Correct C++ update + reorganizing Module bindings

multipers/_slicer_nanobind.cpp

@@ -32,8 +32,10 @@
 #include "ext_interface/nanobind_registry_helpers.hpp"
 #include "ext_interface/nanobind_registry_runtime.hpp"
 #include "gudhi/Multi_parameter_filtered_complex.h"
+#include "gudhi/Multi_persistence/Box.h"
 #include "gudhi/slicer_conversion_core.hpp"
 #include "gudhi/slicer_helpers.h"
+#include "gudhi/Module_interface.h"
 #include <python_interfaces/numpy_utils.h>
 #include "multi_parameter_rank_invariant/hilbert_function.h"
 #include "multi_parameter_rank_invariant/rank_invariant.h"
@@ -306,7 +308,7 @@ nb::tuple dim_barcode_to_tuple(const Barcode& barcode) {
 
 template <typename Desc, typename Wrapper, typename Value>
 nb::tuple compute_persistence_on_slices(Wrapper& self,
-                                        const nb::ndarray<const Value, nb::ndim<2>, nb::any_contig>& values,
+                                        const nb::ndarray<const Value, nb::ndim<2> >& values,
                                         bool ignore_infinite_filtration_values) {
   using Barcode = decltype(self.truc.template get_flat_barcode<true, Value, false>());
   using Concrete = std::remove_reference_t<decltype(self.truc)>;
@@ -316,7 +318,7 @@ nb::tuple compute_persistence_on_slices(Wrapper& self,
     throw nb::value_error("Expected one filtration value per generator.");
   }
   std::vector<Barcode> barcodes(num_slices);
-  Numpy_2d_span<Value> view(values);
+  Numpy_2d_span view(values);
   {
     nb::gil_scoped_release release;
     if constexpr (Desc::is_vine) {
@@ -1900,7 +1902,7 @@ void bind_slicer_class(nb::module_& m, nb::list& available_slicers) {
       .def(
           "_compute_persistence_on_slices",
           [](Wrapper& self,
-             nb::ndarray<const Value, nb::ndim<2>, nb::any_contig> values,
+             nb::ndarray<const Value, nb::ndim<2> > values,
              bool ignore_infinite_filtration_values) -> nb::tuple {
             return compute_persistence_on_slices<Desc>(self, values, ignore_infinite_filtration_values);
           },
@@ -2112,7 +2114,7 @@ nb::tuple compute_rank_signed_measure_sparse(type_list<Ds...>,
 }
 
 template <typename Desc>
-nb::object module_approximation_from_desc(typename Desc::wrapper& wrapper,
+Gudhi::multi_persistence::Module_interface<double> module_approximation_from_desc(typename Desc::wrapper& wrapper,
                                           const std::vector<double>& direction,
                                           double max_error,
                                           Gudhi::multi_persistence::Box<double> box,
@@ -2129,12 +2131,12 @@ nb::object module_approximation_from_desc(typename Desc::wrapper& wrapper,
       mod = Gudhi::multiparameter::mma::multiparameter_module_approximation(
           wrapper.truc, direction, max_error, box, threshold, complete, verbose, n_jobs);
     }
-    return nb::cast(std::move(mod));
+    return {std::move(mod), box};
   }
 }
 
 template <typename... Ds>
-nb::object compute_module_approximation_from_slicer(type_list<Ds...>,
+Gudhi::multi_persistence::Module_interface<double> compute_module_approximation_from_slicer(type_list<Ds...>,
                                                     nb::handle slicer,
                                                     const std::vector<double>& direction,
                                                     double max_error,
@@ -2146,7 +2148,7 @@ nb::object compute_module_approximation_from_slicer(type_list<Ds...>,
   if (!has_slicer_template_id(slicer)) {
     throw std::runtime_error("Unsupported slicer type for module approximation.");
   }
-  return dispatch_slicer_by_template_id(template_id_of(slicer), [&]<typename D>() -> nb::object {
+  return dispatch_slicer_by_template_id(template_id_of(slicer), [&]<typename D>() -> Gudhi::multi_persistence::Module_interface<double> {
     auto& wrapper = nb::cast<typename D::wrapper&>(slicer);
     return module_approximation_from_desc<D>(wrapper, direction, max_error, box, threshold, complete, verbose, n_jobs);
   });

multipers/grids.py

@@ -667,28 +667,28 @@ def _push_pts_to_lines(pts, basepoints, directions=None, api=None, return_coordi
     return out, coordinates
 
 
-def evaluate_mod_in_grid(mod, grid, box=None):
-    """Given an MMA module, pushes it into the specified grid.
-    Useful for e.g., make it differentiable.
-
-    Input
-    -----
-     - mod: PyModule
-     - grid: Iterable of 1d array, for num_parameters
-    Ouput
-    -----
-    torch-compatible module in the format:
-    (num_degrees) x (num_interval of degree) x ((num_birth, num_parameter), (num_death, num_parameters))
-
-    """
-    (birth_sizes, death_sizes), births, deaths = mod.to_flat_idx(grid)
-    births = evaluate_in_grid(births, grid)
-    deaths = evaluate_in_grid(deaths, grid)
-    api = api_from_tensors(births, deaths)
-    diff_mod = tuple(
-        zip(
-            api.split_with_sizes(births, birth_sizes.tolist()),
-            api.split_with_sizes(deaths, death_sizes.tolist()),
-        )
-    )
-    return diff_mod
+# def evaluate_mod_in_grid(mod, grid, box=None):
+#     """Given an MMA module, pushes it into the specified grid.
+#     Useful for e.g., make it differentiable.
+
+#     Input
+#     -----
+#      - mod: PyModule
+#      - grid: Iterable of 1d array, for num_parameters
+#     Ouput
+#     -----
+#     torch-compatible module in the format:
+#     (num_degrees) x (num_interval of degree) x ((num_birth, num_parameter), (num_death, num_parameters))
+
+#     """
+#     (birth_sizes, death_sizes), births, deaths = mod.to_flat_idx(grid)
+#     births = evaluate_in_grid(births, grid)
+#     deaths = evaluate_in_grid(deaths, grid)
+#     api = api_from_tensors(births, deaths)
+#     diff_mod = tuple(
+#         zip(
+#             api.split_with_sizes(births, birth_sizes.tolist()),
+#             api.split_with_sizes(deaths, death_sizes.tolist()),
+#         )
+#     )
+#     return diff_mod