documented
This commit is contained in:
Martin Diehl
parent
75401dd280
commit
347c88cbb6
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@ -2,6 +2,7 @@ import copy
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import numpy as np
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from . import grid_filters
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from . import Config
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from . import Lattice
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from . import Rotation
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@ -18,7 +19,7 @@ class ConfigMaterial(Config):
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----------
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fname : file, str, or pathlib.Path, optional
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Filename or file for writing. Defaults to 'material.yaml'.
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**kwargs : dict
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**kwargs
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Keyword arguments parsed to yaml.dump.
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"""
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@ -27,8 +28,50 @@ class ConfigMaterial(Config):
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@staticmethod
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def load_table(fname,coordinates=None,constituents={},**kwargs):
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"""
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Load from an ASCII table.
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Parameters
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----------
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fname : str, file handle, or damask.Table
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Table that contains material information.
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coordinates : str, optional
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Label of spatial coordiates. Used for sorting and performing a
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sanity check. Default to None, in which case no sorting or checking is
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peformed.
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constituents : dict, optional
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Entries for 'constituents'. The key is the name and the value specifies
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the label of the data column in the table
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**kwargs
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Keyword arguments where the key is the name and the value specifies
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the label of the data column in the table
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Examples
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--------
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>>> import damask
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>>> import damask.ConfigMaterial as cm
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>>> damask.Table.load('small.txt')
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pos pos pos qu qu qu qu phase homog
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0 0 0 0 0.19 0.8 0.24 -0.51 Aluminum SX
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1 1 0 0 0.8 0.19 0.24 -0.51 Steel SX
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>>> cm.load_table('small.txt','pos',{'O':'qu','phase':'phase'},homogenization='h')
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material:
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- constituents:
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- O: [0.19, 0.8, 0.24, -0.51]
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fraction: 1.0
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phase: Aluminum
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homogenization: SX
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- constituents:
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- O: [0.8, 0.19, 0.24, -0.51]
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fraction: 1.0
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phase: Steel
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homogenization: SX
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"""
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t = Table.load(fname)
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if coordinates is not None: t = t.sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
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if coordinates is not None:
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t = t.sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
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grid_filters.coord0_check(t.get(coordinates))
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constituents_ = {k:t.get(v) for k,v in constituents.items()}
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kwargs_ = {k:t.get(v) for k,v in kwargs.items()}
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@ -183,17 +226,37 @@ class ConfigMaterial(Config):
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Parameters
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----------
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constituents: scalar or numpy.ndarray
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**kwargs: tbd
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constituents : dict
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Entries for 'constituents'. The key is the name and the value specifies
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the label of the data column in the table
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**kwargs
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Keyword arguments where the key is the name and the value specifies
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the label of the data column in the table
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Examples
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--------
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m = damask.ConfigMaterial()
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O = damask.Rotation.from_random(3).as_quaternion()
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phase = ['Aluminum','Steel','Aluminum']
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m.material_add(constituents={'phase':phase,'O':O},homogenization='SX')
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>>> import damask
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>>> m = damask.ConfigMaterial()
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>>> O = damask.Rotation.from_random(3).as_quaternion()
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>>> phase = ['Aluminum','Steel','Aluminum']
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>>> m.material_add(constituents={'phase':phase,'O':O},homogenization='SX')
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material:
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- constituents:
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- O: [0.577764, -0.146299, -0.617669, 0.513010]
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fraction: 1.0
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phase: Aluminum
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homogenization: SX
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- constituents:
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- O: [0.184176, 0.340305, 0.737247, 0.553840]
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fraction: 1.0
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phase: Steel
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homogenization: SX
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- constituents:
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- O: [0.0886257, -0.144848, 0.615674, -0.769487]
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fraction: 1.0
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phase: Aluminum
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homogenization: SX
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"""
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c = [{'constituents':u} for u in ConfigMaterial._constituents(**constituents)]
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for k,v in kwargs.items():
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@ -210,6 +210,69 @@ class Geom:
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return Geom(material.reshape(grid,order='F'),size,origin,comments)
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@staticmethod
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def load_DREAM3D(fname,base_group,point_data=None,material='FeatureIds'):
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"""
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Load a DREAM.3D file.
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Parameters
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----------
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fname : str
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Filename of the DREAM.3D file
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base_group : str
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Name of the group (folder) below 'DataContainers'. For example
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'SyntheticVolumeDataContainer'.
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point_data : str, optional
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Name of the group (folder) containing the point wise material data,
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for example 'CellData'. Defaults to None, in which case points consecutively numbered.
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material : str, optional
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Name of the dataset containing the material ID. Defaults to
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'FeatureIds'.
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"""
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root_dir ='DataContainers'
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f = h5py.File(fname, 'r')
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g = path.join(root_dir,base_group,'_SIMPL_GEOMETRY')
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size = f[path.join(g,'DIMENSIONS')][()] * f[path.join(g,'SPACING')][()]
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grid = f[path.join(g,'DIMENSIONS')][()]
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origin = f[path.join(g,'ORIGIN')][()]
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group_pointwise = path.join(root_dir,base_group,point_data)
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ma = np.arange(1,np.product(grid)+1,dtype=int) if point_data is None else \
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np.reshape(f[path.join(group_pointwise,material)],grid.prod())
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return Geom(ma.reshape(grid,order='F'),size,origin,util.execution_stamp('Geom','load_DREAM3D'))
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@staticmethod
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def load_table(fname,coordinates,labels):
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"""
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Load an ASCII table.
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Parameters
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----------
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fname : str, file handle, or damask.Table
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Table that contains geometry information.
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coordinates : str
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Label of the column containing the spatial coordinates.
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labels : str or list of str
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Label(s) of the columns containing the material definition.
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Each unique combintation of values results in a material.
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"""
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table = (fname if isinstance(fname,Table) else Table.load(fname)). \
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sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
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grid,size,origin = grid_filters.cell_coord0_gridSizeOrigin(table.get(coordinates))
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labels_ = [labels] if isinstance(labels,str) else labels
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_,unique_inverse = np.unique(np.hstack([table.get(l) for l in labels_]),return_inverse=True,axis=0)
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ma = unique_inverse.reshape(grid,order='F') + 1
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return Geom(ma,size,origin,util.execution_stamp('Geom','load_table'))
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@staticmethod
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def _find_closest_seed(seeds, weights, point):
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return np.argmin(np.sum((np.broadcast_to(point,(len(seeds),3))-seeds)**2,axis=1) - weights)
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@ -400,38 +463,9 @@ class Geom:
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)
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@staticmethod
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def load_DREAM3D(fname,base_group,point_data=None,material='FeatureIds'):
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root_dir ='DataContainers'
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f = h5py.File(fname, 'r')
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g = path.join(root_dir,base_group,'_SIMPL_GEOMETRY')
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size = f[path.join(g,'DIMENSIONS')][()] * f[path.join(g,'SPACING')][()]
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grid = f[path.join(g,'DIMENSIONS')][()]
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origin = f[path.join(g,'ORIGIN')][()]
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group_pointwise = path.join(root_dir,base_group,point_data)
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ma = np.arange(1,np.product(grid)+1,dtype=int) if point_data is None else \
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np.reshape(f[path.join(group_pointwise,material)],grid.prod())
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return Geom(ma.reshape(grid,order='F'),size,origin,util.execution_stamp('Geom','from_DREAM3D'))
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@staticmethod
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def load_table(fname,coordinates,labels):
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table = Table.load(fname).sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
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grid,size,origin = grid_filters.cell_coord0_gridSizeOrigin(table.get(coordinates))
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labels_ = [labels] if isinstance(labels,str) else labels
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_,unique_inverse = np.unique(np.hstack([table.get(l) for l in labels_]),return_inverse=True,axis=0)
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ma = unique_inverse.reshape(grid,order='F') + 1
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return Geom(ma,size,origin,util.execution_stamp('Geom','from_table'))
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def save(self,fname,compress=True):
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"""
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Generates vtk rectilinear grid.
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Store as vtk rectilinear grid.
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Parameters
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----------
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