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Merge pull request FABLE-3DXRD#462 from haixing0a/master
minor update with exporting xdmf (including 5 dimensional datasets, e.g. eps_sample, UBI etc) for grainmaps.py
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‎ImageD11/forward_model/grainmaps.py

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@@ -446,6 +446,109 @@ def DS_merge_and_identify_grains_sub(DS, FirstGrainID = 0, min_misori = 3.0, dis
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print('{} grains identified out of {} regions.'.format(i+1, id0))
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return DS_merge
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def DS_to_paraview(DS, h5name = 'DS.h5'):
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"""
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Write an .xdmf file that lets you read the DS data with ParaView
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Arguments:
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DS -- a dictionary contains DS-like map from the output of ImageD11.forward_model.grainmap class
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h5name -- the corresponding h5 filename, if not exist, I will creat one
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"""
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assert 'labels' in DS.keys() and 'voxel_size' in DS.keys(), 'DS keys must contain "labels" and "voxel_size"'
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h5_relpath = os.path.split(h5name)[1]
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xdmf_filename = h5name.replace('.h5', '.xdmf')
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# write an .h5 file if it does not exist
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if not os.path.exists(h5name):
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print('{} is not found; I am creating one ...'.format(h5name))
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with h5py.File(h5name, 'w') as hout:
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for key, value in DS.items():
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hout.create_dataset(key, data = value)
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print('Done with saving DS to {}'.format(h5name))
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dims = DS['labels'].shape
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scalar_dims = dims
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vector_dims = dims + (3,)
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tensor_dims = dims + (3, 3,)
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MeshDimensions = (dims[0] + 1, dims[1] + 1, dims[2] + 1)
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MeshDimensionsStr = 'Dimensions="%d %d %d"' % MeshDimensions
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ScalarDimensionsStr = 'Dimensions="%d %d %d"' % scalar_dims
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VectorDimensionsStr = 'Dimensions="%d %d %d %d"' % vector_dims
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TensorDimensionsStr = 'Dimensions="%d %d %d %d %d"' % tensor_dims
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steps = tuple(DS['voxel_size'])
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# Write .xdmf file
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with open(xdmf_filename, 'wt') as fileID:
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fileID.write('<?xml version="1.0"?>\n')
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fileID.write('<!DOCTYPE Xdmf SYSTEM "Xdmf.dtd"[]>\n')
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fileID.write('<Xdmf xmlns:xi="http://www.w3.org/2003/XInclude" Version="2.2">\n')
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fileID.write(' <Domain>\n')
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fileID.write(' <Grid Name="GM3D" GridType="Uniform">\n')
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fileID.write(' <Topology TopologyType="3DCoRectMesh" %s></Topology>\n' % MeshDimensionsStr)
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fileID.write(' <Geometry Type="ORIGIN_DXDYDZ">\n')
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fileID.write(' <!-- Origin Z, Y, X -->\n')
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fileID.write(' <DataItem Format="XML" Dimensions="3">0 0 0</DataItem>\n')
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fileID.write(' <!-- DxDyDz (Spacing/Resolution) Z, Y, X -->\n')
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fileID.write(' <DataItem Format="XML" Dimensions="3">%.6f %.6f %.6f</DataItem>\n' % steps)
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fileID.write(' </Geometry>\n')
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# iterate over all the keys
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for key_name in DS.keys():
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array = DS[key_name]
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# work out what sort of array we have
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map_shape = array.shape
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n_dims = len(map_shape)
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if n_dims == 3:
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# scalar field
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fileID.write(' <Attribute Name="%s" AttributeType="Scalar" Center="Cell">\n' % key_name)
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fileID.write(' <DataItem Format="HDF" %s NumberType="Float" Precision="6" >%s:/%s</DataItem>\n' % (
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ScalarDimensionsStr, h5_relpath, '/' + key_name))
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fileID.write(' </Attribute>\n')
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elif n_dims == 4:
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# vector field (like IPF)
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fileID.write(' <Attribute Name="%s" AttributeType="Vector" Center="Cell">\n' % key_name)
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fileID.write(' <DataItem Format="HDF" %s NumberType="Float" Precision="6" >%s:/%s</DataItem>\n' % (
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VectorDimensionsStr, h5_relpath, '/' + key_name))
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fileID.write(' </Attribute>\n')
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elif n_dims == 5:
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assert map_shape == tensor_dims, "Tensor {} shape {} does not match {}".format(key_name, map_shape, tensor_dims)
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# Define the 9 tensor components, e.g. (xx, xy, xz, yx, yy, yz, zx, zy, zz) for eps_sample
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if key_name == 'eps_sample':
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tensor_components = [
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('xx', 0, 0), ('xy', 0, 1), ('xz', 0, 2),
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('yx', 1, 0), ('yy', 1, 1), ('yz', 1, 2),
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('zx', 2, 0), ('zy', 2, 1), ('zz', 2, 2)
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]
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else:
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tensor_components = [
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('11', 0, 0), ('12', 0, 1), ('13', 0, 2),
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('21', 1, 0), ('22', 1, 1), ('23', 1, 2),
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('31', 2, 0), ('32', 2, 1), ('33', 2, 2)
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]
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for comp_name, i, j in tensor_components:
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attr_name = "{}_{}".format(key_name, comp_name)
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fileID.write(' <Attribute Name="%s" AttributeType="Scalar" Center="Cell">\n' % attr_name)
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fileID.write(' <DataItem ItemType="HyperSlab" %s>\n' % ScalarDimensionsStr)
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fileID.write(' <DataItem Dimensions="3 5" Format="XML">\n')
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fileID.write(' %d %d %d %d %d\n' % (0, 0, 0, i, j)) # Origin: fix i, j for the component
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fileID.write(' %d %d %d %d %d\n' % (1, 1, 1, 1, 1)) # Stride: 1 in all dims
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fileID.write(' %d %d %d %d %d\n' % (dims[0], dims[1], dims[2], 1, 1)) # Count: full 3D, 1x1 in tensor dims
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fileID.write(' </DataItem>\n')
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fileID.write(' <DataItem Format="HDF" NumberType="Float" Precision="6" %s >%s:/%s</DataItem>\n' % (
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TensorDimensionsStr, h5_relpath, '/' + key_name))
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fileID.write(' </DataItem>\n')
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fileID.write(' </Attribute>\n')
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continue
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else:
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continue
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fileID.write(' </Grid>\n')
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fileID.write(' </Domain>\n')
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fileID.write('</Xdmf>\n')
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print('Done with writing xdmf file to {}'.format(xdmf_filename))
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def indexing_iterative(cf_strong, grains, ds, ucell, pars, ds_max = 1.6, tol_angle = 0.25, tol_pixel =3, peak_assign_tol = 0.25, tol_misori = 3, crystal_system='cubic', **kwargs):

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