On Oct 8, 2009, at 10:54 AM, Dag Sverre Seljebotn wrote:
> Robert Bradshaw wrote:
>> On Oct 8, 2009, at 6:04 AM, Dag Sverre Seljebotn wrote:
>>
>>> I experience this:
>>>
>>> <Py_ssize_t>np.sqrt(some_float64)
>>> => TypeError: 'numpy.float64' object cannot be interpreted as an
>>> index
>>>
>>> However
>>> a) <int>np.sqrt(...) works fine, as does <long> and <long long>.
>>> b) In Python, int(np.sqrt(...)) and long(np.sqrt(...)) both works
>>> fine
>>>
>>> Is Py_ssize_t "special" when it comes to converting from Python
>>> objects?
>>> If so I find it mildly confusing and something which only increases
>>> learning curve...
>>
>> Py_ssize_t is meant for indexing, and fails for the same reason that
>>
>>>>> L = range(10)
>>>>> L[2]
>> 2
>>>>> L[2.5]
>> Traceback (most recent call last):
>> File "<stdin>", line 1, in <module>
>> TypeError: list indices must be integers, not float
>>
>> fails. This is a feature, not a bug.
>
> OK, if this is a feature, help me out with this then:
>
> I need to iterate from 0 to "lmax". When I allocate an array, it is
> always allocated of size (lmax + 1)**2, and it is convenient to be
> able
> to deduce lmax from the array shape.
>
> What type should I use for lmax to conveniently convert from a float
> (because sqrt is float, but I know I can safely truncate) and
> guarantee
> that I support the range of NumPy arrays (which essentially use
> Py_ssize_t to store shape info)? The type must be signed, otherwise I
> fall into the range(-lmax, lmax) trap all the time.
Is there not a ssize_t?
> (For the record, I think the type system is complicated enough without
> this feature -- does it have usecases where an explicit call to e.g. a
> cython.asindex() function to invoke __index__ isn't clearer?)
def __getitem__(self, Py_ssize_t ix):
...
- Robert
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