MachineLearning/functions.py at main · ife-bat/MachineLearning · GitHub

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import numpy as np
import pandas as pd
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score, mean_absolute_percentage_error


'''_______________________Data work functions__________________________'''

# Function to select a dataset from a cell dataframe
def select_dataset(df, column):

    if not isinstance(column, (list, tuple)):
        column = [column]

    s = df.loc[:, column]
    print(f"Shape of selected packed dataset: {s.shape}")

    s = s.dropna()
    print(f"Shape of selected packed dataset without NaNs: {s.shape}")
    if s.empty:
        print("Non values found")
        return

    s = s.T.apply(pd.Series.explode).set_index("cycle_index")
    print(f"Shape of selected unpacked dataset: {s.shape}")

    return s

'''___________________________ functions for modeling __________________________'''

# Function to get errors
def get_errors(y_train, y_test, y_train_pred, y_test_pred):
    mae_train = mean_absolute_error(np.power(10,y_train), np.power(10,y_train_pred))
    mae_test = mean_absolute_error(np.power(10,y_test), np.power(10,y_test_pred))
    mse_cycles_train = mean_squared_error(np.power(10, y_train), np.power(10, y_train_pred), squared=False)
    mse_cycles_test = mean_squared_error(np.power(10, y_test), np.power(10, y_test_pred), squared=False)
    r2_train = r2_score(y_train, y_train_pred)
    r2_test = r2_score(y_test, y_test_pred)
    mape_train = mean_absolute_percentage_error(y_train, y_train_pred)
    mape_test = mean_absolute_percentage_error(y_test, y_test_pred)

    return mae_train, mae_test, mse_cycles_train, mse_cycles_test,\
        r2_train, r2_test, mape_train, mape_test

# Function for scaling?
def get_errors2(y_train, y_test, y_train_pred, y_test_pred):
    mae_train = mean_absolute_error(y_train, y_train_pred)
    mae_test = mean_absolute_error(y_test, y_test_pred)
    rmse_cycles_train = mean_squared_error(y_train, y_train_pred, squared=False)
    rmse_cycles_test = mean_squared_error(y_test, y_test_pred, squared=False)
    r2_train = r2_score(y_train, y_train_pred)
    r2_test = r2_score(y_test, y_test_pred)
    mape_train = mean_absolute_percentage_error(y_train, y_train_pred)
    mape_test = mean_absolute_percentage_error(y_test, y_test_pred)

    return mae_train, mae_test, rmse_cycles_train, rmse_cycles_test, r2_train, r2_test, mape_train, mape_test