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Octave currently skips structural zeros for most (all?) sparse matrix operations.  Matlab returns a sparse matrix filled with NaNs for something like "sprand (5, 5, 0.1) .^ NaN".  Should we go for full compatibility?  Mathematical correctness?  Traditional behavior of sparse matrix libraries?  It seems no one really agrees on what is correct or best.  Maybe compatibility should win?
 
Octave currently skips structural zeros for most (all?) sparse matrix operations.  Matlab returns a sparse matrix filled with NaNs for something like "sprand (5, 5, 0.1) .^ NaN".  Should we go for full compatibility?  Mathematical correctness?  Traditional behavior of sparse matrix libraries?  It seems no one really agrees on what is correct or best.  Maybe compatibility should win?
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==== etree for sparse logical ====
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Matlab's etree function appears to handle sparse logical arrays.
  
 
==== Indexed assignment ====
 
==== Indexed assignment ====
  
 
In an assignment like Sparse_object(idx) = GrB_object(idx), Octave does not attempt to apply a conversion operator to transform the RHS type to the LHS type.  Is this also a problem for assignments of objects with conversion operators to full matrix objects?
 
In an assignment like Sparse_object(idx) = GrB_object(idx), Octave does not attempt to apply a conversion operator to transform the RHS type to the LHS type.  Is this also a problem for assignments of objects with conversion operators to full matrix objects?
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==== 5th and 6th outputs for dmperm ====
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Octave doesn't support those.
  
 
==== graph and digraph ====
 
==== graph and digraph ====

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