forecast_scale_view

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Axis forecast_scale_view on sub-layer L4_5_B_forecast_scale_view (layer l4_5).

Sub-layer

L4_5_B_forecast_scale_view

Axis metadata

  • Default: 'both_overlay'

  • Sweepable: False

  • Status: operational

Operational status summary

  • Operational: 3 option(s)

  • Future: 0 option(s)

Options

back_transformed_only – operational

Plot forecasts back-transformed to the target’s level.

L4.5.B forecast scale view back_transformed_only.

This option configures the forecast_scale_view axis on the L4_5_B_forecast_scale_view sub-layer of L4.5; output is emitted under manifest.diagnostics/l4_5/L4_5_B_forecast_scale_view/ alongside the other selected views.

When to use

Default reporting view; matches the audience’s mental model of the target.

References

  • macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

Related options: transformed_only, both_overlay

Last reviewed 2026-05-05 by macroforecast author.

both_overlay – operational

Overlay both scales in side-by-side panels.

L4.5.B forecast scale view both_overlay.

This option configures the forecast_scale_view axis on the L4_5_B_forecast_scale_view sub-layer of L4.5; output is emitted under manifest.diagnostics/l4_5/L4_5_B_forecast_scale_view/ alongside the other selected views.

When to use

Comparing transformed vs level forecasts; useful when transformation effects matter.

References

  • macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

Related options: transformed_only, back_transformed_only

Last reviewed 2026-05-05 by macroforecast author.

transformed_only – operational

Plot forecasts in the transformed (model-internal) scale.

L4.5.B forecast scale view transformed_only.

This option configures the forecast_scale_view axis on the L4_5_B_forecast_scale_view sub-layer of L4.5; output is emitted under manifest.diagnostics/l4_5/L4_5_B_forecast_scale_view/ alongside the other selected views.

When to use

Inspecting model-native predictions; useful for diagnosing fit issues at the estimator’s scale.

References

  • macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

Related options: back_transformed_only, both_overlay

Last reviewed 2026-05-05 by macroforecast author.