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add cost model

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This commit is contained in:
Michael Duong 2024-07-04 14:49:43 +01:00
parent d164bff8d2
commit 8d6f1ae739
6 changed files with 35 additions and 28 deletions
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2
.github/workflows/Deploy.yml vendored
View file

@ -2,7 +2,7 @@ name: Sap Change Model Deploy
on:
push:
branches: [ sap-dev, sap-prod, heat-dev, heat-prod, carbon-dev, carbon-prod, lighting-dev, lighting-prod ]
branches: [ sap-dev, sap-prod, heat-dev, heat-prod, carbon-dev, carbon-prod, cost-dev, cost-prod]
jobs:
deploy:

2
.github/workflows/MLPipelinePostMerge.yml vendored
View file

@ -13,7 +13,7 @@ on:
- "sap-dev"
- "heat-dev"
- "carbon-dev"
- "lighting-dev"
- "cost-dev"
permissions: write-all

2
.github/workflows/MLPipelinePullRequest.yml vendored
View file

@ -5,7 +5,7 @@ on:
# branches:
# - "model-**"
pull_request:
branches: ["sap-dev", "heat-dev", "carbon-dev", "lighting-dev"]
branches: ["sap-dev", "heat-dev", "carbon-dev", "cost-dev"]
label:
types: ["created", "edited"]

6
modules/ml-pipeline/src/pipeline/configs/feature_processor_logic.py
View file

@ -44,6 +44,11 @@ def keep_non_zero_rdsap(df):
df = df[df["rdsap_change"] != 0]
return df
def create_overall_costs(df):
df["overall_costs_starting"] = df["lighting_cost_starting"] + df["heating_cost_starting"] + df["hot_water_cost_starting"]
df["overall_costs_ending"] = df["lighting_cost_ending"] + df["heating_cost_ending"] + df["hot_water_cost_ending"]
return df
# def keep_ending_columns(df):
# ending_column_index = [ col_name.endswith("_ENDING") for col_name in list(df.columns)]
@ -54,6 +59,7 @@ def keep_non_zero_rdsap(df):
# return df
business_logic = {
"create_overall_costs": create_overall_costs
# "keep_non_zero_rdsap": keep_non_zero_rdsap,
# "keep_flats": keep_flats,
# "remove_minimum_habitable_room_size": remove_minimum_habitable_room_size,

4
modules/ml-pipeline/src/pipeline/configs/settings.yaml
View file

@ -32,12 +32,12 @@ default:
feature_processor_config:
subsample_amount: null
subsample_seed: 0
target: lighting_cost_ending
target: overall_costs_ending
identifier_columns: ["uprn"]
# drop_columns: ["heat_demand_change", "carbon_change", "rdsap_change", "heat_demand_ending", "carbon_ending", "days_to_starting", "days_to_ending"]
drop_columns: [
"sap_ending", "heat_demand_change", "carbon_change", "rdsap_change", "heat_demand_ending", "carbon_ending",
"heating_cost_ending", "hot_water_cost_ending",
"lighting_cost_ending", "heating_cost_ending", "hot_water_cost_ending",
# "days_to_starting", "days_to_ending",
'number_habitable_rooms_starting', 'number_habitable_rooms_ending', 'number_heated_rooms_starting', 'number_heated_rooms_ending',
'number_habitable_rooms', 'number_heated_rooms']

47
modules/ml-pipeline/src/pipeline/dvc.lock
View file

@ -27,6 +27,7 @@ stages:
- rdsap_change
- heat_demand_ending
- carbon_ending
- lighting_cost_ending
- heating_cost_ending
- hot_water_cost_ending
- number_habitable_rooms_starting
@ -38,7 +39,7 @@ stages:
default.feature_processor.feature_processor_config.retain_features:
default.feature_processor.feature_processor_config.subsample_amount:
default.feature_processor.feature_processor_config.subsample_seed: 0
default.feature_processor.feature_processor_config.target: lighting_cost_ending
default.feature_processor.feature_processor_config.target: overall_costs_ending
default.feature_processor.feature_processor_type: dataframe
default.prepare_data.data_filepath:
s3://retrofit-data-dev/sap_change_model/2024-07-03-23-11-39/dataset_rooms.parquet
@ -50,8 +51,8 @@ stages:
outs:
- path: data/prepared_data/
hash: md5
md5: 0f11a02cf75c0421757c0b26184cec33.dir
size: 48971227
md5: e484d5032d234731d7f0b218310161e6.dir
size: 50645982
nfiles: 2
build_model:
cmd: python 2_build_model.py
@ -62,8 +63,8 @@ stages:
size: 4820
- path: data/prepared_data
hash: md5
md5: 0f11a02cf75c0421757c0b26184cec33.dir
size: 48971227
md5: e484d5032d234731d7f0b218310161e6.dir
size: 50645982
nfiles: 2
params:
configs/build_model.yaml:
@ -95,18 +96,18 @@ stages:
outs:
- path: data/fit_predictions/
hash: md5
md5: 36c41f88681ab90668c17ce63fd9c318.dir
size: 3444201
md5: 815c326a9ef5c5bea201c06cb04fee7e.dir
size: 3445213
nfiles: 1
- path: data/model/
hash: md5
md5: bb9c3f1538e02e20e918ec36a0b7546f.dir
size: 754271944
md5: 3c5340b992ffb3162d65361ba9d09bbd.dir
size: 823603444
nfiles: 37
- path: metrics/fit_metrics.json
hash: md5
md5: 16ae1efa8ac48d8ed978bb3fa67be64a
size: 225
md5: 7d0715b84211f5cdef7a41954e7bc8e5
size: 222
generate_predictions:
cmd: python 3_generate_predictions.py
deps:
@ -116,13 +117,13 @@ stages:
size: 2464
- path: data/model
hash: md5
md5: bb9c3f1538e02e20e918ec36a0b7546f.dir
size: 754271944
md5: 3c5340b992ffb3162d65361ba9d09bbd.dir
size: 823603444
nfiles: 37
- path: data/prepared_data
hash: md5
md5: 0f11a02cf75c0421757c0b26184cec33.dir
size: 48971227
md5: e484d5032d234731d7f0b218310161e6.dir
size: 50645982
nfiles: 2
params:
configs/settings.yaml:
@ -134,8 +135,8 @@ stages:
outs:
- path: data/predictions/
hash: md5
md5: 50909a5b19c2551410e921dc9a92bef7.dir
size: 480359
md5: 7d223c9cf49cdbc520ba607e00868123.dir
size: 480423
nfiles: 1
generate_metrics:
cmd: python 4_generate_metrics.py
@ -146,13 +147,13 @@ stages:
size: 3484
- path: data/predictions
hash: md5
md5: 50909a5b19c2551410e921dc9a92bef7.dir
size: 480359
md5: 7d223c9cf49cdbc520ba607e00868123.dir
size: 480423
nfiles: 1
- path: data/prepared_data
hash: md5
md5: 0f11a02cf75c0421757c0b26184cec33.dir
size: 48971227
md5: e484d5032d234731d7f0b218310161e6.dir
size: 50645982
nfiles: 2
params:
configs/settings.yaml:
@ -162,8 +163,8 @@ stages:
outs:
- path: metrics/metrics.json
hash: md5
md5: d74767b34a1042c9ab0e3d6535791be6
size: 224
md5: 9700491cc19bd64a616cf504b0106896
size: 221
generate_scenerio_metrics:
cmd: python 5_generate_scenarios.py
deps: