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Sampling size parameters are not very intuitive #657

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stelmo opened this issue Aug 29, 2022 · 1 comment
Closed

Sampling size parameters are not very intuitive #657

stelmo opened this issue Aug 29, 2022 · 1 comment
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documentation Improvements or additions to documentation quality improves maintainability and code clarity
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@stelmo
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stelmo commented Aug 29, 2022

Why does the sampling procedure generate as many samples as one inputs warmup points? Shouldn't it return as many samples as requested in sample_iters? See below for a MWE:

using COBREXA, Gurobi

model = load_model(StandardModel, joinpath("data", "models", "e_coli_core.json"))

warmup_points = warmup_from_variability(
    model, 
    Gurobi.Optimizer,
    10,
    modifications = [silence]
)

samples = affine_hit_and_run(
    model,
    warmup_points,
    sample_iters = 1:1:5
)

I expect 5 samples here, but I get 5 * 10 = 50. Is this expected behaviour?

@stelmo stelmo added the bug Something isn't working label Aug 29, 2022
@exaexa exaexa removed the bug Something isn't working label Aug 30, 2022
@exaexa exaexa changed the title Possible bug in sampling Sampling size parameters are not very intuitive Sep 1, 2022
@exaexa exaexa added documentation Improvements or additions to documentation quality improves maintainability and code clarity labels Sep 1, 2022
@exaexa exaexa added this to the v1.5 milestone Sep 2, 2022
@stelmo stelmo linked a pull request Sep 3, 2022 that will close this issue
@exaexa
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exaexa commented May 14, 2024

solved in cobrexa 2

@exaexa exaexa closed this as completed May 14, 2024
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