#WURST MARKET GENERATOR#
#WURST MARKET FULL#
#WURST MARKET ISO#

We recommend using the function relink_technosphere_exchanges, as this should be flexible enough for almost all cases, and has been tested to avoid common corner cases and possible hidden errors.

#WURST MARKET ISO#

Countries are identified by their two-letter ISO 3166-2 codes.

#WURST MARKET FULL#

and instead use set algebra.Ĭonstructive_geometries is based on the natural earth database, and includes all countries, UN regions and subregions, some disputed areas, and a number of ecoinvent-specific regions for full documentation, see the ecoinvent report for a complete list. This means that we can skip GIS functions like intersects, overlaps, etc. As shown above, constructive_geometries splits the world into a consistent set of topological faces, identified by integer ID values. Wurst uses the constructive_geometries library to make spatial calculations easy. Topological faces in Northeastern Canada, showing both political and geographical divisions. In the database component of the input field, you can either use the name of the new database to be written, or the name of one of the input databases (it will be updated automatically). You can also manually create input values - no input value will be overwritten. find the correct input values) exchanges when writing a new database. The Brightway2 exporter will automatically re-link (i.e. This metadata is useful if you want to edit or create new exchange links. Instead of an input field, the exchange will have an activity name, a flow name, a location, and a unit. The default Brightway2 importer will remove the input field for exchanges which are provided by another activity in the same set of input datasets. Production exchanges will have the same value in input and output. The output field is not needed - this is the activity in question, which consumes the input flow. Wurst uses the same convention - the input field is used to uniquely identify an activity that produces the exchange flow (biosphere flows are also considered activities). In Brightway2, this link is the field “input”, whose value takes the form ('database name', 'unique code'). įor more information, see the introduction notebook, API documentation for searching, and: itertools, functools, toolz libraries.Įxchanges are considered “linked” if their input flows are already resolved to point to a certain producing activity.

#WURST MARKET GENERATOR#

It is strongly recommended to use generator instead of list comprehensions, i.e.Always manually check the results of your filtering functions before using them! The world is a complicated place, and our data sources reflect that complexity with unexpected or inconsistent elements.In any case bear in mind the following general guidelines: There will also be times when the helper functions in wurst are not good enough for a specific search. For many people, list and generator expressions are more pythonic in the specific case of wurst, using helper functions that are composable and reusable may allow you to not repeat yourself as often. The difference between the styles is ultimately a question of personal preference. Nuclear_generation = ( ds for ds in lci_database if 'nuclear' in ds and 'nuclear' in ds and ds = 'kilowatt hour' and 'aluminium' not in ds and 'import' not in ds )

Change the values of some of the exchanges in the filtered LCI database using the filtered external data.

Filter the external data source to get the relevant data used for modifications.

to get the subset of activities to modify

Filter the LCI database by name, unit, location, etc.

In general, a modification function will include the following steps:

Separate a global dataset into separate regions.

Change the relative shares of inputs (including adding new inputs) into markets.

Change specific emissions separate from general efficiency improvements.

Change the input material efficiency and associated emissions ( change_exchanges_by_constant_factor).

Wurst supports the following generic modification types:

Write the modified LCI data to some storage mechanism.

See also the separate wurst examples repository.Ī wurst model run will typically consist of the following steps: Current development focuses on modifying the ecoinvent LCI database with scenario data from various data sources, using Brightway2 as the data backend. Wurst is a python package for linking and modifying industrial ecology models, with a focus on sparse matrices in life cycle assessment.

Wurst market