Thanks for the comments.
You are right, that works. So that example was my lengthy scripts too far
simplified. In my actual program the functions have two arrays as input
(expectation and standard uncertainty in a measurement model) and than the
* does not work anymore. I understood from the docs that the
modules='numpy' option was meant to make this work and that is what I
experienced a year or so ago working with 2.7. So here is a modified
example that still works in 2.7 but not with me on 3.3:
import sympy
import numpy
n = 2
x = sympy.symbols('x_0:%d' % n, real=True, bounded=True)
formula = 'x_0 + x_1'
y = sympy.sympify(formula)
fx = f_x = sympy.lambdify(x, y, modules='numpy')
X = numpy.ones(n)
print('function value=', fx(*X)) # works on both pythons
a = sympy.symbols('a_0:%d' % n, real=True, bounded=True)
formula = 'a_0 * x_0 + a_1 * x_1'
y = sympy.sympify(formula)
fx = f_x = sympy.lambdify([x, a], y, modules='numpy')
a = numpy.linspace(0.5, 1.0, n)
print('function value=', fx(*[X, a])) # does not work on 3.3
gives with 3.3
print('function value=', fx(*[X, a]))
TypeError: <lambda>() missing 2 required positional arguments: 'a_0' and
'a_1'
and the same for a variation without *
print('function value=', fx(X, a))
TypeError: <lambda>() missing 2 required positional arguments: 'a_0' and
'a_1'
So still all help and explanations 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
>
>
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