A Tour of NTL: Examples: Vectors and Matrices

The following routine sums up the numbers in a vector of ZZ's.

#include <NTL/vec_ZZ.h>

NTL_CLIENT

ZZ sum(const vec_ZZ& v)
{
   ZZ acc;

   acc = 0;

   for (long i = 0; i < v.length(); i++)
      acc += v[i];

   return acc;
}

The class vec_ZZ is a dynamic-length array of ZZs; more generally, NTL provides template-like macros to create dynamic-length vectors over any type T. By convention, NTL names these vec_T. The reason that macros are used instead of true templates is simple: at the present time, compiler support for templates is not entirely satisfactory, and their use would make NTL much more difficult to port. At some point in the future, a template-version of NTL may be made available.

Vectors in NTL are indexed from 0, but in many situations it is convenient or more natural to index from 1. The generic vector class allows for this; the above example could be written as follows.

#include <NTL/vec_ZZ.h>

NTL_CLIENT

ZZ sum(ZZ& s, const vec_ZZ& v)
{
   ZZ acc;

   acc = 0;

   for (long i = 1; i <= v.length(); i++)
      acc += v(i); 

   return acc;
}

Note that by default, NTL does not perform range checks on vector indices. However, there is a compile-time flag that activates range checking. Therefore, it is good practice to always assume that range checking may be activated, and to not access elements that are out of range.

The following example illustrates vector I/O, as well as changing the length of a vector. This program reads a vec_ZZ, and then creates and prints a "palindrome".

#include <NTL/vec_ZZ.h>

NTL_CLIENT

int main()
{
   vec_ZZ v;
   cin >> v;

   long n = v.length();
   v.SetLength(2*n);

   long i;
   for (i = 0 ; i < n; i++)
      v[n+i] = v[n-1-i];

   cout << v << "\n";
}

Notice that changing the length of a vector does not change its contents.

When we compile and run this program, if we type in

   [1 -2 3]

   [1 -2 3 3 -2 1]

NTL pre-defines a number of vector types. In addition, you can create your own. See vector.txt for complete details of NTL's generic vector mechanism. Also see vec_ZZ.txt for complete details on the arithmetic operations for vec_ZZs provided by NTL.

There is also basic support for matrices in NTL. In general, the class mat_T is a special kind of vec_vec_T, where each row is a vector of the same length. Row i of matrix M can be accessed as M[i] (indexing from 0) or as M(i) (indexing from 1). Column j of row i can be accessed as M[i][j] or M(i)(j); for notational convenience, the latter is equivalent to M(i,j).

Here is a matrix multiplication routine, which in fact is already provided by NTL.

#include <NTL/mat_ZZ.h>

NTL_CLIENT

void mul(mat_ZZ& X, const mat_ZZ& A, const mat_ZZ& B)
{
   long n = A.NumRows();
   long l = A.NumCols();
   long m = B.NumCols();

   if (l != B.NumRows())
      Error("matrix mul: dimension mismatch");

   X.SetDims(n, m); // make X have n rows and m columns

   long i, j, k;
   ZZ acc, tmp;

   for (i = 1; i <= n; i++) {
      for (j = 1; j <= m; j++) {
         acc = 0;
         for(k = 1; k <= l; k++) {
            mul(tmp, A(i,k), B(k,j));
            add(acc, acc, tmp);
         }
         X(i,j) = acc;
      }
   }
}

In case of a dimension mismatch, the routine calls the Error function, which is a part of NTL and which simply prints the message and aborts. That is generally how NTL deals with errors. Currently, NTL makes no use of exceptions (for the same reason it does not use templates--see above), but a future version may incorporate them.

This routine will not work properly if X aliases A or B. The actual matrix multiplication routine in NTL takes care of this. In fact, all of NTL's routines allow outputs to alias inputs.

To call the multiplication routine, one can write

   mul(X, A, B);

   X = A * B;

NTL provides several matrix types. See matrix.txt for complete details on NTL's generic matrix mechanism. Also see mat_ZZ.txt for complete details on the arithmetic operations for mat_ZZs provideed by NTL (including basic linear algebra). Also see LLL.txt for details on routines for lattice basis reduction (as well as routines for finding the kernel and image of a matrix).

One thing you may have noticed by now is that NTL code generally avoids the type int, preferring instead to use long. This seems to go against what most "style" books preach, but nevertheless seems to make the most sense in today's world. Although int was originally meant to represent the "natural" word size, this seems to no longer be the case. On 32-bit machines, int and long are the same, but on 64-bit machines, they are often different, with int's having 32 bits and long's having 64 bits. Indeed, there is a standard, called "LP64", which is being adopted by all Unix-like systems, and which specifies that on 64-bit machines, int's have 32 bits, and long's and pointers have 64 bits. Moreover, on such 64-bit machines, the "natural" word size is usually 64-bits; indeed, it is often more expensive to manipulate 32-bit integers. Thus, for simplicity, efficiency, and safety, NTL uses long for all integer values. If you are used to writing int all the time, it takes a little while to get used to this.