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docs: improve examples of ndarray/iter namespace #1686

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49 changes: 45 additions & 4 deletions lib/node_modules/@stdlib/ndarray/iter/README.md
View file Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@

@license Apache-2.0

Copyright (c) 2018 The Stdlib Authors.
Copyright (c) 2024 The Stdlib Authors.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
Expand Down Expand Up @@ -75,10 +75,51 @@ var o = ns;
<!-- eslint no-undef: "error" -->

```javascript
var objectKeys = require( '@stdlib/utils/keys' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );
var ns = require( '@stdlib/ndarray/iter' );

console.log( objectKeys( ns ) );
var mean = require( '@stdlib/stats/base/mean' );
var variance = require( '@stdlib/stats/base/variance' );
var randu = require( '@stdlib/random/base/randu' );

var rowVariance;
var iterRows;
var rowMean;
var rowData;
var data;
var row;
var x;
var j;
var i;

data = new Array( 25 );
for ( i = 0; i < data.length; i++ ) {
data[ i ] = parseFloat( ( randu() * 100 ).toFixed( 2 ) );
}

console.log( data );

// Logs an array of 25 elements generated randomly as above.

x = ndarray( 'generic', data, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
iterRows = ns.nditerRows( x );

while ( true ) {
row = iterRows.next();
if ( row.done ) {
break;
}
rowData = [];
for ( j = 0; j < row.value.shape[ 0 ]; j++ ) {
rowData.push( row.value.get( j ) );
}
rowMean = parseFloat( ( mean( rowData.length, rowData, 1 ) ).toFixed( 2 ) );
rowVariance = parseFloat( variance( rowData.length, 1, rowData, 1 )
.toFixed( 2 ) );

console.log( rowMean, rowVariance );

// Logs mean and variance of each row in the 5x5 array.
}
```

</section>
Expand Down
47 changes: 44 additions & 3 deletions lib/node_modules/@stdlib/ndarray/iter/examples/index.js
View file Open in desktop
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
* Copyright (c) 2023 The Stdlib Authors.
* Copyright (c) 2024 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
Expand All @@ -18,7 +18,48 @@

'use strict';

var objectKeys = require( '@stdlib/utils/keys' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );
var mean = require( '@stdlib/stats/base/mean' );
var variance = require( '@stdlib/stats/base/variance' );
var randu = require( '@stdlib/random/base/randu' );
var ns = require( './../lib' );

console.log( objectKeys( ns ) );
var rowVariance;
var iterRows;
var rowMean;
var rowData;
var data;
var row;
var x;
var j;
var i;

data = new Array( 25 );
for ( i = 0; i < data.length; i++ ) {
data[ i ] = parseFloat( ( randu() * 100 ).toFixed( 2 ) );
}

console.log( data );

// Logs an array of 25 elements generated randomly as above.

x = ndarray( 'generic', data, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
iterRows = ns.nditerRows( x );

while ( true ) {
row = iterRows.next();
if ( row.done ) {
break;
}
rowData = [];
for ( j = 0; j < row.value.shape[ 0 ]; j++ ) {
rowData.push( row.value.get( j ) );
}
rowMean = parseFloat( ( mean( rowData.length, rowData, 1 ) ).toFixed( 2 ) );
rowVariance = parseFloat( variance( rowData.length, 1, rowData, 1 )
.toFixed( 2 ) );

console.log( rowMean, rowVariance );

// Logs mean and variance of each row in the 5x5 array.
}

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