Interactive tools to explore topographic-like data
sets.  Such data sets take the form of a matrix in which the rows and
columns provide location/frequency information, and the matrix elements
contain altitude/response information.  Such data is found in cartography,
2D spectroscopy and chemometrics.  The functions in this package create
interactive web pages showing the contoured data, possibly with
slices from the original matrix parallel to each dimension. The interactive
behavior is created using the D3.js JavaScript library by Mike Bostock.

c(person("Bryan A.", "Hanson", role = c("aut", "cre"), email =
"hanson@depauw.edu"), person("Kristina R.", "Mulry", role = "ctb"), person("Mike", "Bostock", role = c("cph", "ctb"),
comment = "author of the d3.js library, http://d3js.org"))
Bryan A. Hanson [aut, cre],
Kristina R. Mulry [ctb],
Mike Bostock [cph, ctb] (author of the d3.js library, http://d3js.org)

Interactive tools to explore topographic-like data
sets.  Such data sets take the form of a matrix in which the rows and
columns provide location/frequency information, and the matrix elements
contain altitude/response information.  Such data is found in cartography,
2D spectroscopy and chemometrics.  The functions in this package create
interactive web pages showing the contoured data, possibly with
slices from the original matrix parallel to each dimension. The interactive
behavior is created using the 'D3.js' 'JavaScript' library by Mike Bostock.

Extensible Differential Equations for Mosquito-Borne Pathogen
Modeling
c(
person("Sean L.", "Wu", email = "slwood89@gmail.com", role = c("aut","cre"), comment = c(ORCID = "0000-0002-5781-9493")),
person("David L.", "Smith", email = "smitdave@uw.edu", role = "aut", comment = c(ORCID = "0000-0003-4367-3849"))
)
Provides tools to set up modular ordinary and delay differential equation
models for mosquito-borne pathogens, focusing on malaria. Modular design is achieved
by S3 dispatch on parameter lists for each component which is used to compute
the full set of differential equations which may be solved using
any of the packages for numerical simulation of differential equations in R. The
methods implemented by this package are described in Wu et al. (2022) <doi:10.1101/2022.11.07.22282044>.
ggplot2, data.table, knitr, rmarkdown, testthat (>= 3.0.0)