biopsykit.io.ecg module

I/O functions for files related to ECG processing.

biopsykit.io.ecg.load_hr_phase_dict(file_path, assert_format=True)[source]

Load Excel file containing time series heart rate data of one subject.

The returned dictionary will be a HeartRatePhaseDict, i.e., a dict with heart rate data from one subject split into phases (as exported by write_hr_phase_dict() or write_hr_phase_dict_csv()).

Parameters

  • file_path (Path or str) – path to file

  • assert_format (bool, optional) – whether to check if the imported dict is in the right format or not

Returns

Dict with heart rate data split into phases

Return type

HeartRatePhaseDict

Raises

See also

HeartRatePhaseDict

Dictionary format

write_hr_phase_dict

Write HeartRatePhaseDict to file

biopsykit.io.ecg.load_hr_phase_dict_folder(base_path, filename_pattern, subfolder_pattern=None)[source]

Load a folder with multiple HeartRatePhaseDict and concatenate them into a HeartRateSubjectDataDict.

This functions looks for all files that match the file_pattern in the folder specified by base_path and loads the files that are all expected to be HeartRatePhaseDict.

Subject IDs are extracted from the file name. Hence, file_pattern needs to be a regex including a capture group, e.g. “ecg_results_(\w+).xlsx”.

Alternatively, if the files are stored in subfolders, the name pattern of these subfolders can be specified by subject_folder_pattern. Then, it is expected that the subfolder names correspond to the subject IDs.

The returned dictionary will be a HeartRateSubjectDataDict with the following format:

{ subject_id : HeartRatePhaseDict }

Parameters

  • base_path – path to top-level folder containing all subject folders

  • filename_pattern (str) – filename pattern of exported HeartRatePhaseDict. Must be a regex string with capture group to extract subject IDs, or a regular regex string (without capture group) if subfolder_pattern is specified

  • subfolder_pattern (str, optional) – subfolder name pattern if files are stored in subfolders. Then, filename_pattern does not need to be a regex with a capture group because it is assumed that the names of the subfolders correspond to the subject IDs.

Returns

HeartRateSubjectDataDict, i.e., a dictionary with HeartRatePhaseDict of multiple subjects

Return type

HeartRateSubjectDataDict

Raises

See also

get_subject_dirs

Filter for subject subfolders in a given folder

load_hr_phase_dict

Load HeartRatePhaseDict for one subject

Examples

>>> from biopsykit.io.ecg import load_hr_phase_dict_folder
>>> base_path = "./ecg_results/"
>>> # Option 1: all files are stored in `base_path`, subject IDs are extracted from the file names
>>> dict_hr_subjects = load_hr_phase_dict_folder(
>>>                         base_path,
>>>                         filename_pattern=r"ecg_result_(\\w+).xlsx")
>>> print(dict_hr_subjects)
{
     'Vp01': {}, # one single HeartRatePhaseDict
     'Vp02': {},
     # ...
}
>>> # Option 2: files are stored in subfolders, the name of the subfolders is the corresponding subject ID
>>> dict_hr_subjects = load_hr_phase_dict_folder(
>>>                         base_path,
>>>                         filename_pattern=r"ecg_result*.xlsx",
>>>                         subfolder_pattern="Vp*")
>>> print(dict_hr_subjects)
{
     'Vp01': {}, # one single HeartRatePhaseDict
     'Vp02': {},
     # ...
}
biopsykit.io.ecg.load_hr_phase_dict_csv(folder_path, file_pattern, phase_order=None, assert_format=True)[source]

Load csv file with time series HR data of one subject from folder and combine it into a HeartRatePhaseDict.

The returned dictionary will be a HeartRatePhaseDict, i.e., a dict with heart rate data from one subject split into phases (as exported by write_hr_phase_dict()).

Parameters

  • folder_path (Path or str) – folder path to export csv files

  • file_pattern (Path or str) – file pattern of the csv files. file_pattern must include a regex capture group (see Examples) which is used to extract the phase name from the file name.

  • phase_order (list of str, optional) – list of phase names to order resulting HeartRatePhaseDict or None to order phases according to the file name ordering in folder_path. Default: None

  • assert_format (bool, optional) – whether to check if the imported dict is in the right format or not

Returns

Dict with heart rate data split into phases

Return type

HeartRatePhaseDict

Raises

See also

HeartRatePhaseDict

Dictionary format

write_hr_phase_dict_csv

Write HeartRatePhaseDict to a series of csv files

biopsykit.io.ecg.write_hr_phase_dict(hr_phase_dict, file_path)[source]

Write HeartRatePhaseDict to an Excel file.

The HeartRatePhaseDict is a dictionary with heart rate time series data split into phases.

Each of the phases in the dictionary will be a separate sheet in the Excel file.

Parameters

See also

HeartRatePhaseDict

Dictionary format

load_hr_phase_dict

Load HeartRatePhaseDict written to file

write_pandas_dict_excel

Write dictionary with pandas dataframes to Excel file

biopsykit.io.ecg.write_hr_phase_dict_csv(hr_phase_dict, folder_path, file_pattern)[source]

Write HeartRatePhaseDict to a series of csv files.

The HeartRatePhaseDict is a dictionary with heart rate time series data split into phases.

Each of the phases in the dictionary will be a separate csv file.

Parameters

  • hr_phase_dict (HeartRatePhaseDict) – a HeartRatePhaseDict containing pandas dataframes with heart rate data

  • folder_path (Path or str) – folder path to export csv files

  • file_pattern (Path or str) – file pattern to save. The file pattern must include a placeholder “{}” which will be filled with the name of the phase.

Raises

See also

HeartRatePhaseDict

Dictionary format

load_hr_phase_dict_csv

Load HeartRatePhaseDict written to csv files

biopsykit.io.carwatch_logs module biopsykit.io.eeg module