Man pages for franzikoch/Feedbackloops
Feedback loop analysis for competition networks

assemble_jacobianConstruct a community matrix
find_sFind the relative amount of self-regulation needed for...
find_s_FFind the relative amount of self-regulation needed to...
get_FkCalculates total feedback at a given level _k_
get_namesHelper function to get data set names from the path of csv...
get_names_sansHelper functions to get data set names
interaction_strengthsCalculate interaction strengths
loopsCalculate the strengths and weights of all loops of length...
loops_parallelCalculates the strengths and weights of all loops of length...
loop_weightCalculate the loop strength and weight of a given feedback...
pipePipe operator
randomize_allFull randomisation of an interaction table
randomize_asymmetricMaximise pairwise asymmetry
randomize_asymmetric_hierarchicalMaximise pairwise and community asymmetry
randomize_minimalMinimal randomisation procedure
randomize_pwPairiwise (Weak) randomisation of an interaction table
read_abundanceReads in the abundance raw data file
read_contact_matrixReads in the species-contact matrix and returns a nicely...
read_dataRead in the raw data files
replace_zerosReplace missing diagonal values
scale_interaction_tableScale interaction strengths within an interaction table
scale_matrixScale interaction strengths within a Jacobian matrix
franzikoch/Feedbackloops documentation built on July 1, 2023, 12:42 p.m.