Implement DAA score timestamp estimation #268
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Basic implementation, just return the value back. Commit is focused on adding the API rather than functionality.
Input = array of daa_scores Output = array of timestamps, index matched with input
- acquire prune lock - use tighter indexing logic - ensure sink is included
- avoid assuming that timestamps are strictly monotonic
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michaelsutton
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Nov 23, 2023
michaelsutton
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their stale review
still missing one detail -- will add shortly
It's the same daa_score as checkpoint genesis, but timestamp is different to improve accuracy for queries right before and right after this daa_score
michaelsutton
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* Add GetDaaEstimateTimestamp RPC API Basic implementation, just return the value back. Commit is focused on adding the API rather than functionality. * Implement DAA score timestamp estimation Input = array of daa_scores Output = array of timestamps, index matched with input * Use info for daa TS estimate as opposed to println * Factor in BPS in the last header estimation * - use compact headers - acquire prune lock - use tighter indexing logic - ensure sink is included * eof new line * add todos * - bug fix: use f64, otherwise the fraction is always zero - avoid assuming that timestamps are strictly monotonic * renames * translate score -> miliisecs directly using target time per block * note * Add last data point from jupyter notebook It's the same daa_score as checkpoint genesis, but timestamp is different to improve accuracy for queries right before and right after this daa_score * use an array to avoid prealloc inaccuracies --------- Co-authored-by: Michael Sutton <[email protected]>
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Input = array of
daa_scoresOutput = array of
timestamps, where each index in output matches the index of DAA score in inputTimestamp estimation logic:
Starts with the pruning point headers as the base, then attempts to include additional headers from recent chain blocks to provide better timestamp estimates for recent days after the last pruning point.
Fixes #257