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:
Martin Diehl 2022-03-11 22:22:12 +01:00
parent b1effccafe
commit c5c2763e1f
3 changed files with 393 additions and 402 deletions

View File

@ -717,6 +717,368 @@ class Grid:
.show('material',colormap) .show('material',colormap)
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
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 mirror(self,
directions: Sequence[str],
reflect: bool = False) -> 'Grid':
"""
Mirror grid along given directions.
Parameters
----------
directions : (sequence of) {'x', 'y', 'z'}
Direction(s) along which the grid is mirrored.
reflect : bool, optional
Reflect (include) outermost layers. Defaults to False.
Returns
-------
updated : damask.Grid
Updated grid-based geometry.
Examples
--------
Mirror along x- and y-direction.
>>> import numpy as np
>>> import damask
>>> 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
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 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 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
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 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 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 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. Defaults to all.
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: Union[None,set],
rng):
me = stencil[stencil.size//2]
if selection is None 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_ = 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(
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 add_primitive(self, def add_primitive(self,
dimension: Union[FloatSequence, IntSequence], dimension: Union[FloatSequence, IntSequence],
center: Union[FloatSequence, IntSequence], center: Union[FloatSequence, IntSequence],
@ -809,366 +1171,6 @@ class Grid:
) )
def mirror(self,
directions: Sequence[str],
reflect: bool = False) -> 'Grid':
"""
Mirror grid along given directions.
Parameters
----------
directions : (sequence of) {'x', 'y', 'z'}
Direction(s) along which the grid is mirrored.
reflect : bool, optional
Reflect (include) outermost layers. Defaults to False.
Returns
-------
updated : damask.Grid
Updated grid-based geometry.
Examples
--------
Mirror along x- and y-direction.
>>> import numpy as np
>>> import damask
>>> 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
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
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
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,

View File

@ -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

View File

@ -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