  Logical qubits encoded into a quantum code exhibit improved error rates when
the physical error rates are sufficiently low, below the pseudothreshold.
Logical error rates and pseudothresholds can be estimated for specific circuits
and noise models, and these estimates provide approximate goals for qubit
performance. However, estimates often assume uniform error rates, while real
devices have static and/or dynamic distributions of non-identical error rates
and may exhibit outliers. These distributions make it more challenging to
evaluate, compare, and rank the expected performance of quantum processors. We
numerically investigate how the logical error rate depends on parameters of the
noise distribution for the subsystem surface code and the compass code on a
subdivided hexagonal lattice. Three notable observations are found: (1) the
average logical error rate depends on the average of the physical qubit
infidelity distribution without sensitivity to higher moments (e.g., variance
or outliers) for a wide parameter range; (2) the logical error rate saturates
as errors increase at one or a few "bad" locations; and (3) a decoder that is
aware of location specific error rates modestly improves the logical error
rate. We discuss the implications of these results in the context of several
different practical sources of outliers and non-uniform qubit error rates.
