You are focusing on computational type applications of complex numbers. For those, you can do it with any languages - including machine language. It's just a matter of how much headache you want.
For instance, when constructing "software lego parts" (such as the Matlab/Simulink type), it's very annoying that you need to know what kind of signal comes in and goes out. In Malab/Simulink, for instance, you specify that the signal is of the "inherit" type (meaning you don't care what type it is - just process it). In Python, it's of type "duck", just pass it on...I don't need to care if it's real or complex. I don't need to devise yet another overloaded operator or function whenever I encounter a situation where the native language doesn't handle. "Anno Siegel" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > > What kind of awareness do you mean? > > There are some operations (as comparison) that work for reals, but not > for complex numbers. If you want your program to run with complex input, > you have to avoid such operations, whether the data type is native or not. > > What other considerations are there? A typical numeric program should > just run and give complex output when fed complex input. I made the > experiment with the Perl module Statistics::Descriptive, which was > certainly written without concern for complex input, and it works without > a hitch. I'm not sure if the (complex) variance of several complex > numbers is a reasonably interpretable quantity, but I'm certain the > maths is done right. What else do you want? > > Anno -- http://mail.python.org/mailman/listinfo/python-list
