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fireSense_spreadFit: convergence parameter, in the fit's cache key - #79
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…to runDEoptim inside the fit's Cache() Floors fireSenseUtils 0.2.3.9102, clusters 0.0.80. Depends-on: PredictiveEcology/fireSenseUtils#162, PredictiveEcology/clusters#55 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014G18Mik3fH4z5M5CyMSUS6
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…runDEoptim convergence, #162) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014G18Mik3fH4z5M5CyMSUS6
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Fits sometimes stop while still improving. The stopping rule is now a fit setting that the fit's cache sees, so a stopped fit can be continued with a stricter rule instead of being returned as is or started over.
Affects: every fit cached before this re-keys once (the rule is now in the key); after that, changing the rule or the
clusters.deoptim*options re-runs the fit from its cached generations.Depends-on: PredictiveEcology/fireSenseUtils#162
Depends-on: PredictiveEcology/clusters#55
Technical details
fitSpread()(R/fitSpread.R) gaverunDEoptim()no early-stop settings, so the rule lived only in clusters' options, outside the fit'sCache()key, and a finished fit was returned from cache whatever the rule. New parameterconvergence(list, defaultNULL) is resolved once withclusters::deoptimConvergence()(parameter, else options, else clusters defaults) and the full list is passed asconvergence =inside the existingCache()call; clusters keeps it out of the per-generation keys, so a rerun resumes. Floors: fireSenseUtils 0.2.3.9102, clusters 0.0.80. Newtest-convergence.R(the args a mockedrunDEoptimsees: default, parameter, options; fails on development) and the metadata tests list the parameter. Full module tests withconvertToPackage()+test_local(): 0 failures on the branch; on development, only the new test fails.🤖 Generated with Claude Code
https://claude.ai/code/session_014G18Mik3fH4z5M5CyMSUS6