<jupyter_start><jupyter_text>Running the example Now we are going to execute the code using the csvsample.csv file<jupyter_code>sig.sigProfilerExtractor("csv", "FirstSigs", "data/DNAStyleFrequencies.csv", totalIterations=5, gpu=False)<jupyter_output>************** Reported Current Memory Use: 0.64 GB *****************

Normalization Cutoff is : 75
Extracting signature 1 for mutation type 96
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Time taken to collect 5 iterations for 1 signatures is 0.33 seconds
Optimization time is 0.15107488632202148 seconds
The reconstruction error is 0.3996, average process stability is 1.0 and 
the minimum process stability is 1.0 for 1 signatures


Extracting signature 2 for mutation type 96
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{'fraction_non_alphanumeric': 0.08532695374800638, 'fraction_numerical': 0.049441786283891544, 'mean_word_length': 4.432900432900433, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, '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': '42675', 'license': 'Apache-2.0', 'n_tokens_mistral': 397, 'n_tokens_neox': 324, 'n_words': 159, 'path': 'GoodSignatureResults/Nice Signatures/DNA-Style Run (100 patients)/FirstRun.ipynb', 'repo_name': 'shefaliqamar/HIVMutationSignatures', 'size': '1254'}