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@ -452,14 +452,19 @@ def process(beach_name, beach_scenario, n_runs, start_year, end_year,
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col_names = [c for c in df_in.columns if c.isdigit()]
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col_names = [c for c in df_in.columns if c.isdigit()]
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# Loop through profiles
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# Make sure blocks are always strings
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dff = df_in[df_in['beach'] == beach_name]
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df_omit = pd.DataFrame(omit)
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df_omit['block'] = df_omit['block'].astype(str)
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df_in['block'] = df_in['block'].astype(str)
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# Remove omitted profiles
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# Remove omitted profiles
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dff = pd.merge(
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df_in = pd.merge(
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pd.DataFrame(omit), dff, how='outer',
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df_omit, df_in, how='outer',
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indicator='source').query('source!="both"').drop(columns='source')
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indicator='source').query('source!="both"').drop(columns='source')
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# Loop through profiles
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dff = df_in[df_in['beach'] == beach_name]
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pbar_profile = tqdm(dff.iterrows(), total=dff.shape[0], leave=False)
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pbar_profile = tqdm(dff.iterrows(), total=dff.shape[0], leave=False)
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for i, prof in pbar_profile:
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for i, prof in pbar_profile:
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