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) 2026 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 abs = require( '@stdlib/math/base/special/abs' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var dmediansorted = require( '@stdlib/stats/strided/dmediansorted' );
var floor = require( '@stdlib/math/base/special/floor' );
var ceil = require( '@stdlib/math/base/special/ceil' );
var max = require( '@stdlib/math/base/special/max' );
var min = require( '@stdlib/math/base/special/min' );
var PINF = require( '@stdlib/constants/float64/pinf' );
var NINF = require( '@stdlib/constants/float64/ninf' );
// MAIN //
/**
* Computes the median absolute deviation from the meadian for a sorted double-precision floating-point strided array.
*
* @param {PositiveInteger} N - number of indexed elements
* @param {Float64Array} x - sorted input array
* @param {integer} strideX - stride length
* @param {NonNegativeInteger} offsetX - starting index
* @returns {number} median absolute deviation
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
*
* var v = dmadfmsorted( x.length, x, 1, 0 );
* // returns 1.0
*/
function dmadfmsorted( N, x, strideX, offsetX ) {
var rightStart;
var leftStart;
var median;
var mid1;
var mid2;
var high;
var low;
var l1;
var l2;
var r1;
var r2;
var n1;
var n2;
var k;
if ( N <= 0 ) {
return NaN;
}
median = dmediansorted.ndarray( N, x, strideX, offsetX );
if ( isnan( median ) ) {
return NaN;
}
if ( strideX < 0 ) {
offsetX += ( N - 1 ) * strideX;
strideX = -strideX;
}
// Divide elements into two pools (Pool 1: left of middle, Pool 2: right of middle)
n1 = floor( N / 2 );
n2 = N - n1;
leftStart = offsetX + ( ( n1 - 1 ) * strideX );
rightStart = leftStart + strideX;
k = ceil( N / 2 );
low = max( 0, k - n2 );
high = min( k, n1 );
// O(log N) Binary search for the partition
while ( low <= high ) {
mid1 = floor( ( low + high ) / 2 );
mid2 = k - mid1;
// Left pool: deviations are ascending when moving away from the median (backwards)
l1 = ( mid1 <= 0 ) ? NINF : abs( x[ leftStart - ( ( mid1 - 1 ) * strideX ) ] - median );
r1 = ( mid1 >= n1 ) ? PINF : abs( x[ leftStart - ( mid1 * strideX ) ] - median );
// Right pool: deviations are ascending when moving away from the median (forwards)
l2 = ( mid2 <= 0 ) ? NINF : abs( x[ rightStart + ( ( mid2 - 1 ) * strideX ) ] - median );
r2 = ( mid2 >= n2 ) ? PINF : abs( x[ rightStart + ( mid2 * strideX ) ] - median );
if ( l1 > r2 ) {
high = mid1 - 1;
}
else if ( l2 > r1 ) {
low = mid1 + 1;
}
else {
if ( N % 2 !== 0 ) {
return max( l1, l2 );
}
return ( max( l1, l2 ) + min( r1, r2 ) ) / 2.0;
}
}
return NaN;
}
// EXPORTS //
module.exports = dmadfmsorted;
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