CMSC6950_Project

CMSC6950_Project | ARGOPY | Lavan [201990251]

Installation instruction

Create a conda environment

$ conda create -n env_name python=3.8.5

Activate the conda environment

$ conda activate my_env

Clone the project and change to project directory

$ git clone https://github.com/lavanthaya/CMSC6950_Project.git

$ cd CMSC6950_Project

Run below command to install the dependencies

$ make install

To check the argopy installation run below command in Python shell

from argopy import DataFetcher as ArgoDataFetcher

ArgoPy fetch data from "Argovis" or "Erddap" you can check those server status below

Run make file to execute the project

$ make

You can pass below set of arguments(optional) while running make file (given below are default values)

Lon_min=-75, Lon_Max=-45, Lat_min=20, Lat_max=30, depth_min=0, depth_max=70, year_start=2011, year_end=2012, source=argovis

Example:

$ make source=erddap depth_max=100

Final output can be accessed via below urls (Ctrl + C to stop the server)

http://local-ip:8080/OceanTemp.gif

http://local-ip:8080/Ocean_Sspeed_Temp.gif

http://local-ip:8080/Ocean_Sspeed_Sal.gif

Output Visualization:

Task-01 Visualization

Ocean Temperature Plot on Geo Coordinates, Monthly Visualization

Task-02 Visuaization

Sound Speed Vs Depth Plot With Temperature, Monthly Visualization

Sound Speed Vs Depth Plot With Salinity, Monthly Visualization

Finally, run below command to clean

$ make clean

Reference

Maze et al., (2020). argopy: A Python library for Argo ocean data analysis. Journal of Open Source Software, 5(53), 2425, https://doi.org/10.21105/joss.02425