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Each prediction replicate uses one whole parameter set (new parameter .rep) - #24
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… rep) spreadProbOneELF() averaged one map per parameter set and yearSpreadSDOf() averaged yearSpreadSD, breaking the pairing of each set's yearSpreadSD with its coefficients. Replicate `rep` now uses row ((rep - 1) %% nSets) + 1 of each ELF, via paramSetForRep(). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CwcjqqK59FmTJscyi7xUqv
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CwcjqqK59FmTJscyi7xUqv
eliotmcintire
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spreadProbOneELF() (fireSense_spreadPredict.R:335, rowMeans over one map per parameter set) and yearSpreadSDOf() (mean of yearSpreadSD) averaged the fitted sets, so fireSense_burn applied an averaged sd to an averaged map and each set's yearSpreadSD was no longer paired with its own coefficients. Decision: parameter sets stay whole and separate. New parameter
rep(integer, default 1, min 1) selects row ((rep - 1) %% number of sets) + 1 of each ELF through the new paramSetForRep(), and fireSense_SpreadSD is that same row's yearSpreadSD; the project must passrep. Tests cover rows 1,2,3,1 for rep 1-4, the sd of the chosen row, and two ELFs with 3 and 2 sets each taking their own modulo; they fail on development and pass here (48 tests, 0 failures; development's own 46 pass). The module has no explicit Cache call, sorepreaches the event cache key as an ordinary module parameter.🤖 Generated with Claude Code
https://claude.ai/code/session_01CwcjqqK59FmTJscyi7xUqv