time-to-botec

Benchmark sampling in different programming languages
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snanvariancetk.c (1843B)


      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/snanvariancetk.h"
     20 #include <stdint.h>
     21 
     22 /**
     23 * Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.
     24 *
     25 * @param N           number of indexed elements
     26 * @param correction  degrees of freedom adjustment
     27 * @param X           input array
     28 * @param stride      stride length
     29 * @return            output value
     30 */
     31 float stdlib_strided_snanvariancetk( const int64_t N, const float correction, const float *X, const int64_t stride ) {
     32 	int64_t ix;
     33 	int64_t n;
     34 	int64_t i;
     35 	double nc;
     36 	double dn;
     37 	float S2;
     38 	float S;
     39 	float v;
     40 
     41 	if ( N <= 0 ) {
     42 		return 0.0f / 0.0f; // NaN
     43 	}
     44 	if ( N == 1 || stride == 0 ) {
     45 		v = X[ 0 ];
     46 		if ( v == v && (double)N-(double)correction > 0.0 ) {
     47 			return 0.0f;
     48 		}
     49 		return 0.0f / 0.0f; // NaN
     50 	}
     51 	if ( stride < 0 ) {
     52 		ix = (1-N) * stride;
     53 	} else {
     54 		ix = 0;
     55 	}
     56 	S2 = 0.0f;
     57 	S = 0.0f;
     58 	n = 0;
     59 	for ( i = 0; i < N; i++ ) {
     60 		v = X[ ix ];
     61 		if ( v == v ) {
     62 			S2 += v * v;
     63 			S += v;
     64 			n += 1;
     65 		}
     66 		ix += stride;
     67 	}
     68 	dn = (double)n;
     69 	nc = dn - (double)correction;
     70 	if ( nc <= 0.0 ) {
     71 		return 0.0f / 0.0f; // NaN
     72 	}
     73 	return (float)( (double)( S2 - ( (float)((double)S/dn) * S ) ) / nc );
     74 }