<jupyter_start><jupyter_text>toy model, test the motion of an active swimmer in bulk with very large later rotation.<jupyter_code>from shutil import copyfile

pickle_name = 'ecoC01B05_baseFlow'
mdf_pickle_name = 'ecoC01B05_baseFlow_laterRot'

with open('%s.pickle' % pickle_name, 'rb') as handle:
    pickle_dict = pickle.load(handle)
display(np.vstack(pickle_dict['uw_Base_list'])[1:6, :3])
display(np.vstack(pickle_dict['uw_Base_list'])[1:6, 3:])
display(np.vstack(pickle_dict['uw_Base_list'])[9, :])

t1 = pickle_dict['uw_Base_list'].copy()
# for i0 in (0, 6, 7, 8, 9):
for i0 in (1, 2, 3, 4, 5, ):
    t1[i0] = np.zeros_like(t1[i0])

tfct = 10000
t1[9][:3] = 0
t1[9][3:5] = t1[9][3:5] * tfct 
display(np.vstack(t1)[1:6, :3])
display(np.vstack(t1)[9, :])

pickle_dict['uw_Base_list'] = t1
tname = '%s.pickle' % mdf_pickle_name
with open(tname, 'wb') as handle:
    pickle.dump(pickle_dict, handle, protocol=pickle.HIGHEST_PROTOCOL)
copyfile(tname, os.path.join(os.getcwd(), os.pardir, os.pardir, 'src', tname))
print('save table_data to %s' % tname)

t1[9][3:4] * tfct<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.17983651226158037, 'fraction_numerical': 0.05449591280653951, 'mean_word_length': 6.445945945945946, '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': '154360', 'license': 'MIT', 'n_tokens_mistral': 525, 'n_tokens_neox': 503, 'n_words': 92, 'path': 'head_Force/loop_table/baseFlow_ecoC01B05.ipynb', 'repo_name': 'pcmagic/stokes_flow', 'size': '1101'}