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35 changes: 35 additions & 0 deletions DESCRIPTION
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Package: GillespieSSA2
Type: Package
Title: Gillespie's Stochastic Simulation Algorithm for Impatient People
Version: 0.2.4
Authors@R: c(
person(
"Robrecht",
"Cannoodt",
email = "rcannood@gmail.com",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-3641-729X")
)
)
Description: A fast, scalable, and versatile framework for simulating large
systems with Gillespie's Stochastic Simulation Algorithm ('SSA').
This package is the spiritual successor to the 'GillespieSSA' package
originally written by Mario Pineda-Krch. Benefits of this package
include major speed improvements (>100x), easier to understand documentation,
and many unit tests that try to ensure the package works as intended.
License: GPL (>= 3)
LazyData: TRUE
Depends: R (>= 3.0)
Imports: assertthat, dplyr, dynutils, Matrix, methods, purrr, Rcpp (>=
0.12.3), readr, rlang, stringr, tidyr
Suggests: ggplot2, GillespieSSA, knitr, rmarkdown, testthat (>= 2.1.0)
LinkingTo: Rcpp
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-08-05 14:21:48 UTC; rcannood
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 16:20:02 UTC
93 changes: 93 additions & 0 deletions MD5
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191d22809821009d1f96c27c4e0c90aa *DESCRIPTION
884b7995647e5e5882fe3011464a100c *NAMESPACE
344f4c2a677a88d06a644c80f502739d *R/RcppExports.R
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acbf8be5ab92cc08b9c202088cbcab07 *R/zzz.R
89e541d0bb325872128159c1451a6104 *README.md
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49decf5be23809b1d5abb3daa8a47c22 *build/vignette.rds
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2e880d98e5cfe831cfb9509005ebd6bd *vignettes/an_introduction.Rmd
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6d7c039d97e12d246b67e02b4b186ef3 *vignettes/sir.Rmd
51 changes: 51 additions & 0 deletions NAMESPACE
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# Generated by roxygen2: do not edit by hand

S3method(print,SSA_method)
S3method(print,SSA_reaction)
export(autoplot.ssa)
export(compile_reactions)
export(ode_em)
export(port_reactions)
export(reaction)
export(ssa)
export(ssa_btl)
export(ssa_etl)
export(ssa_exact)
importFrom(Matrix,Matrix)
importFrom(Rcpp,cpp_object_initializer)
importFrom(Rcpp,loadModule)
importFrom(Rcpp,sourceCpp)
importFrom(assertthat,assert_that)
importFrom(dplyr,bind_rows)
importFrom(dplyr,first)
importFrom(dplyr,last)
importFrom(dplyr,mutate)
importFrom(dynutils,"%all_in%")
importFrom(dynutils,inherit_default_params)
importFrom(dynutils,is_sparse)
importFrom(dynutils,safe_tempdir)
importFrom(methods,is)
importFrom(methods,new)
importFrom(purrr,"%>%")
importFrom(purrr,discard)
importFrom(purrr,is_scalar_character)
importFrom(purrr,is_scalar_double)
importFrom(purrr,is_scalar_integer)
importFrom(purrr,is_scalar_logical)
importFrom(purrr,keep)
importFrom(purrr,map)
importFrom(purrr,map_chr)
importFrom(purrr,map_df)
importFrom(purrr,map_int)
importFrom(purrr,set_names)
importFrom(purrr,walk)
importFrom(readr,write_lines)
importFrom(rlang,is_formula)
importFrom(rlang,is_integerish)
importFrom(stringr,str_count)
importFrom(stringr,str_extract_all)
importFrom(stringr,str_replace)
importFrom(stringr,str_replace_all)
importFrom(stringr,str_split)
importFrom(tidyr,gather)
useDynLib(GillespieSSA2)
27 changes: 27 additions & 0 deletions R/RcppExports.R
@@ -0,0 +1,27 @@
# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

make_ode_em <- function(tau, noise_strength) {
.Call('_GillespieSSA2_make_ode_em', PACKAGE = 'GillespieSSA2', tau, noise_strength)
}

make_ssa_btl <- function(mean_firings) {
.Call('_GillespieSSA2_make_ssa_btl', PACKAGE = 'GillespieSSA2', mean_firings)
}

make_ssa_etl <- function(tau) {
.Call('_GillespieSSA2_make_ssa_etl', PACKAGE = 'GillespieSSA2', tau)
}

make_ssa_exact <- function() {
.Call('_GillespieSSA2_make_ssa_exact', PACKAGE = 'GillespieSSA2')
}

test_ssa_method_cpp <- function(ssa_alg, state, propensity, nu_i, nu_p, nu_x) {
.Call('_GillespieSSA2_test_ssa_method_cpp', PACKAGE = 'GillespieSSA2', ssa_alg, state, propensity, nu_i, nu_p, nu_x)
}

test_propensity_cpp <- function(num_functions, propensity_funs, params, buffer_size, propensity_size, state, sim_time) {
.Call('_GillespieSSA2_test_propensity_cpp', PACKAGE = 'GillespieSSA2', num_functions, propensity_funs, params, buffer_size, propensity_size, state, sim_time)
}

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