2008/5/11 Robert Kern <[EMAIL PROTECTED]>: > Basically, you need 3 arrays: functions implementing the type-specific > inner loops, void* extra data to pass to these functions, and an array > of arrays containing the type signatures of the ufunc. In numpy, we > already have generic implementations of the loop functions for common > combinations of types. In your case, for a binary function taking two > doubles and returning a double, we have PyUFunc_dd_d(). As its extra > void* data, it takes a function pointer that actually implements the > element-wise operation. So lets start making the arrays:
Great! Thanks! Is it possible to provide a specialized implementation of reduce()? (Since reduce() can be implemented more efficiently than doing it pairwise.) > PyUFunc_None, // The identity element for reduction. > // No good one to use for this function, > // unfortunately. Is it safe to use minus infinity, or is this going to give people all kinds of warnings if they have seterr() set? Anne _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
