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phase and homogenization dict to be updated when new material added

This commit is contained in:
Sharan Roongta 2022-11-09 22:58:51 +01:00
parent 8d59750b93
commit 443d796643
2 changed files with 19 additions and 10 deletions
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22
python/damask/_configmaterial.py
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@ -209,8 +209,8 @@ class ConfigMaterial(Config):
v: 1.0 v: 1.0
phase: Steel phase: Steel
homogenization: SX homogenization: SX
homogenization: {} homogenization: {SX: {t.b.d}}
phase: {} phase: {Aluminum: {t.b.d}, Steel: {t.b.d}}
>>> cm.from_table(t,O='qu',phase='phase',homogenization='single_crystal') >>> cm.from_table(t,O='qu',phase='phase',homogenization='single_crystal')
material: material:
@ -224,8 +224,8 @@ class ConfigMaterial(Config):
v: 1.0 v: 1.0
phase: Steel phase: Steel
homogenization: single_crystal homogenization: single_crystal
homogenization: {} homogenization: {single_crystal: {t.b.d}}
phase: {} phase: {Aluminum: {t.b.d}, Steel: {t.b.d}}
""" """
kwargs_ = {k:table.get(v) if v in table.labels else np.atleast_2d([v]*len(table)).T for k,v in kwargs.items()} kwargs_ = {k:table.get(v) if v in table.labels else np.atleast_2d([v]*len(table)).T for k,v in kwargs.items()}
@ -428,7 +428,6 @@ class ConfigMaterial(Config):
-------- --------
Create a dual-phase steel microstructure for micromechanical simulations: Create a dual-phase steel microstructure for micromechanical simulations:
>>> import numpy as np
>>> import damask >>> import damask
>>> m = damask.ConfigMaterial() >>> m = damask.ConfigMaterial()
>>> m = m.material_add(phase = ['Ferrite','Martensite'], >>> m = m.material_add(phase = ['Ferrite','Martensite'],
@ -446,12 +445,11 @@ class ConfigMaterial(Config):
v: 1.0 v: 1.0
phase: Martensite phase: Martensite
homogenization: SX homogenization: SX
homogenization: {} homogenization: {SX: {t.b.d}}
phase: {} phase: {Ferrite: {t.b.d}, Martensite: {t.b.d}}
Create a duplex stainless steel microstructure for forming simulations: Create a duplex stainless steel microstructure for forming simulations:
>>> import numpy as np
>>> import damask >>> import damask
>>> m = damask.ConfigMaterial() >>> m = damask.ConfigMaterial()
>>> m = m.material_add(phase = np.array(['Austenite','Ferrite']).reshape(1,2), >>> m = m.material_add(phase = np.array(['Austenite','Ferrite']).reshape(1,2),
@ -476,8 +474,8 @@ class ConfigMaterial(Config):
O: [0.6545817158479885, -0.08004812803625233, -0.6226561293931374, 0.4212059104577611] O: [0.6545817158479885, -0.08004812803625233, -0.6226561293931374, 0.4212059104577611]
v: 0.8 v: 0.8
homogenization: Taylor homogenization: Taylor
homogenization: {} homogenization: {Taylor: {t.b.d}}
phase: {} phase: {Austenite: {t.b.d}, Ferrite: {t.b.d}}
""" """
N,n,shaped = 1,1,{} N,n,shaped = 1,1,{}
@ -507,5 +505,9 @@ class ConfigMaterial(Config):
dup = self.copy() dup = self.copy()
dup['material'] = dup['material'] + mat if 'material' in dup else mat dup['material'] = dup['material'] + mat if 'material' in dup else mat
for k in np.unique(shaped['phase']):
if k not in dup['phase']: dup['phase'][str(k)] = {'t.b.d'}
for k in np.unique(shaped['homogenization']):
if k not in dup['homogenization']: dup['homogenization'][str(k)] = {'t.b.d'}
return dup return dup

7
python/tests/test_ConfigMaterial.py
View File

@ -98,6 +98,13 @@ class TestConfigMaterial:
for i,m in enumerate(c['material']): for i,m in enumerate(c['material']):
assert m['homogenization'] == 1 and (m['constituents'][0]['O'] == [1,0,1,1]).all() assert m['homogenization'] == 1 and (m['constituents'][0]['O'] == [1,0,1,1]).all()
def test_updated_dicts(self,ref_path):
m1 = ConfigMaterial().material_add(phase=['Aluminum'],O=[1.0,0.0,0.0,0.0],homogenization='SX')
m2 = ConfigMaterial.load(ref_path/'material.yaml').material_add(phase=['Aluminum'],O=[1.0,0.0,0.0,0.0],homogenization='SX')
assert m1['phase'] == {'Aluminum': {'t.b.d'}}
assert m1['homogenization'] == {'SX': {'t.b.d'}}
assert not m2['phase']['Aluminum'] == {}
def test_from_table_with_constant(self): def test_from_table_with_constant(self):
N = np.random.randint(3,10) N = np.random.randint(3,10)
a = np.vstack((np.hstack((np.arange(N),np.arange(N)[::-1])), a = np.vstack((np.hstack((np.arange(N),np.arange(N)[::-1])),