
From:  Nicholas Jankowski 
Subject:  Re: Order of matrix multiplication 
Date:  Mon, 12 Sep 2016 17:24:48 0400 
numpy/linalg/linalg.py is a great resource. It seems to me definitely worth trying to perform such optimizations. Even if we in the end preserve mtimes (lack of) parenthesization for some reason, having another function which would figure out an optimal parenthesization by solving the matrix chain ordering problem (assuming it doesn't already exists around these parts) would be a nice thing.On 09/12/2016 04:54 PM, Nicholas Jankowski wrote:
On Mon, Sep 12, 2016 at 2:59 PM, Yu Liu <address@hidden> wrote:
FYI, numpy has a special function np.linalg.multi_dot to do this.
https://github.com/numpy/numpy/blob/b91e8d8f164731bb710cc1e5 173cc8
ec3f8fadf5/numpy/linalg/linalg.py
Their code has very detailed explanation of the wellknown algorithm.
definitely looks like something that could be adapted. That said, I did
just recall that there is an existing bug waiting to have a patch tested
and committed for mtimes related to improperly flattening an ND array. So
if anyone starts looking to make changes it should take the current offered
patch into account: https://savannah.gnu.org/bugs/?47173
from that report it seems fixing mtimes was not the most trivial of tasks,
so 'tread with care'
I think it could definitely be a function of its own. See that the algorithm may introduce some noticeable overhead when determining how to best multiply the matrices while not giving anything back in return. Maybe mtimes docs should then point to this function saying that it does attempt to optimize parenthesization before multiplying the matrices. Also, if this was made into another function, the aforementioned ticked would not be an implementation blocking issue.
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