<commit_before>import os
import logging
import socket

from dessn.blind.blind import blind_om, blind_w
from dessn.framework.fitter import Fitter
from dessn.framework.models.approx_model import ApproximateModelW
from dessn.framework.simulations.snana import SNANASimulation


if __name__ == "__main__":
    logging.basicConfig(level=logging.DEBUG, format="[%(funcName)20s()] %(message)s")
    plot_dir = os.path.dirname(os.path.abspath(__file__)) + "/plots/%s/" % os.path.basename(__file__)[:-3]
    dir_name = plot_dir + "output/"
    pfn = plot_dir + os.path.basename(__file__)[:-3]

    file = os.path.abspath(__file__)

    if not os.path.exists(dir_name):
        os.makedirs(dir_name)

    models = [
        ApproximateModelW(prior=True, statonly=True, lock_systematics=True, lock_disp=True, lock_pop=True),
        ApproximateModelW(prior=True, statonly=True, lock_systematics=True, lock_disp=False, lock_pop=True),
        ApproximateModelW(prior=True, statonly=True, lock_systematics=True, lock_disp=False, lock_pop=False),
        ApproximateModelW(prior=True, statonly=True, lock_systematics=False, lock_disp=False, lock_pop=False),
        ApproximateModelW(prior=True, statonly=False, lock_systematics=False, lock_disp=False, lock_pop=False)
    ]
    # Turn off mass and skewness for easy test

    ndes = 204
    nlowz = 138
    simulations = [
            [SNANASimulation(ndes, "DES3YR_DES_NOMINAL"), SNANASimulation(nlowz, "DES3YR_LOWZ_NOMINAL")],
    ]
    fitter = Fitter(dir_name)

    # data = model[1].get_data(simulations[0], 0)  # For testing<commit_msg>Adding semicolons of happiness<commit_after>import os
import logging
import socket

from dessn.blind.blind import blind_om, blind_w
from dessn.framework.fitter import Fitter
from dessn.framework.models.approx_model import ApproximateModelW
from dessn.framework.simulations.snana import SNANASimulation


if __name__ == "__main__":
    logging.basicConfig(level=logging.DEBUG, format="[%(funcName)20s()] %(message)s")
    plot_dir = os.path.dirname(os.path.abspath(__file__)) + "/plots/%s/" % os.path.basename(__file__)[:-3]
    dir_name = plot_dir + "output/"
    pfn = plot_dir + os.path.basename(__file__)[:-3]

    file = os.path.abspath(__file__)

    if not os.path.exists(dir_name):
        try:
            os.makedirs(dir_name)
        except FileExistsError:
            pass

    models = [
        ApproximateModelW(prior=True, statonly=True, lock_systematics=True, lock_disp=True, lock_pop=True),
        ApproximateModelW(prior=True, statonly=True, lock_systematics=True, lock_disp=False, lock_pop=True),
        ApproximateModelW(prior=True, statonly=True, lock_systematics=True, lock_disp=False, lock_pop=False),
        ApproximateModelW(prior=True, statonly=True, lock_systematics=False, lock_disp=False, lock_pop=False),
        ApproximateModelW(prior=True, statonly=False, lock_systematics=False, lock_disp=False, lock_pop=False)
    ]
    # Turn off mass and skewness for easy test

    ndes = 204
    nlowz = 138
    simulations = [
            [SNANASimulation(ndes, "DES3YR_DES_NOMINAL"), SNANASimulation(nlowz, "DES3YR_LOWZ_NOMINAL")],
    ]
    fitter = Fitter(dir_name)

    # data = model[1].get_data(simulations[0], 0)  # For testing
{'fraction_non_alphanumeric': 0.11601357605677261, 'fraction_numerical': 0.009256402344955261, 'mean_word_length': 4.457912457912458, 'pattern_counts': {'":': 2, '<': 3, '<?xml version=': 0, '>': 3, '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}}
{'dir': 'git-commits-cleaned', 'id': '234946', 'n_tokens_mistral': 1173, 'n_tokens_neox': 1103, 'n_words': 196}