def subsample(X,y, ratio=0.8):
        # pick a random subsample of X and the corresponding y
        nLength = len(X)
        numberOfPicks = int(nLength * ratio)
        rows, columns = X.shape
        sample_X = np.array([])
        sample_y = np.array([])
        for i in range(numberOfPicks):
            if i == 0:
                sample_X = np.asarray(np.zeros((int(rows*ratio), columns)))
                sample_y = np.asarray(np.zeros((int(rows*ratio), 1)))
            randomIndex = random.randrange(0, numberOfPicks, 1)
            sample_X[randomIndex] = X[randomIndex]
            sample_y[randomIndex] = y[randomIndex]
        assert len(sample_X) == numberOfPicks
        return sample_X,sample_y

subsampleTestX, subsampleTestY = subsample(X,y)
print(subsampleTestX)