4.1.1.1.1.7. `lib.data_handling.data_filtering`#

Module that provides functionality in order to filter data.

@author: Thomas Arne Hensel, 2023

4.1.1.1.1.7.1. Module Contents#

4.1.1.1.1.7.1.1. Classes#

`Filter`	Class for filtering data based on certain criteria.
`MinfluxFilter`	Class for filtering Minflux data based on certain criteria.

4.1.1.1.1.7.1.2. Functions#

`filter_single_file`	Filter a single file based on certain criteria.
`filter_experiments`	Check whether experiments comply with filter criteria.

4.1.1.1.1.7.1.3. API#

class lib.data_handling.data_filtering.Filter(collect_artefacts=True)#

Class for filtering data based on certain criteria.

Attributes: - ext (Extractor): Extractor instance for data extraction. - artefacts (Artefacts): Artefacts instance for storing figures and other artifacts. - collect_artefacts (bool): Flag indicating whether to collect and store artifacts.

Methods: - filter_data(in_folder, base_out, max_files=100, batchsize=1, agnostic=True, fast_return=False):

Iterate through a nested directory and filter data based on certain criteria.

Initialization

Constructor for the Filter class.

Parameters:: collect_artefacts (bool, optional, default is True.) – Flag indicating whether to collect and store artifacts.

filter_data(in_folder, base_out, max_files=100, batchsize=1, agnostic=True, fast_return=False)#

Iterate through a nested directory and filter data based on certain criteria.

Parameters:

in_folder (str) – Root of the input directory.
base_out (str) – Root of the output directory.
max_files (int, optional, default is 100.) – Maximum number of files to be analyzed in one directory.
batchsize (int, optional, default is 1.) – Size of moving average.
agnostic (bool, optional, default is True.) – Specify whether construction is agnostic or not.
fast_return (bool, optional, default is False.) – Optional direct return of experiment object.

lib.data_handling.data_filtering.filter_single_file(full_file_path, base_out, batchsize=1, agnostic=True, fast_return=False, collect_artefacts=True)#

Filter a single file based on certain criteria.

Parameters:

full_file_path (str) – Full path to the input file.
base_out (str) – Root of the output directory.
batchsize (int, optional, default is 1.) – Size of moving average.
agnostic (bool, optional, default is True.) – Specify whether construction is agnostic or not.
fast_return (bool, optional, default is False.) – Optional direct return of experiment object.
collect_artefacts (bool, optional, default is True.) – Flag indicating whether to collect and store artifacts.

Returns:

Reason for rejection or None if the file is accepted.

Return type:

str

lib.data_handling.data_filtering.filter_experiments(experiments)#

Check whether experiments comply with filter criteria.

Parameters:: experiments (list) – List of Experiment objects.
Returns:: Reason for rejection or None if the experiments are accepted.
Return type:: str

class lib.data_handling.data_filtering.MinfluxFilter(collect_artefacts=True)#

Class for filtering Minflux data based on certain criteria.

Methods: - __init__(collect_artefacts=True): Constructor for the MinfluxFilter class.