t_code_application_log

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Axis t_code_application_log on sub-layer L2_5_D_cleaning_effect_summary (layer l2_5).

Sub-layer

L2_5_D_cleaning_effect_summary

Axis metadata

  • Default: 'summary'

  • Sweepable: False

  • Status: operational

Operational status summary

  • Operational: 3 option(s)

  • Future: 0 option(s)

Options

none – operational

Skip the tcode log.

L2.5.D tcode log option none.

This option configures the t_code_application_log axis on the L2_5_D_cleaning_effect_summary sub-layer of L2.5; output is emitted under manifest.diagnostics/l2_5/L2_5_D_cleaning_effect_summary/ alongside the other selected views.

When to use

When transform_policy = no_transform and no tcodes were applied.

References

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

  • McCracken & Ng (2016) ‘FRED-MD: A Monthly Database for Macroeconomic Research’, JBES 34(4): 574-589. (doi:10.1080/07350015.2015.1086655)

Related options: summary, per_series_detail

Last reviewed 2026-05-05 by macroforecast author.

per_series_detail – operational

Per-series tcode applied + before/after means.

L2.5.D tcode log option per_series_detail.

This option configures the t_code_application_log axis on the L2_5_D_cleaning_effect_summary sub-layer of L2.5; output is emitted under manifest.diagnostics/l2_5/L2_5_D_cleaning_effect_summary/ alongside the other selected views.

When to use

Forensic audit of tcode application; useful when investigating unexpected post-tcode behaviour.

References

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

  • McCracken & Ng (2016) ‘FRED-MD: A Monthly Database for Macroeconomic Research’, JBES 34(4): 574-589. (doi:10.1080/07350015.2015.1086655)

Related options: summary, none

Last reviewed 2026-05-05 by macroforecast author.

summary – operational

Tcode usage histogram (counts per tcode).

L2.5.D tcode log option summary.

This option configures the t_code_application_log axis on the L2_5_D_cleaning_effect_summary sub-layer of L2.5; output is emitted under manifest.diagnostics/l2_5/L2_5_D_cleaning_effect_summary/ alongside the other selected views.

When to use

Default; quick cumulative summary of which tcodes were applied.

References

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

  • McCracken & Ng (2016) ‘FRED-MD: A Monthly Database for Macroeconomic Research’, JBES 34(4): 574-589. (doi:10.1080/07350015.2015.1086655)

Related options: per_series_detail, none

Last reviewed 2026-05-05 by macroforecast author.