Releases: erthward/geonomics
1.1.1
1.1.0
After adding a new parameter ('jitter_breakpoints'), a bunch more public methods on the Model class, another validation test (recombination), and making some other minor changes (including debugging the Sphinx API generation, which is still in progress), updating to version 1.1.0.
Officially changing to version 1.0.0
Submitted methods paper for publication, added 'submited' citation to docs and README, and officially changed version number to 1.0.0.
Pushing fix of spp._get_genotypes(), and minor tweaks
Pushing fix of spp._get_genotypes(), as well as minor tweaks to language ('polygenic selection coefficient' --> 'phenotypic selection coefficient') and IBD_IBE demo plotted output.
Added Anusha's GEA/CCA code
Added two private methods to Species, one public wrapper method to Model.
Added PID and RAM-usage functionality to Model
Added PID (as an attribute) and RAM-usage (as a method) to the Model class
Class docstrings
Added docstrings to all public-facing classes.
Validations-test code working again (and other minor fixes)
Fixed the validations-test code to run using the new (tskit-based) data structures of Geonomics. Also fixed bug Anusha found in mod.plot_genotype(), as well as the typo she found in the docs, and some other minor tweaks I've made along the way.
Fix knock-on issues arising from mating-radius bug/mate choice bug that I recently changed.
Got rid of sparse pairwise distance matrix that I was using to be lazy and that was a dumb choice that overloaded memory for large pops.
Also trying to figure out how to get the package to stop including the old Yosemite rasters.
Fixed bug in mating functionality
Had not realized that I had left the code such that the nearest neighbor was always being chosen as a mate. Now implemented two new parameters, which together allow user to: 1.) either always choose nearest neighbor or to randomly choose from among individuals within the mating radius; 2.) if randomly choosing within the mating radius, probabilities of choosing each individual can be either uniform or inverse-distance weighted.