changed 'split_data_frame' to 'split'

README.md

@@ -24,7 +24,7 @@ other useful functions for working with the data.
     enhanced_data = sensospot_data.apply_exposure_map(raw_data, exposure_map)
 
     # split the measurement according to channels
-    channels = sensospot_data.split_data_frame(enhanced_data "Exposure.Channel")
+    channels = sensospot_data.split(enhanced_data "Exposure.Channel")
 
     # merge the two cy5 measurements together, creating an extended dynamic range
     cy5_xdr = sensospot_data.create_xdr(channels["cy5"], normalized_time=25)
@@ -40,7 +40,7 @@ from .parser import parse_file, parse_folder  # noqa: F401
 - **parse_file(path_to_csv_file)**
    Parses the csv file into a pandas data frame and will add additional some
    meta data from the file name. Is internally also used by `parse_folder()`
- - **split_data_frame(data_frame, column)**  
+ - **split(data_frame, column)**  
    Splits a data frame based on the unique values of a column. Will return a 
    dict, with the unique values as keys and the corresponding data frame as 
    value

sensospot_data/__init__.py

@@ -11,9 +11,9 @@ from pathlib import Path
 import click
 
 from .utils import (  # noqa: F401
+    split,
     aggregate,
     add_aggregate,
-    split_data_frame,
     apply_exposure_map,
 )
 from .parser import parse_file, parse_folder  # noqa: F401

sensospot_data/dynamic_range.py

@@ -1,6 +1,6 @@
 from pandas.api.types import is_numeric_dtype
 
-from .utils import split_data_frame
+from .utils import split
 from .columns import (
     RAW_DATA_POS_ID,
     CALC_SPOT_OVERFLOW,
@@ -42,7 +42,7 @@ def _calc_overflow_info(data_frame, column=RAW_DATA_SPOT_MEAN, limit=0.5):
 def _reduce_overflow(data_frame):
     """ the heavy lifting for creating an extended dynamic range """
 
-    split_frames = split_data_frame(data_frame, SETTINGS_EXPOSURE_TIME)
+    split_frames = split(data_frame, SETTINGS_EXPOSURE_TIME)
 
     # get the exposure times, longest first
     exposure_times = sorted(split_frames.keys(), reverse=True)

sensospot_data/utils.py

@@ -20,7 +20,7 @@ DEFAULT_AGGREGATION_INDEX = [
 ]
 
 
-def split_data_frame(data_frame, column):
+def split(data_frame, column):
     """ splits a data frame on unique column values """
     values = data_frame[column].unique()
     masks = {value: (data_frame[column] == value) for value in values}

tests/test_sensovation_data.py

@@ -5,11 +5,11 @@ def test_import_api():
     from sensospot_data import ExposureInfo  # noqa: F401
     from sensospot_data import run  # noqa: F401
     from sensospot_data import blend  # noqa: F401
+    from sensospot_data import split  # noqa: F401
     from sensospot_data import aggregate  # noqa: F401
     from sensospot_data import create_xdr  # noqa: F401
     from sensospot_data import parse_file  # noqa: F401
     from sensospot_data import parse_folder  # noqa: F401
     from sensospot_data import add_aggregate  # noqa: F401
     from sensospot_data import normalize_values  # noqa: F401
-    from sensospot_data import split_data_frame  # noqa: F401
     from sensospot_data import apply_exposure_map  # noqa: F401

tests/test_utils.py

@@ -5,10 +5,10 @@ import pytest
 ExposureSetting = namedtuple("ExposureSetting", ["channel", "time"])
 
 
-def test_split_data_frame(data_frame_with_params):
-    from sensospot_data.utils import split_data_frame
+def test_split(data_frame_with_params):
+    from sensospot_data.utils import split
 
-    result = split_data_frame(data_frame_with_params, "Well.Row")
+    result = split(data_frame_with_params, "Well.Row")
 
     assert set(result.keys()) == set("ABC")
     for key, value_df in result.items():