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Add combined results and plot generation #219

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49bd845
Add an option --combined-results to create list with all use cases
avolkov-intel Feb 19, 2026
356dc0a
Add options to draw comparison plots
avolkov-intel Feb 19, 2026
24ab534
Handle n_jobs param correctly and add Summary 2 and All cases 2 pages
avolkov-intel Jun 2, 2026
e842a63
Add footnote for plot and add metrics
avolkov-intel Aug 12, 2026
98fa891
Update footnote
avolkov-intel Aug 17, 2026
1886459
Update docs
avolkov-intel Aug 17, 2026
59276a2
Code format
avolkov-intel Aug 17, 2026
2f671bd
Minor docs update
avolkov-intel Aug 18, 2026
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4 changes: 4 additions & 0 deletions sklbench/report/README.md
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Expand Up @@ -18,6 +18,10 @@ Raw results are converted into a pandas dataframe and the final report is made b
| `--report-file` | str | report.xlsx | | Report file path. |
| `--report-type` | str | separate-tables | ('separate-tables',) | Report type ("separate-tables" is the only supported now). |
| `--compatibility-mode` | | False | | [EXPERIMENTAL] Compatibility mode drops and modifies results to make them comparable (for example, sklearn and cuML parameters). |
| `--performance-stability-metrics`</br>`-psm` | | False | | Adds performance stability metrics (`1st run time[ms]`, `1st-mean run ratio`, `median time[ms]`, `time CV`) to the report. |
| `--combined-results` | | False | | [EXPERIMENTAL] Creates `All cases` and `Summary (for plots)` sheets combining time and speedup of all algorithms with per-dtype/total GEOMEAN rows. This option can only be used for comparing scikit-learn-intelex with stock scikit-learn (use with `--compatibility-mode`). |
| `--draw-plots` | | False | | [EXPERIMENTAL] Draws Training/Inference speedup bar charts from the combined results (requires `--combined-results`). |

@david-cortes-intel david-cortes-intel Aug 18, 2026

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This option without --plot-output doesn't appear to do anything. It doesn't show anything interactive for me, or at least not when used in an SSH session.

| `--plot-output` | str | None | | [EXPERIMENTAL] Output file path for plots (e.g. `plots.png`); if unset, plots are shown interactively. |

@david-cortes-intel david-cortes-intel Aug 18, 2026

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Does this require passing --draw-plots?

@avolkov-intel avolkov-intel Aug 18, 2026 •
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Well technically no, you can provide it without draw plots it would be just ignored

@david-cortes-intel david-cortes-intel Aug 18, 2026

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Please add that kind of detail in these docs.

| `--drop-columns`</br>`--drop-cols` | str | [] | | Columns to drop from report. |
| `--diff-columns`</br>`--diff-cols` | str | ['environment_name', 'library', 'format', 'device'] | | Columns to show difference between. |
| `--split-columns` | str | ['estimator', 'method', 'function'] | | Splitting columns for subreports/sheets. |
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22 changes: 22 additions & 0 deletions sklbench/report/arguments.py
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Expand Up @@ -93,6 +93,28 @@ def add_report_generator_arguments(
help="Selects which part of one-vs-one difference to show "
"(all matrix or one of triangles).",
)
parser.add_argument(
"--combined-results",
default=False,
action="store_true",
help="[EXPERIMENTAL] Creates 'All cases' and 'Summary (for plots)' sheets "
"combining time[ms] and speedup of all algorithms into single pages with "
"per-dtype and total GEOMEAN rows. Use together with --compatibility-mode.",
)
parser.add_argument(
"--draw-plots",
default=False,
action="store_true",
help="[EXPERIMENTAL] Draw Training/Inference speedup bar charts from combined "
"results (requires --combined-results).",
)
parser.add_argument(
"--plot-output",
type=str,
default=None,
help="[EXPERIMENTAL] Output file path for plots (e.g., plots.png). "
"If not specified, plots are displayed.",
)
# color scale settings
parser.add_argument(
"--perf-color-scale",
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6 changes: 6 additions & 0 deletions sklbench/report/compatibility.py
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Expand Up @@ -34,6 +34,12 @@ def transform_results_to_compatible(results: pd.DataFrame):
"min_bin_size",
],
)
if (
"n_jobs" in results.columns
and results["n_jobs"].isna().any()
and results["n_jobs"].notna().any()
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ethanglaser marked this conversation as resolved.
):
results.drop(inplace=True, columns=["n_jobs"])
if results["environment_name"].unique().size > 1:
# DBSCAN `eps` parameter drop for different CPUs
results.drop(
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