Merge branch 'development' into typehints_grid
This commit is contained in:
commit
9a8e7c8445
|
@ -45,7 +45,7 @@ variables:
|
||||||
MPI_INTEL: "MPI/Intel/2022.0.1/IntelMPI/2021.5.0"
|
MPI_INTEL: "MPI/Intel/2022.0.1/IntelMPI/2021.5.0"
|
||||||
# ++++++++++++ PETSc ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
# ++++++++++++ PETSc ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||||
PETSC_GNU: "Libraries/PETSc/3.16.1/GNU-10-OpenMPI-4.1.1"
|
PETSC_GNU: "Libraries/PETSc/3.16.1/GNU-10-OpenMPI-4.1.1"
|
||||||
PETSC_INTELLLVM: "Libraries/PETSc/3.16.2/oneAPI-2022.0.1-IntelMPI-2021.5.0"
|
PETSC_INTELLLVM: "Libraries/PETSc/3.16.3/oneAPI-2022.0.1-IntelMPI-2021.5.0"
|
||||||
PETSC_INTEL: "Libraries/PETSc/3.16.2/Intel-2022.0.1-IntelMPI-2021.5.0"
|
PETSC_INTEL: "Libraries/PETSc/3.16.2/Intel-2022.0.1-IntelMPI-2021.5.0"
|
||||||
# ++++++++++++ MSC Marc +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
# ++++++++++++ MSC Marc +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
|
||||||
MSC: "FEM/MSC/2021.3.1"
|
MSC: "FEM/MSC/2021.3.1"
|
||||||
|
|
|
@ -88,16 +88,12 @@ else()
|
||||||
message(FATAL_ERROR "Compiler type(CMAKE_Fortran_COMPILER_ID) not recognized")
|
message(FATAL_ERROR "Compiler type(CMAKE_Fortran_COMPILER_ID) not recognized")
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
file(STRINGS "$ENV{PETSC_DIR}/$ENV{PETSC_ARCH}/lib/petsc/conf/petscvariables" PETSC_EXTERNAL_LIB REGEX "PETSC_WITH_EXTERNAL_LIB = .*$?")
|
file(STRINGS "$ENV{PETSC_DIR}/$ENV{PETSC_ARCH}/lib/petsc/conf/petscvariables" PETSC_EXTERNAL_LIB REGEX "PETSC_EXTERNAL_LIB_BASIC = .*$?")
|
||||||
string(REGEX MATCHALL "-[lLW]([^\" ]+)" PETSC_EXTERNAL_LIB "${PETSC_EXTERNAL_LIB}")
|
string(REPLACE "PETSC_EXTERNAL_LIB_BASIC = " "" PETSC_EXTERNAL_LIB "${PETSC_EXTERNAL_LIB}")
|
||||||
list(REMOVE_DUPLICATES PETSC_EXTERNAL_LIB)
|
|
||||||
string(REPLACE ";" " " PETSC_EXTERNAL_LIB "${PETSC_EXTERNAL_LIB}")
|
|
||||||
message("PETSC_EXTERNAL_LIB:\n${PETSC_EXTERNAL_LIB}\n")
|
message("PETSC_EXTERNAL_LIB:\n${PETSC_EXTERNAL_LIB}\n")
|
||||||
|
|
||||||
file(STRINGS "$ENV{PETSC_DIR}/$ENV{PETSC_ARCH}/lib/petsc/conf/petscvariables" PETSC_INCLUDES REGEX "PETSC_FC_INCLUDES = .*$?")
|
file(STRINGS "$ENV{PETSC_DIR}/$ENV{PETSC_ARCH}/lib/petsc/conf/petscvariables" PETSC_INCLUDES REGEX "PETSC_FC_INCLUDES = .*$?")
|
||||||
string(REGEX MATCHALL "-I([^\" ]+)" PETSC_INCLUDES "${PETSC_INCLUDES}")
|
string(REPLACE "PETSC_FC_INCLUDES = " "" PETSC_INCLUDES "${PETSC_INCLUDES}")
|
||||||
list(REMOVE_DUPLICATES PETSC_INCLUDES)
|
|
||||||
string(REPLACE ";" " " PETSC_INCLUDES "${PETSC_INCLUDES}")
|
|
||||||
message("PETSC_INCLUDES:\n${PETSC_INCLUDES}\n")
|
message("PETSC_INCLUDES:\n${PETSC_INCLUDES}\n")
|
||||||
|
|
||||||
set(CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE} "${BUILDCMD_PRE} ${OPENMP_FLAGS} ${STANDARD_CHECK} ${OPTIMIZATION_FLAGS} ${COMPILE_FLAGS} ${PRECISION_FLAGS}")
|
set(CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE} "${BUILDCMD_PRE} ${OPENMP_FLAGS} ${STANDARD_CHECK} ${OPTIMIZATION_FLAGS} ${COMPILE_FLAGS} ${PRECISION_FLAGS}")
|
||||||
|
@ -109,7 +105,7 @@ if(CMAKE_BUILD_TYPE STREQUAL "DEBUG")
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
set(CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE} "${CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE}} ${PETSC_INCLUDES} ${BUILDCMD_POST}")
|
set(CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE} "${CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE}} ${PETSC_INCLUDES} ${BUILDCMD_POST}")
|
||||||
set(CMAKE_Fortran_LINK_EXECUTABLE "${CMAKE_Fortran_LINK_EXECUTABLE} <OBJECTS> -o <TARGET> <LINK_LIBRARIES> ${PETSC_EXTERNAL_LIB} -lz ${BUILDCMD_POST}")
|
set(CMAKE_Fortran_LINK_EXECUTABLE "${CMAKE_Fortran_LINK_EXECUTABLE} <OBJECTS> -o <TARGET> <LINK_LIBRARIES> -L${PETSC_LIBRARY_DIRS} -lpetsc ${PETSC_EXTERNAL_LIB} -lz ${BUILDCMD_POST}")
|
||||||
|
|
||||||
message("Fortran Compiler Flags:\n${CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE}}\n")
|
message("Fortran Compiler Flags:\n${CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE}}\n")
|
||||||
message("C Compiler Flags:\n${CMAKE_C_FLAGS_${CMAKE_BUILD_TYPE}}\n")
|
message("C Compiler Flags:\n${CMAKE_C_FLAGS_${CMAKE_BUILD_TYPE}}\n")
|
||||||
|
|
6
Makefile
6
Makefile
|
@ -10,14 +10,12 @@ all: grid mesh
|
||||||
.PHONY: grid
|
.PHONY: grid
|
||||||
grid:
|
grid:
|
||||||
@cmake -B build/grid -DDAMASK_SOLVER=grid -DCMAKE_INSTALL_PREFIX=${PWD} -DCMAKE_BUILD_TYPE=${BUILD_TYPE} -DBUILDCMD_POST=${BUILDCMD_POST} -DBUILDCMD_PRE=${BUILDCMD_PRE} -DOPTIMIZATION=${OPTIMIZATION} -DOPENMP=${OPENMP}
|
@cmake -B build/grid -DDAMASK_SOLVER=grid -DCMAKE_INSTALL_PREFIX=${PWD} -DCMAKE_BUILD_TYPE=${BUILD_TYPE} -DBUILDCMD_POST=${BUILDCMD_POST} -DBUILDCMD_PRE=${BUILDCMD_PRE} -DOPTIMIZATION=${OPTIMIZATION} -DOPENMP=${OPENMP}
|
||||||
@cmake --build build/grid --parallel
|
@cmake --build build/grid --parallel --target install
|
||||||
@cmake --install build/grid
|
|
||||||
|
|
||||||
.PHONY: mesh
|
.PHONY: mesh
|
||||||
mesh:
|
mesh:
|
||||||
@cmake -B build/mesh -DDAMASK_SOLVER=mesh -DCMAKE_INSTALL_PREFIX=${PWD} -DCMAKE_BUILD_TYPE=${BUILD_TYPE} -DBUILDCMD_POST=${BUILDCMD_POST} -DBUILDCMD_PRE=${BUILDCMD_PRE} -DOPTIMIZATION=${OPTIMIZATION} -DOPENMP=${OPENMP}
|
@cmake -B build/mesh -DDAMASK_SOLVER=mesh -DCMAKE_INSTALL_PREFIX=${PWD} -DCMAKE_BUILD_TYPE=${BUILD_TYPE} -DBUILDCMD_POST=${BUILDCMD_POST} -DBUILDCMD_PRE=${BUILDCMD_PRE} -DOPTIMIZATION=${OPTIMIZATION} -DOPENMP=${OPENMP}
|
||||||
@cmake --build build/mesh --parallel
|
@cmake --build build/mesh --parallel --target install
|
||||||
@cmake --install build/mesh
|
|
||||||
|
|
||||||
.PHONY: clean
|
.PHONY: clean
|
||||||
clean:
|
clean:
|
||||||
|
|
|
@ -67,9 +67,7 @@ os.system(f'xvfb-run -a {executable} -compile {menu_file}')
|
||||||
|
|
||||||
print('setting file access rights...')
|
print('setting file access rights...')
|
||||||
|
|
||||||
files = (glob.glob(str(marc_root/f'marc{marc_version}/tools/*_damask*')) +
|
for file in (glob.glob(str(marc_root/f'marc{marc_version}/tools/*_damask*')) +
|
||||||
glob.glob(str(marc_root/f'mentat{marc_version}/bin/kill[4-6]')) +
|
glob.glob(str(marc_root/f'mentat{marc_version}/bin/kill[4-6]')) +
|
||||||
glob.glob(str(marc_root/f'mentat{marc_version}/bin/submit[4-6]')))
|
glob.glob(str(marc_root/f'mentat{marc_version}/bin/submit[4-6]'))):
|
||||||
|
|
||||||
for file in files:
|
|
||||||
os.chmod(file , 0o755)
|
os.chmod(file , 0o755)
|
||||||
|
|
|
@ -1,71 +0,0 @@
|
||||||
#!/usr/bin/env python3
|
|
||||||
|
|
||||||
import os
|
|
||||||
import sys
|
|
||||||
from io import StringIO
|
|
||||||
from optparse import OptionParser
|
|
||||||
|
|
||||||
import damask
|
|
||||||
|
|
||||||
|
|
||||||
scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
|
||||||
scriptID = ' '.join([scriptName,damask.version])
|
|
||||||
|
|
||||||
|
|
||||||
# --------------------------------------------------------------------
|
|
||||||
# MAIN
|
|
||||||
# --------------------------------------------------------------------
|
|
||||||
|
|
||||||
parser = OptionParser(usage='%prog options [ASCIItable(s)]', description = """
|
|
||||||
Add displacments resulting from deformation gradient field.
|
|
||||||
Operates on periodic three-dimensional x,y,z-ordered data sets.
|
|
||||||
Outputs at cell centers or cell nodes (into separate file).
|
|
||||||
|
|
||||||
""", version = scriptID)
|
|
||||||
|
|
||||||
parser.add_option('-f',
|
|
||||||
'--defgrad',
|
|
||||||
dest = 'f',
|
|
||||||
metavar = 'string',
|
|
||||||
help = 'label of deformation gradient [%default]')
|
|
||||||
parser.add_option('-p',
|
|
||||||
'--pos', '--position',
|
|
||||||
dest = 'pos',
|
|
||||||
metavar = 'string',
|
|
||||||
help = 'label of coordinates [%default]')
|
|
||||||
parser.add_option('--nodal',
|
|
||||||
dest = 'nodal',
|
|
||||||
action = 'store_true',
|
|
||||||
help = 'output nodal (instead of cell-centered) displacements')
|
|
||||||
|
|
||||||
parser.set_defaults(f = 'f',
|
|
||||||
pos = 'pos',
|
|
||||||
)
|
|
||||||
|
|
||||||
(options,filenames) = parser.parse_args()
|
|
||||||
|
|
||||||
for name in filenames:
|
|
||||||
damask.util.report(scriptName,name)
|
|
||||||
|
|
||||||
table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
|
|
||||||
grid,size,origin = damask.grid_filters.cellsSizeOrigin_coordinates0_point(table.get(options.pos))
|
|
||||||
|
|
||||||
F = table.get(options.f).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
|
|
||||||
if options.nodal:
|
|
||||||
damask.Table(damask.grid_filters.coordinates0_node(grid,size).reshape(-1,3,order='F'),
|
|
||||||
{'pos':(3,)})\
|
|
||||||
.add('avg({}).{}'.format(options.f,options.pos),
|
|
||||||
damask.grid_filters.displacement_avg_node(size,F).reshape(-1,3,order='F'),
|
|
||||||
scriptID+' '+' '.join(sys.argv[1:]))\
|
|
||||||
.add('fluct({}).{}'.format(options.f,options.pos),
|
|
||||||
damask.grid_filters.displacement_fluct_node(size,F).reshape(-1,3,order='F'),
|
|
||||||
scriptID+' '+' '.join(sys.argv[1:]))\
|
|
||||||
.save((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.displacement_avg_point(size,F).reshape(-1,3,order='F'),
|
|
||||||
scriptID+' '+' '.join(sys.argv[1:]))\
|
|
||||||
.add('fluct({}).{}'.format(options.f,options.pos),
|
|
||||||
damask.grid_filters.displacement_fluct_point(size,F).reshape(-1,3,order='F'),
|
|
||||||
scriptID+' '+' '.join(sys.argv[1:]))\
|
|
||||||
.save((sys.stdout if name is None else name))
|
|
|
@ -1 +1 @@
|
||||||
v3.0.0-alpha5-355-gc29428a60
|
v3.0.0-alpha5-375-g76fe2d2b3
|
||||||
|
|
|
@ -8,6 +8,7 @@ with open(_Path(__file__).parent/_Path('VERSION')) as _f:
|
||||||
version = _re.sub(r'^v','',_f.readline().strip())
|
version = _re.sub(r'^v','',_f.readline().strip())
|
||||||
__version__ = version
|
__version__ = version
|
||||||
|
|
||||||
|
from . import _typehints # noqa
|
||||||
from . import util # noqa
|
from . import util # noqa
|
||||||
from . import seeds # noqa
|
from . import seeds # noqa
|
||||||
from . import tensor # noqa
|
from . import tensor # noqa
|
||||||
|
|
|
@ -3,13 +3,9 @@ import json
|
||||||
import functools
|
import functools
|
||||||
import colorsys
|
import colorsys
|
||||||
from pathlib import Path
|
from pathlib import Path
|
||||||
from typing import Sequence, Union, TextIO
|
from typing import Union, TextIO
|
||||||
|
|
||||||
import numpy as np
|
import numpy as np
|
||||||
try:
|
|
||||||
from numpy.typing import ArrayLike
|
|
||||||
except ImportError:
|
|
||||||
ArrayLike = Union[np.ndarray,Sequence[float]] # type: ignore
|
|
||||||
import scipy.interpolate as interp
|
import scipy.interpolate as interp
|
||||||
import matplotlib as mpl
|
import matplotlib as mpl
|
||||||
if os.name == 'posix' and 'DISPLAY' not in os.environ:
|
if os.name == 'posix' and 'DISPLAY' not in os.environ:
|
||||||
|
@ -18,6 +14,7 @@ import matplotlib.pyplot as plt
|
||||||
from matplotlib import cm
|
from matplotlib import cm
|
||||||
from PIL import Image
|
from PIL import Image
|
||||||
|
|
||||||
|
from ._typehints import FloatSequence, FileHandle
|
||||||
from . import util
|
from . import util
|
||||||
from . import Table
|
from . import Table
|
||||||
|
|
||||||
|
@ -82,8 +79,8 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
|
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def from_range(low: ArrayLike,
|
def from_range(low: FloatSequence,
|
||||||
high: ArrayLike,
|
high: FloatSequence,
|
||||||
name: str = 'DAMASK colormap',
|
name: str = 'DAMASK colormap',
|
||||||
N: int = 256,
|
N: int = 256,
|
||||||
model: str = 'rgb') -> 'Colormap':
|
model: str = 'rgb') -> 'Colormap':
|
||||||
|
@ -197,7 +194,7 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
|
|
||||||
|
|
||||||
def at(self,
|
def at(self,
|
||||||
fraction : Union[float,Sequence[float]]) -> np.ndarray:
|
fraction : Union[float,FloatSequence]) -> np.ndarray:
|
||||||
"""
|
"""
|
||||||
Interpolate color at fraction.
|
Interpolate color at fraction.
|
||||||
|
|
||||||
|
@ -229,7 +226,7 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
|
|
||||||
def shade(self,
|
def shade(self,
|
||||||
field: np.ndarray,
|
field: np.ndarray,
|
||||||
bounds: ArrayLike = None,
|
bounds: FloatSequence = None,
|
||||||
gap: float = None) -> Image:
|
gap: float = None) -> Image:
|
||||||
"""
|
"""
|
||||||
Generate PIL image of 2D field using colormap.
|
Generate PIL image of 2D field using colormap.
|
||||||
|
@ -296,7 +293,7 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
|
|
||||||
|
|
||||||
def _get_file_handle(self,
|
def _get_file_handle(self,
|
||||||
fname: Union[TextIO, str, Path, None],
|
fname: Union[FileHandle, None],
|
||||||
suffix: str = '') -> TextIO:
|
suffix: str = '') -> TextIO:
|
||||||
"""
|
"""
|
||||||
Provide file handle.
|
Provide file handle.
|
||||||
|
@ -323,7 +320,7 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
return fname
|
return fname
|
||||||
|
|
||||||
|
|
||||||
def save_paraview(self, fname: Union[TextIO, str, Path] = None):
|
def save_paraview(self, fname: FileHandle = None):
|
||||||
"""
|
"""
|
||||||
Save as JSON file for use in Paraview.
|
Save as JSON file for use in Paraview.
|
||||||
|
|
||||||
|
@ -350,7 +347,7 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
fhandle.write('\n')
|
fhandle.write('\n')
|
||||||
|
|
||||||
|
|
||||||
def save_ASCII(self, fname: Union[TextIO, str, Path] = None):
|
def save_ASCII(self, fname: FileHandle = None):
|
||||||
"""
|
"""
|
||||||
Save as ASCII file.
|
Save as ASCII file.
|
||||||
|
|
||||||
|
@ -365,7 +362,7 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
t.save(self._get_file_handle(fname,'.txt'))
|
t.save(self._get_file_handle(fname,'.txt'))
|
||||||
|
|
||||||
|
|
||||||
def save_GOM(self, fname: Union[TextIO, str, Path] = None):
|
def save_GOM(self, fname: FileHandle = None):
|
||||||
"""
|
"""
|
||||||
Save as ASCII file for use in GOM Aramis.
|
Save as ASCII file for use in GOM Aramis.
|
||||||
|
|
||||||
|
@ -385,7 +382,7 @@ class Colormap(mpl.colors.ListedColormap):
|
||||||
self._get_file_handle(fname,'.legend').write(GOM_str)
|
self._get_file_handle(fname,'.legend').write(GOM_str)
|
||||||
|
|
||||||
|
|
||||||
def save_gmsh(self, fname: Union[TextIO, str, Path] = None):
|
def save_gmsh(self, fname: FileHandle = None):
|
||||||
"""
|
"""
|
||||||
Save as ASCII file for use in gmsh.
|
Save as ASCII file for use in gmsh.
|
||||||
|
|
||||||
|
|
|
@ -114,12 +114,13 @@ class Crystal():
|
||||||
|
|
||||||
def __repr__(self):
|
def __repr__(self):
|
||||||
"""Represent."""
|
"""Represent."""
|
||||||
return '\n'.join([f'Crystal family {self.family}']
|
family = f'Crystal family: {self.family}'
|
||||||
+ ([] if self.lattice is None else [f'Bravais lattice {self.lattice}']+
|
return family if self.lattice is None else \
|
||||||
list(map(lambda x:f'{x[0]}: {x[1]:.5g}',
|
'\n'.join([family,
|
||||||
zip(['a','b','c','α','β','γ',],
|
f'Bravais lattice: {self.lattice}',
|
||||||
self.parameters))))
|
'a={:.5g}m, b={:.5g}m, c={:.5g}m'.format(*self.parameters[:3]),
|
||||||
)
|
'α={:.5g}°, β={:.5g}°, γ={:.5g}°'.format(*np.degrees(self.parameters[3:]))])
|
||||||
|
|
||||||
|
|
||||||
def __eq__(self,other):
|
def __eq__(self,other):
|
||||||
"""
|
"""
|
||||||
|
@ -378,7 +379,7 @@ class Crystal():
|
||||||
"""
|
"""
|
||||||
_kinematics = {
|
_kinematics = {
|
||||||
'cF': {
|
'cF': {
|
||||||
'slip' :[np.array([
|
'slip': [np.array([
|
||||||
[+0,+1,-1, +1,+1,+1],
|
[+0,+1,-1, +1,+1,+1],
|
||||||
[-1,+0,+1, +1,+1,+1],
|
[-1,+0,+1, +1,+1,+1],
|
||||||
[+1,-1,+0, +1,+1,+1],
|
[+1,-1,+0, +1,+1,+1],
|
||||||
|
@ -398,7 +399,7 @@ class Crystal():
|
||||||
[+1,+0,-1, +1,+0,+1],
|
[+1,+0,-1, +1,+0,+1],
|
||||||
[+0,+1,+1, +0,+1,-1],
|
[+0,+1,+1, +0,+1,-1],
|
||||||
[+0,+1,-1, +0,+1,+1]])],
|
[+0,+1,-1, +0,+1,+1]])],
|
||||||
'twin' :[np.array([
|
'twin': [np.array([
|
||||||
[-2, 1, 1, 1, 1, 1],
|
[-2, 1, 1, 1, 1, 1],
|
||||||
[ 1,-2, 1, 1, 1, 1],
|
[ 1,-2, 1, 1, 1, 1],
|
||||||
[ 1, 1,-2, 1, 1, 1],
|
[ 1, 1,-2, 1, 1, 1],
|
||||||
|
@ -413,7 +414,7 @@ class Crystal():
|
||||||
[-1, 1, 2, -1, 1,-1]])]
|
[-1, 1, 2, -1, 1,-1]])]
|
||||||
},
|
},
|
||||||
'cI': {
|
'cI': {
|
||||||
'slip' :[np.array([
|
'slip': [np.array([
|
||||||
[+1,-1,+1, +0,+1,+1],
|
[+1,-1,+1, +0,+1,+1],
|
||||||
[-1,-1,+1, +0,+1,+1],
|
[-1,-1,+1, +0,+1,+1],
|
||||||
[+1,+1,+1, +0,-1,+1],
|
[+1,+1,+1, +0,-1,+1],
|
||||||
|
@ -464,7 +465,7 @@ class Crystal():
|
||||||
[+1,+1,+1, -3,+2,+1],
|
[+1,+1,+1, -3,+2,+1],
|
||||||
[+1,+1,-1, +3,-2,+1],
|
[+1,+1,-1, +3,-2,+1],
|
||||||
[+1,-1,+1, +3,+2,-1]])],
|
[+1,-1,+1, +3,+2,-1]])],
|
||||||
'twin' :[np.array([
|
'twin': [np.array([
|
||||||
[-1, 1, 1, 2, 1, 1],
|
[-1, 1, 1, 2, 1, 1],
|
||||||
[ 1, 1, 1, -2, 1, 1],
|
[ 1, 1, 1, -2, 1, 1],
|
||||||
[ 1, 1,-1, 2,-1, 1],
|
[ 1, 1,-1, 2,-1, 1],
|
||||||
|
@ -479,7 +480,7 @@ class Crystal():
|
||||||
[ 1, 1, 1, 1, 1,-2]])]
|
[ 1, 1, 1, 1, 1,-2]])]
|
||||||
},
|
},
|
||||||
'hP': {
|
'hP': {
|
||||||
'slip' :[np.array([
|
'slip': [np.array([
|
||||||
[+2,-1,-1,+0, +0,+0,+0,+1],
|
[+2,-1,-1,+0, +0,+0,+0,+1],
|
||||||
[-1,+2,-1,+0, +0,+0,+0,+1],
|
[-1,+2,-1,+0, +0,+0,+0,+1],
|
||||||
[-1,-1,+2,+0, +0,+0,+0,+1]]),
|
[-1,-1,+2,+0, +0,+0,+0,+1]]),
|
||||||
|
@ -514,7 +515,7 @@ class Crystal():
|
||||||
[+1,+1,-2,+3, -1,-1,+2,+2],
|
[+1,+1,-2,+3, -1,-1,+2,+2],
|
||||||
[-1,+2,-1,+3, +1,-2,+1,+2],
|
[-1,+2,-1,+3, +1,-2,+1,+2],
|
||||||
[-2,+1,+1,+3, +2,-1,-1,+2]])],
|
[-2,+1,+1,+3, +2,-1,-1,+2]])],
|
||||||
'twin' :[np.array([
|
'twin': [np.array([
|
||||||
[-1, 0, 1, 1, 1, 0,-1, 2], # shear = (3-(c/a)^2)/(sqrt(3) c/a) <-10.1>{10.2}
|
[-1, 0, 1, 1, 1, 0,-1, 2], # shear = (3-(c/a)^2)/(sqrt(3) c/a) <-10.1>{10.2}
|
||||||
[ 0,-1, 1, 1, 0, 1,-1, 2],
|
[ 0,-1, 1, 1, 0, 1,-1, 2],
|
||||||
[ 1,-1, 0, 1, -1, 1, 0, 2],
|
[ 1,-1, 0, 1, -1, 1, 0, 2],
|
||||||
|
@ -542,7 +543,74 @@ class Crystal():
|
||||||
[-1,-1, 2,-3, -1,-1, 2, 2],
|
[-1,-1, 2,-3, -1,-1, 2, 2],
|
||||||
[ 1,-2, 1,-3, 1,-2, 1, 2],
|
[ 1,-2, 1,-3, 1,-2, 1, 2],
|
||||||
[ 2,-1,-1,-3, 2,-1,-1, 2]])]
|
[ 2,-1,-1,-3, 2,-1,-1, 2]])]
|
||||||
},
|
},
|
||||||
|
'tI': {
|
||||||
|
'slip': [np.array([
|
||||||
|
[+0,+0,+1, +1,+0,+0],
|
||||||
|
[+0,+0,+1, +0,+1,+0]]),
|
||||||
|
np.array([
|
||||||
|
[+0,+0,+1, +1,+1,+0],
|
||||||
|
[+0,+0,+1, -1,+1,+0]]),
|
||||||
|
np.array([
|
||||||
|
[+0,+1,+0, +1,+0,+0],
|
||||||
|
[+1,+0,+0, +0,+1,+0]]),
|
||||||
|
np.array([
|
||||||
|
[+1,-1,+1, +1,+1,+0],
|
||||||
|
[+1,-1,-1, +1,+1,+0],
|
||||||
|
[-1,-1,-1, -1,+1,+0],
|
||||||
|
[-1,-1,+1, -1,+1,+0]]),
|
||||||
|
np.array([
|
||||||
|
[+1,-1,+0, +1,+1,+0],
|
||||||
|
[+1,+1,+0, +1,-1,+0]]),
|
||||||
|
np.array([
|
||||||
|
[+0,+1,+1, +1,+0,+0],
|
||||||
|
[+0,-1,+1, +1,+0,+0],
|
||||||
|
[-1,+0,+1, +0,+1,+0],
|
||||||
|
[+1,+0,+1, +0,+1,+0]]),
|
||||||
|
np.array([
|
||||||
|
[+0,+1,+0, +0,+0,+1],
|
||||||
|
[+1,+0,+0, +0,+0,+1]]),
|
||||||
|
np.array([
|
||||||
|
[+1,+1,+0, +0,+0,+1],
|
||||||
|
[-1,+1,+0, +0,+0,+1]]),
|
||||||
|
np.array([
|
||||||
|
[+0,+1,-1, +0,+1,+1],
|
||||||
|
[+0,-1,-1, +0,-1,+1],
|
||||||
|
[-1,+0,-1, -1,+0,+1],
|
||||||
|
[+1,+0,-1, +1,+0,+1]]),
|
||||||
|
np.array([
|
||||||
|
[+1,-1,+1, +0,+1,+1],
|
||||||
|
[+1,+1,-1, +0,+1,+1],
|
||||||
|
[+1,+1,+1, +0,+1,-1],
|
||||||
|
[-1,+1,+1, +0,+1,-1],
|
||||||
|
[+1,-1,-1, +1,+0,+1],
|
||||||
|
[-1,-1,+1, +1,+0,+1],
|
||||||
|
[+1,+1,+1, +1,+0,-1],
|
||||||
|
[+1,-1,+1, +1,+0,-1]]),
|
||||||
|
np.array([
|
||||||
|
[+1,+0,+0, +0,+1,+1],
|
||||||
|
[+1,+0,+0, +0,+1,-1],
|
||||||
|
[+0,+1,+0, +1,+0,+1],
|
||||||
|
[+0,+1,+0, +1,+0,-1]]),
|
||||||
|
np.array([
|
||||||
|
[+0,+1,-1, +2,+1,+1],
|
||||||
|
[+0,-1,-1, +2,-1,+1],
|
||||||
|
[+1,+0,-1, +1,+2,+1],
|
||||||
|
[-1,+0,-1, -1,+2,+1],
|
||||||
|
[+0,+1,-1, -2,+1,+1],
|
||||||
|
[+0,-1,-1, -2,-1,+1],
|
||||||
|
[-1,+0,-1, -1,-2,+1],
|
||||||
|
[+1,+0,-1, +1,-2,+1]]),
|
||||||
|
np.array([
|
||||||
|
[-1,+1,+1, +2,+1,+1],
|
||||||
|
[-1,-1,+1, +2,-1,+1],
|
||||||
|
[+1,-1,+1, +1,+2,+1],
|
||||||
|
[-1,-1,+1, -1,+2,+1],
|
||||||
|
[+1,+1,+1, -2,+1,+1],
|
||||||
|
[+1,-1,+1, -2,-1,+1],
|
||||||
|
[-1,+1,+1, -1,-2,+1],
|
||||||
|
[+1,+1,+1, +1,-2,+1]])]
|
||||||
|
}
|
||||||
}
|
}
|
||||||
master = _kinematics[self.lattice][mode]
|
master = _kinematics[self.lattice][mode]
|
||||||
if self.lattice == 'hP':
|
if self.lattice == 'hP':
|
||||||
|
|
|
@ -514,6 +514,17 @@ class Orientation(Rotation,Crystal):
|
||||||
[ 0.07359167 -0.36505797 0.92807163]]
|
[ 0.07359167 -0.36505797 0.92807163]]
|
||||||
Bunge Eulers / deg: (11.40, 21.86, 0.60)
|
Bunge Eulers / deg: (11.40, 21.86, 0.60)
|
||||||
|
|
||||||
|
Plot a sample from the Mackenzie distribution.
|
||||||
|
|
||||||
|
>>> import matplotlib.pyplot as plt
|
||||||
|
>>> import damask
|
||||||
|
>>> N = 10000
|
||||||
|
>>> a = damask.Orientation.from_random(shape=N,family='cubic')
|
||||||
|
>>> b = damask.Orientation.from_random(shape=N,family='cubic')
|
||||||
|
>>> d = a.disorientation(b).as_axis_angle(degrees=True,pair=True)[1]
|
||||||
|
>>> plt.hist(d,25)
|
||||||
|
>>> plt.show()
|
||||||
|
|
||||||
"""
|
"""
|
||||||
if self.family != other.family:
|
if self.family != other.family:
|
||||||
raise NotImplementedError('disorientation between different crystal families')
|
raise NotImplementedError('disorientation between different crystal families')
|
||||||
|
|
|
@ -0,0 +1,11 @@
|
||||||
|
"""Functionality for typehints."""
|
||||||
|
|
||||||
|
from typing import Sequence, Union, TextIO
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
import numpy as np
|
||||||
|
|
||||||
|
|
||||||
|
FloatSequence = Union[np.ndarray,Sequence[float]]
|
||||||
|
IntSequence = Union[np.ndarray,Sequence[int]]
|
||||||
|
FileHandle = Union[TextIO, str, Path]
|
|
@ -12,21 +12,23 @@ the following operations are required for tensorial data:
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
|
||||||
from typing import Sequence, Tuple, Union
|
from typing import Tuple as _Tuple
|
||||||
|
|
||||||
from scipy import spatial as _spatial
|
from scipy import spatial as _spatial
|
||||||
import numpy as _np
|
import numpy as _np
|
||||||
|
|
||||||
|
from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence
|
||||||
|
|
||||||
def _ks(size: _np.ndarray, cells: Union[_np.ndarray,Sequence[int]], first_order: bool = False) -> _np.ndarray:
|
|
||||||
|
def _ks(size: _FloatSequence, cells: _IntSequence, first_order: bool = False) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Get wave numbers operator.
|
Get wave numbers operator.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
cells : numpy.ndarray of shape (3)
|
cells : sequence of int, len (3)
|
||||||
Number of cells.
|
Number of cells.
|
||||||
first_order : bool, optional
|
first_order : bool, optional
|
||||||
Correction for first order derivatives, defaults to False.
|
Correction for first order derivatives, defaults to False.
|
||||||
|
@ -45,20 +47,20 @@ def _ks(size: _np.ndarray, cells: Union[_np.ndarray,Sequence[int]], first_order:
|
||||||
return _np.stack(_np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij'), axis=-1)
|
return _np.stack(_np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij'), axis=-1)
|
||||||
|
|
||||||
|
|
||||||
def curl(size: _np.ndarray, f: _np.ndarray) -> _np.ndarray:
|
def curl(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
||||||
u"""
|
u"""
|
||||||
Calculate curl of a vector or tensor field in Fourier space.
|
Calculate curl of a vector or tensor field in Fourier space.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
f : numpy.ndarray of shape (:,:,:,3) or (:,:,:,3,3)
|
f : numpy.ndarray, shape (:,:,:,3) or (:,:,:,3,3)
|
||||||
Periodic field of which the curl is calculated.
|
Periodic field of which the curl is calculated.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
∇ × f : numpy.ndarray
|
∇ × f : numpy.ndarray, shape (:,:,:,3) or (:,:,:,3,3)
|
||||||
Curl of f.
|
Curl of f.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -76,20 +78,20 @@ def curl(size: _np.ndarray, f: _np.ndarray) -> _np.ndarray:
|
||||||
return _np.fft.irfftn(curl_,axes=(0,1,2),s=f.shape[:3])
|
return _np.fft.irfftn(curl_,axes=(0,1,2),s=f.shape[:3])
|
||||||
|
|
||||||
|
|
||||||
def divergence(size: _np.ndarray, f: _np.ndarray) -> _np.ndarray:
|
def divergence(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
||||||
u"""
|
u"""
|
||||||
Calculate divergence of a vector or tensor field in Fourier space.
|
Calculate divergence of a vector or tensor field in Fourier space.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
f : numpy.ndarray of shape (:,:,:,3) or (:,:,:,3,3)
|
f : numpy.ndarray, shape (:,:,:,3) or (:,:,:,3,3)
|
||||||
Periodic field of which the divergence is calculated.
|
Periodic field of which the divergence is calculated.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
∇ · f : numpy.ndarray
|
∇ · f : numpy.ndarray, shape (:,:,:,1) or (:,:,:,3)
|
||||||
Divergence of f.
|
Divergence of f.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -103,20 +105,20 @@ def divergence(size: _np.ndarray, f: _np.ndarray) -> _np.ndarray:
|
||||||
return _np.fft.irfftn(div_,axes=(0,1,2),s=f.shape[:3])
|
return _np.fft.irfftn(div_,axes=(0,1,2),s=f.shape[:3])
|
||||||
|
|
||||||
|
|
||||||
def gradient(size: _np.ndarray, f: _np.ndarray) -> _np.ndarray:
|
def gradient(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
||||||
u"""
|
u"""
|
||||||
Calculate gradient of a scalar or vector fieldin Fourier space.
|
Calculate gradient of a scalar or vector field in Fourier space.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
f : numpy.ndarray of shape (:,:,:,1) or (:,:,:,3)
|
f : numpy.ndarray, shape (:,:,:,1) or (:,:,:,3)
|
||||||
Periodic field of which the gradient is calculated.
|
Periodic field of which the gradient is calculated.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
∇ f : numpy.ndarray
|
∇ f : numpy.ndarray, shape (:,:,:,3) or (:,:,:,3,3)
|
||||||
Divergence of f.
|
Divergence of f.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -130,29 +132,30 @@ def gradient(size: _np.ndarray, f: _np.ndarray) -> _np.ndarray:
|
||||||
return _np.fft.irfftn(grad_,axes=(0,1,2),s=f.shape[:3])
|
return _np.fft.irfftn(grad_,axes=(0,1,2),s=f.shape[:3])
|
||||||
|
|
||||||
|
|
||||||
def coordinates0_point(cells: Union[_np.ndarray, Sequence[int]],
|
def coordinates0_point(cells: _IntSequence,
|
||||||
size: Union[_np.ndarray, Sequence[float]],
|
size: _FloatSequence,
|
||||||
origin: Union[_np.ndarray, Sequence[float]] = _np.zeros(3)) -> _np.ndarray:
|
origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Cell center positions (undeformed).
|
Cell center positions (undeformed).
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
cells : numpy.ndarray of shape (3)
|
cells : sequence of int, len (3)
|
||||||
Number of cells.
|
Number of cells.
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
origin : numpy.ndarray, optional
|
origin : sequence of float, len(3), optional
|
||||||
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
x_p_0 : numpy.ndarray
|
x_p_0 : numpy.ndarray, shape (:,:,:,3)
|
||||||
Undeformed cell center coordinates.
|
Undeformed cell center coordinates.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
start = _np.array(origin) + size/_np.array(cells)*.5
|
size_ = _np.array(size,float)
|
||||||
end = _np.array(origin) + _np.array(size) - size/_np.array(cells)*.5
|
start = origin + size_/_np.array(cells,int)*.5
|
||||||
|
end = origin + size_ - size_/_np.array(cells,int)*.5
|
||||||
|
|
||||||
return _np.stack(_np.meshgrid(_np.linspace(start[0],end[0],cells[0]),
|
return _np.stack(_np.meshgrid(_np.linspace(start[0],end[0],cells[0]),
|
||||||
_np.linspace(start[1],end[1],cells[1]),
|
_np.linspace(start[1],end[1],cells[1]),
|
||||||
|
@ -160,24 +163,24 @@ def coordinates0_point(cells: Union[_np.ndarray, Sequence[int]],
|
||||||
axis = -1)
|
axis = -1)
|
||||||
|
|
||||||
|
|
||||||
def displacement_fluct_point(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
def displacement_fluct_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Cell center displacement field from fluctuation part of the deformation gradient field.
|
Cell center displacement field from fluctuation part of the deformation gradient field.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
u_p_fluct : numpy.ndarray
|
u_p_fluct : numpy.ndarray, shape (:,:,:,3)
|
||||||
Fluctuating part of the cell center displacements.
|
Fluctuating part of the cell center displacements.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
integrator = 0.5j*size/_np.pi
|
integrator = 0.5j*_np.array(size,float)/_np.pi
|
||||||
|
|
||||||
k_s = _ks(size,F.shape[:3],False)
|
k_s = _ks(size,F.shape[:3],False)
|
||||||
k_s_squared = _np.einsum('...l,...l',k_s,k_s)
|
k_s_squared = _np.einsum('...l,...l',k_s,k_s)
|
||||||
|
@ -192,20 +195,20 @@ def displacement_fluct_point(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
||||||
return _np.fft.irfftn(displacement,axes=(0,1,2),s=F.shape[:3])
|
return _np.fft.irfftn(displacement,axes=(0,1,2),s=F.shape[:3])
|
||||||
|
|
||||||
|
|
||||||
def displacement_avg_point(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
def displacement_avg_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Cell center displacement field from average part of the deformation gradient field.
|
Cell center displacement field from average part of the deformation gradient field.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
u_p_avg : numpy.ndarray
|
u_p_avg : numpy.ndarray, shape (:,:,:,3)
|
||||||
Average part of the cell center displacements.
|
Average part of the cell center displacements.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -213,42 +216,42 @@ def displacement_avg_point(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
||||||
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_point(F.shape[:3],size))
|
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_point(F.shape[:3],size))
|
||||||
|
|
||||||
|
|
||||||
def displacement_point(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
def displacement_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Cell center displacement field from deformation gradient field.
|
Cell center displacement field from deformation gradient field.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
u_p : numpy.ndarray
|
u_p : numpy.ndarray, shape (:,:,:,3)
|
||||||
Cell center displacements.
|
Cell center displacements.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
return displacement_avg_point(size,F) + displacement_fluct_point(size,F)
|
return displacement_avg_point(size,F) + displacement_fluct_point(size,F)
|
||||||
|
|
||||||
|
|
||||||
def coordinates_point(size: _np.ndarray, F: _np.ndarray, origin: _np.ndarray = _np.zeros(3)) -> _np.ndarray:
|
def coordinates_point(size: _FloatSequence, F: _np.ndarray, origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Cell center positions.
|
Cell center positions.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
origin : numpy.ndarray of shape (3), optional
|
origin : sequence of float, len(3), optional
|
||||||
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
x_p : numpy.ndarray
|
x_p : numpy.ndarray, shape (:,:,:,3)
|
||||||
Cell center coordinates.
|
Cell center coordinates.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -256,14 +259,14 @@ def coordinates_point(size: _np.ndarray, F: _np.ndarray, origin: _np.ndarray = _
|
||||||
|
|
||||||
|
|
||||||
def cellsSizeOrigin_coordinates0_point(coordinates0: _np.ndarray,
|
def cellsSizeOrigin_coordinates0_point(coordinates0: _np.ndarray,
|
||||||
ordered: bool = True) -> Tuple[_np.ndarray,_np.ndarray,_np.ndarray]:
|
ordered: bool = True) -> _Tuple[_np.ndarray,_np.ndarray,_np.ndarray]:
|
||||||
"""
|
"""
|
||||||
Return grid 'DNA', i.e. cells, size, and origin from 1D array of point positions.
|
Return grid 'DNA', i.e. cells, size, and origin from 1D array of point positions.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
coordinates0 : numpy.ndarray of shape (:,3)
|
coordinates0 : numpy.ndarray, shape (:,3)
|
||||||
Undeformed cell coordinates.
|
Undeformed cell center coordinates.
|
||||||
ordered : bool, optional
|
ordered : bool, optional
|
||||||
Expect coordinates0 data to be ordered (x fast, z slow).
|
Expect coordinates0 data to be ordered (x fast, z slow).
|
||||||
Defaults to True.
|
Defaults to True.
|
||||||
|
@ -277,7 +280,7 @@ def cellsSizeOrigin_coordinates0_point(coordinates0: _np.ndarray,
|
||||||
coords = [_np.unique(coordinates0[:,i]) for i in range(3)]
|
coords = [_np.unique(coordinates0[:,i]) for i in range(3)]
|
||||||
mincorner = _np.array(list(map(min,coords)))
|
mincorner = _np.array(list(map(min,coords)))
|
||||||
maxcorner = _np.array(list(map(max,coords)))
|
maxcorner = _np.array(list(map(max,coords)))
|
||||||
cells = _np.array(list(map(len,coords)),'i')
|
cells = _np.array(list(map(len,coords)),int)
|
||||||
size = cells/_np.maximum(cells-1,1) * (maxcorner-mincorner)
|
size = cells/_np.maximum(cells-1,1) * (maxcorner-mincorner)
|
||||||
delta = size/cells
|
delta = size/cells
|
||||||
origin = mincorner - delta*.5
|
origin = mincorner - delta*.5
|
||||||
|
@ -305,24 +308,24 @@ def cellsSizeOrigin_coordinates0_point(coordinates0: _np.ndarray,
|
||||||
return (cells,size,origin)
|
return (cells,size,origin)
|
||||||
|
|
||||||
|
|
||||||
def coordinates0_node(cells: Union[_np.ndarray, Sequence[int]],
|
def coordinates0_node(cells: _IntSequence,
|
||||||
size: Union[_np.ndarray, Sequence[int]],
|
size: _FloatSequence,
|
||||||
origin: Union[_np.ndarray, Sequence[int]] = _np.zeros(3)) -> _np.ndarray:
|
origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Nodal positions (undeformed).
|
Nodal positions (undeformed).
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
cells : numpy.ndarray of shape (3)
|
cells : sequence of int, len (3)
|
||||||
Number of cells.
|
Number of cells.
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
origin : numpy.ndarray of shape (3), optional
|
origin : sequence of float, len(3), optional
|
||||||
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
x_n_0 : numpy.ndarray
|
x_n_0 : numpy.ndarray, shape (:,:,:,3)
|
||||||
Undeformed nodal coordinates.
|
Undeformed nodal coordinates.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -332,40 +335,40 @@ def coordinates0_node(cells: Union[_np.ndarray, Sequence[int]],
|
||||||
axis = -1)
|
axis = -1)
|
||||||
|
|
||||||
|
|
||||||
def displacement_fluct_node(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
def displacement_fluct_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Nodal displacement field from fluctuation part of the deformation gradient field.
|
Nodal displacement field from fluctuation part of the deformation gradient field.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
u_n_fluct : numpy.ndarray
|
u_n_fluct : numpy.ndarray, shape (:,:,:,3)
|
||||||
Fluctuating part of the nodal displacements.
|
Fluctuating part of the nodal displacements.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
return point_to_node(displacement_fluct_point(size,F))
|
return point_to_node(displacement_fluct_point(size,F))
|
||||||
|
|
||||||
|
|
||||||
def displacement_avg_node(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
def displacement_avg_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Nodal displacement field from average part of the deformation gradient field.
|
Nodal displacement field from average part of the deformation gradient field.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
u_n_avg : numpy.ndarray
|
u_n_avg : numpy.ndarray, shape (:,:,:,3)
|
||||||
Average part of the nodal displacements.
|
Average part of the nodal displacements.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -373,42 +376,42 @@ def displacement_avg_node(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
||||||
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_node(F.shape[:3],size))
|
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_node(F.shape[:3],size))
|
||||||
|
|
||||||
|
|
||||||
def displacement_node(size: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
def displacement_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Nodal displacement field from deformation gradient field.
|
Nodal displacement field from deformation gradient field.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
u_p : numpy.ndarray
|
u_p : numpy.ndarray, shape (:,:,:,3)
|
||||||
Nodal displacements.
|
Nodal displacements.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
return displacement_avg_node(size,F) + displacement_fluct_node(size,F)
|
return displacement_avg_node(size,F) + displacement_fluct_node(size,F)
|
||||||
|
|
||||||
|
|
||||||
def coordinates_node(size: _np.ndarray, F: _np.ndarray, origin: _np.ndarray = _np.zeros(3)) -> _np.ndarray:
|
def coordinates_node(size: _FloatSequence, F: _np.ndarray, origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Nodal positions.
|
Nodal positions.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the periodic field.
|
Physical size of the periodic field.
|
||||||
F : numpy.ndarray
|
F : numpy.ndarray, shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
origin : numpy.ndarray of shape (3), optional
|
origin : sequence of float, len(3), optional
|
||||||
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
x_n : numpy.ndarray
|
x_n : numpy.ndarray, shape (:,:,:,3)
|
||||||
Nodal coordinates.
|
Nodal coordinates.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -416,13 +419,13 @@ def coordinates_node(size: _np.ndarray, F: _np.ndarray, origin: _np.ndarray = _n
|
||||||
|
|
||||||
|
|
||||||
def cellsSizeOrigin_coordinates0_node(coordinates0: _np.ndarray,
|
def cellsSizeOrigin_coordinates0_node(coordinates0: _np.ndarray,
|
||||||
ordered: bool = True) -> Tuple[_np.ndarray,_np.ndarray,_np.ndarray]:
|
ordered: bool = True) -> _Tuple[_np.ndarray,_np.ndarray,_np.ndarray]:
|
||||||
"""
|
"""
|
||||||
Return grid 'DNA', i.e. cells, size, and origin from 1D array of nodal positions.
|
Return grid 'DNA', i.e. cells, size, and origin from 1D array of nodal positions.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
coordinates0 : numpy.ndarray of shape (:,3)
|
coordinates0 : numpy.ndarray, shape (:,3)
|
||||||
Undeformed nodal coordinates.
|
Undeformed nodal coordinates.
|
||||||
ordered : bool, optional
|
ordered : bool, optional
|
||||||
Expect coordinates0 data to be ordered (x fast, z slow).
|
Expect coordinates0 data to be ordered (x fast, z slow).
|
||||||
|
@ -437,7 +440,7 @@ def cellsSizeOrigin_coordinates0_node(coordinates0: _np.ndarray,
|
||||||
coords = [_np.unique(coordinates0[:,i]) for i in range(3)]
|
coords = [_np.unique(coordinates0[:,i]) for i in range(3)]
|
||||||
mincorner = _np.array(list(map(min,coords)))
|
mincorner = _np.array(list(map(min,coords)))
|
||||||
maxcorner = _np.array(list(map(max,coords)))
|
maxcorner = _np.array(list(map(max,coords)))
|
||||||
cells = _np.array(list(map(len,coords)),'i') - 1
|
cells = _np.array(list(map(len,coords)),int) - 1
|
||||||
size = maxcorner-mincorner
|
size = maxcorner-mincorner
|
||||||
origin = mincorner
|
origin = mincorner
|
||||||
|
|
||||||
|
@ -463,12 +466,12 @@ def point_to_node(cell_data: _np.ndarray) -> _np.ndarray:
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
cell_data : numpy.ndarray of shape (:,:,:,...)
|
cell_data : numpy.ndarray, shape (:,:,:,...)
|
||||||
Data defined on the cell centers of a periodic grid.
|
Data defined on the cell centers of a periodic grid.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
node_data : numpy.ndarray of shape (:,:,:,...)
|
node_data : numpy.ndarray, shape (:,:,:,...)
|
||||||
Data defined on the nodes of a periodic grid.
|
Data defined on the nodes of a periodic grid.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -485,12 +488,12 @@ def node_to_point(node_data: _np.ndarray) -> _np.ndarray:
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
node_data : numpy.ndarray of shape (:,:,:,...)
|
node_data : numpy.ndarray, shape (:,:,:,...)
|
||||||
Data defined on the nodes of a periodic grid.
|
Data defined on the nodes of a periodic grid.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
cell_data : numpy.ndarray of shape (:,:,:,...)
|
cell_data : numpy.ndarray, shape (:,:,:,...)
|
||||||
Data defined on the cell centers of a periodic grid.
|
Data defined on the cell centers of a periodic grid.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
@ -507,7 +510,7 @@ def coordinates0_valid(coordinates0: _np.ndarray) -> bool:
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
coordinates0 : numpy.ndarray
|
coordinates0 : numpy.ndarray, shape (:,3)
|
||||||
Array of undeformed cell coordinates.
|
Array of undeformed cell coordinates.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
|
@ -523,17 +526,17 @@ def coordinates0_valid(coordinates0: _np.ndarray) -> bool:
|
||||||
return False
|
return False
|
||||||
|
|
||||||
|
|
||||||
def regrid(size: _np.ndarray, F: _np.ndarray, cells: Union[_np.ndarray,Sequence[int]]) -> _np.ndarray:
|
def regrid(size: _FloatSequence, F: _np.ndarray, cells: _IntSequence) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Return mapping from coordinates in deformed configuration to a regular grid.
|
Return mapping from coordinates in deformed configuration to a regular grid.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size.
|
Physical size.
|
||||||
F : numpy.ndarray of shape (:,:,:,3,3)
|
F : numpy.ndarray, shape (:,:,:,3,3), shape (:,:,:,3,3)
|
||||||
Deformation gradient field.
|
Deformation gradient field.
|
||||||
cells : numpy.ndarray of shape (3)
|
cells : sequence of int, len (3)
|
||||||
Cell count along x,y,z of remapping grid.
|
Cell count along x,y,z of remapping grid.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
|
|
@ -5,7 +5,7 @@ All routines operate on numpy.ndarrays of shape (...,3,3).
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
|
||||||
from typing import Sequence
|
from typing import Sequence as _Sequence
|
||||||
|
|
||||||
import numpy as _np
|
import numpy as _np
|
||||||
|
|
||||||
|
@ -243,7 +243,7 @@ def stretch_right(T: _np.ndarray) -> _np.ndarray:
|
||||||
return _polar_decomposition(T,'U')[0]
|
return _polar_decomposition(T,'U')[0]
|
||||||
|
|
||||||
|
|
||||||
def _polar_decomposition(T: _np.ndarray, requested: Sequence[str]) -> tuple:
|
def _polar_decomposition(T: _np.ndarray, requested: _Sequence[str]) -> tuple:
|
||||||
"""
|
"""
|
||||||
Perform singular value decomposition.
|
Perform singular value decomposition.
|
||||||
|
|
||||||
|
|
|
@ -1,25 +1,27 @@
|
||||||
"""Functionality for generation of seed points for Voronoi or Laguerre tessellation."""
|
"""Functionality for generation of seed points for Voronoi or Laguerre tessellation."""
|
||||||
|
|
||||||
from typing import Sequence,Tuple
|
from typing import Tuple as _Tuple
|
||||||
|
|
||||||
from scipy import spatial as _spatial
|
from scipy import spatial as _spatial
|
||||||
import numpy as _np
|
import numpy as _np
|
||||||
|
|
||||||
|
from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence
|
||||||
from . import util as _util
|
from . import util as _util
|
||||||
from . import grid_filters as _grid_filters
|
from . import grid_filters as _grid_filters
|
||||||
|
|
||||||
|
|
||||||
def from_random(size: _np.ndarray, N_seeds: int, cells: _np.ndarray = None, rng_seed=None) -> _np.ndarray:
|
def from_random(size: _FloatSequence, N_seeds: int, cells: _IntSequence = None,
|
||||||
|
rng_seed=None) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Place seeds randomly in space.
|
Place seeds randomly in space.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the seeding domain.
|
Physical size of the seeding domain.
|
||||||
N_seeds : int
|
N_seeds : int
|
||||||
Number of seeds.
|
Number of seeds.
|
||||||
cells : numpy.ndarray of shape (3), optional.
|
cells : sequence of int, len (3), optional.
|
||||||
If given, ensures that each seed results in a grain when a standard Voronoi
|
If given, ensures that each seed results in a grain when a standard Voronoi
|
||||||
tessellation is performed using the given grid resolution (i.e. size/cells).
|
tessellation is performed using the given grid resolution (i.e. size/cells).
|
||||||
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
|
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
|
||||||
|
@ -28,29 +30,30 @@ def from_random(size: _np.ndarray, N_seeds: int, cells: _np.ndarray = None, rng_
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
coords : numpy.ndarray of shape (N_seeds,3)
|
coords : numpy.ndarray, shape (N_seeds,3)
|
||||||
Seed coordinates in 3D space.
|
Seed coordinates in 3D space.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
size_ = _np.array(size,float)
|
||||||
rng = _np.random.default_rng(rng_seed)
|
rng = _np.random.default_rng(rng_seed)
|
||||||
if cells is None:
|
if cells is None:
|
||||||
coords = rng.random((N_seeds,3)) * size
|
coords = rng.random((N_seeds,3)) * size_
|
||||||
else:
|
else:
|
||||||
grid_coords = _grid_filters.coordinates0_point(cells,size).reshape(-1,3,order='F')
|
grid_coords = _grid_filters.coordinates0_point(cells,size).reshape(-1,3,order='F')
|
||||||
coords = grid_coords[rng.choice(_np.prod(cells),N_seeds, replace=False)] \
|
coords = grid_coords[rng.choice(_np.prod(cells),N_seeds, replace=False)] \
|
||||||
+ _np.broadcast_to(size/cells,(N_seeds,3))*(rng.random((N_seeds,3))*.5-.25) # wobble without leaving cells
|
+ _np.broadcast_to(size_/_np.array(cells,int),(N_seeds,3))*(rng.random((N_seeds,3))*.5-.25) # wobble w/o leaving grid
|
||||||
|
|
||||||
return coords
|
return coords
|
||||||
|
|
||||||
|
|
||||||
def from_Poisson_disc(size: _np.ndarray, N_seeds: int, N_candidates: int, distance: float,
|
def from_Poisson_disc(size: _FloatSequence, N_seeds: int, N_candidates: int, distance: float,
|
||||||
periodic: bool = True, rng_seed=None) -> _np.ndarray:
|
periodic: bool = True, rng_seed=None) -> _np.ndarray:
|
||||||
"""
|
"""
|
||||||
Place seeds according to a Poisson disc distribution.
|
Place seeds according to a Poisson disc distribution.
|
||||||
|
|
||||||
Parameters
|
Parameters
|
||||||
----------
|
----------
|
||||||
size : numpy.ndarray of shape (3)
|
size : sequence of float, len (3)
|
||||||
Physical size of the seeding domain.
|
Physical size of the seeding domain.
|
||||||
N_seeds : int
|
N_seeds : int
|
||||||
Number of seeds.
|
Number of seeds.
|
||||||
|
@ -66,13 +69,13 @@ def from_Poisson_disc(size: _np.ndarray, N_seeds: int, N_candidates: int, distan
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
coords : numpy.ndarray of shape (N_seeds,3)
|
coords : numpy.ndarray, shape (N_seeds,3)
|
||||||
Seed coordinates in 3D space.
|
Seed coordinates in 3D space.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
rng = _np.random.default_rng(rng_seed)
|
rng = _np.random.default_rng(rng_seed)
|
||||||
coords = _np.empty((N_seeds,3))
|
coords = _np.empty((N_seeds,3))
|
||||||
coords[0] = rng.random(3) * size
|
coords[0] = rng.random(3) * _np.array(size,float)
|
||||||
|
|
||||||
s = 1
|
s = 1
|
||||||
i = 0
|
i = 0
|
||||||
|
@ -96,8 +99,8 @@ def from_Poisson_disc(size: _np.ndarray, N_seeds: int, N_candidates: int, distan
|
||||||
return coords
|
return coords
|
||||||
|
|
||||||
|
|
||||||
def from_grid(grid, selection: Sequence[int] = None,
|
def from_grid(grid, selection: _IntSequence = None,
|
||||||
invert: bool = False, average: bool = False, periodic: bool = True) -> Tuple[_np.ndarray, _np.ndarray]:
|
invert: bool = False, average: bool = False, periodic: bool = True) -> _Tuple[_np.ndarray, _np.ndarray]:
|
||||||
"""
|
"""
|
||||||
Create seeds from grid description.
|
Create seeds from grid description.
|
||||||
|
|
||||||
|
@ -105,7 +108,7 @@ def from_grid(grid, selection: Sequence[int] = None,
|
||||||
----------
|
----------
|
||||||
grid : damask.Grid
|
grid : damask.Grid
|
||||||
Grid from which the material IDs are used as seeds.
|
Grid from which the material IDs are used as seeds.
|
||||||
selection : iterable of integers, optional
|
selection : sequence of int, optional
|
||||||
Material IDs to consider.
|
Material IDs to consider.
|
||||||
invert : boolean, false
|
invert : boolean, false
|
||||||
Consider all material IDs except those in selection. Defaults to False.
|
Consider all material IDs except those in selection. Defaults to False.
|
||||||
|
@ -116,7 +119,7 @@ def from_grid(grid, selection: Sequence[int] = None,
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
coords, materials : numpy.ndarray of shape (:,3), numpy.ndarray of shape (:)
|
coords, materials : numpy.ndarray, shape (:,3); numpy.ndarray, shape (:)
|
||||||
Seed coordinates in 3D space, material IDs.
|
Seed coordinates in 3D space, material IDs.
|
||||||
|
|
||||||
"""
|
"""
|
||||||
|
|
|
@ -79,3 +79,23 @@ class TestCrystal:
|
||||||
a=a,b=b,c=c,
|
a=a,b=b,c=c,
|
||||||
alpha=alpha,beta=beta,gamma=gamma)
|
alpha=alpha,beta=beta,gamma=gamma)
|
||||||
assert np.allclose(points,c.lattice_points)
|
assert np.allclose(points,c.lattice_points)
|
||||||
|
|
||||||
|
@pytest.mark.parametrize('crystal,length',
|
||||||
|
[(Crystal(lattice='cF'),[12,6]),
|
||||||
|
(Crystal(lattice='cI'),[12,12,24]),
|
||||||
|
(Crystal(lattice='hP'),[3,3,6,12,6]),
|
||||||
|
(Crystal(lattice='tI',c=1.2),[2,2,2,4,2,4,2,2,4,8,4,8,8])
|
||||||
|
])
|
||||||
|
def test_N_slip(self,crystal,length):
|
||||||
|
assert [len(s) for s in crystal.kinematics('slip')['direction']] == length
|
||||||
|
assert [len(s) for s in crystal.kinematics('slip')['plane']] == length
|
||||||
|
|
||||||
|
@pytest.mark.parametrize('crystal,length',
|
||||||
|
[(Crystal(lattice='cF'),[12]),
|
||||||
|
(Crystal(lattice='cI'),[12]),
|
||||||
|
(Crystal(lattice='hP'),[6,6,6,6]),
|
||||||
|
])
|
||||||
|
def test_N_twin(self,crystal,length):
|
||||||
|
assert [len(s) for s in crystal.kinematics('twin')['direction']] == length
|
||||||
|
assert [len(s) for s in crystal.kinematics('twin')['plane']] == length
|
||||||
|
|
||||||
|
|
|
@ -2,6 +2,8 @@ import pytest
|
||||||
import numpy as np
|
import numpy as np
|
||||||
|
|
||||||
from damask import grid_filters
|
from damask import grid_filters
|
||||||
|
from damask import Grid
|
||||||
|
from damask import seeds
|
||||||
|
|
||||||
class TestGridFilters:
|
class TestGridFilters:
|
||||||
|
|
||||||
|
@ -139,12 +141,19 @@ class TestGridFilters:
|
||||||
else:
|
else:
|
||||||
function(unordered,mode)
|
function(unordered,mode)
|
||||||
|
|
||||||
def test_regrid(self):
|
def test_regrid_identity(self):
|
||||||
size = np.random.random(3)
|
size = np.random.random(3)
|
||||||
cells = np.random.randint(8,32,(3))
|
cells = np.random.randint(8,32,(3))
|
||||||
F = np.broadcast_to(np.eye(3), tuple(cells)+(3,3))
|
F = np.broadcast_to(np.eye(3), tuple(cells)+(3,3))
|
||||||
assert all(grid_filters.regrid(size,F,cells) == np.arange(cells.prod()))
|
assert all(grid_filters.regrid(size,F,cells) == np.arange(cells.prod()))
|
||||||
|
|
||||||
|
def test_regrid_double_cells(self):
|
||||||
|
size = np.random.random(3)
|
||||||
|
cells = np.random.randint(8,32,(3))
|
||||||
|
g = Grid.from_Voronoi_tessellation(cells,size,seeds.from_random(size,10))
|
||||||
|
F = np.broadcast_to(np.eye(3), tuple(cells)+(3,3))
|
||||||
|
assert all(g.scale(cells*2).material.flatten() ==
|
||||||
|
g.material.flatten()[grid_filters.regrid(size,F,cells*2)])
|
||||||
|
|
||||||
@pytest.mark.parametrize('differential_operator',[grid_filters.curl,
|
@pytest.mark.parametrize('differential_operator',[grid_filters.curl,
|
||||||
grid_filters.divergence,
|
grid_filters.divergence,
|
||||||
|
|
|
@ -11,6 +11,6 @@ module constants
|
||||||
real(pReal), parameter :: &
|
real(pReal), parameter :: &
|
||||||
T_ROOM = 300.0_pReal, & !< Room temperature in K. ToDo: IUPAC: 298.15
|
T_ROOM = 300.0_pReal, & !< Room temperature in K. ToDo: IUPAC: 298.15
|
||||||
K_B = 1.38e-23_pReal, & !< Boltzmann constant in J/Kelvin
|
K_B = 1.38e-23_pReal, & !< Boltzmann constant in J/Kelvin
|
||||||
N_A = 6.02214076e-23_pReal !< Avogadro constant in 1/mol
|
N_A = 6.02214076e23_pReal !< Avogadro constant in 1/mol
|
||||||
|
|
||||||
end module constants
|
end module constants
|
||||||
|
|
|
@ -30,7 +30,7 @@ module subroutine elastic_init(phases)
|
||||||
phase, &
|
phase, &
|
||||||
mech, &
|
mech, &
|
||||||
elastic
|
elastic
|
||||||
logical :: thermal_active
|
|
||||||
|
|
||||||
print'(/,1x,a)', '<<<+- phase:mechanical:elastic init -+>>>'
|
print'(/,1x,a)', '<<<+- phase:mechanical:elastic init -+>>>'
|
||||||
print'(/,1x,a)', '<<<+- phase:mechanical:elastic:Hooke init -+>>>'
|
print'(/,1x,a)', '<<<+- phase:mechanical:elastic:Hooke init -+>>>'
|
||||||
|
|
|
@ -372,7 +372,7 @@ end function rotTensor4
|
||||||
|
|
||||||
|
|
||||||
!---------------------------------------------------------------------------------------------------
|
!---------------------------------------------------------------------------------------------------
|
||||||
!> @brief Rotate a rank-4 tensor in Voigt 6x6 notation passively (default) or actively.
|
!> @brief Rotate a rank-4 stiffness tensor in Voigt 6x6 notation passively (default) or actively.
|
||||||
!> @details: https://scicomp.stackexchange.com/questions/35600
|
!> @details: https://scicomp.stackexchange.com/questions/35600
|
||||||
!! ToDo: Need to check active/passive !!!
|
!! ToDo: Need to check active/passive !!!
|
||||||
!---------------------------------------------------------------------------------------------------
|
!---------------------------------------------------------------------------------------------------
|
||||||
|
@ -393,11 +393,11 @@ pure function rotStiffness(self,C,active) result(cRot)
|
||||||
R = self%asMatrix()
|
R = self%asMatrix()
|
||||||
endif
|
endif
|
||||||
|
|
||||||
M = reshape([R(1,1)**2.0_pReal, R(2,1)**2.0_pReal, R(3,1)**2.0_pReal, &
|
M = reshape([R(1,1)**2, R(2,1)**2, R(3,1)**2, &
|
||||||
R(2,1)*R(3,1), R(1,1)*R(3,1), R(1,1)*R(2,1), &
|
R(2,1)*R(3,1), R(1,1)*R(3,1), R(1,1)*R(2,1), &
|
||||||
R(1,2)**2.0_pReal, R(2,2)**2.0_pReal, R(3,2)**2.0_pReal, &
|
R(1,2)**2, R(2,2)**2, R(3,2)**2, &
|
||||||
R(2,2)*R(3,2), R(1,2)*R(3,2), R(1,2)*R(2,2), &
|
R(2,2)*R(3,2), R(1,2)*R(3,2), R(1,2)*R(2,2), &
|
||||||
R(1,3)**2.0_pReal, R(2,3)**2.0_pReal, R(3,3)**2.0_pReal, &
|
R(1,3)**2, R(2,3)**2, R(3,3)**2, &
|
||||||
R(2,3)*R(3,3), R(1,3)*R(3,3), R(1,3)*R(2,3), &
|
R(2,3)*R(3,3), R(1,3)*R(3,3), R(1,3)*R(2,3), &
|
||||||
2.0_pReal*R(1,2)*R(1,3), 2.0_pReal*R(2,2)*R(2,3), 2.0_pReal*R(3,2)*R(3,3), &
|
2.0_pReal*R(1,2)*R(1,3), 2.0_pReal*R(2,2)*R(2,3), 2.0_pReal*R(3,2)*R(3,3), &
|
||||||
R(2,2)*R(3,3)+R(2,3)*R(3,2), R(1,2)*R(3,3)+R(1,3)*R(3,2), R(1,2)*R(2,3)+R(1,3)*R(2,2), &
|
R(2,2)*R(3,3)+R(2,3)*R(3,2), R(1,2)*R(3,3)+R(1,3)*R(3,2), R(1,2)*R(2,3)+R(1,3)*R(2,2), &
|
||||||
|
|
Loading…
Reference in New Issue