Esempio n. 1
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 def name(self, value):
     old_name = getattr(self, 'name', None)
     self._name = value
     if getattr(self, 'problem', None) is not None:
         glp_set_col_name(self.problem.problem,
                          glp_find_col(self.problem.problem, old_name),
                          str(value))
         self.problem.variables.update_key(old_name)
Esempio n. 2
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 def name(self, value):
     old_name = getattr(self, "name", None)
     super(Variable, Variable).name.fset(self, value)
     _glpk_validate_id(value)
     if getattr(self, 'problem', None) is not None:
         glp_set_col_name(self.problem.problem,
                          glp_find_col(self.problem.problem, old_name),
                          str(value))
Esempio n. 3
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 def _add_variables(self, variables):
     for variable in variables:
         glp_add_cols(self.problem, 1)
         index = glp_get_num_cols(self.problem)
         glp_set_col_name(self.problem, index, str(variable.name))
         variable.problem = self
         self._glpk_set_col_bounds(variable)
         glp_set_col_kind(self.problem, variable._index, _VTYPE_TO_GLPK_VTYPE[variable.type])
     super(Model, self)._add_variables(variables)
Esempio n. 4
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 def _add_variables(self, variables):
     for variable in variables:
         glp_add_cols(self.problem, 1)
         index = glp_get_num_cols(self.problem)
         glp_set_col_name(self.problem, index, str(variable.name))
         variable.problem = self
         self._glpk_set_col_bounds(variable)
         glp_set_col_kind(self.problem, variable.index, _VTYPE_TO_GLPK_VTYPE[variable.type])
     super(Model, self)._add_variables(variables)
Esempio n. 5
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 def name(self, value):
     if len(value) > 256:
         raise ValueError(
             "GLPK does not support ID's longer than 256 characters")
     if getattr(self, 'problem', None) is not None:
         glp_set_col_name(self.problem.problem,
                          glp_find_col(self.problem.problem, self.name),
                          str(value))
     super(Variable, Variable).name.fset(self, value)
Esempio n. 6
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def setup_col(
    problem: SwigPyObject,
    j: int,
    recipe: 'Recipe',
    resource_indices: Dict[str, int],
    min_clock: Optional[int] = None,
    fixed_clock: Optional[int] = None,
):
    lp.glp_set_col_name(problem, j, recipe.name)

    # The game's clock scaling resolution is one percentage point, so we
    # ask for integers with an implicit scale of 100
    lp.glp_set_col_kind(problem, j, lp.GLP_IV)

    # All recipes are currently weighed the same
    lp.glp_set_obj_coef(problem, j, 1)

    if fixed_clock is None:
        # All recipes must have at least 0 instances
        lp.glp_set_col_bnds(
            problem,
            j,
            lp.GLP_LO,
            min_clock or 0,
            float('inf'),  # Lower and upper boundaries
        )
    else:
        # Set our desired (fixed) outputs
        lp.glp_set_col_bnds(
            problem,
            j,
            lp.GLP_FX,
            fixed_clock,
            fixed_clock,  # Boundaries are equal (variable is fixed)
        )

    # The constraint coefficients are just the recipe rates
    n_sparse = len(recipe.rates)
    ind = lp.intArray(n_sparse + 1)
    val = lp.doubleArray(n_sparse + 1)
    for i, (resource, rate) in enumerate(recipe.rates.items(), 1):
        ind[i] = resource_indices[resource]
        val[i] = rate
    lp.glp_set_mat_col(problem, j, n_sparse, ind, val)
	def test_swiglpk(self):
		"""Test the underlying GLPK lib and its SWIG interface based on
		the example from https://github.com/biosustain/swiglpk
		"""
		ia = glp.intArray(1 + 1000)
		ja = glp.intArray(1 + 1000)
		ar = glp.doubleArray(1 + 1000)

		lp = glp.glp_create_prob()
		smcp = glp.glp_smcp()
		glp.glp_init_smcp(smcp)
		smcp.msg_lev = glp.GLP_MSG_ALL  # use GLP_MSG_ERR?

		glp.glp_set_prob_name(lp, "sample")
		glp.glp_set_obj_dir(lp, glp.GLP_MAX)

		glp.glp_add_rows(lp, 3)
		glp.glp_set_row_name(lp, 1, "p")
		glp.glp_set_row_bnds(lp, 1, glp.GLP_UP, 0.0, 100.0)
		glp.glp_set_row_name(lp, 2, "q")
		glp.glp_set_row_bnds(lp, 2, glp.GLP_UP, 0.0, 600.0)
		glp.glp_set_row_name(lp, 3, "r")
		glp.glp_set_row_bnds(lp, 3, glp.GLP_UP, 0.0, 300.0)
		glp.glp_add_cols(lp, 3)
		glp.glp_set_col_name(lp, 1, "x1")
		glp.glp_set_col_bnds(lp, 1, glp.GLP_LO, 0.0, 0.0)
		glp.glp_set_obj_coef(lp, 1, 10.0)
		glp.glp_set_col_name(lp, 2, "x2")
		glp.glp_set_col_bnds(lp, 2, glp.GLP_LO, 0.0, 0.0)
		glp.glp_set_obj_coef(lp, 2, 6.0)
		glp.glp_set_col_name(lp, 3, "x3")
		glp.glp_set_col_bnds(lp, 3, glp.GLP_LO, 0.0, 0.0)
		glp.glp_set_obj_coef(lp, 3, 4.0)

		ia[1] = 1; ja[1] = 1; ar[1] = 1.0  # a[1,1] = 1
		ia[2] = 1; ja[2] = 2; ar[2] = 1.0  # a[1,2] = 1
		ia[3] = 1; ja[3] = 3; ar[3] = 1.0  # a[1,3] = 1
		ia[4] = 2; ja[4] = 1; ar[4] = 10.0  # a[2,1] = 10
		ia[5] = 3; ja[5] = 1; ar[5] = 2.0  # a[3,1] = 2
		ia[6] = 2; ja[6] = 2; ar[6] = 4.0  # a[2,2] = 4
		ia[7] = 3; ja[7] = 2; ar[7] = 2.0  # a[3,2] = 2
		ia[8] = 2; ja[8] = 3; ar[8] = 5.0  # a[2,3] = 5
		ia[9] = 3; ja[9] = 3; ar[9] = 6.0  # a[3,3] = 6

		glp.glp_load_matrix(lp, 9, ia, ja, ar)
		glp.glp_simplex(lp, smcp)

		Z = glp.glp_get_obj_val(lp)
		x1 = glp.glp_get_col_prim(lp, 1)
		x2 = glp.glp_get_col_prim(lp, 2)
		x3 = glp.glp_get_col_prim(lp, 3)

		self.assertAlmostEqual(Z, 733.3333, 4)
		self.assertAlmostEqual(x1, 33.3333, 4)
		self.assertAlmostEqual(x2, 66.6667, 4)
		self.assertAlmostEqual(x3, 0)

		glp.glp_delete_prob(lp)
Esempio n. 8
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 def name(self, value):
     if getattr(self, 'problem', None) is not None:
         glp_set_col_name(self.problem.problem,
                          glp_find_col(self.problem.problem, self.name),
                          str(value))
     super(Variable, Variable).name.fset(self, value)
Esempio n. 9
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    def _import_problem(self):
        import swiglpk as glpk

        if self.verbosity() >= 1:
            glpk.glp_term_out(glpk.GLP_ON)
        else:
            glpk.glp_term_out(glpk.GLP_OFF)

        # Create a problem instance.
        p = self.int = glpk.glp_create_prob();

        # Set the objective.
        if self.ext.objective[0] in ("find", "min"):
            glpk.glp_set_obj_dir(p, glpk.GLP_MIN)
        elif self.ext.objective[0] is "max":
            glpk.glp_set_obj_dir(p, glpk.GLP_MAX)
        else:
            raise NotImplementedError("Objective '{0}' not supported by GLPK."
                .format(self.ext.objective[0]))

        # Set objective function shift
        if self.ext.objective[1] is not None \
        and self.ext.objective[1].constant is not None:
            if not isinstance(self.ext.objective[1], AffinExp):
                raise NotImplementedError("Non-linear objective function not "
                    "supported by GLPK.")

            if self.ext.objective[1].constant.size != (1,1):
                raise NotImplementedError("Non-scalar objective function not "
                    "supported by GLPK.")

            glpk.glp_set_obj_coef(p, 0, self.ext.objective[1].constant[0])

        # Add variables.
        # Multideminsional variables are split into multiple scalar variables
        # represented as matrix columns within GLPK.
        for varName in self.ext.varNames:
            var = self.ext.variables[varName]

            # Add a column for every scalar variable.
            numCols = var.size[0] * var.size[1]
            glpk.glp_add_cols(p, numCols)

            for localIndex, picosIndex \
            in enumerate(range(var.startIndex, var.endIndex)):
                glpkIndex = self._picos2glpk_variable_index(picosIndex)

                # Assign a name to the scalar variable.
                scalarName = varName
                if numCols > 1:
                    x = localIndex // var.size[0]
                    y = localIndex % var.size[0]
                    scalarName += "_{:d}_{:d}".format(x + 1, y + 1)
                glpk.glp_set_col_name(p, glpkIndex, scalarName)

                # Assign bounds to the scalar variable.
                lower, upper = var.bnd.get(localIndex, (None, None))
                if lower is not None and upper is not None:
                    if lower == upper:
                        glpk.glp_set_col_bnds(
                            p, glpkIndex, glpk.GLP_FX, lower, upper)
                    else:
                        glpk.glp_set_col_bnds(
                            p, glpkIndex, glpk.GLP_DB, lower, upper)
                elif lower is not None and upper is None:
                    glpk.glp_set_col_bnds(p, glpkIndex, glpk.GLP_LO, lower, 0)
                elif lower is None and upper is not None:
                    glpk.glp_set_col_bnds(p, glpkIndex, glpk.GLP_UP, 0, upper)
                else:
                    glpk.glp_set_col_bnds(p, glpkIndex, glpk.GLP_FR, 0, 0)

                # Assign a type to the scalar variable.
                if var.vtype in ("continuous", "symmetric"):
                    glpk.glp_set_col_kind(p, glpkIndex, glpk.GLP_CV)
                elif var.vtype == "integer":
                    glpk.glp_set_col_kind(p, glpkIndex, glpk.GLP_IV)
                elif var.vtype == "binary":
                    glpk.glp_set_col_kind(p, glpkIndex, glpk.GLP_BV)
                else:
                    raise NotImplementedError("Variable type '{0}' not "
                        "supported by GLPK.".format(var.vtype()))

                # Set objective function coefficient of the scalar variable.
                if self.ext.objective[1] is not None \
                and var in self.ext.objective[1].factors:
                    glpk.glp_set_obj_coef(p, glpkIndex,
                        self.ext.objective[1].factors[var][localIndex])

        # Add constraints.
        # Multideminsional constraints are split into multiple scalar
        # constraints represented as matrix rows within GLPK.
        rowOffset = 1
        for constraintNum, constraint in enumerate(self.ext.constraints):
            if not isinstance(constraint, AffineConstraint):
                raise NotImplementedError(
                    "Non-linear constraints not supported by GLPK.")

            # Add a row for every scalar constraint.
            # Internally, GLPK uses an auxiliary variable for every such row,
            # bounded by the right hand side of the scalar constraint in a
            # canonical form.
            numRows = len(constraint)
            glpk.glp_add_rows(p, numRows)

            self._debug("Handling PICOS Constraint: " + str(constraint))

            # Split multidimensional constraints into multiple scalar ones.
            for localConIndex, (glpkVarIndices, coefficients, rhs) in \
                    enumerate(constraint.sparse_Ab_rows(
                    None, indexFunction = lambda picosVar, i:
                    self._picos2glpk_variable_index(picosVar.startIndex + i))):
                # Determine GLPK's row index of the scalar constraint.
                glpkConIndex = rowOffset + localConIndex
                numColumns   = len(glpkVarIndices)

                # Name the auxiliary variable associated with the current row.
                if constraint.name:
                    name = constraint.name
                else:
                    name = "rhs_{:d}".format(constraintNum)
                if numRows > 1:
                    x = localConIndex // constraint.size[0]
                    y = localConIndex % constraint.size[0]
                    name += "_{:d}_{:d}".format(x + 1, y + 1)
                glpk.glp_set_row_name(p, glpkConIndex, name)

                # Assign bounds to the auxiliary variable.
                if constraint.is_equality():
                    glpk.glp_set_row_bnds(p, glpkConIndex, glpk.GLP_FX, rhs,rhs)
                elif constraint.is_increasing():
                    glpk.glp_set_row_bnds(p, glpkConIndex, glpk.GLP_UP, 0, rhs)
                elif constraint.is_decreasing():
                    glpk.glp_set_row_bnds(p, glpkConIndex, glpk.GLP_LO, rhs, 0)
                else:
                    assert False, "Unexpected constraint relation."

                # Set coefficients for current row.
                # Note that GLPK requires a glpk.intArray containing column
                # indices and a glpk.doubleArray of same size containing the
                # coefficients for the listed column index. The first element
                # of both arrays (with index 0) is skipped by GLPK.
                glpkVarIndicesArray = glpk.intArray(numColumns + 1)
                for i in range(numColumns):
                    glpkVarIndicesArray[i + 1] = glpkVarIndices[i]

                coefficientsArray = glpk.doubleArray(numColumns + 1)
                for i in range(numColumns):
                    coefficientsArray[i + 1] = coefficients[i]

                glpk.glp_set_mat_row(p, glpkConIndex, numColumns,
                    glpkVarIndicesArray, coefficientsArray)

            rowOffset += numRows
Esempio n. 10
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 def name(self, value):
     old_name = getattr(self, 'name', None)
     self._name = value
     if getattr(self, 'problem', None) is not None:
         glp_set_col_name(self.problem.problem, glp_find_col(self.problem.problem, old_name), str(value))
         self.problem.variables.update_key(old_name)
Esempio n. 11
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 def name(self, value):
     if getattr(self, 'problem', None) is not None:
         glp_set_col_name(self.problem.problem, glp_find_col(self.problem.problem, self.name), str(value))
     super(Variable, Variable).name.fset(self, value)
Esempio n. 12
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 def name(self, value):
     old_name = getattr(self, "name", None)
     super(Variable, Variable).name.fset(self, value)
     _glpk_validate_id(value)
     if getattr(self, 'problem', None) is not None:
         glp_set_col_name(self.problem.problem, glp_find_col(self.problem.problem, old_name), str(value))