pastas 0.9.6

Python Applied System TimeSeries Analysis Software

Build Status
Pypi
License
Latest Release

Pastas: what is it?

Pastas is an open source python package for processing, simulating and analyzing hydrological time series (models). The object oriented stucture allows for the quick implementation of new model components. Time series models can be created, calibrated, and analysed with just a few lines of python code with the built-in optimization, visualisation, and statistical analysis tools.

Documentation & Examples

• Documentation is provided on a dedicated website: http://pastas.readthedocs.io/

• Examples can be found on the examples directory on the documentation website.

Get in Touch

• Questions on Pastas can be asked and answered on StackOverFlow.

• Bugs, feature requests and other improvements can be posten as the Github Issues.

• Pull requests will only be accepted on the development branch (dev) of this repository. Please take a look at the developers section on the documentation website for more information on how to develop Pastas.

Quick installation guide

To install Pastas, a working version of Python 3.4, 3.5 or 3.6 has to be installed on your computer. We recommend using the Anaconda Distribution with Python 3.6 as it includes most of the python package dependencies and the Jupyter Notebook software to run the notebooks. However, you are free to install any Python distribution you want.

Stable version

To get the latest stable version, use:

pip install pastas

or directly from Github:

pip install https://github.com/pastas/pastas/zipball/master

Update

To update pastas, use:

pip install pastas --upgrade

Developers

To get the latest development version, use:

pip install https://github.com/pastas/pastas/zipball/dev

Dependencies

Pastas depends on a number of Python packages, of which all of the necessary are automatically installed when using the pip install manager. To summarize, the following pacakges are necessary for a minimal function installation of Pasta:

• numpy>=1.9

• matplotlib>=1.5

• pandas>=0.20,

• scipy>=0.15,

• statsmodels>=0.8.

Background

Work on Pastas started in the spring of 2016 at the Delft University of Technology and Artesia Water.

How to Cite Pastas?

Bakker, M., Collenteur, R., Calje, F. Schaars (2018, April) Untangling groundwater head series using time series analysis and Pastas. In EGU General Assembly 2018.

License

MIT