docs: fix C API examples and server abort/upload docs

cpp/include/cuopt/mathematical_optimization/cuopt_c.h

@@ -623,8 +623,8 @@ cuopt_int_t cuOptGetConstraintMatrixCSR(cuOptOptimizationProblem problem,
  * @param[in] problem - The optimization problem.
  *
  * @param[out] constraint_matrix_column_offsets_ptr - A pointer to an array of type cuopt_int_t of
- *  size num_variables + 1 (see cuOptGetProblemIntAttribute) that on output will contain the column
- * offsets of the constraint matrix.
+ *  size num_variables + 1 that on output will contain the column offsets of the constraint
+ *  matrix.
  *
  * @param[out] constraint_matrix_row_indices_ptr - A pointer to an array of type cuopt_int_t of size
  *  equal to the number of nonzeros (see cuOptGetNumNonZeros) that on output will contain the row

docs/cuopt/source/cuopt-c/convex/convex-c-api.rst

@@ -70,7 +70,7 @@ For problems with quadratic constraints, first create a problem, and then use
    Support for quadratic constraints is currently in **beta**. ``cuOptAddQuadraticConstraint``
    supports three types of quadratic constraints:
    - **Convex quadratic constraints** of the form ``x^T Q x + d^T x <= alpha`` where ``H=(Q+Q^T)/2`` is a symmetric positive semidefinite matrix. `Q` need not be symmetric.
-   - **Second-order cone constraints** of the form ``sum_{i=1}^n x_i^2 <= x_0``, ``x_0 >= 0``
+   - **Second-order cone constraints** of the form ``sum_{i=1}^n x_i^2 <= x_0^2``, ``x_0 >= 0``
    - **Rotated second-order cone constraints** of the form ``sum_{i=2}^n x_i^2 - 2 * x_0 * x_1 <= 0``, ``x_0 >= 0``, ``x_1 >= 0`` (supply ``Q[x_0, x_1] = -2`` in COO, or ``-x_0*x_1`` for the ``<= x_0*x_1`` cone form; see :doc:`/convex-features`)
 
    Only ``CUOPT_LESS_THAN`` and ``CUOPT_GREATER_THAN`` sense is supported; equality constraints are not supported.
@@ -134,6 +134,7 @@ The following functions may be used to get information about an `cuOptimizationP
 .. doxygenfunction:: cuOptGetNumNonZeros
 .. doxygenfunction:: cuOptGetConstraintMatrix
 .. doxygenfunction:: cuOptGetConstraintMatrixCSR
+.. doxygenfunction:: cuOptGetConstraintMatrixCSC
 .. doxygenfunction:: cuOptGetConstraintSense
 .. doxygenfunction:: cuOptGetConstraintRightHandSide
 .. doxygenfunction:: cuOptGetConstraintLowerBounds
@@ -300,6 +301,16 @@ These constants are used to configure `CUOPT_MULTIGPU_PDLP_PARTITIONER` via :c:f
 .. doxygendefine:: CUOPT_MULTIGPU_PDLP_PARTITIONER_KAMINPAR
 .. doxygendefine:: CUOPT_MULTIGPU_PDLP_PARTITIONER_ROUND_ROBIN
 
+Presolve Constants
+------------------
+
+These constants are used to configure `CUOPT_PRESOLVE` via :c:func:`cuOptSetIntegerParameter`.
+
+.. doxygendefine:: CUOPT_PRESOLVE_DEFAULT
+.. doxygendefine:: CUOPT_PRESOLVE_OFF
+.. doxygendefine:: CUOPT_PRESOLVE_PAPILO
+.. doxygendefine:: CUOPT_PRESOLVE_PSLP
+
 .. _barrier-iterative-refinement-constants:
 
 Barrier Iterative Refinement Constants

docs/cuopt/source/cuopt-c/convex/convex-examples.rst

@@ -8,7 +8,7 @@ LP Example with Data
 
 This example demonstrates how to use the LP solver in C. More details on the API can be found in :doc:`C API <convex-c-api>`.
 
-The example code is available at ``examples/cuopt-c/lp/simple_lp_example.c`` (:download:`download <examples/simple_lp_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/convex/examples/simple_lp_example.c`` (:download:`download <examples/simple_lp_example.c>`):
 
 .. literalinclude:: examples/simple_lp_example.c
    :language: c
@@ -22,9 +22,9 @@ If you have built it locally, libcuopt.so will be in the build directory ``cpp/b
 .. code-block:: bash
 
    # Find the cuopt header file and assign to INCLUDE_PATH
-   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/linear_programming/*" -printf "%h\n" | sed 's/\/linear_programming//' 2>/dev/null)
-   # Find the libcuopt library and assign to LIBCUOPT_LIBRARY_PATH
-   LIBCUOPT_LIBRARY_PATH=$(find / -name "libcuopt.so" 2>/dev/null)
+   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/mathematical_optimization/*" -printf "%h\n" 2>/dev/null | head -1 | sed 's/\/cuopt\/mathematical_optimization$//')
+   # Find the libcuopt library directory and assign to LIBCUOPT_LIBRARY_PATH
+   LIBCUOPT_LIBRARY_PATH=$(dirname $(find / -name "libcuopt.so" 2>/dev/null | head -1))
 
 
 Build and run the example
@@ -79,7 +79,7 @@ format is dispatched from the filename extension (case-insensitive):
 their ``.gz`` / ``.bz2`` variants → MPS parser. Unknown extensions are
 rejected. See :ref:`lp-file-example-c` for an LP counterpart.
 
-The example code is available at ``examples/cuopt-c/lp/mps_file_example.c`` (:download:`download <examples/mps_file_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/convex/examples/mps_file_example.c`` (:download:`download <examples/mps_file_example.c>`):
 
 .. literalinclude:: examples/mps_file_example.c
    :language: c
@@ -93,9 +93,9 @@ If you have built it locally, libcuopt.so will be in the build directory ``cpp/b
 .. code-block:: bash
 
    # Find the cuopt header file and assign to INCLUDE_PATH
-   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/linear_programming/*" -printf "%h\n" | sed 's/\/linear_programming//' 2>/dev/null)
-   # Find the libcuopt library and assign to LIBCUOPT_LIBRARY_PATH
-   LIBCUOPT_LIBRARY_PATH=$(find / -name "libcuopt.so" 2>/dev/null)
+   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/mathematical_optimization/*" -printf "%h\n" 2>/dev/null | head -1 | sed 's/\/cuopt\/mathematical_optimization$//')
+   # Find the libcuopt library directory and assign to LIBCUOPT_LIBRARY_PATH
+   LIBCUOPT_LIBRARY_PATH=$(dirname $(find / -name "libcuopt.so" 2>/dev/null | head -1))
 
 A sample MPS file (:download:`download sample.mps <https://raw.githubusercontent.com/BUGSENG/PPL/devel/demos/ppl_lpsol/examples/sample.mps>`):
 
@@ -157,7 +157,7 @@ rejected. See the ``read_lp`` declaration in
 ``cuopt/mathematical_optimization/io/parser.hpp`` for the supported subset of
 the LP format.
 
-The example code is available at ``examples/cuopt-c/lp/lp_file_example.c`` (:download:`download <examples/lp_file_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/convex/examples/lp_file_example.c`` (:download:`download <examples/lp_file_example.c>`):
 
 .. literalinclude:: examples/lp_file_example.c
    :language: c
@@ -187,7 +187,7 @@ Simple Quadratic Programming Example
 
 This example demonstrates how to use the cuOpt C API for quadratic programming.
 
-The example code is available at ``examples/cuopt-c/lp/simple_qp_example.c`` (:download:`download <examples/simple_qp_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/convex/examples/simple_qp_example.c`` (:download:`download <examples/simple_qp_example.c>`):
 
 .. literalinclude:: examples/simple_qp_example.c
    :language: c
@@ -227,7 +227,7 @@ Simple Second-Order Cone Programming Example
 
 This example builds an SOCP directly with the C API: a linear problem is created with :c:func:`cuOptCreateProblem`, then a second-order cone constraint is added with :c:func:`cuOptAddQuadraticConstraint`. It minimizes ``x3`` subject to ``x1 + x2 >= 2`` and the cone ``||(x1, x2)||_2 <= x3``, written as the quadratic inequality ``x1^2 + x2^2 - x3^2 <= 0``. cuOpt detects the second-order cone structure and solves with the barrier method.
 
-The example code is available at ``examples/cuopt-c/lp/simple_socp_example.c`` (:download:`download <examples/simple_socp_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/convex/examples/simple_socp_example.c`` (:download:`download <examples/simple_socp_example.c>`):
 
 .. literalinclude:: examples/simple_socp_example.c
    :language: c
@@ -273,7 +273,7 @@ cone ``x1^2 + x2^2 <= x3*x4`` is expressed as ``x1^2 + x2^2 - x3*x4 <= 0``. See
 for other RSOC forms.
 It minimizes ``x3 + x4`` subject to ``x1 + x2 >= 2`` and the rotated cone.
 
-The example code is available at ``examples/cuopt-c/lp/rotated_socp_example.c`` (:download:`download <examples/rotated_socp_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/convex/examples/rotated_socp_example.c`` (:download:`download <examples/rotated_socp_example.c>`):
 
 .. literalinclude:: examples/rotated_socp_example.c
    :language: c
@@ -320,7 +320,7 @@ This example adds a general convex quadratic constraint with
 ``2*x^2 + 2*x*y + 2*y^2 <= 6``. Note that the quadratic matrix Q that encodes this
 constraint need not be symmetric. Here the term ``2*x*y`` is supplied as a single entry ``Q[0,1] = 2``.
 
-The example code is available at ``examples/cuopt-c/lp/general_quadratic_example.c`` (:download:`download <examples/general_quadratic_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/convex/examples/general_quadratic_example.c`` (:download:`download <examples/general_quadratic_example.c>`):
 
 .. literalinclude:: examples/general_quadratic_example.c
    :language: c

docs/cuopt/source/cuopt-c/convex/examples/simple_qp_example.c

@@ -83,13 +83,14 @@ cuopt_int_t test_simple_qp()
   // 0 is the coefficient of the linear term on y
   cuopt_float_t linear_objective_coefficients[] = {0.0, 0.0};
 
-  // Quadratic objective matrix
+  // Quadratic objective matrix in COO format
   // From the objective function: minimize x^2 + y^2
   // 1 is the coefficient of the quadratic term on x^2
   // 1 is the coefficient of the quadratic term on y^2
-  cuopt_float_t quadratic_objective_matrix_values[]       = {1.0, 1.0};
-  cuopt_int_t quadratic_objective_matrix_row_offsets[]    = {0, 1, 2};
-  cuopt_int_t quadratic_objective_matrix_column_indices[] = {0, 1};
+  cuopt_int_t quadratic_num_entries                = 2;
+  cuopt_int_t quadratic_objective_row_indices[]    = {0, 1};
+  cuopt_int_t quadratic_objective_column_indices[] = {0, 1};
+  cuopt_float_t quadratic_objective_values[]       = {1.0, 1.0};
 
   // Constraint bounds
   // From the constraints:
@@ -115,28 +116,37 @@ cuopt_int_t test_simple_qp()
 
   printf("Creating and solving simple QP problem...\n");
 
-  // Create the problem
-  status = cuOptCreateQuadraticProblem(num_constraints,
-                                       num_variables,
-                                       CUOPT_MINIMIZE,
-                                       0.0,  // objective offset
-                                       linear_objective_coefficients,
-                                       quadratic_objective_matrix_row_offsets,
-                                       quadratic_objective_matrix_column_indices,
-                                       quadratic_objective_matrix_values,
-                                       row_offsets,
-                                       column_indices,
-                                       values,
-                                       constraint_sense,
-                                       constraint_rhs,
-                                       var_lower_bounds,
-                                       var_upper_bounds,
-                                       &problem);
+  // Create the problem with its linear data
+  status = cuOptCreateProblem(num_constraints,
+                              num_variables,
+                              CUOPT_MINIMIZE,
+                              0.0,  // objective offset
+                              linear_objective_coefficients,
+                              row_offsets,
+                              column_indices,
+                              values,
+                              constraint_sense,
+                              constraint_rhs,
+                              var_lower_bounds,
+                              var_upper_bounds,
+                              variable_types,
+                              &problem);
   if (status != CUOPT_SUCCESS) {
     printf("Error creating problem: %d\n", status);
     goto DONE;
   }
 
+  // Set the quadratic objective
+  status = cuOptSetQuadraticObjective(problem,
+                                      quadratic_num_entries,
+                                      quadratic_objective_row_indices,
+                                      quadratic_objective_column_indices,
+                                      quadratic_objective_values);
+  if (status != CUOPT_SUCCESS) {
+    printf("Error setting quadratic objective: %d\n", status);
+    goto DONE;
+  }
+
   // Create solver settings
   status = cuOptCreateSolverSettings(&settings);
   if (status != CUOPT_SUCCESS) {

docs/cuopt/source/cuopt-c/mip/mip-c-api.rst

@@ -77,3 +77,12 @@ These constants are used to configure `CUOPT_MIP_DETERMINISM_MODE` via :c:func:`
 
 .. doxygendefine:: CUOPT_MODE_OPPORTUNISTIC
 .. doxygendefine:: CUOPT_MODE_DETERMINISTIC
+
+MIP Scaling Constants
+---------------------
+
+These constants are used to configure `CUOPT_MIP_SCALING` via :c:func:`cuOptSetIntegerParameter`.
+
+.. doxygendefine:: CUOPT_MIP_SCALING_OFF
+.. doxygendefine:: CUOPT_MIP_SCALING_ON
+.. doxygendefine:: CUOPT_MIP_SCALING_NO_OBJECTIVE

docs/cuopt/source/cuopt-c/mip/mip-examples.rst

@@ -7,7 +7,7 @@ Example with Data
 
 This example demonstrates how to use the MIP solver in C. More details on the API can be found in :doc:`MIP C API <mip-c-api>`.
 
-The example code is available at ``../lp-milp/examples/simple_milp_example.c`` (:download:`download <examples/simple_milp_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/mip/examples/simple_milp_example.c`` (:download:`download <examples/simple_milp_example.c>`):
 
 .. literalinclude:: examples/simple_milp_example.c
    :language: c
@@ -21,9 +21,9 @@ If you have built it locally, libcuopt.so will be in the build directory ``cpp/b
 .. code-block:: bash
 
    # Find the cuopt header file and assign to INCLUDE_PATH
-   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/linear_programming/*" -printf "%h\n" | sed 's/\/linear_programming//' 2>/dev/null)
+   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/mathematical_optimization/*" -printf "%h\n" 2>/dev/null | head -1 | sed 's/\/cuopt\/mathematical_optimization$//')
    # Find the libcuopt library directory and assign to LIBCUOPT_LIBRARY_PATH
-   LIBCUOPT_LIBRARY_PATH=$(dirname $(find / -name "libcuopt.so" 2>/dev/null))
+   LIBCUOPT_LIBRARY_PATH=$(dirname $(find / -name "libcuopt.so" 2>/dev/null | head -1))
 
 
 Build and run the example
@@ -80,7 +80,7 @@ Example with MPS File
 
 This example demonstrates how to use the cuOpt solver in C to solve an MPS file.
 
-The example code is available at ``examples/milp_mps_example.c`` (:download:`download <examples/milp_mps_example.c>`):
+The example code is available at ``docs/cuopt/source/cuopt-c/mip/examples/milp_mps_example.c`` (:download:`download <examples/milp_mps_example.c>`):
 
 .. literalinclude:: examples/milp_mps_example.c
    :language: c
@@ -94,9 +94,9 @@ If you have built it locally, libcuopt.so will be in the build directory ``cpp/b
 .. code-block:: bash
 
    # Find the cuopt header file and assign to INCLUDE_PATH
-   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/linear_programming/*" -printf "%h\n" | sed 's/\/linear_programming//' 2>/dev/null)
+   INCLUDE_PATH=$(find / -name "cuopt_c.h" -path "*/mathematical_optimization/*" -printf "%h\n" 2>/dev/null | head -1 | sed 's/\/cuopt\/mathematical_optimization$//')
    # Find the libcuopt library directory and assign to LIBCUOPT_LIBRARY_PATH
-   LIBCUOPT_LIBRARY_PATH=$(dirname $(find / -name "libcuopt.so" 2>/dev/null))
+   LIBCUOPT_LIBRARY_PATH=$(dirname $(find / -name "libcuopt.so" 2>/dev/null | head -1))
 
 A sample MIP MPS file (:download:`download mip_sample.mps <https://raw.githubusercontent.com/coin-or/SYMPHONY/master/Datasets/sample.mps>`):
 

docs/cuopt/source/cuopt-server/examples/milp-examples.rst

@@ -217,11 +217,11 @@ Aborting a Running Job In CLI
 
 UUID that is returned by the solver while the solver is trying to find a solution so users can come back and check the status or query for results.
 
-This aborts a job with UUID if it's in running state.
+This aborts a job with UUID if it's queued or running.
 
 .. code-block:: bash
 
    # Please update ip and port if the server is running on a different IP address or port
    export ip="localhost"
    export port=5000
-   cuopt_sh -d -r -q <UUID> -i $ip -p $port
+   cuopt_sh -d <UUID> -i $ip -p $port

docs/cuopt/source/cuopt-server/examples/milp/examples/abort_job_example.py

@@ -34,15 +34,8 @@ def main():
         ip="localhost", port=5000
     )
 
-    # Delete the job if it is still queued or running
-    # Parameters:
-    #   - job_uuid: The UUID of the job to abort
-    #   - running=True: Abort if the job is currently running
-    #   - queued=True: Abort if the job is in the queue
-    #   - cached=False: Don't delete from cache (only abort active/queued jobs)
-    response = cuopt_service_client.delete(
-        job_uuid, running=True, queued=True, cached=False
-    )
+    # Abort the job if it is still queued or running
+    response = cuopt_service_client.delete(job_uuid)
 
     print(f"Response: {response}")
 

docs/cuopt/source/cuopt-server/examples/milp/examples/abort_job_example.sh

@@ -27,9 +27,7 @@ echo "Aborting job with UUID: $UUID"
 
 # Abort the job
 # -d: Delete/abort
-# -r: If running
-# -q: If queued
-cuopt_sh -d -r -q $UUID -i $ip -p $port
+cuopt_sh -d $UUID -i $ip -p $port
 
 echo "Job abort request sent"
 echo ""

docs/cuopt/source/cuopt-server/examples/routing-examples.rst

@@ -76,6 +76,9 @@ Initial Solution
 
 Previously run solutions or uploaded solutions can be used as the initial solution for new requests using previously run reqIds as follows:
 
+.. note::
+   This example uploads a solution, which is only supported by the :ref:`legacy HTTP server <legacy-http-server>`. The HTTP proxy server returns 501 for uploaded solutions. See :ref:`legacy-http-differences`.
+
 :download:`initial_solution_example.py <routing/examples/initial_solution_example.py>`
 
 .. literalinclude:: routing/examples/initial_solution_example.py
@@ -255,6 +258,9 @@ Uploading a Solution
 
 Users can also upload a solution which might have been saved for later runs.
 
+.. note::
+   Uploaded solutions are only supported by the :ref:`legacy HTTP server <legacy-http-server>`. The HTTP proxy server returns 501. See :ref:`legacy-http-differences`.
+
 .. code-block:: shell
 
    # Please update ip and port if the server is running on a different IP address or port