From 340635506790a93d8123b195c08581b0b9f7bcd0 Mon Sep 17 00:00:00 2001
From: anna-charlotte <chgerhaher@yahoo.com>
Date: Mon, 27 Jan 2025 09:40:21 +0100
Subject: [PATCH 1/2] add missing max iterations parameter

---
 alphadia/workflow/peptidecentric.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/alphadia/workflow/peptidecentric.py b/alphadia/workflow/peptidecentric.py
index 9c9eafd1..7e6e39ce 100644
--- a/alphadia/workflow/peptidecentric.py
+++ b/alphadia/workflow/peptidecentric.py
@@ -99,6 +99,7 @@
 
 def get_classifier_base(
     enable_two_step_classifier: bool = False,
+    two_step_classifier_max_iterations: int = 5,
     enable_nn_hyperparameter_tuning: bool = False,
     fdr_cutoff: float = 0.01,
 ):
@@ -136,6 +137,7 @@ def get_classifier_base(
             first_classifier=LogisticRegressionClassifier(),
             second_classifier=nn_classifier,
             second_fdr_cutoff=fdr_cutoff,
+            max_iterations=two_step_classifier_max_iterations,
         )
     else:
         return nn_classifier
@@ -179,6 +181,9 @@ def init_fdr_manager(self):
                 enable_two_step_classifier=self.config["fdr"][
                     "enable_two_step_classifier"
                 ],
+                two_step_classifier_max_iterations=self.config["fdr"][
+                    "two_step_classifier_max_iterations"
+                ],
                 enable_nn_hyperparameter_tuning=self.config["fdr"][
                     "enable_nn_hyperparameter_tuning"
                 ],

From 1999c019b723e1a0d930e9f5ffcd88abc9901cf0 Mon Sep 17 00:00:00 2001
From: anna-charlotte <chgerhaher@yahoo.com>
Date: Mon, 27 Jan 2025 09:46:51 +0100
Subject: [PATCH 2/2] fix docstring

---
 alphadia/workflow/peptidecentric.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/alphadia/workflow/peptidecentric.py b/alphadia/workflow/peptidecentric.py
index 7e6e39ce..71747ec3 100644
--- a/alphadia/workflow/peptidecentric.py
+++ b/alphadia/workflow/peptidecentric.py
@@ -111,6 +111,9 @@ def get_classifier_base(
         If True, uses logistic regression + neural network.
         If False (default), uses only neural network.
 
+    two_step_classifier_max_iterations : int
+        Maximum number of iterations withtin .fit_predict() of the two-step classifier.
+
     enable_nn_hyperparameter_tuning: bool, optional
         If True, uses hyperparameter tuning for the neural network.
         If False (default), uses default hyperparameters for the neural network.