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How to use get_root_dir method in autotest

Best Python code snippet using autotest_python

utils.py

Source:utils.py

...7fields_user_num = ['followers_count', 'friends_count', 'listed_count', 'statuses_count', 'favourites_count', 'len_name',8                   'len_screen_name', 'len_description']9fields_user_cat = ['geo_enabled', 'verified', 'has_location']10fields_user = ['followers_count', 'friends_count', 'listed_count', 'statuses_count', 'favourites_count', 'geo_enabled', 'verified', 'has_location']11def get_root_dir():12    """13    Change this to the root data directory14    :return: root directory15    """16    root = osp.join("..", "fake_news_data")17    if os.name == "posix":18        root = osp.join("..", "fake_news_data")19    else:20        root = osp.join("C:\\Workspace", "FakeNews", "fake_news_data")21    return root22def get_processed_dir(exp_name=None):23    if exp_name is not None:24        processed_dir = osp.join(get_root_dir(), "back", exp_name)25        if not osp.exists(processed_dir):26            os.mkdir(processed_dir)27        return processed_dir28    else:29        return get_root_dir()30def load_tweets(dataset):31    return torch.load(osp.join(get_root_dir(), f"{dataset}_tweets.pt"))32def save_tweets(dataset, all_tweets_d, all_replies_d, all_tweets_score_d):33    torch.save((all_tweets_d, all_replies_d, all_tweets_score_d), osp.join(get_root_dir(), f"{dataset}_tweets.pt"))34def load_users(dataset):35    all_user_feat_d = torch.load(osp.join(get_root_dir(), f"{dataset}_users.pt"))36    return all_user_feat_d37def save_users(dataset, all_user_feat_d):38    torch.save(all_user_feat_d, osp.join(get_root_dir(), f"{dataset}_users.pt"))39def load_nx_graphs(dataset):40    all_Gu = torch.load(osp.join(get_root_dir(), f"{dataset}_Gu.pt"))41    return all_Gu42def save_Gu(dataset, all_Gu):43    torch.save(all_Gu, osp.join(get_root_dir(), f"{dataset}_Gu.pt"))44def load_labels(dataset):45    processed_dir = get_root_dir()46    labels_d = torch.load(osp.join(processed_dir, f"{dataset}_labels.pt"))47    return labels_d48def save_labels(dataset, labels_d):49    torch.save(labels_d, osp.join(get_root_dir(), f"{dataset}_labels.pt"))50def load_user_feat(dataset):51    import torch52    all_Gu = torch.load(osp.join(get_root_dir(), f"{dataset}_Gu.pt"))53    return all_Gu54def read_news_article_evidence(dataset):55    """56    format: claim_evi_pair, news_article, label57    :param dataset:58    :return:59    """60    data_dir = get_root_dir()61    path = osp.join(data_dir, f"{dataset}_news_article_evidence.pkl")62    with open(path, "rb") as f:63        examples = pickle.load(f)64    return examples65def read_tweets_and_scores(dataset):66    import torch67    all_tweets_d, all_replies_d, all_tweets_score_d = torch.load(osp.join(get_root_dir(), f"{dataset}_tweets.pt"))68    return all_tweets_d, all_replies_d, all_tweets_score_d69def read_news_articles_text(global_news_article_d, dataset_name="politifact"):70    root = get_root_dir()71    with open(osp.join(root, f"{dataset_name}_news_articles.txt"), 'r', encoding='utf-8') as f:72        for line in f.readlines():73            filename, article = line.split("\t")74            article = article.strip()75            global_news_article_d[filename] = article76        f.close()77def read_news_articles_labels(dataset_name="politifact", n_samples=0):78    KEEP_EMPTY_RETWEETS_AND_REPLIES = 179    # if we only read the first `n_samples` samples in the dataframe80    if n_samples > 0:81        news_article_df = pd.read_csv(get_root_dir() + f"\\{dataset_name}_news_articles.tsv", sep='\t', iterator=True,82                                      header=None)83        news_article_df = news_article_df.get_chunk(n_samples)84    else:85        news_article_df = pd.read_csv(get_root_dir() + f"\\{dataset_name}_news_articles.tsv", sep='\t')86    if KEEP_EMPTY_RETWEETS_AND_REPLIES:87        news_article_cleaned_df = news_article_df[88            (news_article_df.has_tweets == 1) & (news_article_df.has_news_article == 1)]89    else:90        news_article_cleaned_df = news_article_df[91            (news_article_df.has_tweets == 1) & (news_article_df.has_news_article == 1) & (92                    news_article_df.has_retweets == 1) & (news_article_df.has_replies == 1)]93    return news_article_cleaned_df94def only_directories(path):95    return [name for name in os.listdir(path) if osp.isdir(osp.join(path, name))]96def get_data_list():97    politifact_fake = only_directories("politifact_fake")98    politifact_real = only_directories("politifact_real")99    gossipcop_fake = only_directories("gossipcop_fake")100    gossipcop_real = only_directories("gossipcop_real")101    data_list = {102        "politifact_real": politifact_real,103        "politifact_fake": politifact_fake,104        "gossipcop_fake" : gossipcop_fake,105        "gossipcop_real" : gossipcop_real106    }107    return data_list108def get_dataset_names(dataset):109    if dataset == "politifact":110        dataset_names = {111            "politifact": ["politifact_real", "politifact_fake"]112        }113    elif dataset == "gossipcop":114        dataset_names = {115            "gossipcop": ["gossipcop_real", "gossipcop_fake"]116        }117    elif dataset == "both":118        dataset_names = {119            "politifact": ["politifact_real", "politifact_fake"],120            "gossipcop" : ["gossipcop_real", "gossipcop_fake"]121        }122    else:123        raise NotImplementedError124    return dataset_names125def filter_empty_dict_entry(d, filename, log=True):126    is_empty_json = False127    new_d = {}128    for k in d:129        if d[k] != []:130            new_d[k] = d[k]131    if new_d == {}:132        if log:133            print(f"\t{filename} json empty")134        is_empty_json = True135    return new_d, is_empty_json136# For a dict of dicts, filter empty entries, which are {}137def filter_empty_nested_dict(d):138    new_d, empty_li = {}, []139    for k, v in d.items():140        if v == {}:141            empty_li += [k]142        else:143            new_d[k] = d[k]144    return new_d, empty_li145def print_results(results, epoch, dataset_split_name="Train", enable_logging=True, args=None):146    log_str = f"\n[{dataset_split_name}] Epoch {epoch}\n\tPre: {results['pre']:.4f}, Rec: {results['rec']:.4f}\n\tAcc: {results['acc']:.4f}, F1: {results['f1']:.4f}\n"147    print(log_str)148    if enable_logging:149        f = open(f"{args.outdir}/{dataset_split_name}_{args.max_len}_{args.evi_num}_results.txt", "a+")150        f.write(log_str)151def load_tweet_df(filename, dataset):152    import pandas as pd153    import numpy as np154    pd.options.display.max_columns = 20155    pd.set_option('precision', 20)156    # NOTE: reading as int64 is super important157    dtypes = {158        'root_tweet_id': np.int64,159        'tweet_id'     : np.int64,160        'root_user_id' : np.int64,161        'user_id'      : np.int64,162    }163    path = osp.join(get_root_dir(), dataset, filename, "tweets_retweets_comments.tsv")164    if not osp.exists(path):165        print(f"\t SKIP {filename}: no tweet_retweet_comment.tsv")166        return None167    tweet_df = pd.read_csv(path, sep='\t', float_precision='high')168    return tweet_df169def print_heading(dataset):...

window_utils.py

Source:window_utils.py

...11    """Retrieves the pref value under the given name key from the settings file"""12    return load_settings(SETTINGS_FILENAME).get(key)13def open_config_rc(window):14    """Opens the default .jsbeautifyrc file for editing in a new tab"""15    file_path = join(get_root_dir(), '.jsbeautifyrc.defaults.json')16    window.open_file(file_path)17def open_u_config_rc(window):18    """Opens the user's .jsbeautifyrc file for editing in a new tab"""19    defaults = "{\n}"20    old_jsbeautifyrc_path = join(get_root_dir(), '.jsbeautifyrc')21    old_jsbeautifyrc = read_text_from_file(old_jsbeautifyrc_path, defaults)22    file_path = join(get_user_dir(), '.jsbeautifyrc')23    window.open_file(ensure_file(file_path, default_contents=old_jsbeautifyrc))24def open_sublime_settings(window):25    """Opens the default plugin settings file for editing in a new tab"""26    file_path = join(get_root_dir(), SETTINGS_FILENAME)27    window.open_file(file_path)28def open_u_sublime_settings(window):29    """Opens the user's plugin settings file for editing in a new tab"""30    file_path = join(get_user_dir(), SETTINGS_FILENAME)31    window.open_file(ensure_file(file_path, default_contents="{\n}"))32def open_sublime_keymap(window, platform):33    """Opens the default plugin keyboard bindings file for editing in a new tab"""34    file_name = KEYMAP_FILENAME.replace("$PLATFORM", platform)35    file_path = join(get_root_dir(), file_name)36    window.open_file(file_path)37def open_u_sublime_keymap(window, platform):38    """Opens the user's plugin keyboard bindings file for editing in a new tab"""39    file_name = KEYMAP_FILENAME.replace("$PLATFORM", platform)40    file_path = join(get_user_dir(), file_name)...

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