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Created with Raphaël 2.2.012Feb7Dec123Nov2019181613121110527Oct14969Sep824Jul20131130Jun2726242316151110985328May26221811643127Apr30Mar2322212019161312118613Feb1075427Jan26252423222120191817161514128765432131Dec26252322212013121110976543230Nov292322211918141130Oct2927261816151311added functionality to model creation that allows for learned embeddings (or combo of learned and hardcoded). Also, adjusted amino_acid.py to make X's index = 0 so that it can be used as a mask.created hyperparameter files and set up training for models with learned embeddingsadded hyperparam options for learned embeddingscreated benchmarking dataset templateadded manuscript latex filesdeleted original mhcflurry and old scriptDeleted mhcflurry/__init__.py, mhcflurry/allele_encoding.py, mhcflurry/amino_acid.py, mhcflurry/calibrate_percentile_ranks_command.py, mhcflurry/class1_affinity_predictor.py, mhcflurry/class1_neural_network.py, mhcflurry/class1_presentation_predictor.py, mhcflurry/class1_processing_neural_network.py, mhcflurry/class1_processing_predictor.py, mhcflurry/cluster_parallelism.py, mhcflurry/common.py, mhcflurry/custom_loss.py, mhcflurry/data_dependent_weights_initialization.py, mhcflurry/downloads.py, mhcflurry/downloads.yml, mhcflurry/downloads_command.py, mhcflurry/encodable_sequences.py, mhcflurry/ensemble_centrality.py, mhcflurry/fasta.py, mhcflurry/flanking_encoding.py, mhcflurry/hyperparameters.py, mhcflurry/local_parallelism.py, mhcflurry/percent_rank_transform.py, mhcflurry/predict_command.py, mhcflurry/predict_scan_command.py, mhcflurry/random_negative_peptides.py, mhcflurry/regression_target.py, mhcflurry/scoring.py, mhcflurry/select_allele_specific_models_command.py, mhcflurry/select_pan_allele_models_command.py, mhcflurry/select_processing_models_command.py, mhcflurry/testing_utils.py, mhcflurry/train_allele_specific_models_command.py, mhcflurry/train_pan_allele_models_command.py, mhcflurry/train_presentation_models_command.py, mhcflurry/train_processing_models_command.py, mhcflurry/version.py, train_APmodels.sh filesremoved original mhcflurry2.0 filesadding training data from ap models with crossentropy lossaltered training init to work with SLURM and corrected typo (BLOSUM --> BLOSUM62) in hyperparameters, specifically encoding optionssplit hyperparams up so that they can be run as separate jobs in OSCfinished debuggingfixed bug in flanking_encodingqsub and CLI training scriptsfixed train AP models scriptaltered training shell script fror qsubfixed nonsensical import of subpackage in middle of script to point to mhc_rank instead of mhcflurryMerge branch 'master' of https://code.osu.edu/skillman-lawrence.1/mhc_rankminor edittrying to figure out why cleave_radius is an unexpected keyword arg in vector_encode even though vector encode has an explicit argument cleave_radisu...debuggingMerge branch 'master' of https://code.osu.edu/skillman-lawrence.1/mhc_rankeditsworking on training scriptsfixed bugsadded training data used to train mhcflurry AP modelsFixed big in argparse for make_architectures.py script. Created file with architecture options (1296) and saved as hyperparameters.json to ap_models dirdebugged architecture / training & created script to make models fitting all combinations of varied hyperparameters for tuningAdjusted hyperparams and processing architectureRemoved print functions that had been used for debuggingdebugged encoding processadjusted when cleave radius is supplied to produce flank encoding.fixed import error for other scripts in mhc_rank dirfixed bug in pssm retreival for flanking encodingadded feature to flank_encoding.py, enabling pssm scores to be added as first position in residue encoding vectorsextract cleavage site, converted pssm from pd.Series and pd.DataFrames to np.ndarrays, enabled pssm calculation.Added trim feature to seq_score of PSSM.py; Adjusted flanking_encoding.py to account for added encoding methods and for cleavage site extraction; Fixed bug in amino_acid.py so that correct encoding could be achievedCommented code for encodable_sequence.py processing alignment methodAdded alignment method to EncodableSequences class in encodable_sequences.py. Next commit will inlcude commentingAdded PSSM retrieval for peptides. Included padding functionality for peptides shorter than max length using PSSM of X at middle residues of max length k-mer. Also, fully commented code and added docstring for class