diff --git a/CHANGELOG.md b/CHANGELOG.md index dcc6339e..eccb5f3f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -9,11 +9,14 @@ and this project adheres to [Semantic Versioning](http://semver.org/). ## [Unreleased] ### Added + - ML Enabled Galveston CGE [#641](https://github.com/IN-CORE/pyincore/issues/641) - ML Enabled Mobile CGE [#658](https://github.com/IN-CORE/pyincore/issues/658) -- Add ML enabled Seaside CGE [#657](https://github.com/IN-CORE/pyincore/issues/657) +- ML Enabled Seaside CGE [#657](https://github.com/IN-CORE/pyincore/issues/657) +- ML Enabled Lumberton CGE [#447](https://github.com/IN-CORE/incore-docs/issues/447) ### Changed + - Descriptions of the analyses to be more verbose. [#645](https://github.com/IN-CORE/pyincore/issues/645) - Descriptions of the analyses, inputs and parameters. [#649](https://github.com/IN-CORE/pyincore/issues/649) - Descriptions of the analyses, inputs and parameters. [#646](https://github.com/IN-CORE/pyincore/issues/646) @@ -22,12 +25,10 @@ and this project adheres to [Semantic Versioning](http://semver.org/). - Capital Shocks analysis to also output Sectors in building to sector mappings with no guids as unit shocks. [#671](https://github.com/IN-CORE/pyincore/issues/671) ### Fixed -- Building retrofit fails with local building dataset. [#617](https://github.com/IN-CORE/pyincore/issues/617) -### Fixed +- Building retrofit fails with local building dataset. [#617](https://github.com/IN-CORE/pyincore/issues/617) - Network analyses to check if a network dataset is set by the user. [#667](https://github.com/IN-CORE/pyincore/issues/667) - ## [1.21.0] - 2025-02-12 ### Changed diff --git a/docs/source/modules.rst b/docs/source/modules.rst index 9218c474..5705589b 100644 --- a/docs/source/modules.rst +++ b/docs/source/modules.rst @@ -233,13 +233,18 @@ analyses/meandamage .. autoclass:: meandamage.meandamage.MeanDamage :members: +analyses/mlenabledcgelumberton +============================== +.. autoclass:: mlenabledcgelumberton.mlcgelumberton.MlEnabledCgeLumberton + :members: + analyses/mlenabledcgeslc ======================== .. autoclass:: mlenabledcgeslc.mlcgeslc.MlEnabledCgeSlc :members: analyses/mlenabledcgegalveston -======================== +============================== .. autoclass:: mlenabledcgegalveston.mlcgegalveston.MlEnabledCgeGalveston :members: @@ -253,7 +258,7 @@ analyses/mlenabledcgemobile .. autoclass:: mlenabledcgemobile.mlcgemobile.MlEnabledCgeMobile analyses/mlenabledcgeseaside -======================== +============================ .. autoclass:: mlenabledcgeseaside.mlcgeseaside.MlEnabledCgeSeaside :members: diff --git a/pyincore/analyses/mlenabledcgelumberton/DDS_coefficients.csv b/pyincore/analyses/mlenabledcgelumberton/DDS_coefficients.csv new file mode 100644 index 00000000..c23bce55 --- /dev/null +++ b/pyincore/analyses/mlenabledcgelumberton/DDS_coefficients.csv @@ -0,0 +1,44 @@ +"Testbed","Hazard","Model_Type","Model_Name","(Intercept)","AG_MIA","UTILA","CONSTA","MANUA","WHOLEA","RETAILA","TRANSA","INFOA","FINANCEA","REALEA","PRO_MANA","ADMINA","EDUA","HEALTHA","ARTA","ACCOA","OTHERA","AG_MIB","UTILB","CONSTB","MANUB","WHOLEB","RETAILB","TRANSB","INFOB","FINANCEB","REALEB","PRO_MANB","ADMINB","EDUB","HEALTHB","ARTB","ACCOB","OTHERB","HS1A","HS2A","HS3A","HS4A","HS1B","HS2B","HS3B","HS4B" 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--- /dev/null +++ b/pyincore/analyses/mlenabledcgelumberton/DS_base_val.csv @@ -0,0 +1,43 @@ +,sector,value +0,AG_MIA,31.298934763813843 +1,UTILA,38.495387077960146 +2,CONSTA,43.43237441760857 +3,MANUA,187.47298575722326 +4,WHOLEA,53.94209671535652 +5,RETAILA,218.46204202834133 +6,TRANSA,31.64012863998923 +7,INFOA,17.43824706448109 +8,FINANCEA,69.37215817592076 +9,REALEA,17.989379639527357 +10,PRO_MANA,49.637323561444475 +11,ADMINA,107.97617650653676 +12,EDUA,149.11319059869848 +13,HEALTHA,266.7038531914879 +14,ARTA,8.434154934711424 +15,ACCOA,138.2501338253203 +16,OTHERA,90.59040703322542 +17,AG_MIB,180.71635944978604 +18,UTILB,101.05232886259023 +19,CONSTB,73.33835544861495 +20,MANUB,386.308875478173 +21,WHOLEB,52.90227340116769 +22,RETAILB,226.2485089041428 +23,TRANSB,68.74755811839378 +24,INFOB,8.679431495977099 +25,FINANCEB,96.64550109146529 +26,REALEB,14.199552632546215 +27,PRO_MANB,51.04914878790231 +28,ADMINB,42.91329550822672 +29,EDUB,197.35365243060693 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+311,FED_L3IB,1 diff --git a/pyincore/analyses/mlenabledcgelumberton/GI_base_val.csv b/pyincore/analyses/mlenabledcgelumberton/GI_base_val.csv new file mode 100644 index 00000000..81ac538b --- /dev/null +++ b/pyincore/analyses/mlenabledcgelumberton/GI_base_val.csv @@ -0,0 +1,31 @@ +,household,value +0,HH1WA,1.9612088032725903 +1,HH2WA,13.295745563647369 +2,HH3WA,81.61274291942752 +3,HH4WA,93.44290332479737 +4,HH5WA,22.845319628565193 +5,HH1BA,4.31343069593185 +6,HH2BA,17.34287826462197 +7,HH3BA,44.59738584207153 +8,HH4BA,19.94948748993888 +9,HH5BA,1.0150515251760788 +10,HH1IA,3.099753420514396 +11,HH2IA,23.318867901298717 +12,HH3IA,69.80241938457979 +13,HH4IA,76.60932928432055 +14,HH5IA,16.93421667606276 +15,HH1WB,3.4642864930969988 +16,HH2WB,23.8089903022636 +17,HH3WB,144.7745627507663 +18,HH4WB,165.3380452851006 +19,HH5WB,40.84371622794252 +20,HH1BB,7.452246524022701 +21,HH2BB,29.95046868768677 +22,HH3BB,76.97775914347278 +23,HH4BB,34.245655727838766 +24,HH5BB,1.6785473392385593 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mode 100644 index 00000000..3c72ce96 --- /dev/null +++ b/pyincore/analyses/mlenabledcgelumberton/MIGT_coefficients.csv @@ -0,0 +1,32 @@ +"Testbed","Hazard","Model_Type","Model_Name","(Intercept)","AG_MIA","UTILA","CONSTA","MANUA","WHOLEA","RETAILA","TRANSA","INFOA","FINANCEA","REALEA","PRO_MANA","ADMINA","EDUA","HEALTHA","ARTA","ACCOA","OTHERA","AG_MIB","UTILB","CONSTB","MANUB","WHOLEB","RETAILB","TRANSB","INFOB","FINANCEB","REALEB","PRO_MANB","ADMINB","EDUB","HEALTHB","ARTB","ACCOB","OTHERB","HS1A","HS2A","HS3A","HS4A","HS1B","HS2B","HS3B","HS4B" 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HH3BB","4.02662114922789","-0.000546442489052466","0.000367873203826865","0","0.0036270715257141","-0.00520934352793901","0.00145521454993968","0.000118192489590951","-0.00100278004849015","0.00105904055802138","0","2.07533097609677e-05","0.00268921075266434","0","0.00155358558530485","0","0.000420033562093387","0","0.000257591926307088","-0.001069145825442","0.000891681322537178","0.000280091628436688","-0.00327336847433377","-0.00447090886023821","6.07660220907919e-05","0","-0.000849590888681498","0","0.000406177010358543","0.00126742785849975","2.59047473991741e-06","-6.04453956111763e-05","0","-0.000156466596263085","-0.000761325429805914","0.00552310182759647","0.00492494854692289","0.00527119834894873","0.00526065907893156","-0.0452786523802879","-0.046393406234975","-0.0463143809698192","-0.0463133860897613" +"Lumberton","flood/hurricane","sector_model","MIGT _ HH4BB","1.00435914010297","-0.00034100888731132","0","0","0.00110706317978679","-0.000877818454953006","0.000124719541688226","0.000171927821737902","0","0","0","0.00065345433992281","0.000429179577558781","-1.95314008390604e-05","0.000230832551837558","0","0","0","0","-0.000251215521163695","4.71450601226057e-05","0","-0.00135172843823649","-0.00211805474008832","0","0","-0.000746843721842753","0","0","4.32664025248765e-05","-0.000259813827644936","-0.00020369034475376","0","-0.000264800832275648","-0.00034677275692894","0.00103996692752881","0.000962342662780053","0.0011186056173014","0.00110804018292294","-0.0138515607108872","-0.0141688260048801","-0.0141488271039901","-0.0141480971845924" +"Lumberton","flood/hurricane","sector_model","MIGT _ HH5BB","-0.193919140964533","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","-1.01856596602094e-05","-4.75835831187064e-05","-0.000145504294492418","0","0","0","0","0","0","-2.20560650899517e-05","0","0","-1.20260641058433e-06","-1.14141430042049e-05","0","0","0","0","0","-3.23867131252917e-05","-4.11867264294053e-05","-4.3233725107796e-05" +"Lumberton","flood/hurricane","sector_model","MIGT _ HH1IB","-0.259383248976071","0","0","0","0.000284702698149294","8.82014311696618e-06","0.00024084713936819","0","0","0","0","0","0","0","6.22428747287795e-05","0","5.97148852088548e-05","0","0","-0.00101442048964153","0","-0.000653965195124824","-0.0020693644387144","-0.00262635843863151","-3.6260896161219e-05","0","-0.000395556652462459","0","-6.73483037855237e-05","0","-0.000479358595750719","-0.000376021204855186","0","-0.000204869697927625","-0.000455482921805559","0.000209245086907065","0.000373594680263086","0.000477635559265791","0.000484409809228108","-0.00118624915947086","-0.00130456817747727","-0.00131163736454382","-0.00131331253494766" +"Lumberton","flood/hurricane","sector_model","MIGT _ HH2IB","0.933681642338758","-0.000213534818076145","0","0","0.000979454993961116","0","0.000928962387299459","0","0.000802573869555038","0.00139131711880695","0","0","0","0","0.00095072585289872","0","0.000274797649869546","0","9.03347791020925e-05","-0.0032624711011104","0.00042615147232899","-0.00193019916532992","-0.00676037851215555","-0.0083079992371382","-0.00015528366173183","0","-0.00193230517181069","0","-2.51956344005179e-05","0","-0.000787426149356823","-0.00168655849491066","0","-0.000516150019183512","-0.00133407020219828","0.00243490032298058","0.00237593578205615","0.00251847561526853","0.0025217046801599","-0.0152656092501369","-0.0155436794638211","-0.0155146272998355","-0.0155136458278609" +"Lumberton","flood/hurricane","sector_model","MIGT _ HH3IB","2.33147405440798","-0.00174119977406838","7.62698055855239e-05","0","0.00296724284503669","0.0051529775756259","0.000567247560553164","0","0.00327510791193816","0.000986055788335174","-0.00160885532610266","0.00116430592568727","0.00103715303184847","0.000425532183155121","0.000857405422161524","0","0.00155835784346209","0","0.000394977505861853","-0.00540242239791546","0.00147943638792602","-0.00325983528097459","-0.0149644670227952","-0.0182275345327657","-0.000427534122068251","0","-0.00459025829147169","-0.000414974047682992","-0.000421596717425683","0","-0.00125109859513364","-0.00199651220500271","-0.00031447155598415","-0.0013695035880256","-0.00296686842092018","0.0071244935827613","0.00665492602035343","0.00680810573709706","0.00679311693285804","-0.0332957594332173","-0.0337878822667551","-0.0337056278472913","-0.0336936519826029" +"Lumberton","flood/hurricane","sector_model","MIGT _ HH4IB","1.96175483855704","-0.00197834792078102","0","0","0.00244628887681632","0.00597490829971149","-6.43771495279488e-05","0","0","-0.00111966678961416","-0.00191507888848212","0.00104474225291717","0.00195807763612286","0.000140290181825009","-0.000216899047472237","0","0.00133594685652485","-0.000115746688145144","6.64487301479661e-05","-0.00276345537530192","0.000880955627302293","-0.00207919542719953","-0.0107002988855617","-0.0142147649806281","-0.000545189766264438","0","-0.00495043835724285","-3.8584336486022e-06","-3.51101199037562e-05","0","-0.00186747464828337","-0.00188735520908735","-0.000701349730517966","-0.00157995989895185","-0.00227426853456602","0.00448802309647849","0.00418003790478939","0.00433089678662032","0.00431332736151836","-0.0281631481889649","-0.0285928640555684","-0.0285305422680336","-0.0285235222937838" +"Lumberton","flood/hurricane","sector_model","MIGT _ HH5IB","-0.169320677021838","0","0","0","0.000148803983303764","0.000188458722112661","1.97219653302189e-05","0","0","0","0","0","0","0","0","0","3.10893414986698e-05","0","0","-0.000333375106562783","0","-0.000382513402432265","-0.0017740685080656","-0.00266974049312889","-0.000115606290737429","0","-0.000367601160882569","0","-5.37925415532497e-05","0","-0.000789002350569353","-0.000293534988412712","0","-0.000265562594812786","-0.000365625384650863","0","5.94438135108328e-05","0.000184115899989881","0.000186754108746212","-0.0020132602703374","-0.00213122498879589","-0.002137688190892","-0.00214074081549978" diff --git a/pyincore/analyses/mlenabledcgelumberton/__init__.py b/pyincore/analyses/mlenabledcgelumberton/__init__.py new file mode 100644 index 00000000..148bd42b --- /dev/null +++ b/pyincore/analyses/mlenabledcgelumberton/__init__.py @@ -0,0 +1,7 @@ +# Copyright (c) 2024 University of Illinois and others. All rights reserved. +# +# This program and the accompanying materials are made available under the +# terms of the Mozilla Public License v2.0 which accompanies this distribution, +# and is available at https://www.mozilla.org/en-US/MPL/2.0/ + +from pyincore.analyses.mlenabledcgelumberton.mlcgelumberton import MlEnabledCgeLumberton diff --git a/pyincore/analyses/mlenabledcgelumberton/baseKAP.csv b/pyincore/analyses/mlenabledcgelumberton/baseKAP.csv new file mode 100644 index 00000000..b27f2379 --- /dev/null +++ b/pyincore/analyses/mlenabledcgelumberton/baseKAP.csv @@ -0,0 +1,43 @@ +,sector,baseKAP +0,AG_MIA,136.1407 +1,UTILA,179.0113 +2,CONSTA,103.8927 +3,MANUA,328.3917 +4,WHOLEA,120.1557 +5,RETAILA,647.0503 +6,TRANSA,129.7731 +7,INFOA,18.62852 +8,FINANCEA,94.09998 +9,REALEA,84.02082 +10,PRO_MANA,88.87079 +11,ADMINA,37.08617 +12,EDUA,256.5494 +13,HEALTHA,352.0501 +14,ARTA,32.98701 +15,ACCOA,436.5151 +16,OTHERA,570.9037 +17,AG_MIB,668.3757 +18,UTILB,413.1753 +19,CONSTB,137.2915 +20,MANUB,758.7977 +21,WHOLEB,222.0249 +22,RETAILB,853.6339 +23,TRANSB,289.3249 +24,INFOB,30.25995 +25,FINANCEB,451.3223 +26,REALEB,75.96958 +27,PRO_MANB,102.774 +28,ADMINB,47.42921 +29,EDUB,583.6755 +30,HEALTHB,560.355 +31,ARTB,65.63859 +32,ACCOB,847.5539 +33,OTHERB,1106.271 +34,HS1A,77.57334 +35,HS2A,297.5992 +36,HS3A,756.9165 +37,HS4A,1400.018 +38,HS1B,184.4769 +39,HS2B,775.5885 +40,HS3B,1549.249 +41,HS4B,2332.112 diff --git a/pyincore/analyses/mlenabledcgelumberton/mlcgelumberton.py b/pyincore/analyses/mlenabledcgelumberton/mlcgelumberton.py new file mode 100644 index 00000000..855b7af1 --- /dev/null +++ b/pyincore/analyses/mlenabledcgelumberton/mlcgelumberton.py @@ -0,0 +1,227 @@ +# Copyright (c) 2024 University of Illinois and others. All rights reserved. +# +# This program and the accompanying materials are made available under the +# terms of the Mozilla Public License v2.0 which accompanies this distribution, +# and is available at https://www.mozilla.org/en-US/MPL/2.0/ + +import numpy as np +import os +import pandas as pd + +from pyincore import globals as pyglobals +from pyincore.client import IncoreClient +from pyincore.analyses.core_cge_ml import CoreCGEML +from pyincore.utils.cge_ml_file_util import CGEMLFileUtil + +logger = pyglobals.LOGGER + + +class MlEnabledCgeLumberton(CoreCGEML): + """ + The Machine Learning Enabled Computable General Equilibrium (CGE) - Lumberton analysis merges advanced machine + learning with traditional CGE models to offer unprecedented insights into the economic impacts of disaster + scenarios on Lumberton. Trained on a comprehensive dataset of numerous simulated disasters and their economic + effects, this hybrid approach excels in predicting the intricate dynamics of the city's economy under + various crises. + + Args: + CoreCGEML (class): The base class for the ML enabled CGE model. + """ + + model = "Machine Learning Enabled Computable General Equilibrium - Lumberton" + + # Coefficients files + DDS_coefficients_file = "DDS_coefficients.csv" + DY_coefficients_file = "DY_coefficients.csv" + MIGT_coefficients_file = "MIGT_coefficients.csv" + DFFD_coefficients_file = "DFFD_coefficients.csv" + + # Base value files + DS_base_val_file = "DS_base_val.csv" + GI_base_val_file = "GI_base_val.csv" + HH_base_val_file = "HH_base_val.csv" + FD_base_val_file = "FD_base_val.csv" + + Base_KAP_file = "baseKAP.csv" + + base_file_path = os.path.join( + pyglobals.PYINCORE_PACKAGE_HOME, + "analyses", + "mlenabledcgelumberton", + ) + model_filenames = { + "ds": os.path.join( + base_file_path, + DDS_coefficients_file, + ), + "dy": os.path.join( + base_file_path, + DY_coefficients_file, + ), + "migt": os.path.join( + base_file_path, + MIGT_coefficients_file, + ), + "dffd": os.path.join( + base_file_path, + DFFD_coefficients_file, + ), + } + + filenames = [ + os.path.join( + base_file_path, + DS_base_val_file, + ), + os.path.join( + base_file_path, + GI_base_val_file, + ), + os.path.join( + base_file_path, + HH_base_val_file, + ), + os.path.join( + base_file_path, + FD_base_val_file, + ), + os.path.join( + base_file_path, + Base_KAP_file, + ), + ] + + def __init__(self, incore_client: IncoreClient): + ( + sectors, + base_cap_factors, + base_cap, + model_coeffs, + cap_shock_sectors, + ) = CGEMLFileUtil.parse_files(self.model_filenames, self.filenames) + self.base_cap_factors = base_cap_factors + self.base_cap = base_cap + self.model_coeffs = model_coeffs + self.cap_shock_sectors = cap_shock_sectors + labor_grps = [ + "L1BA", + "L1BB", + "L1IA", + "L1IB", + "L1WA", + "L1WB", + "L2BA", + "L2BB", + "L2IA", + "L2IB", + "L2WA", + "L2WB", + "L3BA", + "L3BB", + "L3IA", + "L3IB", + "L3WA", + "L3WB", + "L4BA", + "L4BB", + "L4IA", + "L4IB", + "L4WA", + "L4WB", + ] + super(MlEnabledCgeLumberton, self).__init__( + incore_client, sectors, labor_groups=labor_grps + ) # 4 labor groups + + def run(self) -> bool: + """ + Executes the ML enabled CGE model for Lumberton. + + Returns: + bool: True if the model runs successfully, False otherwise. + """ + logger.info(f"Running {self.model} model...") + sector_shocks = pd.read_csv( + self.get_input_dataset("sector_shocks").get_file_path("csv") + ) + # arrange the capital shocks in the same order as the sectors + shocks = [] + + for sector in self.cap_shock_sectors: + if sector.upper() not in [v.upper() for v in sector_shocks["sector"]]: + raise ValueError( + f"Sector {sector} not found in the sector shocks file with\n {sector_shocks['sector']} sectors.\n" + + "Please make sure you have used the correct capital shocks." + ) + shocks.append( + sector_shocks.loc[sector_shocks["sector"] == sector.upper()]["shock"] + ) + capital_shocks = np.array(shocks, dtype=np.float64).reshape(1, -1) + # logger.info(f"capital_shocks shape: {capital_shocks.shape}") + + super().run_core_cge_ml( + self.base_cap, + capital_shocks, + self.model_coeffs, + self.base_cap_factors, + ) + logger.info(f"Running {self.model} model completed.") + + return True + + def get_spec(self): + return { + "name": "Lumberton-small-calibrated", + "description": "The “Machine Learning Enabled Computable General Equilibrium (CGE) - Lumberton analysis merges advanced" + " machine learning with traditional CGE models to offer unprecedented insights into the economic impacts of disaster " + "scenarios on Lumberton. Trained on a comprehensive dataset of numerous simulated disasters and their economic effects, " + "this hybrid approach excels in predicting the intricate dynamics of the city’s economy under various crises.", + "input_parameters": [ + { + "id": "result_name", + "required": False, + "description": "Prefix of the result CSV dataset name.", + "type": str, + } + ], + "input_datasets": [ + { + "id": "sector_shocks", + "required": True, + "description": "Aggregation of building functionality states to capital shocks per sector.", + "type": ["incore:capitalShocks"], + } + ], + "output_datasets": [ + { + "id": "domestic-supply", + "parent_type": "", + "description": "CSV file of resulting domestic suppl.y", + "type": "incore:Employment", + }, + { + "id": "gross-income", + "parent_type": "", + "description": "CSV file of resulting gross income.", + "type": "incore:Employment", + }, + { + "id": "pre-disaster-factor-demand", + "parent_type": "", + "description": "CSV file of factor demand before disaster.", + "type": "incore:FactorDemand", + }, + { + "id": "post-disaster-factor-demand", + "parent_type": "", + "description": "CSV file of resulting factor-demand.", + "type": "incore:FactorDemand", + }, + { + "id": "household-count", + "parent_type": "", + "description": "CSV file of household count.", + "type": "incore:HouseholdCount", + }, + ], + } diff --git a/tests/pyincore/analyses/mlenabledcgelumberton/test_mlcgelumberton.py b/tests/pyincore/analyses/mlenabledcgelumberton/test_mlcgelumberton.py new file mode 100644 index 00000000..70054b59 --- /dev/null +++ b/tests/pyincore/analyses/mlenabledcgelumberton/test_mlcgelumberton.py @@ -0,0 +1,14 @@ +from pyincore import IncoreClient, globals as pyglobals +from pyincore.analyses.mlenabledcgelumberton import MlEnabledCgeLumberton + +client = IncoreClient(pyglobals.INCORE_API_DEV_URL) + +mlcgelumberton = MlEnabledCgeLumberton(client) + +sector_shocks = "688913ee54892f07695f541c" + +mlcgelumberton.load_remote_input_dataset("sector_shocks", sector_shocks) +# optional +mlcgelumberton.set_parameter("result_name", "test_lumberton_mlcge_result") + +mlcgelumberton.run_analysis()