Merge pull request #466 from MannLabs/config_simplifications

Config simplifications

alphadia/constants/default.yaml

@@ -61,8 +61,8 @@ library_prediction:
   # set path for custom peptdeep model. If set to null, the default model will be used
   peptdeep_model_path: null
 
-  # set peptdeep model type. Possible values are 'generic', 'phospho', 'digly'. If set to null, the generic model will be used
-  peptdeep_model_type: null
+  # set peptdeep model type. Possible values are 'generic', 'phospho', 'digly'.
+  peptdeep_model_type: 'generic'
 
 # define custom alphabase modifications not part of unimod or alphabase
 # also used for decoy channels
@@ -96,7 +96,7 @@ custom_modifications:
     composition: C(12)
 
 search:
-  channel_filter: '0'
+  channel_filter: "" # will be mapped to "0" -> load only the default unmultiplexed channel
   exclude_shared_ions: True
   compete_for_fragments: True
 

alphadia/libtransform.py

@@ -287,7 +287,7 @@ def __init__(
 
         peptdeep_model_type : str, optional
             Use other peptdeep models provided by the peptdeep model manager.
-            Default is None, which means the peptdeep default model ("generic") is being used.
+            Default is None, which means the default model provided by peptdeep (e.g. "generic" for version 1.4.0) is being used.
             Possible values are ['generic','phospho','digly']
 
         fragment_types : list[str], optional
@@ -326,12 +326,13 @@ def forward(self, input: SpecLibBase) -> SpecLibBase:
 
         model_mgr = ModelManager(device=device)
 
-        # will load other model than default generic
         if self.peptdeep_model_type:
             logging.info(f"Loading PeptDeep models of type {self.peptdeep_model_type}")
             model_mgr.load_installed_models(self.peptdeep_model_type)
+        else:
+            logging.info("Using PeptDeep default model.")
 
-        if self.peptdeep_model_path and self.peptdeep_model_path != "":
+        if self.peptdeep_model_path:
             if not os.path.exists(self.peptdeep_model_path):
                 raise ValueError(
                     f"PeptDeep model checkpoint folder {self.peptdeep_model_path} does not exist"

gui/workflows/PeptideCentric.v1.json

@@ -327,7 +327,7 @@
                     "id": "channel_filter",
                     "name": "Channel Filter",
                     "default": "",
-                    "description": "Comma separated list eg. 1,2,3. Only precursors with matching channels will be loaded. Leave empty to load all available channels.",
+                    "description": "Comma separated list eg. 1,2,3. Only precursors with matching channels will be loaded. Leave empty to load only the default unmultiplexed channel (0).",
                     "type": "string"
                 },
                 {