Control Philips Hue smart lighting. Use this package to
connect to a Hue bridge on your local network (remote authentication
not yet supported) and control your smart lights through the Philips
Hue API. All API V1 endpoints are supported. See API documentation at
<https://developers.meethue.com/>.
httr, methods, pkgload, purrr, utils, yaml
covr, DT, fs, knitr, lubridate, mockery, rmarkdown, spelling,
testthat, uuid, withr

Analyzing the Heterogeneity of Single-Cell Populations
A bioinformatics method developed for analyzing the heterogeneity of single-cell populations. Phitest provides an objective and automatic method to evaluate the performance of clustering and quality of cell clusters.

person("Sebastian", "Kuhlgert", email = "sebastian.kuhlgert@gmail.com", role = c("aut", "cre"))
Connect R to the PhotosynQ platform (<https://photosynq.org>). It allows to login and logout,
as well as receive project information and project data. Further it transforms the received JSON objects
into a data frame, which can be used for the final data analysis.

Run Phoenix NLME and Perform Post-Processing
Chay Ngee Lim [aut,cre],
Shuang Liang [aut],
Kevin Feng [aut,cre],
Grygoriy Vasilinin [aut],
Angela Birnbaum [aut,ths],
Jason Chittenden [aut],
Bob Leary [ctb],
Ana Henry [ctb],
Mike Dunlavey [ctb],
Samer Mouksassi[com]
Calls 'Phoenix NLME' (non-linear mixed effects), a population
modeling and simulation software, for pharmacokinetics and pharmacodynamics
analyses and conducts post-processing of the results. This includes creation of
various diagnostic plots, bootstrap and visual predictive checks. See <http://
www.certara.com/software/pkpd-modeling-and-simulation/phoenix-nlme/> for more
information about 'Phoenix NLME'.
ggplot2, gridExtra, manipulate, grid, lattice, testthat
Phoenix NLME with Phoenix Modeling Language (PML)
license

Marks periods of sleep in Actigraph accelerometer data
J. Dustin Tracy, Zhiyi Xu, Leena Choi, Sari Acra, Kong Y. Chen, Maciej S. Buchowski
Applies an automated algorithm to mark Actigraph accelerometer data as either bedrest or active.  There are separate functions for waist and wrist data.  Its input is a dataframe with a timestamp column and one of counts.  The output is the same dataframe with an additional column, bedrest.  Bedrest will have "a" active or "br" for each line.  Options also allow for "n" nap which only differ than "s" in being for a shorter (specifiable) time period.  Designed to be used after wearmarking function in Physical Activity package.