"Evolutionary Virtual Education" - 'evolved' - provides multiple tools to help educators (especially at the graduate level or in advanced undergraduate level courses) apply inquiry-based learning in general evolution classes. In particular, the tools provided include functions that simulate evolutionary processes (e.g., genetic drift, natural selection within a single locus) or concepts (e.g. Hardy-Weinberg equilibrium, phylogenetic distribution of traits). More than only simulating, the package also provides tools for students to analyze (e.g., measuring, testing, visualizing) datasets with characteristics that are common to many fields related to evolutionary biology. Importantly, the package is heavily oriented towards providing tools for inquiry-based learning - where students follow scientific practices to actively construct knowledge. For additional details, see package's vignettes.

Evolutionary process simulation using geometric morphometric data. Manipulation of landmark data files (TPS), shape plotting and distances plotting functions.

The EvoPER, Evolutionary Parameter Estimation for Individual-based Models is an extensible 
      package providing optimization driven parameter estimation methods using metaheuristics  and 
      evolutionary computation techniques (Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization 
      for continuous domains, Tabu Search, Evolutionary Strategies, ...)  which could be more efficient and require, 
      in some cases, fewer model evaluations than alternatives relying on experimental design.  Currently there 
      are built in support for models developed with 'Repast Simphony'  Agent-Based framework (<https://repast.github.io/>)  
      and with NetLogo (<https://www.netlogo.org/>) which are the most used frameworks for Agent-based modeling.

Performs automated morphological character partitioning for 
             phylogenetic analyses and analyze macroevolutionary parameter 
             outputs from clock (time-calibrated) Bayesian inference analyses, following 
             concepts introduced by Simões and Pierce (2021) <doi:10.1038/s41559-021-01532-x>.