lsframe Template

This Template serves as an example layout for a script using lsframe.

Import lsframe and any other packages that may be needed for your function,

import lsframe as ls

# import numpy as np
# etc.

Set the path to a parent directory,

path = "../path/to/parent/directory"

Define a function that accepts the parent directory and any additional arguments in the form of a dictionary and returns a list of outputs. The list must have a single value for each member of the list and have len() equal to the list of 'classifiers' given during the creation of the start object below.

def function_handle(directory, args_dict):

    # insert code that acts on each file or sub-directory and makes output(s)
    # output1 =
    # output2 =

    return [output1, output2]  # make sure outputs are in a list
    # len() outputs list must = len() classifiers list

Create the start object,

lsobject = ls.start(
    path,
    patterns=[],  # any patterns in the file or folder names to use as classifiers
    skip=[],  # any sub-strings in the names of file folders that should be skipped
    classifiers=[
        "output1",
        "output2",
    ],  # the column names corresponding to the function outputs
    function=function_handle,  # complete the function above
    function_args={},  # any arguments required by function_handle
    date_format="YYYYMMDD",  # format of any date strings in the file or folder names
)

Pass the start object to the user defined function to add classifiers to the .frame, then print the .head() of .frame,

lsobject.drive()
print(lsobject.frame.head())

Add a dictionary to the start object that is a map of the parent directory,

lsobject.map_directory()

Create a seaborn.relplot correlating the two outputs. Replace 'None' for hue with date_delta if it exists in your .frame, or maybe with a third output if you have more than two. The 'seaborn_args' dictionary should have keys that are the arguments that would be given to seaborn.relplot and any allowed values according to seaborn.relplot documentation,

lsobject.sea(seaborn_args={"x": "output1", "y": "output2", "hue": None, "s": 100})