problem reading *vtk structured_grid datasets

[pasassi]

I am trying to plot CFD data with turbulucid. I have *vtk files wit STRUCTURED_GRID dataset type. These files work well with other 3d visualization packages as pyvista. But when I try to create the Case with turbulucid i get the following error.

2021-10-13 17:46:03.685 (1410.649s) [ 2DB42740] vtkPolyDataReader.cxx:126 ERR| vtkPolyDataReader (0x3b03f30): Cannot read dataset type: structured_grid

`--------------------------------------------------------------------------- IndexError Traceback (most recent call last) /tmp/ipykernel_871702/3782052166.py in 4 import turbulucid as tb 5 # ----> 6 case = tb.Case(vtk_files[0]) 7 # ------------------------------------------------------------------------- #

/usr/local/lib/python3.8/dist-packages/turbulucid-0.2-py3.8.egg/turbulucid/core/case.py in init(self, fileName, clean, pointData) 38 39 # Read in the data ---> 40 self._blockData = self.read(clean, pointData) 41 42 # Compute the cell-centres

/usr/local/lib/python3.8/dist-packages/turbulucid-0.2-py3.8.egg/turbulucid/core/case.py in read(self, clean, pointData) 458 return reader.data 459 elif fileExt == ".vtk": --> 460 return LegacyReader(fileName, clean=clean, 461 pointData=pointData).data 462 elif (fileExt == ".vtu") or (fileExt == ".vtp"):

/usr/local/lib/python3.8/dist-packages/turbulucid-0.2-py3.8.egg/turbulucid/core/readers.py in init(self, filename, clean, pointData) 175 self._vtkReader.Update() 176 --> 177 internalData = self._transform() 178 if clean: 179 internalData = self._clean(internalData)

/usr/local/lib/python3.8/dist-packages/turbulucid-0.2-py3.8.egg/turbulucid/core/readers.py in _transform(self) 93 transform = vtk.vtkTransform() 94 ---> 95 meanNormal = self._compute_normal() 96 97 axis = np.cross(meanNormal, [0, 0, 1])

/usr/local/lib/python3.8/dist-packages/turbulucid-0.2-py3.8.egg/turbulucid/core/readers.py in _compute_normal(self) 129 vtkNormals.Update() 130 normals = dsa.WrapDataObject(vtkNormals.GetOutput()).CellData["Normals"] --> 131 meanNormal = np.mean(normals, axis=0) 132 meanNormal /= np.linalg.norm(meanNormal) 133 return meanNormal

<array_function internals> in mean(*args, **kwargs)

/usr/lib/python3/dist-packages/numpy/core/fromnumeric.py in mean(a, axis, dtype, out, keepdims) 3254 return mean(axis=axis, dtype=dtype, out=out, **kwargs) 3255 -> 3256 return _methods._mean(a, axis=axis, dtype=dtype, 3257 out=out, **kwargs) 3258

/usr/lib/python3/dist-packages/numpy/core/_methods.py in _mean(a, axis, dtype, out, keepdims) 136 137 is_float16_result = False --> 138 rcount = _count_reduce_items(arr, axis) 139 # Make this warning show up first 140 if rcount == 0:

/usr/lib/python3/dist-packages/numpy/core/_methods.py in _count_reduce_items(arr, axis) 55 items = 1 56 for ax in axis: ---> 57 items *= arr.shape[ax] 58 return items 59

IndexError: tuple index out of range`

Is it possible that structured grids are not supported and I should create polydata files?

[timofeymukha]

Hi! Yes, for the moment one should use polydata. I think writing a converter using vtk should be quite straight-forward. The develop branch also supports .vtk, i.e unstructured grids. I will try to add .vts at a later point.