numpy.logaddexp(x1, x2[, out]) = Logarithm of the sum of exponentiations of the inputs. Calculates log(exp(x1) +

numpy.floor_divide(x1, x2[, out]) = Return the largest integer smaller or equal to the division of the inputs. It is equivalent

numpy.fmod(x1, x2[, out]) = Return the element-wise remainder of division. This is the NumPy implementation of the C library

numpy.sum(a, axis=None, dtype=None, out=None, keepdims=False)

numpy.tan(x[, out]) = Compute tangent element-wise. Equivalent to np.sin(x)/np.cos(x) element-wise.

numpy.cumprod(a, axis=None, dtype=None, out=None)

numpy.fix(x, y=None)

numpy.cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None)

numpy.arctan2(x1, x2[, out]) = Element-wise arc tangent of x1/x2 choosing the quadrant correctly. The quadrant

numpy.power(x1, x2[, out]) = First array elements raised to powers from second array, element-wise. Raise each base in x1