also not needed
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@ -19,8 +19,8 @@ def operator(stretch,strain,eigenvalues):
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'U#ln': np.log(eigenvalues) ,
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'U#ln': np.log(eigenvalues) ,
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'V#Biot': ( np.ones(3,'d') - 1.0/eigenvalues ) ,
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'V#Biot': ( np.ones(3,'d') - 1.0/eigenvalues ) ,
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'U#Biot': ( eigenvalues - np.ones(3,'d') ) ,
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'U#Biot': ( eigenvalues - np.ones(3,'d') ) ,
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'V#Green': ( np.ones(3,'d') - 1.0/eigenvalues/eigenvalues) *0.5,
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'V#Green': ( np.ones(3,'d') - 1.0/eigenvalues**2.0) *0.5,
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'U#Green': ( eigenvalues*eigenvalues - np.ones(3,'d')) *0.5,
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'U#Green': ( eigenvalues**2.0 - np.ones(3,'d')) *0.5,
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}[stretch+'#'+strain]
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}[stretch+'#'+strain]
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@ -141,7 +141,6 @@ for name in filenames:
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stretch['V'] = np.dot(F,R_inv) # F = VR
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stretch['V'] = np.dot(F,R_inv) # F = VR
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for theStretch in stretches:
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for theStretch in stretches:
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stretch[theStretch] = np.where(abs(stretch[theStretch]) < 1e-12, 0, stretch[theStretch]) # kill nasty noisy data
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(D,V) = np.linalg.eigh((stretch[theStretch]+stretch[theStretch].T)*0.5) # eigen decomposition (of symmetric(ed) matrix)
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(D,V) = np.linalg.eigh((stretch[theStretch]+stretch[theStretch].T)*0.5) # eigen decomposition (of symmetric(ed) matrix)
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for theStrain in strains:
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for theStrain in strains:
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d = operator(theStretch,theStrain,D) # operate on eigenvalues of U or V
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d = operator(theStretch,theStrain,D) # operate on eigenvalues of U or V
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