https://github.com/phuijse/bokeh_light_curve_inspector
A simple pure-python web browser application using Bokeh to visualize, inspect and label periodic astronomical time series
https://github.com/phuijse/bokeh_light_curve_inspector
astronomy bokeh interactive light-curves time-series
Last synced: 7 months ago
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A simple pure-python web browser application using Bokeh to visualize, inspect and label periodic astronomical time series
- Host: GitHub
- URL: https://github.com/phuijse/bokeh_light_curve_inspector
- Owner: phuijse
- License: mit
- Created: 2017-09-21T02:16:04.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2017-09-21T20:14:49.000Z (about 8 years ago)
- Last Synced: 2025-01-15T13:05:30.756Z (9 months ago)
- Topics: astronomy, bokeh, interactive, light-curves, time-series
- Language: Python
- Homepage:
- Size: 212 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Bokeh Light Curve Inspector
A simple pure-python web browser application using Bokeh (bokeh.pydata.org) to visualize, inspect and label periodic astronomical time series. Possible use-cases are novelty detection, collaborative research and crowd-sourcing. **Disclaimer:** This code was written for educative purposes and it is not safe for production (see TODO below).
## How to run
cd this_folder
mkdir example/results
bokeh serve . --args example/light_curves example/periods.pkl example/results
Then point your favorite web browser to
http://localhost:5006
### Note about the arguments
The Bokeh server allows to pass arguments to the main code using the *--args* flag. Three arguments are expected:
1. Path to the folder containing the light curve files
2. Path to a pickle file containing file names and light curve periods
3. Path to a folder to dump results from labeling process
Reading and parsing of the light curve files is done in light\_curve\_handler.py
### What you should see when running the example
Log-in interface:
Inspector interface:
### How does it work
* Choose a username and hit enter at the log-in interface
* You should be seeing the inspector interface. Here you can:
* Move from page to page, each showing a set of 9 light curves
* Label the currently selected light curve into one of the available categories
* Each time you move to the next/previous page your labeling results are saved at *resultfolder/username/*
### Remote access to the bokeh server
If you intend to access the bokeh server from another machine in your LAN you will have to add
--allow-websocket-origin=myserverlanip:5006
before *--args* in the execution line above
If you intend to access from outside your LAN just change myserverlanip by the desired domain. Bokeh serve also accepts a *--port* option if you need to use a different port
## Requirements
1. Numpy (numpy.org)
2. Bokeh (bokeh.pydata.org)
Note: Tested with Python 3.6 and Bokeh 0.12.6
## TODO
* ~~Add test data~~
* Improve server security to make this safe for production
* Add user authentication, sessions, etc
## License
MIT