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. -- 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 sympy+unsubscr...@googlegroups.com. To post to this group, send email to sympy@googlegroups.com. Visit this group at http://groups.google.com/group/sympy. For more options, visit https://groups.google.com/groups/opt_out.