Here's a simpler example:
from numpy import *
from sympy import *
x = array([(1.1, 2.2), (3.3, 4.4), (5.5, 6.6)], dtype=[('s0', '<f8'),
('s1', '<f8')])
eq = 2.0 * Symbol('s0') - Symbol('s1')
2.0*x['s0']-x['s1'] # Gives correct result at command prompt
eq.evalf(x) # Fails
The constraints are that the symbols in the equation are unknown, and there
is a random number of them that can be huge, like thousands of variables as
symbols. What is provided is the time course data x and the equation eq
which contains matching variables. I.e., The code has no way of knowing
beforehand what the variables are going to be, nor how many so a predefined
lambda will not solve the problem.
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