Make every fitted ELF's fuel covariates for every pixel - #14
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With several fitted ELFs (sppEquivs, nonForestedLCCGroupsList, missingLCCgroupList from fireSense_dataPrepFit), spread and ignition covariates are built once per ELF with its own species table, non-forest groups and landcoverDT, and merged; the predict modules pick each ELF's columns. One ELF behaves as before. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CwcjqqK59FmTJscyi7xUqv
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For a study area with several fitted ELFs,
fireSense_SpreadPredict(#18 there) applies each ELF's model to its own pixels and to a blend zone around them. So every pixel needs every ELF's covariates. GivensppEquivs,nonForestedLCCGroupsListandmissingLCCgroupListfromfireSense_dataPrepFit(one element per ELF), this module now builds the spread and ignition covariates once per ELF, each with its own species table, non-forest groups andlandcoverDT. It merges them into one table (spread) or one raster stack (ignition). Column names say what they hold, so a column two ELFs share means the same thing.With one ELF nothing changes, and the existing tests pass unchanged. A new test uses two ELFs that group the same species differently: the merged covariates hold the union of columns, and each column equals a single-ELF run with that ELF's objects, for both spread and ignition. The three per-ELF inputs are declared. Version 1.0.4.9001.
Draft until the end-to-end 2-ELF forecast runs.
🤖 Generated with Claude Code
https://claude.ai/code/session_01CwcjqqK59FmTJscyi7xUqv