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Merge branch 'RegularGridInterpolator' into 'development' 

grid assemble + corrected grid.scale

See merge request damask/DAMASK!643
This commit is contained in:
Philip Eisenlohr 2022-11-08 18:52:08 +00:00
parent 507e1a2f05 4f0db64e15
commit 953d5769a0
10 changed files with 220 additions and 66 deletions
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98
python/damask/_grid.py
View File

@ -10,7 +10,7 @@ from pathlib import Path
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import h5py import h5py
from scipy import ndimage, spatial from scipy import ndimage, spatial, interpolate
from . import VTK from . import VTK
from . import util from . import util
@ -41,7 +41,7 @@ class Grid:
Parameters Parameters
---------- ----------
material : numpy.ndarray, shape (:,:,:) material : numpy.ndarray of int, shape (:,:,:)
Material indices. The shape of the material array defines Material indices. The shape of the material array defines
the number of cells. the number of cells.
size : sequence of float, len (3) size : sequence of float, len (3)
@ -50,7 +50,7 @@ class Grid:
Coordinates of grid origin in meter. Defaults to [0.0,0.0,0.0]. Coordinates of grid origin in meter. Defaults to [0.0,0.0,0.0].
initial_conditions : dictionary, optional initial_conditions : dictionary, optional
Labels and values of the inital conditions at each material point. Labels and values of the inital conditions at each material point.
comments : str or iterable of str, optional comments : str or sequence of str, optional
Additional, human-readable information, e.g. history of operations. Additional, human-readable information, e.g. history of operations.
""" """
@ -183,7 +183,7 @@ class Grid:
@comments.setter @comments.setter
def comments(self, def comments(self,
comments: Union[str, Sequence[str]]): comments: Union[str, Sequence[str]]):
self._comments = [str(c) for c in comments] if isinstance(comments,list) else [str(comments)] self._comments = [str(c) for c in comments] if isinstance(comments,Sequence) else [str(comments)]
@property @property
@ -427,7 +427,7 @@ class Grid:
coordinates : str coordinates : str
Label of the vector column containing the spatial coordinates. Label of the vector column containing the spatial coordinates.
Need to be ordered (1./x fast, 3./z slow). Need to be ordered (1./x fast, 3./z slow).
labels : (list of) str labels : str or sequence of str
Label(s) of the columns containing the material definition. Label(s) of the columns containing the material definition.
Each unique combination of values results in one material ID. Each unique combination of values results in one material ID.
@ -474,7 +474,7 @@ class Grid:
Number of cells in x,y,z direction. Number of cells in x,y,z direction.
size : sequence of float, len (3) size : sequence of float, len (3)
Physical size of the grid in meter. Physical size of the grid in meter.
seeds : numpy.ndarray, shape (:,3) seeds : numpy.ndarray of float, shape (:,3)
Position of the seed points in meter. All points need to lay within the box. Position of the seed points in meter. All points need to lay within the box.
weights : sequence of float, len (seeds.shape[0]) weights : sequence of float, len (seeds.shape[0])
Weights of the seeds. Setting all weights to 1.0 gives a standard Voronoi tessellation. Weights of the seeds. Setting all weights to 1.0 gives a standard Voronoi tessellation.
@ -531,7 +531,7 @@ class Grid:
Number of cells in x,y,z direction. Number of cells in x,y,z direction.
size : sequence of float, len (3) size : sequence of float, len (3)
Physical size of the grid in meter. Physical size of the grid in meter.
seeds : numpy.ndarray, shape (:,3) seeds : numpy.ndarray of float, shape (:,3)
Position of the seed points in meter. All points need to lay within the box. Position of the seed points in meter. All points need to lay within the box.
material : sequence of int, len (seeds.shape[0]), optional material : sequence of int, len (seeds.shape[0]), optional
Material ID of the seeds. Material ID of the seeds.
@ -940,17 +940,14 @@ class Grid:
def scale(self, def scale(self,
cells: IntSequence, cells: IntSequence) -> 'Grid':
periodic: bool = True) -> 'Grid':
""" """
Scale grid to new cells. Scale grid to new cell count.
Parameters Parameters
---------- ----------
cells : sequence of int, len (3) cells : sequence of int, len (3)
Number of cells in x,y,z direction. Number of cells in x,y,z direction.
periodic : bool, optional
Assume grid to be periodic. Defaults to True.
Returns Returns
------- -------
@ -963,7 +960,11 @@ class Grid:
>>> import numpy as np >>> import numpy as np
>>> import damask >>> import damask
>>> g = damask.Grid(np.zeros([32]*3,int),np.ones(3)*1e-4) >>> (g := damask.Grid(np.zeros([32]*3,int),np.ones(3)*1e-4))
cells: 32 × 32 × 32
size: 0.0001 × 0.0001 × 0.0001 m³
origin: 0.0 0.0 0.0 m
# materials: 1
>>> g.scale(g.cells*2) >>> g.scale(g.cells*2)
cells : 64 x 64 x 64 cells : 64 x 64 x 64
size : 0.0001 x 0.0001 x 0.0001 m³ size : 0.0001 x 0.0001 x 0.0001 m³
@ -971,20 +972,49 @@ class Grid:
# materials: 1 # materials: 1
""" """
return Grid(material = ndimage.interpolation.zoom( options = ('nearest',False,None)
self.material, orig = tuple(map(np.linspace,self.origin + self.size/self.cells*.5,
cells/self.cells, self.origin + self.size - self.size/self.cells*.5,self.cells))
output=self.material.dtype, new = grid_filters.coordinates0_point(cells,self.size,self.origin)
order=0,
mode='wrap' if periodic else 'nearest', return Grid(material = interpolate.RegularGridInterpolator(orig,self.material,*options)(new).astype(int),
prefilter=False
),
size = self.size, size = self.size,
origin = self.origin, origin = self.origin,
initial_conditions = {k: interpolate.RegularGridInterpolator(orig,v,*options)(new)
for k,v in self.initial_conditions.items()},
comments = self.comments+[util.execution_stamp('Grid','scale')], comments = self.comments+[util.execution_stamp('Grid','scale')],
) )
def assemble(self,
idx: np.ndarray) -> 'Grid':
"""
Assemble new grid from index map.
Parameters
----------
idx : numpy.ndarray of int, shape (:,:,:) or (:,:,:,3)
Grid of flat indices or coordinate indices.
Returns
-------
updated : damask.Grid
Updated grid-based geometry.
Cell count of resulting grid matches shape of index map.
"""
cells = idx.shape[:3]
flat = (idx if len(idx.shape)==3 else grid_filters.ravel_index(idx)).flatten(order='F')
ic = {k: v.flatten(order='F')[flat].reshape(cells,order='F') for k,v in self.initial_conditions.items()}
return Grid(material = self.material.flatten(order='F')[flat].reshape(cells,order='F'),
size = self.size,
origin = self.origin,
initial_conditions = ic,
comments = self.comments+[util.execution_stamp('Grid','assemble')],
)
def renumber(self) -> 'Grid': def renumber(self) -> 'Grid':
""" """
Renumber sorted material indices as 0,...,N-1. Renumber sorted material indices as 0,...,N-1.
@ -1113,13 +1143,13 @@ class Grid:
selection_ = None if selection is None else \ selection_ = None if selection is None else \
set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \ set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \
set(self.material.flatten()) & set(util.aslist(selection)) set(self.material.flatten()) & set(util.aslist(selection))
material = ndimage.filters.generic_filter( material = ndimage.generic_filter(
self.material, self.material,
most_frequent, most_frequent,
footprint=footprint, footprint=footprint,
mode='wrap' if periodic else 'nearest', mode='wrap' if periodic else 'nearest',
extra_keywords=dict(selection=selection_,rng=rng), extra_keywords=dict(selection=selection_,rng=rng),
).astype(self.material.dtype) ).astype(self.material.dtype)
return Grid(material = material, return Grid(material = material,
size = self.size, size = self.size,
origin = self.origin, origin = self.origin,
@ -1269,12 +1299,12 @@ class Grid:
selection_ = None if selection is None else \ selection_ = None if selection is None else \
set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \ set(self.material.flatten()) - set(util.aslist(selection)) if invert_selection else \
set(self.material.flatten()) & set(util.aslist(selection)) set(self.material.flatten()) & set(util.aslist(selection))
mask = ndimage.filters.generic_filter(self.material, mask = ndimage.generic_filter(self.material,
tainted_neighborhood, tainted_neighborhood,
footprint=footprint, footprint=footprint,
mode='wrap' if periodic else 'nearest', mode='wrap' if periodic else 'nearest',
extra_keywords=dict(selection=selection_), extra_keywords=dict(selection=selection_),
) )
return Grid(material = np.where(mask, self.material + offset_,self.material), return Grid(material = np.where(mask, self.material + offset_,self.material),
size = self.size, size = self.size,

118
python/damask/grid_filters.py
View File

@ -541,28 +541,118 @@ def coordinates0_valid(coordinates0: _np.ndarray) -> bool:
return False return False
def unravel_index(idx: _np.ndarray) -> _np.ndarray:
"""
Convert flat indices to coordinate indices.
Parameters
----------
idx : numpy.ndarray, shape (:,:,:)
Grid of flat indices.
Returns
-------
unravelled : numpy.ndarray, shape (:,:,:,3)
Grid of coordinate indices.
Examples
--------
Unravel a linearly increasing sequence of material indices on a 3 × 2 × 1 grid.
>>> import numpy as np
>>> import damask
>>> seq = np.arange(6).reshape((3,2,1),order='F')
>>> (coord_idx := damask.grid_filters.unravel_index(seq))
array([[[[0, 0, 0]],
[[0, 1, 0]]],
[[[1, 0, 0]],
[[1, 1, 0]]],
[[[2, 0, 0]],
[[2, 1, 0]]]])
>>> coord_idx[1,1,0]
array([1, 1, 0])
"""
cells = idx.shape
idx_ = _np.expand_dims(idx,3)
return _np.block([ idx_ %cells[0],
(idx_//cells[0]) %cells[1],
((idx_//cells[0])//cells[1])%cells[2]])
def ravel_index(idx: _np.ndarray) -> _np.ndarray:
"""
Convert coordinate indices to flat indices.
Parameters
----------
idx : numpy.ndarray, shape (:,:,:,3)
Grid of coordinate indices.
Returns
-------
ravelled : numpy.ndarray, shape (:,:,:)
Grid of flat indices.
Examples
--------
Ravel a reversed sequence of coordinate indices on a 2 × 2 × 1 grid.
>>> import numpy as np
>>> import damask
>>> (rev := np.array([[1,1,0],[0,1,0],[1,0,0],[0,0,0]]).reshape((2,2,1,3)))
array([[[[1, 1, 0]],
[[0, 1, 0]]],
[[[1, 0, 0]],
[[0, 0, 0]]]])
>>> (flat_idx := damask.grid_filters.ravel_index(rev))
array([[[3],
[2]],
[[1],
[0]]])
"""
cells = idx.shape[:3]
return idx[:,:,:,0] \
+ idx[:,:,:,1]*cells[0] \
+ idx[:,:,:,2]*cells[0]*cells[1]
def regrid(size: _FloatSequence, def regrid(size: _FloatSequence,
F: _np.ndarray, F: _np.ndarray,
cells: _IntSequence) -> _np.ndarray: cells: _IntSequence) -> _np.ndarray:
""" """
Return mapping from coordinates in deformed configuration to a regular grid. Map a deformed grid A back to a rectilinear grid B.
The size of grid B is chosen as the average deformed size of grid A.
Parameters Parameters
---------- ----------
size : sequence of float, len (3) size : sequence of float, len (3)
Physical size. Physical size of grid A.
F : numpy.ndarray, shape (:,:,:,3,3), shape (:,:,:,3,3) F : numpy.ndarray, shape (:,:,:,3,3)
Deformation gradient field. Deformation gradient field on grid A.
cells : sequence of int, len (3) cells : sequence of int, len (3)
Cell count along x,y,z of remapping grid. Cell count along x,y,z of grid B.
Returns
-------
idx : numpy.ndarray of int, shape (cells)
Flat index of closest point on deformed grid A for each point on grid B.
""" """
c = coordinates_point(size,F) box = _np.dot(_np.average(F,axis=(0,1,2)),size)
c = coordinates_point(size,F)%box
outer = _np.dot(_np.average(F,axis=(0,1,2)),size) tree = _spatial.cKDTree(c.reshape((-1,3),order='F'),boxsize=box)
for d in range(3): return tree.query(coordinates0_point(cells,box))[1]
c[_np.where(c[:,:,:,d]<0)] += outer[d]
c[_np.where(c[:,:,:,d]>outer[d])] -= outer[d]
tree = _spatial.cKDTree(c.reshape(-1,3),boxsize=outer)
return tree.query(coordinates0_point(cells,outer))[1].flatten()

4
python/tests/reference/Grid/scale_grid_10-10-10.vti vendored
View File

@ -3,7 +3,7 @@
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<FieldData> <FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary"> <Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs= AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array> </Array>
</FieldData> </FieldData>
<Piece Extent="0 10 0 10 0 10"> <Piece Extent="0 10 0 10 0 10">
@ -11,7 +11,7 @@
</PointData> </PointData>
<CellData> <CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41"> <DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41">
AQAAAACAAABAHwAA+QAAAA==eF7t2DcSAjEQRFF28d57t3i4/wUJaCVdpYCqH46Sl/1oklZR+70iDMMwDP+wlHXZMJuyJdtmR3Yl3evJvhyYQzmSY3Mip5LuzeRcLsylXMm1uZFbSfd2ci8P5lGe5Nms5EXSvau8ybv5kE/5Mt/yI+kefc90j75nukffM92j75nu0fdM9+h7pnv0PdM9+p7pHn3PdI++Z7pXhmEYhmEYhqi5fyzfD74bfD+k3UD3cjvE94PvBt8PaTfQvdwO8f3gu8H3Q9oNdC+3Q3w/+G7w/VBJupfbIb4ffDf4fki7ge7R90z36Hume/Q90z36nukefc907wt6sixX AQAAAACAAABAHwAACgEAAA==eF7t1zcSAjEQRFEW7723i4f7X5CAVtJVCqB+OEpe9qMJWkXl+4owDMMw/MGqrMm62ZBN2TLbsiPpXlf2ZN8cyKEcmWM5kXRvKmdybi7kUq7MtdxIureVO7k3D/IoT2Ypz5LuXeRV3sy7fMin+ZJvSffoe6Z79D3TPfqe6R59z3SPvme6R98z3aPvme7R90z36Hume/Q9071qGIZhGP5h7p/u+8h3ke+jtIvoXm5n+T7yXeT7KO0iupfbWb6PfBf5Pkq7iO7ldpbvI99Fvo9KSfdyO8v3ke8i30dpF9E9+p7pHn3PdI++Z7pH3zPdo++Z7tH3TPfoe6Z79D3TPfqe6R59z3TvAxSdM5E=
</DataArray> </DataArray>
</CellData> </CellData>
</Piece> </Piece>

4
python/tests/reference/Grid/scale_grid_10-11-10.vti vendored
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@ -3,7 +3,7 @@
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<FieldData> <FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary"> <Array type="String" Name="comments" NumberOfTuples="1" format="binary">
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</Array> </Array>
</FieldData> </FieldData>
<Piece Extent="0 10 0 11 0 10"> <Piece Extent="0 10 0 11 0 10">
@ -11,7 +11,7 @@
</PointData> </PointData>
<CellData> <CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41"> <DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41">
AQAAAACAAABgIgAA/gAAAA==eF7t2CcOA0EQRFHnnHPO8f4XNHAtKWmQPxhZveSxj6ZBbbn0/cphGIZh+EdWZFXWzLpsyKbZkm1J9zqyK3tmXw7k0BzJsaR7EzmVM3MuF3JpruRa5t7byK3cmXt5kEfzJM+S7l3kVd7Mu3zIp/mSb0n36Puge/R90D36Pefeo++D7tH3Qffo+6B79H3QPfo9596j74Pu0fdB9yphGIZhGIZh+IOp/5S+v3x3+f4qdhfdS+0431++u3x/FbuL7qV2nO8l30m+l4qdlHsvteN8f/nu8v11knQvteN8f/nu8v1V7C66R98H3aPvg+7R7zn3Hn0fdI++D7r3AZqNMMY= AQAAAACAAABgIgAAEAEAAA==eF7t2DcOAkEQRFG8996zeLj/BQmoTUqa7Acj1Ju87EfTUmmrld9XDcMwDMM/sibrsmE2ZUu2zY7sSrrXk305MIdyJMfmRE4l3ZvJuVyYS7mSa3MjtzL33k7u5cE8ypM8m4W8SLp3lTd5Nx/yKV/mW34k3aPvg+7R90H36Pece4++D7pH3wfdo++D7tH3Qffo95x7j74PukffB92rhWEYhuEfmvpv4nvQd6DvwXIH0r3UrvQ96DvQ92C5A+lealf6fvPd5vut3G2591K70veg70Dfg4Wke6ld6XvQd6DvwXIH0j36PugefR90j37Puffo+6B79H3QPfo+6B59H3SPfs+59+j7oHv0fdC9L3s9OLk=
</DataArray> </DataArray>
</CellData> </CellData>
</Piece> </Piece>

4
python/tests/reference/Grid/scale_grid_10-13-10.vti vendored
View File

@ -3,7 +3,7 @@
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<FieldData> <FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary"> <Array type="String" Name="comments" NumberOfTuples="1" format="binary">
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<Piece Extent="0 10 0 13 0 10"> <Piece Extent="0 10 0 13 0 10">
@ -11,7 +11,7 @@
</PointData> </PointData>
<CellData> <CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41"> <DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41">
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</CellData> </CellData>
</Piece> </Piece>

4
python/tests/reference/Grid/scale_grid_10-20-2.vti vendored
View File

@ -3,7 +3,7 @@
<ImageData WholeExtent="0 10 0 20 0 2" Origin="0 0 0" Spacing="8e-7 2.5000000000000004e-7 0.000002" Direction="1 0 0 0 1 0 0 0 1"> <ImageData WholeExtent="0 10 0 20 0 2" Origin="0 0 0" Spacing="8e-7 2.5000000000000004e-7 0.000002" Direction="1 0 0 0 1 0 0 0 1">
<FieldData> <FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary"> <Array type="String" Name="comments" NumberOfTuples="1" format="binary">
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<Piece Extent="0 10 0 20 0 2"> <Piece Extent="0 10 0 20 0 2">
@ -11,7 +11,7 @@
</PointData> </PointData>
<CellData> <CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="40"> <DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="40">
AQAAAACAAACADAAAdgAAAA==eF7tzMsWgQAYReEuKJUoRKGLS3n/JzSwJ51ZRq3l35Nvtl3nm2uapmmaP+ihLy5wiSsxwBDn/ltjhLGY4AZTcYs7tN/Yqb8Mc9yLBzxiIZ7wjP/2K7HCi3jFG9Zigy3ab+zUX4d3fIhPfGEvDvjGuf8+MEUQzQ== AQAAAACAAACADAAAbQAAAA==eF7tzDcCggAQBVGiooCYQcFM8P4ntGCqX9ruTvO6CYO50HVd13X/MMJYTDDFhbjEDK39VrjGXCywxI1Y4Rat/Xa4x4N4xBOexRobtPa74BVbscMb3sUHPtHa74Vv/Ig9DjiKE37R2u8H6ycQzQ==
</DataArray> </DataArray>
</CellData> </CellData>
</Piece> </Piece>

4
python/tests/reference/Grid/scale_grid_5-4-20.vti vendored
View File

@ -3,7 +3,7 @@
<ImageData WholeExtent="0 5 0 4 0 20" Origin="0 0 0" Spacing="0.0000016 0.00000125 2e-7" Direction="1 0 0 0 1 0 0 0 1"> <ImageData WholeExtent="0 5 0 4 0 20" Origin="0 0 0" Spacing="0.0000016 0.00000125 2e-7" Direction="1 0 0 0 1 0 0 0 1">
<FieldData> <FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary"> <Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs= AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array> </Array>
</FieldData> </FieldData>
<Piece Extent="0 5 0 4 0 20"> <Piece Extent="0 5 0 4 0 20">
@ -11,7 +11,7 @@
</PointData> </PointData>
<CellData> <CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41"> <DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41">
AQAAAACAAACADAAAeAAAAA==eF7t1TkWggAUQ1EREZS5BFQmB9j/Bin++40b8OBJmtumSoKDJZDyBx7xhGeM8YJXzLDAEmts8YYP7HHECZ/4xg+uqH4W9bOon+W7n5Ryf/oPhxih70yCvjMp5ug7U2GDHd7Rd2ZA35kZX+g7s6D6Wf613wZ8oBHR AQAAAACAAACADAAAeAAAAA==eF7t1bkWglAUQ1GfiICAQMngwKTy/z9occ+t6LVJmt2myUo4WIKUcucRTxhjghlesMASK2ywwwFv+MARJ1xwxTduqH4W9bP8q5+Ucq//SIS+4zOm6DvO0Xd8xRpb7NF3fMcn+o5n9B2/8IPqZ1E/y6/7fQE+LBGB
</DataArray> </DataArray>
</CellData> </CellData>
</Piece> </Piece>

4
python/tests/reference/Grid/scale_grid_8-10-12.vti vendored
View File

@ -3,7 +3,7 @@
<ImageData WholeExtent="0 8 0 10 0 12" Origin="0 0 0" Spacing="0.000001 5.000000000000001e-7 3.333333333333333e-7" Direction="1 0 0 0 1 0 0 0 1"> <ImageData WholeExtent="0 8 0 10 0 12" Origin="0 0 0" Spacing="0.000001 5.000000000000001e-7 3.333333333333333e-7" Direction="1 0 0 0 1 0 0 0 1">
<FieldData> <FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary"> <Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs= AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array> </Array>
</FieldData> </FieldData>
<Piece Extent="0 8 0 10 0 12"> <Piece Extent="0 8 0 10 0 12">
@ -11,7 +11,7 @@
</PointData> </PointData>
<CellData> <CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41"> <DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41">
AQAAAACAAAAAHgAAyAAAAA==eF7t2LcBAkEUxFDu8N5776H/BglQBwpvNnmRskn+FrX/K2KMsWKWWMcGNrGFbexgF23fwz4OcIgjHOMEp2j7Gc5xgUtc4Ro3uEXb73CPBzziCc94wSva/oZ3fOATX/jGD37R9nY/trf7sb3dj+3tfmxv92N7ux/b2/3Y3u7H9nY/trf7sb3dj+3tfmxv92N7ux/b2/3YvowxxhhjjJXS/gPa3t4htrd3iO3tHWJ7e4fY3u7H9nY/trf7sb3dj+3tfmz/A1V7KtE= AQAAAACAAAAAHgAAyQAAAA==eF7t17cRw0AUxFCR8t5776X+G1QgdIAZRnvJi5Bt8K+o/V8RY4wxxsossY4NbGIL29jBLtq+h30c4BBHOMYJTtH2M5zjApe4wjVucIu23+EeD3jEE57xgle0/Q3v+MAnvvCNH/yi7e1+bG/3Y3u7H9vb/dje7sf2dj+2t/uxvd2P7e1+bG/3Y/syxhhjjJVr/8G2t3eg7e0daHt7B9re3oG2t/uxvd2P7e1+bG/3Y3u7H9vb/dje7sf2dj+2t/uxvd2P7X9ILyox
</DataArray> </DataArray>
</CellData> </CellData>
</Piece> </Piece>

8
python/tests/test_Grid.py
View File

@ -212,6 +212,14 @@ class TestGrid:
assert default == modified.renumber() assert default == modified.renumber()
def test_assemble(self):
cells = np.random.randint(8,16,3)
N = cells.prod()
g = Grid(np.arange(N).reshape(cells),np.ones(3))
idx = np.random.randint(0,N,N).reshape(cells)
assert (idx == g.assemble(idx).material).all
def test_substitute(self,default): def test_substitute(self,default):
offset = np.random.randint(1,500) offset = np.random.randint(1,500)
modified = Grid(default.material + offset, modified = Grid(default.material + offset,

38
python/tests/test_grid_filters.py
View File

@ -144,16 +144,15 @@ class TestGridFilters:
def test_regrid_identity(self): def test_regrid_identity(self):
size = np.random.random(3) # noqa size = np.random.random(3) # noqa
cells = np.random.randint(8,32,(3)) cells = np.random.randint(8,32,(3))
F = np.broadcast_to(np.eye(3), tuple(cells)+(3,3)) F = np.broadcast_to(np.eye(3), (*cells,3,3))
assert all(grid_filters.regrid(size,F,cells) == np.arange(cells.prod())) assert (grid_filters.regrid(size,F,cells).flatten() == np.arange(cells.prod())).all
def test_regrid_double_cells(self): def test_regrid_double_cells(self):
size = np.random.random(3) # noqa size = np.random.random(3) # noqa
cells = np.random.randint(8,32,(3)) cells = np.random.randint(8,32,(3))
g = Grid.from_Voronoi_tessellation(cells,size,seeds.from_random(size,10)) g = Grid.from_Voronoi_tessellation(cells,size,seeds.from_random(size,10))
F = np.broadcast_to(np.eye(3), tuple(cells)+(3,3)) F = np.broadcast_to(np.eye(3), (*cells,3,3))
assert all(g.scale(cells*2).material.flatten() == assert g.scale(cells*2) == g.assemble(grid_filters.regrid(size,F,cells*2))
g.material.flatten()[grid_filters.regrid(size,F,cells*2)])
@pytest.mark.parametrize('differential_operator',[grid_filters.curl, @pytest.mark.parametrize('differential_operator',[grid_filters.curl,
grid_filters.divergence, grid_filters.divergence,
@ -319,7 +318,6 @@ class TestGridFilters:
] ]
@pytest.mark.parametrize('field_def,div_def',div_test_data) @pytest.mark.parametrize('field_def,div_def',div_test_data)
def test_div(self,field_def,div_def): def test_div(self,field_def,div_def):
size = np.random.random(3)+1.0 size = np.random.random(3)+1.0
cells = np.random.randint(8,32,(3)) cells = np.random.randint(8,32,(3))
@ -336,3 +334,31 @@ class TestGridFilters:
div=div.reshape(tuple(cells)) div=div.reshape(tuple(cells))
assert np.allclose(div,grid_filters.divergence(size,field)) assert np.allclose(div,grid_filters.divergence(size,field))
def test_ravel_index(self):
cells = np.random.randint(8,32,(3))
indices = np.block(np.meshgrid(np.arange(cells[0]),
np.arange(cells[1]),
np.arange(cells[2]),indexing='ij')).reshape(tuple(cells)+(3,),order='F')
x,y,z = map(np.random.randint,cells)
assert grid_filters.ravel_index(indices)[x,y,z] == np.arange(0,np.product(cells)).reshape(cells,order='F')[x,y,z]
def test_unravel_index(self):
cells = np.random.randint(8,32,(3))
indices = np.arange(np.prod(cells)).reshape(cells,order='F')
x,y,z = map(np.random.randint,cells)
assert np.all(grid_filters.unravel_index(indices)[x,y,z] == [x,y,z])
def test_ravel_unravel_index(self):
cells = np.random.randint(8,32,(3))
indices = np.random.randint(0,np.prod(cells),cells).reshape(cells)
assert np.all(indices==grid_filters.ravel_index(grid_filters.unravel_index(indices)))
def test_unravel_ravel_index(self):
cells = np.hstack([np.random.randint(8,32,(3)),1])
indices = np.block([np.random.randint(0,cells[0],cells),
np.random.randint(0,cells[1],cells),
np.random.randint(0,cells[2],cells)])
assert np.all(indices==grid_filters.unravel_index(grid_filters.ravel_index(indices)))