Numpy References¶
numpy arrays¶
matrix = numpy.zeros([rows, columns])
Access using matrix[2,3] which will return the value in row 2 and column 3.
sum of log probabilities¶
scipy.misc.logsumexp()
logsumexp([-2,-3]) = numpy.log(numpy.exp(-2) + numpy.exp(-3))
logsumexp(a, b) = log(e^a + e^b).
np.uint16
np.around