/Volumes/unix-files/u/ntl-new/ntl-9.10.0dev/doc/mat_ZZ.cpp.html

/**************************************************************************\
MODULE: mat_ZZ
SUMMARY:
Defines the class mat_ZZ.
\**************************************************************************/
#include <NTL/matrix.h>
#include <NTL/vec_vec_ZZ.h>
typedef Mat<ZZ> mat_ZZ; // backward compatibility
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 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);