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Computation library.

Package Exports

  • compute.io

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (compute.io) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

Compute.io

NPM version Build Status Coverage Dependencies

Computation library.

Table of Contents

  1. [Installation](#installation)
  2. [Usage](#usage)
  3. [Fluent Interface](#fluent-interface)
  4. [Tests](#tests)
  5. [License](#license)

Installation

$ npm install compute.io

Usage

To use compute,

var compute = require( 'compute.io' );

The compute module is comprised of several smaller modules. If you want to roll your own compute, follow the links and import the individual modules.

The compute module has the following methods...

Utilities

compute.roundn( x, n )

Rounds values to the nearest multiple of 10^n. x may be either a single numeric value or an array of values. n must be an integer.

compute.roundn( Math.PI, -2 );
// returns 3.14

var x = compute.roundn( 111, 2 );
// returns 100

var data = [ 2.342, 4.943, 2.234, 7.992, 3.142 ];

compute.roundn( data, -2 );
// returns [...] where each value is rounded to nearest hundredth

Note: if provided an array, the array is mutated.

compute.polyval( coef, x )

Evaluates a polynomial with coefficients coef, where x may be a single numeric value or an array of numeric values.

var coef = [ 4, 2, 6, -17 ];

var x = compute.polyval( coef, [ 10, -3] );

compute.reverse( arr )

Reverses an array in place.

var arr = [ 1, 2, 3, 4 ];

compute.reverse( arr );
// returns [ 4, 3, 2, 1 ]

Note: the array is mutated.

compute.shuffle( arr )

Generates a random permutation of (shuffles) an array in place.

var arr = [ 1, 2, 3, 4 ];

compute.shuffle( arr );

Note: the array is mutated.

compute.circshift( x, k )

Circularly shifts elements/characters. x may be an array or a string. k is an integer specifying the number of positions to shift. The sign of k specifies the shift direction.

compute.circshift( [1,2,3,4,5], 2 );
// returns [4,5,1,2,3]

var str = compute.circshift( 'beepboop', -3 );
// returns 'pboopbee'

Note: if provided an array, the array, is mutated.

compute.diff( arr )

Calculates the differences between adjacent elements in an array.

var arr = [ 2, 1, 3, 4 ];

var diff = compute.diff( arr );
// returns [ 1, -2, -1 ]

Note: the length of the returned array is one less than the length of the original array.

compute.find( arr, [opts,] clbk )

Finds array elements which satisfy a test condition.

var arr = [ 2, 1, 3, 4 ];

var opts = {
    'k': -2,
    'returns': '*'
};

function condition( val ) {
    return val < 4;
}

var results = compute.find( arr, opts, condition );
// returns [ [2,3], [1,1] ]

For further documentation, see the compute-find module.

compute.dims( arr[, max] )

Computes array dimensions, including nested arrays.

var data, d;

data = [ 1, 2 ];
d = compute.dims( data );
// returns [2]

data = [ [1,2], [1,2] ];
d = compute.dims( data );
// returns [2,2]

To limit the number of dimensions returned, set the max option.

compute.issorted( arr[, comparator] )

Returns a boolean indicating if an input array is sorted.

var bool = compute.issorted( [ 2, 3, 5, 4 ] );
// returns false

By default, the method assumes ascending order. To impose an arbitrary sort order, provide a comparator function.

function descending( a, b ) {
    return b - a;
}

var bool = compute.issorted( [ 5, 4, 3, 2 ] );
// returns true

compute.isnumeric( arr )

Computes for each array element whether an element is numeric. The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is numeric and 0 means that an element is not numeric.

var out = compute.isnumeric( [ 2, '3', 5, 4, null, NaN ] );
// returns [ 1, 0, 1, 1, 0, 0 ]

compute.isnan( arr )

Computes for each array element whether an element is NaN. The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is NaN and 0 means that an element is not NaN.

var out = compute.isnan( [ 2, '3', 5, 4, null ] );
// returns [ 0, 1, 0, 0, 1 ]

compute.isfinite( arr )

Computes for each array element whether an element is a finite number. The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is a finite number and 0 means that an element is not a finite number.

var out = compute.isfinite( [ 2, 1/0, 'beep', 5, 4, -1/0, null, NaN ] );
// returns [ 1, 0, 0, 1, 1, 0, 0, 0 ]

compute.isinteger( arr )

Computes for each array element whether an element is an integer. The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is an integer and 0 means that an element is not an integer.

var out = compute.isinteger( [ 2, 1/0, 'beep', 0, -4, 3.14, null, NaN ] );
// returns [ 1, 0, 0, 1, 1, 0, 0, 0 ]

compute.isinf( arr )

Computes for each array element whether an element is infinite. The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is infinite and 0 means that an element is not infinite.

var out = compute.isinf( [ 2, 1/0, 'beep', 5, 4, -1/0 ] );
// returns [ 0, 1, 0, 0, 0, 1 ]

compute.zip( arr1, arr2,...[, opts] )

Returns an array of arrays, where the ith element (tuple) in the returned array contains the ith elements of the input arrays.

var zipped = compute.zip( [1,2], ['a','b'] );
// returns [ [1,'a'], [2,'b'] ]

For function options, see the compute-zip module.

compute.linspace( start, stop[, length] )

Generates a linearly spaced numeric array. If a length is not provided, the default output array length is 100.

var arr = compute.linspace( 0, 100, 6 );
// returns [ 0, 20, 40, 60, 80, 100 ]

compute.incrspace( start, stop[, increment] )

Generates a linearly spaced numeric array. If an increment is not provided, the default increment is 1.

var arr = compute.incrspace( 0, 11, 2 );
// returns [ 0, 2, 4, 6, 8, 10 ]

compute.logspace( a, b[, length] )

Generates a logarithmically spaced numeric array. If a length is not provided, the default output array length is 10.

var arr = compute.logspace( 0, 2, 6 );
// returns [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]

Special Functions

compute.abs( arr )

Computes an element-wise absolute value for each element of a numeric array.

var data = [ 2, -4, 2, -7, 3 ];

compute.abs( data );

Note: mutates the input array.

compute.sqrt( arr )

Computes an element-wise principal square root for each element of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

compute.sqrt( data );

Note: mutates the input array.

compute.signum( x )

Evaluates the signum function, where x may be a single numeric value or a numeric array.

var data = [ -10, -1, -0, 0, 1, 10 ];

var x = compute.signum( data );

compute.erf( x )

Evaluates the error function, where x may be a single numeric value or a numeric array.

var data = [ -10, -1, 0, 1, 10 ];

var x = compute.erf( data );

compute.erfc( x )

Evaluates the complementary error function, where x may be a single numeric value or a numeric array.

var data = [ -10, -1, 0, 1, 10 ];

var x = compute.erfc( data );

compute.erfinv( x )

Evaluates the inverse error function, where x may be a single numeric value or a numeric array.

var data = [ -1, -0.5, 0, 0.5, 1 ];

var x = compute.erfinv( data );

compute.erfcinv( x )

Evaluates the inverse complementary error function, where x may be a single numeric value or a numeric array.

var data = [ 0, 0.5, 1, 1.5, 2 ];

var x = compute.erfcinv( data );

Arithmetic

compute.add( arr, x )

Computes an element-wise addition of a numeric array, where x may be an array of equal length or a numeric value.

var data = [ 2, 4, 2, 7, 3 ];

compute.add( data, 5.5 );

Note: mutates the input array.

compute.subtract( arr, x )

Computes an element-wise subtraction of a numeric array, where x may be an array of equal length or a numeric value.

var data = [ 2, 4, 2, 7, 3 ];

compute.subtract( data, 5.5 );

Note: mutates the input array.

compute.multiply( arr, x )

Computes an element-wise multiplication of a numeric array, where x may be an array of equal length or a numeric value.

var data = [ 2, 4, 2, 7, 3 ];

compute.multiply( data, 5.5 );

Note: mutates the input array.

compute.divide( arr, x )

Computes an element-wise division of a numeric array, where x may be an array of equal length or a numeric value.

var data = [ 2, 4, 2, 7, 3 ];

compute.divide( data, 5.5 );

Note: mutates the input array.

Relational Operations

compute.eq( arr, x[, opts] )

Computes an element-wise comparison (equality) of an array, where x may either be an array of equal length or a single value (of any type).

The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is equal to a compared value and 0 means that an element is not equal to a compared value.

var data = [ 2, 4, 2, 7, 3 ],
    out;

out = compute.eq( data, 3 );
// returns [ 0, 0, 0, 0, 1 ]

out = compute.eq( data, [ 3, 4, 1, 7, 4 ] );
// returns [ 0, 1, 0, 1, 0 ]

For function options, see compute-eq.

compute.neq( arr, x[, opts] )

Computes an element-wise comparison (not equal) of an array, where x may either be an array of equal length or a single value (of any type).

The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is not equal to a compared value and 0 means that an element is equal to a compared value.

var data = [ 2, 4, 2, 7, 3 ],
    out;

out = compute.neq( data, 3 );
// returns [ 1, 1, 1, 1, 0 ]

out = compute.neq( data, [ 3, 4, 1, 7, 4 ] );
// returns [ 1, 0, 1, 0, 1 ]

For function options, see compute-neq.

compute.gt( arr, x )

Computes an element-wise comparison (greater than) of an array, where x may either be an array of equal length or a single value (number or string).

The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is greater than a compared value and 0 means that an element is not greater than a compared value.

var data = [ 2, 4, 2, 7, 3 ],
    out;

out = compute.gt( data, 3.14 );
// returns [ 0, 1, 0, 1, 0 ]

out = compute.gt( data, [3, 5, 1, 4, 4 ] );
// returns [ 0, 0, 1, 1, 0 ]

compute.geq( arr, x )

Computes an element-wise comparison (greater than or equal to) of an array, where x may either be an array of equal length or a single value (number or string).

The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is greater than or equal to a compared value and 0 means that an element is not greater than or equal to a compared value.

var data = [ 2, 4, 2, 7, 3 ],
    out;

out = compute.geq( data, 3.14 );
// returns [ 0, 1, 0, 1, 0 ]

out = compute.geq( data, [3, 5, 1, 7, 4 ] );
// returns [ 0, 0, 1, 1, 0 ]

compute.lt( arr, x )

Computes an element-wise comparison (less than) of an array, where x may either be an array of equal length or a single value (number or string).

The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is less than a compared value and 0 means that an element is not less than a compared value.

var data = [ 2, 4, 2, 7, 3 ],
    out;

out = compute.lt( data, 3.14 );
// returns [ 1, 0, 1, 0, 1 ]

out = compute.lt( data, [3, 5, 1, 4, 4 ] );
// returns [ 1, 1, 0, 0, 1 ]

compute.leq( arr, x )

Computes an element-wise comparison (less than or equal to) of an array, where x may either be an array of equal length or a single value (number or string).

The function returns an array with length equal to that of the input array. Each output array element is either 0 or 1. A value of 1 means that an element is less than or equal to a compared value and 0 means that an element is not less than or equal to a compared value.

var data = [ 2, 4, 2, 7, 3 ],
    out;

out = compute.leq( data, 3.14 );
// returns [ 1, 0, 1, 0, 1 ]

out = compute.leq( data, [3, 5, 1, 7, 4 ] );
// returns [ 1, 1, 0, 1, 1 ]

Trigonometry

compute.deg2rad( x )

Converts degrees to radians, where x may be a single numeric value or a numeric array.

var val = compute.deg2rad( 90 );
// returns pi/2

var data = [ 0, 45, 90, 135, 180 ];
compute.deg2rad( data );
// returns [ 0, pi/4, pi/2, 3pi/4, pi ]

Note: mutates the input array.

compute.rad2deg( x )

Converts radians to degrees, where x may be a single numeric value or a numeric array.

var val = compute.rad2deg( Math.PI/2 );
// returns 90

var data = [ 0, Math.PI/4, Math.PI/2, 3*Math.PI/4, Math.PI ];
compute.rad2deg( data );
// returns [ 0, 45, 90, 135, 180 ]

Note: mutates the input array.

Geometry

compute.hypot( a, b )

Computes the hypotenuse of a right triangle.

var a = 10,
    b = 12;

var c = compute.hypot( a, b );

Sets

compute.unique( arr[, sorted] )

Removes duplicate values to determine the subset containing all unique values of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

compute.unique( data );

If the input array is already sorted in ascending order, set the sorted flag to true.

Note: mutates the input array.

Discrete Mathematics

compute.gcd( arr )

Computes the greatest common divisor (gcd) of two or more integers. 

var val = compute.gcd( [48, 18] );
// returns 6

If provided an empty array, returns null.

compute.lcm( arr )

Computes the least common multiple (lcm) of two or more integers. 

var val = compute.lcm( [21, 6] );
// returns 42

If provided an empty array, returns null.

Linear Algebra

compute.l1norm( arr )

Computes the L1 norm (Manhattan/Taxicab norm) of an array of values.

var data = [ 2, 4, 2, 7, 3 ];

var norm = compute.l1norm( data );

compute.l2norm( arr )

Computes the L2 norm (Euclidean norm) of an array of values.

var data = [ 2, 4, 2, 7, 3 ];

var norm = compute.l2norm( data );

compute.linfnorm( arr )

Computes the infinity norm (Chebyshev/maximum/supremum/uniform norm) of an array of values.

var data = [ 2, 4, 2, -7, 3 ];

var norm = compute.linfnorm( data );

compute.lpnorm( arr[, p] )

Computes the Lp norm of an array of values.

var data = [ 2, 4, 2, 7, 3 ];

// Compute the L5 norm:
var norm = compute.lpnorm( data, 5 );

compute.dot( x, y )

Computes the dot product between two arrays of equal length.

var val = compute.dot( [1,2,3], [4,5,6] );

compute.cross( x, y )

Computes the cross product between two arrays of length 3.

var val = compute.cross( [1,2,3], [4,5,6] );

Statistics

compute.min( arr )

Computes the minimum value of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var min = compute.min( data );
// returns 2

compute.argmin( arr )

Computes the minimum value of a numeric array and returns the corresponding array indices.

var data = [ 2, 4, 2, 7, 3 ];

var idx = compute.argmin( data );
// returns [0,2]

compute.nanmin( arr )

Computes the minimum value of an array ignoring non-numeric values.

var data = [ null, 2, 4, 2, null, 7, 3 ];

var min = compute.nanmin( data );
// returns 2

compute.argnanmin( arr )

Computes the minimum value of an array ignoring non-numeric values and returns the corresponding array indices.

var data = [ null, 2, 4, 2, null, 7, 3 ];

var idx = compute.argnanmin( data );
// returns [1,3]

compute.incrmin()

Returns a method to compute a minimum value incrementally.

var data = [ 2, 4, 2, 7, 3 ];

var min = compute.incrmin(),
    m;

for ( var i = 0; i < data.length; i++ ) {
    m = min( data[ i ] );
    console.log( m );
}
console.log( min() );

compute.mmin( arr, window )

Computes a moving minimum over a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var arr = compute.mmin( data, 2 );

compute.cmin( arr )

Computes the cumulative minimum of a numeric array.

var data = [ 7, 4, 2, 4, 3 ];

var arr = compute.cmin( data );

compute.max( arr )

Computes the maximum value of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var max = compute.max( data );
// returns 7

compute.argmax( arr )

Computes the maximum value of a numeric array and returns the corresponding array indices.

var data = [ 2, 4, 2, 7, 7, 3 ];

var idx = compute.argmax( data );
// returns [3,4]

compute.nanmax( arr )

Computes the maximum value of a numeric array ignoring non-numeric values.

var data = [ -2, -4, null, -2, null, -7, -3 ];

var max = compute.nanmax( data );
// returns -2

compute.argnanmax( arr )

Computes the maximum value of an array ignoring non-numeric values and returns the corresponding array indices.

var data = [ null, -2, -4, -2, null, -7, -3 ];

var idx = compute.argnanmax( data );
// returns [1,3]

compute.incrmax()

Returns a method to compute a maximum value incrementally.

var data = [ 2, 4, 2, 7, 3 ];

var max = compute.incrmax(),
    m;

for ( var i = 0; i < data.length; i++ ) {
    m = max( data[ i ] );
    console.log( m );
}
console.log( max() );

compute.mmax( arr, window )

Computes a moving maximum over a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var arr = compute.mmax( data, 2 );

compute.cmax( arr )

Computes the cumulative maximum of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var arr = compute.cmax( data );

compute.range( arr )

Computes the arithmetic range of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var range = compute.range( data );

compute.sum( arr )

Computes the sum of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var sum = compute.sum( data );

compute.nansum( arr )

Computes the sum of an array ignoring any non-numeric values.

var data = [ 2, NaN, 4, 2, 7, NaN, 3 ];

var sum = compute.nansum( data );

compute.incrsum()

Returns a method to compute a sum incrementally.

var data = [ 2, 4, 2, 7, 3 ];

var sum = compute.incrsum(),
    s;

for ( var i = 0; i < data.length; i++ ) {
    s = sum( data[ i ] );
    console.log( s );
}
console.log( sum() );

compute.msum( arr, window )

Computes a moving sum over a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var arr = compute.msum( data, 2 );

compute.csum( arr )

Computes the cumulative sum of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var arr = compute.csum( data );

compute.mean( arr )

Computes the arithmetic mean of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var mean = compute.mean( data );

compute.nanmean( arr )

Computes the arithmetic mean over an array of values ignoring any non-numeric values.

var data = [ 2, 4, NaN, 2, 7, NaN, 3 ];

var mean = compute.nanmean( data );

compute.incrmean()

Returns a method to compute an arithmetic mean incrementally.

var data = [ 2, 4, 2, 7, 3 ];

var mean = compute.incrmean(),
    mu;

for ( var i = 0; i < data.length; i++ ) {
    mu = mean( data[ i ] );
    console.log( mu );
}
console.log( mean() );

compute.mmean( arr, window )

Computes a moving arithmetic mean (sliding window average) over a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var arr = compute.mmean( data, 2 );

compute.incrmmean( window )

Returns a method to compute a moving arithmetic mean incrementally. window sets the window size, i.e., the number of values over which to compute a moving mean.

var data = [ 2, 4, 2, 7, 3 ];

var mmean = compute.incrmmean( 3 ),
    mu;

for ( var i = 0; i < data.length; i++ ) {
    mu = mmean( data[ i ] );
    console.log( mu );
}
console.log( mmean() );

compute.wmean( arr, weights )

Computes a weighted mean of a numeric array.

var data = [ 2, 4, 2, 7, 3 ],
    weights = [ 1, 2, 1, 4, 0 ];

var wmean = compute.wmean( data, weights );

compute.gmean( arr )

Computes the geometric mean of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var gmean = compute.gmean( data );

compute.nangmean( arr )

Computes the geometric mean over an array of values ignoring any non-numeric values.

var data = [ 2, 4, NaN, 2, 7, NaN, 3 ];

var gmean = compute.nangmean( data );

compute.hmean( arr )

Computes the harmonic mean of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var hmean = compute.hmean( data );

compute.nanhmean( arr )

Computes the harmonic mean over an array of values ignoring any non-numeric values.

var data = [ 2, 4, NaN, 2, 7, NaN, 3 ];

var hmean = compute.nanhmean( data );

compute.qmean( arr )

Computes the quadratic mean (root mean square) of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var qmean = compute.qmean( data );

compute.nanqmean( arr )

Computes the quadratic mean (root mean square) over an array of values ignoring any non-numeric values.

var data = [ 2, 4, NaN, 2, 7, NaN, 3 ];

var qmean = compute.nanqmean( data );

compute.variance( arr )

Computes the sample variance over a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var s2 = compute.variance( data );

compute.nanvariance( arr )

Computes the sample variance over an array of values ignoring any non-numeric values.

var data = [ 2, 4, NaN, 2, 7, NaN, 3 ];

var s2 = compute.nanvariance( data );

compute.incrvariance()

Returns a method to compute a sample variance incrementally.

var data = [ 2, 4, 2, 7, 3 ];

var variance = compute.incrvariance(),
    s2;

for ( var i = 0; i < data.length; i++ ) {
    s2 = variance( data[ i ] );
    console.log( s2 );
}
console.log( variance() );

compute.stdev( arr )

Computes the sample standard deviation of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var stdev = compute.stdev( data );

compute.nanstdev( arr )

Computes the sample standard deviation over an array of values ignoring any non-numeric values.

var data = [ 2, 4, NaN, 2, 7, NaN, 3 ];

var stdev = compute.nanstdev( data );

compute.incrstdev()

Returns a method to compute a sample standard deviation incrementally.

var data = [ 2, 4, 2, 7, 3 ];

var stdev = compute.incrstdev(),
    sigma;

for ( var i = 0; i < data.length; i++ ) {
    sigma = stdev( data[ i ] );
    console.log( sigma );
}
console.log( stdev() );

compute.mode( arr )

Computes the mode of an array.

var data = [ 2, 4, 2, 7, 3 ];

var mode = compute.mode( data );

compute.median( arr[, sorted] )

Computes the median of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var median = compute.median( data );

If the input array is already sorted in ascending order, set the sorted flag to true.

compute.quantile( arr, p[, opts] )

Computes a quantile for a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var q = compute.quantile( data, 0.25 );

If the input array is already sorted in ascending order, set the sorted option to true.

var opts = {
    'sorted': true
};

var data = [ 2, 2, 3, 4, 7 ];

var q = compute.quantile( data, 0.25, opts );

compute.quantiles( arr, num[, opts] )

Computes quantiles for a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var arr = compute.quantiles( data, 3 );

If the input array is already sorted in ascending order, set the sorted option to true.

var opts = {
    'sorted': true
};

var data = [ 2, 2, 3, 4, 7 ];

var arr = compute.quantiles( data, 2, opts );

compute.iqr( arr[, opts] )

Computes the interquartile range of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var iqr = compute.iqr( data );

If the input array is already sorted in ascending order, set the sorted options flag to true.

compute.idr( arr[, opts] )

Computes the interdecile range of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var idr = compute.idr( data );

If the input array is already sorted in ascending order, set the sorted options flag to true.

compute.midrange( arr[, sorted] )

Computes the mid-range (mid-extreme) of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var mr = compute.midrange( data );

If the input array is already sorted in ascending order, set the sorted flag to true.

compute.midhinge( arr[, opts] )

Computes the midhinge of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var mh = compute.midhinge( data );

If the input array is already sorted in ascending order, set the sorted options flag to true.

compute.midsummary( arr, n[, opts] )

Computes the n% midsummary of a numeric array. n exists on the interval [0.0, 0.50] and specifies the proportion of values to discard in the distribution tails.

var data = [ 2, 4, 2, 7, 3 ];

var ms = compute.midsummary( data );

If the input array is already sorted in ascending order, set the sorted options flag to true.

compute.midmean( arr[, sorted] )

Computes the midmean of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var mm = compute.midmean( data );

If the input array is already sorted in ascending order, set the sorted flag to true.

compute.lmidmean( arr[, sorted] )

Computes the lower midmean of a numeric array.

var data = [ 2, 4, 2, 7, 3, 7, 5 ];

var lmm = compute.lmidmean( data );

If the input array is already sorted in ascending order, set the sorted flag to true.

compute.umidmean( arr[, sorted] )

Computes the upper midmean of a numeric array.

var data = [ 2, 4, 2, 7, 3, 7, 5 ];

var umm = compute.umidmean( data );

If the input array is already sorted in ascending order, set the sorted flag to true.

compute.trimean( arr[, opts] )

Computes the trimean of a numeric array.

var data = [ 2, 4, 2, 7, 3 ];

var trimean = compute.trimean( data );

If the input array is already sorted in ascending order, set the sorted options flag to true.

compute.skewness( arr )

Computes the sample skewness of an array of values.

var data = [ 2, 4, 2, 7, 3 ];

var skew = compute.skewness( data );

compute.kurtosis( arr )

Computes the sample excess kurtosis of an array of values.

var data = [ 2, 4, 2, 7, 3 ];

var kur = compute.kurtosis( data );

Information Theory

compute.hamdist( a, b )

Computes the Hamming distance between two sequences of equal length.

var a = 'beep',
    b = 'boop';

var dist = compute.hamdist( a, b );

var c = [ 4, 2, 3, 4 ],
    d = [ 2, 4, 3, 1 ];

var dist = compute.hamdist( c, d );

Fluent Interface

For data pipelines, invoking serial methods can become verbose.

data = compute.roundn( data, -3 );
data = compute.mean( data );
data = compute.roundn( data, 0 );
...

Fluent interfaces can help alleviate this problem. Such interfaces have been popularized by libraries such as jQuery and D3 which utilize method chaining.

To create a fluent interface,

var flow = compute.flow();

A flow pipeline should be initialized.

flow.value( data );

Once initialized, all compute methods are now available. The lone difference is that data should not be explicitly passed as an argument. For example,

flow
    .value( data )
    .roundn( -3 )
    .mean()
    .roundn( 0 );

To return the flow value,

var mean = flow.value();

To help understand the transformations comprising a data pipeline, flow exposes an inspect() method, which logs the current value to the console while maintaining the fluent interface.

flow.inspect();

The above flow can be modified accordingly,

flow
    .value( data )
    .inspect()
    .roundn( -3 )
    .inspect()
    .mean()
    .inspect()
    .roundn( 0 )
    .inspect();

To summarize the flow API...

flow.value( [value] )

This method is a setter/getter. If no value is provided, returns the current flow value. If a value is provided, sets the flow value.

flow.value( [ 4, 3, 6, 2 ] );

flow.inspect()

Logs the current flow value to the console, while maintaining the fluent interface.

flow.inspect();

Notes

  1. When creating flows, ensure that the output from one computation matches the input argument requirements for the next computation.
  2. For large datasets, rather than loading datasets into memory, consider using file streams and utilize stream tools such as [Flow.io](https://github.com/flow-io/flow.io).

Tests

Unit

Unit tests use the Mocha test framework with Chai assertions. To run the tests, execute the following command in the top-level application directory:

$ make test

All new feature development should have corresponding unit tests to validate correct functionality.

Test Coverage

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:

$ make test-cov

Istanbul creates a ./reports/coverage directory. To access an HTML version of the report,

$ make view-cov

License

MIT license.

Copyright © 2014. Athan Reines.