<jupyter_start><jupyter_text>With an equal number of origins and destinations (n=16)<jupyter_code>origins = ps.weights.lat2W(4,4)
dests = ps.weights.lat2W(4,4)
origins.n
dests.n
ODw = ODW(origins, dests)
print ODw.n, 16*16
ODw.full()[0].shape<jupyter_output><empty_output><jupyter_text>With non-equal number of origins (n=9) and destinations (m=25)<jupyter_code>origins = ps.weights.lat2W(3,3)
dests = ps.weights.lat2W(5,5)
origins.n
dests.n
ODw = ODW(origins, dests)
print ODw.n, 9*25
ODw.full()[0].shape<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15327102803738318, 'fraction_numerical': 0.048598130841121495, 'mean_word_length': 7.121212121212121, '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': '76925', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 254, 'n_tokens_neox': 238, 'n_words': 41, 'path': 'pysal/contrib/spint/notebooks/ODW_example.ipynb', 'repo_name': 'Aniq55/pysal', 'size': '535'}