diagnostic_format

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Axis diagnostic_format on sub-layer L2_5_Z_export (layer l2_5).

Sub-layer

L2_5_Z_export

Axis metadata

  • Default: 'pdf'

  • Sweepable: False

  • Status: operational

Operational status summary

  • Operational: 7 option(s)

  • Future: 0 option(s)

Options

csv – operational

L2.5 export – plain csv table – one row per series / metric.

Tabular diagnostic outputs (per-series summaries, test p-values, coverage tables) are emitted as comma-separated rows. The fastest path into pandas / R / Excel for ad-hoc analysis.

Diagnostic artifacts land under manifest.diagnostics/l2_5/ with one file per axis per format chosen here.

When to use

Quickest path to spreadsheet / pandas; collaborators who avoid JSON.

References

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

Related options: html, json, latex_table, multi, pdf, png

Last reviewed 2026-05-05 by macroforecast author.

html – operational

L2.5 export – single-file html report with embedded plots and tables.

Renders a self-contained HTML document combining tables (via pandas to_html) and base64-embedded matplotlib figures. Opens in any browser without server-side support; ideal for sharing with stakeholders who lack the codebase.

Diagnostic artifacts land under manifest.diagnostics/l2_5/ with one file per axis per format chosen here.

When to use

Sharing diagnostics with collaborators who do not have the repo checked out.

References

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

Related options: csv, json, latex_table, multi, pdf, png

Last reviewed 2026-05-05 by macroforecast author.

json – operational

L2.5 export – machine-readable json dump of every diagnostic value.

Default format. Round-trips cleanly into Python / JS; mandatory when attach_to_manifest=True so the diagnostics participate in the manifest’s hash-based replication check.

Diagnostic artifacts land under manifest.diagnostics/l2_5/ with one file per axis per format chosen here.

When to use

Default; required when diagnostics participate in the bit-exact replication chain.

References

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

Related options: csv, html, latex_table, multi, pdf, png

Last reviewed 2026-05-05 by macroforecast author.

latex_table – operational

L2.5 export – latex tabular snippets ready to \input into a paper.

Emits one .tex file per tabular diagnostic, ready to be \input from a paper draft without further processing. Booktabs-friendly column alignment + automatic column-name escaping.

Diagnostic artifacts land under manifest.diagnostics/l2_5/ with one file per axis per format chosen here.

When to use

Paper-quality export when the user is drafting a manuscript.

References

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

Related options: csv, html, json, multi, pdf, png

Last reviewed 2026-05-05 by macroforecast author.

multi – operational

L2.5 export – emit json + png + (optional) pdf / html in a single run.

Comprehensive convenience option. Produces JSON for machine consumption + PNG for slides + (when latex_export=True) LaTeX snippets for papers. Equivalent to setting diagnostic_format separately for each consumer.

Diagnostic artifacts land under manifest.diagnostics/l2_5/ with one file per axis per format chosen here.

When to use

Comprehensive runs covering paper, slides and machine-readable consumers in one execution.

References

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

Related options: csv, html, json, latex_table, pdf, png

Last reviewed 2026-05-05 by macroforecast author.

pdf – operational

L2.5 export – vector pdf figures (matplotlib backend).

Matplotlib’s PDF backend produces vector graphics that scale without pixelation. Recommended for paper figures where journals require sub-pixel-precise typography.

Diagnostic artifacts land under manifest.diagnostics/l2_5/ with one file per axis per format chosen here.

When to use

Publication-grade plots; LaTeX-rendered figures.

References

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

Related options: csv, html, json, latex_table, multi, png

Last reviewed 2026-05-05 by macroforecast author.

png – operational

L2.5 export – rasterised png figures (matplotlib backend).

Matplotlib’s AGG backend produces 300dpi-by-default PNG files. Smaller than PDF for plot-heavy reports; the natural choice for slide decks and HTML embeddings.

Diagnostic artifacts land under manifest.diagnostics/l2_5/ with one file per axis per format chosen here.

When to use

Slide / web embedding where vector formats are unnecessary.

References

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

Related options: csv, html, json, latex_table, multi, pdf

Last reviewed 2026-05-05 by macroforecast author.