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stretch is symmetric (play it safe here)

This commit is contained in:
Martin Diehl 2019-09-13 06:34:48 -07:00
parent 79d2432c6c
commit 66d8a3e601
1 changed files with 3 additions and 3 deletions
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6
processing/post/addStrainTensors.py
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@ -142,17 +142,17 @@ for name in filenames:
for theStretch in stretches:
stretch[theStretch] = np.where(abs(stretch[theStretch]) < 1e-12, 0, stretch[theStretch]) # kill nasty noisy data
(D,V) = np.linalg.eig(stretch[theStretch]) # eigen decomposition (of symmetric matrix)
(D,V) = np.linalg.eigh((stretch[theStretch]+stretch[theStretch].T)*0.5) # eigen decomposition (of symmetric(ed) matrix)
neg = np.where(D < 0.0) # find negative eigenvalues ...
D[neg] *= -1. # ... flip value ...
V[:,neg] *= -1. # ... and vector
for i,eigval in enumerate(D):
if np.dot(V[:,i],V[:,(i+1)%3]) != 0.0: # check each vector for orthogonality
V[:,(i+1)%3] = np.cross(V[:,(i+2)%3],V[:,i]) # correct next vector
V[:,(i+1)%3] /= np.sqrt(np.dot(V[:,(i+1)%3],V[:,(i+1)%3].conj())) # and renormalize (hyperphobic?)
V[:,(i+1)%3] /= np.sqrt(np.dot(V[:,(i+1)%3],V[:,(i+1)%3])) # and renormalize (hyperphobic?)
for theStrain in strains:
d = operator(theStretch,theStrain,D) # operate on eigenvalues of U or V
eps = (np.dot(V,np.dot(np.diag(d),V.T)).real).reshape(9) # build tensor back from eigenvalue/vector basis
eps = np.dot(V,np.dot(np.diag(d),V.T)).reshape(9) # build tensor back from eigenvalue/vector basis
table.data_append(list(eps))