Use the activate
function of your network:
numpy.array([network.activate(x) for x, _ in train])
Complete example:
from datasets import XORDataSet
from pybrain.tools.shortcuts import buildNetwork
from pybrain.supervised import BackpropTrainer
import numpy
d = XORDataSet()
n = buildNetwork(d.indim, 4, d.outdim, bias=True)
t = BackpropTrainer(n, learningrate=0.01, momentum=0.99, verbose=True)
t.trainOnDataset(d, 1000)
t.testOnData(verbose=True)
print numpy.array([n.activate(x) for x, _ in d])
(Only works in the directory pybrain/examples/supervised/backprop of pybrain because the XORDataSet is required.)