add widelocal variant

downloads-generation/models_class1_experiments1/GENERATE.sh

@@ -34,10 +34,10 @@ time mhcflurry-class1-train-allele-specific-models \
     --hyperparameters hyperparameters-standard.yaml \
     --out-models-dir models-standard-quantitative \
     --percent-rank-calibration-num-peptides-per-length 0 \
-    --alleles $ALLELES &
+    --allele $ALLELES 2>&1 | tee -a LOG.standard.txt &
 
 # Model variations on qualitative + quantitative
-for mod in 0local_noL1 0local 2local dense16 dense64 noL1 onehot embedding
+for mod in 0local_noL1 0local 2local widelocal dense16 dense64 noL1 onehot embedding
 do
     cp $SCRIPT_DIR/hyperparameters-${mod}.yaml .
     mkdir models-${mod}
@@ -46,12 +46,15 @@ do
         --hyperparameters hyperparameters-${mod}.yaml \
         --out-models-dir models-${mod} \
         --percent-rank-calibration-num-peptides-per-length 0 \
-        --alleles $ALLELES &
+        --allele $ALLELES 2>&1 | tee -a LOG.${mod}.txt &
 done
 wait
 
 cp $SCRIPT_ABSOLUTE_PATH .
-bzip2 LOG.txt
+for i in $(ls *.txt)
+do
+    bzip2 $i
+done
 tar -cjf "../${DOWNLOAD_NAME}.tar.bz2" *
 
 echo "Created archive: $SCRATCH_DIR/$DOWNLOAD_NAME.tar.bz2"

downloads-generation/models_class1_experiments1/hyperparameters-widelocal.yaml

+[{
+##########################################
+# ENSEMBLE SIZE
+##########################################
+"n_models": 8,
+
+##########################################
+# OPTIMIZATION
+##########################################
+"max_epochs": 500,
+"patience": 10,
+"early_stopping": true,
+"validation_split": 0.2,
+
+##########################################
+# RANDOM NEGATIVE PEPTIDES
+##########################################
+"random_negative_rate": 0.0,
+"random_negative_constant": 25,
+"random_negative_affinity_min": 20000.0,
+"random_negative_affinity_max": 50000.0,
+
+##########################################
+# PEPTIDE REPRESENTATION
+##########################################
+# One of "one-hot", "embedding", or "BLOSUM62".
+"peptide_amino_acid_encoding": "BLOSUM62",
+"use_embedding": false,  # maintained for backward compatability
+"embedding_output_dim": 8,  # only used if using embedding
+"kmer_size": 15,
+
+##########################################
+# NEURAL NETWORK ARCHITECTURE
+##########################################
+"locally_connected_layers": [
+    {
+        "filters": 8,
+        "activation": "tanh",
+        "kernel_size": 5
+    }
+],
+"activation": "relu",
+"output_activation": "sigmoid",
+"layer_sizes": [
+    32
+],
+"dense_layer_l1_regularization": 0.001,
+"batch_normalization": false,
+"dropout_probability": 0.0,
+}]