pytorch / botorch
Bayesian optimization in PyTorch
Summary
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| Main Code: 21,923 LOC (144 files) = PY (78%) + IPYNB (11%) + CSS (6%) + JS (3%) + YML (<1%) + CFG (<1%) + IN (<1%) + TOML (<1%) Secondary code: Test: 23,672 LOC (120); Generated: 0 LOC (0); Build & Deploy: 260 LOC (5); Other: 1,681 LOC (28); |
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| Duplication: 15% | |||
| File Size: 0% long (>1000 LOC), 35% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 67% short (<= 10 LOC) | |||
| Conditional Complexity: <1% complex (McCabe index > 50), 75% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (17 components) | ||
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3 years, 6 months old
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4% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
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Features of interest:
TODOs
45 files |
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Latest commit date: 2022-03-31
Reference analysis date: 2022-04-01
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35
commits
(30 days)
7
contributors
(30 days) |
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