@@ -92,6 +92,36 @@ void igt_stats_fini(igt_stats_t *stats)
}
/**
+ * igt_stats_set_population:
+ * @stats: An #igt_stats_t instance
+ * @full_population: Whether we're dealing with sample data or a full
+ * population
+ *
+ * In statistics, we usually deal with a subset of the full data (which may be
+ * a continuous or infinite set). Data analysis is then done on a sample of
+ * this population.
+ *
+ * This has some importance as only having a sample of the data leads to
+ * [biased estimators](https://en.wikipedia.org/wiki/Bias_of_an_estimator). We
+ * currently used the information given by this method to apply
+ * [Bessel's correction](https://en.wikipedia.org/wiki/Bessel%27s_correction)
+ * to the variance.
+ *
+ * When giving #true to this function, the data set in @stats is considered a
+ * full population. It's considered a sample of a bigger population otherwise.
+ *
+ * When newly created, @stats defaults to holding sample data.
+ */
+void igt_stats_set_population(igt_stats_t *stats, bool full_population)
+{
+ if (full_population == stats->is_population)
+ return;
+
+ stats->is_population = full_population;
+ stats->mean_variance_valid = false;
+}
+
+/**
* igt_stats_push:
* @stats: An #igt_stats_t instance
* @value: An integer value
@@ -129,7 +159,10 @@ static void igt_stats_knuth_mean_variance(igt_stats_t *stats)
}
stats->mean = mean;
- stats->variance = m2 / stats->n_values;
+ if (stats->n_values > 1 && !stats->is_population)
+ stats->variance = m2 / (stats->n_values - 1);
+ else
+ stats->variance = m2 / stats->n_values;
stats->mean_variance_valid = true;
}
@@ -38,12 +38,14 @@ typedef struct {
/*< private >*/
unsigned int capacity;
+ unsigned int is_population : 1;
unsigned int mean_variance_valid : 1;
double mean, variance;
} igt_stats_t;
void igt_stats_init(igt_stats_t *stats, unsigned int capacity);
void igt_stats_fini(igt_stats_t *stats);
+void igt_stats_set_population(igt_stats_t *stats, bool full_population);
void igt_stats_push(igt_stats_t *stats, uint64_t value);
double igt_stats_get_mean(igt_stats_t *stats);
double igt_stats_get_variance(igt_stats_t *stats);
@@ -89,6 +89,7 @@ static void test_std_deviation(void)
double mean, variance, std_deviation;
igt_stats_init(&stats, 8);
+ igt_stats_set_population(&stats, true);
igt_stats_push(&stats, 2);
igt_stats_push(&stats, 4);
@@ -867,6 +867,7 @@ static void test_run(struct test_ops *test)
igt_stats_t stats;
igt_stats_init(&stats, ARRAY_SIZE(modes));
+ igt_stats_set_population(&stats, true);
for (m = 0; m < ARRAY_SIZE(modes); m++) {
struct skl_wrpll_params params = {};
This changes how we compute the variance. We want an unbiased variance when reasoning about a sample. Signed-off-by: Damien Lespiau <damien.lespiau@intel.com> --- lib/igt_stats.c | 35 ++++++++++++++++++++++++++++++++++- lib/igt_stats.h | 2 ++ lib/tests/igt_stats.c | 1 + tools/skl_compute_wrpll.c | 1 + 4 files changed, 38 insertions(+), 1 deletion(-)