def TaylorFit(block):
    A = []
    b = []
    for s in range(3):
        for x in range(3):
            for y in range(3):
                z = block[s,x,y]
                row = [s*s,x*x,y*y,x*y,s,x,y,1]
                A.append(row)
                b.append([z])
    params,_,_,s = lstsq(A,b)
    return params.flatten()
Init a `Category` class - 99% of the time, this will be done by setting the dom parameter.
dataset/ETHPy150Open bolme/pyvision/src/pyvision/point/DetectorDOG.py/TaylorFit--crossover with--dataset/ETHPy150Open swordapp/python-client-sword2/sword2/atom_objects.py/Category.__init__