Getting Started

Getting Started#

PyPI - Version

Warning

Experimental.

Installation#

Install using pip:

pip install discontinuum

Models#

loadset-gp#

loadest-gp is Gaussian-process model for estimating river constituent time series, which borrows its namesake from the venerable LOAD ESTimator (LOADEST) software program. However, LOADEST has several serious limitations —it’s essentially a linear regression—and it has been all but replaced by the more flexible Weighted Regression on Time Discharge and Season (WRTDS), which allows the relation between target and covariate to vary through time. loadest-gp takes the WRTDS idea and reimplements it as a GP. Try it out in the loadest-gp demo.

rating-gp#

rating-gp is a Gaussian-process model for estimating river flow from stage time series. Try it out in the rating-gp demo.

Engines#

Currently, the only supported engines are the marginal likelihood implementation in pymc and gpytorch. Latent GP implementations could be added in the future. In general, the gpytorch implementation is faster and provides a lot of powerful features, like GPU support, whereas pymc is a more complete probabilistic-programming framework, which can be “friendlier” for certain use cases.

Roadmap#

        mindmap
  root((discontinuum))
    Data Providers
      USGS
      etc
    Engines
      PyMC
      PyTorch
    Utilities
      [Pre-processing]
      [Post-processing]
      [Plotting]
    Models
      [loadest-gp]
      [rating-gp]
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