Sebastian Haase wrote: > Hi, > This is a vaguely formulated question ... > When I work with memmap'ed files/arrays I have a derived class > that adds special attributes to the array class (referring to the MRC image > file format used in medical / microscopy imaging) > > What are the pros and cons for asarray() vs. asanyarray() > > One obvious con for asanyarray is that its longer and asarray is what I have > been using for the last few years ;-) >
asarray() guarantees you have a base-class array. Thus, you are not going to be thwarted by an re-definitions of infix operators, or other changed methods or attributes which you might use in your routine. asanyarray() allows a simple way of making sure your function returns any sub-class so that, for example, matrices are passed seamlessly through your function (matrix in and matrix out). However, a big drawback of asanyarray is that you must be sure that the way your function is written will not get confused by how a sub-class may overwrite the array methods and attributes. This significantly limits the application of asanyarray in my mind, as it is pretty difficult to predict what a sub-class *might* do to it's methods (including the special methods implementing the infix operators). A better way to write a function that passes any sub-class is to use asarray() so you are sure of the behavior of all methods and "infix" operators and then use the __array_wrap__ method of the actual input arguments (using __array_priority__ to choose between competing input objects). I expect that a decorator that automates this process will be added to NumPy eventually. Several examples have already been posted on this list. After getting the array result, you call the stored __array_wrap__ function which will take a base-class ndarray and return an object of the right Python-type (without copying data if possible). This is how the ufuncs work and why they can take sub-classes (actually anything with an __array__ method) and the same kind of object. -Travis ------------------------------------------------------------------------- Take Surveys. Earn Cash. Influence the Future of IT Join SourceForge.net's Techsay panel and you'll get the chance to share your opinions on IT & business topics through brief surveys -- and earn cash http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
