Colour vision models, colour spaces and colour thresholds. Provides flexibility to build user-defined colour vision models for n number of photoreceptor types. Also includes Vorobyev & Osorio (1998) Receptor Noise Limited models, Chittka (1992) colour hexagon, and Endler & Mielke (2005) model. Models have been extended to accept any number of photoreceptor types.

Colour vision models, colour spaces and colour thresholds. Provides flexibility to build user-defined colour vision models for n number of photoreceptor types. Also includes Vorobyev & Osorio (1998) Receptor Noise Limited models <doi:10.1098/rspb.1998.0302>, Chittka (1992) colour hexagon <doi:10.1007/BF00199331>, and Endler & Mielke (2005) model <doi:10.1111/j.1095-8312.2005.00540.x>. Models have been extended to accept any number of photoreceptor types.
testthat, knitr, rmarkdown, corrplot, rgl

Colour vision models, colour spaces and colour thresholds. Includes Vorobyev & Osorio (1998) Receptor Noise Limited models, Chittka (1992) colour hexagon, and Endler & Mielke (2005) model. Models have been extended to accept any number of photoreceptor types.

Powerful functions to select and rename columns in dataframes, lists and numeric types
by 'Perl' regular expression. Regular expression ('regex') are a very powerful grammar to match
strings, such as column names.

person("Stefan", "Fleck", email = "stefan.b.fleck@gmail.com", role = c("aut", "cre"))
A collection of command-line color styles based on the 'crayon'
package. 'Colt' styles are defined in themes that can easily be switched, to
ensure command line output looks nice on dark as well as light consoles.

Commonly Used Functions for R Shiny Applications
c(
person("Hanming", "Tu", email = "hanming.tu@gmail.com",role = c("aut", "cre"))
)
A set of common functions to be used for displaying messages, checking variables,
finding absolute paths, starting applications, etc. More functions will be added later.

Creates Co-Occurrence Matrices for Spatial Data
c(person(given = "Jakub", family = "Nowosad", role = c("aut", "cre"), email =
"nowosad.jakub@gmail.com", comment = c(ORCID = "0000-0002-1057-3721")),
person("Maximillian H.K.", "Hesselbarth",
role = c("ctb"),
email = "maximilian.hesselbarth@uni-goettingen.de",
comment = "Co-author of underlying C++ code for get_class_index_map(),
get_unique_values(), and rcpp_get_coma() functions"),
person("Marco", "Sciaini",
role = "ctb",
email = "sciaini.marco@gmail.com",
comment = "Co-author of underlying C++ code for get_class_index_map(),
get_unique_values(), and rcpp_get_coma() functions"),
person("Sebastian", "Hanss",
role = "ctb",
comment = "Co-author of underlying C++ code for get_class_index_map(),
get_unique_values(), and rcpp_get_coma() functions"))
Builds co-occurrence matrices based on spatial raster data.
It includes creation of weighted co-occurrence matrices (wecoma) and
integrated co-occurrence matrices
(incoma; Vadivel et al. (2007) <doi:10.1016/j.patrec.2007.01.004>).
Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>),
Maximillian H.K. Hesselbarth [ctb] (Co-author of underlying C++ code
for get_class_index_map(), get_unique_values(), and rcpp_get_coma()
functions),
Marco Sciaini [ctb] (Co-author of underlying C++ code for
get_class_index_map(), get_unique_values(), and rcpp_get_coma()
functions),
Sebastian Hanss [ctb] (Co-author of underlying C++ code for
get_class_index_map(), get_unique_values(), and rcpp_get_coma()
functions)