Dan-Boat/alx-low_level_programming

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Dan-Boat/alx-low_level_programming

Dan-Boat

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This repository contains all the project files for low level programming in the alx software engineering program

PyESD

Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of the package is to downscale any climate variables e.g. precipitation and temperature using predictors from reanalysis datasets (eg. ERA5) to point scale. pyESD adopts many ML and AL as the transfer function.

pyClimat

This repository contains scripts for Python Module for Climate Data Analysis and Visualization, which is under development. The module performs many climate data analysis like correlation, significance testing, causality testing, estimation of climatologies, etc. The current version of package can be used, however, it must be handle with caution since most of the functions are yet to be tested. Kindly contact me for help if required.

TrajView

Python module for trajectory visualization. The module utilizes basemap or cartopy as a backgroup map and mathplotlib linecolections to plot the paths of the trajectories.

Lagranto_echam

This repository contains modified lagranto trajectory model for tracking moisture sources or other related analysis with ECHAM model output. The original installation guide has been modified for easy installation of the relevant programs in a directory by just linking path of installation to netcdf libraries in the Makefile of the source code repository. The test folder contains sample scripts for running the modified package. Read the original module from Sprenger, M. and Wernli, H.: The LAGRANTO Lagrangian analysis tool – version 2.0, Geosci. Model Dev., 8, 2569–2586, https://doi.org/10.5194/gmd-8-2569-2015, 2015 for more details.

Data_science_projects

Consist of various machine learning and Al projects at the experimental stage. These scripts are adopted on higher level structure required for my package development. Therefore I call it no harm in trying folder...Enjoy

Jupyter Notebook