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| from langcodes import Language, standardize_tag | |
| import pandas as pd | |
| import os | |
| import re | |
| flores_dir = "data/floresp-v2.0-rc.3/dev" | |
| def flores_sentences(language): | |
| return open(f"{flores_dir}/dev.{language.flores_path}").readlines() | |
| def aggregate_flores_paths(flores_paths): | |
| # takes a list of paths from the same language but different scripts | |
| # returns the one with the largest writing population | |
| if len(flores_paths) == 1: | |
| return flores_paths.values[0] | |
| populations = [ | |
| Language.get(standardize_tag(x, macro=True)).writing_population() | |
| for x in flores_paths.values | |
| ] | |
| return flores_paths.values[populations.index(max(populations))] | |
| flores = pd.DataFrame( | |
| [f.split(".")[1] for f in os.listdir(flores_dir)], | |
| columns=["flores_path"], | |
| ) | |
| flores["bcp_47"] = flores["flores_path"].apply( | |
| lambda x: standardize_tag(x, macro=True), | |
| ) | |
| # ignore script (language is language) | |
| flores["bcp_47"] = flores["bcp_47"].apply( | |
| lambda x: re.sub(r"-[A-Z][a-z]+$", "", x) | |
| ) | |
| flores = ( | |
| flores.groupby("bcp_47") | |
| .agg({"flores_path": aggregate_flores_paths}) | |
| .reset_index() | |
| ) | |