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fix more deprecation warnings

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This commit is contained in:
martacki 2023-12-21 10:40:10 +01:00
parent dfc2f06033
commit bb160d78b1
1 changed files with 10 additions and 8 deletions
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18
scripts/build_retro_cost.py Normal file → Executable file
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@ -533,15 +533,15 @@ def prepare_temperature_data():
""" """
temperature = xr.open_dataarray(snakemake.input.air_temperature).to_pandas() temperature = xr.open_dataarray(snakemake.input.air_temperature).to_pandas()
d_heat = ( d_heat = (
temperature.groupby(temperature.columns.str[:2], axis=1) temperature.T.groupby(temperature.columns.str[:2])
.mean() .mean().T
.resample("1D") .resample("1D")
.mean() .mean()
< t_threshold < t_threshold
).sum() ).sum()
temperature_average_d_heat = ( temperature_average_d_heat = (
temperature.groupby(temperature.columns.str[:2], axis=1) temperature.T.groupby(temperature.columns.str[:2])
.mean() .mean().T
.apply( .apply(
lambda x: get_average_temperature_during_heating_season(x, t_threshold=15) lambda x: get_average_temperature_during_heating_season(x, t_threshold=15)
) )
@ -610,7 +610,7 @@ def calculate_costs(u_values, l, cost_retro, window_assumptions):
cost_retro.loc[x.name[3], "cost_var"] cost_retro.loc[x.name[3], "cost_var"]
* 100 * 100
* float(l) * float(l)
* l_weight.loc[x.name[3]][0] * l_weight.loc[x.name[3]].iloc[0]
+ cost_retro.loc[x.name[3], "cost_fix"] + cost_retro.loc[x.name[3], "cost_fix"]
) )
* x.A_element * x.A_element
@ -720,6 +720,7 @@ def map_to_lstrength(l_strength, df):
.swaplevel(axis=1) .swaplevel(axis=1)
.dropna(axis=1) .dropna(axis=1)
) )
return pd.concat([df.drop([2, 3], axis=1, level=1), l_strength_df], axis=1) return pd.concat([df.drop([2, 3], axis=1, level=1), l_strength_df], axis=1)
@ -800,6 +801,7 @@ def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor)
* data_tabula.A_envelope * data_tabula.A_envelope
/ data_tabula.A_C_Ref / data_tabula.A_C_Ref
) )
heat_transfer_perm2 = pd.concat( heat_transfer_perm2 = pd.concat(
[ [
heat_transfer_perm2, heat_transfer_perm2,
@ -836,8 +838,8 @@ def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor)
F_red_temp = map_to_lstrength(l_strength, F_red_temp) F_red_temp = map_to_lstrength(l_strength, F_red_temp)
Q_ht = ( Q_ht = (
heat_transfer_perm2.groupby(level=1, axis=1) heat_transfer_perm2.T.groupby(level=1)
.sum() .sum().T
.mul(F_red_temp.droplevel(0, axis=1)) .mul(F_red_temp.droplevel(0, axis=1))
.mul(temperature_factor.reindex(heat_transfer_perm2.index, level=0), axis=0) .mul(temperature_factor.reindex(heat_transfer_perm2.index, level=0), axis=0)
) )
@ -878,7 +880,7 @@ def calculate_gain_utilisation_factor(heat_transfer_perm2, Q_ht, Q_gain):
Calculates gain utilisation factor nu. Calculates gain utilisation factor nu.
""" """
# time constant of the building tau [h] = c_m [Wh/(m^2K)] * 1 /(H_tr_e+H_tb*H_ve) [m^2 K /W] # time constant of the building tau [h] = c_m [Wh/(m^2K)] * 1 /(H_tr_e+H_tb*H_ve) [m^2 K /W]
tau = c_m / heat_transfer_perm2.groupby(level=1, axis=1).sum() tau = c_m / heat_transfer_perm2.T.groupby(level=1).sum().T
alpha = alpha_H_0 + (tau / tau_H_0) alpha = alpha_H_0 + (tau / tau_H_0)
# heat balance ratio # heat balance ratio
gamma = (1 / Q_ht).mul(Q_gain.sum(axis=1), axis=0) gamma = (1 / Q_ht).mul(Q_gain.sum(axis=1), axis=0)