<jupyter_start><jupyter_text>Running SEN3R with a single WFR image<jupyter_code># TESTING SINGLE IMAGE PROCESSING
args = {}

args['input'] = Path('D:/S3/sen3r_wfr_test/S3A_OL_2_WFR____20160522T134229_20160522T134429_20171031T210832_0119_004_238______MR1_R_NT_002.SEN3')
args['out'] = Path('D:/sen3r_out/')
args['roi'] = Path('D:/A1_JM/areas/paper_areas/14100000_manacapuru.geojson')
args['product'] = 'wfr'
args
s3r = Core(args)
%%time
band_data, img_data, doneList = s3r.build_single_file()<jupyter_output>INFO:D:\sen3r_out\sen3r_20211101T155557.log:Searching for WFR file inside: D:\S3\sen3r_wfr_test\S3A_OL_2_WFR____20160522T134229_20160522T134429_20171031T210832_0119_004_238______MR1_R_NT_002.SEN3
INFO:D:\sen3r_out\sen3r_20211101T155557.log:Generating ancillary data folder: D:\sen3r_out\CSV_N1
INFO:D:\sen3r_out\sen3r_20211101T155557.log:Attempting to extract geometries from: D:\A1_JM\areas\paper_areas\14100000_manacapuru.geojson
INFO:D:\sen3r_out\sen3r_20211101T155557.log:4428 - Initializing geometries for: S3A_OL_2_WFR____20160522T134229_20160522T134429_20171031T210832_0119_004_238______MR1_R_NT_002
INFO:D:\sen3r_out\sen3r_20211101T155557.log:Converting the polygon coordinates into a matrix x,y poly...
INFO:D:\sen3r_out\sen3r_20211101T155557.log:Saving DF at : D:\sen3r_out\CSV_N1\S3A_OL_2_WFR____20160522T134229_20160522T134429_20171031T210832_0119_004_238______MR1_R_NT_002.csv<jupyter_text>For a folder of WFR images<jupyter_code>mt_args = {}

mt_args['input'] = Path('D:/S3/sen3r_wfr_test/')
mt_args['out'] = Path('D:/sen3r_out/')
mt_args['roi'] = Path('D:/A1_JM/areas/paper_areas/14100000_manacapuru.geojson')
mt_args['product'] = 'wfr'
mt_args

s3r = Core(mt_args)
%%time
doneList = s3r.build_intermediary_files()
doneList<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1143661971830986, 'fraction_numerical': 0.21295774647887325, 'mean_word_length': 9.895705521472392, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '483974', 'license': 'MIT', 'n_tokens_mistral': 1043, 'n_tokens_neox': 824, 'n_words': 82, 'path': 'SEN3R_Examples.ipynb', 'repo_name': 'daviguima/sen3r', 'size': '1775'}