utils/helpers.py

from typing import Literal
import pandas as pd
import numpy as np

def get_first_valid_return_index(series: pd.Series) -> int:
    return np.where(np.logical_and(series != 0, np.logical_not(np.isnan(series))))[0][0]

def flatten(list_of_lists: list) -> list:
    return [item for sublist in list_of_lists for item in sublist]
refactor(Project): move out load_data to utils, rename fetch_data to `run_fetch_data`, got classifiers to work (#38 ) 2021-12-17 17:41:50 +01:00			`from typing import Literal`
feat(Core): ensemble models, correct forward returns calculation, scaling, only train from when asset returns are available, major bug fixed in walk_forward_train_test (#35 ) 2021-12-17 14:32:17 +01:00			`import pandas as pd`
			`import numpy as np`

			`def get_first_valid_return_index(series: pd.Series) -> int:`
refactor(Project): move out load_data to utils, rename fetch_data to `run_fetch_data`, got classifiers to work (#38 ) 2021-12-17 17:41:50 +01:00			`return np.where(np.logical_and(series != 0, np.logical_not(np.isnan(series))))[0][0]`
feat(Config): feature extractors are enabled one-by-one with a bool, added previous model to model.fit() (#77 ) 2021-12-23 10:35:20 +01:00
			`def flatten(list_of_lists: list) -> list:`
			`return [item for sublist in list_of_lists for item in sublist]`