New experimental setup

[lutteropp]

For all experiments, we will have (unless mentioned otherwise):

• number of MSA sites = 1000 * (number of displayed trees)
• perfect sampling: sites are sampled proportionally to the displayed tree probability
• each displayed tree gets its own partition in the MSA
• all reticulations with probability 0.5
• we will not simulate any "weird" networks (this is, networks with unrecoverable reticulations)
• two setups: starting from raxml-ng best tree vs. starting from 5 parsimony trees + 5 random trees
• two likelihood models: LikelihoodModel.BEST and LikelihoodModel.AVERAGE

I am scripting and then submitting the following experiments:

• 10 taxa, 1 reticulation with probability in {0.1, 0.2, 0.3, 0.4, 0.5} (fixed topology per dataset, just changing the reticulation prob).
• 10 taxa, 1 reticulation, brlen_scaler in {1,2,4,8} (fixed topology per dataset, just scaling the branches).
• 10 taxa, number of reticulations in {1,2,3}
• 10 taxa, 1 reticulation, unpartitioned dataset, LikelihoodModel.AVERAGE

I chose 10 taxa, because it is not super few taxa, but also not extremely large.