Enum: ObservationReductionMode

How an observation is evaluated over the trajectory (see Observation.reduce). Absent (the default) keeps the post-scan pipeline: the observation is computed from a materialised trajectory. streaming opts the observation into an incremental reducer that is folded into the integrator carry via prepare(reduce=…), so the trajectory is never held — byte-identical to the post-scan value (to f64 rounding), but with O(block) instead of O(n_time) peak memory. Required for whole-brain fits whose per-stage simulation is long enough that the full trajectory would not fit in memory (e.g. the Schirner 2023 BOLD/FC group fit).

URI: tvbo:enum/ObservationReductionMode

Permissible Values

Value Meaning Description
streaming None Fold this observation into the integrator carry as an (init, update, finalize…
trials None Evaluate the pipeline across the trial ensemble rather than per solve: the (s…

Slots

Name Description
reduce Opt into streaming evaluation of this observation: fold it into the integrato…

Identifier and Mapping Information

Schema Source

  • from schema: https://w3id.org/tvbo

LinkML Source

name: ObservationReductionMode
description: 'How an observation is evaluated over the trajectory (see Observation.reduce).
  Absent (the default) keeps the post-scan pipeline: the observation is computed from
  a materialised trajectory. `streaming` opts the observation into an incremental
  reducer that is folded into the integrator carry via prepare(reduce=...), so the
  trajectory is never held — byte-identical to the post-scan value (to f64 rounding),
  but with O(block) instead of O(n_time) peak memory. Required for whole-brain fits
  whose per-stage simulation is long enough that the full trajectory would not fit
  in memory (e.g. the Schirner 2023 BOLD/FC group fit).'
from_schema: https://w3id.org/tvbo
rank: 1000
permissible_values:
  streaming:
    text: streaming
    description: Fold this observation into the integrator carry as an (init, update,
      finalize) reducer; never materialise the trajectory. Supported for the HRF-Volterra
      BOLD pipeline (hemodynamic convolution, whose kernel / downsample stride / TR
      stride / Volterra scaling the resolver lifts from the declared pipeline), cumulative
      mean/std/variance aggregations, and a matrix co-moment FC (compute_fc as a running
      covariance).
  trials:
    text: trials
    description: 'Evaluate the pipeline across the trial ensemble rather than per
      solve: the (single) source observation is computed per trial as usual, and after
      the trial map this observation''s (single) pipeline stage runs host-side on
      the trial-stacked source (n_trials, ...) — e.g. a pattern-entropy over an ensemble
      of per-trial evoked patterns. Requires a trial-only exploration (n_trials without
      parameter axes).'