public MetricBundle(S2CellMetric min, S2CellMetric max, S2CellMetric avg)
{
min_ = min;
max_ = max;
avg_ = avg;
}
public void testMinMaxAvg(String label, int level, double count,
double absError, double minValue, double maxValue, double avgValue,
S2CellMetric minMetric, S2CellMetric maxMetric, S2CellMetric avgMetric)
{
// All metrics are minimums, maximums, or averages of differential
// quantities, and therefore will not be exact for cells at any finite
// level. The differential minimum is always a lower bound, and the maximum
// is always an upper bound, but these minimums and maximums may not be
// achieved for two different reasons. First, the cells at each level are
// sampled and we may miss the most extreme examples. Second, the actual
// metric for a cell is obtained by integrating the differential quantity,
// which is not constant across the cell. Therefore cells at low levels
// (bigger cells) have smaller variations.
//
// The "tolerance" below is an attempt to model both of these effects.
// At low levels, error is dominated by the variation of differential
// quantities across the cells, while at high levels error is dominated by
// the effects of random sampling.
var tolerance = (maxMetric.GetValue(level) - minMetric.GetValue(level))
/Math.Sqrt(Math.Min(count, 0.5*(1L << level)))*10;
if (tolerance == 0)
{
tolerance = absError;
}
var minError = minValue - minMetric.GetValue(level);
var maxError = maxMetric.GetValue(level) - maxValue;
var avgError = Math.Abs(avgMetric.GetValue(level) - avgValue);
Console.WriteLine(
"%-10s (%6.0f samples, tolerance %8.3g) - Min (%9.3g : %9.3g) "
+ "Max (%9.3g : %9.3g), avg (%9.3g : %9.3g)\n", label, count,
tolerance, minError/minValue, minError/tolerance, maxError
/maxValue, maxError/tolerance, avgError/avgValue, avgError
/tolerance);
Assert.True(minMetric.GetValue(level) <= minValue + absError);
Assert.True(minMetric.GetValue(level) >= minValue - tolerance);
Console.WriteLine("Level: " + maxMetric.GetValue(level) + " Max " + (maxValue + tolerance));
Assert.True(maxMetric.GetValue(level) <= maxValue + tolerance);
Assert.True(maxMetric.GetValue(level) >= maxValue - absError);
assertDoubleNear(avgMetric.GetValue(level), avgValue, 10*tolerance);
}