Merge master and resolve conflicts

3 files changed, 30 insertions, 14 deletions

diff --git a/src/python/gudhi/simplex_tree.pxd b/src/python/gudhi/simplex_tree.pxd
index 6ec85bca..3c4cbed3 100644
--- a/src/python/gudhi/simplex_tree.pxd
+++ b/src/python/gudhi/simplex_tree.pxd
@@ -64,6 +64,7 @@ cdef extern from "Simplex_tree_interface.h" namespace "Gudhi":
         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
+        void reset_filtration(double filtration, int dimension) nogil
         # Iterators over Simplex tree
         pair[vector[int], double] get_simplex_and_filtration(Simplex_tree_simplex_handle f_simplex) nogil
         Simplex_tree_simplices_iterator get_simplices_iterator_begin() nogil
diff --git a/src/python/gudhi/simplex_tree.pyx b/src/python/gudhi/simplex_tree.pyx
index 5043c621..c671da56 100644
--- a/src/python/gudhi/simplex_tree.pyx
+++ b/src/python/gudhi/simplex_tree.pyx
@@ -342,7 +342,7 @@ cdef class SimplexTree:
         return self.get_ptr().prune_above_filtration(filtration)
 
     def expansion(self, max_dim):
-        """Expands the Simplex_tree containing only its one skeleton
+        """Expands the simplex tree containing only its one skeleton
         until dimension max_dim.
 
         The expanded simplicial complex until dimension :math:`d`
@@ -352,7 +352,7 @@ cdef class SimplexTree:
         The filtration value assigned to a simplex is the maximal filtration
         value of one of its edges.
 
-        The Simplex_tree must contain no simplex of dimension bigger than
+        The simplex tree must contain no simplex of dimension bigger than
         1 when calling the method.
 
         :param max_dim: The maximal dimension.
@@ -372,6 +372,20 @@ cdef class SimplexTree:
         """
         return self.get_ptr().make_filtration_non_decreasing()
 
+    def reset_filtration(self, filtration, min_dim = 0):
+        """This function resets the filtration value of all the simplices of dimension at least min_dim. Resets all the
+        simplex tree when `min_dim = 0`.
+        `reset_filtration` may break the filtration property with `min_dim > 0`, and it is the user's responsibility to
+        make it a valid filtration (using a large enough `filt_value`, or calling `make_filtration_non_decreasing`
+        afterwards for instance).
+
+        :param filtration: New threshold value.
+        :type filtration: float.
+        :param min_dim: The minimal dimension. Default value is 0.
+        :type min_dim: int.
+        """
+        self.get_ptr().reset_filtration(filtration, min_dim)
+
     def extend_filtration(self):
         """ Extend filtration for computing extended persistence. This function only uses the 
         filtration values at the 0-dimensional simplices, and computes the extended persistence 
@@ -380,14 +394,14 @@ cdef class SimplexTree:
         .. note::
 
             Note that after calling this function, the filtration 
-            values are actually modified within the Simplex_tree. 
+            values are actually modified within the simplex tree. 
             The function :func:`extended_persistence`
             retrieves the original values.
 
         .. note::
 
             Note that this code creates an extra vertex internally, so you should make sure that
-            the Simplex_tree does not contain a vertex with the largest possible value (i.e., 4294967295). 
+            the simplex tree does not contain a vertex with the largest possible value (i.e., 4294967295). 
         """
         self.get_ptr().compute_extended_filtration()
 
diff --git a/src/python/gudhi/subsampling.pyx b/src/python/gudhi/subsampling.pyx
index f77c6f75..b11d07e5 100644
--- a/src/python/gudhi/subsampling.pyx
+++ b/src/python/gudhi/subsampling.pyx
@@ -33,7 +33,7 @@ def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_poi
     The iteration starts with the landmark `starting point`.
 
     :param points: The input point set.
-    :type points: Iterable[Iterable[float]].
+    :type points: Iterable[Iterable[float]]
 
     Or
 
@@ -42,14 +42,15 @@ def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_poi
 
     And in both cases
 
-    :param nb_points: Number of points of the subsample.
-    :type nb_points: unsigned.
+    :param nb_points: Number of points of the subsample (the subsample may be \
+    smaller if there are fewer than nb_points distinct input points)
+    :type nb_points: int
     :param starting_point: The iteration starts with the landmark `starting \
-    point`,which is the index of the point to start with. If not set, this \
+    point`, which is the index of the point to start with. If not set, this \
     index is chosen randomly.
-    :type starting_point: unsigned.
+    :type starting_point: int
     :returns:  The subsample point set.
-    :rtype: List[List[float]].
+    :rtype: List[List[float]]
     """
     if off_file:
         if os.path.isfile(off_file):
@@ -76,7 +77,7 @@ def pick_n_random_points(points=None, off_file='', nb_points=0):
     """Subsample a point set by picking random vertices.
 
     :param points: The input point set.
-    :type points: Iterable[Iterable[float]].
+    :type points: Iterable[Iterable[float]]
 
     Or
 
@@ -86,7 +87,7 @@ def pick_n_random_points(points=None, off_file='', nb_points=0):
     And in both cases
 
     :param nb_points: Number of points of the subsample.
-    :type nb_points: unsigned.
+    :type nb_points: int
     :returns:  The subsample point set.
     :rtype: List[List[float]]
     """
@@ -107,7 +108,7 @@ def sparsify_point_set(points=None, off_file='', min_squared_dist=0.0):
     between any two points is greater than or equal to min_squared_dist.
 
     :param points: The input point set.
-    :type points: Iterable[Iterable[float]].
+    :type points: Iterable[Iterable[float]]
 
     Or
 
@@ -118,7 +119,7 @@ def sparsify_point_set(points=None, off_file='', min_squared_dist=0.0):
 
     :param min_squared_dist: Minimum squared distance separating the output \
     points.
-    :type min_squared_dist: float.
+    :type min_squared_dist: float
     :returns:  The subsample point set.
     :rtype: List[List[float]]
     """