Merged
Show file tree
Hide file tree
Changes from all commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Jump to
Failed to load files.
Original file line numberDiff line numberDiff line change
Expand Up@@ -2012,10 +2012,10 @@ base.strided.dvariancewd,"\nbase.strided.dvariancewd( N:integer, correction:numb
base.strided.dvariancewd.ndarray,"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n"
base.strided.dvarianceyc,"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n"
base.strided.dvarianceyc.ndarray,"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n"
base.strided.dvarm,"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n"
base.strided.dvarm.ndarray,"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n"
base.strided.dvarmpn,"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n"
base.strided.dvarmpn.ndarray,"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n"
base.strided.dvarm,"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n"
base.strided.dvarm.ndarray,"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n"
base.strided.dvarmpn,"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n"
base.strided.dvarmpn.ndarray,"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n"
base.strided.dvarmtk,"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n"
base.strided.dvarmtk.ndarray,"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n"
base.strided.gapx,"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each element in a strided array.\n"
Expand DownExpand Up@@ -2189,8 +2189,8 @@ base.strided.nanstdevyc,"\nbase.strided.nanstdevyc( N:integer, correction:number
base.strided.nanstdevyc.ndarray,"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n"
base.strided.nanvariance,"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n"
base.strided.nanvariance.ndarray,"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n"
base.strided.nanvariancech,"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n"
base.strided.nanvariancech.ndarray,"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n"
base.strided.nanvariancech,"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n"
base.strided.nanvariancech.ndarray,"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n"
base.strided.nanvariancepn,"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n"
base.strided.nanvariancepn.ndarray,"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n"
base.strided.nanvariancetk,"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n"
Expand DownExpand Up@@ -2471,12 +2471,12 @@ base.strided.ssumpw,"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:i
base.strided.ssumpw.ndarray,"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n"
base.strided.sswap,"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n"
base.strided.sswap.ndarray,"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n"
base.strided.stdev,"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array.\n"
base.strided.stdev.ndarray,"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n"
base.strided.stdevch,"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n"
base.strided.stdevch.ndarray,"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n"
base.strided.stdevpn,"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n"
base.strided.stdevpn.ndarray,"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n"
base.strided.stdev,"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array.\n"
base.strided.stdev.ndarray,"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n"
base.strided.stdevch,"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n"
base.strided.stdevch.ndarray,"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n"
base.strided.stdevpn,"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n"
base.strided.stdevpn.ndarray,"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n"
base.strided.stdevtk,"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n"
base.strided.stdevtk.ndarray,"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n"
base.strided.stdevwd,"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n"
Expand DownExpand Up@@ -2507,10 +2507,10 @@ base.strided.unaryDtypeSignatures,"\nbase.strided.unaryDtypeSignatures( dtypes1:
base.strided.unarySignatureCallbacks,"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n Assigns callbacks to unary interfaces according to type promotion rules.\n"
base.strided.variance,"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array.\n"
base.strided.variance.ndarray,"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n"
base.strided.variancech,"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n"
base.strided.variancech.ndarray,"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n"
base.strided.variancepn,"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n"
base.strided.variancepn.ndarray,"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n"
base.strided.variancech,"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n"
base.strided.variancech.ndarray,"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n"
base.strided.variancepn,"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n"
base.strided.variancepn.ndarray,"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n"
base.strided.variancetk,"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n"
base.strided.variancetk.ndarray,"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n"
base.strided.variancewd,"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using Welford's algorithm.\n"
Expand Down
Loading