<jupyter_start><jupyter_text>What if not all people stated in whom they are interested?<jupyter_code>import numpy as np
import sys
import os
from pathlib import Path
import matplotlib.pyplot as plt

NOTEBOOK_DIR = os.getcwd()
PROJECT_DIR = str(Path(NOTEBOOK_DIR).resolve().parent)

sys.path.insert(1, PROJECT_DIR+"/tindar-engine")
PROJECT_DIR

import tindar

%load_ext autoreload
%autoreload 2
n = 10
connectedness = 4

tindar_problem = tindar.TindarGenerator(
    n, connectedness, nan_probability=None
)
love_matrix = tindar_problem.love_matrix
love_matrix
nan_probability = 0.3
nan_indicator = np.random.binomial(
    n=1, p=nan_probability, size=love_matrix.shape,
).astype(bool)
nan_indicator
love_matrix[nan_indicator] = np.nan
love_matrix<jupyter_output><empty_output><jupyter_text>After implementing this functionality in src code, we check:<jupyter_code>n = 10
connectedness = 4
nan_probability = 0.3

tindar_problem_new = tindar.TindarGenerator(
    n, connectedness, nan_probability
)
tindar_problem_new.love_matrix<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08522727272727272, 'fraction_numerical': 0.01231060606060606, 'mean_word_length': 6.888059701492537, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '551745', 'license': 'MIT', 'n_tokens_mistral': 403, 'n_tokens_neox': 386, 'n_words': 82, 'path': 'notebooks/4. Add_missing_love_info.ipynb', 'repo_name': 'lennart-damen/tindar', 'size': '1056'}