codecov[bot]
commented
5 years ago Codecov Report
Merging #15 into master will increase coverage by
5.12%. The diff coverage is37.09%.
@@ Coverage Diff @@
## master #15 +/- ##
=========================================
+ Coverage 53.07% 58.2% +5.12%
=========================================
Files 54 57 +3
Lines 4516 4883 +367
=========================================
+ Hits 2397 2842 +445
+ Misses 2119 2041 -78| Flag | Coverage Δ | |
|---|---|---|
| #aprl | 10.87% <0%> (-0.89%) |
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| #modelfree | 51.21% <37.09%> (+5.69%) |
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| Impacted Files | Coverage Δ | |
|---|---|---|
| src/modelfree/visualize/styles.py | 100% <ø> (+100%) |
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| src/modelfree/multi/common.py | 71.13% <ø> (ø) |
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| src/modelfree/policies/transparent.py | 75% <ø> (ø) |
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| src/modelfree/density/visualize.py | 0% <0%> (ø) |
|
| src/modelfree/visualize/util.py | 0% <0%> (ø) |
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| src/modelfree/visualize/training.py | 0% <0%> (ø) |
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| src/modelfree/tsne/pipeline.py | 90.24% <100%> (+90.24%) |
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| src/modelfree/configs/multi/score.py | 44.06% <100%> (+22.3%) |
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| src/modelfree/density/fit_density.py | 44.88% <44.88%> (ø) |
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| src/modelfree/tsne/visualize.py | 87.09% <69.23%> (+87.09%) |
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| ... and 17 more |
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AdamGleave
Adds a pipeline to generate activations of a victim policy network across a range of opponents, fit a Gaussian Mixture Model and plot a bar chart and other visualizations of the mean log likelihood of the activations. Adds test cases for this & the t-SNE pipeline. Some other minor tweaks to t-SNE plotting.
As usual, anything affecting training or scoring should be scrutinized closely. Density model fitting I expect us to use a fair bit so should be looked at reasonably closely, but it'll only be as an interactive tool where errors should be obvious so not as important. Plotting code lowest standards.