junte/Model
1
0
Fork 0
mirror of https://github.com/Hestia-Homes/Model.git synced 2026-07-12 13:29:04 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 1

Merge pull request #236 from Hestia-Homes/main

Browse source 
adding due considerations ecr
This commit is contained in:
KhalimCK 2023-09-25 19:38:56 +01:00 • committed by GitHub
commit 7dc854035a
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
3 changed files with 31 additions and 2 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

5
infrastructure/terraform/main.tf
View file

@ -143,3 +143,8 @@ module "lambda_sap_prediction_ecr" {
ecr_name = "lambda-sap-prediction-${var.stage}" ecr_name = "lambda-sap-prediction-${var.stage}"
source = "./modules/ecr" source = "./modules/ecr"
} }
module "due_considerations_ecr" {
ecr_name = "due-considerations-${var.stage}"
source = "./modules/ecr"
}

5
model_data/simulation_system/core/DataProcessor.py
View file

@ -543,8 +543,11 @@ class DataProcessor:
df[uvalue_col] = pd.to_numeric(df[uvalue_col]) df[uvalue_col] = pd.to_numeric(df[uvalue_col])
key_columns = [ key_columns = [
"RDSAP_CHANGE", "HEAT_DEMAND_CHANGE", "CARBON_CHANGE", "SAP_STARTING", "HEAT_DEMAND_STARTING", "RDSAP_CHANGE", "HEAT_DEMAND_CHANGE", "CARBON_CHANGE",
"SAP_STARTING", "HEAT_DEMAND_STARTING",
"CARBON_STARTING", "UPRN", "CONSTITUENCY", "CARBON_STARTING", "UPRN", "CONSTITUENCY",
"SAP_ENDING", "CARBON_ENDING", "HEAT_DEMAND_ENDING",
"DAYS_TO_STARTING", "DAYS_TO_ENDING"
] ]
ignore_cols = FIXED_FEATURES + FIXED_DESCRIPTON_MAPPED_FEATURES + key_columns ignore_cols = FIXED_FEATURES + FIXED_DESCRIPTON_MAPPED_FEATURES + key_columns

23
model_data/simulation_system/generate_rdsap_change.py
View file

@ -458,6 +458,10 @@ def app():
starting_heat_demand = earliest_record[HEAT_DEMAND_RESPONSE] starting_heat_demand = earliest_record[HEAT_DEMAND_RESPONSE]
starting_carbon = earliest_record[CARBON_RESPONSE] starting_carbon = earliest_record[CARBON_RESPONSE]
ending_sap = latest_record[RDSAP_RESPONSE]
ending_heat_demand = latest_record[HEAT_DEMAND_RESPONSE]
ending_carbon = latest_record[CARBON_RESPONSE]
rdsap_change = latest_record[RDSAP_RESPONSE] - starting_sap rdsap_change = latest_record[RDSAP_RESPONSE] - starting_sap
heat_demand_change = latest_record[HEAT_DEMAND_RESPONSE] - starting_heat_demand heat_demand_change = latest_record[HEAT_DEMAND_RESPONSE] - starting_heat_demand
carbon_change = latest_record[CARBON_RESPONSE] - starting_carbon carbon_change = latest_record[CARBON_RESPONSE] - starting_carbon
@ -469,6 +473,10 @@ def app():
starting_heat_demand = latest_record[HEAT_DEMAND_RESPONSE] starting_heat_demand = latest_record[HEAT_DEMAND_RESPONSE]
starting_carbon = latest_record[CARBON_RESPONSE] starting_carbon = latest_record[CARBON_RESPONSE]
ending_sap = earliest_record[RDSAP_RESPONSE]
ending_heat_demand = earliest_record[HEAT_DEMAND_RESPONSE]
ending_carbon = earliest_record[CARBON_RESPONSE]
rdsap_change = earliest_record[RDSAP_RESPONSE] - starting_sap rdsap_change = earliest_record[RDSAP_RESPONSE] - starting_sap
heat_demand_change = earliest_record[HEAT_DEMAND_RESPONSE] - starting_heat_demand heat_demand_change = earliest_record[HEAT_DEMAND_RESPONSE] - starting_heat_demand
carbon_change = earliest_record[CARBON_RESPONSE] - starting_carbon carbon_change = earliest_record[CARBON_RESPONSE] - starting_carbon
@ -488,8 +496,11 @@ def app():
"HEAT_DEMAND_CHANGE": heat_demand_change, "HEAT_DEMAND_CHANGE": heat_demand_change,
"CARBON_CHANGE": carbon_change, "CARBON_CHANGE": carbon_change,
"SAP_STARTING": starting_sap, "SAP_STARTING": starting_sap,
"SAP_ENDING": ending_sap,
"HEAT_DEMAND_STARTING": starting_heat_demand, "HEAT_DEMAND_STARTING": starting_heat_demand,
"HEAT_DEMAND_ENDING": ending_heat_demand,
"CARBON_STARTING": starting_carbon, "CARBON_STARTING": starting_carbon,
"CARBON_ENDING": ending_carbon,
**fixed_data, **fixed_data,
**features.to_dict(), **features.to_dict(),
} }
@ -553,12 +564,22 @@ def app():
output = pd.concat(dataset) output = pd.concat(dataset)
uvalue_columns = [col for col in output.columns if "thermal_transmittance" in col]
for uvalue_col in uvalue_columns:
output[uvalue_col] = pd.to_numeric(output[uvalue_col])
save_dataframe_to_s3_parquet(
df=output,
bucket_name="retrofit-data-dev",
file_key="sap_change_model/dataset_without_differencing.parquet",
)
output = DataProcessor.difference_data(output) output = DataProcessor.difference_data(output)
save_dataframe_to_s3_parquet( save_dataframe_to_s3_parquet(
df=output, df=output,
bucket_name="retrofit-data-dev", bucket_name="retrofit-data-dev",
file_key="sap_change_model/dataset_new_not_diff.parquet", file_key="sap_change_model/dataset_with_differencing.parquet",
) )