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FBA gives incorrect objective_value 0 for bigg models iMM1415 & iRC1080 #1

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matthiaskoenig opened this issue May 17, 2018 · 7 comments · Fixed by #54
Closed

FBA gives incorrect objective_value 0 for bigg models iMM1415 & iRC1080 #1

matthiaskoenig opened this issue May 17, 2018 · 7 comments · Fixed by #54

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@matthiaskoenig
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When comparing the results of simple FBA simulations of cobrapy with SBSCL the following two BiGG models give different results:

objective_value_cobrapy 	mid 	objective_value_sbscl 	identical
1.3634279056507832 	iMM1415 	0.0 	False
6.156851475936173 	iRC1080 	0.0 	False
@hemilpanchiwala
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@matthiaskoenig, These models now provide correct results in SBSCL. I have updated the changes in PR #54. So, should I link this issue to the PR so that it can be closed once PR gets merged?

Commits Link: c40ef21
9b92496

@hemilpanchiwala
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OPTIMAL LP SOLUTION FOUND
iMM1415.xml
Objective value: 1.3634279056663554

OPTIMAL LP SOLUTION FOUND
iRC1080.xml
Objective value: 6.156851475933738

@matthiaskoenig
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matthiaskoenig commented Aug 7, 2020 via email

@hemilpanchiwala hemilpanchiwala linked a pull request Aug 7, 2020 that will close this issue
@draeger
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draeger commented Aug 8, 2020

OPTIMAL LP SOLUTION FOUND
iMM1415.xml
Objective value: 1.3634279056663554

OPTIMAL LP SOLUTION FOUND
iRC1080.xml
Objective value: 6.156851475933738

@hemilpanchiwala: It would be helpful to also state which software found which value and how large the divergence was. Which solver was used?

@hemilpanchiwala
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@draeger,

OPTIMAL LP SOLUTION FOUND
iMM1415.xml
Objective value: 1.3634279056663554

OPTIMAL LP SOLUTION FOUND
iRC1080.xml
Objective value: 6.156851475933738

These are the results provided by SBSCL.

While the results by cobrapy are

iMM1415.xml -> 1.363427906
iRC1080.xml -> 6.156851476

Deviations (sbscl_results - cobrapy_results):

iMM1415.xml -> -3.3364467e-10
iRC1080.xml -> -6.6261663e-11

@hemilpanchiwala
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I used the FluxBalanceAnalysis class to solve the model.

@draeger
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draeger commented Aug 8, 2020

The divergence is only only the order of or even . This is already getting close to machine precision for some circumstances.

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3 participants