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README.md |
nanmeanors
Calculate the arithmetic mean of a strided array, ignoring
NaN
values and using ordinary recursive summation.
The arithmetic mean is defined as
Usage
var nanmeanors = require( '@stdlib/stats/base/nanmeanors' );
nanmeanors( N, x, stride )
Computes the arithmetic mean of a strided array x
, ignoring NaN
values and using ordinary recursive summation.
var x = [ 1.0, -2.0, NaN, 2.0 ];
var N = x.length;
var v = nanmeanors( N, x, 1 );
// returns ~0.3333
The function has the following parameters:
- N: number of indexed elements.
- x: input
Array
ortyped array
. - stride: index increment for
x
.
The N
and stride
parameters determine which elements in x
are accessed at runtime. For example, to compute the arithmetic mean of every other element in x
,
var floor = require( '@stdlib/math/base/special/floor' );
var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ];
var N = floor( x.length / 2 );
var v = nanmeanors( N, x, 2 );
// returns 1.25
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/array/float64' );
var floor = require( '@stdlib/math/base/special/floor' );
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length / 2 );
var v = nanmeanors( N, x1, 2 );
// returns 1.25
nanmeanors.ndarray( N, x, stride, offset )
Computes the arithmetic mean of a strided array, ignoring NaN
values and using ordinary recursive summation and alternative indexing semantics.
var x = [ 1.0, -2.0, NaN, 2.0 ];
var N = x.length;
var v = nanmeanors.ndarray( N, x, 1, 0 );
// returns ~0.33333
The function has the following additional parameters:
- offset: starting index for
x
.
While typed array
views mandate a view offset based on the underlying buffer
, the offset
parameter supports indexing semantics based on a starting index. For example, to calculate the arithmetic mean for every other value in x
starting from the second value
var floor = require( '@stdlib/math/base/special/floor' );
var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ];
var N = floor( x.length / 2 );
var v = nanmeanors.ndarray( N, x, 2, 1 );
// returns 1.25
Notes
- If
N <= 0
, both functions returnNaN
. - If every indexed element is
NaN
, both functions returnNaN
. - Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation to compute an arithmetic mean is acceptable; in all other cases, exercise due caution.
- Depending on the environment, the typed versions (
dnanmeanors
,snanmeanors
, etc.) are likely to be significantly more performant.
Examples
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var Float64Array = require( '@stdlib/array/float64' );
var nanmeanors = require( '@stdlib/stats/base/nanmeanors' );
var x;
var i;
x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
if ( randu() < 0.2 ) {
x[ i ] = NaN;
} else {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
}
console.log( x );
var v = nanmeanors( x.length, x, 1 );
console.log( v );