fix for logarithmic strain
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00168a5939
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865a505186
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@ -216,8 +216,6 @@ def strain_tensor(F,t,m):
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w,n = _np.linalg.eigh(C)
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w,n = _np.linalg.eigh(C)
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if m > 0.0:
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if m > 0.0:
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#eps = 1.0/(2.0*abs(m)) * (+ _np.matmul(n,_np.einsum('ij,ikj->ijk',w**m,n))
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# - _np.broadcast_to(_np.eye(3),[F_.shape[0],3,3]))
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eps = 1.0/(2.0*abs(m)) * (+ _np.matmul(n,_np.einsum('...j,...kj->...jk',w**m,n))
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eps = 1.0/(2.0*abs(m)) * (+ _np.matmul(n,_np.einsum('...j,...kj->...jk',w**m,n))
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- _np.einsum('...jk->...jk',_np.eye(3)))
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- _np.einsum('...jk->...jk',_np.eye(3)))
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@ -225,7 +223,7 @@ def strain_tensor(F,t,m):
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eps = 1.0/(2.0*abs(m)) * (- _np.matmul(n,_np.einsum('...j,...kj->...jk',w**m,n))
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eps = 1.0/(2.0*abs(m)) * (- _np.matmul(n,_np.einsum('...j,...kj->...jk',w**m,n))
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+ _np.einsum('...jk->...jk',_np.eye(3)))
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+ _np.einsum('...jk->...jk',_np.eye(3)))
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else:
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else:
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eps = _np.matmul(n,_np.einsum('...j,...kj->....jk',0.5*_np.log(w),n))
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eps = _np.matmul(n,_np.einsum('...j,...kj->...jk',0.5*_np.log(w),n))
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return eps.reshape(3,3) if _np.shape(F) == (3,3) else \
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return eps.reshape(3,3) if _np.shape(F) == (3,3) else \
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eps
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eps
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