mirror of https://github.com/BOINC/boinc.git
114 lines
3.0 KiB
C
114 lines
3.0 KiB
C
// This file is part of BOINC.
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// http://boinc.berkeley.edu
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// Copyright (C) 2010 University of California
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//
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// BOINC is free software; you can redistribute it and/or modify it
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// under the terms of the GNU Lesser General Public License
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// as published by the Free Software Foundation,
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// either version 3 of the License, or (at your option) any later version.
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//
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// BOINC is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
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// See the GNU Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public License
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// along with BOINC. If not, see <http://www.gnu.org/licenses/>.
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#include <math.h>
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// structure for tracking the recent average
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// of a distribution that may change over time
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//
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struct AVERAGE {
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double n; // double to avoid integer overflow
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double avg;
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inline void clear() {
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n = avg = 0;
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}
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// return true if sample exceeded limit and was truncated
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//
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inline bool update(
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double sample,
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double n_threshold,
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// after this many samples, use exponential average
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double sample_weight,
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// new samples get this weight in exp avg
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double sample_limit
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// truncate samples at avg*limit
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) {
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double delta, limit;
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bool truncated = false;
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if (sample < 0) return true;
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if (n && avg) {
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if (sample > avg*sample_limit) {
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sample = avg*sample_limit;
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truncated = true;
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}
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}
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n++;
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delta = sample - avg;
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if (n < n_threshold) {
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avg += delta/n;
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} else {
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avg += sample_weight*delta;
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}
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return truncated;
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}
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inline double get_avg() {
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return avg;
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}
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};
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// same, but variance also
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//
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struct AVERAGE_VAR : AVERAGE {
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double var;
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double q;
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inline bool update_var(
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double sample,
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double n_threshold,
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// after this many samples, use exponential average
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double sample_weight,
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// new samples get this weight in exp avg
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double sample_limit
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// truncate samples at avg*limit
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) {
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double delta, limit;
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bool truncated = false;
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if (sample < 0) return true;
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if (n && avg) {
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if (sample > avg*sample_limit) {
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sample = avg*sample_limit;
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truncated = true;
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}
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}
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n++;
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delta = sample - avg;
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if (n < n_threshold) {
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avg += delta/n;
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q += delta*(sample - avg);
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var = q/n;
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} else {
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avg += sample_weight*delta;
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double vdelta = (delta*delta - var);
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var += sample_weight*vdelta;
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}
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return truncated;
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}
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inline double get_var() {
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return var;
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}
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inline void clear() {
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AVERAGE::clear();
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var = 0;
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q = 0;
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}
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};
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