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 # Impakt — Brainstorm
 
-Ideas, feature proposals, and design thoughts collected during development.
-Grouped by theme. Checkboxes indicate implementation status.
+Ideas, feature proposals, and design thoughts. Organized by user workflow and informed by the competitive landscape survey (see `research/landscape.md`).
+
+Priority tiers:
+- **P0** — Unlocks significant capability or addresses a clear gap vs. commercial tools
+- **P1** — Strong quality-of-life improvement for daily use
+- **P2** — Nice to have, longer-term, or exploratory
+
+Where an existing open-source library enables a feature, it's noted with `[lib: name]`. Repos are cloned in `research/repos/`.
 
 ---
 
-## Data Import & Channel Intelligence
+## The Core Experience
 
-- [ ] **Lazy channel loading** — For tests with 500+ channels, don't load `.dat` files until a channel is first accessed. Load headers eagerly, data lazily. This keeps `Session.open()` fast even for large datasets.
-- [ ] **Channel aliasing** — Allow users to define human-friendly aliases for channel codes. e.g., `"head_ax" -> "11HEAD0000ACXA"`. Aliases can live in templates or user config.
-- [ ] **Auto-detect signal type from channel code** — Use the measurement code (AC, FO, MO, DC...) to automatically suggest appropriate CFC class, plot axis labels, and unit handling.
-- [ ] **Batch loader** — Load an entire directory of tests at once. `Session.open_batch("/tests/series_2024/")` returns a `Series` object with cross-test operations.
-- [ ] **Channel search by physical meaning** — "Show me all head accelerations" should work across different test objects (driver, passenger, child dummies).
-- [ ] **Delta channel** — Compute the difference between the same channel across two tests. Useful for design iteration comparisons.
-- [ ] **NHTSA open data integration** — NHTSA publishes crash test data but in their own proprietary format (UDS), not ISO 13499 MME. No publicly available MME datasets exist (the format is industry-internal; Euro NCAP data is confidential). Build a UDS-to-MME converter or direct UDS reader plugin. NHTSA's NCAP database is at `nhtsa.gov/file-downloads?p=nhtsa/downloads/NCAP/` — the Access DB (`NCAP 6-14-10.mdb`) contains summary results, not time-history data. Contact NHTSA (SCI@dot.gov, 888-327-4236) for time-history channel data access.
-- [ ] **Channel metadata editor** — Sometimes `.chn` files have wrong units or missing metadata. Provide a non-destructive override mechanism stored in the session.
-- [ ] **Synthetic data generator** — Built into the test suite (`tests/fixtures/generate_mme.py`) for development. Consider exposing this as `impakt.synth` for users who want to prototype templates or test analysis scripts without real test data.
+The crash test engineer's workflow is: **receive data -> inspect -> filter -> compute -> score -> report**. Every feature below should make one of those steps faster, more reliable, or more insightful.
+
+What we learned from the landscape: commercial tools (measX X-Crash, NI DIAdem, Kistler) dominate because they nail this loop end-to-end with zero friction. No open-source web-based tool does this today. That's Impakt's opportunity.
+
+---
+
+## Rendering & Performance
+
+The most impactful near-term improvements. Large crash test datasets (133+ channels, 10k+ samples each at up to 100kHz) need to render smoothly.
+
+- [ ] **P0 — Integrate plotly-resampler** — Drop-in wrapper for Plotly figures that handles 110M+ points via LTTB downsampling. Replace `go.Figure()` with `FigureResampler(go.Figure())` in the plot engine. Works natively with Dash. `[lib: plotly-resampler]`
+- [ ] **P1 — Progressive rendering** — Show plots immediately with decimated data, refine with full resolution once loaded. Plotly-resampler does this automatically, but the UX should show a loading indicator during refinement.
+- [ ] **P1 — Memory-mapped data** — For very large datasets, use `numpy.memmap` to avoid loading everything into RAM. Enables tests with 500+ channels and multi-GB data files.
+- [ ] **P1 — Lazy channel loading** — Load `.dat` files only when a channel is first accessed. Load headers eagerly, data lazily. Keeps `Session.open()` fast for large tests.
+- [ ] **P2 — Channel cache** — Cache frequently-accessed transformed channels to avoid recomputing CFC filters every time a plot refreshes.
+- [ ] **P2 — Parallel criteria computation** — Compute all injury criteria in parallel using `concurrent.futures`. The individual computations are independent.
+
+---
 
 ## Visualization
 
-- [ ] **Synchronized zoom/pan** — When plotting multiple subplots (e.g., head accel + chest deflection), zoom/pan actions should sync across all subplots.
-- [ ] **Waterfall / 3D surface plots** — For tests with many similar channels (e.g., barrier face loads at multiple locations), a 3D surface or waterfall view shows spatial distribution.
-- [ ] **Animation mode** — Playback the crash event in time, with a vertical cursor sweeping across all plots simultaneously. Sync with video if available.
-- [ ] **Channel comparison sparklines** — In the channel tree sidebar, show tiny inline sparklines next to each channel name so engineers can visually identify signals before selecting them.
-- [ ] **Peak annotation** — Auto-annotate the peak value and time on plots. Toggle-able. Shows a marker + text label at the peak.
-- [ ] **Statistical overlays** — When viewing multiple tests, show mean +/- 1 sigma envelope, min/max envelope. Useful for repeatability studies.
-- [ ] **Color-by-test vs color-by-channel** — When overlaying multiple tests, let the user choose: each test gets a color (channels within a test share the color), or each channel gets a color (tests use line dash variants).
-- [ ] **Dark mode** — Engineers often work in labs with varying lighting. A dark theme would be appreciated.
-- [ ] **Custom plot layouts** — Allow 2x2, 3x1, 1x3, etc. subplot grids within a single view, each with independent channel selection.
-- [ ] **Persistent cursor positions** — When moving between plot views or applying transforms, cursor positions should persist in the session state.
+What makes crash test analysis *fast* is the ability to visually scan, compare, and correlate signals. The best commercial tools (measX, DIAdem, Altair HyperGraph) invest heavily here.
+
+### Multi-signal navigation
+
+- [ ] **P0 — Synchronized zoom/pan** — When plotting multiple subplots, zoom/pan actions sync across all panes sharing an X axis. Bokeh does this natively with linked ranges; in Plotly/Dash this requires shared `xaxis` config or callback-based sync. This is the single most-requested feature in crash test visualization.
+- [ ] **P1 — Channel sparklines** — In the channel grid sidebar, show tiny inline sparklines next to each channel name. Engineers visually identify signals before selecting them. The grid already has Min/Max columns; a 60px-wide sparkline column would be transformative for browsing 100+ channels.
+- [ ] **P1 — Peak annotation** — Auto-annotate peak value and time on plots as a togglable Plotly annotation. Shows a marker + text label at the global peak. Optionally annotate at cursor positions too.
+- [ ] **P1 — Dark mode** — Engineers often work in labs with varying lighting. A Dash Bootstrap dark theme (DARKLY or CYBORG) is a one-line change in `app.py`.
+
+### Multi-test comparison
+
+- [ ] **P0 — Quick comparison mode** — Two tests side-by-side with synchronized cursors. One-click "compare" button. Each test gets its own color family; channels within a test share the hue, differentiated by line dash. This is the most natural workflow after single-test analysis.
+- [ ] **P1 — Statistical overlays** — When viewing multiple tests, show mean +/- 1 sigma envelope, min/max envelope. Essential for repeatability studies and fleet testing.
+- [ ] **P1 — Delta channel** — Compute the difference between the same channel across two tests. Useful for design iteration comparisons (e.g., "how did the head acceleration change after we modified the airbag?").
+- [ ] **P2 — Color-by-test vs color-by-channel toggle** — Let the user choose: each test gets a color, or each channel gets a color.
+
+### Advanced visualization
+
+- [ ] **P1 — Frequency spectrum viewer** — FFT / power spectral density of a channel. Helps diagnose noise, identify resonant frequencies, and verify CFC filter behavior. Show alongside the time-domain plot in a split view.
+- [ ] **P2 — Waterfall / 3D surface plots** — For barrier face loads at multiple spatial locations, a waterfall view shows spatial distribution over time. Taipy and Plotly both support 3D surface natively.
+- [ ] **P2 — Animation mode** — Playback the crash event in time with a vertical cursor sweeping across all plots. Sync with video if available (see Video Sync below).
+- [ ] **P2 — Custom subplot grids** — Allow user-defined subplot grids beyond the current presets. Let users drag-resize panes.
+
+---
+
+## Data Import & Format Support
+
+Impakt currently reads ISO 13499 MME (real + synthetic). The landscape shows several adjacent formats that would broaden the tool's reach significantly.
+
+### High-priority formats
+
+- [ ] **P0 — UDS reader** — NHTSA's proprietary binary format. Required to access the largest public crash test database in the world (NHTSA NCAP). The NHTSA-Tools Fortran source documents the UDS spec thoroughly. Build as a reader plugin. `[ref: NHTSA-Tools]`
+- [ ] **P0 — ASAM MDF reader** — The standard for ECU/CAN bus measurement data. Many crash test labs record vehicle bus data alongside instrumentation in MDF format. asammdf is a mature, well-tested library. Add as an optional dependency like TDMS. `[lib: asammdf]`
+- [ ] **P1 — CSV/TSV flexible reader** — The current CSV reader is basic. Engineers frequently receive data as CSV exports from other tools with varying column layouts, header conventions, and delimiter styles. A flexible CSV reader with column mapping would cover many edge cases.
+
+### Medium-priority formats
+
+- [ ] **P1 — LS-DYNA binout/D3plot** — Simulation results for test-vs-CAE correlation. lasso-python is the maintained Python library for this. Enables overlay of physical test data with simulation predictions — a major workflow in automotive safety development. `[lib: lasso-python]`
+- [ ] **P2 — Abaqus ODB** — Another major FEA solver used in safety simulation.
+- [ ] **P2 — MADYMO** — Occupant simulation results (TNO format).
+
+### Data enrichment
+
+- [ ] **P1 — Channel aliasing** — Allow human-friendly aliases (e.g., `"head_ax" -> "11HEAD0000H3ACXP"`). Aliases stored in templates or user config. Especially useful for teams that have their own naming conventions.
+- [ ] **P1 — Channel metadata editor** — Non-destructive override for wrong units or missing metadata in `.chn` files. Overrides stored in the session's `.impakt/` folder.
+- [ ] **P1 — Auto-detect signal type from channel code** — Use the measurement code (AC, FO, MO, DC) to automatically suggest CFC class, axis labels, and unit handling. The lookup tables in `channel/lookup.py` already have this data.
+- [ ] **P2 — Batch loader** — `Session.open_batch("/tests/series_2024/")` loads an entire directory. Returns a `Series` object with cross-test operations (mean, overlay, delta).
+- [ ] **P2 — NHTSA open data integration** — Build a UDS-to-MME converter or direct UDS reader. The NCAP database Access DB contains summary results; contact NHTSA for time-history channel data access.
+
+---
 
 ## Signal Processing
 
-- [ ] **Frequency spectrum viewer** — FFT / power spectral density of a channel. Helps diagnose noise, identify resonant frequencies, and verify CFC filter behavior.
-- [ ] **Integration / differentiation** — Integrate acceleration to get velocity/displacement. Differentiate displacement to get velocity. Track cumulative units.
-- [ ] **Cross-correlation** — Find time lag between two channels. Useful for understanding signal propagation through the vehicle structure.
-- [ ] **Envelope detection** — Compute the signal envelope (Hilbert transform). Useful for identifying amplitude trends.
-- [ ] **Window functions** — Apply Hanning, Hamming, etc. for spectral analysis pre-processing.
-- [ ] **Savitzky-Golay filter** — Alternative to CFC for smoothing that better preserves peaks.
-- [ ] **Event detection** — Automatically detect impact events from acceleration signals (threshold crossing, change-point detection). Useful for multi-event tests.
-- [ ] **Signal quality metrics** — Detect clipping, saturation, dropout, or excessive noise. Flag channels with potential data quality issues.
+Currently: CFC filtering, alignment, resultant, trim, resample, math expressions. The landscape shows several gaps.
 
-## Injury Criteria & Protocols
+- [ ] **P1 — Integration / differentiation** — Integrate acceleration to get velocity/displacement. Differentiate displacement to get velocity. Track cumulative units (m/s² -> m/s -> m). Fundamental for kinematic analysis.
+- [ ] **P1 — Savitzky-Golay filter** — Alternative to CFC for smoothing that better preserves peaks. Useful when the SAE J211 Butterworth roll-off is too aggressive for a specific analysis.
+- [ ] **P1 — Event detection** — Automatically detect impact events from acceleration signals (threshold crossing, change-point detection). Useful for multi-event tests (primary impact + rebound).
+- [ ] **P2 — Cross-correlation** — Find time lag between two channels. Useful for understanding signal propagation through the vehicle structure.
+- [ ] **P2 — Envelope detection** — Hilbert transform for amplitude trends.
+- [ ] **P2 — Window functions** — Hanning, Hamming, etc. for spectral analysis pre-processing (depends on FFT viewer).
+- [ ] **P2 — Signal quality metrics** — Detect clipping, saturation, dropout, excessive noise. Flag channels with potential data quality issues. Display as badges in the channel grid.
 
-- [ ] **BrIC (Brain Injury Criterion)** — Rotational brain injury metric using angular velocity. Increasingly used in newer protocols.
-- [ ] **DAMAGE (Diffuse Axonal Multi-Axis General Evaluation)** — Related to BrIC, uses angular acceleration.
-- [ ] **SIMon / GHBMC coupling** — Interface with finite element head models for advanced brain injury assessment.
-- [ ] **Thorax Trauma Index (TTI)** — Side impact chest criterion.
-- [ ] **Abdominal Peak Force (APF)** — Abdomen criterion for side impact.
-- [ ] **Acetabular force** — Pelvis criterion for side impact (SID-IIs, WorldSID).
-- [ ] **Pedestrian criteria** — Head Impact Criterion for headform impactors, lower leg bending, upper leg force.
-- [ ] **Protocol version management UI** — Visual diff between protocol versions. Show what thresholds changed between e.g. Euro NCAP 2023 vs 2025.
-- [ ] **Custom protocol builder** — Let users define their own pass/fail criteria with custom thresholds. Useful for internal OEM targets that are stricter than regulation.
-- [ ] **Sensitivity analysis** — "What if" tool: how would the score change if HIC was 50 points lower? Slider-based interactive exploration.
-- [ ] **Regulatory compliance check** — Given a test, automatically check all applicable FMVSS / ECE regulation limits and flag any exceedances.
+---
 
-## Templates & Workflow
+## Injury Criteria & Protocol Scoring
 
-- [ ] **Template marketplace / sharing** — Allow teams to share templates. Git-based version control for template libraries. Team templates synced via a shared directory or Git repo.
-- [ ] **Template inheritance** — A template can extend another template. e.g., "My NCAP template" extends "Euro NCAP 2024" but adds custom corridors and extra plots.
-- [ ] **Channel auto-mapping** — When applying a template to a new test, auto-map channel patterns to actual available channels. Handle naming variations across test facilities.
-- [ ] **Template validation** — When a template references channel patterns, validate that the current test data has matching channels. Show warnings for missing channels.
-- [ ] **Quick comparison mode** — Two tests side-by-side with synchronized cursors. One-click "compare" from the template panel.
-- [ ] **Corridor management UI** — Visual editor for creating and editing tolerance corridors. Draw the envelope on a plot, export to CSV.
-- [ ] **Session history / undo** — Track a history of actions (transforms applied, cursors moved, channels added) with undo/redo.
+Currently: HIC15/36, 3ms clip, Nij, chest deflection, viscous criterion, femur load, tibia index. Euro NCAP, US NCAP, IIHS scoring. The landscape reveals several additional criteria in active use.
 
-## Reports
+### Cross-validation (leverage landscape research)
 
-- [ ] **Multi-page reports** — Combine multiple plots + injury summary + protocol rating into a single PDF with automatic table of contents.
-- [ ] **Configurable report branding** — Company logo, header/footer text, color scheme. Stored in user config.
-- [ ] **Excel export** — Export criteria results and cursor values to Excel, not just PDF. Engineers love spreadsheets.
-- [ ] **PowerPoint export** — Generate slides with one plot per slide. Common request in OEM environments.
-- [ ] **Automated report narration** — Generate natural-language summary paragraphs: "The head acceleration exceeded the Euro NCAP green threshold at t=0.032s, resulting in a yellow rating for the head region."
-- [ ] **Report templates gallery** — Pre-built templates for common submission formats (NHTSA compliance report, Euro NCAP submission, IIHS test report).
-- [ ] **Comparison reports** — Automatically generate a report comparing two or more tests, highlighting differences in criteria and ratings.
+- [ ] **P0 — Validate injury criteria against reference implementations** — Four independent implementations are now available for comparison: NHTSA-Tools (Fortran, authoritative), pyisomme (Python), PyAvia (CFC filter), and EPFL crash-tests-service-robots. Build a validation test suite that runs Impakt's criteria against these reference outputs for the same input data. `[ref: NHTSA-Tools, pyisomme, pyavia, crash-tests-service-robots]`
 
-## Integration & Automation
+### Additional criteria
 
-- [ ] **Jupyter notebook integration** — Impakt objects should display rich output in Jupyter (interactive Plotly plots, HTML tables). Consider `_repr_html_` on key objects.
-- [ ] **Watch mode** — Monitor a directory for new test data. When a new test appears (e.g., DAQ export completes), automatically apply a template and generate a report.
-- [ ] **CI/CD integration** — `impakt evaluate --protocol euro_ncap --exit-code` returns non-zero if any criterion fails. Useful for automated test validation pipelines.
-- [ ] **REST API mode** — Run Impakt as a server with a REST API for integration with other tools (CAE workflows, PLM systems).
-- [ ] **Pre/post-processing hooks** — User-defined Python functions that run before/after template application, criteria computation, or report generation. Part of the plugin system.
-- [ ] **CAE data import** — Read simulation results (LS-DYNA d3plot binodes, Abaqus ODB) so that test vs. simulation overlay is trivial.
-- [ ] **Video sync** — Link high-speed camera footage with channel data. Scrubbing the video moves the time cursor on plots, and vice versa.
+- [ ] **P1 — BrIC (Brain Injury Criterion)** — Rotational brain injury metric using angular velocity. Increasingly required in newer Euro NCAP protocols.
+- [ ] **P1 — DAMAGE** — Diffuse Axonal Multi-Axis General Evaluation. Related to BrIC, uses angular acceleration. pyisomme includes an implementation. `[ref: pyisomme]`
+- [ ] **P1 — Thorax Trauma Index (TTI)** — Side impact chest criterion. Required for US NCAP side impact.
+- [ ] **P1 — Pedestrian criteria** — Head Impact Criterion for headform impactors, lower leg bending, upper leg force. Required for Euro NCAP pedestrian rating.
+- [ ] **P2 — Abdominal Peak Force (APF)** — Abdomen criterion for side impact.
+- [ ] **P2 — Acetabular force** — Pelvis criterion for SID-IIs / WorldSID side impact.
+- [ ] **P2 — OLC (Occupant Load Criterion)** — Structural criterion used in Euro NCAP.
 
-## Performance & Scale
+### Protocol enhancements
 
-- [ ] **Memory-mapped data** — For very large datasets, use `numpy.memmap` to avoid loading everything into RAM.
-- [ ] **Channel cache** — Cache frequently-accessed transformed channels to avoid recomputing CFC filters every time.
-- [ ] **Parallel criteria computation** — Compute all injury criteria in parallel using `concurrent.futures`. The individual computations are independent.
-- [ ] **Web UI performance** — For 500-channel tests, the channel tree and dropdown become unwieldy. Implement virtualized scrolling and tree expansion.
-- [ ] **Progressive rendering** — Show plots immediately with low-resolution data, then refine with full-resolution data once loaded.
+- [ ] **P1 — Protocol version management UI** — Visual diff between protocol versions. Show what thresholds changed between e.g. Euro NCAP 2023 vs 2025. The YAML threshold files already version this data.
+- [ ] **P1 — Regulatory compliance check** — Given a test, automatically check all applicable FMVSS / ECE regulation limits. Flag exceedances with severity indicators.
+- [ ] **P2 — Custom protocol builder** — Let users define pass/fail criteria with custom thresholds. Useful for internal OEM targets stricter than regulation.
+- [ ] **P2 — Sensitivity analysis** — "What if" sliders: how would the score change if HIC was 50 points lower? Interactive exploration for design optimization.
+- [ ] **P2 — Additional NCAP programs** — J-NCAP (Japan), C-NCAP (China), K-NCAP (Korea), ANCAP (Australia), Latin NCAP. Each as a protocol plugin.
+
+---
 
 ## Data Quality & Validation
 
-- [ ] **Channel polarity check** — Verify SAE sign convention compliance. Detect if a channel appears to have inverted polarity (e.g., positive compression forces that should be negative).
-- [ ] **Sensor sanity checks** — Flag physically impossible values (e.g., head acceleration > 500g, negative femur tension during frontal impact).
-- [ ] **Inter-channel consistency** — Check that related channels are consistent (e.g., resultant acceleration is actually sqrt of sum of squares of components).
-- [ ] **Time sync verification** — Check that all channels have consistent timing (same sample rate, same trigger point, no time drift).
-- [ ] **Missing channel detection** — For a given protocol, check which required channels are missing from the test data and warn the user.
+No commercial competitor has strong automated data quality features. This is an opportunity to differentiate.
+
+- [ ] **P1 — Channel polarity check** — Verify SAE sign convention compliance. Detect inverted polarity (e.g., positive compression forces that should be negative per J211).
+- [ ] **P1 — Sensor sanity checks** — Flag physically impossible values (head acceleration > 500g, negative femur tension in frontal impact, displacement > 1m).
+- [ ] **P1 — Missing channel detection** — For a given protocol, check which required channels are missing from the test data. Show a completeness score before the user starts analysis.
+- [ ] **P2 — Inter-channel consistency** — Verify that resultant acceleration equals sqrt(sum of squares) of components. Detect disagreement between redundant sensors.
+- [ ] **P2 — Time sync verification** — Check that all channels have consistent timing (same trigger point, no drift between DAQ systems).
+- [ ] **P2 — Data quality dashboard** — Single-page overview showing pass/fail for each quality check across all channels. Color-coded. Exportable.
+
+---
+
+## Templates & Workflow
+
+The template system is one of Impakt's differentiators. Commercial tools (DIAdem, HyperGraph, Simcenter Testlab) all have template-driven workflows. Impakt should go further.
+
+- [ ] **P1 — Template inheritance** — A template can extend another. "My NCAP template" extends "Euro NCAP 2024" but adds custom corridors and extra plots.
+- [ ] **P1 — Channel auto-mapping** — When applying a template to a new test, auto-map channel patterns to actual available channels. Handle naming variations across test facilities (BASt vs. Calspan vs. Volkswagen conventions).
+- [ ] **P1 — Template validation** — When a template references channel patterns, validate that the current test data has matching channels. Show warnings for missing channels with suggested alternatives.
+- [ ] **P1 — Session history / undo** — Track a history of actions with undo/redo. Store in `.impakt/` session folder.
+- [ ] **P2 — Template sharing** — Git-based version control for template libraries. Team templates synced via shared directory or Git repo.
+- [ ] **P2 — Corridor management UI** — Visual editor for creating and editing tolerance corridors. Draw the envelope on a plot, export to CSV. Currently corridors are CSV-upload only.
+- [ ] **P2 — Structured corridor format** — Metadata-rich corridor files: source protocol, year, applicable dummy type, confidence level. Bundle official protocol corridors with the tool.
+
+---
+
+## Reports & Export
+
+Report generation is the final deliverable. This is where Impakt replaces hours of manual Excel/PowerPoint work.
+
+- [ ] **P0 — Multi-page reports** — Combine multiple plots + injury summary + protocol rating into a single PDF with automatic table of contents. Currently each report type is standalone.
+- [ ] **P1 — Excel export** — Export criteria results and cursor values to Excel, not just PDF/CSV. Engineers live in spreadsheets. Use openpyxl or xlsxwriter.
+- [ ] **P1 — PowerPoint export** — One plot per slide with metadata. Common request in OEM environments. pyisomme generates PowerPoint — confirms the demand. `[ref: pyisomme uses python-pptx]`
+- [ ] **P1 — Configurable report branding** — Company logo, header/footer, color scheme. Stored in `~/.impakt/brand.yaml`.
+- [ ] **P1 — Static HTML export** — Bundle all data and Plotly.js into a single self-contained HTML file. Opens in any browser without a Python server. Solves the "share with stakeholders" problem. Plotly's `write_html(include_plotlyjs=True)` does most of the work.
+- [ ] **P2 — Report templates gallery** — Pre-built templates for NHTSA compliance, Euro NCAP submission, IIHS test report formats.
+- [ ] **P2 — Comparison reports** — Automatically generate a report comparing two or more tests. Highlight differences in criteria and ratings.
+- [ ] **P2 — Automated narration** — Generate natural-language summary: "The head acceleration exceeded the Euro NCAP green threshold at t=0.032s, resulting in a yellow rating for the head region." Could leverage an LLM for nuanced interpretation.
+
+---
+
+## Video Synchronization
+
+Every major commercial competitor (measX, DIAdem, Kistler, FalCon) has video-signal sync. It's the most visible gap in Impakt vs. commercial tools. Engineers watch high-speed camera footage frame-by-frame alongside the data.
+
+- [ ] **P0 — Video playback linked to time axis** — Load an MP4/AVI alongside test data. Scrubbing the video moves the cursor on plots, and moving the cursor on plots seeks the video. The time offset between video start and DAQ trigger is configurable.
+- [ ] **P1 — Multiple camera views** — Crash tests typically have 4-8 high-speed cameras (frontal, side, overhead, onboard). Support tiled video views synced to the same timeline.
+- [ ] **P2 — Frame annotation** — Mark specific frames with notes (e.g., "airbag deployment", "head contact with steering wheel"). Export annotated frames.
+
+Implementation notes: Foxglove and Rerun both demonstrate web-native signal+video sync. Dash can embed HTML5 `<video>` elements. The main challenge is sub-millisecond sync at high-speed camera frame rates (1000-10000 fps). A lightweight approach: decode video server-side with OpenCV, serve frames as images synced to the Dash callback timestamp. A heavier approach: WebCodecs API for client-side decoding.
+
+---
+
+## Integration & Automation
+
+- [ ] **P0 — Jupyter notebook integration** — `Session`, `Channel`, and `ProtocolResult` objects should display rich output in Jupyter (`_repr_html_` with interactive Plotly plots, HTML tables). This makes Impakt a first-class citizen in the data science workflow.
+- [ ] **P1 — CI/CD integration** — `impakt evaluate --protocol euro_ncap --exit-code` returns non-zero if any criterion fails. Useful for automated test validation in manufacturing pipelines.
+- [ ] **P1 — Watch mode** — Monitor a directory for new test data. When a new test appears (DAQ export complete), auto-apply a template and generate a report. Valuable for high-throughput sled test labs.
+- [ ] **P1 — REST API mode** — Run Impakt as a server with a REST API. Enables integration with PLM systems, CAE workflows, and custom dashboards.
+- [ ] **P2 — Pre/post-processing hooks** — User-defined Python functions that run before/after template application, criteria computation, or report generation.
+- [ ] **P2 — Real-time collaboration** — WebSocket-based sync of cursor positions, channel selections, and annotations. "Presenter mode" for post-test review sessions where one engineer drives.
+
+---
 
 ## User Experience
 
-- [ ] **Keyboard shortcuts** — `Ctrl+1` through `Ctrl+9` for quick channel groups. `Space` to toggle play/pause on animation. `R` to reset zoom.
-- [ ] **Right-click context menus** — Right-click on a channel in the tree to apply common transforms, compute criteria, or export data.
-- [ ] **Drag-and-drop** — Drag channels from the tree onto the plot area. Drag a test directory onto the app to open it.
-- [ ] **Recent files** — Remember recently opened tests for quick access.
-- [ ] **Bookmarks** — Save specific views (channel selection + zoom range + cursors) as named bookmarks within a session.
-- [ ] **Multi-window** — Open multiple test sessions in separate browser tabs, synchronized or independent.
-- [ ] **Guided analysis wizards** — Step-by-step guided workflows: "Run frontal NCAP analysis" walks the user through channel selection, filtering, criteria computation, and report generation.
-- [ ] **Tooltip glossary** — Hover over terms like "HIC15", "CFC 180", "Nij" to see a brief explanation. Aids learning for junior engineers.
-
-## Plugin Ideas
-
-- [ ] **impakt-dicom** — Import DICOM medical imaging data for correlation with dummy injury metrics.
-- [ ] **impakt-catia** — Link to CATIA vehicle models for 3D visualization of sensor locations.
-- [ ] **impakt-abaqus** — Import Abaqus simulation results.
-- [ ] **impakt-lsdyna** — Import LS-DYNA simulation results (binout, d3plot).
-- [ ] **impakt-madymo** — Import MADYMO occupant simulation results.
-- [ ] **impakt-jncap** — Japanese NCAP scoring protocol.
-- [ ] **impakt-cncap** — Chinese NCAP scoring protocol.
-- [ ] **impakt-kncap** — Korean NCAP scoring protocol.
-- [ ] **impakt-ancap** — Australian NCAP scoring protocol.
-- [ ] **impakt-latinncap** — Latin NCAP scoring protocol.
+- [ ] **P1 — Keyboard shortcuts** — `Ctrl+1..9` for channel groups. `Space` for play/pause animation. `R` to reset zoom. `F` for fullscreen plot. `/` for channel search focus. These are expected in professional tools.
+- [ ] **P1 — Drag-and-drop** — Drag channels from the grid onto the plot area. Drag a test directory onto the app to open it.
+- [ ] **P1 — Right-click context menus** — Right-click on a channel to apply transforms, compute criteria, or export.
+- [ ] **P1 — Recent files** — Remember recently opened tests for quick access from the landing page.
+- [ ] **P1 — Tooltip glossary** — Hover over "HIC15", "CFC 180", "Nij" to see a brief explanation. Aids learning for junior engineers and non-specialists reviewing results.
+- [ ] **P2 — Guided analysis wizards** — Step-by-step workflows: "Run frontal NCAP analysis" walks through channel selection, filtering, criteria computation, and report generation.
+- [ ] **P2 — Bookmarks** — Save specific views (channel selection + zoom + cursors) as named bookmarks within a session.
+- [ ] **P2 — Multi-window** — Open multiple test sessions in separate browser tabs, optionally synchronized.
+- [ ] **P2 — Synthetic data generator API** — Expose `tests/fixtures/generate_mme.py` as `impakt.synth` for users prototyping templates without real test data.
 
 ---
 
 ## Architecture Notes
 
-### Transform Pipeline Composition
+### Transform pipeline
 
-Currently transforms are a flat chain. Consider a DAG-based pipeline for more complex workflows where a channel needs to be both filtered and unfiltered, with the resultant computed from filtered components but cursor values shown on unfiltered data.
+Currently transforms are a flat chain. Consider a DAG-based pipeline where a channel can be both filtered and unfiltered, with the resultant computed from filtered components but cursor values shown on unfiltered data. This matters when engineers want to see the effect of filtering without losing the original signal context.
 
-### Real-time Collaboration
+### Static HTML export as a distribution format
 
-Multiple engineers often need to look at the same test data simultaneously during post-test review sessions. Consider WebSocket-based real-time sync of cursor positions, channel selections, and annotations. A "presenter mode" where one engineer drives and others follow.
+Learned from FalCon's CustomerView model: OEMs need to share test results with recipients who don't have the analysis software installed. A self-contained HTML file with embedded Plotly.js, data, and interactive plots solves this without requiring a Python server or license.
 
-### Offline Mode
+### CFC filter implementation verification
 
-The web UI requires a running Python server. For situations where engineers need to share results with non-technical stakeholders, consider an "export to static HTML" mode that bundles all data and Plotly.js into a single self-contained HTML file that can be opened in any browser.
+PyAvia's author notes that for CFC 180 and 60, the SAE J211 Appendix C digital Butterworth algorithm should be used rather than scipy's generic `sosfiltfilt`. Impakt's current implementation uses scipy. This should be verified by comparing output against PyAvia's `J211_2pole` and NHTSA-Tools' `BwFilt` Fortran implementation for the same input signals.
 
-### Standardization of Corridor Files
+### Multi-rate data architecture
 
-Corridors currently use a simple CSV format. Consider adopting or defining a more structured format that includes metadata (source protocol, year, applicable dummy type, confidence level). Corridors from official protocol documents could be bundled with the tool.
+Rerun's time-aware database handles channels sampled at different rates natively. Crash tests mix channels at 10kHz (accelerometers), 1kHz (displacement), and 100Hz (vehicle bus). Currently Impakt resamples to a common rate. A multi-rate architecture would be more accurate and memory-efficient.
+
+### Corridor standardization
+
+Corridors currently use simple CSV (time, lower, upper). Consider a structured format with metadata: source protocol, year, applicable dummy type, confidence level, units. Bundle official corridors from published protocol documents. NHTSA and Euro NCAP both publish reference corridors.
+
+### Test-vs-simulation correlation
+
+With lasso-python enabling LS-DYNA data import, the natural workflow becomes: load physical test + simulation, overlay the same channels, compute correlation metrics (CORA, ISO/TS 18571 rating). This is a premium feature in commercial tools (Altair HyperGraph, Siemens Simcenter) and a strong differentiator for an open-source tool.
+
+---
+
+## Plugin Ideas
+
+- [ ] **impakt-lsdyna** — LS-DYNA binout/D3plot import `[lib: lasso-python]`
+- [ ] **impakt-mdf** — ASAM MDF v2/v3/v4 import `[lib: asammdf]`
+- [ ] **impakt-uds** — NHTSA UDS format reader `[ref: NHTSA-Tools]`
+- [ ] **impakt-abaqus** — Abaqus ODB import
+- [ ] **impakt-madymo** — MADYMO occupant simulation results
+- [ ] **impakt-dicom** — DICOM medical imaging for injury correlation
+- [ ] **impakt-jncap** — Japanese NCAP scoring
+- [ ] **impakt-cncap** — Chinese NCAP scoring
+- [ ] **impakt-kncap** — Korean NCAP scoring
+- [ ] **impakt-ancap** — Australian NCAP scoring
+- [ ] **impakt-latinncap** — Latin NCAP scoring
+- [ ] **impakt-cora** — ISO/TS 18571 cross-correlation for test-vs-simulation rating