Conclude JumpModel

test/Project.toml

@@ -6,6 +6,7 @@ version = "0.1.0"
 [deps]
 HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
 HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MIPLearn = "2b1277c3-b477-4c49-a15e-7ba350325c68"

test/src/solvers/test_jump.jl

@@ -1,3 +1,6 @@
+using JuMP
+import MIPLearn: from_str_array, to_str_array
+
 function build_model()
     data = SetCoverData(
         costs = [5, 10, 12, 6, 8],
@@ -12,6 +15,10 @@ end
 
 function test_solvers_jump()
     test_solvers_jump_extract()
+    test_solvers_jump_add_constrs()
+    test_solvers_jump_fix_vars()
+    test_solvers_jump_warm_starts()
+    test_solvers_jump_write()
 end
 
 function test_solvers_jump_extract()
@@ -30,7 +37,7 @@ function test_solvers_jump_extract()
     end
 
     function test_str_array(key, expected)
-        actual = MIPLearn.from_str_array(h5.get_array(key))
+        actual = from_str_array(h5.get_array(key))
         @debug actual, expected
         @test actual !== nothing
         @test all(actual .== expected)
@@ -74,7 +81,7 @@ function test_solvers_jump_extract()
     test_array("lp_var_reduced_costs", [-5, 0, 6, 0, 2])
     test_array("lp_var_values", [1, 0, 0, 1, 0])
     test_str_array("lp_var_basis_status", ["U", "B", "L", "B", "L"])
-    test_str_array("lp_constr_basis_status", ["B","N","N"])
+    test_str_array("lp_constr_basis_status", ["B", "N", "N"])
     test_array("lp_constr_sa_rhs_up", [2, 2, 1])
     test_array("lp_constr_sa_rhs_down", [-Inf, 1, 0])
     test_array("lp_var_sa_obj_up", [10, Inf, Inf, 8, Inf])
@@ -96,3 +103,54 @@ function test_solvers_jump_extract()
     mip_wallclock_time = h5.get_scalar("mip_wallclock_time")
     @test mip_wallclock_time >= 0
 end
+
+function test_solvers_jump_add_constrs()
+    h5 = H5File(tempname(), "w")
+    model = build_model()
+    model.extract_after_load(h5)
+    model.add_constrs(
+        to_str_array(["x[2]", "x[3]"]),
+        [
+            0 1
+            1 0
+        ],
+        to_str_array(["=", "="]),
+        [0, 0],
+    )
+    model.optimize()
+    model.extract_after_mip(h5)
+    @test all(h5.get_array("mip_var_values") .≈ [1, 0, 0, 0, 1])
+end
+
+function test_solvers_jump_fix_vars()
+    h5 = H5File(tempname(), "w")
+    model = build_model()
+    model.extract_after_load(h5)
+    model.fix_variables(
+        to_str_array(["x[2]", "x[3]"]),
+        [0, 0],
+    )
+    model.optimize()
+    model.extract_after_mip(h5)
+    @test all(h5.get_array("mip_var_values") .≈ [1, 0, 0, 0, 1])
+end
+
+function test_solvers_jump_warm_starts()
+    # TODO: Check presence of warm start on log file
+    h5 = H5File(tempname(), "w")
+    model = build_model()
+    model.extract_after_load(h5)
+    model.set_warm_starts(
+        to_str_array(["x[0]", "x[1]", "x[2]", "x[3]", "x[4]"]),
+        [1 0 0 0 1],
+    )
+    model.optimize()
+end
+
+function test_solvers_jump_write()
+    mps_filename = "$(tempname()).mps"
+    model = build_model()
+    model.write(mps_filename)
+    @test isfile(mps_filename)
+    rm(mps_filename)
+end