init_object_graph_data | R Documentation |
This function looks at various flags that have generally been set in the parameters object built from project.yaml and determines which, if any, graph metrics should be computed for the problem. It also sets the corresponding slot's value for each of the flags in the RSprob object.
init_object_graph_data( rsprob, top_dir, compute_network_metrics, compute_network_metrics_COR_APP_WRAP, use_igraph_metrics, use_bipartite_metrics, bipartite_metrics_to_use = "ALLBUTDD", write_to_disk = TRUE )
rsprob |
An RSprob reserve selection problem object to run graph metrics over if desired |
top_dir |
character string |
compute_network_metrics |
boolean flag indicating whether any graph metrics should be computed for this problem; TRUE implies metrics should be computed, FALSE implies not |
compute_network_metrics_COR_APP_WRAP |
boolean flag indicating whether this type of problem (base_cor, base_app, wrapped_cor, or wrapped_app) should have metrics computed for it; TRUE implies metrics should be computed, FALSE implies not |
use_igraph_metrics |
boolean flag indicating whether metrics based on the igraph package should be computed for this problem; TRUE implies they should be computed, FALSE implies not |
use_bipartite_metrics |
boolean flag indicating whether metrics based on the bipartite package should be computed for this problem; TRUE implies they should be computed, FALSE implies not |
bipartite_metrics_to_use |
character string indication which set of bipartite package metrics should be computed if any from that package are to be computed; current choices are "ALLBUTDD" or "all_except_slow_indices" |
write_to_disk |
boolean flag indicating whether metrics should be written to disk before being returned; TRUE implies write to disk, FALSE implies not The bipartite package has a range of measures that can be computed and some of them are quite slow, so the argument called "bipartite_metrics_to_use" is provided for this function to allow some control over the amount of time spent in the bipartite package computations. "ALLBUTDD" runs all of the metrics (including the slow ones) except for fitting parameters of the degree distribution, which is even slower than all the rest. "all_except_slow_indices" runs all metrics other than the slow ones, where "slow" is defined to be the degree distribution fitting and all of the metrics that are listed in the bipartite::networklevel() function's help page in its section called "Reducing computation time". Currently, the metrics identified in that routine as being somewhat slow are: "extinction slope", # #1a slowest "robustness", # #1b slowest "weighted cluster coefficient", # #2 slowest "degree distribution", # #3 slowest ("somewhat time consuming") "Fisher alpha", # #4 slowest ("computed iteratively and hence time consuming") "nestedness", # #5a slowest ("not the fastest of routines") "weighted nestedness", # #5b slowest ("not the fastest of routines") "number of compartments", # #6a slowest ("calls a recursive and hence relatively slow algorithm.") "compartment diversity", # #6b slowest ("calls a recursive and hence relatively slow algorithm.") "H2 # #7a slowest ("require an iterative, heuristic search algorithm", #7b - same for specialisation asymmetry but it's not in this list) "discrepancy", # #7c slowest ("excluding discrepancy can also moderately decrease computation time") It's easy to specify which metrics to include and exclude when calling bipartite::networklevel, so it would be easy to add other options of metrics to compute by making small modifcations to the bdpg function compute_network_measures_using_bipartite_package(). |
modified version of the rsrun input variable, i.e., with graph-related flags set
## Not run: Xu_bdprob_cor <- init_object_graph_data (Xu_bdprob_cor, parameters$compute_network_metrics_COR, parameters$use_igraph_metrics, parameters$use_bipartite_metrics, parameters$bipartite_metrics_to_use) ## End(Not run)
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