PKG Add optlang package (#1093)

packages/glpk/meta.yaml

@@ -0,0 +1,13 @@
+package:
+  name: glpk
+  version: 4.65
+
+source:
+  sha256: 4281e29b628864dfe48d393a7bedd781e5b475387c20d8b0158f329994721a10
+  url: https://ftp.gnu.org/gnu/glpk/glpk-4.65.tar.gz
+
+build:
+  library: true
+  script: |
+     CFLAGS="-fPIC" emconfigure ./configure  --prefix=$PWD
+     emmake make -j ${PYODIDE_JOBS:-3}

packages/optlang/meta.yaml

@@ -0,0 +1,19 @@
+package:
+  name: optlang
+  version: 1.4.7
+
+source:
+  sha256: 0c9d7aae9babd5f9eac296b6f975a0e475545ac7ced9790f43796671157eb017
+  url: https://files.pythonhosted.org/packages/47/85/9d028fbc971b1db9b8c3e58072237e8a7fda5cd936dd73f0b179805b5464/optlang-1.4.7.tar.gz
+
+requirements:
+  run:
+    - sympy
+    - six
+    - swiglpk
+
+test:
+  imports:
+    - optlang
+    - optlang.glpk_interface
+    - optlang.symbolics

packages/optlang/test_optlang.py

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+import pytest
+
+
+def test_optlang(selenium):
+    selenium.load_package("optlang")
+    selenium.run(
+        """
+        from optlang import Model, Variable, Constraint, Objective
+
+        # All the (symbolic) variables are declared, with a name and optionally a lower and/or upper bound.
+        x1 = Variable('x1', lb=0)
+        x2 = Variable('x2', lb=0)
+        x3 = Variable('x3', lb=0)
+
+        # A constraint is constructed from an expression of variables and a lower and/or upper bound (lb and ub).
+        c1 = Constraint(x1 + x2 + x3, ub=100)
+        c2 = Constraint(10 * x1 + 4 * x2 + 5 * x3, ub=600)
+        c3 = Constraint(2 * x1 + 2 * x2 + 6 * x3, ub=300)
+
+        # An objective can be formulated
+        obj = Objective(10 * x1 + 6 * x2 + 4 * x3, direction='max')
+
+        # Variables, constraints and objective are combined in a Model object, which can subsequently be optimized.
+        model = Model(name='Simple model')
+        model.objective = obj
+        model.add([c1, c2, c3])
+
+        status = model.optimize()
+        """
+    )
+    result = selenium.run("model.status")
+    assert result == "optimal"
+    result = selenium.run("model.objective.value")
+    assert result == pytest.approx(733.3333, abs=1e-4)
+    result = selenium.run("model.variables['x1'].primal")
+    assert result == pytest.approx(33.3333, abs=1e-4)
+    result = selenium.run("model.variables['x2'].primal")
+    assert result == pytest.approx(66.6667, abs=1e-4)
+    result = selenium.run("model.variables['x3'].primal")
+    assert result == pytest.approx(0.0000, abs=1e-4)

packages/swiglpk/meta.yaml

@@ -0,0 +1,20 @@
+package:
+  name: swiglpk
+  version: 4.65.1
+
+source:
+  sha256: 0216db2930a6fe2c07ac7f0e28e76e9a2711a647836a3a4067113091c7ae221e
+  url: https://files.pythonhosted.org/packages/0e/c9/9b0ec3e2ca942b6d067e84e52d72818fa9c3a1a1524671fcbec4841b54b2/swiglpk-4.65.1.tar.gz
+  extras: 
+    - [../glpk/build/glpk-4.65/src/glpk.h, ./glpk.h]
+
+build:
+  ldflags: -L../../../glpk/build/glpk-4.65/src/.libs/
+
+requirements:
+  run:
+    - glpk
+
+test:
+  imports:
+    - swiglpk

packages/swiglpk/test_swiglpk.py

@@ -0,0 +1,48 @@
+def test_swiglpk(selenium):
+    selenium.load_package("swiglpk")
+    selenium.run(
+        """
+        from swiglpk import *
+
+        ia = intArray(1+1000); ja = intArray(1+1000);
+        ar = doubleArray(1+1000);
+        lp = glp_create_prob();
+        glp_set_prob_name(lp, "sample");
+        glp_set_obj_dir(lp, GLP_MAX);
+        glp_add_rows(lp, 3);
+        glp_set_row_name(lp, 1, "p");
+        glp_set_row_bnds(lp, 1, GLP_UP, 0.0, 100.0);
+        glp_set_row_name(lp, 2, "q");
+        glp_set_row_bnds(lp, 2, GLP_UP, 0.0, 600.0);
+        glp_set_row_name(lp, 3, "r");
+        glp_set_row_bnds(lp, 3, GLP_UP, 0.0, 300.0);
+        glp_add_cols(lp, 3);
+        glp_set_col_name(lp, 1, "x1");
+        glp_set_col_bnds(lp, 1, GLP_LO, 0.0, 0.0);
+        glp_set_obj_coef(lp, 1, 10.0);
+        glp_set_col_name(lp, 2, "x2");
+        glp_set_col_bnds(lp, 2, GLP_LO, 0.0, 0.0);
+        glp_set_obj_coef(lp, 2, 6.0);
+        glp_set_col_name(lp, 3, "x3");
+        glp_set_col_bnds(lp, 3, GLP_LO, 0.0, 0.0);
+        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_load_matrix(lp, 9, ia, ja, ar);
+        glp_simplex(lp, None);
+        Z = glp_get_obj_val(lp);
+        x1 = glp_get_col_prim(lp, 1);
+        x2 = glp_get_col_prim(lp, 2);
+        x3 = glp_get_col_prim(lp, 3);
+        glp_delete_prob(lp);
+        """
+    )
+    result = selenium.run("""'Z = %g; x1 = %g; x2 = %g; x3 = %g' % (Z, x1, x2, x3)""")
+    assert result == "Z = 733.333; x1 = 33.3333; x2 = 66.6667; x3 = 0"