Rename dim to ambient_dim for sphere (to be consistent with dim in torus)

2 files changed, 10 insertions, 10 deletions

diff --git a/src/python/example/alpha_complex_from_generated_points_on_sphere_example.py b/src/python/example/alpha_complex_from_generated_points_on_sphere_example.py
index e73584d3..267e6436 100644
--- a/src/python/example/alpha_complex_from_generated_points_on_sphere_example.py
+++ b/src/python/example/alpha_complex_from_generated_points_on_sphere_example.py
@@ -22,7 +22,7 @@ print("#####################################################################")
 print("AlphaComplex creation from generated points on sphere")
 
 
-gen_points = points.sphere(n_samples = 50, dim = 2, radius = 1, sample = "random")
+gen_points = points.sphere(n_samples = 50, ambient_dim = 2, radius = 1, sample = "random")
 
 # Create an alpha complex
 alpha_complex = AlphaComplex(points = gen_points)
diff --git a/src/python/gudhi/datasets/generators/points.cc b/src/python/gudhi/datasets/generators/points.cc
index f02c7d73..e2626b09 100644
--- a/src/python/gudhi/datasets/generators/points.cc
+++ b/src/python/gudhi/datasets/generators/points.cc
@@ -21,27 +21,27 @@ namespace py = pybind11;
 
 typedef CGAL::Epick_d< CGAL::Dynamic_dimension_tag > Kern;
 
-py::array_t<double> generate_points_on_sphere(size_t n_samples, int dim, double radius, std::string sample) {
+py::array_t<double> generate_points_on_sphere(size_t n_samples, int ambient_dim, double radius, std::string sample) {
     
     if (sample != "random") {
         throw pybind11::value_error("sample type is not supported");
     }
 
-    py::array_t<double> points({n_samples, (size_t)dim});
+    py::array_t<double> points({n_samples, (size_t)ambient_dim});
 
     py::buffer_info buf = points.request();
     double *ptr = static_cast<double *>(buf.ptr);
 
     GUDHI_CHECK(n_samples == buf.shape[0], "Py array first dimension not matching n_samples on sphere");
-    GUDHI_CHECK(dim == buf.shape[1], "Py array second dimension not matching the ambient space dimension");
+    GUDHI_CHECK(ambient_dim == buf.shape[1], "Py array second dimension not matching the ambient space dimension");
 
 
     py::gil_scoped_release release;
-    auto points_generated = Gudhi::generate_points_on_sphere_d<Kern>(n_samples, dim, radius);
+    auto points_generated = Gudhi::generate_points_on_sphere_d<Kern>(n_samples, ambient_dim, radius);
 
     for (size_t i = 0; i < n_samples; i++)
-        for (int j = 0; j < dim; j++)
-            ptr[i*dim+j] = points_generated[i][j];
+        for (int j = 0; j < ambient_dim; j++)
+            ptr[i*ambient_dim+j] = points_generated[i][j];
 
     return points;
 }
@@ -49,15 +49,15 @@ py::array_t<double> generate_points_on_sphere(size_t n_samples, int dim, double
 PYBIND11_MODULE(points, m) {
       m.attr("__license__") = "LGPL v3";
       m.def("sphere", &generate_points_on_sphere,
-          py::arg("n_samples"), py::arg("dim"),
+          py::arg("n_samples"), py::arg("ambient_dim"),
           py::arg("radius") = 1, py::arg("sample") = "random",
           R"pbdoc(
     Generate random i.i.d. points uniformly on a (d-1)-sphere in R^d
 
     :param n_samples: The number of points to be generated.
     :type n_samples: integer
-    :param dim: The ambient dimension d.
-    :type dim: integer
+    :param ambient_dim: The ambient dimension d.
+    :type ambient_dim: integer
     :param radius: The radius.
     :type radius: float
     :param sample: The sample type.