normilization api for single channels has changed

CHANGES.md

@@ -1,3 +1,11 @@
+0.3.0  - normalization api
+--------------------------
+
+ - normilization api for single channels has changed and is exposed in package
+   `normalize_channel(single_channel_data_frame, normalized_time_in_ms)`
+   
+
+
 0.2.0  - remove custom normalization map
 ----------------------------------------
 

sensospot_data/__init__.py

@@ -3,7 +3,7 @@
 Parsing the numerical output from Sensovations Sensospot image analysis.
 """
 
-__version__ = "0.2.0"
+__version__ = "0.3.0"
 
 VERSION_TABLE_NAME = f"v{__version__}".replace(".", "_")
 
@@ -15,4 +15,4 @@ from .parser import (  # noqa: F401
     process_folder,
     parse_multiple_files,
 )
-from .normalisation import normalize_measurement  # noqa: F401
+from .normalisation import normalize_channel, normalize_measurement  # noqa: F401

sensospot_data/normalisation.py

@@ -130,12 +130,12 @@ def normalize_exposure_time(split_data_frames):
     """
     normalization_map = _infer_normalization_map(split_data_frames)
     return {
-        key: _normalize_exposure(frame, normalization_map[key])
+        key: normalize_channel(frame, normalization_map[key])
         for key, frame in split_data_frames.items()
     }
 
 
-def _normalize_exposure(channel_frame, normalized_time):
+def normalize_channel(channel_frame, normalized_time):
     """ add time normalized values to a channel data frames """
     channel_frame[COL_NAME_NORMALIZED_EXPOSURE_TIME] = normalized_time
 

tests/test_normailsation.py

@@ -215,20 +215,20 @@ def test_infer_normalization_map(normalization_data_frame):
     assert result == {"Cy3": 25, "Cy5": 50}
 
 
-def test_normalize_exposure(normalization_data_frame):
+def test_normalize_channel(normalization_data_frame):
     from sensospot_data.columns import COLUMN_NORMALIZATION
     from sensospot_data.normalisation import (
         reduce_overflow,
-        _normalize_exposure,
+        normalize_channel,
     )
 
     reduced = reduce_overflow(normalization_data_frame, "Saturation", 1)
-    result = _normalize_exposure(reduced["Cy5"], 100)
+    result = normalize_channel(reduced["Cy5"], 50)
 
     sorted_results = result.sort_values(
         by=["Well.Row", "Well.Column", "Pos.Id"]
     )
-    expected_values = [1, 4, 15, 1, 10, 10, 10, 10, 100, 100, 100, 100]
+    expected_values = [2, 8, 30, 2, 20, 20, 20, 20, 200, 200, 200, 200]
 
     for normalized_col in COLUMN_NORMALIZATION.values():
         list(sorted_results[normalized_col]) == expected_values