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If you check the result, which is returned by bdew.HeatBuilding(), you'll find that its sum differs slightly from your input in annual_heat_demand.
To reproduce this, you can add these two lines to heat_demand_example.py here after calling bdew.HeatBuilding() for a single family housing ('efh'):
heat_demand_example.py
result_annual_heat_demand = sum(demand["efh"]) print("Sum of heat demand 'efh': ", result_annual_heat_demand)
The text was updated successfully, but these errors were encountered:
To simplify discussion for those who cannot run the code right away: What are the numbers?
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If you pass annual_heat_demand=25000 and shlp_type='EFH', then you'll get sum(demand["efh"]) = 25001.458160603575
annual_heat_demand=25000
shlp_type='EFH'
sum(demand["efh"]) = 25001.458160603575
I think, this inaccuracy is quite expected when using floating point numbers. If it's really necessary, it might be mitigated but not avoided.
I found that the results in this area in the code are pretty sensitive to code changes. Maybe, it is possible to reduce the inaccuracy.
p-snft
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If you check the result, which is returned by bdew.HeatBuilding(), you'll find that its sum differs slightly from your input in annual_heat_demand.
To reproduce this, you can add these two lines to
heat_demand_example.py
here after calling bdew.HeatBuilding() for a single family housing ('efh'):The text was updated successfully, but these errors were encountered: