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…se variable from autoplot.epi_df
… quantile_pred by hardhat or parsnip
Co-authored-by: brookslogan <lcbrooks@cs.cmu.edu>
Fix error where autoplot called nonexistent .response column
print.canned_epipred() was supposed to surface latency-adjustment information for canned forecasters whose recipe contains a step_adjust_latency. The gating conditional checked for a top-level "pre" field on the canned forecaster, but canned forecasters' top-level fields are predictions, epi_workflow, and metadata. The check always evaluated FALSE, leaving the latency-info block as dead code. Replace the predicate with !is.null(x$epi_workflow$pre$actions$recipe), which correctly tests for a recipe preprocessor on the embedded workflow. The existing snapshot tests for arx_forecaster with extend_lags and extend_ahead regenerate to include the previously-missing "Lags adjusted" / "Aheads adjusted" lines. Two supplementary expect_match assertions are added as defensive guards. Also adds .workflow/, .plans/, .claude/ to both .gitignore and .Rbuildignore for personal agent-tooling directories. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
fix: display latency adjustment info on canned forecasters (#447)
…454) flatline_forecaster() was returning K+1 duplicate prediction rows per geo when the input epi_df had K trailing rows with NA in the outcome column. The duplication came from R/get_test_data.R's filter max_time_value - time_value <= keep being one-sided: when na.omit() set max_time_value earlier than the actual max (because trailing rows had NA in the outcome), rows with time_value > max_time_value slipped through and produced duplicate predictions downstream. Add time_value <= max_time_value to both filter calls in get_test_data. The new bound is a no-op when there are no trailing NAs, so the existing test-snapshots.R flatline snapshots and test-get_test_data.R assertions all pass unchanged. The deeper na.omit-touches-all-columns issue (#468) is separately tracked and orthogonal to this narrow fix. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
fix: flatline_forecaster duplicate predictions on trailing-NA input (#454)
) When args_list = arx_args_list(target_date = ...) produces forecast_date + ahead != target_date, the validation error inside arx_fcast_epi_workflow() was short-circuited by a broken cli template: the message at R/arx_forecaster.R:147 referenced {ahead}, but inside that function the value lives at args_list$ahead. Users saw "Could not evaluate cli {} expression: 'ahead' not found" instead of the documented validation error. Change {.val {ahead}} -> {.val {args_list$ahead}} on that line. The error now fires with class epipredict__arx_forecaster__inconsistent_target_ahead_forecaste_date and a message naming all three values. The sibling template at line 335 (inside arx_args_list()) is unchanged because there ahead is a formal argument. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
fix: `arx_forecaster()` cli template error on inconsistent target_date (#473)
Pure regeneration via devtools::document(). The recorded example output for step_adjust_latency had drifted relative to the current epi_df print phrasing (lag -> latency) from upstream epiprocess; running document() updates 12 lines across three example blocks. No source code or behavior change. The drift surfaced repeatedly during recent fix PRs (#477, #478, #479); landing the regen once eliminates the friction. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…er (#229) arx_forecaster() and flatline_forecaster() now error at the forecaster boundary when quantile_by_key contains columns that are not in key_colnames(epi_data), instead of silently dropping them downstream. For flatline_forecaster() in particular the layer-level warning was invisible because forecast(wf) is wrapped in suppressWarnings(), so users got no signal at all on invalid input. Also adds a warning when arx_forecaster() is called with a quantile- output trainer (quantile_reg() or rand_forest with engine "grf_quantiles") plus a non-empty quantile_by_key. The argument is silently dropped in that code branch; the warning surfaces the no-op without breaking working code. The 2023 headline failure (flatline crashing on a valid key) no longer reproduces - residuals.flatline carries geo_value through and the call works cleanly. cdc_baseline_forecaster uses a different layer with the same parallel-structure vulnerability; deferred to a follow-up issue. Version bumped 0.2.5 -> 0.2.7 (skipping 0.2.6 for the open PR #480 collision). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Switches the version bump for #229 from 0.2.7 to 0.2.6 so the maintainer can choose the merge order against the still-open PR #480 (doc regen, also targeting 0.2.6). Whichever PR merges first claims 0.2.6; the other rebases to 0.2.7 at merge time. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
chore: regenerate roxygen-derived `man/step_adjust_latency.Rd`
…-229 fix: validate `quantile_by_key` in `arx_forecaster()` and `flatline_forecaster()` (#229)
enh: pivot_quantiles_longer adds quantile_level to epi_df other_keys
…autoplot.canned_epipred to match
…ng in autoplot methods
…-target-date forecasts
…n as an epi_df key
Reinclusion of `.max_keys = Inf` in `autoplot.epi_workflow`
Djm/summer cleaning
JavierMtzRdz
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Aug 21, 2026
JavierMtzRdz
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I reviewed the changes quickly, file by file. Most of them involve formatting, replacing broken links, fixing global checks, and correcting the autoplot, its corresponding tests, and small fixes discussed on the epitooling Slack before. Those lgtm.
I'm unsure about the changes in R/arx_forecaster.R and other adjustments to the forecasters. They seem to match what is mentioned in the NEWS.md. Do you want me to take a closer look?
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I reviewed the commits more closely, and everything appears to be in order. I checked |
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mainis about 11 months behind!? Anddevhas some feature upgrades as well as key website simplifications @dsweber2 made a while back.Any objections or potential barriers?