Merge branch 'development' into NoCoreModule
This commit is contained in:
Martin Diehl
commit
573d10f1e1
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@ -0,0 +1,8 @@
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# from https://help.github.com/articles/dealing-with-line-endings/
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#
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||||
# always use LF, even if the files are edited on windows, they need to be compiled/used on unix
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* text eol=lf
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||||
|
||||
# Denote all files that are truly binary and should not be modified.
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*.png binary
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*.jpg binary
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@ -2,7 +2,7 @@
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# usage: source DAMASK_env.sh
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|
||||
if [ "$OSTYPE" == "linux-gnu" ] || [ "$OSTYPE" == 'linux' ]; then
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DAMASK_ROOT=$(readlink -f "`dirname $BASH_SOURCE`")
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DAMASK_ROOT=$(python -c "import os,sys; print(os.path.realpath(os.path.expanduser(sys.argv[1])))" "`dirname $BASH_SOURCE`")
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else
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[[ "${BASH_SOURCE::1}" == "/" ]] && BASE="" || BASE="`pwd`/"
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STAT=$(stat "`dirname $BASE$BASH_SOURCE`")
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@ -18,11 +18,11 @@ fi
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SOLVER=`which DAMASK_spectral 2>/dev/null`
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if [ "x$SOLVER" == "x" ]; then
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export SOLVER='Not found!'
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SOLVER='Not found!'
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fi
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PROCESSING=`which postResults 2>/dev/null`
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if [ "x$PROCESSING" == "x" ]; then
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export PROCESSING='Not found!'
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PROCESSING='Not found!'
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fi
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# according to http://software.intel.com/en-us/forums/topic/501500
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@ -55,7 +55,8 @@ if [ ! -z "$PS1" ]; then
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echo "Multithreading DAMASK_NUM_THREADS=$DAMASK_NUM_THREADS"
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if [ "x$PETSC_DIR" != "x" ]; then
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echo "PETSc location $PETSC_DIR"
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[[ `readlink -f $PETSC_DIR` == $PETSC_DIR ]] || echo " ~~> "`readlink -f $PETSC_DIR`
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[[ `python -c "import os,sys; print(os.path.realpath(os.path.expanduser(sys.argv[1])))" "$PETSC_DIR"` == $PETSC_DIR ]] \
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|| echo " ~~> "`python -c "import os,sys; print(os.path.realpath(os.path.expanduser(sys.argv[1])))" "$PETSC_DIR"`
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fi
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||||
[[ "x$PETSC_ARCH" != "x" ]] && echo "PETSc architecture $PETSC_ARCH"
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echo "MSC.Marc/Mentat $MSC_ROOT"
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|
|
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@ -13,7 +13,8 @@ program DAMASK_spectral
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pInt, &
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pLongInt, &
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pReal, &
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tol_math_check
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tol_math_check, &
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dNeq
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use DAMASK_interface, only: &
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DAMASK_interface_init, &
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loadCaseFile, &
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@ -147,7 +148,9 @@ program DAMASK_spectral
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MPI_file_seek, &
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MPI_file_get_position, &
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MPI_file_write, &
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MPI_allreduce
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MPI_abort, &
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MPI_allreduce, &
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PETScFinalize
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|
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!--------------------------------------------------------------------------------------------------
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! init DAMASK (all modules)
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@ -339,7 +342,7 @@ program DAMASK_spectral
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reshape(spread(tol_math_check,1,9),[ 3,3]))&
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.or. abs(math_det33(loadCases(currentLoadCase)%rotation)) > &
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1.0_pReal + tol_math_check) errorID = 846_pInt ! given rotation matrix contains strain
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if (any(loadCases(currentLoadCase)%rotation /= math_I3)) &
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if (any(dNeq(loadCases(currentLoadCase)%rotation, math_I3))) &
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write(6,'(2x,a,/,3(3(3x,f12.7,1x)/))',advance='no') 'rotation of loadframe:',&
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math_transpose33(loadCases(currentLoadCase)%rotation)
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if (loadCases(currentLoadCase)%time < 0.0_pReal) errorID = 834_pInt ! negative time increment
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@ -423,17 +426,21 @@ program DAMASK_spectral
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!--------------------------------------------------------------------------------------------------
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! prepare MPI parallel out (including opening of file)
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allocate(outputSize(worldsize), source = 0_MPI_OFFSET_KIND)
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outputSize(worldrank+1) = int(size(materialpoint_results)*pReal,MPI_OFFSET_KIND)
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call MPI_allreduce(MPI_IN_PLACE,outputSize,worldsize,MPI_INT,MPI_SUM,PETSC_COMM_WORLD,ierr) ! get total output size over each process
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outputSize(worldrank+1) = size(materialpoint_results,kind=MPI_OFFSET_KIND)*int(pReal,MPI_OFFSET_KIND)
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call MPI_allreduce(MPI_IN_PLACE,outputSize,worldsize,MPI_LONG,MPI_SUM,PETSC_COMM_WORLD,ierr) ! get total output size over each process
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if(ierr /=0_pInt) call IO_error(894_pInt, ext_msg='MPI_allreduce')
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call MPI_file_open(PETSC_COMM_WORLD, &
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trim(getSolverWorkingDirectoryName())//trim(getSolverJobName())//'.spectralOut', &
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MPI_MODE_WRONLY + MPI_MODE_APPEND, &
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MPI_INFO_NULL, &
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resUnit, &
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ierr)
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if(ierr /=0_pInt) call IO_error(894_pInt, ext_msg='MPI_file_open')
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call MPI_file_get_position(resUnit,fileOffset,ierr) ! get offset from header
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if(ierr /=0_pInt) call IO_error(894_pInt, ext_msg='MPI_file_get_position')
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fileOffset = fileOffset + sum(outputSize(1:worldrank)) ! offset of my process in file (header + processes before me)
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call MPI_file_seek (resUnit,fileOffset,MPI_SEEK_SET,ierr)
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if(ierr /=0_pInt) call IO_error(894_pInt, ext_msg='MPI_file_seek')
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||||
|
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if (.not. appendToOutFile) then ! if not restarting, write 0th increment
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do i=1, size(materialpoint_results,3)/(maxByteOut/(materialpoint_sizeResults*pReal))+1 ! slice the output of my process in chunks not exceeding the limit for one output
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|
@ -443,6 +450,7 @@ program DAMASK_spectral
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|||
[(outputIndex(2)-outputIndex(1)+1)*materialpoint_sizeResults]), &
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||||
(outputIndex(2)-outputIndex(1)+1)*materialpoint_sizeResults,&
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||||
MPI_DOUBLE, MPI_STATUS_IGNORE, ierr)
|
||||
if(ierr /=0_pInt) call IO_error(894_pInt, ext_msg='MPI_file_write')
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enddo
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||||
fileOffset = fileOffset + sum(outputSize) ! forward to current file position
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||||
if (worldrank == 0) &
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|
|
@ -643,6 +651,7 @@ program DAMASK_spectral
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write(6,'(1/,a)') ' ... writing results to file ......................................'
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call materialpoint_postResults()
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call MPI_file_seek (resUnit,fileOffset,MPI_SEEK_SET,ierr)
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if(ierr /=0_pInt) call IO_error(894_pInt, ext_msg='MPI_file_seek')
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||||
do i=1, size(materialpoint_results,3)/(maxByteOut/(materialpoint_sizeResults*pReal))+1 ! slice the output of my process in chunks not exceeding the limit for one output
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||||
outputIndex=int([(i-1_pInt)*((maxByteOut/pReal)/materialpoint_sizeResults)+1_pInt, &
|
||||
min(i*((maxByteOut/pReal)/materialpoint_sizeResults),size(materialpoint_results,3))],pLongInt)
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||||
|
|
@ -650,6 +659,7 @@ program DAMASK_spectral
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|||
[(outputIndex(2)-outputIndex(1)+1)*materialpoint_sizeResults]), &
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||||
(outputIndex(2)-outputIndex(1)+1)*materialpoint_sizeResults,&
|
||||
MPI_DOUBLE, MPI_STATUS_IGNORE, ierr)
|
||||
if(ierr /=0_pInt) call IO_error(894_pInt, ext_msg='MPI_file_write')
|
||||
enddo
|
||||
fileOffset = fileOffset + sum(outputSize) ! forward to current file position
|
||||
endif
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||||
|
|
@ -698,7 +708,7 @@ program DAMASK_spectral
|
|||
enddo
|
||||
call utilities_destroy()
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||||
|
||||
call PetscFinalize(ierr); CHKERRQ(ierr)
|
||||
call PETScFinalize(ierr); CHKERRQ(ierr)
|
||||
|
||||
if (notConvergedCounter > 0_pInt) call quit(3_pInt) ! error if some are not converged
|
||||
call quit(0_pInt) ! no complains ;)
|
||||
|
|
|
|||
|
|
@ -1669,6 +1669,8 @@ subroutine IO_error(error_ID,el,ip,g,ext_msg)
|
|||
msg = 'unknown filter type selected'
|
||||
case (893_pInt)
|
||||
msg = 'PETSc: SNES_DIVERGED_FNORM_NAN'
|
||||
case (894_pInt)
|
||||
msg = 'MPI error'
|
||||
|
||||
!-------------------------------------------------------------------------------------------------
|
||||
! error messages related to parsing of Abaqus input file
|
||||
|
|
|
|||
|
|
@ -1280,7 +1280,7 @@ subroutine material_populateGrains
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|||
integer(pInt) :: t,e,i,g,j,m,c,r,homog,micro,sgn,hme, myDebug, &
|
||||
phaseID,textureID,dGrains,myNgrains,myNorientations,myNconstituents, &
|
||||
grain,constituentGrain,ipGrain,symExtension, ip
|
||||
real(pReal) :: extreme,rnd
|
||||
real(pReal) :: deviation,extreme,rnd
|
||||
integer(pInt), dimension (:,:), allocatable :: Nelems ! counts number of elements in homog, micro array
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||||
type(p_intvec), dimension (:,:), allocatable :: elemsOfHomogMicro ! lists element number in homog, micro array
|
||||
|
||||
|
|
@ -1407,8 +1407,11 @@ subroutine material_populateGrains
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extreme = 0.0_pReal
|
||||
t = 0_pInt
|
||||
do i = 1_pInt,myNconstituents ! find largest deviator
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if (real(sgn,pReal)*log(NgrainsOfConstituent(i)/myNgrains/microstructure_fraction(i,micro)) > extreme) then
|
||||
extreme = real(sgn,pReal)*log(NgrainsOfConstituent(i)/myNgrains/microstructure_fraction(i,micro))
|
||||
deviation = real(sgn,pReal)*log( microstructure_fraction(i,micro) / &
|
||||
!-------------------------------- &
|
||||
(real(NgrainsOfConstituent(i),pReal)/real(myNgrains,pReal) ) )
|
||||
if (deviation > extreme) then
|
||||
extreme = deviation
|
||||
t = i
|
||||
endif
|
||||
enddo
|
||||
|
|
|
|||
|
|
@ -7,14 +7,11 @@
|
|||
!! untextured polycrystal
|
||||
!--------------------------------------------------------------------------------------------------
|
||||
module plastic_isotropic
|
||||
#ifdef HDF
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||||
use hdf5, only: &
|
||||
HID_T
|
||||
#endif
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||||
|
||||
use prec, only: &
|
||||
pReal,&
|
||||
pInt
|
||||
pInt, &
|
||||
DAMASK_NaN
|
||||
|
||||
implicit none
|
||||
private
|
||||
|
|
@ -40,16 +37,16 @@ module plastic_isotropic
|
|||
integer(kind(undefined_ID)), allocatable, dimension(:) :: &
|
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outputID
|
||||
real(pReal) :: &
|
||||
fTaylor, &
|
||||
tau0, &
|
||||
gdot0, &
|
||||
n, &
|
||||
h0, &
|
||||
h0_slopeLnRate, &
|
||||
tausat, &
|
||||
a, &
|
||||
aTolFlowstress, &
|
||||
aTolShear , &
|
||||
fTaylor = DAMASK_NaN, &
|
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tau0 = DAMASK_NaN, &
|
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gdot0 = DAMASK_NaN, &
|
||||
n = DAMASK_NaN, &
|
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h0 = DAMASK_NaN, &
|
||||
h0_slopeLnRate = 0.0_pReal, &
|
||||
tausat = DAMASK_NaN, &
|
||||
a = DAMASK_NaN, &
|
||||
aTolFlowstress = 1.0_pReal, &
|
||||
aTolShear = 1.0e-6_pReal, &
|
||||
tausat_SinhFitA= 0.0_pReal, &
|
||||
tausat_SinhFitB= 0.0_pReal, &
|
||||
tausat_SinhFitC= 0.0_pReal, &
|
||||
|
|
@ -474,7 +471,8 @@ subroutine plastic_isotropic_LiAndItsTangent(Li,dLi_dTstar_3333,Tstar_v,ipc,ip,e
|
|||
implicit none
|
||||
real(pReal), dimension(3,3), intent(out) :: &
|
||||
Li !< plastic velocity gradient
|
||||
|
||||
real(pReal), dimension(3,3,3,3), intent(out) :: &
|
||||
dLi_dTstar_3333 !< derivative of Li with respect to Tstar as 4th order tensor
|
||||
real(pReal), dimension(6), intent(in) :: &
|
||||
Tstar_v !< 2nd Piola Kirchhoff stress tensor in Mandel notation
|
||||
integer(pInt), intent(in) :: &
|
||||
|
|
@ -484,8 +482,6 @@ subroutine plastic_isotropic_LiAndItsTangent(Li,dLi_dTstar_3333,Tstar_v,ipc,ip,e
|
|||
|
||||
real(pReal), dimension(3,3) :: &
|
||||
Tstar_sph_33 !< sphiatoric part of the 2nd Piola Kirchhoff stress tensor as 2nd order tensor
|
||||
real(pReal), dimension(3,3,3,3), intent(out) :: &
|
||||
dLi_dTstar_3333 !< derivative of Li with respect to Tstar as 4th order tensor
|
||||
real(pReal) :: &
|
||||
gamma_dot, & !< strainrate
|
||||
norm_Tstar_sph, & !< euclidean norm of Tstar_sph
|
||||
|
|
@ -523,6 +519,9 @@ subroutine plastic_isotropic_LiAndItsTangent(Li,dLi_dTstar_3333,Tstar_v,ipc,ip,e
|
|||
dLi_dTstar_3333 = gamma_dot / param(instance)%fTaylor * &
|
||||
dLi_dTstar_3333 / norm_Tstar_sph
|
||||
endif
|
||||
else
|
||||
Li = 0.0_pReal
|
||||
dLi_dTstar_3333 = 0.0_pReal
|
||||
endif
|
||||
|
||||
end subroutine plastic_isotropic_LiAndItsTangent
|
||||
|
|
|
|||
|
|
@ -207,9 +207,6 @@ subroutine plastic_j2_init(fileUnit)
|
|||
phase = phase + 1_pInt ! advance section counter
|
||||
if (phase_plasticity(phase) == PLASTICITY_J2_ID) then
|
||||
instance = phase_plasticityInstance(phase)
|
||||
#ifdef HDF
|
||||
outID(instance)=HDF5_addGroup(str1,tempResults)
|
||||
#endif
|
||||
endif
|
||||
cycle ! skip to next line
|
||||
endif
|
||||
|
|
@ -226,21 +223,11 @@ subroutine plastic_j2_init(fileUnit)
|
|||
plastic_j2_outputID(plastic_j2_Noutput(instance),instance) = flowstress_ID
|
||||
plastic_j2_output(plastic_j2_Noutput(instance),instance) = &
|
||||
IO_lc(IO_stringValue(line,chunkPos,2_pInt))
|
||||
#ifdef HDF
|
||||
call HDF5_addScalarDataset(outID(instance),myConstituents,'flowstress','MPa')
|
||||
allocate(plastic_j2_Output2(instance)%flowstress(myConstituents))
|
||||
plastic_j2_Output2(instance)%flowstressActive = .true.
|
||||
#endif
|
||||
case ('strainrate')
|
||||
plastic_j2_Noutput(instance) = plastic_j2_Noutput(instance) + 1_pInt
|
||||
plastic_j2_outputID(plastic_j2_Noutput(instance),instance) = strainrate_ID
|
||||
plastic_j2_output(plastic_j2_Noutput(instance),instance) = &
|
||||
IO_lc(IO_stringValue(line,chunkPos,2_pInt))
|
||||
#ifdef HDF
|
||||
call HDF5_addScalarDataset(outID(instance),myConstituents,'strainrate','1/s')
|
||||
allocate(plastic_j2_Output2(instance)%strainrate(myConstituents))
|
||||
plastic_j2_Output2(instance)%strainrateActive = .true.
|
||||
#endif
|
||||
case default
|
||||
|
||||
end select
|
||||
|
|
|
|||
|
|
@ -113,7 +113,9 @@ module prec
|
|||
|
||||
public :: &
|
||||
prec_init, &
|
||||
prec_isNaN
|
||||
prec_isNaN, &
|
||||
dEq, &
|
||||
dNeq
|
||||
|
||||
contains
|
||||
|
||||
|
|
|
|||
|
|
@ -1,37 +0,0 @@
|
|||
### $Id$ ###
|
||||
|
||||
[Tungsten]
|
||||
elasticity hooke
|
||||
plasticity dislokmc
|
||||
|
||||
### Material parameters ###
|
||||
lattice_structure bcc
|
||||
C11 523.0e9 # From Marinica et al. Journal of Physics: Condensed Matter(2013)
|
||||
C12 202.0e9
|
||||
C44 161.0e9
|
||||
|
||||
grainsize 2.0e-5 # Average grain size [m] 2.0e-5
|
||||
SolidSolutionStrength 0.0 # Strength due to elements in solid solution
|
||||
|
||||
### Dislocation glide parameters ###
|
||||
#per family
|
||||
Nslip 12 0
|
||||
slipburgers 2.72e-10 # Burgers vector of slip system [m]
|
||||
rhoedge0 1.0e12 # Initial edge dislocation density [m/m**3]
|
||||
rhoedgedip0 1.0 # Initial edged dipole dislocation density [m/m**3]
|
||||
Qedge 2.725e-19 # Activation energy for dislocation glide [J]
|
||||
v0 3560.3 # Initial glide velocity [m/s](kmC)
|
||||
p_slip 0.16 # p-exponent in glide velocity
|
||||
q_slip 1.00 # q-exponent in glide velocity
|
||||
u_slip 2.47 # u-exponent of stress pre-factor (kmC)
|
||||
s_slip 0.97 # self hardening in glide velocity (kmC)
|
||||
tau_peierls 2.03e9 # peierls stress [Pa]
|
||||
|
||||
#hardening
|
||||
dipoleformationfactor 0 # to have hardening due to dipole formation off
|
||||
CLambdaSlip 10.0 # Adj. parameter controlling dislocation mean free path
|
||||
D0 4.0e-5 # Vacancy diffusion prefactor [m**2/s]
|
||||
Qsd 4.5e-19 # Activation energy for climb [J]
|
||||
Catomicvolume 1.0 # Adj. parameter controlling the atomic volume [in b]
|
||||
Cedgedipmindistance 1.0 # Adj. parameter controlling the minimum dipole distance [in b]
|
||||
interaction_slipslip 0.2 0.11 0.19 0.15 0.11 0.17
|
||||
|
|
@ -40,12 +40,12 @@ class ASCIItable():
|
|||
self.__IO__['in'] = name
|
||||
|
||||
try:
|
||||
self.__IO__['out'] = (open(outname,'w') if (not os.path.isfile(outname) \
|
||||
or os.access( outname, os.W_OK) \
|
||||
) \
|
||||
and (not self.__IO__['inPlace'] \
|
||||
or not os.path.isfile(name) \
|
||||
or os.access( name, os.W_OK) \
|
||||
self.__IO__['out'] = (open(outname,'w') if (not os.path.isfile(outname) or
|
||||
os.access( outname, os.W_OK)
|
||||
) and
|
||||
(not self.__IO__['inPlace'] or
|
||||
not os.path.isfile(name) or
|
||||
os.access( name, os.W_OK)
|
||||
) else None) if outname else sys.stdout
|
||||
except TypeError:
|
||||
self.__IO__['out'] = outname
|
||||
|
|
@ -272,7 +272,7 @@ class ASCIItable():
|
|||
for label in labels:
|
||||
if label is not None:
|
||||
try:
|
||||
idx.append(int(label)) # column given as integer number?
|
||||
idx.append(int(label)-1) # column given as integer number?
|
||||
except ValueError:
|
||||
try:
|
||||
idx.append(self.labels.index(label)) # locate string in label list
|
||||
|
|
@ -283,7 +283,7 @@ class ASCIItable():
|
|||
idx.append(-1) # not found...
|
||||
else:
|
||||
try:
|
||||
idx = int(labels)
|
||||
idx = int(labels)-1 # offset for python array indexing
|
||||
except ValueError:
|
||||
try:
|
||||
idx = self.labels.index(labels)
|
||||
|
|
@ -293,7 +293,7 @@ class ASCIItable():
|
|||
except ValueError:
|
||||
idx = None if labels is None else -1
|
||||
|
||||
return np.array(idx) if isinstance(idx,list) else idx
|
||||
return np.array(idx) if isinstance(idx,Iterable) else idx
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
def label_dimension(self,
|
||||
|
|
@ -312,7 +312,7 @@ class ASCIItable():
|
|||
if label is not None:
|
||||
myDim = -1
|
||||
try: # column given as number?
|
||||
idx = int(label)
|
||||
idx = int(label)-1
|
||||
myDim = 1 # if found has at least dimension 1
|
||||
if self.labels[idx].startswith('1_'): # column has multidim indicator?
|
||||
while idx+myDim < len(self.labels) and self.labels[idx+myDim].startswith("%i_"%(myDim+1)):
|
||||
|
|
@ -331,7 +331,7 @@ class ASCIItable():
|
|||
dim = -1 # assume invalid label
|
||||
idx = -1
|
||||
try: # column given as number?
|
||||
idx = int(labels)
|
||||
idx = int(labels)-1
|
||||
dim = 1 # if found has at least dimension 1
|
||||
if self.labels[idx].startswith('1_'): # column has multidim indicator?
|
||||
while idx+dim < len(self.labels) and self.labels[idx+dim].startswith("%i_"%(dim+1)):
|
||||
|
|
@ -345,7 +345,7 @@ class ASCIItable():
|
|||
while idx+dim < len(self.labels) and self.labels[idx+dim].startswith("%i_"%(dim+1)):
|
||||
dim += 1 # keep adding while going through object
|
||||
|
||||
return np.array(dim) if isinstance(dim,list) else dim
|
||||
return np.array(dim) if isinstance(dim,Iterable) else dim
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
def label_indexrange(self,
|
||||
|
|
|
|||
Binary file not shown.
|
Before Width: | Height: | Size: 80 KiB After Width: | Height: | Size: 34 KiB |
|
|
@ -0,0 +1,222 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: UTF-8 no BOM -*-
|
||||
|
||||
import os,sys,math
|
||||
import numpy as np
|
||||
import scipy.ndimage
|
||||
from optparse import OptionParser
|
||||
import damask
|
||||
|
||||
scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
||||
scriptID = ' '.join([scriptName,damask.version])
|
||||
|
||||
|
||||
#--------------------------------------------------------------------------------------------------
|
||||
def cell2node(cellData,grid):
|
||||
|
||||
nodeData = 0.0
|
||||
datalen = np.array(cellData.shape[3:]).prod()
|
||||
|
||||
for i in xrange(datalen):
|
||||
node = scipy.ndimage.convolve(cellData.reshape(tuple(grid)+(datalen,))[...,i],
|
||||
np.ones((2,2,2))/8., # 2x2x2 neighborhood of cells
|
||||
mode = 'wrap',
|
||||
origin = -1, # offset to have cell origin as center
|
||||
) # now averaged at cell origins
|
||||
node = np.append(node,node[np.newaxis,0,:,:,...],axis=0) # wrap along z
|
||||
node = np.append(node,node[:,0,np.newaxis,:,...],axis=1) # wrap along y
|
||||
node = np.append(node,node[:,:,0,np.newaxis,...],axis=2) # wrap along x
|
||||
|
||||
nodeData = node[...,np.newaxis] if i==0 else np.concatenate((nodeData,node[...,np.newaxis]),axis=-1)
|
||||
|
||||
return nodeData
|
||||
|
||||
#--------------------------------------------------------------------------------------------------
|
||||
def displacementAvgFFT(F,grid,size,nodal=False,transformed=False):
|
||||
"""calculate average cell center (or nodal) displacement for deformation gradient field specified in each grid cell"""
|
||||
if nodal:
|
||||
x, y, z = np.meshgrid(np.linspace(0,size[0],1+grid[0]),
|
||||
np.linspace(0,size[1],1+grid[1]),
|
||||
np.linspace(0,size[2],1+grid[2]),
|
||||
indexing = 'ij')
|
||||
else:
|
||||
x, y, z = np.meshgrid(np.linspace(0,size[0],grid[0],endpoint=False),
|
||||
np.linspace(0,size[1],grid[1],endpoint=False),
|
||||
np.linspace(0,size[2],grid[2],endpoint=False),
|
||||
indexing = 'ij')
|
||||
|
||||
origCoords = np.concatenate((z[:,:,:,None],y[:,:,:,None],x[:,:,:,None]),axis = 3)
|
||||
|
||||
F_fourier = F if transformed else np.fft.rfftn(F,axes=(0,1,2)) # transform or use provided data
|
||||
Favg = np.real(F_fourier[0,0,0,:,:])/grid.prod() # take zero freq for average
|
||||
avgDisplacement = np.einsum('ml,ijkl->ijkm',Favg-np.eye(3),origCoords) # dX = Favg.X
|
||||
|
||||
return avgDisplacement
|
||||
|
||||
#--------------------------------------------------------------------------------------------------
|
||||
def displacementFluctFFT(F,grid,size,nodal=False,transformed=False):
|
||||
"""calculate cell center (or nodal) displacement for deformation gradient field specified in each grid cell"""
|
||||
integrator = 0.5j * size / math.pi
|
||||
|
||||
kk, kj, ki = np.meshgrid(np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2])),
|
||||
np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1])),
|
||||
np.arange(grid[0]//2+1),
|
||||
indexing = 'ij')
|
||||
k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3)
|
||||
k_sSquared = np.einsum('...l,...l',k_s,k_s)
|
||||
k_sSquared[0,0,0] = 1.0 # ignore global average frequency
|
||||
|
||||
#--------------------------------------------------------------------------------------------------
|
||||
# integration in Fourier space
|
||||
|
||||
displacement_fourier = -np.einsum('ijkml,ijkl,l->ijkm',
|
||||
F if transformed else np.fft.rfftn(F,axes=(0,1,2)),
|
||||
k_s,
|
||||
integrator,
|
||||
) / k_sSquared[...,np.newaxis]
|
||||
|
||||
#--------------------------------------------------------------------------------------------------
|
||||
# backtransformation to real space
|
||||
|
||||
displacement = np.fft.irfftn(displacement_fourier,grid,axes=(0,1,2))
|
||||
|
||||
return cell2node(displacement,grid) if nodal else displacement
|
||||
|
||||
|
||||
# --------------------------------------------------------------------
|
||||
# MAIN
|
||||
# --------------------------------------------------------------------
|
||||
|
||||
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """
|
||||
Add deformed configuration of given initial coordinates.
|
||||
Operates on periodic three-dimensional x,y,z-ordered data sets.
|
||||
|
||||
""", version = scriptID)
|
||||
|
||||
parser.add_option('-f', '--defgrad',
|
||||
dest = 'defgrad',
|
||||
metavar = 'string',
|
||||
help = 'column label of deformation gradient [%default]')
|
||||
parser.add_option('-c', '--coordinates',
|
||||
dest = 'coords',
|
||||
metavar = 'string',
|
||||
help = 'column label of coordinates [%default]')
|
||||
parser.add_option('--nodal',
|
||||
dest = 'nodal',
|
||||
action = 'store_true',
|
||||
help = 'output nodal (not cell-centered) displacements')
|
||||
|
||||
parser.set_defaults(defgrad = 'f',
|
||||
coords = 'ipinitialcoord',
|
||||
nodal = False,
|
||||
)
|
||||
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
outname = (os.path.splitext(name)[0]+
|
||||
'_nodal'+
|
||||
os.path.splitext(name)[1]) if (options.nodal and name) else None,
|
||||
buffered = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
||||
# ------------------------------------------ read header ------------------------------------------
|
||||
|
||||
table.head_read()
|
||||
|
||||
# ------------------------------------------ sanity checks ----------------------------------------
|
||||
|
||||
errors = []
|
||||
remarks = []
|
||||
|
||||
if table.label_dimension(options.defgrad) != 9:
|
||||
errors.append('deformation gradient "{}" is not a 3x3 tensor.'.format(options.defgrad))
|
||||
|
||||
coordDim = table.label_dimension(options.coords)
|
||||
if not 3 >= coordDim >= 1: errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.coords))
|
||||
elif coordDim < 3: remarks.append('appending {} dimensions to coordinates "{}"...'.format(3-coordDim,options.coords))
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
damask.util.croak(errors)
|
||||
table.close(dismiss=True)
|
||||
continue
|
||||
|
||||
# --------------- figure out size and grid ---------------------------------------------------------
|
||||
|
||||
table.data_readArray([options.defgrad,options.coords])
|
||||
table.data_rewind()
|
||||
|
||||
if len(table.data.shape) < 2: table.data.shape += (1,) # expand to 2D shape
|
||||
if table.data[:,9:].shape[1] < 3:
|
||||
table.data = np.hstack((table.data,
|
||||
np.zeros((table.data.shape[0],
|
||||
3-table.data[:,9:].shape[1]),dtype='f'))) # fill coords up to 3D with zeros
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
damask.util.croak(errors)
|
||||
table.close(dismiss = True)
|
||||
continue
|
||||
|
||||
# --------------- figure out size and grid ---------------------------------------------------------
|
||||
|
||||
coords = [np.unique(table.data[:,9+i]) for i in xrange(3)]
|
||||
mincorner = np.array(map(min,coords))
|
||||
maxcorner = np.array(map(max,coords))
|
||||
grid = np.array(map(len,coords),'i')
|
||||
size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
|
||||
size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 set to smallest among other spacings
|
||||
|
||||
N = grid.prod()
|
||||
|
||||
if N != len(table.data): errors.append('data count {} does not match grid {}x{}x{}.'.format(N,*grid))
|
||||
if errors != []:
|
||||
damask.util.croak(errors)
|
||||
table.close(dismiss = True)
|
||||
continue
|
||||
|
||||
# ------------------------------------------ process data ------------------------------------------
|
||||
|
||||
F_fourier = np.fft.rfftn(table.data[:,:9].reshape(grid[2],grid[1],grid[0],3,3),axes=(0,1,2)) # perform transform only once...
|
||||
|
||||
displacement = displacementFluctFFT(F_fourier,grid,size,options.nodal,transformed=True)
|
||||
avgDisplacement = displacementAvgFFT (F_fourier,grid,size,options.nodal,transformed=True)
|
||||
|
||||
# ------------------------------------------ assemble header ---------------------------------------
|
||||
|
||||
if options.nodal:
|
||||
table.info_clear()
|
||||
table.labels_clear()
|
||||
|
||||
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
|
||||
table.labels_append((['{}_pos' .format(i+1) for i in xrange(3)] if options.nodal else []) +
|
||||
['{}_avg({}).{}' .format(i+1,options.defgrad,options.coords) for i in xrange(3)] +
|
||||
['{}_fluct({}).{}'.format(i+1,options.defgrad,options.coords) for i in xrange(3)] )
|
||||
table.head_write()
|
||||
|
||||
# ------------------------------------------ output data -------------------------------------------
|
||||
|
||||
zrange = np.linspace(0,size[2],1+grid[2]) if options.nodal else xrange(grid[2])
|
||||
yrange = np.linspace(0,size[1],1+grid[1]) if options.nodal else xrange(grid[1])
|
||||
xrange = np.linspace(0,size[0],1+grid[0]) if options.nodal else xrange(grid[0])
|
||||
|
||||
for i,z in enumerate(zrange):
|
||||
for j,y in enumerate(yrange):
|
||||
for k,x in enumerate(xrange):
|
||||
if options.nodal: table.data_clear()
|
||||
else: table.data_read()
|
||||
table.data_append([x,y,z] if options.nodal else [])
|
||||
table.data_append(list(avgDisplacement[i,j,k,:]))
|
||||
table.data_append(list( displacement[i,j,k,:]))
|
||||
table.data_write()
|
||||
|
||||
# ------------------------------------------ output finalization -----------------------------------
|
||||
|
||||
table.close() # close ASCII tables
|
||||
|
|
@ -5,7 +5,6 @@ import numpy as np
|
|||
import damask
|
||||
from optparse import OptionParser
|
||||
from scipy import spatial
|
||||
from collections import defaultdict
|
||||
|
||||
scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
||||
scriptID = ' '.join([scriptName,damask.version])
|
||||
|
|
@ -23,7 +22,7 @@ parser.add_option('-r', '--radius',
|
|||
parser.add_option('-d', '--disorientation',
|
||||
dest = 'disorientation',
|
||||
type = 'float', metavar = 'float',
|
||||
help = 'disorientation threshold per grain [%default] (degrees)')
|
||||
help = 'disorientation threshold in degrees [%default]')
|
||||
parser.add_option('-s', '--symmetry',
|
||||
dest = 'symmetry',
|
||||
type = 'string', metavar = 'string',
|
||||
|
|
@ -61,7 +60,8 @@ parser.add_option('-p', '--position',
|
|||
type = 'string', metavar = 'string',
|
||||
help = 'spatial position of voxel [%default]')
|
||||
|
||||
parser.set_defaults(symmetry = 'cubic',
|
||||
parser.set_defaults(disorientation = 5,
|
||||
symmetry = 'cubic',
|
||||
coords = 'pos',
|
||||
degrees = False,
|
||||
)
|
||||
|
|
@ -87,15 +87,14 @@ if np.sum(input) != 1: parser.error('needs exactly one input format.')
|
|||
(options.quaternion,4,'quaternion'),
|
||||
][np.where(input)[0][0]] # select input label that was requested
|
||||
toRadians = np.pi/180.0 if options.degrees else 1.0 # rescale degrees to radians
|
||||
cos_disorientation = np.cos(options.disorientation/2.*toRadians)
|
||||
cos_disorientation = np.cos(np.radians(options.disorientation/2.)) # cos of half the disorientation angle
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
buffered = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
|
@ -109,8 +108,10 @@ for name in filenames:
|
|||
errors = []
|
||||
remarks = []
|
||||
|
||||
if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords))
|
||||
if not np.all(table.label_dimension(label) == dim): errors.append('input {} does not have dimension {}.'.format(label,dim))
|
||||
if not 3 >= table.label_dimension(options.coords) >= 1:
|
||||
errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.coords))
|
||||
if not np.all(table.label_dimension(label) == dim):
|
||||
errors.append('input {} does not have dimension {}.'.format(label,dim))
|
||||
else: column = table.label_index(label)
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
|
|
@ -122,8 +123,10 @@ for name in filenames:
|
|||
# ------------------------------------------ assemble header ---------------------------------------
|
||||
|
||||
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
|
||||
table.labels_append('grainID_{}@{}'.format(label,
|
||||
options.disorientation if options.degrees else np.degrees(options.disorientation))) # report orientation source and disorientation in degrees
|
||||
table.labels_append('grainID_{}@{:g}'.format('+'.join(label)
|
||||
if isinstance(label, (list,tuple))
|
||||
else label,
|
||||
options.disorientation)) # report orientation source and disorientation
|
||||
table.head_write()
|
||||
|
||||
# ------------------------------------------ process data ------------------------------------------
|
||||
|
|
@ -162,7 +165,7 @@ for name in filenames:
|
|||
|
||||
time_delta = (time.clock()-tick) * (len(grainID) - p) / p
|
||||
bg.set_message('(%02i:%02i:%02i) processing point %i of %i (grain count %i)...'\
|
||||
%(time_delta//3600,time_delta%3600//60,time_delta%60,p,len(grainID),len(orientations)))
|
||||
%(time_delta//3600,time_delta%3600//60,time_delta%60,p,len(grainID),np.count_nonzero(memberCounts)))
|
||||
|
||||
if inputtype == 'eulers':
|
||||
o = damask.Orientation(Eulers = np.array(map(float,table.data[column:column+3]))*toRadians,
|
||||
|
|
@ -180,83 +183,50 @@ for name in filenames:
|
|||
symmetry = options.symmetry).reduced()
|
||||
|
||||
matched = False
|
||||
|
||||
# check against last matched needs to be really picky. best would be to exclude jumps across the poke (checking distance between last and me?)
|
||||
# when walking through neighborhood first check whether grainID of that point has already been tested, if yes, skip!
|
||||
|
||||
if matchedID != -1: # has matched before?
|
||||
matched = (o.quaternion.conjugated() * orientations[matchedID].quaternion).w > cos_disorientation
|
||||
|
||||
if not matched:
|
||||
alreadyChecked = {}
|
||||
candidates = []
|
||||
bestDisorientation = damask.Quaternion([0,0,0,1]) # initialize to 180 deg rotation as worst case
|
||||
|
||||
for i in kdtree.query_ball_point(kdtree.data[p],options.radius): # check all neighboring points
|
||||
gID = grainID[i]
|
||||
if gID != -1 and gID not in alreadyChecked: # indexed point belonging to a grain not yet tested?
|
||||
alreadyChecked[gID] = True # remember not to check again
|
||||
disorientation = o.disorientation(orientations[gID],SST = False)[0] # compare against other orientation
|
||||
if disorientation.quaternion.w > cos_disorientation and \
|
||||
disorientation.quaternion.w >= bestDisorientation.w: # within threshold and betterthan current best?
|
||||
if disorientation.quaternion.w > cos_disorientation: # within threshold ...
|
||||
candidates.append(gID) # remember as potential candidate
|
||||
if disorientation.quaternion.w >= bestDisorientation.w: # ... and better than current best?
|
||||
matched = True
|
||||
matchedID = gID # remember that grain
|
||||
bestDisorientation = disorientation.quaternion
|
||||
|
||||
if not matched: # no match -> new grain found
|
||||
memberCounts += [1] # start new membership counter
|
||||
if matched: # did match existing grain
|
||||
memberCounts[matchedID] += 1
|
||||
if len(candidates) > 1: # ambiguity in grain identification?
|
||||
largestGrain = sorted(candidates,key=lambda x:memberCounts[x])[-1] # find largest among potential candidate grains
|
||||
matchedID = largestGrain
|
||||
for c in [c for c in candidates if c != largestGrain]: # loop over smaller candidates
|
||||
memberCounts[largestGrain] += memberCounts[c] # reassign member count of smaller to largest
|
||||
memberCounts[c] = 0
|
||||
grainID = np.where(np.in1d(grainID,candidates), largestGrain, grainID) # relabel grid points of smaller candidates as largest one
|
||||
|
||||
else: # no match -> new grain found
|
||||
orientations += [o] # initialize with current orientation
|
||||
memberCounts += [1] # start new membership counter
|
||||
matchedID = g
|
||||
g += 1 # increment grain counter
|
||||
|
||||
else: # did match existing grain
|
||||
memberCounts[matchedID] += 1
|
||||
|
||||
grainID[p] = matchedID # remember grain index assigned to point
|
||||
p += 1 # increment point
|
||||
|
||||
bg.set_message('identifying similar orientations among {} grains...'.format(len(orientations)))
|
||||
|
||||
memberCounts = np.array(memberCounts)
|
||||
similarOrientations = [[] for i in xrange(len(orientations))]
|
||||
|
||||
for i,orientation in enumerate(orientations[:-1]): # compare each identified orientation...
|
||||
for j in xrange(i+1,len(orientations)): # ...against all others that were defined afterwards
|
||||
if orientation.disorientation(orientations[j],SST = False)[0].quaternion.w > cos_disorientation: # similar orientations in both grainIDs?
|
||||
similarOrientations[i].append(j) # remember in upper triangle...
|
||||
similarOrientations[j].append(i) # ...and lower triangle of matrix
|
||||
|
||||
if similarOrientations[i] != []:
|
||||
bg.set_message('grainID {} is as: {}'.format(i,' '.join(map(str,similarOrientations[i]))))
|
||||
|
||||
stillShifting = True
|
||||
while stillShifting:
|
||||
stillShifting = False
|
||||
tick = time.clock()
|
||||
|
||||
for p,gID in enumerate(grainID): # walk through all points
|
||||
if p > 0 and p % 1000 == 0:
|
||||
|
||||
time_delta = (time.clock()-tick) * (len(grainID) - p) / p
|
||||
bg.set_message('(%02i:%02i:%02i) shifting ID of point %i out of %i (grain count %i)...'
|
||||
%(time_delta//3600,time_delta%3600//60,time_delta%60,p,len(grainID),len(orientations)))
|
||||
if similarOrientations[gID] != []: # orientation of my grainID is similar to someone else?
|
||||
similarNeighbors = defaultdict(int) # frequency of neighboring grainIDs sharing my orientation
|
||||
for i in kdtree.query_ball_point(kdtree.data[p],options.radius): # check all neighboring point
|
||||
if grainID[i] in similarOrientations[gID]: # neighboring point shares my orientation?
|
||||
similarNeighbors[grainID[i]] += 1 # remember its grainID
|
||||
if similarNeighbors != {}: # found similar orientation(s) in neighborhood
|
||||
candidates = np.array([gID]+similarNeighbors.keys()) # possible replacement grainIDs for me
|
||||
grainID[p] = candidates[np.argsort(memberCounts[candidates])[-1]] # adopt ID that is most frequent in overall dataset
|
||||
memberCounts[gID] -= 1 # my former ID loses one fellow
|
||||
memberCounts[grainID[p]] += 1 # my new ID gains one fellow
|
||||
bg.set_message('{}:{} --> {}'.format(p,gID,grainID[p])) # report switch of grainID
|
||||
stillShifting = True
|
||||
grainIDs = np.where(np.array(memberCounts) > 0)[0] # identify "live" grain identifiers
|
||||
packingMap = dict(zip(list(grainIDs),range(len(grainIDs)))) # map to condense into consecutive IDs
|
||||
|
||||
table.data_rewind()
|
||||
|
||||
outputAlive = True
|
||||
p = 0
|
||||
while outputAlive and table.data_read(): # read next data line of ASCII table
|
||||
table.data_append(1+grainID[p]) # add grain ID
|
||||
table.data_append(1+packingMap[grainID[p]]) # add (condensed) grain ID
|
||||
outputAlive = table.data_write() # output processed line
|
||||
p += 1
|
||||
|
||||
|
|
|
|||
|
|
@ -239,7 +239,9 @@ for name in filenames:
|
|||
# ------------------------------------------ assemble header ---------------------------------------
|
||||
|
||||
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
|
||||
table.labels_append(['{id}_S[{direction[0]:.1g}_{direction[1]:.1g}_{direction[2]:.1g}]({normal[0]:.1g}_{normal[1]:.1g}_{normal[2]:.1g})'\
|
||||
table.labels_append(['{id}_'
|
||||
'S[{direction[0]:.1g}_{direction[1]:.1g}_{direction[2]:.1g}]'
|
||||
'({normal[0]:.1g}_{normal[1]:.1g}_{normal[2]:.1g})'\
|
||||
.format( id = i+1,
|
||||
normal = theNormal,
|
||||
direction = theDirection,
|
||||
|
|
|
|||
|
|
@ -37,9 +37,13 @@ if options.label is None:
|
|||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,
|
||||
outname = options.label+'_averaged_'+name if name else name,
|
||||
damask.util.croak(name)
|
||||
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
outname = os.path.join(
|
||||
os.path.split(name)[0],
|
||||
options.label+'_averaged_'+os.path.split(name)[1]
|
||||
) if name else name,
|
||||
buffered = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,142 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: UTF-8 no BOM -*-
|
||||
|
||||
import os,sys
|
||||
import numpy as np
|
||||
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 [file[s]]', description = """
|
||||
Generate histogram of N bins in given data range.
|
||||
|
||||
""", version = scriptID)
|
||||
|
||||
parser.add_option('-d','--data',
|
||||
dest = 'data',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column heading for data')
|
||||
parser.add_option('-w','--weights',
|
||||
dest = 'weights',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column heading for weights')
|
||||
parser.add_option('--range',
|
||||
dest = 'range',
|
||||
type = 'float', nargs = 2, metavar = 'float float',
|
||||
help = 'data range of histogram [min - max]')
|
||||
parser.add_option('-N',
|
||||
dest = 'N',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'number of bins')
|
||||
parser.add_option('--density',
|
||||
dest = 'density',
|
||||
action = 'store_true',
|
||||
help = 'report probability density')
|
||||
parser.add_option('--logarithmic',
|
||||
dest = 'log',
|
||||
action = 'store_true',
|
||||
help = 'logarithmically spaced bins')
|
||||
parser.set_defaults(data = None,
|
||||
weights = None,
|
||||
range = None,
|
||||
N = None,
|
||||
density = False,
|
||||
log = False,
|
||||
)
|
||||
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
||||
if not options.data: parser.error('no data specified.')
|
||||
if not options.N: parser.error('no bin number specified.')
|
||||
|
||||
if options.log:
|
||||
def forward(x):
|
||||
return np.log(x)
|
||||
def reverse(x):
|
||||
return np.exp(x)
|
||||
else:
|
||||
def forward(x):
|
||||
return x
|
||||
def reverse(x):
|
||||
return x
|
||||
|
||||
|
||||
# --- loop over input files ------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
buffered = False,
|
||||
readonly = True)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
||||
# ------------------------------------------ read header ------------------------------------------
|
||||
|
||||
table.head_read()
|
||||
|
||||
# ------------------------------------------ sanity checks ----------------------------------------
|
||||
|
||||
errors = []
|
||||
remarks = []
|
||||
|
||||
if table.label_dimension(options.data) != 1: errors.append('data {} are not scalar.'.format(options.data))
|
||||
if options.weights and \
|
||||
table.label_dimension(options.data) != 1: errors.append('weights {} are not scalar.'.format(options.weights))
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
damask.util.croak(errors)
|
||||
table.close(dismiss = True)
|
||||
continue
|
||||
|
||||
# --------------- read data ----------------------------------------------------------------
|
||||
|
||||
table.data_readArray([options.data,options.weights])
|
||||
|
||||
# --------------- auto range ---------------------------------------------------------------
|
||||
|
||||
if options.range is None:
|
||||
rangeMin,rangeMax = min(table.data[:,0]),max(table.data[:,0])
|
||||
else:
|
||||
rangeMin,rangeMax = min(options.range),max(options.range)
|
||||
|
||||
# --------------- bin data ----------------------------------------------------------------
|
||||
|
||||
count,edges = np.histogram(table.data[:,0],
|
||||
bins = reverse(forward(rangeMin) + np.arange(options.N+1) *
|
||||
(forward(rangeMax)-forward(rangeMin))/options.N),
|
||||
range = (rangeMin,rangeMax),
|
||||
weights = None if options.weights is None else table.data[:,1],
|
||||
density = options.density,
|
||||
)
|
||||
bincenter = reverse(forward(rangeMin) + (0.5+np.arange(options.N)) *
|
||||
(forward(rangeMax)-forward(rangeMin))/options.N) # determine center of bins
|
||||
|
||||
# ------------------------------------------ assemble header ---------------------------------------
|
||||
|
||||
table.info_clear()
|
||||
table.info_append([scriptID + '\t' + ' '.join(sys.argv[1:]),
|
||||
scriptID + ':\t' +
|
||||
'data range {} -- {}'.format(rangeMin,rangeMax) +
|
||||
(' (log)' if options.log else ''),
|
||||
])
|
||||
table.labels_clear()
|
||||
table.labels_append(['bincenter','count'])
|
||||
table.head_write()
|
||||
|
||||
# ------------------------------------------ output result -----------------------------------------
|
||||
|
||||
table.data = np.squeeze(np.dstack((bincenter,count)))
|
||||
table.data_writeArray()
|
||||
|
||||
# ------------------------------------------ output finalization -----------------------------------
|
||||
|
||||
table.close() # close ASCII tables
|
||||
|
|
@ -1,7 +1,7 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: UTF-8 no BOM -*-
|
||||
|
||||
import os,sys
|
||||
import os,sys,re
|
||||
import damask
|
||||
from optparse import OptionParser
|
||||
|
||||
|
|
@ -32,13 +32,16 @@ parser.set_defaults(label = [],
|
|||
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
||||
pattern = [re.compile('^()(.+)$'), # label pattern for scalar
|
||||
re.compile('^(\d+_)?(.+)$'), # label pattern for multidimension
|
||||
]
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
buffered = False)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
|
@ -63,8 +66,9 @@ for name in filenames:
|
|||
for i,index in enumerate(indices):
|
||||
if index == -1: remarks.append('label {} not present...'.format(options.label[i]))
|
||||
else:
|
||||
m = pattern[dimensions[i]>1].match(table.labels[index]) # isolate label name
|
||||
for j in xrange(dimensions[i]):
|
||||
table.labels[index+j] = table.labels[index+j].replace(options.label[i],options.substitute[i])
|
||||
table.labels[index+j] = table.labels[index+j].replace(m.group(2),options.substitute[i]) # replace name with substitute
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
|
|
|
|||
|
|
@ -1,8 +1,9 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: UTF-8 no BOM -*-
|
||||
|
||||
import os,sys,vtk
|
||||
import os,vtk
|
||||
import damask
|
||||
from collections import defaultdict
|
||||
from optparse import OptionParser
|
||||
|
||||
scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
||||
|
|
@ -17,27 +18,38 @@ Add scalar and RGB tuples from ASCIItable to existing VTK point cloud (.vtp).
|
|||
|
||||
""", version = scriptID)
|
||||
|
||||
parser.add_option('-v', '--vtk', dest='vtk', \
|
||||
parser.add_option( '--vtk',
|
||||
dest = 'vtk',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'VTK file name')
|
||||
parser.add_option( '--inplace',
|
||||
dest = 'inplace',
|
||||
action = 'store_true',
|
||||
help = 'modify VTK file in-place')
|
||||
parser.add_option('-r', '--render',
|
||||
dest = 'render',
|
||||
action = 'store_true',
|
||||
help = 'open output in VTK render window')
|
||||
parser.add_option('-s', '--scalar', dest='scalar', action='extend', \
|
||||
help = 'scalar values')
|
||||
parser.add_option('-v', '--vector',
|
||||
dest = 'vector',
|
||||
action = 'extend', metavar = '<string LIST>',
|
||||
help = 'vector value label(s)')
|
||||
parser.add_option('-c', '--color', dest='color', action='extend', \
|
||||
help = 'RGB color tuples')
|
||||
|
||||
parser.set_defaults(scalar = [])
|
||||
parser.set_defaults(color = [])
|
||||
parser.set_defaults(scalar = [],
|
||||
vector = [],
|
||||
color = [],
|
||||
inplace = False,
|
||||
render = False,
|
||||
)
|
||||
|
||||
(options, filenames) = parser.parse_args()
|
||||
|
||||
datainfo = { # list of requested labels per datatype
|
||||
'scalar': {'len':1,
|
||||
'label':[]},
|
||||
'color': {'len':3,
|
||||
'label':[]},
|
||||
}
|
||||
|
||||
if not os.path.exists(options.vtk):
|
||||
parser.error('VTK file does not exist'); sys.exit()
|
||||
if not options.vtk: parser.error('No VTK file specified.')
|
||||
if not os.path.exists(options.vtk): parser.error('VTK file does not exist.')
|
||||
|
||||
reader = vtk.vtkXMLPolyDataReader()
|
||||
reader.SetFileName(options.vtk)
|
||||
|
|
@ -48,69 +60,64 @@ Nvertices = reader.GetNumberOfVerts()
|
|||
Polydata = reader.GetOutput()
|
||||
|
||||
if Npoints != Ncells or Npoints != Nvertices:
|
||||
parser.error('Number of points, cells, and vertices in VTK differ from each other'); sys.exit()
|
||||
if options.scalar is not None: datainfo['scalar']['label'] += options.scalar
|
||||
if options.color is not None: datainfo['color']['label'] += options.color
|
||||
parser.error('Number of points, cells, and vertices in VTK differ from each other.')
|
||||
|
||||
# ------------------------------------------ setup file handles ---------------------------------------
|
||||
damask.util.croak('{}: {} points, {} vertices, and {} cells...'.format(options.vtk,Npoints,Nvertices,Ncells))
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
files = []
|
||||
if filenames == []:
|
||||
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr})
|
||||
else:
|
||||
for name in filenames:
|
||||
if os.path.exists(name):
|
||||
files.append({'name':name, 'input':open(name), 'output':sys.stderr, 'croak':sys.stderr})
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
buffered = False,
|
||||
readonly = True)
|
||||
except: continue
|
||||
damask.util.report(scriptName, name)
|
||||
|
||||
#--- loop over input files ------------------------------------------------------------------------
|
||||
for file in files:
|
||||
if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
|
||||
else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
|
||||
# --- interpret header ----------------------------------------------------------------------------
|
||||
|
||||
table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
|
||||
table.head_read() # read ASCII header info
|
||||
table.head_read()
|
||||
|
||||
# --------------- figure out columns to process
|
||||
active = {}
|
||||
column = {}
|
||||
remarks = []
|
||||
errors = []
|
||||
VTKarray = {}
|
||||
active = defaultdict(list)
|
||||
|
||||
array = {}
|
||||
for datatype,dimension,label in [['scalar',1,options.scalar],
|
||||
['vector',3,options.vector],
|
||||
['color',3,options.color],
|
||||
]:
|
||||
for i,dim in enumerate(table.label_dimension(label)):
|
||||
me = label[i]
|
||||
if dim == -1: remarks.append('{} "{}" not found...'.format(datatype,me))
|
||||
elif dim > dimension: remarks.append('"{}" not of dimension {}...'.format(me,dimension))
|
||||
else:
|
||||
remarks.append('adding {} "{}"...'.format(datatype,me))
|
||||
active[datatype].append(me)
|
||||
|
||||
for datatype,info in datainfo.items():
|
||||
for label in info['label']:
|
||||
foundIt = False
|
||||
for key in ['1_'+label,label]:
|
||||
if key in table.labels:
|
||||
foundIt = True
|
||||
if datatype not in active: active[datatype] = []
|
||||
if datatype not in column: column[datatype] = {}
|
||||
if datatype not in array: array[datatype] = {}
|
||||
active[datatype].append(label)
|
||||
column[datatype][label] = table.labels.index(key) # remember columns of requested data
|
||||
if datatype == 'scalar':
|
||||
array[datatype][label] = vtk.vtkDoubleArray()
|
||||
array[datatype][label].SetNumberOfComponents(1)
|
||||
array[datatype][label].SetName(label)
|
||||
elif datatype == 'color':
|
||||
array[datatype][label] = vtk.vtkUnsignedCharArray()
|
||||
array[datatype][label].SetNumberOfComponents(3)
|
||||
array[datatype][label].SetName(label)
|
||||
if not foundIt:
|
||||
file['croak'].write('column %s not found...\n'%label)
|
||||
if datatype in ['scalar','vector']: VTKarray[me] = vtk.vtkDoubleArray()
|
||||
elif datatype == 'color': VTKarray[me] = vtk.vtkUnsignedCharArray()
|
||||
|
||||
VTKarray[me].SetNumberOfComponents(dimension)
|
||||
VTKarray[me].SetName(label[i])
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
damask.util.croak(errors)
|
||||
table.close(dismiss = True)
|
||||
continue
|
||||
|
||||
# ------------------------------------------ process data ---------------------------------------
|
||||
|
||||
while table.data_read(): # read next data line of ASCII table
|
||||
|
||||
for datatype,labels in active.items(): # loop over scalar,color
|
||||
for label in labels: # loop over all requested items
|
||||
theData = table.data[column[datatype][label]:\
|
||||
column[datatype][label]+datainfo[datatype]['len']] # read strings
|
||||
if datatype == 'color':
|
||||
theData = map(lambda x: int(255.*float(x)),theData)
|
||||
array[datatype][label].InsertNextTuple3(theData[0],theData[1],theData[2],)
|
||||
elif datatype == 'scalar':
|
||||
array[datatype][label].InsertNextValue(float(theData[0]))
|
||||
for me in labels: # loop over all requested items
|
||||
theData = [table.data[i] for i in table.label_indexrange(me)] # read strings
|
||||
if datatype == 'color': VTKarray[me].InsertNextTuple3(*map(lambda x: int(255.*float(x)),theData))
|
||||
elif datatype == 'vector': VTKarray[me].InsertNextTuple3(*map(float,theData))
|
||||
elif datatype == 'scalar': VTKarray[me].InsertNextValue(float(theData[0]))
|
||||
|
||||
table.input_close() # close input ASCII table
|
||||
|
||||
|
|
@ -118,24 +125,50 @@ for file in files:
|
|||
|
||||
for datatype,labels in active.items(): # loop over scalar,color
|
||||
if datatype == 'color':
|
||||
Polydata.GetPointData().SetScalars(array[datatype][labels[0]])
|
||||
Polydata.GetCellData().SetScalars(array[datatype][labels[0]])
|
||||
for label in labels: # loop over all requested items
|
||||
Polydata.GetPointData().AddArray(array[datatype][label])
|
||||
Polydata.GetCellData().AddArray(array[datatype][label])
|
||||
Polydata.GetPointData().SetScalars(VTKarray[active['color'][0]])
|
||||
Polydata.GetCellData().SetScalars(VTKarray[active['color'][0]])
|
||||
for me in labels: # loop over all requested items
|
||||
Polydata.GetPointData().AddArray(VTKarray[me])
|
||||
Polydata.GetCellData().AddArray(VTKarray[me])
|
||||
|
||||
Polydata.Modified()
|
||||
if vtk.VTK_MAJOR_VERSION <= 5:
|
||||
Polydata.Update()
|
||||
if vtk.VTK_MAJOR_VERSION <= 5: Polydata.Update()
|
||||
|
||||
# ------------------------------------------ output result ---------------------------------------
|
||||
|
||||
writer = vtk.vtkXMLPolyDataWriter()
|
||||
writer.SetDataModeToBinary()
|
||||
writer.SetCompressorTypeToZLib()
|
||||
writer.SetFileName(os.path.splitext(options.vtk)[0]+'_added.vtp')
|
||||
if vtk.VTK_MAJOR_VERSION <= 5:
|
||||
writer.SetInput(Polydata)
|
||||
else:
|
||||
writer.SetInputData(Polydata)
|
||||
writer.SetFileName(os.path.splitext(options.vtk)[0]+('.vtp' if options.inplace else '_added.vtp'))
|
||||
if vtk.VTK_MAJOR_VERSION <= 5: writer.SetInput(Polydata)
|
||||
else: writer.SetInputData(Polydata)
|
||||
writer.Write()
|
||||
|
||||
# ------------------------------------------ render result ---------------------------------------
|
||||
|
||||
if options.render:
|
||||
mapper = vtk.vtkDataSetMapper()
|
||||
mapper.SetInputData(Polydata)
|
||||
actor = vtk.vtkActor()
|
||||
actor.SetMapper(mapper)
|
||||
|
||||
# Create the graphics structure. The renderer renders into the
|
||||
# render window. The render window interactor captures mouse events
|
||||
# and will perform appropriate camera or actor manipulation
|
||||
# depending on the nature of the events.
|
||||
|
||||
ren = vtk.vtkRenderer()
|
||||
|
||||
renWin = vtk.vtkRenderWindow()
|
||||
renWin.AddRenderer(ren)
|
||||
|
||||
ren.AddActor(actor)
|
||||
ren.SetBackground(1, 1, 1)
|
||||
renWin.SetSize(200, 200)
|
||||
|
||||
iren = vtk.vtkRenderWindowInteractor()
|
||||
iren.SetRenderWindow(renWin)
|
||||
|
||||
iren.Initialize()
|
||||
renWin.Render()
|
||||
iren.Start()
|
||||
|
|
|
|||
|
|
@ -83,9 +83,9 @@ damask.util.croak('{}: {} points and {} cells...'.format(options.vtk,Npoints,Nce
|
|||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,
|
||||
buffered = False, readonly = True)
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
buffered = False,
|
||||
readonly = True)
|
||||
except: continue
|
||||
damask.util.report(scriptName, name)
|
||||
|
||||
|
|
@ -133,6 +133,8 @@ for name in filenames:
|
|||
elif datatype == 'vector': VTKarray[me].InsertNextTuple3(*map(float,theData))
|
||||
elif datatype == 'scalar': VTKarray[me].InsertNextValue(float(theData[0]))
|
||||
|
||||
table.input_close() # close input ASCII table
|
||||
|
||||
# ------------------------------------------ add data ---------------------------------------
|
||||
|
||||
for datatype,labels in active.items(): # loop over scalar,color
|
||||
|
|
|
|||
|
|
@ -18,12 +18,12 @@ Produce a VTK point cloud dataset based on coordinates given in an ASCIItable.
|
|||
|
||||
""", version = scriptID)
|
||||
|
||||
parser.add_option('-d', '--deformed',
|
||||
dest = 'deformed',
|
||||
parser.add_option('-c', '--coordinates',
|
||||
dest = 'pos',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'deformed coordinate label [%default]')
|
||||
help = 'coordinate label [%default]')
|
||||
|
||||
parser.set_defaults(deformed = 'ipdeformedcoord'
|
||||
parser.set_defaults(pos = 'pos'
|
||||
)
|
||||
|
||||
(options, filenames) = parser.parse_args()
|
||||
|
|
@ -46,9 +46,9 @@ for name in filenames:
|
|||
|
||||
errors = []
|
||||
remarks = []
|
||||
coordDim = table.label_dimension(options.deformed)
|
||||
if not 3 >= coordDim >= 1: errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.deformed))
|
||||
elif coordDim < 3: remarks.append('appending {} dimensions to coordinates "{}"...'.format(3-coordDim,options.deformed))
|
||||
coordDim = table.label_dimension(options.pos)
|
||||
if not 3 >= coordDim >= 1: errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.pos))
|
||||
elif coordDim < 3: remarks.append('appending {} dimensions to coordinates "{}"...'.format(3-coordDim,options.pos))
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
|
|
@ -58,7 +58,7 @@ for name in filenames:
|
|||
|
||||
# ------------------------------------------ process data ---------------------------------------
|
||||
|
||||
table.data_readArray(options.deformed)
|
||||
table.data_readArray(options.pos)
|
||||
if len(table.data.shape) < 2: table.data.shape += (1,) # expand to 2D shape
|
||||
if table.data.shape[1] < 3:
|
||||
table.data = np.hstack((table.data,
|
||||
|
|
|
|||
|
|
@ -38,9 +38,9 @@ parser.set_defaults(position ='ipinitialcoord',
|
|||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,
|
||||
buffered = False, readonly = True)
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
buffered = False,
|
||||
readonly = True)
|
||||
except: continue
|
||||
damask.util.report(scriptName,name)
|
||||
|
||||
|
|
@ -48,10 +48,13 @@ for name in filenames:
|
|||
|
||||
table.head_read()
|
||||
|
||||
remarks = []
|
||||
errors = []
|
||||
if table.label_dimension(options.position) != 3:
|
||||
errors.append('coordinates {} are not a vector.'.format(options.position))
|
||||
coordDim = table.label_dimension(options.position)
|
||||
if not 3 >= coordDim >= 1: errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.position))
|
||||
elif coordDim < 3: remarks.append('appending {} dimensions to coordinates "{}"...'.format(3-coordDim,options.position))
|
||||
|
||||
if remarks != []: damask.util.croak(remarks)
|
||||
if errors != []:
|
||||
damask.util.croak(errors)
|
||||
table.close(dismiss=True)
|
||||
|
|
@ -60,6 +63,11 @@ for name in filenames:
|
|||
# --------------- figure out size and grid ---------------------------------------------------------
|
||||
|
||||
table.data_readArray(options.position)
|
||||
if len(table.data.shape) < 2: table.data.shape += (1,) # expand to 2D shape
|
||||
if table.data.shape[1] < 3:
|
||||
table.data = np.hstack((table.data,
|
||||
np.zeros((table.data.shape[0],
|
||||
3-table.data.shape[1]),dtype='f'))) # fill coords up to 3D with zeros
|
||||
|
||||
coords = [np.unique(table.data[:,i]) for i in xrange(3)]
|
||||
if options.mode == 'cell':
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
import os,sys,math
|
||||
import numpy as np
|
||||
import multiprocessing
|
||||
from optparse import OptionParser
|
||||
from optparse import OptionParser,OptionGroup
|
||||
from scipy import spatial
|
||||
import damask
|
||||
|
||||
|
|
@ -109,71 +109,83 @@ Generate geometry description and material configuration by standard Voronoi tes
|
|||
|
||||
""", version = scriptID)
|
||||
|
||||
parser.add_option('-g', '--grid',
|
||||
dest = 'grid',
|
||||
type = 'int', nargs = 3, metavar = ' '.join(['int']*3),
|
||||
help = 'a,b,c grid of hexahedral box [auto]')
|
||||
parser.add_option('-s', '--size',
|
||||
dest = 'size',
|
||||
type = 'float', nargs = 3, metavar=' '.join(['float']*3),
|
||||
help = 'x,y,z size of hexahedral box [auto]')
|
||||
parser.add_option('-o', '--origin',
|
||||
dest = 'origin',
|
||||
type = 'float', nargs = 3, metavar=' '.join(['float']*3),
|
||||
help = 'offset from old to new origin of grid')
|
||||
parser.add_option('-p', '--position',
|
||||
dest = 'position',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed positions [%default]')
|
||||
parser.add_option('-w', '--weight',
|
||||
dest = 'weight',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed weights [%default]')
|
||||
parser.add_option('-m', '--microstructure',
|
||||
dest = 'microstructure',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed microstructures [%default]')
|
||||
parser.add_option('-e', '--eulers',
|
||||
dest = 'eulers',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed Euler angles [%default]')
|
||||
parser.add_option('--axes',
|
||||
dest = 'axes',
|
||||
type = 'string', nargs = 3, metavar = ' '.join(['string']*3),
|
||||
help = 'orientation coordinate frame in terms of position coordinate frame')
|
||||
parser.add_option('--homogenization',
|
||||
dest = 'homogenization',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'homogenization index to be used [%default]')
|
||||
parser.add_option('--crystallite',
|
||||
dest = 'crystallite',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'crystallite index to be used [%default]')
|
||||
parser.add_option('--phase',
|
||||
dest = 'phase',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'phase index to be used [%default]')
|
||||
parser.add_option('-r', '--rnd',
|
||||
dest = 'randomSeed',
|
||||
type = 'int', metavar='int',
|
||||
help = 'seed of random number generator for second phase distribution [%default]')
|
||||
parser.add_option('--secondphase',
|
||||
dest = 'secondphase',
|
||||
type = 'float', metavar= 'float',
|
||||
help = 'volume fraction of randomly distribute second phase [%default]')
|
||||
parser.add_option('-l', '--laguerre',
|
||||
|
||||
group = OptionGroup(parser, "Tessellation","")
|
||||
|
||||
group.add_option('-l', '--laguerre',
|
||||
dest = 'laguerre',
|
||||
action = 'store_true',
|
||||
help = 'use Laguerre (weighted Voronoi) tessellation')
|
||||
parser.add_option('--cpus',
|
||||
group.add_option('--cpus',
|
||||
dest = 'cpus',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'number of parallel processes to use for Laguerre tessellation [%default]')
|
||||
parser.add_option('--nonperiodic',
|
||||
group.add_option('--nonperiodic',
|
||||
dest = 'nonperiodic',
|
||||
action = 'store_true',
|
||||
help = 'use nonperiodic tessellation')
|
||||
|
||||
parser.add_option_group(group)
|
||||
|
||||
group = OptionGroup(parser, "Geometry","")
|
||||
|
||||
group.add_option('-g', '--grid',
|
||||
dest = 'grid',
|
||||
type = 'int', nargs = 3, metavar = ' '.join(['int']*3),
|
||||
help = 'a,b,c grid of hexahedral box [auto]')
|
||||
group.add_option('-s', '--size',
|
||||
dest = 'size',
|
||||
type = 'float', nargs = 3, metavar=' '.join(['float']*3),
|
||||
help = 'x,y,z size of hexahedral box [auto]')
|
||||
group.add_option('-o', '--origin',
|
||||
dest = 'origin',
|
||||
type = 'float', nargs = 3, metavar=' '.join(['float']*3),
|
||||
help = 'origin of grid')
|
||||
|
||||
parser.add_option_group(group)
|
||||
|
||||
group = OptionGroup(parser, "Seeds","")
|
||||
|
||||
group.add_option('-p', '--position',
|
||||
dest = 'position',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed positions [%default]')
|
||||
group.add_option('-w', '--weight',
|
||||
dest = 'weight',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed weights [%default]')
|
||||
group.add_option('-m', '--microstructure',
|
||||
dest = 'microstructure',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed microstructures [%default]')
|
||||
group.add_option('-e', '--eulers',
|
||||
dest = 'eulers',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'column label for seed Euler angles [%default]')
|
||||
group.add_option('--axes',
|
||||
dest = 'axes',
|
||||
type = 'string', nargs = 3, metavar = ' '.join(['string']*3),
|
||||
help = 'orientation coordinate frame in terms of position coordinate frame')
|
||||
|
||||
parser.add_option_group(group)
|
||||
|
||||
group = OptionGroup(parser, "Configuration","")
|
||||
|
||||
group.add_option('--homogenization',
|
||||
dest = 'homogenization',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'homogenization index to be used [%default]')
|
||||
group.add_option('--crystallite',
|
||||
dest = 'crystallite',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'crystallite index to be used [%default]')
|
||||
group.add_option('--phase',
|
||||
dest = 'phase',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'phase index to be used [%default]')
|
||||
|
||||
parser.add_option_group(group)
|
||||
|
||||
parser.set_defaults(position = 'pos',
|
||||
weight = 'weight',
|
||||
microstructure = 'microstructure',
|
||||
|
|
@ -181,24 +193,18 @@ parser.set_defaults(position = 'pos',
|
|||
homogenization = 1,
|
||||
crystallite = 1,
|
||||
phase = 1,
|
||||
secondphase = 0.0,
|
||||
cpus = 2,
|
||||
laguerre = False,
|
||||
nonperiodic = False,
|
||||
randomSeed = None,
|
||||
)
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
||||
if options.secondphase > 1.0 or options.secondphase < 0.0:
|
||||
parser.error('volume fraction of second phase ({}) out of bounds.'.format(options.secondphase))
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
if filenames == []: filenames = [None]
|
||||
|
||||
for name in filenames:
|
||||
try:
|
||||
table = damask.ASCIItable(name = name,
|
||||
try: table = damask.ASCIItable(name = name,
|
||||
outname = os.path.splitext(name)[-2]+'.geom' if name else name,
|
||||
buffered = False)
|
||||
except: continue
|
||||
|
|
@ -294,20 +300,11 @@ for name in filenames:
|
|||
config_header = []
|
||||
formatwidth = 1+int(math.log10(NgrainIDs))
|
||||
|
||||
phase = options.phase * np.ones(NgrainIDs,'i')
|
||||
if int(options.secondphase*info['microstructures']) > 0:
|
||||
phase[0:int(options.secondphase*info['microstructures'])] += 1 # alter fraction 'options.secondphase' of used grainIDs
|
||||
randomSeed = options.randomSeed if options.randomSeed \
|
||||
else int(os.urandom(4).encode('hex'), 16) # random seed for second phase
|
||||
np.random.seed(randomSeed)
|
||||
np.random.shuffle(phase)
|
||||
config_header += ['# random seed (phase shuffling): {}'.format(randomSeed)]
|
||||
|
||||
config_header += ['<microstructure>']
|
||||
for i,ID in enumerate(grainIDs):
|
||||
config_header += ['[Grain%s]'%(str(ID).zfill(formatwidth)),
|
||||
'crystallite %i'%options.crystallite,
|
||||
'(constituent)\tphase %i\ttexture %s\tfraction 1.0'%(phase[i],str(ID).rjust(formatwidth)),
|
||||
'(constituent)\tphase %i\ttexture %s\tfraction 1.0'%(options.phase,str(ID).rjust(formatwidth)),
|
||||
]
|
||||
if hasEulers:
|
||||
config_header += ['<texture>']
|
||||
|
|
|
|||
|
|
@ -48,8 +48,11 @@ parser.add_option('-m', '--microstructure',
|
|||
parser.add_option('-r', '--rnd',
|
||||
dest = 'randomSeed', type = 'int', metavar = 'int',
|
||||
help = 'seed of random number generator [%default]')
|
||||
parser.add_option('--format',
|
||||
dest = 'format', type = 'string', metavar = 'string',
|
||||
help = 'number format of output [auto]')
|
||||
|
||||
group = OptionGroup(parser, "Laguerre Tessellation Options",
|
||||
group = OptionGroup(parser, "Laguerre Tessellation",
|
||||
"Parameters determining shape of weight distribution of seed points"
|
||||
)
|
||||
group.add_option('-w', '--weights',
|
||||
|
|
@ -70,8 +73,8 @@ group.add_option('--sigma',
|
|||
help='standard deviation of normal distribution for weights [%default]')
|
||||
parser.add_option_group(group)
|
||||
|
||||
group = OptionGroup(parser, "Selective Seeding Options",
|
||||
"More uniform distribution of seed points using Mitchell\'s Best Candidate Algorithm"
|
||||
group = OptionGroup(parser, "Selective Seeding",
|
||||
"More uniform distribution of seed points using Mitchell's Best Candidate Algorithm"
|
||||
)
|
||||
group.add_option('-s','--selective',
|
||||
action = 'store_true',
|
||||
|
|
@ -103,6 +106,7 @@ parser.set_defaults(randomSeed = None,
|
|||
force = False,
|
||||
distance = 0.2,
|
||||
numCandidates = 10,
|
||||
format = None,
|
||||
)
|
||||
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
|
@ -215,7 +219,7 @@ for name in filenames:
|
|||
# --- write seeds information ------------------------------------------------------------
|
||||
|
||||
table.data = seeds
|
||||
table.data_writeArray()
|
||||
table.data_writeArray(fmt = options.format)
|
||||
|
||||
# --- output finalization --------------------------------------------------------------------------
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue