Merge branch 'master' into SCIPvarMarkRelaxationOnly

Author: Joao-Dionisio

CHANGELOG.md

@@ -11,6 +11,7 @@
 ### Fixed
 - Raised an error when an expression is used when a variable is required
 ### Changed
+- MatrixExpr.sum() now supports axis arguments and can return either a scalar or MatrixExpr depending on the result dimensions
 ### Removed
 
 ## 5.5.0 - 2025.05.06

INSTALL.md

@@ -26,7 +26,7 @@ If installing SCIP from source or using PyPI with a python and operating system
 you need to specify the install location using the environment variable
 `SCIPOPTDIR`:
 
--   on Linux and OS X:\
+-   on Linux and MacOS:\
     `export SCIPOPTDIR=<path_to_install_dir>`
 -   on Windows:\
     `set SCIPOPTDIR=<path_to_install_dir>` (**cmd**, **Cmder**, **WSL**)\
@@ -45,8 +45,9 @@ contains the corresponding header files:
         > nlpi
         > ...
 
-Please note that some Mac configurations require adding the library installation path to `DYLD_LIBRARY_PATH` when using a locally installed version of SCIP.
+On MacOS, to ensure that the SCIP dynamic library can be located at runtime by PySCIPOpt, you should add your SCIP installation path to the ``DYLD_LIBRARY_PATH`` environment variable by running:
 
+`export DYLD_LIBRARY_PATH="<path_to_install_dir>/lib:$DYLD_LIBRARY_PATH"`
 
 When building SCIP from source using Windows it is highly recommended to use the [Anaconda Python
 Platform](https://www.anaconda.com/).
@@ -75,7 +76,7 @@ at runtime by adjusting your `PATH` environment variable:
 
 -   on Windows: `set PATH=%PATH%;%SCIPOPTDIR%\bin`
 
-On Linux and OS X this is encoded in the generated PySCIPOpt library and
+On Linux and MacOS this is encoded in the generated PySCIPOpt library and
 therefore not necessary.
 
 Building everything from source

docs/build.rst

@@ -100,6 +100,15 @@ For Linux and MacOS systems set the variable with the following command:
 
   export SCIPOPTDIR=<path_to_install_dir>
 
+.. note::
+
+  For macOS users, to ensure that the SCIP dynamic library can be found at runtime by PySCIPOpt,
+  you should add your SCIP installation path to the ``DYLD_LIBRARY_PATH`` environment variable by running:
+
+  .. code-block::
+
+    export DYLD_LIBRARY_PATH="<path_to_install_dir>/lib:$DYLD_LIBRARY_PATH"
+
 For Windows use the following command:
 
 .. code-block:: bash

src/pyscipopt/lp.pxi

@@ -58,7 +58,8 @@ cdef class LP:
         """Adds a single column to the LP.
 
         Keyword arguments:
-        entries -- list of tuples, each tuple consists of a row index and a coefficient
+        entries -- a list of tuples; if p is the index of the new column, then each tuple (i, k) indicates that
+        A[i][p] = k, where A is the constraint matrix and k is a nonzero entry.
         obj     -- objective coefficient (default 0.0)
         lb      -- lower bound (default 0.0)
         ub      -- upper bound (default infinity)
@@ -85,7 +86,8 @@ cdef class LP:
         """Adds multiple columns to the LP.
 
         Keyword arguments:
-        entrieslist -- list containing lists of tuples, each tuple contains a coefficient and a row index
+        entrieslist -- a list of lists, where the j-th inner list contains tuples (i, k) such that A[i][p] = k,
+        where A is the constraint matrix, p is the index of the j-th new column, and k is a nonzero entry.
         objs  -- objective coefficient (default 0.0)
         lbs   -- lower bounds (default 0.0)
         ubs   -- upper bounds (default infinity)
@@ -147,7 +149,8 @@ cdef class LP:
         """Adds a single row to the LP.
 
         Keyword arguments:
-        entries -- list of tuples, each tuple contains a coefficient and a column index
+        entries -- a list of tuples; if q is the index of the new row, then each tuple (j, k) indicates that
+        A[q][j] = k, where A is the constraint matrix and k is a nonzero entry.
         lhs     -- left-hand side of the row (default 0.0)
         rhs     -- right-hand side of the row (default infinity)
         """
@@ -172,7 +175,8 @@ cdef class LP:
         """Adds multiple rows to the LP.
 
         Keyword arguments:
-        entrieslist -- list containing lists of tuples, each tuple contains a coefficient and a column index
+        entrieslist -- a list of lists, where the i-th inner list contains tuples (j, k) such that A[q][j] = k,
+        where A is the constraint matrix, q is the index of the i-th new row, and k is a nonzero entry.
         lhss        -- left-hand side of the row (default 0.0)
         rhss        -- right-hand side of the row (default infinity)
         """

src/pyscipopt/matrix.pxi

@@ -17,8 +17,13 @@ def _is_number(e):
 
 class MatrixExpr(np.ndarray):
     def sum(self, **kwargs):
-        return super().sum(**kwargs).item()
-    
+        """
+        Based on `numpy.ndarray.sum`, but returns a scalar if the result is a single value.
+        This is useful for matrix expressions where the sum might reduce to a single value.
+        """
+        res = super().sum(**kwargs)
+        return res if res.size > 1 else res.item()
+
     def __le__(self, other: Union[float, int, Variable, np.ndarray, 'MatrixExpr']) -> np.ndarray:
 
         expr_cons_matrix = np.empty(self.shape, dtype=object)

tests/test_matrix_variable.py

@@ -164,6 +164,30 @@ def test_expr_from_matrix_vars():
         for term, coeff in expr_list:
             assert len(term) == 3
 
+def test_matrix_sum_argument():
+    m = Model()
+
+    # compare the result of summing 2d array to a scalar with a scalar
+    x = m.addMatrixVar((2, 3), "x", "I", ub=4)
+    m.addCons(x.sum() == 24)
+
+    # compare the result of summing 2d array to 1d array
+    y = m.addMatrixVar((2, 4), "y", "I", ub=4)
+    m.addMatrixCons(x.sum(axis=1) == y.sum(axis=1))
+
+    # compare the result of summing 3d array to a 2d array with a 2d array
+    z = m.addMatrixVar((2, 3, 4), "z", "I", ub=4)
+    m.addMatrixCons(z.sum(axis=2) == x)
+    m.addMatrixCons(z.sum(axis=1) == y)
+
+    # to fix the element values
+    m.addMatrixCons(z == np.ones((2, 3, 4)))
+
+    m.setObjective(x.sum() + y.sum() + z.sum(), "maximize")
+    m.optimize()
+
+    assert (m.getVal(x) == np.full((2, 3), 4)).all().all()
+    assert (m.getVal(y) == np.full((2, 4), 3)).all().all()
 
 def test_add_cons_matrixVar():
     m = Model()