Skip to main content

NC² NetCDF viewer

Project description

Welcome To NC²

PyPI version

What are NetCDF Files?

NetCDF (Network Common Data Form) is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. NetCDF files are widely used in climate science, meteorology, oceanography, and other fields to store and distribute large datasets. These files are valuable for their ability to store multi-dimensional data (such as temperature, humidity, and wind speed) efficiently, making them essential for researchers and scientists dealing with complex environmental data.

NCview and Panoply

Programs such as NCview and Panoply have become indispensable tools for scientists working with NetCDF files.

NCview: NCview is a simple yet powerful visual browser for NetCDF files. It allows users to quickly view the data stored in these files through various plotting options. NCview is particularly useful for scientists who need to quickly check the contents of their datasets.

Panoply: Panoply, developed by NASA, is another powerful tool that provides more advanced features than NCview. It allows users to visualize georeferenced and other arrays from NetCDF, HDF, and GRIB datasets. Panoply offers a range of plotting options, including latitude-longitude, latitude-vertical, and time-latitude plots, making it a versatile tool for in-depth data analysis.

Both NCview and Panoply are essential for scientists who need to visualize and analyze their data quickly. However, these tools come with limitations, such as less intuitive user interfaces and a lack of customization options for publication-quality plots.

What is NC²?

Logo4

NC² is a next-generation NetCDF viewer designed to overcome the limitations of traditional tools like NCview and Panoply. Built with CartoPy and Matplotlib, NC² offers a versatile and user-friendly platform for visualizing and analyzing NetCDF data. Here’s what NC² brings to the table:

Modern GUI: NC² features a clean and intuitive graphical user interface (GUI) that significantly reduces the learning curve for new users. 

Familiar Tools: NC² is built with familiar scientific Python libraries, including CartoPy for cartographic projections and Matplotlib for plotting. This makes it easy for users who are already familiar with these tools to extend and customize their data visualizations.

Publication-Quality Plots: One of the standout features of NC² is its ability to produce publication-quality plots. Users can create highly customizable plots that meet standards required for scientific publications, ensuring that their visualizations are both accurate and aesthetically pleasing.

Versatility: NC² is designed to handle a wide range of NetCDF data types. Whether you are working with atmospheric data, oceanographic measurements, or climate model outputs, NC² provides the tools you need to visualize and analyze your data effectively.

Easy Customization: NC² offers a variety of customization options, allowing users to tailor their plots to their specific needs. From adjusting color maps and scales to adding annotations and labels, NC² makes it easy to create detailed and informative visualizations.

Advanced Features: In addition to basic plotting functionalities, NC² provides advanced features such as time series analysis, depth profiling, and GIF generations. These features enable users to gain deeper insights into their data and conduct more comprehensive analyses.

Explore the features and capabilities of NC², and see how it can enhance your research and data analysis workflows.

Screenshot from 2024-07-23 22-41-41

Installation

To install NC², run the following command:

pip install nc2

After installation, you can run NC² from the command line as follows:

nc2 path/to/your/file.nc

Contact Me!

rhettadambusiness@gmail.com

Rhett R. Adam 7/25/24

VU Undergrad EES

License

NC² is distributed under the GPL-3.0 License. See the LICENSE file for details.

Copyright (c) 2024 Rhett R. Adam

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nc2-0.2.1.tar.gz (38.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

nc2-0.2.1-py3-none-any.whl (34.7 kB view details)

Uploaded Python 3

File details

Details for the file nc2-0.2.1.tar.gz.

File metadata

  • Download URL: nc2-0.2.1.tar.gz
  • Upload date:
  • Size: 38.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.2

File hashes

Hashes for nc2-0.2.1.tar.gz
Algorithm Hash digest
SHA256 0e7179bb3780041fb1fe2ee80b63f166bffe3b0d3833b7066064c6b91b3c8cd6
MD5 60bd7b819563d8599b3559a2b5b4dee0
BLAKE2b-256 4524b16eb4195c227aa82a79e6181f52e2c7281e952233ddab508cc03d211dcf

See more details on using hashes here.

File details

Details for the file nc2-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: nc2-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 34.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.2

File hashes

Hashes for nc2-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 eb8d5c03b48d725b6c48fb26aeefa1d525d9f4e14f4c9749ba6569971e686d2b
MD5 6b7d5a9f3257f94e58350c3eff71561c
BLAKE2b-256 720afd180bbed11e2e33b8ffc5a8d1a6d106036e5b12e624a6c491202df90576

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page