legacy code not needed anymore
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Vitesh Shah
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8bb193cc70
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#!/usr/bin/env python3
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import argparse
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import os
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from pathlib import Path
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import h5py
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import numpy as np
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import damask
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from damask import Rotation
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from damask import Orientation
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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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# --------------------------------------------------------------------
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# Crystal structure specifications
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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
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class DAMASKtoDREAM3D():
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"""
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This class can convert the DAMASK data to DREAM3D compatible data.
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There can be various different types of ways DAMASK data can be represented.
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Therefore, there are multiple functions available for different purposes.
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"""
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def __init__(self,job_file,geom_file,load_file):
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"""
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Defining the common quantities for all the functions in this class.
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Parameters
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----------
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job_file: str or pathlib.Path
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Full path of the DAMASK results file.
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geom_file : str
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name of the geom file.
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load_file :
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name of the load file.
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"""
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self.job_file = Path(job_file).expanduser().absolute()
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self.geom_file = geom_file
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self.load_file = load_file
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def DAMASKtoDREAM3D(self,dx,inc):
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"""
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Creates a dream3D file from DAMASK output.
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Without any regridding.
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Considers the original grid from DAMASK.
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Parameters:
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-----------
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dx : float
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The grid spacing.
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inc: int
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increment of interest for DREAM3D processing.
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"""
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os.chdir(self.job_file.parents[0])
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#--------------------------------------------------------------------------
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#Build array of euler angles for each cell
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#--------------------------------------------------------------------------
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d = damask.Result(self.job_file)
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inc_data = d.view(increments=inc) # selecting only relevant data to reduce overload
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f = h5py.File(self.job_file,'r')
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cells = f['geometry'].attrs['cells']
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size = f['geometry'].attrs['size']
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dx = size/cells
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O_dict = inc_data.get('O')
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cell_orientation_array = np.zeros((np.prod(cells),3))
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phase_ID_array = np.zeros((np.prod(cells)),dtype=np.int32) #need to reshape it later
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for count,p in enumerate(d.phases):
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phase_index = np.where(f['cell_to/phase']['label'] == f'{p}'.encode())[0]
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if len(d.phases) > 1:
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cell_orientation_array[phase_index,:] = Rotation(O_dict[p]).as_Euler_angles()
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else:
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cell_orientation_array[phase_index,:] = Rotation(O_dict).as_Euler_angles()
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phase_ID_array[phase_index] = count + 1
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#--------------------------------------------------------------------------
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job_file_no_ext = os.path.splitext(self.job_file)[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(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(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(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(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(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(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]))
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o[ensemble_label + '/CrystalStructures'] = np.uint32(np.array([999] + [1]*len(d.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(d.phases))).reshape((len(d.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(d.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(d.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(d.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(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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