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| import os | |
| import re | |
| from sklearn.utils.validation import _check_feature_names_in | |
| def _csv_filename_to_pkl_filename(csv_filename: str) -> str: | |
| if os.path.splitext(csv_filename)[1] == ".pkl": | |
| return csv_filename | |
| # Assume that the csv filename is of the form "foo.csv" | |
| assert str(csv_filename).endswith(".csv") | |
| dirname = str(os.path.dirname(csv_filename)) | |
| basename = str(os.path.basename(csv_filename)) | |
| base = str(os.path.splitext(basename)[0]) | |
| pkl_basename = base + ".pkl" | |
| return os.path.join(dirname, pkl_basename) | |
| _regexp_im = re.compile(r"\b(\d+\.\d+)im\b") | |
| _regexp_im_sci = re.compile(r"\b(\d+\.\d+)[eEfF]([+-]?\d+)im\b") | |
| _regexp_sci = re.compile(r"\b(\d+\.\d+)[eEfF]([+-]?\d+)\b") | |
| _apply_regexp_im = lambda x: _regexp_im.sub(r"\1j", x) | |
| _apply_regexp_im_sci = lambda x: _regexp_im_sci.sub(r"\1e\2j", x) | |
| _apply_regexp_sci = lambda x: _regexp_sci.sub(r"\1e\2", x) | |
| def _preprocess_julia_floats(s: str) -> str: | |
| if isinstance(s, str): | |
| s = _apply_regexp_im(s) | |
| s = _apply_regexp_im_sci(s) | |
| s = _apply_regexp_sci(s) | |
| return s | |
| def _safe_check_feature_names_in(self, variable_names, generate_names=True): | |
| """_check_feature_names_in with compat for old versions.""" | |
| try: | |
| return _check_feature_names_in( | |
| self, variable_names, generate_names=generate_names | |
| ) | |
| except TypeError: | |
| return _check_feature_names_in(self, variable_names) | |
| def _subscriptify(i: int) -> str: | |
| """Converts integer to subscript text form. | |
| For example, 123 -> "βββ". | |
| """ | |
| return "".join([chr(0x2080 + int(c)) for c in str(i)]) | |