I ended up making a shim between the two. 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') - sqrt(Symbol('s1')) from collections import Mapping class FilterNdarray(Mapping): def __init__(self, source, t): self.source = source self.t = t def __getitem__(self, key): return self.source[key.name][self.t] def __len__(self): return len(self.source) def __iter__(self): for key in self.source: yield key def set_time(self, t): self.t = t return self y = FilterNdarray(x, 0) [eq.evalf(subs=y.set_time(t)) for t in range(x.size)] It's still horribly slow. I found someone who wrote an integrator, and they have an evalf that compiles it down to bytecode somehow. I'm going to pursue that, and it bears fruit, I'll post it as a sympy -> numpy evalf. -- 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.