DAMASK_EICMD/python/damask/_configmaterial.py

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import numpy as np
import h5py
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from typing import Optional, Union, Sequence, Dict, Any, Collection
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from ._typehints import FileHandle
from . import Config
from . import Rotation
from . import Orientation
from . import util
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from . import Table
class ConfigMaterial(Config):
"""
Material configuration.
Manipulate material configurations for storage in YAML format.
A complete material configuration file has the entries 'material',
'phase', and 'homogenization'. For use in DAMASK, it needs to be
stored as 'material.yaml'.
"""
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def __init__(self,
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d: Optional[Dict[str, Any]] = None,
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**kwargs):
"""
New material configuration.
Parameters
----------
d : dictionary or YAML string, optional
Initial content. Defaults to None, in which case empty entries for
any missing material, homogenization, and phase entry are created.
kwargs : key=value pairs, optional
Initial content specified as pairs of key=value.
"""
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default: Collection
if d is None:
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for section, default in {'material':[],'homogenization':{},'phase':{}}.items():
if section not in kwargs: kwargs.update({section:default})
super().__init__(d,**kwargs)
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def save(self,
fname: FileHandle = 'material.yaml',
**kwargs):
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"""
Save to yaml file.
Parameters
----------
fname : file, str, or pathlib.Path, optional
Filename or file for writing. Defaults to 'material.yaml'.
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**kwargs
Keyword arguments parsed to yaml.dump.
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"""
super().save(fname,**kwargs)
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@classmethod
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def load(cls,
fname: FileHandle = 'material.yaml') -> 'ConfigMaterial':
"""
Load from yaml file.
Parameters
----------
fname : file, str, or pathlib.Path, optional
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Filename or file to read from. Defaults to 'material.yaml'.
Returns
-------
loaded : damask.ConfigMaterial
Material configuration from file.
"""
return super(ConfigMaterial,cls).load(fname)
@staticmethod
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def load_DREAM3D(fname: str,
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grain_data: Optional[str] = None,
cell_data: Optional[str] = None,
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cell_ensemble_data: str = 'CellEnsembleData',
phases: str = 'Phases',
Euler_angles: str = 'EulerAngles',
phase_names: str = 'PhaseName',
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base_group: Optional[str] = None) -> 'ConfigMaterial':
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"""
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Load DREAM.3D (HDF5) file.
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Data in DREAM.3D files can be stored per cell ('CellData')
and/or per grain ('Grain Data'). Per default, cell-wise data
is assumed.
damask.Grid.load_DREAM3D allows to get the corresponding geometry
for the grid solver.
Parameters
----------
fname : str
Filename of the DREAM.3D (HDF5) file.
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grain_data : str
Name of the group (folder) containing grain-wise data. Defaults
to None, in which case cell-wise data is used.
cell_data : str
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Name of the group (folder) containing cell-wise data. Defaults to
None in wich case it is automatically detected.
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cell_ensemble_data : str
Name of the group (folder) containing data of cell ensembles. This
group is used to inquire the name of the phases. Phases will get
numeric IDs if this group is not found. Defaults to 'CellEnsembleData'.
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phases : str
Name of the dataset containing the phase ID (cell-wise or grain-wise).
Defaults to 'Phases'.
Euler_angles : str
Name of the dataset containing the crystallographic orientation as
Euler angles in radians (cell-wise or grain-wise). Defaults to 'EulerAngles'.
phase_names : str
Name of the dataset containing the phase names. Phases will get
numeric IDs if this dataset is not found. Defaults to 'PhaseName'.
base_group : str
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Path to the group (folder) that contains geometry (_SIMPL_GEOMETRY),
and grain- or cell-wise data. Defaults to None, in which case
it is set as the path that contains _SIMPL_GEOMETRY/SPACING.
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Notes
-----
Homogenization and phase entries are emtpy and need to be defined separately.
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Returns
-------
loaded : damask.ConfigMaterial
Material configuration from file.
"""
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b = util.DREAM3D_base_group(fname) if base_group is None else base_group
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c = util.DREAM3D_cell_data_group(fname) if cell_data is None else cell_data
f = h5py.File(fname,'r')
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if grain_data is None:
phase = f['/'.join([b,c,phases])][()].flatten()
O = Rotation.from_Euler_angles(f['/'.join([b,c,Euler_angles])]).as_quaternion().reshape(-1,4) # noqa
_,idx = np.unique(np.hstack([O,phase.reshape(-1,1)]),return_index=True,axis=0)
idx = np.sort(idx)
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else:
phase = f['/'.join([b,grain_data,phases])][()]
O = Rotation.from_Euler_angles(f['/'.join([b,grain_data,Euler_angles])]).as_quaternion() # noqa
idx = np.arange(phase.size)
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if cell_ensemble_data is not None and phase_names is not None:
try:
names = np.array([s.decode() for s in f['/'.join([b,cell_ensemble_data,phase_names])]])
phase = names[phase]
except KeyError:
pass
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base_config = ConfigMaterial({'phase':{k if isinstance(k,int) else str(k): None for k in np.unique(phase)},
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'homogenization':{'direct':{'N_constituents':1}}})
constituent = {k:np.atleast_1d(v[idx].squeeze()) for k,v in zip(['O','phase'],[O,phase])}
return base_config.material_add(**constituent,homogenization='direct')
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@staticmethod
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def from_table(table: Table,
**kwargs) -> 'ConfigMaterial':
"""
Generate from an ASCII table.
Parameters
----------
table : damask.Table
Table that contains material information.
**kwargs
Keyword arguments where the key is the property name and
the value specifies either the label of the data column in the table
or a constant value.
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Returns
-------
new : damask.ConfigMaterial
Material configuration from values in table.
Examples
--------
>>> import damask
>>> import damask.ConfigMaterial as cm
>>> t = damask.Table.load('small.txt')
>>> t
3:pos pos pos 4:qu qu qu qu phase homog
0 0 0 0 0.19 0.8 0.24 -0.51 Aluminum SX
1 1 0 0 0.8 0.19 0.24 -0.51 Steel SX
2 1 1 0 0.8 0.19 0.24 -0.51 Steel SX
>>> cm.from_table(t,O='qu',phase='phase',homogenization='homog')
material:
- constituents:
- O: [0.19, 0.8, 0.24, -0.51]
v: 1.0
phase: Aluminum
homogenization: SX
- constituents:
- O: [0.8, 0.19, 0.24, -0.51]
v: 1.0
phase: Steel
homogenization: SX
homogenization: {SX: null}
phase: {Aluminum: null, Steel: null}
>>> cm.from_table(t,O='qu',phase='phase',homogenization='single_crystal')
material:
- constituents:
- O: [0.19, 0.8, 0.24, -0.51]
v: 1.0
phase: Aluminum
homogenization: single_crystal
- constituents:
- O: [0.8, 0.19, 0.24, -0.51]
v: 1.0
phase: Steel
homogenization: single_crystal
homogenization: {single_crystal: null}
phase: {Aluminum: null, Steel: null}
"""
kwargs_ = {k:table.get(v) if v in table.labels else np.atleast_2d([v]*len(table)).T for k,v in kwargs.items()}
_,idx = np.unique(np.hstack(list(kwargs_.values())),return_index=True,axis=0)
idx = np.sort(idx)
kwargs_ = {k:np.atleast_1d(v[idx].squeeze()) for k,v in kwargs_.items()}
for what in ['phase','homogenization']:
if what not in kwargs_: kwargs_[what] = what+'_label'
return ConfigMaterial().material_add(**kwargs_)
@property
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def is_complete(self) -> bool:
"""
Check for completeness.
Only the general file layout is considered.
This check does not consider whether specific parameters for
a particular phase/homogenization model are missing.
Returns
-------
complete : bool
Whether the material.yaml definition is complete.
"""
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def LabeledList(label,items):
return f'{label.capitalize()}{"s" if len(items)>1 else ""} {util.srepr(items,",",quote=True)}'
ok = True
msg = []
all = set(['homogenization','phase','material'])
miss = set([item for item in all if item not in self])
empty = set([item for item in all-miss if self[item] is None])
if miss:
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msg.append(f'{LabeledList("top-level",miss)} missing')
ok = False
if empty:
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msg.append(f'{LabeledList("top-level",empty)} empty')
if ok:
ok &= len(self['material']) > 0
if len(self['material']) < 1: msg.append('No materials defined')
homogenization = set()
phase = set()
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for i,v in enumerate(self['material']):
if 'homogenization' in v:
homogenization.add(v['homogenization'])
else:
msg.append(f'No homogenization specified for material {i}')
ok = False
if 'constituents' in v:
for ii,vv in enumerate(v['constituents']):
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if 'O' not in vv:
msg.append(f'No orientation specified for constituent {ii} of material {i}')
ok = False
if 'phase' in vv:
phase.add(vv['phase'])
else:
msg.append(f'No phase specified for constituent {ii} of material {i}')
ok = False
for v,other in {'phase':phase,
'homogenization':homogenization}.items():
me = set([] if v in empty else self[v])
if _miss := other - me:
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msg.append(f'{LabeledList(v,_miss)} missing')
ok = False
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if len(_empty := [item for item in me if self[v][item] is None]) > 0:
msg.append(f'{LabeledList(v,_empty)} undefined')
ok = False
print(util.srepr(msg))
return ok
@property
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def is_valid(self) -> bool:
"""
Check for valid content.
Only the generic file content is considered.
This check does not consider whether parameters for a
particular phase/homogenization mode are out of bounds.
Returns
-------
valid : bool
Whether the material.yaml definition is valid.
"""
ok = True
if 'phase' in self:
for k,v in self['phase'].items():
if v is not None and 'lattice' in v:
try:
Orientation(lattice=v['lattice'])
except KeyError:
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print(f"Invalid lattice '{v['lattice']}' in phase '{k}'")
ok = False
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if 'material' in self:
for i,m in enumerate(self['material']):
if 'constituents' in m:
v = 0.0
for c in m['constituents']:
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v += float(c['v'])
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if 'O' in c:
try:
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Rotation.from_quaternion(c['O'])
except ValueError:
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print(f"Invalid orientation '{c['O']}' in material '{i}'")
ok = False
if not np.isclose(v,1.0):
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print(f"Total fraction v = {v} ≠ 1 in material '{i}'")
ok = False
return ok
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def material_rename_phase(self,
mapping: Dict[str, str],
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ID: Optional[Sequence[int]] = None,
constituent: Optional[Sequence[int]] = None) -> 'ConfigMaterial':
"""
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Change phase name in material.
Parameters
----------
mapping: dictionary
Mapping from old name to new name
ID: list of ints, optional
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Limit renaming to selected material IDs.
constituent: list of ints, optional
Limit renaming to selected constituents.
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Returns
-------
updated : damask.ConfigMaterial
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Updated material configuration.
"""
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dup = self.copy()
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for i,m in enumerate(dup['material']):
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if ID is not None and i not in ID: continue
for c in m['constituents']:
if constituent is not None and c not in constituent: continue
try:
c['phase'] = mapping[c['phase']]
except KeyError:
continue
return dup
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def material_rename_homogenization(self,
mapping: Dict[str, str],
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ID: Optional[Sequence[int]] = None) -> 'ConfigMaterial':
"""
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Change homogenization name in material.
Parameters
----------
mapping: dictionary
Mapping from old name to new name
ID: list of ints, optional
Limit renaming to selected homogenization IDs.
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Returns
-------
updated : damask.ConfigMaterial
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Updated material configuration.
"""
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dup = self.copy()
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for i,m in enumerate(dup['material']):
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if ID is not None and i not in ID: continue
try:
m['homogenization'] = mapping[m['homogenization']]
except KeyError:
continue
return dup
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def material_add(self,
**kwargs: Any) -> 'ConfigMaterial':
"""
Add material entries.
Parameters
----------
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**kwargs
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Key-value pairs.
First index of array-like values runs over materials,
whereas second index runs over constituents.
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Returns
-------
updated : damask.ConfigMaterial
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Updated material configuration.
Examples
--------
Create two grains of ferrite and one grain of martensite, each with random orientation:
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>>> import damask
>>> m = damask.ConfigMaterial()
>>> m = m.material_add(phase = ['Ferrite','Martensite','Ferrite'],
... O = damask.Rotation.from_random(3),
... homogenization = 'SX')
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>>> m
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material:
- constituents:
- O: [0.577764, -0.146299, -0.617669, 0.513010]
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v: 1.0
phase: Ferrite
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homogenization: SX
- constituents:
- O: [0.184176, 0.340305, 0.737247, 0.553840]
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v: 1.0
phase: Martensite
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homogenization: SX
- constituents:
- O: [0.47925185, -0.04294454, 0.78760173, -0.3849116 ]
v: 1.0
phase: Ferrite
homogenization: SX
homogenization: {SX: null}
phase: {Ferrite: null, Martensite: null}
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Create hundred materials that each approximate a duplex stainless steel microstructure
with three austenite and one relatively bigger ferrite grain of random orientation each:
>>> import damask
>>> m = damask.ConfigMaterial()
>>> m = m.material_add(phase = np.array(['Austenite']*3+['Ferrite']),
... O = damask.Rotation.from_random((100,4)),
... v = np.array([0.2]*3+[0.4]),
... homogenization = 'Taylor')
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>>> m
material:
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- constituents:
- v: 0.2
phase: Austenite
O: [0.46183665006602664, 0.2215160420973196, -0.5594313187331139, 0.6516702781083836]
- v: 0.2
phase: Austenite
O: [0.11321658382410027, 0.6354079414360444, 0.00562701344273936, 0.7638108992590535]
- v: 0.2
phase: Austenite
O: [0.050991978809077604, 0.8069522034362003, -0.11352928955610851, -0.5773552285027659]
- v: 0.4
phase: Ferrite
O: [0.9460076150721788, 0.15880754622367604, -0.0069841062241482385, -0.28249066842661014]
homogenization: Taylor
.
.
.
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- constituents:
- v: 0.2
phase: Austenite
O: [0.12531400788494199, -0.18637769037997565, 0.31737548053338394, -0.9213210951197429]
- v: 0.2
phase: Austenite
O: [0.37453930577161404, -0.33529507696450805, -0.3266564259130028, -0.800370601162502]
- v: 0.2
phase: Austenite
O: [0.035776891752713764, -0.720706371010592, -0.4540438656728926, -0.5226342017569017]
- v: 0.4
phase: Ferrite
O: [0.6782596727966124, -0.20800082041703685, -0.138636083554039, 0.6909989227925536]
homogenization: Taylor
homogenization: {Taylor: null}
phase: {Austenite: null, Ferrite: null}
"""
_constituent_properties = ['phase','O','v','V_e']
_dim = {'O':(4,),'V_e':(3,3,)}
_ex = dict((k, -len(v)) for k, v in _dim.items())
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N,n = 1,1
shaped : Dict[str, Union[None,np.ndarray]] = \
{'v': None,
'phase': None,
'homogenization': None,
}
for k,v in kwargs.items():
shaped[k] = np.array(v)
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s = shaped[k].shape[:_ex.get(k,None)] # type: ignore
N = max(N,s[0]) if len(s)>0 else N
n = max(n,s[1]) if len(s)>1 else n
shaped['v'] = np.array(1./n) if shaped['v'] is None else shaped['v']
mat: Sequence[dict] = [{'constituents':[{} for _ in range(n)]} for _ in range(N)]
for k,v in shaped.items():
target = (N,n) + _dim.get(k,())
obj = np.broadcast_to(np.array(v).reshape(util.shapeshifter(() if v is None else v.shape,
target,
mode = 'right')),
target)
for i in range(N):
if k in _constituent_properties:
for j in range(n):
mat[i]['constituents'][j][k] = obj[i,j].item() if isinstance(obj[i,j],np.generic) else obj[i,j]
else:
mat[i][k] = obj[i,0].item() if isinstance(obj[i,0],np.generic) else obj[i,0]
dup = self.copy()
dup['material'] = dup['material'] + mat if 'material' in dup else mat
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for what in [item for item in ['phase','homogenization'] if shaped[item] is not None]:
for k in np.unique(shaped[what]): # type: ignore
if k not in dup[what]: dup[what][str(k)] = None
return dup