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
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