Plot results of capm model functions

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Description

Plot results of one of the following functions: SolveIASA, SolveSI or SolveTC.

Usage

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PlotModels(model.out = NULL, variable = NULL, col = "red",
  col1 = c("cadetblue1", "yellow", "red"), col2 = c("blue", "darkgreen",
  "darkred"), x.label = "Years", y.label = NULL,
  scenarios.label = "v = (__ * owned carrying capacity)",
  legend.label = NULL, pop = NULL)

Arguments

model.out

output of one of the function previously mentioned.

variable

string to specify the variable to be ploted.

For SolveSI function:

"n" (population size).

"q" (proportion of sterilized animals).

For SolveIASA function using only point estimates:

"f1" (owned intact females).

"fs1" (owned sterilized females).

"m1" (owned intact males).

"ms1" (owned sterilized males).

"f2" (stray intact females).

"fs2" (stray sterilized females).

"m2" (stray intact males).

"ms2" (stray sterilized males).

"n1" (owned intact animals).

"ns1" (owned sterilized animals).

"n2" (stray intact animals).

"ns2" (stray sterilized animals).

"N1" (owned animals).

"N2" (stray animals).

"N" (total population).

For SolveIASA function using *.range arguments:

"f" (intact females).

"fs" (sterilized females).

"m" (intact males).

"ms" (sterilized males).

"n" (intact animals).

"ns" (sterilized animals).

"N" (Total population stratified by reproductive status).

For SolveTC function:

"n" (fertile animals).

"g" (sterilized animals).

"u" (cumulative of sterilized animals)

col

string indicating the color of ploted line, when s.range is NULL.

col1

character vector indicating the color of lowest (highest) population sizes (proportion of sterilized animals), when s.range is not NULL.

col2

character vector indicating the color of highest (lowest) population sizes (proportion of sterilized animals), when s.range is not NULL.

x.label

string with the name of x axis.

y.label

string with the name of y axis.

scenarios.label

string with the name of scenarios of SolveIASA output, determined by the immigartion rates. Within the string, use the expression __ in the location where you want to appear the value of the immigartion rate. For line breaking, use \n (see examples).

legend.label

string with the name of legend, for plots of SolveIASA output.

pop

value indicating the output of SolveIASA to be ploted. When NULL (default), plots for owned and stray populations under scenarios created by immigartion rate are created. If 1, the plots of owned population for the minimum immigartion rate are ploted. When 2, the plots of stray population for the minimum immigartion rate are ploted. If 3, the plots of owned population for the maximum immigartion rate are ploted. When 4, the plots of owned population for the maximum immigartion rate are ploted.

Details

Font size of saved plots is usually different to the font size seen in graphic browsers. Before changing font sizes, see the final result in saved (or preview) plots.

Other details of the plot can be modifyed using appropriate functions from ggplot2 package.

References

Chang W (2012). R Graphics Cookbook. O'Reilly Media, Inc.

http://oswaldosantos.github.io/capm

See Also

plot.deSolve.

Examples

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#####################
## SolveIASA model ##
#####################

## Parameters and intial conditions.
pars.solve.iasa = c(
   b1 = 21871, b2 = 4374,
   df1 = 0.104, dm1 = 0.098, df2 = 0.125, dm2 = 0.118,
   sf1 = 0.069, sf2 = 0.05, sm1 = 0.028, sm2 = 0.05,
   k1 = 98050, k2 = 8055, h1 = 1, h2 = 0.5,
   a = 0.054, alpha = 0.1, v = 0.2, z = 0.1)
   
init.solve.iasa = c(
   f1 = 33425, fs1 = 10865,
   m1 = 38039, ms1 = 6808,
   f2 = 3343, fs2 = 109,
   m2 = 3804, ms2 = 68)
   

# Solve for point estimates.
solveiasa.pt <- SolveIASA(pars = pars.solve.iasa, 
                          init = init.solve.iasa, 
                          time = 0:10, method = 'rk4')

# Solve for parameter ranges.
solveiasa.rg <- SolveIASA(pars = pars.solve.iasa, 
                          init = init.solve.iasa, 
                          time = 0:10,
                          s.range = seq(0, .4, l = 15), 
                          a.range = c(0, .2), 
                          alpha.range = c(0, .2),
                          v.range = c(0, .1),
                          method = 'rk4')
                
## Plot stray population sizes using point estimates
# Uncomment the following line:
# PlotModels(solveiasa.pt, variable = "ns2")

## Plot all scenarios and change the label for the scenarios.
# Uncomment the following line:
# PlotModels(solveiasa.rg, variable = 'ns')