<jupyter_start><jupyter_text>Initial research on example matrices structuresA scratch pad for initial structuring ideas, and using the first version of exmats.<jupyter_code>import pandas as pd
import numpy as np
df = pd.DataFrame(columns=['a', 'mat'])
#df = df.append(pd.Series({'mat':np.identity(2)}, name='bill'), )
df.loc['bill']=['what', np.identity(2)]
m=df.iloc[0]['mat']
m[0,0]
?str.
df.loc['bill']
from pyanp.exmats import SUPERMATRIX_EXS, supermatrix_ex, matrix_matching
supermatrix_ex('4x4ex1')
[('b' in x) for x in SUPERMATRIX_EXS['keywords']]
SUPERMATRIX_EXS
matrix_matching(keywords=['full'])
supermatrix_matching(description='staNdardg')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15565345080763582, 'fraction_numerical': 0.011747430249632892, 'mean_word_length': 8.884057971014492, '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': '639804', 'license': 'MIT', 'n_tokens_mistral': 263, 'n_tokens_neox': 251, 'n_words': 55, 'path': 'scrap/ScratchPadForExmatsModule.ipynb', 'repo_name': 'georg-cantor/pyanp', 'size': '681'}