Visualization utilities for IMU factor evaluation. Supports Plotly (interactive HTML) and Matplotlib (static PNG) outputs, with per-trace legend toggling in all interactive plots.
# From source
cd python
pip install -e .
# Or install dependencies directly
pip install numpy pandas plotly matplotlibfrom imuFactors.vis import (
load_trajectory_from_build,
plot_3d_trajectory_multi_interval,
plot_position_timeseries_multi_interval,
)
# Interactive 3-D plot comparing all preintegration intervals — opens in browser
fig = plot_3d_trajectory_multi_interval("MH01", filter_name="gal3", build_dir="./build")
fig.show()
# Save as self-contained HTML (legend-toggleable traces)
fig = plot_position_timeseries_multi_interval(
"MH01", filter_name="gal3", build_dir="./build",
save_path="./vis/MH01/html/position.html",
)This repository now includes a Delama Gal3 evaluator in
imuFactors.delama_gal3.preintegration_delama_gal3.
Install torch in your active Python environment, then run:
cd python
pip install -e .[delama_gal3]Then run from the repository root:
./.venv/bin/python python/run_delama_gal3.pyIf you are already inside the python/ directory, this also works:
python run_delama_gal3.pyCommon options:
python run_delama_gal3.py \
--dataset-glob "../data/euroc/euroc_*.csv" \
--output-dir "../build/results/delama_gal3" \
--alpha 8.4 \
--preint-times 0.2 0.5 1.0Outputs include per-sequence pickle files plus summary CSV files in the output directory.
The imuFactors.visualize_all script auto-discovers every dataset in the build folder and writes both PNG and HTML outputs.
# PNG + HTML for all datasets
python -m imuFactors.visualize_all --build-dir ./build --output-dir ./visualizations
# Specific datasets only
python -m imuFactors.visualize_all --datasets MH01 V202 V203 --build-dir ./build
# Specific intervals only
python -m imuFactors.visualize_all --datasets MH01 --intervals 2s 5s --build-dir ./build
# Interactive HTML only (no matplotlib required at runtime)
python -m imuFactors.visualize_all --no-png
# Static PNG only
python -m imuFactors.visualize_all --no-htmlvisualizations/
└── MH01/
├── 3d_trajectory.png
├── position.png
├── velocity.png
├── acceleration.png
├── orientation.png
├── displacement.png
└── html/
├── 3d_trajectory.html ← interactive, legend-toggleable
├── position.html
├── velocity.html
├── acceleration.html
├── orientation.html
└── displacement.html
Each HTML file is a standalone HTML document that does not require a local server; Plotly is loaded from the CDN. Open in any browser.
All Plotly figures support:
| Interaction | Action |
|---|---|
| Toggle a trace | Single-click its legend entry |
| Isolate a trace | Double-click its legend entry |
| Zoom / pan | Click-drag on the plot |
| Scroll zoom | Mouse wheel |
| Export PNG | Camera icon in the mode bar |
| Reset view | Home icon in the mode bar |
This lets you, for example, hide all predictions and examine ground truth alone, or isolate the 10 s preintegration interval against GT.
Loads CSV output from the C++ evaluation apps and exposes a TrajectoryData dataclass with separate gt_* and pred_* fields.
from imuFactors.vis import (
load_trajectory,
load_trajectory_from_build,
discover_intervals,
discover_all_datasets,
TrajectoryData,
DEFAULT_BUILD_DIR,
)
# Load a single CSV directly
traj = load_trajectory("gal3_trajectory_MH01_2s.csv")
# traj.gt_position → (N, 3) ground truth XYZ
# traj.pred_position → (N, 3) predicted XYZ
# traj.gt_velocity, traj.pred_velocity, traj.gt_rpy, traj.pred_rpy ...
# Load from build folder by name
traj = load_trajectory_from_build("gal3", "MH01", interval="2s", build_dir="./build")
# Discover what's available
datasets = discover_all_datasets("./build") # {"gal3": ["MH01", "V202", ...]}
intervals = discover_intervals("MH01", "gal3", "./build") # ["2s", "5s", "10s"]All functions accept an optional save_path argument. When provided, the figure is written to a self-contained HTML file automatically.
from imuFactors.vis import (
plot_3d_trajectory, # single TrajectoryData object
plot_3d_trajectory_multi_interval, # GT + all intervals from build folder
plot_3d_trajectory_from_build, # single interval from build folder
)
# Multi-interval comparison (most common)
fig = plot_3d_trajectory_multi_interval(
"MH01",
filter_name="gal3",
build_dir="./build",
intervals=["2s", "5s", "10s"], # omit to auto-discover
save_path="./vis/MH01/html/3d_trajectory.html",
)
fig.show()
# Single interval
fig = plot_3d_trajectory_from_build("MH01", interval="5s", build_dir="./build")
fig.show()Each function follows the same signature and produces a 3-row shared-x figure.
from imuFactors.vis import (
plot_position_timeseries_multi_interval,
plot_velocity_timeseries_multi_interval,
plot_acceleration_timeseries_multi_interval, # derived from velocity via finite diff
plot_orientation_timeseries_multi_interval, # roll, pitch, yaw (degrees)
plot_displacement_timeseries_multi_interval, # Δposition between timesteps
)
for plot_fn, name in [
(plot_position_timeseries_multi_interval, "position"),
(plot_velocity_timeseries_multi_interval, "velocity"),
(plot_acceleration_timeseries_multi_interval,"acceleration"),
(plot_orientation_timeseries_multi_interval, "orientation"),
(plot_displacement_timeseries_multi_interval,"displacement"),
]:
plot_fn(
"MH01",
filter_name="gal3",
build_dir="./build",
save_path=f"./vis/MH01/html/{name}.html",
)from imuFactors.vis import plot_best_worst_comparison_plotly, plot_comparison
# From build folder (loads BEST/WORST CSVs automatically)
fig = plot_best_worst_comparison_plotly(
"MH01",
filter_name="gal3",
build_dir="./build",
save_path="./vis/MH01/html/best_worst.html",
)
# From pre-loaded TrajectoryData objects
fig = plot_comparison(
"MH01", ground_truth=gt, best_trajectory=best, worst_trajectory=worst,
best_nees=0.42, worst_nees=3.71,
save_path="./vis/MH01/html/comparison.html",
)from imuFactors.vis import save_html
fig = plot_3d_trajectory_multi_interval("MH01", build_dir="./build")
save_html(fig, "./my_output/MH01_3d.html")from imuFactors.vis import (
# Single TrajectoryData
plot_position_timeseries,
plot_velocity_timeseries,
plot_acceleration_timeseries,
plot_orientation_timeseries,
plot_displacement_timeseries,
plot_3d_trajectory_matplotlib,
# Multi-interval comparisons (mirrors Plotly API)
plot_position_multi_interval,
plot_velocity_multi_interval,
plot_acceleration_multi_interval,
plot_orientation_multi_interval,
plot_displacement_multi_interval,
plot_3d_trajectory_multi_interval_matplotlib,
)
# Single-trajectory plots (require a loaded TrajectoryData)
traj = load_trajectory_from_build("gal3", "MH01", "2s", "./build")
plot_position_timeseries(traj, save_path="position.png")
plot_3d_trajectory_matplotlib(traj, save_path="trajectory_3d.png")
# Multi-interval comparison (loads from build folder, same API as Plotly versions)
plot_position_multi_interval("MH01", filter_name="gal3", build_dir="./build",
save_path="position_multi.png")
plot_3d_trajectory_multi_interval_matplotlib("MH01", build_dir="./build",
save_path="3d_multi.png")Output of evalExportTrajectories.cpp:
timestamp,
gt_x,gt_y,gt_z,
gt_vx,gt_vy,gt_vz,
gt_roll,gt_pitch,gt_yaw,
pred_x,pred_y,pred_z,
pred_vx,pred_vy,pred_vz,
pred_roll,pred_pitch,pred_yaw
See LICENSE in the repository root (BSD-3-Clause).