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@ -36,7 +36,6 @@ def forecast_twl(
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# cross-section profiles once per site.
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# cross-section profiles once per site.
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logger.info("Calculating beach slopes")
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logger.info("Calculating beach slopes")
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site_ids = df_twl.index.get_level_values("site_id").unique()
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site_ids = df_twl.index.get_level_values("site_id").unique()
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# site_ids = [x for x in site_ids if 'NARRA' in x] # todo remove this - for testing narrabeen only
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if slope == "foreshore":
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if slope == "foreshore":
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# Process each site_id with a different process and combine results at the end
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# Process each site_id with a different process and combine results at the end
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@ -47,7 +46,6 @@ def forecast_twl(
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df_twl["beta"] = pd.concat(results)
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df_twl["beta"] = pd.concat(results)
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elif slope == "mean":
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elif slope == "mean":
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# todo mean beach profile
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df_temp = df_twl.join(df_profile_features, how="inner")
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df_temp = df_twl.join(df_profile_features, how="inner")
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df_temp["mhw"] = 0.5
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df_temp["mhw"] = 0.5
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with Pool(processes=n_processes) as pool:
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with Pool(processes=n_processes) as pool:
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