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There are two applications that require using the NumPy array type in C extension modules: Access to numerical libraries: Extension modules can be used to make numerical libraries written in C (or languages linkable to C, such as Fortran) accessible to Python programs. The NumPy array type has the advantage of using the same data layout as arrays in C and Fortran. Mixed-language numerical code: In most numerical applications, only a small part of the total code is CPU time intensive. Only this part should thus be written in C, the rest can be written in Python. NumPy arrays are important for the interface between these two parts, because they provide equally simple access to their contents from Python and from C. This document is a tutorial for using NumPy arrays in C extensions.

If I have:     from sympy import Symbol, Integrate     x = Symbol('x')     f = x**2 + x     g = Integrate(f, x) how can I apply g to a numpy array? In other words, how can I "numpify" the g expression, injecting in it x = numpy.linspace(1, 9, 9)? What would be even nicer would be to be able to retrieve a lambda using numpy functions for g as a function of x (that way I don't have the overhead of numpifying it each time I want to apply it to an array).

Your example works as you describe on recent matplotlib versions. I suspect you are using an old one. The preferred way of handling missing points in numpy, and therefore in matplotlib and pylab, however, is via masked arrays.import pylabimport numpy as npfrom numpy import maa = [1,2,3,4,5]b = np.array([6,2,np.nan,1,9])bm = ma.masked_where(np.isnan(b), b)pylab.plot(a,bm)pylab.show()There are many other examples of masked array use in the examples directory of the matplotlib distribution.EricFernando Abilleira wrote:> Dear sourceforge community,> > I come from a Matlab environment so I am used to plotting matrices that > contain NaN elements. This is very useful because in some cases one > doesn't have data for the entire matrix. If one tries plotting the data, > the NaN elements won't be plotted.

Pyspread is a spreadsheet that accepts a pure python expression in each cell. Requires Python 2.4, Numpy 1.0.4, and wxPython 2.8.7.1.

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