[FEAT] Feat Include Undamaged Node Classification #98
@@ -103,9 +103,10 @@ def generate_df_tuples(total_dfs=30, group_size=5, prefix="zzzAD", ext="TXT", fi
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class DataProcessor:
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def __init__(self, file_index, cache_path: str = None, base_path: str = None):
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def __init__(self, file_index, cache_path: str = None, base_path: str = None, include_time: bool = False):
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self.file_index = file_index
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self.base_path = base_path
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self.include_time = include_time
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if cache_path:
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self.data = load(cache_path)
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else:
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@@ -115,6 +116,9 @@ class DataProcessor:
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for idxs, group in enumerate(self.file_index):
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for idx, tuple in enumerate(group):
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file_path = os.path.join(self.base_path, tuple[0]) # ('zzzAD1.TXT')
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if self.include_time:
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col_indices = [0] + tuple[1] # [1, 26] + [0] -> [0, 1, 26]
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else:
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col_indices = tuple[1] # [1, 26]
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try:
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# Read the CSV file
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@@ -272,30 +276,18 @@ class DataProcessor:
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:param output_dir: Directory to save the CSV files.
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:param file_prefix: Prefix for the output filenames.
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"""
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for group_idx, group in enumerate(self.data, start=0):
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for group_idx, group in enumerate(self.file_index, start=0):
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group_folder = os.path.join(output_dir, f"{file_prefix}_{group_idx}")
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os.makedirs(group_folder, exist_ok=True)
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for test_idx, df in enumerate(group, start=1):
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# Ensure columns are named uniquely if duplicated
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df = df.copy()
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df.columns = ["Time", "Real_0", "Real_1"] # Rename
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# Export first Real column
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out1 = os.path.join(
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group_folder, f"{file_prefix}_{group_idx}_TEST{test_idx}_01.csv"
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)
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df[["Time", "Real_0"]].rename(columns={"Real_0": "Real"}).to_csv(
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out1, index=False
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)
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# Export last Real column
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out2 = os.path.join(
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group_folder, f"{file_prefix}_{group_idx}_TEST{test_idx}_02.csv"
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)
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df[["Time", "Real_1"]].rename(columns={"Real_1": "Real"}).to_csv(
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out2, index=False
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)
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out1 = os.path.join(group_folder, f"{file_prefix}_{group_idx}_TEST{test_idx}_01.csv")
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cols_to_export = [0, 1] if self.include_time else [1]
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df.iloc[:, cols_to_export].to_csv(out1, index=False)
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out2 = os.path.join(group_folder, f"{file_prefix}_{group_idx}_TEST{test_idx}_02.csv")
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cols_to_export = [0, 2] if self.include_time else [2]
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df.iloc[:, cols_to_export].to_csv(out2, index=False)
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# def create_damage_files(base_path, output_base, prefix):
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# # Initialize colorama
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