148 lines
6.7 KiB
Python
148 lines
6.7 KiB
Python
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import random, math
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from functions import insert_linebreaks, insert_text_block, convert_to_figlet_font, insert_symbol_background
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zones = {
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'en' : {
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'writers' : {
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'subjects' : ['data workers', 'many authors', 'every human being who has access to the internet', 'we', 'we', 'we', 'some neural networks', 'human editors', 'poets, playwrights or novelists'],
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'actions' : ['work', 'write', 'interacts', 'chat, write, click, like and share', 'leave our data', 'find ourselves writing in Python', 'write', 'assist', 'assist'],
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'verb' : 'write'
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},
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'oracles' : {
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'subjects' : ['machine learning', 'models', 'models', 'they', 'they', 'information extraction', 'text classification'],
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'actions' : ['analyses and predicts', 'have learned', 'are used', 'influence', 'have their say', 'recognizes', 'detects'],
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'verb' : 'predict'
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},
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'cleaners' : {
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'subjects' : ['we', 'we', 'human work', 'poorly-paid freelancers', 'volunteers', 'whoever'],
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'actions' : ['helped', 'cleaned', 'is needed', 'carry out', 'do fantastic work', 'cleans up text'],
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'verb' : 'clean'
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},
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'informants' : {
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'subjects' : ['each dataset', 'datasets', 'some datasets', 'models that require supervision', 'models', 'some of the datasets', 'humans'],
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'actions' : ['collects different information about the world', 'are imbued with collector\'s bias', 'combine machinic logic with human logic', 'multiply the subjectivities', 'propagate what they\'ve been taught', 'pass as default in the machine learning field', 'guide machines'],
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'verb' : 'inform'
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},
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'readers' : {
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'subjects' : ['a computer', 'all models', 'some models', 'some models'],
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'actions' : ['understands', 'translate', 'count', 'replace'],
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'verb' : 'read'
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},
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'learners' : {
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'subjects' : ['learners', 'learners', 'learners', 'classifiers', 'learners', 'learners'],
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'actions' : ['are pattern finders', 'are crawling through data', 'generate some kind of specific \'grammar\'', 'generate, evaluate and readjust', 'understand and reveal patterns', 'don\'t always distuinguish well which patterns should be repeated'],
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'verb' : 'learn'
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}
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},
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'fr' : {
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'écrivains' : {
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'subjects' : ['data workers', 'many authors', 'every human being who has access to the internet', 'we', 'we', 'we', 'some neural networks', 'human editors', 'poets, playwrights or novelists'],
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'actions' : ['work', 'write', 'interacts', 'chat, write, click, like and share', 'leave our data', 'find ourselves writing in Python', 'write', 'assist', 'assist'],
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'subject' : 'writers',
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'verb' : 'write'
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},
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'oracles' : {
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'subjects' : ['machine learning', 'models', 'models', 'they', 'they', 'information extraction', 'text classification'],
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'actions' : ['analyses and predicts', 'have learned', 'are used', 'influence', 'have their say', 'recognizes', 'detects'],
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'subject' : 'oracles',
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'verb' : 'predict'
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},
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'nettoyeurs' : {
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'subjects' : ['we', 'we', 'human work', 'poorly-paid freelancers', 'volunteers', 'whoever'],
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'actions' : ['helped', 'cleaned', 'is needed', 'carry out', 'do fantastic work', 'cleans up text'],
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'subject' : 'cleaners',
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'verb' : 'clean'
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},
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'informateurs' : {
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'subjects' : ['each dataset', 'datasets', 'some datasets', 'models that require supervision', 'models', 'some of the datasets', 'humans'],
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'actions' : ['collects different information about the world', 'are imbued with collector\'s bias', 'combine machinic logic with human logic', 'multiply the subjectivities', 'propagate what they\'ve been taught', 'pass as default in the machine learning field', 'guide machines'],
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'subject' : 'informants',
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'verb' : 'inform'
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},
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'lecteurs' : {
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'subjects' : ['a computer', 'all models', 'some models', 'some models'],
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'actions' : ['understands', 'translate', 'count', 'replace'],
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'subject' : 'readers',
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'verb' : 'read'
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},
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'apprenants' : {
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'subjects' : ['learners', 'learners', 'learners', 'classifiers', 'learners', 'learners'],
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'actions' : ['are pattern finders', 'are crawling through data', 'generate some kind of specific \'grammar\'', 'generate, evaluate and readjust', 'understand and reveal patterns', 'don\'t always distuinguish well which patterns should be repeated'],
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'subject' : 'learners',
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'verb' : 'learn'
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}
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}
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}
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def create_zone_backcover(zone, language, symbols):
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print('... Creating zone_backcover')
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symbols = symbols.replace('\n', '')
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if language == 'fr':
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zone = zones[language][zone.lower()]['subject']
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language = 'en'
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subjects = zones[language][zone.lower()]['subjects']
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actions = zones[language][zone.lower()]['actions']
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subject_figlets = [convert_to_figlet_font(subject, 18, font='digital', alignment='right') for subject in subjects]
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action_figlets = [convert_to_figlet_font(action, 18, font='digital', alignment='left') for action in actions]
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# Sync the left and right column
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# Count the length of the lines for each subject and action
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subjects_num_of_lines = [int(len(subject.split('\n')) / 3) for subject in subject_figlets]
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actions_num_of_lines = [int(len(action.split('\n')) / 3) for action in action_figlets]
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# Apply the counting, append extra lines
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subjects_string = ''
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for s, subject in enumerate(subjects):
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if actions_num_of_lines[s] == 1:
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actions_num_of_lines[s] = 0
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subjects_string += subject_figlets[s] + ('\n\n\n' * (actions_num_of_lines[s] - 1))
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# print('subject', actions_num_of_lines[s], subject)
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actions_string = ''
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for a, action in enumerate(actions):
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if subjects_num_of_lines[a] == 1:
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subjects_num_of_lines[a] = 0
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actions_string += ('\n\n\n' * (subjects_num_of_lines[a] - 1)) + action_figlets[a]
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# print(' action', subjects_num_of_lines[a], action)
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left = insert_linebreaks(subjects_string, 56, type='wrap')
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right = insert_linebreaks(actions_string, 56, type='wrap')
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two_columns = insert_text_block(left, right, 57, 55)
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page = ''
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# Append the header
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subject_left = convert_to_figlet_font(zone.lower(), 18, font='digital', alignment='right')+'\n'
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subject_left = insert_linebreaks(subject_left, 56, type='wrap')
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action_right = convert_to_figlet_font(zones[language][zone.lower()]['verb'], 18, font='digital', alignment='left')+'\n'
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action_right = insert_linebreaks(action_right, 56, type='wrap')
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page += insert_text_block(subject_left, action_right, 57, 55)
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page += '\n'
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# Insert the two columns
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page += two_columns + '\n'
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# Fill the remaining empty lines on the page
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current_page_lines = len(page.split('\n'))
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if current_page_lines < 70:
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for x in range(current_page_lines, 69):
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print(x)
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for y in range(1, 110):
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print(y)
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page += ' '
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page += '\n'
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# Apply symbols background
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multiplier = 500
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page = insert_symbol_background(page, 110, symbols, multiplier)
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print('>>> current_page_lines:', len(page.split('\n')))
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return page
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# print(create_zone_backcover('writers'))
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