<jupyter_start><jupyter_text>Experiments<jupyter_code>alpha = 7
# sigma_list = [0.1, 0.25, 0.5, 0.75, 0.9]
sigma_list = [0.9]
c = 5.0
Klist = [int(10 ** x) for x in np.linspace(2, 5, 7)]
nreps = 5

for sigma in sigma_list:
    print("================== sigma:", str(sigma), "=============================")
    num_triang, mean_triang, clust_coeff, num_nodes, num_edges, mean_deg = generate_stats(Klist[:7], nreps, alpha, sigma, c)
    filename = 'stats_sigma_0_{}.pkl'.format(str(sigma)[2:])
    with open(filename, 'wb') as fn:
        pickle.dump((num_triang, mean_triang, clust_coeff, num_nodes, num_edges, mean_deg), fn)<jupyter_output>================== sigma: 0.9 =============================
Finished rep  1 with K:    100 nt:   15996  mt:   26.35 cc: 0.96 nv:    607 ne:    2392 deg: 7.88
Finished rep  1 with K:    316 nt:   58644  mt:   36.11 cc: 0.94 nv:   1624 ne:    7823 deg: 9.63
Finished rep  1 with K:   1000 nt:  168759  mt:   36.43 cc: 0.93 nv:   4632 ne:   22634 deg: 9.77
Finished rep  1 with K:   3162 nt:  500601  mt:   38.25 cc: 0.93 nv:  13089 ne:   65336 deg: 9.98
Finished rep  1 with K:  10000 nt: 2429361  mt:   66.35 cc: 0.94 nv:  36613 ne:  220045 deg: 12.02
{'fraction_non_alphanumeric': 0.20570948782535683, 'fraction_numerical': 0.1486146095717884, 'mean_word_length': 3.4477611940298507, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '193181', 'license': 'MIT', 'n_tokens_mistral': 598, 'n_tokens_neox': 480, 'n_words': 147, 'path': 'experiments/triangles/triangles_assymptotics.ipynb', 'repo_name': 'mauriciogtec/random-clique-covers', 'size': '1191'}