linted

sensospot_data/dynamic_range.py

@@ -21,7 +21,7 @@ PROBE_MULTI_INDEX = [
 
 
 def _check_if_xdr_ready(data_frame):
-    """ check if a data frame meets the constraints for xdr """
+    """check if a data frame meets the constraints for xdr"""
     required_columns = {SETTINGS_EXPOSURE_CHANNEL, SETTINGS_EXPOSURE_TIME}
     if not required_columns.issubset(data_frame.columns):
         raise ValueError("XDR: Apply an exposure map first")
@@ -34,13 +34,13 @@ def _check_if_xdr_ready(data_frame):
 
 
 def _calc_overflow_info(data_frame, column=RAW_DATA_SPOT_SAT, limit=2):
-    """ add overflow info, based on column and limit """
+    """add overflow info, based on column and limit"""
     data_frame.loc[:, CALC_SPOT_OVERFLOW] = data_frame[column] > limit
     return data_frame
 
 
 def _reduce_overflow(data_frame):
-    """ the heavy lifting for creating an extended dynamic range """
+    """the heavy lifting for creating an extended dynamic range"""
 
     split_frames = split(data_frame, SETTINGS_EXPOSURE_TIME)
 
@@ -67,7 +67,7 @@ def _reduce_overflow(data_frame):
 
 
 def blend(data_frame, column=RAW_DATA_SPOT_SAT, limit=2):
-    """ creates an extended dynamic range, eliminating overflowing spots """
+    """creates an extended dynamic range, eliminating overflowing spots"""
     _check_if_xdr_ready(data_frame)
     if CALC_SPOT_OVERFLOW not in data_frame.columns:
         data_frame = _calc_overflow_info(data_frame, column, limit)

sensospot_data/parameters.py

@@ -9,18 +9,18 @@ from collections import namedtuple
 import numpy
 from defusedxml import ElementTree
 
+from .utils import apply_map
 from .columns import (
     META_DATA_EXPOSURE_ID,
     META_DATA_PARAMETERS_TIME,
     META_DATA_PARAMETERS_CHANNEL,
 )
-from .utils import apply_map
 
 ExposureInfo = namedtuple("ExposureInfo", ["channel", "time"])
 
 
 def _search_measurement_params_file(folder):
-    """ searches for a exposure settings file in a folder """
+    """searches for a exposure settings file in a folder"""
     folder_path = Path(folder)
     params_folder = folder_path / "Parameters"
     if not params_folder.is_dir():
@@ -33,7 +33,7 @@ def _search_measurement_params_file(folder):
 
 
 def _parse_measurement_params(params_file):
-    """ parses the cannel informations from a settings file """
+    """parses the cannel informations from a settings file"""
     file_path = Path(params_file)
     with file_path.open("r") as file_handle:
         tree = ElementTree.parse(file_handle)
@@ -50,7 +50,7 @@ def _parse_measurement_params(params_file):
 
 
 def get_measurement_params(folder):
-    """ returns measurement parameters """
+    """returns measurement parameters"""
     params_file = _search_measurement_params_file(folder)
     if params_file is not None:
         return _parse_measurement_params(params_file)
@@ -58,14 +58,14 @@ def get_measurement_params(folder):
 
 
 def _add_measurement_params(data_frame, params):
-    """ adds measurement parameters to a data frame """
-    columns=[META_DATA_PARAMETERS_CHANNEL, META_DATA_PARAMETERS_TIME]
+    """adds measurement parameters to a data frame"""
+    columns = [META_DATA_PARAMETERS_CHANNEL, META_DATA_PARAMETERS_TIME]
     map = {k: dict(zip(columns, v)) for k, v in params.items()}
     return apply_map(data_frame, map, META_DATA_EXPOSURE_ID)
 
 
 def add_optional_measurement_parameters(data_frame, folder):
-    """ adds measurement params to the data frame, if they could be parsed """
+    """adds measurement params to the data frame, if they could be parsed"""
     params = get_measurement_params(folder)
     if params:
         available_exposures = set(data_frame[META_DATA_EXPOSURE_ID].unique())

sensospot_data/parser.py

@@ -13,9 +13,9 @@ from .columns import (
     RAW_DATA_POS_ID,
     META_DATA_WELL_ROW,
     META_DATA_WELL_NAME,
-    PARSED_DATA_COLUMN_SET,
     META_DATA_EXPOSURE_ID,
     META_DATA_WELL_COLUMN,
+    PARSED_DATA_COLUMN_SET,
     RAW_DATA_NORMALIZATION_MAP,
     RAW_DATA_COLUMNS_RENAME_MAP,
 )
@@ -33,7 +33,7 @@ FileInfo = namedtuple("FileInfo", ["row", "column", "exposure"])
 
 
 def _guess_decimal_separator(file_handle):
-    """ guesses the decimal spearator of a opened data file """
+    """guesses the decimal spearator of a opened data file"""
     file_handle.seek(0)
     headers = next(file_handle)  # noqa: F841
     data = next(file_handle)
@@ -43,7 +43,7 @@ def _guess_decimal_separator(file_handle):
 
 
 def _parse_csv(data_file):
-    """ parse a csv sensovation data file """
+    """parse a csv sensovation data file"""
     data_path = Path(data_file)
     with data_path.open("r") as handle:
         decimal_sep = _guess_decimal_separator(handle)
@@ -51,7 +51,7 @@ def _parse_csv(data_file):
 
 
 def _extract_measurement_info(data_file):
-    """ extract measurement meta data from a file name """
+    """extract measurement meta data from a file name"""
     data_path = Path(data_file)
     *rest, well, exposure = data_path.stem.rsplit("_", 2)  # noqa: F841
     matched = REGEX_WELL.match(well)
@@ -64,7 +64,7 @@ def _extract_measurement_info(data_file):
 
 
 def _cleanup_data_columns(data_frame):
-    """ renames some data columns for consistency and drops unused columns """
+    """renames some data columns for consistency and drops unused columns"""
     renamed = data_frame.rename(columns=RAW_DATA_COLUMNS_RENAME_MAP)
     surplus_columns = set(renamed.columns) - PARSED_DATA_COLUMN_SET
     return renamed.drop(columns=surplus_columns)
@@ -99,7 +99,7 @@ def _silenced_parse_file(data_file):
 
 
 def parse_multiple_files(file_list):
-    """ parses a list of file paths to one combined dataframe """
+    """parses a list of file paths to one combined dataframe"""
     if not file_list:
         raise ValueError("Empty file list provided")
     collection = (_silenced_parse_file(path) for path in file_list)
@@ -114,7 +114,7 @@ def parse_multiple_files(file_list):
 
 
 def list_csv_files(folder):
-    """ returns all csv files in a folder """
+    """returns all csv files in a folder"""
     folder_path = Path(folder)
     files = (item for item in folder_path.iterdir() if item.is_file())
     visible = (item for item in files if not item.stem.startswith("."))
@@ -122,7 +122,7 @@ def list_csv_files(folder):
 
 
 def _sanity_check(data_frame):
-    """ checks some basic constrains of a combined data frame """
+    """checks some basic constrains of a combined data frame"""
     field_rows = len(data_frame[META_DATA_WELL_ROW].unique())
     field_cols = len(data_frame[META_DATA_WELL_COLUMN].unique())
     exposures = len(data_frame[META_DATA_EXPOSURE_ID].unique())
@@ -139,7 +139,7 @@ def _sanity_check(data_frame):
 
 
 def parse_folder(folder, quiet=False):
-    """ parses all csv files in a folder to one large dataframe """
+    """parses all csv files in a folder to one large dataframe"""
     file_list = list_csv_files(Path(folder))
     data_frame = parse_multiple_files(file_list)
     data_frame = add_optional_measurement_parameters(data_frame, folder)

sensospot_data/utils.py

@@ -20,26 +20,26 @@ DEFAULT_AGGREGATION_INDEX = [
 
 
 def split(data_frame, column):
-    """ splits a data frame on unique column values """
+    """splits a data frame on unique column values"""
     values = data_frame[column].unique()
     masks = {value: (data_frame[column] == value) for value in values}
     return {value: data_frame[mask] for value, mask in masks.items()}
 
 
 def _is_list_or_tuple(something):
-    """ returns true if something is a list or tuple """
+    """returns true if something is a list or tuple"""
     if isinstance(something, Sequence):
         return not isinstance(something, str)
     return False
 
 
 def _is_numerical(something):
-    """ returns true if something is an int or float """
+    """returns true if something is an int or float"""
     return isinstance(something, int) or isinstance(something, float)
 
 
 def _check_valid_exposure_map_entry(entry):
-    """ raises a ValueError, if an exposure map entry is not suitable """
+    """raises a ValueError, if an exposure map entry is not suitable"""
     if not _is_list_or_tuple(entry):
         raise ValueError("Eposure Map: entries must be tuples or lists")
     if not len(entry) == 2:
@@ -104,7 +104,7 @@ def apply_exposure_map(data_frame, exposure_map=None):
 
     _check_exposure_map(data_frame, exposure_map)
 
-    columns=[SETTINGS_EXPOSURE_CHANNEL, SETTINGS_EXPOSURE_TIME]
+    columns = [SETTINGS_EXPOSURE_CHANNEL, SETTINGS_EXPOSURE_TIME]
     map = {k: dict(zip(columns, v)) for k, v in exposure_map.items()}
 
     return apply_map(data_frame, map, META_DATA_EXPOSURE_ID)

tests/test_sensovation_data.py

@@ -6,9 +6,9 @@ def test_import_api():
     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 apply_map  # 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 normalize_values  # noqa: F401
     from sensospot_data import apply_exposure_map  # noqa: F401
-    from sensospot_data import apply_map  # noqa: F401