Please note that the recommended version of Scilab is 6.1.0. This page might be outdated.

See the recommended documentation of this function

# prod

product of array elements

### Calling Sequence

y=prod(x) y=prod(x,orientation) y=prod(x,outtype) y=prod(x,orientation,outtype)

### Arguments

- x
an array of reals, complex, booleans, polynomials or rational fractions.

- orientation
it can be either

a string with possible values

`"*"`

,`"r"`

,`"c"`

or`"m"`

a number with positive integer value

- outtype
a string with possible values

`"native"`

or`"double"`

.- y
scalar or array

### Description

For an array `x`

,
`y=prod(x)`

returns in the scalar `y`

the
product of all the elements of `x`

.

`y=prod(x,orientation)`

returns in
`y`

the product of `x`

along the
dimension given by `orientation`

:

if

`orientation`

is equal to 1 or "r" thenor

if

`orientation`

is equal to 2 or "c" then:or

if

`orientation`

is equal to n then`y=prod(x,"*")`

is equivalent to`y=prod(x)`

`y=prod(x,"m")`

is equivalent to`y=prod(x,orientation)`

where`orientation`

is the index of the first dimension of`x`

that is greater than 1.

The `outtype`

argument rules the way the summation is done:

For arrays of floats, of polynomials, of rational fractions, the evaluation is always done using floating points computations. The

`"double"`

or`"native"`

options are equivalent.For arrays of integers,

if

`outtype="native"`

the evaluation is done using integer computations (modulo 2^b, where b is the number of bits used),if

`outtype="double"`

the evaluation is done using floating point computations.The default value is

`outtype="native"`

.For arrays of booleans,

if

`outtype="native"`

the evaluation is done using boolean computations ( + is replaced by |),if

`outtype="double"`

the evaluation is done using floating point computations (%t values are replaced by 1 and %f values by 0).The default value is

`outtype="double"`

. This option is used for Matlab compatibility.

### Remark

This function applies, with identical rules to sparse matrices and hypermatrices.

## Comments

Add a comment:Please login to comment this page.