# HG changeset patch
# User recetox
# Date 1600785735 0
# Node ID 362a66a3889ce643d57dc4077eb856a79a0baf53
# Parent  b5b62d04625a9be49f8a073ab556bf1fada9053e
"planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/biotransformer commit 833817386e90cca9ac4737e6857fcaf672f2a011"

diff -r b5b62d04625a -r 362a66a3889c biotransformer.xml
--- a/biotransformer.xml	Thu Aug 27 12:55:38 2020 +0000
+++ b/biotransformer.xml	Tue Sep 22 14:42:15 2020 +0000
@@ -1,10 +1,13 @@
-<tool id="biotransformer" name="BioTransformer" version="1.1.0">
-    <requirements>
-      <container type="docker">registry.gitlab.ics.muni.cz:443/recetox/mass-spectrometry/biotransformer:1.1.0</container>
-    </requirements>
-  <command><![CDATA[ cd /biotransformer && python3 wrapper_biotransformer.py
+<tool id="biotransformer" name="BioTransformer" version="1.1.5+galaxy0">
+  <requirements>
+     <requirement type="package" version="1.1.5">biotransformer</requirement>
+     <requirement type="package" version="3.1.1">openbabel</requirement>
+     <requirement type="package" version="1.1.1">pandas</requirement>
+     <requirement type="package" version="3.7">python</requirement>
+  </requirements>
+  <command><![CDATA[ python3 '${__tool_directory__}/wrapper_biotransformer.py'
  -k $k
- -b $b 
+ -b $b
  -s $steps
  -t $tolerance
  -a
@@ -20,7 +23,7 @@
    #if $input.type_selector == "csv"
 	-ocsv $output_file
         -ocsvDup $output_file2
-        -ocsvDup2 $output_file3	
+        -ocsvDup2 $output_file3
    #else if $input.type_selector == "smile"
 	-ocsv $output_file
    #end if
@@ -127,3 +130,4 @@
     <citation type="doi">https://doi.org/10.1186/s13321-018-0324-5</citation>
   </citations>
 </tool>
+
diff -r b5b62d04625a -r 362a66a3889c wrapper_biotransformer.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/wrapper_biotransformer.py	Tue Sep 22 14:42:15 2020 +0000
@@ -0,0 +1,88 @@
+import subprocess
+import sys
+import tempfile
+
+import pandas
+from openbabel import pybel
+
+
+# function for translating inchi to smiles
+def InchiToSmiles(df):
+    sm = []
+    for item in df['InChI']:
+        tmp = pybel.readstring("inchi", item)
+        sm.append(tmp.write("smi"))
+    return(sm)
+
+
+executable = ["biotransformer"]
+# executable_r = ["Rscript", "inchi_to_smiles.r"]
+
+argv = sys.argv[1:]
+if "-icsv" in argv:
+    icsv = argv.pop(argv.index("-icsv") + 1)
+    argv.remove("-icsv")
+
+    if "-ocsv" not in argv:
+        sys.stderr.write("excpected -ocsv parameter\n")
+        sys.exit(1)
+    ocsv = argv.pop(argv.index("-ocsv") + 1)
+    argv.remove("-ocsv")
+    ocsv_dup = argv.pop(argv.index("-ocsvDup") + 1)
+    argv.remove("-ocsvDup")
+    ocsv_dup2 = argv.pop(argv.index("-ocsvDup2") + 1)
+    argv.remove("-ocsvDup2")
+
+    in_df = pandas.read_csv(icsv, header=None)
+    out_df1 = pandas.DataFrame()  # all results
+    out_df2 = pandas.DataFrame()  # filtered results based on 6 columns
+    out_df3 = pandas.DataFrame()  # filtered results based on 3 columns
+
+    tmp2 = pandas.DataFrame()
+    tmp3 = pandas.DataFrame()
+
+    smList1 = []  # list with smiles string
+    smList2 = []
+    smList3 = []
+    for _, (smiles,) in in_df.iterrows():
+        with tempfile.NamedTemporaryFile() as out:
+            subprocess.run(executable + argv + ["-ismi", smiles] + ["-ocsv", out.name])
+            tmp2 = pandas.read_csv(out.name)
+            tmp3 = pandas.read_csv(out.name)
+            tmp2.drop_duplicates(inplace=True, subset=["InChI", "InChIKey", "Synonyms", "Molecular formula", "Major Isotope Mass", "ALogP"])
+            tmp3.drop_duplicates(inplace=True, subset=["Molecular formula", "Major Isotope Mass", "ALogP"])
+            smList2.append([smiles] * tmp2.shape[0])
+            smList3.append([smiles] * tmp3.shape[0])
+            out_df1 = pandas.concat([out_df1, pandas.read_csv(out.name)])
+            out_df2 = pandas.concat([out_df2, tmp2])
+            out_df3 = pandas.concat([out_df3, tmp3])
+            smList1.append([smiles] * pandas.read_csv(out.name).shape[0])
+    smList1 = sum(smList1, [])  # merge sublists into one list
+    smList2 = sum(smList2, [])
+    smList3 = sum(smList3, [])
+
+    out_df1.insert(0, "SMILES query", smList1)
+    out_df1.drop_duplicates(inplace=True)
+    out_df1.insert(1, "SMILES target", InchiToSmiles(out_df1))
+    out_df1.to_csv(ocsv)
+
+    out_df2.insert(0, "SMILES query", smList2)
+    out_df3.insert(0, "SMILES query", smList3)
+    out_df2.drop_duplicates(inplace=True)
+    out_df3.drop_duplicates(inplace=True)
+    out_df2.insert(1, "SMILES target", InchiToSmiles(out_df2))
+    out_df3.insert(1, "SMILES target", InchiToSmiles(out_df3))
+    # out_df.drop_duplicates(inplace=True, subset=["InChI", "InChIKey", "Synonyms", "Molecular formula", "Major Isotope Mass", "ALogP"])
+    out_df2.to_csv(ocsv_dup)
+    out_df3.to_csv(ocsv_dup2)
+else:
+    # code = subprocess.run(executable + argv).returncode
+    # sys.exit(code)
+    subprocess.run(executable + argv)
+    smile = argv.pop(argv.index("-ismi") + 1)
+    tmp = pandas.DataFrame()
+    out = argv.pop(argv.index("-ocsv") + 1)
+    tmp = pandas.read_csv(out)   # reads created output file
+    tmp.insert(0, "SMILES query", smile)  # add SMILES string for query
+    tmp.insert(1, "SMILES target", InchiToSmiles(tmp))  # add SMILES string for target
+    tmp.to_csv(out)