Computes an element-wise principal square root.
npm install compute-sqrtSquare Root
===
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> Computes an element-wise principal square root.
The principal square root is defined as
For negative numbers, the principal square root is __not__ defined.
`` bash`
$ npm install compute-sqrt
For use in the browser, use browserify.
` javascript`
var sqrt = require( 'compute-sqrt' );
#### sqrt( x[, opts] )
Computes an element-wise principal square root. x may be either a number, an array, a typed array, or a matrix.
` javascript
var matrix = require( 'dstructs-matrix' ),
data,
mat,
out,
i;
out = sqrt( 9 );
// returns 3
out = sqrt( -9 );
// returns NaN
data = [ 4, 9, 16 ];
out = sqrt( data );
// returns [ 2, 3, 4 ]
data = new Int8Array( data );
out = sqrt( data );
// returns Float64Array( [2,3,4] )
data = new Int16Array( 6 );
for ( i = 0; i < 6; i++ ) {
data[ i ] = i*i;
}
mat = matrix( data, [3,2], 'int16' );
/*
[ 0 1
4 9
16 25 ]
*/
out = sqrt( mat );
/*
[ 0 1
2 3
4 5 ]
*/
`
The function accepts the following options:
* __accessor__: accessor function for accessing array values.typed array
* __dtype__: output or matrix data type. Default: float64.boolean
* __copy__: indicating if the function should return a new data structure. Default: true.'.'
* __path__: deepget/deepset key path.
* __sep__: deepget/deepset key path separator. Default: .
For non-numeric arrays, provide an accessor function for accessing array values.
` javascript
var data = [
[0,4],
[1,9],
[2,16],
[3,25],
[4,36]
];
function getValue( d, i ) {
return d[ 1 ];
}
var out = sqrt( data, {
'accessor': getValue
});
// returns [ 2, 3, 4, 5, 6 ]
`
To deepset an object array, provide a key path and, optionally, a key path separator.
` javascript
var data = [
{'x':[0,4]},
{'x':[1,9]},
{'x':[2,16]},
{'x':[3,25]},
{'x':[4,36]}
];
var out = sqrt( data, 'x|1', '|' );
/*
[
{'x':[0,2]},
{'x':[1,3]},
{'x':[2,4]},
{'x':[3,5]},
{'x':[4,6]}
]
*/
var bool = ( data === out );
// returns true
`
By default, when provided a typed array or matrix, the output data structure is float64 in order to preserve precision. To specify a different data type, set the dtype option (see matrix for a list of acceptable data types).
` javascript
var data, out;
data = new Int8Array( [4,9,16] );
out = sqrt( data, {
'dtype': 'int32'
});
// returns Int32Array( [2,3,4] )
// Works for plain arrays, as well...
out = sqrt( [4,9,16], {
'dtype': 'uint8'
});
// returns Uint8Array( [2,3,4] )
`
By default, the function returns a new data structure. To mutate the input data structure (e.g., when input values can be discarded or when optimizing memory usage), set the copy option to false.
` javascript
var data,
bool,
mat,
out,
i;
data = [ 4, 9, 16 ];
out = sqrt( data, {
'copy': false
});
// returns [ 2, 3, 4 ]
bool = ( data === out );
// returns true
data = new Int16Array( 6 );
for ( i = 0; i < 6; i++ ) {
data[ i ] = i*i;
}
mat = matrix( data, [3,2], 'int16' );
/*
[ 0 1
4 9
16 25 ]
*/
out = sqrt( mat, {
'copy': false
});
/*
[ 0 1
2 3
4 5 ]
*/
bool = ( mat === out );
// returns true
`
* If an element is __not__ a numeric value, the evaluated principal square root is NaN.
` javascript
var data, out;
out = sqrt( null );
// returns NaN
out = sqrt( true );
// returns NaN
out = sqrt( {'a':'b'} );
// returns NaN
out = sqrt( [ true, null, [] ] );
// returns [ NaN, NaN, NaN ]
function getValue( d, i ) {
return d.x;
}
data = [
{'x':true},
{'x':[]},
{'x':{}},
{'x':null}
];
out = sqrt( data, {
'accessor': getValue
});
// returns [ NaN, NaN, NaN, NaN ]
out = sqrt( data, {
'path': 'x'
});
/*
[
{'x':NaN},
{'x':NaN},
{'x':NaN,
{'x':NaN}
]
*/
`
* Be careful when providing a data structure which contains non-numeric elements and specifying an integer output data type, as NaN values are cast to 0.
` javascript`
var out = sqrt( [ true, null, [] ], {
'dtype': 'int8'
});
// returns Int8Array( [0,0,0] );
` javascript
var matrix = require( 'dstructs-matrix' ),
sqrt = require( 'compute-sqrt' );
var data,
mat,
out,
tmp,
i;
// Plain arrays...
data = new Array( 10 );
for ( i = 0; i < data.length; i++ ) {
data[ i ] = Math.round( Math.random()*1000 );
}
out = sqrt( data );
// Object arrays (accessors)...
function getValue( d ) {
return d.x;
}
for ( i = 0; i < data.length; i++ ) {
data[ i ] = {
'x': data[ i ]
};
}
out = sqrt( data, {
'accessor': getValue
});
// Deep set arrays...
for ( i = 0; i < data.length; i++ ) {
data[ i ] = {
'x': [ i, data[ i ].x ]
};
}
out = sqrt( data, {
'path': 'x/1',
'sep': '/'
});
// Typed arrays...
data = new Int32Array( 10 );
for ( i = 0; i < data.length; i++ ) {
data[ i ] = Math.random() * 100;
}
out = sqrt( data );
// Matrices...
mat = matrix( data, [5,2], 'int32' );
out = sqrt( mat );
// Matrices (custom output data type)...
out = sqrt( mat, {
'dtype': 'uint8'
});
`
To run the example code from the top-level application directory,
` bash`
$ node ./examples/index.js
Unit tests use the Mocha test framework with Chai assertions. To run the tests, execute the following command in the top-level application directory:
` bash`
$ make test
All new feature development should have corresponding unit tests to validate correct functionality.
This repository uses Istanbul as its code coverage tool. To generate a test coverage report, execute the following command in the top-level application directory:
` bash`
$ make test-cov
Istanbul creates a ./reports/coverage directory. To access an HTML version of the report,
` bash``
$ make view-cov
---
Copyright © 2014-2015. The Compute.io Authors.
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