phytoclass (version 2.3.1)

simulated_annealing: This is the main phytoclass algorithm. It performs simulated annealing algorithm for S and F matrices. See the examples (Fm, Sm) for how to set up matrices, and the vignette for more detailed instructions. Different pigments and phytoplankton groups may be used.

Description

This is the main phytoclass algorithm. It performs simulated annealing algorithm for S and F matrices. See the examples (Fm, Sm) for how to set up matrices, and the vignette for more detailed instructions. Different pigments and phytoplankton groups may be used.

Usage

simulated_annealing(
  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,
  alt_pro_name = NULL
)

Value

A list containing

1. Fmat matrix

2. RMSE (Root Mean Square Error)

3. condition number

4. Class abundances

5. Figure (plot of results)

6. MAE (Mean Absolute Error)

7. Error

8. F_mat_iter

9. converge_plot

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 number to reproduce the same results

check_converge

TRUE/FALSE/integer; set the number of F matrices to for convergence checking

alt_pro_name

Optional: additional alternate versions of divinyl-chlorophyll-a spellings used to detect prochlorococcus (Default: "dvchl", "dvchla", "dv_chla")

Examples

# Using the built-in matrices Sm and Fm
set.seed(5326)
sa.example <- simulated_annealing(Sm, Fm, niter = 5)
sa.example$Figure