Skip to main content

A Python package for nonlinear paleoclimate data analysis

Project description

Ammonyte

Python package designed for conducting non-linear time series analysis of paleoclimate data. Recommended for usage in tandem with Pyleoclim. Developed by Alexander James with the University of Southern California Climate Dynamics Lab Group. Currently under heavy construction.

Much of Ammonyte's capability is enabled by PyRQA, a tool designed to conduct recurrence analysis in a massively parallel manner. Many of our functions are essentially wrappers around PyRQA functions, so we recommend looking into that package if you're curious about the bones of how recurrence analysis is done in Ammonyte.

Install instructions:

  1. It's recommended you create a new environment using anaconda before installing.

  2. Inside your environment install cartopy with the command conda install -c conda-forge cartopy

  3. Run pip install ammonyte

Things to note:

  • Current releases of Ammonyte are highly experimental. These are mainly done to facilitate our research, though others are welcome to use the functionality. Just be aware that the package is currently subject to constant change and will remain unstable for some time.

  • Certain functionalities such as RecurrenceNetwork and the synthetic_series utilities are currently non-functional and are acting as placeholders for features that will be included in the future.

  • This function has only been tested on macOS/Unix based operating systems, so if you encounter errors they may be system specific.

  • Raising issues/feature requests is appreciated but there is no guarantee they'll be addressed hastily at this stage of the package's development as we are focused on building core features that are of use to our lab.

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

ammonyte-0.0.5.tar.gz (31.9 kB view details)

Uploaded Source

Built Distribution

ammonyte-0.0.5-py3-none-any.whl (39.6 kB view details)

Uploaded Python 3

File details

Details for the file ammonyte-0.0.5.tar.gz.

File metadata

  • Download URL: ammonyte-0.0.5.tar.gz
  • Upload date:
  • Size: 31.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.9

File hashes

Hashes for ammonyte-0.0.5.tar.gz
Algorithm Hash digest
SHA256 83e6aa45a0c19f7fbff4a083aac2aecbbd9424967dc448587cbbea3aa443010e
MD5 675a6560f645637ad95570e838488388
BLAKE2b-256 92cd312229492b8ad9f9554d87e7cf2ad2dc8ceac95820e988f4befc49df57c3

See more details on using hashes here.

File details

Details for the file ammonyte-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: ammonyte-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 39.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.9

File hashes

Hashes for ammonyte-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 d20c196d374014091fd5fb35dade7637b92b7893adbad558a796bc6e72528311
MD5 fdf71f79730231eaa39d7e529260f64a
BLAKE2b-256 c9dabd334e90492f04495c3d9ee60376241a4d12e0e65791a84510d4ce1b8a61

See more details on using hashes here.

Supported by

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