diff --git a/lib/node_modules/@stdlib/math/base/ops/README.md b/lib/node_modules/@stdlib/math/base/ops/README.md index 7d7e40b51d98..82fd9e76fca3 100644 --- a/lib/node_modules/@stdlib/math/base/ops/README.md +++ b/lib/node_modules/@stdlib/math/base/ops/README.md @@ -45,7 +45,6 @@ The namespace contains the following functions:
-- [`cdiv( z1, z2 )`][@stdlib/complex/float64/base/div]: divide two double-precision complex floating-point numbers. - [`cneg( z )`][@stdlib/math/base/ops/cneg]: negate a double-precision complex floating-point number. - [`cnegf( z )`][@stdlib/math/base/ops/cnegf]: negate a single-precision complex floating-point number. - [`csub( z1, z2 )`][@stdlib/math/base/ops/csub]: subtract two double-precision complex floating-point numbers. @@ -68,20 +67,9 @@ The namespace contains the following functions: ```javascript -var Complex128 = require( '@stdlib/complex/float64/ctor' ); var ns = require( '@stdlib/math/base/ops' ); -console.log( ns.sub( 1.25, 0.45 ) ); -// => 0.8 - -console.log( ns.divf( 1.2, 0.4 ) ); -// => 3.0 - -// Operations for complex numbers: -var z1 = new Complex128( 5.0, 3.0 ); -var z2 = new Complex128( -2.0, 1.0 ); -console.log( ns.cmul( z1, z2 ) ); // { 're': -13.0, 'im': -1.0 } -// => +console.log( ns ); ``` @@ -102,8 +90,6 @@ console.log( ns.cmul( z1, z2 ) ); // { 're': -13.0, 'im': -1.0 } -[@stdlib/complex/float64/base/div]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/complex/float64/base/div - [@stdlib/math/base/ops/cneg]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/cneg [@stdlib/math/base/ops/cnegf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/cnegf diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md index 8033485ccdea..14659ee62370 100644 --- a/lib/node_modules/@stdlib/stats/base/README.md +++ b/lib/node_modules/@stdlib/stats/base/README.md @@ -85,7 +85,7 @@ The namespace contains the following statistical functions: - [`dnanstdevpn( N, correction, x, stride )`][@stdlib/stats/base/dnanstdevpn]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. - [`dnanstdevtk( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevtk]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm. - [`dnanstdevwd( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevwd]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm. -- [`dnanstdevyc( N, correction, x, stride )`][@stdlib/stats/base/dnanstdevyc]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. +- [`dnanstdevyc( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevyc]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - [`dnanvariance( N, correction, x, stride )`][@stdlib/stats/base/dnanvariance]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values. - [`dnanvariancech( N, correction, x, strideX )`][@stdlib/stats/base/dnanvariancech]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - [`dnanvariancepn( N, correction, x, strideX )`][@stdlib/stats/base/dnanvariancepn]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. @@ -104,13 +104,13 @@ The namespace contains the following statistical functions: - [`dsmeanpn( N, x, strideX )`][@stdlib/stats/base/dsmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. - [`dsmeanpw( N, x, strideX )`][@stdlib/stats/base/dsmeanpw]: calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. - [`dsmeanwd( N, x, strideX )`][@stdlib/stats/base/dsmeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. -- [`dsnanmean( N, x, stride )`][@stdlib/stats/base/dsnanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using extended accumulation, and returning an extended precision result. +- [`dsnanmean( N, x, strideX )`][@stdlib/stats/base/dsnanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using extended accumulation, and returning an extended precision result. - [`dsnanmeanors( N, x, strideX )`][@stdlib/stats/base/dsnanmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using ordinary recursive summation with extended accumulation, and returning an extended precision result. - [`dsnanmeanpn( N, x, strideX )`][@stdlib/stats/base/dsnanmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result. - [`dsnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dsnanmeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result. - [`dstdev( N, correction, x, stride )`][@stdlib/stats/base/dstdev]: calculate the standard deviation of a double-precision floating-point strided array. - [`dstdevch( N, correction, x, strideX )`][@stdlib/stats/base/dstdevch]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. -- [`dstdevpn( N, correction, x, stride )`][@stdlib/stats/base/dstdevpn]: calculate the standard deviation of a double-precision floating-point strided array using a two-pass algorithm. +- [`dstdevpn( N, correction, x, strideX )`][@stdlib/stats/base/dstdevpn]: calculate the standard deviation of a double-precision floating-point strided array using a two-pass algorithm. - [`dstdevtk( N, correction, x, strideX )`][@stdlib/stats/base/dstdevtk]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. - [`dstdevwd( N, correction, x, strideX )`][@stdlib/stats/base/dstdevwd]: calculate the standard deviation of a double-precision floating-point strided array using Welford's algorithm. - [`dstdevyc( N, correction, x, strideX )`][@stdlib/stats/base/dstdevyc]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. @@ -241,7 +241,7 @@ The namespace contains the following statistical functions: - [`stdevyc( N, correction, x, stride )`][@stdlib/stats/base/stdevyc]: calculate the standard deviation of a strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`svariance( N, correction, x, stride )`][@stdlib/stats/base/svariance]: calculate the variance of a single-precision floating-point strided array. - [`svariancech( N, correction, x, strideX )`][@stdlib/stats/base/svariancech]: calculate the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. -- [`svariancepn( N, correction, x, stride )`][@stdlib/stats/base/svariancepn]: calculate the variance of a single-precision floating-point strided array using a two-pass algorithm. +- [`svariancepn( N, correction, x, strideX )`][@stdlib/stats/base/svariancepn]: calculate the variance of a single-precision floating-point strided array using a two-pass algorithm. - [`svariancetk( N, correction, x, strideX )`][@stdlib/stats/base/svariancetk]: calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. - [`svariancewd( N, correction, x, stride )`][@stdlib/stats/base/svariancewd]: calculate the variance of a single-precision floating-point strided array using Welford's algorithm. - [`svarianceyc( N, correction, x, strideX )`][@stdlib/stats/base/svarianceyc]: calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.