R/createInputMatrix.r
In AndySouth/resistance: an insecticide resistance population genetics model with 2 loci and 2 insecticides
Defines functions
createInputMatrix
#' create input parameters matrix from a file or hardcoded scenarios
#'
#' Creates a matrix with parameters in rows and scenarios in columns.
#' Either from a csv file or hardcoded scenarios set by the calibration argument.
#'
#' @param params.csv whether parameters are defined in an input file TRUE/FALSE
#' @param inFile parameters filename
#' @param calibration one of a limited set of integers effecting how scenarios are run
#' @param save.fitvals whether to save fitness scores to csv 0=no, 1=yes
#'
#' @seealso \code{\link{setInputOneScenario}} and \code{\link{setInputSensiScenarios}} for creating input objects from passed arguments
#'
#' @return matrix
#' @export
createInputMatrix <- function(params.csv,
inFile = system.file("extdata","input.parameters.csv", package="resistance"),
calibration = 1012,
save.fitvals = 0 ){
#todo may be able to combine params.csv and file arguments
## if parameters from input file -
#params.csv <- TRUE #testing whether this always needs to be done
if( params.csv )
{
#todo add check that file exists
input <- read.csv( inFile, header=T, stringsAsFactors=F )
# make into matrix from data.frame
input <- make.matrix(input, input$Input)
return(input)
}
#seeing if I need to initialise the matrix outside of the callibration loops below
#input <- matrix()
## Scenario 1 Calibration 1011 - Fig 1 Curtis ####
if( !params.csv && calibration == 1011 ){
input <- matrix( ncol=2, nrow=53 )
input[1,1] <- calibration # calibration a code to run specific set of scenarios
input[2,1] <- 18 # max_gen number of generations
input[3,1] <- 1 # coll.fitvals save fitness values in a matrix 0/1
input[4,1] <- save.fitvals # save.fitvals save fitness values to an external .csv 0/1
input[5,1] <- 0.001 # P_1 locus 1 frequency of resistance allele
input[6,1] <- 0.001 # P_2 locus 2 frequency of resistance allele
input[7,1] <- 0.5 # recomb_rate recombination rate
input[8,1] <- 0.1 # a.m_00 insecticide exposure male no1 no2
input[9,1] <- 0 # a.m_a0 insecticide exposure male lo1 no2
input[10,1] <- 0 # a.m_A0 insecticide exposure male hi1 no2
input[11,1] <- 0 # a.m_0b insecticide exposure male no1 lo2
input[12,1] <- 0 # a.m_0B insecticide exposure male no1 hi2
input[13,1] <- 0 # a.m_ab insecticide exposure male lo1 lo2
input[14,1] <- 0.9 # a.m_AB insecticide exposure male hi1 hi2
input[15,1] <- 0 # a.m_Ab insecticide exposure male hi1 lo2
input[16,1] <- 0 # a.m_aB insecticide exposure male lo1 hi2
input[17,1] <- 0.1 # a.f_00 insecticide exposure female no1 no2
input[18,1] <- 0 # a.f_a0 insecticide exposure female lo1 no2
input[19,1] <- 0 # a.f_A0 insecticide exposure female hi1 no2
input[20,1] <- 0 # a.f_0b insecticide exposure female no1 lo2
input[21,1] <- 0 # a.f_0B insecticide exposure female no1 hi2
input[22,1] <- 0 # a.f_ab insecticide exposure female lo1 lo2
input[23,1] <- 0.9 # a.f_AB insecticide exposure female hi1 hi2
input[24,1] <- 0 # a.f_Ab insecticide exposure female hi1 lo2
input[25,1] <- 0 # a.f_aB insecticide exposure female lo1 hi2
input[26,1] <- 0 # phi.SS1_a0 Baseline fitness of SS1 in a0
input[27,1] <- 1 # phi.SS1_A0 Baseline fitness of SS1 in A0
input[28,1] <- 0 # phi.SS2_0b Baseline fitness of SS2 in 0b
input[29,1] <- 1 # phi.SS2_0B Baseline fitness of SS2 in 0B
input[30,1] <- 1 # W.SS1_00 Fitness of SS1 in 00 (no insecticide)
input[31,1] <- 1 # W.SS2_00 Fitness of SS2 in 00 (no insecticide)
input[32,1] <- 0 # h.RS1_00 Dominance coefficient locus1 in 00
input[33,1] <- 0 # h.RS1_a0 Dominance coefficient locus1 in a0
input[34,1] <- 1 # h.RS1_A0 Dominance coefficient locus1 in A0
input[35,1] <- 0 # h.RS2_00 Dominance coefficient locus2 in 00
input[36,1] <- 0 # h.RS2_0b Dominance coefficient locus2 in 0b
input[37,1] <- 1 # h.RS2_0B Dominance coefficient locus2 in 0B
input[38,1] <- 0 # s.RR1_a0 Selection coefficient locus1 in a
input[39,1] <- 1 # s.RR1_A0 Selection coefficient locus1 in A
input[40,1] <- 0 # s.RR2_0b Selection coefficient locus2 in b
input[41,1] <- 1 # s.RR2_0B Selection coefficient locus2 in B
input[42,1] <- 0 # z.RR1_00 fitness cost of resistance allele 1 in insecticide free environment
input[43,1] <- 0 # z.RR2_00 fitness cost of resistance allele 2 in insecticide free environment
input[44,1] <- 1 # niche_00 insecticide niche toggle no1 no2 0=off 1=on
input[45,1] <- 0 # niche_a0 insecticide niche toggle no1 no2 0=off 1=on
input[46,1] <- 0 # niche_A0 insecticide niche toggle hi1 no2 0=off 1=on
input[47,1] <- 0 # niche_0b insecticide niche toggle no1 lo2 0=off 1=on
input[48,1] <- 0 # niche_0B insecticide niche toggle no1 hi2 0=off 1=on
input[49,1] <- 0 # niche_ab insecticide niche toggle lo1 lo2 0=off 1=on
input[50,1] <- 1 # niche_AB insecticide niche toggle hi1 hi2 0=off 1=on
input[51,1] <- 0 # niche_Ab insecticide niche toggle hi1 lo2 0=off 1=on
input[52,1] <- 0 # niche_aB insecticide niche toggle lo1 hi2 0=off 1=on
input[53,1] <- 0 # sexLinked 0=FALSE 1=TRUE
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
# }
input[,2] <- input[,1]
}
# Calibration 1012 - Fig 2 Curtis: Sequential (B,A) and then combination treatments
if( !params.csv && calibration == 1012 ){
input <- matrix( ncol=3, nrow=53 )
colnames(input) <- c("B (HCH)", "A (DDT)","Combination")
### Sequential Treatment
## Column 1 - Scenario 1, Insecticide B (Dieldrin)
input[1,1] <- calibration
### Results Matrix ###
# Give number of generations
input[2,1] <- 70
### Saving Parameters ###
# To save parameters in a matrix, set coll.fitvals to 1 ##
input[3,1] <- 1
# to save this matrix to an external .csv set to 1, will overwrite ##
input[4,1] <- save.fitvals
### Genotype Frequencies ###
## setting up to get proportions of genotypes in population
## User enters value of P - frequency of resistance allele at locus 1&2 respectively
input[5,1] <- 0.01 # locus 1
input[6,1] <- 0.01 # locus 2
## Recombination ##
input[7,1] <- 0.5 # recombination rate
### Insecticides are represented as a and b ###
### small case = low concentration, upper case = high concentration, 0 = absence (zero not UC o). ###
### Exposure Values ###
## Exposure levels of males and females to each insecticide niche ##
# males
input[8,1] <- 0.1 #Niche -,-
input[9,1] <- 0
input[10,1] <- 0
input[11,1] <- 0
input[12,1] <- 0.9 #Niche 0,B
input[13,1] <- 0
input[14,1] <- 0
input[15,1] <- 0
input[16,1] <- 0
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }else{
# print( paste( "Male exposures total 1: ", a.m ))
# }
# females
input[17,1] <- 0.1 #niche -,-
input[18,1] <- 0
input[19,1] <- 0
input[20,1] <- 0
input[21,1] <- 0.9 #Niche 0,B
input[22,1] <- 0
input[23,1] <- 0
input[24,1] <- 0
input[25,1] <- 0
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
#
# }else{
# print( paste( "female exposures total 1: ", a.f ))
# }
### Selection from distributions ###
### Fitness Values ###
## Baseline of SS in each insecticide/concentration (NOT niche, see Table 3. of brief)
## User entered fitness values to allow some survival of homozygote susceptible due to chance
# set as variables to be used in function calls/equations
# phi = baseline fitness value
input[26,1] <- 0
input[27,1] <- 0.73 #Phi SS1 in A
input[28,1] <- 0
input[29,1] <- 1 #Phi SS2 in B
# fitness of SS in environment with no insecticide are set to 1
# W = fitness value
input[30,1] <- 1
input[31,1] <- 1
## Dominance and selection coefficients
## needed to find fitness values of genotype in exposure to relating insecticide
# h = dominance coefficient
input[32,1] <- 0
input[33,1] <- 0
input[34,1] <- 0.17 #Dominance coefficient in A
input[35,1] <- 0
input[36,1] <- 0
input[37,1] <- 0.0016 #Dominance coefficient in B
# s = selection coefficient
input[38,1] <- 0
input[39,1] <- 0.23 #in A
input[40,1] <- 0
input[41,1] <- 0.43 #in B
# z = fitness cost of resistance allele in insecticide free environment
input[42,1] <- 0
input[43,1] <- 0
### Toggle Insecticide Niches on and off ###
## Allows for setting of specific combinations of insecticide niches to be used
## if toggled FALSE the calculation of fitness in that niche is cancelled and results printed as 0
## even if all set to TRUE, calibration == 1011||1012 will change the correct ones to OFF to run Curtis/Comparator
input[44,1] <- 1 #Niche 00
input[45,1] <- 0
input[46,1] <- 0
input[47,1] <- 0
input[48,1] <- 1 #Niche 0B
input[49,1] <- 0
input[50,1] <- 0
input[51,1] <- 0
input[52,1] <- 0
input[53,1] <- 0 # sexLinked 0=FALSE 1=TRUE
## Scenario 2 - Insecticide A (DDT) ####
input[1,2] <- calibration
### Results Matrix ###
# Give number of generations
input[2,2] <- 70
### Saving Parameters ###
# To save parameters in a matrix, set coll.fitvals to 1 ##
input[3,2] <- 1
# to save this matrix to an external .csv set to 1, will overwrite ##
input[4,2] <- save.fitvals
### Genotype Frequencies ###
## setting up to get proportions of genotypes in population
## User enters value of P - frequency of resistance allele at locus 1&2 respectively
input[5,2] <- 0.01 # locus 1
input[6,2] <- 0.01 # locus 2
## From this, the function HW will find the proportions of each genotype
## RR = p, RS = pq, SS = q
## P = p = R
## Recombination ##
input[7,2] <- 0.5 # recombination rate
### Insecticides are represented as a and b ###
### small case = low concentration, upper case = high concentration, 0 = absence (zero not UC o). ###
### Exposure Values ###
## Exposure levels of males and females to each insecticide niche ##
# males
input[8,2] <- 0.1 #Niche -,-
input[9,2] <- 0
input[10,2] <- 0.9 #Niche A,0
input[11,2] <- 0
input[12,2] <- 0
input[13,2] <- 0
input[14,2] <- 0
input[15,2] <- 0
input[16,2] <- 0
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }else{
# print( paste( "Male exposures total 1: ", a.m ))
# }
# females
input[17,2] <- 0.1 #niche -,-
input[18,2] <- 0
input[19,2] <- 0.9 #Niche A,0
input[20,2] <- 0
input[21,2] <- 0
input[22,2] <- 0
input[23,2] <- 0
input[24,2] <- 0
input[25,2] <- 0
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
#
# }else{
# print( paste( "female exposures total 1: ", a.f ))
# }
### Selection from distributions ###
### Fitness Values ###
## Baseline of SS in each insecticide/concentration (NOT niche, see Table 3. of brief)
## User entered fitness values to allow some survival of homozygote susceptible due to chance
# set as variables to be used in function calls/equations
# phi = baseline fitness value
input[26,2] <- 0
input[27,2] <- 0.73 #Phi SS1 in A
input[28,2] <- 0
input[29,2] <- 1 #Phi SS2 in B
# fitness of SS in environment with no insecticide are set to 1
# W = fitness value
input[30,2] <- 1
input[31,2] <- 1
## Dominance and selection coefficients
## needed to find fitness values of genotype in exposure to relating insecticide
# h = dominance coefficient
input[32,2] <- 0
input[33,2] <- 0
input[34,2] <- 0.17 #Dominance coefficient in A
input[35,2] <- 0
input[36,2] <- 0
input[37,2] <- 0.0016 #Dominance coefficient in B
# s = selection coefficient
input[38,2] <- 0
input[39,2] <- 0.23 #in A
input[40,2] <- 0
input[41,2] <- 0.43 #in B
# z = fitness cost of resistance allele in insecticide free environment
input[42,2] <- 0
input[43,2] <- 0
### Toggle Insecticide Niches on and off ###
## Allows for setting of specific combinations of insecticide niches to be used
## if toggled FALSE the calculation of fitness in that niche is cancelled and results printed as 0
## even if all set to TRUE, calibration == 1011||1012 will change the correct ones to OFF to run Curtis/Comparator
input[44,2] <- 1 #Niche 00
input[45,2] <- 0
input[46,2] <- 1 #Niche A0
input[47,2] <- 0
input[48,2] <- 0
input[49,2] <- 0
input[50,2] <- 0
input[51,2] <- 0
input[52,2] <- 0
input[53,2] <- 0 # sexLinked 0=FALSE 1=TRUE
### Scenario 3 Combination Treatment ####
input[1,3] <- calibration
### Results Matrix ###
# Give number of generations
input[2,3] <- 160
### Saving Parameters ###
# To save parameters in a matrix, set coll.fitvals to 1 ##
input[3,3] <- 1
# to save this matrix to an external .csv set to 1, will overwrite ##
input[4,3] <- save.fitvals
### Genotype Frequencies ###
## setting up to get proportions of genotypes in population
## User enters value of P - frequency of resistance allele at locus 1&2 respectively
input[5,3] <- 0.01 # locus 1
input[6,3] <- 0.01 # locus 2
## From this, the function HW will find the proportions of each genotype
## RR = p, RS = pq, SS = q
## P = p = R
## Recombination ##
input[7,3] <- 0.5 # recombination rate
### Insecticides are represented as a and b ###
### small case = low concentration, upper case = high concentration, 0 = absence (zero not UC o). ###
### Exposure Values ###
## Exposure levels of males and females to each insecticide niche ##
# males
input[8,3] <- 0.1 #Niche -,-
input[9,3] <- 0
input[10,3] <- 0
input[11,3] <- 0
input[12,3] <- 0
#todo check this is wanted
#input[13,3] <-
#i think it was a bug it made total exposure > 1 (it set ab to 0.9 and total to 1.9)
input[13,3] <- 0
input[14,3] <- 0.9 #Niche A,B
input[15,3] <- 0
input[16,3] <- 0
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }else{
# print( paste( "Male exposures total 1: ", a.m ))
# }
# females
input[17,3] <- 0.1 #niche -,-
input[18,3] <- 0
input[19,3] <- 0
input[20,3] <- 0
input[21,3] <- 0
input[22,3] <- 0
input[23,3] <- 0.9 #niche A,B
input[24,3] <- 0
input[25,3] <- 0
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
#
# }else{
# print( paste( "female exposures total 1: ", a.f ))
# }
### Selection from distributions ###
### Fitness Values ###
## Baseline of SS in each insecticide/concentration (NOT niche, see Table 3. of brief)
## User entered fitness values to allow some survival of homozygote susceptible due to chance
# set as variables to be used in function calls/equations
# phi = baseline fitness value
input[26,3] <- 0
input[27,3] <- 0.73 #Phi SS1 in A
input[28,3] <- 0
input[29,3] <- 1 #Phi SS2 in B
# fitness of SS in environment with no insecticide are set to 1
# W = fitness value
input[30,3] <- 1
input[31,3] <- 1
## Dominance and selection coefficients
## needed to find fitness values of genotype in exposure to relating insecticide
# h = dominance coefficient
input[32,3] <- 0
input[33,3] <- 0
input[34,3] <- 0.17 #Dominance coefficient in A
input[35,3] <- 0
input[36,3] <- 0
#input[37,3] <- 0.00016 #Dominance coefficient in B
#? should this be the same as the value in ,2 & ,1
input[37,3] <- 0.0016 #Dominance coefficient in B
# s = selection coefficient
input[38,3] <- 0
input[39,3] <- 0.23 #in A
input[40,3] <- 0
input[41,3] <- 0.43 #in B
# z = fitness cost of resistance allele in insecticide free environment
input[42,3] <- 0
input[43,3] <- 0
### Toggle Insecticide Niches on and off ###
## Allows for setting of specific combinations of insecticide niches to be used
## if toggled FALSE the calculation of fitness in that niche is cancelled and results printed as 0
## even if all set to TRUE, calibration == 1011||1012 will change the correct ones to OFF to run Curtis/Comparator
input[44,3] <- 1 #Niche 00
input[45,3] <- 0
input[46,3] <- 0
input[47,3] <- 0
input[48,3] <- 0
input[49,3] <- 0
input[50,3] <- 1 #Niche AB
input[51,3] <- 0
input[52,3] <- 0
input[53,3] <- 0 # sexLinked 0=FALSE 1=TRUE
}
if( !params.csv ){
rownames(input) <- c( "Calibration (100 default)","Number of generations ",
"Collect fitness scores in matrix (1/0)","Export fitness scores matrix to .csv (1/0)",
"Frequency of R at locus 1","Frequency of R at locus 2","Recombination Rate","Exposure Males -,-","Exposure Males a,-",
"Exposure Males A,-","Exposure Males -,b","Exposure Males -,B","Exposure males a,b","Exposure Males A,B",
"Exposure Males A,b","Exposure Males a,B","Exposure Females -,-","Exposure Females a,-","Exposure Females A,-",
"Exposure Females -,b","Exposure Females -,B","Exposure Females a,b","Exposure Females A,B","Exposure Females A,b",
"Exposure Females a,B","Baseline fitness of SS1 in a,-","Baseline fitness of SS1 in A,-","Baseline fitness of SS2 in -,b",
"Baseline fitness of SS2 in -,B","Fitness of SS1 in -,-","Fitness of SS2 in -,-","Dominance coefficient L1 in -,-",
"Dominance coefficient L1 in a,-","Dominance coefficient L1 in A,-","Dominance coefficient L2 in -,-","Dominance coefficient L2 in -,b",
"Dominance coefficient L2 in -,B","Selection coefficient L1 in a","Selection coefficient L1 in A","Selection coefficient L2 in b",
"Selection coefficient L2 in B","Fitness cost of R at L1 in -,-","Fitness cost of R at L2 in -,-","Niche -,- on (1/0)",
"Niche a,- on","Niche A,- on","Niche -,b on","Niche -,B on","Niche a,b on","Niche A,B on","Niche A,b on","Niche a,B on","sexLinked" )
}
return(input)
}
AndySouth/resistance documentation built on Nov. 12, 2020, 3:39 a.m.
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Defines functions createInputMatrix
#' create input parameters matrix from a file or hardcoded scenarios
#'
#' Creates a matrix with parameters in rows and scenarios in columns.
#' Either from a csv file or hardcoded scenarios set by the calibration argument.
#'
#' @param params.csv whether parameters are defined in an input file TRUE/FALSE
#' @param inFile parameters filename
#' @param calibration one of a limited set of integers effecting how scenarios are run
#' @param save.fitvals whether to save fitness scores to csv 0=no, 1=yes
#'
#' @seealso \code{\link{setInputOneScenario}} and \code{\link{setInputSensiScenarios}} for creating input objects from passed arguments
#'
#' @return matrix
#' @export
createInputMatrix <- function(params.csv,
inFile = system.file("extdata","input.parameters.csv", package="resistance"),
calibration = 1012,
save.fitvals = 0 ){
#todo may be able to combine params.csv and file arguments
## if parameters from input file -
#params.csv <- TRUE #testing whether this always needs to be done
if( params.csv )
{
#todo add check that file exists
input <- read.csv( inFile, header=T, stringsAsFactors=F )
# make into matrix from data.frame
input <- make.matrix(input, input$Input)
return(input)
}
#seeing if I need to initialise the matrix outside of the callibration loops below
#input <- matrix()
## Scenario 1 Calibration 1011 - Fig 1 Curtis ####
if( !params.csv && calibration == 1011 ){
input <- matrix( ncol=2, nrow=53 )
input[1,1] <- calibration # calibration a code to run specific set of scenarios
input[2,1] <- 18 # max_gen number of generations
input[3,1] <- 1 # coll.fitvals save fitness values in a matrix 0/1
input[4,1] <- save.fitvals # save.fitvals save fitness values to an external .csv 0/1
input[5,1] <- 0.001 # P_1 locus 1 frequency of resistance allele
input[6,1] <- 0.001 # P_2 locus 2 frequency of resistance allele
input[7,1] <- 0.5 # recomb_rate recombination rate
input[8,1] <- 0.1 # a.m_00 insecticide exposure male no1 no2
input[9,1] <- 0 # a.m_a0 insecticide exposure male lo1 no2
input[10,1] <- 0 # a.m_A0 insecticide exposure male hi1 no2
input[11,1] <- 0 # a.m_0b insecticide exposure male no1 lo2
input[12,1] <- 0 # a.m_0B insecticide exposure male no1 hi2
input[13,1] <- 0 # a.m_ab insecticide exposure male lo1 lo2
input[14,1] <- 0.9 # a.m_AB insecticide exposure male hi1 hi2
input[15,1] <- 0 # a.m_Ab insecticide exposure male hi1 lo2
input[16,1] <- 0 # a.m_aB insecticide exposure male lo1 hi2
input[17,1] <- 0.1 # a.f_00 insecticide exposure female no1 no2
input[18,1] <- 0 # a.f_a0 insecticide exposure female lo1 no2
input[19,1] <- 0 # a.f_A0 insecticide exposure female hi1 no2
input[20,1] <- 0 # a.f_0b insecticide exposure female no1 lo2
input[21,1] <- 0 # a.f_0B insecticide exposure female no1 hi2
input[22,1] <- 0 # a.f_ab insecticide exposure female lo1 lo2
input[23,1] <- 0.9 # a.f_AB insecticide exposure female hi1 hi2
input[24,1] <- 0 # a.f_Ab insecticide exposure female hi1 lo2
input[25,1] <- 0 # a.f_aB insecticide exposure female lo1 hi2
input[26,1] <- 0 # phi.SS1_a0 Baseline fitness of SS1 in a0
input[27,1] <- 1 # phi.SS1_A0 Baseline fitness of SS1 in A0
input[28,1] <- 0 # phi.SS2_0b Baseline fitness of SS2 in 0b
input[29,1] <- 1 # phi.SS2_0B Baseline fitness of SS2 in 0B
input[30,1] <- 1 # W.SS1_00 Fitness of SS1 in 00 (no insecticide)
input[31,1] <- 1 # W.SS2_00 Fitness of SS2 in 00 (no insecticide)
input[32,1] <- 0 # h.RS1_00 Dominance coefficient locus1 in 00
input[33,1] <- 0 # h.RS1_a0 Dominance coefficient locus1 in a0
input[34,1] <- 1 # h.RS1_A0 Dominance coefficient locus1 in A0
input[35,1] <- 0 # h.RS2_00 Dominance coefficient locus2 in 00
input[36,1] <- 0 # h.RS2_0b Dominance coefficient locus2 in 0b
input[37,1] <- 1 # h.RS2_0B Dominance coefficient locus2 in 0B
input[38,1] <- 0 # s.RR1_a0 Selection coefficient locus1 in a
input[39,1] <- 1 # s.RR1_A0 Selection coefficient locus1 in A
input[40,1] <- 0 # s.RR2_0b Selection coefficient locus2 in b
input[41,1] <- 1 # s.RR2_0B Selection coefficient locus2 in B
input[42,1] <- 0 # z.RR1_00 fitness cost of resistance allele 1 in insecticide free environment
input[43,1] <- 0 # z.RR2_00 fitness cost of resistance allele 2 in insecticide free environment
input[44,1] <- 1 # niche_00 insecticide niche toggle no1 no2 0=off 1=on
input[45,1] <- 0 # niche_a0 insecticide niche toggle no1 no2 0=off 1=on
input[46,1] <- 0 # niche_A0 insecticide niche toggle hi1 no2 0=off 1=on
input[47,1] <- 0 # niche_0b insecticide niche toggle no1 lo2 0=off 1=on
input[48,1] <- 0 # niche_0B insecticide niche toggle no1 hi2 0=off 1=on
input[49,1] <- 0 # niche_ab insecticide niche toggle lo1 lo2 0=off 1=on
input[50,1] <- 1 # niche_AB insecticide niche toggle hi1 hi2 0=off 1=on
input[51,1] <- 0 # niche_Ab insecticide niche toggle hi1 lo2 0=off 1=on
input[52,1] <- 0 # niche_aB insecticide niche toggle lo1 hi2 0=off 1=on
input[53,1] <- 0 # sexLinked 0=FALSE 1=TRUE
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
# }
input[,2] <- input[,1]
}
# Calibration 1012 - Fig 2 Curtis: Sequential (B,A) and then combination treatments
if( !params.csv && calibration == 1012 ){
input <- matrix( ncol=3, nrow=53 )
colnames(input) <- c("B (HCH)", "A (DDT)","Combination")
### Sequential Treatment
## Column 1 - Scenario 1, Insecticide B (Dieldrin)
input[1,1] <- calibration
### Results Matrix ###
# Give number of generations
input[2,1] <- 70
### Saving Parameters ###
# To save parameters in a matrix, set coll.fitvals to 1 ##
input[3,1] <- 1
# to save this matrix to an external .csv set to 1, will overwrite ##
input[4,1] <- save.fitvals
### Genotype Frequencies ###
## setting up to get proportions of genotypes in population
## User enters value of P - frequency of resistance allele at locus 1&2 respectively
input[5,1] <- 0.01 # locus 1
input[6,1] <- 0.01 # locus 2
## Recombination ##
input[7,1] <- 0.5 # recombination rate
### Insecticides are represented as a and b ###
### small case = low concentration, upper case = high concentration, 0 = absence (zero not UC o). ###
### Exposure Values ###
## Exposure levels of males and females to each insecticide niche ##
# males
input[8,1] <- 0.1 #Niche -,-
input[9,1] <- 0
input[10,1] <- 0
input[11,1] <- 0
input[12,1] <- 0.9 #Niche 0,B
input[13,1] <- 0
input[14,1] <- 0
input[15,1] <- 0
input[16,1] <- 0
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }else{
# print( paste( "Male exposures total 1: ", a.m ))
# }
# females
input[17,1] <- 0.1 #niche -,-
input[18,1] <- 0
input[19,1] <- 0
input[20,1] <- 0
input[21,1] <- 0.9 #Niche 0,B
input[22,1] <- 0
input[23,1] <- 0
input[24,1] <- 0
input[25,1] <- 0
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
#
# }else{
# print( paste( "female exposures total 1: ", a.f ))
# }
### Selection from distributions ###
### Fitness Values ###
## Baseline of SS in each insecticide/concentration (NOT niche, see Table 3. of brief)
## User entered fitness values to allow some survival of homozygote susceptible due to chance
# set as variables to be used in function calls/equations
# phi = baseline fitness value
input[26,1] <- 0
input[27,1] <- 0.73 #Phi SS1 in A
input[28,1] <- 0
input[29,1] <- 1 #Phi SS2 in B
# fitness of SS in environment with no insecticide are set to 1
# W = fitness value
input[30,1] <- 1
input[31,1] <- 1
## Dominance and selection coefficients
## needed to find fitness values of genotype in exposure to relating insecticide
# h = dominance coefficient
input[32,1] <- 0
input[33,1] <- 0
input[34,1] <- 0.17 #Dominance coefficient in A
input[35,1] <- 0
input[36,1] <- 0
input[37,1] <- 0.0016 #Dominance coefficient in B
# s = selection coefficient
input[38,1] <- 0
input[39,1] <- 0.23 #in A
input[40,1] <- 0
input[41,1] <- 0.43 #in B
# z = fitness cost of resistance allele in insecticide free environment
input[42,1] <- 0
input[43,1] <- 0
### Toggle Insecticide Niches on and off ###
## Allows for setting of specific combinations of insecticide niches to be used
## if toggled FALSE the calculation of fitness in that niche is cancelled and results printed as 0
## even if all set to TRUE, calibration == 1011||1012 will change the correct ones to OFF to run Curtis/Comparator
input[44,1] <- 1 #Niche 00
input[45,1] <- 0
input[46,1] <- 0
input[47,1] <- 0
input[48,1] <- 1 #Niche 0B
input[49,1] <- 0
input[50,1] <- 0
input[51,1] <- 0
input[52,1] <- 0
input[53,1] <- 0 # sexLinked 0=FALSE 1=TRUE
## Scenario 2 - Insecticide A (DDT) ####
input[1,2] <- calibration
### Results Matrix ###
# Give number of generations
input[2,2] <- 70
### Saving Parameters ###
# To save parameters in a matrix, set coll.fitvals to 1 ##
input[3,2] <- 1
# to save this matrix to an external .csv set to 1, will overwrite ##
input[4,2] <- save.fitvals
### Genotype Frequencies ###
## setting up to get proportions of genotypes in population
## User enters value of P - frequency of resistance allele at locus 1&2 respectively
input[5,2] <- 0.01 # locus 1
input[6,2] <- 0.01 # locus 2
## From this, the function HW will find the proportions of each genotype
## RR = p, RS = pq, SS = q
## P = p = R
## Recombination ##
input[7,2] <- 0.5 # recombination rate
### Insecticides are represented as a and b ###
### small case = low concentration, upper case = high concentration, 0 = absence (zero not UC o). ###
### Exposure Values ###
## Exposure levels of males and females to each insecticide niche ##
# males
input[8,2] <- 0.1 #Niche -,-
input[9,2] <- 0
input[10,2] <- 0.9 #Niche A,0
input[11,2] <- 0
input[12,2] <- 0
input[13,2] <- 0
input[14,2] <- 0
input[15,2] <- 0
input[16,2] <- 0
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }else{
# print( paste( "Male exposures total 1: ", a.m ))
# }
# females
input[17,2] <- 0.1 #niche -,-
input[18,2] <- 0
input[19,2] <- 0.9 #Niche A,0
input[20,2] <- 0
input[21,2] <- 0
input[22,2] <- 0
input[23,2] <- 0
input[24,2] <- 0
input[25,2] <- 0
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
#
# }else{
# print( paste( "female exposures total 1: ", a.f ))
# }
### Selection from distributions ###
### Fitness Values ###
## Baseline of SS in each insecticide/concentration (NOT niche, see Table 3. of brief)
## User entered fitness values to allow some survival of homozygote susceptible due to chance
# set as variables to be used in function calls/equations
# phi = baseline fitness value
input[26,2] <- 0
input[27,2] <- 0.73 #Phi SS1 in A
input[28,2] <- 0
input[29,2] <- 1 #Phi SS2 in B
# fitness of SS in environment with no insecticide are set to 1
# W = fitness value
input[30,2] <- 1
input[31,2] <- 1
## Dominance and selection coefficients
## needed to find fitness values of genotype in exposure to relating insecticide
# h = dominance coefficient
input[32,2] <- 0
input[33,2] <- 0
input[34,2] <- 0.17 #Dominance coefficient in A
input[35,2] <- 0
input[36,2] <- 0
input[37,2] <- 0.0016 #Dominance coefficient in B
# s = selection coefficient
input[38,2] <- 0
input[39,2] <- 0.23 #in A
input[40,2] <- 0
input[41,2] <- 0.43 #in B
# z = fitness cost of resistance allele in insecticide free environment
input[42,2] <- 0
input[43,2] <- 0
### Toggle Insecticide Niches on and off ###
## Allows for setting of specific combinations of insecticide niches to be used
## if toggled FALSE the calculation of fitness in that niche is cancelled and results printed as 0
## even if all set to TRUE, calibration == 1011||1012 will change the correct ones to OFF to run Curtis/Comparator
input[44,2] <- 1 #Niche 00
input[45,2] <- 0
input[46,2] <- 1 #Niche A0
input[47,2] <- 0
input[48,2] <- 0
input[49,2] <- 0
input[50,2] <- 0
input[51,2] <- 0
input[52,2] <- 0
input[53,2] <- 0 # sexLinked 0=FALSE 1=TRUE
### Scenario 3 Combination Treatment ####
input[1,3] <- calibration
### Results Matrix ###
# Give number of generations
input[2,3] <- 160
### Saving Parameters ###
# To save parameters in a matrix, set coll.fitvals to 1 ##
input[3,3] <- 1
# to save this matrix to an external .csv set to 1, will overwrite ##
input[4,3] <- save.fitvals
### Genotype Frequencies ###
## setting up to get proportions of genotypes in population
## User enters value of P - frequency of resistance allele at locus 1&2 respectively
input[5,3] <- 0.01 # locus 1
input[6,3] <- 0.01 # locus 2
## From this, the function HW will find the proportions of each genotype
## RR = p, RS = pq, SS = q
## P = p = R
## Recombination ##
input[7,3] <- 0.5 # recombination rate
### Insecticides are represented as a and b ###
### small case = low concentration, upper case = high concentration, 0 = absence (zero not UC o). ###
### Exposure Values ###
## Exposure levels of males and females to each insecticide niche ##
# males
input[8,3] <- 0.1 #Niche -,-
input[9,3] <- 0
input[10,3] <- 0
input[11,3] <- 0
input[12,3] <- 0
#todo check this is wanted
#input[13,3] <-
#i think it was a bug it made total exposure > 1 (it set ab to 0.9 and total to 1.9)
input[13,3] <- 0
input[14,3] <- 0.9 #Niche A,B
input[15,3] <- 0
input[16,3] <- 0
#a.m <- sum(a.m_00, a.m_a0, a.m_A0, a.m_0b, a.m_0B, a.m_ab, a.m_AB, a.m_Ab, a.m_aB)
#if ( a.m != 1 ){
# print( paste("Error in male exposures: must total one: ", a.m) )
# }else{
# print( paste( "Male exposures total 1: ", a.m ))
# }
# females
input[17,3] <- 0.1 #niche -,-
input[18,3] <- 0
input[19,3] <- 0
input[20,3] <- 0
input[21,3] <- 0
input[22,3] <- 0
input[23,3] <- 0.9 #niche A,B
input[24,3] <- 0
input[25,3] <- 0
#a.f <- sum(a.f_00, a.f_a0, a.f_A0, a.f_0b, a.f_0B, a.f_ab, a.f_AB, a.f_Ab, a.f_aB)
#if ( a.f != 1 ){
# print( paste("Error in female exposures: must total one: ", a.f) )
#
# }else{
# print( paste( "female exposures total 1: ", a.f ))
# }
### Selection from distributions ###
### Fitness Values ###
## Baseline of SS in each insecticide/concentration (NOT niche, see Table 3. of brief)
## User entered fitness values to allow some survival of homozygote susceptible due to chance
# set as variables to be used in function calls/equations
# phi = baseline fitness value
input[26,3] <- 0
input[27,3] <- 0.73 #Phi SS1 in A
input[28,3] <- 0
input[29,3] <- 1 #Phi SS2 in B
# fitness of SS in environment with no insecticide are set to 1
# W = fitness value
input[30,3] <- 1
input[31,3] <- 1
## Dominance and selection coefficients
## needed to find fitness values of genotype in exposure to relating insecticide
# h = dominance coefficient
input[32,3] <- 0
input[33,3] <- 0
input[34,3] <- 0.17 #Dominance coefficient in A
input[35,3] <- 0
input[36,3] <- 0
#input[37,3] <- 0.00016 #Dominance coefficient in B
#? should this be the same as the value in ,2 & ,1
input[37,3] <- 0.0016 #Dominance coefficient in B
# s = selection coefficient
input[38,3] <- 0
input[39,3] <- 0.23 #in A
input[40,3] <- 0
input[41,3] <- 0.43 #in B
# z = fitness cost of resistance allele in insecticide free environment
input[42,3] <- 0
input[43,3] <- 0
### Toggle Insecticide Niches on and off ###
## Allows for setting of specific combinations of insecticide niches to be used
## if toggled FALSE the calculation of fitness in that niche is cancelled and results printed as 0
## even if all set to TRUE, calibration == 1011||1012 will change the correct ones to OFF to run Curtis/Comparator
input[44,3] <- 1 #Niche 00
input[45,3] <- 0
input[46,3] <- 0
input[47,3] <- 0
input[48,3] <- 0
input[49,3] <- 0
input[50,3] <- 1 #Niche AB
input[51,3] <- 0
input[52,3] <- 0
input[53,3] <- 0 # sexLinked 0=FALSE 1=TRUE
}
if( !params.csv ){
rownames(input) <- c( "Calibration (100 default)","Number of generations ",
"Collect fitness scores in matrix (1/0)","Export fitness scores matrix to .csv (1/0)",
"Frequency of R at locus 1","Frequency of R at locus 2","Recombination Rate","Exposure Males -,-","Exposure Males a,-",
"Exposure Males A,-","Exposure Males -,b","Exposure Males -,B","Exposure males a,b","Exposure Males A,B",
"Exposure Males A,b","Exposure Males a,B","Exposure Females -,-","Exposure Females a,-","Exposure Females A,-",
"Exposure Females -,b","Exposure Females -,B","Exposure Females a,b","Exposure Females A,B","Exposure Females A,b",
"Exposure Females a,B","Baseline fitness of SS1 in a,-","Baseline fitness of SS1 in A,-","Baseline fitness of SS2 in -,b",
"Baseline fitness of SS2 in -,B","Fitness of SS1 in -,-","Fitness of SS2 in -,-","Dominance coefficient L1 in -,-",
"Dominance coefficient L1 in a,-","Dominance coefficient L1 in A,-","Dominance coefficient L2 in -,-","Dominance coefficient L2 in -,b",
"Dominance coefficient L2 in -,B","Selection coefficient L1 in a","Selection coefficient L1 in A","Selection coefficient L2 in b",
"Selection coefficient L2 in B","Fitness cost of R at L1 in -,-","Fitness cost of R at L2 in -,-","Niche -,- on (1/0)",
"Niche a,- on","Niche A,- on","Niche -,b on","Niche -,B on","Niche a,b on","Niche A,B on","Niche A,b on","Niche a,B on","sexLinked" )
}
return(input)
}
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