# HG changeset patch
# User jay
# Date 1612061038 0
# Node ID 8697dc4a7f45d083ae37c0c4b9b425c29609a6ac
# Parent  d5a209484c170e7b7a2edf7645c6a33e2338e55b
"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit e8c8198105af7eab636fb2405e5ff335539ca14b"

diff -r d5a209484c17 -r 8697dc4a7f45 PDAUG_AA_Property_Based_Peptide_Generation/PDAUG_AA_Property_Based_Peptide_Generation.py
--- a/PDAUG_AA_Property_Based_Peptide_Generation/PDAUG_AA_Property_Based_Peptide_Generation.py	Thu Jan 28 04:26:52 2021 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/PDAUG_AA_Property_Based_Peptide_Generation.py	Sun Jan 31 02:43:58 2021 +0000
@@ -129,6 +129,21 @@
             OutFasta.write(">sequence_"+str(i)+'\n')
             OutFasta.write(O+'\n')
 
+
+def MixedLibrary_seq(seqnum, centrosymmetric, centroasymmetric, helix, kinked, oblique, rand, randAMP, randAMPnoCM, OutFasta):
+
+    lib = MixedLibrary(int(seqnum), int(centrosymmetric), int(centroasymmetric), int(helix), int(kinked), int(oblique), int(rand), int(randAMP), int(randAMPnoCM))
+    lib.generate_sequences()
+    OutFasta = open(OutFasta, 'w')
+
+    OutPep = lib.sequences
+        
+    for i,O in enumerate(OutPep):
+        OutFasta.write(">sequence_"+str(i)+'\n')
+        OutFasta.write(O+'\n')
+
+
+
 if __name__=='__main__':
 
     parser = argparse.ArgumentParser(description='Deployment tool')
@@ -192,6 +207,19 @@
     Arc.add_argument("-y","--hyd_gra", default='False', help="Method to mutate the generated sequences to have a hydrophobic gradient by substituting the last third of the sequence amino acids to hydrophobic.")
     Arc.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")
 
+    Mix = subparsers.add_parser('MixedLibrary')
+    Mix.add_argument("-s","--seq_num", required=True, default=None, help="number of sequences to be generated")
+    Mix.add_argument("-c","--centrosymmetric", required=False, default=1, help="ratio of symmetric centrosymmetric sequences in the library")
+    Mix.add_argument("-ca","--centroasymmetric", required=False, default=1, help="ratio of asymmetric centrosymmetric sequences in the library")
+    Mix.add_argument("-hl","--helix", required=False, default=1, help="ratio of asymmetric centrosymmetric sequences in the library")
+    Mix.add_argument("-k","--kinked", required=False, default=1,   help="ratio of asymmetric centrosymmetric sequences in the library")
+    Mix.add_argument("-o", "--oblique", required=False, default=1,  help=" ratio of oblique oriented amphipathic helical sequences in the library")
+    Mix.add_argument("-r", "--rand", required=False, default=1,  help="ratio of random sequneces in the library")
+    Mix.add_argument("-ra", "--randAMP", required=False, default=1,  help="ratio of random sequences with APD2 amino acid distribution in the library")
+    Mix.add_argument("-rp", "--randAMPnoCM", required=False, default=1, help="ratio of random sequences with APD2 amino acid distribution without Cys and Met in the library")
+    Mix.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")
+
+
     args = parser.parse_args()
 
     if sys.argv[1] == 'Random':
@@ -212,5 +240,9 @@
         AMPngrams_seq(args.seq_num, args.n_min, args.n_max, args.OutFasta)
     elif sys.argv[1] == 'AmphipathicArc':
         AmphipathicArc_seq(int(args.seq_num), int(args.lenmin_s), int(args.lenmax_s), int(args.arcsize), args.hyd_gra, args.OutFasta)
+    elif sys.argv[1] == 'MixedLibrary':
+        MixedLibrary_seq(args.seq_num, args.centrosymmetric, args.centroasymmetric, args.helix, args.kinked, args.oblique, args.rand, args.randAMP, args.randAMPnoCM, args.OutFasta)
     else:
-        print("You entered Wrong Values: ")
\ No newline at end of file
+        print("You entered Wrong Values: ")
+
+
diff -r d5a209484c17 -r 8697dc4a7f45 PDAUG_ML_Models/PDAUG_ML_Models.xml
--- a/PDAUG_ML_Models/PDAUG_ML_Models.xml	Thu Jan 28 04:26:52 2021 +0000
+++ b/PDAUG_ML_Models/PDAUG_ML_Models.xml	Sun Jan 31 02:43:58 2021 +0000
@@ -585,10 +585,10 @@
 
       <conditional name='TestMethods'>
         <param name="SelTestMethods" type="select" label="Choose the Test method" argument="--TestMethod" help="Data testing method">
-          <option value="Internal">Internal</option>
-          <option value="TestSplit">TestSplit</option>
-          <option value="External">External</option>
-          <option value="Predict">Predict</option>
+          <option value="Internal">Internal Test</option>
+          <option value="TestSplit">Train Test Split</option>
+          <option value="External">External Test Data</option>
+          <option value="Predict">Predict Unknown</option>
         </param>
         <when value="Internal">
           <param name="nFolds" type="integer" label="Cross validation" value="5" min="5" max="10" argument="--nfold" help="Cross validation"/>
@@ -720,7 +720,7 @@
     * **Training File**  Tabulalr files with labeled peptide descriptor data.  
     * **Select Machine Learning algorithms** Select algorithm. 
     * **Select Advanced Parameters** Select the advance parameter details of each of the parameters that can be found on sklearn website. 
-    * **Select the test method** (predict or internal test)
+    * **Select the test method** (Internal Test, Train Test Split, External Test Data, and Predict Unknown)
     * **Cross Validation** Up to 10 fold cross-validation. 
     * **Method to Scale the data** MinMaxScaler and  standard scaler.