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DAMASK_EICMD
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Merge branch 'lattice-structure-rename' into ShowGrainBoundaries

This commit is contained in:
Martin Diehl 2020-11-29 20:50:41 +01:00
parent 3c1f1af009 718511c08c
commit 4d2bf37193
189 changed files with 7093 additions and 5469 deletions
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269
.gitlab-ci.yml
View File

@ -2,14 +2,10 @@
stages:
- prepareAll
- python
- preprocessing
- postprocessing
- compilePETSc
- prepareGrid
- deprecated
- compile
- grid
- compileMarc
- marc
- example
- performance
- createPackage
- createDocumentation
@ -20,12 +16,12 @@ stages:
###################################################################################################
before_script:
- if [ $(awk "/$CI_PIPELINE_ID/{print NR}" $TESTROOT/GitLabCI.queue)x == 'x' ];
then echo $CI_PIPELINE_ID >> $TESTROOT/GitLabCI.queue;
- if [ $(awk "/$CI_PIPELINE_ID/{print NR}" $LOCAL_HOME/GitLabCI.queue)x == 'x' ];
then echo $CI_PIPELINE_ID >> $LOCAL_HOME/GitLabCI.queue;
fi
- while [ $(awk "/$CI_PIPELINE_ID/{print NR}" $TESTROOT/GitLabCI.queue) != 1 ];
- while [ $(awk "/$CI_PIPELINE_ID/{print NR}" $LOCAL_HOME/GitLabCI.queue) != 1 ];
do sleep 5m;
echo -e "Currently queued pipelines:\n$(cat $TESTROOT/GitLabCI.queue)\n";
echo -e "Currently queued pipelines:\n$(cat $LOCAL_HOME/GitLabCI.queue)\n";
done
- source $DAMASKROOT/env/DAMASK.sh
- cd $DAMASKROOT/PRIVATE/testing
@ -45,61 +41,55 @@ variables:
# ===============================================================================================
# Shortcut names
# ===============================================================================================
DAMASKROOT: "$TESTROOT/GitLabCI_Pipeline_$CI_PIPELINE_ID/DAMASK"
DAMASKROOT: "$LOCAL_HOME/GitLabCI_Pipeline_$CI_PIPELINE_ID/DAMASK"
TESTROOT: "$LOCAL_HOME/GitLabCI_Pipeline_$CI_PIPELINE_ID/tests"
# ===============================================================================================
# Names of module files to load
# ===============================================================================================
# ++++++++++++ Compiler +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
IntelCompiler17_8: "Compiler/Intel/17.8 Libraries/IMKL/2017"
IntelCompiler18_4: "Compiler/Intel/18.4 Libraries/IMKL/2018"
GNUCompiler8_2: "Compiler/GNU/8.2"
IntelCompiler19_1: "Compiler/Intel/19.1.2 Libraries/IMKL/2020"
GNUCompiler10: "Compiler/GNU/10"
# ------------ Defaults ----------------------------------------------
IntelCompiler: "$IntelCompiler18_4"
GNUCompiler: "$GNUCompiler8_2"
IntelCompiler: "$IntelCompiler19_1"
GNUCompiler: "$GNUCompiler10"
# ++++++++++++ MPI ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
IMPI2018Intel18_4: "MPI/Intel/18.4/IntelMPI/2018"
MPICH3_3GNU8_2: "MPI/GNU/8.2/MPICH/3.3"
IMPI2020Intel19_1: "MPI/Intel/19.1.2/IntelMPI/2019"
OMPI4_0GNU10: "MPI/GNU/10/OpenMPI/4.0.5"
# ------------ Defaults ----------------------------------------------
MPICH_Intel: "$IMPI2018Intel18_4"
MPICH_GNU: "$MPICH3_3GNU8_2"
MPI_Intel: "$IMPI2020Intel19_1"
MPI_GNU: "$OMPI4_0GNU10"
# ++++++++++++ PETSc ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
PETSc3_10_3IMPI2018Intel18_4: "Libraries/PETSc/3.10.3/Intel-18.4-IntelMPI-2018"
PETSc3_10_3MPICH3_3GNU8_2: "Libraries/PETSc/3.10.3/GNU-8.2-MPICH-3.3"
PETSc3_14_0IMPI2020Intel19_1: "Libraries/PETSc/3.14.0/Intel-19.1.2-IntelMPI-2019"
PETSc3_14_0OMPI4_0GNU10: "Libraries/PETSc/3.14.0/GNU-10-OpenMPI-4.0.5"
# ------------ Defaults ----------------------------------------------
PETSc_MPICH_Intel: "$PETSc3_10_3IMPI2018Intel18_4"
PETSc_MPICH_GNU: "$PETSc3_10_3MPICH3_3GNU8_2"
PETSc_Intel: "$PETSc3_14_0IMPI2020Intel19_1"
PETSc_GNU: "$PETSc3_14_0OMPI4_0GNU10"
# ++++++++++++ commercial FEM ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
MSC2019_1: "FEM/MSC/2019.1"
MSC2020: "FEM/MSC/2020"
# ------------ Defaults ----------------------------------------------
MSC: "$MSC2019_1"
IntelMarc: "$IntelCompiler17_8"
HDF5Marc: "HDF5/1.10.5/Intel-17.8"
# ++++++++++++ Documentation ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Doxygen1_8_17: "Documentation/Doxygen/1.8.17"
# ------------ Defaults ----------------------------------------------
Doxygen: "$Doxygen1_8_17"
MSC: "$MSC2020"
IntelMarc: "$IntelCompiler19_1"
HDF5Marc: "HDF5/1.12.0/Intel-19.1.2"
###################################################################################################
checkout:
stage: prepareAll
before_script:
- echo $CI_PIPELINE_ID >> $TESTROOT/GitLabCI.queue
- while [ $(awk "/$CI_PIPELINE_ID/{print NR}" $TESTROOT/GitLabCI.queue) != 1 ];
- echo $CI_PIPELINE_ID >> $LOCAL_HOME/GitLabCI.queue
- while [ $(awk "/$CI_PIPELINE_ID/{print NR}" $LOCAL_HOME/GitLabCI.queue) != 1 ];
do sleep 5m;
echo -e "Currently queued pipelines:\n$(cat $TESTROOT/GitLabCI.queue)\n";
echo -e "Currently queued pipelines:\n$(cat $LOCAL_HOME/GitLabCI.queue)\n";
done
script:
- mkdir -p $DAMASKROOT
- mkdir -p $TESTROOT
- cd $DAMASKROOT
- if [ -d DAMASK ]; then rm -rf DAMASK; fi # there might be some leftovers from a failed clone
- git clone -q git@magit1.mpie.de:damask/DAMASK.git .
- git checkout $CI_COMMIT_SHA
- git submodule update --init
- source env/DAMASK.sh
- make processing
- mkdir /tmp/$CI_PIPELINE_ID
except:
- master
- release
@ -109,78 +99,77 @@ Pytest_python:
stage: python
script:
- cd $DAMASKROOT/python
- pytest --basetemp=/tmp/${CI_PIPELINE_ID}/python
- pytest --basetemp=${TESTROOT}/python -v
except:
- master
- release
###################################################################################################
Pre_SeedGeneration:
stage: preprocessing
stage: deprecated
script: PreProcessing_SeedGeneration/test.py
except:
- master
- release
Pre_GeomGeneration:
stage: preprocessing
stage: deprecated
script: PreProcessing_GeomGeneration/test.py
except:
- master
- release
Pre_GeomModification:
stage: preprocessing
stage: deprecated
script: PreProcessing_GeomModification/test.py
except:
- master
- release
Pre_General:
stage: preprocessing
stage: deprecated
script: PreProcessing/test.py
except:
- master
- release
###################################################################################################
Post_General:
stage: postprocessing
stage: deprecated
script: PostProcessing/test.py
except:
- master
- release
Post_GeometryReconstruction:
stage: postprocessing
stage: deprecated
script: spectral_geometryReconstruction/test.py
except:
- master
- release
Post_addCurl:
stage: postprocessing
stage: deprecated
script: addCurl/test.py
except:
- master
- release
Post_addDivergence:
stage: postprocessing
stage: deprecated
script: addDivergence/test.py
except:
- master
- release
Post_addGradient:
stage: postprocessing
stage: deprecated
script: addGradient/test.py
except:
- master
- release
Post_OrientationAverageMisorientation:
stage: postprocessing
stage: deprecated
script:
- OrientationAverageMisorientation/test.py
except:
@ -188,61 +177,76 @@ Post_OrientationAverageMisorientation:
- release
###################################################################################################
grid_mech_compile_Intel:
stage: compilePETSc
compile_grid_Intel:
stage: compile
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel
- cp -r grid_mech_compile grid_mech_compile_Intel
- grid_mech_compile_Intel/test.py
- module load $IntelCompiler $MPI_Intel $PETSc_Intel
- cd pytest
- pytest -k 'compile and grid' --basetemp=/tmp/${CI_PIPELINE_ID}/compile_grid_Intel
- pytest -k 'compile and grid' --basetemp=${TESTROOT}/compile_grid_Intel
except:
- master
- release
Compile_FEM_Intel:
stage: compilePETSc
compile_mesh_Intel:
stage: compile
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel
- cp -r FEM_compile FEM_compile_Intel
- FEM_compile_Intel/test.py
- module load $IntelCompiler $MPI_Intel $PETSc_Intel
- cd pytest
- pytest -k 'compile and mesh' --basetemp=/tmp/${CI_PIPELINE_ID}/compile_mesh_Intel
- pytest -k 'compile and mesh' --basetemp=${TESTROOT}/compile_mesh_Intel
except:
- master
- release
grid_mech_compile_GNU:
stage: compilePETSc
compile_grid_GNU:
stage: compile
script:
- module load $GNUCompiler $MPICH_GNU $PETSc_MPICH_GNU
- cp -r grid_mech_compile grid_mech_compile_GNU
- grid_mech_compile_GNU/test.py
- module load $GNUCompiler $MPI_GNU $PETSc_GNU
- cd pytest
- pytest -k 'compile and grid' --basetemp=/tmp/${CI_PIPELINE_ID}/compile_grid_GNU
- pytest -k 'compile and grid' --basetemp=${TESTROOT}/compile_grid_GNU
except:
- master
- release
Compile_FEM_GNU:
stage: compilePETSc
compile_mesh_GNU:
stage: compile
script:
- module load $GNUCompiler $MPICH_GNU $PETSc_MPICH_GNU
- cp -r FEM_compile FEM_compile_GNU
- FEM_compile_GNU/test.py
- module load $GNUCompiler $MPI_GNU $PETSc_GNU
- cd pytest
- pytest -k 'compile and mesh' --basetemp=/tmp/${CI_PIPELINE_ID}/compile_mesh_GNU
- pytest -k 'compile and mesh' --basetemp=${TESTROOT}/compile_mesh_GNU
except:
- master
- release
###################################################################################################
Compile_Intel_Prepare:
stage: prepareGrid
compile_MARC:
stage: compile
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel
- cd $DAMASKROOT
- make clean grid processing
- module load $IntelMarc $HDF5Marc $MSC
- cd pytest
- pytest -k 'compile and Marc' --basetemp=${TESTROOT}/compile_Marc
except:
- master
- release
setup_grid:
stage: compile
script:
- module load $IntelCompiler $MPI_Intel $PETSc_Intel
- BUILD_DIR=$(mktemp -d)
- cd ${BUILD_DIR}
- cmake -DDAMASK_SOLVER=GRID -DCMAKE_INSTALL_PREFIX=${DAMASKROOT} ${DAMASKROOT}
- make -j2 all install
except:
- master
- release
setup_mesh:
stage: compile
script:
- module load $IntelCompiler $MPI_Intel $PETSc_Intel
- BUILD_DIR=$(mktemp -d)
- cd ${BUILD_DIR}
- cmake -DDAMASK_SOLVER=MESH -DCMAKE_INSTALL_PREFIX=${DAMASKROOT} ${DAMASKROOT}
- make -j2 all install
except:
- master
- release
@ -251,9 +255,9 @@ Compile_Intel_Prepare:
Pytest_grid:
stage: grid
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel
- module load $IntelCompiler $MPI_Intel $PETSc_Intel
- cd pytest
- pytest -m 'not compile' --basetemp=/tmp/${CI_PIPELINE_ID}/fortran
- pytest -k 'not compile' --basetemp=${TESTROOT}/fortran -v
except:
- master
- release
@ -265,13 +269,6 @@ Thermal:
- master
- release
grid_parsingArguments:
stage: grid
script: grid_parsingArguments/test.py
except:
- master
- release
Nonlocal_Damage_DetectChanges:
stage: grid
script: Nonlocal_Damage_DetectChanges/test.py
@ -279,22 +276,6 @@ Nonlocal_Damage_DetectChanges:
- master
- release
grid_all_restart:
stage: grid
script: grid_all_restart/test.py
except:
- master
- release
grid_all_restartMPI:
stage: grid
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel
- grid_all_restartMPI/test.py
except:
- master
- release
Plasticity_DetectChanges:
stage: grid
script: Plasticity_DetectChanges/test.py
@ -309,46 +290,8 @@ Phenopowerlaw_singleSlip:
- master
- release
###################################################################################################
Marc_compileIfort:
stage: compileMarc
script:
- module load $IntelMarc $HDF5Marc $MSC
- Marc_compileIfort/test.py
- cd pytest
- pytest -k 'compile and Marc'
except:
- master
- release
###################################################################################################
Hex_elastic:
stage: marc
script:
- module load $IntelMarc $HDF5Marc $MSC
- Hex_elastic/test.py
except:
- master
- release
CubicFCC_elastic:
stage: marc
script:
- module load $IntelMarc $HDF5Marc $MSC
- CubicFCC_elastic/test.py
except:
- master
- release
CubicBCC_elastic:
stage: marc
script:
- module load $IntelMarc $HDF5Marc $MSC
- CubicBCC_elastic/test.py
except:
- master
- release
J2_plasticBehavior:
stage: marc
script:
@ -367,25 +310,17 @@ Marc_elementLib:
- master
- release
###################################################################################################
grid_all_example:
stage: example
script: grid_all_example/test.py
except:
- master
- release
###################################################################################################
SpectralRuntime:
stage: performance
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel
- module load $IntelCompiler $MPI_Intel $PETSc_Intel
- cd $DAMASKROOT
- make clean grid processing OPTIMIZATION=AGGRESSIVE
- cd $TESTROOT/performance # location of old results
- cd $LOCAL_HOME/performance # location of old results
- git checkout . # undo any changes (i.e. run time data from non-development branch)
- cd $DAMASKROOT/PRIVATE/testing
- SpectralAll_runtime/test.py -d $TESTROOT/performance
- SpectralAll_runtime/test.py -d $LOCAL_HOME/performance
except:
- master
- release
@ -401,20 +336,10 @@ createTar:
- release
###################################################################################################
Marc:
Python:
stage: createDocumentation
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel $Doxygen
- $DAMASKROOT/PRIVATE/documenting/runDoxygen.sh $DAMASKROOT marc
except:
- master
- release
GridSolver:
stage: createDocumentation
script:
- module load $IntelCompiler $MPICH_Intel $PETSc_MPICH_Intel $Doxygen
- $DAMASKROOT/PRIVATE/documenting/runDoxygen.sh $DAMASKROOT grid
- echo 'tbd one matesting1'
except:
- master
- release
@ -423,11 +348,11 @@ GridSolver:
backupData:
stage: saveDocumentation
script:
- cd $TESTROOT/performance # location of new runtime results
- cd $LOCAL_HOME/performance # location of new runtime results
- git commit -am"${CI_PIPELINE_ID}_${CI_COMMIT_SHA}"
- mkdir $BACKUP/${CI_PIPELINE_ID}_${CI_COMMIT_SHA}
- mv $TESTROOT/performance/time.png $BACKUP/${CI_PIPELINE_ID}_${CI_COMMIT_SHA}/
- mv $TESTROOT/performance/memory.png $BACKUP/${CI_PIPELINE_ID}_${CI_COMMIT_SHA}/
- mv $LOCAL_HOME/performance/time.png $BACKUP/${CI_PIPELINE_ID}_${CI_COMMIT_SHA}/
- mv $LOCAL_HOME/performance/memory.png $BACKUP/${CI_PIPELINE_ID}_${CI_COMMIT_SHA}/
- mv $DAMASKROOT/PRIVATE/documenting/DAMASK_* $BACKUP/${CI_PIPELINE_ID}_${CI_COMMIT_SHA}/
only:
- development
@ -457,8 +382,8 @@ removeData:
before_script:
- echo "Removing data and lock of pipeline $CI_PIPELINE_ID"
script:
- rm -rf $TESTROOT/GitLabCI_Pipeline_$CI_PIPELINE_ID
- sed -i "/$CI_PIPELINE_ID/d" $TESTROOT/GitLabCI.queue # in case pipeline was manually (web GUI) restarted and releaseLock was performed already
- rm -rf $LOCAL_HOME/GitLabCI_Pipeline_$CI_PIPELINE_ID
- sed -i "/$CI_PIPELINE_ID/d" $LOCAL_HOME/GitLabCI.queue # in case pipeline was manually (web GUI) restarted and releaseLock was performed already
except:
- master
- release
@ -469,7 +394,7 @@ removeLock:
before_script:
- echo "Removing lock of pipeline $CI_PIPELINE_ID"
when: always
script: sed -i "/$CI_PIPELINE_ID/d" $TESTROOT/GitLabCI.queue
script: sed -i "/$CI_PIPELINE_ID/d" $LOCAL_HOME/GitLabCI.queue
except:
- master
- release

2
PRIVATE

@ -1 +1 @@
Subproject commit 1e8c66897820468ab46958d995005e2b69204d0e
Subproject commit 751f96155294e449b31c5d4913fea7bc02ce81b1

2
VERSION
View File

@ -1 +1 @@
v3.0.0-alpha-556-gf379aecd8
v3.0.0-alpha-868-gb8344973d

7
cmake/Compiler-Intel.cmake
View File

@ -98,11 +98,12 @@ set (DEBUG_FLAGS "${DEBUG_FLAGS} -ftrapuv")
set (DEBUG_FLAGS "${DEBUG_FLAGS} -fpe-all=0")
# ... capture all floating-point exceptions, sets -ftz automatically
set (DEBUG_FLAGS "${DEBUG_FLAGS} -warn")
# disable due to compiler bug https://community.intel.com/t5/Intel-Fortran-Compiler/false-positive-stand-f18-and-IEEE-SELECTED-REAL-KIND/m-p/1227336
#set (DEBUG_FLAGS "${DEBUG_FLAGS} -warn")
# enables warnings ...
set (DEBUG_FLAGS "${DEBUG_FLAGS} errors")
#set (DEBUG_FLAGS "${DEBUG_FLAGS} errors")
# ... warnings are changed to errors
set (DEBUG_FLAGS "${DEBUG_FLAGS},stderrors")
#set (DEBUG_FLAGS "${DEBUG_FLAGS},stderrors")
# ... warnings about Fortran standard violations are changed to errors
set (DEBUG_FLAGS "${DEBUG_FLAGS} -debug-parameters all")

2
env/CONFIG vendored
View File

@ -2,4 +2,4 @@
set DAMASK_NUM_THREADS = 4
set MSC_ROOT = /opt/msc
set MARC_VERSION = 2019.1
set MSC_VERSION = 2020

2
env/DAMASK.csh vendored
View File

@ -51,4 +51,4 @@ else
setenv PYTHONPATH $DAMASK_ROOT/python:$PYTHONPATH
endif
setenv MSC_ROOT
setenv MARC_VERSION
setenv MSC_VERSION

3
examples/.gitignore vendored
View File

@ -3,6 +3,3 @@
*.xdmf
*.sta
*.vt*
*.geom
*.seeds
postProc

26
examples/ConfigFiles/Phase_Isotropic_AluminumIsotropic.yaml
View File

@ -1,16 +1,16 @@
# Kuo, J. C., Mikrostrukturmechanik von Bikristallen mit Kippkorngrenzen. Shaker-Verlag 2004. http://edoc.mpg.de/204079
Aluminum:
elasticity: {C_11: 110.9e9, C_12: 58.34e9, type: hooke}
generic:
mechanics:
lattice: aP
elasticity: {C_11: 110.9e9, C_12: 58.34e9, type: hooke}
output: [F, P, Fe, Fp, Lp]
lattice: iso
plasticity:
type: isotropic
output: [xi]
xi_0: 31e6
xi_inf: 63e6
dot_gamma_0: 0.001
n: 20
M: 3
h_0: 75e6
a: 2.25
plasticity:
type: isotropic
output: [xi]
xi_0: 31e6
xi_inf: 63e6
dot_gamma_0: 0.001
n: 20
M: 3
h_0: 75e6
a: 2.25

28
examples/ConfigFiles/Phase_Isotropic_FreeSurface.yaml
View File

@ -1,17 +1,17 @@
# Maiti and Eisenlohr 2018 Scripta Materialia
Air:
elasticity: {C_11: 10e9, C_12: 0.0, type: hooke}
generic:
mechanics:
lattice: aP
elasticity: {C_11: 10e9, C_12: 0.0, type: hooke}
output: [F, P, Fe, Fp, Lp]
lattice: iso
plasticity:
type: isotropic
output: [xi]
xi_0: 0.3e6
xi_inf: 0.6e6
dot_gamma_0: 0.001
n: 5
M: 3
h_0: 1e6
a: 2
dilatation: true
plasticity:
type: isotropic
output: [xi]
xi_0: 0.3e6
xi_inf: 0.6e6
dot_gamma_0: 0.001
n: 5
M: 3
h_0: 1e6
a: 2
dilatation: true

25
examples/ConfigFiles/Phase_Phenopowerlaw_BCC-Ferrite.yaml
View File

@ -2,15 +2,16 @@
# Tasan et.al. 2015 International Journal of Plasticity
# Diehl et.al. 2015 Meccanica
Ferrite:
elasticity: {C_11: 233.3e9, C_12: 135.5e9, C_44: 118.0e9, type: hooke}
lattice: bcc
plasticity:
N_sl: [12, 12]
a_sl: 2.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 1000.0e6
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
type: phenopowerlaw
xi_0_sl: [95.e6, 96.e6]
xi_inf_sl: [222.e6, 412.7e6]
mechanics:
lattice: cI
elasticity: {C_11: 233.3e9, C_12: 135.5e9, C_44: 118.0e9, type: hooke}
plasticity:
N_sl: [12, 12]
a_sl: 2.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 1000.0e6
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
type: phenopowerlaw
xi_0_sl: [95.e6, 96.e6]
xi_inf_sl: [222.e6, 412.7e6]

25
examples/ConfigFiles/Phase_Phenopowerlaw_BCC-Martensite.yaml
View File

@ -2,15 +2,16 @@
# Tasan et.al. 2015 International Journal of Plasticity
# Diehl et.al. 2015 Meccanica
Martensite:
elasticity: {C_11: 417.4e9, C_12: 242.4e9, C_44: 211.1e9, type: hooke}
lattice: bcc
plasticity:
N_sl: [12, 12]
a_sl: 2.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 563.0e9
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
type: phenopowerlaw
xi_0_sl: [405.8e6, 456.7e6]
xi_inf_sl: [872.9e6, 971.2e6]
mechanics:
lattice: cI
elasticity: {C_11: 417.4e9, C_12: 242.4e9, C_44: 211.1e9, type: hooke}
plasticity:
N_sl: [12, 12]
a_sl: 2.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 563.0e9
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
type: phenopowerlaw
xi_0_sl: [405.8e6, 456.7e6]
xi_inf_sl: [872.9e6, 971.2e6]

34
examples/FEM/polyXtal/material.yaml
View File

@ -1,26 +1,26 @@
homogenization:
SX:
N_constituents: 1
mech: {type: none}
mechanics: {type: none}
phase:
Aluminum:
elasticity: {C_11: 106.75e9, C_12: 60.41e9, C_44: 28.34e9, type: hooke}
generic:
output: [F, P, Fe, Fp, Lp]
lattice: fcc
plasticity:
N_sl: [12]
a_sl: 2.25
atol_xi: 1.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 75e6
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
output: [xi_sl]
type: phenopowerlaw
xi_0_sl: [31e6]
xi_inf_sl: [63e6]
mechanics:
lattice: cF
output: [F, P, F_e, F_p, L_p]
elasticity: {C_11: 106.75e9, C_12: 60.41e9, C_44: 28.34e9, type: hooke}
plasticity:
N_sl: [12]
a_sl: 2.25
atol_xi: 1.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 75e6
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
output: [xi_sl]
type: phenopowerlaw
xi_0_sl: [31e6]
xi_inf_sl: [63e6]
material:
- constituents:

34
examples/SpectralMethod/Polycrystal/material.yaml
View File

@ -2,7 +2,7 @@
homogenization:
SX:
N_constituents: 1
mech: {type: none}
mechanics: {type: none}
material:
- homogenization: SX
@ -108,19 +108,19 @@ material:
phase:
Aluminum:
elasticity: {C_11: 106.75e9, C_12: 60.41e9, C_44: 28.34e9, type: hooke}
generic:
output: [F, P, Fe, Fp, Lp, O]
lattice: fcc
plasticity:
N_sl: [12]
a_sl: 2.25
atol_xi: 1.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 75e6
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
output: [xi_sl]
type: phenopowerlaw
xi_0_sl: [31e6]
xi_inf_sl: [63e6]
lattice: cF
mechanics:
output: [F, P, F_e, F_p, L_p, O]
elasticity: {C_11: 106.75e9, C_12: 60.41e9, C_44: 28.34e9, type: hooke}
plasticity:
N_sl: [12]
a_sl: 2.25
atol_xi: 1.0
dot_gamma_0_sl: 0.001
h_0_sl_sl: 75e6
h_sl_sl: [1, 1, 1.4, 1.4, 1.4, 1.4]
n_sl: 20
output: [xi_sl]
type: phenopowerlaw
xi_0_sl: [31e6]
xi_inf_sl: [63e6]

2
examples/SpectralMethod/Polycrystal/shearXY.yaml
View File

@ -1,5 +1,5 @@
step:
- mech:
- mechanics:
dot_F: [0, 0, 0,
1e-3, 0, 0,
0, 0, 0]

2
examples/SpectralMethod/Polycrystal/shearZX.yaml
View File

@ -1,6 +1,6 @@
---
step:
- mech:
- mechanics:
dot_F: [0, 0, 1e-3,
0, 0, 0,
0, 0, 0]

4
examples/SpectralMethod/Polycrystal/tensionX.yaml
View File

@ -1,7 +1,7 @@
---
step:
- mech:
- mechanics:
dot_F: [1.0e-3, 0, 0,
0, x, 0,
0, 0, x]
@ -12,7 +12,7 @@ step:
t: 10
N: 40
f_out: 4
- mech:
- mechanics:
dot_F: [1.0e-3, 0, 0,
0, x, 0,
0, 0, x]

34
installation/mods_MarcMentat/apply_DAMASK_modifications.py
View File

@ -7,15 +7,15 @@ from pathlib import Path
import damask
marc_version = float(damask.environment.options['MARC_VERSION'])
if int(marc_version) == marc_version:
marc_version = int(marc_version)
msc_version = float(damask.environment.options['MSC_VERSION'])
if int(msc_version) == msc_version:
msc_version = int(msc_version)
msc_root = Path(damask.environment.options['MSC_ROOT'])
damask_root = damask.environment.root_dir
parser = argparse.ArgumentParser(
description='Apply DAMASK modification to MSC.Marc/Mentat',
epilog = f'MSC_ROOT={msc_root} and MARC_VERSION={marc_version} (from {damask_root}/env/CONFIG)')
epilog = f'MSC_ROOT={msc_root} and MSC_VERSION={msc_version} (from {damask_root}/env/CONFIG)')
parser.add_argument('--editor', dest='editor', metavar='string', default='vi',
help='Name of the editor for MSC.Mentat (executable)')
@ -23,8 +23,8 @@ parser.add_argument('--editor', dest='editor', metavar='string', default='vi',
def copy_and_replace(in_file,dst):
with open(in_file) as f:
content = f.read()
content = content.replace('%INSTALLDIR%',msc_root)
content = content.replace('%VERSION%',str(marc_version))
content = content.replace('%INSTALLDIR%',str(msc_root))
content = content.replace('%VERSION%',str(msc_version))
content = content.replace('%EDITOR%', parser.parse_args().editor)
with open(dst/Path(in_file).name,'w') as f:
f.write(content)
@ -32,36 +32,36 @@ def copy_and_replace(in_file,dst):
print('adapting Marc tools...\n')
src = damask_root/f'installation/mods_MarcMentat/{marc_version}/Marc_tools'
dst = msc_root/f'marc{marc_version}/tools'
src = damask_root/f'installation/mods_MarcMentat/{msc_version}/Marc_tools'
dst = msc_root/f'marc{msc_version}/tools'
for in_file in glob.glob(str(src/'*damask*')) + [str(src/'include_linux64')]:
copy_and_replace(in_file,dst)
print('adapting Mentat scripts and menus...\n')
src = damask_root/f'installation/mods_MarcMentat/{marc_version}/Mentat_bin'
dst = msc_root/f'mentat{marc_version}/bin'
src = damask_root/f'installation/mods_MarcMentat/{msc_version}/Mentat_bin'
dst = msc_root/f'mentat{msc_version}/bin'
for in_file in glob.glob(str(src/'*[!.original]')):
copy_and_replace(in_file,dst)
src = damask_root/f'installation/mods_MarcMentat/{marc_version}/Mentat_menus'
dst = msc_root/f'mentat{marc_version}/menus'
src = damask_root/f'installation/mods_MarcMentat/{msc_version}/Mentat_menus'
dst = msc_root/f'mentat{msc_version}/menus'
for in_file in glob.glob(str(src/'job_run.ms')):
copy_and_replace(in_file,dst)
print('compiling Mentat menu binaries...')
executable = str(msc_root/f'mentat{marc_version}/bin/mentat')
menu_file = str(msc_root/f'mentat{marc_version}/menus/linux64/main.msb')
executable = str(msc_root/f'mentat{msc_version}/bin/mentat')
menu_file = str(msc_root/f'mentat{msc_version}/menus/linux64/main.msb')
os.system(f'xvfb-run {executable} -compile {menu_file}')
print('setting file access rights...\n')
for pattern in [msc_root/f'marc{marc_version}/tools/*damask*',
msc_root/f'mentat{marc_version}/bin/submit?',
msc_root/f'mentat{marc_version}/bin/kill?']:
for pattern in [msc_root/f'marc{msc_version}/tools/*damask*',
msc_root/f'mentat{msc_version}/bin/submit?',
msc_root/f'mentat{msc_version}/bin/kill?']:
for f in glob.glob(str(pattern)):
os.chmod(f,0o755)

12
processing/post/DADF5_postResults.py
View File

@ -20,9 +20,9 @@ parser.add_argument('filenames', nargs='+',
parser.add_argument('-d','--dir', dest='dir',default='postProc',metavar='string',
help='name of subdirectory relative to the location of the DADF5 file to hold output')
parser.add_argument('--mat', nargs='+',
help='labels for materialpoint',dest='mat')
help='labels for homogenization',dest='mat')
parser.add_argument('--con', nargs='+',
help='labels for constituent',dest='con')
help='labels for phase',dest='con')
options = parser.parse_args()
@ -41,15 +41,15 @@ for filename in options.filenames:
table = damask.Table(np.ones(np.product(results.grid),dtype=int)*int(inc[3:]),{'inc':(1,)})\
.add('pos',coords.reshape(-1,3))
results.pick('materialpoints',False)
results.pick('constituents', True)
results.pick('homogenizations',False)
results.pick('phases',True)
for label in options.con:
x = results.get_dataset_location(label)
if len(x) != 0:
table = table.add(label,results.read_dataset(x,0,plain=True).reshape(results.grid.prod(),-1))
results.pick('constituents', False)
results.pick('materialpoints',True)
results.pick('phases',False)
results.pick('homogenizations',True)
for label in options.mat:
x = results.get_dataset_location(label)
if len(x) != 0:

128
processing/post/addCompatibilityMismatch.py
View File

@ -13,85 +13,6 @@ import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def volTetrahedron(coords):
"""
Return the volume of the tetrahedron with given vertices or sides.
If vertices are given they must be in a NumPy array with shape (4,3): the
position vectors of the 4 vertices in 3 dimensions; if the six sides are
given, they must be an array of length 6. If both are given, the sides
will be used in the calculation.
This method implements
Tartaglia's formula using the Cayley-Menger determinant:
|0 1 1 1 1 |
|1 0 s1^2 s2^2 s3^2|
288 V^2 = |1 s1^2 0 s4^2 s5^2|
|1 s2^2 s4^2 0 s6^2|
|1 s3^2 s5^2 s6^2 0 |
where s1, s2, ..., s6 are the tetrahedron side lengths.
from http://codereview.stackexchange.com/questions/77593/calculating-the-volume-of-a-tetrahedron
"""
# The indexes of rows in the vertices array corresponding to all
# possible pairs of vertices
vertex_pair_indexes = np.array(((0, 1), (0, 2), (0, 3),
(1, 2), (1, 3), (2, 3)))
# Get all the squares of all side lengths from the differences between
# the 6 different pairs of vertex positions
vertices = np.concatenate((coords[0],coords[1],coords[2],coords[3])).reshape(4,3)
vertex1, vertex2 = vertex_pair_indexes[:,0], vertex_pair_indexes[:,1]
sides_squared = np.sum((vertices[vertex1] - vertices[vertex2])**2,axis=-1)
# Set up the Cayley-Menger determinant
M = np.zeros((5,5))
# Fill in the upper triangle of the matrix
M[0,1:] = 1
# The squared-side length elements can be indexed using the vertex
# pair indices (compare with the determinant illustrated above)
M[tuple(zip(*(vertex_pair_indexes + 1)))] = sides_squared
# The matrix is symmetric, so we can fill in the lower triangle by
# adding the transpose
M = M + M.T
return np.sqrt(np.linalg.det(M) / 288)
def volumeMismatch(size,F,nodes):
"""
Calculates the volume mismatch.
volume mismatch is defined as the difference between volume of reconstructed
(compatible) cube and determinant of deformation gradient at Fourier point.
"""
coords = np.empty([8,3])
vMismatch = np.empty(F.shape[:3])
#--------------------------------------------------------------------------------------------------
# calculate actual volume and volume resulting from deformation gradient
for k in range(grid[0]):
for j in range(grid[1]):
for i in range(grid[2]):
coords[0,0:3] = nodes[k, j, i ,0:3]
coords[1,0:3] = nodes[k ,j, i+1,0:3]
coords[2,0:3] = nodes[k ,j+1,i+1,0:3]
coords[3,0:3] = nodes[k, j+1,i ,0:3]
coords[4,0:3] = nodes[k+1,j, i ,0:3]
coords[5,0:3] = nodes[k+1,j, i+1,0:3]
coords[6,0:3] = nodes[k+1,j+1,i+1,0:3]
coords[7,0:3] = nodes[k+1,j+1,i ,0:3]
vMismatch[k,j,i] = \
( abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[7,0:3],coords[3,0:3]])) \
+ abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[7,0:3],coords[4,0:3]])) \
+ abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[2,0:3],coords[3,0:3]])) \
+ abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[2,0:3],coords[1,0:3]])) \
+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[5,0:3]])) \
+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[0,0:3]]))) \
/np.linalg.det(F[k,j,i,0:3,0:3])
return vMismatch/(size.prod()/grid.prod())
def shapeMismatch(size,F,nodes,centres):
"""
@ -101,42 +22,23 @@ def shapeMismatch(size,F,nodes,centres):
the corners of reconstructed (combatible) volume element and the vectors calculated by deforming
the initial volume element with the current deformation gradient.
"""
sMismatch = np.empty(F.shape[:3])
#--------------------------------------------------------------------------------------------------
# initial positions
delta = size/grid*.5
coordsInitial = np.vstack((delta * np.array((-1,-1,-1)),
delta * np.array((+1,-1,-1)),
delta * np.array((+1,+1,-1)),
delta * np.array((-1,+1,-1)),
delta * np.array((-1,-1,+1)),
delta * np.array((+1,-1,+1)),
delta * np.array((+1,+1,+1)),
delta * np.array((-1,+1,+1))))
#--------------------------------------------------------------------------------------------------
# compare deformed original and deformed positions to actual positions
for k in range(grid[0]):
for j in range(grid[1]):
for i in range(grid[2]):
sMismatch[k,j,i] = \
+ np.linalg.norm(nodes[k, j, i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[0,0:3]))\
+ np.linalg.norm(nodes[k+1,j, i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[1,0:3]))\
+ np.linalg.norm(nodes[k+1,j+1,i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[2,0:3]))\
+ np.linalg.norm(nodes[k, j+1,i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[3,0:3]))\
+ np.linalg.norm(nodes[k, j, i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[4,0:3]))\
+ np.linalg.norm(nodes[k+1,j, i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[5,0:3]))\
+ np.linalg.norm(nodes[k+1,j+1,i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[6,0:3]))\
+ np.linalg.norm(nodes[k ,j+1,i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[7,0:3]))
return sMismatch
return + np.linalg.norm(nodes[:-1,:-1,:-1] -centres - np.dot(F,delta * np.array((-1,-1,-1))),axis=-1)\
+ np.linalg.norm(nodes[+1:,:-1,:-1] -centres - np.dot(F,delta * np.array((+1,-1,-1))),axis=-1)\
+ np.linalg.norm(nodes[+1:,+1:,:-1] -centres - np.dot(F,delta * np.array((+1,+1,-1))),axis=-1)\
+ np.linalg.norm(nodes[:-1,+1:,:-1] -centres - np.dot(F,delta * np.array((-1,+1,-1))),axis=-1)\
+ np.linalg.norm(nodes[:-1,:-1,+1:] -centres - np.dot(F,delta * np.array((-1,-1,+1))),axis=-1)\
+ np.linalg.norm(nodes[+1:,:-1,+1:] -centres - np.dot(F,delta * np.array((+1,-1,+1))),axis=-1)\
+ np.linalg.norm(nodes[+1:,+1:,+1:] -centres - np.dot(F,delta * np.array((+1,+1,+1))),axis=-1)\
+ np.linalg.norm(nodes[:-1,+1:,+1:] -centres - np.dot(F,delta * np.array((-1,+1,+1))),axis=-1)
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
parser = OptionParser(usage='%prog options [ASCIItable(s)]', description = """
Add column(s) containing the shape and volume mismatch resulting from given deformation gradient.
Operates on periodic three-dimensional x,y,z-ordered data sets.
@ -155,10 +57,6 @@ parser.add_option('--no-shape','-s',
dest = 'shape',
action = 'store_false',
help = 'omit shape mismatch')
parser.add_option('--no-volume','-v',
dest = 'volume',
action = 'store_false',
help = 'omit volume mismatch')
parser.set_defaults(pos = 'pos',
defgrad = 'f',
shape = True,
@ -185,10 +83,4 @@ for name in filenames:
shapeMismatch.reshape(-1,1,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
if options.volume:
volumeMismatch = volumeMismatch(size,F,nodes)
table = table.add('volMismatch(({}))'.format(options.defgrad),
volumeMismatch.reshape(-1,1,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)
table.save((sys.stdout if name is None else name))

2
processing/post/addCurl.py
View File

@ -55,4 +55,4 @@ for name in filenames:
curl.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape),order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)
table.save((sys.stdout if name is None else name))

74
processing/post/addDerivative.py
View File

@ -1,74 +0,0 @@
#!/usr/bin/env python3
import os
import sys
from io import StringIO
from optparse import OptionParser
import numpy as np
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def derivative(coordinates,what):
result = np.empty_like(what)
# use differentiation by interpolation
# as described in http://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf
result[1:-1,:] = + what[1:-1,:] * (2.*coordinates[1:-1]-coordinates[:-2]-coordinates[2:]) / \
((coordinates[1:-1]-coordinates[:-2])*(coordinates[1:-1]-coordinates[2:])) \
+ what[2:,:] * (coordinates[1:-1]-coordinates[:-2]) / \
((coordinates[2:]-coordinates[1:-1])*(coordinates[2:]-coordinates[:-2])) \
+ what[:-2,:] * (coordinates[1:-1]-coordinates[2:]) / \
((coordinates[:-2]-coordinates[1:-1])*(coordinates[:-2]-coordinates[2:])) \
result[0,:] = (what[0,:] - what[1,:]) / \
(coordinates[0] - coordinates[1])
result[-1,:] = (what[-1,:] - what[-2,:]) / \
(coordinates[-1] - coordinates[-2])
return result
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
Add column(s) containing numerical derivative of requested column(s) with respect to given coordinates.
""", version = scriptID)
parser.add_option('-c','--coordinates',
dest = 'coordinates',
type = 'string', metavar='string',
help = 'heading of coordinate column')
parser.add_option('-l','--label',
dest = 'labels',
action = 'extend', metavar = '<string LIST>',
help = 'heading of column(s) to differentiate')
(options,filenames) = parser.parse_args()
if filenames == []: filenames = [None]
if options.coordinates is None:
parser.error('no coordinate column specified.')
if options.labels is None:
parser.error('no data column specified.')
for name in filenames:
damask.util.report(scriptName,name)
table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
for label in options.labels:
table = table.add('d({})/d({})'.format(label,options.coordinates),
derivative(table.get(options.coordinates),table.get(label)),
scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)

6
processing/post/addDisplacement.py
View File

@ -16,7 +16,7 @@ scriptID = ' '.join([scriptName,damask.version])
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
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).
@ -60,7 +60,7 @@ for name in filenames:
.add('fluct({}).{}'.format(options.f,options.pos),
damask.grid_filters.node_displacement_fluct(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'), legacy=True)
.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.cell_displacement_avg(size,F).reshape(-1,3,order='F'),
@ -68,4 +68,4 @@ for name in filenames:
.add('fluct({}).{}'.format(options.f,options.pos),
damask.grid_filters.cell_displacement_fluct(size,F).reshape(-1,3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))\
.save((sys.stdout if name is None else name), legacy=True)
.save((sys.stdout if name is None else name))

2
processing/post/addDivergence.py
View File

@ -55,4 +55,4 @@ for name in filenames:
div.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)//3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)
table.save((sys.stdout if name is None else name))

2
processing/post/addEuclideanDistance.py
View File

@ -184,4 +184,4 @@ for name in filenames:
distance[i,:],
scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)
table.save((sys.stdout if name is None else name))

2
processing/post/addGradient.py
View File

@ -55,4 +55,4 @@ for name in filenames:
grad.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)*3,order='F'),
scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)
table.save((sys.stdout if name is None else name))

150
processing/post/addOrientations.py
View File

@ -1,150 +0,0 @@
#!/usr/bin/env python3
import os
import sys
from io import StringIO
from optparse import OptionParser
import numpy as np
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
Add quaternion and/or Bunge Euler angle representation of crystal lattice orientation.
Orientation is given by quaternion, Euler angles, rotation matrix, or crystal frame coordinates
(i.e. component vectors of rotation matrix).
Additional (globally fixed) rotations of the lab frame and/or crystal frame can be applied.
""", version = scriptID)
representations = ['quaternion', 'rodrigues', 'eulers', 'matrix', 'axisangle']
parser.add_option('-o',
'--output',
dest = 'output',
action = 'extend', metavar = '<string LIST>',
help = 'output orientation formats {{{}}}'.format(', '.join(representations)))
parser.add_option('-d',
'--degrees',
dest = 'degrees',
action = 'store_true',
help = 'all angles in degrees')
parser.add_option('-R',
'--labrotation',
dest='labrotation',
type = 'float', nargs = 4, metavar = ' '.join(['float']*4),
help = 'axis and angle of additional lab frame rotation [%default]')
parser.add_option('-r',
'--crystalrotation',
dest='crystalrotation',
type = 'float', nargs = 4, metavar = ' '.join(['float']*4),
help = 'axis and angle of additional crystal frame rotation [%default]')
parser.add_option('--eulers',
dest = 'eulers',
metavar = 'string',
help = 'Euler angles label')
parser.add_option('--rodrigues',
dest = 'rodrigues',
metavar = 'string',
help = 'Rodrigues vector label')
parser.add_option('--matrix',
dest = 'matrix',
metavar = 'string',
help = 'orientation matrix label')
parser.add_option('--quaternion',
dest = 'quaternion',
metavar = 'string',
help = 'quaternion label')
parser.add_option('-x',
dest = 'x',
metavar = 'string',
help = 'label of lab x vector (expressed in crystal coords)')
parser.add_option('-y',
dest = 'y',
metavar = 'string',
help = 'label of lab y vector (expressed in crystal coords)')
parser.add_option('-z',
dest = 'z',
metavar = 'string',
help = 'label of lab z vector (expressed in crystal coords)')
parser.add_option('--lattice',
dest = 'lattice',
metavar = 'string',
help = 'lattice structure to reduce rotation into fundamental zone')
parser.set_defaults(output = [],
labrotation = (1.,1.,1.,0.), # no rotation about (1,1,1)
crystalrotation = (1.,1.,1.,0.), # no rotation about (1,1,1)
lattice = None,
)
(options, filenames) = parser.parse_args()
if filenames == []: filenames = [None]
if options.output == [] or (not set(options.output).issubset(set(representations))):
parser.error('output must be chosen from {}.'.format(', '.join(representations)))
input = [options.eulers is not None,
options.rodrigues is not None,
options.x is not None and \
options.y is not None and \
options.z is not None,
options.matrix is not None,
options.quaternion is not None,
]
if np.sum(input) != 1: parser.error('needs exactly one input format.')
r = damask.Rotation.from_axis_angle(np.array(options.crystalrotation),options.degrees,normalize=True)
R = damask.Rotation.from_axis_angle(np.array(options.labrotation),options.degrees,normalize=True)
for name in filenames:
damask.util.report(scriptName,name)
table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
if options.eulers is not None:
label = options.eulers
print(np.max(table.get(options.eulers),axis=0))
o = damask.Rotation.from_Eulers(table.get(options.eulers), options.degrees)
elif options.rodrigues is not None:
label = options.rodrigues
o = damask.Rotation.from_Rodrigues(table.get(options.rodrigues))
elif options.matrix is not None:
label = options.matrix
o = damask.Rotation.from_matrix(table.get(options.matrix).reshape(-1,3,3))
elif options.x is not None:
label = '<{},{},{}>'.format(options.x,options.y,options.z)
M = np.block([table.get(options.x),table.get(options.y),table.get(options.z)]).reshape(-1,3,3)
o = damask.Rotation.from_matrix(M/np.linalg.norm(M,axis=0))
elif options.quaternion is not None:
label = options.quaternion
o = damask.Rotation.from_quaternion(table.get(options.quaternion))
o = r.broadcast_to(o.shape) @ o @ R.broadcast_to(o.shape)
#if options.lattice is not None:
# o = damask.Orientation(rotation = o,lattice = options.lattice).reduced().rotation
if 'rodrigues' in options.output:
table = table.add('ro({})'.format(label),o.as_Rodrigues(), scriptID+' '+' '.join(sys.argv[1:]))
if 'eulers' in options.output:
table = table.add('eu({})'.format(label),o.as_Eulers(options.degrees), scriptID+' '+' '.join(sys.argv[1:]))
if 'quaternion' in options.output:
table = table.add('qu({})'.format(label),o.as_quaternion(), scriptID+' '+' '.join(sys.argv[1:]))
if 'matrix' in options.output:
table = table.add('om({})'.format(label),o.as_matrix(), scriptID+' '+' '.join(sys.argv[1:]))
if 'axisangle' in options.output:
table = table.add('om({})'.format(label),o.as_axisangle(options.degrees), scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)

89
processing/post/addSchmidfactors.py
View File

@ -14,91 +14,16 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
slipSystems = {
'fcc':
np.array([
[+0,+1,-1 , +1,+1,+1],
[-1,+0,+1 , +1,+1,+1],
[+1,-1,+0 , +1,+1,+1],
[+0,-1,-1 , -1,-1,+1],
[+1,+0,+1 , -1,-1,+1],
[-1,+1,+0 , -1,-1,+1],
[+0,-1,+1 , +1,-1,-1],
[-1,+0,-1 , +1,-1,-1],
[+1,+1,+0 , +1,-1,-1],
[+0,+1,+1 , -1,+1,-1],
[+1,+0,-1 , -1,+1,-1],
[-1,-1,+0 , -1,+1,-1],
],'d'),
'bcc':
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],
[-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 , +2,+1,+1],
[+1,+1,+1 , -2,+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,+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,-1,+2],
[+1,+1,+1 , +1,+1,-2],
],'d'),
'hex':
np.array([
[+2,-1,-1,+0 , +0,+0,+0,+1],
[-1,+2,-1,+0 , +0,+0,+0,+1],
[-1,-1,+2,+0 , +0,+0,+0,+1],
[+2,-1,-1,+0 , +0,+1,-1,+0],
[-1,+2,-1,+0 , -1,+0,+1,+0],
[-1,-1,+2,+0 , +1,-1,+0,+0],
[-1,+1,+0,+0 , +1,+1,-2,+0],
[+0,-1,+1,+0 , -2,+1,+1,+0],
[+1,+0,-1,+0 , +1,-2,+1,+0],
[-1,+2,-1,+0 , +1,+0,-1,+1],
[-2,+1,+1,+0 , +0,+1,-1,+1],
[-1,-1,+2,+0 , -1,+1,+0,+1],
[+1,-2,+1,+0 , -1,+0,+1,+1],
[+2,-1,-1,+0 , +0,-1,+1,+1],
[+1,+1,-2,+0 , +1,-1,+0,+1],
[-2,+1,+1,+3 , +1,+0,-1,+1],
[-1,-1,+2,+3 , +1,+0,-1,+1],
[-1,-1,+2,+3 , +0,+1,-1,+1],
[+1,-2,+1,+3 , +0,+1,-1,+1],
[+1,-2,+1,+3 , -1,+1,+0,+1],
[+2,-1,-1,+3 , -1,+1,+0,+1],
[+2,-1,-1,+3 , -1,+0,+1,+1],
[+1,+1,-2,+3 , -1,+0,+1,+1],
[+1,+1,-2,+3 , +0,-1,+1,+1],
[-1,+2,-1,+3 , +0,-1,+1,+1],
[-1,+2,-1,+3 , +1,-1,+0,+1],
[-2,+1,+1,+3 , +1,-1,+0,+1],
[-1,-1,+2,+3 , +1,+1,-2,+2],
[+1,-2,+1,+3 , -1,+2,-1,+2],
[+2,-1,-1,+3 , -2,+1,+1,+2],
[+1,+1,-2,+3 , -1,-1,+2,+2],
[-1,+2,-1,+3 , +1,-2,+1,+2],
[-2,+1,+1,+3 , +2,-1,-1,+2],
],'d'),
'fcc': damask.lattice.kinematics['cF']['slip'][:12],
'bcc': damask.lattice.kinematics['cI']['slip'],
'hex': damask.lattice.kinematics['hP']['slip'],
}
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
parser = OptionParser(usage='%prog options [ASCIItable(s)]', description = """
Add columns listing Schmid factors (and optional trace vector of selected system) for given Euler angles.
""", version = scriptID)
@ -156,11 +81,11 @@ elif options.lattice == 'hex':
# convert 4 Miller index notation of hex to orthogonal 3 Miller index notation
for i in range(len(slip_direction)):
slip_direction[i] = np.array([slipSystems['hex'][i,0]*1.5,
(slipSystems['hex'][i,0] + 2.*slipSystems['hex'][i,1])*0.5*np.sqrt(3),
(slipSystems['hex'][i,0] + 2.*slipSystems['hex'][i,1])*0.5*np.sqrt(3),
slipSystems['hex'][i,3]*options.CoverA,
])
slip_normal[i] = np.array([slipSystems['hex'][i,4],
(slipSystems['hex'][i,4] + 2.*slipSystems['hex'][i,5])/np.sqrt(3),
(slipSystems['hex'][i,4] + 2.*slipSystems['hex'][i,5])/np.sqrt(3),
slipSystems['hex'][i,7]/options.CoverA,
])
@ -189,4 +114,4 @@ for name in filenames:
for i,label in enumerate(labels):
table = table.add(label,S[:,i],scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)
table.save((sys.stdout if name is None else name))

61
processing/post/permuteData.py
View File

@ -1,61 +0,0 @@
#!/usr/bin/env python3
import os
import sys
from io import StringIO
from optparse import OptionParser
import numpy as np
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
Permute all values in given column(s).
""", version = scriptID)
parser.add_option('-l','--label',
dest = 'label',
action = 'extend', metavar = '<string LIST>',
help ='column(s) to permute')
parser.add_option('-u', '--unique',
dest = 'unique',
action = 'store_true',
help = 'shuffle unique values as group')
parser.add_option('-r', '--rnd',
dest = 'randomSeed',
type = 'int', metavar = 'int',
help = 'seed of random number generator [%default]')
parser.set_defaults(label = [],
unique = False,
randomSeed = None,
)
(options,filenames) = parser.parse_args()
if filenames == []: filenames = [None]
for name in filenames:
damask.util.report(scriptName,name)
table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
randomSeed = int(os.urandom(4).hex(), 16) if options.randomSeed is None else options.randomSeed # random seed per file
rng = np.random.default_rng(randomSeed)
for label in options.label:
data = table.get(label)
uniques,inverse = np.unique(data,return_inverse=True,axis=0) if options.unique else (data,np.arange(len(data)))
rng.shuffle(uniques)
table = table.set(label,uniques[inverse], scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name), legacy=True)

2
processing/pre/geom_fromDREAM3D.py
View File

@ -14,7 +14,7 @@ scriptID = ' '.join([scriptName,damask.version])
# MAIN
#--------------------------------------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [DREAM.3Dfile(s)]', description = """
parser = OptionParser(usage='%prog options [DREAM.3Dfile(s)]', description = """
Converts DREAM.3D file. Input can be cell data (direct pointwise takeover) or grain data (individual
grains are segmented). Requires orientation data as quaternion.

69
processing/pre/geom_fromMinimalSurface.py
View File

@ -1,69 +0,0 @@
#!/usr/bin/env python3
import os
import sys
from optparse import OptionParser
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
minimal_surfaces = list(damask.Geom._minimal_surface.keys())
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [geomfile]', description = """
Generate a bicontinuous structure of given type.
""", version = scriptID)
parser.add_option('-t','--type',
dest = 'type',
choices = minimal_surfaces, metavar = 'string',
help = 'type of minimal surface [primitive] {%s}' %(','.join(minimal_surfaces)))
parser.add_option('-f','--threshold',
dest = 'threshold',
type = 'float', metavar = 'float',
help = 'threshold value defining minimal surface [%default]')
parser.add_option('-g', '--grid',
dest = 'grid',
type = 'int', nargs = 3, metavar = 'int int int',
help = 'a,b,c grid of hexahedral box [%default]')
parser.add_option('-s', '--size',
dest = 'size',
type = 'float', nargs = 3, metavar = 'float float float',
help = 'x,y,z size of hexahedral box [%default]')
parser.add_option('-p', '--periods',
dest = 'periods',
type = 'int', metavar = 'int',
help = 'number of repetitions of unit cell [%default]')
parser.add_option('--m',
dest = 'microstructure',
type = 'int', nargs = 2, metavar = 'int int',
help = 'two microstructure indices to be used [%default]')
parser.set_defaults(type = minimal_surfaces[0],
threshold = 0.0,
periods = 1,
grid = (16,16,16),
size = (1.0,1.0,1.0),
microstructure = (1,2),
)
(options,filename) = parser.parse_args()
name = None if filename == [] else filename[0]
damask.util.report(scriptName,name)
geom=damask.Geom.from_minimal_surface(options.grid,options.size,options.type,options.threshold,
options.periods,options.microstructure)
damask.util.croak(geom)
geom.save_ASCII(sys.stdout if name is None else name)

2
processing/pre/geom_fromOsteonGeometry.py
View File

@ -17,7 +17,7 @@ scriptID = ' '.join([scriptName,damask.version])
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [geomfile]', description = """
parser = OptionParser(usage='%prog options [geomfile]', description = """
Generate description of an osteon enclosing the Harvesian canal and separated by interstitial tissue.
The osteon phase is lamellar with a twisted plywood structure.
Its fiber orientation is oscillating by +/- amplitude within one period.

57
processing/pre/geom_fromTable.py
View File

@ -1,57 +0,0 @@
#!/usr/bin/env python3
import os
import sys
from optparse import OptionParser
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
Converts ASCII table. Input can be microstructure or orientation (as quaternion). For the latter,
phase information can be given additionally.
""", version = scriptID)
parser.add_option('--coordinates',
dest = 'pos',
type = 'string', metavar = 'string',
help = 'coordinates label (%default)')
parser.add_option('--phase',
dest = 'phase',
type = 'string', metavar = 'string',
help = 'phase label')
parser.add_option('--microstructure',
dest = 'microstructure',
type = 'string', metavar = 'string',
help = 'microstructure label')
parser.add_option('-q', '--quaternion',
dest = 'quaternion',
type = 'string', metavar='string',
help = 'quaternion label')
parser.set_defaults(pos= 'pos')
(options,filenames) = parser.parse_args()
if filenames == []: filenames = [None]
for name in filenames:
damask.util.report(scriptName,name)
labels = []
for l in [options.quaternion,options.phase,options.microstructure]:
if l is not None: labels.append(l)
t = damask.Table.load(name)
geom = damask.Geom.from_table(t,options.pos,labels)
damask.util.croak(geom)
geom.save_ASCII(sys.stdout if name is None else os.path.splitext(name)[0]+'.geom')

8
processing/pre/geom_grainGrowth.py
View File

@ -15,8 +15,8 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
getInterfaceEnergy = lambda A,B: np.float32((A*B != 0)*(A != B)*1.0) # 1.0 if A & B are distinct & nonzero, 0.0 otherwise
struc = ndimage.generate_binary_structure(3,1) # 3D von Neumann neighborhood
getInterfaceEnergy = lambda A,B: np.float32((A != B)*1.0) # 1.0 if A & B are distinct, 0.0 otherwise
struc = ndimage.generate_binary_structure(3,1) # 3D von Neumann neighborhood
#--------------------------------------------------------------------------------------------------
@ -62,7 +62,7 @@ if filenames == []: filenames = [None]
for name in filenames:
damask.util.report(scriptName,name)
geom = damask.Geom.load_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
geom = damask.Geom.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
grid_original = geom.grid
damask.util.croak(geom)
@ -174,4 +174,4 @@ for name in filenames:
origin = geom.origin,
comments = geom.comments + [scriptID + ' ' + ' '.join(sys.argv[1:])],
)\
.save_ASCII(sys.stdout if name is None else name)
.save(sys.stdout if name is None else name)

41
processing/pre/mentat_pbcOnBoxMesh.py
View File

@ -11,8 +11,6 @@ import numpy as np
import damask
sys.path.append(str(damask.solver.Marc().library_path))
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
@ -30,11 +28,11 @@ def parseMFD(dat):
# lines that start with a space are numerical data
if line[0] == ' ':
formatted[section]['els'].append([])
# grab numbers
nums = re.split(r'\s+', line.strip())
for num in nums:
for num in nums:
# floating point has format ' -x.xxxxxxxxxxxxe+yy'
# scientific notation is used for float
if (len(num) >= 4) and (num[-4] == 'e'):
@ -47,7 +45,7 @@ def parseMFD(dat):
else:
formatted[section]['els'].append([])
formatted[section]['els'][-1] = line
else: # Not in a section, we are looking for a =beg= now
search = re.search(r'=beg=\s+(\d+)\s\((.*?)\)', line)
if search is not None: # found start of a new section
@ -60,7 +58,7 @@ def parseMFD(dat):
section += 1
formatted.append({'label': '', 'uid': -2, 'els': []}) # make dummy section to store unrecognized data
formatted[section]['els'].append(line)
return formatted
def asMFD(mfd_data):
@ -93,14 +91,14 @@ def add_servoLinks(mfd_data,active=[True,True,True]): # directions on which to
'max': np.zeros(3,dtype='d'),
'delta': np.zeros(3,dtype='d'),
}
mfd_dict = {}
for i in range(len(mfd_data)):
mfd_dict[mfd_data[i]['label']] = i
NodeCoords = np.array(mfd_data[mfd_dict['nodes']]['els'][1::4])[:,1:4]
Nnodes = NodeCoords.shape[0]
Nnodes = NodeCoords.shape[0]
box['min'] = NodeCoords.min(axis=0) # find the bounding box
box['max'] = NodeCoords.max(axis=0)
box['delta'] = box['max']-box['min']
@ -131,7 +129,7 @@ def add_servoLinks(mfd_data,active=[True,True,True]): # directions on which to
elif (key[base[coord]] == "%.8e"%box['max'][coord]): # compare to max of bounding box (i.e. is on outer face?)
Nmax += 1 # count outer (front) face membership
maxFlag[coord] = True # remember face membership (for linked nodes)
if Nmin > 0: # node is on a back face
# prepare for any non-existing entries in the data structure
if key['x'] not in baseNode.keys():
@ -140,17 +138,17 @@ def add_servoLinks(mfd_data,active=[True,True,True]): # directions on which to
baseNode[key['x']][key['y']] = {}
if key['z'] not in baseNode[key['x']][key['y']].keys():
baseNode[key['x']][key['y']][key['z']] = 0
baseNode[key['x']][key['y']][key['z']] = node+1 # remember the base node id
if Nmax > 0 and Nmax >= Nmin: # node is on at least as many front than back faces
if any([maxFlag[i] and active[i] for i in range(3)]):
linkNodes.append({'id': node+1,'coord': NodeCoords[node], 'faceMember': [maxFlag[i] and active[i] for i in range(3)]})
mfd_data[mfd_dict['entities']]['els'][0][0] += len(linkNodes) * 3
baseCorner = baseNode["%.8e"%box['min'][0]]["%.8e"%box['min'][1]]["%.8e"%box['min'][2]] # detect ultimate base node
links = {'uid': 1705, 'label': 'links', 'els': [[7,0],[9,0]]}
linkID = 0
for node in linkNodes: # loop over all linked nodes
@ -165,7 +163,7 @@ def add_servoLinks(mfd_data,active=[True,True,True]): # directions on which to
for dof in [1,2,3]:
tied_node = node['id']
nterms = 1 + nLinks
linkID += 1
# Link header
links['els'].append('link{0}\n'.format(linkID))
@ -173,10 +171,10 @@ def add_servoLinks(mfd_data,active=[True,True,True]): # directions on which to
links['els'].append([0])
links['els'].append([0])
links['els'].append([0, 0, 0, tied_node])
# these need to be put in groups of four
link_payload = [dof, 0, nterms]
# Individual node contributions (node, dof, coef.)
for i in range(nterms):
if i == nLinks:
@ -190,7 +188,7 @@ def add_servoLinks(mfd_data,active=[True,True,True]): # directions on which to
link_payload.append(1.0 - nLinks)
else:
link_payload.append(1.0)
# Needs to be formatted 4 data points per row, character width of 20, so 80 total
for j in range(0, len(link_payload), 4):
links['els'].append(link_payload[j:j+4])
@ -206,9 +204,9 @@ def add_servoLinks(mfd_data,active=[True,True,True]): # directions on which to
#--------------------------------------------------------------------------------------------------
# MAIN
#--------------------------------------------------------------------------------------------------
#--------------------------------------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
parser = OptionParser(usage='%prog options [file[s]]', description = """
Set up servo linking to achieve periodic boundary conditions for a regular hexahedral mesh.
Use *py_connection to operate on model presently opened in MSC.Mentat.
""", version = scriptID)
@ -235,6 +233,7 @@ if remote and filenames != []:
if filenames == []: filenames = [None]
if remote:
sys.path.append(str(damask.solver.Marc().library_path))
import py_mentat
damask.util.report(scriptName, 'waiting to connect...')

8
processing/pre/mentat_spectralBox.py
View File

@ -9,7 +9,6 @@ import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
sys.path.append(str(damask.solver.Marc().library_path))
#-------------------------------------------------------------------------------------------------
def outMentat(cmd,locals):
@ -168,7 +167,7 @@ def initial_conditions(material):
# MAIN
#--------------------------------------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
parser = OptionParser(usage='%prog options [file[s]]', description = """
Generate MSC.Marc FE hexahedral mesh from geom file.
""", version = scriptID)
@ -185,9 +184,10 @@ parser.set_defaults(port = None,
if options.port is not None:
try:
sys.path.append(str(damask.solver.Marc().library_path))
import py_mentat
except ImportError:
parser.error('no valid Mentat release found.')
parser.error('no valid Mentat release found')
# --- loop over input files ------------------------------------------------------------------------
@ -196,7 +196,7 @@ if filenames == []: filenames = [None]
for name in filenames:
damask.util.report(scriptName,name)
geom = damask.Geom.load_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
geom = damask.Geom.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
material = geom.material.flatten(order='F')
cmds = [\

2
processing/pre/seeds_fromDistribution.py
View File

@ -164,7 +164,7 @@ class myThread (threading.Thread):
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
parser = OptionParser(usage='%prog options [file[s]]', description = """
Monte Carlo simulation to produce seed file that gives same size distribution like given geometry file.
""", version = scriptID)

2
processing/pre/seeds_fromPokes.py
View File

@ -16,7 +16,7 @@ scriptID = ' '.join([scriptName,damask.version])
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
parser = OptionParser(usage='%prog options [file[s]]', description = """
Create seeds file by poking at 45 degree through given geom file.
Mimics APS Beamline 34-ID-E DAXM poking.

17
python/damask/__init__.py
View File

@ -1,4 +1,12 @@
"""Tools for pre and post processing of DAMASK simulations."""
"""
Tools for pre and post processing of DAMASK simulations.
Modules that contain only one class (of the same name),
are prefixed by a '_'. For example, '_colormap' contains
a class called 'Colormap' which is imported as 'damask.Colormap'.
"""
from pathlib import Path as _Path
import re as _re
@ -12,15 +20,16 @@ from ._environment import Environment as _ # noqa
environment = _()
from . import util # noqa
from . import seeds # noqa
from . import tensor # noqa
from . import mechanics # noqa
from . import solver # noqa
from . import grid_filters # noqa
from ._lattice import Symmetry, Lattice# noqa
from ._table import Table # noqa
from . import lattice # noqa
from ._rotation import Rotation # noqa
from ._orientation import Orientation # noqa
from ._table import Table # noqa
from ._vtk import VTK # noqa
from ._colormap import Colormap # noqa
from ._orientation import Orientation # noqa
from ._config import Config # noqa
from ._configmaterial import ConfigMaterial # noqa
from ._geom import Geom # noqa

35
python/damask/_asciitable.py
View File

@ -385,38 +385,3 @@ class ASCIItable():
self.data = np.loadtxt(self.__IO__['in'],usecols=use,ndmin=2)
return labels_missing
# ------------------------------------------------------------------
def data_write(self):
"""Write current data array and report alive output back."""
if len(self.data) == 0: return True
if isinstance(self.data[0],list):
return self.output_write(['\t'.join(map(self._quote,items)) for items in self.data])
else:
return self.output_write( '\t'.join(map(self._quote,self.data)))
# ------------------------------------------------------------------
def data_writeArray(self):
"""Write whole numpy array data."""
for row in self.data:
try:
output = list(map(repr,row))
except Exception:
output = [repr(row)]
try:
self.__IO__['out'].write('\t'.join(output) + '\n')
except Exception:
pass
# ------------------------------------------------------------------
def data_append(self,
what):
if isinstance(what, str):
self.data += [what]
else:
try:
for item in what: self.data_append(item)
except TypeError:
self.data += [str(what)]

168
python/damask/_colormap.py
View File

@ -22,6 +22,19 @@ _ref_white = np.array([.95047, 1.00000, 1.08883])
# - support NaN color (paraview)
class Colormap(mpl.colors.ListedColormap):
"""
Enhance matplotlib colormap functionality to be used within DAMASK.
References
----------
[1] DAMASK colormap theory
https://www.kennethmoreland.com/color-maps/ColorMapsExpanded.pdf
[2] DAMASK colormaps first use
https://doi.org/10.1016/j.ijplas.2012.09.012
[3] Matplotlib colormaps overview
https://matplotlib.org/tutorials/colors/colormaps.html
"""
def __add__(self,other):
"""Concatenate colormaps."""
@ -36,6 +49,17 @@ class Colormap(mpl.colors.ListedColormap):
"""Return inverted colormap."""
return self.reversed()
def __repr__(self):
"""Show colormap as matplotlib figure."""
fig = plt.figure(self.name,figsize=(5,.5))
ax1 = fig.add_axes([0, 0, 1, 1])
ax1.set_axis_off()
ax1.imshow(np.linspace(0,1,self.N).reshape(1,-1),
aspect='auto', cmap=self, interpolation='nearest')
plt.show(block = False)
return self.name
@staticmethod
def from_range(low,high,name='DAMASK colormap',N=256,model='rgb'):
"""
@ -126,40 +150,16 @@ class Colormap(mpl.colors.ListedColormap):
"""
# matplotlib presets
for cat in Colormap._predefined_mpl:
for n in cat[1]:
if n == name:
colormap = cm.__dict__[name]
if isinstance(colormap,mpl.colors.LinearSegmentedColormap):
return Colormap(np.array(list(map(colormap,np.linspace(0,1,N)))),name=name)
else:
return Colormap(np.array(colormap.colors),name=name)
# DAMASK presets
definition = Colormap._predefined_DAMASK[name]
return Colormap.from_range(definition['low'],definition['high'],name,N)
@staticmethod
def list_predefined():
"""
List predefined colormaps by category.
References
----------
[1] DAMASK colormap theory
https://www.kennethmoreland.com/color-maps/ColorMapsExpanded.pdf
[2] DAMASK colormaps first use
https://doi.org/10.1016/j.ijplas.2012.09.012
[3] Matplotlib colormaps overview
https://matplotlib.org/tutorials/colors/colormaps.html
"""
print('DAMASK colormaps')
print(' '+', '.join(Colormap._predefined_DAMASK.keys()))
for cat in Colormap._predefined_mpl:
print(f'{cat[0]}')
print(' '+', '.join(cat[1]))
try:
colormap = cm.__dict__[name]
return Colormap(np.array(list(map(colormap,np.linspace(0,1,N)))
if isinstance(colormap,mpl.colors.LinearSegmentedColormap) else
colormap.colors),
name=name)
except KeyError:
# DAMASK presets
definition = Colormap._predefined_DAMASK[name]
return Colormap.from_range(definition['low'],definition['high'],name,N)
def shade(self,field,bounds=None,gap=None):
@ -168,9 +168,9 @@ class Colormap(mpl.colors.ListedColormap):
Parameters
----------
field : numpy.array of shape(:,:)
field : numpy.array of shape (:,:)
Data to be shaded.
bounds : iterable of len(2), optional
bounds : iterable of len (2), optional
Colormap value range (low,high).
gap : field.dtype, optional
Transparent value. NaN will always be rendered transparent.
@ -203,18 +203,6 @@ class Colormap(mpl.colors.ListedColormap):
mode='RGBA')
def show(self,aspect=10,vertical=False):
"""Show colormap as matplotlib figure."""
fig = plt.figure(figsize=(5/aspect,5) if vertical else (5,5/aspect))
ax1 = fig.add_axes([0, 0, 1, 1])
ax1.set_axis_off()
ax1.imshow(np.linspace(1 if vertical else 0,
0 if vertical else 1,
self.N).reshape((-1,1) if vertical else (1,-1)),
aspect='auto', cmap=self, interpolation='nearest')
plt.show()
def reversed(self,name=None):
"""
Make a reversed instance of the colormap.
@ -235,7 +223,6 @@ class Colormap(mpl.colors.ListedColormap):
return Colormap(np.array(rev.colors),rev.name[:-4] if rev.name.endswith('_r_r') else rev.name)
def save_paraview(self,fname=None):
"""
Write colormap to JSON file for Paraview.
@ -247,13 +234,13 @@ class Colormap(mpl.colors.ListedColormap):
consist of the name of the colormap and extension '.json'.
"""
if fname is not None:
if fname is None:
fhandle = None
else:
try:
fhandle = open(fname,'w')
except TypeError:
fhandle = fname
else:
fhandle = None
colors = []
for i,c in enumerate(np.round(self.colors,6).tolist()):
@ -266,11 +253,9 @@ class Colormap(mpl.colors.ListedColormap):
'DefaultMap':True,
'RGBPoints':colors
}]
if fhandle is None:
with open(self.name.replace(' ','_')+'.json', 'w') as f:
json.dump(out, f,indent=4)
else:
json.dump(out,fhandle,indent=4)
with open(self.name.replace(' ','_')+'.json', 'w') if fhandle is None else fhandle as f:
json.dump(out, f,indent=4)
def save_ASCII(self,fname=None):
@ -284,22 +269,19 @@ class Colormap(mpl.colors.ListedColormap):
consist of the name of the colormap and extension '.txt'.
"""
if fname is not None:
if fname is None:
fhandle = None
else:
try:
fhandle = open(fname,'w')
except TypeError:
fhandle = fname
else:
fhandle = None
labels = {'RGBA':4} if self.colors.shape[1] == 4 else {'RGB': 3}
t = Table(self.colors,labels,f'Creator: {util.execution_stamp("Colormap")}')
if fhandle is None:
with open(self.name.replace(' ','_')+'.txt', 'w') as f:
t.save(f)
else:
t.save(fhandle)
with open(self.name.replace(' ','_')+'.txt', 'w') if fhandle is None else fhandle as f:
t.save(f)
def save_GOM(self,fname=None):
@ -313,24 +295,21 @@ class Colormap(mpl.colors.ListedColormap):
consist of the name of the colormap and extension '.legend'.
"""
if fname is not None:
if fname is None:
fhandle = None
else:
try:
fhandle = open(fname,'w')
except TypeError:
fhandle = fname
else:
fhandle = None
# ToDo: test in GOM
GOM_str = '1 1 {name} 9 {name} '.format(name=self.name.replace(" ","_")) \
+ '0 1 0 3 0 0 -1 9 \\ 0 0 0 255 255 255 0 0 255 ' \
+ f'30 NO_UNIT 1 1 64 64 64 255 1 0 0 0 0 0 0 3 0 {len(self.colors)}' \
+ ' '.join([f' 0 {c[0]} {c[1]} {c[2]} 255 1' for c in reversed((self.colors*255).astype(int))]) \
+ '\n'
if fhandle is None:
with open(self.name.replace(' ','_')+'.legend', 'w') as f:
f.write(GOM_str)
else:
fhandle.write(GOM_str)
with open(self.name.replace(' ','_')+'.legend', 'w') if fhandle is None else fhandle as f:
f.write(GOM_str)
def save_gmsh(self,fname=None):
@ -344,22 +323,19 @@ class Colormap(mpl.colors.ListedColormap):
consist of the name of the colormap and extension '.msh'.
"""
if fname is not None:
if fname is None:
fhandle = None
else:
try:
fhandle = open(fname,'w')
except TypeError:
fhandle = fname
else:
fhandle = None
# ToDo: test in gmsh
gmsh_str = 'View.ColorTable = {\n' \
+'\n'.join([f'{c[0]},{c[1]},{c[2]},' for c in self.colors[:,:3]*255]) \
+'\n}\n'
if fhandle is None:
with open(self.name.replace(' ','_')+'.msh', 'w') as f:
f.write(gmsh_str)
else:
fhandle.write(gmsh_str)
with open(self.name.replace(' ','_')+'.msh', 'w') if fhandle is None else fhandle as f:
f.write(gmsh_str)
@staticmethod
@ -387,7 +363,6 @@ class Colormap(mpl.colors.ListedColormap):
if msh_sat[2] < - np.pi/3.0: hSpin *= -1.0
return msh_sat[2] + hSpin
lo = np.array(low)
hi = np.array(high)
@ -407,28 +382,28 @@ class Colormap(mpl.colors.ListedColormap):
return (1.0 - frac) * lo + frac * hi
_predefined_mpl= [('Perceptually Uniform Sequential', [
'viridis', 'plasma', 'inferno', 'magma', 'cividis']),
('Sequential', [
_predefined_mpl= {'Perceptually Uniform Sequential': [
'viridis', 'plasma', 'inferno', 'magma', 'cividis'],
'Sequential': [
'Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds',
'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu',
'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn']),
('Sequential (2)', [
'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn'],
'Sequential (2)': [
'binary', 'gist_yarg', 'gist_gray', 'gray', 'bone', 'pink',
'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia',
'hot', 'afmhot', 'gist_heat', 'copper']),
('Diverging', [
'hot', 'afmhot', 'gist_heat', 'copper'],
'Diverging': [
'PiYG', 'PRGn', 'BrBG', 'PuOr', 'RdGy', 'RdBu',
'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic']),
('Cyclic', ['twilight', 'twilight_shifted', 'hsv']),
('Qualitative', [
'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic'],
'Cyclic': ['twilight', 'twilight_shifted', 'hsv'],
'Qualitative': [
'Pastel1', 'Pastel2', 'Paired', 'Accent',
'Dark2', 'Set1', 'Set2', 'Set3',
'tab10', 'tab20', 'tab20b', 'tab20c']),
('Miscellaneous', [
'tab10', 'tab20', 'tab20b', 'tab20c'],
'Miscellaneous': [
'flag', 'prism', 'ocean', 'gist_earth', 'terrain', 'gist_stern',
'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg',
'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar'])]
'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar']}
_predefined_DAMASK = {'orientation': {'low': [0.933334,0.878432,0.878431],
'high': [0.250980,0.007843,0.000000]},
@ -437,6 +412,9 @@ class Colormap(mpl.colors.ListedColormap):
'stress': {'low': [0.878432,0.874511,0.949019],
'high': [0.000002,0.000000,0.286275]}}
predefined = dict(**{'DAMASK':list(_predefined_DAMASK)},**_predefined_mpl)
@staticmethod
def _hsv2rgb(hsv):
"""

21
python/damask/_config.py
View File

@ -1,6 +1,7 @@
from io import StringIO
import abc
import numpy as np
import yaml
class NiceDumper(yaml.SafeDumper):
@ -15,6 +16,11 @@ class NiceDumper(yaml.SafeDumper):
def increase_indent(self, flow=False, indentless=False):
return super().increase_indent(flow, False)
def represent_data(self, data):
"""Cast Config objects and its subclasses to dict."""
return self.represent_data(dict(data)) if isinstance(data, dict) and type(data) != dict else \
super().represent_data(data)
class Config(dict):
"""YAML-based configuration."""
@ -64,7 +70,20 @@ class Config(dict):
kwargs['width'] = 256
if 'default_flow_style' not in kwargs:
kwargs['default_flow_style'] = None
fhandle.write(yaml.dump(dict(self),Dumper=NiceDumper,**kwargs))
if 'sort_keys' not in kwargs:
kwargs['sort_keys'] = False
def array_representer(dumper, data):
"""Convert numpy array to list of native types."""
return dumper.represent_list([d.item() for d in data])
NiceDumper.add_representer(np.ndarray, array_representer)
try:
fhandle.write(yaml.dump(self,Dumper=NiceDumper,**kwargs))
except TypeError: # compatibility with old pyyaml
del kwargs['sort_keys']
fhandle.write(yaml.dump(self,Dumper=NiceDumper,**kwargs))
@property

86
python/damask/_configmaterial.py
View File

@ -2,10 +2,9 @@ import copy
import numpy as np
from . import grid_filters
from . import Config
from . import Lattice
from . import Rotation
from . import Orientation
class ConfigMaterial(Config):
"""Material configuration."""
@ -25,8 +24,22 @@ class ConfigMaterial(Config):
super().save(fname,**kwargs)
@classmethod
def load(cls,fname='material.yaml'):
"""
Load from yaml file.
Parameters
----------
fname : file, str, or pathlib.Path, optional
Filename or file for writing. Defaults to 'material.yaml'.
"""
return super(ConfigMaterial,cls).load(fname)
@staticmethod
def from_table(table,coordinates=None,constituents={},**kwargs):
def from_table(table,constituents={},**kwargs):
"""
Load from an ASCII table.
@ -34,10 +47,6 @@ class ConfigMaterial(Config):
----------
table : damask.Table
Table that contains material information.
coordinates : str, optional
Label of spatial coordiates. Used for sorting and performing a
sanity check. Default to None, in which case no sorting or checking is
peformed.
constituents : dict, optional
Entries for 'constituents'. The key is the name and the value specifies
the label of the data column in the table
@ -54,7 +63,7 @@ class ConfigMaterial(Config):
pos pos pos qu qu qu qu phase homog
0 0 0 0 0.19 0.8 0.24 -0.51 Aluminum SX
1 1 0 0 0.8 0.19 0.24 -0.51 Steel SX
>>> cm.from_table(t,'pos',{'O':'qu','phase':'phase'},homogenization='homog')
>>> cm.from_table(t,{'O':'qu','phase':'phase'},homogenization='homog')
material:
- constituents:
- O: [0.19, 0.8, 0.24, -0.51]
@ -68,19 +77,14 @@ class ConfigMaterial(Config):
homogenization: SX
"""
if coordinates is not None:
t = table.sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
grid_filters.coord0_check(t.get(coordinates))
else:
t = table
constituents_ = {k:t.get(v) for k,v in constituents.items()}
kwargs_ = {k:t.get(v) for k,v in kwargs.items()}
constituents_ = {k:table.get(v) for k,v in constituents.items()}
kwargs_ = {k:table.get(v) for k,v in kwargs.items()}
_,idx = np.unique(np.hstack(list({**constituents_,**kwargs_}.values())),return_index=True,axis=0)
constituents_ = {k:v[idx].squeeze() for k,v in constituents_.items()}
kwargs_ = {k:v[idx].squeeze() for k,v in kwargs_.items()}
idx = np.sort(idx)
constituents_ = {k:np.atleast_1d(v[idx].squeeze()) for k,v in constituents_.items()}
kwargs_ = {k:np.atleast_1d(v[idx].squeeze()) for k,v in kwargs_.items()}
return ConfigMaterial().material_add(constituents_,**kwargs_)
@ -148,7 +152,7 @@ class ConfigMaterial(Config):
for k,v in self['phase'].items():
if 'lattice' in v:
try:
Lattice(v['lattice'])
Orientation(lattice=v['lattice'])
except KeyError:
s = v['lattice']
print(f"Invalid lattice: '{s}' in phase '{k}'")
@ -222,26 +226,25 @@ class ConfigMaterial(Config):
return dup
def material_add(self,constituents,**kwargs):
def material_add(self,constituents=None,**kwargs):
"""
Add material entries.
Parameters
----------
constituents : dict
Entries for 'constituents'. The key is the name and the value specifies
the label of the data column in the table
constituents : dict, optional
Entries for 'constituents' as key-value pair.
**kwargs
Keyword arguments where the key is the name and the value specifies
the label of the data column in the table
Key-value pairs.
Examples
--------
>>> import damask
>>> m = damask.ConfigMaterial()
>>> O = damask.Rotation.from_random(3).as_quaternion()
>>> phase = ['Aluminum','Steel','Aluminum']
>>> m.material_add(constituents={'phase':phase,'O':O},homogenization='SX')
>>> m = damask.ConfigMaterial().material_add(constituents={'phase':phase,'O':O},
... homogenization='SX')
>>> m
material:
- constituents:
- O: [0.577764, -0.146299, -0.617669, 0.513010]
@ -260,19 +263,31 @@ class ConfigMaterial(Config):
homogenization: SX
"""
c = [{'constituents':u} for u in ConfigMaterial._constituents(**constituents)]
length = -1
for v in kwargs.values():
if hasattr(v,'__len__') and not isinstance(v,str):
if length != -1 and len(v) != length:
raise ValueError('Cannot add entries of different length')
else:
length = len(v)
length = max(1,length)
c = [{} for _ in range(length)] if constituents is None else \
[{'constituents':u} for u in ConfigMaterial._constituents(**constituents)]
if len(c) == 1: c = [copy.deepcopy(c[0]) for _ in range(length)]
if length != 1 and length != len(c):
raise ValueError('Cannot add entries of different length')
for k,v in kwargs.items():
if hasattr(v,'__len__') and not isinstance(v,str):
if len(v) != len(c):
raise ValueError('len mismatch 1')
for i,vv in enumerate(v):
c[i][k] = [w.item() for w in vv] if isinstance(vv,np.ndarray) else vv.item()
c[i][k] = vv.item() if isinstance(vv,np.generic) else vv
else:
for i in range(len(c)):
c[i][k] = v
dup = copy.deepcopy(self)
if 'material' not in dup: dup['material'] = []
dup['material'] +=c
dup['material'] = dup['material'] + c if 'material' in dup else c
return dup
@ -280,6 +295,7 @@ class ConfigMaterial(Config):
@staticmethod
def _constituents(N=1,**kwargs):
"""Construct list of constituents."""
N_material=1
for v in kwargs.values():
if hasattr(v,'__len__') and not isinstance(v,str): N_material = len(v)
@ -288,9 +304,9 @@ class ConfigMaterial(Config):
for k,v in kwargs.items():
if hasattr(v,'__len__') and not isinstance(v,str):
if len(v) != N_material:
raise ValueError('len mismatch 2')
raise ValueError('Cannot add entries of different length')
for i,vv in enumerate(np.array(v)):
m[i][0][k] = [w.item() for w in vv] if isinstance(vv,np.ndarray) else vv.item()
m[i][0][k] = vv.item() if isinstance(vv,np.generic) else vv
else:
for i in range(N_material):
m[i][0][k] = v

17
python/damask/_environment.py
View File

@ -3,14 +3,8 @@ from pathlib import Path
class Environment:
def __init__(self):
"""Do Nothing."""
pass
@property
def screen_size(self):
width = 1024
height = 768
try:
import wx
_ = wx.App(False) # noqa
@ -23,7 +17,9 @@ class Environment:
height = tk.winfo_screenheight()
tk.destroy()
except Exception as e:
pass
width = 1024
height = 768
return (width,height)
@ -32,7 +28,7 @@ class Environment:
options = {}
for item in ['DAMASK_NUM_THREADS',
'MSC_ROOT',
'MARC_VERSION',
'MSC_VERSION',
]:
options[item] = os.environ[item] if item in os.environ else None
@ -43,8 +39,3 @@ class Environment:
def root_dir(self):
"""Return DAMASK root path."""
return Path(__file__).parents[2]
# for compatibility
def rootDir(self):
return str(self.root_dir)

294
python/damask/_geom.py
View File

@ -2,8 +2,10 @@ import copy
import multiprocessing as mp
from functools import partial
from os import path
import warnings
import numpy as np
import pandas as pd
import h5py
from scipy import ndimage,spatial
@ -19,7 +21,7 @@ class Geom:
def __init__(self,material,size,origin=[0.0,0.0,0.0],comments=[]):
"""
New geometry definition from array of material, size, and origin.
New geometry definition from array of materials, size, and origin.
Parameters
----------
@ -33,28 +35,10 @@ class Geom:
Comment lines.
"""
if len(material.shape) != 3:
raise ValueError(f'Invalid material shape {material.shape}.')
elif material.dtype not in np.sctypes['float'] + np.sctypes['int']:
raise TypeError(f'Invalid material data type {material.dtype}.')
else:
self.material = np.copy(material)
if self.material.dtype in np.sctypes['float'] and \
np.all(self.material == self.material.astype(int).astype(float)):
self.material = self.material.astype(int)
if len(size) != 3 or any(np.array(size) <= 0):
raise ValueError(f'Invalid size {size}.')
else:
self.size = np.array(size)
if len(origin) != 3:
raise ValueError(f'Invalid origin {origin}.')
else:
self.origin = np.array(origin)
self.comments = [str(c) for c in comments] if isinstance(comments,list) else [str(comments)]
self.material = material
self.size = size
self.origin = origin
self.comments = comments
def __repr__(self):
@ -90,35 +74,90 @@ class Geom:
"""
message = []
if np.any(other.grid != self.grid):
message.append(util.delete(f'grid a b c: {util.srepr(other.grid," x ")}'))
message.append(util.deemph(f'grid a b c: {util.srepr(other.grid," x ")}'))
message.append(util.emph( f'grid a b c: {util.srepr( self.grid," x ")}'))
if not np.allclose(other.size,self.size):
message.append(util.delete(f'size x y z: {util.srepr(other.size," x ")}'))
message.append(util.deemph(f'size x y z: {util.srepr(other.size," x ")}'))
message.append(util.emph( f'size x y z: {util.srepr( self.size," x ")}'))
if not np.allclose(other.origin,self.origin):
message.append(util.delete(f'origin x y z: {util.srepr(other.origin," ")}'))
message.append(util.deemph(f'origin x y z: {util.srepr(other.origin," ")}'))
message.append(util.emph( f'origin x y z: {util.srepr( self.origin," ")}'))
if other.N_materials != self.N_materials:
message.append(util.delete(f'# materials: {other.N_materials}'))
message.append(util.deemph(f'# materials: {other.N_materials}'))
message.append(util.emph( f'# materials: { self.N_materials}'))
if np.nanmax(other.material) != np.nanmax(self.material):
message.append(util.delete(f'max material: {np.nanmax(other.material)}'))
message.append(util.deemph(f'max material: {np.nanmax(other.material)}'))
message.append(util.emph( f'max material: {np.nanmax( self.material)}'))
return util.return_message(message)
@property
def material(self):
"""Material indices."""
return self._material
@material.setter
def material(self,material):
if len(material.shape) != 3:
raise ValueError(f'Invalid material shape {material.shape}.')
elif material.dtype not in np.sctypes['float'] + np.sctypes['int']:
raise TypeError(f'Invalid material data type {material.dtype}.')
else:
self._material = np.copy(material)
if self.material.dtype in np.sctypes['float'] and \
np.all(self.material == self.material.astype(int).astype(float)):
self._material = self.material.astype(int)
@property
def size(self):
"""Physical size of geometry in meter."""
return self._size
@size.setter
def size(self,size):
if len(size) != 3 or any(np.array(size) <= 0):
raise ValueError(f'Invalid size {size}.')
else:
self._size = np.array(size)
@property
def origin(self):
"""Coordinates of geometry origin in meter."""
return self._origin
@origin.setter
def origin(self,origin):
if len(origin) != 3:
raise ValueError(f'Invalid origin {origin}.')
else:
self._origin = np.array(origin)
@property
def comments(self):
"""Comments/history of geometry."""
return self._comments
@comments.setter
def comments(self,comments):
self._comments = [str(c) for c in comments] if isinstance(comments,list) else [str(comments)]
@property
def grid(self):
"""Grid dimension of geometry."""
return np.asarray(self.material.shape)
@property
def N_materials(self):
"""Number of (unique) material indices within geometry."""
return np.unique(self.material).size
@ -131,7 +170,7 @@ class Geom:
----------
fname : str or or pathlib.Path
Geometry file to read.
Valid extension is .vtr, it will be appended if not given.
Valid extension is .vtr, which will be appended if not given.
"""
v = VTK.load(fname if str(fname).endswith('.vtr') else str(fname)+'.vtr')
@ -150,12 +189,16 @@ class Geom:
"""
Read a geom file.
Storing geometry files in ASCII format is deprecated.
This function will be removed in a future version of DAMASK.
Parameters
----------
fname : str or file handle
fname : str, pathlib.Path, or file handle
Geometry file to read.
"""
warnings.warn('Support for ASCII-based geom format will be removed in DAMASK 3.1.0', DeprecationWarning)
try:
f = open(fname)
except TypeError:
@ -170,9 +213,8 @@ class Geom:
if not keyword.startswith('head') or header_length < 3:
raise TypeError('Header length information missing or invalid')
content = f.readlines()
comments = []
content = f.readlines()
for i,line in enumerate(content[:header_length]):
items = line.split('#')[0].lower().strip().split()
key = items[0] if items else ''
@ -185,7 +227,7 @@ class Geom:
else:
comments.append(line.strip())
material = np.empty(grid.prod()) # initialize as flat array
material = np.empty(grid.prod()) # initialize as flat array
i = 0
for line in content[header_length:]:
items = line.split('#')[0].split()
@ -203,13 +245,12 @@ class Geom:
if i != grid.prod():
raise TypeError(f'Invalid file: expected {grid.prod()} entries, found {i}')
if not np.any(np.mod(material,1) != 0.0): # no float present
material = material.astype('int')
if not np.any(np.mod(material,1) != 0.0): # no float present
material = material.astype('int') - (1 if material.min() > 0 else 0)
return Geom(material.reshape(grid,order='F'),size,origin,comments)
@staticmethod
def load_DREAM3D(fname,base_group,point_data=None,material='FeatureIds'):
"""
@ -220,26 +261,26 @@ class Geom:
fname : str
Filename of the DREAM.3D file
base_group : str
Name of the group (folder) below 'DataContainers'. For example
'SyntheticVolumeDataContainer'.
Name of the group (folder) below 'DataContainers',
for example 'SyntheticVolumeDataContainer'.
point_data : str, optional
Name of the group (folder) containing the point wise material data,
for example 'CellData'. Defaults to None, in which case points consecutively numbered.
Name of the group (folder) containing the pointwise material data,
for example 'CellData'. Defaults to None, in which case points are consecutively numbered.
material : str, optional
Name of the dataset containing the material ID. Defaults to
'FeatureIds'.
Name of the dataset containing the material ID.
Defaults to 'FeatureIds'.
"""
root_dir ='DataContainers'
f = h5py.File(fname, 'r')
g = path.join(root_dir,base_group,'_SIMPL_GEOMETRY')
size = f[path.join(g,'DIMENSIONS')][()] * f[path.join(g,'SPACING')][()]
grid = f[path.join(g,'DIMENSIONS')][()]
size = f[path.join(g,'SPACING')][()] * grid
origin = f[path.join(g,'ORIGIN')][()]
group_pointwise = path.join(root_dir,base_group,point_data)
ma = np.arange(1,np.product(grid)+1,dtype=int) if point_data is None else \
np.reshape(f[path.join(group_pointwise,material)],grid.prod())
ma = np.arange(grid.prod(),dtype=int) \
if point_data is None else \
np.reshape(f[path.join(root_dir,base_group,point_data,material)],grid.prod())
return Geom(ma.reshape(grid,order='F'),size,origin,util.execution_stamp('Geom','load_DREAM3D'))
@ -247,28 +288,29 @@ class Geom:
@staticmethod
def from_table(table,coordinates,labels):
"""
Load an ASCII table.
Derive geometry from an ASCII table.
Parameters
----------
table : damask.Table
Table that contains material information.
coordinates : str
Label of the column containing the spatial coordinates.
Label of the vector column containing the spatial coordinates.
Need to be ordered (1./x fast, 3./z slow).
labels : str or list of str
Label(s) of the columns containing the material definition.
Each unique combintation of values results in a material.
Each unique combintation of values results in one material ID.
"""
t = table.sort_by([f'{i}_{coordinates}' for i in range(3,0,-1)])
grid,size,origin = grid_filters.cell_coord0_gridSizeOrigin(t.get(coordinates))
grid,size,origin = grid_filters.cell_coord0_gridSizeOrigin(table.get(coordinates))
labels_ = [labels] if isinstance(labels,str) else labels
_,unique_inverse = np.unique(np.hstack([t.get(l) for l in labels_]),return_inverse=True,axis=0)
ma = unique_inverse.reshape(grid,order='F') + 1
unique,unique_inverse = np.unique(np.hstack([table.get(l) for l in labels_]),return_inverse=True,axis=0)
return Geom(ma,size,origin,util.execution_stamp('Geom','from_table'))
ma = np.arange(grid.prod()) if len(unique) == grid.prod() else \
np.arange(unique.size)[np.argsort(pd.unique(unique_inverse))][unique_inverse]
return Geom(ma.reshape(grid,order='F'),size,origin,util.execution_stamp('Geom','from_table'))
@staticmethod
@ -291,8 +333,8 @@ class Geom:
weights : numpy.ndarray of shape (seeds.shape[0])
Weights of the seeds. Setting all weights to 1.0 gives a standard Voronoi tessellation.
material : numpy.ndarray of shape (seeds.shape[0]), optional
Material ID of the seeds. Defaults to None, in which case materials are
consecutively numbered.
Material ID of the seeds.
Defaults to None, in which case materials are consecutively numbered.
periodic : Boolean, optional
Perform a periodic tessellation. Defaults to True.
@ -340,8 +382,8 @@ class Geom:
seeds : numpy.ndarray of shape (:,3)
Position of the seed points in meter. All points need to lay within the box.
material : numpy.ndarray of shape (seeds.shape[0]), optional
Material ID of the seeds. Defaults to None, in which case materials are
consecutively numbered.
Material ID of the seeds.
Defaults to None, in which case materials are consecutively numbered.
periodic : Boolean, optional
Perform a periodic tessellation. Defaults to True.
@ -417,7 +459,7 @@ class Geom:
Number of periods per unit cell. Defaults to 1.
materials : (int, int), optional
Material IDs. Defaults to (1,2).
Notes
-----
The following triply-periodic minimal surfaces are implemented:
@ -436,19 +478,19 @@ class Geom:
References
----------
Surface curvature in triply-periodic minimal surface architectures as
a distinct design parameter in preparing advanced tissue engineering scaffolds
Sébastien B G Blanquer, Maike Werner, Markus Hannula, Shahriar Sharifi,
Guillaume P R Lajoinie, David Eglin, Jari Hyttinen, André A Poot, and Dirk W Grijpma
10.1088/1758-5090/aa6553
Surface curvature in triply-periodic minimal surface architectures as
a distinct design parameter in preparing advanced tissue engineering scaffolds
https://doi.org/10.1088/1758-5090/aa6553
Triply Periodic Bicontinuous Cubic Microdomain Morphologies by Symmetries
Meinhard Wohlgemuth, Nataliya Yufa, James Hoffman, and Edwin L. Thomas
10.1021/ma0019499
Triply Periodic Bicontinuous Cubic Microdomain Morphologies by Symmetries
https://doi.org/10.1021/ma0019499
Minisurf – A minimal surface generator for finite element modeling and additive manufacturing
Meng-Ting Hsieh, Lorenzo Valdevit
10.1016/j.simpa.2020.100026
Minisurf – A minimal surface generator for finite element modeling and additive manufacturing
https://doi.org/10.1016/j.simpa.2020.100026
"""
x,y,z = np.meshgrid(periods*2.0*np.pi*(np.arange(grid[0])+0.5)/grid[0],
@ -463,17 +505,17 @@ class Geom:
def save(self,fname,compress=True):
"""
Store as vtk rectilinear grid.
Store as VTK rectilinear grid.
Parameters
----------
fname : str or or pathlib.Path
fname : str or pathlib.Path
Filename to write. Valid extension is .vtr, it will be appended if not given.
compress : bool, optional
Compress with zlib algorithm. Defaults to True.
"""
v = VTK.from_rectilinearGrid(self.grid,self.size,self.origin)
v = VTK.from_rectilinear_grid(self.grid,self.size,self.origin)
v.add(self.material.flatten(order='F'),'material')
v.add_comments(self.comments)
@ -484,6 +526,9 @@ class Geom:
"""
Write a geom file.
Storing geometry files in ASCII format is deprecated.
This function will be removed in a future version of DAMASK.
Parameters
----------
fname : str or file handle
@ -492,6 +537,7 @@ class Geom:
Compress geometry with 'x of y' and 'a to b'.
"""
warnings.warn('Support for ASCII-based geom format will be removed in DAMASK 3.1.0', DeprecationWarning)
header = [f'{len(self.comments)+4} header'] + self.comments \
+ ['grid a {} b {} c {}'.format(*self.grid),
'size x {} y {} z {}'.format(*self.size),
@ -508,8 +554,7 @@ class Geom:
def show(self):
"""Show on screen."""
v = VTK.from_rectilinearGrid(self.grid,self.size,self.origin)
v.show()
VTK.from_rectilinear_grid(self.grid,self.size,self.origin).show()
def add_primitive(self,dimension,center,exponent,
@ -519,20 +564,20 @@ class Geom:
Parameters
----------
dimension : int or float numpy.ndarray of shape(3)
dimension : int or float numpy.ndarray of shape (3)
Dimension (diameter/side length) of the primitive. If given as
integers, grid point locations (cell centers) are addressed.
If given as floats, coordinates are addressed.
center : int or float numpy.ndarray of shape(3)
center : int or float numpy.ndarray of shape (3)
Center of the primitive. If given as integers, grid point
locations (cell centers) are addressed.
If given as floats, coordinates are addressed.
exponent : numpy.ndarray of shape(3) or float
coordinates (cell centers) are addressed.
If given as floats, coordinates in space are addressed.
exponent : numpy.ndarray of shape (3) or float
Exponents for the three axes.
0 gives octahedron (ǀxǀ^(2^0) + ǀyǀ^(2^0) + ǀzǀ^(2^0) < 1)
1 gives sphere (ǀxǀ^(2^1) + ǀyǀ^(2^1) + ǀzǀ^(2^1) < 1)
fill : int, optional
Fill value for primitive. Defaults to material.max() + 1.
Fill value for primitive. Defaults to material.max()+1.
R : damask.Rotation, optional
Rotation of primitive. Defaults to no rotation.
inverse : Boolean, optional
@ -542,25 +587,27 @@ class Geom:
Repeat primitive over boundaries. Defaults to True.
"""
# normalized 'radius' and center
r = np.array(dimension)/self.grid/2.0 if np.array(dimension).dtype in np.sctypes['int'] else \
np.array(dimension)/self.size/2.0
c = (np.array(center) + .5)/self.grid if np.array(center).dtype in np.sctypes['int'] else \
(np.array(center) - self.origin)/self.size
# radius and center
r = np.array(dimension)/2.0*self.size/self.grid if np.array(dimension).dtype in np.sctypes['int'] else \
np.array(dimension)/2.0
c = (np.array(center) + .5)*self.size/self.grid if np.array(center).dtype in np.sctypes['int'] else \
(np.array(center) - self.origin)
coords = grid_filters.cell_coord0(self.grid,np.ones(3)) \
- ((np.ones(3)-(1./self.grid if np.array(center).dtype in np.sctypes['int'] else 0))*0.5 if periodic else c) # periodic center is always at CoG
coords = grid_filters.cell_coord0(self.grid,self.size,
-(0.5*(self.size + (self.size/self.grid
if np.array(center).dtype in np.sctypes['int'] else
0)) if periodic else c))
coords_rot = R.broadcast_to(tuple(self.grid))@coords
with np.errstate(all='ignore'):
mask = np.sum(np.power(coords_rot/r,2.0**np.array(exponent)),axis=-1) > 1.0
if periodic: # translate back to center
mask = np.roll(mask,((c-np.ones(3)*.5)*self.grid).astype(int),(0,1,2))
mask = np.roll(mask,((c/self.size-0.5)*self.grid).round().astype(int),(0,1,2))
fill_ = np.full_like(self.material,np.nanmax(self.material)+1 if fill is None else fill)
return Geom(material = np.where(np.logical_not(mask) if inverse else mask, self.material,fill_),
return Geom(material = np.where(np.logical_not(mask) if inverse else mask,
self.material,
np.nanmax(self.material)+1 if fill is None else fill),
size = self.size,
origin = self.origin,
comments = self.comments+[util.execution_stamp('Geom','add_primitive')],
@ -687,12 +734,10 @@ class Geom:
def renumber(self):
"""Renumber sorted material indices to 1,...,N."""
renumbered = np.empty(self.grid,dtype=self.material.dtype)
for i, oldID in enumerate(np.unique(self.material)):
renumbered = np.where(self.material == oldID, i+1, renumbered)
"""Renumber sorted material indices as 0,...,N-1."""
_,renumbered = np.unique(self.material,return_inverse=True)
return Geom(material = renumbered,
return Geom(material = renumbered.reshape(self.grid),
size = self.size,
origin = self.origin,
comments = self.comments+[util.execution_stamp('Geom','renumber')],
@ -714,7 +759,7 @@ class Geom:
if fill is None: fill = np.nanmax(self.material) + 1
dtype = float if np.isnan(fill) or int(fill) != fill or self.material.dtype==np.float else int
Eulers = R.as_Eulers(degrees=True)
Eulers = R.as_Euler_angles(degrees=True)
material_in = self.material.copy()
# These rotations are always applied in the reference coordinate system, i.e. (z,x,z) not (z,x',z'')
@ -783,17 +828,33 @@ class Geom:
New material indices.
"""
substituted = self.material.copy()
for from_ms,to_ms in zip(from_material,to_material):
substituted[self.material==from_ms] = to_ms
def mp(entry,mapper):
return mapper[entry] if entry in mapper else entry
return Geom(material = substituted,
mp = np.vectorize(mp)
mapper = dict(zip(from_material,to_material))
return Geom(material = mp(self.material,mapper).reshape(self.grid),
size = self.size,
origin = self.origin,
comments = self.comments+[util.execution_stamp('Geom','substitute')],
)
def sort(self):
"""Sort material indices such that min(material) is located at (0,0,0)."""
a = self.material.flatten(order='F')
from_ma = pd.unique(a)
sort_idx = np.argsort(from_ma)
ma = np.unique(a)[sort_idx][np.searchsorted(from_ma,a,sorter = sort_idx)]
return Geom(material = ma.reshape(self.grid,order='F'),
size = self.size,
origin = self.origin,
comments = self.comments+[util.execution_stamp('Geom','sort')],
)
def vicinity_offset(self,vicinity=1,offset=None,trigger=[],periodic=True):
"""
Offset material index of points in the vicinity of xxx.
@ -809,7 +870,7 @@ class Geom:
Defaults to 1.
offset : int, optional
Offset (positive or negative) to tag material indices,
defaults to material.max() + 1.
defaults to material.max()+1.
trigger : list of ints, optional
List of material indices that trigger a change.
Defaults to [], meaning that any different neighbor triggers a change.
@ -820,15 +881,11 @@ class Geom:
def tainted_neighborhood(stencil,trigger):
me = stencil[stencil.shape[0]//2]
if len(trigger) == 0:
return np.any(stencil != me)
if me in trigger:
trigger = set(trigger)
trigger.remove(me)
trigger = list(trigger)
return np.any(np.in1d(stencil,np.array(trigger)))
return np.any(stencil != me
if len(trigger) == 0 else
np.in1d(stencil,np.array(list(set(trigger) - {me}))))
offset_ = np.nanmax(self.material) if offset is None else offset
offset_ = np.nanmax(self.material)+1 if offset is None else offset
mask = ndimage.filters.generic_filter(self.material,
tainted_neighborhood,
size=1+2*vicinity,
@ -850,28 +907,31 @@ class Geom:
----------
periodic : bool, optional
Show boundaries across periodicity. Defaults to True.
direction : string, optional
Directions to consider ('x','y','z'). Defaults to 'xyz'.
directions : iterable containing str, optional
Direction(s) along which the geometry is mirrored.
Valid entries are 'x', 'y', 'z'. Defaults to 'xyz'.
"""
valid = ['x','y','z']
if not set(directions).issubset(valid):
raise ValueError(f'Invalid direction {set(directions).difference(valid)} specified.')
# offset (for connectivity)
o = [[0, self.grid[0]+1, np.prod(self.grid[:2]+1)+self.grid[0]+1, np.prod(self.grid[:2]+1)],
[0, np.prod(self.grid[:2]+1), np.prod(self.grid[:2]+1)+1, 1],
[0, 1, self.grid[0]+1+1, self.grid[0]+1]]
[0, 1, self.grid[0]+1+1, self.grid[0]+1]] # offset for connectivity
connectivity = []
for i,d in enumerate(['x','y','z']):
if d not in directions.lower(): continue
if d not in directions: continue
mask = self.material != np.roll(self.material,1,i)
for j in [0,1,2]:
mask = np.concatenate((mask,np.take(mask,[0],j)*(i==j)),j)
if i == 0 and not periodic: mask[0,:,:] = mask[-1,:,:] = False
if i == 1 and not periodic: mask[:,0,:] = mask[:,-1,:] = False
if i == 2 and not periodic: mask[:,:,0] = mask[:,:,-1] = False
base_nodes = np.argwhere(mask.flatten(order='F')).reshape(-1,1)
connectivity.append(np.block([base_nodes + o[i][k] for k in range(4)]))
coords = grid_filters.node_coord0(self.grid,self.size,self.origin).reshape(-1,3,order='F')
return VTK.from_unstructuredGrid(coords,np.vstack(connectivity),'QUAD')
return VTK.from_unstructured_grid(coords,np.vstack(connectivity),'QUAD')

646
python/damask/_lattice.py
View File

@ -1,646 +0,0 @@
import numpy as np
class Symmetry:
"""
Symmetry-related operations for crystal systems.
References
----------
https://en.wikipedia.org/wiki/Crystal_system
"""
crystal_systems = [None,'orthorhombic','tetragonal','hexagonal','cubic']
def __init__(self, system = None):
"""
Symmetry Definition.
Parameters
----------
system : {None,'orthorhombic','tetragonal','hexagonal','cubic'}, optional
Name of the crystal system. Defaults to 'None'.
"""
if system is not None and system.lower() not in self.crystal_systems:
raise KeyError(f'Crystal system "{system}" is unknown')
self.system = system.lower() if isinstance(system,str) else system
def __copy__(self):
"""Copy."""
return self.__class__(self.system)
copy = __copy__
def __repr__(self):
"""Readable string."""
return f'{self.system}'
def __eq__(self, other):
"""
Equal to other.
Parameters
----------
other : Symmetry
Symmetry to check for equality.
"""
return self.system == other.system
def __neq__(self, other):
"""
Not Equal to other.
Parameters
----------
other : Symmetry
Symmetry to check for inequality.
"""
return not self.__eq__(other)
def __cmp__(self,other):
"""
Linear ordering.
Parameters
----------
other : Symmetry
Symmetry to check for for order.
"""
myOrder = self.crystal_systems.index(self.system)
otherOrder = self.crystal_systems.index(other.system)
return (myOrder > otherOrder) - (myOrder < otherOrder)
@property
def symmetry_operations(self):
"""Symmetry operations as quaternions."""
if self.system == 'cubic':
sym_quats = [
[ 1.0, 0.0, 0.0, 0.0 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, 0.0, 0.0, 1.0 ],
[ 0.0, 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2) ],
[ 0.0, 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
[ 0.0, -0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
[ 0.5, 0.5, 0.5, 0.5 ],
[-0.5, 0.5, 0.5, 0.5 ],
[-0.5, 0.5, 0.5, -0.5 ],
[-0.5, 0.5, -0.5, 0.5 ],
[-0.5, -0.5, 0.5, 0.5 ],
[-0.5, -0.5, 0.5, -0.5 ],
[-0.5, -0.5, -0.5, 0.5 ],
[-0.5, 0.5, -0.5, -0.5 ],
[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[-0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2), 0.0 ],
[-0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2), 0.0 ],
[-0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0, 0.0 ],
[-0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0, 0.0 ],
]
elif self.system == 'hexagonal':
sym_quats = [
[ 1.0, 0.0, 0.0, 0.0 ],
[-0.5*np.sqrt(3), 0.0, 0.0, -0.5 ],
[ 0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
[ 0.0, 0.0, 0.0, 1.0 ],
[-0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
[-0.5*np.sqrt(3), 0.0, 0.0, 0.5 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, -0.5*np.sqrt(3), 0.5, 0.0 ],
[ 0.0, 0.5, -0.5*np.sqrt(3), 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, -0.5, -0.5*np.sqrt(3), 0.0 ],
[ 0.0, 0.5*np.sqrt(3), 0.5, 0.0 ],
]
elif self.system == 'tetragonal':
sym_quats = [
[ 1.0, 0.0, 0.0, 0.0 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, 0.0, 0.0, 1.0 ],
[ 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
[ 0.0, -0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
]
elif self.system == 'orthorhombic':
sym_quats = [
[ 1.0,0.0,0.0,0.0 ],
[ 0.0,1.0,0.0,0.0 ],
[ 0.0,0.0,1.0,0.0 ],
[ 0.0,0.0,0.0,1.0 ],
]
else:
sym_quats = [
[ 1.0,0.0,0.0,0.0 ],
]
return np.array(sym_quats)
def in_FZ(self,rho):
"""
Check whether given Rodrigues-Frank vector falls into fundamental zone.
Fundamental zone in Rodrigues space is point symmetric around origin.
"""
if(rho.shape[-1] != 3):
raise ValueError('Input is not a Rodrigues-Frank vector field.')
rho_abs = np.abs(rho)
with np.errstate(invalid='ignore'):
# using '*'/prod for 'and'
if self.system == 'cubic':
return np.where(np.prod(np.sqrt(2)-1. >= rho_abs,axis=-1) *
(1. >= np.sum(rho_abs,axis=-1)),True,False)
elif self.system == 'hexagonal':
return np.where(np.prod(1. >= rho_abs,axis=-1) *
(2. >= np.sqrt(3)*rho_abs[...,0] + rho_abs[...,1]) *
(2. >= np.sqrt(3)*rho_abs[...,1] + rho_abs[...,0]) *
(2. >= np.sqrt(3) + rho_abs[...,2]),True,False)
elif self.system == 'tetragonal':
return np.where(np.prod(1. >= rho_abs[...,:2],axis=-1) *
(np.sqrt(2) >= rho_abs[...,0] + rho_abs[...,1]) *
(np.sqrt(2) >= rho_abs[...,2] + 1.),True,False)
elif self.system == 'orthorhombic':
return np.where(np.prod(1. >= rho_abs,axis=-1),True,False)
else:
return np.where(np.all(np.isfinite(rho_abs),axis=-1),True,False)
def in_disorientation_SST(self,rho):
"""
Check whether given Rodrigues-Frank vector (of misorientation) falls into standard stereographic triangle.
References
----------
A. Heinz and P. Neumann, Acta Crystallographica Section A 47:780-789, 1991
https://doi.org/10.1107/S0108767391006864
"""
if(rho.shape[-1] != 3):
raise ValueError('Input is not a Rodrigues-Frank vector field.')
with np.errstate(invalid='ignore'):
# using '*' for 'and'
if self.system == 'cubic':
return np.where((rho[...,0] >= rho[...,1]) * \
(rho[...,1] >= rho[...,2]) * \
(rho[...,2] >= 0),True,False)
elif self.system == 'hexagonal':
return np.where((rho[...,0] >= rho[...,1]*np.sqrt(3)) * \
(rho[...,1] >= 0) * \
(rho[...,2] >= 0),True,False)
elif self.system == 'tetragonal':
return np.where((rho[...,0] >= rho[...,1]) * \
(rho[...,1] >= 0) * \
(rho[...,2] >= 0),True,False)
elif self.system == 'orthorhombic':
return np.where((rho[...,0] >= 0) * \
(rho[...,1] >= 0) * \
(rho[...,2] >= 0),True,False)
else:
return np.ones_like(rho[...,0],dtype=bool)
#ToDo: IPF color in separate function
def in_SST(self,vector,proper=False,color=False):
"""
Check whether given vector falls into standard stereographic triangle of own symmetry.
proper considers only vectors with z >= 0, hence uses two neighboring SSTs.
Return inverse pole figure color if requested.
Bases are computed from
>>> basis = {'cubic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,1.]/np.sqrt(2.), # direction of green
... [1.,1.,1.]/np.sqrt(3.)]).T), # direction of blue
... 'hexagonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # direction of green
... [np.sqrt(3.),1.,0.]/np.sqrt(4.)]).T), # direction of blue
... 'tetragonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # direction of green
... [1.,1.,0.]/np.sqrt(2.)]).T), # direction of blue
... 'orthorhombic': np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # direction of green
... [0.,1.,0.]]).T), # direction of blue
... }
"""
if(vector.shape[-1] != 3):
raise ValueError('Input is not a 3D vector field.')
if self.system == 'cubic':
basis = {'improper':np.array([ [-1. , 0. , 1. ],
[ np.sqrt(2.) , -np.sqrt(2.) , 0. ],
[ 0. , np.sqrt(3.) , 0. ] ]),
'proper':np.array([ [ 0. , -1. , 1. ],
[-np.sqrt(2.) , np.sqrt(2.) , 0. ],
[ np.sqrt(3.) , 0. , 0. ] ]),
}
elif self.system == 'hexagonal':
basis = {'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -np.sqrt(3.) , 0. ],
[ 0. , 2. , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , np.sqrt(3.) , 0. ],
[ np.sqrt(3.) , -1. , 0. ] ]),
}
elif self.system == 'tetragonal':
basis = {'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -1. , 0. ],
[ 0. , np.sqrt(2.) , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , 1. , 0. ],
[ np.sqrt(2.) , 0. , 0. ] ]),
}
elif self.system == 'orthorhombic':
basis = {'improper':np.array([ [ 0., 0., 1.],
[ 1., 0., 0.],
[ 0., 1., 0.] ]),
'proper':np.array([ [ 0., 0., 1.],
[-1., 0., 0.],
[ 0., 1., 0.] ]),
}
else: # direct exit for unspecified symmetry
if color:
return (np.ones_like(vector[...,0],bool),np.zeros_like(vector))
else:
return np.ones_like(vector[...,0],bool)
b_i = np.broadcast_to(basis['improper'],vector.shape+(3,))
if proper:
b_p = np.broadcast_to(basis['proper'], vector.shape+(3,))
improper = np.all(np.around(np.einsum('...ji,...i',b_i,vector),12)>=0.0,axis=-1,keepdims=True)
theComponents = np.where(np.broadcast_to(improper,vector.shape),
np.around(np.einsum('...ji,...i',b_i,vector),12),
np.around(np.einsum('...ji,...i',b_p,vector),12))
else:
vector_ = np.block([vector[...,0:2],np.abs(vector[...,2:3])]) # z component projects identical
theComponents = np.around(np.einsum('...ji,...i',b_i,vector_),12)
in_SST = np.all(theComponents >= 0.0,axis=-1)
if color: # have to return color array
with np.errstate(invalid='ignore',divide='ignore'):
rgb = (theComponents/np.linalg.norm(theComponents,axis=-1,keepdims=True))**0.5 # smoothen color ramps
rgb = np.minimum(1.,rgb) # limit to maximum intensity
rgb /= np.max(rgb,axis=-1,keepdims=True) # normalize to (HS)V = 1
rgb[np.broadcast_to(~in_SST.reshape(vector[...,0].shape+(1,)),vector.shape)] = 0.0
return (in_SST,rgb)
else:
return in_SST
# ******************************************************************************************
class Lattice: # ToDo: Make a subclass of Symmetry!
"""
Bravais lattice.
This contains only a mapping from Bravais lattice to symmetry
and orientation relationships. It could include twin and slip systems.
References
----------
https://en.wikipedia.org/wiki/Bravais_lattice
"""
lattices = {
'iso': {'system':None},
'triclinic':{'system':None},
'bct': {'system':'tetragonal'},
'hex': {'system':'hexagonal'},
'fcc': {'system':'cubic','c/a':1.0},
'bcc': {'system':'cubic','c/a':1.0},
}
def __init__(self,lattice,c_over_a=None):
"""
New lattice of given type.
Parameters
----------
lattice : str
Bravais lattice.
"""
self.lattice = lattice
self.symmetry = Symmetry(self.lattices[lattice]['system'])
# transition to subclass
self.system = self.symmetry.system
self.in_SST = self.symmetry.in_SST
self.in_FZ = self.symmetry.in_FZ
self.in_disorientation_SST = self.symmetry.in_disorientation_SST
def __repr__(self):
"""Report basic lattice information."""
return f'Bravais lattice {self.lattice} ({self.symmetry} crystal system)'
# Kurdjomov--Sachs orientation relationship for fcc <-> bcc transformation
# from S. Morito et al., Journal of Alloys and Compounds 577:s587-s592, 2013
# also see K. Kitahara et al., Acta Materialia 54:1279-1288, 2006
_KS = {'mapping':{'fcc':0,'bcc':1},
'planes': 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]],
[[ 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]],
[[ -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]],
[[ 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]]],dtype='float'),
'directions': np.array([
[[ -1, 0, 1],[ -1, -1, 1]],
[[ -1, 0, 1],[ -1, 1, -1]],
[[ 0, 1, -1],[ -1, -1, 1]],
[[ 0, 1, -1],[ -1, 1, -1]],
[[ 1, -1, 0],[ -1, -1, 1]],
[[ 1, -1, 0],[ -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]],
[[ 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, 1, 0],[ -1, -1, 1]],
[[ 1, 1, 0],[ -1, 1, -1]],
[[ -1, 1, 0],[ -1, -1, 1]],
[[ -1, 1, 0],[ -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]]],dtype='float')}
# Greninger--Troiano orientation relationship for fcc <-> bcc transformation
# from Y. He et al., Journal of Applied Crystallography 39:72-81, 2006
_GT = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 1, 1, 1],[ 1, 0, 1]],
[[ 1, 1, 1],[ 1, 1, 0]],
[[ 1, 1, 1],[ 0, 1, 1]],
[[ -1, -1, 1],[ -1, 0, 1]],
[[ -1, -1, 1],[ -1, -1, 0]],
[[ -1, -1, 1],[ 0, -1, 1]],
[[ -1, 1, 1],[ -1, 0, 1]],
[[ -1, 1, 1],[ -1, 1, 0]],
[[ -1, 1, 1],[ 0, 1, 1]],
[[ 1, -1, 1],[ 1, 0, 1]],
[[ 1, -1, 1],[ 1, -1, 0]],
[[ 1, -1, 1],[ 0, -1, 1]],
[[ 1, 1, 1],[ 1, 1, 0]],
[[ 1, 1, 1],[ 0, 1, 1]],
[[ 1, 1, 1],[ 1, 0, 1]],
[[ -1, -1, 1],[ -1, -1, 0]],
[[ -1, -1, 1],[ 0, -1, 1]],
[[ -1, -1, 1],[ -1, 0, 1]],
[[ -1, 1, 1],[ -1, 1, 0]],
[[ -1, 1, 1],[ 0, 1, 1]],
[[ -1, 1, 1],[ -1, 0, 1]],
[[ 1, -1, 1],[ 1, -1, 0]],
[[ 1, -1, 1],[ 0, -1, 1]],
[[ 1, -1, 1],[ 1, 0, 1]]],dtype='float'),
'directions': np.array([
[[ -5,-12, 17],[-17, -7, 17]],
[[ 17, -5,-12],[ 17,-17, -7]],
[[-12, 17, -5],[ -7, 17,-17]],
[[ 5, 12, 17],[ 17, 7, 17]],
[[-17, 5,-12],[-17, 17, -7]],
[[ 12,-17, -5],[ 7,-17,-17]],
[[ -5, 12,-17],[-17, 7,-17]],
[[ 17, 5, 12],[ 17, 17, 7]],
[[-12,-17, 5],[ -7,-17, 17]],
[[ 5,-12,-17],[ 17, -7,-17]],
[[-17, -5, 12],[-17,-17, 7]],
[[ 12, 17, 5],[ 7, 17, 17]],
[[ -5, 17,-12],[-17, 17, -7]],
[[-12, -5, 17],[ -7,-17, 17]],
[[ 17,-12, -5],[ 17, -7,-17]],
[[ 5,-17,-12],[ 17,-17, -7]],
[[ 12, 5, 17],[ 7, 17, 17]],
[[-17, 12, -5],[-17, 7,-17]],
[[ -5,-17, 12],[-17,-17, 7]],
[[-12, 5,-17],[ -7, 17,-17]],
[[ 17, 12, 5],[ 17, 7, 17]],
[[ 5, 17, 12],[ 17, 17, 7]],
[[ 12, -5,-17],[ 7,-17,-17]],
[[-17,-12, 5],[-17,-7, 17]]],dtype='float')}
# Greninger--Troiano' orientation relationship for fcc <-> bcc transformation
# from Y. He et al., Journal of Applied Crystallography 39:72-81, 2006
_GTprime = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 7, 17, 17],[ 12, 5, 17]],
[[ 17, 7, 17],[ 17, 12, 5]],
[[ 17, 17, 7],[ 5, 17, 12]],
[[ -7,-17, 17],[-12, -5, 17]],
[[-17, -7, 17],[-17,-12, 5]],
[[-17,-17, 7],[ -5,-17, 12]],
[[ 7,-17,-17],[ 12, -5,-17]],
[[ 17, -7,-17],[ 17,-12, -5]],
[[ 17,-17, -7],[ 5,-17,-12]],
[[ -7, 17,-17],[-12, 5,-17]],
[[-17, 7,-17],[-17, 12, -5]],
[[-17, 17, -7],[ -5, 17,-12]],
[[ 7, 17, 17],[ 12, 17, 5]],
[[ 17, 7, 17],[ 5, 12, 17]],
[[ 17, 17, 7],[ 17, 5, 12]],
[[ -7,-17, 17],[-12,-17, 5]],
[[-17, -7, 17],[ -5,-12, 17]],
[[-17,-17, 7],[-17, -5, 12]],
[[ 7,-17,-17],[ 12,-17, -5]],
[[ 17, -7,-17],[ 5, -12,-17]],
[[ 17,-17, -7],[ 17, -5,-12]],
[[ -7, 17,-17],[-12, 17, -5]],
[[-17, 7,-17],[ -5, 12,-17]],
[[-17, 17, -7],[-17, 5,-12]]],dtype='float'),
'directions': np.array([
[[ 0, 1, -1],[ 1, 1, -1]],
[[ -1, 0, 1],[ -1, 1, 1]],
[[ 1, -1, 0],[ 1, -1, 1]],
[[ 0, -1, -1],[ -1, -1, -1]],
[[ 1, 0, 1],[ 1, -1, 1]],
[[ 1, -1, 0],[ 1, -1, -1]],
[[ 0, 1, -1],[ -1, 1, -1]],
[[ 1, 0, 1],[ 1, 1, 1]],
[[ -1, -1, 0],[ -1, -1, 1]],
[[ 0, -1, -1],[ 1, -1, -1]],
[[ -1, 0, 1],[ -1, -1, 1]],
[[ -1, -1, 0],[ -1, -1, -1]],
[[ 0, -1, 1],[ 1, -1, 1]],
[[ 1, 0, -1],[ 1, 1, -1]],
[[ -1, 1, 0],[ -1, 1, 1]],
[[ 0, 1, 1],[ -1, 1, 1]],
[[ -1, 0, -1],[ -1, -1, -1]],
[[ -1, 1, 0],[ -1, 1, -1]],
[[ 0, -1, 1],[ -1, -1, 1]],
[[ -1, 0, -1],[ -1, 1, -1]],
[[ 1, 1, 0],[ 1, 1, 1]],
[[ 0, 1, 1],[ 1, 1, 1]],
[[ 1, 0, -1],[ 1, -1, -1]],
[[ 1, 1, 0],[ 1, 1, -1]]],dtype='float')}
# Nishiyama--Wassermann orientation relationship for fcc <-> bcc transformation
# from H. Kitahara et al., Materials Characterization 54:378-386, 2005
_NW = {'mapping':{'fcc':0,'bcc':1},
'planes': 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]],
[[ 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]]],dtype='float'),
'directions': np.array([
[[ 2, -1, -1],[ 0, -1, 1]],
[[ -1, 2, -1],[ 0, -1, 1]],
[[ -1, -1, 2],[ 0, -1, 1]],
[[ -2, -1, -1],[ 0, -1, 1]],
[[ 1, 2, -1],[ 0, -1, 1]],
[[ 1, -1, 2],[ 0, -1, 1]],
[[ 2, 1, -1],[ 0, -1, 1]],
[[ -1, -2, -1],[ 0, -1, 1]],
[[ -1, 1, 2],[ 0, -1, 1]],
[[ 2, -1, 1],[ 0, -1, 1]], #It is wrong in the paper, but matrix is correct
[[ -1, 2, 1],[ 0, -1, 1]],
[[ -1, -1, -2],[ 0, -1, 1]]],dtype='float')}
# Pitsch orientation relationship for fcc <-> bcc transformation
# from Y. He et al., Acta Materialia 53:1179-1190, 2005
_Pitsch = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 0, 1, 0],[ -1, 0, 1]],
[[ 0, 0, 1],[ 1, -1, 0]],
[[ 1, 0, 0],[ 0, 1, -1]],
[[ 1, 0, 0],[ 0, -1, -1]],
[[ 0, 1, 0],[ -1, 0, -1]],
[[ 0, 0, 1],[ -1, -1, 0]],
[[ 0, 1, 0],[ -1, 0, -1]],
[[ 0, 0, 1],[ -1, -1, 0]],
[[ 1, 0, 0],[ 0, -1, -1]],
[[ 1, 0, 0],[ 0, -1, 1]],
[[ 0, 1, 0],[ 1, 0, -1]],
[[ 0, 0, 1],[ -1, 1, 0]]],dtype='float'),
'directions': np.array([
[[ 1, 0, 1],[ 1, -1, 1]],
[[ 1, 1, 0],[ 1, 1, -1]],
[[ 0, 1, 1],[ -1, 1, 1]],
[[ 0, 1, -1],[ -1, 1, -1]],
[[ -1, 0, 1],[ -1, -1, 1]],
[[ 1, -1, 0],[ 1, -1, -1]],
[[ 1, 0, -1],[ 1, -1, -1]],
[[ -1, 1, 0],[ -1, 1, -1]],
[[ 0, -1, 1],[ -1, -1, 1]],
[[ 0, 1, 1],[ -1, 1, 1]],
[[ 1, 0, 1],[ 1, -1, 1]],
[[ 1, 1, 0],[ 1, 1, -1]]],dtype='float')}
# Bain orientation relationship for fcc <-> bcc transformation
# from Y. He et al., Journal of Applied Crystallography 39:72-81, 2006
_Bain = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 1, 0, 0],[ 1, 0, 0]],
[[ 0, 1, 0],[ 0, 1, 0]],
[[ 0, 0, 1],[ 0, 0, 1]]],dtype='float'),
'directions': np.array([
[[ 0, 1, 0],[ 0, 1, 1]],
[[ 0, 0, 1],[ 1, 0, 1]],
[[ 1, 0, 0],[ 1, 1, 0]]],dtype='float')}
def relation_operations(self,model):
"""
Crystallographic orientation relationships for phase transformations.
References
----------
S. Morito et al., Journal of Alloys and Compounds 577:s587-s592, 2013
https://doi.org/10.1016/j.jallcom.2012.02.004
K. Kitahara et al., Acta Materialia 54(5):1279-1288, 2006
https://doi.org/10.1016/j.actamat.2005.11.001
Y. He et al., Journal of Applied Crystallography 39:72-81, 2006
https://doi.org/10.1107/S0021889805038276
H. Kitahara et al., Materials Characterization 54(4-5):378-386, 2005
https://doi.org/10.1016/j.matchar.2004.12.015
Y. He et al., Acta Materialia 53(4):1179-1190, 2005
https://doi.org/10.1016/j.actamat.2004.11.021
"""
models={'KS':self._KS, 'GT':self._GT, 'GT_prime':self._GTprime,
'NW':self._NW, 'Pitsch': self._Pitsch, 'Bain':self._Bain}
try:
relationship = models[model]
except KeyError :
raise KeyError(f'Orientation relationship "{model}" is unknown')
if self.lattice not in relationship['mapping']:
raise ValueError(f'Relationship "{model}" not supported for lattice "{self.lattice}"')
r = {'lattice':Lattice((set(relationship['mapping'])-{self.lattice}).pop()), # target lattice
'rotations':[] }
myPlane_id = relationship['mapping'][self.lattice]
otherPlane_id = (myPlane_id+1)%2
myDir_id = myPlane_id +2
otherDir_id = otherPlane_id +2
for miller in np.hstack((relationship['planes'],relationship['directions'])):
myPlane = miller[myPlane_id]/ np.linalg.norm(miller[myPlane_id])
myDir = miller[myDir_id]/ np.linalg.norm(miller[myDir_id])
myMatrix = np.array([myDir,np.cross(myPlane,myDir),myPlane])
otherPlane = miller[otherPlane_id]/ np.linalg.norm(miller[otherPlane_id])
otherDir = miller[otherDir_id]/ np.linalg.norm(miller[otherDir_id])
otherMatrix = np.array([otherDir,np.cross(otherPlane,otherDir),otherPlane])
r['rotations'].append(np.dot(otherMatrix.T,myMatrix))
r['rotations'] = np.array(r['rotations'])
return r

1318
python/damask/_orientation.py
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502
python/damask/_result.py
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@ -7,6 +7,7 @@ import xml.etree.ElementTree as ET
import xml.dom.minidom
from pathlib import Path
from functools import partial
from collections import defaultdict
import h5py
import numpy as np
@ -15,12 +16,13 @@ from numpy.lib import recfunctions as rfn
import damask
from . import VTK
from . import Table
from . import Rotation
from . import Orientation
from . import grid_filters
from . import mechanics
from . import tensor
from . import util
h5py3 = h5py.__version__[0] == '3'
class Result:
"""
@ -35,20 +37,16 @@ class Result:
Parameters
----------
fname : str
name of the DADF5 file to be opened.
fname : str or pathlib.Path
Name of the DADF5 file to be opened.
"""
with h5py.File(fname,'r') as f:
try:
self.version_major = f.attrs['DADF5_version_major']
self.version_minor = f.attrs['DADF5_version_minor']
except KeyError:
self.version_major = f.attrs['DADF5-major']
self.version_minor = f.attrs['DADF5-minor']
self.version_major = f.attrs['DADF5_version_major']
self.version_minor = f.attrs['DADF5_version_minor']
if self.version_major != 0 or not 2 <= self.version_minor <= 7:
if self.version_major != 0 or not 7 <= self.version_minor <= 9:
raise TypeError(f'Unsupported DADF5 version {self.version_major}.{self.version_minor}')
self.structured = 'grid' in f['geometry'].attrs.keys()
@ -56,35 +54,33 @@ class Result:
if self.structured:
self.grid = f['geometry'].attrs['grid']
self.size = f['geometry'].attrs['size']
self.origin = f['geometry'].attrs['origin'] if self.version_major == 0 and self.version_minor >= 5 else \
np.zeros(3)
self.origin = f['geometry'].attrs['origin']
r=re.compile('inc[0-9]+')
increments_unsorted = {int(i[3:]):i for i in f.keys() if r.match(i)}
self.increments = [increments_unsorted[i] for i in sorted(increments_unsorted)]
self.times = [round(f[i].attrs['time/s'],12) for i in self.increments]
self.Nmaterialpoints, self.Nconstituents = np.shape(f['mapping/cellResults/constituent'])
self.materialpoints = [m.decode() for m in np.unique(f['mapping/cellResults/materialpoint']['Name'])]
self.constituents = [c.decode() for c in np.unique(f['mapping/cellResults/constituent'] ['Name'])]
self.N_materialpoints, self.N_constituents = np.shape(f['mapping/phase'])
# faster, but does not work with (deprecated) DADF5_postResults
#self.materialpoints = [m for m in f['inc0/materialpoint']]
#self.constituents = [c for c in f['inc0/constituent']]
self.homogenizations = [m.decode() for m in np.unique(f['mapping/homogenization']['Name'])]
self.phases = [c.decode() for c in np.unique(f['mapping/phase']['Name'])]
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.out_type_ph = []
for c in self.phases:
self.out_type_ph += f['/'.join([self.increments[0],'phase',c])].keys()
self.out_type_ph = list(set(self.out_type_ph)) # 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.out_type_ho = []
for m in self.homogenizations:
self.out_type_ho += f['/'.join([self.increments[0],'homogenization',m])].keys()
self.out_type_ho = list(set(self.out_type_ho)) # make unique
self.selection = {'increments': self.increments,
'constituents': self.constituents,'materialpoints': self.materialpoints,
'con_physics': self.con_physics, 'mat_physics': self.mat_physics
self.selection = {'increments': self.increments,
'phases': self.phases,
'homogenizations': self.homogenizations,
'out_type_ph': self.out_type_ph,
'out_type_ho': self.out_type_ho
}
self.fname = Path(fname).absolute()
@ -93,7 +89,7 @@ class Result:
def __repr__(self):
"""Show selected data."""
"""Show summary of file content."""
all_selected_increments = self.selection['increments']
self.pick('increments',all_selected_increments[0:1])
@ -117,14 +113,18 @@ class Result:
Parameters
----------
action : str
select from 'set', 'add', and 'del'
Select from 'set', 'add', and 'del'.
what : str
attribute to change (must be from self.selection)
Attribute to change (must be from self.selection).
datasets : list of str or bool
name of datasets as list, supports ? and * wildcards.
Name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
"""
def natural_sort(key):
convert = lambda text: int(text) if text.isdigit() else text
return [ convert(c) for c in re.split('([0-9]+)', key) ]
# allow True/False and string arguments
if datasets is True:
datasets = ['*']
@ -158,25 +158,60 @@ class Result:
self.selection[what] = valid
elif action == 'add':
add = existing.union(valid)
add_sorted = sorted(add, key=lambda x: int("".join([i for i in x if i.isdigit()])))
add_sorted = sorted(add, key=natural_sort)
self.selection[what] = add_sorted
elif action == 'del':
diff = existing.difference(valid)
diff_sorted = sorted(diff, key=lambda x: int("".join([i for i in x if i.isdigit()])))
diff_sorted = sorted(diff, key=natural_sort)
self.selection[what] = diff_sorted
def _get_attribute(self,path,attr):
"""
Get the attribute of a dataset.
Parameters
----------
Path : str
Path to the dataset.
attr : str
Name of the attribute to get.
Returns
-------
attr at path, str or None.
The requested attribute, None if not found.
"""
with h5py.File(self.fname,'r') as f:
try:
return f[path].attrs[attr] if h5py3 else f[path].attrs[attr].decode()
except KeyError:
return None
def allow_modification(self):
print(util.bcolors().WARNING+util.bcolors().BOLD+
'Warning: Modification of existing datasets allowed!'+
util.bcolors().ENDC)
"""Allow to overwrite existing data."""
print(util.warn('Warning: Modification of existing datasets allowed!'))
self._allow_modification = True
def disallow_modification(self):
"""Disllow to overwrite existing data (default case)."""
self._allow_modification = False
def incs_in_range(self,start,end):
"""
Select all increments within a given range.
Parameters
----------
start : int or str
Start increment.
end : int or str
End increment.
"""
selected = []
for i,inc in enumerate([int(i[3:]) for i in self.increments]):
s,e = map(lambda x: int(x[3:] if isinstance(x,str) and x.startswith('inc') else x), (start,end))
@ -186,6 +221,17 @@ class Result:
def times_in_range(self,start,end):
"""
Select all increments within a given time range.
Parameters
----------
start : float
Time of start increment.
end : float
Time of end increment.
"""
selected = []
for i,time in enumerate(self.times):
if start <= time <= end:
@ -200,7 +246,7 @@ class Result:
Parameters
----------
what : str
attribute to change (must be from self.selection)
Attribute to change (must be from self.selection).
"""
datasets = self.selection[what]
@ -280,43 +326,41 @@ class Result:
for path_old in self.get_dataset_location(name_old):
path_new = os.path.join(os.path.dirname(path_old),name_new)
f[path_new] = f[path_old]
f[path_new].attrs['Renamed'] = 'Original name: {}'.encode()
f[path_new].attrs['Renamed'] = f'Original name: {name_old}' if h5py3 else \
f'Original name: {name_old}'.encode()
del f[path_old]
else:
raise PermissionError('Rename operation not permitted')
# def datamerger(regular expression to filter groups into one copy)
def place(self,datasets,component=0,tagged=False,split=True):
def place(self,datasets,constituent=0,tagged=False,split=True):
"""
Distribute datasets onto geometry and return Table or (split) dictionary of Tables.
Must not mix nodal end cell data.
Only data within
- inc?????/constituent/*_*/*
- inc?????/materialpoint/*_*/*
- inc?????/geometry/*
- inc*/phase/*/*
- inc*/homogenization/*/*
- inc*/geometry/*
are considered.
Parameters
----------
datasets : iterable or str
component : int
homogenization component to consider for constituent data
constituent : int
Constituent to consider for phase data
tagged : bool
tag Table.column name with '#component'
tag Table.column name with '#constituent'
defaults to False
split : bool
split Table by increment and return dictionary of Tables
defaults to True
"""
sets = datasets if hasattr(datasets,'__iter__') and not isinstance(datasets,str) \
else [datasets]
tag = f'#{component}' if tagged else ''
sets = datasets if hasattr(datasets,'__iter__') and not isinstance(datasets,str) else \
[datasets]
tag = f'#{constituent}' if tagged else ''
tbl = {} if split else None
inGeom = {}
inData = {}
@ -328,15 +372,15 @@ class Result:
key = '/'.join([prop,name+tag])
if key not in inGeom:
if prop == 'geometry':
inGeom[key] = inData[key] = np.arange(self.Nmaterialpoints)
elif prop == 'constituent':
inGeom[key] = np.where(f['mapping/cellResults/constituent'][:,component]['Name'] == str.encode(name))[0]
inData[key] = f['mapping/cellResults/constituent'][inGeom[key],component]['Position']
else:
inGeom[key] = np.where(f['mapping/cellResults/materialpoint']['Name'] == str.encode(name))[0]
inData[key] = f['mapping/cellResults/materialpoint'][inGeom[key].tolist()]['Position']
inGeom[key] = inData[key] = np.arange(self.N_materialpoints)
elif prop == 'phase':
inGeom[key] = np.where(f['mapping/phase'][:,constituent]['Name'] == str.encode(name))[0]
inData[key] = f['mapping/phase'][inGeom[key],constituent]['Position']
elif prop == 'homogenization':
inGeom[key] = np.where(f['mapping/homogenization']['Name'] == str.encode(name))[0]
inData[key] = f['mapping/homogenization'][inGeom[key].tolist()]['Position']
shape = np.shape(f[path])
data = np.full((self.Nmaterialpoints,) + (shape[1:] if len(shape)>1 else (1,)),
data = np.full((self.N_materialpoints,) + (shape[1:] if len(shape)>1 else (1,)),
np.nan,
dtype=np.dtype(f[path]))
data[inGeom[key]] = (f[path] if len(shape)>1 else np.expand_dims(f[path],1))[inData[key]]
@ -345,12 +389,12 @@ class Result:
try:
tbl[inc].add(path,data)
except KeyError:
tbl[inc] = Table(data.reshape(self.Nmaterialpoints,-1),{path:data.shape[1:]})
tbl[inc] = Table(data.reshape(self.N_materialpoints,-1),{path:data.shape[1:]})
else:
try:
tbl.add(path,data)
except AttributeError:
tbl = Table(data.reshape(self.Nmaterialpoints,-1),{path:data.shape[1:]})
tbl = Table(data.reshape(self.N_materialpoints,-1),{path:data.shape[1:]})
return tbl
@ -360,8 +404,8 @@ class Result:
Return groups that contain all requested datasets.
Only groups within
- inc*/constituent/*/*
- inc*/materialpoint/*/*
- inc*/phase/*/*
- inc*/homogenization/*/*
- inc*/geometry/*
are considered as they contain user-relevant data.
@ -393,7 +437,7 @@ class Result:
with h5py.File(self.fname,'r') as f:
for i in self.iterate('increments'):
for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
for o,p in zip(['phases','homogenizations'],['out_type_ph','out_type_ho']):
for oo in self.iterate(o):
for pp in self.iterate(p):
group = '/'.join([i,o[:-1],oo,pp]) # o[:-1]: plural/singular issue
@ -412,7 +456,7 @@ class Result:
with h5py.File(self.fname,'r') as f:
for i in self.iterate('increments'):
message += f'\n{i} ({self.times[self.increments.index(i)]}s)\n'
for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
for o,p in zip(['phases','homogenizations'],['out_type_ph','out_type_ho']):
message += f' {o[:-1]}\n'
for oo in self.iterate(o):
message += f' {oo}\n'
@ -422,8 +466,13 @@ class Result:
for d in f[group].keys():
try:
dataset = f['/'.join([group,d])]
unit = f" / {dataset.attrs['Unit'].decode()}" if 'Unit' in dataset.attrs else ''
description = dataset.attrs['Description'].decode()
if 'Unit' in dataset.attrs:
unit = f" / {dataset.attrs['Unit']}" if h5py3 else \
f" / {dataset.attrs['Unit'].decode()}"
else:
unit = ''
description = dataset.attrs['Description'] if h5py3 else \
dataset.attrs['Description'].decode()
message += f' {d}{unit}: {description}\n'
except KeyError:
pass
@ -441,7 +490,7 @@ class Result:
path.append(k)
except KeyError:
pass
for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
for o,p in zip(['phases','homogenizations'],['out_type_ph','out_type_ho']):
for oo in self.iterate(o):
for pp in self.iterate(p):
k = '/'.join([i,o[:-1],oo,pp,label])
@ -453,19 +502,6 @@ class Result:
return path
def get_constituent_ID(self,c=0):
"""Pointwise constituent ID."""
with h5py.File(self.fname,'r') as f:
names = f['/mapping/cellResults/constituent']['Name'][:,c].astype('str')
return np.array([int(n.split('_')[0]) for n in names.tolist()],dtype=np.int32)
def get_crystal_structure(self): # ToDo: extension to multi constituents/phase
"""Info about the crystal structure."""
with h5py.File(self.fname,'r') as f:
return f[self.get_dataset_location('orientation')[0]].attrs['Lattice'].astype('str') # np.bytes_ to string
def enable_user_function(self,func):
globals()[func.__name__]=func
print(f'Function {func.__name__} enabled in add_calculation.')
@ -476,9 +512,21 @@ class Result:
Dataset for all points/cells.
If more than one path is given, the dataset is composed of the individual contributions.
Parameters
----------
path : list of strings
The name of the datasets to consider.
c : int, optional
The constituent to consider. Defaults to 0.
plain: boolean, optional
Convert into plain numpy datatype.
Only relevant for compound datatype, e.g. the orientation.
Defaults to False.
"""
with h5py.File(self.fname,'r') as f:
shape = (self.Nmaterialpoints,) + np.shape(f[path[0]])[1:]
shape = (self.N_materialpoints,) + np.shape(f[path[0]])[1:]
if len(shape) == 1: shape = shape +(1,)
dataset = np.full(shape,np.nan,dtype=np.dtype(f[path[0]]))
for pa in path:
@ -488,17 +536,17 @@ class Result:
dataset = np.array(f[pa])
continue
p = np.where(f['mapping/cellResults/constituent'][:,c]['Name'] == str.encode(label))[0]
p = np.where(f['mapping/phase'][:,c]['Name'] == str.encode(label))[0]
if len(p)>0:
u = (f['mapping/cellResults/constituent']['Position'][p,c])
u = (f['mapping/phase']['Position'][p,c])
a = np.array(f[pa])
if len(a.shape) == 1:
a=a.reshape([a.shape[0],1])
dataset[p,:] = a[u,:]
p = np.where(f['mapping/cellResults/materialpoint']['Name'] == str.encode(label))[0]
p = np.where(f['mapping/homogenization']['Name'] == str.encode(label))[0]
if len(p)>0:
u = (f['mapping/cellResults/materialpoint']['Position'][p.tolist()])
u = (f['mapping/homogenization']['Position'][p.tolist()])
a = np.array(f[pa])
if len(a.shape) == 1:
a=a.reshape([a.shape[0],1])
@ -589,19 +637,19 @@ class Result:
@staticmethod
def _add_Cauchy(P,F):
def _add_stress_Cauchy(P,F):
return {
'data': mechanics.Cauchy(P['data'],F['data']),
'data': mechanics.stress_Cauchy(P['data'],F['data']),
'label': 'sigma',
'meta': {
'Unit': P['meta']['Unit'],
'Description': "Cauchy stress calculated "
f"from {P['label']} ({P['meta']['Description']})"
f" and {F['label']} ({F['meta']['Description']})",
'Creator': 'add_Cauchy'
'Creator': 'add_stress_Cauchy'
}
}
def add_Cauchy(self,P='P',F='F'):
def add_stress_Cauchy(self,P='P',F='F'):
"""
Add Cauchy stress calculated from first Piola-Kirchhoff stress and deformation gradient.
@ -613,7 +661,7 @@ class Result:
Label of the dataset containing the deformation gradient. Defaults to ‘F’.
"""
self._add_generic_pointwise(self._add_Cauchy,{'P':P,'F':F})
self._add_generic_pointwise(self._add_stress_Cauchy,{'P':P,'F':F})
@staticmethod
@ -643,7 +691,7 @@ class Result:
@staticmethod
def _add_deviator(T):
return {
'data': mechanics.deviatoric_part(T['data']),
'data': tensor.deviatoric(T['data']),
'label': f"s_{T['label']}",
'meta': {
'Unit': T['meta']['Unit'],
@ -674,7 +722,7 @@ class Result:
label,p = 'Minimum',0
return {
'data': mechanics.eigenvalues(T_sym['data'])[:,p],
'data': tensor.eigenvalues(T_sym['data'])[:,p],
'label': f"lambda_{eigenvalue}({T_sym['label']})",
'meta' : {
'Unit': T_sym['meta']['Unit'],
@ -706,7 +754,7 @@ class Result:
elif eigenvalue == 'min':
label,p = 'minimum',0
return {
'data': mechanics.eigenvectors(T_sym['data'])[:,p],
'data': tensor.eigenvectors(T_sym['data'])[:,p],
'label': f"v_{eigenvalue}({T_sym['label']})",
'meta' : {
'Unit': '1',
@ -734,9 +782,11 @@ class Result:
@staticmethod
def _add_IPF_color(q,l):
m = util.scale_to_coprime(np.array(l))
o = Orientation(Rotation(rfn.structured_to_unstructured(q['data'])),
lattice = q['meta']['Lattice'])
try:
lattice = {'fcc':'cF','bcc':'cI','hex':'hP'}[q['meta']['Lattice']]
except KeyError:
lattice = q['meta']['Lattice']
o = Orientation(rotation = (rfn.structured_to_unstructured(q['data'])),lattice=lattice)
return {
'data': np.uint8(o.IPF_color(l)*255),
@ -788,20 +838,27 @@ class Result:
@staticmethod
def _add_Mises(T_sym):
t = 'strain' if T_sym['meta']['Unit'] == '1' else \
'stress'
def _add_equivalent_Mises(T_sym,kind):
k = kind
if k is None:
if T_sym['meta']['Unit'] == '1':
k = 'strain'
elif T_sym['meta']['Unit'] == 'Pa':
k = 'stress'
if k not in ['stress', 'strain']:
raise ValueError('invalid von Mises kind {kind}')
return {
'data': (mechanics.Mises_strain if t=='strain' else mechanics.Mises_stress)(T_sym['data']),
'data': (mechanics.equivalent_strain_Mises if k=='strain' else \
mechanics.equivalent_stress_Mises)(T_sym['data']),
'label': f"{T_sym['label']}_vM",
'meta': {
'Unit': T_sym['meta']['Unit'],
'Description': f"Mises equivalent {t} of {T_sym['label']} ({T_sym['meta']['Description']})",
'Description': f"Mises equivalent {k} of {T_sym['label']} ({T_sym['meta']['Description']})",
'Creator': 'add_Mises'
}
}
def add_Mises(self,T_sym):
def add_equivalent_Mises(self,T_sym,kind=None):
"""
Add the equivalent Mises stress or strain of a symmetric tensor.
@ -809,9 +866,12 @@ class Result:
----------
T_sym : str
Label of symmetric tensorial stress or strain dataset.
kind : {'stress', 'strain', None}, optional
Kind of the von Mises equivalent. Defaults to None, in which case
it is selected based on the unit of the dataset ('1' -> strain, 'Pa' -> stress').
"""
self._add_generic_pointwise(self._add_Mises,{'T_sym':T_sym})
self._add_generic_pointwise(self._add_equivalent_Mises,{'T_sym':T_sym},{'kind':kind})
@staticmethod
@ -853,19 +913,19 @@ class Result:
@staticmethod
def _add_PK2(P,F):
def _add_stress_second_Piola_Kirchhoff(P,F):
return {
'data': mechanics.PK2(P['data'],F['data']),
'data': mechanics.stress_second_Piola_Kirchhoff(P['data'],F['data']),
'label': 'S',
'meta': {
'Unit': P['meta']['Unit'],
'Description': "2. Piola-Kirchhoff stress calculated "
f"from {P['label']} ({P['meta']['Description']})"
f" and {F['label']} ({F['meta']['Description']})",
'Creator': 'add_PK2'
'Creator': 'add_stress_second_Piola_Kirchhoff'
}
}
def add_PK2(self,P='P',F='F'):
def add_stress_second_Piola_Kirchhoff(self,P='P',F='F'):
"""
Add second Piola-Kirchhoff stress calculated from first Piola-Kirchhoff stress and deformation gradient.
@ -877,59 +937,64 @@ class Result:
Label of deformation gradient dataset. Defaults to ‘F’.
"""
self._add_generic_pointwise(self._add_PK2,{'P':P,'F':F})
self._add_generic_pointwise(self._add_stress_second_Piola_Kirchhoff,{'P':P,'F':F})
# The add_pole functionality needs discussion.
# The new Crystal object can perform such a calculation but the outcome depends on the lattice parameters
# as well as on whether a direction or plane is concerned (see the DAMASK_examples/pole_figure notebook).
# Below code appears to be too simplistic.
# @staticmethod
# def _add_pole(q,p,polar):
# pole = np.array(p)
# unit_pole = pole/np.linalg.norm(pole)
# m = util.scale_to_coprime(pole)
# rot = Rotation(q['data'].view(np.double).reshape(-1,4))
#
# rotatedPole = rot @ np.broadcast_to(unit_pole,rot.shape+(3,)) # rotate pole according to crystal orientation
# xy = rotatedPole[:,0:2]/(1.+abs(unit_pole[2])) # stereographic projection
# coords = xy if not polar else \
# np.block([np.sqrt(xy[:,0:1]*xy[:,0:1]+xy[:,1:2]*xy[:,1:2]),np.arctan2(xy[:,1:2],xy[:,0:1])])
# return {
# 'data': coords,
# 'label': 'p^{}_[{} {} {})'.format(u'rφ' if polar else 'xy',*m),
# 'meta' : {
# 'Unit': '1',
# 'Description': '{} coordinates of stereographic projection of pole (direction/plane) in crystal frame'\
# .format('Polar' if polar else 'Cartesian'),
# 'Creator': 'add_pole'
# }
# }
# def add_pole(self,q,p,polar=False):
# """
# Add coordinates of stereographic projection of given pole in crystal frame.
#
# Parameters
# ----------
# q : str
# Label of the dataset containing the crystallographic orientation as quaternions.
# p : numpy.array of shape (3)
# Crystallographic direction or plane.
# polar : bool, optional
# Give pole in polar coordinates. Defaults to False.
#
# """
# self._add_generic_pointwise(self._add_pole,{'q':q},{'p':p,'polar':polar})
@staticmethod
def _add_pole(q,p,polar):
pole = np.array(p)
unit_pole = pole/np.linalg.norm(pole)
m = util.scale_to_coprime(pole)
rot = Rotation(q['data'].view(np.double).reshape(-1,4))
rotatedPole = rot @ np.broadcast_to(unit_pole,rot.shape+(3,)) # rotate pole according to crystal orientation
xy = rotatedPole[:,0:2]/(1.+abs(unit_pole[2])) # stereographic projection
coords = xy if not polar else \
np.block([np.sqrt(xy[:,0:1]*xy[:,0:1]+xy[:,1:2]*xy[:,1:2]),np.arctan2(xy[:,1:2],xy[:,0:1])])
def _add_rotation(F):
return {
'data': coords,
'label': 'p^{}_[{} {} {})'.format(u'rφ' if polar else 'xy',*m),
'meta' : {
'Unit': '1',
'Description': '{} coordinates of stereographic projection of pole (direction/plane) in crystal frame'\
.format('Polar' if polar else 'Cartesian'),
'Creator': 'add_pole'
}
}
def add_pole(self,q,p,polar=False):
"""
Add coordinates of stereographic projection of given pole in crystal frame.
Parameters
----------
q : str
Label of the dataset containing the crystallographic orientation as quaternions.
p : numpy.array of shape (3)
Crystallographic direction or plane.
polar : bool, optional
Give pole in polar coordinates. Defaults to False.
"""
self._add_generic_pointwise(self._add_pole,{'q':q},{'p':p,'polar':polar})
@staticmethod
def _add_rotational_part(F):
return {
'data': mechanics.rotational_part(F['data']),
'data': mechanics.rotation(F['data']).as_matrix(),
'label': f"R({F['label']})",
'meta': {
'Unit': F['meta']['Unit'],
'Description': f"Rotational part of {F['label']} ({F['meta']['Description']})",
'Creator': 'add_rotational_part'
'Creator': 'add_rotation'
}
}
def add_rotational_part(self,F):
def add_rotation(self,F):
"""
Add rotational part of a deformation gradient.
@ -939,13 +1004,13 @@ class Result:
Label of deformation gradient dataset.
"""
self._add_generic_pointwise(self._add_rotational_part,{'F':F})
self._add_generic_pointwise(self._add_rotation,{'F':F})
@staticmethod
def _add_spherical(T):
return {
'data': mechanics.spherical_part(T['data']),
'data': tensor.spherical(T['data'],False),
'label': f"p_{T['label']}",
'meta': {
'Unit': T['meta']['Unit'],
@ -967,21 +1032,21 @@ class Result:
@staticmethod
def _add_strain_tensor(F,t,m):
def _add_strain(F,t,m):
return {
'data': mechanics.strain_tensor(F['data'],t,m),
'data': mechanics.strain(F['data'],t,m),
'label': f"epsilon_{t}^{m}({F['label']})",
'meta': {
'Unit': F['meta']['Unit'],
'Description': f"Strain tensor of {F['label']} ({F['meta']['Description']})",
'Creator': 'add_strain_tensor'
'Creator': 'add_strain'
}
}
def add_strain_tensor(self,F='F',t='V',m=0.0):
def add_strain(self,F='F',t='V',m=0.0):
"""
Add strain tensor of a deformation gradient.
For details refer to damask.mechanics.strain_tensor
For details refer to damask.mechanics.strain
Parameters
----------
@ -994,13 +1059,13 @@ class Result:
Order of the strain calculation. Defaults to ‘0.0’.
"""
self._add_generic_pointwise(self._add_strain_tensor,{'F':F},{'t':t,'m':m})
self._add_generic_pointwise(self._add_strain,{'F':F},{'t':t,'m':m})
@staticmethod
def _add_stretch_tensor(F,t):
return {
'data': (mechanics.left_stretch if t.upper() == 'V' else mechanics.right_stretch)(F['data']),
'data': (mechanics.stretch_left if t.upper() == 'V' else mechanics.stretch_right)(F['data']),
'label': f"{t}({F['label']})",
'meta': {
'Unit': F['meta']['Unit'],
@ -1035,7 +1100,7 @@ class Result:
loc = f[group+'/'+label]
datasets_in[arg]={'data' :loc[()],
'label':label,
'meta': {k:v.decode() for k,v in loc.attrs.items()}}
'meta': {k:(v if h5py3 else v.decode()) for k,v in loc.attrs.items()}}
lock.release()
r = func(**datasets_in,**args)
return [group,r]
@ -1080,17 +1145,21 @@ class Result:
if self._allow_modification and result[0]+'/'+result[1]['label'] in f:
dataset = f[result[0]+'/'+result[1]['label']]
dataset[...] = result[1]['data']
dataset.attrs['Overwritten'] = 'Yes'.encode()
dataset.attrs['Overwritten'] = 'Yes' if h5py3 else \
'Yes'.encode()
else:
dataset = f[result[0]].create_dataset(result[1]['label'],data=result[1]['data'])
now = datetime.datetime.now().astimezone()
dataset.attrs['Created'] = now.strftime('%Y-%m-%d %H:%M:%S%z').encode()
dataset.attrs['Created'] = now.strftime('%Y-%m-%d %H:%M:%S%z') if h5py3 else \
now.strftime('%Y-%m-%d %H:%M:%S%z').encode()
for l,v in result[1]['meta'].items():
dataset.attrs[l]=v.encode()
creator = f"damask.Result.{dataset.attrs['Creator'].decode()} v{damask.version}"
dataset.attrs['Creator'] = creator.encode()
dataset.attrs[l]=v if h5py3 else v.encode()
creator = dataset.attrs['Creator'] if h5py3 else \
dataset.attrs['Creator'].decode()
dataset.attrs['Creator'] = f"damask.Result.{creator} v{damask.version}" if h5py3 else \
f"damask.Result.{creator} v{damask.version}".encode()
except (OSError,RuntimeError) as err:
print(f'Could not add dataset: {err}.')
@ -1107,7 +1176,7 @@ class Result:
This works only for scalar, 3-vector and 3x3-tensor data.
Selection is not taken into account.
"""
if len(self.constituents) != 1 or not self.structured:
if self.N_constituents != 1 or not self.structured:
raise NotImplementedError('XDMF only available for grid results with 1 constituent.')
xdmf=ET.Element('Xdmf')
@ -1158,9 +1227,11 @@ class Result:
delta.text="{} {} {}".format(*(self.size/self.grid))
type_map = defaultdict(lambda:'Matrix', ( ((),'Scalar'), ((3,),'Vector'), ((3,3),'Tensor')) )
with h5py.File(self.fname,'r') as f:
attributes.append(ET.SubElement(grid, 'Attribute'))
attributes[-1].attrib={'Name': 'u',
attributes[-1].attrib={'Name': 'u / m',
'Center': 'Node',
'AttributeType': 'Vector'}
data_items.append(ET.SubElement(attributes[-1], 'DataItem'))
@ -1169,7 +1240,7 @@ class Result:
'Dimensions': '{} {} {} 3'.format(*(self.grid+1))}
data_items[-1].text=f'{os.path.split(self.fname)[1]}:/{inc}/geometry/u_n'
for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
for o,p in zip(['phases','homogenizations'],['out_type_ph','out_type_ho']):
for oo in getattr(self,o):
for pp in getattr(self,p):
g = '/'.join([inc,o[:-1],oo,pp])
@ -1177,19 +1248,21 @@ class Result:
name = '/'.join([g,l])
shape = f[name].shape[1:]
dtype = f[name].dtype
prec = f[name].dtype.itemsize
if (shape not in [(1,), (3,), (3,3)]) or dtype != np.float64: continue
if dtype != np.float64: continue
prec = f[name].dtype.itemsize
unit = f[name].attrs['Unit'] if h5py3 else f[name].attrs['Unit'].decode()
attributes.append(ET.SubElement(grid, 'Attribute'))
attributes[-1].attrib={'Name': name.split('/',2)[2],
'Center': 'Cell',
'AttributeType': 'Tensor'}
attributes[-1].attrib={'Name': name.split('/',2)[2]+f' / {unit}',
'Center': 'Cell',
'AttributeType': type_map[shape]}
data_items.append(ET.SubElement(attributes[-1], 'DataItem'))
data_items[-1].attrib={'Format': 'HDF',
'NumberType': 'Float',
'Precision': f'{prec}',
'Dimensions': '{} {} {} {}'.format(*self.grid,np.prod(shape))}
'Dimensions': '{} {} {} {}'.format(*self.grid,1 if shape == () else
np.prod(shape))}
data_items[-1].text=f'{os.path.split(self.fname)[1]}:{name}'
with open(self.fname.with_suffix('.xdmf').name,'w') as f:
@ -1212,58 +1285,53 @@ class Result:
if mode.lower()=='cell':
if self.structured:
v = VTK.from_rectilinearGrid(self.grid,self.size,self.origin)
v = VTK.from_rectilinear_grid(self.grid,self.size,self.origin)
else:
with h5py.File(self.fname,'r') as f:
v = VTK.from_unstructuredGrid(f['/geometry/x_n'][()],
f['/geometry/T_c'][()]-1,
f['/geometry/T_c'].attrs['VTK_TYPE'].decode())
v = VTK.from_unstructured_grid(f['/geometry/x_n'][()],
f['/geometry/T_c'][()]-1,
f['/geometry/T_c'].attrs['VTK_TYPE'] if h5py3 else \
f['/geometry/T_c'].attrs['VTK_TYPE'].decode())
elif mode.lower()=='point':
v = VTK.from_polyData(self.cell_coordinates())
v = VTK.from_poly_data(self.cell_coordinates)
N_digits = int(np.floor(np.log10(max(1,int(self.increments[-1][3:])))))+1
for inc in util.show_progress(self.iterate('increments'),len(self.selection['increments'])):
materialpoints_backup = self.selection['materialpoints'].copy()
self.pick('materialpoints',False)
picked_backup_ho = self.selection['homogenizations'].copy()
self.pick('homogenizations',False)
for label in (labels if isinstance(labels,list) else [labels]):
for p in self.iterate('con_physics'):
if p != 'generic':
for c in self.iterate('constituents'):
x = self.get_dataset_location(label)
if len(x) == 0:
for o in self.iterate('out_type_ph'):
for c in range(self.N_constituents):
prefix = '' if self.N_constituents == 1 else f'constituent{c}/'
if o != 'mechanics':
for _ in self.iterate('phases'):
path = self.get_dataset_location(label)
if len(path) == 0:
continue
array = self.read_dataset(path,c)
v.add(array,prefix+path[0].split('/',1)[1]+f' / {self._get_attribute(path[0],"Unit")}')
else:
paths = self.get_dataset_location(label)
if len(paths) == 0:
continue
array = self.read_dataset(x,0)
v.add(array,'1_'+x[0].split('/',1)[1]) #ToDo: hard coded 1!
else:
x = self.get_dataset_location(label)
if len(x) == 0:
continue
array = self.read_dataset(x,0)
ph_name = re.compile(r'(?<=(constituent\/))(.*?)(?=(generic))') # identify phase name
dset_name = '1_' + re.sub(ph_name,r'',x[0].split('/',1)[1]) # removing phase name
v.add(array,dset_name)
self.pick('materialpoints',materialpoints_backup)
array = self.read_dataset(paths,c)
ph_name = re.compile(r'(?<=(phase\/))(.*?)(?=(mechanics))') # identify phase name
dset_name = prefix+re.sub(ph_name,r'',paths[0].split('/',1)[1]) # remove phase name
v.add(array,dset_name+f' / {self._get_attribute(paths[0],"Unit")}')
self.pick('homogenizations',picked_backup_ho)
constituents_backup = self.selection['constituents'].copy()
self.pick('constituents',False)
picked_backup_ph = self.selection['phases'].copy()
self.pick('phases',False)
for label in (labels if isinstance(labels,list) else [labels]):
for p in self.iterate('mat_physics'):
if p != 'generic':
for m in self.iterate('materialpoints'):
x = self.get_dataset_location(label)
if len(x) == 0:
continue
array = self.read_dataset(x,0)
v.add(array,'1_'+x[0].split('/',1)[1]) #ToDo: why 1_?
else:
x = self.get_dataset_location(label)
if len(x) == 0:
continue
array = self.read_dataset(x,0)
v.add(array,'1_'+x[0].split('/',1)[1])
self.pick('constituents',constituents_backup)
for _ in self.iterate('out_type_ho'):
paths = self.get_dataset_location(label)
if len(paths) == 0:
continue
array = self.read_dataset(paths)
v.add(array,paths[0].split('/',1)[1]+f' / {self._get_attribute(paths[0],"Unit")}')
self.pick('phases',picked_backup_ph)
u = self.read_dataset(self.get_dataset_location('u_n' if mode.lower() == 'cell' else 'u_p'))
v.add(u,'u')

454
python/damask/_rotation.py
View File

@ -1,6 +1,6 @@
import numpy as np
from . import mechanics
from . import tensor
from . import util
from . import grid_filters
@ -13,18 +13,18 @@ _R1 = (3.*np.pi/4.)**(1./3.)
class Rotation:
u"""
Orientation stored with functionality for conversion to different representations.
Rotation with functionality for conversion between different representations.
The following conventions apply:
- coordinate frames are right-handed.
- a rotation angle ω is taken to be positive for a counterclockwise rotation
- Coordinate frames are right-handed.
- A rotation angle ω is taken to be positive for a counterclockwise rotation
when viewing from the end point of the rotation axis towards the origin.
- rotations will be interpreted in the passive sense.
- Rotations will be interpreted in the passive sense.
- Euler angle triplets are implemented using the Bunge convention,
with the angular ranges as [0,2π], [0,π], [0,2π].
- the rotation angle ω is limited to the interval [0,π].
- the real part of a quaternion is positive, Re(q) > 0
with angular ranges of [0,2π], [0,π], [0,2π].
- The rotation angle ω is limited to the interval [0,π].
- The real part of a quaternion is positive, Re(q) > 0
- P = -1 (as default).
Examples
@ -33,7 +33,7 @@ class Rotation:
coordinates "b" expressed in system "B":
- b = Q @ a
- b = np.dot(Q.asMatrix(),a)
- b = np.dot(Q.as_matrix(),a)
References
----------
@ -44,20 +44,70 @@ class Rotation:
__slots__ = ['quaternion']
def __init__(self,quaternion = np.array([1.0,0.0,0.0,0.0])):
def __init__(self,rotation = np.array([1.0,0.0,0.0,0.0])):
"""
Initializes to identity unless specified.
Initialize rotation object.
Parameters
----------
quaternion : numpy.ndarray, optional
rotation : list, numpy.ndarray, Rotation, optional
Unit quaternion in positive real hemisphere.
Use .from_quaternion to perform a sanity check.
Defaults to no rotation.
"""
if quaternion.shape[-1] != 4:
raise ValueError('Not a quaternion')
self.quaternion = quaternion.copy()
if isinstance(rotation,Rotation):
self.quaternion = rotation.quaternion.copy()
elif np.array(rotation).shape[-1] == 4:
self.quaternion = np.array(rotation)
else:
raise TypeError('"rotation" is neither a Rotation nor a quaternion')
def __repr__(self):
"""Represent rotation as unit quaternion, rotation matrix, and Bunge-Euler angles."""
if self == Rotation():
return 'Rotation()'
else:
return f'Quaternions {self.shape}:\n'+str(self.quaternion) \
if self.quaternion.shape != (4,) else \
'\n'.join([
'Quaternion: (real={:.3f}, imag=<{:+.3f}, {:+.3f}, {:+.3f}>)'.format(*(self.quaternion)),
'Matrix:\n{}'.format(np.round(self.as_matrix(),8)),
'Bunge Eulers / deg: ({:3.2f}, {:3.2f}, {:3.2f})'.format(*self.as_Euler_angles(degrees=True)),
])
# ToDo: Check difference __copy__ vs __deepcopy__
def __copy__(self,**kwargs):
"""Copy."""
return self.__class__(rotation=kwargs['rotation'] if 'rotation' in kwargs else self.quaternion)
copy = __copy__
def __getitem__(self,item):
"""Return slice according to item."""
return self.copy() \
if self.shape == () else \
self.copy(rotation=self.quaternion[item+(slice(None),)] if isinstance(item,tuple) else self.quaternion[item])
def __eq__(self,other):
"""
Equal to other.
Equality is determined taking limited floating point precision into
account. See numpy.allclose for details.
Parameters
----------
other : Rotation
Rotation to check for equality.
"""
return np.prod(self.shape,dtype=int) == np.prod(other.shape,dtype=int) \
and np.allclose(self.quaternion,other.quaternion)
@property
@ -65,39 +115,36 @@ class Rotation:
return self.quaternion.shape[:-1]
# ToDo: Check difference __copy__ vs __deepcopy__
def __copy__(self):
"""Copy."""
return self.__class__(self.quaternion)
copy = __copy__
def __repr__(self):
"""Orientation displayed as unit quaternion, rotation matrix, and Bunge-Euler angles."""
if self.quaternion.shape != (4,):
return 'Quaternions:\n'+str(self.quaternion) # ToDo: could be nicer ...
return '\n'.join([
'Quaternion: (real={:.3f}, imag=<{:+.3f}, {:+.3f}, {:+.3f}>)'.format(*(self.quaternion)),
'Matrix:\n{}'.format(np.round(self.as_matrix(),8)),
'Bunge Eulers / deg: ({:3.2f}, {:3.2f}, {:3.2f})'.format(*self.as_Eulers(degrees=True)),
])
def __getitem__(self,item):
"""Iterate over leading/leftmost dimension of Rotation array."""
if self.shape == (): return self.copy()
if isinstance(item,tuple) and len(item) >= len(self):
raise IndexError('Too many indices')
return self.__class__(self.quaternion[item])
def __len__(self):
"""Length of leading/leftmost dimension of Rotation array."""
return 0 if self.shape == () else self.shape[0]
def __matmul__(self, other):
def __invert__(self):
"""Inverse rotation (backward rotation)."""
dup = self.copy()
dup.quaternion[...,1:] *= -1
return dup
def __pow__(self,pwr):
"""
Raise quaternion to power.
Equivalent to performing the rotation 'pwr' times.
Parameters
----------
pwr : float
Power to raise quaternion to.
"""
phi = np.arccos(self.quaternion[...,0:1])
p = self.quaternion[...,1:]/np.linalg.norm(self.quaternion[...,1:],axis=-1,keepdims=True)
return self.copy(rotation=Rotation(np.block([np.cos(pwr*phi),np.sin(pwr*phi)*p]))._standardize())
def __matmul__(self,other):
"""
Rotation of vector, second or fourth order tensor, or rotation object.
@ -112,14 +159,14 @@ class Rotation:
Rotated vector, second or fourth order tensor, or rotation object.
"""
if isinstance(other, Rotation):
if isinstance(other,Rotation):
q_m = self.quaternion[...,0:1]
p_m = self.quaternion[...,1:]
q_o = other.quaternion[...,0:1]
p_o = other.quaternion[...,1:]
q = (q_m*q_o - np.einsum('...i,...i',p_m,p_o).reshape(self.shape+(1,)))
p = q_m*p_o + q_o*p_m + _P * np.cross(p_m,p_o)
return self.__class__(np.block([q,p]))._standardize()
return Rotation(np.block([q,p]))._standardize()
elif isinstance(other,np.ndarray):
if self.shape + (3,) == other.shape:
@ -146,27 +193,89 @@ class Rotation:
def _standardize(self):
"""Standardize (ensure positive real hemisphere)."""
"""Standardize quaternion (ensure positive real hemisphere)."""
self.quaternion[self.quaternion[...,0] < 0.0] *= -1
return self
def inverse(self):
"""In-place inverse rotation (backward rotation)."""
self.quaternion[...,1:] *= -1
return self
def __invert__(self):
"""Inverse rotation (backward rotation)."""
return self.copy().inverse()
def append(self,other):
"""Extend rotation array along first dimension with other array."""
return self.copy(rotation=np.vstack((self.quaternion,other.quaternion)))
def inversed(self):
"""Inverse rotation (backward rotation)."""
return ~ self
def flatten(self,order = 'C'):
"""Flatten quaternion array."""
return self.copy(rotation=self.quaternion.reshape((-1,4),order=order))
def reshape(self,shape,order = 'C'):
"""Reshape quaternion array."""
if isinstance(shape,(int,np.integer)): shape = (shape,)
return self.copy(rotation=self.quaternion.reshape(tuple(shape)+(4,),order=order))
def broadcast_to(self,shape,mode = 'right'):
"""
Broadcast quaternion array to shape.
Parameters
----------
shape : tuple
Shape of broadcasted array.
mode : str, optional
Where to preferentially locate missing dimensions.
Either 'left' or 'right' (default).
"""
if isinstance(shape,(int,np.integer)): shape = (shape,)
return self.copy(rotation=np.broadcast_to(self.quaternion.reshape(util.shapeshifter(self.shape,shape,mode)+(4,)),
shape+(4,)))
def average(self,weights = None):
"""
Average rotations along last dimension.
Parameters
----------
weights : list of floats, optional
Relative weight of each rotation.
Returns
-------
average : Rotation
Weighted average of original Rotation field.
References
----------
Quaternion averaging
F. Landis Markley, Yang Cheng, John L. Crassidis, Yaakov Oshman
Journal of Guidance, Control, and Dynamics 30(4):1193-1197, 2007
10.2514/1.28949
"""
def _M(quat):
"""Intermediate representation supporting quaternion averaging."""
return np.einsum('...i,...j',quat,quat)
if not weights:
weights = np.ones(self.shape,dtype=float)
eig, vec = np.linalg.eig(np.sum(_M(self.quaternion) * weights[...,np.newaxis,np.newaxis],axis=-3) \
/np.sum( weights[...,np.newaxis,np.newaxis],axis=-3))
return Rotation.from_quaternion(np.real(
np.squeeze(
np.take_along_axis(vec,
eig.argmax(axis=-1)[...,np.newaxis,np.newaxis],
axis=-1),
axis=-1)),
accept_homomorph = True)
def misorientation(self,other):
"""
Get Misorientation.
Calculate misorientation from self to other Rotation.
Parameters
----------
@ -177,33 +286,6 @@ class Rotation:
return other@~self
def broadcast_to(self,shape):
if isinstance(shape,(int,np.integer)): shape = (shape,)
if self.shape == ():
q = np.broadcast_to(self.quaternion,shape+(4,))
else:
q = np.block([np.broadcast_to(self.quaternion[...,0:1],shape).reshape(shape+(1,)),
np.broadcast_to(self.quaternion[...,1:2],shape).reshape(shape+(1,)),
np.broadcast_to(self.quaternion[...,2:3],shape).reshape(shape+(1,)),
np.broadcast_to(self.quaternion[...,3:4],shape).reshape(shape+(1,))])
return self.__class__(q)
def average(self,other): #ToDo: discuss calling for vectors
"""
Calculate the average rotation.
Parameters
----------
other : Rotation
Rotation from which the average is rotated.
"""
if self.quaternion.shape != (4,) or other.quaternion.shape != (4,):
raise NotImplementedError('Support for multiple rotations missing')
return Rotation.from_average([self,other])
################################################################################################
# convert to different orientation representations (numpy arrays)
@ -219,8 +301,8 @@ class Rotation:
"""
return self.quaternion.copy()
def as_Eulers(self,
degrees = False):
def as_Euler_angles(self,
degrees = False):
"""
Represent as Bunge-Euler angles.
@ -277,8 +359,8 @@ class Rotation:
"""
return Rotation._qu2om(self.quaternion)
def as_Rodrigues(self,
vector = False):
def as_Rodrigues_vector(self,
compact = False):
"""
Represent as Rodrigues-Frank vector with separated axis and angle argument.
@ -296,7 +378,7 @@ class Rotation:
"""
ro = Rotation._qu2ro(self.quaternion)
if vector:
if compact:
with np.errstate(invalid='ignore'):
return ro[...,:3]*ro[...,3:4]
else:
@ -309,7 +391,7 @@ class Rotation:
Returns
-------
h : numpy.ndarray of shape (...,3)
Homochoric vector: (h_1, h_2, h_3), ǀhǀ < 1/2*π^(2/3).
Homochoric vector: (h_1, h_2, h_3), ǀhǀ < (3/4*π)^(1/3).
"""
return Rotation._qu2ho(self.quaternion)
@ -326,20 +408,6 @@ class Rotation:
"""
return Rotation._qu2cu(self.quaternion)
@property
def M(self): # ToDo not sure about the name: as_M or M? we do not have a from_M
"""
Intermediate representation supporting quaternion averaging.
References
----------
F. Landis Markley et al., Journal of Guidance, Control, and Dynamics 30(4):1193-1197, 2007
https://doi.org/10.2514/1.28949
"""
return np.einsum('...i,...j',self.quaternion,self.quaternion)
################################################################################################
# Static constructors. The input data needs to follow the conventions, options allow to
# relax the conventions.
@ -347,7 +415,7 @@ class Rotation:
def from_quaternion(q,
accept_homomorph = False,
P = -1,
acceptHomomorph = None): # old name (for compatibility)
**kwargs):
"""
Initialize from quaternion.
@ -363,15 +431,13 @@ class Rotation:
Convention used. Defaults to -1.
"""
if acceptHomomorph is not None:
accept_homomorph = acceptHomomorph # for compatibility
qu = np.array(q,dtype=float)
if qu.shape[:-2:-1] != (4,):
raise ValueError('Invalid shape.')
if abs(P) != 1:
raise ValueError('P ∉ {-1,1}')
if P == 1: qu[...,1:4] *= -1
qu[...,1:4] *= -P
if accept_homomorph:
qu[qu[...,0] < 0.0] *= -1
else:
@ -383,8 +449,9 @@ class Rotation:
return Rotation(qu)
@staticmethod
def from_Eulers(phi,
degrees = False):
def from_Euler_angles(phi,
degrees = False,
**kwargs):
"""
Initialize from Bunge-Euler angles.
@ -411,7 +478,8 @@ class Rotation:
def from_axis_angle(axis_angle,
degrees = False,
normalize = False,
P = -1):
P = -1,
**kwargs):
"""
Initialize from Axis angle pair.
@ -434,7 +502,7 @@ class Rotation:
if abs(P) != 1:
raise ValueError('P ∉ {-1,1}')
if P == 1: ax[...,0:3] *= -1
ax[...,0:3] *= -P
if degrees: ax[..., 3] = np.radians(ax[...,3])
if normalize: ax[...,0:3] /= np.linalg.norm(ax[...,0:3],axis=-1,keepdims=True)
if np.any(ax[...,3] < 0.0) or np.any(ax[...,3] > np.pi):
@ -448,14 +516,15 @@ class Rotation:
@staticmethod
def from_basis(basis,
orthonormal = True,
reciprocal = False):
reciprocal = False,
**kwargs):
"""
Initialize from lattice basis vectors.
Parameters
----------
basis : numpy.ndarray of shape (...,3,3)
Three lattice basis vectors in three dimensions.
Three three-dimensional lattice basis vectors.
orthonormal : boolean, optional
Basis is strictly orthonormal, i.e. is free of stretch components. Defaults to True.
reciprocal : boolean, optional
@ -463,15 +532,15 @@ class Rotation:
"""
om = np.array(basis,dtype=float)
if om.shape[:-3:-1] != (3,3):
if om.shape[-2:] != (3,3):
raise ValueError('Invalid shape.')
if reciprocal:
om = np.linalg.inv(mechanics.transpose(om)/np.pi) # transform reciprocal basis set
om = np.linalg.inv(tensor.transpose(om)/np.pi) # transform reciprocal basis set
orthonormal = False # contains stretch
if not orthonormal:
(U,S,Vh) = np.linalg.svd(om) # singular value decomposition
om = np.einsum('...ij,...jl->...il',U,Vh)
om = np.einsum('...ij,...jl',U,Vh)
if not np.all(np.isclose(np.linalg.det(om),1.0)):
raise ValueError('Orientation matrix has determinant ≠ 1.')
if not np.all(np.isclose(np.einsum('...i,...i',om[...,0],om[...,1]), 0.0)) \
@ -482,7 +551,7 @@ class Rotation:
return Rotation(Rotation._om2qu(om))
@staticmethod
def from_matrix(R):
def from_matrix(R,**kwargs):
"""
Initialize from rotation matrix.
@ -495,17 +564,46 @@ class Rotation:
return Rotation.from_basis(R)
@staticmethod
def from_Rodrigues(rho,
normalize = False,
P = -1):
def from_parallel(a,b,
**kwargs):
"""
Initialize from Rodrigues-Frank vector.
Initialize from pairs of two orthogonal lattice basis vectors.
Parameters
----------
a : numpy.ndarray of shape (...,2,3)
Two three-dimensional lattice vectors of first orthogonal basis.
b : numpy.ndarray of shape (...,2,3)
Corresponding three-dimensional lattice vectors of second basis.
"""
a_ = np.array(a)
b_ = np.array(b)
if a_.shape[-2:] != (2,3) or b_.shape[-2:] != (2,3) or a_.shape != b_.shape:
raise ValueError('Invalid shape.')
am = np.stack([ a_[...,0,:],
a_[...,1,:],
np.cross(a_[...,0,:],a_[...,1,:]) ],axis=-2)
bm = np.stack([ b_[...,0,:],
b_[...,1,:],
np.cross(b_[...,0,:],b_[...,1,:]) ],axis=-2)
return Rotation.from_basis(np.swapaxes(am/np.linalg.norm(am,axis=-1,keepdims=True),-1,-2))\
.misorientation(Rotation.from_basis(np.swapaxes(bm/np.linalg.norm(bm,axis=-1,keepdims=True),-1,-2)))
@staticmethod
def from_Rodrigues_vector(rho,
normalize = False,
P = -1,
**kwargs):
"""
Initialize from Rodrigues-Frank vector (angle separated from axis).
Parameters
----------
rho : numpy.ndarray of shape (...,4)
Rodrigues-Frank vector (angle separated from axis).
(n_1, n_2, n_3, tan(ω/2)), ǀnǀ = 1 and ω ∈ [0,π].
Rodrigues-Frank vector. (n_1, n_2, n_3, tan(ω/2)), ǀnǀ = 1 and ω ∈ [0,π].
normalize : boolean, optional
Allow ǀnǀ ≠ 1. Defaults to False.
P : int ∈ {-1,1}, optional
@ -518,7 +616,7 @@ class Rotation:
if abs(P) != 1:
raise ValueError('P ∉ {-1,1}')
if P == 1: ro[...,0:3] *= -1
ro[...,0:3] *= -P
if normalize: ro[...,0:3] /= np.linalg.norm(ro[...,0:3],axis=-1,keepdims=True)
if np.any(ro[...,3] < 0.0):
raise ValueError('Rodrigues vector rotation angle not positive.')
@ -529,7 +627,8 @@ class Rotation:
@staticmethod
def from_homochoric(h,
P = -1):
P = -1,
**kwargs):
"""
Initialize from homochoric vector.
@ -547,7 +646,7 @@ class Rotation:
if abs(P) != 1:
raise ValueError('P ∉ {-1,1}')
if P == 1: ho *= -1
ho *= -P
if np.any(np.linalg.norm(ho,axis=-1) >_R1+1e-9):
raise ValueError('Homochoric coordinate outside of the sphere.')
@ -556,7 +655,8 @@ class Rotation:
@staticmethod
def from_cubochoric(c,
P = -1):
P = -1,
**kwargs):
"""
Initialize from cubochoric vector.
@ -577,46 +677,15 @@ class Rotation:
if np.abs(np.max(cu)) > np.pi**(2./3.) * 0.5+1e-9:
raise ValueError('Cubochoric coordinate outside of the cube.')
ho = Rotation._cu2ho(cu)
if P == 1: ho *= -1
ho = -P * Rotation._cu2ho(cu)
return Rotation(Rotation._ho2qu(ho))
@staticmethod
def from_average(rotations,weights = None):
"""
Average rotation.
References
----------
F. Landis Markley et al., Journal of Guidance, Control, and Dynamics 30(4):1193-1197, 2007
https://doi.org/10.2514/1.28949
Parameters
----------
rotations : list of Rotations
Rotations to average from
weights : list of floats, optional
Weights for each rotation used for averaging
"""
if not all(isinstance(item, Rotation) for item in rotations):
raise TypeError('Only instances of Rotation can be averaged.')
N = len(rotations)
if not weights:
weights = np.ones(N,dtype='i')
for i,(r,n) in enumerate(zip(rotations,weights)):
M = r.M * n if i == 0 \
else M + r.M * n # noqa add (multiples) of this rotation to average noqa
eig, vec = np.linalg.eig(M/N)
return Rotation.from_quaternion(np.real(vec.T[eig.argmax()]),accept_homomorph = True)
@staticmethod
def from_random(shape=None,seed=None):
def from_random(shape = None,
rng_seed = None,
**kwargs):
"""
Draw random rotation.
@ -627,18 +696,13 @@ class Rotation:
shape : tuple of ints, optional
Shape of the sample. Defaults to None which gives a
single rotation
seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
A seed to initialize the BitGenerator. Defaults to None.
If None, then fresh, unpredictable entropy will be pulled from the OS.
"""
rng = np.random.default_rng(seed)
if shape is None:
r = rng.random(3)
elif hasattr(shape, '__iter__'):
r = rng.random(tuple(shape)+(3,))
else:
r = rng.random((shape,3))
rng = np.random.default_rng(rng_seed)
r = rng.random(3 if shape is None else tuple(shape)+(3,) if hasattr(shape, '__iter__') else (shape,3))
A = np.sqrt(r[...,2])
B = np.sqrt(1.0-r[...,2])
@ -647,14 +711,17 @@ class Rotation:
np.cos(2.0*np.pi*r[...,1])*B,
np.sin(2.0*np.pi*r[...,0])*A],axis=-1)
return Rotation(q.reshape(r.shape[:-1]+(4,)) if shape is not None else q)._standardize()
# for compatibility
__mul__ = __matmul__
return Rotation(q if shape is None else q.reshape(r.shape[:-1]+(4,)))._standardize()
@staticmethod
def from_ODF(weights,Eulers,N=500,degrees=True,fractions=True,seed=None):
def from_ODF(weights,
phi,
N = 500,
degrees = True,
fractions = True,
rng_seed = None,
**kwargs):
"""
Sample discrete values from a binned ODF.
@ -662,7 +729,7 @@ class Rotation:
----------
weights : numpy.ndarray of shape (n)
Texture intensity values (probability density or volume fraction) at Euler grid points.
Eulers : numpy.ndarray of shape (n,3)
phi : numpy.ndarray of shape (n,3)
Grid coordinates in Euler space at which weights are defined.
N : integer, optional
Number of discrete orientations to be sampled from the given ODF.
@ -672,7 +739,7 @@ class Rotation:
fractions : boolean, optional
ODF values correspond to volume fractions, not probability density.
Defaults to True.
seed: {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
rng_seed: {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
A seed to initialize the BitGenerator. Defaults to None, i.e. unpredictable entropy
will be pulled from the OS.
@ -695,19 +762,24 @@ class Rotation:
"""
def _dg(eu,deg):
"""Return infinitesimal Euler space volume of bin(s)."""
Eulers_sorted = eu[np.lexsort((eu[:,0],eu[:,1],eu[:,2]))]
steps,size,_ = grid_filters.cell_coord0_gridSizeOrigin(Eulers_sorted)
phi_sorted = eu[np.lexsort((eu[:,0],eu[:,1],eu[:,2]))]
steps,size,_ = grid_filters.cell_coord0_gridSizeOrigin(phi_sorted)
delta = np.radians(size/steps) if deg else size/steps
return delta[0]*2.0*np.sin(delta[1]/2.0)*delta[2] / 8.0 / np.pi**2 * np.sin(np.radians(eu[:,1]) if deg else eu[:,1])
dg = 1.0 if fractions else _dg(Eulers,degrees)
dg = 1.0 if fractions else _dg(phi,degrees)
dV_V = dg * np.maximum(0.0,weights.squeeze())
return Rotation.from_Eulers(Eulers[util.hybrid_IA(dV_V,N,seed)],degrees)
return Rotation.from_Euler_angles(phi[util.hybrid_IA(dV_V,N,rng_seed)],degrees)
@staticmethod
def from_spherical_component(center,sigma,N=500,degrees=True,seed=None):
def from_spherical_component(center,
sigma,
N = 500,
degrees = True,
rng_seed = None,
**kwargs):
"""
Calculate set of rotations with Gaussian distribution around center.
@ -721,12 +793,12 @@ class Rotation:
Number of samples, defaults to 500.
degrees : boolean, optional
sigma is given in degrees.
seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
A seed to initialize the BitGenerator. Defaults to None, i.e. unpredictable entropy
will be pulled from the OS.
"""
rng = np.random.default_rng(seed)
rng = np.random.default_rng(rng_seed)
sigma = np.radians(sigma) if degrees else sigma
u,Theta = (rng.random((N,2)) * 2.0 * np.array([1,np.pi]) - np.array([1.0, 0])).T
omega = abs(rng.normal(scale=sigma,size=N))
@ -738,7 +810,13 @@ class Rotation:
@staticmethod
def from_fiber_component(alpha,beta,sigma=0.0,N=500,degrees=True,seed=None):
def from_fiber_component(alpha,
beta,
sigma = 0.0,
N = 500,
degrees = True,
rng_seed = None,
**kwargs):
"""
Calculate set of rotations with Gaussian distribution around direction.
@ -755,12 +833,12 @@ class Rotation:
Number of samples, defaults to 500.
degrees : boolean, optional
sigma, alpha, and beta are given in degrees.
seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
A seed to initialize the BitGenerator. Defaults to None, i.e. unpredictable entropy
will be pulled from the OS.
"""
rng = np.random.default_rng(seed)
rng = np.random.default_rng(rng_seed)
sigma_,alpha_,beta_ = map(np.radians,(sigma,alpha,beta)) if degrees else (sigma,alpha,beta)
d_cr = np.array([np.sin(alpha_[0])*np.cos(alpha_[1]), np.sin(alpha_[0])*np.sin(alpha_[1]), np.cos(alpha_[0])])

7
python/damask/_table.py
View File

@ -31,7 +31,7 @@ class Table:
def __repr__(self):
"""Brief overview."""
return util.srepr(self.comments)+'\n'+self.data.__repr__()
return '\n'.join(['# '+c for c in self.comments])+'\n'+self.data.__repr__()
def __len__(self):
"""Number of rows."""
@ -159,7 +159,7 @@ class Table:
comments = [util.execution_stamp('Table','from_ang')]
for line in content:
if line.startswith('#'):
comments.append(line.strip())
comments.append(line.split('#',1)[1].strip())
else:
break
@ -175,7 +175,7 @@ class Table:
@property
def labels(self):
return list(self.shapes.keys())
return list(self.shapes)
def get(self,label):
@ -222,6 +222,7 @@ class Table:
dup.data[label] = data.reshape(dup.data[label].shape)
return dup
def add(self,label,data,info=None):
"""
Add column data.

6
python/damask/_test.py
View File

@ -316,12 +316,6 @@ class Test:
return self.compare_Array(refName,curName)
def compare_ArrayCurCur(self,cur0,cur1):
cur0Name = self.fileInCurrent(cur0)
cur1Name = self.fileInCurrent(cur1)
return self.compare_Array(cur0Name,cur1Name)
def compare_Table(self,headings0,file0,
headings1,file1,
normHeadings='',normType=None,

30
python/damask/_vtk.py
View File

@ -1,3 +1,4 @@
import os
import multiprocessing as mp
from pathlib import Path
@ -36,7 +37,7 @@ class VTK:
@staticmethod
def from_rectilinearGrid(grid,size,origin=np.zeros(3)):
def from_rectilinear_grid(grid,size,origin=np.zeros(3)):
"""
Create VTK of type vtk.vtkRectilinearGrid.
@ -64,7 +65,7 @@ class VTK:
@staticmethod
def from_unstructuredGrid(nodes,connectivity,cell_type):
def from_unstructured_grid(nodes,connectivity,cell_type):
"""
Create VTK of type vtk.vtkUnstructuredGrid.
@ -96,7 +97,7 @@ class VTK:
@staticmethod
def from_polyData(points):
def from_poly_data(points):
"""
Create VTK of type vtk.polyData.
@ -108,11 +109,18 @@ class VTK:
Spatial position of the points.
"""
N = points.shape[0]
vtk_points = vtk.vtkPoints()
vtk_points.SetData(np_to_vtk(points))
vtk_cells = vtk.vtkCellArray()
vtk_cells.SetNumberOfCells(N)
vtk_cells.SetCells(N,np_to_vtkIdTypeArray(np.stack((np.ones (N,dtype=np.int64),
np.arange(N,dtype=np.int64)),axis=1).ravel(),deep=True))
vtk_data = vtk.vtkPolyData()
vtk_data.SetPoints(vtk_points)
vtk_data.SetVerts(vtk_cells)
return VTK(vtk_data)
@ -131,6 +139,8 @@ class VTK:
vtkUnstructuredGrid, and vtkPolyData.
"""
if not os.path.isfile(fname): # vtk has a strange error handling
raise FileNotFoundError(f'no such file: {fname}')
ext = Path(fname).suffix
if ext == '.vtk' or dataset_type is not None:
reader = vtk.vtkGenericDataObjectReader()
@ -164,6 +174,7 @@ class VTK:
return VTK(vtk_data)
@staticmethod
def _write(writer):
"""Wrapper for parallel writing."""
@ -189,11 +200,10 @@ class VTK:
elif isinstance(self.vtk_data,vtk.vtkPolyData):
writer = vtk.vtkXMLPolyDataWriter()
default_ext = writer.GetDefaultFileExtension()
default_ext = '.'+writer.GetDefaultFileExtension()
ext = Path(fname).suffix
if ext and ext != '.'+default_ext:
raise ValueError(f'Given extension {ext} does not match default .{default_ext}')
writer.SetFileName(str(Path(fname).with_suffix('.'+default_ext)))
writer.SetFileName(str(fname)+(default_ext if default_ext != ext else ''))
if compress:
writer.SetCompressorTypeToZLib()
else:
@ -238,10 +248,10 @@ class VTK:
else data).reshape(N_data,-1),deep=True) # avoid large files
d.SetName(label)
if N_data == N_cells:
self.vtk_data.GetCellData().AddArray(d)
elif N_data == N_points:
if N_data == N_points:
self.vtk_data.GetPointData().AddArray(d)
elif N_data == N_cells:
self.vtk_data.GetCellData().AddArray(d)
else:
raise ValueError(f'Cell / point count ({N_cells} / {N_points}) differs from data ({N_data}).')
elif isinstance(data,pd.DataFrame):

420
python/damask/lattice.py Normal file
View File

@ -0,0 +1,420 @@
import numpy as _np
kinematics = {
'cF': {
'slip' : _np.array([
[+0,+1,-1 , +1,+1,+1],
[-1,+0,+1 , +1,+1,+1],
[+1,-1,+0 , +1,+1,+1],
[+0,-1,-1 , -1,-1,+1],
[+1,+0,+1 , -1,-1,+1],
[-1,+1,+0 , -1,-1,+1],
[+0,-1,+1 , +1,-1,-1],
[-1,+0,-1 , +1,-1,-1],
[+1,+1,+0 , +1,-1,-1],
[+0,+1,+1 , -1,+1,-1],
[+1,+0,-1 , -1,+1,-1],
[-1,-1,+0 , -1,+1,-1],
[+1,+1,+0 , +1,-1,+0],
[+1,-1,+0 , +1,+1,+0],
[+1,+0,+1 , +1,+0,-1],
[+1,+0,-1 , +1,+0,+1],
[+0,+1,+1 , +0,+1,-1],
[+0,+1,-1 , +0,+1,+1],
],'d'),
'twin' : _np.array([
[-2, 1, 1, 1, 1, 1],
[ 1,-2, 1, 1, 1, 1],
[ 1, 1,-2, 1, 1, 1],
[ 2,-1, 1, -1,-1, 1],
[-1, 2, 1, -1,-1, 1],
[-1,-1,-2, -1,-1, 1],
[-2,-1,-1, 1,-1,-1],
[ 1, 2,-1, 1,-1,-1],
[ 1,-1, 2, 1,-1,-1],
[ 2, 1,-1, -1, 1,-1],
[-1,-2,-1, -1, 1,-1],
[-1, 1, 2, -1, 1,-1],
],dtype=float),
},
'cI': {
'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 , +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,+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 , +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,+1,+2],
[+1,-1,+1 , -1,+1,+2],
[-1,+1,+1 , +1,-1,+2],
[+1,+1,+1 , +1,+1,-2],
],'d'),
'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, 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, 1, 2],
[ 1,-1, 1, -1, 1, 2],
[-1, 1, 1, 1,-1, 2],
[ 1, 1, 1, 1, 1,-2],
],dtype=float),
},
'hP': {
'slip' : _np.array([
[+2,-1,-1,+0 , +0,+0,+0,+1],
[-1,+2,-1,+0 , +0,+0,+0,+1],
[-1,-1,+2,+0 , +0,+0,+0,+1],
[+2,-1,-1,+0 , +0,+1,-1,+0],
[-1,+2,-1,+0 , -1,+0,+1,+0],
[-1,-1,+2,+0 , +1,-1,+0,+0],
[-1,+1,+0,+0 , +1,+1,-2,+0],
[+0,-1,+1,+0 , -2,+1,+1,+0],
[+1,+0,-1,+0 , +1,-2,+1,+0],
[-1,+2,-1,+0 , +1,+0,-1,+1],
[-2,+1,+1,+0 , +0,+1,-1,+1],
[-1,-1,+2,+0 , -1,+1,+0,+1],
[+1,-2,+1,+0 , -1,+0,+1,+1],
[+2,-1,-1,+0 , +0,-1,+1,+1],
[+1,+1,-2,+0 , +1,-1,+0,+1],
[-2,+1,+1,+3 , +1,+0,-1,+1],
[-1,-1,+2,+3 , +1,+0,-1,+1],
[-1,-1,+2,+3 , +0,+1,-1,+1],
[+1,-2,+1,+3 , +0,+1,-1,+1],
[+1,-2,+1,+3 , -1,+1,+0,+1],
[+2,-1,-1,+3 , -1,+1,+0,+1],
[+2,-1,-1,+3 , -1,+0,+1,+1],
[+1,+1,-2,+3 , -1,+0,+1,+1],
[+1,+1,-2,+3 , +0,-1,+1,+1],
[-1,+2,-1,+3 , +0,-1,+1,+1],
[-1,+2,-1,+3 , +1,-1,+0,+1],
[-2,+1,+1,+3 , +1,-1,+0,+1],
[-1,-1,+2,+3 , +1,+1,-2,+2],
[+1,-2,+1,+3 , -1,+2,-1,+2],
[+2,-1,-1,+3 , -2,+1,+1,+2],
[+1,+1,-2,+3 , -1,-1,+2,+2],
[-1,+2,-1,+3 , +1,-2,+1,+2],
[-2,+1,+1,+3 , +2,-1,-1,+2],
],'d'),
'twin' : _np.array([
[-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],
[ 1, -1, 0, 1, -1, 1, 0, 2],
[ 1, 0, -1, 1, -1, 0, 1, 2],
[ 0, 1, -1, 1, 0, -1, 1, 2],
[-1, 1, 0, 1, 1, -1, 0, 2],
[-1, -1, 2, 6, 1, 1, -2, 1], # shear = 1/(c/a) <11.6>{-1-1.1}
[ 1, -2, 1, 6, -1, 2, -1, 1],
[ 2, -1, -1, 6, -2, 1, 1, 1],
[ 1, 1, -2, 6, -1, -1, 2, 1],
[-1, 2, -1, 6, 1, -2, 1, 1],
[-2, 1, 1, 6, 2, -1, -1, 1],
[ 1, 0, -1, -2, 1, 0, -1, 1], # shear = (4(c/a)^2-9)/(4 sqrt(3) c/a) <10.-2>{10.1}
[ 0, 1, -1, -2, 0, 1, -1, 1],
[-1, 1, 0, -2, -1, 1, 0, 1],
[-1, 0, 1, -2, -1, 0, 1, 1],
[ 0, -1, 1, -2, 0, -1, 1, 1],
[ 1, -1, 0, -2, 1, -1, 0, 1],
[ 1, 1, -2, -3, 1, 1, -2, 2], # shear = 2((c/a)^2-2)/(3 c/a) <11.-3>{11.2}
[-1, 2, -1, -3, -1, 2, -1, 2],
[-2, 1, 1, -3, -2, 1, 1, 2],
[-1, -1, 2, -3, -1, -1, 2, 2],
[ 1, -2, 1, -3, 1, -2, 1, 2],
[ 2, -1, -1, -3, 2, -1, -1, 2],
],dtype=float),
},
}
# Kurdjomov--Sachs orientation relationship for fcc <-> bcc transformation
# from S. Morito et al., Journal of Alloys and Compounds 577:s587-s592, 2013
# also see K. Kitahara et al., Acta Materialia 54:1279-1288, 2006
relations = {
'KS': {
'cF' : _np.array([
[[ -1, 0, 1],[ 1, 1, 1]],
[[ -1, 0, 1],[ 1, 1, 1]],
[[ 0, 1, -1],[ 1, 1, 1]],
[[ 0, 1, -1],[ 1, 1, 1]],
[[ 1, -1, 0],[ 1, 1, 1]],
[[ 1, -1, 0],[ 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]],
[[ 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, 1, 0],[ -1, 1, 1]],
[[ 1, 1, 0],[ -1, 1, 1]],
[[ -1, 1, 0],[ 1, 1, -1]],
[[ -1, 1, 0],[ 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]],
],dtype=float),
'cI' : _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]],
[[ -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]],
[[ -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]],
[[ -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]],
],dtype=float),
},
'GT': {
'cF' : _np.array([
[[ -5,-12, 17],[ 1, 1, 1]],
[[ 17, -5,-12],[ 1, 1, 1]],
[[-12, 17, -5],[ 1, 1, 1]],
[[ 5, 12, 17],[ -1, -1, 1]],
[[-17, 5,-12],[ -1, -1, 1]],
[[ 12,-17, -5],[ -1, -1, 1]],
[[ -5, 12,-17],[ -1, 1, 1]],
[[ 17, 5, 12],[ -1, 1, 1]],
[[-12,-17, 5],[ -1, 1, 1]],
[[ 5,-12,-17],[ 1, -1, 1]],
[[-17, -5, 12],[ 1, -1, 1]],
[[ 12, 17, 5],[ 1, -1, 1]],
[[ -5, 17,-12],[ 1, 1, 1]],
[[-12, -5, 17],[ 1, 1, 1]],
[[ 17,-12, -5],[ 1, 1, 1]],
[[ 5,-17,-12],[ -1, -1, 1]],
[[ 12, 5, 17],[ -1, -1, 1]],
[[-17, 12, -5],[ -1, -1, 1]],
[[ -5,-17, 12],[ -1, 1, 1]],
[[-12, 5,-17],[ -1, 1, 1]],
[[ 17, 12, 5],[ -1, 1, 1]],
[[ 5, 17, 12],[ 1, -1, 1]],
[[ 12, -5,-17],[ 1, -1, 1]],
[[-17,-12, 5],[ 1, -1, 1]],
],dtype=float),
'cI' : _np.array([
[[-17, -7, 17],[ 1, 0, 1]],
[[ 17,-17, -7],[ 1, 1, 0]],
[[ -7, 17,-17],[ 0, 1, 1]],
[[ 17, 7, 17],[ -1, 0, 1]],
[[-17, 17, -7],[ -1, -1, 0]],
[[ 7,-17,-17],[ 0, -1, 1]],
[[-17, 7,-17],[ -1, 0, 1]],
[[ 17, 17, 7],[ -1, 1, 0]],
[[ -7,-17, 17],[ 0, 1, 1]],
[[ 17, -7,-17],[ 1, 0, 1]],
[[-17,-17, 7],[ 1, -1, 0]],
[[ 7, 17, 17],[ 0, -1, 1]],
[[-17, 17, -7],[ 1, 1, 0]],
[[ -7,-17, 17],[ 0, 1, 1]],
[[ 17, -7,-17],[ 1, 0, 1]],
[[ 17,-17, -7],[ -1, -1, 0]],
[[ 7, 17, 17],[ 0, -1, 1]],
[[-17, 7,-17],[ -1, 0, 1]],
[[-17,-17, 7],[ -1, 1, 0]],
[[ -7, 17,-17],[ 0, 1, 1]],
[[ 17, 7, 17],[ -1, 0, 1]],
[[ 17, 17, 7],[ 1, -1, 0]],
[[ 7,-17,-17],[ 0, -1, 1]],
[[-17, -7, 17],[ 1, 0, 1]],
],dtype=float),
},
'GT_prime': {
'cF' : _np.array([
[[ 0, 1, -1],[ 7, 17, 17]],
[[ -1, 0, 1],[ 17, 7, 17]],
[[ 1, -1, 0],[ 17, 17, 7]],
[[ 0, -1, -1],[ -7,-17, 17]],
[[ 1, 0, 1],[-17, -7, 17]],
[[ 1, -1, 0],[-17,-17, 7]],
[[ 0, 1, -1],[ 7,-17,-17]],
[[ 1, 0, 1],[ 17, -7,-17]],
[[ -1, -1, 0],[ 17,-17, -7]],
[[ 0, -1, -1],[ -7, 17,-17]],
[[ -1, 0, 1],[-17, 7,-17]],
[[ -1, -1, 0],[-17, 17, -7]],
[[ 0, -1, 1],[ 7, 17, 17]],
[[ 1, 0, -1],[ 17, 7, 17]],
[[ -1, 1, 0],[ 17, 17, 7]],
[[ 0, 1, 1],[ -7,-17, 17]],
[[ -1, 0, -1],[-17, -7, 17]],
[[ -1, 1, 0],[-17,-17, 7]],
[[ 0, -1, 1],[ 7,-17,-17]],
[[ -1, 0, -1],[ 17, -7,-17]],
[[ 1, 1, 0],[ 17,-17, -7]],
[[ 0, 1, 1],[ -7, 17,-17]],
[[ 1, 0, -1],[-17, 7,-17]],
[[ 1, 1, 0],[-17, 17, -7]],
],dtype=float),
'cI' : _np.array([
[[ 1, 1, -1],[ 12, 5, 17]],
[[ -1, 1, 1],[ 17, 12, 5]],
[[ 1, -1, 1],[ 5, 17, 12]],
[[ -1, -1, -1],[-12, -5, 17]],
[[ 1, -1, 1],[-17,-12, 5]],
[[ 1, -1, -1],[ -5,-17, 12]],
[[ -1, 1, -1],[ 12, -5,-17]],
[[ 1, 1, 1],[ 17,-12, -5]],
[[ -1, -1, 1],[ 5,-17,-12]],
[[ 1, -1, -1],[-12, 5,-17]],
[[ -1, -1, 1],[-17, 12, -5]],
[[ -1, -1, -1],[ -5, 17,-12]],
[[ 1, -1, 1],[ 12, 17, 5]],
[[ 1, 1, -1],[ 5, 12, 17]],
[[ -1, 1, 1],[ 17, 5, 12]],
[[ -1, 1, 1],[-12,-17, 5]],
[[ -1, -1, -1],[ -5,-12, 17]],
[[ -1, 1, -1],[-17, -5, 12]],
[[ -1, -1, 1],[ 12,-17, -5]],
[[ -1, 1, -1],[ 5,-12,-17]],
[[ 1, 1, 1],[ 17, -5,-12]],
[[ 1, 1, 1],[-12, 17, -5]],
[[ 1, -1, -1],[ -5, 12,-17]],
[[ 1, 1, -1],[-17, 5,-12]],
],dtype=float),
},
'NW': {
'cF' : _np.array([
[[ 2, -1, -1],[ 1, 1, 1]],
[[ -1, 2, -1],[ 1, 1, 1]],
[[ -1, -1, 2],[ 1, 1, 1]],
[[ -2, -1, -1],[ -1, 1, 1]],
[[ 1, 2, -1],[ -1, 1, 1]],
[[ 1, -1, 2],[ -1, 1, 1]],
[[ 2, 1, -1],[ 1, -1, 1]],
[[ -1, -2, -1],[ 1, -1, 1]],
[[ -1, 1, 2],[ 1, -1, 1]],
[[ 2, -1, 1],[ -1, -1, 1]],
[[ -1, 2, 1],[ -1, -1, 1]],
[[ -1, -1, -2],[ -1, -1, 1]],
],dtype=float),
'cI' : _np.array([
[[ 0, -1, 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],[ 0, 1, 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]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
],dtype=float),
},
'Pitsch': {
'cF' : _np.array([
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 0, 1, -1],[ 1, 0, 0]],
[[ -1, 0, 1],[ 0, 1, 0]],
[[ 1, -1, 0],[ 0, 0, 1]],
[[ 1, 0, -1],[ 0, 1, 0]],
[[ -1, 1, 0],[ 0, 0, 1]],
[[ 0, -1, 1],[ 1, 0, 0]],
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
],dtype=float),
'cI' : _np.array([
[[ 1, -1, 1],[ -1, 0, 1]],
[[ 1, 1, -1],[ 1, -1, 0]],
[[ -1, 1, 1],[ 0, 1, -1]],
[[ -1, 1, -1],[ 0, -1, -1]],
[[ -1, -1, 1],[ -1, 0, -1]],
[[ 1, -1, -1],[ -1, -1, 0]],
[[ 1, -1, -1],[ -1, 0, -1]],
[[ -1, 1, -1],[ -1, -1, 0]],
[[ -1, -1, 1],[ 0, -1, -1]],
[[ -1, 1, 1],[ 0, -1, 1]],
[[ 1, -1, 1],[ 1, 0, -1]],
[[ 1, 1, -1],[ -1, 1, 0]],
],dtype=float),
},
'Bain': {
'cF' : _np.array([
[[ 0, 1, 0],[ 1, 0, 0]],
[[ 0, 0, 1],[ 0, 1, 0]],
[[ 1, 0, 0],[ 0, 0, 1]],
],dtype=float),
'cI' : _np.array([
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
],dtype=float),
},
'Burgers' : {
'cI' : _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]],
[[ 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],[ 0, 1, 1]],
[[ 1, 1, -1],[ 0, 1, 1]],
[[ -1, 1, 1],[ 0, -1, 1]],
[[ 1, 1, 1],[ 0, -1, 1]],
],dtype=float),
'hP' : _np.array([
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
],dtype=float),
},
}

343
python/damask/mechanics.py
View File

@ -1,307 +1,282 @@
"""Finite-strain continuum mechanics."""
from . import tensor as _tensor
from . import _rotation
import numpy as _np
def Cauchy(P,F):
"""
Return Cauchy stress calculated from first Piola-Kirchhoff stress and deformation gradient.
Resulting tensor is symmetrized as the Cauchy stress needs to be symmetric.
def deformation_Cauchy_Green_left(F):
"""
Calculate left Cauchy-Green deformation tensor (Finger deformation tensor).
Parameters
----------
F : numpy.ndarray of shape (:,3,3) or (3,3)
F : numpy.ndarray of shape (...,3,3)
Deformation gradient.
P : numpy.ndarray of shape (:,3,3) or (3,3)
First Piola-Kirchhoff stress.
Returns
-------
B : numpy.ndarray of shape (...,3,3)
Left Cauchy-Green deformation tensor.
"""
if _np.shape(F) == _np.shape(P) == (3,3):
sigma = 1.0/_np.linalg.det(F) * _np.dot(P,F.T)
else:
sigma = _np.einsum('i,ijk,ilk->ijl',1.0/_np.linalg.det(F),P,F)
return symmetric(sigma)
return _np.matmul(F,_tensor.transpose(F))
def deviatoric_part(T):
def deformation_Cauchy_Green_right(F):
"""
Return deviatoric part of a tensor.
Calculate right Cauchy-Green deformation tensor.
Parameters
----------
T : numpy.ndarray of shape (:,3,3) or (3,3)
Tensor of which the deviatoric part is computed.
F : numpy.ndarray of shape (...,3,3)
Deformation gradient.
Returns
-------
C : numpy.ndarray of shape (...,3,3)
Right Cauchy-Green deformation tensor.
"""
return T - _np.eye(3)*spherical_part(T) if _np.shape(T) == (3,3) else \
T - _np.einsum('ijk,i->ijk',_np.broadcast_to(_np.eye(3),[T.shape[0],3,3]),spherical_part(T))
return _np.matmul(_tensor.transpose(F),F)
def eigenvalues(T_sym):
def equivalent_strain_Mises(epsilon):
"""
Return the eigenvalues, i.e. principal components, of a symmetric tensor.
The eigenvalues are sorted in ascending order, each repeated according to
its multiplicity.
Calculate the Mises equivalent of a strain tensor.
Parameters
----------
T_sym : numpy.ndarray of shape (:,3,3) or (3,3)
Symmetric tensor of which the eigenvalues are computed.
epsilon : numpy.ndarray of shape (...,3,3)
Symmetric strain tensor of which the von Mises equivalent is computed.
Returns
-------
epsilon_vM : numpy.ndarray of shape (...)
Von Mises equivalent strain of epsilon.
"""
return _np.linalg.eigvalsh(symmetric(T_sym))
return _equivalent_Mises(epsilon,2.0/3.0)
def eigenvectors(T_sym,RHS=False):
def equivalent_stress_Mises(sigma):
"""
Return eigenvectors of a symmetric tensor.
The eigenvalues are sorted in ascending order of their associated eigenvalues.
Calculate the Mises equivalent of a stress tensor.
Parameters
----------
T_sym : numpy.ndarray of shape (:,3,3) or (3,3)
Symmetric tensor of which the eigenvectors are computed.
RHS: bool, optional
Enforce right-handed coordinate system. Default is False.
sigma : numpy.ndarray of shape (...,3,3)
Symmetric stress tensor of which the von Mises equivalent is computed.
Returns
-------
sigma_vM : numpy.ndarray of shape (...)
Von Mises equivalent stress of sigma.
"""
(u,v) = _np.linalg.eigh(symmetric(T_sym))
if RHS:
if _np.shape(T_sym) == (3,3):
if _np.linalg.det(v) < 0.0: v[:,2] *= -1.0
else:
v[_np.linalg.det(v) < 0.0,:,2] *= -1.0
return v
def left_stretch(T):
"""
Return the left stretch of a tensor.
Parameters
----------
T : numpy.ndarray of shape (:,3,3) or (3,3)
Tensor of which the left stretch is computed.
"""
return _polar_decomposition(T,'V')[0]
return _equivalent_Mises(sigma,3.0/2.0)
def maximum_shear(T_sym):
"""
Return the maximum shear component of a symmetric tensor.
Calculate the maximum shear component of a symmetric tensor.
Parameters
----------
T_sym : numpy.ndarray of shape (:,3,3) or (3,3)
T_sym : numpy.ndarray of shape (...,3,3)
Symmetric tensor of which the maximum shear is computed.
Returns
-------
gamma_max : numpy.ndarray of shape (...)
Maximum shear of T_sym.
"""
w = eigenvalues(T_sym)
return (w[0] - w[2])*0.5 if _np.shape(T_sym) == (3,3) else \
(w[:,0] - w[:,2])*0.5
w = _tensor.eigenvalues(T_sym)
return (w[...,0] - w[...,2])*0.5
def Mises_strain(epsilon):
def rotation(T):
"""
Return the Mises equivalent of a strain tensor.
Calculate the rotational part of a tensor.
Parameters
----------
epsilon : numpy.ndarray of shape (:,3,3) or (3,3)
Symmetric strain tensor of which the von Mises equivalent is computed.
"""
return _Mises(epsilon,2.0/3.0)
def Mises_stress(sigma):
"""
Return the Mises equivalent of a stress tensor.
Parameters
----------
sigma : numpy.ndarray of shape (:,3,3) or (3,3)
Symmetric stress tensor of which the von Mises equivalent is computed.
"""
return _Mises(sigma,3.0/2.0)
def PK2(P,F):
"""
Calculate second Piola-Kirchhoff stress from first Piola-Kirchhoff stress and deformation gradient.
Parameters
----------
P : numpy.ndarray of shape (...,3,3) or (3,3)
First Piola-Kirchhoff stress.
F : numpy.ndarray of shape (...,3,3) or (3,3)
Deformation gradient.
"""
if _np.shape(F) == _np.shape(P) == (3,3):
S = _np.dot(_np.linalg.inv(F),P)
else:
S = _np.einsum('...jk,...kl->...jl',_np.linalg.inv(F),P)
return symmetric(S)
def right_stretch(T):
"""
Return the right stretch of a tensor.
Parameters
----------
T : numpy.ndarray of shape (:,3,3) or (3,3)
Tensor of which the right stretch is computed.
"""
return _polar_decomposition(T,'U')[0]
def rotational_part(T):
"""
Return the rotational part of a tensor.
Parameters
----------
T : numpy.ndarray of shape (:,3,3) or (3,3)
T : numpy.ndarray of shape (...,3,3)
Tensor of which the rotational part is computed.
"""
return _polar_decomposition(T,'R')[0]
def spherical_part(T,tensor=False):
"""
Return spherical (hydrostatic) part of a tensor.
Parameters
----------
T : numpy.ndarray of shape (:,3,3) or (3,3)
Tensor of which the hydrostatic part is computed.
tensor : bool, optional
Map spherical part onto identity tensor. Default is false
Returns
-------
R : damask.Rotation of shape (...)
Rotational part of the vector.
"""
if T.shape == (3,3):
sph = _np.trace(T)/3.0
return sph if not tensor else _np.eye(3)*sph
else:
sph = _np.trace(T,axis1=1,axis2=2)/3.0
if not tensor:
return sph
else:
return _np.einsum('ijk,i->ijk',_np.broadcast_to(_np.eye(3),(T.shape[0],3,3)),sph)
return _rotation.Rotation.from_matrix(_polar_decomposition(T,'R')[0])
def strain_tensor(F,t,m):
def strain(F,t,m):
"""
Return strain tensor calculated from deformation gradient.
Calculate strain tensor (Seth–Hill family).
For details refer to https://en.wikipedia.org/wiki/Finite_strain_theory and
https://de.wikipedia.org/wiki/Verzerrungstensor
Parameters
----------
F : numpy.ndarray of shape (:,3,3) or (3,3)
F : numpy.ndarray of shape (...,3,3)
Deformation gradient.
t : {‘V’, ‘U’}
Type of the polar decomposition, ‘V’ for left stretch tensor and ‘U’ for right stretch tensor.
Type of the polar decomposition, ‘V’ for left stretch tensor
and ‘U’ for right stretch tensor.
m : float
Order of the strain.
Returns
-------
epsilon : numpy.ndarray of shape (...,3,3)
Strain of F.
"""
F_ = F.reshape(1,3,3) if F.shape == (3,3) else F
if t == 'V':
B = _np.matmul(F_,transpose(F_))
w,n = _np.linalg.eigh(B)
w,n = _np.linalg.eigh(deformation_Cauchy_Green_left(F))
elif t == 'U':
C = _np.matmul(transpose(F_),F_)
w,n = _np.linalg.eigh(C)
w,n = _np.linalg.eigh(deformation_Cauchy_Green_right(F))
if m > 0.0:
eps = 1.0/(2.0*abs(m)) * (+ _np.matmul(n,_np.einsum('ij,ikj->ijk',w**m,n))
- _np.broadcast_to(_np.eye(3),[F_.shape[0],3,3]))
eps = 1.0/(2.0*abs(m)) * (+ _np.einsum('...j,...kj,...lj',w**m,n,n) - _np.eye(3))
elif m < 0.0:
eps = 1.0/(2.0*abs(m)) * (- _np.matmul(n,_np.einsum('ij,ikj->ijk',w**m,n))
+ _np.broadcast_to(_np.eye(3),[F_.shape[0],3,3]))
eps = 1.0/(2.0*abs(m)) * (- _np.einsum('...j,...kj,...lj',w**m,n,n) + _np.eye(3))
else:
eps = _np.matmul(n,_np.einsum('ij,ikj->ijk',0.5*_np.log(w),n))
eps = _np.einsum('...j,...kj,...lj',0.5*_np.log(w),n,n)
return eps.reshape(3,3) if _np.shape(F) == (3,3) else \
eps
return eps
def symmetric(T):
def stress_Cauchy(P,F):
"""
Return the symmetrized tensor.
Calculate the Cauchy stress (true stress).
Resulting tensor is symmetrized as the Cauchy stress needs to be symmetric.
Parameters
----------
T : numpy.ndarray of shape (...,3,3) or (3,3)
Tensor of which the symmetrized values are computed.
P : numpy.ndarray of shape (...,3,3)
First Piola-Kirchhoff stress.
F : numpy.ndarray of shape (...,3,3)
Deformation gradient.
Returns
-------
sigma : numpy.ndarray of shape (...,3,3)
Cauchy stress.
"""
return (T+transpose(T))*0.5
return _tensor.symmetric(_np.einsum('...,...ij,...kj',1.0/_np.linalg.det(F),P,F))
def transpose(T):
def stress_second_Piola_Kirchhoff(P,F):
"""
Return the transpose of a tensor.
Calculate the second Piola-Kirchhoff stress.
Resulting tensor is symmetrized as the second Piola-Kirchhoff stress
needs to be symmetric.
Parameters
----------
T : numpy.ndarray of shape (...,3,3) or (3,3)
Tensor of which the transpose is computed.
P : numpy.ndarray of shape (...,3,3)
First Piola-Kirchhoff stress.
F : numpy.ndarray of shape (...,3,3)
Deformation gradient.
Returns
-------
S : numpy.ndarray of shape (...,3,3)
Second Piola-Kirchhoff stress.
"""
return T.T if _np.shape(T) == (3,3) else \
_np.swapaxes(T,axis2=-2,axis1=-1)
return _tensor.symmetric(_np.einsum('...ij,...jk',_np.linalg.inv(F),P))
def stretch_left(T):
"""
Calculate left stretch of a tensor.
Parameters
----------
T : numpy.ndarray of shape (...,3,3)
Tensor of which the left stretch is computed.
Returns
-------
V : numpy.ndarray of shape (...,3,3)
Left stretch tensor from Polar decomposition of T.
"""
return _polar_decomposition(T,'V')[0]
def stretch_right(T):
"""
Calculate right stretch of a tensor.
Parameters
----------
T : numpy.ndarray of shape (...,3,3)
Tensor of which the right stretch is computed.
Returns
-------
U : numpy.ndarray of shape (...,3,3)
Left stretch tensor from Polar decomposition of T.
"""
return _polar_decomposition(T,'U')[0]
def _polar_decomposition(T,requested):
"""
Singular value decomposition.
Perform singular value decomposition.
Parameters
----------
T : numpy.ndarray of shape (:,3,3) or (3,3)
T : numpy.ndarray of shape (...,3,3)
Tensor of which the singular values are computed.
requested : iterable of str
Requested outputs: ‘R’ for the rotation tensor,
‘V’ for left stretch tensor and ‘U’ for right stretch tensor.
"""
u, s, vh = _np.linalg.svd(T)
R = _np.dot(u,vh) if _np.shape(T) == (3,3) else \
_np.einsum('ijk,ikl->ijl',u,vh)
u, _, vh = _np.linalg.svd(T)
R = _np.einsum('...ij,...jk',u,vh)
output = []
if 'R' in requested:
output.append(R)
if 'V' in requested:
output.append(_np.dot(T,R.T) if _np.shape(T) == (3,3) else _np.einsum('ijk,ilk->ijl',T,R))
output.append(_np.einsum('...ij,...kj',T,R))
if 'U' in requested:
output.append(_np.dot(R.T,T) if _np.shape(T) == (3,3) else _np.einsum('ikj,ikl->ijl',R,T))
output.append(_np.einsum('...ji,...jk',R,T))
if len(output) == 0:
raise ValueError('output needs to be out of V, R, U')
return tuple(output)
def _Mises(T_sym,s):
def _equivalent_Mises(T_sym,s):
"""
Base equation for Mises equivalent of a stres or strain tensor.
Base equation for Mises equivalent of a stress or strain tensor.
Parameters
----------
T_sym : numpy.ndarray of shape (:,3,3) or (3,3)
T_sym : numpy.ndarray of shape (...,3,3)
Symmetric tensor of which the von Mises equivalent is computed.
s : float
Scaling factor (2/3 for strain, 3/2 for stress).
"""
d = deviatoric_part(T_sym)
return _np.sqrt(s*(_np.sum(d**2.0))) if _np.shape(T_sym) == (3,3) else \
_np.sqrt(s*_np.einsum('ijk->i',d**2.0))
d = _tensor.deviatoric(T_sym)
return _np.sqrt(s*_np.sum(d**2.0,axis=(-1,-2)))

14
python/damask/seeds.py
View File

@ -1,3 +1,5 @@
"""Functionality for generation of seed points for Voronoi or Laguerre tessellation."""
from scipy import spatial as _spatial
import numpy as _np
@ -5,7 +7,7 @@ from . import util
from . import grid_filters
def from_random(size,N_seeds,grid=None,seed=None):
def from_random(size,N_seeds,grid=None,rng_seed=None):
"""
Random seeding in space.
@ -18,12 +20,12 @@ def from_random(size,N_seeds,grid=None,seed=None):
grid : numpy.ndarray of shape (3), optional.
If given, ensures that all seeds initiate one grain if using a
standard Voronoi tessellation.
seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
A seed to initialize the BitGenerator. Defaults to None.
If None, then fresh, unpredictable entropy will be pulled from the OS.
"""
rng = _np.random.default_rng(seed)
rng = _np.random.default_rng(rng_seed)
if grid is None:
coords = rng.random((N_seeds,3)) * size
else:
@ -34,7 +36,7 @@ def from_random(size,N_seeds,grid=None,seed=None):
return coords
def from_Poisson_disc(size,N_seeds,N_candidates,distance,periodic=True,seed=None):
def from_Poisson_disc(size,N_seeds,N_candidates,distance,periodic=True,rng_seed=None):
"""
Seeding in space according to a Poisson disc distribution.
@ -50,12 +52,12 @@ def from_Poisson_disc(size,N_seeds,N_candidates,distance,periodic=True,seed=None
Minimum acceptable distance to other seeds.
periodic : boolean, optional
Calculate minimum distance for periodically repeated grid.
seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
A seed to initialize the BitGenerator. Defaults to None.
If None, then fresh, unpredictable entropy will be pulled from the OS.
"""
rng = _np.random.default_rng(seed)
rng = _np.random.default_rng(rng_seed)
coords = _np.empty((N_seeds,3))
coords[0] = rng.random(3) * size

65
python/damask/solver/_marc.py
View File

@ -1,6 +1,7 @@
import subprocess
import shlex
import string
import re
import io
from pathlib import Path
from .. import environment
@ -8,7 +9,7 @@ from .. import environment
class Marc:
"""Wrapper to run DAMASK with MSCMarc."""
def __init__(self,version=environment.options['MARC_VERSION']):
def __init__(self,version=environment.options['MSC_VERSION']):
"""
Create a Marc solver object.
@ -27,7 +28,10 @@ class Marc:
path_MSC = environment.options['MSC_ROOT']
path_lib = Path(f'{path_MSC}/mentat{self.version}/shlib/linux64')
return path_lib if path_lib.is_dir() else None
if not path_lib.is_dir():
raise FileNotFoundError(f'library path "{path_lib}" not found')
return path_lib
@property
@ -36,10 +40,12 @@ class Marc:
path_MSC = environment.options['MSC_ROOT']
path_tools = Path(f'{path_MSC}/marc{self.version}/tools')
return path_tools if path_tools.is_dir() else None
if not path_tools.is_dir():
raise FileNotFoundError(f'tools path "{path_tools}" not found')
return path_tools
#--------------------------
def submit_job(self,
model,
job = 'job1',
@ -48,38 +54,37 @@ class Marc:
optimization = '',
):
usersub = environment.root_dir/'src/DAMASK_marc'
usersub = usersub.parent/(usersub.name + ('.f90' if compile else '.marc'))
if not usersub.is_file():
raise FileNotFoundError("DAMASK4Marc ({}) '{}' not found".format(('source' if compile else 'binary'),usersub))
raise FileNotFoundError(f'subroutine ({"source" if compile else "binary"}) "{usersub}" not found')
# Define options [see Marc Installation and Operation Guide, pp 23]
script = f'run_damask_{optimization}mp'
cmd = str(self.tools_path/Path(script)) + \
' -jid ' + model + '_' + job + \
' -nprocd 1 -autorst 0 -ci n -cr n -dcoup 0 -b no -v no'
if compile: cmd += ' -u ' + str(usersub) + ' -save y'
else: cmd += ' -prog ' + str(usersub.with_suffix(''))
print('job submission {} compilation: {}'.format(('with' if compile else 'without'),usersub))
if logfile: log = open(logfile, 'w')
cmd = str(self.tools_path/script) + \
' -jid ' + model+'_'+job + \
' -nprocd 1 -autorst 0 -ci n -cr n -dcoup 0 -b no -v no'
cmd += ' -u ' + str(usersub) + ' -save y' if compile else \
' -prog ' + str(usersub.with_suffix(''))
print(cmd)
process = subprocess.Popen(shlex.split(cmd),stdout = log,stderr = subprocess.STDOUT)
log.close()
process.wait()
#--------------------------
def exit_number_from_outFile(self,outFile=None):
exitnumber = -1
with open(outFile,'r') as fid_out:
for line in fid_out:
if (string.find(line,'tress iteration') != -1):
print(line)
elif (string.find(line,'Exit number') != -1):
substr = line[string.find(line,'Exit number'):len(line)]
exitnumber = int(substr[12:16])
if logfile is not None:
try:
f = open(logfile,'w+')
except TypeError:
f = logfile
else:
f = io.StringIO()
return exitnumber
proc = subprocess.Popen(shlex.split(cmd),stdout=f,stderr=subprocess.STDOUT)
proc.wait()
f.seek(0)
try:
v = int(re.search('Exit number ([0-9]+)',''.join(f.readlines())).group(1))
except (AttributeError,ValueError):
raise RuntimeError('Marc simulation failed (unknown return value)')
if v != 3004:
raise RuntimeError(f'Marc simulation failed ({v})')

131
python/damask/tensor.py Normal file
View File

@ -0,0 +1,131 @@
"""
Tensor operations.
Notes
-----
This is not a tensor class, but a collection of routines
to operate on numpy.ndarrays of shape (...,3,3).
"""
import numpy as _np
def deviatoric(T):
"""
Calculate deviatoric part of a tensor.
Parameters
----------
T : numpy.ndarray of shape (...,3,3)
Tensor of which the deviatoric part is computed.
Returns
-------
T' : numpy.ndarray of shape (...,3,3)
Deviatoric part of T.
"""
return T - spherical(T,tensor=True)
def eigenvalues(T_sym):
"""
Eigenvalues, i.e. principal components, of a symmetric tensor.
Parameters
----------
T_sym : numpy.ndarray of shape (...,3,3)
Symmetric tensor of which the eigenvalues are computed.
Returns
-------
lambda : numpy.ndarray of shape (...,3)
Eigenvalues of T_sym sorted in ascending order, each repeated
according to its multiplicity.
"""
return _np.linalg.eigvalsh(symmetric(T_sym))
def eigenvectors(T_sym,RHS=False):
"""
Eigenvectors of a symmetric tensor.
Parameters
----------
T_sym : numpy.ndarray of shape (...,3,3)
Symmetric tensor of which the eigenvectors are computed.
RHS: bool, optional
Enforce right-handed coordinate system. Defaults to False.
Returns
-------
x : numpy.ndarray of shape (...,3,3)
Eigenvectors of T_sym sorted in ascending order of their
associated eigenvalues.
"""
(u,v) = _np.linalg.eigh(symmetric(T_sym))
if RHS:
v[_np.linalg.det(v) < 0.0,:,2] *= -1.0
return v
def spherical(T,tensor=True):
"""
Calculate spherical part of a tensor.
Parameters
----------
T : numpy.ndarray of shape (...,3,3)
Tensor of which the spherical part is computed.
tensor : bool, optional
Map spherical part onto identity tensor. Defaults to True.
Returns
-------
p : numpy.ndarray of shape (...,3,3)
unless tensor == False: shape (...,)
Spherical part of tensor T. p is an isotropic tensor.
"""
sph = _np.trace(T,axis2=-2,axis1=-1)/3.0
return _np.einsum('...jk,...',_np.eye(3),sph) if tensor else sph
def symmetric(T):
"""
Symmetrize tensor.
Parameters
----------
T : numpy.ndarray of shape (...,3,3)
Tensor of which the symmetrized values are computed.
Returns
-------
T_sym : numpy.ndarray of shape (...,3,3)
Symmetrized tensor T.
"""
return (T+transpose(T))*0.5
def transpose(T):
"""
Transpose tensor.
Parameters
----------
T : numpy.ndarray of shape (...,3,3)
Tensor of which the transpose is computed.
Returns
-------
T.T : numpy.ndarray of shape (...,3,3)
Transpose of tensor T.
"""
return _np.swapaxes(T,axis2=-2,axis1=-1)

190
python/damask/util.py
View File

@ -3,6 +3,7 @@ import datetime
import os
import subprocess
import shlex
import re
import fractions
from functools import reduce
from optparse import Option
@ -16,14 +17,17 @@ __all__=[
'srepr',
'croak',
'report',
'emph','deemph','delete','strikeout',
'emph','deemph','warn','strikeout',
'execute',
'show_progress',
'scale_to_coprime',
'project_stereographic',
'hybrid_IA',
'return_message',
'extendableOption',
'execution_stamp'
'execution_stamp',
'shapeshifter', 'shapeblender',
'extend_docstring', 'extended_docstring'
]
####################################################################################################
@ -38,7 +42,7 @@ def srepr(arg,glue = '\n'):
arg : iterable
Items to join.
glue : str, optional
Defaults to \n.
Glue used for joining operation. Defaults to \n.
"""
if (not hasattr(arg, "strip") and
@ -52,6 +56,8 @@ def croak(what, newline = True):
"""
Write formated to stderr.
DEPRECATED
Parameters
----------
what : str or iterable
@ -68,7 +74,7 @@ def croak(what, newline = True):
def report(who = None,
what = None):
"""
Reports script and file name.
Report script and file name.
DEPRECATED
@ -80,16 +86,13 @@ def emph(what):
"""Formats string with emphasis."""
return bcolors.BOLD+srepr(what)+bcolors.ENDC
def deemph(what):
"""Formats string with deemphasis."""
return bcolors.DIM+srepr(what)+bcolors.ENDC
def delete(what):
"""Formats string as deleted."""
return bcolors.DIM+srepr(what)+bcolors.ENDC
def warn(what):
"""Formats string for warning."""
return bcolors.WARNING+emph(what)+bcolors.ENDC
def strikeout(what):
"""Formats string as strikeout."""
@ -160,7 +163,15 @@ def show_progress(iterable,N_iter=None,prefix='',bar_length=50):
def scale_to_coprime(v):
"""Scale vector to co-prime (relatively prime) integers."""
"""
Scale vector to co-prime (relatively prime) integers.
Parameters
----------
v : numpy.ndarray of shape (:)
Vector to scale.
"""
MAX_DENOMINATOR = 1000000
def get_square_denominator(x):
@ -169,6 +180,7 @@ def scale_to_coprime(v):
def lcm(a, b):
"""Least common multiple."""
# Python 3.9 provides math.lcm, see https://stackoverflow.com/questions/51716916.
return a * b // np.gcd(a, b)
m = (np.array(v) * reduce(lcm, map(lambda x: int(get_square_denominator(x)),v)) ** 0.5).astype(np.int)
@ -181,6 +193,28 @@ def scale_to_coprime(v):
return m
def project_stereographic(vector,normalize=False):
"""
Apply stereographic projection to vector.
Parameters
----------
vector : numpy.ndarray of shape (...,3)
Vector coordinates to be projected.
normalize : bool
Ensure unit length for vector. Defaults to False.
Returns
-------
coordinates : numpy.ndarray of shape (...,2)
Projected coordinates.
"""
v_ = vector/np.linalg.norm(vector,axis=-1,keepdims=True) if normalize else vector
return np.block([v_[...,:2]/(1+np.abs(v_[...,2:3])),
np.zeros_like(v_[...,2:3])])
def execution_stamp(class_name,function_name=None):
"""Timestamp the execution of a (function within a) class."""
now = datetime.datetime.now().astimezone().strftime('%Y-%m-%d %H:%M:%S%z')
@ -188,7 +222,21 @@ def execution_stamp(class_name,function_name=None):
return f'damask.{class_name}{_function_name} v{version} ({now})'
def hybrid_IA(dist,N,seed=None):
def hybrid_IA(dist,N,rng_seed=None):
"""
Hybrid integer approximation.
Parameters
----------
dist : numpy.ndarray
Distribution to be approximated
N : int
Number of samples to draw.
rng_seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional
A seed to initialize the BitGenerator. Defaults to None.
If None, then fresh, unpredictable entropy will be pulled from the OS.
"""
N_opt_samples,N_inv_samples = (max(np.count_nonzero(dist),N),0) # random subsampling if too little samples requested
scale_,scale,inc_factor = (0.0,float(N_opt_samples),1.0)
@ -199,7 +247,112 @@ def hybrid_IA(dist,N,seed=None):
if N_inv_samples < N_opt_samples else \
(scale_,0.5*(scale_ + scale), 1.0)
return np.repeat(np.arange(len(dist)),repeats)[np.random.default_rng(seed).permutation(N_inv_samples)[:N]]
return np.repeat(np.arange(len(dist)),repeats)[np.random.default_rng(rng_seed).permutation(N_inv_samples)[:N]]
def shapeshifter(fro,to,mode='left',keep_ones=False):
"""
Return a tuple that reshapes 'fro' to become broadcastable to 'to'.
Parameters
----------
fro : tuple
Original shape of array.
to : tuple
Target shape of array after broadcasting.
len(to) cannot be less than len(fro).
mode : str, optional
Indicates whether new axes are preferably added to
either 'left' or 'right' of the original shape.
Defaults to 'left'.
keep_ones : bool, optional
Treat '1' in fro as literal value instead of dimensional placeholder.
Defaults to False.
"""
beg = dict(left ='(^.*\\b)',
right='(^.*?\\b)')
sep = dict(left ='(.*\\b)',
right='(.*?\\b)')
end = dict(left ='(.*?$)',
right='(.*$)')
fro = (1,) if not len(fro) else fro
to = (1,) if not len(to) else to
try:
grp = re.match(beg[mode]
+f',{sep[mode]}'.join(map(lambda x: f'{x}'
if x>1 or (keep_ones and len(fro)>1) else
'\\d+',fro))
+f',{end[mode]}',
','.join(map(str,to))+',').groups()
except AttributeError:
raise ValueError(f'Shapes can not be shifted {fro} --> {to}')
fill = ()
for g,d in zip(grp,fro+(None,)):
fill += (1,)*g.count(',')+(d,)
return fill[:-1]
def shapeblender(a,b):
"""
Return a shape that overlaps the rightmost entries of 'a' with the leftmost of 'b'.
Parameters
----------
a : tuple
Shape of first array.
b : tuple
Shape of second array.
Examples
--------
>>> shapeblender((4,4,3),(3,2,1))
(4,4,3,2,1)
>>> shapeblender((1,2),(1,2,3))
(1,2,3)
>>> shapeblender((1,),(2,2,1))
(1,2,2,1)
>>> shapeblender((3,2),(3,2))
(3,2)
"""
i = min(len(a),len(b))
while i > 0 and a[-i:] != b[:i]: i -= 1
return a + b[i:]
def extend_docstring(extra_docstring):
"""
Decorator: Append to function's docstring.
Parameters
----------
extra_docstring : str
Docstring to append.
"""
def _decorator(func):
func.__doc__ += extra_docstring
return func
return _decorator
def extended_docstring(f,extra_docstring):
"""
Decorator: Combine another function's docstring with a given docstring.
Parameters
----------
f : function
Function of which the docstring is taken.
extra_docstring : str
Docstring to append.
"""
def _decorator(func):
func.__doc__ = f.__doc__ + extra_docstring
return func
return _decorator
####################################################################################################
@ -295,17 +448,6 @@ class bcolors:
UNDERLINE = '\033[4m'
CROSSOUT = '\033[9m'
def disable(self):
self.HEADER = ''
self.OKBLUE = ''
self.OKGREEN = ''
self.WARNING = ''
self.FAIL = ''
self.ENDC = ''
self.BOLD = ''
self.UNDERLINE = ''
self.CROSSOUT = ''
class return_message:
"""Object with formatted return message."""

22
python/tests/conftest.py
View File

@ -1,8 +1,13 @@
from pathlib import Path
import datetime
import os
import numpy as np
import pytest
import matplotlib as mpl
if os.name == 'posix' and 'DISPLAY' not in os.environ:
mpl.use('Agg')
import matplotlib.pyplot as plt
import damask
@ -25,8 +30,9 @@ def patch_datetime_now(monkeypatch):
monkeypatch.setattr(datetime, 'datetime', mydatetime)
@pytest.fixture
def execution_stamp(monkeypatch):
def patch_execution_stamp(monkeypatch):
"""Set damask.util.execution_stamp for reproducible tests results."""
def execution_stamp(class_name,function_name=None):
_function_name = '' if function_name is None else f'.{function_name}'
@ -35,21 +41,31 @@ def execution_stamp(monkeypatch):
monkeypatch.setattr(damask.util, 'execution_stamp', execution_stamp)
@pytest.fixture
def patch_plt_show(monkeypatch):
def _None(block=None):
pass
monkeypatch.setattr(plt, 'show', _None, raising=True)
def pytest_addoption(parser):
parser.addoption("--update",
action="store_true",
default=False)
@pytest.fixture
def update(request):
"""Store current results as new reference results."""
return request.config.getoption("--update")
@pytest.fixture
def reference_dir_base():
def ref_path_base():
"""Directory containing reference results."""
return Path(__file__).parent/'reference'
@pytest.fixture
def set_of_quaternions():
"""A set of n random rotations."""
@ -66,7 +82,7 @@ def set_of_quaternions():
return qu
n = 1100
n = 600
scatter=1.e-2
specials = np.array([
[1.0, 0.0, 0.0, 0.0],

16
python/tests/reference/ConfigMaterial/material.yaml
View File

@ -33,12 +33,12 @@ material:
phase:
Aluminum:
elasticity: {C_11: 106.75e9, C_12: 60.41e9, C_44: 28.34e9, type: hooke}
generic:
output: [F, P, Fe, Fp, Lp]
lattice: fcc
lattice: cF
mech:
output: [F, P, F_e, F_p, L_p]
elasticity: {C_11: 106.75e9, C_12: 60.41e9, C_44: 28.34e9, type: hooke}
Steel:
elasticity: {C_11: 233.3e9, C_12: 135.5e9, C_44: 118.0e9, type: hooke}
generic:
output: [F, P, Fe, Fp, Lp]
lattice: bcc
lattice: cI
mech:
output: [F, P, F_e, F_p, L_p]
elasticity: {C_11: 233.3e9, C_12: 135.5e9, C_44: 118.0e9, type: hooke}

30
python/tests/reference/Geom/get_grain_boundaries_4g12x15x20.vtr
View File

@ -1,30 +0,0 @@
<?xml version="1.0"?>
<VTKFile type="RectilinearGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
<RectilinearGrid WholeExtent="0 12 0 15 0 20">
<FieldData>
<Array type="String" Name="comments" NumberOfTuples="1" format="binary">
AQAAAACAAABdAAAAYAAAAA==eF4NwlsKgCAQAMCO4mcRK6tmrwt0g35jKXuQtqHR+WuYhQKlUw6Og1wjh2nkyBcf0+NSct7Tc/AlXiNRIpC/dwJra9hW03Tk5qUVuUaNoBRoKxT2lf6XqBCL7APiGxu3
</Array>
</FieldData>
<Piece Extent="0 12 0 15 0 20">
<PointData>
</PointData>
<CellData>
<DataArray type="Int64" Name="material" format="binary" RangeMin="0" RangeMax="3">
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315.0 0.0 0.0 1 3

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356.59977719102034 43.39784965440254 12.173896584899929 1 2
75.92521636876346 43.82007387041961 277.8843642946069 1 3
326.75362934444064 9.976439066337806 76.39559432734703 1 4
176.59977719102034 43.397849654402556 192.17389658489986 1 5
255.92521636876344 43.82007387041961 97.88436429460687 1 6
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93.40022280897969 43.39784965440255 257.8261034151001 1 16
303.24637065555936 9.976439066337804 13.604405672652977 1 17
14.074783631236542 43.82007387041961 352.1156357053931 1 18
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26
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5
python/tests/reference/Orientation/cI_Bain.txt Normal file
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1 header
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26
python/tests/reference/Orientation/cI_GT.txt Normal file
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1 header
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26
python/tests/reference/Orientation/cI_GT_prime.txt Normal file
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1 header
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26
python/tests/reference/Orientation/cI_KS.txt Normal file
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1 header
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14
python/tests/reference/Orientation/cI_NW.txt Normal file
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1 header
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14
python/tests/reference/Orientation/cI_Pitsch.txt Normal file
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@ -0,0 +1,14 @@
1 header
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25
python/tests/reference/Orientation/cI_slip.txt Normal file
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3x3:1_Schmid 3x3:2_Schmid 3x3:3_Schmid 3x3:4_Schmid 3x3:5_Schmid 3x3:6_Schmid 3x3:7_Schmid 3x3:8_Schmid 3x3:9_Schmid
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13
python/tests/reference/Orientation/cI_twin.txt Normal file
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34
python/tests/reference/Orientation/hP_slip.txt Normal file
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