Daniel Huppmann
Daniel Huppmann
It is often useful to validate that values of timeseries are within a specified range. Similar packages implement constraints: - https://github.com/sentinel-energy/friendly_data - https://github.com/transportenergy/database
We often use `tier` as a variable-attribute to indicate importance of a variable - tier 1 is mandatory to be reported in a scenario-comparison project, tier 2 and 3 are...
Currently, the tag-processing in a code replaces the tag-name in a code-name or any attributes with the values of the matching attributes in the tag-item. However, if there are attributes...
Most of the repository with a `workflow.py` file are very generic, see for example https://github.com/iiasa/prisma-workflow/blob/main/workflow.py. This could be abstracted away by moving this into `nomenclature.yaml`, for example ```yaml workflow: [definitions:...
To make it easier for non-expert users to check their data against a DataStructureDefinition, we need a simple CLI that takes an input file (IAMC scenario data) and validates it...
@laurinks asked me about a model-specific common-region-to-country mapping, so I whipped together this code. Maybe useful going forward ```python dsd = nomenclature.DataStructureDefinition("definitions/") rp = nomenclature.RegionProcessor.from_directory("mappings/", dsd) def get_model_country_mapping(model): model_mapping =...
Issue https://github.com/IAMconsortium/common-definitions/pull/133 identified a problem where tags in code-attributes (description in that case) were not replaced because they were not misplaced. We already have a validation of stray tags in...
While reviewing #876 by @korsbakken, I noticed that the sheet-name argument is ignored when reading an xlsx file that has only one sheet. This should be fixed such that sheet_name...
The tutorials should be revised to be more modular and relevant prior to Release 3.0 Also, per suggestion by @phackstock in https://github.com/IAMconsortium/pyam/pull/870#pullrequestreview-2222735923, the description of filter options in the docs...
The `interpolate()` method currently works on a wide representation of the timeseries data, and then casts the result back to the long-form `_data` series. It would probably be more efficient...