Janwillem, thanks for sending the script to the list. That's the most efficient way to get things done.
Ondrej On Mon, Jan 13, 2014 at 1:28 AM, Janwillem van Dijk <[email protected]> wrote: > I would be very glad if that could be done. My little project is part of a > discussion on uncertainty evaluation in radiation dose measurements. I try > to convince my colleagues that the traditional method developed by Gauss in > 1800 is not reliable in our field. The method of choice is Monte Carlo > integration. So I want a script where the traditional (called LPU) functions > look as much as possible to the Monte Carlo method (MCM) functions as > possible. When starting this project I also tried the *-way but thought it > ugly and not very convincing when comparing it with the numpy/scipy based > MCM (and old people like me reminds it of pointers and crashing computers). > So I was very glad discovering the numpy option in lambdify which worked as > I understood it would. So again I would be very pleased to see it working > with 3.3. > For your info please find the problem scripts and some background in the > attached archive (comments very welcome). > Cheers, Janwillem > > On Tuesday, 7 January 2014 11:04:30 UTC+1, Janwillem van Dijk wrote: >> >> I have a SymPy script with a.o. >> >> f_mean = lambdify([mu, sigma], mean, modules='numpy') >> >> >> where mean is a function of mu and sigma and mu and sigma are both arrays >> >> mu = symbols('mu_0:%d' % n, real=True, bounded=True) >> >> sigma = symbols('sigma_0:%d' % n, positive=True, real=True, bounded=True) >> >> >> Under Python 2.7.5+ SymPy 0.12.0 I can use: >> >> y = f_mean(x_n, ux_n) >> >> returning y as a numpy array of size n when x_n and ux_n are both numpy >> arrays of size n. >> >> However, with Python 3.3.2+ and SymPy 0.7.4.1-git I get (for n=5): >> >> y = f_mean(x_n, ux_n) >> TypeError: <lambda>() missing 10 required positional arguments: 'mu_2', >> 'mu_3', 'mu_4', 'mu_5', 'sigma_0', 'sigma_1', 'sigma_2', 'sigma_3', >> 'sigma_4', and 'sigma_5' >> >> >> Which is similar to what I got in Python 2.7 before I added the >> modules=numpy argument >> >> All this on ubuntu 13.10 >> >> >> Have I missed something in the docs or did I stumble on a not yet >> implemented feature? >> >> Any help very welcome.heers, >> >> Cheers, Janwillem >> >> > -- > You received this message because you are subscribed to the Google Groups > "sympy" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To post to this group, send email to [email protected]. > Visit this group at http://groups.google.com/group/sympy. > For more options, visit https://groups.google.com/groups/opt_out. -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/sympy. For more options, visit https://groups.google.com/groups/opt_out.
