--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cfmid.py	Wed Nov 15 16:28:04 2023 +0000
@@ -0,0 +1,149 @@
+import argparse
+import csv
+import os
+import shutil
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--input")
+parser.add_argument("--db_local")
+parser.add_argument("--num_highest")
+parser.add_argument("--ppm_db")
+parser.add_argument("--ppm_mass_tol")
+parser.add_argument("--abs_mass_tol")
+parser.add_argument("--polarity")
+parser.add_argument("--score_type")
+parser.add_argument("--results")
+parser.add_argument("--tool_directory")
+
+args = parser.parse_args()
+print(args)
+
+# Example
+# python cfmid.py --abs_mass_tol='0.01' --db_local='test-data/demo_db.tsv' --input='test-data/input.msp' --num_highest='10' --polarity='pos' --ppm_db='10.0' --ppm_mass_tol='10.0' --results='results.txt' --score_type='Jaccard' --tool_directory='/home/rw/Documents/cfm-galaxy/tools/cfm'
+
+id2info = {}
+mz2id = []
+# store DB in dicts
+with open(args.db_local) as csvfile:
+    csvreader = csv.DictReader(csvfile, delimiter="\t")
+    for row in csvreader:
+        id2info[row["Identifier"]] = row
+        mz2id.append((float(row["MonoisotopicMass"]), row["Identifier"]))
+
+name_tmp = "tmp"
+if os.path.isdir(name_tmp):
+    shutil.rmtree(name_tmp)
+
+os.makedirs(name_tmp)
+with open(args.input, "r") as infile:
+    numlines = 0
+    for line in infile:
+        line = line.strip()
+        if numlines == 0:
+            print(line)
+            if "NAME" in line:
+                featid = line.split("NAME: ")[1]
+            if "PRECURSORMZ" in line:
+                mz = float(line.split("PRECURSORMZ: ")[1])
+                if args.polarity == "pos":
+                    mz2 = mz - 1.007276
+                else:
+                    mz2 = mz + 1.007276
+            if "Num Peaks" in line:
+                numlines = int(line.split("Num Peaks: ")[1])
+                linesread = 0
+                peaklist = []
+        else:
+            if linesread == numlines:
+                numlines = 0
+                cand_id_list = []
+                mz_ranges = (float(args.ppm_db) * mz2) / 1e6
+                mz_ranges = (mz2 - mz_ranges, mz2 + mz_ranges)
+                # check hits
+                for t in mz2id:
+                    if (t[0] > mz_ranges[0]) and (t[0] < mz_ranges[1]):
+                        cand_id_list.append(t[1])
+                # run only if we got candidates
+                if len(cand_id_list) > 0:
+                    # write spec file
+                    with open("./tmpspec.txt", "w") as outfile:
+                        for e in ["low", "mid", "high"]:
+                            outfile.write(e + "\n")
+                            for p in peaklist:
+                                outfile.write(p[0] + "\t" + p[1] + "\n")
+                    # write candidates file
+                    with open("./tmpcand.txt", "w") as outfile:
+                        for c in cand_id_list:
+                            outfile.write(
+                                "{0} {1}\n".format(c, id2info[c]["InChI"])
+                            )  # TODO: Use InChI or SMILES
+
+                    # create command line call
+                    outi = os.path.join(name_tmp, "cfm_" + featid + ".txt")
+                    cmd_command = "cfm-id tmpspec.txt {0} tmpcand.txt ".format(featid)
+                    cmd_command += "{0} {1} {2} {3} ".format(
+                        args.num_highest,
+                        args.ppm_db,
+                        args.ppm_mass_tol,
+                        args.abs_mass_tol,
+                    )
+                    if args.polarity == "pos":
+                        cmd_command += (
+                            os.path.join(
+                                args.tool_directory,
+                                "data",
+                                "positive_metab_se_cfm",
+                                "param_output0.log",
+                            )
+                            + " "
+                        )
+                        cmd_command += (
+                            os.path.join(
+                                args.tool_directory,
+                                "data",
+                                "positive_metab_se_cfm",
+                                "param_config.txt",
+                            )
+                            + " "
+                        )
+                    else:
+                        cmd_command += (
+                            os.path.join(
+                                args.tool_directory,
+                                "data",
+                                "negative_metab_se_cfm/param_output0.log",
+                            )
+                            + " "
+                        )
+                        cmd_command += (
+                            os.path.join(
+                                args.tool_directory,
+                                "data",
+                                "negative_metab_se_cfm/param_config.txt",
+                            )
+                            + " "
+                        )
+                    cmd_command += "{0} 1 {1}".format(args.score_type, outi)
+                    # run
+                    print(cmd_command)
+                    os.system(cmd_command)
+            else:
+                line = tuple(line.split("\t"))
+                linesread += 1
+                peaklist.append(line)
+
+
+# merge outputs
+outfiles = os.listdir(name_tmp)
+outfiles.sort(key=lambda x: os.path.getmtime(os.path.join(name_tmp, x)))
+with open(args.results, "w") as outfile:
+    outfile.write("UID\tRank\tScore\tIdentifier\tInChI\n")
+    for fname in outfiles:
+        fileid = os.path.basename(fname)
+        fileid = fileid.split("_")[1]
+        fileid = fileid.split(".txt")[0]
+        with open(os.path.join(name_tmp, fname)) as infile:
+            for line in infile:
+                line = line.replace(" ", "\t")
+                outfile.write(fileid + "\t" + line)