Updated and structured scripts to evaluate electric and video data of two competing fish in staged competition experiments.
complete_analysis.py | ||
eval_LED.py | ||
event_time_analysis.py | ||
event_videos.py | ||
id_meta.csv | ||
LED_detect.py | ||
order_meta.csv | ||
README.md | ||
trail_analysis.py | ||
trial_summary_eval.py | ||
trial_summary.csv |
How to competition experiment
Workflow (Python-scripts/applications):
- wavetracker.trackingGUI
- wavetracker.EODsorter
- LED_detect.py
- eval_LED.py
- trial_analysis.py
- event_videos.py (optional)
Raw data analysis using the wavetracker-modul
trackingGUI.py
Frequency extraction and tracking
- open Raw-file (traces-grid1.raw)
- 'Spectrogram'-settings:
- overlap fraction: 0.8
- frequency resolution: 1
- check 'Auto-save'; press 'Run'
Fine spectrogram
- repeat steps above but press 'Calc. fine spec' instead of Run
- fine spec data saved in /home/"user"/analysis/"filename"
EODsorter.py
- load dataset/folder
- correct tracked EOD traces
- fill EOD traces
- fine spec data needs to be manually added to the dataset-folder
Competition trial analysis
trail_analysis.py
- Detection of winners, their EODf traces, rises, etc. Results stored in "data-path"/analysis.
- (optional) Meta.csv file in base-path of analyzed data. Creates entries for each analyzed recording (index = file names) and stores Meta-data. Manual competation suggested.
Video analysis
LED_detect.py
- Detect blinking LED (emitted by electric recording setup). Used for synchronization.
- "-c" argument to identify correct detection area for LED
- '-x' (tuple) borders of LED detection window on X-axis (in pixels)
- '-y' (tuple) borders of LED detection window on Y-axis (in pixels)
eval_LED.py
- creates time vector to synchronize electric and video recording
- for each frame contains a time-point (in s) that corresponds to the electric recordings.
Rise videos (optional)
- generates for each detected rise a short video showing the fish's behavior around the rise event.
- sorted in 'base-path'/rise_video.