<jupyter_start><jupyter_text>check the plot w/o decimation<jupyter_code>def reject_outliers(velo, m=2):
    return velo[abs(velo - np.mean(velo)) < m * np.std(velo)]
reject
filt_velo = reject_outliers(velo)
plt.plot(filt_velo)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13671875, 'fraction_numerical': 0.00390625, 'mean_word_length': 7.862068965517241, 'pattern_counts': {'":': 0, '<': 6, '<?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': '419517', 'license': 'MIT', 'n_tokens_mistral': 116, 'n_tokens_neox': 111, 'n_words': 16, 'path': 'notebooks/tester.ipynb', 'repo_name': 'GergelyTuri/fiberphotometry', 'size': '256'}