diff --git a/lib/node_modules/@stdlib/ndarray/base/README.md b/lib/node_modules/@stdlib/ndarray/base/README.md index 7ffc007d37ac..bc613bb1afde 100644 --- a/lib/node_modules/@stdlib/ndarray/base/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/README.md @@ -150,7 +150,9 @@ var o = ns; - [`prependSingletonDimensions( x, n, writable )`][@stdlib/ndarray/base/prepend-singleton-dimensions]: prepend singleton dimensions. - [`promoteDataTypes( dtypes )`][@stdlib/ndarray/base/promote-dtypes]: resolve the data type that results from applying promotion rules to a provided list of data types. - [`quaternaryLoopOrder( shape, stridesX, stridesY, stridesZ, stridesW, stridesU )`][@stdlib/ndarray/base/quaternary-loop-interchange-order]: reorder ndarray dimensions and associated strides for loop interchange. +- [`quaternaryBlockSize( dtypeX, dtypeY, dtypeZ, dtypeW, dtypeU )`][@stdlib/ndarray/base/quaternary-tiling-block-size]: resolve a loop block size for multi-dimensional array tiled loops. - [`quinaryLoopOrder( shape, stridesX, stridesY, stridesZ, stridesW, stridesU, stridesV )`][@stdlib/ndarray/base/quinary-loop-interchange-order]: reorder ndarray dimensions and associated strides for loop interchange. +- [`quinaryBlockSize( dtypeX, dtypeY, dtypeZ, dtypeW, dtypeU, dtypeV )`][@stdlib/ndarray/base/quinary-tiling-block-size]: resolve a loop block size for multi-dimensional array tiled loops. - [`removeSingletonDimensions( x )`][@stdlib/ndarray/base/remove-singleton-dimensions]: remove singleton dimensions. - [`reverseDimension( x, dim, writable )`][@stdlib/ndarray/base/reverse-dimension]: return a view of an input ndarray in which the order of elements along a specified dimension is reversed. - [`reverse( x, writable )`][@stdlib/ndarray/base/reverse]: return a view of an input ndarray in which the order of elements along each dimension is reversed. @@ -178,6 +180,7 @@ var o = ns; - [`ternaryOutputDataType( xdtype, ydtype, zdtype, policy )`][@stdlib/ndarray/base/ternary-output-dtype]: resolve the output ndarray data type for a ternary function. - [`ternaryBlockSize( dtypeX, dtypeY, dtypeZ, dtypeW )`][@stdlib/ndarray/base/ternary-tiling-block-size]: resolve a loop block size for multi-dimensional array tiled loops. - [`ternary( arrays, fcn )`][@stdlib/ndarray/base/ternary]: apply a ternary callback to elements in input ndarrays and assign results to elements in an output ndarray. +- [`blockSize( dtypes )`][@stdlib/ndarray/base/tiling-block-size]: resolve a loop block size for multi-dimensional array tiled loops. - [`ndarray2array( buffer, shape, strides, offset, order )`][@stdlib/ndarray/base/to-array]: convert an ndarray buffer to a generic array. - [`toFlippedlr( x )`][@stdlib/ndarray/base/to-flippedlr]: return a new ndarray where the order of elements along the last dimension of an input ndarray is reversed. - [`toFlippedud( x )`][@stdlib/ndarray/base/to-flippedud]: return a new ndarray where the order of elements along the second-to-last dimension of an input ndarray is reversed. @@ -481,8 +484,12 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/quaternary-loop-interchange-order]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/quaternary-loop-interchange-order +[@stdlib/ndarray/base/quaternary-tiling-block-size]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/quaternary-tiling-block-size + [@stdlib/ndarray/base/quinary-loop-interchange-order]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/quinary-loop-interchange-order +[@stdlib/ndarray/base/quinary-tiling-block-size]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/quinary-tiling-block-size + [@stdlib/ndarray/base/remove-singleton-dimensions]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/remove-singleton-dimensions [@stdlib/ndarray/base/reverse-dimension]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/reverse-dimension @@ -537,6 +544,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/ternary]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/ternary +[@stdlib/ndarray/base/tiling-block-size]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/tiling-block-size + [@stdlib/ndarray/base/to-array]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/to-array [@stdlib/ndarray/base/to-flippedlr]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/to-flippedlr diff --git a/lib/node_modules/@stdlib/stats/strided/README.md b/lib/node_modules/@stdlib/stats/strided/README.md index 0eeab66acb0e..cd3e7b464588 100644 --- a/lib/node_modules/@stdlib/stats/strided/README.md +++ b/lib/node_modules/@stdlib/stats/strided/README.md @@ -62,6 +62,7 @@ The namespace exports the following: - [`dcumaxabs( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. - [`dcumin( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcumin]: calculate the cumulative minimum of double-precision floating-point strided array elements. - [`dcuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcuminabs]: calculate the cumulative minimum absolute value of double-precision floating-point strided array elements. +- [`distances`][@stdlib/stats/strided/distances]: distance metrics for strided arrays. - [`dmax( N, x, strideX )`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`dmaxabs( N, x, strideX )`][@stdlib/stats/strided/dmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array. - [`dmaxabssorted( N, x, strideX )`][@stdlib/stats/strided/dmaxabssorted]: calculate the maximum absolute value of a sorted double-precision floating-point strided array. @@ -85,6 +86,7 @@ The namespace exports the following: - [`dminabs( N, x, strideX )`][@stdlib/stats/strided/dminabs]: calculate the minimum absolute value of a double-precision floating-point strided array. - [`dminsorted( N, x, strideX )`][@stdlib/stats/strided/dminsorted]: calculate the minimum value of a sorted double-precision floating-point strided array. - [`dmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask. +- [`dmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmidrange]: calculate the mid-range of a double-precision floating-point strided array according to a mask. - [`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask. - [`dmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskrange]: calculate the range of a double-precision floating-point strided array according to a mask. - [`dnanmax( N, x, strideX )`][@stdlib/stats/strided/dnanmax]: calculate the maximum value of a double-precision floating-point strided array, ignoring `NaN` values. @@ -94,9 +96,11 @@ The namespace exports the following: - [`dnanmeanpn( N, x, strideX )`][@stdlib/stats/strided/dnanmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. - [`dnanmeanpw( N, x, strideX )`][@stdlib/stats/strided/dnanmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. - [`dnanmeanwd( N, x, strideX )`][@stdlib/stats/strided/dnanmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. +- [`dnanmidrange( N, x, strideX )`][@stdlib/stats/strided/dnanmidrange]: calculate the mid-range of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmin( N, x, strideX )`][@stdlib/stats/strided/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanminabs( N, x, strideX )`][@stdlib/stats/strided/dnanminabs]: calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. +- [`dnanmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmidrange]: calculate the mid-range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskrange]: calculate the range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanrange( N, x, strideX )`][@stdlib/stats/strided/dnanrange]: calculate the range of a double-precision floating-point strided array, ignoring `NaN` values. @@ -113,6 +117,7 @@ The namespace exports the following: - [`dnanvariancewd( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancewd]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm. - [`dnanvarianceyc( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvarianceyc]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - [`drange( N, x, strideX )`][@stdlib/stats/strided/drange]: calculate the range of a double-precision floating-point strided array. +- [`drangeabs( N, x, strideX )`][@stdlib/stats/strided/drangeabs]: compute the range of absolute values of a double-precision floating-point strided array. - [`dsem( N, correction, x, strideX )`][@stdlib/stats/strided/dsem]: calculate the standard error of the mean of a double-precision floating-point strided array. - [`dsemch( N, correction, x, strideX )`][@stdlib/stats/strided/dsemch]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dsempn( N, correction, x, strideX )`][@stdlib/stats/strided/dsempn]: calculate the standard error of the mean of a double-precision floating-point strided array using a two-pass algorithm. @@ -159,11 +164,15 @@ The namespace exports the following: - [`meanpw( N, x, strideX )`][@stdlib/stats/strided/meanpw]: calculate the arithmetic mean of a strided array using pairwise summation. - [`meanwd( N, x, strideX )`][@stdlib/stats/strided/meanwd]: calculate the arithmetic mean of a strided array using Welford's algorithm. - [`mediansorted( N, x, strideX )`][@stdlib/stats/strided/mediansorted]: calculate the median value of a sorted strided array. +- [`midrangeBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/midrange-by]: calculate the mid-range of a strided array via a callback function. +- [`midrange( N, x, strideX )`][@stdlib/stats/strided/midrange]: calculate the mid-range of a strided array. - [`minBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/min-by]: calculate the minimum value of a strided array via a callback function. - [`min( N, x, strideX )`][@stdlib/stats/strided/min]: calculate the minimum value of a strided array. - [`minabs( N, x, strideX )`][@stdlib/stats/strided/minabs]: calculate the minimum absolute value of a strided array. - [`minsorted( N, x, strideX )`][@stdlib/stats/strided/minsorted]: calculate the minimum value of a sorted strided array. - [`mskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmax]: calculate the maximum value of a strided array according to a mask. +- [`mskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmaxabs]: calculate the maximum absolute value of a strided array according to a mask. +- [`mskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmidrange]: calculate the mid-range of a strided array according to a mask. - [`mskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmin]: calculate the minimum value of a strided array according to a mask. - [`mskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskrange]: calculate the range of a strided array according to a mask. - [`nanmaxBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanmax-by]: calculate the maximum value of a strided array via a callback function, ignoring `NaN` values. @@ -173,10 +182,13 @@ The namespace exports the following: - [`nanmeanors( N, x, strideX )`][@stdlib/stats/strided/nanmeanors]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using ordinary recursive summation. - [`nanmeanpn( N, x, strideX )`][@stdlib/stats/strided/nanmeanpn]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm. - [`nanmeanwd( N, x, strideX )`][@stdlib/stats/strided/nanmeanwd]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm. +- [`nanmidrangeBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanmidrange-by]: calculate the mid-range of a strided array via a callback function, ignoring `NaN` values. +- [`nanmidrange( N, x, strideX )`][@stdlib/stats/strided/nanmidrange]: calculate the mid-range of a strided array, ignoring `NaN` values. - [`nanminBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanmin-by]: calculate the minimum value of a strided array via a callback function, ignoring `NaN` values. - [`nanmin( N, x, strideX )`][@stdlib/stats/strided/nanmin]: calculate the minimum value of a strided array, ignoring `NaN` values. - [`nanminabs( N, x, strideX )`][@stdlib/stats/strided/nanminabs]: calculate the minimum absolute value of a strided array, ignoring `NaN` values. - [`nanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/nanmskmax]: calculate the maximum value of a strided array according to a mask, ignoring `NaN` values. +- [`nanmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/nanmskmidrange]: calculate the mid-range of a strided array according to a mask, ignoring `NaN` values. - [`nanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/nanmskmin]: calculate the minimum value of a strided array according to a mask, ignoring `NaN` values. - [`nanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/nanmskrange]: calculate the range of a strided array according to a mask, ignoring `NaN` values. - [`nanrangeBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanrange-by]: calculate the range of a strided array via a callback function, ignoring `NaN` values. @@ -195,6 +207,7 @@ The namespace exports the following: - [`nanvarianceyc( N, correction, x, strideX )`][@stdlib/stats/strided/nanvarianceyc]: calculate the variance of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - [`rangeBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/range-by]: calculate the range of a strided array via a callback function. - [`range( N, x, strideX )`][@stdlib/stats/strided/range]: calculate the range of a strided array. +- [`rangeabs( N, x, strideX )`][@stdlib/stats/strided/rangeabs]: calculate the range of absolute values of a strided array. - [`scovarmtk( N, correction, meanx, x, strideX, meany, y, strideY )`][@stdlib/stats/strided/scovarmtk]: calculate the covariance of two single-precision floating-point strided arrays provided known means and using a one-pass textbook algorithm. - [`scumax( N, x, strideX, y, strideY )`][@stdlib/stats/strided/scumax]: calculate the cumulative maximum of single-precision floating-point strided array elements. - [`scumaxabs( N, x, strideX, y, strideY )`][@stdlib/stats/strided/scumaxabs]: calculate the cumulative maximum absolute value of single-precision floating-point strided array elements. @@ -222,6 +235,8 @@ The namespace exports the following: - [`sminabs( N, x, strideX )`][@stdlib/stats/strided/sminabs]: calculate the minimum absolute value of a single-precision floating-point strided array. - [`sminsorted( N, x, strideX )`][@stdlib/stats/strided/sminsorted]: calculate the minimum value of a sorted single-precision floating-point strided array. - [`smskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskmax]: calculate the maximum value of a single-precision floating-point strided array according to a mask. +- [`smskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskmaxabs]: calculate the maximum absolute value of a single-precision floating-point strided array according to a mask. +- [`smskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskmidrange]: calculate the mid-range of a single-precision floating-point strided array according to a mask. - [`smskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask. - [`smskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/smskrange]: calculate the range of a single-precision floating-point strided array according to a mask. - [`snanmax( N, x, strideX )`][@stdlib/stats/strided/snanmax]: calculate the maximum value of a single-precision floating-point strided array, ignoring `NaN` values. @@ -230,13 +245,16 @@ The namespace exports the following: - [`snanmeanors( N, x, strideX )`][@stdlib/stats/strided/snanmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation. - [`snanmeanpn( N, x, strideX )`][@stdlib/stats/strided/snanmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. - [`snanmeanwd( N, x, strideX )`][@stdlib/stats/strided/snanmeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm. +- [`snanmidrange( N, x, strideX )`][@stdlib/stats/strided/snanmidrange]: calculate the mid-range of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmin( N, x, strideX )`][@stdlib/stats/strided/snanmin]: calculate the minimum value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanminabs( N, x, strideX )`][@stdlib/stats/strided/snanminabs]: calculate the minimum absolute value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmax]: calculate the maximum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. +- [`snanmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmidrange]: calculate the mid-range of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskrange]: calculate the range of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanrange( N, x, strideX )`][@stdlib/stats/strided/snanrange]: calculate the range of a single-precision floating-point strided array, ignoring `NaN` values. - [`srange( N, x, strideX )`][@stdlib/stats/strided/srange]: calculate the range of a single-precision floating-point strided array. +- [`srangeabs( N, x, strideX )`][@stdlib/stats/strided/srangeabs]: compute the range of absolute values of a single-precision floating-point strided array. - [`sstdev( N, correction, x, strideX )`][@stdlib/stats/strided/sstdev]: calculate the standard deviation of a single-precision floating-point strided array. - [`sstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/sstdevch]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. - [`sstdevpn( N, correction, x, strideX )`][@stdlib/stats/strided/sstdevpn]: calculate the standard deviation of a single-precision floating-point strided array using a two-pass algorithm. @@ -331,6 +349,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dcuminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcuminabs +[@stdlib/stats/strided/distances]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/distances + [@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/strided/dmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmaxabs @@ -377,6 +397,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmskmax +[@stdlib/stats/strided/dmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmskmidrange + [@stdlib/stats/strided/dmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmskmin [@stdlib/stats/strided/dmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmskrange @@ -395,12 +417,16 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dnanmeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmeanwd +[@stdlib/stats/strided/dnanmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmidrange + [@stdlib/stats/strided/dnanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmin [@stdlib/stats/strided/dnanminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanminabs [@stdlib/stats/strided/dnanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmax +[@stdlib/stats/strided/dnanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmidrange + [@stdlib/stats/strided/dnanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmin [@stdlib/stats/strided/dnanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskrange @@ -433,6 +459,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/drange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/drange +[@stdlib/stats/strided/drangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/drangeabs + [@stdlib/stats/strided/dsem]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dsem [@stdlib/stats/strided/dsemch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dsemch @@ -525,6 +553,10 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/mediansorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mediansorted +[@stdlib/stats/strided/midrange-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/midrange-by + +[@stdlib/stats/strided/midrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/midrange + [@stdlib/stats/strided/min-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/min-by [@stdlib/stats/strided/min]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/min @@ -535,6 +567,10 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/mskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmax +[@stdlib/stats/strided/mskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmaxabs + +[@stdlib/stats/strided/mskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmidrange + [@stdlib/stats/strided/mskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmin [@stdlib/stats/strided/mskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskrange @@ -553,6 +589,10 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/nanmeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmeanwd +[@stdlib/stats/strided/nanmidrange-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmidrange-by + +[@stdlib/stats/strided/nanmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmidrange + [@stdlib/stats/strided/nanmin-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmin-by [@stdlib/stats/strided/nanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmin @@ -561,6 +601,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/nanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmskmax +[@stdlib/stats/strided/nanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmskmidrange + [@stdlib/stats/strided/nanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmskmin [@stdlib/stats/strided/nanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmskrange @@ -597,6 +639,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/range]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/range +[@stdlib/stats/strided/rangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/rangeabs + [@stdlib/stats/strided/scovarmtk]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/scovarmtk [@stdlib/stats/strided/scumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/scumax @@ -651,6 +695,10 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/smskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smskmax +[@stdlib/stats/strided/smskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smskmaxabs + +[@stdlib/stats/strided/smskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smskmidrange + [@stdlib/stats/strided/smskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smskmin [@stdlib/stats/strided/smskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smskrange @@ -667,12 +715,16 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/snanmeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmeanwd +[@stdlib/stats/strided/snanmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmidrange + [@stdlib/stats/strided/snanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmin [@stdlib/stats/strided/snanminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanminabs [@stdlib/stats/strided/snanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmax +[@stdlib/stats/strided/snanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmidrange + [@stdlib/stats/strided/snanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmin [@stdlib/stats/strided/snanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskrange @@ -681,6 +733,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/srange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/srange +[@stdlib/stats/strided/srangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/srangeabs + [@stdlib/stats/strided/sstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/sstdev [@stdlib/stats/strided/sstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/sstdevch diff --git a/lib/node_modules/@stdlib/stats/strided/distances/README.md b/lib/node_modules/@stdlib/stats/strided/distances/README.md index 2dd45b70c9ff..afc70bb56999 100644 --- a/lib/node_modules/@stdlib/stats/strided/distances/README.md +++ b/lib/node_modules/@stdlib/stats/strided/distances/README.md @@ -53,6 +53,17 @@ The namespace exports the following: +
+ +- [`dchebychev( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dchebychev]: compute the Chebychev distance between two double-precision floating-point strided arrays. +- [`dcityblock( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dcityblock]: compute the city block (Manhattan) distance between two double-precision floating-point strided arrays. +- [`dcosineDistance( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dcosine-distance]: compute the cosine distance between two double-precision floating-point strided arrays. +- [`dcosineSimilarity( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dcosine-similarity]: compute the cosine similarity of two double-precision floating-point strided arrays. +- [`deuclidean( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/deuclidean]: compute the Euclidean distance between two double-precision floating-point strided arrays. +- [`dsquaredEuclidean( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dsquared-euclidean]: compute the squared Euclidean distance between two double-precision floating-point strided arrays. + +
+ @@ -100,6 +111,22 @@ console.log( objectKeys( ns ) );
+ + +[@stdlib/stats/strided/distances/dchebychev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/distances/dchebychev + +[@stdlib/stats/strided/distances/dcityblock]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/distances/dcityblock + +[@stdlib/stats/strided/distances/dcosine-distance]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/distances/dcosine-distance + +[@stdlib/stats/strided/distances/dcosine-similarity]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/distances/dcosine-similarity + +[@stdlib/stats/strided/distances/deuclidean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/distances/deuclidean + +[@stdlib/stats/strided/distances/dsquared-euclidean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/distances/dsquared-euclidean + + +