Changelog
Source:NEWS.md
Version 0.8.93.0000
- Change function plot_troph_level_visNet_multi() and plot_troph_level_visNet() legend of layer above line of layer and width = “100%”, height = “400px”
Version 0.8.92.0000
- Change functions plot_troph_level_visNet_multi() and plot_troph_level_visNet() parameter physic=“x” order by trophic level in the y axes but you can change the position of the nodes.
Version 0.8.91.0000
- Added a new function plot_troph_level_visNet_multi()
- Change name of plot_troph_level_visNetwork() to plot_troph_level_visNet()
Version 0.8.70.0000
- Updated netData[26] “Simon Bay” deleting isolated vertex “Terrestrial POM”.
- Added a vignette with examples of the package.
Version 0.8.40.0000
Updated calc_QSS to effectively use the parameter selfDamping, before this changes it was used only for positive values of the diagonal of the adyacency matrix. Now the equivalent to the previous version is to set selfDamping=0.
Updated toGLVadjMat which does not take into account the names of the networks in the mgraph object, now it uses the position the negative/positive/trophic.
Version 0.8.30.0000
- add aggregate_multiplex_network() function to aggregate a multiplex network into a single layer network
Version 0.8.20.0000
- add plot_multiplex_modules() function to plot the modules of a multiplex network
Version 0.8.10.0000
- Improve plot_multi3D() and added harmonized_node_sets to add all the nodes to all layers, needed for plot_multi3D().
Version 0.8.00.0000
-
Added functions
- plot_multi3D() was adapted from package muxViz.
- convert_infomap_result_to_muxviz() to convert the output of
run_infomap_multi()to muxViz-Compatible Format.
Version 0.7.90.0000
- The function plot_troph_level_ggplot() was updated to use return the ggplot2 object.
Version 0.7.80.0000
- Added functions
- run_infomap_multi to run the python implementation of Infomap for node aligned multiplex networks
- Other aux functions like write_multilayer_network() convert_to_intra_format()
Version 0.7.40.0000
- Added functions
- run_infomap to run the python implementation of Infomap
- calc_centrality instead of calc_eigencentrality to calculate the centrality of a network using any defined measure
Version 0.7.30.0000
- Added functions calc_svd_entropy shuffle_network_deg shuffle_network_deg_svd calc_eigencentrality calc_svd_entropy_importance
Version 0.7.10.0000
- Added function generate_niche to generate a niche model with a given number of species and connectance
Version 0.7.00.0000
- Added function calc_interaction_intensity2() with estimation of interaction strength using O’Gorman 2010 method
Version 0.6.9.0000
- Updated function calc_interaction_intensity() with more error checking and warnings
Version 0.6.8.0000
- Updated function calc_QSS_extinctions_seq() and calc_QSS_extinction_dif_grp() to return the raw values of the QSS simulations, KA and AD test are not performed.
Version 0.6.7.0000
- Updated function calc_QSS_extinction_dif() to return the raw values of the QSS simulations and the difference between them, KA and AD test are not performed, the null model with mean IS is also deleted.
Version 0.6.66.0000
- Updated function classify_topological_roles() when all species are module specialists ‘modspe’
Version 0.6.65.0000
Updated README with function fromIgraphToMgraph
Fixed calc_QSS for mgraph objects
Version 0.6.60.0000
- Add function calc_QSS_extinction_dif_grp to calculate the difference in QSS with a group of species.
Version 0.6.50.0000
- Updated version of calc_interaction_intensity() with different sd for the normal distributions used for simulations around the mean of the coeficients estimated by Pawar 2012.
Version 0.6.31.0000
Updated documentation of calc_interaction_intensity function
Add @importFrom kSamples to calc_QSS_extinction_dif
Version 0.6.30.0000
Updated defaults of calc_QSS(), now the parameters defaults are
negative=-10, positive=1, selfDamping=-1equivalent to a ecological transfer efficieny of 10%. Previusly they werenegative=-10, positive=.1, selfDamping=-1.Updated documentation with better explication of calc_interaction_intensity function