CSRConstraint drops auxiliary coordinates when a sparse expression becomes a constraint

[FabianHofmann]

Note

This issue was written by AI (Claude), based on a limitation found while working on #940.

Version Checks (indicate both or one)

• I have confirmed this bug exists on the lastest release of Linopy.
• I have confirmed this bug exists on the current master branch of Linopy (with feat(v1): CSR sparse groupby-sum accepts multi-key groupers (#757) #940 applied, which is the first change that puts auxiliary coordinates onto a CSR payload).

Issue Description

Under v1 semantics, a CSR-backed LinearExpression (the result of groupby(...).sum(sparse=True)) carries one-dimensional auxiliary coordinates, e.g. the period/region labels of a multi-key observed=True grouping on the flat group dim, or aux coords on surviving dims. When such an expression is turned into a constraint via Model.add_constraints, the resulting CSRConstraint drops every auxiliary coordinate and keeps only the per-dimension index.

The dense path keeps them, so the sparse and dense results differ in their coordinates. This matters for later sel/where on the constraint by aux label and for the v1 aux-conflict rule, which cannot fire on the constraint side anymore.

Cause: CSRConstraint.from_payload builds the constraint from payload.indexes[d] for d in payload.grid_dims only and never looks at payload.coords (linopy/constraints.py, from_payload). CSRConstraint itself stores only a list of per-dim pd.Index, so there is currently no slot for aux coords to live in.

Reproducible Example

import linopy
import pandas as pd
from linopy import Model

linopy.options["semantics"] = "v1"

m = Model()
x = m.add_variables(coords=[pd.RangeIndex(4, name="s")], name="x")
expr = x.to_linexpr().assign_coords(
    period=("s", [1, 1, 2, 2]), region=("s", ["n", "s", "n", "s"])
)

dense = expr.groupby(["period", "region"]).sum(observed=True)
sparse = expr.groupby(["period", "region"]).sum(observed=True, sparse=True)

print(list(dense.coords))   # ['period', 'region', 'group']
print(list(sparse.coords))  # ['group', 'period', 'region']

c_dense = m.add_constraints(dense <= 1, name="dense")
c_sparse = m.add_constraints(sparse <= 1, name="sparse")

print(list(c_dense.coords))   # ['period', 'region', 'group']
print(list(c_sparse.coords))  # ['group']   <- period and region are gone

Expected Behavior

c_sparse.coords contains period and region on the group dim, matching the dense constraint and the sparse expression it was built from.

Installed Versions

Details

linopy 0.9.1.post1.dev20+g73e65c22d plus PR #940, Python 3.13, xarray/pandas from uv sync --extra dev.