def data_received(keywords_freq_files, keywords_stats_files):
if keywords_freq_files:
text_test_significance = settings['generation_settings']['test_significance']
text_measure_effect_size = settings['generation_settings']['measure_effect_size']
(text_test_stat,
text_p_value,
text_bayes_factor) = main.settings_global['tests_significance']['keywords'][text_test_significance]['cols']
text_effect_size = main.settings_global['measures_effect_size']['keywords'][text_measure_effect_size]['col']
if settings['fig_settings']['use_data'] == main.tr('Frequency'):
wordless_fig_freq.wordless_fig_freq_ref(main, keywords_freq_files,
ref_file = ref_file,
settings = settings['fig_settings'],
label_x = main.tr('Keywords'))
else:
if settings['fig_settings']['use_data'] == text_test_stat:
keywords_stat_files = {keyword: numpy.array(stats_files)[:, 0]
for keyword, stats_files in keywords_stats_files.items()}
label_y = text_test_stat
elif settings['fig_settings']['use_data'] == text_p_value:
keywords_stat_files = {keyword: numpy.array(stats_files)[:, 1]
for keyword, stats_files in keywords_stats_files.items()}
label_y = text_p_value
elif settings['fig_settings']['use_data'] == text_bayes_factor:
keywords_stat_files = {keyword: numpy.array(stats_files)[:, 2]
for keyword, stats_files in keywords_stats_files.items()}
label_y = text_bayes_factor
elif settings['fig_settings']['use_data'] == text_effect_size:
keywords_stat_files = {keyword: numpy.array(stats_files)[:, 3]
for keyword, stats_files in keywords_stats_files.items()}
label_y = text_effect_size
wordless_fig_stat.wordless_fig_stat_ref(main, keywords_stat_files,
ref_file = ref_file,
settings = settings['fig_settings'],
label_y = label_y)
wordless_msg.wordless_msg_generate_fig_success(main)
else:
wordless_msg_box.wordless_msg_box_no_results(main)
wordless_msg.wordless_msg_generate_fig_error(main)
dialog_progress.accept()
if keywords_freq_files:
wordless_fig.show_fig()
def data_received(tokens_freq_files, tokens_stats_files):
if tokens_freq_files:
measure_dispersion = settings['generation_settings'][
'measure_dispersion']
measure_adjusted_freq = settings['generation_settings'][
'measure_adjusted_freq']
col_dispersion = main.settings_global['measures_dispersion'][
measure_dispersion]['col']
col_adjusted_freq = main.settings_global['measures_adjusted_freq'][
measure_adjusted_freq]['col']
if settings['fig_settings']['use_data'] == main.tr('Frequency'):
wordless_fig_freq.wordless_fig_freq(
main,
tokens_freq_files,
settings=settings['fig_settings'],
label_x=main.tr('Tokens'))
else:
if settings['fig_settings']['use_data'] == col_dispersion:
tokens_stat_files = {
token: numpy.array(stats_files)[:, 0]
for token, stats_files in tokens_stats_files.items()
}
label_y = col_dispersion
elif settings['fig_settings']['use_data'] == col_adjusted_freq:
tokens_stat_files = {
token: numpy.array(stats_files)[:, 1]
for token, stats_files in tokens_stats_files.items()
}
label_y = col_adjusted_freq
wordless_fig_stat.wordless_fig_stat(
main,
tokens_stat_files,
settings=settings['fig_settings'],
label_x=main.tr('Tokens'),
label_y=label_y)
wordless_msg.wordless_msg_generate_fig_success(main)
else:
wordless_msg_box.wordless_msg_box_no_results(main)
wordless_msg.wordless_msg_generate_fig_error(main)
dialog_progress.accept()
if tokens_freq_files:
wordless_fig.show_fig()