feat: add BaseExpression.has_terms property

doc/api.rst

@@ -248,6 +248,7 @@ Structure
    expressions.LinearExpression.coeffs
    expressions.LinearExpression.const
    expressions.LinearExpression.nterm
+   expressions.LinearExpression.has_terms
 
 Conversion
 ----------
@@ -288,6 +289,7 @@ Structure
    expressions.QuadraticExpression.coeffs
    expressions.QuadraticExpression.const
    expressions.QuadraticExpression.nterm
+   expressions.QuadraticExpression.has_terms
 
 Conversion
 ----------

doc/release_notes.rst

@@ -5,6 +5,7 @@ Upcoming Version
 ----------------
 
 * Add documentation about `LinearExpression.where` with `drop=True`. Add `BaseExpression.variable_names` property.
+* Add ``BaseExpression.has_terms`` property: boolean array, true at slots with at least one live term (`#741 <https://github.com/PyPSA/linopy/issues/741>`_).
 
 **Features**
 

linopy/expressions.py

@@ -1338,6 +1338,37 @@ def nterm(self) -> int:
         """
         return len(self.data._term)
 
+    @property
+    def has_terms(self) -> DataArray:
+        """
+        Get a boolean array which is true at slots with at least one live term.
+
+        A term is live when it references a variable (``vars != -1``). Slots
+        without any live term arise from outer joins in
+        :func:`merge <linopy.expressions.merge>`, from reindexing past the
+        original coordinates, or from masking. In contrast to
+        :meth:`isnull`, the constant is ignored: a slot carrying only a
+        constant has no terms.
+
+        Returns
+        -------
+        xr.DataArray
+
+        Examples
+        --------
+        Mask out constraint rows whose left-hand side has no terms:
+
+        >>> import linopy
+        >>> import pandas as pd
+        >>> m = linopy.Model()
+        >>> x = m.add_variables(coords=[pd.RangeIndex(3, name="i")], name="x")
+        >>> lhs = (1 * x).reindex(i=pd.RangeIndex(5, name="i"))
+        >>> lhs.has_terms.values
+        array([ True,  True,  True, False, False])
+        """
+        helper_dims = set(self.vars.dims).intersection(HELPER_DIMS)
+        return (self.vars != -1).any(helper_dims).rename("has_terms")
+
     @property
     def variable_names(self) -> set[str]:
         """

test/test_linear_expression.py

@@ -1156,6 +1156,56 @@ def test_linear_expression_isnull(v: Variable) -> None:
     assert expr.isnull().sum() == 10
 
 
+class TestHasTerms:
+    """has_terms: true at slots with at least one live term, regardless of the constant."""
+
+    def test_basic_and_masking(self, v: Variable) -> None:
+        expr = np.arange(20) * v
+        assert expr.has_terms.all()
+
+        filter = (expr.coeffs >= 10).any(TERM_DIM)
+        masked = expr.where(filter)
+        assert_equal(masked.has_terms, filter.rename("has_terms"))
+
+    def test_ignores_const(self, v: Variable) -> None:
+        # has_terms differs from isnull() at slots whose constant was revived by
+        # fillna: no longer null, but still without terms
+        expr = np.arange(20) * v
+        filter = (expr.coeffs >= 10).any(TERM_DIM)
+        masked = expr.where(filter)
+        assert_equal(masked.isnull(), ~masked.has_terms)
+
+        filled = masked.fillna(0)
+        assert not filled.isnull().any()
+        assert_equal(filled.has_terms, filter.rename("has_terms"))
+
+    def test_merge_reindex(self, x: Variable, y: Variable) -> None:
+        # the nodal-balance pattern: outer merge, then reindex to a superset of
+        # coordinates; slots beyond the original coordinates carry no terms
+        lhs = merge([1 * x, 1 * y], join="outer").reindex(
+            dim_0=pd.RangeIndex(4, name="dim_0")
+        )
+        assert lhs.has_terms.values.tolist() == [True, True, False, False]
+
+    def test_constant_only(self, m: Model) -> None:
+        expr = LinearExpression(xr.DataArray([1, 2], dims=["dim_0"]), m)
+        assert expr.nterm == 0
+        assert not expr.has_terms.any()
+
+    def test_quadratic(self, v: Variable) -> None:
+        # linear terms inside a quadratic expression carry one factor == -1;
+        # they must still count as live terms
+        quad = v * v + 2 * v
+        assert quad.has_terms.all()
+        assert TERM_DIM not in quad.has_terms.dims
+
+        filter = xr.DataArray(
+            np.arange(20) >= 10, dims="dim_2", coords={"dim_2": range(20)}
+        )
+        masked = quad.where(filter)
+        assert_equal(masked.has_terms, filter.rename("has_terms"))
+
+
 def test_linear_expression_flat(v: Variable) -> None:
     coeff = np.arange(1, 21)  # use non-zero coefficients
     expr = coeff * v