56 lines
1.3 KiB
Python
56 lines
1.3 KiB
Python
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# we want to see if there are clear rules to filling numbers in the pattern
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# format
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# %%
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# %%
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import pandas as pd
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# from utils import Retriever, cosine_similarity_chunked
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import os
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import glob
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import numpy as np
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# %%
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fold = 5
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data_path = f'../../train/mapping_pattern/mapping_prediction/exports/result_group_{fold}.csv'
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test_df = pd.read_csv(data_path, skipinitialspace=True)
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data_path = f"../../data_preprocess/exports/dataset/group_{fold}/train_all.csv"
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train_df = pd.read_csv(data_path, skipinitialspace=True)
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# %%
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data_path = '../../data_import/exports/data_mapping_mdm.csv'
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# data_path = '../../data_preprocess/exports/preprocessed_data.csv'
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df = pd.read_csv(data_path, skipinitialspace=True)
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mdm_list = sorted(list((set(df['pattern']))))
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# %%
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symbol_pattern_list = [elem for elem in mdm_list if '#' in elem]
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# %%
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symbol_pattern_list
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# %%
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len(symbol_pattern_list)
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# %%
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idx = 22
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print(symbol_pattern_list[idx])
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condition1 = df['pattern'] == symbol_pattern_list[idx]
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subset_df = df[df['pattern'] == symbol_pattern_list[idx]]
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ship = list(set(subset_df['ships_idx']))
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print(ship)
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# %%
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subset_df[['thing', 'property', 'tag_name', 'tag_description', 'ships_idx']].to_csv('output.csv')
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# %%
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ship_idx = 10
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condition2 = df['ships_idx'] == ship_idx
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subset_df = df[condition1 & condition2]
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subset_df
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# %%
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