From 99d299fd24d035502b01876ae1ca800b5fc2ecfe Mon Sep 17 00:00:00 2001 From: rakadu1 Date: Wed, 22 Apr 2026 08:50:46 +0530 Subject: [PATCH] graphify trial 1. --- graphify-out/.graphify_python | 1 + graphify-out/GRAPH_REPORT.md | 263 + graphify-out/graph.html | 257 + graphify-out/graph.json | 8680 +++++++++++++++++++++++++++++++++ 4 files changed, 9201 insertions(+) create mode 100644 graphify-out/.graphify_python create mode 100644 graphify-out/GRAPH_REPORT.md create mode 100644 graphify-out/graph.html create mode 100644 graphify-out/graph.json diff --git a/graphify-out/.graphify_python b/graphify-out/.graphify_python new file mode 100644 index 0000000..a0f30ed --- /dev/null +++ b/graphify-out/.graphify_python @@ -0,0 +1 @@ +C:\Users\rakadu1\AppData\Local\Programs\Python\Python314\python.exe \ No newline at end of file diff --git a/graphify-out/GRAPH_REPORT.md b/graphify-out/GRAPH_REPORT.md new file mode 100644 index 0000000..7f18d70 --- /dev/null +++ b/graphify-out/GRAPH_REPORT.md @@ -0,0 +1,263 @@ +# Graph Report - . (2026-04-21) + +## Corpus Check +- 89 files · ~92,297 words +- Verdict: corpus is large enough that graph structure adds value. + +## Summary +- 330 nodes · 475 edges · 33 communities detected +- Extraction: 68% EXTRACTED · 32% INFERRED · 0% AMBIGUOUS · INFERRED: 151 edges (avg confidence: 0.7) +- Token cost: 0 input · 0 output + +## Community Hubs (Navigation) +- [[_COMMUNITY_Scenario Framework & Maneuvers|Scenario Framework & Maneuvers]] +- [[_COMMUNITY_Radar Simulation & Processing|Radar Simulation & Processing]] +- [[_COMMUNITY_Orchestration & Sensor Management|Orchestration & Sensor Management]] +- [[_COMMUNITY_Data Recording & Heatmaps|Data Recording & Heatmaps]] +- [[_COMMUNITY_Data Conversion Utilities|Data Conversion Utilities]] +- [[_COMMUNITY_Web Dashboard & Loader|Web Dashboard & Loader]] +- [[_COMMUNITY_LiDAR & Fast Heatmap Gen|LiDAR & Fast Heatmap Gen]] +- [[_COMMUNITY_DSP & CFAR Detection|DSP & CFAR Detection]] +- [[_COMMUNITY_Scene Reconstruction|Scene Reconstruction]] +- [[_COMMUNITY_Dashboard Frontend (JS)|Dashboard Frontend (JS)]] +- [[_COMMUNITY_MCAP Dataset Conversion|MCAP Dataset Conversion]] +- [[_COMMUNITY_Radar Signal Detection|Radar Signal Detection]] +- [[_COMMUNITY_Data Quality Inspection|Data Quality Inspection]] +- [[_COMMUNITY_Deep Metrology Analysis|Deep Metrology Analysis]] +- [[_COMMUNITY_Metrology Comparison|Metrology Comparison]] +- [[_COMMUNITY_Community 15|Community 15]] +- [[_COMMUNITY_Community 16|Community 16]] +- [[_COMMUNITY_Community 17|Community 17]] +- [[_COMMUNITY_Community 18|Community 18]] +- [[_COMMUNITY_Community 19|Community 19]] +- [[_COMMUNITY_Community 20|Community 20]] +- [[_COMMUNITY_Community 21|Community 21]] +- [[_COMMUNITY_Community 22|Community 22]] +- [[_COMMUNITY_Community 23|Community 23]] +- [[_COMMUNITY_Community 24|Community 24]] +- [[_COMMUNITY_Community 25|Community 25]] +- [[_COMMUNITY_Community 26|Community 26]] +- [[_COMMUNITY_Community 27|Community 27]] +- [[_COMMUNITY_Community 28|Community 28]] +- [[_COMMUNITY_Community 29|Community 29]] +- [[_COMMUNITY_Community 30|Community 30]] +- [[_COMMUNITY_Community 31|Community 31]] +- [[_COMMUNITY_Community 32|Community 32]] + +## God Nodes (most connected - your core abstractions) +1. `ScenarioBase` - 26 edges +2. `ShenronRadarModel` - 22 edges +3. `radar` - 20 edges +4. `RadarProcessor` - 20 edges +5. `main()` - 20 edges +6. `run_testbench()` - 12 edges +7. `Recorder` - 11 edges +8. `SensorManager` - 11 edges +9. `BrakingScenario` - 9 edges +10. `CutInScenario` - 9 edges + +## Surprising Connections (you probably didn't know these) +- `scenarios/showcase.py --------------------- Custom high-impact demo scene: Left` --uses--> `ScenarioBase` [INFERRED] + scenarios\showcase.py → scenarios\base.py +- `Step 11: Deep Intersection Guidance for Ego.` --uses--> `ScenarioBase` [INFERRED] + scenarios\showcase.py → scenarios\base.py +- `Step 11: Multi-stage steering logic.` --uses--> `ScenarioBase` [INFERRED] + scenarios\showcase.py → scenarios\base.py +- `src/scenario_loader.py ---------------------- Dynamic scenario discovery and loa` --uses--> `ScenarioBase` [INFERRED] + src\scenario_loader.py → scenarios\base.py +- `Discover all scenario modules inside the 'scenarios' package. Returns a sort` --uses--> `ScenarioBase` [INFERRED] + src\scenario_loader.py → scenarios\base.py + +## Communities + +### Community 0 - "Scenario Framework & Maneuvers" +Cohesion: 0.05 +Nodes (18): ABC, scenarios/base.py ----------------- Abstract base class for all CARLA simulati, Return a dict that will be merged into every recorded frame's metadata, Convenience method: destroy all actors tracked in self._actors. Call th, Return a waypoint `distance` metres ahead of the ego vehicle. lane_offs, Abstract interface for all ADAS simulation scenarios. Lifecycle ----, Unified 1:1 logging for all scenarios. This method ensures clean consol, ScenarioBase (+10 more) + +### Community 1 - "Radar Simulation & Processing" +Cohesion: 0.08 +Nodes (22): radar, Load normalized antenna gain LUTs (dB) from CSV files. Expected CSV f, class to define the radar object with it's settings and to extract time interval, _get_gpu_info(), main(), process_session(), Retrieve GPU hardware info for telemetry display., Return the raw internal heatmaps and thresholds for the last processed frame. (+14 more) + +### Community 2 - "Orchestration & Sensor Management" +Cohesion: 0.08 +Nodes (13): Called immediately after the ego vehicle is spawned. Override to react, Allow the orchestrator to inject parameters parsed from CLI. This maps, main(), parse_args(), src/main.py ----------- Scenario-agnostic orchestrator for the CARLA ADAS simu, SensorManager, scenarios/showcase.py --------------------- Custom high-impact demo scene: Left, Step 11: Deep Intersection Guidance for Ego. (+5 more) + +### Community 3 - "Data Recording & Heatmaps" +Cohesion: 0.09 +Nodes (18): check_save_path(), main(), Stitch captured frames into .mp4 files for easy viewing., Categorise actor into broad ADAS classes., Calculate relative range, azimuth, and closing velocity. Uses right-han, Helper to convert world location to transform-local location., Helper to save image in a background thread., Recorder (+10 more) + +### Community 4 - "Data Conversion Utilities" +Cohesion: 0.1 +Nodes (14): convert2D_img_func(), convert_sem_lidar_2D_img_func(), main(), converts the 3D radar raw data to 2d range-angle image of dimension 256X256, converts the semantic_lidar data to the range angle 2D image of dimension 256X25, # apply fft on each antenna to get angle profile, cart2polar(), get_range_angle() (+6 more) + +### Community 5 - "Web Dashboard & Loader" +Cohesion: 0.09 +Nodes (16): get_config(), get_scenario_params(), is_simulation_running(), PollingFilter, dashboard/app.py ---------------- Flask backend for the BATL CARLA Orchestrator, Forces all CarlaUE4 processes to terminate., Stops the Flask server itself., Returns True if a scenario process is currently alive. (+8 more) + +### Community 6 - "LiDAR & Fast Heatmap Gen" +Cohesion: 0.11 +Nodes (13): get_gpu_id_most_avlbl_mem(), heatmap_gen(), heatmap_gen(), Cropped_forRadar(), map_carla_semantic_lidar_latest(), Function to map material column in the collected carla ray_cast_shenron to shenr, Removes Occlusions and calculates loss for each point, rotate_points() (+5 more) + +### Community 7 - "DSP & CFAR Detection" +Cohesion: 0.14 +Nodes (8): CA_CFAR, cart2polar(), convert_adc_to_3d_fft(), polar_to_cart(), Description: ------------ Cell Averaging - Constant False Alarm Ra, Description: ------------ Performs the automatic detection, Function to convert adc data to RA tensor Input: adcData:, convert a polar range angle tensor to cartesian array Input: RATe + +### Community 8 - "Scene Reconstruction" +Cohesion: 0.18 +Nodes (8): cart2sph(), get_loss_2(), get_loss_3(), Class with all the functions to modify OSM scenario and thus generate the points, Note: angles should be used for power calculation as it is in reflecting surface, Note: angles should be used for power calculation as it is in reflecting surface, Sceneset, sph2cart() + +### Community 9 - "Dashboard Frontend (JS)" +Cohesion: 0.33 +Nodes (7): appendLog(), chip(), renderShenronTelemetry(), resetIdleTimer(), setLoadingState(), startStream(), updateShenronProgress() + +### Community 10 - "MCAP Dataset Conversion" +Cohesion: 0.31 +Nodes (9): convert_folder(), load_frames(), main(), postprocess_ra(), Refined RA post-processing pipeline for Physical Realism. Restores the natu, Polar-to-Cartesian scan conversion following FIG / Guide logic. Converts RA, Convert 2D array to colormapped B64 PNG with guide-compliant normalization., render_heatmap() (+1 more) + +### Community 11 - "Radar Signal Detection" +Cohesion: 0.22 +Nodes (5): CA_CFAR, Description: ------------ Performs the automatic detection o, Description: ------------ Cell Averaging - Constant False Alarm Rate, apply range window and doppler window and apply fft on each sample to get range, apply fft on each chirp to get doppler profile + +### Community 12 - "Data Quality Inspection" +Cohesion: 0.33 +Nodes (2): inspect_gt(), load_frame() + +### Community 13 - "Deep Metrology Analysis" +Cohesion: 0.83 +Nodes (3): analyze_iteration(), power_law(), run_metrology_suite() + +### Community 14 - "Metrology Comparison" +Cohesion: 1.0 +Nodes (0): + +### Community 15 - "Community 15" +Cohesion: 1.0 +Nodes (0): + +### Community 16 - "Community 16" +Cohesion: 1.0 +Nodes (0): + +### Community 17 - "Community 17" +Cohesion: 1.0 +Nodes (0): + +### Community 18 - "Community 18" +Cohesion: 1.0 +Nodes (0): + +### Community 19 - "Community 19" +Cohesion: 1.0 +Nodes (0): + +### Community 20 - "Community 20" +Cohesion: 1.0 +Nodes (1): Human-readable scenario identifier (e.g. 'braking'). + +### Community 21 - "Community 21" +Cohesion: 1.0 +Nodes (1): Initialise the scenario: - Store world / ego / tm references. + +### Community 22 - "Community 22" +Cohesion: 1.0 +Nodes (1): Per-tick logic executed inside the main simulation loop. Parameters + +### Community 23 - "Community 23" +Cohesion: 1.0 +Nodes (1): Destroy all actors spawned by this scenario. Always call this in a fina + +### Community 24 - "Community 24" +Cohesion: 1.0 +Nodes (1): Override to request a specific weather preset for this scenario. If Non + +### Community 25 - "Community 25" +Cohesion: 1.0 +Nodes (1): Override to request a specific duration for this scenario. If None, the + +### Community 26 - "Community 26" +Cohesion: 1.0 +Nodes (1): Override to request a specific spawn point for the ego vehicle. Returns + +### Community 27 - "Community 27" +Cohesion: 1.0 +Nodes (0): + +### Community 28 - "Community 28" +Cohesion: 1.0 +Nodes (0): + +### Community 29 - "Community 29" +Cohesion: 1.0 +Nodes (0): + +### Community 30 - "Community 30" +Cohesion: 1.0 +Nodes (0): + +### Community 31 - "Community 31" +Cohesion: 1.0 +Nodes (0): + +### Community 32 - "Community 32" +Cohesion: 1.0 +Nodes (0): + +## Knowledge Gaps +- **39 isolated node(s):** `dashboard/app.py ---------------- Flask backend for the BATL CARLA Orchestrator`, `Returns True if a scenario process is currently alive.`, `Forces all CarlaUE4 processes to terminate.`, `Stops the Flask server itself.`, `scenarios/base.py ----------------- Abstract base class for all CARLA simulati` (+34 more) + These have ≤1 connection - possible missing edges or undocumented components. +- **Thin community `Metrology Comparison`** (2 nodes): `analyze_session()`, `compare_metrology.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 15`** (2 nodes): `get_pos()`, `get_pos.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 16`** (2 nodes): `track_full_state.py`, `track_full_state()` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 17`** (2 nodes): `track_peaks.py`, `get_peak_tracking()` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 18`** (2 nodes): `compare_folders()`, `compare_iterations.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 19`** (2 nodes): `research_metrology()`, `research_metrology.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 20`** (1 nodes): `Human-readable scenario identifier (e.g. 'braking').` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 21`** (1 nodes): `Initialise the scenario: - Store world / ego / tm references.` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 22`** (1 nodes): `Per-tick logic executed inside the main simulation loop. Parameters` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 23`** (1 nodes): `Destroy all actors spawned by this scenario. Always call this in a fina` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 24`** (1 nodes): `Override to request a specific weather preset for this scenario. If Non` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 25`** (1 nodes): `Override to request a specific duration for this scenario. If None, the` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 26`** (1 nodes): `Override to request a specific spawn point for the ego vehicle. Returns` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 27`** (1 nodes): `__init__.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 28`** (1 nodes): `__init__.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 29`** (1 nodes): `verify_tags.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 30`** (1 nodes): `path_config.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 31`** (1 nodes): `__init__.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. +- **Thin community `Community 32`** (1 nodes): `check_lidar.py` + Too small to be a meaningful cluster - may be noise or needs more connections extracted. + +## Suggested Questions +_Questions this graph is uniquely positioned to answer:_ + +- **Why does `main()` connect `Orchestration & Sensor Management` to `Scenario Framework & Maneuvers`, `Radar Simulation & Processing`, `Data Recording & Heatmaps`, `Web Dashboard & Loader`, `MCAP Dataset Conversion`?** + _High betweenness centrality (0.263) - this node is a cross-community bridge._ +- **Why does `ShenronRadarModel` connect `Radar Simulation & Processing` to `Data Recording & Heatmaps`?** + _High betweenness centrality (0.179) - this node is a cross-community bridge._ +- **Why does `ScenarioBase` connect `Scenario Framework & Maneuvers` to `Orchestration & Sensor Management`, `Web Dashboard & Loader`?** + _High betweenness centrality (0.122) - this node is a cross-community bridge._ +- **Are the 16 inferred relationships involving `ScenarioBase` (e.g. with `BrakingScenario` and `scenarios/braking.py -------------------- Lead Vehicle Hard Braking Scenario. A`) actually correct?** + _`ScenarioBase` has 16 INFERRED edges - model-reasoned connections that need verification._ +- **Are the 15 inferred relationships involving `ShenronRadarModel` (e.g. with `Retrieve GPU hardware info for telemetry display.` and `FastHeatmapEngine`) actually correct?** + _`ShenronRadarModel` has 15 INFERRED edges - model-reasoned connections that need verification._ +- **Are the 15 inferred relationships involving `radar` (e.g. with `ShenronRadarModel` and `Initialize the Shenron Radar Model. Args: radar_`) actually correct?** + _`radar` has 15 INFERRED edges - model-reasoned connections that need verification._ +- **Are the 14 inferred relationships involving `RadarProcessor` (e.g. with `ShenronRadarModel` and `Initialize the Shenron Radar Model. Args: radar_`) actually correct?** + _`RadarProcessor` has 14 INFERRED edges - model-reasoned connections that need verification._ \ No newline at end of file diff --git a/graphify-out/graph.html b/graphify-out/graph.html new file mode 100644 index 0000000..acdcfce --- /dev/null +++ b/graphify-out/graph.html @@ -0,0 +1,257 @@ + + + + +graphify - graphify-out/graph.html + + + + +
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"scripts\\ISOLATE\\e2e_agent_sem_lidar2shenron_package\\shenron\\Sceneset.py", + "source_location": "L378", + "id": "sceneset_rationale_378", + "community": 8, + "norm_label": "note: angles should be used for power calculation as it is in reflecting surface" + }, + { + "label": "cfar_detector.py", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\cfar_detector.py", + "source_location": "L1", + "id": "scripts_isolate_sim_radar_utils_cfar_detector_py", + "community": 11, + "norm_label": "cfar_detector.py" + }, + { + "label": "CA_CFAR", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\cfar_detector.py", + "source_location": "L4", + "id": "cfar_detector_ca_cfar", + "community": 11, + "norm_label": "ca_cfar" + }, + { + "label": ".__init__()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\cfar_detector.py", + "source_location": "L30", + "id": "cfar_detector_ca_cfar_init", + "community": 11, + "norm_label": ".__init__()" + }, + { + "label": ".__call__()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\cfar_detector.py", + "source_location": "L46", + "id": "cfar_detector_ca_cfar_call", + "community": 11, + "norm_label": ".__call__()" + }, + { + "label": "Description: ------------ Cell Averaging - Constant False Alarm Rate", + "file_type": "rationale", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\cfar_detector.py", + "source_location": "L5", + "id": "cfar_detector_rationale_5", + "community": 11, + "norm_label": "description: ------------ cell averaging - constant false alarm rate" + }, + { + "label": "Description: ------------ Performs the automatic detection o", + "file_type": "rationale", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\cfar_detector.py", + "source_location": "L47", + "id": "cfar_detector_rationale_47", + "community": 11, + "norm_label": "description: ------------ performs the automatic detection o" + }, + { + "label": "convert2D_img.py", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\convert2D_img.py", + "source_location": "L1", + "id": "scripts_isolate_sim_radar_utils_convert2d_img_py", + "community": 4, + "norm_label": "convert2d_img.py" + }, + { + "label": "convert2D_img_func()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\convert2D_img.py", + "source_location": "L22", + "id": "convert2d_img_convert2d_img_func", + "community": 4, + "norm_label": "convert2d_img_func()" + }, + { + "label": "convert_sem_lidar_2D_img_func()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\convert2D_img.py", + "source_location": "L40", + "id": "convert2d_img_convert_sem_lidar_2d_img_func", + "community": 4, + "norm_label": "convert_sem_lidar_2d_img_func()" + }, + { + "label": "main()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\convert2D_img.py", + "source_location": "L74", + "id": "convert2d_img_main", + "community": 4, + "norm_label": "main()" + }, + { + "label": "converts the 3D radar raw data to 2d range-angle image of dimension 256X256", + "file_type": "rationale", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\convert2D_img.py", + "source_location": "L23", + "id": "convert2d_img_rationale_23", + "community": 4, + "norm_label": "converts the 3d radar raw data to 2d range-angle image of dimension 256x256" + }, + { + "label": "converts the semantic_lidar data to the range angle 2D image of dimension 256X25", + "file_type": "rationale", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\convert2D_img.py", + "source_location": "L41", + "id": "convert2d_img_rationale_41", + "community": 4, + "norm_label": "converts the semantic_lidar data to the range angle 2d image of dimension 256x25" + }, + { + "label": "radar_processor.py", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L1", + "id": "scripts_isolate_sim_radar_utils_radar_processor_py", + "community": 1, + "norm_label": "radar_processor.py" + }, + { + "label": "RadarProcessor", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L22", + "id": "radar_processor_radarprocessor", + "community": 1, + "norm_label": "radarprocessor" + }, + { + "label": ".__init__()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L23", + "id": "radar_processor_radarprocessor_init", + "community": 11, + "norm_label": ".__init__()" + }, + { + "label": ".cal_range_fft()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L52", + "id": "radar_processor_radarprocessor_cal_range_fft", + "community": 1, + "norm_label": ".cal_range_fft()" + }, + { + "label": ".cal_doppler_fft()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L56", + "id": "radar_processor_radarprocessor_cal_doppler_fft", + "community": 1, + "norm_label": ".cal_doppler_fft()" + }, + { + "label": ".cal_angle_fft()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L60", + "id": "radar_processor_radarprocessor_cal_angle_fft", + "community": 4, + "norm_label": ".cal_angle_fft()" + }, + { + "label": ".convert_to_pcd()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L64", + "id": "radar_processor_radarprocessor_convert_to_pcd", + "community": 1, + "norm_label": ".convert_to_pcd()" + }, + { + "label": "apply range window and doppler window and apply fft on each sample to get range", + "file_type": "rationale", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L53", + "id": "radar_processor_rationale_53", + "community": 11, + "norm_label": "apply range window and doppler window and apply fft on each sample to get range" + }, + { + "label": "apply fft on each chirp to get doppler profile", + "file_type": "rationale", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L57", + "id": "radar_processor_rationale_57", + "community": 11, + "norm_label": "apply fft on each chirp to get doppler profile" + }, + { + "label": "# apply fft on each antenna to get angle profile", + "file_type": "rationale", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\radar_processor.py", + "source_location": "L61", + "id": "radar_processor_rationale_61", + "community": 4, + "norm_label": "# apply fft on each antenna to get angle profile" + }, + { + "label": "transform_utils.py", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\transform_utils.py", + "source_location": "L1", + "id": 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"source_file": "scripts\\ISOLATE\\sim_radar_utils\\transform_utils.py", + "source_location": "L19", + "id": "transform_utils_rationale_19", + "community": 4, + "norm_label": "convert a polar range angle tensor to cartesian array input: rate" + }, + { + "label": "utils_radar.py", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L1", + "id": "scripts_isolate_sim_radar_utils_utils_radar_py", + "community": 4, + "norm_label": "utils_radar.py" + }, + { + "label": "config_save_path()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L25", + "id": "utils_radar_config_save_path", + "community": 4, + "norm_label": "config_save_path()" + }, + { + "label": "create_folder()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L30", + "id": "utils_radar_create_folder", + "community": 4, + "norm_label": 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"community": 4, + "norm_label": "reformat_adc()" + }, + { + "label": "read_radar_data()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L63", + "id": "utils_radar_read_radar_data", + "community": 4, + "norm_label": "read_radar_data()" + }, + { + "label": "read_radar_data_shenron()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L69", + "id": "utils_radar_read_radar_data_shenron", + "community": 4, + "norm_label": "read_radar_data_shenron()" + }, + { + "label": "read_radar_pcd()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L75", + "id": "utils_radar_read_radar_pcd", + "community": 4, + "norm_label": "read_radar_pcd()" + }, + { + "label": "read_camera_img()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L80", + "id": "utils_radar_read_camera_img", + "community": 4, + "norm_label": "read_camera_img()" + }, + { + "label": "read_lidar_pcd()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L86", + "id": "utils_radar_read_lidar_pcd", + "community": 4, + "norm_label": "read_lidar_pcd()" + }, + { + "label": "plot_range_doppler()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L91", + "id": "utils_radar_plot_range_doppler", + "community": 4, + "norm_label": "plot_range_doppler()" + }, + { + "label": "plot_range_aoa()", + "file_type": "code", + "source_file": "scripts\\ISOLATE\\sim_radar_utils\\utils_radar.py", + "source_location": "L103", + "id": "utils_radar_plot_range_aoa", + "community": 4, + "norm_label": "plot_range_aoa()" + }, + { + "label": "main.py", + "file_type": "code", + "source_file": "src\\main.py", + "source_location": "L1", + "id": "src_main_py", + "community": 2, + "norm_label": "main.py" + }, + { + "label": "parse_args()", + "file_type": "code", + "source_file": "src\\main.py", + "source_location": "L34", + "id": "main_parse_args", + "community": 2, + "norm_label": "parse_args()" + }, + { + "label": "main()", + "file_type": "code", + "source_file": "src\\main.py", + "source_location": "L85", + "id": "main_main", + "community": 2, + "norm_label": "main()" + }, + { + "label": "src/main.py ----------- Scenario-agnostic orchestrator for the CARLA ADAS simu", + "file_type": "rationale", + "source_file": "src\\main.py", + "source_location": "L1", + "id": "main_rationale_1", + "community": 2, + "norm_label": "src/main.py ----------- scenario-agnostic orchestrator for the carla adas simu" + }, + { + "label": "recorder.py", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L1", + "id": "src_recorder_py", + "community": 3, + "norm_label": "recorder.py" + }, + { + "label": "Recorder", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L12", + "id": "recorder_recorder", + "community": 3, + "norm_label": "recorder" + }, + { + "label": ".__init__()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L13", + "id": "recorder_recorder_init", + "community": 3, + "norm_label": ".__init__()" + }, + { + "label": "._async_save_image()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L39", + "id": "recorder_recorder_async_save_image", + "community": 3, + "norm_label": "._async_save_image()" + }, + { + "label": ".save()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L44", + "id": "recorder_recorder_save", + "community": 3, + "norm_label": ".save()" + }, + { + "label": ".close()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L214", + "id": "recorder_recorder_close", + "community": 1, + "norm_label": ".close()" + }, + { + "label": "._generate_videos()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L223", + "id": "recorder_recorder_generate_videos", + "community": 3, + "norm_label": "._generate_videos()" + }, + { + "label": "._get_actor_class()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L253", + "id": "recorder_recorder_get_actor_class", + "community": 3, + "norm_label": "._get_actor_class()" + }, + { + "label": "._calculate_relative_metrics()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L264", + "id": "recorder_recorder_calculate_relative_metrics", + "community": 3, + "norm_label": "._calculate_relative_metrics()" + }, + { + "label": "._to_local_location()", + "file_type": "code", + "source_file": "src\\recorder.py", + "source_location": "L305", + "id": "recorder_recorder_to_local_location", + "community": 3, + "norm_label": "._to_local_location()" + }, + { + "label": "Helper to save image in a background thread.", + "file_type": "rationale", + "source_file": "src\\recorder.py", + "source_location": "L40", + "id": "recorder_rationale_40", + "community": 3, + "norm_label": "helper to save image in a background thread." + }, + { + "label": "Stitch captured frames into .mp4 files for easy viewing.", + "file_type": "rationale", + "source_file": "src\\recorder.py", + "source_location": "L224", + "id": "recorder_rationale_224", + "community": 3, + "norm_label": "stitch captured frames into .mp4 files for easy viewing." + }, + { + "label": "Categorise actor into broad ADAS classes.", + "file_type": "rationale", + "source_file": "src\\recorder.py", + "source_location": "L254", + "id": "recorder_rationale_254", + "community": 3, + "norm_label": "categorise actor into broad adas classes." + }, + { + "label": "Calculate relative range, azimuth, and closing velocity. Uses right-han", + "file_type": "rationale", + "source_file": "src\\recorder.py", + "source_location": "L265", + "id": "recorder_rationale_265", + "community": 3, + "norm_label": "calculate relative range, azimuth, and closing velocity. uses right-han" + }, + { + "label": "Helper to convert world location to transform-local location.", + "file_type": "rationale", + "source_file": "src\\recorder.py", + "source_location": "L306", + "id": "recorder_rationale_306", + "community": 3, + "norm_label": "helper to convert world location to transform-local location." + }, + { + "label": "scenario_loader.py", + "file_type": "code", + "source_file": "src\\scenario_loader.py", + "source_location": "L1", + "id": "src_scenario_loader_py", + "community": 5, + "norm_label": "scenario_loader.py" + }, + { + "label": "list_scenarios()", + "file_type": "code", + "source_file": "src\\scenario_loader.py", + "source_location": "L28", + "id": "scenario_loader_list_scenarios", + "community": 5, + "norm_label": "list_scenarios()" + }, + { + "label": "load_scenario()", + "file_type": "code", + "source_file": "src\\scenario_loader.py", + "source_location": "L45", + "id": "scenario_loader_load_scenario", + "community": 5, + "norm_label": "load_scenario()" + }, + { + "label": "src/scenario_loader.py ---------------------- Dynamic scenario discovery and loa", + "file_type": "rationale", + "source_file": "src\\scenario_loader.py", + "source_location": "L1", + "id": "scenario_loader_rationale_1", + "community": 5, + "norm_label": "src/scenario_loader.py ---------------------- dynamic scenario discovery and loa" + }, + { + "label": "Discover all scenario modules inside the 'scenarios' package. Returns a sort", + "file_type": "rationale", + "source_file": "src\\scenario_loader.py", + "source_location": "L29", + "id": "scenario_loader_rationale_29", + "community": 5, + "norm_label": "discover all scenario modules inside the 'scenarios' package. returns a sort" + }, + { + "label": "Dynamically import scenario module 'scenarios.' and return an instance", + "file_type": "rationale", + "source_file": "src\\scenario_loader.py", + "source_location": "L46", + "id": "scenario_loader_rationale_46", + "community": 5, + "norm_label": "dynamically import scenario module 'scenarios.' and return an instance" + }, + { + "label": "sensors.py", + "file_type": "code", + "source_file": "src\\sensors.py", + "source_location": "L1", + "id": "src_sensors_py", + "community": 2, + "norm_label": "sensors.py" + }, + { + "label": "SensorManager", + "file_type": "code", + "source_file": "src\\sensors.py", + "source_location": "L12", + "id": "sensors_sensormanager", + "community": 2, + "norm_label": 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