From the Octave command-line run:

pkg install 'https://github.com/gnu-octave/apa/releases/download/v1.0.0/apa-1.0.0.zip'
pkg load apa
pkg test apa

From the Matlab command-line run (also works for Octave):

urlwrite ('https://github.com/gnu-octave/apa/releases/download/v1.0.0/apa-1.0.0.zip', ...
          'apa-1.0.0.zip');
unzip ('apa-1.0.0.zip');
cd (fullfile ('apa-1.0.0', 'inst'))
install_apa
test_apa

The high-level MPFR interface is given through the @mpfr_t class. A variable of that type "behaves" like a "normal" built-in Octave/Matlab data type.

op1 = mpfr_t (eye (3) * 4);

rop = op1 + 1

rop =

   5   1   1
   1   5   1
   1   1   5

However, you can adjust the binary precision.

The default Octave/Matlab data type (double) has a precision of 53 binary digits. Thus the following calculation exceeds the given precision:

format long
too_small = (2 ^ (-60))
A = ones (3);
A(3,3) = A(3,3) + too_small

too_small = 8.673617379884035e-19
A =

   1   1   1
   1   1   1
   1   1   1

B = A - ones (3)

B =

   0   0   0
   0   0   0
   0   0   0

The same calculation using APA and quadruple precision (113 binary digits):

A = mpfr_t (ones (3), 113);
A(3,3) = A(3,3) + too_small

A =

   1   1                                       1
   1   1                                       1
   1   1   1.00000000000000000086736173798840355

apa ('format.fmt', 'scientific')
apa ('format.base', 2)
B = A - ones (3)

B =

   0 * 2^(0)   0 * 2^(0)     0 * 2^(0)
   0 * 2^(0)   0 * 2^(0)     0 * 2^(0)
   0 * 2^(0)   0 * 2^(0)   1 * 2^(-60)

The high-level MPFR interface is the preferred choice for quick numerical experiments.

However, if performance is more critical, please use the low-level MPFR interface (explained below) and vectorization wherever possible.

Please note that an interface from an interpreted high-level programming language like Octave/Matlab is most likely slower than a pre-compiled C program.

If performance is highly-critical, use this tool for initial experiments and translate the developed algorithm to native MPFR C-code.

For information how to compile/develop the interface, see doc/MEX_INTERFACE.md.

The low-level MPFR interface permits efficient access to almost all functions specified by MPFR 4.1.0 https://www.mpfr.org/mpfr-4.1.0/mpfr.html.

All supported functions are listed in the inst folder and can be called from Octave/Matlab like in the C programming language.

For example, the C function:

int mpfr_add (mpfr_t rop, mpfr_t op1, mpfr_t op2, mpfr_rnd_t rnd)

can be called from Octave/Matlab with scalar, vector, or matrix quantities:

% Reset to default APA output.
clear apa

% Prepare input and output variables.
rop = mpfr_t (zeros (3));
op1 = mpfr_t (eye (3) * 4);
op2 = mpfr_t (2);
rnd = mpfr_get_default_rounding_mode ();

% Call mpfr_add.  Note unlike Octave/Matlab the
% left-hand side does NOT contain the result.
ret = mpfr_add (rop, op1, op2, rnd);

rop  % Note rop vs. ret!

rop =

   6   2   2
   2   6   2
   2   2   6

In the low-level interface the type checks are stricter, but scalar and matrix quantities can still be mixed.

Another benefit of using the low-level MPFR interface is that in-place operations are permitted, which do not create new (temporary) variables:

ret = mpfr_add (op1, op1, op1, rnd);  % op1 += op1

• NVR workshop (Nov) 2021