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Message #20230
[Question #135076]: assemble.py crashes with 'matrices not aligned' error
New question #135076 on DOLFIN:
https://answers.launchpad.net/dolfin/+question/135076
A colleague of mine wrote some python code for a finite element project. It seems to run fine on his Mac, but I get the error below. I have been getting this error somewhat randomly at other times. Sometimes instant-clean will fix the problem, but not for everything. As is obvious from the traceback, this involves a lot of code that is not part of dolfin, but perhaps the error still makes sense?
I am running fenics under Ubuntu Maverick and installed it through a ppa repository.
Any help is appreciated.
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (10, 0))
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/home/martin/matlab/UAF-inverse/maxwell_inverse/python/experiments/plap_vs_ssa1d/invert_ssa1d_from_plap.py in <module>()
164 params.forwardproblem.l2Weight = 1e-8
165 params.forwardproblem.useH1=True # Use H1 norm for bed strength functions
--> 166 solver = InverseSolver(Vsurface,f,P,sigma,Bh,bcs=[bc],params=params)
167
168 # Perform the inversion starting with initial guess gamma0
/home/martin/matlab/UAF-inverse/maxwell_inverse/python/inverseproblems/ssa1d.pyc in __init__(self, V, f, P, sigma, Bh, bcs, params)
270 InvertIGN.__init__(self,params)
271 self.V = V
--> 272 self.forward_problem = SSA1dForward(V,f,P,sigma,Bh,bcs=bcs,params=self.params.forwardproblem)
273
274 def forwardProblem(self):
/home/martin/matlab/UAF-inverse/maxwell_inverse/python/inverseproblems/ssa1d.pyc in __init__(self, V, f, P, sigma, Bh, bcs, params)
52 raise ValueError("Unsupported boundary condition")
53
---> 54 area = assemble(Constant(1)*dx,mesh=self.V.mesh())
55 self.range_form = assemble(Constant(1/area)*self.uu*self.vv*dx)
56 if self.params.useH1:
/usr/lib/python2.6/dist-packages/dolfin/fem/assemble.pyc in assemble(form, tensor, mesh, coefficients, function_spaces, cell_domains, exterior_facet_domains, interior_facet_domains, reset_sparsity, add_values, backend, form_compiler_parameters)
98 coefficients=coefficients,
99 form_compiler_parameters=form_compiler_parameters,
--> 100 common_cell=common_cell)
101
102 # Set mesh if specified (important for functionals without a function spaces)
/usr/lib/python2.6/dist-packages/dolfin/fem/form.pyc in __init__(self, form, function_spaces, coefficients, form_compiler_parameters, common_cell)
32 # Compile form if necessary
33 if not hasattr(form, "create_cell_integral"):
---> 34 (self._compiled_form, module, self.form_data) = jit(form, form_compiler_parameters, common_cell)
35
36 else:
/usr/lib/python2.6/dist-packages/dolfin/compilemodules/jit.pyc in mpi_jit(*args, **kwargs)
45 # Just call JIT compiler when running in serial
46 if MPI.num_processes() == 1:
---> 47 return local_jit(*args, **kwargs)
48
49 # Compile first on process 0
/usr/lib/python2.6/dist-packages/dolfin/compilemodules/jit.pyc in jit(form, form_compiler_parameters, common_cell)
112 raise RuntimeError, "Form compiler must implement the jit function."
113
--> 114 return jit_compile(form, parameters=p, common_cell=common_cell)
115
116
/usr/lib/python2.6/dist-packages/ffc/jitcompiler.pyc in jit(object, parameters, common_cell)
62 return jit_element(object, parameters)
63 else:
---> 64 return jit_form(object, parameters, common_cell)
65
66 def jit_form(form, parameters=None, common_cell=None):
/usr/lib/python2.6/dist-packages/ffc/jitcompiler.pyc in jit_form(form, parameters, common_cell)
120
121 # Generate code
--> 122 compile_form(preprocessed_form, prefix=jit_object.signature(), parameters=parameters)
123
124 # Build module using Instant (through UFC)
/usr/lib/python2.6/dist-packages/ffc/compiler.pyc in compile_form(forms, object_names, prefix, parameters)
138 # Stage 2: intermediate representation
139 cpu_time = time()
--> 140 ir = compute_ir(analysis, parameters)
141 _print_timing(2, time() - cpu_time)
142
/usr/lib/python2.6/dist-packages/ffc/representation.pyc in compute_ir(analysis, parameters)
56 # Compute representation of elements
57 info("Computing representation of %d elements" % len(elements))
---> 58 ir_elements = [_compute_element_ir(e, i, element_map) for (i, e) in enumerate(elements)]
59
60 # Compute representation of dofmaps
/usr/lib/python2.6/dist-packages/ffc/representation.pyc in _compute_element_ir(ufl_element, element_id, element_map)
93 ir["evaluate_basis"] = _evaluate_basis(element, cell)
94 ir["evaluate_dof"] = _evaluate_dof(element, cell)
---> 95 ir["interpolate_vertex_values"] = _interpolate_vertex_values(element, cell)
96 ir["num_sub_elements"] = ufl_element.num_sub_elements()
97 ir["create_sub_element"] = _create_sub_foo(ufl_element, element_map)
/usr/lib/python2.6/dist-packages/ffc/representation.pyc in _interpolate_vertex_values(element, cell)
428 "mapping": e.mapping()[0],
429 "space_dim": e.space_dimension()}
--> 430 for e in all_elements(element)]
431 return ir
432
/usr/lib/python2.6/dist-packages/FIAT/finite_element.pyc in tabulate(self, order, points)
106 """Return tabulated values of derivatives up to given order of
107 basis functions at given points."""
--> 108 return self.poly_set.tabulate(points, order)
109
110 def value_shape(self):
/usr/lib/python2.6/dist-packages/FIAT/polynomial_set.pyc in tabulate(self, pts, jet_order)
65 """Returns the values of the polynomial set."""
66 result = {}
---> 67 base_vals = self.expansion_set.tabulate( self.embedded_degree , pts )
68 for i in range( jet_order + 1 ):
69 alphas = mis( self.ref_el.get_spatial_dimension() , i )
/usr/lib/python2.6/dist-packages/FIAT/expansions.pyc in tabulate(self, n, pts)
100 return numpy.array( [] )
101
--> 102 ref_pts = [ self.mapping( pt ) for pt in pts ]
103
104 def idx(p,q):
/usr/lib/python2.6/dist-packages/FIAT/expansions.pyc in <lambda>(x)
90 v2 = self.base_ref_el.get_vertices()
91 self.A,self.b = reference_element.make_affine_mapping( v1 , v2 )
---> 92 self.mapping = lambda x: numpy.dot( self.A , x ) + self.b
93 # self.scale = numpy.sqrt( numpy.linalg.det( self.A ) )
94
ValueError: matrices are not aligned
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