linopy - pypi Package Compare versions

Comparing version 0.6.0 to 0.6.1

doc/release_notes.rst

@@ -5,12 +5,38 @@ Release Notes
 .. Upcoming Version
-* Add ``mock_solve`` option to model.solve for quick testing without actual solving
-* Bugfix for missing dependency for jupyter notebook example in documentation
+
+Version 0.6.1
+--------------
+
+* Avoid Gurobi initialization on linopy import.
+* Fix LP file writing for negative zero (-0.0) values that produced invalid syntax like "+-0.0" rejected by Gurobi
+
+Version 0.6.0
+--------------
+
+**Features**
+
+* Add ``mock_solve`` option to ``Model.solve()`` for quick testing without actual solving
 * Add support for SOS1 and SOS2 (Special Ordered Sets) constraints via ``Model.add_sos_constraints()`` and ``Model.remove_sos_constraints()``
-* Add simplify method to LinearExpression to combine duplicate terms
-* Add convenience function to create LinearExpression from constant
-* Fix compatibility for xpress versions below 9.6 (regression)
-* Performance: Up to 50x faster ``repr()`` for variables/constraints via O(log n) label lookup and direct numpy indexing
-* Performance: Up to 46x faster ``ncons`` property by replacing ``.flat.labels.unique()`` with direct counting
-* Add support for GPU-accelerated solver [cuPDLPx](https://github.com/MIT-Lu-Lab/cuPDLPx)
+* Add ``simplify`` method to ``LinearExpression`` to combine duplicate terms
+* Add convenience function to create ``LinearExpression`` from constant
+* Add support for GPU-accelerated solver `cuPDLPx <https://github.com/MIT-Lu-Lab/cuPDLPx>`_
+* Add solver features registry for introspection of solver capabilities
 
+**Performance**
+
+* Up to 50x faster ``repr()`` for variables/constraints via O(log n) label lookup and direct numpy indexing
+* Up to 46x faster ``ncons`` property by replacing ``.flat.labels.unique()`` with direct counting
+
+**Bug Fixes**
+
+* Fix HiGHS solver to properly stop on Ctrl-C keyboard interrupt
+* Fix CBC solver to correctly parse negative objective values
+* Fix Xpress compatibility for versions below 9.6 (regression from namespace change)
+* Fix Xpress ``getDual()`` fallback for older versions
+* Fix missing dependency for jupyter notebook example in documentation
+
+**Solver Updates**
+
+* Add Xpress 9.8+ API support with full backward compatibility to 9.6+
+
 Version 0.5.8
@@ -17,0 +43,0 @@ --------------

linopy.egg-info/PKG-INFO

 Metadata-Version: 2.4
 Name: linopy
-Version: 0.6.0
+Version: 0.6.1
 Summary: Linear optimization with N-D labeled arrays in Python
@@ -5,0 +5,0 @@ Author-email: Fabian Hofmann <[e-mail]>

linopy/io.py

@@ -57,2 +57,22 @@ #!/usr/bin/env python3
 
+def signed_number(expr: pl.Expr) -> tuple[pl.Expr, pl.Expr]:
+    """
+    Return polars expressions for a signed number string, handling -0.0 correctly.
+
+    Parameters
+    ----------
+    expr : pl.Expr
+        Numeric value
+
+    Returns
+    -------
+    tuple[pl.Expr, pl.Expr]
+        value_string with sign
+    """
+    return (
+        pl.when(expr >= 0).then(pl.lit("+")).otherwise(pl.lit("")),
+        pl.when(expr == 0).then(pl.lit("0.0")).otherwise(expr.cast(pl.String)),
+    )
+
+
 def print_coord(coord: str) -> str:
@@ -136,4 +156,3 @@ from linopy.common import print_coord
     cols = [
-        pl.when(pl.col("coeffs") >= 0).then(pl.lit("+")).otherwise(pl.lit("")),
-        pl.col("coeffs").cast(pl.String),
+        *signed_number(pl.col("coeffs")),
         *print_variable(pl.col("vars")),
@@ -151,4 +170,3 @@ ]
     cols = [
-        pl.when(pl.col("coeffs") >= 0).then(pl.lit("+")).otherwise(pl.lit("")),
-        pl.col("coeffs").mul(2).cast(pl.String),
+        *signed_number(pl.col("coeffs").mul(2)),
         *print_variable(pl.col("vars1")),
@@ -235,9 +253,7 @@ pl.lit(" *"),
             columns = [
-                pl.when(pl.col("lower") >= 0).then(pl.lit("+")).otherwise(pl.lit("")),
-                pl.col("lower").cast(pl.String),
+                *signed_number(pl.col("lower")),
                 pl.lit(" <= "),
                 *print_variable(pl.col("labels")),
                 pl.lit(" <= "),
-                pl.when(pl.col("upper") >= 0).then(pl.lit("+")).otherwise(pl.lit("")),
-                pl.col("upper").cast(pl.String),
+                *signed_number(pl.col("upper")),
             ]
@@ -470,4 +486,3 @@
                 .alias(":"),
-                pl.when(pl.col("coeffs") >= 0).then(pl.lit("+")),
-                pl.col("coeffs").cast(pl.String),
+                *signed_number(pl.col("coeffs")),
                 pl.when(pl.col("vars").is_not_null()).then(col_labels[0]),
@@ -474,0 +489,0 @@ pl.when(pl.col("vars").is_not_null()).then(col_labels[1]),

linopy/version.py

@@ -31,5 +31,5 @@ # file generated by setuptools-scm
 
-__version__ = version = '0.6.0'
-__version_tuple__ = version_tuple = (0, 6, 0)
+__version__ = version = '0.6.1'
+__version_tuple__ = version_tuple = (0, 6, 1)
 
-__commit_id__ = commit_id = 'ge698fb25f'
+__commit_id__ = commit_id = 'g67e3484dc'

PKG-INFO

 Metadata-Version: 2.4
 Name: linopy
-Version: 0.6.0
+Version: 0.6.1
 Summary: Linear optimization with N-D labeled arrays in Python
@@ -5,0 +5,0 @@ Author-email: Fabian Hofmann <[e-mail]>

test/test_io.py

@@ -11,3 +11,5 @@ #!/usr/bin/env python3
 
+import numpy as np
 import pandas as pd
+import polars as pl
 import pytest
@@ -17,2 +19,3 @@ import xarray as xr
 from linopy import LESS_EQUAL, Model, available_solvers, read_netcdf
+from linopy.io import signed_number
 from linopy.testing import assert_model_equal
@@ -222,1 +225,117 @@
         m.to_block_files(tmp_path)
+
+
+class TestSignedNumberExpr:
+    """Test the signed_number helper function for LP file formatting."""
+
+    def test_positive_numbers(self) -> None:
+        """Positive numbers should get a '+' prefix."""
+        df = pl.DataFrame({"value": [1.0, 2.5, 100.0]})
+        result = df.select(pl.concat_str(signed_number(pl.col("value"))))
+        values = result.to_series().to_list()
+        assert values == ["+1.0", "+2.5", "+100.0"]
+
+    def test_negative_numbers(self) -> None:
+        """Negative numbers should not get a '+' prefix (already have '-')."""
+        df = pl.DataFrame({"value": [-1.0, -2.5, -100.0]})
+        result = df.select(pl.concat_str(signed_number(pl.col("value"))))
+        values = result.to_series().to_list()
+        assert values == ["-1.0", "-2.5", "-100.0"]
+
+    def test_positive_zero(self) -> None:
+        """Positive zero should get a '+' prefix."""
+        df = pl.DataFrame({"value": [0.0]})
+        result = df.select(pl.concat_str(signed_number(pl.col("value"))))
+        values = result.to_series().to_list()
+        assert values == ["+0.0"]
+
+    def test_negative_zero(self) -> None:
+        """Negative zero is normalized to +0.0 - this is the bug fix."""
+        # Create negative zero using numpy
+        neg_zero = np.float64(-0.0)
+        df = pl.DataFrame({"value": [neg_zero]})
+        result = df.select(pl.concat_str(signed_number(pl.col("value"))))
+        values = result.to_series().to_list()
+        # The key assertion: should NOT be "+-0.0", -0.0 is normalized to +0.0
+        assert values == ["+0.0"]
+        assert "+-" not in values[0]
+
+    def test_mixed_values_including_negative_zero(self) -> None:
+        """Test a mix of positive, negative, and zero values."""
+        neg_zero = np.float64(-0.0)
+        df = pl.DataFrame({"value": [1.0, -1.0, 0.0, neg_zero, 2.5, -2.5]})
+        result = df.select(pl.concat_str(signed_number(pl.col("value"))))
+        values = result.to_series().to_list()
+        # -0.0 is normalized to +0.0
+        assert values == ["+1.0", "-1.0", "+0.0", "+0.0", "+2.5", "-2.5"]
+        # No value should contain "+-"
+        for v in values:
+            assert "+-" not in v
+
+
[e-mail]("gurobi" not in available_solvers, reason="Gurobipy not installed")
+def test_to_file_lp_with_negative_zero_bounds(tmp_path: Path) -> None:
+    """
+    Test that LP files with negative zero bounds are valid.
+
+    This is a regression test for the bug where -0.0 bounds would produce
+    invalid LP file syntax like "+-0.0 <= x1 <= +0.0".
+
+    See: https://github.com/PyPSA/linopy/issues/XXX
+    """
+    import gurobipy
+
+    m = Model()
+
+    # Create bounds that could produce -0.0
+    # Using numpy to ensure we can create actual negative zeros
+    lower = pd.Series([np.float64(-0.0), np.float64(0.0), np.float64(-0.0)])
+    upper = pd.Series([np.float64(0.0), np.float64(-0.0), np.float64(1.0)])
+
+    m.add_variables(lower, upper, name="x")
+    m.add_objective(m.variables["x"].sum())
+
+    fn = tmp_path / "test_neg_zero.lp"
+    m.to_file(fn)
+
+    # Read the LP file content and verify no "+-" appears
+    with open(fn) as f:
+        content = f.read()
+    assert "+-" not in content, f"Found invalid '+-' in LP file: {content}"
+
+    # Verify Gurobi can read it without errors
+    gurobipy.read(str(fn))
+
+
[e-mail]("gurobi" not in available_solvers, reason="Gurobipy not installed")
+def test_to_file_lp_with_negative_zero_coefficients(tmp_path: Path) -> None:
+    """
+    Test that LP files with negative zero coefficients are valid.
+
+    Coefficients can also potentially be -0.0 due to floating point arithmetic.
+    """
+    import gurobipy
+
+    m = Model()
+
+    x = m.add_variables(name="x", lower=0, upper=10)
+    y = m.add_variables(name="y", lower=0, upper=10)
+
+    # Create an expression where coefficients could become -0.0
+    # through arithmetic operations
+    coeff = np.float64(-0.0)
+    expr = coeff * x + 1 * y
+
+    m.add_constraints(expr <= 5)
+    m.add_objective(x + y)
+
+    fn = tmp_path / "test_neg_zero_coeffs.lp"
+    m.to_file(fn)
+
+    # Read the LP file content and verify no "+-" appears
+    with open(fn) as f:
+        content = f.read()
+    assert "+-" not in content, f"Found invalid '+-' in LP file: {content}"
+
+    # Verify Gurobi can read it without errors
+    gurobipy.read(str(fn))

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