numpy.logaddexp2(x1, x2[, out]) = Logarithm of the sum of exponentiations of the inputs in base-2. Calculates log2(2**x1

numpy.cosh(x[, out]) = Hyperbolic cosine, element-wise. Equivalent to 1/2 * (np.exp(x) + np.exp(-x)) and np

numpy.rollaxis(a, axis, start=0)

chararray.real The real part of the array. See

class numpy.random.RandomState Container for the Mersenne Twister pseudo-random number generator.

numpy.random.standard_cauchy(size=None) Draw samples from a standard Cauchy distribution with mode = 0. Also

RandomState.exponential(scale=1.0, size=None) Draw samples from an exponential distribution. Its

numpy.histogramdd(sample, bins=10, range=None, normed=False, weights=None)

classmethod HermiteE.fromroots(roots, domain=[], window=None)

numpy.exp(x[, out]) = Calculate the exponential of all elements in the input array.