stats: Add the interquartile mean (IQM)

https://en.wikipedia.org/wiki/Interquartile_mean

	The IQM is a truncated mean and so is very similar to the scoring
	method used in sports that are evaluated by a panel of judges:
	discard the lowest and the highest scores; calculate the mean
	value of the remaining scores.

It's useful to hide outliers in measurements (due to cold cache etc),
without having to worry too much about the actual distribution.

Signed-off-by: Chris Wilson <chris@chris-wilson.co.uk>

1 files changed, 37 insertions, 0 deletions

diff --git a/lib/igt_stats.c b/lib/igt_stats.c
index 9032a685..cec35876 100644
--- a/lib/igt_stats.c
+++ b/lib/igt_stats.c
@@ -491,3 +491,40 @@ double igt_stats_get_std_deviation(igt_stats_t *stats)
 
 	return sqrt(stats->variance);
 }
+
+/**
+ * igt_stats_get_iqm:
+ * @stats: An #igt_stats_t instance
+ *
+ * Retrieves the interquartile mean of the @stats dataset.
+ *
+ * The interquartile mean is a "statistical measure of central tendency".
+ * It is a truncated mean that discards the lowest and highest 25% of values,
+ * and calculates the mean value of the remaining central values.
+ */
+double igt_stats_get_iqm(igt_stats_t *stats)
+{
+	unsigned int q1, q3, i;
+	double mean;
+
+	igt_stats_ensure_sorted_values(stats);
+
+	q1 = (stats->n_values + 3) / 4;
+	q3 = 3 * stats->n_values / 4;
+
+	mean = 0;
+	for (i = 0; i <= q3 - q1; i++)
+		mean += (stats->sorted[q1 + i] - mean) / (i + 1);
+
+	if (stats->n_values % 4) {
+		double rem = .5 * (stats->n_values % 4) / 4;
+
+		q1 = (stats->n_values) / 4;
+		q3 = (3 * stats->n_values + 3) / 4;
+
+		mean += rem * (stats->sorted[q1] - mean) / i++;
+		mean += rem * (stats->sorted[q3] - mean) / i++;
+	}
+
+	return mean;
+}