Better naming for sparse model building

lib/stormpy/__init__.py

@@ -22,6 +22,7 @@ except ImportError:
 
 core._set_up("")
 
+
 def _convert_sparse_model(model, parametric=False):
     """
     Convert (parametric) model in sparse representation into model corresponding to exact model type.
@@ -68,9 +69,9 @@ def build_model(symbolic_description, properties=None):
 
     if properties:
         formulae = [prop.raw_formula for prop in properties]
-        intermediate = core._build_sparse_model_from_prism_program(symbolic_description, formulae)
+        intermediate = core._build_sparse_model_from_symbolic_description(symbolic_description, formulae)
     else:
-        intermediate = core._build_sparse_model_from_prism_program(symbolic_description)
+        intermediate = core._build_sparse_model_from_symbolic_description(symbolic_description)
     return _convert_sparse_model(intermediate, parametric=False)
 
 
@@ -87,9 +88,9 @@ def build_parametric_model(symbolic_description, properties=None):
 
     if properties:
         formulae = [prop.raw_formula for prop in properties]
-        intermediate = core._build_sparse_parametric_model_from_prism_program(symbolic_description, formulae)
+        intermediate = core._build_sparse_parametric_model_from_symbolic_description(symbolic_description, formulae)
     else:
-        intermediate = core._build_sparse_parametric_model_from_prism_program(symbolic_description)
+        intermediate = core._build_sparse_parametric_model_from_symbolic_description(symbolic_description)
     return _convert_sparse_model(intermediate, parametric=True)
 
 
@@ -115,7 +116,6 @@ def build_parametric_model_from_drn(file):
     return _convert_sparse_model(intermediate, parametric=True)
 
 
-
 def perform_bisimulation(model, properties, bisimulation_type):
     """
     Perform bisimulation on model.

src/core/core.cpp

@@ -46,9 +46,9 @@ void define_parse(py::module& m) {
     ;
 }
 
-// Thin wrapper for model building using one formula as argument
+// Thin wrapper for model building using sparse representation
 template<typename ValueType>
-std::shared_ptr<storm::models::ModelBase> buildSparseModel(storm::storage::SymbolicModelDescription const& modelDescription, std::vector<std::shared_ptr<storm::logic::Formula const>> const& formulas, bool jit = false, bool doctor = false) {
+std::shared_ptr<storm::models::sparse::Model<ValueType>> buildSparseModel(storm::storage::SymbolicModelDescription const& modelDescription, std::vector<std::shared_ptr<storm::logic::Formula const>> const& formulas, bool jit = false, bool doctor = false) {
     if (formulas.empty()) {
         // Build all labels and rewards
         storm::builder::BuilderOptions options(true, true);
@@ -61,8 +61,8 @@ std::shared_ptr<storm::models::ModelBase> buildSparseModel(storm::storage::Symbo
 
 void define_build(py::module& m) {
     // Build model
-    m.def("_build_sparse_model_from_prism_program", &buildSparseModel<double>, "Build the model", py::arg("model_description"), py::arg("formulas") = std::vector<std::shared_ptr<storm::logic::Formula const>>(), py::arg("use_jit") = false, py::arg("doctor") = false);
-    m.def("_build_sparse_parametric_model_from_prism_program", &buildSparseModel<storm::RationalFunction>, "Build the parametric model", py::arg("model_description"), py::arg("formulas") = std::vector<std::shared_ptr<storm::logic::Formula const>>(), py::arg("use_jit") = false, py::arg("doctor") = false);
+    m.def("_build_sparse_model_from_symbolic_description", &buildSparseModel<double>, "Build the model in sparse representation", py::arg("model_description"), py::arg("formulas") = std::vector<std::shared_ptr<storm::logic::Formula const>>(), py::arg("use_jit") = false, py::arg("doctor") = false);
+    m.def("_build_sparse_parametric_model_from_symbolic_description", &buildSparseModel<storm::RationalFunction>, "Build the parametric model in sparse representation", py::arg("model_description"), py::arg("formulas") = std::vector<std::shared_ptr<storm::logic::Formula const>>(), py::arg("use_jit") = false, py::arg("doctor") = false);
     m.def("_build_sparse_model_from_drn", &storm::api::buildExplicitDRNModel<double>, "Build the model from DRN", py::arg("file"));
     m.def("_build_sparse_parametric_model_from_drn", &storm::api::buildExplicitDRNModel<storm::RationalFunction>, "Build the parametric model from DRN", py::arg("file"));
     m.def("build_sparse_model_from_explicit", &storm::api::buildExplicitModel<double>, "Build the model model from explicit input", py::arg("transition_file"), py::arg("labeling_file"), py::arg("state_reward_file") = "", py::arg("transition_reward_file") = "", py::arg("choice_labeling_file") = "");

src/core/core.h

@@ -1,5 +1,4 @@
-#ifndef PYTHON_CORE_CORE_H_
-#define PYTHON_CORE_CORE_H_
+#pragma once
 
 #include "common.h"
 
@@ -8,5 +7,3 @@ void define_parse(py::module& m);
 void define_build(py::module& m);
 void define_export(py::module& m);
 void define_optimality_type(py::module& m);
-
-#endif /* PYTHON_CORE_CORE_H_ */

tests/storage/test_model.py

@@ -4,7 +4,7 @@ from helpers.helper import get_example_path
 import pytest
 
 
-class TestModel:
+class TestSparseModel:
     def test_build_dtmc_from_prism_program(self):
         program = stormpy.parse_prism_program(get_example_path("dtmc", "die.pm"))
         model = stormpy.build_model(program)
@@ -26,7 +26,7 @@ class TestModel:
         assert not model.supports_parameters
         assert type(model) is stormpy.SparseDtmc
 
-    def test_build_dtmc_from_prism_program_formulas(self):
+    def test_build_dtmc_from_prism_program_reward_formulas(self):
         program = stormpy.parse_prism_program(get_example_path("dtmc", "die.pm"))
         prop = "R=? [F \"done\"]"
         properties = stormpy.parse_properties_for_prism_program(prop, program, None)
@@ -65,16 +65,6 @@ class TestModel:
         assert not model.supports_parameters
         assert type(model) is stormpy.SparseDtmc
 
-    def test_build_dtmc(self):
-        program = stormpy.parse_prism_program(get_example_path("dtmc", "die.pm"))
-        formulas = stormpy.parse_properties_for_prism_program("P=? [ F \"one\" ]", program)
-        model = stormpy.build_model(program, formulas)
-        assert model.nr_states == 13
-        assert model.nr_transitions == 20
-        assert model.model_type == stormpy.ModelType.DTMC
-        assert not model.supports_parameters
-        assert type(model) is stormpy.SparseDtmc
-
     def test_build_dtmc_with_undefined_constants(self):
         jani_model, properties = stormpy.parse_jani_model(get_example_path("dtmc", "brp.jani"))
         assert jani_model.has_undefined_constants