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predict_trans_pot: reuse stored potentials without requiring fitted models - #61
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…odels The check for fitted models ran before the per-transition reuse check, so a run whose trans_pot_t was written directly (potentials from an external estimator, e.g. Dinamica's Weights of Evidence) could not be allocated by alloc_clumpy() or alloc_dinamica(). Only require models when something is left to predict. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01D1LLswXe3jLjGTFrBsxgPf
mmyrte
added this pull request to stack #67
October 6, 2026 09:43
mmyrte
commented
Oct 7, 2026
Collect the transitions left to predict up front and loop over those only; the "Found trans_pot_t" message per skipped transition is gone (a comment marks where verbose logging could bring it back). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01D1LLswXe3jLjGTFrBsxgPf
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Stack 3/6, on top of #60.
What
predict_trans_pot()checked for fitted models before it checked, per transition, whether potentials were already stored. A run whosetrans_pot_twas written directly could therefore not be allocated byalloc_clumpy()/alloc_dinamica(); for example, Dinamica's Weights-of-Evidence probabilities, or class suitabilities from lulcc or CLUinPy.Now the models are only required when something is left to predict (or with
force = TRUE). The PIE benchmark uses this to allocate other tools' surfaces with CLUMPY: the estimator × allocator crossings.Tests
test_integ_trans_models_t.R: once potentials exist, aselect_scorethat no model carries no longer errors; the stored potentials are reused. All 67 results pass.🤖 Generated with Claude Code
https://claude.ai/code/session_01D1LLswXe3jLjGTFrBsxgPf
Generated by Claude Code