Temporary Commit at 8/23/2024, 3:24:47 PM #2701
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This pull request was exported from Phabricator. Differential Revision: D61730570 |
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Summary: `MapData` has an attribute `df` that takes only the last row from each of `map_df`'s trial-arm-metric groups (when sorted by map_key values), and drops `map_key` columns. This diff makes it so that `map_key` columns are still present in the `df` attribute, showing their values for each kept row. This will make it easier to understand and model partially complete trials in the future. [RfC] I've patched up a few tests that assert these dataframes have a specific form, but there don't seem to be any tests failing for functional reasons (since the unused map_key columns would just go unused if not needed). Putting this up as an RfC though in case others feel strongly that these columns should be dropped. Differential Revision: D61730570
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This pull request was exported from Phabricator. Differential Revision: D61730570 |
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Summary: `MapData` has an attribute `df` that takes only the last row from each of `map_df`'s trial-arm-metric groups (when sorted by map_key values), and drops `map_key` columns. This diff makes it so that `map_key` columns are still present in the `df` attribute, showing their values for each kept row. This will make it easier to understand and model partially complete trials in the future. [RfC] I've patched up a few tests that assert these dataframes have a specific form, but there don't seem to be any tests failing for functional reasons (since the unused map_key columns would just go unused if not needed). Putting this up as an RfC though in case others feel strongly that these columns should be dropped. Reviewed By: Balandat Differential Revision: D61730570
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Summary: `MapData` has an attribute `df` that takes only the last row from each of `map_df`'s trial-arm-metric groups (when sorted by map_key values), and drops `map_key` columns. This diff makes it so that `map_key` columns are still present in the `df` attribute, showing their values for each kept row. This will make it easier to understand and model partially complete trials in the future. [RfC] I've patched up a few tests that assert these dataframes have a specific form, but there don't seem to be any tests failing for functional reasons (since the unused map_key columns would just go unused if not needed). Putting this up as an RfC though in case others feel strongly that these columns should be dropped. Reviewed By: Balandat Differential Revision: D61730570
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This pull request was exported from Phabricator. Differential Revision: D61730570 |
bernardbeckerman
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Aug 26, 2024
Summary: `MapData` has an attribute `df` that takes only the last row from each of `map_df`'s trial-arm-metric groups (when sorted by map_key values), and drops `map_key` columns. This diff makes it so that `map_key` columns are still present in the `df` attribute, showing their values for each kept row. This will make it easier to understand and model partially complete trials in the future. [RfC] I've patched up a few tests that assert these dataframes have a specific form, but there don't seem to be any tests failing for functional reasons (since the unused map_key columns would just go unused if not needed). Putting this up as an RfC though in case others feel strongly that these columns should be dropped. Reviewed By: Balandat Differential Revision: D61730570
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This pull request was exported from Phabricator. Differential Revision: D61730570 |
bernardbeckerman
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Summary: `MapData` has an attribute `df` that takes only the last row from each of `map_df`'s trial-arm-metric groups (when sorted by map_key values), and drops `map_key` columns. This diff makes it so that `map_key` columns are still present in the `df` attribute, showing their values for each kept row. This will make it easier to understand and model partially complete trials in the future. [RfC] I've patched up a few tests that assert these dataframes have a specific form, but there don't seem to be any tests failing for functional reasons (since the unused map_key columns would just go unused if not needed). Putting this up as an RfC though in case others feel strongly that these columns should be dropped. Reviewed By: Balandat Differential Revision: D61730570
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #2701 +/- ##
==========================================
+ Coverage 95.27% 95.28% +0.01%
==========================================
Files 493 493
Lines 47903 47903
==========================================
+ Hits 45641 45646 +5
+ Misses 2262 2257 -5 ☔ View full report in Codecov by Sentry. |
Summary: `MapData` has an attribute `df` that takes only the last row from each of `map_df`'s trial-arm-metric groups (when sorted by map_key values), and drops `map_key` columns. This diff makes it so that `map_key` columns are still present in the `df` attribute, showing their values for each kept row. This will make it easier to understand and model partially complete trials in the future. [RfC] I've patched up a few tests that assert these dataframes have a specific form, but there don't seem to be any tests failing for functional reasons (since the unused map_key columns would just go unused if not needed). Putting this up as an RfC though in case others feel strongly that these columns should be dropped. Reviewed By: Balandat Differential Revision: D61730570
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This pull request was exported from Phabricator. Differential Revision: D61730570 |
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Summary: `MapData` has an attribute `df` that takes only the last row from each of `map_df`'s trial-arm-metric groups (when sorted by map_key values), and drops `map_key` columns. This diff makes it so that `map_key` columns are still present in the `df` attribute, showing their values for each kept row. This will make it easier to understand and model partially complete trials in the future. [RfC] I've patched up a few tests that assert these dataframes have a specific form, but there don't seem to be any tests failing for functional reasons (since the unused map_key columns would just go unused if not needed). Putting this up as an RfC though in case others feel strongly that these columns should be dropped. Reviewed By: Balandat Differential Revision: D61730570 fbshipit-source-id: 0f09b357e0382b48a42b61d5c0f5a63206736196
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Differential Revision: D61730570