diff --git a/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts index f6e5c3d6fc0e..06cab01df747 100644 --- a/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts @@ -24,7 +24,6 @@ import caddf = require( '@stdlib/complex/float32/base/add' ); import cmulf = require( '@stdlib/complex/float32/base/mul' ); import cadd = require( '@stdlib/complex/float64/base/add' ); import cmul = require( '@stdlib/complex/float64/base/mul' ); -import addf = require( '@stdlib/number/float32/base/add' ); import cdiv = require( '@stdlib/math/base/ops/cdiv' ); import cneg = require( '@stdlib/math/base/ops/cneg' ); import cnegf = require( '@stdlib/math/base/ops/cnegf' ); @@ -40,6 +39,7 @@ import sub = require( '@stdlib/math/base/ops/sub' ); import subf = require( '@stdlib/math/base/ops/subf' ); import umul = require( '@stdlib/math/base/ops/umul' ); import umuldw = require( '@stdlib/math/base/ops/umuldw' ); +import addf = require( '@stdlib/number/float32/base/add' ); /** * Interface describing the `ops` namespace. @@ -212,35 +212,6 @@ interface Namespace { */ cmul: typeof cmul; - /** - * Computes the sum of two single-precision floating-point numbers `x` and `y`. - * - * @param x - first input value - * @param y - second input value - * @returns sum - * - * @example - * var v = ns.addf( -1.0, 5.0 ); - * // returns 4.0 - * - * @example - * var v = ns.addf( 2.0, 5.0 ); - * // returns 7.0 - * - * @example - * var v = ns.addf( 0.0, 5.0 ); - * // returns 5.0 - * - * @example - * var v = ns.addf( -0.0, 0.0 ); - * // returns 0.0 - * - * @example - * var v = ns.addf( NaN, NaN ); - * // returns NaN - */ - addf: typeof addf; - /** * Divides two double-precision complex floating-point numbers. * @@ -679,6 +650,35 @@ interface Namespace { * // returns [ 954437176, 1908874354 ] */ umuldw: typeof umuldw; + + /** + * Computes the sum of two single-precision floating-point numbers `x` and `y`. + * + * @param x - first input value + * @param y - second input value + * @returns sum + * + * @example + * var v = ns.addf( -1.0, 5.0 ); + * // returns 4.0 + * + * @example + * var v = ns.addf( 2.0, 5.0 ); + * // returns 7.0 + * + * @example + * var v = ns.addf( 0.0, 5.0 ); + * // returns 5.0 + * + * @example + * var v = ns.addf( -0.0, 0.0 ); + * // returns 0.0 + * + * @example + * var v = ns.addf( NaN, NaN ); + * // returns NaN + */ + addf: typeof addf; } /** diff --git a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts index 7fa953bbe50f..3e5443e421c2 100644 --- a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts @@ -27,12 +27,7 @@ import cuminabs = require( '@stdlib/stats/base/cuminabs' ); import dcumin = require( '@stdlib/stats/base/dcumin' ); import dists = require( '@stdlib/stats/base/dists' ); import dmean = require( '@stdlib/stats/base/dmean' ); -import dmeankbn2 = require( '@stdlib/stats/strided/dmeankbn2' ); -import dmeanli = require( '@stdlib/stats/strided/dmeanli' ); -import dmeanlipw = require( '@stdlib/stats/strided/dmeanlipw' ); -import dmeanors = require( '@stdlib/stats/strided/dmeanors' ); import dmeanpn = require( '@stdlib/stats/base/dmeanpn' ); -import dmeanpw = require( '@stdlib/stats/strided/dmeanpw' ); import dmeanstdev = require( '@stdlib/stats/base/dmeanstdev' ); import dmeanstdevpn = require( '@stdlib/stats/base/dmeanstdevpn' ); import dmeanvar = require( '@stdlib/stats/base/dmeanvar' ); @@ -230,6 +225,11 @@ import variancepn = require( '@stdlib/stats/base/variancepn' ); import variancetk = require( '@stdlib/stats/base/variancetk' ); import variancewd = require( '@stdlib/stats/base/variancewd' ); import varianceyc = require( '@stdlib/stats/base/varianceyc' ); +import dmeankbn2 = require( '@stdlib/stats/strided/dmeankbn2' ); +import dmeanli = require( '@stdlib/stats/strided/dmeanli' ); +import dmeanlipw = require( '@stdlib/stats/strided/dmeanlipw' ); +import dmeanors = require( '@stdlib/stats/strided/dmeanors' ); +import dmeanpw = require( '@stdlib/stats/strided/dmeanpw' ); /** * Interface describing the `base` namespace. @@ -240,9 +240,9 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -400,110 +400,6 @@ interface Namespace { */ dmean: typeof dmean; - /** - * Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. - * - * @param N - number of indexed elements - * @param x - input array - * @param strideX - stride length - * @returns arithmetic mean - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeankbn2( x.length, x, 1 ); - * // returns ~0.3333 - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeankbn2.ndarray( x.length, x, 1, 0 ); - * // returns ~0.3333 - */ - dmeankbn2: typeof dmeankbn2; - - /** - * Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. - * - * @param N - number of indexed elements - * @param x - input array - * @param strideX - stride length - * @returns arithmetic mean - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanli( x.length, x, 1 ); - * // returns ~0.3333 - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanli.ndarray( x.length, x, 1, 0 ); - * // returns ~0.3333 - */ - dmeanli: typeof dmeanli; - - /** - * Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. - * - * @param N - number of indexed elements - * @param x - input array - * @param strideX - stride length - * @returns arithmetic mean - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanlipw( x.length, x, 1 ); - * // returns ~0.3333 - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanlipw.ndarray( x.length, x, 1, 0 ); - * // returns ~0.3333 - */ - dmeanlipw: typeof dmeanlipw; - - /** - * Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. - * - * @param N - number of indexed elements - * @param x - input array - * @param strideX - stride length - * @returns arithmetic mean - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanors( x.length, x, 1 ); - * // returns ~0.3333 - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanors.ndarray( x.length, x, 1, 0 ); - * // returns ~0.3333 - */ - dmeanors: typeof dmeanors; - /** * Computes the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm. * @@ -530,32 +426,6 @@ interface Namespace { */ dmeanpn: typeof dmeanpn; - /** - * Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation. - * - * @param N - number of indexed elements - * @param x - input array - * @param strideX - stride length - * @returns arithmetic mean - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanpw( x.length, x, 1 ); - * // returns ~0.3333 - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmeanpw.ndarray( x.length, x, 1, 0 ); - * // returns ~0.3333 - */ - dmeanpw: typeof dmeanpw; - /** * Computes the mean and standard deviation of a double-precision floating-point strided array. * @@ -5793,6 +5663,136 @@ interface Namespace { * // returns ~4.3333 */ varianceyc: typeof varianceyc; + + /** + * Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns arithmetic mean + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeankbn2( x.length, x, 1 ); + * // returns ~0.3333 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeankbn2.ndarray( x.length, x, 1, 0 ); + * // returns ~0.3333 + */ + dmeankbn2: typeof dmeankbn2; + + /** + * Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns arithmetic mean + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanli( x.length, x, 1 ); + * // returns ~0.3333 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanli.ndarray( x.length, x, 1, 0 ); + * // returns ~0.3333 + */ + dmeanli: typeof dmeanli; + + /** + * Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns arithmetic mean + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanlipw( x.length, x, 1 ); + * // returns ~0.3333 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanlipw.ndarray( x.length, x, 1, 0 ); + * // returns ~0.3333 + */ + dmeanlipw: typeof dmeanlipw; + + /** + * Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns arithmetic mean + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanors( x.length, x, 1 ); + * // returns ~0.3333 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanors.ndarray( x.length, x, 1, 0 ); + * // returns ~0.3333 + */ + dmeanors: typeof dmeanors; + + /** + * Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns arithmetic mean + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanpw( x.length, x, 1 ); + * // returns ~0.3333 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + * + * var v = ns.dmeanpw.ndarray( x.length, x, 1, 0 ); + * // returns ~0.3333 + */ + dmeanpw: typeof dmeanpw; } /**