<jupyter_start><jupyter_text>PPI Model Demo NotebookThis short notebook shows how to import and use the model_fit function, using fully simulated data as an example. Please refer to the Readme for more information.<jupyter_code># This is all you need to get started using the model.
from model import model_fit
# More info is in the Readme file 
help(model_fit)
# Try running the model on some fully simulated test data
import numpy as np
import pandas as pd
import pprint

test_data = np.array(pd.read_csv('./test_data.csv', delimiter=',', header=None))
model = model_fit(test_data)

print("This dictionary contains the parameters of the model for an individual animal: \n")
pprint.pprint(model)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.06887052341597796, 'fraction_numerical': 0.0, 'mean_word_length': 5.609090909090909, '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': '192462', 'license': 'MIT', 'n_tokens_mistral': 215, 'n_tokens_neox': 210, 'n_words': 93, 'path': 'ppi_model_demo.ipynb', 'repo_name': 'angevineMiller/ppi_model', 'size': '726'}