[FEAT] Feat Include Undamaged Node Classification #98
@@ -73,26 +73,6 @@ class DataProcessor:
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else:
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else:
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self.data = self._load_all_data()
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self.data = self._load_all_data()
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def _extract_column_names(self, file_path: str) -> List[str]:
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"""
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Extracts column names from the header of the given file.
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Assumes the 6th line contains column names.
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:param file_path: Path to the data file.
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:return: List of column names.
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"""
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with open(file_path, "r") as f:
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header_lines = [next(f) for _ in range(12)]
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# Extract column names from the 6th line
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channel_line = header_lines[10].strip()
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tokens = re.findall(r'"([^"]+)"', channel_line)
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if not channel_line.startswith('"'):
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first_token = channel_line.split()[0]
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tokens = [first_token] + tokens
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return tokens # Prepend 'Time' column if applicable
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def _load_dataframe(self, file_path: str) -> OriginalSingleDamageScenario:
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def _load_dataframe(self, file_path: str) -> OriginalSingleDamageScenario:
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"""
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"""
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Loads a single data file into a pandas DataFrame.
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Loads a single data file into a pandas DataFrame.
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@@ -100,11 +80,7 @@ class DataProcessor:
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:param file_path: Path to the data file.
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:param file_path: Path to the data file.
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:return: DataFrame containing the numerical data.
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:return: DataFrame containing the numerical data.
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"""
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"""
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col_names = self._extract_column_names(file_path)
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df = pd.read_csv(file_path, delim_whitespace=True, skiprows=10, header=0, memory_map=True)
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df = pd.read_csv(
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file_path, delim_whitespace=True, skiprows=11, header=None, memory_map=True
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)
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df.columns = col_names
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return df
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return df
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def _load_all_data(self) -> GroupDataset:
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def _load_all_data(self) -> GroupDataset:
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