Numpy's tests are a good starting point, but they tend to ignore corner
cases such as:
improper arguments,
strange mixtures of options,
passing in virtual ndarrays (lazy evaluation and slices),
empty arrays or scalars,
so we generally start with theirs and add more, trying to retain
compatibility.
Matti
On 14/08/2012 8:15 AM, Brandon Rhodes wrote:
... I will have to ask him - or do you know? - whether we are writing
our own tests, or just copying over NumPy's existing tests each time
we add a new feature and want to be sure that it works?
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