Adds flow maps to 'ggplot2' plots. The flow maps consist of 'ggplot2' layers which visualize the nodes as circles and the bilateral flows between the nodes as bidirectional half-arrows.

Provides functionality to perform machine-learning-based modeling in a computation pipeline.
    Its functions contain the basic steps of machine-learning-based knowledge discovery workflows,
    including model training and optimization, model evaluation, and model testing.
    To perform these tasks, the package builds heavily on existing machine-learning packages,
    such as 'caret' <https://github.com/topepo/caret/> and associated packages.
    The package can train multiple models, optimize model hyperparameters by performing a grid search
    or a random search, and evaluates model performance by different metrics.
    Models can be validated either on a test data set, or in case of a small sample size
    by k-fold cross validation or repeated bootstrapping.
    It also allows for 0-Hypotheses generation by performing permutation experiments.
    Additionally, it offers methods of model interpretation and item categorization
    to identify the most informative features from a high dimensional data space.
    The functions of this package can easily be integrated into computation pipelines
    (e.g. 'nextflow' <https://www.nextflow.io/>) and hereby improve scalability,
    standardization, and re-producibility in the context of machine-learning.

This framework allows you to design and implement complex
    pipelines, and deploy them on your institution's computing cluster. This has
    been built keeping in mind the needs of bioinformatics workflows. However, it is
    easily extendable to any field where a series of steps (shell commands) are to
    be executed in a (work)flow.

An application to calculate the daily environmental costs of river flow regulation by dams based on García de Jalon et al. 2017 <doi:10.1007/s11269-017-1663-0>.

Screens daily streamflow time series for temporal trends and
    change-points. This package has been primarily developed for assessing the
    quality of daily streamflow time series. It also contains tools for plotting
    and calculating many different streamflow metrics. The package can be used to
    produce summary screening plots showing change-points and significant temporal
    trends for high flow, low flow, and/or baseflow statistics, or it can be used
    to perform more detailed hydrological time series analyses. The package was
    designed for screening daily streamflow time series from Water Survey Canada
    and the United States Geological Survey but will also work with streamflow time
    series from many other agencies.