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Compute the tangent of a double-precision floating-point number on
[-π/4, π/4].
npm install @stdlib/math-base-special-kernel-tanAlternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var kernelTan = require( '@stdlib/math-base-special-kernel-tan' );Computes the tangent of a double-precision floating-point number on [-π/4, π/4].
var out = kernelTan( 3.141592653589793/4.0, 0.0, 1 );
// returns ~1.0
out = kernelTan( 3.141592653589793/6.0, 0.0, 1 );
// returns ~0.577
out = kernelTan( 0.664, 5.288e-17, 1 );
// returns ~0.783If k = 1, the function returns tan(x+y). To return the negative inverse -1/tan(x+y), set k = -1.
var out = kernelTan( 3.141592653589793/4.0, 0.0, -1 );
// returns ~-1.0If either x or y is NaN, the function returns NaN.
var out = kernelTan( NaN, 0.0, 1 );
// returns NaN
out = kernelTan( 3.0, NaN, 1 );
// returns NaN
out = kernelTan( NaN, NaN, 1 );
// returns NaN-
For increased accuracy, the number for which the tangent should be evaluated can be supplied as a double-double number (i.e., a non-evaluated sum of two double-precision floating-point numbers
xandy). -
As components of a double-double number, the two double-precision floating-point numbers
xandymust satisfywhere
ulpstands for units in the last place.
var linspace = require( '@stdlib/array-base-linspace' );
var binomial = require( '@stdlib/random-base-binomial' ).factory;
var PI = require( '@stdlib/constants-float64-pi' );
var kernelTan = require( '@stdlib/math-base-special-kernel-tan' );
var x = linspace( -PI/4.0, PI/4.0, 100 );
var rbinom = binomial( 1, 0.5 );
var descr;
var i;
var k;
for ( i = 0; i < x.length; i++ ) {
k = rbinom();
descr = ( k === 1 ) ? 'tan(%d) = %d' : '-1/tan(%d) = %d';
console.log( descr, x[ i ], kernelTan( x[ i ], 0.0, k ) );
}#include "stdlib/math/base/special/kernel_tan.h"Computes the tangent of a double-precision floating-point number on [-π/4, π/4].
double out = stdlib_base_kernel_tan( 3.141592653589793/4.0, 0.0, 1 );
// returns ~1.0
out = stdlib_base_kernel_tan( 3.141592653589793/6.0, 0.0, 1 );
// returns ~0.577The function accepts the following arguments:
- x:
[in] doubleinput value (in radians, assumed to be bounded by~pi/4in magnitude). - y:
[in] doubletail ofx. - k:
[in] int32_tindicates whethertan(x+y)(ifk = 1) or-1/tan(x+y)(ifk = -1) is returned.
double stdlib_base_kernel_tan( const double x, const double y, const int32_t k );- For increased accuracy, the number for which the tangent should be evaluated can be supplied as a double-double number (i.e., a non-evaluated sum of two double-precision floating-point numbers
xandy).
#include "stdlib/math/base/special/kernel_tan.h"
#include <stdio.h>
int main( void ) {
const double x[] = { -0.7853981633974483, -0.6108652381980153, -0.4363323129985824, -0.26179938779914946, -0.08726646259971649, 0.08726646259971649, 0.26179938779914935, 0.43633231299858233, 0.6108652381980153, 0.7853981633974483 };
double out;
int i;
for ( i = 0; i < 10; i++ ) {
out = stdlib_base_kernel_tan( x[ i ], 0.0, 1 );
printf( "tan(%lf) = %lf\n", x[ i ], out );
}
}@stdlib/math-base/special/kernel-cos: compute the cosine of a double-precision floating-point number on [-π/4, π/4].@stdlib/math-base/special/kernel-sin: compute the sine of a double-precision floating-point number on [-π/4, π/4].@stdlib/math-base/special/tan: evaluate the tangent of a number.
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
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