Commit 4ce6f522 authored by Tiago Peixoto's avatar Tiago Peixoto

_reconstruction.rst: Limit output precision

This fixes tests with Python 2.7.
parent 1d7916cd
......@@ -185,9 +185,9 @@ Which yields the following output:
.. testoutput:: measured
Posterior probability of edge (11, 36): 0.801980198019802
Posterior probability of non-edge (15, 73): 0.09730973097309731
Estimated average local clustering: 0.572154 ± 0.00485314
Posterior probability of edge (11, 36): 0.801980...
Posterior probability of non-edge (15, 73): 0.097309...
Estimated average local clustering: 0.572154 ± 0.004853...
We have a successful reconstruction, where both ambiguous adjacency
matrix entries are correctly recovered. The value for the average
......@@ -306,9 +306,9 @@ Which yields:
.. testoutput:: measured
Posterior probability of edge (11, 36): 0.7901790179017901
Posterior probability of non-edge (15, 73): 0.10901090109010901
Estimated average local clustering: 0.572504 ± 0.00545337
Posterior probability of edge (11, 36): 0.790179...
Posterior probability of non-edge (15, 73): 0.109010...
Estimated average local clustering: 0.572504 ± 0.005453...
The results are very similar to the ones obtained with the uniform model
in this case, but can be quite different in situations where a large
......@@ -434,9 +434,9 @@ The above yields the output:
.. testoutput:: uncertain
Posterior probability of edge (11, 36): 0.9504950495049505
Posterior probability of non-edge (15, 73): 0.0674067406740674
Estimated average local clustering: 0.552333 ± 0.0191831
Posterior probability of edge (11, 36): 0.950495...
Posterior probability of non-edge (15, 73): 0.067406...
Estimated average local clustering: 0.552333 ± 0.019183...
The reconstruction is accurate, despite the two ambiguous entries having
the same measurement probability. The reconstructed network is visualized below.
......
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