Press n or j to go to the next uncovered block, b, p or k for the previous block.
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* @license Apache-2.0
*
* Copyright (c) 2018 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.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
'use strict';
// MODULES //
var sqrt = require( '@stdlib/math/base/special/sqrt' );
// MAIN //
/**
* Returns an accumulator for computing cluster statistics.
*
* @private
* @param {ndarray} out - matrix for storing cluster statistics
* @param {PositiveInteger} k - number of clusters
* @returns {Function} accumulator
*/
function stats( out, k ) {
var M2;
var i;
// Create an array for storing second moments:
M2 = [];
for ( i = 0; i < k; i++ ) {
M2.push( 0.0 );
}
return accumulator;
/**
* Updates cluster statistics.
*
* @private
* @param {NonNegativeInteger} c - cluster index to which a data point belongs
* @param {number} dist - a data point's squared distance to its respective centroid
* @returns {ndarray} matrix containing cluster statistics
*/
function accumulator( c, dist ) {
var delta;
var mu;
var N;
// Update number of data points belonging to a cluster:
N = out.get( c, 0 ) + 1;
out.set( c, 0, N );
// Update the total sum of squared distances within a cluster:
out.set( c, 1, out.get( c, 1 )+dist );
// Update the cluster's squared distance mean and standard deviation (using Welford's algorithm):
mu = out.get( c, 2 );
delta = dist - mu;
mu += delta / N;
M2[ c ] += delta * ( dist-mu );
out.set( c, 2, mu );
out.set( c, 3, sqrt( M2[c]/(N-1) ) );
return out;
}
}
// EXPORTS //
module.exports = stats;
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