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Merge pull request #142 from Hestia-Homes/hotwaterkwh-dev-model

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Hotwaterkwh dev model
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KhalimCK 2024-08-07 10:00:44 +01:00 • committed by GitHub
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3 changed files with 32 additions and 48 deletions
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7
modules/ml-pipeline/src/pipeline/configs/feature_processor_logic.py
View file

@ -160,7 +160,9 @@ def add_features_from_code(df):
return df
def add_estimate_annual_kwh(df):
df['estimate_annual_kwh'] = df['energy-consumption-current'] * df['total-floor-area']
return df
# def keep_ending_columns(df):
# ending_column_index = [ col_name.endswith("_ENDING") for col_name in list(df.columns)]
@ -172,7 +174,8 @@ def add_features_from_code(df):
business_logic = {
"add_features_from_code": add_features_from_code,
"remove_hotwaterkwh_bottom_percentile": remove_hotwaterkwh_bottom_percentile
"remove_hotwaterkwh_bottom_percentile": remove_hotwaterkwh_bottom_percentile,
"add_estimate_annual_kwh": add_estimate_annual_kwh
# "keep_non_zero_rdsap": keep_non_zero_rdsap,
# "keep_flats": keep_flats,
# "remove_minimum_habitable_room_size": remove_minimum_habitable_room_size,

20
modules/ml-pipeline/src/pipeline/configs/settings.yaml
View file

@ -38,16 +38,13 @@ default:
'hot-water-cost-current',
'total-floor-area',
'secondheat-description',
'environment-impact-current',
'floor-description',
'mainheat-energy-eff',
'current-energy-efficiency',
'mainheat-env-eff',
'walls-energy-eff',
'roof-energy-eff',
'property-type',
'mainheat-description',
'hot-water-env-eff',
'mechanical-ventilation',
'floor-level',
'built-form',
@ -57,7 +54,6 @@ default:
'energy-consumption-current',
'construction-age-band',
'hotwater-description',
# 'lodgement-datetime',
'main-fuel',
'hot-water-energy-eff',
'co2-emiss-curr-per-floor-area',
@ -67,37 +63,25 @@ default:
'extension-count',
'number-open-fireplaces',
'number-heated-rooms',
# 'lodgement-date',
# 'number-habitable-rooms',
'windows-description',
# 'local-authority',
'photo-supply',
'heat-loss-corridor',
# 'posttown',
# 'address',
'flat-top-storey',
'unheated-corridor-length',
'fixed-lighting-outlets-count',
# 'inspection-date',
'tenure',
# 'county',
# 'constituency-label',
'multi-glaze-proportion',
'solar-water-heating-flag',
# 'address2',
'energy-tariff',
'floor-height',
'constituency',
# 'uprn-source',
'transaction-type',
'floor-energy-eff',
# 'postcode',
'lodgement-month',
'lighting-cost-current',
'glazed-area',
# 'address1',
'floor-env-eff',
'main-heating-controls'
'main-heating-controls',
'estimate_annual_kwh',
]
generate_predictions:

53
modules/ml-pipeline/src/pipeline/dvc.lock
View file

@ -29,16 +29,13 @@ stages:
- hot-water-cost-current
- total-floor-area
- secondheat-description
- environment-impact-current
- floor-description
- mainheat-energy-eff
- current-energy-efficiency
- mainheat-env-eff
- walls-energy-eff
- roof-energy-eff
- property-type
- mainheat-description
- hot-water-env-eff
- mechanical-ventilation
- floor-level
- built-form
@ -74,8 +71,8 @@ stages:
- lodgement-month
- lighting-cost-current
- glazed-area
- floor-env-eff
- main-heating-controls
- estimate_annual_kwh
default.feature_processor.feature_processor_config.subsample_amount:
default.feature_processor.feature_processor_config.subsample_seed: 0
default.feature_processor.feature_processor_config.target: hot_water_kwh
@ -90,8 +87,8 @@ stages:
outs:
- path: data/prepared_data/
hash: md5
md5: 295ac4fd05a1a3373401a7318b0b5186.dir
size: 13131853
md5: 19abfc15e24cd8a869a0f3f087e09584.dir
size: 13396685
nfiles: 2
build_model:
cmd: python 2_build_model.py
@ -102,8 +99,8 @@ stages:
size: 4820
- path: data/prepared_data
hash: md5
md5: 295ac4fd05a1a3373401a7318b0b5186.dir
size: 13131853
md5: 19abfc15e24cd8a869a0f3f087e09584.dir
size: 13396685
nfiles: 2
params:
configs/build_model.yaml:
@ -135,18 +132,18 @@ stages:
outs:
- path: data/fit_predictions/
hash: md5
md5: 3e48cec68f702bc822eed8fcb2c5c603.dir
size: 1787931
md5: 0e2f1131b24eafa09ccbab91a36cac6c.dir
size: 1787805
nfiles: 1
- path: data/model/
hash: md5
md5: 37f7480141e920c68faacd39478a1a68.dir
size: 451364406
nfiles: 35
md5: 77c0900cda64c1beaef6782d04fd712e.dir
size: 518798187
nfiles: 36
- path: metrics/fit_metrics.json
hash: md5
md5: e7a2a5efea57b1ddd1431b713d78bb11
size: 219
md5: 0e03bb46cd03e9521095bf141ee92ed7
size: 220
generate_predictions:
cmd: python 3_generate_predictions.py
deps:
@ -156,13 +153,13 @@ stages:
size: 2464
- path: data/model
hash: md5
md5: 37f7480141e920c68faacd39478a1a68.dir
size: 451364406
nfiles: 35
md5: 77c0900cda64c1beaef6782d04fd712e.dir
size: 518798187
nfiles: 36
- path: data/prepared_data
hash: md5
md5: 295ac4fd05a1a3373401a7318b0b5186.dir
size: 13131853
md5: 19abfc15e24cd8a869a0f3f087e09584.dir
size: 13396685
nfiles: 2
params:
configs/settings.yaml:
@ -174,8 +171,8 @@ stages:
outs:
- path: data/predictions/
hash: md5
md5: 9267a66c6fae4da5a589faab76fac14c.dir
size: 192482
md5: efc7b9dd9d40e42ad93e3e5acbeac92d.dir
size: 192502
nfiles: 1
generate_metrics:
cmd: python 4_generate_metrics.py
@ -186,13 +183,13 @@ stages:
size: 3484
- path: data/predictions
hash: md5
md5: 9267a66c6fae4da5a589faab76fac14c.dir
size: 192482
md5: efc7b9dd9d40e42ad93e3e5acbeac92d.dir
size: 192502
nfiles: 1
- path: data/prepared_data
hash: md5
md5: 295ac4fd05a1a3373401a7318b0b5186.dir
size: 13131853
md5: 19abfc15e24cd8a869a0f3f087e09584.dir
size: 13396685
nfiles: 2
params:
configs/settings.yaml:
@ -202,8 +199,8 @@ stages:
outs:
- path: metrics/metrics.json
hash: md5
md5: 3a08c29f028f5e3cb50fb8cd3608e2f4
size: 221
md5: a8b7699dd2b171da5fead1fb04d954aa
size: 220
generate_scenerio_metrics:
cmd: python 5_generate_scenarios.py
deps: