def test_node_hash():
from EvoDAG.node import Add, Mul
add = Add([21, 3])
sets = set()
sets.add(add.signature())
add2 = Add([21, 3])
assert add2.signature() in sets
assert Add([3, 21]).signature() in sets
assert Mul([2, 3]).signature() == Mul([3, 2]).signature()
def test_node_mul():
from EvoDAG.node import Mul
gp, args = create_problem_node()
r = Mul.cumprod([x.hy for x in args])
n = Mul(list(range(len(args))), ytr=gp._ytr, mask=gp._mask)
coef = n.compute_weight([r])[0]
assert n.eval(args)
r = r * coef
assert n.hy.SSE(r) == 0
assert n.hy_test.SSE(r) == 0
def test_node_mul():
from EvoDAG.node import Mul
gp, args = create_problem_node()
r = Mul.cumprod([x.hy for x in args])
n = Mul(list(range(len(args))), ytr=gp._ytr, mask=gp._mask)
coef = n.compute_weight([r])[0]
assert n.eval(args)
r = r * coef
assert n.hy.SSE(r) == 0
assert n.hy_test.SSE(r) == 0
def test_indindividual_decision_function():
Add.nargs = 2
Mul.nargs = 2
vars = Model.convert_features(X)
for x in vars:
x._eval_ts = x._eval_tr.copy()
vars = [Variable(k, weight=np.ones(1)) for k in range(len(vars))]
for i in range(len(vars)):
ind = Individual([vars[i]])
ind.decision_function(X)
hy = tonparray(ind._ind[0].hy)
[assert_almost_equals(a, b) for a, b in zip(X[:, i], hy)]
ind = Individual([
Sin(0, weight=np.ones(1)),
Add(range(2), np.ones(2)), vars[0], vars[-1]
])
ind.decision_function(X)
print(ind._ind[0].hy, ind._ind[1].hy)
hy = tonparray(ind._ind[0].hy)
y = np.sin(X[:, 0] + X[:, -1])
[assert_almost_equals(a, b) for a, b in zip(y, hy)]
y = np.sin((X[:, 0] + X[:, 1]) * X[:, 0] + X[:, 2])
ind = Individual([
Sin(0, weight=1),
Add(range(2), weight=np.ones(2)),
Mul(range(2), weight=1),
Add(range(2), weight=np.ones(2)), vars[0], vars[1], vars[0], vars[2]
])
ind.decision_function(X)
# assert v.hy.SSE(v.hy_test) == 0
hy = tonparray(ind._ind[0].hy)
[assert_almost_equals(a, b) for a, b in zip(hy, y)]
default_nargs()