Expert’s Guide

Customizing your workflow

The documentation on previous tutorial covered all basic pamflow’s functionalities through a simple example on available data. For the sake of continuity, this tutorial will be based on the same data but covering functionalities relevant users trained in python coding. Due to this we assume you are already fammiliar with the data and already ran pamflow with it. Hopefully, at the end you will be able to extend pamflow to cover the specific of your project.

Context: Continuation of The Guaviare Project The National biodiversity institute in Colombia, the Humboldt Institute, collaborated with communities at Guaviare, Colombia to perform a communitary project on the local bird fauna. You already processed all the passively collected acoustic data and based on your resulting insights, you now want to calculate some statistics on the detections. Instead of taking the outputs and working with them independently from pamflow, you will leverage its convenient architecture and functionalities to complete your task.

Your tasks:

1. Generate a table showing the diel activity pattern for each target species.

2. Generate spider plots showing diel activity patterns for the target species.

3. Generate KDE plots showing diel activity patterns for the target species.

On each of the followig sections you will find relevant information on how to use pamflow to complete all of your tasks. Next session is devoted to show you how to use pamflow’s jupyter notebook kernel to keep your code development clean.