On Jun 27, 2011, at 9:59 PM, josef.p...@gmail.com wrote: > > Just a question how things would work with the new model. > How can you implement the "use" keyword from R's cov (or cor), with > minimal data copying > > I think the basic masked array version would (or does) just assign 0 > to the missing values calculate the covariance or correlation and then > correct with the correct count.
Basically, yes. Basic operations have a generic internal fill value (0 for sum/subtraction, 1 for multiplication/division), then you just have to correct by the count. > > especially I'm interested in the complete.obs (drop any rows that > contains a NA) case In numpy.ma, there are functions to drop rows/columns that contain a masked value (they are in numpy.ma.extras, if I recall correctly): just filter your data by these functions before parsing it to np.cov. That's the kind of trivial example that is probably not worth overloading a function with optional parameters for. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
