Merge branch 'development' into unified-RK4-RKCK45
This commit is contained in:
Martin Diehl
commit
49963b9f04
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@ -203,7 +203,6 @@ Post_OrientationConversion:
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stage: postprocessing
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script:
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- OrientationConversion/test.py
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- OrientationConversion/test2.py
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except:
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- master
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- release
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@ -33,7 +33,7 @@ for filename in options.filenames:
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results = damask.Result(filename)
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if not results.structured: continue
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coords = damask.grid_filters.cell_coord0(results.grid,results.size,results.origin)
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coords = damask.grid_filters.cell_coord0(results.grid,results.size,results.origin).reshape(-1,3,order='F')
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N_digits = int(np.floor(np.log10(int(results.increments[-1][3:]))))+1
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N_digits = 5 # hack to keep test intact
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@ -17,7 +17,7 @@ def volTetrahedron(coords):
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"""
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Return the volume of the tetrahedron with given vertices or sides.
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Ifvertices are given they must be in a NumPy array with shape (4,3): the
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If vertices are given they must be in a NumPy array with shape (4,3): the
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position vectors of the 4 vertices in 3 dimensions; if the six sides are
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given, they must be an array of length 6. If both are given, the sides
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will be used in the calculation.
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@ -67,14 +67,13 @@ def volumeMismatch(size,F,nodes):
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(compatible) cube and determinant of deformation gradient at Fourier point.
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"""
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coords = np.empty([8,3])
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vMismatch = np.empty(grid[::-1])
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volInitial = size.prod()/grid.prod()
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vMismatch = np.empty(F.shape[:3])
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#--------------------------------------------------------------------------------------------------
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# calculate actual volume and volume resulting from deformation gradient
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for k in range(grid[2]):
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for k in range(grid[0]):
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for j in range(grid[1]):
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for i in range(grid[0]):
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for i in range(grid[2]):
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coords[0,0:3] = nodes[k, j, i ,0:3]
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coords[1,0:3] = nodes[k ,j, i+1,0:3]
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coords[2,0:3] = nodes[k ,j+1,i+1,0:3]
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@ -91,8 +90,7 @@ def volumeMismatch(size,F,nodes):
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+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[5,0:3]])) \
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+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[0,0:3]]))) \
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/np.linalg.det(F[k,j,i,0:3,0:3])
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return vMismatch/volInitial
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return vMismatch/(size.prod()/grid.prod())
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def shapeMismatch(size,F,nodes,centres):
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@ -103,35 +101,34 @@ def shapeMismatch(size,F,nodes,centres):
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the corners of reconstructed (combatible) volume element and the vectors calculated by deforming
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the initial volume element with the current deformation gradient.
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"""
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coordsInitial = np.empty([8,3])
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sMismatch = np.empty(grid[::-1])
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sMismatch = np.empty(F.shape[:3])
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#--------------------------------------------------------------------------------------------------
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# initial positions
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coordsInitial[0,0:3] = [-size[0]/grid[0],-size[1]/grid[1],-size[2]/grid[2]]
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coordsInitial[1,0:3] = [+size[0]/grid[0],-size[1]/grid[1],-size[2]/grid[2]]
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coordsInitial[2,0:3] = [+size[0]/grid[0],+size[1]/grid[1],-size[2]/grid[2]]
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coordsInitial[3,0:3] = [-size[0]/grid[0],+size[1]/grid[1],-size[2]/grid[2]]
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coordsInitial[4,0:3] = [-size[0]/grid[0],-size[1]/grid[1],+size[2]/grid[2]]
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coordsInitial[5,0:3] = [+size[0]/grid[0],-size[1]/grid[1],+size[2]/grid[2]]
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coordsInitial[6,0:3] = [+size[0]/grid[0],+size[1]/grid[1],+size[2]/grid[2]]
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coordsInitial[7,0:3] = [-size[0]/grid[0],+size[1]/grid[1],+size[2]/grid[2]]
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coordsInitial = coordsInitial/2.0
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delta = size/grid*.5
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coordsInitial = np.vstack((delta * np.array((-1,-1,-1)),
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delta * np.array((+1,-1,-1)),
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delta * np.array((+1,+1,-1)),
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delta * np.array((-1,+1,-1)),
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delta * np.array((-1,-1,+1)),
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delta * np.array((+1,-1,+1)),
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delta * np.array((+1,+1,+1)),
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delta * np.array((-1,+1,+1))))
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#--------------------------------------------------------------------------------------------------
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# compare deformed original and deformed positions to actual positions
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for k in range(grid[2]):
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for k in range(grid[0]):
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for j in range(grid[1]):
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for i in range(grid[0]):
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for i in range(grid[2]):
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sMismatch[k,j,i] = \
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))\
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+ 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]))
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+ 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]))
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return sMismatch
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@ -178,20 +175,20 @@ for name in filenames:
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table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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F = table.get(options.defgrad).reshape(grid[2],grid[1],grid[0],3,3)
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F = table.get(options.defgrad).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
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nodes = damask.grid_filters.node_coord(size,F)
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if options.shape:
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centers = damask.grid_filters.cell_coord(size,F)
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shapeMismatch = shapeMismatch( size,table.get(options.defgrad).reshape(grid[2],grid[1],grid[0],3,3),nodes,centers)
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shapeMismatch = shapeMismatch(size,F,nodes,centers)
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table.add('shapeMismatch(({}))'.format(options.defgrad),
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shapeMismatch.reshape(-1,1),
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shapeMismatch.reshape(-1,1,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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if options.volume:
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volumeMismatch = volumeMismatch(size,table.get(options.defgrad).reshape(grid[2],grid[1],grid[0],3,3),nodes)
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volumeMismatch = volumeMismatch(size,F,nodes)
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table.add('volMismatch(({}))'.format(options.defgrad),
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volumeMismatch.reshape(-1,1),
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volumeMismatch.reshape(-1,1,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.to_ASCII(sys.stdout if name is None else name)
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@ -49,9 +49,10 @@ for name in filenames:
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for label in options.labels:
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field = table.get(label)
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shape = (3,) if np.prod(field.shape)//np.prod(grid) == 3 else (3,3) # vector or tensor
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field = field.reshape(np.append(grid[::-1],shape))
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field = field.reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+shape)
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curl = damask.grid_filters.curl(size,field)
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table.add('curlFFT({})'.format(label),
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damask.grid_filters.curl(size[::-1],field).reshape(-1,np.prod(shape)),
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curl.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape),order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.to_ASCII(sys.stdout if name is None else name)
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@ -5,8 +5,6 @@ import sys
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from io import StringIO
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from optparse import OptionParser
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import numpy as np
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import damask
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@ -52,22 +50,22 @@ for name in filenames:
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table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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F = table.get(options.f).reshape(np.append(grid[::-1],(3,3)))
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F = table.get(options.f).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
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if options.nodal:
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table = damask.Table(damask.grid_filters.node_coord0(grid[::-1],size[::-1]).reshape(-1,3),
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table = damask.Table(damask.grid_filters.node_coord0(grid,size).reshape(-1,3,order='F'),
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{'pos':(3,)})
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table.add('avg({}).{}'.format(options.f,options.pos),
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damask.grid_filters.node_displacement_avg(size[::-1],F).reshape(-1,3),
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damask.grid_filters.node_displacement_avg(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.add('fluct({}).{}'.format(options.f,options.pos),
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damask.grid_filters.node_displacement_fluct(size[::-1],F).reshape(-1,3),
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damask.grid_filters.node_displacement_fluct(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.to_ASCII(sys.stdout if name is None else os.path.splitext(name)[0]+'_nodal.txt')
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else:
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table.add('avg({}).{}'.format(options.f,options.pos),
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damask.grid_filters.cell_displacement_avg(size[::-1],F).reshape(-1,3),
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damask.grid_filters.cell_displacement_avg(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.add('fluct({}).{}'.format(options.f,options.pos),
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damask.grid_filters.cell_displacement_fluct(size[::-1],F).reshape(-1,3),
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damask.grid_filters.cell_displacement_fluct(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.to_ASCII(sys.stdout if name is None else name)
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@ -49,9 +49,10 @@ for name in filenames:
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for label in options.labels:
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field = table.get(label)
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shape = (3,) if np.prod(field.shape)//np.prod(grid) == 3 else (3,3) # vector or tensor
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field = field.reshape(np.append(grid[::-1],shape))
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field = field.reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+shape)
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div = damask.grid_filters.divergence(size,field)
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table.add('divFFT({})'.format(label),
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damask.grid_filters.divergence(size[::-1],field).reshape(-1,np.prod(shape)//3),
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div.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)//3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.to_ASCII(sys.stdout if name is None else name)
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@ -49,9 +49,10 @@ for name in filenames:
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for label in options.labels:
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field = table.get(label)
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shape = (1,) if np.prod(field.shape)//np.prod(grid) == 1 else (3,) # scalar or vector
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field = field.reshape(np.append(grid[::-1],shape))
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field = field.reshape(tuple(grid)+(-1,),order='F')
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grad = damask.grid_filters.gradient(size,field)
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table.add('gradFFT({})'.format(label),
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damask.grid_filters.gradient(size[::-1],field).reshape(-1,np.prod(shape)*3),
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grad.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)*3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))
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table.to_ASCII(sys.stdout if name is None else name)
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@ -91,7 +91,7 @@ for name in filenames:
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table = damask.Table(averagedDown,table.shapes,table.comments)
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coords = damask.grid_filters.cell_coord0(packedGrid,size,shift/packedGrid*size+origin)
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table.set(options.pos, coords.reshape(-1,3))
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table.set(options.pos, coords.reshape(-1,3,order='F'))
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outname = os.path.join(os.path.dirname(name),prefix+os.path.basename(name))
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@ -59,13 +59,13 @@ for name in filenames:
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packing = np.array(options.packing,'i')
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outSize = grid*packing
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data = table.data.values.reshape(tuple(grid)+(-1,))
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blownUp = ndimage.interpolation.zoom(data,tuple(packing)+(1,),order=0,mode='nearest').reshape(outSize.prod(),-1)
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data = table.data.values.reshape(tuple(grid)+(-1,),order='F')
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blownUp = ndimage.interpolation.zoom(data,tuple(packing)+(1,),order=0,mode='nearest').reshape(outSize.prod(),-1,order='F')
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table = damask.Table(blownUp,table.shapes,table.comments)
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coords = damask.grid_filters.cell_coord0(outSize,size,origin)
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table.set(options.pos,coords.reshape(-1,3))
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table.set(options.pos,coords.reshape(-1,3,order='F'))
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table.set('elem',np.arange(1,outSize.prod()+1))
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outname = os.path.join(os.path.dirname(name),prefix+os.path.basename(name))
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@ -97,10 +97,10 @@ for name in filenames:
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for col,dim in zip(columns,dims):
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if options.unique:
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s = set(map(tuple,table.data[:,col:col+dim])) # generate set of (unique) values
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uniques = np.array(map(np.array,s)) # translate set to np.array
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uniques = np.array(list(map(np.array,s))) # translate set to np.array
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shuffler = dict(zip(s,np.random.permutation(len(s)))) # random permutation
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table.data[:,col:col+dim] = uniques[np.array(map(lambda x: shuffler[tuple(x)],
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table.data[:,col:col+dim]))] # fill table with mapped uniques
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table.data[:,col:col+dim] = uniques[np.array(list(map(lambda x: shuffler[tuple(x)],
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table.data[:,col:col+dim])))] # fill table with mapped uniques
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else:
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np.random.shuffle(table.data[:,col:col+dim]) # independently shuffle every row
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@ -24,22 +24,22 @@ def findClosestSeed(seeds, weights, point):
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def Laguerre_tessellation(grid, size, seeds, weights, origin = np.zeros(3), periodic = True, cpus = 2):
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if periodic:
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weights_p = np.tile(weights,27).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
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weights_p = np.tile(weights.squeeze(),27) # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
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seeds_p = np.vstack((seeds -np.array([size[0],0.,0.]),seeds, seeds +np.array([size[0],0.,0.])))
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seeds_p = np.vstack((seeds_p-np.array([0.,size[1],0.]),seeds_p,seeds_p+np.array([0.,size[1],0.])))
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seeds_p = np.vstack((seeds_p-np.array([0.,0.,size[2]]),seeds_p,seeds_p+np.array([0.,0.,size[2]])))
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coords = damask.grid_filters.cell_coord0(grid*3,size*3,-origin-size).reshape(-1,3,order='F')
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coords = damask.grid_filters.cell_coord0(grid*3,size*3,-origin-size).reshape(-1,3)
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else:
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weights_p = weights.flatten()
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weights_p = weights.squeeze()
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seeds_p = seeds
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coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
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coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3)
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if cpus > 1:
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pool = multiprocessing.Pool(processes = cpus)
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result = pool.map_async(partial(findClosestSeed,seeds_p,weights_p), [coord for coord in coords])
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pool.close()
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pool.join()
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closest_seed = np.array(result.get())
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closest_seed = np.array(result.get()).reshape(-1,3)
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else:
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closest_seed= np.array([findClosestSeed(seeds_p,weights_p,coord) for coord in coords])
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@ -52,7 +52,7 @@ def Laguerre_tessellation(grid, size, seeds, weights, origin = np.zeros(3), peri
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def Voronoi_tessellation(grid, size, seeds, origin = np.zeros(3), periodic = True):
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||||
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coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
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||||
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3)
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KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
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||||
devNull,closest_seed = KDTree.query(coords)
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||||
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||||
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|
@ -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:]),
|
||||
|
|
|
|||
|
|
@ -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:
|
||||
|
|
|
|||
|
|
@ -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)
|
||||
|
||||
|
|
|
|||
|
|
@ -68,12 +68,12 @@ class Result:
|
|||
self.con_physics = []
|
||||
for c in self.constituents:
|
||||
self.con_physics += f['/'.join([self.increments[0],'constituent',c])].keys()
|
||||
self.con_physics = list(set(self.con_physics)) # make unique
|
||||
self.con_physics = list(set(self.con_physics)) # make unique
|
||||
|
||||
self.mat_physics = []
|
||||
for m in self.materialpoints:
|
||||
self.mat_physics += f['/'.join([self.increments[0],'materialpoint',m])].keys()
|
||||
self.mat_physics = list(set(self.mat_physics)) # make unique
|
||||
self.mat_physics = list(set(self.mat_physics)) # make unique
|
||||
|
||||
self.selection = {'increments': self.increments,
|
||||
'constituents': self.constituents,'materialpoints': self.materialpoints,
|
||||
|
|
@ -86,13 +86,19 @@ class Result:
|
|||
def __repr__(self):
|
||||
"""Show selected data."""
|
||||
all_selected_increments = self.selection['increments']
|
||||
|
||||
self.pick('increments',all_selected_increments[0:1])
|
||||
first = self.list_data()
|
||||
|
||||
self.pick('increments',all_selected_increments[-1:])
|
||||
last = self.list_data()
|
||||
last = '' if len(all_selected_increments) < 2 else self.list_data()
|
||||
|
||||
self.pick('increments',all_selected_increments)
|
||||
in_between = ''.join(['\n{}\n ...\n'.format(inc) for inc in all_selected_increments[1:-2]])
|
||||
return util.srepr(first+ in_between + last)
|
||||
|
||||
in_between = '' if len(all_selected_increments) < 3 else \
|
||||
''.join(['\n{}\n ...\n'.format(inc) for inc in all_selected_increments[1:-2]])
|
||||
|
||||
return util.srepr(first + in_between + last)
|
||||
|
||||
|
||||
def _manage_selection(self,action,what,datasets):
|
||||
|
|
@ -105,7 +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 []
|
||||
|
||||
|
|
@ -197,7 +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 []
|
||||
|
||||
|
|
@ -213,7 +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 []
|
||||
|
||||
|
|
@ -229,7 +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 []
|
||||
|
||||
|
|
@ -256,10 +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
|
||||
|
||||
|
|
@ -320,7 +326,7 @@ class Result:
|
|||
|
||||
Parameters
|
||||
----------
|
||||
datasets : iterable or str or Boolean
|
||||
datasets : iterable or str or bool
|
||||
|
||||
Examples
|
||||
--------
|
||||
|
|
@ -454,7 +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'][()]
|
||||
|
|
@ -1009,7 +1015,7 @@ class Result:
|
|||
continue
|
||||
lock.acquire()
|
||||
with h5py.File(self.fname, 'a') as f:
|
||||
try:
|
||||
try: # ToDo: Replace if exists?
|
||||
dataset = f[result[0]].create_dataset(result[1]['label'],data=result[1]['data'])
|
||||
for l,v in result[1]['meta'].items():
|
||||
dataset.attrs[l]=v.encode()
|
||||
|
|
|
|||
|
|
@ -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:])
|
||||
|
|
@ -41,8 +60,8 @@ def curl(size,field):
|
|||
e[0, 2, 1] = e[2, 1, 0] = e[1, 0, 2] = -1.0
|
||||
|
||||
field_fourier = _np.fft.rfftn(field,axes=(0,1,2))
|
||||
curl_ = (_np.einsum('slm,ijkl,ijkm ->ijks', e,k_s,field_fourier)*2.0j*_np.pi if n == 3 else # vector, 3 -> 3
|
||||
_np.einsum('slm,ijkl,ijknm->ijksn',e,k_s,field_fourier)*2.0j*_np.pi) # tensor, 3x3 -> 3x3
|
||||
curl_ = (_np.einsum('slm,ijkl,ijkm ->ijks', e,k_s,field_fourier)*2.0j*_np.pi if n == 3 else # vector, 3 -> 3
|
||||
_np.einsum('slm,ijkl,ijknm->ijksn',e,k_s,field_fourier)*2.0j*_np.pi) # tensor, 3x3 -> 3x3
|
||||
|
||||
return _np.fft.irfftn(curl_,axes=(0,1,2),s=field.shape[:3])
|
||||
|
||||
|
|
@ -53,36 +72,40 @@ 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:])
|
||||
k_s = _ks(size,field.shape[:3],True)
|
||||
|
||||
field_fourier = _np.fft.rfftn(field,axes=(0,1,2))
|
||||
div_ = (_np.einsum('ijkl,ijkl ->ijk', k_s,field_fourier)*2.0j*_np.pi if n == 3 else # vector, 3 -> 1
|
||||
_np.einsum('ijkm,ijklm->ijkl',k_s,field_fourier)*2.0j*_np.pi) # tensor, 3x3 -> 3
|
||||
div_ = (_np.einsum('ijkl,ijkl ->ijk', k_s,field_fourier)*2.0j*_np.pi if n == 3 else # vector, 3 -> 1
|
||||
_np.einsum('ijkm,ijklm->ijkl',k_s,field_fourier)*2.0j*_np.pi) # tensor, 3x3 -> 3
|
||||
|
||||
return _np.fft.irfftn(div_,axes=(0,1,2),s=field.shape[:3])
|
||||
|
||||
|
||||
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:])
|
||||
k_s = _ks(size,field.shape[:3],True)
|
||||
|
||||
field_fourier = _np.fft.rfftn(field,axes=(0,1,2))
|
||||
grad_ = (_np.einsum('ijkl,ijkm->ijkm', field_fourier,k_s)*2.0j*_np.pi if n == 1 else # scalar, 1 -> 3
|
||||
_np.einsum('ijkl,ijkm->ijklm',field_fourier,k_s)*2.0j*_np.pi) # vector, 3 -> 3x3
|
||||
grad_ = (_np.einsum('ijkl,ijkm->ijkm', field_fourier,k_s)*2.0j*_np.pi if n == 1 else # scalar, 1 -> 3
|
||||
_np.einsum('ijkl,ijkm->ijklm',field_fourier,k_s)*2.0j*_np.pi) # vector, 3 -> 3x3
|
||||
|
||||
return _np.fft.irfftn(grad_,axes=(0,1,2),s=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('I_nput 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('I_nput 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)
|
||||
|
||||
|
|
|
|||
|
|
@ -24,6 +24,10 @@ def reference_dir(reference_dir_base):
|
|||
|
||||
class TestResult:
|
||||
|
||||
def test_self_report(self,default):
|
||||
print(default)
|
||||
|
||||
|
||||
def test_time_increments(self,default):
|
||||
shape = default.read_dataset(default.get_dataset_location('F'),0).shape
|
||||
default.set_by_time(0.0,20.0)
|
||||
|
|
|
|||
|
|
@ -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()))
|
||||
|
|
|
|||
|
|
@ -184,8 +184,6 @@ subroutine materialpoint_stressAndItsTangent(updateJaco,dt)
|
|||
e, & !< element number
|
||||
mySource, &
|
||||
myNgrains
|
||||
real(pReal), dimension(3,3) :: &
|
||||
subF
|
||||
real(pReal), dimension(discretization_nIP,discretization_nElem) :: &
|
||||
subFrac, &
|
||||
subStep
|
||||
|
|
@ -376,16 +374,15 @@ subroutine materialpoint_stressAndItsTangent(updateJaco,dt)
|
|||
|
||||
!--------------------------------------------------------------------------------------------------
|
||||
! deformation partitioning
|
||||
! based on materialpoint_subF0,.._subF,crystallite_partionedF0, and homogenization_state,
|
||||
! results in crystallite_partionedF
|
||||
!$OMP PARALLEL DO PRIVATE(myNgrains,subF)
|
||||
!$OMP PARALLEL DO PRIVATE(myNgrains)
|
||||
elementLooping2: do e = FEsolving_execElem(1),FEsolving_execElem(2)
|
||||
myNgrains = homogenization_Ngrains(material_homogenizationAt(e))
|
||||
IpLooping2: do i = FEsolving_execIP(1),FEsolving_execIP(2)
|
||||
if(requested(i,e) .and. .not. doneAndHappy(1,i,e)) then ! requested but not yet done
|
||||
subF = materialpoint_F0(1:3,1:3,i,e) &
|
||||
+ (materialpoint_F(1:3,1:3,i,e)-materialpoint_F0(1:3,1:3,i,e))*(subStep(i,e)+subFrac(i,e))
|
||||
call partitionDeformation(subF,i,e) ! partition deformation onto constituents
|
||||
call partitionDeformation(materialpoint_F0(1:3,1:3,i,e) &
|
||||
+ (materialpoint_F(1:3,1:3,i,e)-materialpoint_F0(1:3,1:3,i,e))&
|
||||
*(subStep(i,e)+subFrac(i,e)), &
|
||||
i,e)
|
||||
crystallite_dt(1:myNgrains,i,e) = dt*subStep(i,e) ! propagate materialpoint dt to grains
|
||||
crystallite_requested(1:myNgrains,i,e) = .true. ! request calculation for constituents
|
||||
else
|
||||
|
|
@ -397,23 +394,22 @@ subroutine materialpoint_stressAndItsTangent(updateJaco,dt)
|
|||
|
||||
!--------------------------------------------------------------------------------------------------
|
||||
! crystallite integration
|
||||
! based on crystallite_partionedF0,.._partionedF
|
||||
! incrementing by crystallite_dt
|
||||
|
||||
converged = crystallite_stress() !ToDo: MD not sure if that is the best logic
|
||||
|
||||
!--------------------------------------------------------------------------------------------------
|
||||
! state update
|
||||
!$OMP PARALLEL DO PRIVATE(subF)
|
||||
!$OMP PARALLEL DO
|
||||
elementLooping3: do e = FEsolving_execElem(1),FEsolving_execElem(2)
|
||||
IpLooping3: do i = FEsolving_execIP(1),FEsolving_execIP(2)
|
||||
if (requested(i,e) .and. .not. doneAndHappy(1,i,e)) then
|
||||
if (.not. converged(i,e)) then
|
||||
doneAndHappy(1:2,i,e) = [.true.,.false.]
|
||||
else
|
||||
subF = materialpoint_F0(1:3,1:3,i,e) &
|
||||
+ (materialpoint_F(1:3,1:3,i,e)-materialpoint_F0(1:3,1:3,i,e))*(subStep(i,e)+subFrac(i,e))
|
||||
doneAndHappy(1:2,i,e) = updateState(dt*subStep(i,e),subF,i,e)
|
||||
doneAndHappy(1:2,i,e) = updateState(dt*subStep(i,e), &
|
||||
materialpoint_F0(1:3,1:3,i,e) &
|
||||
+ (materialpoint_F(1:3,1:3,i,e)-materialpoint_F0(1:3,1:3,i,e)) &
|
||||
*(subStep(i,e)+subFrac(i,e)), &
|
||||
i,e)
|
||||
converged(i,e) = all(doneAndHappy(1:2,i,e)) ! converged if done and happy
|
||||
endif
|
||||
endif
|
||||
|
|
|
|||
|
|
@ -118,7 +118,7 @@ end subroutine quaternions_init
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> construct a quaternion from a 4-vector
|
||||
!> @brief construct a quaternion from a 4-vector
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) pure function init__(array)
|
||||
|
||||
|
|
@ -133,7 +133,7 @@ end function init__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> assign a quaternion
|
||||
!> @brief assign a quaternion
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
elemental pure subroutine assign_quat__(self,other)
|
||||
|
||||
|
|
@ -146,7 +146,7 @@ end subroutine assign_quat__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> assign a 4-vector
|
||||
!> @brief assign a 4-vector
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
pure subroutine assign_vec__(self,other)
|
||||
|
||||
|
|
@ -162,7 +162,7 @@ end subroutine assign_vec__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> add a quaternion
|
||||
!> @brief add a quaternion
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function add__(self,other)
|
||||
|
||||
|
|
@ -175,7 +175,7 @@ end function add__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> return (unary positive operator)
|
||||
!> @brief return (unary positive operator)
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function pos__(self)
|
||||
|
||||
|
|
@ -187,7 +187,7 @@ end function pos__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> subtract a quaternion
|
||||
!> @brief subtract a quaternion
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function sub__(self,other)
|
||||
|
||||
|
|
@ -200,7 +200,7 @@ end function sub__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> negate (unary negative operator)
|
||||
!> @brief negate (unary negative operator)
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function neg__(self)
|
||||
|
||||
|
|
@ -212,7 +212,7 @@ end function neg__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> multiply with a quaternion
|
||||
!> @brief multiply with a quaternion
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function mul_quat__(self,other)
|
||||
|
||||
|
|
@ -227,7 +227,7 @@ end function mul_quat__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> multiply with a scalar
|
||||
!> @brief multiply with a scalar
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function mul_scal__(self,scal)
|
||||
|
||||
|
|
@ -240,7 +240,7 @@ end function mul_scal__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> divide by a quaternion
|
||||
!> @brief divide by a quaternion
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function div_quat__(self,other)
|
||||
|
||||
|
|
@ -252,7 +252,7 @@ end function div_quat__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> divide by a scalar
|
||||
!> @brief divide by a scalar
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function div_scal__(self,scal)
|
||||
|
||||
|
|
@ -265,7 +265,7 @@ end function div_scal__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> test equality
|
||||
!> @brief test equality
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
logical elemental pure function eq__(self,other)
|
||||
|
||||
|
|
@ -278,7 +278,7 @@ end function eq__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> test inequality
|
||||
!> @brief test inequality
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
logical elemental pure function neq__(self,other)
|
||||
|
||||
|
|
@ -290,7 +290,7 @@ end function neq__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> raise to the power of a quaternion
|
||||
!> @brief raise to the power of a quaternion
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function pow_quat__(self,expon)
|
||||
|
||||
|
|
@ -303,7 +303,7 @@ end function pow_quat__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> raise to the power of a scalar
|
||||
!> @brief raise to the power of a scalar
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function pow_scal__(self,expon)
|
||||
|
||||
|
|
@ -316,7 +316,7 @@ end function pow_scal__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> take exponential
|
||||
!> @brief take exponential
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function exp__(a)
|
||||
|
||||
|
|
@ -336,7 +336,7 @@ end function exp__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> take logarithm
|
||||
!> @brief take logarithm
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function log__(a)
|
||||
|
||||
|
|
@ -356,7 +356,7 @@ end function log__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> return norm
|
||||
!> @brief return norm
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
real(pReal) elemental pure function abs__(self)
|
||||
|
||||
|
|
@ -368,7 +368,7 @@ end function abs__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> calculate dot product
|
||||
!> @brief calculate dot product
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
real(pReal) elemental pure function dot_product__(a,b)
|
||||
|
||||
|
|
@ -380,7 +380,7 @@ end function dot_product__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> take conjugate complex
|
||||
!> @brief take conjugate complex
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function conjg__(self)
|
||||
|
||||
|
|
@ -392,7 +392,7 @@ end function conjg__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> homomorph
|
||||
!> @brief homomorph
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function homomorphed(self)
|
||||
|
||||
|
|
@ -404,7 +404,7 @@ end function homomorphed
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> return as plain array
|
||||
!> @brief return as plain array
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
pure function asArray(self)
|
||||
|
||||
|
|
@ -417,7 +417,7 @@ end function asArray
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> real part (scalar)
|
||||
!> @brief real part (scalar)
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
pure function real__(self)
|
||||
|
||||
|
|
@ -430,7 +430,7 @@ end function real__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> imaginary part (3-vector)
|
||||
!> @brief imaginary part (3-vector)
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
pure function aimag__(self)
|
||||
|
||||
|
|
@ -443,7 +443,7 @@ end function aimag__
|
|||
|
||||
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
!> inverse
|
||||
!> @brief inverse
|
||||
!---------------------------------------------------------------------------------------------------
|
||||
type(quaternion) elemental pure function inverse(self)
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue