<jupyter_start><jupyter_text>Isochrone Grid<jupyter_code>from berliner.utils import IsochroneGrid
ig = IsochroneGrid(isoc_lgage, isoc_mhini, isocs_ps1, model="mist")
isoc0 = ig.get_a_isoc(9,0)
isoc0
for _lgage in np.arange(6,10,0.05):
    isoc0 = ig.get_a_isoc(_lgage,0)
    plot(isoc0["log_Teff"],isoc0["log_g"],)
for _lgage in np.arange(6,10,0.05):
    isoc0 = ig.get_a_isoc(_lgage,0)
    plot(isoc0["EEP"],isoc0["log_g"],)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.16043956043956045, 'fraction_numerical': 0.054945054945054944, 'mean_word_length': 7.290909090909091, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '297943', 'license': 'MIT', 'n_tokens_mistral': 233, 'n_tokens_neox': 222, 'n_words': 27, 'path': 'notebook/how_to_read_mist_isochrones.ipynb', 'repo_name': 'hypergravity/berliner', 'size': '455'}