documented

python/damask/_configmaterial.py

@@ -2,6 +2,7 @@ import copy
 
 import numpy as np
 
+from . import grid_filters
 from . import Config
 from . import Lattice
 from . import Rotation
@@ -18,7 +19,7 @@ class ConfigMaterial(Config):
         ----------
         fname : file, str, or pathlib.Path, optional
             Filename or file for writing. Defaults to 'material.yaml'.
-        **kwargs : dict
+        **kwargs
             Keyword arguments parsed to yaml.dump.
 
         """
@@ -27,8 +28,50 @@ class ConfigMaterial(Config):
 
     @staticmethod
     def load_table(fname,coordinates=None,constituents={},**kwargs):
+        """
+        Load from an ASCII table.
+
+        Parameters
+        ----------
+        fname : str, file handle, or damask.Table
+            Table that contains material information.
+        coordinates : str, optional
+            Label of spatial coordiates. Used for sorting and performing a
+            sanity check. Default to None, in which case no sorting or checking is
+            peformed.
+        constituents : dict, optional
+            Entries for 'constituents'. The key is the name and the value specifies
+            the label of the data column in the table
+        **kwargs
+            Keyword arguments where the key is the name and  the value specifies
+            the label of the data column in the table
+
+        Examples
+        --------
+        >>> import damask
+        >>> import damask.ConfigMaterial as cm
+        >>> damask.Table.load('small.txt')
+            pos  pos  pos   qu   qu    qu    qu   phase    homog
+        0    0    0    0  0.19  0.8   0.24 -0.51  Aluminum SX
+        1    1    0    0  0.8   0.19  0.24 -0.51  Steel    SX
+        >>> cm.load_table('small.txt','pos',{'O':'qu','phase':'phase'},homogenization='h')
+        material:
+          - constituents:
+              - O: [0.19, 0.8, 0.24, -0.51]
+                fraction: 1.0
+                phase: Aluminum
+            homogenization: SX
+          - constituents:
+              - O: [0.8, 0.19, 0.24, -0.51]
+                fraction: 1.0
+                phase: Steel
+            homogenization: SX
+
+        """
         t = Table.load(fname)
-        if coordinates is not None: t = t.sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
+        if coordinates is not None:
+            t = t.sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
+            grid_filters.coord0_check(t.get(coordinates))
         constituents_ = {k:t.get(v) for k,v in constituents.items()}
         kwargs_       = {k:t.get(v) for k,v in kwargs.items()}
 
@@ -183,17 +226,37 @@ class ConfigMaterial(Config):
 
         Parameters
         ----------
-        constituents: scalar or numpy.ndarray
+        constituents : dict
-        **kwargs: tbd
+            Entries for 'constituents'. The key is the name and the value specifies
+            the label of the data column in the table
+        **kwargs
+            Keyword arguments where the key is the name and  the value specifies
+            the label of the data column in the table
 
         Examples
         --------
-        m = damask.ConfigMaterial()
+        >>> import damask
-        O = damask.Rotation.from_random(3).as_quaternion()
+        >>> m = damask.ConfigMaterial()
-        phase = ['Aluminum','Steel','Aluminum']
+        >>> O = damask.Rotation.from_random(3).as_quaternion()
-
+        >>> phase = ['Aluminum','Steel','Aluminum']
-        m.material_add(constituents={'phase':phase,'O':O},homogenization='SX')
+        >>> m.material_add(constituents={'phase':phase,'O':O},homogenization='SX')
-
+        material:
+          - constituents:
+              - O: [0.577764, -0.146299, -0.617669, 0.513010]
+                fraction: 1.0
+                phase: Aluminum
+            homogenization: SX
+          - constituents:
+              - O: [0.184176, 0.340305, 0.737247, 0.553840]
+                fraction: 1.0
+                phase: Steel
+            homogenization: SX
+          - constituents:
+              - O: [0.0886257, -0.144848, 0.615674, -0.769487]
+                fraction: 1.0
+                phase: Aluminum
+            homogenization: SX
+        
         """
         c = [{'constituents':u} for u in ConfigMaterial._constituents(**constituents)]
         for k,v in kwargs.items():

python/damask/_geom.py

@@ -210,6 +210,69 @@ class Geom:
         return Geom(material.reshape(grid,order='F'),size,origin,comments)
 
 
+
+    @staticmethod
+    def load_DREAM3D(fname,base_group,point_data=None,material='FeatureIds'):
+        """
+        Load a DREAM.3D file.
+
+        Parameters
+        ----------
+        fname : str
+            Filename of the DREAM.3D file
+        base_group : str
+            Name of the group (folder) below 'DataContainers'. For example
+            'SyntheticVolumeDataContainer'.
+        point_data : str, optional
+            Name of the group (folder) containing the point wise material data,
+            for example 'CellData'. Defaults to None, in which case points consecutively numbered.
+        material : str, optional
+            Name of the dataset containing the material ID. Defaults to
+            'FeatureIds'.
+
+        """
+        root_dir ='DataContainers'
+        f = h5py.File(fname, 'r')
+        g = path.join(root_dir,base_group,'_SIMPL_GEOMETRY')
+        size   = f[path.join(g,'DIMENSIONS')][()] * f[path.join(g,'SPACING')][()]
+        grid   = f[path.join(g,'DIMENSIONS')][()]
+        origin = f[path.join(g,'ORIGIN')][()]
+        group_pointwise = path.join(root_dir,base_group,point_data)
+
+        ma = np.arange(1,np.product(grid)+1,dtype=int) if point_data is None else \
+             np.reshape(f[path.join(group_pointwise,material)],grid.prod())
+
+        return Geom(ma.reshape(grid,order='F'),size,origin,util.execution_stamp('Geom','load_DREAM3D'))
+
+
+    @staticmethod
+    def load_table(fname,coordinates,labels):
+        """
+        Load an ASCII table.
+
+        Parameters
+        ----------
+        fname : str, file handle, or damask.Table
+            Table that contains geometry information.
+        coordinates : str
+            Label of the column containing the spatial coordinates.
+        labels : str or list of str
+            Label(s) of the columns containing the material definition.
+            Each unique combintation of values results in a material.
+
+        """
+        table = (fname if isinstance(fname,Table) else Table.load(fname)). \
+                sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
+
+        grid,size,origin = grid_filters.cell_coord0_gridSizeOrigin(table.get(coordinates))
+
+        labels_ = [labels] if isinstance(labels,str) else labels
+        _,unique_inverse = np.unique(np.hstack([table.get(l) for l in labels_]),return_inverse=True,axis=0)
+        ma = unique_inverse.reshape(grid,order='F') + 1
+
+        return Geom(ma,size,origin,util.execution_stamp('Geom','load_table'))
+
+
     @staticmethod
     def _find_closest_seed(seeds, weights, point):
         return np.argmin(np.sum((np.broadcast_to(point,(len(seeds),3))-seeds)**2,axis=1) - weights)
@@ -400,38 +463,9 @@ class Geom:
                    )
 
 
-    @staticmethod
-    def load_DREAM3D(fname,base_group,point_data=None,material='FeatureIds'):
-        root_dir ='DataContainers'
-        f = h5py.File(fname, 'r')
-        g = path.join(root_dir,base_group,'_SIMPL_GEOMETRY')
-        size   = f[path.join(g,'DIMENSIONS')][()] * f[path.join(g,'SPACING')][()]
-        grid   = f[path.join(g,'DIMENSIONS')][()]
-        origin = f[path.join(g,'ORIGIN')][()]
-        group_pointwise = path.join(root_dir,base_group,point_data)
-
-        ma = np.arange(1,np.product(grid)+1,dtype=int) if point_data is None else \
-             np.reshape(f[path.join(group_pointwise,material)],grid.prod())
-
-        return Geom(ma.reshape(grid,order='F'),size,origin,util.execution_stamp('Geom','from_DREAM3D'))
-
-
-    @staticmethod
-    def load_table(fname,coordinates,labels):
-        table = Table.load(fname).sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
-
-        grid,size,origin = grid_filters.cell_coord0_gridSizeOrigin(table.get(coordinates))
-
-        labels_ = [labels] if isinstance(labels,str) else labels
-        _,unique_inverse = np.unique(np.hstack([table.get(l) for l in labels_]),return_inverse=True,axis=0)
-        ma = unique_inverse.reshape(grid,order='F') + 1
-
-        return Geom(ma,size,origin,util.execution_stamp('Geom','from_table'))
-
-
     def save(self,fname,compress=True):
         """
-        Generates vtk rectilinear grid.
+        Store as vtk rectilinear grid.
 
         Parameters
         ----------