leap_days need to be filtered for daily data too in heat
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@ -25,9 +25,12 @@ if __name__ == '__main__':
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else:
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else:
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snapshots = snakemake.config['snapshots']
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snapshots = snakemake.config['snapshots']
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drop_leap_day = snakemake.config["atlite"].get("drop_leap_day", False)
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time = pd.date_range(freq='h', **snapshots)
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time = pd.date_range(freq='h', **snapshots)
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if snakemake.config["atlite"].get("drop_leap_day", False):
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daily = pd.date_range(freq='D', **snapshots)
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if drop_leap_day:
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time = time[~((time.month == 2) & (time.day == 29))]
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time = time[~((time.month == 2) & (time.day == 29))]
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daily = daily[~((daily.month == 2) & (daily.day == 29))]
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cutout = atlite.Cutout(cutout_name).sel(time=time)
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cutout = atlite.Cutout(cutout_name).sel(time=time)
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@ -44,6 +47,6 @@ if __name__ == '__main__':
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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heat_demand = cutout.heat_demand(
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heat_demand = cutout.heat_demand(
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matrix=M.T, index=clustered_regions.index)
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matrix=M.T, index=clustered_regions.index).sel(time=daily)
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heat_demand.to_netcdf(snakemake.output[f"heat_demand_{area}"])
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heat_demand.to_netcdf(snakemake.output[f"heat_demand_{area}"])
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