facebookresearch / neural_stpp
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.
Summary
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| Main Code: 3,518 LOC (34 files) = PY (97%) + PYX (2%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 124 LOC (3); |
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| Duplication: 8% | |||
| File Size: 0% long (>1000 LOC), 62% short (<= 200 LOC) | |||
| Unit Size: 8% long (>100 LOC), 62% short (<= 10 LOC) | |||
| Conditional Complexity: 8% complex (McCabe index > 50), 67% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (7 components) | ||
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10 months old
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0% 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) | |||
Latest commit date: 2021-12-28
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2
commits
(30 days)
1
contributors
(30 days) |
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