diff options
Diffstat (limited to 'src/python/gudhi/subsampling.pyx')
| -rw-r--r-- | src/python/gudhi/subsampling.pyx | 72 |
1 files changed, 39 insertions, 33 deletions
diff --git a/src/python/gudhi/subsampling.pyx b/src/python/gudhi/subsampling.pyx index 1135c1fb..46f32335 100644 --- a/src/python/gudhi/subsampling.pyx +++ b/src/python/gudhi/subsampling.pyx @@ -1,19 +1,18 @@ +# 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 + 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" @@ -34,29 +33,32 @@ 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: vector[vector[double]]. + :type points: Iterable[Iterable[float]] 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. + And in both cases + + :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 poit to start with. If not set, this \ - index is choosen randomly. - :type starting_point: unsigned. + point`, which is the index of the point to start with. If not set, this \ + index is chosen randomly. + :type starting_point: int :returns: The subsample point set. - :rtype: vector[vector[double]] + :rtype: List[List[float]] """ - if off_file is not '': + if off_file: if os.path.isfile(off_file): - if starting_point is '': - return subsampling_n_farthest_points_from_file(str.encode(off_file), + if starting_point == '': + return subsampling_n_farthest_points_from_file(off_file.encode('utf-8'), nb_points) else: - return subsampling_n_farthest_points_from_file(str.encode(off_file), + return subsampling_n_farthest_points_from_file(off_file.encode('utf-8'), nb_points, starting_point) else: @@ -65,7 +67,7 @@ def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_poi if points is None: # Empty points points=[] - if starting_point is '': + if starting_point == '': return subsampling_n_farthest_points(points, nb_points) else: return subsampling_n_farthest_points(points, nb_points, @@ -75,21 +77,23 @@ 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]]. + :type points: Iterable[Iterable[float]] Or :param off_file: An OFF file style name. :type off_file: string + 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: vector[vector[double]] + :rtype: List[List[float]] """ - if off_file is not '': + if off_file: if os.path.isfile(off_file): - return subsampling_n_random_points_from_file(str.encode(off_file), + return subsampling_n_random_points_from_file(off_file.encode('utf-8'), nb_points) else: print("file " + off_file + " not found.") @@ -101,25 +105,27 @@ def pick_n_random_points(points=None, off_file='', nb_points=0): 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. + between any two points is greater than min_squared_dist. :param points: The input point set. - :type points: vector[vector[double]]. + :type points: Iterable[Iterable[float]] Or :param off_file: An OFF file style name. :type off_file: string + And in both cases + :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: vector[vector[double]] + :rtype: List[List[float]] """ - if off_file is not '': + if off_file: if os.path.isfile(off_file): - return subsampling_sparsify_points_from_file(str.encode(off_file), + return subsampling_sparsify_points_from_file(off_file.encode('utf-8'), min_squared_dist) else: print("file " + off_file + " not found.") |