Commit dc7c5a8b authored by Jean-Francois Rey's avatar Jean-Francois Rey
Browse files

update package

parent 662ac0a5
Pipeline #3845 canceled with stages
in 5 minutes and 43 seconds
......@@ -34,7 +34,6 @@ Description: A stochastic, spatially-explicit, demo-genetic model simulating the
Peter H Thrall (2018) <doi:10.1371/journal.pcbi.1006067>.
URL: https://csiro-inra.pages.biosp.inrae.fr/landsepi/,
https://gitlab.paca.inra.fr/CSIRO-INRA/landsepi
BugReports: https://gitlab.paca.inrae.fr/CSIRO-INRA/landsepi/-/issues
License: GPL (>= 2) | file LICENSE
LazyData: true
......
#! /bin/sh
# Guess values for system-dependent variables and create Makefiles.
# Generated by GNU Autoconf 2.69 for landsepiDev 1.0.2.
# Generated by GNU Autoconf 2.69 for landsepi 1.1.0.
#
# Report bugs to <jean-francois.rey@inrae.fr>.
#
......@@ -577,10 +577,10 @@ MFLAGS=
MAKEFLAGS=
# Identity of this package.
PACKAGE_NAME='landsepiDev'
PACKAGE_TARNAME='landsepidev'
PACKAGE_VERSION='1.0.2'
PACKAGE_STRING='landsepiDev 1.0.2'
PACKAGE_NAME='landsepi'
PACKAGE_TARNAME='landsepi'
PACKAGE_VERSION='1.1.0'
PACKAGE_STRING='landsepi 1.1.0'
PACKAGE_BUGREPORT='jean-francois.rey@inrae.fr'
PACKAGE_URL=''
......@@ -1198,7 +1198,7 @@ if test "$ac_init_help" = "long"; then
# Omit some internal or obsolete options to make the list less imposing.
# This message is too long to be a string in the A/UX 3.1 sh.
cat <<_ACEOF
\`configure' configures landsepiDev 1.0.2 to adapt to many kinds of systems.
\`configure' configures landsepi 1.1.0 to adapt to many kinds of systems.
Usage: $0 [OPTION]... [VAR=VALUE]...
......@@ -1247,7 +1247,7 @@ Fine tuning of the installation directories:
--infodir=DIR info documentation [DATAROOTDIR/info]
--localedir=DIR locale-dependent data [DATAROOTDIR/locale]
--mandir=DIR man documentation [DATAROOTDIR/man]
--docdir=DIR documentation root [DATAROOTDIR/doc/landsepidev]
--docdir=DIR documentation root [DATAROOTDIR/doc/landsepi]
--htmldir=DIR html documentation [DOCDIR]
--dvidir=DIR dvi documentation [DOCDIR]
--pdfdir=DIR pdf documentation [DOCDIR]
......@@ -1260,7 +1260,7 @@ fi
if test -n "$ac_init_help"; then
case $ac_init_help in
short | recursive ) echo "Configuration of landsepiDev 1.0.2:";;
short | recursive ) echo "Configuration of landsepi 1.1.0:";;
esac
cat <<\_ACEOF
......@@ -1345,7 +1345,7 @@ fi
test -n "$ac_init_help" && exit $ac_status
if $ac_init_version; then
cat <<\_ACEOF
landsepiDev configure 1.0.2
landsepi configure 1.1.0
generated by GNU Autoconf 2.69
Copyright (C) 2012 Free Software Foundation, Inc.
......@@ -1446,7 +1446,7 @@ cat >config.log <<_ACEOF
This file contains any messages produced by compilers while
running configure, to aid debugging if configure makes a mistake.
It was created by landsepiDev $as_me 1.0.2, which was
It was created by landsepi $as_me 1.1.0, which was
generated by GNU Autoconf 2.69. Invocation command line was
$ $0 $@
......@@ -3053,7 +3053,7 @@ cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1
# report actual input values of CONFIG_FILES etc. instead of their
# values after options handling.
ac_log="
This file was extended by landsepiDev $as_me 1.0.2, which was
This file was extended by landsepi $as_me 1.1.0, which was
generated by GNU Autoconf 2.69. Invocation command line was
CONFIG_FILES = $CONFIG_FILES
......@@ -3106,7 +3106,7 @@ _ACEOF
cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1
ac_cs_config="`$as_echo "$ac_configure_args" | sed 's/^ //; s/[\\""\`\$]/\\\\&/g'`"
ac_cs_version="\\
landsepiDev config.status 1.0.2
landsepi config.status 1.1.0
configured by $0, generated by GNU Autoconf 2.69,
with options \\"\$ac_cs_config\\"
......
......@@ -14,9 +14,9 @@ epid_output(
cultivars_param,
eco_param,
GLAnoDis = cultivars_param$max_density[1],
ylim_param = list(audpc = c(0, 0.38), gla_abs = c(0, 1.48), gla_rel = c(0, 1),
eco_cost = c(0, NA), eco_product = c(0, NA), eco_benefit = c(0, NA), eco_grossmargin
= c(NA, NA)),
ylim_param = list(audpc = c(0, 0.76), audpc_rel = c(0, 1), gla = c(0, 1.48), gla_rel
= c(0, 1), eco_cost = c(0, NA), eco_yield = c(0, NA), eco_product = c(0, NA),
eco_margin = c(NA, NA)),
writeTXT = TRUE,
graphic = TRUE,
path = getwd()
......@@ -26,12 +26,13 @@ epid_output(
\item{types}{a character string (or a vector of character strings if several outputs are to be computed)
specifying the type of outputs to generate (see details):\itemize{
\item "audpc": Area Under Disease Progress Curve
\item "gla_abs": Absolute Green Leaf Area
\item "audpc_rel": Relative Area Under Disease Progress Curve
\item "gla": Green Leaf Area
\item "gla_rel": Relative Green Leaf Area
\item "eco_product": Crop production
\item "eco_cost": Crop costs
\item "eco_benefit": Crop benefits
\item "eco_grossmargin": Gross Margin (benefits - costs)
\item "eco_yield": Total crop yield
\item "eco_cost": Operational crop costs
\item "eco_product": Crop products
\item "eco_margin": Margin (products - operational costs)
\item "HLIR_dynamics", "H_dynamics", "L_dynamics", "IR_dynamics", "HLI_dynamics", etc.: Epidemic dynamics
related to the specified sanitary status (H, L, I or R and all their combinations).
Graphics only, works only if graphic=TRUE.
......@@ -57,23 +58,25 @@ of simulated years.}
\item{cultivars_param}{list of parameters associated with each host genotype (i.e. cultivars):
\itemize{
\item name = vector of cultivar names,
\item initial_density = vector of host densities (per square meter) at the beginning of the cropping season,
\item max_density = vector of maximum host densities (per square meter) at the end of the cropping season,
\item initial_density = vector of host densities (per square meter) at the beginning of the cropping season
as if cultivated in pure crop,
\item max_density = vector of maximum host densities (per square meter) at the end of the cropping season
as if cultivated in pure crop,
\item cultivars_genes_list = a list containing, for each host genotype, the indices of carried resistance genes.
}}
\item{eco_param}{a list of economic parameters for each host genotype as if cultivated in pure crop:\itemize{
\item yield_perHa = a dataframe of 4 columns for the yield associated with hosts in sanitary status H, L, I and R,
and one row per host genotype (yields are expressed in weight or volume units / ha / cropping season),
\item production_cost_perHa = a vector of overall production costs (in monetary units / ha / cropping season)
including planting costs, amortisation, labour etc.,
\item market_value = a vector of market values of the productions (in monetary units / weight or volume unit).
\item yield_perHa = a dataframe of 4 columns for the theoretical yield associated with hosts in sanitary status H, L, I and R,
as if cultivated in pure crops, and one row per host genotype
(yields are expressed in weight or volume units / ha / cropping season),
\item planting_cost_perHa = a vector of planting costs (in monetary units / ha / cropping season),
\item market_value = a vector of market values of the production (in monetary units / weight or volume unit).
}}
\item{GLAnoDis}{the value of absolute GLA in absence of disease (required to compute economic outputs).}
\item{ylim_param}{a list of graphical parameters for each required output: bounds for y-axes for
audpc, gla_abs, gla_rel, eco_cost, eco_product, eco_benefit, eco_grossmargin.}
audpc, gla, gla_rel, eco_cost, eco_yield, eco_product, eco_margin.}
\item{writeTXT}{a logical indicating if the output is written in a text file (TRUE) or not (FALSE).}
......@@ -93,22 +96,24 @@ Generates epidemiological and economic outputs from model simulations.
Outputs are computed every year for every cultivar as well as for the whole landscape. \describe{
\item{\strong{Epidemiological outputs.}}{
The epidemiological impact of pathogen spread can be evaluated by different measures: \enumerate{
\item Area Under Disease Progress Curve (AUDPC): average proportion of diseased hosts (status I + R)
relative to the carrying capacity (i.e. disease severity).
\item Absolute Green Leaf Area (GLAa): average number of healthy hosts (status H) per time step and per square meter.
\item Relative Green Leaf Area (GLAr): average proportion of healthy hosts (status H) relative to the total number
\item Area Under Disease Progress Curve (AUDPC): average number of diseased host individuals (status I + R)
per time step and square meter.
\item Relative Area Under Disease Progress Curve (AUDPCr): average proportion of diseased host individuals
(status I + R) relative to the total number of existing hosts (H+L+I+R).
\item Green Leaf Area (GLA): average number of healthy host individuals (status H) per time step and per square meter.
\item Relative Green Leaf Area (GLAr): average proportion of healthy host individuals (status H) relative to the total number
of existing hosts (H+L+I+R).
}
}
\item{\strong{Economic outputs.}}{
The economic outcome of a simulation can be evaluated using: \enumerate{
\item Crop production: yearly crop production (e.g. grains, fruits, wine) in weight (or volume) units
per hectare (depends on the number of productive hosts and associated yield).
\item Crop benefits: yearly benefits generated from product sales, in monetary units per hectare
(depends on crop production and market value of the product).
\item Crop costs: yearly costs associated with crop production (including planting, amortisation, labour, ...)
in monetary units per hectare (depends on initial host density and production cost).
\item Crop gross margin, i.e. benefits - costs, in monetary units per hectare.
\item Crop yield: yearly crop yield (e.g. grains, fruits, wine) in weight (or volume) units
per hectare (depends on the number of productive hosts and associated theoretical yield).
\item Crop products: yearly product generated from sales, in monetary units per hectare
(depends on crop yield and market value).
\item Operational crop costs: yearly costs associated with crop planting in monetary units per hectare
(depends on initial host density and planting cost).
\item Crop margin, i.e. products - operational costs, in monetary units per hectare.
}
}
}
......
......@@ -69,7 +69,7 @@ For each pathogen genotype, several computations are performed: \itemize{
\item R_infection: time to first true infection of a resistant host;
\item R_invasion: time when the number of infections of resistant hosts reaches a threshold above which
the genotype is unlikely to go extinct.}
The value Nyears + 1 timestep is used if the genotype never appeared/infected/invaded.
The value Nyears + 1 time step is used if the genotype never appeared/infected/invaded.
}
\examples{
\dontrun{
......
......@@ -16,8 +16,8 @@ resistance deployment strategies.
\tabular{ll}{
Package: \tab landsepi\cr
Type: \tab Package\cr
Version: \tab 1.0.2\cr
Date: \tab 2020-07-02\cr
Version: \tab 1.1.0\cr
Date: \tab 2021-07-19\cr
License: \tab GPL (>=2)\cr
}
......@@ -31,7 +31,8 @@ evolution of a pathogen in a heterogeneous cropping landscape, across cropping s
potential bottlenecks to the pathogen.
The lansdcape is represented by a set of polygons where the pathogen can disperse
(the basic spatial unit is an individual field). \emph{landsepi} includes built-in simulated landscapes
(the basic spatial unit is an individual polygon; an agricultural field may be composed of a single
or several polygons). \emph{landsepi} includes built-in simulated landscapes
(and associated dispersal matrices for rust pathogens, see below), but is it possible
to use your own landscape (in shapefile format) and dispersal matrix.
......@@ -77,9 +78,10 @@ for details on how to use landsepi.
\describe{
\item{\strong{Assumptions} (in bold those that can be relaxed with appropriate parameterization): }{
\enumerate{
\item The spatial unit is the field, i.e. a piece of land delimited by boundaries and possibly cultivated with a crop.
Such crop may be host or non-host, and the field is considered a homogeneous mixture of individuals (i.e. there is no
intra-field structuration).
\item The spatial unit is a polygon, i.e. a piece of land delimited by boundaries and possibly
cultivated with a crop. Such crop may be host or non-host, and the polygon is considered a homogeneous
mixture of host individuals (i.e. there is no intra-polygon structuration). A field may be composed
of a single or several polygons..
\item Host individuals are in one of these four categories: H (healthy),
E (latent, i.e. infected but not infectious nor symptomatic), I (infectious and symptomatic),
or R (removed, i.e. epidemiologically inactive).
......@@ -95,6 +97,9 @@ only healthy hosts (state H) contribute to plant growth (castrating pathogen).
susceptible to disease from the first to the last day of every cropping season.
\item Crop yield depends on the average amount of producing host individuals during the cropping season
and does not depend on the time of epidemic peak. \strong{Only healthy individuals (state H) contribute to crop yield.}
\item Components of a mixture are independent each other (i.e. there is neither plant-plant interaction
nor competition for space, and harvests are segregated).
\item The pathogen is haploid.
\item Initially, the pathogen is not adapted to any source of resistance, and is only present on
susceptible hosts (at state I).
\item \strong{Pathogen dispersal is isotropic (i.e. equally probable in every direction).}
......@@ -108,18 +113,21 @@ the one targeted by the resistance gene.
\item When there is a delay for activation of a given resistance gene (APR), the time to activation is the same for
all hosts carrying this gene and located in the same field.
\item Variances of the durations of the latent and the infectious periods of the pathogen are not affected by plant resistance.
\item If there is sexual reproduction (or gene recombination), it occurs only between parental infections located in the same field
and the same host genotype. The propagule production rate of a couple is the sum of the propagule production rates of the parents.
The genotype of each daughter propagule is issued from random loci segregation between parental loci.
\item If there is sexual reproduction (or gene recombination), it occurs only between parental infections located
in the same polygon and the same host genotype. The host population is panmictic (i.e. all pairs of parents have
the same probability to occur). The propagule production rate of a couple is the sum of the propagule production
rates of the parents. The genotype of each daughter propagule is issued from random loci segregation between parental loci.
}
}
\item{\strong{Epidemiological outputs}}{
The epidemiological outcome of a deployment strategy is evaluated using: \enumerate{
\item the area under the disease progress curve (AUDPC) to measure disease severity
(i.e. the average proportion of diseased hosts -status I and R- relative to the carrying capacity),
\item the absolute Green Leaf Area (GLAa) to measure the average amount of healthy tissue (status H),
(i.e. the average number of diseased plant tissue -status I and R- per time step and square meter),
\item the relative area under the disease progress curve (AUDPCr) to measure the average proportion
of diseased tissue (status I and R) relative to the total number of existing host individuals (H+L+I+R).
\item the Green Leaf Area (GLA) to measure the average amount of healthy plant tissue (status H) per time step and square meter,
\item the relative Green Leaf Area (GLAr) to measure the average proportion of healthy tissue (status H)
relative to the total number of existing hosts (H+L+I+R).
relative to the total number of existing host individuals (H+L+I+R).
}
A set of graphics and a video showing epidemic dynamics can also be generated.
}
......@@ -135,13 +143,13 @@ steps to adapt to plant resistance: (1) first appearance of adapted mutants,
}
\item{\strong{Economic outputs}}{
The economic outcome of a simulation can be evaluated using: \enumerate{
\item the crop production: yearly crop production (e.g. grains, fruits, wine) in weight (or volume) units
per hectare (depends on the number of productive hosts and associated yield),
\item the crop benefits: yearly benefits generated from product sales, in monetary units per hectare
(depends on crop production and market value of the product),
\item the crop costs: yearly costs associated with crop production (including planting, amortisation, labour, ...)
in monetary units per hectare (depends on initial host density and production cost),
\item the gross margin, i.e. benefits - costs, in monetary units per hectare.
\item the crop yield: yearly crop production (e.g. grains, fruits, wine) in weight (or volume) units
per hectare (depends on the number of productive hosts and associated theoretical yield),
\item the crop products: yearly products generated from sales, in monetary units per hectare
(depends on crop yield and market value),
\item the crop operational costs: yearly costs associated with crop planting,
in monetary units per hectare (depends on initial host density and planting cost),
\item the margin, i.e. products - operational costs, in monetary units per hectare.
}
}
}
......@@ -202,7 +210,8 @@ url: https://cran.r-project.org/package=landsepi.
\seealso{
Useful links:
\itemize{
\item \url{https://gitlab.paca.inrae.fr/CSIRO-INRA/landsepi}
\item \url{https://csiro-inra.pages.biosp.inrae.fr/landsepi/}
\item \url{https://gitlab.paca.inra.fr/CSIRO-INRA/landsepi}
\item Report bugs at \url{https://gitlab.paca.inrae.fr/CSIRO-INRA/landsepi/-/issues}
}
......
......@@ -10,15 +10,17 @@ loadOutputs(epid_outputs = "all", evol_outputs = "all")
\item{epid_outputs}{a character string (or a vector of character strings if several outputs
are to be computed) specifying the type of epidemiological and economic outputs to generate
(see details):\itemize{
\item "audpc" : Area Under Disease Progress Curve (average proportion of diseased hosts relative
to the carryng capacity)
\item "gla_abs" : Absolute Green Leaf Area (average number of healthy hosts per square meter)
\item "gla_rel" : Relative Green Leaf Area (average proportion of healthy hosts relative to the
\item "audpc" : Area Under Disease Progress Curve (average number of diseased host individuals
per time step and square meter)
\item "audpc_rel" : Relative Area Under Disease Progress Curve (average proportion of diseased host
individuals relative to the total number of existing hosts)
\item "gla" : Green Leaf Area (average number of healthy host individuals per time step and square meter)
\item "gla_rel" : Relative Green Leaf Area (average proportion of healthy host individuals relative to the
total number of existing hosts)
\item "eco_product" : total crop production (in weight or volume units per ha)
\item "eco_cost" : total crop costs (in monetary units per ha)
\item "eco_benefit" : total crop benefits (in monetary units per ha)
\item "eco_grossmargin" : Gross Margin (benefits - costs, in monetary units per ha)
\item "eco_yield" : total crop yield (in weight or volume units per ha)
\item "eco_cost" : operational crop costs (in monetary units per ha)
\item "eco_product" : total crop products (in monetary units per ha)
\item "eco_margin" : Margin (products - operational costs, in monetary units per ha)
\item "HLIR_dynamics", "H_dynamics", "L_dynamics", "IR_dynamics", "HLI_dynamics", etc.:
Epidemic dynamics related to the specified sanitary status (H, L, I or R and all their
combinations). Graphics only, works only if graphic=TRUE.
......
......@@ -145,7 +145,7 @@ eco_param <- list(yield_perHa = cbind(H = as.numeric(cultivars$yield_H),
L = as.numeric(cultivars$yield_L),
I = as.numeric(cultivars$yield_I),
R = as.numeric(cultivars$yield_R)),
production_cost_perHa = as.numeric(cultivars$production_cost),
planting_cost_perHa = as.numeric(cultivars$planting_cost),
market_value = as.numeric(cultivars$market_value))
evol_res <- evol_output(, time_param, Npoly, cultivars, genes)
......
......@@ -24,7 +24,7 @@ or not (FALSE).}
or not (FALSE).}
\item{videoMP4}{a logical indicating if a video must be generated (TRUE) or not (FALSE, default).
Works only if graphic=TRUE and audpc is computed.}
Works only if graphic=TRUE and audpc_rel is computed.}
\item{keepRawResults}{a logical indicating if binary files must be kept after the end of
the simulation (default=FALSE). Careful, many files may be generated if keepRawResults=TRUE.}
......
......@@ -22,26 +22,27 @@ Updates a LandsepiParams object with cultivars parameters
dfCultivars is a dataframe of parameters associated with each host genotype
(i.e. cultivars, lines) when cultivated in pure crops. Columns of the dataframe are:\itemize{
\item cultivarName: cultivar names (cannot accept space),
\item initial_density: host densities (per square meter) at the beginning of the cropping season,
\item max_density: maximum host densities (per square meter) at the end of the cropping season,
\item initial_density: host densities (per square meter) at the beginning of the cropping season
as if cultivated in pure crop,
\item max_density: maximum host densities (per square meter) at the end of the cropping season
as if cultivated in pure crop,
\item growth rate: host growth rates,
\item reproduction rate: host reproduction rates,
\item death rate: host death rates,
\item yield_H: yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status H,
\item yield_L: yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status L,
\item yield_I: yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status I,
\item yield_R: yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status R,
\item production_cost = overall production costs (in monetary units / ha / cropping season)
including planting costs, amortisation, labour etc.,
\item market_value = market values of the productions (in monetary units / weight or volume unit).
\item yield_H: theoretical yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status H as if cultivated in pure crop,
\item yield_L: theoretical yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status L as if cultivated in pure crop,
\item yield_I: theoretical yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status I as if cultivated in pure crop,
\item yield_R: theoretical yield (in weight or volume units / ha / cropping season)
associated with hosts in sanitary status R as if cultivated in pure crop,
\item planting_cost = planting costs (in monetary units / ha / cropping season) as if cultivated in pure crop,
\item market_value = market values of the production (in monetary units / weight or volume unit).
}
The data.frame must be defined as follow (example):\tabular{llllllllllll}{
cultivarName \tab initial_density \tab max_density \tab growth_rate \tab reproduction_rate \tab death_rate \tab yield_H \tab yield_L \tab yield_I \tab yield_R \tab production_cost \tab market_value \cr
cultivarName \tab initial_density \tab max_density \tab growth_rate \tab reproduction_rate \tab death_rate \tab yield_H \tab yield_L \tab yield_I \tab yield_R \tab planting_cost \tab market_value \cr
Susceptible \tab 0.1 \tab 2.0 \tab 0.1 \tab 0.0 \tab 0.0 \tab 2.5 \tab 0.0 \tab 0.0 \tab 0.0 \tab 225 \tab 200 \cr
Resistant1 \tab 0.1 \tab 2.0 \tab 0.1 \tab 0.0 \tab 0.0 \tab 2.5 \tab 0.0 \tab 0.0 \tab 0.0 \tab 225 \tab 200 \cr
Resistant2 \tab 0.1 \tab 2.0 \tab 0.1 \tab 0.0 \tab 0.0 \tab 2.5 \tab 0.0 \tab 0.0 \tab 0.0 \tab 225 \tab 200 \cr
......
......@@ -21,7 +21,7 @@ if several thresholds are given in a vector).
\item GLAnoDis = the absolute Green Leaf Area in absence of disease (used to compute
economic outputs).
\item audpc100S = the audpc in a fully susceptible landscape (used as reference value
for graphics and video).
for graphics).
}}
}
\value{
......@@ -35,15 +35,17 @@ Updates a LandsepiParams object with a list of output parameters.
outputs are to be computed) specifying the type of epidemiological and economic outputs
to generate:
\itemize{
\item "audpc" : Area Under Disease Progress Curve (average proportion of diseased hosts relative
to the carryng capacity)
\item "gla_abs" : Absolute Green Leaf Area (average number of healthy hosts per square meter)
\item "gla_rel" : Relative Green Leaf Area (average proportion of healthy hosts relative to the
\item "audpc" : Area Under Disease Progress Curve (average number of diseased host individuals
per time step and square meter)
\item "audpc_rel" : Relative Area Under Disease Progress Curve (average proportion of diseased host
individuals relative to the total number of existing hosts)
\item "gla" : Green Leaf Area (average number of healthy host individuals per square meter)
\item "gla_rel" : Relative Green Leaf Area (average proportion of healthy host individuals relative to the
total number of existing hosts)
\item "eco_product" : total crop production (in weight or volume units per ha)
\item "eco_cost" : total crop costs (in monetary units per ha)
\item "eco_benefit" : total crop benefits (in monetary units per ha)
\item "eco_grossmargin" : Gross Margin (benefits - costs, in monetary units per ha)
\item "eco_yield" : total crop yield (in weight or volume units per ha)
\item "eco_cost" : operational crop costs (in monetary units per ha)
\item "eco_product" : total crop products (in monetary units per ha)
\item "eco_margin" : Margin (products - costs, in monetary units per ha)
\item "HLIR_dynamics", "H_dynamics", "L_dynamics", "IR_dynamics", "HLI_dynamics", etc.:
Epidemic dynamics related to the specified sanitary status (H, L, I or R and all their
combinations). Graphics only, works only if graphic=TRUE.
......
......@@ -13,7 +13,7 @@ setPathogen(params, patho_params)
for a pathogen genotype not adapted to resistance: \itemize{
\item infection_rate = maximal expected infection rate of a propagule on a healthy host,
\item propagule_prod_rate = maximal expected effective propagule production rate of an
infectious host per timestep,
infectious host per time step,
\item latent_period_exp = minimal expected duration of the latent period,
\item latent_period_var = variance of the latent period duration,
\item infectious_period_exp = maximal expected duration of the infectious period,
......
......@@ -23,7 +23,7 @@ simul_landsepi(
evol_outputs = "all",
thres_breakdown = 50000,
GLAnoDis = 1.48315,
audpc100S = 0.38,
audpc100S = 0.76,
writeTXT = TRUE,
graphic = TRUE,
videoMP4 = FALSE,
......@@ -46,18 +46,23 @@ simul_landsepi(
\item{cultivars}{a dataframe of parameters associated with each host genotype (i.e. cultivars)
when cultivated in pure crops. Columns of the dataframe are:\itemize{
\item cultivarName: cultivar names,
\item initial_density: host densities (per square meter) at the beginning of the cropping season,
\item max_density: maximum host densities (per square meter) at the end of the cropping season,
\item growth rate: host growth rates,
\item initial_density: host densities (per square meter) at the beginning of the cropping season
as if cultivated in pure crop,
\item max_density: maximum host densities (per square meter) at the end of the cropping season
as if cultivated in pure crop,
\item growth_rate: host growth rates,
\item reproduction rate: host reproduction rates,
\item death rate: host death rates,
\item yield_H: yield (in weight or volume units / ha / cropping season) associated with hosts in sanitary status H,
\item yield_L: yield (in weight or volume units / ha / cropping season) associated with hosts in sanitary status L,
\item yield_I: yield (in weight or volume units / ha / cropping season) associated with hosts in sanitary status I,
\item yield_R: yield (in weight or volume units / ha / cropping season) associated with hosts in sanitary status R,
\item production_cost = overall production costs (in monetary units / ha / cropping season)
including planting costs, amortisation, labour etc.,
\item market_value = market values of the productions (in monetary units / weight or volume unit).
\item death_rate: host death rates,
\item yield_H: theoretical yield (in weight or volume units / ha / cropping season) associated with
hosts in sanitary status H as if cultivated in pure crop,
\item yield_L: theoretical yield (in weight or volume units / ha / cropping season) associated with
hosts in sanitary status L as if cultivated in pure crop,
\item yield_I: theoretical yield (in weight or volume units / ha / cropping season) associated with
hosts in sanitary status I as if cultivated in pure crop,
\item yield_R: theoretical yield (in weight or volume units / ha / cropping season) associated with
hosts in sanitary status R as if cultivated in pure crop,
\item planting_cost = planting costs (in monetary units / ha / cropping season) as if cultivated in pure crop,
\item market_value = market values of the production (in monetary units / weight or volume unit).
}}
\item{cultivars_genes_list}{a list containing, for each host genotype, the indices of carried resistance genes.}
......@@ -90,7 +95,7 @@ of simulated years.}
\item{basic_patho_param}{a list of pathogen aggressiveness parameters on a susceptible host
for a pathogen genotype not adapted to resistance: \itemize{
\item infection_rate = maximal expected infection rate of a propagule on a healthy host,
\item propagule_prod_rate = maximal expected effective propagule production rate of an infectious host per timestep,
\item propagule_prod_rate = maximal expected effective propagule production rate of an infectious host per time step,
\item latent_period_exp = minimal expected duration of the latent period,
\item latent_period_var = variance of the latent period duration,
\item infectious_period_exp = maximal expected duration of the infectious period,
......@@ -114,15 +119,17 @@ at the beginning of the simulation. Must be between 0 and 1.}
\item{epid_outputs}{a character string (or a vector of character strings if several outputs are to be computed)
specifying the type of epidemiological and economic outputs to generate (see details):
\itemize{
\item "audpc" : Area Under Disease Progress Curve (average proportion of diseased hosts relative
to the carryng capacity)
\item "gla_abs" : Absolute Green Leaf Area (average number of healthy hosts per square meter)
\item "gla_rel" : Relative Green Leaf Area (average proportion of healthy hosts relative to the
\item "audpc" : Area Under Disease Progress Curve (average number of diseased host individuals
per time step and square meter)
\item "audpc_rel" : Relative Area Under Disease Progress Curve (average proportion of diseased host
individuals relative to the total number of existing hosts)
\item "gla" : Green Leaf Area (average number of healthy host individuals per time step and square meter)
\item "gla_rel" : Relative Green Leaf Area (average proportion of healthy host individuals relative to the
total number of existing hosts)
\item "eco_product" : total crop production (in weight or volume units per ha)
\item "eco_cost" : total crop costs (in monetary units per ha)
\item "eco_benefit" : total crop benefits (in monetary units per ha)
\item "eco_grossmargin" : Gross Margin (benefits - costs, in monetary units per ha)
\item "eco_yield" : total crop yield (in weight or volume units per ha)
\item "eco_cost" : operational crop costs (in monetary units per ha)
\item "eco_product" : total crop products (in monetary units per ha)
\item "eco_margin" : Margin (products - operational costs, in monetary units per ha)
\item "HLIR_dynamics", "H_dynamics", "L_dynamics", "IR_dynamics", "HLI_dynamics", etc.: Epidemic dynamics
related to the specified sanitary status (H, L, I or R and all their combinations). Graphics only,
works only if graphic=TRUE.
......@@ -145,14 +152,14 @@ of resistant hosts (several values are computed if several thresholds are given
\item{GLAnoDis}{the absolute Green Leaf Area in absence of disease (used to compute economic outputs).}
\item{audpc100S}{the audpc in a fully susceptible landscape (used as reference value for graphics and video).}
\item{audpc100S}{the audpc in a fully susceptible landscape (used as reference value for graphics).}
\item{writeTXT}{a logical indicating if outputs must be written in text files (TRUE, default) or not (FALSE).}
\item{graphic}{a logical indicating if graphics must be generated (TRUE, default) or not (FALSE).}
\item{videoMP4}{a logical indicating if a video must be generated (TRUE) or not (FALSE, default).
Works only if graphic=TRUE and epid_outputs="audpc" (or epid_outputs="all").}
Works only if graphic=TRUE and epid_outputs="audpc_rel" (or epid_outputs="all").}
\item{keepRawResults}{a logical indicating if binary files must be kept after the end of the simulation (default=FALSE).
Careful, many files may be generated if keepRawResults=TRUE.}
......
......@@ -14,7 +14,6 @@ video(
croptypes,
croptype_names = c(),
cultivars_param,
audpc100S,
keyDates = NULL,
nMapPY = 5,
path = getwd()
......@@ -47,13 +46,12 @@ of simulated years.}
\item{cultivars_param}{a list of parameters associated with each host genotype (i.e. cultivars)
when cultivated in pure crops:\itemize{
\item name = vector of cultivar names,
\item max_density = vector of maximum host densities (per square meter) at the end of the cropping season,
\item max_density = vector of maximum host densities (per square meter) at the end of the cropping season
as if cultivated in pure crops,
\item cultivars_genes_list = a list containing, for each host genotype, the indices of carried resistance genes.
}}
\item{audpc100S}{AUDPC of a 100\% susceptible landscape, used as a reference.}
\item{keyDates}{a vector of times (in timesteps) where to draw vertical lines in the AUDPC graphic. Usually
\item{keyDates}{a vector of times (in time steps) where to draw vertical lines in the AUDPC graphic. Usually
used to delimit durabilities of the resistance genes. No line is drawn if keyDates=NULL (default).}
\item{nMapPY}{an integer specifying the number of epidemic maps per year to generate.}
......@@ -68,7 +66,7 @@ Generates a video showing the epidemic dynamics on a map representing the croppi
(requires ffmpeg library).
}
\details{
The left panel shows the year-after-year dynamics of AUDPC, relative to a fully susceptible landscape,
The left panel shows the year-after-year dynamics of AUDPC,
for each cultivar as well as the global average. The right panel illustrates the landscape,
where fields are hatched depending on the cultivated croptype, and coloured depending on the prevalence of the disease.
Note that up to 9 different croptypes can be represented properly in the right panel.
......
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