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fixed problem with nested data in pyscf hdf5 3idx ints (needs testing for nk>1)
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@ -440,9 +440,10 @@ def get_j3ao_new(fname,nao,Nk):
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# in new(?) version of PySCF, there is an extra layer of groups before the datasets
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# datasets used to be [/j3c/0, /j3c/1, /j3c/2, ...]
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# datasets now are [/j3c/0/0, /j3c/1/0, /j3c/2/0, ...]
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keysub = '/0' if bool(j3c.get('0/0',getclass=True)) else ''
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#keysub = '/0' if bool(j3c.get('0/0',getclass=True)) else ''
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naux = max(map(lambda k: j3c[k+keysub].shape[0],j3c.keys()))
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#naux = max(map(lambda k: j3c[k+keysub].shape[0],j3c.keys()))
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naux = max(map(lambda k: j3c[k]['0'].shape[0],j3c.keys()))
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naosq = nao*nao
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naotri = (nao*(nao+1))//2
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@ -451,11 +452,12 @@ def get_j3ao_new(fname,nao,Nk):
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j3arr = np.zeros((nkpairs,naux,nao,nao),dtype=np.complex128)
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for i,kpair in enumerate(j3ckeys):
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iaux,dim2 = j3c[kpair+keysub].shape
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tmpdat = np.concatenate([j3c[kpair][ii][()] for ii in j3c[kpair]],axis=1)
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iaux,dim2 = tmpdat.shape
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if (dim2==naosq):
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j3arr[i,:iaux,:,:] = j3c[kpair+keysub][()].reshape([iaux,nao,nao]).transpose((0,2,1)) * nkinvsq
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j3arr[i,:iaux,:,:] = tmpdat.reshape([iaux,nao,nao]).transpose((0,2,1)) * nkinvsq
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else:
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j3arr[i,:iaux,:,:] = makesq3(j3c[kpair+keysub][()].conj(),nao) * nkinvsq
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j3arr[i,:iaux,:,:] = makesq3(tmpdat.conj(),nao) * nkinvsq
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return j3arr
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