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safe-eliminations's Introduction

Identifying numerically safe eliminations automatically

The background is discussed in 2. Identifying feasible assignments of

Ordering matrices to bordered lower triangular form with minimal border width.

The code here is derived from:

https://github.com/baharev/sdopt-tearing/blob/master/sympy_tree.py

However, sympy_tree.py is concerned with binary expression trees coming from Modelica and generating output for AMPL. The solvable.py is only concerned with expression trees coming from, and going to SymPy.
The caveats mentioned in the last two paragraphs of 2.2. Identifying numerically troublesome assignments in Ordering matrices to bordered lower triangular form with minimal border width do apply!

Of course, the long-term goal is to merge the code back into sdopt-tearing.

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safe-eliminations's Issues

Value errors when checking validity of matrix

The following error is encountered when running

  • rpc_api.fine_dulmage_mendelsohn
  • heap_md.hessenberg
  • bordered.to_bordered_form

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

The errors originate from the following lines:
dm_decomp.py line 148
order_util.py line 104 + 105

Trying to understand the use cases

@EDWhyte There is an important piece that the original sympy_tree.py in sdopt-tearing does but solvable.py doesn't: In sympy_tree.py all the possible safe eliminations are stored in a dictionary (unfortunately as string). I am almost sure that you will need the eliminations too.

Please clarify your use case, and suggest a solution. The simplest is to do it as in sympy_tree.py but store the SymPy expression trees for all possible eliminations that were flagged as safe.

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