train_test_split

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from sklearn  import  datasets


class train_test_split1:
    def __init__(self):
        print()


    def train_test_split2(x, y, test_ratio=0.2, seed=None):
        assert x.shape[0] == y.shape[0]
        assert 0.0 <= test_ratio <= 1.0
        if seed:
           np.random.seed(seed)
        shuffle_indexes = np.random.permutation(len(x))
        test_size = int(len(x)*test_ratio)

        test_indexes = shuffle_indexes[:test_size]
        train_indexes = shuffle_indexes[test_size:]

        x_train = x[train_indexes]
        y_train = y[train_indexes]

        x_test = x[test_indexes]
        y_test = y[test_indexes]

        return  x_train, x_test,y_train, y_test