We are an engineering services company that focus on drone technologies. We decided to opensource TiPlot, our log visualising tool, so the world can benefit from a nice and easy way to display logs from PX4, CSV, or even from your Python code or your Jupyter Notebook.
Please reach out to us via our website Tilak.io, we are happy to help !
TiPlot is an open-source visualisation tool for flight logs. With TiPlot, you can easily visualize your flight data in 2D graphs and a 3D view, helping you better understand the performance and behavior of your unmanned aerial vehicle (UAV).
- Supports multiple file formats, including :
- PX4's .ulg
- Generic .csv
- DJI's .DAT
- QGroundControl's .tlog
- Ardupilot's .BIN Logs.
- 2D yt and xy graphs for visualizing flight data.
- 3D viewer for displaying the paths of your UAVs.
- Add multiple UAVs to compare flights.
- Sync the 3D view with a specific timestamp by hovering over it.
- Perform customized operations on data currently being processed.
- Ability to send a data dictionary and entities to be displayed in the 3D view over TCP port
5555from a Python script or a Jupyter notebook. - Layouts are automatically saved after every change.
- Drag and drop plots to reposition them.
- Plot multiple fields from different topics in yt graphs.
- X scale of all graphs is synced when zooming in.
- Y scale of graphs is automatically set to fit all available data in the timestamp range.
- Change view layout from split to detached to detach the 3D view as a new window.
- Adjust camera settings and change background color and show grids on the 3 axis in the settings page.
To run TiPlot using the prebuilt AppImage, follow these steps:
- Download the latest AppImage from the releases page.
- Make the AppImage executable by running:
cd ~/Downloads
chmod +x tiplot-1.x.x.AppImage- Run the AppImage:
./tiplot-1.x.x.AppImageTo build TiPlot from source, follow these steps:
- Clone the repository:
git clone https://github.com/tilak-io/tiplot
cd tiplot
- Install dependencies:
# Install Node dependencies
yarn install
# Install Python dependencies:
pip3 install -r api/requirements.txt
- Start the API server:
yarn start:api
In a new terminal, start the front end:
yarn start
To use TiPlot, follow these steps:
- Launch TiPlot's AppImage, exe or compiled build.
- Click the "Browse" button to select a flight log file.
- Add a graph (yt or xy).
- Use the ALT + hover feature to sync the 3D view with a specific timestamp.
- Use the entities page to choose the UAV's position/attitude tables.
To send data to TiPlot from a Python script or Jupyter notebook, you can use the following code:
import zmq
import zlib
import pickle
import pyulog
import pandas as pd
port = '5555'
context = zmq.Context()
socket = context.socket(zmq.REQ)
socket.connect("tcp://0.0.0.0:%s" % port)
def send_zipped_pickle(socket, obj, flags=0, protocol=-1):
p = pickle.dumps(obj, protocol)
z = zlib.compress(p)
return socket.send(z, flags=flags)
send_zipped_pickle(socket, [datadict, []])Note that datadict is the data dictionary returned by the parser.
[] is the entities array (empty array means we don't want to display anything on 3d view)
For more info check out the Jupyter notebooks in the templates folder.
In this guide, we will walk you through the process of creating and executing sequences, which are Python functions containing a set of operations to manipulate log data. These sequences can be customized to suit your specific needs. Follow these steps to get started:
-
Set Preferred Editor: Ensure that you have configured your preferred code editor in the tool settings by navigating to
Tools > Settings > General > External Editor. If you intend to use a terminal-based editor such as Vim or Nano, make sure to specify the appropriate command to launch the terminal. (i.e:kitty nvimfor kitty,gnome-terminal -- nvimfor ubuntu's default terminal,xterm -e nvimfor xterm...) -
Create a New Sequence: To begin, create a new sequence by navigating to
Tools > Sequences > Add New Sequence. -
Provide a Descriptive Name: Give your sequence a meaningful and descriptive name that reflects its purpose.
-
Edit the Sequence: Upon creating a new sequence, your preferred code editor will open with a template function. You can now define the operations you want to perform on the log data.
Here's an example of a sequence that transforms log data from the NED (North-East-Down) representation to the ENU (East-North-Up) representation for a topic called vehicle_local_position_enu:
def handle_data(datadict):
import numpy as np
new = datadict
# Coordinate transformation matrix from NED to ENU
NED_to_ENU = np.array([
[0, 1, 0], # East (ENU X) corresponds to North (NED Y)
[1, 0, 0], # North (ENU Y) corresponds to East (NED X)
[0, 0, -1] # Up (ENU Z) corresponds to -Down (NED Z)
])
# Apply the coordinate transformation to the 'x', 'y', and 'z' columns
new['vehicle_local_position_enu'] = new['vehicle_local_position'].copy()
xyz_ned = new['vehicle_local_position_enu'][['x', 'y', 'z']].values
xyz_enu = np.dot(xyz_ned, NED_to_ENU.T) # Transpose the transformation matrix for NED to ENU
new['vehicle_local_position_enu'][['x', 'y', 'z']] = xyz_enu
return newNOTE: the imports should be inside the function
Feel free to adapt and customize your sequence function to perform the operations that are relevant to your data processing needs.
Happy sequencing 🎉!
We welcome contributions to TiPlot. If you would like to contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your changes.
- Make your changes and commit them to your branch.
- Push your branch to your forked repository.
- Create a new pull request.
This project is licensed under the Apache License, Version 2.0. See the LICENSE file for details.
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