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Feature/tests for restore bug #467

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merged 5 commits into from
Jan 15, 2024
Merged

Feature/tests for restore bug #467

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4b28555
improve incomplete update tests
mgovers Jan 11, 2024
630f4c6
test for repro restore bug
mgovers Jan 12, 2024
6378ec2
test for repro restore bug
mgovers Jan 12, 2024
0a0a6f4
refactor tests
mgovers Jan 12, 2024
725eb87
refactor tests
mgovers Jan 12, 2024
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218 changes: 170 additions & 48 deletions tests/cpp_unit_tests/test_main_model.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1089,37 +1089,44 @@ TEST_CASE("Test main model - runtime dispatch") {
}
}

TEST_CASE("Test main model - incomplete input but complete dataset") {
namespace {
auto incomplete_input_model(State const& state) -> MainModel {
MainModel main_model{50.0};

std::vector<SourceInput> const incomplete_source_input{{6, 1, 1, nan, nan, 1e12, nan, nan},
{10, 3, 1, nan, nan, 1e12, nan, nan}};
std::vector<SymLoadGenInput> incomplete_sym_load_input{{7, 3, 1, LoadGenType::const_y, nan, 0.0}};
std::vector<AsymLoadGenInput> incomplete_asym_load_input{
{8, 3, 1, LoadGenType::const_y, RealValue<false>{nan}, RealValue<false>{0.0}}};

ConstDataset input_data;
main_model.add_component<Node>(state.node_input);
main_model.add_component<Line>(state.line_input);
main_model.add_component<Link>(state.link_input);
main_model.add_component<Source>(incomplete_source_input);
main_model.add_component<SymLoad>(incomplete_sym_load_input);
main_model.add_component<AsymLoad>(incomplete_asym_load_input);
main_model.add_component<Shunt>(state.shunt_input);
main_model.set_construction_complete();

return main_model;
}
} // namespace

TEST_CASE("Test main model - incomplete input") {
using CalculationMethod::iterative_current;
using CalculationMethod::linear;
using CalculationMethod::linear_current;
using CalculationMethod::newton_raphson;

State state;
auto main_model = default_model(state);

std::vector<SourceInput> const incomplete_source_input{{6, 1, 1, nan, nan, 1e12, nan, nan},
{10, 3, 1, nan, nan, 1e12, nan, nan}};
std::vector<SymLoadGenInput> incomplete_sym_load_input{{7, 3, 1, LoadGenType::const_y, nan, nan}};
std::vector<AsymLoadGenInput> incomplete_asym_load_input{
{8, 3, 1, LoadGenType::const_y, RealValue<false>{nan}, RealValue<false>{nan}}};

ConstDataset input_data;
input_data["node"] = DataPointer<true>{state.node_input.data(), static_cast<Idx>(state.node_input.size())};
input_data["line"] = DataPointer<true>{state.line_input.data(), static_cast<Idx>(state.line_input.size())};
input_data["link"] = DataPointer<true>{state.link_input.data(), static_cast<Idx>(state.link_input.size())};
input_data["source"] =
DataPointer<true>{incomplete_source_input.data(), static_cast<Idx>(incomplete_source_input.size())};
input_data["sym_load"] =
DataPointer<true>{incomplete_sym_load_input.data(), static_cast<Idx>(incomplete_sym_load_input.size())};
input_data["asym_load"] =
DataPointer<true>{incomplete_asym_load_input.data(), static_cast<Idx>(incomplete_asym_load_input.size())};
input_data["shunt"] = DataPointer<true>{state.shunt_input.data(), static_cast<Idx>(state.shunt_input.size())};
auto test_model = incomplete_input_model(state);

std::vector<SourceUpdate> complete_source_update{{6, 1, 1.05, nan}, {10, 1, 1.05, 0}};
std::vector<SymLoadGenUpdate> complete_sym_load_update{{7, 1, 0.5e6, 0.0}};
std::vector<SymLoadGenUpdate> complete_sym_load_update{{7, 1, 0.5e6, nan}};
std::vector<AsymLoadGenUpdate> complete_asym_load_update{
{8, 1, RealValue<false>{0.5e6 / 3.0}, RealValue<false>{0.0}}};
{8, 1, RealValue<false>{0.5e6 / 3.0}, RealValue<false>{nan}}};

ConstDataset update_data;
update_data["source"] =
Expand All @@ -1129,13 +1136,25 @@ TEST_CASE("Test main model - incomplete input but complete dataset") {
update_data["asym_load"] =
DataPointer<true>{complete_asym_load_update.data(), static_cast<Idx>(complete_asym_load_update.size())};

MainModel test_model{50.0, input_data};
std::vector<SourceUpdate> incomplete_source_update{{6, na_IntS, nan, nan}, {10, na_IntS, nan, nan}};
std::vector<SymLoadGenUpdate> incomplete_sym_load_update{{7, na_IntS, nan, nan}};
std::vector<AsymLoadGenUpdate> incomplete_asym_load_update{
{8, na_IntS, RealValue<false>{nan}, RealValue<false>{nan}}};

ConstDataset incomplete_update_data;
incomplete_update_data["source"] =
DataPointer<true>{incomplete_source_update.data(), static_cast<Idx>(incomplete_source_update.size())};
incomplete_update_data["sym_load"] =
DataPointer<true>{incomplete_sym_load_update.data(), static_cast<Idx>(incomplete_sym_load_update.size())};
incomplete_update_data["asym_load"] =
DataPointer<true>{incomplete_asym_load_update.data(), static_cast<Idx>(incomplete_asym_load_update.size())};

MainModel const ref_model{main_model};

Dataset test_result_data;
Dataset ref_result_data;

SUBCASE("Symmetrical") {
SUBCASE("Symmetrical - Complete") {
std::vector<NodeOutput<true>> test_sym_node(state.sym_node.size());
std::vector<NodeOutput<true>> ref_sym_node(state.sym_node.size());
test_result_data["node"] = DataPointer<false>{test_sym_node.data(), static_cast<Idx>(test_sym_node.size())};
Expand Down Expand Up @@ -1166,7 +1185,7 @@ TEST_CASE("Test main model - incomplete input but complete dataset") {
CHECK(test_sym_node[2].u_pu == doctest::Approx(ref_sym_node[2].u_pu));
}

SUBCASE("Asymmetrical") {
SUBCASE("Asymmetrical - Complete") {
std::vector<NodeOutput<false>> test_asym_node(state.asym_node.size());
std::vector<NodeOutput<false>> ref_asym_node(state.asym_node.size());
test_result_data["node"] = DataPointer<false>{test_asym_node.data(), static_cast<Idx>(test_asym_node.size())};
Expand All @@ -1192,43 +1211,146 @@ TEST_CASE("Test main model - incomplete input but complete dataset") {
main_model.calculate_power_flow<false>(1e-8, 20, newton_raphson, ref_result_data, update_data, -1);
}

CHECK(test_asym_node[0].u_pu(0) == doctest::Approx(ref_asym_node[0].u_pu(0)));
CHECK(test_asym_node[0].u_pu(1) == doctest::Approx(ref_asym_node[0].u_pu(1)));
CHECK(test_asym_node[0].u_pu(2) == doctest::Approx(ref_asym_node[0].u_pu(2)));
CHECK(test_asym_node[1].u_pu(0) == doctest::Approx(ref_asym_node[1].u_pu(0)));
CHECK(test_asym_node[1].u_pu(1) == doctest::Approx(ref_asym_node[1].u_pu(1)));
CHECK(test_asym_node[1].u_pu(2) == doctest::Approx(ref_asym_node[1].u_pu(2)));
CHECK(test_asym_node[2].u_pu(0) == doctest::Approx(ref_asym_node[2].u_pu(0)));
CHECK(test_asym_node[2].u_pu(1) == doctest::Approx(ref_asym_node[2].u_pu(1)));
CHECK(test_asym_node[2].u_pu(2) == doctest::Approx(ref_asym_node[2].u_pu(2)));
for (auto component_idx : {0, 1, 2}) {
CAPTURE(component_idx);

for (auto phase_idx : {0, 1, 2}) {
CAPTURE(phase_idx);

CHECK(test_asym_node[component_idx].u_pu(phase_idx) ==
doctest::Approx(ref_asym_node[component_idx].u_pu(phase_idx)));
}
}
}

SUBCASE("Symmetrical - Incomplete") {
update_data = {};

std::vector<NodeOutput<true>> test_sym_node(state.sym_node.size());
std::vector<NodeOutput<true>> ref_sym_node(state.sym_node.size());
test_result_data["node"] = DataPointer<false>{test_sym_node.data(), static_cast<Idx>(test_sym_node.size())};
ref_result_data["node"] = DataPointer<false>{ref_sym_node.data(), static_cast<Idx>(ref_sym_node.size())};

CHECK_THROWS_AS(test_model.calculate_power_flow<true>(1e-8, 1, linear), SparseMatrixError);
CHECK_THROWS_AS(test_model.calculate_power_flow<true>(1e-8, 1, linear, test_result_data), SparseMatrixError);
CHECK_THROWS_AS(test_model.calculate_power_flow<true>(1e-8, 1, linear, test_result_data, update_data),
SparseMatrixError);
SUBCASE("Direct call") {
CHECK_THROWS_AS(test_model.calculate_power_flow<true>(1e-8, 1, linear), SparseMatrixError);
}
SUBCASE("Target dataset") {
CHECK_THROWS_AS(test_model.calculate_power_flow<true>(1e-8, 1, linear, test_result_data),
SparseMatrixError);
}
SUBCASE("Empty update dataset") {
update_data = {};

CHECK_THROWS_AS(test_model.calculate_power_flow<true>(1e-8, 1, linear, test_result_data, update_data),
SparseMatrixError);
}
SUBCASE("Update dataset") {
CHECK_THROWS_AS(
test_model.calculate_power_flow<true>(1e-8, 1, linear, test_result_data, incomplete_update_data),
BatchCalculationError);
}
}

SUBCASE("Asymmetrical - Incomplete") {
update_data = {};

std::vector<NodeOutput<false>> test_sym_node(state.sym_node.size());
std::vector<NodeOutput<false>> ref_sym_node(state.sym_node.size());
test_result_data["node"] = DataPointer<false>{test_sym_node.data(), static_cast<Idx>(test_sym_node.size())};

SUBCASE("Direct call") {
CHECK_THROWS_AS(test_model.calculate_power_flow<false>(1e-8, 1, linear), SparseMatrixError);
}
SUBCASE("Target dataset") {
CHECK_THROWS_AS(test_model.calculate_power_flow<false>(1e-8, 1, linear, test_result_data),
SparseMatrixError);
}
SUBCASE("Empty update dataset") {
update_data = {};

CHECK_THROWS_AS(test_model.calculate_power_flow<false>(1e-8, 1, linear, test_result_data, update_data),
SparseMatrixError);
}
SUBCASE("Update dataset") {
CHECK_THROWS_AS(
test_model.calculate_power_flow<false>(1e-8, 1, linear, test_result_data, incomplete_update_data),
BatchCalculationError);
}
}
}

TEST_CASE("Incomplete followed by complete") {
using CalculationMethod::linear;

State state;
auto main_model = default_model(state);
auto test_model = incomplete_input_model(state);

constexpr Idx batch_size = 2;

std::vector<SourceUpdate> mixed_source_update{
{6, 1, nan, nan}, {10, 1, nan, nan}, {6, 1, 1.05, nan}, {10, 1, 1.05, 0}};
std::vector<SymLoadGenUpdate> mixed_sym_load_update{{7, 1, nan, 1.0}, {7, 1, 0.5e6, nan}};
std::vector<AsymLoadGenUpdate> mixed_asym_load_update{{8, 1, RealValue<false>{nan}, RealValue<false>{1.0}},
{8, 1, RealValue<false>{0.5e6 / 3.0}, RealValue<false>{nan}}};

auto const source_indptr = IdxVector{0, 0, static_cast<Idx>(mixed_source_update.size())};

REQUIRE(source_indptr.size() == batch_size + 1);

ConstDataset mixed_update_data;
mixed_update_data["source"] = DataPointer<true>{mixed_source_update.data(), batch_size, 2};
mixed_update_data["sym_load"] = DataPointer<true>{mixed_sym_load_update.data(), batch_size, 1};
mixed_update_data["asym_load"] = DataPointer<true>{mixed_asym_load_update.data(), batch_size, 1};

ConstDataset second_scenario_update_data;
second_scenario_update_data["source"] = DataPointer<true>{mixed_source_update.data() + 2, 2};
second_scenario_update_data["sym_load"] = DataPointer<true>{mixed_sym_load_update.data() + 1, 1};
second_scenario_update_data["asym_load"] = DataPointer<true>{mixed_asym_load_update.data() + 1, 1};

Dataset test_result_data;
Dataset ref_result_data;

SUBCASE("Symmetrical") {
std::vector<NodeOutput<true>> test_sym_node(batch_size * state.sym_node.size(),
{na_IntID, na_IntS, nan, nan, nan, nan, nan});
std::vector<NodeOutput<true>> ref_sym_node(state.sym_node.size(), {na_IntID, na_IntS, nan, nan, nan, nan, nan});
test_result_data["node"] =
DataPointer<false>{test_sym_node.data(), batch_size, static_cast<Idx>(state.sym_node.size())};
ref_result_data["node"] = DataPointer<false>{ref_sym_node.data(), static_cast<Idx>(ref_sym_node.size())};

CHECK_THROWS_AS(test_model.calculate_power_flow<false>(1e-8, 1, linear), SparseMatrixError);
CHECK_THROWS_AS(test_model.calculate_power_flow<false>(1e-8, 1, linear, test_result_data), SparseMatrixError);
CHECK_THROWS_AS(test_model.calculate_power_flow<false>(1e-8, 1, linear, test_result_data, update_data),
SparseMatrixError);
CHECK_THROWS_AS(test_model.calculate_power_flow<true>(1e-8, 1, linear, test_result_data, mixed_update_data),
BatchCalculationError);
main_model.calculate_power_flow<true>(1e-8, 1, linear, ref_result_data, second_scenario_update_data, -1);

CHECK(is_nan(test_sym_node[0].u_pu));
CHECK(is_nan(test_sym_node[1].u_pu));
CHECK(is_nan(test_sym_node[2].u_pu));
CHECK(test_sym_node[state.sym_node.size() + 0].u_pu == doctest::Approx(ref_sym_node[0].u_pu));
CHECK(test_sym_node[state.sym_node.size() + 1].u_pu == doctest::Approx(ref_sym_node[1].u_pu));
CHECK(test_sym_node[state.sym_node.size() + 2].u_pu == doctest::Approx(ref_sym_node[2].u_pu));
}

SUBCASE("Asymmetrical") {
std::vector<NodeOutput<false>> test_asym_node(
batch_size * state.sym_node.size(), {na_IntID, na_IntS, RealValue<false>{nan}, RealValue<false>{nan},
RealValue<false>{nan}, RealValue<false>{nan}, RealValue<false>{nan}});
std::vector<NodeOutput<false>> ref_asym_node(
state.sym_node.size(), {na_IntID, na_IntS, RealValue<false>{nan}, RealValue<false>{nan},
RealValue<false>{nan}, RealValue<false>{nan}, RealValue<false>{nan}});
test_result_data["node"] =
DataPointer<false>{test_asym_node.data(), batch_size, static_cast<Idx>(state.sym_node.size())};
ref_result_data["node"] = DataPointer<false>{ref_asym_node.data(), static_cast<Idx>(ref_asym_node.size())};

CHECK_THROWS_AS(test_model.calculate_power_flow<false>(1e-8, 1, linear, test_result_data, mixed_update_data),
BatchCalculationError);
main_model.calculate_power_flow<false>(1e-8, 1, linear, ref_result_data, second_scenario_update_data, -1);

for (auto component_idx : {0, 1, 2}) {
CAPTURE(component_idx);

CHECK(is_nan(test_asym_node[component_idx].u_pu));

for (auto phase_idx : {0, 1, 2}) {
CAPTURE(phase_idx);

CHECK(test_asym_node[state.asym_node.size() + component_idx].u_pu(phase_idx) ==
doctest::Approx(ref_asym_node[component_idx].u_pu(phase_idx)));
}
}
}
}

Expand Down