There can be issues parallelizing things with SymPy because of serialization bugs.
@asmeurer K so, the best way to do this is by serialising a function that wraps lambidfy rather than creating your lambidfied function first then trying to serialise that. Thi is working for me in task nicely
def numba_func(consts): model = sp.lambdify(tuple(consts.keys()),integral,"mpmath") return model(*tuple(consts.values())) out = client.map(numba_func, consts_list) result = client.gather(out)
subeq: UNDERSCORE L_BRACE equality R_BRACE; supeq: UNDERSCORE L_BRACE equality R_BRACE;
supeqshould be using
plot.pyand came across the
check_arguments()function here. Though I sort of understand how it works, I still don't understand it's purpose. The docstrings aren't much of a help either. Can someone tell me why the function behaves that way?
>>> Sum(exp(x*sin(n/m)),(n,1,m)) Sum(exp(x*sin(n/m)), (n, 1, m)) >>> Sum(exp(x*sin(n/m)),(n,1,m)).doit() Piecewise((m*exp(c3_), Eq(exp(c2_), 1)), ((exp(c2_) - exp(c2_*(m + 1)))*exp(c3_)/(1 - exp(c2_)), True))
pip install -eor
setup.py develop. Although I personally just run Python directly from the
sympydirectory. That does not require reinstalling, as it will just import the development version of SymPy directly.
./bin/test test_solvers.py, and use
-kto select a specific test like
./bin/test -k test_whatever