[Numpy-discussion] A correction to numpy trapz function

[Nadav Horesh]

The function trapz accepts x axis vector only for axis=-1. Here is my modification (correction?) to let it accept a vector x for integration along any axis:

def trapz(y, x=None, dx=1.0, axis=-1):
    """
    Integrate y(x) using samples along the given axis and the composite
    trapezoidal rule.  If x is None, spacing given by dx is assumed. If x
    is an array, it must have either the dimensions of y, or a vector of
    length matching the dimension of y along the integration axis.
    """
    y = asarray(y)
    nd = y.ndim
    slice1 = [slice(None)]*nd
    slice2 = [slice(None)]*nd
    slice1[axis] = slice(1,None)
    slice2[axis] = slice(None,-1)
    if x is None:
        d = dx
    else:
        x = asarray(x)
        if x.ndim == 1:
            if len(x) != y.shape[axis]:
                raise ValueError('x length (%d) does not match y axis %d length (%d)' % (len(x), axis, y.shape[axis]))
            d = diff(x)
            return tensordot(d, (y[slice1]+y[slice2])/2.0,(0, axis))
        d = diff(x, axis=axis)
    return add.reduce(d * (y[slice1]+y[slice2])/2.0,axis)


  Nadav.