On 11/12/06, Pierre GM <[EMAIL PROTECTED]> wrote: > On Sunday 12 November 2006 17:08, A. M. Archibald wrote: > > On 12/11/06, Keith Goodman <[EMAIL PROTECTED]> wrote: > > > Is anybody interested in making x.max() and nanmax() behave the same > > > for matrices, except for the NaN part? That is, make > > > numpy.matlib.nanmax return a matrix instead of an array. > > Or, you could use masked arrays... In the new implementation, you can add a > mask to a subclassed array (such as matrix) to get a regular masked array. If > you fill this masked array, you get an array of the same subclass. > > >>> import numpy as N > >>> import numpy.matlib as M > >>> import maskedarray as MA > >>> x=M.rand(3,3) > >>> assert isinstance(x.max(0), M.matrix) > >>> assert isinstance(N.max(x,0), M.matrix) > >>> assert isinstance(MA.max(x,0).filled(0), M.matrix) > >>> assert isinstance(MA.max(x,0)._data, M.matrix) > > >>> x[-1,-1] = N.nan > >>> tmp = MA.max(MA.array(x,mask=N.isnan(x)), 0) > >>> assert (tmp == N.nanmax(x,0)).all() > >>> assert isinstance(tmp.filled(0), M.matrix)
I didn't know you could use masked arrays with matrices. I guess I took the name literally. I think an easier way to use masked arrays would be to introduce a new thing called mis. I could make a regular matrix x = M.rand(3,3) and assign a missing value x[0,0] = M.mis x would then behave as a missing array matrix. I could also do x[M.isnan(x)] = M.mis or x[mask] = M.mis To get the mask from x: x.mask or M.ismis(x) I think that would make missing arrays accessible to everyone. ------------------------------------------------------------------------- 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
