Note

The lib is still under development and is not fully usable at this time

General Info

Library to process, format, and analyze BlueDrop accelerometer data. The main functions and classes are in the lib folder. An example is provided using the library for the analysis of a folder of BlueDrop data.

Instructions to set up BlueDrop Analysis on your computer

Purpose

The purpose of these instructions are to set up BlueDrop Analysis on your own computer. These instructions are subject to change in the future. The goal for this repo is to change it to be a python package hosted through conda.

Necessary downloads

The necessary downloads to use this code are:

1) An IDE that can run jupyter notebooks (VS Code is what I recommend, VS Code Download link) 2) git, link 3) Anaconda (or miniconda), miniconda link

Steps to get started with BlueDrop Analysis Lib

1) Clone the repo to a local folder using the following command in your terminal:

git clone https://github.com/UF-Coastal-Geotech/BlueDrop_Analysis_Lib.git

2) Use VS Code to open the newly cloned BlueDrop_Analysis_Lib folder

3) Using the side menu view the Examples folder and open the Example_PFFP_walkthrough.ipynb file. This is a jupyter notebook and walks through some of the common steps and functions that are used to process PFFP data files.

4) On Windows open the Anaconda Prompt or on Linux open a terminal of your choice that has conda added to it.

The purpose of the next couple of steps are to use conda and the environment.yml file to install all the necessary packages and modules to run the all the functions in the library.

5) Using the terminal change your working directory to the BlueDrop_Analysis_Lib folder.

6) The following is the command is the command to create the conda environment

If on windows run the following command in the ```conda``` terminal: 
```python
conda env create --file environment_win.yml --name PFFP_Analysis
```

If on linux run the following command:
```conda
conda env create --file environment.yml
```

Installing the packages may take a few minutes.

7) Activate the PFFP_Analysis conda environment.

• The easiest way to do this in VS Code is to try running a cell in Example_PFFP_walkthrough.ipynb. VS Code should ask you which kernel you want to use. Choose Python Environments > PFFP_Analysis

8) Once the Python Kernel is selected and the cells in Example_PFFP_walkthrough.ipynb are running you are good to go.