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sourcestats: use median distance in weight calculation

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Replace mean distance with median distance in the weight calculation.
This should make the weights less sensitive to outliers.
This commit is contained in:
Miroslav Lichvar 2017-06-26 13:54:48 +02:00
parent 6207655ab2
commit 17f32c266e
1 changed files with 6 additions and 6 deletions
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12
sourcestats.c
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@ -463,7 +463,7 @@ correct_asymmetry(SST_Stats inst, double *times_back, double *offsets)
time. E.g. a value of 4 means that we think the standard deviation time. E.g. a value of 4 means that we think the standard deviation
is four times the fluctuation of the peer distance */ is four times the fluctuation of the peer distance */
#define SD_TO_DIST_RATIO 1.0 #define SD_TO_DIST_RATIO 0.7
/* ================================================== */ /* ================================================== */
/* This function runs the linear regression operation on the data. It /* This function runs the linear regression operation on the data. It
@ -483,7 +483,7 @@ SST_DoNewRegression(SST_Stats inst)
int best_start, times_back_start; int best_start, times_back_start;
double est_intercept, est_slope, est_var, est_intercept_sd, est_slope_sd; double est_intercept, est_slope, est_var, est_intercept_sd, est_slope_sd;
int i, j, nruns; int i, j, nruns;
double min_distance, mean_distance; double min_distance, median_distance;
double sd_weight, sd; double sd_weight, sd;
double old_skew, old_freq, stress; double old_skew, old_freq, stress;
double precision; double precision;
@ -495,21 +495,21 @@ SST_DoNewRegression(SST_Stats inst)
offsets[i + inst->runs_samples] = inst->offsets[get_runsbuf_index(inst, i)]; offsets[i + inst->runs_samples] = inst->offsets[get_runsbuf_index(inst, i)];
} }
for (i = 0, mean_distance = 0.0, min_distance = DBL_MAX; i < inst->n_samples; i++) { for (i = 0, min_distance = DBL_MAX; i < inst->n_samples; i++) {
j = get_buf_index(inst, i); j = get_buf_index(inst, i);
peer_distances[i] = 0.5 * inst->peer_delays[get_runsbuf_index(inst, i)] + peer_distances[i] = 0.5 * inst->peer_delays[get_runsbuf_index(inst, i)] +
inst->peer_dispersions[j]; inst->peer_dispersions[j];
mean_distance += peer_distances[i];
if (peer_distances[i] < min_distance) { if (peer_distances[i] < min_distance) {
min_distance = peer_distances[i]; min_distance = peer_distances[i];
} }
} }
mean_distance /= inst->n_samples;
/* And now, work out the weight vector */ /* And now, work out the weight vector */
precision = LCL_GetSysPrecisionAsQuantum(); precision = LCL_GetSysPrecisionAsQuantum();
sd = (mean_distance - min_distance) / SD_TO_DIST_RATIO; median_distance = RGR_FindMedian(peer_distances, inst->n_samples);
sd = (median_distance - min_distance) / SD_TO_DIST_RATIO;
sd = CLAMP(precision, sd, min_distance); sd = CLAMP(precision, sd, min_distance);
min_distance += precision; min_distance += precision;