bugfix

include/xerus/misc/fileIO.h

@@ -110,7 +110,7 @@ namespace xerus { namespace misc {
     T deserialize(const std::string& _bytes) {
         T obj;
         std::string header = _bytes.substr(0, _bytes.find("\n"));
-        XERUS_REQUIRE(header == std::string("Xerus ") + misc::demangle_cxa(typeid(T).name()) + " serialized object.", "Invalid binary input. DBG: " << header);
+        XERUS_REQUIRE(header == std::string("Xerus ") + misc::demangle_cxa(typeid(T).name()) + " serialized object.", "Invalid binary input. \nExpected: \"" << std::string("Xerus ") + misc::demangle_cxa(typeid(T).name()) + " serialized object.\"\nGot: \"" << header << "\"");
         std::stringstream stream(_bytes.substr(_bytes.find("\n")+1));  // +1 because of the last \n
         XERUS_REQUIRE(stream, "Unexpected end of stream in load_from_file().");
         stream_reader(stream, obj, FileFormat::BINARY);

src/xerus/python/blocktt.cpp → src/xerus/python/blocktt.cpp.

@@ -29,31 +29,31 @@
 using namespace internal;
 
 void expose_blocktt() {
-	VECTOR_TO_PY(BlockTT, "BlockTTVector");
-
-	class_<BlockTT>("BlockTT")
-		.def(init<const std::vector<size_t>&, const std::vector<size_t>&, const size_t,const size_t>())
-		.def(init<const TTTensor &,const size_t,const size_t >())
-		.def("get_component", &BlockTT::get_component, return_value_policy<copy_const_reference>())
-		.def("set_component", &BlockTT::set_component)
-		.def("ranks", &BlockTT::ranks)
-		.def("rank", &BlockTT::rank)
-		.def("num_components", &BlockTT::num_components)
-		.def("get_core", &BlockTT::get_core)
-		.def("get_average_core", &BlockTT::get_average_core)
-		.def("get_average_tt", &BlockTT::get_average_tt)
-		.def("order", &BlockTT::order)
-		.def("move_core", static_cast<void (BlockTT::*)(const size_t,const double,const size_t)>(&BlockTT::move_core),
-			(arg("position"), arg("epsilon")=EPSILON, arg("maxRank")=std::numeric_limits<size_t>::max())
-		)
-		.def("average_core", &BlockTT::average_core)
-		.def("all_entries_valid", &BlockTT::all_entries_valid)
-		.def("frob_norm", &BlockTT::frob_norm)
-		.def("dofs", &BlockTT::dofs)
-
-		.def("move_core_left", &BlockTT::move_core_left)
-		.def("move_core_right", &BlockTT::move_core_left)
-	;
-
-	def("frob_norm", static_cast<value_t (*)(const BlockTT&)>(&frob_norm));
+    VECTOR_TO_PY(BlockTT, "BlockTTVector");
+
+    class_<BlockTT>("BlockTT")
+        .def(init<const std::vector<size_t>&, const std::vector<size_t>&, const size_t,const size_t>())
+        .def(init<const TTTensor &,const size_t,const size_t >())
+        .def("get_component", &BlockTT::get_component, return_value_policy<copy_const_reference>())
+        .def("set_component", &BlockTT::set_component)
+        .def("ranks", &BlockTT::ranks)
+        .def("rank", &BlockTT::rank)
+        .def("num_components", &BlockTT::num_components)
+        .def("get_core", &BlockTT::get_core)
+        .def("get_average_core", &BlockTT::get_average_core)
+        .def("get_average_tt", &BlockTT::get_average_tt)
+        .def("order", &BlockTT::order)
+        .def("move_core", static_cast<void (BlockTT::*)(const size_t,const double,const size_t)>(&BlockTT::move_core),
+            (arg("position"), arg("epsilon")=EPSILON, arg("maxRank")=std::numeric_limits<size_t>::max())
+        )
+        .def("average_core", &BlockTT::average_core)
+        .def("all_entries_valid", &BlockTT::all_entries_valid)
+        .def("frob_norm", &BlockTT::frob_norm)
+        .def("dofs", &BlockTT::dofs)
+
+        .def("move_core_left", &BlockTT::move_core_left)
+        .def("move_core_right", &BlockTT::move_core_left)
+    ;
+
+    def("frob_norm", static_cast<value_t (*)(const BlockTT&)>(&frob_norm));
 }

src/xerus/python/misc.cpp

@@ -79,9 +79,11 @@ void expose_misc(module& m) {
 	});
 
 	m.def("serialize", +[](const Tensor &_obj){ return bytes(misc::serialize(_obj)); }, arg("object"));
-	m.def("serialize", +[](const TensorNetwork &_obj){ return bytes(misc::serialize(_obj)); }, arg("object"));
 	m.def("serialize", +[](const TTTensor &_obj){ return bytes(misc::serialize(_obj)); }, arg("object"));
 	m.def("serialize", +[](const TTOperator &_obj){ return bytes(misc::serialize(_obj)); }, arg("object"));
+	m.def("serialize", +[](const HTTensor &_obj){ return bytes(misc::serialize(_obj)); }, arg("object"));
+	m.def("serialize", +[](const HTOperator &_obj){ return bytes(misc::serialize(_obj)); }, arg("object"));
+	m.def("serialize", +[](const TensorNetwork &_obj){ return bytes(misc::serialize(_obj)); }, arg("object"));
 
 	m.def("deserialize", +[](std::string _bytes){
 		// determine type stored in the file

src/xerus/python/python.cpp

@@ -26,7 +26,20 @@
 
 
 PYBIND11_MODULE(xerus, m) {
-	// m.doc() = "...";
+	m.doc() = "\
+The `xerus` library is a general purpose library for numerical calculations with higher order tensors, Tensor-Train Decompositions / Matrix Product States and general Tensor Networks.\n\
+The focus of development was the simple usability and adaptibility to any setting that requires higher order tensors or decompositions thereof.\n\
+\n\
+The key features include:\n\
+* Modern code and concepts incorporating many features of the `C++11` standard.\n\
+* Full python bindings with very similar syntax for easy transitions from and to c++.\n\
+* Calculation with tensors of arbitrary orders using an intuitive Einstein-like notation `A(i,j) = B(i,k,l) * C(k,j,l);`.\n\
+* Full implementation of the Tensor-Train decompositions (MPS) with all neccessary capabilities (including Algorithms like ALS, ADF and CG).\n\
+* Lazy evaluation of (multiple) tensor contractions featuring heuristics to automatically find efficient contraction orders.\n\
+* Direct integration of the `blas` and `lapack`, as high performance linear algebra backends.\n\
+* Fast sparse tensor calculation by usage of the `suiteSparse` sparse matrix capabilities.\n\
+* Capabilites to handle arbitrary Tensor Networks.\n\
+";
 
 	// xerus version
 	m.attr("VERSION_MAJOR") = VERSION_MAJOR;