numpy.trapz(y, x=None, dx=1.0, axis=-1)

numpy.interp(x, xp, fp, left=None, right=None, period=None)

numpy.square(x[, out]) = Return the element-wise square of the input.

numpy.nan_to_num(x)

numpy.maximum(x1, x2[, out]) = Element-wise maximum of array elements. Compare two arrays and returns a new array containing

numpy.frexp(x[, out1, out2]) = Decompose the elements of x into mantissa and twos exponent. Returns (mantissa

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

numpy.log(x[, out]) = Natural logarithm, element-wise. The natural logarithm

numpy.mod(x1, x2[, out]) = Return element-wise remainder of division. Computes the remainder complementary to the

numpy.cos(x[, out]) = Cosine element-wise.