Re: [Numpy-discussion] setting the attributes of an array of object
Hi, there is a way of doing this. As far as I know, you have to create your own version of numpy arrays. E. g. try this: class myNumpy(numpy.ndarray): pass Then creating an instance as in a = myNumpy(otherNumpyArray) would make `a` behave just like any other array, except that you CAN attach attributes to it. Be carefull that some (many / most ?) operations on that array will return you a normal numpy array again. I don't understand the reasons behind all of this. HTH, Sebastian Haase On 9/29/07, jelle [EMAIL PROTECTED] wrote: Hi, I'm wondering whether i can re-write the following idiom with numpy arrays: for i in some_list: i.some_attr = some_value it would be wonderful if one was able to write this idiom as arr[just_these].some_attr = some_value or setattr(arr[just_these], 'some_attr', some_value) since often expensive loops through lists of object could be avoided. any thoughts on this are much appreciated, thanks, -jelle ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] setting the attributes of an array of object
On Tuesday 16 October 2007 11:47:35 Sebastian Haase wrote: Hi, there is a way of doing this. As far as I know, you have to create your own version of numpy arrays. E. g. try this: ... Be carefull that some (many / most ?) operations on that array will return you a normal numpy array again. I don't understand the reasons behind all of this. Maybe http://www.scipy.org/Subclasses could give you some hints ? ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] setting the attributes of an array of object
Sebastian Haase wrote: Hi, there is a way of doing this. As far as I know, you have to create your own version of numpy arrays. E. g. try this: class myNumpy(numpy.ndarray): pass Then creating an instance as in a = myNumpy(otherNumpyArray) would make `a` behave just like any other array, except that you CAN attach attributes to it. Be carefull that some (many / most ?) operations on that array will return you a normal numpy array again. I don't understand the reasons behind all of this. The __array_priority__ attribute determines who wins when two different sub-classes are involved in an operation. The ndarray has a priority of 0.0. -Travis ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
