Displaying 1 to 18 from 18 results

satpy - Python package for earth-observing satellite data processing

  •    Python

The Satpy package is a python library for reading and manipulating meteorological remote sensing data and writing it to various image and data file formats. Satpy comes with the ability to make various RGB composites directly from satellite instrument channel data or higher level processing output. The pyresample package is used to resample data to different uniform areas or grids. The documentation is available at http://satpy.readthedocs.org/.

stumpy - STUMPY is a powerful and scalable Python library for modern time series analysis

  •    Python

Whether you are an academic, data scientist, software developer, or time series enthusiast, STUMPY is straightforward to install and our goal is to allow you to get to your time series insights faster. See documentation for more information. Please see our API documentation for a complete list of available functions and see our informative tutorials for more comprehensive example use cases. Below, you will find code snippets that quickly demonstrate how to use STUMPY.

mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions

  •    Python

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and many other libraries. More details about installing Mars can be found at installation section in Mars document.

distributed - Distributed computation in Python

  •    Python

A library for distributed computation. See documentation for more details.

dask-ec2 - Start a cluster in EC2 for dask.distributed

  •    Python

Easily launch a cluster on Amazon EC2 configured with dask.distributed, Jupyter Notebooks, and Anaconda. Note: dask-ec2 uses boto3 to interact with Amazon EC2. You can configure your AWS credentials using Environment Variables or Configuration Files.


  •    TypeScript

A JupyterLab extension for dask.

knit - Python interface to YARN

  •    Python

The knit library provides a Python interface to Scala for interacting with the YARN resource manager. View the documentation for knit.

dask-jobqueue - Deploy Dask on job schedulers like PBS, SLURM, and SGE

  •    Python

Easy deployment of Dask Distributed on job queuing systems such as PBS, Slurm, or SGE. See documentation for more information. New BSD. See License File.

bytehub - ByteHub: making feature stores simple

  •    Python

An easy-to-use feature store. A feature store is a data storage system for data science and machine-learning. It can store raw data and also transformed features, which can be fed straight into an ML model or training script.

cesm-lens-aws - Examples of analysis of CESM LENS data publicly available on Amazon S3 (us-west-2 region) using xarray and dask

  •    Jupyter

Examples of analysis of CESM LENS data publicly available on Amazon S3 (us-west-2 region) using xarray and dask. This catalog is an ESM collection catalog. The data is stored in Zarr format and meant to be opened with Xarray.

esmlab - Earth System Model Lab (esmlab)

  •    Python

Tools for working with earth system multi-model analyses with xarray. See documentation for more information.

ncar-python-tutorial - Numerical & Scientific Computing with Python Tutorial

  •    Jupyter

NOTE: For windows users, setup scripts provided in this repository don't work on Windows machines for the time being. NOTE: Be prepared for the script to take up to 15 minutes to complete.

pyresample - Geospatial image resampling in Python

  •    Python

Pyresample is a python package for resampling geospatial image data. It is the primary method for resampling in the Satpy library, but can also be used as a standalone library. Resampling or reprojection is the process of mapping input geolocated data points to a new target geographic projection and area. Pyresample can operate on both fixed grids of data and geolocated swath data. To describe these data Pyresample uses various "geometry" objects including the AreaDefinition and SwathDefinition classes.

lazycluster - 🎛 Distributed machine learning made simple.

  •    Python

Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. lazycluster is a Python library intended to liberate data scientists and machine learning engineers by abstracting away cluster management and configuration so that they are able to focus on their actual tasks. Especially, the easy and convenient cluster setup with Python for various distributed machine learning frameworks is emphasized.

climpred - :earth_americas: Verification of weather and climate forecasts. :earth_africa:

  •    Python

Verification of weather and climate forecasts. We are actively looking for new contributors for climpred! Riley moved to McKinsey's Climate Analytics team. Aaron is finishing his PhD, but will stay in academia. We especially hope for python enthusiasts from seasonal, subseasonal or weather prediction community. In our past coding journey, collaborative coding, feedbacking issues and pull requests advanced our code and thinking about forecast verification more than we could have ever expected. Aaron can provide guidance on implementing new features into climpred. Feel free to implement your own new feature or take a look at the good first issue tag in the issues. Please reach out to us via gitter.

pangeo-binder - Pangeo + Binder (dev repo for a binder/pangeo fusion concept)

  •    Python

Deployment and configuration documentation files for the public binder.pangeo.io service. Monitoring of the binderhubs is done with Prometheus and Grafana.

paperboy - A web frontend for scheduling Jupyter notebook reports

  •    Python

Paperboy is a production-grade application for scheduling reports. It has a flexible architecture and extensible APIs, and can integrate into a wide variety of deployments. It is composed of various industrial-strength technologies from the open source world. Paperboy requires Python and Node.js, which can be installed from conda-forge if conda is available.

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