<jupyter_start><jupyter_text>Get all INTER interactions between the chromosomes<jupyter_code>cell_line = 'IMR90'
# cell_line = 'GM12878'

for main_chromosome in chromosome_list:
    print(f'Comparing Chromosome {main_chromosome} to all others')
    
    for chromosome_name in chromosome_list:
        print(f'currently to {chromosome_name}')
        
        if main_chromosome == 'X':
            pass
        
        if chromosome_name == 'X':
            if cell_line == 'GM12878':
                cooReader = gmlib.importer.CooMatrixHandler(f'/data/analysis/ag-reils/ag-reils-shared/Hi-C/meeteu/www.lcqb.upmc.fr/meetu/dataforstudent/HiC/GM12878/100kb_resolution_interchromosomal/chr{main_chromosome}_{chromosome_name}_100kb.RAWobserved', mapType = 'inter')
                cooReader.save_ccmaps(f'./cmap_files/inter/chr{main_chromosome}/cmap_chr{main_chromosome}_with_{chromosome_name}.ccmap', xlabels=f'{main_chromosome}', ylabels=f'{chromosome_name}')
            if cell_line == 'IMR90':
                cooReader = gmlib.importer.CooMatrixHandler(f'/data/analysis/ag-reils/ag-reils-shared/Hi-C/meeteu/www.lcqb.upmc.fr/meetu/dataforstudent/HiC/IMR90/100kb_resolution_interchromosomal/chr{main_chromosome}_chr{chromosome_name}/MAPQGE30/chr{main_chromosome}_{chromosome_name}_100kb.RAWobserved', mapType = 'inter')
                cooReader.save_ccmaps(f'./cmap_files/IMR90/inter/chr{main_chromosome}/cmap_chr{main_chromosome}_with_{chromosome_name}.ccmap', xlabels=f'{main_chromosome}', ylabels=f'{chromosome_name}')
            del cooReader
            
        elif chromosome_name == main_chromosome or chromosome_name < main_chromosome:
            pass
        
        else:
            if cell_line == 'GM12878':
                cooReader = gmlib.importer.CooMatrixHandler(f'/data/analysis/ag-reils/ag-reils-shared/Hi-C/meeteu/www.lcqb.upmc.fr/meetu/dataforstudent/HiC/GM12878/100kb_resolution_interchromosomal/chr{main_chromosome}_{chromosome_name}_100kb.RAWobserved', mapType = 'inter')
                cooReader.save_ccmaps(f'./cmap_files/inter/chr{main_chromosome}/cmap_chr{main_chromosome}_with_{chromosome_name}.ccmap', xlabels=f'{main_chromosome}', ylabels=f'{chromosome_name}')
           
            if cell_line == 'IMR90':
                cooReader = gmlib.importer.CooMatrixHandler(f'/data/analysis/ag-reils/ag-reils-shared/Hi-C/meeteu/www.lcqb.upmc.fr/meetu/dataforstudent/HiC/IMR90/100kb_resolution_interchromosomal/chr{main_chromosome}_chr{chromosome_name}/MAPQGE30/chr{main_chromosome}_{chromosome_name}_100kb.RAWobserved', mapType = 'inter')
                cooReader.save_ccmaps(f'./cmap_files/IMR90/inter/chr{main_chromosome}/cmap_chr{main_chromosome}_with_{chromosome_name}.ccmap', xlabels=f'{main_chromosome}', ylabels=f'{chromosome_name}')
            del cooReader<jupyter_output><empty_output><jupyter_text>Get INTRA interactions<jupyter_code>for chromosome in chromosome_list:
    if cell_line == 'IMR90':
        cooReader = gmlib.importer.CooMatrixHandler(f'/data/analysis/ag-reils/ag-reils-shared/Hi-C/meeteu/www.lcqb.upmc.fr/meetu/dataforstudent/HiC/IMR90/25kb_resolution_intrachromosomal/chr{chromosome}/MAPQGE30/chr{chromosome}_25kb.RAWobserved', mapType = 'intra')
        cooReader.save_ccmaps(f'./cmap_files/25kb/IMR90/intra/cmap_{chromosome}.ccmap', xlabels=f'{chromosome}', ylabels=f'{chromosome}')
    if cell_line == 'GM12878':
        cooReader = gmlib.importer.CooMatrixHandler(f'/data/analysis/ag-reils/ag-reils-shared/Hi-C/meeteu/www.lcqb.upmc.fr/meetu/dataforstudent/HiC/GM12878/25kb_resolution_intrachromosomal/chr{chromosome}_25kb.RAWobserved', mapType = 'intra')
        cooReader.save_ccmaps(f'./cmap_files/25kb/GM12878/intra/cmap_{chromosome}.ccmap', xlabels=f'{chromosome}', ylabels=f'{chromosome}')
    del cooReader<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12667191188040913, 'fraction_numerical': 0.02675059008654603, 'mean_word_length': 4.433048433048433, 'pattern_counts': {'":': 0, '<': 10, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 6, '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': '412622', 'license': 'MIT', 'n_tokens_mistral': 1598, 'n_tokens_neox': 1368, 'n_words': 113, 'path': 'tad_detection/preprocessing/ccmap_generator.ipynb', 'repo_name': 'meet-eu-21/Team-HA1', 'size': '3813'}