Default method for run_searchlight

By default, if an object's class does not implement a specific run_searchlight.<class> method, this fallback will call run_searchlight_base.

Usage

# Default S3 method
run_searchlight(
  model_spec,
  radius = 8,
  method = c("standard", "randomized", "resampled"),
  niter = 4,
  backend = c("default", "shard", "auto"),
  ...
)

Arguments

model_spec

A mvpa_model instance containing the model specifications

radius

The searchlight radius in millimeters

method

The type of searchlight, either 'randomized' or 'standard'

niter

The number of searchlight iterations (used only for 'randomized' method)

backend

Execution backend: "default" (standard pipeline), "shard" (shared-memory backend), or "auto" (try shard and fall back to default).

...

Additional arguments passed through:

engine

Searchlight engine: "auto" (default), "legacy" (the compatibility key for the general-purpose iterator), "swift", "dual_lda_fast", "naive_xdec_fast", or "era_rsa_fast". "auto" only selects engines that compute the same estimator as the model specification. "swift" is never selected automatically: it replaces the specified classifier with SWIFT's z-scored nearest-class-mean estimator and must be requested explicitly.

combiner

Combiner function or name for randomized/resampled methods (default "average").

drop_probs

If TRUE, drop probability predictions (default FALSE).

fail_fast

If TRUE, stop on first ROI error (default FALSE).

k

Number of neighbors for searchlight construction (default NULL).

verbose

If TRUE, print progress messages (default FALSE).

incremental, gamma

Engine-specific arguments for dual LDA engine.

Value

A `searchlight_result` object containing spatial maps for each metric.

Examples

# An mvpa_model has no dedicated method, so dispatch uses this default
ds <- gen_sample_dataset(D = c(3, 3, 3), nobs = 24, nlevels = 2, blocks = 3)
cval <- blocked_cross_validation(ds$design$block_var)
mspec <- mvpa_model(load_model("corclass"), dataset = ds$dataset,
                    design = ds$design, crossval = cval)
res <- run_searchlight(mspec, radius = 2, method = "standard")
#> INFO [2026-10-16 11:46:41] searchlight engine: aggregate_fast
names(res$results)
#> [1] "Accuracy" "AUC"