> I was also a bit surprised at the following behavior: >>> a = numpy.asarray([1,1]) >>> a array([1, 1]) >>> a[0]=numpy.nan >>> a array([0, 1])
Seems to affect only the int_ arrays: >>> a = numpy.asarray([1,1], dtype=float_) >>> a array([1., 1.]) >>> a[0]=numpy.nan >>> a array([ nan, 1. ]) 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 [email protected] https://lists.sourceforge.net/lists/listinfo/numpy-discussion
