<jupyter_start><jupyter_text>Download data for sea ice tutorial:  set email and uid for earthdata:<jupyter_code>earthdata_email=''
earthdata_uid=''<jupyter_output><empty_output><jupyter_text>set folder path for downloaded data:<jupyter_code>data_home='/home/jovyan/data'
if not os.path.isdir(data_home):
    os.mkdir(data_home)<jupyter_output><empty_output><jupyter_text>download granules required for tutorial:<jupyter_code># set DOWNLOAD to true if you're ready to download the data:
DOWNLOAD=False
    
requests=[
    {   'short_name' : 'ATL03',
        'spatial_extent' :[153.6, 79.98, 153.61, 79.99],
        'date_range' : ['2019-02-06','2019-02-06']},
    {   'short_name' : 'ATL03',
        'spatial_extent' :[-38.8,64.63,-38.7,64.64],
        'date_range' : ['2019-04-30','2019-04-30']},
    {   'short_name' : 'ATL03',
        'spatial_extent' :[99.5, 76.4, 99.6, 76.5],
        'date_range' : ['2019-03-24','2019-03-24']},
    {   'short_name' : 'ATL03',
        'spatial_extent' :[-168.65,73.74,-168.64,73.75],
        'date_range' : ['2018-11-15','2018-11-15']},
    {   'short_name' : 'ATL07',
        'spatial_extent' :[-38.8,64.63,-38.7,64.64],
        'date_range' : ['2019-04-30','2019-04-30']},
    {   'short_name' : 'ATL07',
        'spatial_extent' :[99.5, 76.4, 99.6, 76.5],
        'date_range' : ['2019-03-24','2019-03-24']},
    {   'short_name' : 'ATL07',
        'spatial_extent' :[-168.65,73.74,-168.64,73.75],
        'date_range' : ['2018-11-15','2018-11-15']},
    {   'short_name' : 'ATL10',
        'spatial_extent' :[-168.65,73.74,-168.64,73.75],
        'date_range' : ['2018-11-15','2018-11-15']}]
for req in requests:
    #### Download this data: (uncomment and run)
    region_a = ipd.Icesat2Data(req['short_name'], req['spatial_extent'], req['date_range'])
    if DOWNLOAD:
        region_a.earthdata_login(earthdata_uid, earthdata_email)
        region_a.download_granules(data_home,subset=False)
#     print(region_a.dataset)
#     print(region_a.dates)
#     print(region_a.start_time)
#     print(region_a.end_time)
#     print(region_a.dataset_version)
#     print(region_a.spatial_extent)
#     region_a.visualize_spatial_extent()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.18948322756119673, 'fraction_numerical': 0.1214868540344515, 'mean_word_length': 3.5318275154004106, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 6, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '422181', 'license': 'MIT', 'n_tokens_mistral': 1077, 'n_tokens_neox': 904, 'n_words': 122, 'path': '10.Sea_Ice_Applications/DataAccess.ipynb', 'repo_name': 'SmithB/2020_ICESat-2_Hackweek_Tutorials', 'size': '2206'}