Chi-squared distribution median.
The median for a Chi-squared random variable is
where k > 0
is the degrees of freedom.
$ npm install distributions-chisquare-median
For use in the browser, use browserify.
var median = require( 'distributions-chisquare-median' );
Computes the median for a Chi-squared distribution with parameter k
. k
may be either a number
, an array
, a typed array
, or a matrix
.
var matrix = require( 'dstructs-matrix' ),
data,
mat,
out,
i;
out = median( 2 );
// returns ~1.405
k = [ 2, 4, 8, 16 ];
out = median( k );
// returns [ ~1.405, ~3.370, ~7.352, ~15.343 ]
k = new Float32Array( k );
out = median( k );
// returns Float64Array( [~1.405,~3.370,~7.352,~15.343] )
k = matrix( [ 2, 4, 8, 16 ], [2,2] );
/*
[ 2 4,
8 16 ]
*/
out = median( k );
/*
[ ~1.405 ~3.370,
~7.352 ~15.343 ]
*/
The function accepts the following options
:
- accessor: accessor
function
for accessingarray
values. - dtype: output
typed array
ormatrix
data type. Default:float64
. - copy:
boolean
indicating if thefunction
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.
var k = [
[0,2],
[1,4],
[2,8],
[3,16]
];
function getValue( d, i ) {
return d[ 1 ];
}
var out = median( k, {
'accessor': getValue
});
// returns [ ~1.405, ~3.370, ~7.352, ~15.343 ]
To deepset an object array
, provide a key path and, optionally, a key path separator.
var k = [
{'x':[9,2]},
{'x':[9,4]},
{'x':[9,8]},
{'x':[9,16]}
];
var out = median( k, 'x|1', '|' );
/*
[
{'x':[9,~1.405]},
{'x':[9,~3.370]},
{'x':[9,~7.352]},
{'x':[9,~15.343]},
]
*/
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).
var k, out;
k = new Float64Array( [ 2,4,8,16 ] );
out = median( k, {
'dtype': 'int32'
});
// returns Int32Array( [ 1,3,7,15 ] )
// Works for plain arrays, as well...
out = median( [2,4,8,16], {
'dtype': 'int32'
});
// returns Int32Array( [ 1,3,7,15 ] )
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
.
var k,
bool,
mat,
out,
i;
k = [ 2, 4, 8, 16 ];
out = median( k, {
'copy': false
});
// returns [ ~1.405, ~3.370, ~7.352, ~15.343 ]
bool = ( data === out );
// returns true
mat = matrix( [ 2, 4, 8, 16 ], [2,2] );
/*
[ 2 4,
8 16 ]
*/
out = median( mat, {
'copy': false
});
/*
[ ~1.405 ~3.370,
~7.352 ~15.343 ]
*/
bool = ( mat === out );
// returns true
-
If an element is not a positive number, the median is
NaN
.var k, out; out = median( -1 ); // returns NaN out = median( 0 ); // returns NaN out = median( null ); // returns NaN out = median( true ); // returns NaN out = median( {'a':'b'} ); // returns NaN out = median( [ true, null, [] ] ); // returns [ NaN, NaN, NaN ] function getValue( d, i ) { return d.x; } k = [ {'x':true}, {'x':[]}, {'x':{}}, {'x':null} ]; out = median( k, { 'accessor': getValue }); // returns [ NaN, NaN, NaN, NaN ] out = median( k, { '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, asNaN
values are cast to0
.var out = median( [ true, null, [] ], { 'dtype': 'int8' }); // returns Int8Array( [0,0,0] );
var matrix = require( 'dstructs-matrix' ),
median = require( 'distributions-chisquare-median' );
var k,
mat,
out,
tmp,
i;
// Plain arrays...
k = new Array( 10 );
for ( i = 0; i < k.length; i++ ) {
k[ i ] = i;
}
out = median( k );
// Object arrays (accessors)...
function getValue( d ) {
return d.x;
}
for ( i = 0; i < k.length; i++ ) {
k[ i ] = {
'x': k[ i ]
};
}
out = median( k, {
'accessor': getValue
});
// Deep set arrays...
for ( i = 0; i < k.length; i++ ) {
k[ i ] = {
'x': [ i, k[ i ].x ]
};
}
out = median( k, {
'path': 'x/1',
'sep': '/'
});
// Typed arrays...
k = new Float64Array( 10 );
for ( i = 0; i < k.length; i++ ) {
k[ i ] = i;
}
out = median( k );
// Matrices...
mat = matrix( k, [5,2], 'float64' );
out = median( mat );
// Matrices (custom output data type)...
out = median( mat, {
'dtype': 'uint8'
});
To run the example code from the top-level application directory,
$ 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:
$ 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:
$ make test-cov
Istanbul creates a ./reports/coverage
directory. To access an HTML version of the report,
$ make view-cov
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