time-to-botec

Benchmark sampling in different programming languages
Log | Files | Refs | README

dmeankbn.c (1622B)


      1 /**
      2 * @license Apache-2.0
      3 *
      4 * Copyright (c) 2020 The Stdlib Authors.
      5 *
      6 * Licensed under the Apache License, Version 2.0 (the "License");
      7 * you may not use this file except in compliance with the License.
      8 * You may obtain a copy of the License at
      9 *
     10 *    http://www.apache.org/licenses/LICENSE-2.0
     11 *
     12 * Unless required by applicable law or agreed to in writing, software
     13 * distributed under the License is distributed on an "AS IS" BASIS,
     14 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     15 * See the License for the specific language governing permissions and
     16 * limitations under the License.
     17 */
     18 
     19 #include "stdlib/stats/base/dmeankbn.h"
     20 #include "stdlib/blas/ext/base/dsum.h"
     21 #include <stdint.h>
     22 
     23 /**
     24 * Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.
     25 *
     26 * ## Method
     27 *
     28 * -   This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974).
     29 *
     30 * ## References
     31 *
     32 * -   Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106).
     33 *
     34 * @param N       number of indexed elements
     35 * @param X       input array
     36 * @param stride  stride length
     37 * @return        output value
     38 */
     39 double stdlib_strided_dmeankbn( const int64_t N, const double *X, const int64_t stride ) {
     40 	if ( N <= 0 ) {
     41 		return 0.0 / 0.0; // NaN
     42 	}
     43 	if ( N == 1 || stride == 0 ) {
     44 		return X[ 0 ];
     45 	}
     46 	return stdlib_strided_dsum( N, X, stride ) / (double)N;
     47 }