b);
mat_ZZ operator-(const mat_ZZ& a, const mat_ZZ& b);
mat_ZZ operator*(const mat_ZZ& a, const mat_ZZ& b);

mat_ZZ operator-(const mat_ZZ& a);


// matrix/scalar multiplication:

mat_ZZ operator*(const mat_ZZ& a, const ZZ& b);
mat_ZZ operator*(const mat_ZZ& a, long b);

mat_ZZ operator*(const ZZ& a, const mat_ZZ& b);
mat_ZZ operator*(long a, const mat_ZZ& b);

// matrix/vector multiplication:

vec_ZZ operator*(const mat_ZZ& a, const vec_ZZ& b);

vec_ZZ operator*(const vec_ZZ& a, const mat_ZZ& b);



// assignment operator notation:

mat_ZZ& operator+=(mat_ZZ& x, const mat_ZZ& a);
mat_ZZ& operator-=(mat_ZZ& x, const mat_ZZ& a);
mat_ZZ& operator*=(mat_ZZ& x, const mat_ZZ& a);

mat_ZZ& operator*=(mat_ZZ& x, const ZZ& a);
mat_ZZ& operator*=(mat_ZZ& x, long a);

vec_ZZ& operator*=(vec_ZZ& x, const mat_ZZ& a);