Provided by: afnix_3.8.0-1_amd64 
NAME
mth - standard math module
STANDARD MATH MODULE
The Standard Mathematical module is an original implementation of various mathematical
facilities. The module can be divided into several catgeories which include convenient
functions, linear algebra and real analysis.
Random number
The math module provides various functions that generate random numbers in different
formats.
Function Description
get-random-integer return a random integer number
get-random-real return a random real number between 0.0 and 1.0
get-random-relatif return a random relatif number
get-random-prime return a random probable prime relatif number
The numbers are generated with the help of the system random generator. Such generator is
machine dependant and results can vary from one machine to another.
Primality testing
The math module provides various predicates that test a number for a primality condition.
Most of these predicates are intricate and are normally not used except the prime-
probable-p predicate.
Predicate Description
fermat-p Fermat test predicate
miller-rabin-p Miller-Rabin test predicate
prime-probable-p general purpose prime probable test
get-random-prime return a random probable prime relatif number
The fermat-p and miller-rabin-p predicates return true if the primality condition is
verified. These predicate operate with a base number. The prime number to test is the
second argument.
Fermat primality testing
The fermat-p predicate is a simple primality test based on the "little Fermat theorem". A
base number greater than 1 and less than the number to test must be given to run the test.
afnix:mth:fermat-p 2 7
In the preceeding example, the number 7 is tested, and the fermat-p predicate returns
true. If a number is prime, it is guaranted to pass the test. The oppositte is not true.
For example, 561 is a composite number, but the Fermat test will succeed with the base 2.
Numbers that successfully pass the Fermat test but which are composite are called
Carmichael numbers. For those numbers, a better test needs to be employed, such like the
Miller-Rabin test.
Miller-Rabin primality testing
The miller-rabin-p predicate is a complex primality test that is more efficient in
detecting prime number at the cost of a longer computation. A base number greater than 1
and less than the number to test must be given to run the test.
afnix:mth:miller-rabin-p 2 561
In the preceeding example, the number 561, which is a Carmichael number, is tested, and
the miller-rabin-p predicate returns false. The probability that a number is prime depends
on the number of times the test is ran. Numerous studies have been made to determine the
optimal number of passes that are needed to declare that a number is prime with a good
probability. The prime-probable-p predicate takes care to run the optimal number of
passes.
General primality testing
The prime-probable-p predicate is a complex primality test that incorporates various
primality tests. To make the story short, the prime candidate is first tested with a
series of small prime numbers. Then a fast Fermat test is executed. Finally, a series of
Miller-Rabin tests are executed. Unlike the other primality tests, this predicate operates
with a number only and optionally, the number of test passes. This predicate is the
recommended test for the folks who want to test their numbers.
afnix:mth:prime-probable-p 17863
Linear algebra
The math module provides an original and extensive support for linear and non linear
algebra. This includes vector, matrix and solvers. Complex methods for non linear
operations are also integrated tightly in this module.
Real vector
The math module provides the Rvector object which implements the real vector interface
Rvi. Such interface provides numerous operators and methods for manipulating vectors as
traditionnaly found in linear algebra packages.
Operator Description
== compare two vectors for equality
!= compare two vectors for difference
?= compare two vectors upto a precision
+= add a scalar or vector to the vector
-= substract a scalar or vector to the vector
*= multiply a scalar or vector to the vector
/= divide a vector by a scalar
Method Description
set set a vector component by index
get get a vector component by index
clear clear a vector
reset reset a vector
get-size get the vector dimension
dot compute the dot product with another vector
norm compute the vector norm
Creating a vector
A vector is always created by size. A null size is perfectly valid. When a vector is
created, it can be filled by setting the components by index.
# create a simple vector
const rv (afnix:mth:Rvector 3)
# set the components by index
rv:set 0 0.0
rv:set 1 3.0
rv:set 2 4.0
Real matrix
The math module provides the Rmatrix object which implements the real matrix interface
Rmi. This interface is designed to operate with the vector interface and can handle sparse
or full matrix.
Operator Description
== compare two matrices for equality
!= compare two matrices for difference
?= compare two matrices upto a precision
Method Description
set set a matrix component by index
get get a matrix component by index
clear clear a vector
get-row-size get the matrix row dimension
get-col-size get the matrix column dimension
norm compute the matrix norm
STANDARD MATH REFERENCE
Rvi
The Rvi class an abstract class that models the behavior of a real based vector. The class
defines the vector length as well as the accessor and mutator methods.
Predicate
rvi-p
Inheritance
Serial
Operators
== -> Boolean (Vector)
The == operator returns true if the calling object is equal to the vector argument.
!= -> Boolean (Vector)
The == operator returns true if the calling object is not equal to the vector
argument.
?= -> Boolean (Vector)
The ?= operator returns true if the calling object is equal to the vector argument
upto a certain precision.
+= -> Vector (Real|Vector)
The += operator returns the calling vector by adding the argument object. In the
first form, the real argument is added to all vector components. In the second
form, the vector components are added one by one.
-= -> Vector (Real|Vector)
The -= operator returns the calling vector by substracting the argument object. In
the first form, the real argument is substracted to all vector components. In the
second form, the vector components are substracted one by one.
*= -> Vector (Real|Vector)
The *= operator returns the calling vector by multiplying the argument object. In
the first form, the real argument is multiplied to all vector components. In the
second form, the vector components are multiplied one by one.
/= -> Vector (Real)
The /= operator returns the calling vector by dividing the argument object. The
vector components are divided by the real argument.
Methods
set -> None (Integer Real)
The set method sets a vector component by index.
get -> Real (Integer)
The get method gets a vector component by index.
clear -> None (None)
The clear method clears a vector. The dimension is not changed.
reset -> None (None)
The reset method resets a vector. The size is set to 0.
get-size -> Real ( None)
The get-size method returns the vector dimension.
dot -> Real (Vector)
The dot method computes the dot product with the vector argument.
norm -> Real (None)
The norm method computes the vector norm.
permutate -> Vector (Cpi)
The permutate method permutates the vector components with the help of a
combinatoric permutation object.
reverse -> Vector (Cpi)
The reverse method reverse (permutate) the vector components with the help of a
combinatoric permutation object.
Rvector
The Rvector class is the default implementation of the real vector interface.
Predicate
r-vector-p
Inheritance
Rvi
Constructors
Rvector (None)
The Rvector constructor creates a default null real vector.
Rvector (Integer)
The Rvector constructor creates a real vector those dimension is given as the
calling argument.
Functions
get-random-integer -> Integer (none|Integer)
The get-random-integer function returns a random integer number. Without argument,
the integer range is machine dependent. With one integer argument, the resulting
integer number is less than the specified maximum bound.
get-random-real -> Real (none|Boolean)
The get-random-real function returns a random real number between 0.0 and 1.0. In
the first form, without argument, the random number is between 0.0 and 1.0 with 1.0
included. In the second form, the boolean flag controls whether or not the 1.0 is
included in the result. If the argument is false, the 1.0 value is guaranted to be
excluded from the result. If the argument is true, the 1.0 is a possible random
real value. Calling this function with the argument set to true is equivalent to
the first form without argument.
get-random-relatif -> Relatif (Integer|Integer Boolean)
The get-random-relatif function returns a n bits random positive relatif number. In
the first form, the argument is the number of bits. In the second form, the first
argument is the number of bits and the second argument, when true produce an odd
number, or an even number when false.
get-random-prime -> Relatif (Integer)
The get-random-prime function returns a n bits random positive relatif probable
prime number. The argument is the number of bits. The prime number is generated by
using the Miller-Rabin primality test. As such, the returned number is declared
probable prime. The more bits needed, the longer it takes to generate such number.
get-random-bitset -> Bitset (Integer)
The get-random-bitset function returns a n bits random bitset. The argument is the
number of bits.
fermat-p -> Boolean (Integer|Relatif Integer|Relatif)
The fermat-p predicate returns true if the little fermat theorem is validated. The
first argument is the base number and the second argument is the prime number to
validate.
miller-rabin-p -> Boolean (Integer|Relatif Integer|Relatif)
The miller-rabin-p predicate returns true if the Miller-Rabin test is validated.
The first argument is the base number and the second argument is the prime number
to validate.
prime-probable-p -> Boolean (Integer|Relatif [Integer])
The prime-probable-p predicate returns true if the argument is a probable prime. In
the first form, only an integer or relatif number is required. In the second form,
the number of iterations is specified as the second argument. By default, the
number of iterations is specified to 56.