proper dealing with default/mandatory items in material_add
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Philip Eisenlohr
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@ -424,6 +424,8 @@ class ConfigMaterial(Config):
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----------
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**kwargs
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Key-value pairs.
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First index of array-like values runs over materials,
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whereas second index runs over constituents.
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Returns
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-------
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@ -432,12 +434,12 @@ class ConfigMaterial(Config):
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Examples
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--------
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Create a dual-phase steel microstructure for micromechanical simulations:
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Create two grains of ferrite and one grain of martensite, each with random orientation:
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>>> import damask
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>>> m = damask.ConfigMaterial()
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>>> m = m.material_add(phase = ['Ferrite','Martensite'],
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... O = damask.Rotation.from_random(2),
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>>> m = m.material_add(phase = ['Ferrite','Martensite','Ferrite'],
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... O = damask.Rotation.from_random(3),
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... homogenization = 'SX')
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>>> m
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material:
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@ -451,59 +453,89 @@ class ConfigMaterial(Config):
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v: 1.0
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phase: Martensite
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homogenization: SX
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- constituents:
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- O: [0.47925185, -0.04294454, 0.78760173, -0.3849116 ]
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v: 1.0
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phase: Ferrite
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homogenization: SX
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homogenization: {SX: null}
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phase: {Ferrite: null, Martensite: null}
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Create a duplex stainless steel microstructure for forming simulations:
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Create hundred materials that each approximate a duplex stainless steel microstructure
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with three austenite and one relatively bigger ferrite grain of random orientation each:
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>>> import damask
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>>> m = damask.ConfigMaterial()
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>>> m = m.material_add(phase = np.array(['Austenite','Ferrite']).reshape(1,2),
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... O = damask.Rotation.from_random((2,2)),
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... v = np.array([0.2,0.8]).reshape(1,2),
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>>> m = m.material_add(phase = np.array(['Austenite']*3+['Ferrite']),
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... O = damask.Rotation.from_random((100,4)),
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... v = np.array([0.2]*3+[0.4]),
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... homogenization = 'Taylor')
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>>> m
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material:
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- constituents:
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- phase: Austenite
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O: [0.659802978293224, 0.6953785848195171, 0.22426295326327111, -0.17554139512785227]
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v: 0.2
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- phase: Ferrite
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O: [0.49356745891301596, 0.2841806579193434, -0.7487679215072818, -0.339085707289975]
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v: 0.8
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- v: 0.2
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phase: Austenite
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O: [0.46183665006602664, 0.2215160420973196, -0.5594313187331139, 0.6516702781083836]
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- v: 0.2
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phase: Austenite
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O: [0.11321658382410027, 0.6354079414360444, 0.00562701344273936, 0.7638108992590535]
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- v: 0.2
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phase: Austenite
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O: [0.050991978809077604, 0.8069522034362003, -0.11352928955610851, -0.5773552285027659]
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- v: 0.4
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phase: Ferrite
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O: [0.9460076150721788, 0.15880754622367604, -0.0069841062241482385, -0.28249066842661014]
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homogenization: Taylor
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.
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.
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.
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- constituents:
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- phase: Austenite
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O: [0.26542221365204055, 0.7268854930702071, 0.4474726435701472, -0.44828201137283735]
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v: 0.2
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- phase: Ferrite
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O: [0.6545817158479885, -0.08004812803625233, -0.6226561293931374, 0.4212059104577611]
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v: 0.8
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- v: 0.2
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phase: Austenite
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O: [0.12531400788494199, -0.18637769037997565, 0.31737548053338394, -0.9213210951197429]
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- v: 0.2
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phase: Austenite
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O: [0.37453930577161404, -0.33529507696450805, -0.3266564259130028, -0.800370601162502]
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- v: 0.2
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phase: Austenite
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O: [0.035776891752713764, -0.720706371010592, -0.4540438656728926, -0.5226342017569017]
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- v: 0.4
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phase: Ferrite
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O: [0.6782596727966124, -0.20800082041703685, -0.138636083554039, 0.6909989227925536]
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homogenization: Taylor
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homogenization: {Taylor: null}
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phase: {Austenite: null, Ferrite: null}
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"""
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N,n,shaped = 1,1,{}
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_constituent_properties = ['phase','O','v','V_e']
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_dim = {'O':(4,),'V_e':(3,3,)}
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_ex = dict((k, -len(v)) for k, v in _dim.items())
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N,n,shaped = 1,1,{'v': None,
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'phase': None,
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'homogenization': None,
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}
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map_dim = {'O':-1,'V_e':-2}
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for k,v in kwargs.items():
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shaped[k] = np.array(v)
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s = shaped[k].shape[:map_dim.get(k,None)]
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s = shaped[k].shape[:_ex.get(k,None)]
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N = max(N,s[0]) if len(s)>0 else N
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n = max(n,s[1]) if len(s)>1 else n
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shaped['v'] = np.array(1./n) if shaped['v'] is None else shaped['v']
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mat: Sequence[dict] = [{'constituents':[{} for _ in range(n)]} for _ in range(N)]
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if 'v' not in kwargs:
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shaped['v'] = np.broadcast_to(1/n,(N,n))
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map_shape = {'O':(N,n,4),'V_e':(N,n,3,3)}
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for k,v in shaped.items():
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target = map_shape.get(k,(N,n))
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obj = np.broadcast_to(v.reshape(util.shapeshifter(v.shape, target, mode = 'right')), target)
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target = (N,n) + _dim.get(k,())
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obj = np.broadcast_to(np.array(v).reshape(util.shapeshifter(() if v is None else v.shape,
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target,
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mode = 'right')),
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target)
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for i in range(N):
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if k in ['phase','O','v','V_e']:
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if k in _constituent_properties:
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for j in range(n):
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mat[i]['constituents'][j][k] = obj[i,j].item() if isinstance(obj[i,j],np.generic) else obj[i,j]
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else:
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@ -514,6 +546,6 @@ class ConfigMaterial(Config):
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for what in ['phase','homogenization']:
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for k in np.unique(shaped[what]):
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if k not in dup[what]: dup[what][str(k)] = None
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if not (k is None or k in dup[what]): dup[what][str(k)] = None
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return dup
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