<jupyter_start><jupyter_text>We use iter_subplots to check the output:<jupyter_code>fig, axes = iter_subplots(1, 2, figsize=(7,3))
axes[0].iter_imshow(bf_cy3b, cmap='gray')
axes[1].iter_imshow(output[0],cmap='gray')
fig.display()
fig, axes = iter_subplots(1, 2, figsize=(7,3))
axes[0].iter_imshow(bf_egfp, cmap='gray')
axes[1].iter_imshow(output[1],cmap='gray')
fig.display()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.19012345679012346, 'fraction_numerical': 0.037037037037037035, 'mean_word_length': 11.6875, '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': '321333', 'license': 'MIT', 'n_tokens_mistral': 188, 'n_tokens_neox': 176, 'n_words': 24, 'path': 'figures/Figure_6/03_Applying_neural_networks.ipynb', 'repo_name': 'Jhsmit/ColiCoords-Paper', 'size': '405'}