function mbp.normalize() now only normalizes available columns

src/conda_helpers/mbp.py

@@ -1,3 +1,5 @@
+import contextlib
+
 import pandas as pd
 from sensospot_tools import (
     normalize as normalize_xdr_data,
@@ -7,10 +9,15 @@ from sensospot_tools import (
     split,
 )
 
+# column names
+
 EXPOSURE_ID = "Exposure.Id"
 EXPOSURE_CHANNEL = "Exposure.Channel"
 EXPOSURE_TIME = "Exposure.Time"
 EXPOSURE_TIME_NORMALIZED = "Exposure.Time.Normalized"
+NET_SIGNAL = "NetSignal"
+SPOT_SATURATION = "Spot.Saturation"
+TEST_OVERFLOW = "Test.Spot.Overflow"
 
 EXPOSURE_COLUMNS = [
     EXPOSURE_ID,
@@ -19,11 +26,6 @@ EXPOSURE_COLUMNS = [
     EXPOSURE_TIME_NORMALIZED,
 ]
 
-SATURATION_LIMIT = 2
-SPOT_SATURATION = "Spot.Saturation"
-
-TEST_OVERFLOW = "Test.Spot.Overflow"
-
 SPOT_ID_COLUMNS = ["Analysis.Name", "Well.Name", "Pos.Id"]
 
 TIME_DEPENDENT_COLUMNS = [
@@ -37,6 +39,8 @@ TIME_DEPENDENT_COLUMNS = [
     "Spot.Sum",
 ]
 
+SATURATION_LIMIT = 2
+
 
 def add_exposure_info(data: pd.DataFrame, analysis="hyb") -> pd.DataFrame:
     time_cy3 = 100 if "1" in analysis else 200
@@ -61,7 +65,7 @@ def normalize(raw_data: pd.DataFrame, analysis="hyb"):
         _normalize_channel(data)
         for _, data in split(overflow_tested, EXPOSURE_CHANNEL)
     )
-    return pd.concat(normalized_data).reset_index()
+    return pd.concat(normalized_data).reset_index(drop=True)
 
 
 def _normalize_channel(data: pd.DataFrame) -> pd.DataFrame:
@@ -72,10 +76,17 @@ def _normalize_channel(data: pd.DataFrame) -> pd.DataFrame:
     available_columns = [
         c for c in hdr_data.columns if c in TIME_DEPENDENT_COLUMNS
     ]
-    return normalize_xdr_data(
+    normalized = normalize_xdr_data(
         hdr_data,
         normalized_time,
         EXPOSURE_TIME,
         available_columns,
         "{}.Normalized",
     )
+    with contextlib.suppress(KeyError):
+        normalized[NET_SIGNAL] = (
+            normalized["Spot.Mean.Normalized"]
+            - normalized["Bkg.Median.Normalized"]
+        )
+
+    return normalized