Added protein ids for dlib format

spectrum_io/spectral_library/dlib.py

@@ -20,6 +20,7 @@
     "PeptideSeq",
     "RTInSeconds",
     "PrecursorMz",
+    "ProteinIds"
 ]
 
 
@@ -102,7 +103,8 @@ def _create_database(conn: sqlite3.Connection):
                 RTInSecondsStop REAL,
                 MedianChromatogramEncodedLength INTEGER,
                 MedianChromatogramArray BLOB,
-                SourceFile TEXT NOT NULL DEFAULT 'Oktoberfest'
+                SourceFile TEXT NOT NULL DEFAULT 'Oktoberfest',
+                ProteinIds TEXT NOT NULL
             )
         """
         sql_create_p2p = """
@@ -136,6 +138,8 @@ def _write(self, out: Union[IO, sqlite3.Connection], data: Dict[str, np.ndarray]
         p_mzs = (metadata["MASS"] + (p_charges * PARTICLE_MASSES["PROTON"])) / p_charges
         # ces = metadata["COLLISION_ENERGY"]
 
+        pr_ids = metadata["PROTEINS"]
+
         # prepare spectra
         irts = data["irt"][:, 0]  # should create a 1D view of the (n_peptides, 1) shaped array
         f_mzss = data["mz"]
@@ -144,7 +148,7 @@ def _write(self, out: Union[IO, sqlite3.Connection], data: Dict[str, np.ndarray]
 
         masked_values = self._calculate_masked_values(f_mzss, f_intss)
 
-        data_list = [*masked_values, p_charges, mass_mod_sequences, seqs, irts, p_mzs]
+        data_list = [*masked_values, p_charges, mass_mod_sequences, seqs, irts, p_mzs, pr_ids]
         entries = pd.DataFrame(dict(zip(DLIB_COL_NAMES, data_list)))
         p2p = pd.DataFrame({"PeptideSeq": seqs})