Pyleoclim is a Python package primarily geared towards the analysis and visualization of paleoclimate data. Such data often come in the form of timeseries with missing values and age uncertainties, and the package includes several low-level methods to deal with these issues, as well as high-level methods that re-use those to perform scientific workflows.
The package assumes that data are stored in the Linked Paleo Data (LiPD) format and makes extensive use of the LiPD utilities. The package is aware of age ensembles stored via LiPD and uses them for time-uncertain analyses very much like GeoChronR.
- plotting maps, timeseries, and basic age model information
- paleo-aware correlation analysis (isopersistent, isospectral, and classical t-test)
- spectral analysis (Multi-Taper Method, Lomb-Scargle)
- weighted wavelet Z transform (WWZ)
- cross-wavelet analysis
- index reconstruction
- climate field reconstruction
- ensemble methods for all of the above
If you have specific requests, please contact us.
Python v3.5+ is required.
Pyleoclim is published through PyPi and easily installed via
pip install pyleoclim
You can download Pyleoclim from our GitHub repository.
The Jupyter Notebook is a web application that allows to create and share documents that contain live codes, equations, visualizations, and explanatory text. We will create notebooks that represent common workflows in paleoclimate studies using the utilities developed in Pyleoclim.