/.../geopluspara.sagedGOIBq.py in EXPshoot(Y, zeta, I, poladapt)
    333         Y.append(Y[_sage_const_0 ]+zeta)
    334         print('Y2 wird nun berechnet, EXP2 liefert Ausgabe über verbose')
--> 335         expI = EXP2(Y[_sage_const_0 ],zeta,poladapt).x
    336         Y.append(expI)
    337         print('EXPshoot nun ein Array von Laenge',len(Y))
 
/.../geopluspara.sagedGOIBq.py in EXP2(p0, zeta, poladapt)
    311         p2 = scipy.optimize.root(FEXP2, guess,(p0,p1),method='krylov',options={'disp':True,'line_search' : 'wolfe'})
    312     else:
--> 313         p2 = scipy.optimize.root(FEXP2, guess,(p0,p1),method='hybr',options={})
    314     #p2 = scipy.optimize.root(FEXP2, guess,(p0,p1),method='anderson',options={'disp':True})
    315     return p2
 
/.../_root.py in root(fun, x0, args, method, jac, tol, callback, options)
    169
    170     if meth == 'hybr':
--> 171         sol = _root_hybr(fun, x0, args=args, jac=jac, **options)
    172     elif meth == 'lm':
    173         sol = _root_leastsq(fun, x0, args=args, jac=jac, **options)
 
/.../scipy/optimize/minpack.py in _root_hybr(func, x0, args, jac, col_deriv, xtol, maxfev, band, eps, factor, diag, full_output, **unknown_opti
ons)
    197             maxfev = 200*(n + 1)
    198         retval = _minpack._hybrd(func, x0, args, 1, xtol, maxfev,
--> 199                                  ml, mu, epsfcn, factor, diag)
    200     else:
    201         _check_func('fsolve', 'fprime', Dfun, x0, args, n, (n,n))
 
TypeError: Cannot cast array data from dtype('O') to dtype('float64') according to the rule 'safe'

sage: arr1 = [[0,1,2],[pi,e,1]]
sage: arr1 = np.array(arr1)
sage: arr1
array([[0, 1, 2],
       [pi, e, 1]], dtype=object)

sage: nptest
array([[-0.140494062453033, -0.464602179413757],
       [0.656986598718789, 0.924412375280624]], dtype=object)

def FEXP2(p2,p0,p1):#POLYGONE müssen rein!!!
    glg = np.empty((nint,2))
    p2 = p2.reshape(nint,2)
    p0 = p0.reshape(nint,2)
    p1 = p1.reshape(nint,2)
    for i in range(-2,nint-2):
        glg[i] = WI(p0,p1,i) + WII(p1,p2,i) + WIII(p0,p1,i) + WIV(p1,p2,i)
    glg = glg.flatten()
    return glg

def startEXP(p0,zeta):#POLYGON muss rein, kein Array von Polygonen
    guess = np.empty((nint,2))
    for i in range(0,nint):
        guess[i] = vector(p0[i]) + 2*vector(zeta[i])
    print('guess shape',np.array(guess).shape, '-- wir haben einen Schaetzer!')
    return guess # will ein np.array sein...

def EXP2(p0,zeta,poladapt):
    guess = startEXP(p0,zeta) #sollte ein FLACHES Polygon-np.array sein
    p1 = np.empty((nint,2))
    for i in range(0,nint):
        p1[i] = vector(p0[i]) + vector(zeta[i])
    p0 = np.array(p0).reshape(nint,2) #testet vor allem, ob alles funktioniert
    p0 = p0.flatten()
    p1 = p1.flatten()
    guess = guess.flatten()
    if K*nint > 128:
        p2 = scipy.optimize.root(FEXP2, guess,(p0,p1),method='krylov',options={'disp':True,'line_search' : 'wolfe'})
    else:
        p2 = scipy.optimize.root(FEXP2, guess,(p0,p1),method='hybr',options={})
    return p2

--> 340         Y1 = np.empty(nint,_sage_const_2 )
TypeError: data type not understood

def NintDouble(poly): # macht aus einem Polygon ein Polygon mit doppelt so vielen Stützstellen, linear interpoliert
    polout = []
    for i in range(-1,len(poly)-1):
        polout.append(poly[i])
        temp = 1/2*(vector(poly[i+1]) - vector(poly[i]))
        polout.append(poly[i]+temp)
    return polout

polout=np.array(polout)

ValueError: could not broadcast input array from shape (16,2) into shape (8,2)