28 lines
904 B
Python
28 lines
904 B
Python
def gen_metric_row(row):
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return ((row['run'], row['timestep'], row['substep']), {'s1': row['s1'], 'policies': row['policies']})
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def gen_metric_row(row):
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return {
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'run': row['run'],
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'timestep': row['timestep'],
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'substep': row['substep'],
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's1': row['s1'],
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'policies': row['policies']
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}
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def gen_metric_dict(df):
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return [gen_metric_row(row) for index, row in df.iterrows()]
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def generate_assertions_df(df, expected_results, target_cols):
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def df_filter(run, timestep, substep):
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return df[
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(df['run'] == run) & (df['timestep'] == timestep) & (df['substep'] == substep)
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][target_cols].to_dict(orient='records')[0]
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df['test'] = df.apply(
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lambda x: \
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df_filter(x['run'], x['timestep'], x['substep']) == expected_results[(x['run'], x['timestep'], x['substep'])]
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, axis=1
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)
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return df |