1 files changed, 140 insertions, 0 deletions
diff --git a/cython/cython/subsampling.pyx b/cython/cython/subsampling.pyx
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+++ b/cython/cython/subsampling.pyx
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+from cython cimport numeric
+from libcpp.vector cimport vector
+from libcpp.string cimport string
+from libcpp cimport bool
+import os
+
+"""This file is part of the Gudhi Library. The Gudhi library
+   (Geometric Understanding in Higher Dimensions) is a generic C++
+   library for computational topology.
+
+   Author(s):       Vincent Rouvreau
+
+   Copyright (C) 2016 INRIA
+
+   This program is free software: you can redistribute it and/or modify
+   it under the terms of the GNU General Public License as published by
+   the Free Software Foundation, either version 3 of the License, or
+   (at your option) any later version.
+
+   This program is distributed in the hope that it will be useful,
+   but WITHOUT ANY WARRANTY; without even the implied warranty of
+   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+   GNU General Public License for more details.
+
+   You should have received a copy of the GNU General Public License
+   along with this program.  If not, see <http://www.gnu.org/licenses/>.
+"""
+
+__author__ = "Vincent Rouvreau"
+__copyright__ = "Copyright (C) 2016 INRIA"
+__license__ = "GPL v3"
+
+cdef extern from "Subsampling_interface.h" namespace "Gudhi::subsampling":
+    vector[vector[double]] subsampling_n_farthest_points(vector[vector[double]] points, unsigned nb_points)
+    vector[vector[double]] subsampling_n_farthest_points(vector[vector[double]] points, unsigned nb_points, unsigned starting_point)
+    vector[vector[double]] subsampling_n_farthest_points_from_file(string off_file, unsigned nb_points)
+    vector[vector[double]] subsampling_n_farthest_points_from_file(string off_file, unsigned nb_points, unsigned starting_point)
+    vector[vector[double]] subsampling_n_random_points(vector[vector[double]] points, unsigned nb_points)
+    vector[vector[double]] subsampling_n_random_points_from_file(string off_file, unsigned nb_points)
+    vector[vector[double]] subsampling_sparsify_points(vector[vector[double]] points, double min_squared_dist)
+    vector[vector[double]] subsampling_sparsify_points_from_file(string off_file, double min_squared_dist)
+
+def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_point = ''):
+    """Subsample by a greedy strategy of iteratively adding the farthest point
+    from the current chosen point set to the subsampling.
+    The iteration starts with the landmark `starting point`.
+
+    :param points: The input point set.
+    :type points: vector[vector[double]].
+
+    Or
+
+    :param off_file: An OFF file style name.
+    :type off_file: string
+
+    :param nb_points: Number of points of the subsample.
+    :type nb_points: unsigned.
+    :param starting_point: The iteration starts with the landmark `starting \
+    point`,which is the index of the poit to start with. If not set, this \
+    index is choosen randomly.
+    :type starting_point: unsigned.
+    :returns:  The subsample point set.
+    :rtype: vector[vector[double]]
+    """
+    if off_file is not '':
+        if os.path.isfile(off_file):
+            if starting_point is '':
+                return subsampling_n_farthest_points_from_file(str.encode(off_file),
+                                                               nb_points)
+            else:
+                return subsampling_n_farthest_points_from_file(str.encode(off_file),
+                                                               nb_points,
+                                                               starting_point)
+        else:
+            print("file " + off_file + " not found.")
+    else:
+        if points is None:
+            # Empty points
+            points=[]
+        if starting_point is '':
+            return subsampling_n_farthest_points(points, nb_points)
+        else:
+            return subsampling_n_farthest_points(points, nb_points,
+                                                 starting_point)
+
+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: vector[vector[double]].
+
+    Or
+
+    :param off_file: An OFF file style name.
+    :type off_file: string
+
+    :param nb_points: Number of points of the subsample.
+    :type nb_points: unsigned.
+    :returns:  The subsample point set.
+    :rtype: vector[vector[double]]
+    """
+    if off_file is not '':
+        if os.path.isfile(off_file):
+            return subsampling_n_random_points_from_file(str.encode(off_file),
+                nb_points)
+        else:
+            print("file " + off_file + " not found.")
+    else:
+        if points is None:
+            # Empty points
+            points=[]
+        return subsampling_n_random_points(points, nb_points)
+
+def sparsify_point_set(points=None, off_file='', min_squared_dist=0.0):
+    """Subsample a point set by picking random vertices.
+
+    :param points: The input point set.
+    :type points: vector[vector[double]].
+
+    Or
+
+    :param off_file: An OFF file style name.
+    :type off_file: string
+
+    :param min_squared_dist: Number of points of the subsample.
+    :type min_squared_dist: unsigned.
+    :returns:  The subsample point set.
+    :rtype: vector[vector[double]]
+    """
+    if off_file is not '':
+        if os.path.isfile(off_file):
+            return subsampling_sparsify_points_from_file(str.encode(off_file),
+                                                         min_squared_dist)
+        else:
+            print("file " + off_file + " not found.")
+    else:
+        if points is None:
+            # Empty points
+            points=[]
+        return subsampling_sparsify_points(points, min_squared_dist)