Merge remote-tracking branch 'upstream/master' into fetch_datasets

6 files changed, 15 insertions, 21 deletions

diff --git a/src/python/gudhi/__init__.py.in b/src/python/gudhi/__init__.py.in
index 3043201a..79e12fbc 100644
--- a/src/python/gudhi/__init__.py.in
+++ b/src/python/gudhi/__init__.py.in
@@ -23,10 +23,6 @@ __all__ = [@GUDHI_PYTHON_MODULES@ @GUDHI_PYTHON_MODULES_EXTRA@]
 __available_modules = ''
 __missing_modules = ''
 
-# For unitary tests purpose
-# could use "if 'collapse_edges' in gudhi.__all__" when collapse edges will have a python module
-__GUDHI_USE_EIGEN3 = @GUDHI_USE_EIGEN3@
-
 # Try to import * from gudhi.__module_name for default modules.
 # Extra modules require an explicit import by the user (mostly because of
 # unusual dependencies, but also to avoid cluttering namespace gudhi and
diff --git a/src/python/gudhi/hera/wasserstein.cc b/src/python/gudhi/hera/wasserstein.cc
index 1a21f02f..fa0cf8aa 100644
--- a/src/python/gudhi/hera/wasserstein.cc
+++ b/src/python/gudhi/hera/wasserstein.cc
@@ -29,7 +29,7 @@ double wasserstein_distance(
   if(std::isinf(internal_p)) internal_p = hera::get_infinity<double>();
   params.internal_p = internal_p;
   params.delta = delta;
-  // The extra parameters are purposedly not exposed for now.
+  // The extra parameters are purposely not exposed for now.
   return hera::wasserstein_dist(diag1, diag2, params);
 }
 
diff --git a/src/python/gudhi/persistence_graphical_tools.py b/src/python/gudhi/persistence_graphical_tools.py
index 7ed11360..21275cdd 100644
--- a/src/python/gudhi/persistence_graphical_tools.py
+++ b/src/python/gudhi/persistence_graphical_tools.py
@@ -332,7 +332,7 @@ def plot_persistence_diagram(
             axes.plot([axis_start, axis_end], [infinity, infinity], linewidth=1.0, color="k", alpha=alpha)
             # Infinity label
             yt = axes.get_yticks()
-            yt = yt[np.where(yt < axis_end)]  # to avoid ploting ticklabel higher than infinity
+            yt = yt[np.where(yt < axis_end)]  # to avoid plotting ticklabel higher than infinity
             yt = np.append(yt, infinity)
             ytl = ["%.3f" % e for e in yt]  # to avoid float precision error
             ytl[-1] = r"$+\infty$"
diff --git a/src/python/gudhi/simplex_tree.pxd b/src/python/gudhi/simplex_tree.pxd
index 4f229663..5642f82d 100644
--- a/src/python/gudhi/simplex_tree.pxd
+++ b/src/python/gudhi/simplex_tree.pxd
@@ -63,7 +63,6 @@ cdef extern from "Simplex_tree_interface.h" namespace "Gudhi":
         bool prune_above_filtration(double filtration) nogil
         bool make_filtration_non_decreasing() nogil
         void compute_extended_filtration() nogil
-        vector[vector[pair[int, pair[double, double]]]] compute_extended_persistence_subdiagrams(vector[pair[int, pair[double, double]]] dgm, double min_persistence) nogil
         Simplex_tree_interface_full_featured* collapse_edges(int nb_collapse_iteration) nogil except +
         void reset_filtration(double filtration, int dimension) nogil
         bint operator==(Simplex_tree_interface_full_featured) nogil
@@ -81,7 +80,7 @@ cdef extern from "Simplex_tree_interface.h" namespace "Gudhi":
         void expansion_with_blockers_callback(int dimension, blocker_func_t user_func, void *user_data)
 
 cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi":
-    cdef cppclass Simplex_tree_persistence_interface "Gudhi::Persistent_cohomology_interface<Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_full_featured>>":
+    cdef cppclass Simplex_tree_persistence_interface "Gudhi::Persistent_cohomology_interface<Gudhi::Simplex_tree_interface<Gudhi::Simplex_tree_options_full_featured>>":
         Simplex_tree_persistence_interface(Simplex_tree_interface_full_featured * st, bool persistence_dim_max) nogil
         void compute_persistence(int homology_coeff_field, double min_persistence) nogil except +
         vector[pair[int, pair[double, double]]] get_persistence() nogil
@@ -92,3 +91,4 @@ cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi":
         vector[pair[vector[int], vector[int]]] persistence_pairs() nogil
         pair[vector[vector[int]], vector[vector[int]]] lower_star_generators() nogil
         pair[vector[vector[int]], vector[vector[int]]] flag_generators() nogil
+        vector[vector[pair[int, pair[double, double]]]] compute_extended_persistence_subdiagrams(double min_persistence) nogil
diff --git a/src/python/gudhi/simplex_tree.pyx b/src/python/gudhi/simplex_tree.pyx
index a4914184..521a7763 100644
--- a/src/python/gudhi/simplex_tree.pyx
+++ b/src/python/gudhi/simplex_tree.pyx
@@ -474,8 +474,7 @@ cdef class SimplexTree:
             del self.pcohptr
         self.pcohptr = new Simplex_tree_persistence_interface(self.get_ptr(), False)
         self.pcohptr.compute_persistence(homology_coeff_field, -1.)
-        persistence_result = self.pcohptr.get_persistence()
-        return self.get_ptr().compute_extended_persistence_subdiagrams(persistence_result, min_persistence)
+        return self.pcohptr.compute_extended_persistence_subdiagrams(min_persistence)
 
     def expansion_with_blocker(self, max_dim, blocker_func):
         """Expands the Simplex_tree containing only a graph. Simplices corresponding to cliques in the graph are added
@@ -676,18 +675,17 @@ cdef class SimplexTree:
         return (normal0, normals, infinite0, infinites)
 
     def collapse_edges(self, nb_iterations = 1):
-        """Assuming the simplex tree is a 1-skeleton graph, this method collapse edges (simplices of higher dimension
-        are ignored) and resets the simplex tree from the remaining edges.
-        A good candidate is to build a simplex tree on top of a :class:`~gudhi.RipsComplex` of dimension 1 before
-        collapsing edges
+        """Assuming the complex is a graph (simplices of higher dimension are ignored), this method implicitly
+        interprets it as the 1-skeleton of a flag complex, and replaces it with another (smaller) graph whose
+        expansion has the same persistent homology, using a technique known as edge collapses
+        (see :cite:`edgecollapsearxiv`).
+
+        A natural application is to get a simplex tree of dimension 1 from :class:`~gudhi.RipsComplex`,
+        then collapse edges, perform :meth:`expansion()` and finally compute persistence
         (cf. :download:`rips_complex_edge_collapse_example.py <../example/rips_complex_edge_collapse_example.py>`).
-        For implementation details, please refer to :cite:`edgecollapsesocg2020`.
 
         :param nb_iterations: The number of edge collapse iterations to perform. Default is 1.
         :type nb_iterations: int
-
-        :note: collapse_edges method requires `Eigen <installation.html#eigen>`_ >= 3.1.0 and an exception is thrown
-            if this method is not available.
         """
         # Backup old pointer
         cdef Simplex_tree_interface_full_featured* ptr = self.get_ptr()
diff --git a/src/python/gudhi/wasserstein/barycenter.py b/src/python/gudhi/wasserstein/barycenter.py
index d67bcde7..bb6e641e 100644
--- a/src/python/gudhi/wasserstein/barycenter.py
+++ b/src/python/gudhi/wasserstein/barycenter.py
@@ -37,7 +37,7 @@ def lagrangian_barycenter(pdiagset, init=None, verbose=False):
     :param init: The initial value for barycenter estimate.
         If ``None``, init is made on a random diagram from the dataset.
         Otherwise, it can be an ``int`` (then initialization is made on ``pdiagset[init]``)
-        or a `(n x 2)` ``numpy.array`` enconding a persistence diagram with `n` points.
+        or a `(n x 2)` ``numpy.array`` encoding a persistence diagram with `n` points.
     :type init: ``int``, or (n x 2) ``np.array``
     :param verbose: if ``True``, returns additional information about the barycenter.
     :type verbose: boolean
@@ -45,7 +45,7 @@ def lagrangian_barycenter(pdiagset, init=None, verbose=False):
         (local minimum of the energy function).
         If ``pdiagset`` is empty, returns ``None``.
         If verbose, returns a couple ``(Y, log)`` where ``Y`` is the barycenter estimate,
-        and ``log`` is a ``dict`` that contains additional informations:
+        and ``log`` is a ``dict`` that contains additional information:
 
         - `"groupings"`, a list of list of pairs ``(i,j)``. Namely, ``G[k] = [...(i, j)...]``, where ``(i,j)`` indicates that `pdiagset[k][i]`` is matched to ``Y[j]`` if ``i = -1`` or ``j = -1``, it means they represent the diagonal.
 
@@ -73,7 +73,7 @@ def lagrangian_barycenter(pdiagset, init=None, verbose=False):
 
     nb_iter = 0
 
-    converged = False  # stoping criterion
+    converged = False  # stopping criterion
     while not converged:
         nb_iter += 1
         K = len(Y)  # current nb of points in Y (some might be on diagonal)