phytoclass2.3.1 package

Estimate Chla Concentrations of Phytoplankton Groups

Bounded_weights

Add weights to the data, bound at a maximum.

Cluster

Cluster things

Condition_test

Calculate the mean condition number for randomized F matrices

Conduit

Conduit between minimise_elements function and Fac_F_R of steepest des...

convergence_figure

Convergence Figure

Default_min_max

Sets the default minimum and maximum values for phytoplankton groups p...

Fac_F_RR

Part of the steepest descent algorithm that works to reduce error give...

Matrix_checks

Remove any column values that average 0. Further to this, also remove ...

Minimise_elements_comb

Part of the steepest descent algorithm

NNLS_MF_Final

Perform matrix factorisation for phytoplankton pigments and pigments r...

NNLS_MF

Performs the non-negative matrix factorisation for given phytoplankton...

Normalise_F

This function normalises each column in F to row sum

Normalise_S

Normalise matrix to row sum

phyto_figure

Phytoplankton Class Abundance Figure

Prochloro_Normalise_F

Normalize F matrix specifically for Prochlorococcus pigments

Prochloro_Random_Neighbour

Selects a random neighbour for a subset of non-zero pigments that are ...

Prochloro_Wrangling

Prochloro Wrangling

Random_neighbour

Select a random neighbour when the previous random neighbour is beyond...

Randomise_elements

Randomise value by applying scaling factors within specified bounds. S...

Replace_Rand

Select the new F matrix element with lowest error in the steepest desc...

SAALS

Apply the steepest descent algorithm to optimize pigment ratios in phy...

simulated_annealing_Prochloro

Perform simulated annealing algorithm for samples with divinyl chlorop...

simulated_annealing

This is the main phytoclass algorithm. It performs simulated annealing...

Steepest_Desc

Stand-alone version of steepest descent algorithm. This is similar to ...

Steepest_Descent

Performs the steepest descent algorithm for a set number of iterations...

vectorise

Vectorise a matrix and keep non-zero elements

Weight_error

Apply weights to F/S matrices by diagonal multiplication

Wrangling

Wrangle data to vectors

Determine the chlorophyll a (Chl a) concentrations of different phytoplankton groups based on their pigment biomarkers. The method uses non-negative matrix factorisation and simulated annealing to minimise error between the observed and estimated values of pigment concentrations (Hayward et al. (2023) <doi:10.1002/lom3.10541>). The approach is similar to the widely used 'CHEMTAX' program (Mackey et al. 1996) <doi:10.3354/meps144265>, but is more straightforward, accurate, and not reliant on initial guesses for the pigment to Chl a ratios for phytoplankton groups.

  • Maintainer: Alexander Hayward
  • License: MIT + file LICENSE
  • Last published: 2026-01-30