time-to-botec

Benchmark sampling in different programming languages
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dnansumkbn.c (2070B)

      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/blas/ext/base/dnansumkbn.h"
     20 #include "stdlib/math/base/assert/is_nan.h"
     21 #include <stdint.h>
     22 #include <math.h>
     23 
     24 /**
     25 * Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.
     26 *
     27 * ## Method
     28 *
     29 * -   This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974).
     30 *
     31 * ## References
     32 *
     33 * -   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).
     34 *
     35 * @param N       number of indexed elements
     36 * @param X       input array
     37 * @param stride  stride length
     38 * @return        output value
     39 */
     40 double stdlib_strided_dnansumkbn( const int64_t N, const double *X, const int64_t stride ) {
     41 	double sum;
     42 	int64_t ix;
     43 	int64_t i;
     44 	double v;
     45 	double t;
     46 	double c;
     47 
     48 	if ( N <= 0 ) {
     49 		return 0.0;
     50 	}
     51 	if ( N == 1 || stride == 0 ) {
     52 		if ( stdlib_base_is_nan( X[ 0 ] ) ) {
     53 			return 0.0;
     54 		}
     55 		return X[ 0 ];
     56 	}
     57 	if ( stride < 0 ) {
     58 		ix = (1-N) * stride;
     59 	} else {
     60 		ix = 0;
     61 	}
     62 	sum = 0.0;
     63 	c = 0.0;
     64 	for ( i = 0; i < N; i++ ) {
     65 		v = X[ ix ];
     66 		if ( !stdlib_base_is_nan( v ) ) {
     67 			t = sum + v;
     68 			if ( fabs( sum ) >= fabs( v ) ) {
     69 				c += (sum-t) + v;
     70 			} else {
     71 				c += (v-t) + sum;
     72 			}
     73 			sum = t;
     74 		}
     75 		ix += stride;
     76 	}
     77 	return sum + c;
     78 }