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tabgab (@tabgab) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Opp Repl Module Image Tests by tabgab

Name: Opp Repl Module Image Tests
Author: tabgab

Opp Repl Module Image Tests

Detect visual regressions in OMNeT++ module rendering. capture_module_images renders one image per compound module from each filtered simulation (via Qtenv); run_module_image_tests compares fresh renders against a baseline using an RMSE metric. Distinct from chart tests (which compare analysis plots). Requires the httpx extra. Load when module display strings, icons, or layout must stay stable.

tabgab 7e59e1e 3.7 KB Updated Sep 17, 2026

File contents

Module-image tests

Module-image tests render the network/module visualization that Qtenv would draw (display strings, icons, layout, submodule arrangement) and compare it against a stored baseline image. This catches regressions in NED display strings and visualization code — something neither fingerprint tests (event behavior) nor chart tests (analysis plots) cover.

Upstream reference: https://github.com/omnetpp/opp_repl/blob/main/doc/module_image_tests.md

Requirements

pip install "opp_repl[mcp]"   # provides httpx, used to drive Qtenv

Baseline images live in the project's module_image_baseline_folder.

Python API

# 1. Seed/refresh the baseline (first run, or after intended changes)
update_module_image_test_results(simulation_project=inet_project)

# 2. Run the comparison
r = run_module_image_tests(simulation_project=inet_project)

# 3. Capture images to an arbitrary directory (e.g. for review)
capture_module_images(simulation_project=inet_project,
                      output_dir="/tmp/inet-modules")

run_module_image_tests returns MultipleTestTaskResults with PASS / FAIL / SKIP / ERROR per simulation (see opp-repl-tasks-and-results).

Command line

opp_capture_module_images            --load inet.opp -p inet --output-dir /tmp/imgs
opp_update_module_image_test_results --load inet.opp -p inet
opp_run_module_image_tests           --load inet.opp -p inet

--output-dir is required for opp_capture_module_images.

Useful options (CLI and kwargs)

Option	Meaning
`--module-path-filter`	glob on a module's full path (e.g. `*.host[]`)
`--module-type-filter`	glob on a module's NED type
`--group-by`	`path` (default) / `type` / `path_no_indices`
`--area`	`all_elements` (default) / `module_rectangle` / `viewport`
`--margin`	pixels around the captured area (default 5)
`--startup-timeout`	seconds to wait per simulation's MCP endpoint (default 30)
`--metric-threshold`	max RMSE for a PASS (default 0 = pixel-perfect)
`--baseline-simulation-project`	project supplying the baseline (run only)

Loosen --metric-threshold slightly (e.g. 2.0) when minor anti-aliasing noise causes spurious FAILs.

Pitfalls

Rendering drives Qtenv through opp_repl's MCP machinery, so the mcp extra (httpx) must be installed even for a "headless" run.
Fonts, Qt version, and display scaling change the pixels. Pin the toolchain (ideally a fixed container) across baseline and CI, like chart tests.
Pixel-perfect default (--metric-threshold 0) is strict; a one-pixel shift FAILs. Use a small RMSE threshold for stability.
This is a different suite from chart tests — keep their baselines and thresholds separate.

---name: opp-repl-module-image-testsdescription: Detect visual regressions in OMNeT++ module rendering. capture_module_images renders one image per compound module from each filtered simulation (via Qtenv); run_module_image_tests compares fresh renders against a baseline using an RMSE metric. Distinct from chart tests (which compare analysis plots). Requires the httpx extra. Load when module display strings, icons, or layout must stay stable.---# Module-image testsModule-image tests render the **network/module visualization** thatQtenv would draw (display strings, icons, layout, submodulearrangement) and compare it against a stored baseline image. Thiscatches regressions in NED display strings and visualization code —something neither fingerprint tests (event behavior) nor chart tests(analysis plots) cover.Upstream reference:https://github.com/omnetpp/opp_repl/blob/main/doc/module_image_tests.md## Requirements pip install "opp_repl[mcp]" # provides httpx, used to drive QtenvBaseline images live in the project's `module_image_baseline_folder`.## Python API # 1. Seed/refresh the baseline (first run, or after intended changes) update_module_image_test_results(simulation_project=inet_project) # 2. Run the comparison r = run_module_image_tests(simulation_project=inet_project) # 3. Capture images to an arbitrary directory (e.g. for review) capture_module_images(simulation_project=inet_project, output_dir="/tmp/inet-modules")`run_module_image_tests` returns `MultipleTestTaskResults` withPASS / FAIL / SKIP / ERROR per simulation (see`opp-repl-tasks-and-results`).## Command line opp_capture_module_images --load inet.opp -p inet --output-dir /tmp/imgs opp_update_module_image_test_results --load inet.opp -p inet opp_run_module_image_tests --load inet.opp -p inet`--output-dir` is required for `opp_capture_module_images`.## Useful options (CLI and kwargs)| Option | Meaning ||---------------------------|----------------------------------------------------------|| `--module-path-filter` | glob on a module's full path (e.g. `**.host[*]`) || `--module-type-filter` | glob on a module's NED type || `--group-by` | `path` (default) / `type` / `path_no_indices` || `--area` | `all_elements` (default) / `module_rectangle` / `viewport` || `--margin` | pixels around the captured area (default 5) || `--startup-timeout` | seconds to wait per simulation's MCP endpoint (default 30) || `--metric-threshold` | max RMSE for a PASS (default 0 = pixel-perfect) || `--baseline-simulation-project` | project supplying the baseline (run only) |Loosen `--metric-threshold` slightly (e.g. `2.0`) when minoranti-aliasing noise causes spurious FAILs.## Pitfalls- Rendering drives Qtenv through opp_repl's MCP machinery, so the `mcp` extra (httpx) must be installed even for a "headless" run.- Fonts, Qt version, and display scaling change the pixels. Pin the toolchain (ideally a fixed container) across baseline and CI, like chart tests.- Pixel-perfect default (`--metric-threshold 0`) is strict; a one-pixel shift FAILs. Use a small RMSE threshold for stability.- This is a different suite from chart tests — keep their baselines and thresholds separate.## See also- `opp-repl-chart-tests` — visual regression for analysis plots.- `opp-repl-tasks-and-results` — inspect FAIL/ERROR results.- `opp-repl-running-simulations` — underlying run machinery.- `opp-repl-feature-and-release-tests` — run as part of a full suite.

Frequently asked questions