Perform simulated annealing algorithm for samples with divinyl chlorophyll and prochlorococcus. Chlorophyll must be the final column of both S and F matrices, with Divinyl Chlorophyll a the 2nd to last column. See how the example Sp and Fp matrices are organised.

Usage

simulated_annealing_Prochloro(
  S,
  Fmat = NULL,
  user_defined_min_max = NULL,
  do_matrix_checks = TRUE,
  niter = 500,
  step = 0.009,
  weight.upper.bound = 30,
  verbose = TRUE,
  seed = NULL,
  check_converge = 100
)

Arguments

S: Sample data matrix – a matrix of pigment samples
Fmat: Pigment to Chl a matrix
user_defined_min_max: data frame with some format as min_max built-in data
do_matrix_checks: This should only be set to TRUE when using the default values. This will remove pigment columns that have column sums of 0. Set to FALSE if using customised names for pigments and phytoplankton groups
niter: Number of iterations (default is 500)
step: Step ratio used (default is 0.009)
weight.upper.bound: Upper limit of the weights applied (default value is 30).
verbose: Logical value. Output error and temperature at each iteration. Default value of TRUE
seed: Set seed number to reproduce the same results
check_converge: TRUE/FALSE/integer; set the number of F matrices to for convergence checking

Value

A list containing

Fmat matrix
RMSE (Root Mean Square Error)
condition number
Class abundances
Figure (plot of results)
MAE (Mean Absolute Error)
Error

Examples

# Using the built-in matrices Sp and Fp.
set.seed(5326)
sa.example <- simulated_annealing_Prochloro(Sp, Fp, niter = 1)
#> 
#> Condition number = 9290
#> 
#> Iterations:         001 of 1 
#> Current error:      0.0079 
#> Neighbour's error:  0.0079 
#> Temperature (%):    99.1 
#> Using 15 color palette for `convergence plot`.
sa.example$Figure