Does anyone have some vectorized code that pulls out all the row indices for any row which has an nan (or a number less than 1 or whatever). I want to subsequently be able to perform an operation with all the good rows. See the imaginary code below.
a = numpy.array([[1,2],[nan,1], [2,3]]) is_row_nan(a) == array([1]) ii = numpy.negative(is_row_nan(a)) a[ii,:] # these are the ones I want. Hopefully this is array([[1,2],[2,3]]) I can imagine doing this with a loop or with (maybe) some fancy set union stuff, but I am at a loss for vectorized versions. Thanks ------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
