Hi all, I'm currently working on a function that converts a sympy (http://code.google.com/p/sympy) expression to a lambda-function. In this lambda-function all sympy builtin functions are replaced by numpy functions, since they are faster. Now it may happen that users pass sympy-symbols like pi to these lambda functions and so it is possible that numpy-functions get these symbols. The same functionality is implemented using python's math module, and it works because the math functions call the __float__ method and therefor get a number they can work with. However, numpy doesn't do this, it only looks if there is a method with the same name as the called function. e.g: >> numpy.cos(sympy.pi) <type 'exceptions.AttributeError'>: cos
whereas: >> math.cos(sympy.pi) -1.0 Would it be possible to change numpys behaviour so that x.__float__() is tried after x.cos() has failed? Or are there any other possible solutions? Thanks in advance, Sebastian _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion