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Merge branch 'fix-grid-convention' into 'development' 

Fix grid convention

See merge request damask/DAMASK!160
This commit is contained in:
Francisco Jose Gallardo Basile 2020-04-23 19:02:23 +02:00
parent 289808875c 936ce6a160
commit 898cf42aca
15 changed files with 209 additions and 150 deletions
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2
processing/post/DADF5_postResults.py
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@ -33,7 +33,7 @@ for filename in options.filenames:
results = damask.Result(filename)
if not results.structured: continue
coords = damask.grid_filters.cell_coord0(results.grid,results.size,results.origin)
coords = damask.grid_filters.cell_coord0(results.grid,results.size,results.origin).reshape(-1,3,order='F')
N_digits = int(np.floor(np.log10(int(results.increments[-1][3:]))))+1
N_digits = 5 # hack to keep test intact

55
processing/post/addCompatibilityMismatch.py
View File

@ -17,7 +17,7 @@ def volTetrahedron(coords):
"""
Return the volume of the tetrahedron with given vertices or sides.
Ifvertices are given they must be in a NumPy array with shape (4,3): the
If vertices are given they must be in a NumPy array with shape (4,3): the
position vectors of the 4 vertices in 3 dimensions; if the six sides are
given, they must be an array of length 6. If both are given, the sides
will be used in the calculation.
@ -67,14 +67,13 @@ def volumeMismatch(size,F,nodes):
(compatible) cube and determinant of deformation gradient at Fourier point.
"""
coords = np.empty([8,3])
vMismatch = np.empty(grid[::-1])
volInitial = size.prod()/grid.prod()
vMismatch = np.empty(F.shape[:3])
#--------------------------------------------------------------------------------------------------
# calculate actual volume and volume resulting from deformation gradient
for k in range(grid[2]):
for k in range(grid[0]):
for j in range(grid[1]):
for i in range(grid[0]):
for i in range(grid[2]):
coords[0,0:3] = nodes[k, j, i ,0:3]
coords[1,0:3] = nodes[k ,j, i+1,0:3]
coords[2,0:3] = nodes[k ,j+1,i+1,0:3]
@ -91,8 +90,7 @@ def volumeMismatch(size,F,nodes):
+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[5,0:3]])) \
+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[0,0:3]]))) \
/np.linalg.det(F[k,j,i,0:3,0:3])
return vMismatch/volInitial
return vMismatch/(size.prod()/grid.prod())
def shapeMismatch(size,F,nodes,centres):
@ -103,35 +101,34 @@ def shapeMismatch(size,F,nodes,centres):
the corners of reconstructed (combatible) volume element and the vectors calculated by deforming
the initial volume element with the current deformation gradient.
"""
coordsInitial = np.empty([8,3])
sMismatch = np.empty(grid[::-1])
sMismatch = np.empty(F.shape[:3])
#--------------------------------------------------------------------------------------------------
# initial positions
coordsInitial[0,0:3] = [-size[0]/grid[0],-size[1]/grid[1],-size[2]/grid[2]]
coordsInitial[1,0:3] = [+size[0]/grid[0],-size[1]/grid[1],-size[2]/grid[2]]
coordsInitial[2,0:3] = [+size[0]/grid[0],+size[1]/grid[1],-size[2]/grid[2]]
coordsInitial[3,0:3] = [-size[0]/grid[0],+size[1]/grid[1],-size[2]/grid[2]]
coordsInitial[4,0:3] = [-size[0]/grid[0],-size[1]/grid[1],+size[2]/grid[2]]
coordsInitial[5,0:3] = [+size[0]/grid[0],-size[1]/grid[1],+size[2]/grid[2]]
coordsInitial[6,0:3] = [+size[0]/grid[0],+size[1]/grid[1],+size[2]/grid[2]]
coordsInitial[7,0:3] = [-size[0]/grid[0],+size[1]/grid[1],+size[2]/grid[2]]
coordsInitial = coordsInitial/2.0
delta = size/grid*.5
coordsInitial = np.vstack((delta * np.array((-1,-1,-1)),
delta * np.array((+1,-1,-1)),
delta * np.array((+1,+1,-1)),
delta * np.array((-1,+1,-1)),
delta * np.array((-1,-1,+1)),
delta * np.array((+1,-1,+1)),
delta * np.array((+1,+1,+1)),
delta * np.array((-1,+1,+1))))
#--------------------------------------------------------------------------------------------------
# compare deformed original and deformed positions to actual positions
for k in range(grid[2]):
for k in range(grid[0]):
for j in range(grid[1]):
for i in range(grid[0]):
for i in range(grid[2]):
sMismatch[k,j,i] = \
+ np.linalg.norm(nodes[k, j, i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[0,0:3]))\
+ np.linalg.norm(nodes[k, j, i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[1,0:3]))\
+ np.linalg.norm(nodes[k, j+1,i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[2,0:3]))\
+ np.linalg.norm(nodes[k+1,j, i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[1,0:3]))\
+ np.linalg.norm(nodes[k+1,j+1,i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[2,0:3]))\
+ np.linalg.norm(nodes[k, j+1,i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[3,0:3]))\
+ np.linalg.norm(nodes[k+1,j, i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[4,0:3]))\
+ np.linalg.norm(nodes[k, j, i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[4,0:3]))\
+ np.linalg.norm(nodes[k+1,j, i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[5,0:3]))\
+ np.linalg.norm(nodes[k+1,j+1,i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[6,0:3]))\
+ np.linalg.norm(nodes[k+1,j+1,i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[7,0:3]))
+ np.linalg.norm(nodes[k ,j+1,i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[7,0:3]))
return sMismatch
@ -178,20 +175,20 @@ for name in filenames:
table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
F = table.get(options.defgrad).reshape(grid[2],grid[1],grid[0],3,3)
F = table.get(options.defgrad).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
nodes = damask.grid_filters.node_coord(size,F)
if options.shape:
centers = damask.grid_filters.cell_coord(size,F)
shapeMismatch = shapeMismatch( size,table.get(options.defgrad).reshape(grid[2],grid[1],grid[0],3,3),nodes,centers)
shapeMismatch = shapeMismatch(size,F,nodes,centers)
table.add('shapeMismatch(({}))'.format(options.defgrad),
shapeMismatch.reshape(-1,1),
shapeMismatch.reshape(-1,1,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
if options.volume:
volumeMismatch = volumeMismatch(size,table.get(options.defgrad).reshape(grid[2],grid[1],grid[0],3,3),nodes)
volumeMismatch = volumeMismatch(size,F,nodes)
table.add('volMismatch(({}))'.format(options.defgrad),
volumeMismatch.reshape(-1,1),
volumeMismatch.reshape(-1,1,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

5
processing/post/addCurl.py
View File

@ -49,9 +49,10 @@ for name in filenames:
for label in options.labels:
field = table.get(label)
shape = (3,) if np.prod(field.shape)//np.prod(grid) == 3 else (3,3) # vector or tensor
field = field.reshape(np.append(grid[::-1],shape))
field = field.reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+shape)
curl = damask.grid_filters.curl(size,field)
table.add('curlFFT({})'.format(label),
damask.grid_filters.curl(size[::-1],field).reshape(-1,np.prod(shape)),
curl.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape),order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

14
processing/post/addDisplacement.py
View File

@ -5,8 +5,6 @@ import sys
from io import StringIO
from optparse import OptionParser
import numpy as np
import damask
@ -52,22 +50,22 @@ for name in filenames:
table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
F = table.get(options.f).reshape(np.append(grid[::-1],(3,3)))
F = table.get(options.f).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
if options.nodal:
table = damask.Table(damask.grid_filters.node_coord0(grid[::-1],size[::-1]).reshape(-1,3),
table = damask.Table(damask.grid_filters.node_coord0(grid,size).reshape(-1,3,order='F'),
{'pos':(3,)})
table.add('avg({}).{}'.format(options.f,options.pos),
damask.grid_filters.node_displacement_avg(size[::-1],F).reshape(-1,3),
damask.grid_filters.node_displacement_avg(size,F).reshape(-1,3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.add('fluct({}).{}'.format(options.f,options.pos),
damask.grid_filters.node_displacement_fluct(size[::-1],F).reshape(-1,3),
damask.grid_filters.node_displacement_fluct(size,F).reshape(-1,3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else os.path.splitext(name)[0]+'_nodal.txt')
else:
table.add('avg({}).{}'.format(options.f,options.pos),
damask.grid_filters.cell_displacement_avg(size[::-1],F).reshape(-1,3),
damask.grid_filters.cell_displacement_avg(size,F).reshape(-1,3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.add('fluct({}).{}'.format(options.f,options.pos),
damask.grid_filters.cell_displacement_fluct(size[::-1],F).reshape(-1,3),
damask.grid_filters.cell_displacement_fluct(size,F).reshape(-1,3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

5
processing/post/addDivergence.py
View File

@ -49,9 +49,10 @@ for name in filenames:
for label in options.labels:
field = table.get(label)
shape = (3,) if np.prod(field.shape)//np.prod(grid) == 3 else (3,3) # vector or tensor
field = field.reshape(np.append(grid[::-1],shape))
field = field.reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+shape)
div = damask.grid_filters.divergence(size,field)
table.add('divFFT({})'.format(label),
damask.grid_filters.divergence(size[::-1],field).reshape(-1,np.prod(shape)//3),
div.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)//3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

5
processing/post/addGradient.py
View File

@ -49,9 +49,10 @@ for name in filenames:
for label in options.labels:
field = table.get(label)
shape = (1,) if np.prod(field.shape)//np.prod(grid) == 1 else (3,) # scalar or vector
field = field.reshape(np.append(grid[::-1],shape))
field = field.reshape(tuple(grid)+(-1,),order='F')
grad = damask.grid_filters.gradient(size,field)
table.add('gradFFT({})'.format(label),
damask.grid_filters.gradient(size[::-1],field).reshape(-1,np.prod(shape)*3),
grad.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)*3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

2
processing/post/averageDown.py
View File

@ -91,7 +91,7 @@ for name in filenames:
table = damask.Table(averagedDown,table.shapes,table.comments)
coords = damask.grid_filters.cell_coord0(packedGrid,size,shift/packedGrid*size+origin)
table.set(options.pos, coords.reshape(-1,3))
table.set(options.pos, coords.reshape(-1,3,order='F'))
outname = os.path.join(os.path.dirname(name),prefix+os.path.basename(name))

6
processing/post/blowUp.py
View File

@ -59,13 +59,13 @@ for name in filenames:
packing = np.array(options.packing,'i')
outSize = grid*packing
data = table.data.values.reshape(tuple(grid)+(-1,))
blownUp = ndimage.interpolation.zoom(data,tuple(packing)+(1,),order=0,mode='nearest').reshape(outSize.prod(),-1)
data = table.data.values.reshape(tuple(grid)+(-1,),order='F')
blownUp = ndimage.interpolation.zoom(data,tuple(packing)+(1,),order=0,mode='nearest').reshape(outSize.prod(),-1,order='F')
table = damask.Table(blownUp,table.shapes,table.comments)
coords = damask.grid_filters.cell_coord0(outSize,size,origin)
table.set(options.pos,coords.reshape(-1,3))
table.set(options.pos,coords.reshape(-1,3,order='F'))
table.set('elem',np.arange(1,outSize.prod()+1))
outname = os.path.join(os.path.dirname(name),prefix+os.path.basename(name))

12
processing/pre/geom_fromVoronoiTessellation.py
View File

@ -24,22 +24,22 @@ def findClosestSeed(seeds, weights, point):
def Laguerre_tessellation(grid, size, seeds, weights, origin = np.zeros(3), periodic = True, cpus = 2):
if periodic:
weights_p = np.tile(weights,27).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
weights_p = np.tile(weights.squeeze(),27) # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
seeds_p = np.vstack((seeds -np.array([size[0],0.,0.]),seeds, seeds +np.array([size[0],0.,0.])))
seeds_p = np.vstack((seeds_p-np.array([0.,size[1],0.]),seeds_p,seeds_p+np.array([0.,size[1],0.])))
seeds_p = np.vstack((seeds_p-np.array([0.,0.,size[2]]),seeds_p,seeds_p+np.array([0.,0.,size[2]])))
coords = damask.grid_filters.cell_coord0(grid*3,size*3,-origin-size).reshape(-1,3,order='F')
coords = damask.grid_filters.cell_coord0(grid*3,size*3,-origin-size).reshape(-1,3)
else:
weights_p = weights.flatten()
weights_p = weights.squeeze()
seeds_p = seeds
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3)
if cpus > 1:
pool = multiprocessing.Pool(processes = cpus)
result = pool.map_async(partial(findClosestSeed,seeds_p,weights_p), [coord for coord in coords])
pool.close()
pool.join()
closest_seed = np.array(result.get())
closest_seed = np.array(result.get()).reshape(-1,3)
else:
closest_seed= np.array([findClosestSeed(seeds_p,weights_p,coord) for coord in coords])
@ -52,7 +52,7 @@ def Laguerre_tessellation(grid, size, seeds, weights, origin = np.zeros(3), peri
def Voronoi_tessellation(grid, size, seeds, origin = np.zeros(3), periodic = True):
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3)
KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
devNull,closest_seed = KDTree.query(coords)

2
processing/pre/seeds_fromGeom.py
View File

@ -54,7 +54,7 @@ for name in filenames:
np.in1d(microstructure,options.blacklist,invert=True) if options.blacklist else \
np.full(geom.grid.prod(),True,dtype=bool))
seeds = damask.grid_filters.cell_coord0(geom.grid,geom.size).reshape(-1,3)
seeds = damask.grid_filters.cell_coord0(geom.grid,geom.size).reshape(-1,3,order='F')
comments = geom.comments \
+ [scriptID + ' ' + ' '.join(sys.argv[1:]),

2
processing/pre/seeds_fromRandom.py
View File

@ -128,7 +128,7 @@ for name in filenames:
if not options.selective:
coords = damask.grid_filters.cell_coord0(grid,size).reshape(-1,3)
coords = damask.grid_filters.cell_coord0(grid,size).reshape(-1,3,order='F')
seeds = coords[np.random.choice(np.prod(grid), options.N, replace=False)] \
+ np.broadcast_to(size/grid,(options.N,3))*(np.random.rand(options.N,3)*.5-.25) # wobble without leaving grid
else:

16
python/damask/_geom.py
View File

@ -322,11 +322,10 @@ class Geom:
if i != grid.prod():
raise TypeError('Invalid file: expected {} entries, found {}'.format(grid.prod(),i))
microstructure = microstructure.reshape(grid,order='F')
if not np.any(np.mod(microstructure.flatten(),1) != 0.0): # no float present
if not np.any(np.mod(microstructure,1) != 0.0): # no float present
microstructure = microstructure.astype('int')
return Geom(microstructure.reshape(grid),size,origin,homogenization,comments)
return Geom(microstructure.reshape(grid,order='F'),size,origin,homogenization,comments)
@staticmethod
@ -352,16 +351,15 @@ class Geom:
"""
if periodic:
weights_p = np.tile(weights,27).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
weights_p = np.tile(weights,27) # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
seeds_p = np.vstack((seeds -np.array([size[0],0.,0.]),seeds, seeds +np.array([size[0],0.,0.])))
seeds_p = np.vstack((seeds_p-np.array([0.,size[1],0.]),seeds_p,seeds_p+np.array([0.,size[1],0.])))
seeds_p = np.vstack((seeds_p-np.array([0.,0.,size[2]]),seeds_p,seeds_p+np.array([0.,0.,size[2]])))
coords = grid_filters.cell_coord0(grid*3,size*3,-size).reshape(-1,3,order='F')
coords = grid_filters.cell_coord0(grid*3,size*3,-size).reshape(-1,3)
else:
weights_p = weights.flatten()
weights_p = weights
seeds_p = seeds
coords = grid_filters.cell_coord0(grid,size).reshape(-1,3,order='F')
coords = grid_filters.cell_coord0(grid,size).reshape(-1,3)
pool = multiprocessing.Pool(processes = int(Environment().options['DAMASK_NUM_THREADS']))
result = pool.map_async(partial(Geom._find_closest_seed,seeds_p,weights_p), [coord for coord in coords])
@ -396,7 +394,7 @@ class Geom:
perform a periodic tessellation. Defaults to True.
"""
coords = grid_filters.cell_coord0(grid,size).reshape(-1,3,order='F')
coords = grid_filters.cell_coord0(grid,size).reshape(-1,3)
KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
devNull,microstructure = KDTree.query(coords)

16
python/damask/_result.py
View File

@ -111,7 +111,7 @@ class Result:
select from 'set', 'add', and 'del'
what : str
attribute to change (must be from self.selection)
datasets : list of str or Boolean
datasets : list of str or bool
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
@ -203,7 +203,7 @@ class Result:
----------
what : str
attribute to change (must be from self.selection)
datasets : list of str or Boolean
datasets : list of str or bool
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
@ -219,7 +219,7 @@ class Result:
----------
what : str
attribute to change (must be from self.selection)
datasets : list of str or Boolean
datasets : list of str or bool
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
@ -235,7 +235,7 @@ class Result:
----------
what : str
attribute to change (must be from self.selection)
datasets : list of str or Boolean
datasets : list of str or bool
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
@ -262,10 +262,10 @@ class Result:
datasets : iterable or str
component : int
homogenization component to consider for constituent data
tagged : Boolean
tagged : bool
tag Table.column name with '#component'
defaults to False
split : Boolean
split : bool
split Table by increment and return dictionary of Tables
defaults to True
@ -326,7 +326,7 @@ class Result:
Parameters
----------
datasets : iterable or str or Boolean
datasets : iterable or str or bool
Examples
--------
@ -460,7 +460,7 @@ class Result:
def cell_coordinates(self):
"""Return initial coordinates of the cell centers."""
if self.structured:
return grid_filters.cell_coord0(self.grid,self.size,self.origin).reshape(-1,3)
return grid_filters.cell_coord0(self.grid,self.size,self.origin).reshape(-1,3,order='F')
else:
with h5py.File(self.fname,'r') as f:
return f['geometry/x_c'][()]

130
python/damask/grid_filters.py
View File

@ -1,3 +1,17 @@
"""
Filters for operations on regular grids.
Notes
-----
The grids are defined as (x,y,z,...) where x is fastest and z is slowest.
This convention is consistent with the geom file format.
When converting to/from a plain list (e.g. storage in ASCII table),
the following operations are required for tensorial data:
D3 = D1.reshape(grid+(-1,),order='F').reshape(grid+(3,3))
D1 = D3.reshape(grid+(-1,)).reshape(-1,9,order='F')
"""
from scipy import spatial as _spatial
import numpy as _np
@ -7,8 +21,12 @@ def _ks(size,grid,first_order=False):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
grid : numpy.ndarray of shape (3)
number of grid points.
first_order : bool, optional
correction for first order derivatives, defaults to False.
"""
k_sk = _np.where(_np.arange(grid[0])>grid[0]//2,_np.arange(grid[0])-grid[0],_np.arange(grid[0]))/size[0]
@ -19,8 +37,7 @@ def _ks(size,grid,first_order=False):
k_si = _np.arange(grid[2]//2+1)/size[2]
kk, kj, ki = _np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij')
return _np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3)
return _np.stack(_np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij'), axis=-1)
def curl(size,field):
@ -29,8 +46,10 @@ def curl(size,field):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
field : numpy.ndarray of shape (:,:,:,3) or (:,:,:,3,3)
periodic field of which the curl is calculated.
"""
n = _np.prod(field.shape[3:])
@ -53,8 +72,10 @@ def divergence(size,field):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
field : numpy.ndarray of shape (:,:,:,3) or (:,:,:,3,3)
periodic field of which the divergence is calculated.
"""
n = _np.prod(field.shape[3:])
@ -69,12 +90,14 @@ def divergence(size,field):
def gradient(size,field):
"""
Calculate gradient of a vector or scalar field in Fourier space.
Calculate gradient of a scalar or vector field in Fourier space.
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
field : numpy.ndarray of shape (:,:,:,1) or (:,:,:,3)
periodic field of which the gradient is calculated.
"""
n = _np.prod(field.shape[3:])
@ -93,9 +116,9 @@ def cell_coord0(grid,size,origin=_np.zeros(3)):
Parameters
----------
grid : numpy.ndarray
grid : numpy.ndarray of shape (3)
number of grid points.
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
origin : numpy.ndarray, optional
physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
@ -103,7 +126,11 @@ def cell_coord0(grid,size,origin=_np.zeros(3)):
"""
start = origin + size/grid*.5
end = origin + size - size/grid*.5
return _np.mgrid[start[0]:end[0]:grid[0]*1j,start[1]:end[1]:grid[1]*1j,start[2]:end[2]:grid[2]*1j].T
return _np.stack(_np.meshgrid(_np.linspace(start[0],end[0],grid[0]),
_np.linspace(start[1],end[1],grid[1]),
_np.linspace(start[2],end[2],grid[2]),indexing = 'ij'),
axis = -1)
def cell_displacement_fluct(size,F):
@ -112,7 +139,7 @@ def cell_displacement_fluct(size,F):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
@ -139,14 +166,14 @@ def cell_displacement_avg(size,F):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
"""
F_avg = _np.average(F,axis=(0,1,2))
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),cell_coord0(F.shape[:3][::-1],size))
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),cell_coord0(F.shape[:3],size))
def cell_displacement(size,F):
@ -155,7 +182,7 @@ def cell_displacement(size,F):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
@ -170,25 +197,25 @@ def cell_coord(size,F,origin=_np.zeros(3)):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
origin : numpy.ndarray, optional
origin : numpy.ndarray of shape (3), optional
physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
"""
return cell_coord0(F.shape[:3][::-1],size,origin) + cell_displacement(size,F)
return cell_coord0(F.shape[:3],size,origin) + cell_displacement(size,F)
def cell_coord0_gridSizeOrigin(coord0,ordered=True):
"""
Return grid 'DNA', i.e. grid, size, and origin from array of cell positions.
Return grid 'DNA', i.e. grid, size, and origin from 1D array of cell positions.
Parameters
----------
coord0 : numpy.ndarray
array of undeformed cell coordinates.
coord0 : numpy.ndarray of shape (:,3)
undeformed cell coordinates.
ordered : bool, optional
expect coord0 data to be ordered (x fast, z slow).
@ -211,13 +238,13 @@ def cell_coord0_gridSizeOrigin(coord0,ordered=True):
start = origin + delta*.5
end = origin - delta*.5 + size
if not _np.allclose(coords[0],_np.linspace(start[0],end[0],grid[0])) and \
_np.allclose(coords[1],_np.linspace(start[1],end[1],grid[1])) and \
_np.allclose(coords[2],_np.linspace(start[2],end[2],grid[2])):
if not (_np.allclose(coords[0],_np.linspace(start[0],end[0],grid[0])) and \
_np.allclose(coords[1],_np.linspace(start[1],end[1],grid[1])) and \
_np.allclose(coords[2],_np.linspace(start[2],end[2],grid[2]))):
raise ValueError('Regular grid spacing violated.')
if ordered and not _np.allclose(coord0.reshape(tuple(grid[::-1])+(3,)),cell_coord0(grid,size,origin)):
raise ValueError('Input data is not a regular grid.')
if ordered and not _np.allclose(coord0.reshape(tuple(grid)+(3,),order='F'),cell_coord0(grid,size,origin)):
raise ValueError('Input data is not ordered (x fast, z slow).')
return (grid,size,origin)
@ -241,17 +268,18 @@ def node_coord0(grid,size,origin=_np.zeros(3)):
Parameters
----------
grid : numpy.ndarray
grid : numpy.ndarray of shape (3)
number of grid points.
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
origin : numpy.ndarray, optional
origin : numpy.ndarray of shape (3), optional
physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
"""
return _np.mgrid[origin[0]:size[0]+origin[0]:(grid[0]+1)*1j,
origin[1]:size[1]+origin[1]:(grid[1]+1)*1j,
origin[2]:size[2]+origin[2]:(grid[2]+1)*1j].T
return _np.stack(_np.meshgrid(_np.linspace(origin[0],size[0]+origin[0],grid[0]+1),
_np.linspace(origin[1],size[1]+origin[1],grid[1]+1),
_np.linspace(origin[2],size[2]+origin[2],grid[2]+1),indexing = 'ij'),
axis = -1)
def node_displacement_fluct(size,F):
@ -260,7 +288,7 @@ def node_displacement_fluct(size,F):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
@ -275,14 +303,14 @@ def node_displacement_avg(size,F):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
"""
F_avg = _np.average(F,axis=(0,1,2))
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),node_coord0(F.shape[:3][::-1],size))
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),node_coord0(F.shape[:3],size))
def node_displacement(size,F):
@ -291,7 +319,7 @@ def node_displacement(size,F):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
@ -306,15 +334,15 @@ def node_coord(size,F,origin=_np.zeros(3)):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size of the periodic field.
F : numpy.ndarray
deformation gradient field.
origin : numpy.ndarray, optional
origin : numpy.ndarray of shape (3), optional
physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
"""
return node_coord0(F.shape[:3][::-1],size,origin) + node_displacement(size,F)
return node_coord0(F.shape[:3],size,origin) + node_displacement(size,F)
def cell_2_node(cell_data):
@ -335,14 +363,14 @@ def node_2_cell(node_data):
return c[:-1,:-1,:-1]
def node_coord0_gridSizeOrigin(coord0,ordered=False):
def node_coord0_gridSizeOrigin(coord0,ordered=True):
"""
Return grid 'DNA', i.e. grid, size, and origin from array of nodal positions.
Return grid 'DNA', i.e. grid, size, and origin from 1D array of nodal positions.
Parameters
----------
coord0 : numpy.ndarray
array of undeformed nodal coordinates.
coord0 : numpy.ndarray of shape (:,3)
undeformed nodal coordinates.
ordered : bool, optional
expect coord0 data to be ordered (x fast, z slow).
@ -357,13 +385,13 @@ def node_coord0_gridSizeOrigin(coord0,ordered=False):
if (grid+1).prod() != len(coord0):
raise ValueError('Data count {} does not match grid {}.'.format(len(coord0),grid))
if not _np.allclose(coords[0],_np.linspace(mincorner[0],maxcorner[0],grid[0]+1)) and \
_np.allclose(coords[1],_np.linspace(mincorner[1],maxcorner[1],grid[1]+1)) and \
_np.allclose(coords[2],_np.linspace(mincorner[2],maxcorner[2],grid[2]+1)):
if not (_np.allclose(coords[0],_np.linspace(mincorner[0],maxcorner[0],grid[0]+1)) and \
_np.allclose(coords[1],_np.linspace(mincorner[1],maxcorner[1],grid[1]+1)) and \
_np.allclose(coords[2],_np.linspace(mincorner[2],maxcorner[2],grid[2]+1))):
raise ValueError('Regular grid spacing violated.')
if ordered and not _np.allclose(coord0.reshape(tuple((grid+1)[::-1])+(3,)),node_coord0(grid,size,origin)):
raise ValueError('Input data is not a regular grid.')
if ordered and not _np.allclose(coord0.reshape(tuple(grid+1)+(3,),order='F'),node_coord0(grid,size,origin)):
raise ValueError('Input data is not ordered (x fast, z slow).')
return (grid,size,origin)
@ -374,15 +402,15 @@ def regrid(size,F,new_grid):
Parameters
----------
size : numpy.ndarray
size : numpy.ndarray of shape (3)
physical size
F : numpy.ndarray
F : numpy.ndarray of shape (:,:,:,3,3)
deformation gradient field
new_grid : numpy.ndarray
new_grid : numpy.ndarray of shape (3)
new grid for undeformed coordinates
"""
c = cell_coord0(F.shape[:3][::-1],size) \
c = cell_coord0(F.shape[:3],size) \
+ cell_displacement_avg(size,F) \
+ cell_displacement_fluct(size,F)

47
python/tests/test_grid_filters.py
View File

@ -9,13 +9,13 @@ class TestGridFilters:
size = np.random.random(3)
grid = np.random.randint(8,32,(3))
coord = grid_filters.cell_coord0(grid,size)
assert np.allclose(coord[0,0,0],size/grid*.5) and coord.shape == tuple(grid[::-1]) + (3,)
assert np.allclose(coord[0,0,0],size/grid*.5) and coord.shape == tuple(grid) + (3,)
def test_node_coord0(self):
size = np.random.random(3)
grid = np.random.randint(8,32,(3))
coord = grid_filters.node_coord0(grid,size)
assert np.allclose(coord[-1,-1,-1],size) and coord.shape == tuple(grid[::-1]+1) + (3,)
assert np.allclose(coord[-1,-1,-1],size) and coord.shape == tuple(grid+1) + (3,)
def test_coord0(self):
size = np.random.random(3)
@ -31,7 +31,7 @@ class TestGridFilters:
size = np.random.random(3)
origin = np.random.random(3)
coord0 = eval('grid_filters.{}_coord0(grid,size,origin)'.format(mode)) # noqa
_grid,_size,_origin = eval('grid_filters.{}_coord0_gridSizeOrigin(coord0.reshape(-1,3))'.format(mode))
_grid,_size,_origin = eval('grid_filters.{}_coord0_gridSizeOrigin(coord0.reshape(-1,3,order="F"))'.format(mode))
assert np.allclose(grid,_grid) and np.allclose(size,_size) and np.allclose(origin,_origin)
def test_displacement_fluct_equivalence(self):
@ -57,9 +57,9 @@ class TestGridFilters:
shifted = eval('grid_filters.{}_coord0(grid,size,origin)'.format(mode))
unshifted = eval('grid_filters.{}_coord0(grid,size)'.format(mode))
if mode == 'cell':
assert np.allclose(shifted,unshifted+np.broadcast_to(origin,tuple(grid[::-1]) +(3,)))
assert np.allclose(shifted,unshifted+np.broadcast_to(origin,tuple(grid) +(3,)))
elif mode == 'node':
assert np.allclose(shifted,unshifted+np.broadcast_to(origin,tuple(grid[::-1]+1)+(3,)))
assert np.allclose(shifted,unshifted+np.broadcast_to(origin,tuple(grid+1)+(3,)))
@pytest.mark.parametrize('function',[grid_filters.cell_displacement_avg,
grid_filters.node_displacement_avg])
@ -80,8 +80,43 @@ class TestGridFilters:
F = np.broadcast_to(np.random.random((3,3)), tuple(grid)+(3,3))
assert np.allclose(function(size,F),0.0)
@pytest.mark.parametrize('function',[grid_filters.coord0_check,
grid_filters.node_coord0_gridSizeOrigin,
grid_filters.cell_coord0_gridSizeOrigin])
def test_invalid_coordinates(self,function):
invalid_coordinates = np.random.random((np.random.randint(12,52),3))
with pytest.raises(ValueError):
function(invalid_coordinates)
@pytest.mark.parametrize('function',[grid_filters.node_coord0_gridSizeOrigin,
grid_filters.cell_coord0_gridSizeOrigin])
def test_uneven_spaced_coordinates(self,function):
start = np.random.random(3)
end = np.random.random(3)*10. + start
grid = np.random.randint(8,32,(3))
uneven = np.stack(np.meshgrid(np.logspace(start[0],end[0],grid[0]),
np.logspace(start[1],end[1],grid[1]),
np.logspace(start[2],end[2],grid[2]),indexing = 'ij'),
axis = -1).reshape((grid.prod(),3),order='F')
with pytest.raises(ValueError):
function(uneven)
@pytest.mark.parametrize('mode',[True,False])
@pytest.mark.parametrize('function',[grid_filters.node_coord0_gridSizeOrigin,
grid_filters.cell_coord0_gridSizeOrigin])
def test_unordered_coordinates(self,function,mode):
origin = np.random.random(3)
size = np.random.random(3)*10.+origin
grid = np.random.randint(8,32,(3))
unordered = grid_filters.node_coord0(grid,size,origin).reshape(-1,3)
if mode:
with pytest.raises(ValueError):
function(unordered,mode)
else:
function(unordered,mode)
def test_regrid(self):
size = np.random.random(3)
grid = np.random.randint(8,32,(3))
F = np.broadcast_to(np.eye(3), tuple(grid[::-1])+(3,3))
F = np.broadcast_to(np.eye(3), tuple(grid)+(3,3))
assert all(grid_filters.regrid(size,F,grid) == np.arange(grid.prod()))