def y1(w,x,y,z):
        return 3x\**4 + 0.5y\**3 + 2z\**2 + w
    def y2(w,x,y,z):
        return x*y * exp(z**2 - w)
    def f(x0):
        w,x,y,z = x0
        error = []
        #assuming your data is of the form
        #expected_output = [(1,2),(3,4)]
        for i in expected_output :
            error += [ y1( w, x, y, z ) - i[0],
                       y2( w, x, y, z ) - i[1],
                     ]
        return error
    x0 = ( 0.1, 2, 0.03, 40 ) # initial parameters for w,x,y,z
    result = scipy.optimize.leastsq( f, x0, epsfcn = 1e-3)