def train_gmm(data,n_compenents=3,n_steps=50, plot_intermediate_steps_flag=True):
    """ Training step of the GMM model

    Parameters
    ----------
    data : array-like, shape (n_samples,)
        The data.
    n_components : int
        The number of clusters
    n_steps: int
        number of iterations to run
    """

    #intilize model parameters at the start
    means,variances,pi = random_init(n_compenents)

    for step in range(n_steps):
        #perform E step
        weights = step_expectation(data,n_compenents,means,variances)
        #perform M step
        variances,means,pi = step_maximization(X, weights, means, variances, n_compenents, pi)

    plot_pdf(means,variances)