223031012
/
DAMASK_EICMD
mirror of https://github.com/achalhp/DAMASK_EICMD.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

grid assemble + corrected grid.scale

This commit is contained in:
Martin Diehl 2022-11-08 18:52:08 +00:00 committed by Philip Eisenlohr
parent 507e1a2f05
commit 4f0db64e15
10 changed files with 220 additions and 66 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

76
python/damask/_grid.py
View File

@ -10,7 +10,7 @@ from pathlib import Path
import numpy as np
import pandas as pd
import h5py
from scipy import ndimage, spatial
from scipy import ndimage, spatial, interpolate
from . import VTK
from . import util
@ -41,7 +41,7 @@ class Grid:
Parameters
----------
material : numpy.ndarray, shape (:,:,:)
material : numpy.ndarray of int, shape (:,:,:)
Material indices. The shape of the material array defines
the number of cells.
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].
initial_conditions : dictionary, optional
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.
"""
@ -183,7 +183,7 @@ class Grid:
@comments.setter
def comments(self,
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
@ -427,7 +427,7 @@ class Grid:
coordinates : str
Label of the vector column containing the spatial coordinates.
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.
Each unique combination of values results in one material ID.
@ -474,7 +474,7 @@ class Grid:
Number of cells in x,y,z direction.
size : sequence of float, len (3)
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.
weights : sequence of float, len (seeds.shape[0])
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.
size : sequence of float, len (3)
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.
material : sequence of int, len (seeds.shape[0]), optional
Material ID of the seeds.
@ -940,17 +940,14 @@ class Grid:
def scale(self,
cells: IntSequence,
periodic: bool = True) -> 'Grid':
cells: IntSequence) -> 'Grid':
"""
Scale grid to new cells.
Scale grid to new cell count.
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
-------
@ -963,7 +960,11 @@ class Grid:
>>> import numpy as np
>>> 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)
cells : 64 x 64 x 64
size : 0.0001 x 0.0001 x 0.0001 m³
@ -971,20 +972,49 @@ class Grid:
# 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
),
options = ('nearest',False,None)
orig = tuple(map(np.linspace,self.origin + self.size/self.cells*.5,
self.origin + self.size - self.size/self.cells*.5,self.cells))
new = grid_filters.coordinates0_point(cells,self.size,self.origin)
return Grid(material = interpolate.RegularGridInterpolator(orig,self.material,*options)(new).astype(int),
size = self.size,
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')],
)
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':
"""
Renumber sorted material indices as 0,...,N-1.
@ -1113,7 +1143,7 @@ class Grid:
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))
material = ndimage.filters.generic_filter(
material = ndimage.generic_filter(
self.material,
most_frequent,
footprint=footprint,
@ -1269,7 +1299,7 @@ class Grid:
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))
mask = ndimage.filters.generic_filter(self.material,
mask = ndimage.generic_filter(self.material,
tainted_neighborhood,
footprint=footprint,
mode='wrap' if periodic else 'nearest',

118
python/damask/grid_filters.py
View File

@ -541,28 +541,118 @@ def coordinates0_valid(coordinates0: _np.ndarray) -> bool:
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,
F: _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
----------
size : sequence of float, len (3)
Physical size.
F : numpy.ndarray, shape (:,:,:,3,3), shape (:,:,:,3,3)
Deformation gradient field.
Physical size of grid A.
F : numpy.ndarray, shape (:,:,:,3,3)
Deformation gradient field on grid A.
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)
outer = _np.dot(_np.average(F,axis=(0,1,2)),size)
for d in range(3):
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()
box = _np.dot(_np.average(F,axis=(0,1,2)),size)
c = coordinates_point(size,F)%box
tree = _spatial.cKDTree(c.reshape((-1,3),order='F'),boxsize=box)
return tree.query(coordinates0_point(cells,box))[1]

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

@ -3,7 +3,7 @@
<ImageData WholeExtent="0 10 0 10 0 10" Origin="0 0 0" Spacing="8e-7 5.000000000000001e-7 4e-7" Direction="1 0 0 0 1 0 0 0 1">
<FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs=
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array>
</FieldData>
<Piece Extent="0 10 0 10 0 10">
@ -11,7 +11,7 @@
</PointData>
<CellData>
<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>
</CellData>
</Piece>

4
python/tests/reference/Grid/scale_grid_10-11-10.vti vendored
View File

@ -3,7 +3,7 @@
<ImageData WholeExtent="0 10 0 11 0 10" Origin="0 0 0" Spacing="8e-7 4.5454545454545457e-7 4e-7" Direction="1 0 0 0 1 0 0 0 1">
<FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs=
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array>
</FieldData>
<Piece Extent="0 10 0 11 0 10">
@ -11,7 +11,7 @@
</PointData>
<CellData>
<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>
</CellData>
</Piece>

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

@ -3,7 +3,7 @@
<ImageData WholeExtent="0 10 0 13 0 10" Origin="0 0 0" Spacing="8e-7 3.8461538461538463e-7 4e-7" Direction="1 0 0 0 1 0 0 0 1">
<FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs=
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array>
</FieldData>
<Piece Extent="0 10 0 13 0 10">
@ -11,7 +11,7 @@
</PointData>
<CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="1" RangeMax="41">
AQAAAACAAACgKAAACQEAAA==eF7t2blWAlEURFEBlcGJQcAZZBD4/x804HRSa72sghtUJzs72Q3qde/m+vVijDHGGLGPA7wV7/Aeh+IIx+juTfABH8UnfMYXcYozrN6b4wJfxSWucC2+4TtW733gJ36J3/iDG3GLv1i9t8M9HsQj/uFJPOMF3T33/bp77nur3nPfW/We+96q99z36+6579fdc99b9Z773qr33PdWvee+X3evH2OMMcYYY4wNW/8ZdP/r7tf93+1+d6/1jqB7XXe67vVup1fvtd4RdK/rTte93u306r3WO4Ludd3pute3WL3XekfQ/a+7X/d/t/vdPff9unvue6vec99b9Z773qr33Pfr7v0DeUA5pA==
AQAAAACAAACgKAAAFwEAAA==eF7t2DduA1EUQ1ErWcHK0co57X+DKsRpCPyOBQtOc7rbEXh/aj/frxZjjDHGCOuwAZtkC/7CNtmBXeje68E/2CcHcAhH5BhOoLo3hTM4JxdwCVfkP1xD994GbuGO3MMDPJIneIbq3gVe4Y28wwd8ki/4hu499d7ce+r9qnvqvbn31PtV99R7c++p9+beU+9X3VPvzb2n3q+6p96be68eY4wxxkiW/ivyfc53Od/n1V3u3iu9G/je5zuf7/3qzlf3Su8Gvs/5Luf7vLrL3XuldwPf+3zn871/gupe6d3A9znf5XyfV3e5e0+9N/eeer/qnnpv7j31ftU99d7ce+q9uffU+1X31Htz76n3q+6p9+be+wA2m0MJ
</DataArray>
</CellData>
</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">
<FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs=
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array>
</FieldData>
<Piece Extent="0 10 0 20 0 2">
@ -11,7 +11,7 @@
</PointData>
<CellData>
<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>
</CellData>
</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">
<FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs=
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array>
</FieldData>
<Piece Extent="0 5 0 4 0 20">
@ -11,7 +11,7 @@
</PointData>
<CellData>
<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>
</CellData>
</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">
<FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wc0/Nz9UrTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFYKEKs=
AQAAAACAAAA+AAAAQQAAAA==eF5LScxNLM7Wcy/KTNErTk7MSVUos7TUAyNdSyDQLagsSS0uUdAwMjC01DU01DUwUjA0tDK1sDIw0GQAAFW2EKk=
</Array>
</FieldData>
<Piece Extent="0 8 0 10 0 12">
@ -11,7 +11,7 @@
</PointData>
<CellData>
<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>
</CellData>
</Piece>

8
python/tests/test_Grid.py
View File

@ -212,6 +212,14 @@ class TestGrid:
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):
offset = np.random.randint(1,500)
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):
size = np.random.random(3) # noqa
cells = np.random.randint(8,32,(3))
F = np.broadcast_to(np.eye(3), tuple(cells)+(3,3))
assert all(grid_filters.regrid(size,F,cells) == np.arange(cells.prod()))
F = np.broadcast_to(np.eye(3), (*cells,3,3))
assert (grid_filters.regrid(size,F,cells).flatten() == np.arange(cells.prod())).all
def test_regrid_double_cells(self):
size = np.random.random(3) # noqa
cells = np.random.randint(8,32,(3))
g = Grid.from_Voronoi_tessellation(cells,size,seeds.from_random(size,10))
F = np.broadcast_to(np.eye(3), tuple(cells)+(3,3))
assert all(g.scale(cells*2).material.flatten() ==
g.material.flatten()[grid_filters.regrid(size,F,cells*2)])
F = np.broadcast_to(np.eye(3), (*cells,3,3))
assert g.scale(cells*2) == g.assemble(grid_filters.regrid(size,F,cells*2))
@pytest.mark.parametrize('differential_operator',[grid_filters.curl,
grid_filters.divergence,
@ -319,7 +318,6 @@ class TestGridFilters:
]
@pytest.mark.parametrize('field_def,div_def',div_test_data)
def test_div(self,field_def,div_def):
size = np.random.random(3)+1.0
cells = np.random.randint(8,32,(3))
@ -336,3 +334,31 @@ class TestGridFilters:
div=div.reshape(tuple(cells))
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)))