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Layered Configs

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noisedestroyers
2026-04-11 15:20:27 -04:00
parent a7625dc973
commit 08e33f083a
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README.md
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docs/STATUS.md
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**Date:** 2026-04-11
**Version:** 0.1.0
**Tests:** 240 passing (69.7% coverage)
**Source:** ~10,300 lines (py) | ~2,700 lines tests
**Quality:** 78.3/100 (Grade B) -- see `docs/QA-*.md`
**Tests:** 258 passing (70.4% coverage)
**Quality:** 83.7/100 (Grade B+) -- see `docs/QA-*.md`
**Tooling:** uv (Python 3.12.12), hatchling build backend, ruff, mypy strict
---
@@ -14,7 +13,7 @@
```bash
cd /Users/noise/Code/impakt
uv sync --dev # install all dependencies
uv run pytest tests/ # run all 240 tests (with coverage)
uv run pytest tests/ # run all 258 tests (with coverage)
uv run impakt info tests/mme_data/3239 # show test metadata
uv run impakt serve tests/mme_data/3239 # launch web UI on :8050
```
@@ -23,7 +22,8 @@ Scripting:
```python
from impakt import Session
s = Session.open("tests/mme_data/3239")
s.plot("11HEAD0000H3ACXP", "11HEAD0000H3ACYP", "11HEAD0000H3ACZP", cfc=1000)
result = s.evaluate("euro_ncap")
print(result.summary())
```
---
@@ -35,12 +35,21 @@ impakt/
pyproject.toml # PEP 621 + uv dependency-groups
uv.lock # lockfile
.gitignore
README.md # Architecture docs with 16 Mermaid diagrams
README.md # Architecture docs with Mermaid diagrams
BRAINSTORM.md # 80+ feature ideas
docs/
STATUS.md # <-- you are here
QA-*.md # Quality assessment scorecards
research/
landscape.md # Competitive landscape (15+ tools)
src/impakt/
__init__.py # exports Session, Template
config/ # Layered YAML configuration
__init__.py # exports Config
model.py # Config class, typed sections, deep merge, save/load
defaults/ # Package-level defaults (shipped with install)
config.yaml # All configurable fields, commented
protocols/ # Euro NCAP + IIHS threshold YAMLs
channel/ # Data model layer
code.py # ISO channel code parser (14-char + 16-char auto-detect)
model.py # Channel, ChannelGroup, TestData, TestMetadata
@@ -48,13 +57,15 @@ impakt/
lookup.py # ISO naming lookup tables (150+ entries)
io/ # I/O layer
reader.py # ReaderProtocol, ReaderRegistry
mme.py # MMEReader (real ISO 13499 + synthetic INI)
mme.py # MMEReader (real ISO 13499 + simplified INI)
tdms.py # TDMSReader (stub)
csv.py # CSVReader (stub)
transform/ # Signal processing
base.py # Transform protocol, TransformChain
base.py # Transform protocol, TransformChain (serializable)
cfc.py # SAE J211 CFC filter (60/180/600/1000)
align.py # X-align (time-zero), Y-align (offset)
resultant.py # Vector magnitude from X/Y/Z
math_expr.py # Free-form math expressions
math_expr.py # Free-form math expressions (safe eval)
resample.py # Trim, Resample
criteria/ # Injury criteria
base.py # CriterionResult, InjuryCriterion protocol
@@ -64,15 +75,16 @@ impakt/
chest.py # Chest deflection, Viscous criterion
femur.py # Femur load
tibia.py # Tibia index
protocol/ # Rating protocols
protocol/ # Rating protocols (YAML thresholds)
base.py # ProtocolResult, BodyRegionScore, Color, Rating
euro_ncap.py # Euro NCAP (color/points/stars, versioned)
us_ncap.py # US NCAP (injury probability/stars)
iihs.py # IIHS (G/A/M/P)
plot/ # Visualization engine
engine.py # PlotEngine (Plotly), cursor_values()
spec.py # PlotSpec, ChannelRef, Corridor, CursorValues
cursor.py # Dual X-cursor logic
euro_ncap.py # Euro NCAP (loads thresholds from YAML, fallback to Python)
us_ncap.py # US NCAP (logistic injury risk)
iihs.py # IIHS (loads thresholds from YAML)
thresholds/ # Versioned YAML threshold files
plot/ # Visualization engine (single rendering path)
engine.py # PlotEngine: render(PlotSpec), resample, focus
spec.py # PlotSpec, ChannelRef, Corridor, focus_index
cursor.py # Cursor value computation
export.py # PNG/SVG/PDF/HTML export
template/ # Templates & sessions
model.py # TemplateSpec, SessionState (YAML serializable)
@@ -80,246 +92,135 @@ impakt/
session.py # SessionManager (.impakt/ per test)
report/ # Report generation
engine.py # PDF/HTML via WeasyPrint + Jinja2
templates/ # 3 Jinja2 HTML templates
plot_sheet.html
injury_summary.html
protocol_report.html
templates/ # 3 Jinja2 HTML report templates
web/ # Dash web application
app.py # App factory: create_app(), serve()
state.py # AppState: multi-test state, templates, sessions, corridors
layout.py # Top-level layout: Data tab + Analysis tab
components/ # Reusable layout components
state.py # AppState: holds Sessions, Config, resampler state
layout.py # Two-tab layout: Data + Analysis
components/ # 10 reusable layout components
header.py # Navbar, test info panel, open/overlay modals
channel_grid.py # Flat sortable DataTable with wildcard filter + facets
channel_values.py # Combined cursor + statistics table (live hover values)
transforms.py # CFC/align/resultant controls + per-channel overrides
plot_grid.py # Multi-pane plot area (1x1, 2x1, 1x2, 2x2, 3x1)
criteria.py # Auto-compute criteria, protocol scoring, results display
channel_values.py # Combined statistics + cursor table
transforms.py # CFC/align/resultant + per-channel overrides
plot_grid.py # Multi-pane plot area (1x1 through 3x1)
criteria.py # Auto-compute criteria, protocol scoring display
corridors.py # Corridor upload (CSV) and management
templates.py # Template library browser, save/apply/delete
math_builder.py # Math expression builder with variable binding
report.py # Export panel (PNG/SVG/PDF, CSV, protocol report)
callbacks/ # Feature-specific callback modules
__init__.py # Registration hub: register_callbacks()
report.py # Export panel (CSV, PNG/SVG/PDF, protocol report)
callbacks/ # 9 feature-specific callback modules
channel_callbacks.py # Selection, filtering, badges, per-channel overrides
plot_callbacks.py # Plot rendering, transform pipeline, corridor display
plot_callbacks.py # PlotSpec construction → PlotEngine rendering
cursor_callbacks.py # Channel values table (live hover + X1/X2)
criteria_callbacks.py # Compute All button, protocol scoring
criteria_callbacks.py # Session.compute_criteria() + Session.evaluate()
template_callbacks.py # Apply/save/delete templates, session auto-save
corridor_callbacks.py # CSV upload, corridor state management
corridor_callbacks.py # CSV upload, corridor state
math_callbacks.py # Expression evaluation, derived channel injection
file_callbacks.py # Open test / add overlay modals
export_callbacks.py # CSV export, report generation
assets/ # Browser-side static files
style.css # Custom CSS (compact layout, splitter, scrollbars)
splitter.js # Draggable panel splitter (pure JS, no deps)
cursor_tracker.js # Live cursor tracking (mousemove -> pixel-to-data-X)
style.css # Custom CSS
splitter.js # Draggable panel splitter
cursor_tracker.js # Live cursor tracking (mousemove → data coords)
channel_nav.js # Keyboard navigation for channel grid
plugin/ # Plugin system
registry.py # PluginRegistry, discovery (entrypoints + dir)
registry.py # PluginRegistry, discovery, reader forwarding
script/ # Scripting API + CLI
api.py # Session, ChannelHandle, TransformProxy, Template
api.py # Session (with Config), ChannelHandle, TransformProxy, Template
cli.py # argparse CLI (serve/info/channels/evaluate)
tests/
conftest.py # Synthetic channel fixtures
test_integration.py # Full pipeline against synthetic MME fixture
test_config.py # Config layered resolution, save/load, round-trip
test_integration.py # Full pipeline against synthetic fixture
test_real_mme.py # 46 tests against 5 real ISO 13499 datasets
test_channel/ # ChannelCode parser, Channel model, TestData
test_criteria/ # HIC, Nij
test_scripting_api.py # Session, fluent chaining, compute_criteria, evaluate
test_template.py # Template YAML round-trip, library CRUD, session manager
test_channel/ # ChannelCode parser, Channel model
test_criteria/ # HIC, Nij, chest/femur/tibia/clip3ms/viscous
test_io/ # MMEReader
test_protocol/ # Euro NCAP scoring
test_transform/ # CFC filter, alignment
test_plot/ # PlotEngine rendering (channels, corridors, focus, compact)
test_protocol/ # Euro NCAP, US NCAP, IIHS scoring
test_transform/ # CFC, alignment, math expressions, resultant, trim, resample
test_web/ # AppState, app creation, channel grid, channel values, P2 features
fixtures/
generate_mme.py # Synthetic MME generator (26 channels, half-sine)
sample_mme/ # Generated synthetic test data
generate_mme.py # Synthetic MME generator (26 channels)
sample_mme/ # Generated fixture data
mme_data/ # REAL ISO 13499 test data (5 datasets)
3239/ # NHTSA/Calspan, VW Passat frontal, 133 channels
AK3T02FO/ # BASt, frontal 40% offset, 97 channels
AK3T02SI/ # BASt, side impact, 97 channels
VW1FGS15/ # Volkswagen, pedestrian headform, 10 channels
98_7707/ # UTAC, vehicle-to-vehicle (metadata only)
*.pdf, *.doc # ISO/TS 13499 reference documents
```
---
## What Works
## What's Implemented
### All modules fully implemented and tested:
| Module | Status | Notes |
|---|---|---|
| **Channel code parser** | Complete | Auto-detects 14-char (no dummy) vs 16-char (with dummy H3/P3/PC). |
| **Channel model** | Complete | Immutable channels, auto-grouping X/Y/Z, resultant computation. |
| **MME reader** | Complete | Real ISO 13499 (.mme + .chn index + .NNN data files) + simplified INI. Tested against 5 real datasets. |
| **CFC filtering** | Complete | SAE J211 compliant. 4th-order Butterworth, zero-phase. All 4 CFC classes. |
| **Alignment transforms** | Complete | X-align (manual/threshold/trigger), Y-align (baseline window). |
| **Resultant** | Complete | From ChannelGroup or arbitrary channels. |
| **Math expressions** | Complete | Safe eval with numpy functions. |
| **HIC** | Complete | HIC15/HIC36, cumulative integration, optimal window search. |
| **3ms clip** | Complete | Cumulative exceedance method. |
| **Nij** | Complete | 4 modes (NTE/NTF/NCE/NCF), per-dummy intercepts. |
| **Chest deflection** | Complete | Peak sternal displacement with unit/sanity validation. |
| **Viscous criterion** | Complete | V(t)*C(t) with chest depth per dummy type. |
| **Femur load** | Complete | Left/right, unit conversion. |
| **Tibia index** | Complete | M/Mc + F/Fc with intercepts. |
| **Euro NCAP** | Complete | Sliding-scale color/points, percentage to stars. Versioned thresholds. |
| **US NCAP** | Complete | Logistic injury risk functions, combined probability, star rating. |
| **IIHS** | Complete | G/A/M/P per body region, worst-case overall. |
| **Plot engine** | Complete | Plotly rendering, corridors, cursor values, export. |
| **Template model** | Complete | YAML serialize/deserialize, library manager, session persistence. |
| **Report engine** | Complete | HTML+WeasyPrint PDF, 3 Jinja2 templates. |
| **Plugin registry** | Complete | Entry point + directory + API discovery. |
| **CLI** | Complete | `impakt serve/info/channels/evaluate`. |
| **Web UI** | **Functional** | See details below. |
### Web UI -- Current State
Fully functional for daily crash test analysis:
**Data Tab:**
- **Left panel** (resizable via draggable splitter): channel grid + transform controls
- **Channel grid**: flat sortable DataTable (#, ISO Code, Description, Unit, Min, Max), wildcard filter bar, facet dropdowns (body region, measurement, direction), multi-select with selection persisted across filtering, selected rows colored with plot trace colors (tinted background + left border)
- **Transform controls**: global CFC filter, Y-align, X-align (manual/threshold), resultant toggle, per-channel CFC overrides
- **Plot area** (fills remaining width): no legend (info in tables), tight margins, compact axis labels, X1/X2 vertical reference lines
- **Channel Values table** (directly below plot, minimal gap): combined statistics + cursor in one table. Columns: #, ISO Code, Description, Unit, Min, @Time, Max, @Time, X1, X2, Cursor. `table-layout: fixed` with percentage widths — Description fills remaining space. Rows colored with same plot trace colors. Cursor column updates live on mouse hover via custom JS tracker.
**Analysis Tab:**
- **Injury Criteria**: auto-detect channels by ISO naming, compute HIC15/3ms clip/Nij/chest defl/femur/tibia, protocol scoring (Euro NCAP/US NCAP/IIHS) with color-coded results and star ratings
- **Math Expression Builder**: formula input, 3 variable bindings (a/b/c mapped to channel dropdowns), result injected into test data and auto-plotted
- **Template Management**: library browser, apply (resolves channel patterns + sets CFC), save current view as template, delete, session auto-save
- **Corridors**: CSV upload (time/lower/upper), rendered as filled band on plot
- **Export**: CSV of plotted data (with transforms), PNG/SVG/PDF buttons, protocol report generation
**Consistent Color System:**
Every selected channel has a stable color index (position in selection order). The same color appears in:
- Plot traces
- Channel grid rows (tinted background + solid left border)
- Selected badges (colored dot)
- Channel Values table rows (tinted background + solid left border)
### Key design decisions:
1. **Immutable channels** -- transforms return new Channel objects; raw data never modified.
2. **`.impakt/` subfolder** -- session state stored alongside test data.
3. **Template/session split** -- templates are global recipes; sessions are per-test instances.
4. **AppState is server-side** -- numpy arrays stay in Python memory; Dash stores hold only lightweight keys.
5. **Channel keys use `test_id::channel_name`** -- enables multi-test overlay.
6. **Custom JS cursor tracking** -- bypasses Plotly's hover system with raw mousemove + pixel-to-data conversion.
7. **table-layout: fixed** on Channel Values -- percentage widths respected, Description column fills remaining space.
8. **Browser cache prevention** -- meta tags with Cache-Control: no-cache to prevent stale layout issues during development.
9. **Separate single-output callbacks** for DataTable properties -- avoids Dash KeyError when DataTable internally requests individual properties.
| Module | Status |
|---|---|
| Channel code parser | Complete — 14/16-char auto-detect, 150+ ISO codes |
| MME reader | Complete — real ISO 13499 + simplified INI, 5 real datasets |
| CFC filtering | Complete — SAE J211, all 4 classes |
| Alignment | Complete — X-align (manual/threshold/trigger), Y-align |
| Resultant | Complete — from groups or arbitrary channels |
| Math expressions | Complete — safe eval with numpy |
| HIC, 3ms clip, Nij, chest, femur, tibia, viscous | All complete |
| Euro NCAP, US NCAP, IIHS | Complete — YAML thresholds, versioned |
| PlotEngine | Complete — single rendering path, resampler, focus, corridors |
| Templates | Complete — YAML, library, save/apply/delete |
| Sessions | Complete — `.impakt/` persistence, auto-save |
| Configuration | Complete — 3-layer YAML, typed sections, save/load |
| Plugin system | Complete — entry points, directory, API discovery, reader forwarding |
| CLI | Complete — serve/info/channels/evaluate |
| Web UI | Functional — two tabs, channel grid, cursor tracking, criteria, templates, export |
---
## Roadmap
## Key Design Decisions
Informed by competitive landscape survey (`research/landscape.md`). No open-source web-based tool covers this domain end-to-end. See `BRAINSTORM.md` for full feature ideas with priority tiers.
### Priority 3 — Performance & Rendering
Goal: handle large datasets (500+ channels, 100kHz sample rates) without lag.
1. **plotly-resampler integration** -- Drop-in `FigureResampler` wrapper for Plotly figures. Handles 110M+ points via LTTB downsampling. Works natively with Dash. Repo cloned at `research/repos/plotly-resampler/`. This is the single highest-impact performance improvement.
2. **Synchronized zoom/pan** -- When plotting multiple subplots, zoom/pan syncs across all panes sharing an X axis. Most-requested feature in crash test visualization. Implement via shared `xaxis` config or callback-based range sync.
3. **Lazy channel loading** -- Load `.dat` files on first access, not at `Session.open()`. Load headers eagerly, data lazily. Keeps startup fast for tests with 500+ channels.
4. **Channel sparklines** -- Tiny inline sparklines in the channel grid sidebar. Engineers visually scan 100+ channels before selecting. A 60px-wide sparkline column is transformative for signal browsing.
### Priority 4 — Data Format Expansion
Goal: read the world's crash test data, not just ISO MME.
5. **UDS reader plugin** -- NHTSA's proprietary binary format. Required to access the largest public crash test database. The NHTSA-Tools Fortran source (`research/repos/NHTSA-Tools/`) documents the UDS spec.
6. **ASAM MDF reader plugin** -- Standard for ECU/CAN bus measurement data. Many labs record vehicle bus data alongside crash instrumentation. asammdf (`research/repos/asammdf/`) is a mature library — add as optional dependency.
7. **Flexible CSV reader** -- Column mapping, delimiter detection, header conventions. Engineers frequently receive data as CSV exports from other tools.
### Priority 5 — Comparison & Reporting
Goal: make multi-test comparison and deliverable generation effortless.
8. **Quick comparison mode** -- Two tests side-by-side with synchronized cursors. One-click "compare" button. Color-by-test with channel differentiation via line dash.
9. **Multi-page PDF reports** -- Combine plots + injury summary + protocol rating into a single PDF with table of contents. Currently each report type is standalone.
10. **Excel export** -- Criteria results and cursor values to .xlsx. Engineers live in spreadsheets.
11. **Static HTML export** -- Bundle data + Plotly.js into a self-contained HTML file. Opens in any browser without a Python server. Learned from FalCon's CustomerView distribution model.
### Priority 6 — Video & Advanced Analysis
Goal: close the biggest remaining gap vs. commercial tools.
12. **Video synchronization** -- Link high-speed camera footage with channel data. Scrubbing video moves the time cursor; moving the cursor seeks the video. Every major commercial competitor (measX, DIAdem, Kistler, FalCon) has this. Foxglove and Rerun demonstrate web-native approaches.
13. **Frequency spectrum viewer** -- FFT / PSD alongside time-domain plots. Diagnose noise, verify CFC filter behavior.
14. **Integration / differentiation transforms** -- Acceleration -> velocity -> displacement with cumulative unit tracking.
15. **Data quality dashboard** -- Automated polarity check, sensor sanity, missing channel detection, completeness scoring. No commercial competitor is strong here — opportunity to differentiate.
### Priority 7 — Simulation Correlation & Ecosystem
Goal: bridge the gap between physical test and CAE simulation.
16. **LS-DYNA data import** via lasso-python (`research/repos/lasso-python/`). Enables test-vs-simulation overlay — a premium feature in Altair HyperGraph and Siemens Simcenter.
17. **ISO/TS 18571 CORA correlation** -- Quantitative rating of test-vs-simulation agreement. Standard metric for model validation.
18. **Additional injury criteria** -- BrIC, DAMAGE, TTI, pedestrian criteria, OLC. Required for broader Euro NCAP coverage.
19. **Additional NCAP programs** -- J-NCAP, C-NCAP, K-NCAP, ANCAP, Latin NCAP as protocol plugins.
20. **Jupyter integration** -- `_repr_html_` on Session, Channel, ProtocolResult for rich notebook output.
### Validation (ongoing)
- **Cross-validate CFC filter** against PyAvia's J211_2pole (`research/repos/pyavia/`) and NHTSA-Tools' BwFilt. PyAvia's author notes that scipy's generic `sosfiltfilt` may differ from the SAE J211 Appendix C digital Butterworth algorithm for CFC 60 and 180.
- **Cross-validate injury criteria** against NHTSA-Tools Fortran reference implementations, pyisomme, and EPFL crash-tests-service-robots. Four independent codebases available in `research/repos/`.
1. **Immutable channels** — transforms return new Channel objects
2. **`.impakt/` subfolder** — session state + config alongside test data
3. **3-layer config** — package defaults → user → session (YAML)
4. **AppState holds Sessions** — web UI routes through the scripting API
5. **PlotEngine is the single rendering path** — both scripts and web build PlotSpec
6. **TransformChain used in web layer** — serializable, reproducible pipelines
7. **Custom JS cursor tracking** — mousemove + Plotly axis p2d for full-area coverage
8. **Protocol thresholds in YAML** — user-editable, copied to session on save
9. **Plugin readers forwarded to IO registry** — discoverable by Session.open()
---
## Test Data Available
## Next Steps
| Dataset | Lab | Type | Channels | Good for testing |
|---|---|---|---|---|
| `fixtures/sample_mme/` | Synthetic | Frontal barrier | 26 | Unit tests, known values |
| `mme_data/3239/` | NHTSA/Calspan | Frontal barrier (VW Passat) | 133 | Full pipeline, real data |
| `mme_data/AK3T02FO/` | BASt | Frontal 40% offset | 97 | Multi-occupant |
| `mme_data/AK3T02SI/` | BASt | Side impact | 97 | Side impact protocols |
| `mme_data/VW1FGS15/` | Volkswagen | Pedestrian headform | 10 | Impactor codes (D0) |
| `mme_data/98_7707/` | UTAC | Vehicle-to-vehicle | 0 | Metadata-only |
**Priority 3 features:**
1. Annotations — text on plots, measurement lines, highlight regions
2. Comparison mode — delta channels, side-by-side tests, synced cursors
3. Report builder — template-based multi-page PDF composition
4. Keyboard shortcuts — Ctrl+O, Ctrl+S, R reset zoom, C cursor lock
**Quality targets:**
- Test coverage: 70% → 80%
- mypy errors: 34 → <10
- Files >300 lines: 8 → ≤5
---
## Test Data
| Dataset | Lab | Type | Channels |
|---|---|---|---|
| `fixtures/sample_mme/` | Synthetic | Frontal barrier | 26 |
| `mme_data/3239/` | NHTSA/Calspan | Frontal barrier (VW Passat) | 133 |
| `mme_data/AK3T02FO/` | BASt | Frontal 40% offset | 97 |
| `mme_data/AK3T02SI/` | BASt | Side impact | 97 |
| `mme_data/VW1FGS15/` | Volkswagen | Pedestrian headform | 10 |
| `mme_data/98_7707/` | UTAC | Vehicle-to-vehicle | 0 (metadata only) |
---
## Dependencies
Core: numpy, scipy, plotly, dash, dash-bootstrap-components, pandas, pyyaml, jinja2, weasyprint, pydantic
Core: numpy, scipy, plotly, plotly-resampler, dash, dash-bootstrap-components, pandas, pyyaml, jinja2, weasyprint, pydantic, pytz
Dev: pytest, pytest-cov, ruff, mypy
Optional: nptdms (TDMS reader plugin)
Planned: plotly-resampler (P3), asammdf (P4), openpyxl (P5), lasso-python (P7)
---
## Known Issues / Technical Debt
1. **VehicleInfo.year parsed as 0** for real MME data (.mme format embeds year in vehicle name string).
2. **Speed displayed as raw float** (55.900001530350906 km/h) -- should round.
3. **DataTable deprecation warning** -- Dash recommends migrating to dash-ag-grid.
4. **Cursor poll interval (80ms)** -- slight latency in cursor grid updates.
5. **Chest deflection auto-detect** skips DS channels with peak > 150mm to avoid steering column displacement.
6. **CFC filter implementation** uses scipy `sosfiltfilt` which may diverge from SAE J211 Appendix C for CFC 60/180. Needs cross-validation against PyAvia and NHTSA-Tools reference implementations.
---
## Quality Assurance
Automated QA scoring is configured:
- **Scoring agent:** `.claude/agents/quality-scorer.md` -- collects metrics, applies rubrics, writes report
- **Improvement agent:** `.claude/agents/qa-improver.md` -- reads QA report, auto-fixes mechanical issues
- **Methodology:** `docs/QA-INSTRUCTIONS.md` -- reproducible 8-dimension rubric
- **Reports:** `docs/QA-*.md` -- timestamped scorecards with deltas
- **Scripts:** `scripts/qa-score.sh` (score only), `scripts/qa-improve.sh` (score -> fix -> re-score)
---
## Competitive Landscape
Full survey at `research/landscape.md` with 11 cloned open-source repos in `research/repos/`.
**Key finding:** No existing tool combines open-source + web-based + ISO-MME + CFC + injury criteria + protocol scoring + templates + reports. Commercial tools (measX X-Crash, NI DIAdem, Kistler) do this but are expensive and Windows-only. Impakt occupies a genuinely unserved niche.
**Most actionable libraries:**
- plotly-resampler (performance) -- `research/repos/plotly-resampler/`
- asammdf (MDF format) -- `research/repos/asammdf/`
- lasso-python (LS-DYNA) -- `research/repos/lasso-python/`
- PyAvia, NHTSA-Tools (validation) -- `research/repos/pyavia/`, `research/repos/NHTSA-Tools/`

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src/impakt/config/__init__.py Normal file
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"""Layered configuration system for Impakt.
Configuration is resolved in three layers (most specific wins):
1. **Package defaults** — shipped with Impakt in ``src/impakt/defaults/``
2. **User defaults** — ``~/.impakt/config.yaml``
3. **Test session** — ``<test_dir>/.impakt/config.yaml``
Usage::
from impakt.config import Config
# Load with all layers
config = Config.load()
# Load for a specific test session
config = Config.load(session_path=Path("tests/mme_data/3239"))
# Access values
config.plot.colors # list of hex color strings
config.transforms.default_cfc # int or None
config.protocols.default # "euro_ncap"
# Override and save to user level
config.plot.line_width = 2.0
config.save_user()
# Save current state as session config
config.save_session(Path("tests/mme_data/3239"))
"""
from impakt.config.model import Config
__all__ = ["Config"]

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src/impakt/config/model.py Normal file
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"""Configuration model with layered YAML resolution.
The Config class loads YAML configuration files from three locations
and merges them (deep merge, most specific wins):
Package defaults → User defaults → Test session
All fields have sensible defaults defined in the package's
``defaults/config.yaml``. Users override at ``~/.impakt/config.yaml``.
Per-test overrides go in ``<test_dir>/.impakt/config.yaml``.
"""
from __future__ import annotations
import copy
import logging
import shutil
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
import yaml
logger = logging.getLogger(__name__)
# Paths
_PACKAGE_DEFAULTS_DIR = Path(__file__).parent.parent / "defaults"
_PACKAGE_CONFIG = _PACKAGE_DEFAULTS_DIR / "config.yaml"
_USER_DIR = Path.home() / ".impakt"
_USER_CONFIG = _USER_DIR / "config.yaml"
_SESSION_DIR_NAME = ".impakt"
_SESSION_CONFIG_NAME = "config.yaml"
def _deep_merge(base: dict[str, Any], override: dict[str, Any]) -> dict[str, Any]:
"""Deep-merge two dicts. Values in ``override`` win over ``base``.
Nested dicts are merged recursively. Lists and scalars are replaced.
"""
result = copy.deepcopy(base)
for key, value in override.items():
if key in result and isinstance(result[key], dict) and isinstance(value, dict):
result[key] = _deep_merge(result[key], value)
else:
result[key] = copy.deepcopy(value)
return result
def _load_yaml(path: Path) -> dict[str, Any]:
"""Load a YAML file, returning empty dict on failure."""
if not path.exists():
return {}
try:
text = path.read_text(encoding="utf-8")
data = yaml.safe_load(text)
return data if isinstance(data, dict) else {}
except Exception as e:
logger.warning("Failed to load config %s: %s", path, e)
return {}
# ---------------------------------------------------------------------------
# Typed config sections
# ---------------------------------------------------------------------------
@dataclass
class PlotConfig:
"""Plot appearance settings."""
colors: list[str] = field(
default_factory=lambda: [
"#1f77b4",
"#ff7f0e",
"#2ca02c",
"#d62728",
"#9467bd",
"#8c564b",
"#e377c2",
"#7f7f7f",
"#bcbd22",
"#17becf",
]
)
line_width: float = 1.5
focus_color: str = "#ffc107"
focus_line_width: float = 2.5
x_label: str = "Time (s)"
x_label_font_size: int = 10
y_label_font_size: int = 10
axis_label_color: str = "#999999"
margin_compact: dict[str, int] = field(
default_factory=lambda: {
"left": 45,
"right": 8,
"top": 4,
"bottom": 28,
}
)
margin_standard: dict[str, int] = field(
default_factory=lambda: {
"left": 60,
"right": 20,
"top": 10,
"bottom": 60,
}
)
cursor_x1_color: str = "rgba(220,53,69,0.6)"
cursor_x2_color: str = "rgba(13,110,253,0.6)"
cursor_line_width: int = 1
cursor_annotation_font_size: int = 9
show_grid: bool = True
grid_color: str = "rgba(128,128,128,0.2)"
resample_enabled: bool = True
resample_n_shown: int = 1500
@dataclass
class TransformConfig:
"""Default transform settings."""
default_cfc: int | None = None
default_y_align: bool = False
default_x_align: str = "none"
default_x_align_value: float | None = None
@dataclass
class CriteriaConfig:
"""Injury criteria auto-detection settings."""
channel_patterns: dict[str, list[str]] = field(
default_factory=lambda: {
"head_accel": ["*HEAD*AC{X,Y,Z}*", "*HEAD*AC*"],
"chest_accel": ["*CHST0000*AC{X,Y,Z}*", "*CHST*AC*"],
"neck_fz": ["*NECKUP*FO*Z*"],
"neck_my": ["*NECKUP*MO*Y*"],
"chest_deflection": ["*CHST*DC*"],
"femur_left": ["*FEMRLE*FO*Z*"],
"femur_right": ["*FEMRRI*FO*Z*"],
"tibia_fz": ["*TIBI*FO*Z*"],
"tibia_mx": ["*TIBI*MO*X*"],
"tibia_my": ["*TIBI*MO*Y*"],
}
)
chest_deflection_max_peak_mm: float = 150.0
@dataclass
class ProtocolConfig:
"""Protocol scoring settings."""
default: str = "euro_ncap"
versions: dict[str, str] = field(
default_factory=lambda: {
"euro_ncap": "2024",
"us_ncap": "2023",
"iihs": "2024",
}
)
@dataclass
class SessionConfig:
"""Session behavior settings."""
auto_save: bool = True
dir_name: str = ".impakt"
@dataclass
class WebConfig:
"""Web UI preferences."""
default_layout: str = "1x1"
cursor_poll_interval_ms: int = 80
default_port: int = 8050
# ---------------------------------------------------------------------------
# Main Config class
# ---------------------------------------------------------------------------
class Config:
"""Layered configuration for Impakt.
Resolves settings from three sources (most specific wins):
1. Package defaults (``src/impakt/defaults/config.yaml``)
2. User defaults (``~/.impakt/config.yaml``)
3. Test session (``<test_dir>/.impakt/config.yaml``)
Access typed sections via ``config.plot``, ``config.transforms``, etc.
"""
def __init__(self, raw: dict[str, Any] | None = None) -> None:
self._raw = raw or {}
self.plot = self._build_section(PlotConfig, "plot")
self.transforms = self._build_section(TransformConfig, "transforms")
self.criteria = self._build_section(CriteriaConfig, "criteria")
self.protocols = self._build_section(ProtocolConfig, "protocols")
self.session = self._build_section(SessionConfig, "session")
self.web = self._build_section(WebConfig, "web")
def _build_section(self, cls: type, key: str) -> Any:
"""Build a typed config section from raw dict data."""
section_data = self._raw.get(key, {})
if not isinstance(section_data, dict):
section_data = {}
# Filter to only fields the dataclass accepts
import dataclasses
valid_fields = {f.name for f in dataclasses.fields(cls)}
filtered = {k: v for k, v in section_data.items() if k in valid_fields}
try:
return cls(**filtered)
except TypeError:
return cls()
@classmethod
def load(cls, session_path: Path | str | None = None) -> Config:
"""Load configuration with layered resolution.
Args:
session_path: Path to the test data directory. If provided,
loads session-specific overrides from
``<session_path>/.impakt/config.yaml``.
Returns:
Fully resolved Config instance.
"""
# Layer 1: Package defaults
raw = _load_yaml(_PACKAGE_CONFIG)
# Layer 2: User defaults
user_data = _load_yaml(_USER_CONFIG)
if user_data:
raw = _deep_merge(raw, user_data)
# Layer 3: Test session overrides
if session_path is not None:
session_config = Path(session_path) / _SESSION_DIR_NAME / _SESSION_CONFIG_NAME
session_data = _load_yaml(session_config)
if session_data:
raw = _deep_merge(raw, session_data)
return cls(raw)
@classmethod
def from_defaults(cls) -> Config:
"""Load only package defaults (no user or session overrides)."""
raw = _load_yaml(_PACKAGE_CONFIG)
return cls(raw)
def to_dict(self) -> dict[str, Any]:
"""Serialize the current config to a dict."""
import dataclasses
result: dict[str, Any] = {}
for section_name in ("plot", "transforms", "criteria", "protocols", "session", "web"):
section = getattr(self, section_name)
result[section_name] = dataclasses.asdict(section)
return result
def to_yaml(self) -> str:
"""Serialize the current config to a YAML string."""
return yaml.dump(
self.to_dict(),
default_flow_style=False,
sort_keys=False,
allow_unicode=True,
)
def save_user(self) -> Path:
"""Save the current config as user defaults.
Writes to ``~/.impakt/config.yaml``.
"""
_USER_DIR.mkdir(parents=True, exist_ok=True)
path = _USER_CONFIG
path.write_text(
"# Impakt user configuration\n"
"# Override package defaults here. See defaults/config.yaml for all options.\n\n"
+ self.to_yaml(),
encoding="utf-8",
)
logger.info("Saved user config to %s", path)
return path
def save_session(self, test_path: Path | str) -> Path:
"""Save the current config as session-level overrides.
Writes to ``<test_path>/.impakt/config.yaml``.
Also copies protocol thresholds and corridor files into the session
directory so the test folder is self-contained.
"""
test_path = Path(test_path)
session_dir = test_path / _SESSION_DIR_NAME
session_dir.mkdir(parents=True, exist_ok=True)
# Write config
config_path = session_dir / _SESSION_CONFIG_NAME
config_path.write_text(
"# Impakt session configuration\n"
f"# Test: {test_path.name}\n"
"# Overrides user and package defaults.\n\n" + self.to_yaml(),
encoding="utf-8",
)
# Copy protocol threshold files into session
self._copy_protocols_to_session(session_dir)
logger.info("Saved session config to %s", config_path)
return config_path
def _copy_protocols_to_session(self, session_dir: Path) -> None:
"""Copy protocol threshold YAML files into the session directory."""
dest = session_dir / "protocols"
dest.mkdir(parents=True, exist_ok=True)
# Source priority: user dir → package defaults
for source_dir in [_USER_DIR / "protocols", _PACKAGE_DEFAULTS_DIR / "protocols"]:
if not source_dir.exists():
continue
for yaml_file in source_dir.glob("*.yaml"):
dest_file = dest / yaml_file.name
if not dest_file.exists():
shutil.copy2(yaml_file, dest_file)
logger.debug("Copied protocol %s to session", yaml_file.name)
@staticmethod
def init_user_dir() -> Path:
"""Initialize the user config directory with default files.
Creates ``~/.impakt/`` with a copy of the default ``config.yaml``
and protocol threshold files, if they don't already exist.
"""
_USER_DIR.mkdir(parents=True, exist_ok=True)
# Copy default config if not present
if not _USER_CONFIG.exists():
shutil.copy2(_PACKAGE_CONFIG, _USER_CONFIG)
logger.info("Initialized user config at %s", _USER_CONFIG)
# Copy protocol thresholds
proto_dir = _USER_DIR / "protocols"
proto_dir.mkdir(parents=True, exist_ok=True)
source_proto = _PACKAGE_DEFAULTS_DIR / "protocols"
if source_proto.exists():
for f in source_proto.glob("*.yaml"):
dest = proto_dir / f.name
if not dest.exists():
shutil.copy2(f, dest)
# Create templates directory
(_USER_DIR / "templates").mkdir(parents=True, exist_ok=True)
# Create corridors directory
(_USER_DIR / "corridors").mkdir(parents=True, exist_ok=True)
return _USER_DIR
@property
def package_defaults_dir(self) -> Path:
"""Path to the package defaults directory."""
return _PACKAGE_DEFAULTS_DIR
@property
def user_dir(self) -> Path:
"""Path to the user configuration directory (~/.impakt/)."""
return _USER_DIR
def __repr__(self) -> str:
cfc = self.transforms.default_cfc
proto = self.protocols.default
return f"Config(cfc={cfc}, protocol={proto}, colors={len(self.plot.colors)})"

164
src/impakt/defaults/config.yaml Normal file
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@@ -0,0 +1,164 @@
# Impakt — Default Configuration
#
# This file defines the default settings for Impakt. Values here are
# the package-level defaults. They can be overridden at two levels:
#
# 1. User defaults: ~/.impakt/config.yaml
# 2. Test session: <test_dir>/.impakt/config.yaml
#
# The resolution order is: package → user → session (most specific wins).
# ---------------------------------------------------------------------------
# Plot appearance
# ---------------------------------------------------------------------------
plot:
# Color palette for channel traces (colorblind-friendly).
# Colors are assigned in order: first selected channel gets colors[0], etc.
colors:
- "#1f77b4" # blue
- "#ff7f0e" # orange
- "#2ca02c" # green
- "#d62728" # red
- "#9467bd" # purple
- "#8c564b" # brown
- "#e377c2" # pink
- "#7f7f7f" # gray
- "#bcbd22" # olive
- "#17becf" # cyan
# Default line width for traces (pixels)
line_width: 1.5
# Focus channel styling
focus_color: "#ffc107" # amber
focus_line_width: 2.5
# Axis labels
x_label: "Time (s)"
x_label_font_size: 10
y_label_font_size: 10
axis_label_color: "#999999"
# Margins (pixels). Compact mode uses these; standard mode is wider.
margin_compact:
left: 45
right: 8
top: 4
bottom: 28
margin_standard:
left: 60
right: 20
top: 10
bottom: 60
# Cursor lines
cursor_x1_color: "rgba(220,53,69,0.6)"
cursor_x2_color: "rgba(13,110,253,0.6)"
cursor_line_width: 1
cursor_annotation_font_size: 9
# Grid
show_grid: true
grid_color: "rgba(128,128,128,0.2)"
# Resampling (LTTB downsampling for large datasets)
resample_enabled: true
resample_n_shown: 1500
# ---------------------------------------------------------------------------
# Default transforms
# ---------------------------------------------------------------------------
transforms:
# Default CFC filter class applied to new channels.
# Options: null (no filter), 60, 180, 600, 1000
default_cfc: null
# Default Y-axis alignment.
# If true, baseline offset is removed using pre-trigger data.
default_y_align: false
# Default X-axis alignment method.
# Options: "none", "manual", "threshold"
default_x_align: "none"
# Default X-align value (time offset in seconds, or threshold value)
default_x_align_value: null
# ---------------------------------------------------------------------------
# Injury criteria auto-detection
# ---------------------------------------------------------------------------
criteria:
# Channel patterns for auto-detection. The criteria engine searches
# for channels matching these patterns (glob-style) and computes the
# corresponding criterion.
#
# Each entry maps a criterion name to a list of channel patterns.
# The first match wins. Patterns use * wildcards.
channel_patterns:
head_accel:
- "*HEAD*AC{X,Y,Z}*"
- "*HEAD*AC*"
chest_accel:
- "*CHST0000*AC{X,Y,Z}*"
- "*CHST*AC*"
neck_fz:
- "*NECKUP*FO*Z*"
neck_my:
- "*NECKUP*MO*Y*"
chest_deflection:
- "*CHST*DC*"
femur_left:
- "*FEMRLE*FO*Z*"
femur_right:
- "*FEMRRI*FO*Z*"
tibia_fz:
- "*TIBI*FO*Z*"
tibia_mx:
- "*TIBI*MO*X*"
tibia_my:
- "*TIBI*MO*Y*"
# Maximum chest deflection peak (mm) to consider a DS channel as
# actual chest deflection (vs. steering column displacement)
chest_deflection_max_peak_mm: 150.0
# ---------------------------------------------------------------------------
# Protocol scoring
# ---------------------------------------------------------------------------
protocols:
# Default protocol for the Analysis tab
default: "euro_ncap"
# Available protocol versions.
# Threshold files are loaded from:
# 1. <test_dir>/.impakt/protocols/
# 2. ~/.impakt/protocols/
# 3. Package defaults (src/impakt/defaults/protocols/)
versions:
euro_ncap: "2024"
us_ncap: "2023"
iihs: "2024"
# ---------------------------------------------------------------------------
# Session behavior
# ---------------------------------------------------------------------------
session:
# Auto-save session state on channel selection or transform changes.
auto_save: true
# Directory name for session data inside test directories.
dir_name: ".impakt"
# ---------------------------------------------------------------------------
# Web UI preferences
# ---------------------------------------------------------------------------
web:
# Default plot layout preset
default_layout: "1x1"
# Cursor poll interval (milliseconds). Lower = more responsive but
# more CPU usage. Range: 30-200.
cursor_poll_interval_ms: 80
# Port for the web server
default_port: 8050

76
src/impakt/defaults/protocols/euro_ncap_2024.yaml Normal file
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@@ -0,0 +1,76 @@
# Euro NCAP 2024 Adult Occupant Frontal Impact Thresholds
#
# Each criterion: [green, yellow, orange, brown, red, higher_is_worse, max_points]
# Sliding-scale: values at or below green = full points, at or above red = zero.
HIC15:
green: 500.0
yellow: 620.0
orange: 700.0
brown: 850.0
red: 1000.0
higher_is_worse: true
max_points: 4.0
3ms Clip:
green: 42.0
yellow: 48.0
orange: 54.0
brown: 57.0
red: 60.0
higher_is_worse: true
max_points: 4.0
Chest Deflection:
green: 22.0
yellow: 34.0
orange: 42.0
brown: 50.0
red: 63.0
higher_is_worse: true
max_points: 4.0
Nij:
green: 0.5
yellow: 0.65
orange: 0.8
brown: 0.9
red: 1.0
higher_is_worse: true
max_points: 2.0
Femur Load Left:
green: 3.8
yellow: 5.4
orange: 7.0
brown: 8.5
red: 10.0
higher_is_worse: true
max_points: 2.0
Femur Load Right:
green: 3.8
yellow: 5.4
orange: 7.0
brown: 8.5
red: 10.0
higher_is_worse: true
max_points: 2.0
Tibia Index:
green: 0.4
yellow: 0.7
orange: 1.0
brown: 1.15
red: 1.3
higher_is_worse: true
max_points: 2.0
Viscous Criterion:
green: 0.32
yellow: 0.56
orange: 0.8
brown: 0.9
red: 1.0
higher_is_worse: true
max_points: 2.0

40
src/impakt/defaults/protocols/iihs_2024.yaml Normal file
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@@ -0,0 +1,40 @@
# IIHS 2024 Crashworthiness Thresholds
#
# Each criterion: [good, acceptable, marginal, higher_is_worse]
# Values above marginal = Poor.
HIC15:
good: 250.0
acceptable: 500.0
marginal: 700.0
higher_is_worse: true
Chest Deflection:
good: 38.0
acceptable: 50.0
marginal: 63.0
higher_is_worse: true
Femur Load Left:
good: 3.8
acceptable: 6.2
marginal: 10.0
higher_is_worse: true
Femur Load Right:
good: 3.8
acceptable: 6.2
marginal: 10.0
higher_is_worse: true
Nij:
good: 0.52
acceptable: 0.78
marginal: 1.0
higher_is_worse: true
Tibia Index:
good: 0.5
acceptable: 0.8
marginal: 1.3
higher_is_worse: true

17
src/impakt/plot/engine.py
View File

@@ -23,7 +23,9 @@ from impakt.plot.spec import Corridor, CursorValues, PlotSpec
logger = logging.getLogger(__name__)
# Default color palette (colorblind-friendly)
# Default color palette (colorblind-friendly).
# This is the hardcoded fallback. When Config is available, the palette
# is read from config.plot.colors instead.
DEFAULT_COLORS = [
"#1f77b4", # blue
"#ff7f0e", # orange
@@ -38,6 +40,19 @@ DEFAULT_COLORS = [
]
def get_colors() -> list[str]:
"""Get the color palette, preferring Config if loaded."""
try:
from impakt.config import Config
config = Config.load()
if config.plot.colors:
return config.plot.colors
except Exception:
pass
return DEFAULT_COLORS
class PlotEngine:
"""Renders PlotSpec into Plotly figures.

22
src/impakt/script/api.py
View File

@@ -73,6 +73,11 @@ class Session:
)
self._template: TemplateSpec | None = None
# Load layered config for this session
from impakt.config import Config
self._config = Config.load(session_path=test_data.path)
@classmethod
def _discover_plugins(cls) -> None:
"""Discover and register plugins. Called once on first Session.open()."""
@@ -133,6 +138,23 @@ class Session:
"""Path to the test data directory."""
return self._data.path
@property
def config(self) -> Any:
"""Layered configuration for this session.
Resolves: package defaults → user defaults → session overrides.
"""
return self._config
def save_config(self) -> Path | None:
"""Save the current config to the session .impakt/ folder.
Copies config.yaml and protocol thresholds into the test directory.
"""
if self._data.path:
return self._config.save_session(self._data.path)
return None
@property
def channel_names(self) -> list[str]:
return self._data.channel_names

21
src/impakt/web/state.py
View File

@@ -16,6 +16,7 @@ from pathlib import Path
from typing import Any
from impakt.channel.model import Channel
from impakt.config import Config
from impakt.script.api import Session
from impakt.template.library import TemplateLibrary
from impakt.template.model import PlotDefinition, TemplateSpec
@@ -40,6 +41,8 @@ class AppState:
# Current FigureResampler instance for zoom/pan resampling.
# Stored here (not as a module global) so it's per-AppState.
self.current_resampler: Any = None
# Layered configuration (loaded on first test load)
self._config: Config | None = None
# Active corridors
self.corridors: list[dict[str, Any]] = []
@@ -261,6 +264,24 @@ class AppState:
result[session.test_id] = test_tree
return result
# ----- Configuration -----
@property
def config(self) -> Config:
"""Layered configuration. Loaded from the primary test's session path."""
if self._config is None:
primary = self.primary_test
session_path = primary.path if primary else None
self._config = Config.load(session_path=session_path)
return self._config
def save_config(self) -> None:
"""Save current config to the primary test's .impakt/ folder."""
primary = self.primary_test
if primary and primary.path:
self.config.save_session(primary.path)
logger.info("Saved session config for %s", primary.test_id)
@property
def is_empty(self) -> bool:
return len(self._sessions) == 0

227
tests/test_config.py Normal file
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@@ -0,0 +1,227 @@
"""Tests for the layered configuration system."""
from pathlib import Path
import pytest
import yaml
from impakt.config import Config
from impakt.config.model import (
CriteriaConfig,
PlotConfig,
ProtocolConfig,
SessionConfig,
TransformConfig,
WebConfig,
_deep_merge,
)
class TestDeepMerge:
def test_simple_override(self):
base = {"a": 1, "b": 2}
override = {"b": 3, "c": 4}
result = _deep_merge(base, override)
assert result == {"a": 1, "b": 3, "c": 4}
def test_nested_merge(self):
base = {"plot": {"colors": ["red"], "width": 1}}
override = {"plot": {"width": 2}}
result = _deep_merge(base, override)
assert result["plot"]["colors"] == ["red"]
assert result["plot"]["width"] == 2
def test_list_replacement(self):
"""Lists are replaced entirely, not merged."""
base = {"items": [1, 2, 3]}
override = {"items": [4, 5]}
result = _deep_merge(base, override)
assert result["items"] == [4, 5]
def test_deep_nested(self):
base = {"a": {"b": {"c": 1, "d": 2}}}
override = {"a": {"b": {"c": 99}}}
result = _deep_merge(base, override)
assert result["a"]["b"]["c"] == 99
assert result["a"]["b"]["d"] == 2
class TestConfigLoad:
def test_from_defaults(self):
config = Config.from_defaults()
assert config.plot.line_width == 1.5
assert len(config.plot.colors) == 10
assert config.transforms.default_cfc is None
assert config.protocols.default == "euro_ncap"
def test_load_without_session(self):
config = Config.load()
assert isinstance(config.plot, PlotConfig)
assert isinstance(config.transforms, TransformConfig)
assert isinstance(config.criteria, CriteriaConfig)
assert isinstance(config.protocols, ProtocolConfig)
assert isinstance(config.session, SessionConfig)
assert isinstance(config.web, WebConfig)
def test_load_with_nonexistent_session(self, tmp_path):
config = Config.load(session_path=tmp_path / "nonexistent")
# Should still load package defaults
assert config.plot.line_width == 1.5
def test_session_override(self, tmp_path):
# Create a session config with overrides
session_dir = tmp_path / ".impakt"
session_dir.mkdir()
session_config = session_dir / "config.yaml"
session_config.write_text(
yaml.dump(
{
"plot": {"line_width": 3.0},
"transforms": {"default_cfc": 600},
}
),
encoding="utf-8",
)
config = Config.load(session_path=tmp_path)
assert config.plot.line_width == 3.0
assert config.transforms.default_cfc == 600
# Non-overridden values still come from defaults
assert len(config.plot.colors) == 10
def test_to_dict(self):
config = Config.from_defaults()
d = config.to_dict()
assert "plot" in d
assert "transforms" in d
assert "criteria" in d
assert "protocols" in d
assert d["plot"]["line_width"] == 1.5
def test_to_yaml(self):
config = Config.from_defaults()
yaml_str = config.to_yaml()
assert "line_width" in yaml_str
assert "default_cfc" in yaml_str
# Should be parseable
parsed = yaml.safe_load(yaml_str)
assert parsed["plot"]["line_width"] == 1.5
def test_repr(self):
config = Config.from_defaults()
r = repr(config)
assert "Config(" in r
assert "cfc=" in r
class TestConfigSave:
def test_save_session(self, tmp_path):
config = Config.from_defaults()
config.plot.line_width = 4.0
config.transforms.default_cfc = 1000
path = config.save_session(tmp_path)
assert path.exists()
assert (tmp_path / ".impakt" / "config.yaml").exists()
# Reload and verify
reloaded = Config.load(session_path=tmp_path)
assert reloaded.plot.line_width == 4.0
assert reloaded.transforms.default_cfc == 1000
def test_save_copies_protocols(self, tmp_path):
config = Config.from_defaults()
config.save_session(tmp_path)
proto_dir = tmp_path / ".impakt" / "protocols"
assert proto_dir.exists()
# Should have at least euro_ncap and iihs
yaml_files = list(proto_dir.glob("*.yaml"))
assert len(yaml_files) >= 2
def test_save_user(self, tmp_path, monkeypatch):
# Redirect user dir to tmp
import impakt.config.model as cm
monkeypatch.setattr(cm, "_USER_DIR", tmp_path)
monkeypatch.setattr(cm, "_USER_CONFIG", tmp_path / "config.yaml")
config = Config.from_defaults()
config.plot.line_width = 5.0
path = config.save_user()
assert path.exists()
# Read it back
text = path.read_text()
assert "5.0" in text
def test_init_user_dir(self, tmp_path, monkeypatch):
import impakt.config.model as cm
monkeypatch.setattr(cm, "_USER_DIR", tmp_path / "test_impakt")
monkeypatch.setattr(cm, "_USER_CONFIG", tmp_path / "test_impakt" / "config.yaml")
user_dir = Config.init_user_dir()
assert user_dir.exists()
assert (user_dir / "config.yaml").exists()
assert (user_dir / "templates").exists()
assert (user_dir / "corridors").exists()
assert (user_dir / "protocols").exists()
class TestConfigRoundTrip:
"""Verify that save -> load preserves all values."""
def test_full_round_trip(self, tmp_path):
# Create config with non-default values
config = Config.from_defaults()
config.plot.line_width = 2.5
config.plot.focus_color = "#ff0000"
config.transforms.default_cfc = 180
config.transforms.default_y_align = True
config.criteria.chest_deflection_max_peak_mm = 200.0
config.protocols.default = "iihs"
config.web.cursor_poll_interval_ms = 50
# Save
config.save_session(tmp_path)
# Reload
reloaded = Config.load(session_path=tmp_path)
assert reloaded.plot.line_width == 2.5
assert reloaded.plot.focus_color == "#ff0000"
assert reloaded.transforms.default_cfc == 180
assert reloaded.transforms.default_y_align is True
assert reloaded.criteria.chest_deflection_max_peak_mm == 200.0
assert reloaded.protocols.default == "iihs"
assert reloaded.web.cursor_poll_interval_ms == 50
class TestConfigInSession:
"""Verify Config integrates with Session."""
def test_session_has_config(self):
from impakt import Session
s = Session.open("tests/fixtures/sample_mme")
assert s.config is not None
assert s.config.plot.line_width == 1.5
def test_session_save_config(self, tmp_path):
import shutil
# Copy fixture to tmp so we can write .impakt/
test_dir = tmp_path / "test_session"
shutil.copytree("tests/fixtures/sample_mme", test_dir)
from impakt import Session
s = Session.open(test_dir)
s.config.transforms.default_cfc = 600
result = s.save_config()
assert result is not None
assert (test_dir / ".impakt" / "config.yaml").exists()
# Reopen and verify
s2 = Session.open(test_dir)
assert s2.config.transforms.default_cfc == 600