diff --git a/README.md b/README.md
index 041c40e..35d51b5 100644
--- a/README.md
+++ b/README.md
@@ -753,12 +753,10 @@ The function fitting the input samples can be by calling the point interpolant:
Then, the reconstructed function can be evaluated at the evaluation samples by calling the adaptive tree visualization:
% AdaptiveTreeVisualization --in quadratic.2D.tree --samples quadratic.2D.evaluation.samples
This will output the evaluation positions and values:
-
-0 0 1.33836e-05
-0.5 0 0.25001
-0.5 0.5 0.500006
-2 2 nan
-
+0 0 1.33836e-05
+0.5 0 0.25001
+0.5 0.5 0.500006
+2 2 nan
Note that because the last evaluation position, (2,2), is outside the bounding box of the fitting samples, the function cannot be evaluated at this point and a value of "nan" is output.