Updates
The complete commit history for phyddle is located here: https://github.com/mlandis/phyddle/commits/main
phyddle v0.0.7 – (in progress)
Format now splits training from test datasets.
Estimate now applies trained model against test dataset.
Steps now initialize using settings look-up table.
Add PCA contour plot.
Simplify filenames within projects for many steps.
Timestamp step start/end/duration.
phyddle v0.0.6 – 23.08.09
Refreshed documentation, plus added setting tables and glossary.
Centralize management of settings.
Settings now automatically apply default config, then user config, then command line arguments.
Format only enodes for a single tree width category now.
Format now downsamples and stores raw num. taxa for each data point.
Allow for “all-but-X” CPUs for multiprocessing.
Simulate wth –sim_more option to add new replicates to training examples.
Format encodes all detected datasets by default.
Support to allow scripts to simulate batches (>1) of replicates.
Major overhaul of help docs, but not done.
phyddle v0.0.5 – 23.07.30
Pipeline steps renamed to: Simulate, Format, Train, Estimate, Plot
Simulators now in scripts/sim/MASTER, scripts/sim/R, scripts/sim/Rev
Streamlined handling of phyddle settings, internally
Model configuration code moved outside phyddle
MASTER simulator now outside phyddle, in scripts/sim/MASTER
Complete source code reorg/rename
Pipeline script now prints pipeline steps
Support for granular management of flow of projects across pipeline steps
Support asymmetric CPI calibration
Better handling of FileNotFoundError related to Estimate step
Much faster Formatting step (>100x speedup)
Pipeline steps now generate logs in
workspace/log/<project_name>
to track phyddle is used during a project analysisTested against Apple M1. Not an easy install, because unsupported by Tensorflow. Thanks Albert and Sean!
phyddle v0.0.4 – 23.07.09
Simulating now supports command-line scripts
Better backend support for alternative phylostate tensor encodings
Simplified pipeline scripts and interface
Docs improved to reflect current code design
Tests now cover Simulating and Formatting
phyddle v0.0.3 – 23.07.02
Sphinx configuration for documentation
TestPyPI configuration for package deployment
GitHub Actions configuration for unit testing
phyddle v0.0.2 – 23.06.25
(first internal working version)
trained network generates parameter estimates and coverage-calibrated prediction intervals (CPIs) for input datasets
provides several state-dependent birth-death model types and variants (more to come)
parallelized simulating, formatting, and learning
encoding of phylogenetic-state tensor from serial and extant-only input with multiple states (CBLV+S and CDV+S extensions)
encoding of auxiliary data tensor from automatically computed summary statistics and “known” parameter (e.g. sampling rate)
HDF5 with gzip compression for tensor data
shuffles and splits input tensors into training, test, validation, and calibration datasets for supervised learning
builds network with convolution, pooling, and dense layers that match input tensors
trains network and saves history
automatic figure generation with Matplotlib
phyddle v0.0.1 – 23.03.16
(initial development version)
Planned features
better back-end documentation for developers/hackers/etc.
expanded library of model types/variants for discrete and continuous state types
expanded support for standard simulators and a generic script-based simulator interface
better parallelization for hdf5-chunking of very large datasets
better subsampling support
expansion of standard prediction tasks
expansion of unit/integration testing