This document is automtically created by querying the live copies of the game config google docs. We can use it for testing and balancing outside of the game.

#### load required packages
library(googlesheets)
library(readr)
library(resistanceGame)
library(dplyr)
library(ggplot2)
#eval et to false to not query gdocs

url_locations <- "https://docs.google.com/spreadsheets/d/1w6vZvxqX3FgtkmM8mUSvB67reekKz148LoQY2OT012M/"
url_resistances <- "https://docs.google.com/spreadsheets/d/1f9omxuMru95xBkmR0hLhrM88tvnxvJjsEXIiDjJOgL4"
url_interventions <- "https://docs.google.com/spreadsheets/d/1SVyZZTR6tmDHRr0hLAyn3UYS6n0x9vuu1YEKJ4M8MIs"
url_vectors <- "https://docs.google.com/spreadsheets/d/10urCBTuW-_E7i1alJOfqXF3r2jglrAQGBsvOGo7k1sA"

#reading location config file from googledocs
gd <- gs_url(url_locations)
locations <- gs_read(gd)

gd <- gs_url(url_resistances)
resistances <- gs_read(gd)

gd <- gs_url(url_interventions)
interventions <- gs_read(gd)

gd <- gs_url(url_vectors)
vectors <- gs_read(gd)


#cut first 2 rows which have junk in
locations <- as.data.frame( locations[-c(1:2),] )
#cut columns after 9 which contain non useful stuff
locations <- locations[,c(1:9)] 
#cut rows with NULL & NA in Vector ID column
locations <- locations[ -which(is.na(locations["Vector IDs"]) | locations["Vector IDs"]=='NULL'), ] 

#rename columns to more useful
colnames(locations)[colnames(locations)=="Location ID"] <- "loc_id"
colnames(locations)[colnames(locations)=="Vector\nEmergences"] <- "emergences"
colnames(locations)[colnames(locations)=="Vector IDs"] <- "vec_ids"
colnames(locations)[colnames(locations)=="Vector Resistance\nIDs (*)"] <- "vec_res_ids"
colnames(locations)[colnames(locations)=="Vector\nPopulations (*)"] <- "vec_abund"
colnames(locations)[colnames(locations)=="Vector Resistance\nFrequencies (*)"] <- "vec_res_freqs"
colnames(locations)[colnames(locations)=="Vector Resistance\nIntensities (*)"] <- "vec_res_ints"

colnames(vectors)[colnames(vectors)=="Vector ID"] <- "vec_id"
colnames(vectors)[colnames(vectors)=="Name"] <- "name"
colnames(vectors)[colnames(vectors)=="Survival Rate"] <- "survival"
colnames(vectors)[colnames(vectors)=="Infection Rate"] <- "infection"

#save example edited data to the package
devtools::use_data(locations, overwrite=TRUE)
devtools::use_data(resistances, overwrite=TRUE)
devtools::use_data(interventions, overwrite=TRUE)
devtools::use_data(vectors, overwrite=TRUE)
#create a composite dataframe of vectors at locations for later use
vecbyloc <- vecbyloc_from_gdocs()
devtools::use_data(vecbyloc, overwrite=TRUE)

Emergence patterns by location and vector over 12 months.

#locations should be got from saved ver. in package
#data(locations)

plot_config_gdocs_emergences()

Expected abundance patterns in absence of interventions over 3 years.

  #for each vecloc combination
  for (i in 1:nrow(vecbyloc))
  {
      #expanding the emergence string
      tmp5 <- expand_season(vecbyloc$emer_string[i], return_tstep = 'weeks')

      #run sim & just plot pop
      plot_sim_pop( run_sim(num_tsteps=144,
                    emergence=tmp5, survival=vecbyloc$survival[i]),
         title=paste0(vecbyloc$id[i]," survival:",vecbyloc$survival[i]), axis_x=TRUE, leg_pos='topleft')
  }

Expected abundance and resistance under one example scenario of intervention, insecticide_kill (0.9) & resistance

  #for each vecloc combination
  for (i in 1:nrow(vecbyloc))
  {
      #expanding the emergence string
      tmp5 <- expand_season(vecbyloc$emer_string[i], return_tstep = 'weeks')

      #run sim
      l_config2 <- config_plan(read_config(), t_strt=c(12*4, 24*4), t_stop=c(18*4,30*4),
                          control_id=c('irs_pyr'))
      plot_sim( run_sim(num_tsteps=144, emergence=tmp5, survival=vecbyloc$survival[i],
                   l_config=l_config2,
                   insecticide_kill=0.9, resist_freq_start = 0.05, resist_mech='metabolic',
                   resist_incr=0.1, resist_decr = 0.02),           
                   plot_emergence=TRUE, title=paste0(vecbyloc$id[i]), leg_pos='topleft' )

  }


AndySouth/resistanceGame documentation built on May 5, 2019, 6:01 a.m.