But, what do you mean "inheriting" from NumPy's double for your scalar
data-type. This has significant implications. To define a new
data-type object (that doesn't build from the VOID data-type), you need
to flesh out the PyArray_Descr * structure and this can only be done in
C. Perhaps you are borrowing most entries in the structure builtin
double type and then filling in a few differently like setitem and
getitem? Is that accurate?
Sorry, I should have been clearer. When I talk about inheritance, I mean of the type underlying the array. For example, the built-in scalar double array has an underlying type of PyDoubleArrType_Type. My underlying type is a separate PyTypeObject. The interesting changes here are to tp_repr, tp_str, and tp_as_number. The rest of the fields are inherited from PyDoubleArrType_Type using the tp_base field.
The array itself has another statically defined type object of type PyArray_Descr, which I'm creating with a PyObject_New call and filling in with many of the entries from the descriptor returned by PyArray_DescrFromType(NPY_DOUBLE), while overriding getitem and setitem to handle PyObject* of type mxDateTime as you guessed.
> The interface used by Array_FromPyScalar does not conform with the
> documentation's claim that a negative return value indicates an error.
You must be talking about a different function. Array_FromPyScalar is
an internal function and not a C-API call. It also returns a PyObject *
not an integer. So, which function are you actually referring to?
> The return code from setitem is not checked. Instead, the code depends
> on a Python error being set.
This may be true, but how is it a problem?
It's just confusing as the documentation indicates that the setitem function should return 0 for success and a negative number for failure. But within Array_FromPyScalar, we have:
ret->descr->f->setitem(op, ret->data, ret);
if (PyErr_Occurred()) {
Py_DECREF(ret);
return NULL;
} else {
return (PyObject *)ret;
}
So, someone reading the documentation could return -1 on failure without setting the Python error flag, and the function would happily continue on its way and fail to perform the proper casts.
>
> I seem to be able to load values into the array, but I can't extract
> anything out of the array, even to print it. In gdb I've verified that
> loading DateTime.now() correctly puts a float representation of the
> date into my array. However, if I try to get the value out, I get an
> error:
> >>> mxArr[0] = DateTime.now()
> >>> mxArr[0]
> Traceback (most recent call last):
> File "<stdin>", line 1, in ?
> File "/usr/lib/python2.4/site-packages/numpy/core/numeric.py", line
> 391, in array_repr
> ', ', "array(")
> File "/usr/lib/python2.4/site-packages/numpy/core/arrayprint.py",
> line 204, in array2string
> separator, prefix)
> File "/usr/lib/python2.4/site-packages/numpy/core/arrayprint.py",
> line 160, in _array2string
> format = _floatFormat(data, precision, suppress_small)
> File "/usr/lib/python2.4/site-packages/numpy/core/arrayprint.py",
> line 281, in _floatFormat
> non_zero = _uf.absolute(data.compress(_uf.not_equal(data, 0)))
> TypeError: bad operand type for abs()
>
> I'm not sure why it's trying to call abs() on my object to print it.
Because that's the implication of inheriting from a double. It's just
part of the code that tries to format your values into an array (notice
the _floatFormat). I actually borrowed this code from numarray so I
can't speak to exactly what it's doing without more study.
Hmm, so does Numpy ignore the tp_repr and tp_str fields in the PyTypeObject of the underlying type? I admittedly haven't had a chance to look at this code closely yet.
> I have a separate PyNumberMethods attached to my object type, copied
> from the float scalar type, and nb_absolute is set to 0. When I break
> at the various functions I've registered, the last thing Numpy tries
> to do is cast my custom data type to an object type (which it does so
> successfully) via _broadcast_cast.
Don't confuse the Python object associated when an element of the array
is extracted and the data-type of the array. Also don't confuse the
PyNumberMethods of the scalar object with the ufuncs. Defining
PyNumberMethods won't usually give you the ability to calculate ufuncs.
Okay, is my understanding here correct? I am defining two type descriptors:
PyArray_Descr mxNumpyType - describes the Numpy array type.
PyTypeObject mxNumpyDataType - describes the data type of the contents of the array (i.e. mxNumpyType->typeobj points to this), inherits from PyDoubleArrType_Type and overrides some fields as mentioned above.
And the getitem and setitem functions are designed to only give/take PyObject* of type mxDateTime.
I guess it's not clear to me whether the abs() referred to by the error is an abs() ufunc or the nb_absolute pointer in the PyNumberMethods. Let me try overriding ufuncs and get back to you...
Perhaps you just want to construct an "object" array of mxDateTime's.
What is the reason you want to define an mxDateTime data-type?
Currently I am using an object array of mxDateTime's, but it's rather frustrating that I can't treat them as normal floats internally since that's really all they are.
Jonathan
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