DAMASK_EICMD/python/damask/dadf5.py

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from queue import Queue
import re
import glob
import os
import vtk
from vtk.util import numpy_support
import h5py
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import numpy as np
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from . import util
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from . import version
from . import mechanics
# ------------------------------------------------------------------
class DADF5():
"""
Read and write to DADF5 files.
DADF5 files contain DAMASK results.
"""
# ------------------------------------------------------------------
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def __init__(self,fname):
"""
Opens an existing DADF5 file.
Parameters
----------
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fname : str
name of the DADF5 file to be openend.
"""
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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']
if self.version_major != 0 or not 2 <= self.version_minor <= 5:
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raise TypeError('Unsupported DADF5 version {} '.format(f.attrs['DADF5-version']))
self.structured = 'grid' in f['geometry'].attrs.keys()
if self.structured:
self.grid = f['geometry'].attrs['grid']
self.size = f['geometry'].attrs['size']
if self.version_major == 0 and self.version_minor >= 5:
self.origin = f['geometry'].attrs['origin']
r=re.compile('inc[0-9]+')
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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]
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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'])]
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self.con_physics = []
for c in self.constituents:
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self.con_physics += f['/'.join([self.increments[0],'constituent',c])].keys()
self.con_physics = list(set(self.con_physics)) # make unique
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self.mat_physics = []
for m in self.materialpoints:
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self.mat_physics += f['/'.join([self.increments[0],'materialpoint',m])].keys()
self.mat_physics = list(set(self.mat_physics)) # make unique
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self.visible= {'increments': self.increments,
'constituents': self.constituents,
'materialpoints': self.materialpoints,
'constituent': range(self.Nconstituents), # ToDo: stupid naming
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'con_physics': self.con_physics,
'mat_physics': self.mat_physics}
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self.fname = fname
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def __manage_visible(self,datasets,what,action):
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"""
Manages the visibility of the groups.
Parameters
----------
datasets : list of str or Boolean
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
what : str
attribute to change (must be in self.visible)
action : str
select from 'set', 'add', and 'del'
"""
# allow True/False and string arguments
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if datasets is True:
datasets = ['*']
elif datasets is False:
datasets = []
choice = [datasets] if isinstance(datasets,str) else datasets
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valid = [e for e_ in [glob.fnmatch.filter(getattr(self,what),s) for s in choice] for e in e_]
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existing = set(self.visible[what])
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if action == 'set':
self.visible[what] = valid
elif action == 'add':
self.visible[what] = list(existing.union(valid))
elif action == 'del':
self.visible[what] = list(existing.difference_update(valid))
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def __time_to_inc(self,start,end):
selected = []
for i,time in enumerate(self.times):
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if start <= time <= end:
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selected.append(self.increments[i])
return selected
def set_by_time(self,start,end):
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"""
Set active increments based on start and end time.
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Parameters
----------
start : float
start time (included)
end : float
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end time (included)
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"""
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self.__manage_visible(self.__time_to_inc(start,end),'increments','set')
def add_by_time(self,start,end):
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"""
Add to active increments based on start and end time.
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Parameters
----------
start : float
start time (included)
end : float
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end time (included)
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"""
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self.__manage_visible(self.__time_to_inc(start,end),'increments','add')
def del_by_time(self,start,end):
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"""
Delete from active increments based on start and end time.
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Parameters
----------
start : float
start time (included)
end : float
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end time (included)
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"""
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self.__manage_visible(self.__time_to_inc(start,end),'increments','del')
def set_by_increment(self,start,end):
"""
Set active time increments based on start and end increment.
Parameters
----------
start : int
start increment (included)
end : int
end increment (included)
"""
if self.version_minor >= 4:
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self.__manage_visible([ 'inc{}'.format(i) for i in range(start,end+1)],'increments','set')
else:
self.__manage_visible(['inc{:05d}'.format(i) for i in range(start,end+1)],'increments','set')
def add_by_increment(self,start,end):
"""
Add to active time increments based on start and end increment.
Parameters
----------
start : int
start increment (included)
end : int
end increment (included)
"""
if self.version_minor >= 4:
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self.__manage_visible([ 'inc{}'.format(i) for i in range(start,end+1)],'increments','add')
else:
self.__manage_visible(['inc{:05d}'.format(i) for i in range(start,end+1)],'increments','add')
def del_by_increment(self,start,end):
"""
Delet from active time increments based on start and end increment.
Parameters
----------
start : int
start increment (included)
end : int
end increment (included)
"""
if self.version_minor >= 4:
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self.__manage_visible([ 'inc{}'.format(i) for i in range(start,end+1)],'increments','del')
else:
self.__manage_visible(['inc{:05d}'.format(i) for i in range(start,end+1)],'increments','del')
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def iter_visible(self,what):
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"""
Iterate over visible items by setting each one visible.
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Parameters
----------
what : str
attribute to change (must be in self.visible)
"""
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datasets = self.visible[what]
last_datasets = datasets.copy()
for dataset in datasets:
if last_datasets != self.visible[what]:
self.__manage_visible(datasets,what,'set')
raise Exception
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self.__manage_visible(dataset,what,'set')
last_datasets = self.visible[what]
yield dataset
self.__manage_visible(datasets,what,'set')
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def set_visible(self,what,datasets):
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"""
Set active groups.
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Parameters
----------
datasets : list of str or Boolean
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
what : str
attribute to change (must be in self.visible)
"""
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self.__manage_visible(datasets,what,'set')
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def add_visible(self,what,datasets):
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"""
Add to active groups.
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Parameters
----------
datasets : list of str or Boolean
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
what : str
attribute to change (must be in self.visible)
"""
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self.__manage_visible(datasets,what,'add')
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def del_visible(self,what,datasets):
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"""
Delete from active groupse.
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Parameters
----------
datasets : list of str or Boolean
name of datasets as list, supports ? and * wildcards.
True is equivalent to [*], False is equivalent to []
what : str
attribute to change (must be in self.visible)
"""
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self.__manage_visible(datasets,what,'del')
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def groups_with_datasets(self,datasets):
"""
Get groups that contain all requested datasets.
Only groups within inc?????/constituent/*_*/* inc?????/materialpoint/*_*/*
are considered as they contain the data.
Single strings will be treated as list with one entry.
Wild card matching is allowed, but the number of arguments need to fit.
Parameters
----------
datasets : iterable or str or boolean
Examples
--------
datasets = False matches no group
datasets = True matches all groups
datasets = ['F','P'] matches a group with ['F','P','sigma']
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datasets = ['*','P'] matches a group with ['F','P']
datasets = ['*'] does not match a group with ['F','P','sigma']
datasets = ['*','*'] does not match a group with ['F','P','sigma']
datasets = ['*','*','*'] matches a group with ['F','P','sigma']
"""
if datasets is False: return []
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sets = [datasets] if isinstance(datasets,str) else datasets
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groups = []
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with h5py.File(self.fname,'r') as f:
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for i in self.iter_visible('increments'):
for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
for oo in self.iter_visible(o):
for pp in self.iter_visible(p):
group = '/'.join([i,o[:-1],oo,pp]) # o[:-1]: plural/singular issue
if sets is True:
groups.append(group)
else:
match = [e for e_ in [glob.fnmatch.filter(f[group].keys(),s) for s in sets] for e in e_]
if len(set(match)) == len(sets) : groups.append(group)
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return groups
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def list_data(self):
"""Return information on all active datasets in the file."""
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message = ''
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with h5py.File(self.fname,'r') as f:
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for s,i in enumerate(self.iter_visible('increments')):
message+='\n{} ({}s)\n'.format(i,self.times[s])
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for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
for oo in self.iter_visible(o):
message+=' {}\n'.format(oo)
for pp in self.iter_visible(p):
message+=' {}\n'.format(pp)
group = '/'.join([i,o[:-1],oo,pp]) # o[:-1]: plural/singular issue
for d in f[group].keys():
try:
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dataset = f['/'.join([group,d])]
message+=' {} / ({}): {}\n'.format(d,dataset.attrs['Unit'].decode(),dataset.attrs['Description'].decode())
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except KeyError:
pass
return message
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def get_dataset_location(self,label):
"""Return the location of all active datasets with given label."""
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path = []
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with h5py.File(self.fname,'r') as f:
for i in self.iter_visible('increments'):
k = '/'.join([i,'geometry',label])
try:
f[k]
path.append(k)
except KeyError as e:
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pass
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for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
for oo in self.iter_visible(o):
for pp in self.iter_visible(p):
k = '/'.join([i,o[:-1],oo,pp,label])
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try:
f[k]
path.append(k)
except KeyError as e:
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pass
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return path
def get_constituent_ID(self,c=0):
"""Pointwise constituent ID."""
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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."""
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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 read_dataset(self,path,c=0,plain=False):
"""
Dataset for all points/cells.
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If more than one path is given, the dataset is composed of the individual contributions.
"""
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with h5py.File(self.fname,'r') as f:
shape = (self.Nmaterialpoints,) + np.shape(f[path[0]])[1:]
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if len(shape) == 1: shape = shape +(1,)
dataset = np.full(shape,np.nan,dtype=np.dtype(f[path[0]]))
for pa in path:
label = pa.split('/')[2]
if (pa.split('/')[1] == 'geometry'):
dataset = np.array(f[pa])
continue
p = np.where(f['mapping/cellResults/constituent'][:,c]['Name'] == str.encode(label))[0]
if len(p)>0:
u = (f['mapping/cellResults/constituent']['Position'][p,c])
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a = np.array(f[pa])
if len(a.shape) == 1:
a=a.reshape([a.shape[0],1])
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dataset[p,:] = a[u,:]
p = np.where(f['mapping/cellResults/materialpoint']['Name'] == str.encode(label))[0]
if len(p)>0:
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u = (f['mapping/cellResults/materialpoint']['Position'][p.tolist()])
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a = np.array(f[pa])
if len(a.shape) == 1:
a=a.reshape([a.shape[0],1])
dataset[p,:] = a[u,:]
if plain and dataset.dtype.names is not None:
return dataset.view(('float64',len(dataset.dtype.names)))
else:
return dataset
def cell_coordinates(self):
"""Return initial coordinates of the cell centers."""
if self.structured:
delta = self.size/self.grid*0.5
z, y, x = np.meshgrid(np.linspace(delta[2],self.size[2]-delta[2],self.grid[2]),
np.linspace(delta[1],self.size[1]-delta[1],self.grid[1]),
np.linspace(delta[0],self.size[0]-delta[0],self.grid[0]),
)
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return np.concatenate((x[:,:,:,None],y[:,:,:,None],z[:,:,:,None]),axis = 3).reshape([np.product(self.grid),3])
else:
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with h5py.File(self.fname,'r') as f:
return f['geometry/x_c'][()]
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def add_absolute(self,x):
"""
Add absolute value.
Parameters
----------
x : str
Label of the dataset containing a scalar, vector, or tensor.
"""
def __add_absolute(x):
return {
'data': np.abs(x['data']),
'label': '|{}|'.format(x['label']),
'meta': {
'Unit': x['meta']['Unit'],
'Description': 'Absolute value of {} ({})'.format(x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_abs v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_absolute,requested)
def add_calculation(self,formula,label,unit='n/a',description=None,vectorized=True):
"""
Add result of a general formula.
Parameters
----------
formula : str
Formula, refer to datasets by #Label#.
label : str
Label of the dataset containing the result of the calculation.
unit : str, optional
Physical unit of the result.
description : str, optional
Human readable description of the result.
vectorized : bool, optional
Indicate whether the formula is written in vectorized form. Default is True.
"""
if vectorized is not True:
raise NotImplementedError
def __add_calculation(**kwargs):
formula = kwargs['formula']
for d in re.findall(r'#(.*?)#',formula):
formula = formula.replace('#{}#'.format(d),"kwargs['{}']['data']".format(d))
return {
'data': eval(formula),
'label': kwargs['label'],
'meta': {
'Unit': kwargs['unit'],
'Description': '{} (formula: {})'.format(kwargs['description'],kwargs['formula']),
'Creator': 'dadf5.py:add_calculation v{}'.format(version)
}
}
requested = [{'label':d,'arg':d} for d in set(re.findall(r'#(.*?)#',formula))] # datasets used in the formula
pass_through = {'formula':formula,'label':label,'unit':unit,'description':description}
self.__add_generic_pointwise(__add_calculation,requested,pass_through)
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def add_Cauchy(self,P='P',F='F'):
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"""
Add Cauchy stress calculated from 1. Piola-Kirchhoff stress and deformation gradient.
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Parameters
----------
P : str, optional
Label of the dataset containing the 1. Piola-Kirchhoff stress. Default value is P.
F : str, optional
Label of the dataset containing the deformation gradient. Default value is F.
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"""
def __add_Cauchy(F,P):
return {
'data': mechanics.Cauchy(F['data'],P['data']),
'label': 'sigma',
'meta': {
'Unit': P['meta']['Unit'],
'Description': 'Cauchy stress calculated from {} ({}) '.format(P['label'],P['meta']['Description'])+\
'and deformation gradient {} ({})'.format(F['label'],F['meta']['Description']),
'Creator': 'dadf5.py:add_Cauchy v{}'.format(version)
}
}
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requested = [{'label':F,'arg':'F'},
{'label':P,'arg':'P'} ]
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self.__add_generic_pointwise(__add_Cauchy,requested)
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def add_determinant(self,x):
"""
Add the determinant of a tensor.
Parameters
----------
x : str
Label of the dataset containing a tensor.
"""
def __add_determinant(x):
return {
'data': np.linalg.det(x['data']),
'label': 'det({})'.format(x['label']),
'meta': {
'Unit': x['meta']['Unit'],
'Description': 'Determinant of tensor {} ({})'.format(x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_determinant v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_determinant,requested)
def add_deviator(self,x):
"""
Add the deviatoric part of a tensor.
Parameters
----------
x : str
Label of the dataset containing a tensor.
"""
def __add_deviator(x):
if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])):
raise ValueError
return {
'data': mechanics.deviatoric_part(x['data']),
'label': 's_{}'.format(x['label']),
'meta': {
'Unit': x['meta']['Unit'],
'Description': 'Deviator of tensor {} ({})'.format(x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_deviator v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_deviator,requested)
def add_maximum_shear(self,x):
"""
Add maximum shear components of symmetric tensor.
Parameters
----------
x : str
Label of the dataset containing a symmetric tensor.
"""
def __add_maximum_shear(x):
return {
'data': mechanics.maximum_shear(x['data']),
'label': 'max_shear({})'.format(x['label']),
'meta': {
'Unit': x['meta']['Unit'],
'Description': 'Maximum shear component of of {} ({})'.format(x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_maximum_shear v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_maximum_shear,requested)
def add_Mises(self,x):
"""
Add the equivalent Mises stress or strain of a symmetric tensor.
Parameters
----------
x : str
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Label of the dataset containing a symmetric stress or strain tensor.
"""
def __add_Mises(x):
t = 'strain' if x['meta']['Unit'] == '1' else \
'stress'
return {
'data': mechanics.Mises_strain(x['data']) if t=='strain' else mechanics.Mises_stress(x['data']),
'label': '{}_vM'.format(x['label']),
'meta': {
'Unit': x['meta']['Unit'],
'Description': 'Mises equivalent {} of {} ({})'.format(t,x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_Mises v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_Mises,requested)
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def add_norm(self,x,ord=None):
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"""
Add the norm of vector or tensor.
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Parameters
----------
x : str
Label of the dataset containing a vector or tensor.
ord : {non-zero int, inf, -inf, fro, nuc}, optional
Order of the norm. inf means numpys inf object. For details refer to numpy.linalg.norm.
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"""
def __add_norm(x,ord):
o = ord
if len(x['data'].shape) == 2:
axis = 1
t = 'vector'
if o is None: o = 2
elif len(x['data'].shape) == 3:
axis = (1,2)
t = 'tensor'
if o is None: o = 'fro'
else:
raise ValueError
return {
'data': np.linalg.norm(x['data'],ord=o,axis=axis,keepdims=True),
'label': '|{}|_{}'.format(x['label'],o),
'meta': {
'Unit': x['meta']['Unit'],
'Description': '{}-Norm of {} {} ({})'.format(ord,t,x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_norm v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_norm,requested,{'ord':ord})
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def add_principal_components(self,x):
"""
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Add principal components of symmetric tensor.
The principal components are sorted in descending order, each repeated according to its multiplicity.
Parameters
----------
x : str
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Label of the dataset containing a symmetric tensor.
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"""
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def __add_principal_components(x):
return {
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'data': mechanics.principal_components(x['data']),
'label': 'lambda_{}'.format(x['label']),
'meta': {
'Unit': x['meta']['Unit'],
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'Description': 'Pricipal components of {} ({})'.format(x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_principal_components v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_principal_components,requested)
def add_spherical(self,x):
"""
Add the spherical (hydrostatic) part of a tensor.
Parameters
----------
x : str
Label of the dataset containing a tensor.
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"""
def __add_spherical(x):
if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])):
raise ValueError
return {
'data': mechanics.spherical_part(x['data']),
'label': 'p_{}'.format(x['label']),
'meta': {
'Unit': x['meta']['Unit'],
'Description': 'Spherical component of tensor {} ({})'.format(x['label'],x['meta']['Description']),
'Creator': 'dadf5.py:add_spherical v{}'.format(version)
}
}
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_spherical,requested)
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def add_strain_tensor(self,F='F',t='U',m=0):
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"""
Add strain tensor calculated from a deformation gradient.
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For details refer to damask.mechanics.strain_tensor
Parameters
----------
F : str, optional
Label of the dataset containing the deformation gradient. Default value is F.
t : {V, U}, optional
Type of the polar decomposition, V for right stretch tensor and U for left stretch tensor.
Defaults value is U.
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m : float, optional
Order of the strain calculation. Default value is 0.0.
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"""
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def __add_strain_tensor(F,t,m):
return {
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'data': mechanics.strain_tensor(F['data'],t,m),
'label': 'epsilon_{}^{}({})'.format(t,m,F['label']),
'meta': {
'Unit': F['meta']['Unit'],
'Description': 'Strain tensor of {} ({})'.format(F['label'],F['meta']['Description']),
'Creator': 'dadf5.py:add_strain_tensor v{}'.format(version)
}
}
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requested = [{'label':F,'arg':'F'}]
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self.__add_generic_pointwise(__add_strain_tensor,requested,{'t':t,'m':m})
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def __add_generic_pointwise(self,func,datasets_requested,extra_args={}):
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"""
General function to add pointwise data.
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Parameters
----------
func : function
Function that calculates a new dataset from one or more datasets per HDF5 group.
datasets_requested : list of dictionaries
Details of the datasets to be used: label (in HDF5 file) and arg (argument to which the data is parsed in func).
extra_args : dictionary, optional
Any extra arguments parsed to func.
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"""
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def job(args):
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"""Call function with input data + extra arguments, returns results + group."""
args['results'].put({**args['func'](**args['in']),'group':args['group']})
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N_threads = 1 # ToDo: should be a parameter
results = Queue(N_threads)
pool = util.ThreadPool(N_threads)
N_added = N_threads + 1
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todo = []
# ToDo: It would be more memory efficient to read only from file when required, i.e. do to it in pool.add_task
for group in self.groups_with_datasets([d['label'] for d in datasets_requested]):
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with h5py.File(self.fname,'r') as f:
datasets_in = {}
for d in datasets_requested:
loc = f[group+'/'+d['label']]
data = loc[()]
meta = {k:loc.attrs[k].decode() for k in loc.attrs.keys()}
datasets_in[d['arg']] = {'data': data, 'meta' : meta, 'label' : d['label']}
todo.append({'in':{**datasets_in,**extra_args},'func':func,'group':group,'results':results})
pool.map(job, todo[:N_added]) # initialize
N_not_calculated = len(todo)
while N_not_calculated > 0:
result = results.get()
with h5py.File(self.fname,'a') as f: # write to file
dataset_out = f[result['group']].create_dataset(result['label'],data=result['data'])
for k in result['meta'].keys():
dataset_out.attrs[k] = result['meta'][k].encode()
N_not_calculated-=1
if N_added < len(todo): # add more jobs
pool.add_task(job,todo[N_added])
N_added +=1
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pool.wait_completion()
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def to_vtk(self,labels,mode='Cell'):
"""
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Export to vtk cell/point data.
Parameters
----------
labels : list of str
Labels of the datasets to be exported.
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mode : str, either 'Cell' or 'Point'
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Export in cell format or point format.
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Default value is 'Cell'.
"""
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if mode=='Cell':
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if self.structured:
coordArray = [vtk.vtkDoubleArray(),vtk.vtkDoubleArray(),vtk.vtkDoubleArray()]
for dim in [0,1,2]:
for c in np.linspace(0,self.size[dim],1+self.grid[dim]):
coordArray[dim].InsertNextValue(c)
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vtk_geom = vtk.vtkRectilinearGrid()
vtk_geom.SetDimensions(*(self.grid+1))
vtk_geom.SetXCoordinates(coordArray[0])
vtk_geom.SetYCoordinates(coordArray[1])
vtk_geom.SetZCoordinates(coordArray[2])
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else:
nodes = vtk.vtkPoints()
with h5py.File(self.fname) as f:
nodes.SetData(numpy_support.numpy_to_vtk(f['/geometry/x_n'][()],deep=True))
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vtk_geom = vtk.vtkUnstructuredGrid()
vtk_geom.SetPoints(nodes)
vtk_geom.Allocate(f['/geometry/T_c'].shape[0])
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for i in f['/geometry/T_c']:
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vtk_geom.InsertNextCell(vtk.VTK_HEXAHEDRON,8,i-1) # not for all elements!
elif mode == 'Point':
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Points = vtk.vtkPoints()
Vertices = vtk.vtkCellArray()
for c in self.cell_coordinates():
pointID = Points.InsertNextPoint(c)
Vertices.InsertNextCell(1)
Vertices.InsertCellPoint(pointID)
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vtk_geom = vtk.vtkPolyData()
vtk_geom.SetPoints(Points)
vtk_geom.SetVerts(Vertices)
vtk_geom.Modified()
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N_digits = int(np.floor(np.log10(int(self.increments[-1][3:]))))+1
for i,inc in enumerate(self.iter_visible('increments')):
vtk_data = []
materialpoints_backup = self.visible['materialpoints'].copy()
self.set_visible('materialpoints',False)
for label in labels:
for p in self.iter_visible('con_physics'):
if p != 'generic':
for c in self.iter_visible('constituents'):
x = self.get_dataset_location(label)
if len(x) == 0:
continue
array = self.read_dataset(x,0)
shape = [array.shape[0],np.product(array.shape[1:])]
vtk_data.append(numpy_support.numpy_to_vtk(num_array=array.reshape(shape),
deep=True,array_type= vtk.VTK_DOUBLE))
vtk_data[-1].SetName('1_'+x[0].split('/',1)[1]) #ToDo: hard coded 1!
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vtk_geom.GetCellData().AddArray(vtk_data[-1])
else:
x = self.get_dataset_location(label)
if len(x) == 0:
continue
array = self.read_dataset(x,0)
shape = [array.shape[0],np.product(array.shape[1:])]
vtk_data.append(numpy_support.numpy_to_vtk(num_array=array.reshape(shape),
deep=True,array_type= vtk.VTK_DOUBLE))
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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
vtk_data[-1].SetName(dset_name)
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vtk_geom.GetCellData().AddArray(vtk_data[-1])
self.set_visible('materialpoints',materialpoints_backup)
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constituents_backup = self.visible['constituents'].copy()
self.set_visible('constituents',False)
for label in labels:
for p in self.iter_visible('mat_physics'):
if p != 'generic':
for m in self.iter_visible('materialpoints'):
x = self.get_dataset_location(label)
if len(x) == 0:
continue
array = self.read_dataset(x,0)
shape = [array.shape[0],np.product(array.shape[1:])]
vtk_data.append(numpy_support.numpy_to_vtk(num_array=array.reshape(shape),
deep=True,array_type= vtk.VTK_DOUBLE))
vtk_data[-1].SetName('1_'+x[0].split('/',1)[1]) #ToDo: why 1_?
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vtk_geom.GetCellData().AddArray(vtk_data[-1])
else:
x = self.get_dataset_location(label)
if len(x) == 0:
continue
array = self.read_dataset(x,0)
shape = [array.shape[0],np.product(array.shape[1:])]
vtk_data.append(numpy_support.numpy_to_vtk(num_array=array.reshape(shape),
deep=True,array_type= vtk.VTK_DOUBLE))
vtk_data[-1].SetName('1_'+x[0].split('/',1)[1])
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vtk_geom.GetCellData().AddArray(vtk_data[-1])
self.set_visible('constituents',constituents_backup)
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if mode=='Cell':
writer = vtk.vtkXMLRectilinearGridWriter() if self.structured else \
vtk.vtkXMLUnstructuredGridWriter()
x = self.get_dataset_location('u_n')
vtk_data.append(numpy_support.numpy_to_vtk(num_array=self.read_dataset(x,0),
deep=True,array_type=vtk.VTK_DOUBLE))
vtk_data[-1].SetName('u')
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vtk_geom.GetPointData().AddArray(vtk_data[-1])
elif mode == 'Point':
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writer = vtk.vtkXMLPolyDataWriter()
file_out = '{}_inc{}.{}'.format(os.path.splitext(os.path.basename(self.fname))[0],
inc[3:].zfill(N_digits),
writer.GetDefaultFileExtension())
writer.SetCompressorTypeToZLib()
writer.SetDataModeToBinary()
writer.SetFileName(file_out)
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writer.SetInputData(vtk_geom)
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writer.Write()