docs: update REPL namespace documentation

PR-URL: stdlib-js#6316
Reviewed-by: Athan Reines <kgryte@gmail.com>

Author: stdlib-bot

lib/node_modules/@stdlib/repl/code-blocks/data/data.csv

@@ -2118,8 +2118,8 @@ base.strided.meanpn,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length,
 base.strided.meanpn.ndarray,"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n"
 base.strided.meanpw,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n"
 base.strided.meanpw.ndarray,"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n"
-base.strided.meanwd,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n"
-base.strided.meanwd.ndarray,"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n"
+base.strided.meanwd,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanwd( 3, x1, 2 )\n"
+base.strided.meanwd.ndarray,"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanwd.ndarray( 3, x, 2, 1 )\n"
 base.strided.mediansorted,"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mediansorted( 3, x1, 2 )\n"
 base.strided.mediansorted.ndarray,"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.mediansorted.ndarray( 3, x, 2, 1 )\n"
 base.strided.metaDataProps,"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n"
@@ -2166,8 +2166,8 @@ base.strided.nanmskmax,"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0
 base.strided.nanmskmax.ndarray,"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
 base.strided.nanmskmin,"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n"
 base.strided.nanmskmin.ndarray,"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
-base.strided.nanmskrange,"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n"
-base.strided.nanmskrange.ndarray,"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
+base.strided.nanmskrange,"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( 5, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n"
+base.strided.nanmskrange.ndarray,"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n"
 base.strided.nanrange,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n"
 base.strided.nanrange.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n"
 base.strided.nanrangeBy,"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n"
@@ -4160,6 +4160,7 @@ ndarrayStrides,"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n"
 ndat,"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n"
 ndempty,"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n"
 ndemptyLike,"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n"
+ndfill,"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nndfill( x, 10.0 );\nx.get( 0, 0 )\n"
 ndfilter,"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n"
 ndfilterMap,"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n"
 ndforEach,"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n"