phytoclass (version 2.3.1)

Prochloro_Random_Neighbour: Selects a random neighbour for a subset of non-zero pigments that are outside the min and max bounds for the simulated annealing algorithm, specifically handling Prochlorococcus pigments.

Description

Selects a random neighbour for a subset of non-zero pigments that are outside the min and max bounds for the simulated annealing algorithm, specifically handling Prochlorococcus pigments.

Usage

Prochloro_Random_Neighbour(
  f_new,
  Temp,
  chlv,
  chlvp,
  N,
  place,
  S,
  S_weights,
  minF,
  maxF
)

Value

A list containing:

F matrix

The new F matrix with randomly modified values

RMSE

Root mean square error of the new solution

C matrix

The concentration matrix from NNLS

Arguments

f_new

F matrix of pigment ratios

Temp

Temperature of the annealing

chlv

Chlorophyll-a column

chlvp

Dvchla column

N

Indexs of pigment ratios to be changed

place

Indexes in F matrix where values are non-zero

S

S matrix of samples

S_weights

Weights for NNLS algorithm

minF

Minimum bounds for each phytoplankton group and pigments

maxF

Maximum bounds for each phytoplankton group and pigments

Examples

 Fmat <- as.matrix(phytoclass::Fp)
 S <- as.matrix(phytoclass::Sp)
 S_weights <- as.numeric(phytoclass:::Bounded_weights(S))
 place <- which(Fmat[, seq(ncol(Fmat) - 2)] > 0)

 # Get min_max from package data
 min_max_mat <- phytoclass:::Default_min_max(phytoclass::min_max, Fmat[, -ncol(Fmat)])

 # Get bounds using Prochloro_Wrangling as in simulated_annealing_Prochloro
 f_c <- Fmat
 W0 <- phytoclass:::Prochloro_Wrangling(f_c, min_max_mat[[1]], min_max_mat[[2]])
 minF <- W0[[1]]
 maxF <- W0[[2]]

 # Extract chlv and chlvp from the matrix
 chlv <- f_c[, ncol(f_c)] # Chl a (Tchla)
 chlvp <- f_c[, ncol(f_c) - 1] # dvChl a

 Temp <- 0.5
 N <- place

 # Run Prochloro_Random_Neighbour
 result <- phytoclass:::Prochloro_Random_Neighbour(
   f_c, Temp, chlv, chlvp, N, place, S, S_weights, minF, maxF
 )