from numpy import * import current as pc function = lambda q: q[0]*e**q[1]+1 dist = pc.Iid(pc.Normal(), 2) approx = pc.pcm(function, 2, dist, rule="G") print pc.around(approx, 14) # 1.64234906518q0q1+1.64796896005q0+1.0 print pc.E(approx, dist) # 1.0 print pc.Var(approx, dist) # 5.41311214518 #end
from numpy import * import current as pc function = lambda q: q[0] * e**q[1] + 1 dist = pc.Iid(pc.Normal(), 2) approx = pc.pcm(function, 2, dist, rule="G") print pc.around(approx, 14) # 1.64234906518q0q1+1.64796896005q0+1.0 print pc.E(approx, dist) # 1.0 print pc.Var(approx, dist) # 5.41311214518 #end
model_wrapper = pc.lazy_eval(model_wrapper, load="model_data.d") #end model_wrapper.save("model_data.d") #end samples = Q.sample(5) U = [model_wrapper(q) for q in samples.T] #end plot(z, array(U).T, "k") xlabel(r"Spacial location \verb;x;") ylabel(r"Flow velocity \verb;U;") savefig("intro1.pdf") clf() approx = pc.pcm(model_wrapper, 2, Q) #end sample = Q.sample() U1 = model_wrapper(sample) U2 = approx(*sample) #end plot(z, U1, "k-") plot(z, U2, "k--") xlabel(r"Spacial location \verb;x;") ylabel(r"Flow velocity \verb;U;") legend([r"\verb;model_solver;", r"\verb;approx;"], loc="upper left") savefig("intro2.pdf") clf()
model_wrapper = pc.lazy_eval(model_wrapper, load="model_data.d") #end model_wrapper.save("model_data.d") #end samples = Q.sample(5) U = [model_wrapper(q) for q in samples.T] #end plot(z, array(U).T, "k") xlabel(r"Spacial location \verb;x;") ylabel(r"Flow velocity \verb;U;") savefig("intro1.pdf"); clf() approx = pc.pcm(model_wrapper, 2, Q) #end sample = Q.sample() U1 = model_wrapper(sample) U2 = approx(*sample) #end plot(z, U1, "k-") plot(z, U2, "k--") xlabel(r"Spacial location \verb;x;") ylabel(r"Flow velocity \verb;U;") legend([r"\verb;model_solver;",r"\verb;approx;"], loc="upper left") savefig("intro2.pdf"); clf() E = pc.E(approx, Q)