From dc8e7d5273c1b34ba2e64742d0e626edba2cec23 Mon Sep 17 00:00:00 2001 From: Holger Frey Date: Mon, 22 Feb 2021 13:09:40 +0100 Subject: [PATCH] changed 'split_data_frame' to 'split' --- README.md | 4 ++-- sensospot_data/__init__.py | 2 +- sensospot_data/dynamic_range.py | 4 ++-- sensospot_data/utils.py | 2 +- tests/test_sensovation_data.py | 2 +- tests/test_utils.py | 6 +++--- 6 files changed, 10 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 2ffc9f4..6b74c13 100644 --- a/README.md +++ b/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 diff --git a/sensospot_data/__init__.py b/sensospot_data/__init__.py index 83d87a6..fae0abb 100644 --- a/sensospot_data/__init__.py +++ b/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 diff --git a/sensospot_data/dynamic_range.py b/sensospot_data/dynamic_range.py index 790288f..63c7116 100644 --- a/sensospot_data/dynamic_range.py +++ b/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) diff --git a/sensospot_data/utils.py b/sensospot_data/utils.py index c2ea921..17dedf5 100644 --- a/sensospot_data/utils.py +++ b/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} diff --git a/tests/test_sensovation_data.py b/tests/test_sensovation_data.py index 4b6e31d..79a739b 100644 --- a/tests/test_sensovation_data.py +++ b/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 diff --git a/tests/test_utils.py b/tests/test_utils.py index 804f4f3..c169828 100644 --- a/tests/test_utils.py +++ b/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():