def evaluate(A, C):
# accelerator results
acc = A.predict(X)
# classification by C and truly
cls_c = [1 if v[1] > v[0] else 0 for v in C.predict(X)]
cls_t = [accept(Y[i], acc[i]) for i in range(N)] # to bool
# relatvie error for all test data
if eb_type == 1:
re = [error.relative_error(Y[i], acc[i]) for i in range(N)]
re_c = [
error.relative_error(Y[i], acc[i]) for i in range(N)
if cls_c[i]
]
else:
re = [error.absolute_error(Y[i], acc[i]) for i in range(N)]
re_c = [
error.absolute_error(Y[i], acc[i]) for i in range(N)
if cls_c[i]
]
# accuracy of C, recall of C
accuracy_of_C = sum(
[1.0 if cls_t[i] == cls_c[i] else 0
for i in range(N)]) / float(1e-10 + N)
recall_of_C = sum([
1.0 if cls_t[i] and cls_c[i] else 0 for i in range(N)
]) / float(1e-10 + sum([1 if v else 0 for v in cls_t]))
# invocation of C, invocation truly
invocation_of_C = float(sum([1 if v else 0
for v in cls_c])) / float(1e-10 + N)
invocation_truly = float(sum([1 if v else 0
for v in cls_t])) / float(1e-10 + N)
# re of A, re of A with C
mean_relative_error_of_A = sum(re) / float(1e-10 + len(re))
mean_relative_error_of_A_with_C = sum(re_c) / (1e-10 + len(re_c))
mean_relative_error_overall = sum(re_c) / float(1e-10 + N)
return {
'accuracy_of_C': accuracy_of_C,
'recall_of_C': recall_of_C,
'invocation_of_C': invocation_of_C,
'invocation_truly': invocation_truly,
'mean_relative_error_of_A': mean_relative_error_of_A,
'mean_relative_error_of_A_with_C': mean_relative_error_of_A_with_C,
'mean_relative_error_overall': mean_relative_error_overall
}
import error as e
import application_potential as ap
xs = [x for x, y in ap.pde_data]
ys = [y for x, y in ap.pde_data]
def analytical_function(y):
return 18*y-8
analytical = [analytical_function(y) for x, y in ap.pde_data]
print('Valor de y: ', list(y for [x, y] in ap.pde_data))
collocation_error = e.absolute_error(analytical, ap.answer)
print('Analitico:', analytical)
print('Aproximado: ', ap.answer)
print('Erro: ', collocation_error)
print(max(collocation_error))
def accept(v0, v1):
return error.relative_error(
v0, v1) <= re_bound if eb_type == 1 else error.absolute_error(
v0, v1) <= re_bound
import error as e
import application_elasticity as ae
displacement_y = []
for i in range(len(ae.answer)):
if (i % 2) != 0 and i != 0:
displacement_y.append(ae.answer[i])
xs = [x for x, y in ae.pde_data]
ys = [y for x, y in ae.pde_data]
def analytical_function(y):
return -y / 4
analytical = [analytical_function(y) for x, y in ae.pde_data]
print('Valor de y: ', list(y for [x, y] in ae.pde_data))
collocation_error = e.absolute_error(analytical, displacement_y)
print('Analitico:', analytical)
print('Aproximado: ', displacement_y)
print(collocation_error)
print(max(collocation_error))