Project Heimdall is a stand-alone web-based application using Streamlit.io to identify and categorize X-ray bursts.
Submission for the Inter-IIT Tech Meet's Mid Prep event: ISRO'S Web-Based Automatic Identifiaction Of Solar Bursts In X-Ray Light Curves
Team: MP_ISRO_T8
An active internet connection is required to run the application, unless you build the application from source. In order to build application from source, click here
- Download and unzip the zip file from here
- Once unzipped, click on
Heimdall.exe
to launch the application
- Download and unzip the zip file from here
- Once unzipped, click on
Heimdall.app
to launch the application
- Download and unzip the zip file from here
- Once unzipped, run the following command to cd into the dirctory using the terminal
cd Heimdall-linux-x64
- Then run the following command to run the binary
./Heimdall
- Python3
- Clone the repository using
git clone https://github.com/Heimdallr-Rig/MP_ISRO_T8.git
- Create a virtual environment, using:
virtualenv venv
- Activate the virtual environment using:
source venv/bin/activate
cd
into the repo and install dependencies using the following command
pip install -r requirements.txt
- Run the app using
streamlit run app.py
- On successful deployment you should get the following output. Click on the Local URL to open the application in your browser
You can now view your Streamlit app in your browser.
Local URL: http://localhost:8501
Network URL: http://xx.xx.xx.xx:8501
Once the app is up and running , you'll be welcomed with a very simple welcome screen with an upload option.
We support the following file extensions:
lc, csv, ascii, txt, xls, xlsv, xlsm, xlsb, odf, odt
The files are then extracted for data using a pretty neat library called Astropy. This data is then further processed using various methods and processed.
To know if the app is processing your data, look at the upper right corner to see the status of your upload
Once done, we get the following outputs. Each section comes with a description of each of our steps, making it easier to follow along
In order to get the output shown below we used the ch2_xsm_20211111_v1_level2.lc
file under the data
directory here
Here we visualise the data with a graph to plot the raw data before any processing
Heimdall being a web app has dynamic graphs that are interactive, improving accessibility by supporting dragging and scrolling. You can also hover your mouse over points on the graph to view it's co-ordinates.
Visit https://bevel-bass-f2e.notion.site/Project-Heimdall-252649f8745b441d88cc9173f43179bc for more details