Summarize Deviation from Isometry

Computes the standard benchmark summary used to compare graph geodesic distances with reference geodesic distances: optimal scalar calibration, relative RMS error, relative absolute error quantiles, multiplicative distortion quantiles, and distance correlations.

Usage

summarize.isometry.deviation(
  D.estimated,
  D.true,
  scale = TRUE,
  true.tol = sqrt(.Machine$double.eps)
)

Arguments

D.estimated

Estimated distance matrix or dist object.

D.true

Ground-truth distance matrix or dist object.

scale

Logical scalar. If TRUE, use isometry.scale() to optimally rescale estimated distances before computing the error.

true.tol

Non-negative tolerance. Pairs with true distance less than or equal to this value are excluded from relative metrics.

Value

A one-row data frame.

Examples

D <- as.matrix(dist(1:4))
summarize.isometry.deviation(1.1 * D, D)
#>       scale rel_rms_error rel_abs_error_median rel_abs_error_q95 distortion_q05
#> 1 0.9090909  1.289963e-16         1.110223e-16      1.387779e-16              1
#>   distortion_median distortion_q95 pearson_cor spearman_cor rel_geodesic_stress
#> 1                 1              1           1            1        1.289963e-16
#>     signed_bias shortcut_fraction q50_rel_abs_residual q90_rel_abs_residual
#> 1 -1.221245e-16                 1         1.110223e-16          1.29526e-16
#>   q95_rel_abs_residual short_band_bias mid_band_bias long_band_bias
#> 1         1.387779e-16   -1.110223e-16 -1.110223e-16  -1.480297e-16