def step_expectation(X,n_components,means,variances):
    """E Step

    Parameters
    ----------
    X : array-like, shape (n_samples,)
        The data.
    n_components : int
        The number of clusters
    means : array-like, shape (n_components,)
        The means of each mixture component.
    variances : array-like, shape (n_components,)
        The variances of each mixture component.

    Returns
    -------
    weights : array-like, shape (n_components,n_samples)
    """
    weights = np.zeros((n_components,len(X)))
    for j in range(n_components):
        weights[j,:] = norm(loc=means[j],scale=np.sqrt(variances[j])).pdf(X)
    return weights