[eugenegujing]

What changes were proposed in this PR?

The Volcano Plot draws a plain scatter of effect size vs -log10(p), colored by effect size, which is already the x axis. Nothing shows where the significance bar is or which points clear it. This PR adds three optional properties, all off by default, so saved workflows render as before.

Property	Type	Effect when set
Significance threshold	number, 0 < x <= 1	dashed horizontal line at -log10(threshold)
Effect-size threshold	number, > 0	dashed vertical lines at +threshold and -threshold
Color by significance	boolean	with both thresholds set, points are colored Up / Down / Not significant with a legend instead of the continuous RdBu scale

Before:  px.scatter(color=<effect column>, color_continuous_scale="RdBu")
After:   same by default
         + fig.add_hline(...)                        when a significance threshold is set
         + fig.add_vline(+eff) / fig.add_vline(-eff) when an effect-size threshold is set
         + color="Significance", 3-color map         when the toggle is on and both thresholds are set

Categories use strict comparisons on the selected p-value column: Up = p < sig and effect > eff, Down = p < sig and effect < -eff, everything else Not significant. The category is written to a column named Significance (also the legend title); an input column of that name would be shadowed inside the operator only. Colors are ColorBrewer RdBu end points #B2182B / #2166AC plus grey #9E9E9E.

Validation: the JSON schema bounds above stop bad values in the property panel. For hand-edited JSON the operator also ignores a threshold it cannot draw (NaN, infinite, <= 0, or a p cut-off > 1) and falls back to the continuous coloring if the toggle is on but a threshold is missing. A cut-off of exactly 1 is allowed and draws its line at y = 0. If the cut-off's -log10 is beyond the data range the line may fall outside the auto-ranged axis; extending the range is left for a follow-up.

Since #8504 merged, the operator also exports a standalone script through generateStandaloneCode(). This PR adds the cut-off lines, the Significance column and the three-color map there too, from the same helpers where possible: the color map and category order are one shared literal, the threshold lines come from the same builder, and only the column names differ (Python literals instead of decoded strings). A spec checks that both paths make the same line and coloring decisions for eight threshold shapes, so the exported figure cannot drift from the engine's.

Independent of the label-fix (#9037) and hover-column (#9038) PRs; all three touch neighbouring lines of VolcanoPlotOpDesc.scala, so whichever lands second needs a small rebase.

Figures below are the operator's generated Python from main and from this branch, run on the 430-gene example workflow from the issue, with thresholds 0.05 and 1.

Before	After (lines only)	After (lines + Color by significance)

Any related issues, documentation, discussions?

Closes #9039

PR #8504 (merged) added the generateStandaloneCode() export path; the mirroring described above is the follow-up it needed.

How was this PR tested?

New tests in VolcanoPlotOpDescSpec, written before the source change:

• defaults: no lines, continuous coloring; each threshold alone emits only its own line(s); both with the toggle off keep the continuous coloring
• toggle on with both thresholds: strict comparisons, np.select column, exact color map and category order, no color_continuous_scale
• toggle on with one or no threshold: continuous fallback
• zero / negative thresholds and a p cut-off above 1 emit no line of their own; Infinity, -Infinity, NaN from JSON never reach the Python
• a cut-off of exactly 1 draws its line and still colors by category
• thresholds are emitted as valid Python floats, checked for 1e-300, Double.MIN_VALUE and 1e21 in every site they appear
• the generated JSON schema carries exclusiveMinimum / maximum on the two thresholds
• JSON deserialization: numbers, numeric strings, null, blank, absent, and the boolean toggle
• a workflow JSON saved before this change generates byte-for-byte the same code as a default-constructed operator
• generateStandaloneCode: defaults draw no line and keep the continuous coloring; thresholds with the toggle off draw the dashed lines only; the toggle on colors Up / Down / Not significant with the column names as literals; a cross-path test checks that the exported script makes the same cut-off and coloring decisions as the engine for eight threshold shapes (unset, one side only, zero, p cut-off above 1, non-finite, exactly 1); a saved workflow renders as a default-constructed operator

sbt -Dsbt.server.forcestart=true "WorkflowOperator/testOnly *VolcanoPlotOpDescSpec"
# Tests: succeeded 30, failed 0, canceled 0, ignored 0, pending 1   (the pending one is pre-existing)

sbt -Dsbt.server.forcestart=true "WorkflowOperator/scalafmtAll" "WorkflowOperator/Test/scalafmtAll"
sbt -Dsbt.server.forcestart=true "WorkflowOperator/scalafixAll --check"
# success

Smoke run outside Texera (pytexera stubbed, pandas + plotly 5.24.1) on the 430-gene mock table, 420 rows after the operator drops zero and missing p-values:

Configuration	Lines	Traces
defaults	none	1 continuous trace, 420 points
0.05 / 1, toggle off	hline y = 1.301, vlines x = ±1	1 continuous trace
0.05 / 1, toggle on	same	Up 35, Down 35, Not significant 350
0.05 only, toggle on	hline only	continuous (fallback)
0.05 / -1, toggle on	hline only	continuous (fallback)
2 / 1, toggle on	vlines only	continuous (fallback)
"Infinity" / "NaN" from JSON	none	continuous, no such token in the code
1e-300 / 1e21, toggle on	hline y = 300, vlines x = ±1e21	Not significant 420
1 / 1, toggle on	hline y = 0, vlines x = ±1	Up 41, Down 38, Not significant 341

The exponent-form dumps pass python -m py_compile. The exported script for the default, lines-only and colored configurations parses with ast.parse.

Was this PR authored or co-authored using generative AI tooling?

Yes. Generated-by: Claude Code (claude-fable-5-1). Co-authored with Claude; the author reviewed the change before submission.

[github-actions]

Automated Reviewer Suggestions

Based on the git blame history of the changed files, we recommend the following reviewers:

• Contributors with relevant context: @kz930, @Yicong-Huang
  You can notify them by mentioning @kz930, @Yicong-Huang in a comment.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 91.87%. Comparing base (98c6337) to head (d5dadbb).

Additional details and impacted files

@@            Coverage Diff            @@
##               main    #9041   +/-   ##
=========================================
  Coverage     91.87%   91.87%           
  Complexity     5049     5049           
=========================================
  Files          1265     1265           
  Lines         54915    54913    -2     
  Branches       6940     6940           
=========================================
- Hits          50453    50452    -1     
+ Misses         2769     2768    -1     
  Partials       1693     1693           

Flag	Coverage Δ		*Carryforward flag
access-control-service	77.38% <ø> (ø)
agent-service	99.16% <ø> (ø)		Carriedforward from 98c6337
amber	86.07% <ø> (+<0.01%)	⬆️	Carriedforward from 98c6337
computing-unit-managing-service	60.48% <ø> (ø)
config-service	87.37% <ø> (ø)
file-service	82.00% <ø> (ø)
frontend	96.50% <ø> (ø)		Carriedforward from 98c6337
notebook-migration-service	83.73% <ø> (ø)
pyamber	98.54% <ø> (ø)		Carriedforward from 98c6337
workflow-compiling-service	72.43% <ø> (ø)

*This pull request uses carry forward flags. Click here to find out more.

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[github-actions]

⚠️ Benchmark changes need a look

🟢 2 better · 🔴 5 worse · ⚪ 8 noise (<±5%) · 0 without baseline

Compared against main 98c6337 benchmarked on this same runner, so the delta is largely free of cross-runner hardware noise. The "7d avg" column still reflects the gh-pages dashboard. Treat <±5% as noise unless repeated.

Dashboard · Run

	config	throughput	MB/s	latency	max Δ latest / 7d
🔴	bs=10 sw=10 sl=64	378	0.23	26,351/35,663/35,663 us	🟢 -60.5% / 🔴 +150.6%
🔴	bs=100 sw=10 sl=64	835	0.51	115,024/156,302/156,302 us	🔴 +15.1% / 🔴 +62.0%
⚪	bs=1000 sw=10 sl=64	982	0.599	1,017,149/1,077,295/1,077,295 us	⚪ within ±5% / 🔴 +18.4%

Baseline details

Latest main 98c6337 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	378 tuples/sec	379 tuples/sec	879.16 tuples/sec	-0.3%	-57.0%
bs=10 sw=10 sl=64	MB/s	0.23 MB/s	0.231 MB/s	0.537 MB/s	-0.4%	-57.1%
bs=10 sw=10 sl=64	p50	26,351 us	24,156 us	11,504 us	+9.1%	+129.1%
bs=10 sw=10 sl=64	p95	35,663 us	90,374 us	14,234 us	-60.5%	+150.6%
bs=10 sw=10 sl=64	p99	35,663 us	90,374 us	17,338 us	-60.5%	+105.7%
bs=100 sw=10 sl=64	throughput	835 tuples/sec	886 tuples/sec	1,147 tuples/sec	-5.8%	-27.2%
bs=100 sw=10 sl=64	MB/s	0.51 MB/s	0.54 MB/s	0.7 MB/s	-5.6%	-27.2%
bs=100 sw=10 sl=64	p50	115,024 us	111,137 us	88,987 us	+3.5%	+29.3%
bs=100 sw=10 sl=64	p95	156,302 us	135,787 us	96,473 us	+15.1%	+62.0%
bs=100 sw=10 sl=64	p99	156,302 us	135,787 us	102,791 us	+15.1%	+52.1%
bs=1000 sw=10 sl=64	throughput	982 tuples/sec	999 tuples/sec	1,182 tuples/sec	-1.7%	-16.9%
bs=1000 sw=10 sl=64	MB/s	0.599 MB/s	0.61 MB/s	0.721 MB/s	-1.8%	-17.0%
bs=1000 sw=10 sl=64	p50	1,017,149 us	999,973 us	872,751 us	+1.7%	+16.5%
bs=1000 sw=10 sl=64	p95	1,077,295 us	1,039,866 us	910,151 us	+3.6%	+18.4%
bs=1000 sw=10 sl=64	p99	1,077,295 us	1,039,866 us	941,479 us	+3.6%	+14.4%

Raw CSV

config_idx,batch_size,schema_width,string_len,num_batches,total_ms,total_tuples,total_bytes,tuples_per_sec,mb_per_sec,lat_p50_us,lat_p95_us,lat_p99_us
0,10,10,64,20,529.67,200,128000,378,0.230,26351.19,35662.75,35662.75
1,100,10,64,20,2393.99,2000,1280000,835,0.510,115023.87,156301.77,156301.77
2,1000,10,64,20,20374.77,20000,12800000,982,0.599,1017148.93,1077294.56,1077294.56