making export DREAM3D compatible with results class
This commit is contained in:
Vitesh Shah
parent
12c39c0977
commit
f619cf4ff2
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@ -63,6 +63,30 @@ def _empty_like(dataset: np.ma.core.MaskedArray,
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fill_value = fill_float if dataset.dtype in np.sctypes['float'] else fill_int,
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mask = True)
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class AttributeManagerNullterm(h5py.AttributeManager):
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"""
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Attribute management for DREAM.3D hdf5 files.
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String attribute values are stored as fixed-length string with NULLTERM
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References
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----------
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https://stackoverflow.com/questions/38267076
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https://stackoverflow.com/questions/52750232
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"""
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def create(self, name, data, shape=None, dtype=None):
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if isinstance(data,str):
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tid = h5py.h5t.C_S1.copy()
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tid.set_size(len(data + ' '))
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super().create(name=name,data=data+' ',dtype = h5py.Datatype(tid))
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else:
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super().create(name=name,data=data,shape=shape,dtype=dtype)
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h5py._hl.attrs.AttributeManager = AttributeManagerNullterm # 'Monkey patch'
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class Result:
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"""
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Add data to and export data from a DADF5 file.
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@ -1920,6 +1944,127 @@ class Result:
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v.save(vtk_dir/f'{self.fname.stem}_inc{inc.split(prefix_inc)[-1].zfill(N_digits)}',
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parallel=parallel)
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def export_DREAM3D(self):
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"""
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Export the visible components to DREAM3D compatible files.
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One DREAM3D file per visible increment is created.
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The DREAM3D file is based on HDF5 file format.
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Without any regridding.
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Considers the original grid from DAMASK.
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Needs orientation data, O, present in the file.
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Parameters
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----------
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"""
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Crystal_structures = {'fcc': 1,
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'bcc': 1,
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'hcp': 0,
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'bct': 7,
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'ort': 6} #TODO: is bct Tetragonal low/Tetragonal high?
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Phase_types = {'Primary': 0} #further additions to these can be done by looking at 'Create Ensemble Info' filter, other options could be 'Precipitate' and so on.
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dx = self.size/self.cells
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for inc in util.show_progress(self.visible['increments']):
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for label in self.visible['phases']:
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try:
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data = ma.array(_read(f['/'.join([inc,'phase',label,'mechanical/O'])]))
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except ValueError: #check if the exception is correct
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print("Orientation data is not present")
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exit() # need to check if such a statement would really work.
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cell_orientation_array = np.zeros((np.prod(self.cells),3))
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phase_ID_array = np.zeros((np.prod(self.cells)),dtype=np.int32) #need to reshape it later
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at_cell_ph,in_data_ph,at_cell_ho,in_data_ho = self._mappings()
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for c in range(self.N_constituents):
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for ph in self.phases:
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cell_orientation_array[at_cell_ph[c][ph],:] = data[,:]# need to figure out these mappings a bit
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cell_orientation_array[in_data_ph[ph],:] = # need to figure out these mappings a bit
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phase_ID_array[phase_index] = count + 1 #need to figure out these mappings a bit
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job_file_no_ext = os.path.splitext(self.fname)[0]
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o = h5py.File(f'{job_file_no_ext}_increment{inc}.dream3D','w')
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o.attrs['DADF5toDREAM3D'] = '1.0'
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o.attrs['FileVersion'] = '7.0'
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for g in ['DataContainerBundles','Pipeline']: # empty groups (needed)
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o.create_group(g)
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data_container_label = 'DataContainers/SyntheticVolumeDataContainer'
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cell_data_label = data_container_label + '/CellData'
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# Data phases
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o[cell_data_label + '/Phases'] = np.reshape(phase_ID_array, \
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tuple(np.flip(self.cells))+(1,))
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# Data eulers
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orientation_data = cell_orientation_array.astype(np.float32)
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o[cell_data_label + '/Eulers'] = orientation_data.reshape(tuple(np.flip(self.cells))+(3,))
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# Attributes to CellData group
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o[cell_data_label].attrs['AttributeMatrixType'] = np.array([3],np.uint32)
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o[cell_data_label].attrs['TupleDimensions'] = np.array(self.cells,np.uint64)
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# Common Attributes for groups in CellData
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for group in ['/Phases','/Eulers']:
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o[cell_data_label + group].attrs['DataArrayVersion'] = np.array([2],np.int32)
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o[cell_data_label + group].attrs['Tuple Axis Dimensions'] = 'x={},y={},z={}'.format(*np.array(self.cells))
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# phase attributes
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o[cell_data_label + '/Phases'].attrs['ComponentDimensions'] = np.array([1],np.uint64)
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o[cell_data_label + '/Phases'].attrs['ObjectType'] = 'DataArray<int32_t>'
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o[cell_data_label + '/Phases'].attrs['TupleDimensions'] = np.array(self.cells,np.uint64)
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# Eulers attributes
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o[cell_data_label + '/Eulers'].attrs['ComponentDimensions'] = np.array([3],np.uint64)
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o[cell_data_label + '/Eulers'].attrs['ObjectType'] = 'DataArray<float>'
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o[cell_data_label + '/Eulers'].attrs['TupleDimensions'] = np.array(self.cells,np.uint64)
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# Create EnsembleAttributeMatrix
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ensemble_label = data_container_label + '/CellEnsembleData'
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# Data CrystalStructures
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o[ensemble_label + '/CrystalStructures'] = np.uint32(np.array([999] + [1]*len(self.phases)))
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# assuming only cubic crystal structures
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# Damask can give the crystal structure info but need to look into dream3d which crystal structure corresponds to which number
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o[ensemble_label + '/PhaseTypes'] = np.uint32(np.array([999] + [Phase_types['Primary']]*len(self.phases))).reshape((len(self.phases)+1,1))
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# also assuming Primary phases
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# there can be precipitates etc as well
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# Attributes Ensemble Matrix
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o[ensemble_label].attrs['AttributeMatrixType'] = np.array([11],np.uint32)
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o[ensemble_label].attrs['TupleDimensions'] = np.array([len(self.phases) + 1], np.uint64)
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# Attributes for data in Ensemble matrix
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for group in ['CrystalStructures','PhaseTypes']: # 'PhaseName' not required MD: But would be nice to take the phase name mapping
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o[ensemble_label+'/'+group].attrs['ComponentDimensions'] = np.array([1],np.uint64)
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o[ensemble_label+'/'+group].attrs['Tuple Axis Dimensions'] = f'x={len(self.phases)+1}'
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o[ensemble_label+'/'+group].attrs['DataArrayVersion'] = np.array([2],np.int32)
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o[ensemble_label+'/'+group].attrs['ObjectType'] = 'DataArray<uint32_t>'
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o[ensemble_label+'/'+group].attrs['TupleDimensions'] = np.array([len(self.phases) + 1],np.uint64)
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# Create geometry info
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geom_label = data_container_label + '/_SIMPL_GEOMETRY'
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o[geom_label + '/DIMENSIONS'] = np.int64(np.array(self.cells))
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o[geom_label + '/ORIGIN'] = np.float32(np.zeros(3))
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o[geom_label + '/SPACING'] = np.float32(dx)
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o[geom_label].attrs['GeometryName'] = 'ImageGeometry'
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o[geom_label].attrs['GeometryTypeName'] = 'ImageGeometry'
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o[geom_label].attrs['GeometryType'] = np.array([0],np.uint32)
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o[geom_label].attrs['SpatialDimensionality'] = np.array([3],np.uint32)
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o[geom_label].attrs['UnitDimensionality'] = np.array([3],np.uint32)
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def export_DADF5(self,
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fname,
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output: Union[str, List[str]] = '*'):
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