t_code_application_log
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Axis
t_code_application_logon sub-layerL2_5_D_cleaning_effect_summary(layerl2_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.