several improvements
- DataFrame.append is deprecated - restored special case `None` for Grid.vicinity_offset and Grid.clean - sorted procedures of Grid according to functionality
This commit is contained in:
parent
b1effccafe
commit
c5c2763e1f
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@ -717,6 +717,368 @@ class Grid:
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.show('material',colormap)
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.show('material',colormap)
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def canvas(self,
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cells: IntSequence = None,
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offset: IntSequence = None,
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fill: int = None) -> 'Grid':
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"""
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Crop or enlarge/pad grid.
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Parameters
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----------
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cells : sequence of int, len (3), optional
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Number of cells x,y,z direction.
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offset : sequence of int, len (3), optional
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Offset (measured in cells) from old to new grid.
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Defaults to [0,0,0].
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fill : int, optional
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Material ID to fill the background.
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Defaults to material.max() + 1.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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Examples
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--------
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Remove lower 1/2 of the microstructure in z-direction.
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>>> import numpy as np
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>>> import damask
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>>> g = damask.Grid(np.zeros([32]*3,int),np.ones(3)*1e-4)
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>>> g.canvas([32,32,16],[0,0,16])
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cells : 33 x 32 x 16
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size : 0.0001 x 0.0001 x 5e-05 m³
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origin: 0.0 0.0 5e-05 m
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# materials: 1
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"""
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offset_ = np.array(offset,int) if offset is not None else np.zeros(3,int)
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cells_ = np.array(cells,int) if cells is not None else self.cells
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canvas = np.full(cells_,np.nanmax(self.material) + 1 if fill is None else fill,self.material.dtype)
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LL = np.clip( offset_, 0,np.minimum(self.cells, cells_+offset_))
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UR = np.clip( offset_+cells_, 0,np.minimum(self.cells, cells_+offset_))
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ll = np.clip(-offset_, 0,np.minimum( cells_,self.cells-offset_))
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ur = np.clip(-offset_+self.cells,0,np.minimum( cells_,self.cells-offset_))
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canvas[ll[0]:ur[0],ll[1]:ur[1],ll[2]:ur[2]] = self.material[LL[0]:UR[0],LL[1]:UR[1],LL[2]:UR[2]]
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return Grid(material = canvas,
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size = self.size/self.cells*np.asarray(canvas.shape),
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origin = self.origin+offset_*self.size/self.cells,
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comments = self.comments+[util.execution_stamp('Grid','canvas')],
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)
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def mirror(self,
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directions: Sequence[str],
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reflect: bool = False) -> 'Grid':
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"""
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Mirror grid along given directions.
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Parameters
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----------
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directions : (sequence of) {'x', 'y', 'z'}
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Direction(s) along which the grid is mirrored.
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reflect : bool, optional
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Reflect (include) outermost layers. Defaults to False.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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Examples
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--------
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Mirror along x- and y-direction.
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>>> import numpy as np
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>>> import damask
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>>> g = damask.Grid(np.zeros([32]*3,int), np.ones(3)*1e-4)
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>>> g.mirror('xy',True)
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cells : 64 x 64 x 32
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size : 0.0002 x 0.0002 x 0.0001 m³
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origin: 0.0 0.0 0.0 m
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# materials: 1
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"""
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if not set(directions).issubset(valid := ['x', 'y', 'z']):
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raise ValueError(f'invalid direction "{set(directions).difference(valid)}" specified')
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limits: Sequence[Optional[int]] = [None,None] if reflect else [-2,0]
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mat = self.material.copy()
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if 'x' in directions:
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mat = np.concatenate([mat,mat[limits[0]:limits[1]:-1,:,:]],0)
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if 'y' in directions:
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mat = np.concatenate([mat,mat[:,limits[0]:limits[1]:-1,:]],1)
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if 'z' in directions:
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mat = np.concatenate([mat,mat[:,:,limits[0]:limits[1]:-1]],2)
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return Grid(material = mat,
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size = self.size/self.cells*np.asarray(mat.shape),
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','mirror')],
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)
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def flip(self,
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directions: Sequence[str]) -> 'Grid':
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"""
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Flip grid along given directions.
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Parameters
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----------
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directions : (sequence of) {'x', 'y', 'z'}
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Direction(s) along which the grid is flipped.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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"""
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if not set(directions).issubset(valid := ['x', 'y', 'z']):
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raise ValueError(f'invalid direction "{set(directions).difference(valid)}" specified')
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mat = np.flip(self.material, [valid.index(d) for d in directions if d in valid])
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return Grid(material = mat,
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size = self.size,
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','flip')],
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)
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def rotate(self,
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R: Rotation,
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fill: int = None) -> 'Grid':
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"""
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Rotate grid (and pad if required).
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Parameters
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----------
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R : damask.Rotation
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Rotation to apply to the grid.
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fill : int, optional
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Material ID to fill enlarged bounding box.
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Defaults to material.max() + 1.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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"""
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material = self.material
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# These rotations are always applied in the reference coordinate system, i.e. (z,x,z) not (z,x',z'')
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# see https://www.cs.utexas.edu/~theshark/courses/cs354/lectures/cs354-14.pdf
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for angle,axes in zip(R.as_Euler_angles(degrees=True)[::-1], [(0,1),(1,2),(0,1)]):
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material_temp = ndimage.rotate(material,angle,axes,order=0,prefilter=False,
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output=self.material.dtype,
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cval=np.nanmax(self.material) + 1 if fill is None else fill)
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# avoid scipy interpolation errors for rotations close to multiples of 90°
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material = material_temp if np.prod(material_temp.shape) != np.prod(material.shape) else \
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np.rot90(material,k=np.rint(angle/90.).astype(int),axes=axes)
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origin = self.origin-(np.asarray(material.shape)-self.cells)*.5 * self.size/self.cells
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return Grid(material = material,
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size = self.size/self.cells*np.asarray(material.shape),
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origin = origin,
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comments = self.comments+[util.execution_stamp('Grid','rotate')],
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)
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def scale(self,
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cells: IntSequence,
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periodic: bool = True) -> 'Grid':
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"""
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Scale grid to new cells.
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Parameters
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----------
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cells : sequence of int, len (3)
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Number of cells in x,y,z direction.
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periodic : bool, optional
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Assume grid to be periodic. Defaults to True.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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Examples
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--------
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Double resolution.
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>>> import numpy as np
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>>> import damask
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>>> g = damask.Grid(np.zeros([32]*3,int),np.ones(3)*1e-4)
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>>> g.scale(g.cells*2)
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cells : 64 x 64 x 64
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size : 0.0001 x 0.0001 x 0.0001 m³
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origin: 0.0 0.0 0.0 m
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# materials: 1
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"""
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return Grid(material = ndimage.interpolation.zoom(
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self.material,
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cells/self.cells,
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output=self.material.dtype,
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order=0,
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mode='wrap' if periodic else 'nearest',
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prefilter=False
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),
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size = self.size,
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','scale')],
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)
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def renumber(self) -> 'Grid':
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"""
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Renumber sorted material indices as 0,...,N-1.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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"""
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_,renumbered = np.unique(self.material,return_inverse=True)
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return Grid(material = renumbered.reshape(self.cells),
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size = self.size,
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','renumber')],
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)
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def substitute(self,
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from_material: Union[int,IntSequence],
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to_material: Union[int,IntSequence]) -> 'Grid':
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"""
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Substitute material indices.
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Parameters
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----------
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from_material : int or sequence of int
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Material indices to be substituted.
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to_material : int or sequence of int
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New material indices.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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"""
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material = self.material.copy()
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for f,t in zip(from_material if isinstance(from_material,(Sequence,np.ndarray)) else [from_material],
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to_material if isinstance(to_material,(Sequence,np.ndarray)) else [to_material]): # ToDo Python 3.10 has strict mode for zip
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material[self.material==f] = t
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return Grid(material = material,
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size = self.size,
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','substitute')],
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)
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def sort(self) -> 'Grid':
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"""
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Sort material indices such that min(material) is located at (0,0,0).
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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"""
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a = self.material.flatten(order='F')
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from_ma = pd.unique(a)
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sort_idx = np.argsort(from_ma)
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ma = np.unique(a)[sort_idx][np.searchsorted(from_ma,a,sorter = sort_idx)]
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return Grid(material = ma.reshape(self.cells,order='F'),
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size = self.size,
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','sort')],
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)
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def clean(self,
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distance: float = np.sqrt(3),
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selection: IntCollection = None,
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invert_selection: bool = False,
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periodic: bool = True,
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rng_seed: NumpyRngSeed = None) -> 'Grid':
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"""
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Smooth grid by selecting most frequent material ID within given stencil at each location.
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Parameters
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----------
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distance : float, optional
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Voxel distance checked for presence of other materials.
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Defaults to sqrt(3).
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selection : int or collection of int, optional
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Material IDs to consider. Defaults to all.
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invert_selection : bool, optional
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Consider all material IDs except those in selection. Defaults to False.
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periodic : bool, optional
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Assume grid to be periodic. Defaults to True.
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rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
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A seed to initialize the BitGenerator. Defaults to None.
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If None, then fresh, unpredictable entropy will be pulled from the OS.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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Notes
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-----
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If multiple material IDs are most frequent within a stencil, a random choice is taken.
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"""
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def most_frequent(stencil: np.ndarray,
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selection: Union[None,set],
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rng):
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me = stencil[stencil.size//2]
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if selection is None or me in selection:
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unique, counts = np.unique(stencil,return_counts=True)
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return rng.choice(unique[counts==np.max(counts)])
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else:
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return me
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rng = np.random.default_rng(rng_seed)
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d = np.floor(distance).astype(int)
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ext = np.linspace(-d,d,1+2*d,dtype=float),
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xx,yy,zz = np.meshgrid(ext,ext,ext)
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footprint = xx**2+yy**2+zz**2 <= distance**2+distance*1e-8
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selection_ = None if selection is None else \
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set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \
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set(self.material.flatten()) & set(util.aslist(selection))
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material = ndimage.filters.generic_filter(
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self.material,
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most_frequent,
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footprint=footprint,
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mode='wrap' if periodic else 'nearest',
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extra_keywords=dict(selection=selection_,rng=rng),
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).astype(self.material.dtype)
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return Grid(material = material,
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size = self.size,
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','clean')],
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)
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def add_primitive(self,
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def add_primitive(self,
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dimension: Union[FloatSequence, IntSequence],
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dimension: Union[FloatSequence, IntSequence],
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center: Union[FloatSequence, IntSequence],
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center: Union[FloatSequence, IntSequence],
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@ -809,366 +1171,6 @@ class Grid:
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)
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)
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def mirror(self,
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directions: Sequence[str],
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reflect: bool = False) -> 'Grid':
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"""
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Mirror grid along given directions.
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Parameters
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----------
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directions : (sequence of) {'x', 'y', 'z'}
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Direction(s) along which the grid is mirrored.
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reflect : bool, optional
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Reflect (include) outermost layers. Defaults to False.
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Returns
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-------
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updated : damask.Grid
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Updated grid-based geometry.
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Examples
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--------
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Mirror along x- and y-direction.
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>>> import numpy as np
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>>> import damask
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>>> g = damask.Grid(np.zeros([32]*3,int), np.ones(3)*1e-4)
|
|
||||||
>>> g.mirror('xy',True)
|
|
||||||
cells : 64 x 64 x 32
|
|
||||||
size : 0.0002 x 0.0002 x 0.0001 m³
|
|
||||||
origin: 0.0 0.0 0.0 m
|
|
||||||
# materials: 1
|
|
||||||
|
|
||||||
"""
|
|
||||||
if not set(directions).issubset(valid := ['x', 'y', 'z']):
|
|
||||||
raise ValueError(f'invalid direction "{set(directions).difference(valid)}" specified')
|
|
||||||
|
|
||||||
limits: Sequence[Optional[int]] = [None,None] if reflect else [-2,0]
|
|
||||||
mat = self.material.copy()
|
|
||||||
|
|
||||||
if 'x' in directions:
|
|
||||||
mat = np.concatenate([mat,mat[limits[0]:limits[1]:-1,:,:]],0)
|
|
||||||
if 'y' in directions:
|
|
||||||
mat = np.concatenate([mat,mat[:,limits[0]:limits[1]:-1,:]],1)
|
|
||||||
if 'z' in directions:
|
|
||||||
mat = np.concatenate([mat,mat[:,:,limits[0]:limits[1]:-1]],2)
|
|
||||||
|
|
||||||
return Grid(material = mat,
|
|
||||||
size = self.size/self.cells*np.asarray(mat.shape),
|
|
||||||
origin = self.origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','mirror')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def flip(self,
|
|
||||||
directions: Sequence[str]) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Flip grid along given directions.
|
|
||||||
|
|
||||||
Parameters
|
|
||||||
----------
|
|
||||||
directions : (sequence of) {'x', 'y', 'z'}
|
|
||||||
Direction(s) along which the grid is flipped.
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
"""
|
|
||||||
if not set(directions).issubset(valid := ['x', 'y', 'z']):
|
|
||||||
raise ValueError(f'invalid direction "{set(directions).difference(valid)}" specified')
|
|
||||||
|
|
||||||
|
|
||||||
mat = np.flip(self.material, [valid.index(d) for d in directions if d in valid])
|
|
||||||
|
|
||||||
return Grid(material = mat,
|
|
||||||
size = self.size,
|
|
||||||
origin = self.origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','flip')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def scale(self,
|
|
||||||
cells: IntSequence,
|
|
||||||
periodic: bool = True) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Scale grid to new cells.
|
|
||||||
|
|
||||||
Parameters
|
|
||||||
----------
|
|
||||||
cells : sequence of int, len (3)
|
|
||||||
Number of cells in x,y,z direction.
|
|
||||||
periodic : bool, optional
|
|
||||||
Assume grid to be periodic. Defaults to True.
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
Examples
|
|
||||||
--------
|
|
||||||
Double resolution.
|
|
||||||
|
|
||||||
>>> import numpy as np
|
|
||||||
>>> import damask
|
|
||||||
>>> g = damask.Grid(np.zeros([32]*3,int),np.ones(3)*1e-4)
|
|
||||||
>>> g.scale(g.cells*2)
|
|
||||||
cells : 64 x 64 x 64
|
|
||||||
size : 0.0001 x 0.0001 x 0.0001 m³
|
|
||||||
origin: 0.0 0.0 0.0 m
|
|
||||||
# materials: 1
|
|
||||||
|
|
||||||
"""
|
|
||||||
return Grid(material = ndimage.interpolation.zoom(
|
|
||||||
self.material,
|
|
||||||
cells/self.cells,
|
|
||||||
output=self.material.dtype,
|
|
||||||
order=0,
|
|
||||||
mode='wrap' if periodic else 'nearest',
|
|
||||||
prefilter=False
|
|
||||||
),
|
|
||||||
size = self.size,
|
|
||||||
origin = self.origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','scale')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def clean(self,
|
|
||||||
distance: float = np.sqrt(3),
|
|
||||||
selection: IntCollection = None,
|
|
||||||
invert_selection: bool = False,
|
|
||||||
periodic: bool = True,
|
|
||||||
rng_seed: NumpyRngSeed = None) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Smooth grid by selecting most frequent material ID within given stencil at each location.
|
|
||||||
|
|
||||||
Parameters
|
|
||||||
----------
|
|
||||||
distance : float, optional
|
|
||||||
Voxel distance checked for presence of other materials.
|
|
||||||
Defaults to sqrt(3).
|
|
||||||
selection : int or collection of int, optional
|
|
||||||
Material IDs to consider.
|
|
||||||
invert_selection : bool, optional
|
|
||||||
Consider all material IDs except those in selection. Defaults to False.
|
|
||||||
periodic : bool, optional
|
|
||||||
Assume grid to be periodic. Defaults to True.
|
|
||||||
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
|
|
||||||
A seed to initialize the BitGenerator. Defaults to None.
|
|
||||||
If None, then fresh, unpredictable entropy will be pulled from the OS.
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
Notes
|
|
||||||
-----
|
|
||||||
If multiple material IDs are most frequent within a stencil, a random choice is taken.
|
|
||||||
|
|
||||||
"""
|
|
||||||
def most_frequent(stencil: np.ndarray,
|
|
||||||
selection: set,
|
|
||||||
rng):
|
|
||||||
me = stencil[stencil.size//2]
|
|
||||||
if not selection or me in selection:
|
|
||||||
unique, counts = np.unique(stencil,return_counts=True)
|
|
||||||
return rng.choice(unique[counts==np.max(counts)])
|
|
||||||
else:
|
|
||||||
return me
|
|
||||||
|
|
||||||
rng = np.random.default_rng(rng_seed)
|
|
||||||
d = np.floor(distance).astype(int)
|
|
||||||
ext = np.linspace(-d,d,1+2*d,dtype=float),
|
|
||||||
xx,yy,zz = np.meshgrid(ext,ext,ext)
|
|
||||||
footprint = xx**2+yy**2+zz**2 <= distance**2+distance*1e-8
|
|
||||||
selection_ = set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \
|
|
||||||
set(util.aslist(selection))
|
|
||||||
material = ndimage.filters.generic_filter(
|
|
||||||
self.material,
|
|
||||||
most_frequent,
|
|
||||||
footprint=footprint,
|
|
||||||
mode='wrap' if periodic else 'nearest',
|
|
||||||
extra_keywords=dict(selection=selection_,rng=rng),
|
|
||||||
).astype(self.material.dtype)
|
|
||||||
return Grid(material = material,
|
|
||||||
size = self.size,
|
|
||||||
origin = self.origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','clean')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def renumber(self) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Renumber sorted material indices as 0,...,N-1.
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
"""
|
|
||||||
_,renumbered = np.unique(self.material,return_inverse=True)
|
|
||||||
|
|
||||||
return Grid(material = renumbered.reshape(self.cells),
|
|
||||||
size = self.size,
|
|
||||||
origin = self.origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','renumber')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def rotate(self,
|
|
||||||
R: Rotation,
|
|
||||||
fill: int = None) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Rotate grid (and pad if required).
|
|
||||||
|
|
||||||
Parameters
|
|
||||||
----------
|
|
||||||
R : damask.Rotation
|
|
||||||
Rotation to apply to the grid.
|
|
||||||
fill : int, optional
|
|
||||||
Material ID to fill enlarged bounding box.
|
|
||||||
Defaults to material.max() + 1.
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
"""
|
|
||||||
material = self.material
|
|
||||||
# These rotations are always applied in the reference coordinate system, i.e. (z,x,z) not (z,x',z'')
|
|
||||||
# see https://www.cs.utexas.edu/~theshark/courses/cs354/lectures/cs354-14.pdf
|
|
||||||
for angle,axes in zip(R.as_Euler_angles(degrees=True)[::-1], [(0,1),(1,2),(0,1)]):
|
|
||||||
material_temp = ndimage.rotate(material,angle,axes,order=0,prefilter=False,
|
|
||||||
output=self.material.dtype,
|
|
||||||
cval=np.nanmax(self.material) + 1 if fill is None else fill)
|
|
||||||
# avoid scipy interpolation errors for rotations close to multiples of 90°
|
|
||||||
material = material_temp if np.prod(material_temp.shape) != np.prod(material.shape) else \
|
|
||||||
np.rot90(material,k=np.rint(angle/90.).astype(int),axes=axes)
|
|
||||||
|
|
||||||
origin = self.origin-(np.asarray(material.shape)-self.cells)*.5 * self.size/self.cells
|
|
||||||
|
|
||||||
return Grid(material = material,
|
|
||||||
size = self.size/self.cells*np.asarray(material.shape),
|
|
||||||
origin = origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','rotate')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def canvas(self,
|
|
||||||
cells: IntSequence = None,
|
|
||||||
offset: IntSequence = None,
|
|
||||||
fill: int = None) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Crop or enlarge/pad grid.
|
|
||||||
|
|
||||||
Parameters
|
|
||||||
----------
|
|
||||||
cells : sequence of int, len (3), optional
|
|
||||||
Number of cells x,y,z direction.
|
|
||||||
offset : sequence of int, len (3), optional
|
|
||||||
Offset (measured in cells) from old to new grid.
|
|
||||||
Defaults to [0,0,0].
|
|
||||||
fill : int, optional
|
|
||||||
Material ID to fill the background.
|
|
||||||
Defaults to material.max() + 1.
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
Examples
|
|
||||||
--------
|
|
||||||
Remove lower 1/2 of the microstructure in z-direction.
|
|
||||||
|
|
||||||
>>> import numpy as np
|
|
||||||
>>> import damask
|
|
||||||
>>> g = damask.Grid(np.zeros([32]*3,int),np.ones(3)*1e-4)
|
|
||||||
>>> g.canvas([32,32,16],[0,0,16])
|
|
||||||
cells : 33 x 32 x 16
|
|
||||||
size : 0.0001 x 0.0001 x 5e-05 m³
|
|
||||||
origin: 0.0 0.0 5e-05 m
|
|
||||||
# materials: 1
|
|
||||||
|
|
||||||
"""
|
|
||||||
offset_ = np.array(offset,int) if offset is not None else np.zeros(3,int)
|
|
||||||
cells_ = np.array(cells,int) if cells is not None else self.cells
|
|
||||||
|
|
||||||
canvas = np.full(cells_,np.nanmax(self.material) + 1 if fill is None else fill,self.material.dtype)
|
|
||||||
|
|
||||||
LL = np.clip( offset_, 0,np.minimum(self.cells, cells_+offset_))
|
|
||||||
UR = np.clip( offset_+cells_, 0,np.minimum(self.cells, cells_+offset_))
|
|
||||||
ll = np.clip(-offset_, 0,np.minimum( cells_,self.cells-offset_))
|
|
||||||
ur = np.clip(-offset_+self.cells,0,np.minimum( cells_,self.cells-offset_))
|
|
||||||
|
|
||||||
canvas[ll[0]:ur[0],ll[1]:ur[1],ll[2]:ur[2]] = self.material[LL[0]:UR[0],LL[1]:UR[1],LL[2]:UR[2]]
|
|
||||||
|
|
||||||
return Grid(material = canvas,
|
|
||||||
size = self.size/self.cells*np.asarray(canvas.shape),
|
|
||||||
origin = self.origin+offset_*self.size/self.cells,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','canvas')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def substitute(self,
|
|
||||||
from_material: Union[int,IntSequence],
|
|
||||||
to_material: Union[int,IntSequence]) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Substitute material indices.
|
|
||||||
|
|
||||||
Parameters
|
|
||||||
----------
|
|
||||||
from_material : int or sequence of int
|
|
||||||
Material indices to be substituted.
|
|
||||||
to_material : int or sequence of int
|
|
||||||
New material indices.
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
"""
|
|
||||||
material = self.material.copy()
|
|
||||||
for f,t in zip(from_material if isinstance(from_material,(Sequence,np.ndarray)) else [from_material],
|
|
||||||
to_material if isinstance(to_material,(Sequence,np.ndarray)) else [to_material]): # ToDo Python 3.10 has strict mode for zip
|
|
||||||
material[self.material==f] = t
|
|
||||||
|
|
||||||
return Grid(material = material,
|
|
||||||
size = self.size,
|
|
||||||
origin = self.origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','substitute')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def sort(self) -> 'Grid':
|
|
||||||
"""
|
|
||||||
Sort material indices such that min(material) is located at (0,0,0).
|
|
||||||
|
|
||||||
Returns
|
|
||||||
-------
|
|
||||||
updated : damask.Grid
|
|
||||||
Updated grid-based geometry.
|
|
||||||
|
|
||||||
"""
|
|
||||||
a = self.material.flatten(order='F')
|
|
||||||
from_ma = pd.unique(a)
|
|
||||||
sort_idx = np.argsort(from_ma)
|
|
||||||
ma = np.unique(a)[sort_idx][np.searchsorted(from_ma,a,sorter = sort_idx)]
|
|
||||||
|
|
||||||
return Grid(material = ma.reshape(self.cells,order='F'),
|
|
||||||
size = self.size,
|
|
||||||
origin = self.origin,
|
|
||||||
comments = self.comments+[util.execution_stamp('Grid','sort')],
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def vicinity_offset(self,
|
def vicinity_offset(self,
|
||||||
distance: float = np.sqrt(3),
|
distance: float = np.sqrt(3),
|
||||||
offset: int = None,
|
offset: int = None,
|
||||||
|
@ -1204,9 +1206,9 @@ class Grid:
|
||||||
Updated grid-based geometry.
|
Updated grid-based geometry.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
def tainted_neighborhood(stencil: np.ndarray, selection: set):
|
def tainted_neighborhood(stencil: np.ndarray, selection: Union[None,set]):
|
||||||
me = stencil[stencil.size//2]
|
me = stencil[stencil.size//2]
|
||||||
return np.any(stencil != me if not selection else
|
return np.any(stencil != me if selection is None else
|
||||||
np.in1d(stencil,np.array(list(selection - {me}))))
|
np.in1d(stencil,np.array(list(selection - {me}))))
|
||||||
|
|
||||||
d = np.floor(distance).astype(int)
|
d = np.floor(distance).astype(int)
|
||||||
|
@ -1214,8 +1216,9 @@ class Grid:
|
||||||
xx,yy,zz = np.meshgrid(ext,ext,ext)
|
xx,yy,zz = np.meshgrid(ext,ext,ext)
|
||||||
footprint = xx**2+yy**2+zz**2 <= distance**2+distance*1e-8
|
footprint = xx**2+yy**2+zz**2 <= distance**2+distance*1e-8
|
||||||
offset_ = np.nanmax(self.material)+1 if offset is None else offset
|
offset_ = np.nanmax(self.material)+1 if offset is None else offset
|
||||||
selection_ = set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \
|
selection_ = None if selection is None else \
|
||||||
set(util.aslist(selection))
|
set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \
|
||||||
|
set(self.material.flatten()) & set(util.aslist(selection))
|
||||||
mask = ndimage.filters.generic_filter(self.material,
|
mask = ndimage.filters.generic_filter(self.material,
|
||||||
tainted_neighborhood,
|
tainted_neighborhood,
|
||||||
footprint=footprint,
|
footprint=footprint,
|
||||||
|
|
|
@ -535,7 +535,7 @@ class Table:
|
||||||
raise KeyError('mismatch of shapes or labels or their order')
|
raise KeyError('mismatch of shapes or labels or their order')
|
||||||
|
|
||||||
dup = self.copy()
|
dup = self.copy()
|
||||||
dup.data = dup.data.append(other.data,ignore_index=True)
|
dup.data = pd.concat([dup.data,other.data],ignore_index=True)
|
||||||
return dup
|
return dup
|
||||||
|
|
||||||
|
|
||||||
|
|
|
@ -12,11 +12,6 @@ from damask import seeds
|
||||||
from damask import grid_filters
|
from damask import grid_filters
|
||||||
|
|
||||||
|
|
||||||
def grid_equal(a,b):
|
|
||||||
return np.all(a.material == b.material) and \
|
|
||||||
np.all(a.cells == b.cells) and \
|
|
||||||
np.allclose(a.size, b.size)
|
|
||||||
|
|
||||||
@pytest.fixture
|
@pytest.fixture
|
||||||
def default():
|
def default():
|
||||||
"""Simple geometry."""
|
"""Simple geometry."""
|
||||||
|
@ -66,7 +61,7 @@ class TestGrid:
|
||||||
def test_read_write_vtr(self,default,tmp_path):
|
def test_read_write_vtr(self,default,tmp_path):
|
||||||
default.save(tmp_path/'default')
|
default.save(tmp_path/'default')
|
||||||
new = Grid.load(tmp_path/'default.vti')
|
new = Grid.load(tmp_path/'default.vti')
|
||||||
assert grid_equal(new,default)
|
assert new == default
|
||||||
|
|
||||||
def test_invalid_no_material(self,tmp_path):
|
def test_invalid_no_material(self,tmp_path):
|
||||||
v = VTK.from_image_data(np.random.randint(5,10,3)*2,np.random.random(3) + 1.0)
|
v = VTK.from_image_data(np.random.randint(5,10,3)*2,np.random.random(3) + 1.0)
|
||||||
|
@ -90,7 +85,7 @@ class TestGrid:
|
||||||
def test_save_load_ASCII(self,default,tmp_path):
|
def test_save_load_ASCII(self,default,tmp_path):
|
||||||
default.save_ASCII(tmp_path/'ASCII')
|
default.save_ASCII(tmp_path/'ASCII')
|
||||||
default.material -= 1
|
default.material -= 1
|
||||||
assert grid_equal(Grid.load_ASCII(tmp_path/'ASCII'),default)
|
assert Grid.load_ASCII(tmp_path/'ASCII') == default
|
||||||
|
|
||||||
def test_invalid_origin(self,default):
|
def test_invalid_origin(self,default):
|
||||||
with pytest.raises(ValueError):
|
with pytest.raises(ValueError):
|
||||||
|
@ -124,8 +119,7 @@ class TestGrid:
|
||||||
tag = f'directions_{"-".join(directions)}+reflect_{reflect}'
|
tag = f'directions_{"-".join(directions)}+reflect_{reflect}'
|
||||||
reference = ref_path/f'mirror_{tag}.vti'
|
reference = ref_path/f'mirror_{tag}.vti'
|
||||||
if update: modified.save(reference)
|
if update: modified.save(reference)
|
||||||
assert grid_equal(Grid.load(reference),
|
assert Grid.load(reference) == modified
|
||||||
modified)
|
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize('directions',[(1,2,'y'),('a','b','x'),[1]])
|
@pytest.mark.parametrize('directions',[(1,2,'y'),('a','b','x'),[1]])
|
||||||
|
@ -146,17 +140,16 @@ class TestGrid:
|
||||||
tag = f'directions_{"-".join(directions)}'
|
tag = f'directions_{"-".join(directions)}'
|
||||||
reference = ref_path/f'flip_{tag}.vti'
|
reference = ref_path/f'flip_{tag}.vti'
|
||||||
if update: modified.save(reference)
|
if update: modified.save(reference)
|
||||||
assert grid_equal(Grid.load(reference),
|
assert Grid.load(reference) == modified
|
||||||
modified)
|
|
||||||
|
|
||||||
|
|
||||||
def test_flip_invariant(self,default):
|
def test_flip_invariant(self,default):
|
||||||
assert grid_equal(default,default.flip([]))
|
assert default == default.flip([])
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize('direction',[['x'],['x','y']])
|
@pytest.mark.parametrize('direction',[['x'],['x','y']])
|
||||||
def test_flip_double(self,default,direction):
|
def test_flip_double(self,default,direction):
|
||||||
assert grid_equal(default,default.flip(direction).flip(direction))
|
assert default == default.flip(direction).flip(direction)
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize('directions',[(1,2,'y'),('a','b','x'),[1]])
|
@pytest.mark.parametrize('directions',[(1,2,'y'),('a','b','x'),[1]])
|
||||||
|
@ -173,7 +166,7 @@ class TestGrid:
|
||||||
reference = ref_path/f'clean_{distance}_{"+".join(map(str,util.aslist(selection)))}_{periodic}.vti'
|
reference = ref_path/f'clean_{distance}_{"+".join(map(str,util.aslist(selection)))}_{periodic}.vti'
|
||||||
if update:
|
if update:
|
||||||
current.save(reference)
|
current.save(reference)
|
||||||
assert grid_equal(Grid.load(reference),current)
|
assert Grid.load(reference) == current
|
||||||
|
|
||||||
@pytest.mark.parametrize('selection',[list(np.random.randint(1,20,6)),set(np.random.randint(1,20,6)),np.random.randint(1,20,6)])
|
@pytest.mark.parametrize('selection',[list(np.random.randint(1,20,6)),set(np.random.randint(1,20,6)),np.random.randint(1,20,6)])
|
||||||
@pytest.mark.parametrize('invert',[True,False])
|
@pytest.mark.parametrize('invert',[True,False])
|
||||||
|
@ -201,8 +194,7 @@ class TestGrid:
|
||||||
tag = f'grid_{util.srepr(cells,"-")}'
|
tag = f'grid_{util.srepr(cells,"-")}'
|
||||||
reference = ref_path/f'scale_{tag}.vti'
|
reference = ref_path/f'scale_{tag}.vti'
|
||||||
if update: modified.save(reference)
|
if update: modified.save(reference)
|
||||||
assert grid_equal(Grid.load(reference),
|
assert Grid.load(reference) == modified
|
||||||
modified)
|
|
||||||
|
|
||||||
|
|
||||||
def test_renumber(self,default):
|
def test_renumber(self,default):
|
||||||
|
@ -213,9 +205,8 @@ class TestGrid:
|
||||||
modified = Grid(material,
|
modified = Grid(material,
|
||||||
default.size,
|
default.size,
|
||||||
default.origin)
|
default.origin)
|
||||||
assert not grid_equal(modified,default)
|
assert not default == modified
|
||||||
assert grid_equal(default,
|
assert default == modified.renumber()
|
||||||
modified.renumber())
|
|
||||||
|
|
||||||
|
|
||||||
def test_substitute(self,default):
|
def test_substitute(self,default):
|
||||||
|
@ -223,10 +214,9 @@ class TestGrid:
|
||||||
modified = Grid(default.material + offset,
|
modified = Grid(default.material + offset,
|
||||||
default.size,
|
default.size,
|
||||||
default.origin)
|
default.origin)
|
||||||
assert not grid_equal(modified,default)
|
assert not default == modified
|
||||||
assert grid_equal(default,
|
assert default == modified.substitute(np.arange(default.material.max())+1+offset,
|
||||||
modified.substitute(np.arange(default.material.max())+1+offset,
|
np.arange(default.material.max())+1)
|
||||||
np.arange(default.material.max())+1))
|
|
||||||
|
|
||||||
def test_substitute_integer_list(self,random):
|
def test_substitute_integer_list(self,random):
|
||||||
f = np.random.randint(30)
|
f = np.random.randint(30)
|
||||||
|
@ -237,8 +227,8 @@ class TestGrid:
|
||||||
f = np.unique(default.material.flatten())[:np.random.randint(1,default.material.max())]
|
f = np.unique(default.material.flatten())[:np.random.randint(1,default.material.max())]
|
||||||
t = np.random.permutation(f)
|
t = np.random.permutation(f)
|
||||||
modified = default.substitute(f,t)
|
modified = default.substitute(f,t)
|
||||||
assert np.array_equiv(t,f) or (not grid_equal(modified,default))
|
assert np.array_equiv(t,f) or modified != default
|
||||||
assert grid_equal(default, modified.substitute(t,f))
|
assert default == modified.substitute(t,f)
|
||||||
|
|
||||||
def test_sort(self):
|
def test_sort(self):
|
||||||
cells = np.random.randint(5,20,3)
|
cells = np.random.randint(5,20,3)
|
||||||
|
@ -252,7 +242,7 @@ class TestGrid:
|
||||||
modified = default.copy()
|
modified = default.copy()
|
||||||
for i in range(np.rint(360/axis_angle[3]).astype(int)):
|
for i in range(np.rint(360/axis_angle[3]).astype(int)):
|
||||||
modified.rotate(Rotation.from_axis_angle(axis_angle,degrees=True))
|
modified.rotate(Rotation.from_axis_angle(axis_angle,degrees=True))
|
||||||
assert grid_equal(default,modified)
|
assert default == modified
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize('Eulers',[[32.0,68.0,21.0],
|
@pytest.mark.parametrize('Eulers',[[32.0,68.0,21.0],
|
||||||
|
@ -262,8 +252,7 @@ class TestGrid:
|
||||||
tag = f'Eulers_{util.srepr(Eulers,"-")}'
|
tag = f'Eulers_{util.srepr(Eulers,"-")}'
|
||||||
reference = ref_path/f'rotate_{tag}.vti'
|
reference = ref_path/f'rotate_{tag}.vti'
|
||||||
if update: modified.save(reference)
|
if update: modified.save(reference)
|
||||||
assert grid_equal(Grid.load(reference),
|
assert Grid.load(reference) == modified
|
||||||
modified)
|
|
||||||
|
|
||||||
|
|
||||||
def test_canvas_extend(self,default):
|
def test_canvas_extend(self,default):
|
||||||
|
@ -321,7 +310,7 @@ class TestGrid:
|
||||||
fill = np.random.randint(10)+2
|
fill = np.random.randint(10)+2
|
||||||
G_1 = Grid(np.ones(g,'i'),s).add_primitive(.3,center,1,fill,inverse=inverse,periodic=periodic)
|
G_1 = Grid(np.ones(g,'i'),s).add_primitive(.3,center,1,fill,inverse=inverse,periodic=periodic)
|
||||||
G_2 = Grid(np.ones(g,'i'),s).add_primitive(.3,center,1,fill,Rotation.from_random(),inverse,periodic=periodic)
|
G_2 = Grid(np.ones(g,'i'),s).add_primitive(.3,center,1,fill,Rotation.from_random(),inverse,periodic=periodic)
|
||||||
assert grid_equal(G_1,G_2)
|
assert G_1 == G_2
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize('selection',[1,None])
|
@pytest.mark.parametrize('selection',[1,None])
|
||||||
|
@ -346,11 +335,10 @@ class TestGrid:
|
||||||
|
|
||||||
@pytest.mark.parametrize('selection',[list(np.random.randint(1,20,6)),set(np.random.randint(1,20,6)),np.random.randint(1,20,6)])
|
@pytest.mark.parametrize('selection',[list(np.random.randint(1,20,6)),set(np.random.randint(1,20,6)),np.random.randint(1,20,6)])
|
||||||
@pytest.mark.parametrize('invert',[True,False])
|
@pytest.mark.parametrize('invert',[True,False])
|
||||||
def test_vicinit_offset_invert(self,random,selection,invert):
|
def test_vicinity_offset_invert(self,random,selection,invert):
|
||||||
selection_inverse = set(random.material.flatten()) - set(selection)
|
selection_inverse = set(random.material.flatten()) - set(selection)
|
||||||
assert selection_inverse == set() or \
|
assert random.vicinity_offset(selection=selection ,invert_selection=not invert) == \
|
||||||
(random.vicinity_offset(selection=selection,invert_selection=invert) ==
|
random.vicinity_offset(selection=selection_inverse,invert_selection= invert)
|
||||||
random.vicinity_offset(selection=selection_inverse,invert_selection=not invert))
|
|
||||||
|
|
||||||
def test_vicinity_offset_selection_empty(self,random):
|
def test_vicinity_offset_selection_empty(self,random):
|
||||||
assert random.vicinity_offset(selection=None,invert_selection=False) == random.vicinity_offset() and \
|
assert random.vicinity_offset(selection=None,invert_selection=False) == random.vicinity_offset() and \
|
||||||
|
@ -372,7 +360,7 @@ class TestGrid:
|
||||||
seeds = np.random.rand(N_seeds,3) * np.broadcast_to(size,(N_seeds,3))
|
seeds = np.random.rand(N_seeds,3) * np.broadcast_to(size,(N_seeds,3))
|
||||||
Voronoi = Grid.from_Voronoi_tessellation( cells,size,seeds, np.arange(N_seeds)+5,periodic)
|
Voronoi = Grid.from_Voronoi_tessellation( cells,size,seeds, np.arange(N_seeds)+5,periodic)
|
||||||
Laguerre = Grid.from_Laguerre_tessellation(cells,size,seeds,np.ones(N_seeds),np.arange(N_seeds)+5,periodic)
|
Laguerre = Grid.from_Laguerre_tessellation(cells,size,seeds,np.ones(N_seeds),np.arange(N_seeds)+5,periodic)
|
||||||
assert grid_equal(Laguerre,Voronoi)
|
assert Laguerre == Voronoi
|
||||||
|
|
||||||
|
|
||||||
def test_Laguerre_weights(self):
|
def test_Laguerre_weights(self):
|
||||||
|
@ -462,7 +450,7 @@ class TestGrid:
|
||||||
grid = Grid.from_Voronoi_tessellation(cells,size,s)
|
grid = Grid.from_Voronoi_tessellation(cells,size,s)
|
||||||
coords = grid_filters.coordinates0_point(cells,size)
|
coords = grid_filters.coordinates0_point(cells,size)
|
||||||
t = Table(np.column_stack((coords.reshape(-1,3,order='F'),grid.material.flatten(order='F'))),{'c':3,'m':1})
|
t = Table(np.column_stack((coords.reshape(-1,3,order='F'),grid.material.flatten(order='F'))),{'c':3,'m':1})
|
||||||
assert grid_equal(grid.sort().renumber(),Grid.from_table(t,'c',['m']))
|
assert grid.sort().renumber() == Grid.from_table(t,'c',['m'])
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize('periodic',[True,False])
|
@pytest.mark.parametrize('periodic',[True,False])
|
||||||
|
@ -496,7 +484,7 @@ class TestGrid:
|
||||||
if update:
|
if update:
|
||||||
current.save(ref_path/'measured.vti')
|
current.save(ref_path/'measured.vti')
|
||||||
|
|
||||||
assert grid_equal(current,reference)
|
assert current == reference
|
||||||
|
|
||||||
def test_load_Neper_reference(self,ref_path,update):
|
def test_load_Neper_reference(self,ref_path,update):
|
||||||
current = Grid.load_Neper(ref_path/'n10-id1_scaled.vtk')
|
current = Grid.load_Neper(ref_path/'n10-id1_scaled.vtk')
|
||||||
|
@ -504,4 +492,4 @@ class TestGrid:
|
||||||
if update:
|
if update:
|
||||||
current.save(ref_path/'n10-id1_scaled.vti')
|
current.save(ref_path/'n10-id1_scaled.vti')
|
||||||
|
|
||||||
assert grid_equal(current,reference)
|
assert current == reference
|
||||||
|
|
Loading…
Reference in New Issue