release 1.5.0

.github/workflows/black.yml

@@ -0,0 +1,35 @@
+name: Black linter
+
+on:
+  pull_request:
+    paths:
+      - '**.py'
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          ref: ${{ github.head_ref }}
+          token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Install Black
+        run: pip install 'black[jupyter]==23.11.0'
+
+      - name: Run Black
+        id: black_check
+        run: |
+          black --check --verbose . || echo "CHANGES_NEEDED=true" >> $GITHUB_ENV
+        continue-on-error: true
+
+      - name: Apply Black reformatting
+        if: env.CHANGES_NEEDED=='true'
+        run: |
+          black .
+          git config --global user.name 'github-actions'
+          git config --global user.email '[email protected]'
+          git add -A
+          git diff --quiet && git diff --staged --quiet || (git commit -m "Apply Black formatting" && git push)
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

alphadia/__init__.py

@@ -2,7 +2,7 @@
 
 
 __project__ = "alphadia"
-__version__ = "1.4.0"
+__version__ = "1.5.0"
 __license__ = "Apache"
 __description__ = "An open-source Python package of the AlphaPept ecosystem"
 __author__ = "Mann Labs"

alphadia/cli.py

@@ -11,6 +11,23 @@
 from alphadia.workflow import reporting
 from alphadia import utils
 
+from alphabase.constants import modification
+
+modification.add_new_modifications(
+    {
+        "Dimethyl:d12@Protein N-term": {"composition": "H(-2)2H(8)13C(2)"},
+        "Dimethyl:d12@Any N-term": {
+            "composition": "H(-2)2H(8)13C(2)",
+        },
+        "Dimethyl:d12@R": {
+            "composition": "H(-2)2H(8)13C(2)",
+        },
+        "Dimethyl:d12@K": {
+            "composition": "H(-2)2H(8)13C(2)",
+        },
+    }
+)
+
 # alpha family imports
 
 # third party imports
@@ -101,6 +118,7 @@ def gui():
     "--config-update",
     help="Dict which will be used to update the default config.",
     type=str,
+    default={},
 )
 @click.option(
     "--neptune-token",
@@ -124,7 +142,7 @@ def extract(**kwargs):
     kwargs["neptune_tag"] = list(kwargs["neptune_tag"])
 
     # load config file if specified
-    config_update = None
+    config_update = {}
     if kwargs["config"] is not None:
         with open(kwargs["config"], "r") as f:
             config_update = yaml.safe_load(f)

alphadia/fdr.py

@@ -27,6 +27,7 @@ def perform_fdr(
     competetive: bool = False,
     group_channels: bool = True,
     figure_path: Optional[str] = None,
+    neptune_run=None,
 ):
     """Performs FDR calculation on a dataframe of PSMs
 
@@ -123,7 +124,7 @@ def perform_fdr(
         classifier,
         psm_df["qval"],
         figure_path=figure_path,
-        # neptune_run=neptune_run
+        neptune_run=neptune_run,
     )
 
     return psm_df
@@ -339,6 +340,7 @@ def plot_fdr(
     ax[0].set_ylabel("true positive rate")
     ax[0].legend()
 
+    ax[1].set_xlim(0, 1)
     ax[1].hist(
         np.concatenate([y_test_proba[y_test == 0], y_train_proba[y_train == 0]]),
         bins=50,
@@ -376,7 +378,7 @@ def plot_fdr(
     if figure_path is not None:
         fig.savefig(os.path.join(figure_path, "fdr.pdf"))
 
-    # if neptune_run is not None:
-    #    neptune_run['eval/fdr'].log(fig)
+    if neptune_run is not None:
+        neptune_run["eval/fdr"].log(fig)
 
     plt.close()