dnanminabs
Calculate the minimum absolute value of a double-precision floating-point strided array, ignoring
NaNvalues.
Usage
var dnanminabs = require( '@stdlib/stats/base/dnanminabs' );
dnanminabs( N, x, strideX )
Computes the minimum absolute value of a double-precision floating-point strided array x, ignoring NaN values.
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var v = dnanminabs( x.length, x, 1 );
// returns 1.0
The function has the following parameters:
- N: number of indexed elements.
- x: input Float64Array.
- strideX: stride length for x.
The N and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the minimum absolute value of every other element in x,
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, NaN, NaN ] );
var v = dnanminabs( 4, x, 2 );
// returns 1.0
Note that indexing is relative to the first index. To introduce an offset, use typed array views.
var Float64Array = require( '@stdlib/array/float64' );
var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var v = dnanminabs( 4, x1, 2 );
// returns 1.0
dnanminabs.ndarray( N, x, strideX, offsetX )
Computes the minimum absolute value of a double-precision floating-point strided array, ignoring NaN values and using alternative indexing semantics.
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var v = dnanminabs.ndarray( x.length, x, 1, 0 );
// returns 1.0
The function has the following additional parameters:
- offsetX: starting index for x.
While typed array views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the minimum absolute value for every other element in x starting from the second element
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
var v = dnanminabs.ndarray( 4, x, 2, 1 );
// returns 1.0
Notes
- If N <= 0, both functions returnNaN.
Examples
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var Float64Array = require( '@stdlib/array/float64' );
var dnanminabs = require( '@stdlib/stats/base/dnanminabs' );
var x;
var i;
x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
    if ( randu() < 0.2 ) {
        x[ i ] = NaN;
    } else {
        x[ i ] = round( (randu()*100.0) - 50.0 );
    }
}
console.log( x );
var v = dnanminabs( x.length, x, 1 );
console.log( v );
C APIs
Usage
#include "stdlib/stats/base/dnanminabs.h"
stdlib_strided_dnanminabs( N, *X, strideX )
Calculate the minimum absolute value of a double-precision floating-point strided array, ignoring NaN values.
const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 };
double v = stdlib_strided_dnanminabs( 4, x, 1 );
// returns 1.0
The function accepts the following arguments:
- N: [in] CBLAS_INTnumber of indexed elements.
- X: [in] double*input array.
- strideX: [in] CBLAS_INTstride length forX.
double stdlib_strided_dnanminabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
stdlib_strided_dnanminabs_ndarray( N, *X, strideX, offsetX )
Computes the minimum absolute value of a double-precision floating-point strided array, ignoring NaN values and using alternative indexing semantics.
const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 };
double v = stdlib_strided_dnanminabs_ndarray( 4, x, 1, 0 );
// returns 1.0
The function accepts the following arguments:
- N: [in] CBLAS_INTnumber of indexed elements.
- X: [in] double*input array.
- strideX: [in] CBLAS_INTstride length forX.
- offsetX: [in] CBLAS_INTstarting index forX.
double stdlib_strided_dnanminabs_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
Examples
#include "stdlib/stats/base/dnanminabs.h"
#include <stdio.h>
int main( void ) {
    // Create a strided array:
    const double x[] = { 1.0, -2.0, -3.0, 4.0, -5.0, -6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 };
    // Specify the number of elements:
    const int N = 5;
    // Specify the stride length:
    const int strideX = 2;
    // Compute the minimum absolute value:
    double v = stdlib_strided_dnanminabs( N, x, strideX );
    // Print the result:
    printf( "minabs: %lf\n", v );
}