57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
# %%
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import pandas as pd
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import json
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# %%
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data_path = '../loss_comparisons_without_augmentation/results/predictions.txt'
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df = pd.read_csv(data_path, header=None)
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df = df.rename(columns={0: 'actual', 1: 'predicted'})
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# %%
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with open('../esAppMod/tca_entities.json', 'r') as file:
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entities = json.load(file)
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all_entity_id_name = {entity['entity_id']: entity['entity_name'] for _, entity in entities['data'].items()}
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with open('../esAppMod/train.json', 'r') as file:
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train = json.load(file)
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train_entity_id_mentions = {data['entity_id']: data['mentions'] for _, data in train['data'].items()}
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train_entity_id_name = {data['entity_id']: all_entity_id_name[data['entity_id']] for _, data in train['data'].items()}
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# %%
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df['predicted_name'] = df['predicted'].map(all_entity_id_name)
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# %%
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# import test file
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data_path = '../esAppMod_data_import/test.csv'
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# data_path = '../esAppMod_data_import/parent_test.csv'
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test_df = pd.read_csv(data_path)
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# %%
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df_out = pd.concat([test_df,df], axis=1)
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# %%
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mask1 = (df['predicted'] != df['actual'])
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# %%
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print(df_out[mask1].sort_values(by=['entity_id']).to_markdown())
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# %%
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data_path = '../loss_comparisons_with_augmentations/results/predictions.txt'
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df2 = pd.read_csv(data_path, header=None)
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df2 = df2.rename(columns={0: 'actual', 1: 'predicted'})
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mask2 = df2['actual'] != df2['predicted']
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# %%
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# i want to find entries that were:
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# - correct in mask1
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# - wrong in mask2
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mask_left = ~mask1 & mask2
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predicted_entity = df2['predicted'].map(all_entity_id_name)
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df_out = pd.concat([test_df,df2, predicted_entity], axis=1)
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print(df_out[mask_left].sort_values(by=['entity_id']).to_markdown())
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# %%
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