def classification_tex(f, weblog, threshold_requests_per_session,
    classification_wanted_transaction, weblog_columns_dict):
    """
    Write on latex file information variables on classification
    
    Parameters
    ----------
        f: file 
        
        weblog: pandas dataframe of requests
        
        threshold_requests_per_session: int for filter number of requests per session
                        
        classification_wanted_transaction: list of items wanted to analyse corresponding to the ones given in 
                    classification_diversity
        
        weblog_columns_dict: dict recupered with function of 'file_function'
            
    Returns
    -------
        File (Optionnal)
    """
    classification_wanted_transaction = list(set(
        classification_wanted_transaction) - {'social', 'search', 'other'})
    requests_per_session = weblog.groupby('session_id').size()
    sessions_requests_over_threshold = list(requests_per_session[
        requests_per_session > threshold_requests_per_session].index)
    divpat_log = weblog[weblog.session_id.isin(
        sessions_requests_over_threshold)]
    num_reqs_inside = divpat_log.shape[0]
    divpat_log = divpat_log[~divpat_log.requested_category.isin(['social',
        'search', 'other'])]
    divpat_log = divpat_log[~divpat_log.referrer_category.isin(['social',
        'search', 'other'])]
    num_reqs_selected_cats = divpat_log.shape[0]
    f.write('\n% 5. Diversifying patterns according to classification')
    f.write('\n\\newcommand{\\%s}{%.1f}' % ('PCDivPatTotalSelectedCat', 
        100.0 * num_reqs_selected_cats / num_reqs_inside))
    f.write('\n\\newcommand{\\%s}{%d}' % ('DivPatTotalNumberRequests',
        divpat_log.shape[0]))
    f.write('\n\\newcommand{\\%s}{%d}' % ('DivPatTotalNumberUsers', len(
        divpat_log.userID.unique())))
    f.write('\n\\newcommand{\\%s}{%d}' % ('DivPatTotalNumberSessions', len(
        divpat_log.session_id.unique())))
    f.write('\n\\newcommand{\\%s}{%d}' % ('DivPatTotalNumberPages', len(
        list(set(divpat_log[weblog_columns_dict['requested_page_column']].
        unique()) | set(divpat_log[weblog_columns_dict[
        'referrer_page_column']].unique())))))
    return f
