Python

Installation¶

While the Python package has not been released yet, you have to install it from GitHub source using:

# when using poetry
poetry add git+https://github.com:PhilippVerpoort/scenario-vetting-criteria.git

# when using pip
pip install git+https://github.com:PhilippVerpoort/scenario-vetting-criteria.git

Raw file paths¶

The package contains definition files for the criteria. The paths to those files are contained in file_paths.

In [1]:

from scenario_vetting_criteria import file_paths

for component_id, component_path in file_paths.items():
    print(f"{component_id}:  ...{str(component_path)[-40:]}")

from scenario_vetting_criteria import file_paths for component_id, component_path in file_paths.items(): print(f"{component_id}: ...{str(component_path)[-40:]}")

operations:  ...io_vetting_criteria/data/operations.yaml
criteria-thresholds:  ...ng_criteria/data/criteria-thresholds.csv
criteria-types:  ...etting_criteria/data/criteria-types.yaml
sources:  ...enario_vetting_criteria/data/sources.bib
criteria-metadata:  ...ing_criteria/data/criteria-metadata.yaml

Load functions¶

Instead of loading the data from these files manually, it is recommended to use the built-in load functions from the package via load_criteria. For instance, the following will load the definition of the thresholds values.

In [2]:

from scenario_vetting_criteria import load_criteria

load_criteria('criteria-thresholds')

from scenario_vetting_criteria import load_criteria load_criteria('criteria-thresholds')

Out[2]:

	criterion	region	year	variable	reference_data	unit	level_of_concern	lower	upper
0	hist_pop	World	2010, 2015, 2020, 2025	Population	range(WDI-2025, WDI-2025-extrapol25, WDI-2025-...	dimensionless	strong	0.75	1.25
1	hist_pop	All Countries	2010, 2015, 2020, 2025	Population	range(WDI-2025, WDI-2025-extrapol25, WDI-2025-...	dimensionless	strong	0.65	1.35
2	hist_gdp	World	2010, 2015, 2020, 2025	GDP|PPP	range(WDI-2025, WDI-2025-extrapol25, WDI-2025-...	dimensionless	strong	0.75	1.25
3	hist_gdp	All Countries	2010, 2015, 2020, 2025	GDP|PPP	range(WDI-2025, WDI-2025-extrapol25, WDI-2025-...	dimensionless	strong	0.65	1.35
4	hist_emi_afolu	World	2010, 2015, 2020	Emissions|CO2|AFOLU	range(EDGAR-2024, FAO-2025, PRIMAP-2020-HISTCR...	dimensionless	strong	0.80	1.20
...	...	...	...	...	...	...	...	...	...
91	sustainable_deforestation	World	2030	Forest Area Change|Deforestation	NaN	million ha/yr	medium	NaN	0.00
92	sustainable_primary_deforestation	World	2030	Forest Area Change|Deforestation|Primary	NaN	million ha/yr	medium	NaN	0.00
93	sustainable_biodiversity_intactness	World	2030	Terrestrial Biodiversity|BII, Terrestrial Biod...	NaN	%/yr	medium	NaN	0.00
94	sustainable_bioenergy	World	2025, 2030, 2035, 2040, 2045, 2050	Primary Energy|Biomass	NaN	EJ/yr	strong	NaN	100.00
95	sustainable_hydropower	World	2050	Capacity|Electricity|Hydro	NaN	GW	strong	NaN	1500.00

96 rows × 9 columns

Multiple files can be loaded in one go.

In [3]:

criteria = load_criteria(['criteria-thresholds', 'operations'])
display(criteria['operations'])

criteria = load_criteria(['criteria-thresholds', 'operations']) display(criteria['operations'])

[{'criterion_type': 'historical',
  'level_of_concern': 'strong',
  'threshold_type': ['upper', 'lower'],
  'operation': 'drop'},
 {'criterion_id': 'nearterm_land_cover',
  'level_of_concern': 'strong',
  'threshold_type': ['upper', 'lower'],
  'operation': 'drop'},
 {'criterion_type': 'near_term_feasibility',
  'level_of_concern': 'strong',
  'threshold_type': ['upper', 'lower'],
  'operation': 'flag',
  'colour': 'red'},
 {'criterion_type': 'near_term_feasibility',
  'level_of_concern': 'medium',
  'threshold_type': ['upper', 'lower'],
  'operation': 'flag',
  'colour': 'yellow'},
 {'criterion_type': 'long_term_feasibility',
  'level_of_concern': 'strong',
  'threshold_type': ['upper', 'lower'],
  'operation': 'flag',
  'colour': 'red'},
 {'criterion_type': 'long_term_feasibility',
  'level_of_concern': 'medium',
  'threshold_type': ['upper', 'lower'],
  'operation': 'flag',
  'colour': 'yellow'},
 {'criterion_type': 'sustainability',
  'level_of_concern': 'strong',
  'threshold_type': ['upper', 'lower'],
  'operation': 'flag',
  'colour': 'purple'}]

Formatting citations and sources¶

Loading the reference sources from the BibTeX file will return a pybtex object.

In [4]:

sources = load_criteria('sources')

sources = load_criteria('sources')

The entries in this object can be formatted according to some predefined style.

In [5]:

from scenario_vetting_criteria.formatting import format_sources
sources_formatted = format_sources(sources)
display(sources_formatted['Creutzig-2014'])

from scenario_vetting_criteria.formatting import format_sources sources_formatted = format_sources(sources) display(sources_formatted['Creutzig-2014'])

{'cite_auth': 'Creutzig',
 'cite_year': '2014',
 'cite': 'Creutzig (2014)',
 'citep': '(Creutzig, 2014)',
 'bib': 'Felix Creutzig, N. H. Ravindranath, Göran Berndes, Simon Bolwig, Ryan Bright, Francesco Cherubini, Helena Chum, Esteve Corbera, Mark Delucchi, Andre Faaij, Joseph Fargione, Helmut Haberl, Garvin Heath, Oswaldo Lucon, Richard Plevin, Alexander Popp, Carmenza Robledo?Abad, Steven Rose, Pete Smith, Anders Stromman, Sangwon Suh, and Omar Masera. Bioenergy and climate change mitigation: an assessment. GCB Bioenergy, 7(5):916–944, July 2014. doi:10.1111/gcbb.12205.',
 'doi': '10.1111/gcbb.12205',
 'link': 'https://doi.org/10.1111/gcbb.12205'}

The insert_citations function can be used to insert citations into text with citation patterns.

In [6]:

from scenario_vetting_criteria.formatting import insert_citations

text = load_criteria('criteria-metadata')['sustainable_bioenergy']['justification_threshold']
text_inserted = insert_citations(text, sources_formatted)

print(text[:30], '...   →  ', text_inserted[:30], '...')

from scenario_vetting_criteria.formatting import insert_citations text = load_criteria('criteria-metadata')['sustainable_bioenergy']['justification_threshold'] text_inserted = insert_citations(text, sources_formatted) print(text[:30], '... → ', text_inserted[:30], '...')

{{cite:Creutzig-2014}} have de ...   →   Creutzig (2014) have derived a ...

Apply vetting criteria to scenarios¶

A tutorial on how to apply the vetting criteria to a list of scenarios based on the IAMC Nomenclature package will be made available later.