added accessor.js, changed related files and added tests

thedeeppp · thedeeppp · commit 3289245c5c78 · 2025-03-11T15:57:09.000+05:30
Signed-off-by: the_deeppp &lt;deepbtrivedi04@gmail.com&gt;
diff --git a/lib/node_modules/@stdlib/stats/base/variancech/lib/accessors.js b/lib/node_modules/@stdlib/stats/base/variancech/lib/accessors.js
@@ -0,0 +1,94 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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';
+
+// MAIN //
+
+/**
+* Computes the variance of a strided array using a one-pass trial mean algorithm.
+*
+* ## Method
+*
+* -   This implementation uses a one-pass trial mean approach, as suggested by Chan et al (1983).
+*
+* ## References
+*
+* -   Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958).
+* -   Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154).
+* -   Chan, Tony F., Gene H. Golub, and Randall J. LeVeque. 1983. "Algorithms for Computing the Sample Variance: Analysis and Recommendations." _The American Statistician_ 37 (3). American Statistical Association, Taylor & Francis, Ltd.: 242–47. doi:[10.1080/00031305.1983.10483115](https://doi.org/10.1080/00031305.1983.10483115).
+* -   Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036).
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {Object} x - input array object
+* @param {Function} x.get - accessor function
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - starting index
+* @returns {number} variance
+*
+* @example
+* var x = {
+*     'get': function get( i ) {
+*         return [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ][ i ];
+*     }
+* };
+* var N = 4;
+* var stride = 2;
+* var offset = 1;
+*
+* var v = variancech( N, 1, x, stride, offset );
+* // returns 6.25
+*/
+function variancech( N, correction, x, stride, offset ) {
+    var mu;
+    var ix;
+    var M2;
+    var M;
+    var d;
+    var n;
+    var i;
+
+    n = N - correction;
+    if ( N <= 0 || n <= 0.0 ) {
+        return NaN;
+    }
+    if ( N === 1 || stride === 0 ) {
+        return 0.0;
+    }
+    ix = offset;
+
+    // Use an estimate for the mean:
+    mu = x.get( ix );
+    ix += stride;
+
+    // Compute the variance...
+    M2 = 0.0;
+    M = 0.0;
+    for ( i = 1; i < N; i++ ) {
+        d = x.get( ix ) - mu;
+        M2 += d * d;
+        M += d;
+        ix += stride;
+    }
+    return (M2/n) - ((M/N)*(M/n));
+}
+
+// EXPORTS //
+
+module.exports = variancech;
diff --git a/lib/node_modules/@stdlib/stats/base/variancech/lib/index.js b/lib/node_modules/@stdlib/stats/base/variancech/lib/index.js
@@ -24,32 +24,45 @@
 * @module @stdlib/stats/base/variancech
 *
 * @example
+* var Float64Array = require( '@stdlib/array/float64' );
 * var variancech = require( '@stdlib/stats/base/variancech' );
 *
-* var x = [ 1.0, -2.0, 2.0 ];
-* var N = x.length;
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
 *
-* var v = variancech( N, 1, x, 1 );
+* var v = variancech( x.length, 1, x, 1 );
 * // returns ~4.3333
 *
 * @example
+* var Float64Array = require( '@stdlib/array/float64' );
 * var floor = require( '@stdlib/math/base/special/floor' );
 * var variancech = require( '@stdlib/stats/base/variancech' );
 *
-* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var N = floor( x.length / 2 );
 *
 * var v = variancech.ndarray( N, 1, x, 2, 1 );
 * // returns 6.25
+*
+* @example
+* var variancech = require( '@stdlib/stats/base/variancech' );
+*
+* var x = {
+*     'get': function get( i ) {
+*         return [ 1.0, -2.0, 2.0 ][ i ];
+*     }
+* };
+*
+* var v = variancech( 3, 1, x, 1 );
+* // returns ~4.3333
 */
 
 // MODULES //
 
+var ndarray = require( './ndarray.js' );
 var main = require( './main.js' );
 
 
 // EXPORTS //
 
 module.exports = main;
-
-// exports: { "ndarray": "main.ndarray" }
+module.exports.ndarray = ndarray;
diff --git a/lib/node_modules/@stdlib/stats/base/variancech/lib/main.js b/lib/node_modules/@stdlib/stats/base/variancech/lib/main.js
@@ -20,16 +20,32 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
-var variancech = require( './variancech.js' );
 var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
 
-setReadOnly( variancech, 'ndarray', ndarray );
+/**
+* Computes the variance of a strided array using a one-pass trial mean algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {NumericArray} x - input array
+* @param {integer} stride - stride length
+* @returns {number} variance
+*
+* @example
+* var x = [ 1.0, -2.0, 2.0 ];
+*
+* var v = variancech( x.length, 1, x, 1 );
+* // returns ~4.3333
+*/
+function variancech( N, correction, x, stride ) {
+    return ndarray( N, correction, x, stride, 0 );
+}
 
 
 // EXPORTS //
 
 module.exports = variancech;
+module.exports.ndarray = ndarray;
diff --git a/lib/node_modules/@stdlib/stats/base/variancech/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/variancech/lib/ndarray.js
@@ -18,6 +18,11 @@
 
 'use strict';
 
+// MODULES //
+
+var accessors = require( './accessors.js' );
+
+
 // MAIN //
 
 /**
@@ -59,6 +64,11 @@ function variancech( N, correction, x, stride, offset ) {
 	var n;
 	var i;
 
+	// Check for accessor array:
+	if ( x.get ) {
+		return accessors( N, correction, x, stride, offset );
+	}
+
 	n = N - correction;
 	if ( N <= 0 || n <= 0.0 ) {
 		return NaN;
diff --git a/lib/node_modules/@stdlib/stats/base/variancech/test/test.accessors.js b/lib/node_modules/@stdlib/stats/base/variancech/test/test.accessors.js
@@ -0,0 +1,93 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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 tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var variancech = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+    t.ok( true, __filename );
+    t.strictEqual( typeof variancech, 'function', 'main export is a function' );
+    t.end();
+});
+
+tape( 'the function supports accessor arrays', function test( t ) {
+    var x;
+    var v;
+
+    x = {
+        'get': function get( i ) {
+            return [ 1.0, -2.0, 2.0 ][ i ];
+        }
+    };
+    v = variancech( 3, 1, x, 1 );
+    t.equal( v, 4.333333333333333, 'returns expected value' );
+    t.end();
+});
+
+tape( 'the function supports accessor arrays using ndarray interface', function test( t ) {
+    var x;
+    var v;
+
+    x = {
+        'get': function get( i ) {
+            return [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ][ i ];
+        }
+    };
+    v = variancech.ndarray( 4, 1, x, 2, 1 );
+    t.equal( v, 6.25, 'returns expected value' );
+    t.end();
+});
+
+tape( 'if provided an array of length <= 0, the function returns NaN', function test( t ) {
+    var x;
+    var v;
+
+    x = {
+        'get': function get( i ) {
+            return [ 1.0, -2.0, 2.0 ][ i ];
+        }
+    };
+
+    v = variancech( 0, 1, x, 1 );
+    t.equal( isnan( v ), true, 'returns expected value' );
+    t.end();
+});
+
+tape( 'if provided a stride of 0, the function returns 0', function test( t ) {
+    var x;
+    var v;
+
+    x = {
+        'get': function get( i ) {
+            return [ 1.0, -2.0, 2.0 ][ i ];
+        }
+    };
+
+    v = variancech( 3, 1, x, 0 );
+    t.equal( v, 0.0, 'returns expected value' );
+    t.end();
+});
