EMGFlow

Appearance

access_files Module ​

These functions access files, set up file structures for working with sEMG signals, and load EMGFlow's built-in dataset. The functions are mostly used internally by the package.

Module Structure ​

make_paths ​

Description

Generates a file structure for an EMG workflow, and returns a dictionary of the locations for these files for easy use with EMG processing functions.

Creates 'Raw', 'Notch', 'Bandpass', 'FWR', 'Screened', 'Filled', 'Smooth', and 'Feature' subfolders at a given location. If no path is given, will create a 'Data' folder in the current working directory, with these subfolders inside.

python
make_paths(root:str=None)

Parameters

root: str, optional (None)

  • The root where the data is generated. The default is None.

Returns

path_names: dict-str

  • A dictionary of file locations with keys for stage in the processing pipeline.

Example

python
# Create folders and get locations
path_names = EMGFlow.make_paths()

make_sample_data ​

Description

Generates sample data in the 'Raw' folder of a provided dictionary of file locations.

Creates '01' and '02' folders, which each contain two sample data files ('01/sample_data_01.csv', '01/sample_data_02.csv', '02/sample_data_03.csv', '02/sample_data_04.csv')

The sample data will not be written if it already exists in the folder.

python
make_sample_data(path_names:dict)

Parameters

path_names: dict-str

  • A dictionary of file locations with keys for stage in the processing pipeline.

Raises

An exception is raised if 'Raw' is not a key of the path_names dictionary provided.

An exception is raised if the sample data cannot be loaded.

Returns

None.

Example

python
# Create file paths, then create sample data
path_names = EMGFlow.make_paths()
EMGFlow.make_sample_data(path_names)

read_file_type ​

Description

Wrapper for reading files of a given extension.

Switches between different reading methods based on the extension provided.

Supported formats that can be read are: 'csv'.

python
read_file_type(path:str, file_ext:str)

Parameters

path: str

  • The path of the file to read.

file_ext: str

  • The file extension for files to read. Only reads files with this extension. The default is 'csv'.

Raises

An exception is raised if the file could not be read.

An exception is raised if an unsupported file format was provided for file_ext.

Returns

file: pd.DataFrame

  • Returns a Pandas dataframe of the file contents.

Example

python
# Read a csv file
path = '/Data/1_raw/01/sample_data_01.csv'
ext = 'csv'
df = EMGFlow.read_file_type(path, ext)

map_files ​

Description

Generate a dictionary of file names and locations (keys/values) from the subfiles of a folder.

python
map_files(in_path:str, file_ext:str='csv', expression:str=None, base:str=None)

Parameters

in_path: str

  • The filepath to a directory to read files.

file_ext: str, optional ('csv')

  • The file extension for files to read. Only reads files with this extension. The default is 'csv'.

expression: str, optional (None)

  • A regular expression. If provided, will only count files whose relative paths from 'base' match the regular expression. The default is None.

base: str, optional (None)

  • The path of the root folder the path keys should start from. Used to track the relative path during recursion. The default is None.

Raises

An exception is raised if expression is not None or a valid regular expression.

Returns

file_dirs: dict-str

  • Returns dictionary of file name keys and file path location values.

Example

python
# Map all csv files in 'dataFiles' folder and subfolders
file_loc_1 = EMGFlow.map_files('data')

# Map all csv files in 'dataFiles' folder and subfolders
# that start with 'DATA_'
file_loc_2 = EMGFlow.map_files('data', expression='^DATA_')

map_files_fuse ​

Description

Merge mapped file dictionaries into a single dataframe. Uses 'names' as the column names, and stores the file path to a file in different stages of the processing pipeline.

python
map_files_fuse(file_dirs, names)

Parameters

file_dirs: list-dict-str

  • List of file location directories.

names: list-str

  • List of names to use for file directory columns. Same order as file_dirs.

Raises

An exception is raised if a file contained in the first file directory (file_dirs[0]) is not found in the other file directories.

Returns

path_df: pd.DataFrame

  • A dataframe of file names, and their locations in each file directory.

Example

python
# Create file directory dictionaries
raw_path = EMGFlow.map_files('/Data/Raw')
notch_path = EMGFlow.map_files('/Data/Notch')
band_path = EMGFlow.map_files('/Data/Bandpass')

# Create dictionary list and names
file_dirs = [raw_path, notch_path, band_path]
names = ['Raw', 'Notch', 'Bandpass']

# Create data frame
dfDirs = EMGFlow.map_files_fuse(file_dirs, names)