From 68753b3c28321e28eedd5829c94234da84e25c8d Mon Sep 17 00:00:00 2001
From: ROUVREAU Vincent <vincent.rouvreau@inria.fr>
Date: Mon, 9 Sep 2019 16:03:40 +0200
Subject: Code review: rename cython as python (make target and directory

---
 src/python/gudhi/subsampling.pyx | 130 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 130 insertions(+)
 create mode 100644 src/python/gudhi/subsampling.pyx

(limited to 'src/python/gudhi/subsampling.pyx')

diff --git a/src/python/gudhi/subsampling.pyx b/src/python/gudhi/subsampling.pyx
new file mode 100644
index 00000000..1135c1fb
--- /dev/null
+++ b/src/python/gudhi/subsampling.pyx
@@ -0,0 +1,130 @@
+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 - https://gudhi.inria.fr/ - which is released under MIT.
+    See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+    Author(s):       Vincent Rouvreau
+
+    Copyright (C) 2016 Inria
+
+    Modification(s):
+      - YYYY/MM Author: Description of the modification
+"""
+
+__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):
+    """Outputs a subset of the input points so that the squared distance
+    between any two points is greater than or equal to min_squared_dist.
+
+    :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: Minimum squared distance separating the output \
+    points.
+    :type min_squared_dist: float.
+    :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)
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