itsdfish / SequentialSamplingModels.jl

A unified interface for simulating and evaluating sequential sampling models in Julia.
https://itsdfish.github.io/SequentialSamplingModels.jl/dev/
MIT License
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CompatHelper: bump compat for FunctionZeros to 1, (keep existing compat) #56

Closed github-actions[bot] closed 9 months ago

github-actions[bot] commented 9 months ago

This pull request changes the compat entry for the FunctionZeros package from 0.2.0,0.3.0 to 0.2.0,0.3.0, 1. This keeps the compat entries for earlier versions.

Note: I have not tested your package with this new compat entry. It is your responsibility to make sure that your package tests pass before you merge this pull request.

github-actions[bot] commented 9 months ago

Benchmark Results

master 40e70bcd50f155... t[master]/t[40e70bcd50f155...]
logpdf/("SequentialSamplingModels.DDM", 10) 1.81 ± 0.21 μs 1.66 ± 0.11 μs 1.09
logpdf/("SequentialSamplingModels.DDM", 100) 17.3 ± 0.99 μs 17.2 ± 0.99 μs 1
logpdf/("SequentialSamplingModels.LBA", 10) 2.46 ± 0.19 μs 2.44 ± 0.18 μs 1.01
logpdf/("SequentialSamplingModels.LBA", 100) 23.4 ± 0.61 μs 23.4 ± 0.65 μs 1
logpdf/("SequentialSamplingModels.LNR", 10) 1.01 ± 0.15 μs 0.999 ± 0.15 μs 1.01
logpdf/("SequentialSamplingModels.LNR", 100) 8.56 ± 0.28 μs 8.59 ± 0.29 μs 0.996
logpdf/("SequentialSamplingModels.RDM", 10) 2.63 ± 0.23 μs 2.63 ± 0.25 μs 0.999
logpdf/("SequentialSamplingModels.RDM", 100) 24.8 ± 0.68 μs 24.8 ± 0.69 μs 1
logpdf/("SequentialSamplingModels.Wald", 10) 0.229 ± 0.16 μs 0.229 ± 0.17 μs 0.996
logpdf/("SequentialSamplingModels.Wald", 100) 2.01 ± 0.17 μs 2.02 ± 0.18 μs 0.994
logpdf/("SequentialSamplingModels.WaldMixture", 10) 1.08 ± 0.16 μs 1.08 ± 0.16 μs 0.993
logpdf/("SequentialSamplingModels.WaldMixture", 100) 10.5 ± 0.17 μs 10.6 ± 0.16 μs 0.992
rand/("SequentialSamplingModels.DDM", 10) 3.95 ± 0.55 μs 3.91 ± 0.56 μs 1.01
rand/("SequentialSamplingModels.DDM", 100) 0.0384 ± 0.002 ms 0.0385 ± 0.002 ms 0.997
rand/("SequentialSamplingModels.LBA", 10) 3.24 ± 0.36 μs 3.19 ± 0.35 μs 1.01
rand/("SequentialSamplingModels.LBA", 100) 16.5 ± 0.74 μs 16.3 ± 0.39 μs 1.01
rand/("SequentialSamplingModels.LCA", 10) 0.78 ± 0.29 ms 0.767 ± 0.27 ms 1.02
rand/("SequentialSamplingModels.LCA", 100) 8.56 ± 0.37 ms 8.3 ± 0.26 ms 1.03
rand/("SequentialSamplingModels.LNR", 10) 1.09 ± 0.33 μs 1.09 ± 0.38 μs 1
rand/("SequentialSamplingModels.LNR", 100) 7.56 ± 3.8 μs 7.54 ± 3.7 μs 1
rand/("SequentialSamplingModels.RDM", 10) 1.35 ± 0.22 μs 1.35 ± 0.25 μs 0.999
rand/("SequentialSamplingModels.RDM", 100) 11.1 ± 3.7 μs 11.1 ± 3.7 μs 0.999
rand/("SequentialSamplingModels.Wald", 10) 0.459 ± 0.16 μs 0.459 ± 0.16 μs 1
rand/("SequentialSamplingModels.Wald", 100) 2.87 ± 0.2 μs 2.89 ± 0.2 μs 0.994
rand/("SequentialSamplingModels.WaldMixture", 10) 1.19 ± 0.15 μs 1.19 ± 0.15 μs 1
rand/("SequentialSamplingModels.WaldMixture", 100) 11.4 ± 0.2 μs 11.4 ± 0.18 μs 0.998
simulate/SequentialSamplingModels.DDM 3.77 ± 1.5 μs 3.71 ± 1.5 μs 1.01
simulate/SequentialSamplingModels.LBA 3.75 ± 0.41 μs 2.2 ± 0.081 μs 1.7
simulate/SequentialSamplingModels.LCA 0.105 ± 0.023 ms 0.103 ± 0.027 ms 1.01
simulate/SequentialSamplingModels.RDM 0.0697 ± 0.029 ms 0.0682 ± 0.029 ms 1.02
simulate/SequentialSamplingModels.Wald 9.29 ± 5.2 μs 9.12 ± 4.5 μs 1.02
simulate/SequentialSamplingModels.WaldMixture 4.07 ± 1.5 μs 4.16 ± 1.6 μs 0.98
time_to_load 3.88 ± 0.063 s 3.88 ± 0.058 s 1

Benchmark Plots

A plot of the benchmark results have been uploaded as an artifact to the workflow run for this PR. Go to "Actions"->"Benchmark a pull request"->[the most recent run]->"Artifacts" (at the bottom).