Basic inspections#

This notebook starts from the packaged MARIO IOT test table and then repeats the same inspection pattern on the packaged SUT fixture.

[1]:

import mario

Load the test table#

[2]:

db = mario.load_test("IOT")
db

INFO Parser: excel reading IOT flows from /Users/lorenzorinaldi/Documents/GitHub/MARIO/mario/test/tables/test_IOT_standard.xlsx.
INFO Parser: state payload ready with 6 canonical blocks.
INFO Parser: excel state ready for IOT.
INFO Metadata: initialized.

[2]:

name = IOT test (standard)
table = IOT
scenarios = ['baseline']
Factor of production = 3
Satellite account = 2
Consumption category = 1
Region = 2
Sector = 3

Check scenarios and sets#

[3]:

db.scenarios

[3]:

['baseline']

[4]:

db.sets

[4]:

['Factor of production',
 'Satellite account',
 'Consumption category',
 'Region',
 'Sector']

[5]:

db.get_index("all")

[5]:

{'Factor of production': ['Taxes', 'Wages', 'Capital'],
 'Satellite account': ['Employment', 'CO2'],
 'Consumption category': ['Final demand'],
 'Region': ['Reg1', 'Reg2'],
 'Sector': ['Agriculture', 'Services', 'Industry']}

[6]:

db.Sector

[6]:

['Agriculture', 'Services', 'Industry']

[7]:

db.sectors # sets name are now not case-sensitive or singular-plural sensitive

[7]:

['Agriculture', 'Services', 'Industry']

Search labels#

[8]:

db.search("Agr")

[8]:

{'Sector': ['Agriculture']}

Check stored matrices#

[ ]:

db.list_matrices(scenario='baseline')  # change baseline to the name of the scenario you want to inspect

dict_keys(['E', 'EY', 'V', 'VY', 'Y', 'Z'])

Query for a matrix#

[10]:

db.Z

[10]:
Region Reg1 Reg2
Level Sector Sector
Item Agriculture Industry Services Agriculture Industry Services
Region Level Item
Reg1 Sector Agriculture 9.308651e+05 5.357799e+06 1.075278e+06 2363.029548 50607.806861 10341.916110
Industry 1.122397e+06 2.289284e+07 1.065096e+07 1413.697219 134910.657543 30367.209709
Services 1.893586e+06 9.737509e+06 3.059785e+07 1301.725200 27813.857216 58525.384254
Reg2 Sector Agriculture 4.168587e+02 2.596041e+03 8.430071e+02 2962.557738 30635.045696 7961.643900
Industry 6.890987e+03 1.335193e+05 6.555829e+04 9736.931972 287300.673355 161126.940614
Services 1.590090e+03 1.555045e+04 3.843707e+04 16680.335207 312355.775242 722089.042972

If you want to query for multiple matrices in given scenarios use the “query” method.

[11]:

db.query(
    matrices=["E"], # provide a matrix of list of matrices
    scenarios="baseline" # provide a scenario or list of scenarios (baseline is default)
    )

[11]:
Region Reg1 Reg2
Level Sector Sector
Item Agriculture Industry Services Agriculture Industry Services
Item
Employment 1.702588e+06 6.547713e+05 2.050334e+06 7.393224e+02 3.939633e+03 1.852450e+04
CO2 3.415989e+12 8.884627e+12 1.878737e+13 2.315340e+10 4.839515e+10 1.679321e+11

The “query” method will also calculate matrices in case they are missing

[12]:

db.query("e")

INFO Resolver: resolving e for baseline.
INFO Resolver: trying e via formula build_iot_e_from_E_X.
INFO Resolver: resolved e via formula build_iot_e_from_E_X.

[12]:
Region Reg1 Reg2
Level Sector Sector
Item Agriculture Industry Services Agriculture Industry Services
Item
Employment 0.170734 0.012327 0.019621 0.009259 0.003295 0.007659
CO2 342552.270192 167269.943085 179791.790027 289962.466193 40474.898330 69431.794242

Repeat the same checks on a SUT#

The same inspection methods work on SUT databases, but you will see Activity and Commodity sets plus split blocks such as U, S, Ya, and Yc.

[3]:

sut = mario.load_test("SUT")
sut

INFO Parser: excel reading SUT flows from /Users/lorenzorinaldi/Documents/GitHub/MARIO/mario/test/tables/test_SUT_standard.xlsx.
INFO Parser: state payload ready with 10 canonical blocks.
INFO Parser: excel state ready for SUT.
INFO Metadata: initialized.

[3]:

name = SUT test (standard)
table = SUT
tech_assumption = industry-based
scenarios = ['baseline']
Activity = 2
Commodity = 2
Factor of production = 3
Satellite account = 2
Consumption category = 1
Region = 2

[14]:

sut.sets

[14]:

['Activity',
 'Commodity',
 'Factor of production',
 'Satellite account',
 'Consumption category',
 'Region']

[15]:

sut.get_index("all")

[15]:

{'Activity': ['Manufacturing', 'Services'],
 'Commodity': ['Goods', 'Services'],
 'Factor of production': ['Taxes', 'Wages', 'Capital'],
 'Satellite account': ['Employment', 'CO2'],
 'Consumption category': ['Final demand'],
 'Region': ['Region 1', 'Region 2']}

[16]:

sut.search("Serv")

[16]:

{'Activity': ['Services'], 'Commodity': ['Services']}

Check stored SUT matrices#

[17]:

sut.matrices["baseline"].keys()

[17]:

dict_keys(['EY', 'Ea', 'Ec', 'S', 'U', 'VY', 'Va', 'Vc', 'Ya', 'Yc'])

[18]:

sut.U

[18]:
Region Region 1 Region 2
Level Activity Activity
Item Manufacturing Services Manufacturing Services
Region Level Item
Region 1 Commodity Goods 3.334903e+11 1.657755e+11 1.487965e+11 6.895332e+10
Services 3.261811e+11 7.254021e+11 1.176727e+10 3.588505e+10
Region 2 Commodity Goods 1.922623e+11 4.099986e+10 3.038628e+13 1.157115e+13
Services 2.614852e+10 5.823465e+10 1.154871e+13 3.075294e+13

Query derived SUT matrices#

query(...) behaves the same way on SUT databases and can materialize missing split or unified blocks on demand.

[19]:

sut.query("u")

INFO Resolver: resolving u for baseline.
INFO Resolver: trying u via extract.
INFO Resolver: trying u via formula build_sut_u_from_U_Xa.
INFO Resolver: resolved u via formula build_sut_u_from_U_Xa.

[19]:
Region Region 1 Region 2
Level Activity Activity
Item Manufacturing Services Manufacturing Services
Region Level Item
Region 1 Commodity Goods 0.261452 0.068540 0.002359 0.000660
Services 0.255721 0.299919 0.000187 0.000343
Region 2 Commodity Goods 0.150731 0.016951 0.481652 0.110734
Services 0.020500 0.024077 0.183058 0.294300 
[20]:

sut.query("Xc")

INFO Resolver: resolving Xc for baseline.
INFO Resolver: trying Xc via formula build_sut_Xc_from_U_Yc.
INFO Resolver: resolved Xc via formula build_sut_Xc_from_U_Yc.

[20]:
Item production
Region Level Item
Region 1 Commodity Goods 1.311430e+12
Services 2.382765e+12
Region 2 Commodity Goods 6.302777e+13
Services 1.045551e+14

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