sigma-py / pacopy Goto Github PK

ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (3,19602,3)->(3,19602,3) (3,19602,2)->(3,19602,2)"

  # test_f_i_psi()
   # test_df_dlmbda()
--->      test_ginzburg_landau(max_steps=100, n=100)
   # plot_data()'''

<ipython-input-1-cd6944349cb4> in test_ginzburg_landau(max_steps, n)'''
   302         #     newton_tol=1.0e-10,
   303         # )
--> 304         pacopy.euler_newton(
   305             problem,
   306             u0,

~/opt/anaconda3/envs/fenicsproject/lib/python3.8/site-packages/pacopy/euler_newton.py in euler_newton(problem, u0, lmbda0, callback, max_steps, verbose, newton_tol, max_newton_steps, predictor_variant, corrector_variant, stepsize0, stepsize_max, stepsize_aggressiveness, cos_alpha_min, theta0, adaptive_theta, converge_onto_zero_eigenvalue)'''
   140     k = 0
   141     try:
--> 142         u, _ = newton(
   143             lambda u: problem.f(u, lmbda),
   144             lambda u, rhs: problem.jacobian_solver(u, lmbda, rhs),

~/opt/anaconda3/envs/fenicsproject/lib/python3.8/site-packages/pacopy/newton.py in newton(f, jacobian_solver, norm2, u0, tol, max_iter, verbose)'''
     9     u = u0
    10 
---> 11     fu = f(u)
    12     nrm = math.sqrt(norm2(fu))
    13     if verbose:

~/opt/anaconda3/envs/fenicsproject/lib/python3.8/site-packages/pacopy/euler_newton.py in <lambda>(u)'''
   141     try:
   142         u, _ = newton(
--> 143             lambda u: problem.f(u, lmbda),
   144             lambda u, rhs: problem.jacobian_solver(u, lmbda, rhs),
   145             problem.norm2_r,

<ipython-input-1-cd6944349cb4> in f(self, psi, mu)'''
    99     def f(self, psi, mu):
--> 100         keo = pyfvm.get_fvm_matrix(self.mesh, edge_kernels=[Energy(mu)])
   101         cv = self.mesh.control_volumes
   102         out = (keo * psi) / cv + (self.V + self.g * numpy.abs(psi) ** 2) * psi

~/opt/anaconda3/envs/fenicsproject/lib/python3.8/site-packages/pyfvm/fvm_matrix.py in get_fvm_matrix(mesh, edge_kernels, vertex_kernels, face_kernels, dirichlets)'''
    11     dirichlets = [] if dirichlets is None else dirichlets
    12 
---> 13     V, I, J = _get_VIJ(mesh, edge_kernels, vertex_kernels, face_kernels)
    14 
    15     # One unknown per vertex

~/opt/anaconda3/envs/fenicsproject/lib/python3.8/site-packages/pyfvm/fvm_matrix.py in _get_VIJ(mesh, edge_kernels, vertex_kernels, face_kernels)'''
    44             cell_mask = mesh.get_cell_mask(subdomain)
    45 
---> 46             v_matrix = edge_kernel.eval(mesh, cell_mask)
    47 
    48             V.append(v_matrix[0, 0].flatten())

<ipython-input-1-cd6944349cb4> in eval(self, mesh, cell_mask)'''
    35         # The dot product <magnetic_potential, edge>, executed for many
    36         # points at once; cf. <http://stackoverflow.com/a/26168677/353337>.
---> 37         beta = numpy.einsum("...k,...k->...", magnetic_potential, edge)
    38 
    39         return numpy.array( <__array_function__ internals> in einsum(*args, **kwargs)

~/opt/anaconda3/envs/fenicsproject/lib/python3.8/site-packages/numpy/core/einsumfunc.py in einsum(out, optimize, *operands, **kwargs)'''
  1348         if specified_out:
  1349             kwargs['out'] = out
-> 1350         return c_einsum(*operands, **kwargs)
  1351 
  1352     # Check the kwargs to avoid a more cryptic error later, without having to

ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (3,19602,3)->(3,19602,3) (3,19602,2)->(3,19602,2)