royalosyin Goto Github PK

100daysofcode-with-python-course

Course materials and handouts for #100DaysOfCode in Python course

a-beginner-guide-to-carry-out-extreme-value-analysis-with-codes-in-python

A beginner's guide to carry out extreme value analysis, which consists of basic steps, multiple distribution fitting, confidential intervals, IDF/DDF, and a simple application of IDF information for roof drainage design. The guide mainly focuses on extreme rainfall analysis. However, the basic steps are also suitable for other climatic or hydrologic variables such as temperature, wind speed or runoff.

ansible

Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications— automate in a language that approaches plain English, using SSH, with no agents to install on remote systems.

atspy

Automated Time Series Models in Python (AtsPy)

auto-sklearn

Automated Machine Learning with scikit-learn

calculate-precipitation-based-agricultural-drought-indices-with-python

Precipitation-based indices are generally considered as the simplest indices because they are calculated solely based on long-term rainfall records that are often available. The mostly used precipitation-based indices consist of Decile Index (DI) Hutchinson Drought Severity Index (HDSI) Percen of Normal Index (PNI) Z-Score Index (ZSI) China-Z Index (CZI) Modified China-Z Index (MCZI) Rainfall Anomaly Index (RAI) Effective Drought Index (EDI) Standardized Precipitation Index (SPI).

climate_indices

Climate indices for drought monitoring, community reference implementations in Python

concord

Coordinate conversion program - unix implementation

create-concise-charts-for-reporting

Some practical tutorials for creating concise charts for project summary reporting. At present, only focus on Line and Bar Charts. It might be extended in the future

crossfilter-1

Fast n-dimensional filtering and grouping of records.

cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more (from UC Berkeley)

datasette

A tool for exploring and publishing data

datetime-fortran

Date and time manipulation for modern Fortran

docker-node.js

Docker build Node.js development environment

dockermet

Using Docker Compose to rapidly deploy a Jupyter Notebook environment for processing meteorological and climatic data. The Dockerfile was created based on the data-science stack image from Jupyter project. Besides default tools and packages, only added several met-clim specific packages such as xarray and dask for netCDF, sfgrib for Grib1/2, and MetPy for met.

elves

开源自动化运维开发平台(IT Automatic Develop Platform)

evapo_gfs

calculate EVAPOTRANSPIRATION (Et0) from GFS data on a specific area and for a date within the last 14 days

explain-100-year-weather-events-with-python

fastapi-zarr-xarray-dask

A demo of FastAPI application to extract data at the specific points defined by [latitudes and longitudes] from a zarr dataset using Dask and Xarray. The key aim to speed up point data extraction from data in zarr formats using dask's local cluster.

fill-missing-values

Functions used to fill missing values in a 2D array or matrix. Mostly written by Fortran.

fimex

File Interpolation, Manipulation and EXtraction

fortran-ls-svm

Support Vector Machine aplication written in fortran 90

fortran-string-utility-module

fswatch-rsync

Watches and synchronizes a local folder with a remote folder via another server over ssh

functional-fortran

Functional programming for modern Fortran

geoviews

ghcnpy

Package to import, analyze, and visualize data from the Global Historical Climatology Network - Daily (GHCN-D) Dataset 0

grads

Scripts to pull NCEP atmospheric science data and visualize with GrADS

grads-1

GrADS scripts

grib2json

converts GRIB2 files to JSON