diff options
Diffstat (limited to 'cython/cython')
| -rw-r--r-- | cython/cython/nerve_gic.pyx | 401 | ||||
| -rwxr-xr-x | cython/cython/persistence_graphical_tools.py | 377 | ||||
| -rw-r--r-- | cython/cython/rips_complex.pyx | 2 | ||||
| -rw-r--r-- | cython/cython/subsampling.pyx | 8 |
4 files changed, 598 insertions, 190 deletions
diff --git a/cython/cython/nerve_gic.pyx b/cython/cython/nerve_gic.pyx new file mode 100644 index 00000000..30a14d3b --- /dev/null +++ b/cython/cython/nerve_gic.pyx @@ -0,0 +1,401 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +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) 2018 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) 2018 Inria" +__license__ = "GPL v3" + +cdef extern from "Nerve_gic_interface.h" namespace "Gudhi": + cdef cppclass Nerve_gic_interface "Gudhi::cover_complex::Nerve_gic_interface": + Nerve_gic_interface() + double compute_confidence_level_from_distance(double distance) + double compute_distance_from_confidence_level(double alpha) + void compute_distribution(int N) + double compute_p_value() + void compute_PD() + void find_simplices() + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree) + bool read_point_cloud(string off_file_name) + double set_automatic_resolution() + void set_color_from_coordinate(int k) + void set_color_from_file(string color_file_name) + void set_color_from_vector(vector[double] color) + void set_cover_from_file(string cover_file_name) + void set_cover_from_function() + void set_cover_from_Euclidean_Voronoi(int m) + void set_function_from_coordinate(int k) + void set_function_from_file(string func_file_name) + void set_function_from_range(vector[double] function) + void set_gain(double g) + double set_graph_from_automatic_euclidean_rips(int N) + void set_graph_from_file(string graph_file_name) + void set_graph_from_OFF() + void set_graph_from_euclidean_rips(double threshold) + void set_mask(int nodemask) + void set_resolution_with_interval_length(double resolution) + void set_resolution_with_interval_number(int resolution) + void set_subsampling(double constant, double power) + void set_type(string type) + void set_verbose(bool verbose) + vector[int] subpopulation(int c) + void write_info() + void plot_DOT() + void plot_OFF() + +# CoverComplex python interface +cdef class CoverComplex: + """Cover complex data structure. + + The data structure is a simplicial complex, representing a Graph Induced + simplicial Complex (GIC) or a Nerve, and whose simplices are computed with + a cover C of a point cloud P, which often comes from the preimages of + intervals covering the image of a function f defined on P. These intervals + are parameterized by their resolution (either their length or their number) + and their gain (percentage of overlap). To compute a GIC, one also needs a + graph G built on top of P, whose cliques with vertices belonging to + different elements of C correspond to the simplices of the GIC. + """ + + cdef Nerve_gic_interface * thisptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self): + """CoverComplex constructor. + """ + + # The real cython constructor + def __cinit__(self): + self.thisptr = new Nerve_gic_interface() + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + + def __is_defined(self): + """Returns true if CoverComplex pointer is not NULL. + """ + return self.thisptr != NULL + + def compute_confidence_level_from_distance(self, distance): + """Computes the confidence level of a specific bottleneck distance + threshold. + + :param distance: Bottleneck distance. + :type distance: double + :rtype: double + :returns: Confidence level. + """ + return self.thisptr.compute_confidence_level_from_distance(distance) + + def compute_distance_from_confidence_level(self, alpha): + """Computes the bottleneck distance threshold corresponding to a + specific confidence level. + + :param alpha: Confidence level. + :type alpha: double + :rtype: double + :returns: Bottleneck distance. + """ + return self.thisptr.compute_distance_from_confidence_level(alpha) + + def compute_distribution(self, N=100): + """Computes bootstrapped distances distribution. + + :param N: Loop number (default value is 100). + :type alpha: int + """ + self.thisptr.compute_distribution(N) + + def compute_p_value(self): + """Computes the p-value, i.e. the opposite of the confidence level of + the largest bottleneck distance preserving the points in the + persistence diagram of the output simplicial complex. + + :rtype: double + :returns: p-value. + """ + return self.thisptr.compute_p_value() + + def compute_PD(self): + """Computes the extended persistence diagram of the complex. + """ + self.thisptr.compute_PD() + + def create_simplex_tree(self): + """ + :returns: A simplex tree created from the Cover complex. + :rtype: SimplexTree + """ + simplex_tree = SimplexTree() + self.thisptr.create_simplex_tree(simplex_tree.thisptr) + return simplex_tree + + def find_simplices(self): + """Computes the simplices of the simplicial complex. + """ + self.thisptr.find_simplices() + + def read_point_cloud(self, off_file): + """Reads and stores the input point cloud. + + :param off_file: Name of the input .OFF or .nOFF file. + :type off_file: string + :rtype: bool + :returns: Read file status. + """ + if os.path.isfile(off_file): + return self.thisptr.read_point_cloud(str.encode(off_file)) + else: + print("file " + off_file + " not found.") + return False + + def set_automatic_resolution(self): + """Computes the optimal length of intervals (i.e. the smallest interval + length avoiding discretization artifacts—see :cite:`Carriere17c`) for a + functional cover. + + :rtype: double + :returns: reso interval length used to compute the cover. + """ + return self.thisptr.set_automatic_resolution() + + def set_color_from_coordinate(self, k=0): + """Computes the function used to color the nodes of the simplicial + complex from the k-th coordinate. + + :param k: Coordinate to use (start at 0). Default value is 0. + :type k: int + """ + return self.thisptr.set_color_from_coordinate(k) + + def set_color_from_file(self, color_file_name): + """Computes the function used to color the nodes of the simplicial + complex from a file containing the function values. + + :param color_file_name: Name of the input color file. + :type color_file_name: string + """ + if os.path.isfile(color_file_name): + self.thisptr.set_color_from_file(str.encode(color_file_name)) + else: + print("file " + color_file_name + " not found.") + + def set_color_from_vector(self, color): + """Computes the function used to color the nodes of the simplicial + complex from a vector stored in memory. + + :param color: Input vector of values. + :type color: vector[double] + """ + self.thisptr.set_color_from_vector(color) + + def set_cover_from_file(self, cover_file_name): + """Creates the cover C from a file containing the cover elements of + each point (the order has to be the same as in the input file!). + + :param cover_file_name: Name of the input cover file. + :type cover_file_name: string + """ + if os.path.isfile(cover_file_name): + self.thisptr.set_cover_from_file(str.encode(cover_file_name)) + else: + print("file " + cover_file_name + " not found.") + + def set_cover_from_function(self): + """Creates a cover C from the preimages of the function f. + """ + self.thisptr.set_cover_from_function() + + def set_cover_from_Voronoi(self, m=100): + """Creates the cover C from the Voronoï cells of a subsampling of the + point cloud. + + :param m: Number of points in the subsample. Default value is 100. + :type m: int + """ + self.thisptr.set_cover_from_Euclidean_Voronoi(m) + + def set_function_from_coordinate(self, k): + """Creates the function f from the k-th coordinate of the point cloud. + + :param k: Coordinate to use (start at 0). + :type k: int + """ + self.thisptr.set_function_from_coordinate(k) + + def set_function_from_file(self, func_file_name): + """Creates the function f from a file containing the function values. + + :param func_file_name: Name of the input function file. + :type func_file_name: string + """ + if os.path.isfile(func_file_name): + self.thisptr.set_function_from_file(str.encode(func_file_name)) + else: + print("file " + func_file_name + " not found.") + + def set_function_from_range(self, function): + """Creates the function f from a vector stored in memory. + + :param function: Input vector of values. + :type function: vector[double] + """ + self.thisptr.set_function_from_range(function) + + def set_gain(self, g = 0.3): + """Sets a gain from a value stored in memory. + + :param g: Gain (default value is 0.3). + :type g: double + """ + self.thisptr.set_gain(g) + + def set_graph_from_automatic_rips(self, N=100): + """Creates a graph G from a Rips complex whose threshold value is + automatically tuned with subsampling—see. + + :param N: Number of subsampling iteration (the default reasonable value + is 100, but there is no guarantee on how to choose it). + :type N: int + :rtype: double + :returns: Delta threshold used for computing the Rips complex. + """ + return self.thisptr.set_graph_from_automatic_euclidean_rips(N) + + def set_graph_from_file(self, graph_file_name): + """Creates a graph G from a file containing the edges. + + :param graph_file_name: Name of the input graph file. The graph file + contains one edge per line, each edge being represented by the IDs of + its two nodes. + :type graph_file_name: string + """ + if os.path.isfile(graph_file_name): + self.thisptr.set_graph_from_file(str.encode(graph_file_name)) + else: + print("file " + graph_file_name + " not found.") + + def set_graph_from_OFF(self): + """Creates a graph G from the triangulation given by the input OFF + file. + """ + self.thisptr.set_graph_from_OFF() + + def set_graph_from_rips(self, threshold): + """Creates a graph G from a Rips complex. + + :param threshold: Threshold value for the Rips complex. + :type threshold: double + """ + self.thisptr.set_graph_from_euclidean_rips(threshold) + + def set_mask(self, nodemask): + """Sets the mask, which is a threshold integer such that nodes in the + complex that contain a number of data points which is less than or + equal to this threshold are not displayed. + + :param nodemask: Threshold. + :type nodemask: int + """ + self.thisptr.set_mask(nodemask) + + def set_resolution_with_interval_length(self, resolution): + """Sets a length of intervals from a value stored in memory. + + :param resolution: Length of intervals. + :type resolution: double + """ + self.thisptr.set_resolution_with_interval_length(resolution) + + def set_resolution_with_interval_number(self, resolution): + """Sets a number of intervals from a value stored in memory. + + :param resolution: Number of intervals. + :type resolution: int + """ + self.thisptr.set_resolution_with_interval_number(resolution) + + def set_subsampling(self, constant, power): + """Sets the constants used to subsample the data set. These constants + are explained in :cite:`Carriere17c`. + + :param constant: Constant. + :type constant: double + :param power: Power. + :type resolution: double + """ + self.thisptr.set_subsampling(constant, power) + + def set_type(self, type): + """Specifies whether the type of the output simplicial complex. + + :param type: either "GIC" or "Nerve". + :type type: string + """ + self.thisptr.set_type(str.encode(type)) + + def set_verbose(self, verbose): + """Specifies whether the program should display information or not. + + :param verbose: true = display info, false = do not display info. + :type verbose: boolean + """ + self.thisptr.set_verbose(verbose) + + def subpopulation(self, c): + """Returns the data subset corresponding to a specific node of the + created complex. + + :param c: ID of the node. + :type c: int + :rtype: vector[int] + :returns: Vector of IDs of data points. + """ + return self.thisptr.subpopulation(c) + + def write_info(self): + """Creates a .txt file called SC.txt describing the 1-skeleton, which can + then be plotted with e.g. KeplerMapper. + """ + return self.thisptr.write_info() + + def plot_dot(self): + """Creates a .dot file called SC.dot for neato (part of the graphviz + package) once the simplicial complex is computed to get a visualization of + its 1-skeleton in a .pdf file. + """ + return self.thisptr.plot_DOT() + + def plot_off(self): + """Creates a .off file called SC.off for 3D visualization, which contains + the 2-skeleton of the GIC. This function assumes that the cover has been + computed with Voronoi. If data points are in 1D or 2D, the remaining + coordinates of the points embedded in 3D are set to 0. + """ + return self.thisptr.plot_OFF() diff --git a/cython/cython/persistence_graphical_tools.py b/cython/cython/persistence_graphical_tools.py index 216ab8d6..314bd6db 100755 --- a/cython/cython/persistence_graphical_tools.py +++ b/cython/cython/persistence_graphical_tools.py @@ -1,8 +1,3 @@ -import matplotlib.pyplot as plt -import matplotlib.patches as mpatches -import numpy as np -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. @@ -29,187 +24,197 @@ __author__ = "Vincent Rouvreau, Bertrand Michel" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" -def __min_birth_max_death(persistence, band=0.): - """This function returns (min_birth, max_death) from the persistence. - - :param persistence: The persistence to plot. - :type persistence: list of tuples(dimension, tuple(birth, death)). - :param band: band - :type band: float. - :returns: (float, float) -- (min_birth, max_death). - """ - # Look for minimum birth date and maximum death date for plot optimisation - max_death = 0 - min_birth = persistence[0][1][0] - for interval in reversed(persistence): - if float(interval[1][1]) != float('inf'): - if float(interval[1][1]) > max_death: - max_death = float(interval[1][1]) - if float(interval[1][0]) > max_death: - max_death = float(interval[1][0]) - if float(interval[1][0]) < min_birth: - min_birth = float(interval[1][0]) - if band > 0.: - max_death += band - return (min_birth, max_death) +try: + import matplotlib.pyplot as plt + import matplotlib.patches as mpatches + import numpy as np + import os + + def __min_birth_max_death(persistence, band=0.): + """This function returns (min_birth, max_death) from the persistence. + + :param persistence: The persistence to plot. + :type persistence: list of tuples(dimension, tuple(birth, death)). + :param band: band + :type band: float. + :returns: (float, float) -- (min_birth, max_death). + """ + # Look for minimum birth date and maximum death date for plot optimisation + max_death = 0 + min_birth = persistence[0][1][0] + for interval in reversed(persistence): + if float(interval[1][1]) != float('inf'): + if float(interval[1][1]) > max_death: + max_death = float(interval[1][1]) + if float(interval[1][0]) > max_death: + max_death = float(interval[1][0]) + if float(interval[1][0]) < min_birth: + min_birth = float(interval[1][0]) + if band > 0.: + max_death += band + return (min_birth, max_death) -""" -Only 13 colors for the palette -""" -palette = ['#ff0000', '#00ff00', '#0000ff', '#00ffff', '#ff00ff', '#ffff00', - '#000000', '#880000', '#008800', '#000088', '#888800', '#880088', - '#008888'] - -def plot_persistence_barcode(persistence=[], persistence_file='', alpha=0.6, - max_barcodes=1000, inf_delta=0.1, legend=False): - """This function plots the persistence bar code from persistence values list - or from a :doc:`persistence file <fileformats>`. - - :param persistence: Persistence values list. - :type persistence: list of tuples(dimension, tuple(birth, death)). - :param persistence_file: A :doc:`persistence file <fileformats>` style name - (reset persistence if both are set). - :type persistence_file: string - :param alpha: barcode transparency value (0.0 transparent through 1.0 opaque - default is 0.6). - :type alpha: float. - :param max_barcodes: number of maximal barcodes to be displayed. - Set it to 0 to see all, Default value is 1000. - (persistence will be sorted by life time if max_barcodes is set) - :type max_barcodes: int. - :param inf_delta: Infinity is placed at ((max_death - min_birth) x inf_delta). - A reasonable value is between 0.05 and 0.5 - default is 0.1. - :type inf_delta: float. - :returns: A matplotlib object containing horizontal bar plot of persistence - (launch `show()` method on it to display it). """ - if persistence_file is not '': - if os.path.isfile(persistence_file): - # Reset persistence - persistence = [] - diag = read_persistence_intervals_grouped_by_dimension(persistence_file=persistence_file) - for key in diag.keys(): - for persistence_interval in diag[key]: - persistence.append((key, persistence_interval)) - else: - print("file " + persistence_file + " not found.") - return None - - if max_barcodes > 0 and max_barcodes < len(persistence): - # Sort by life time, then takes only the max_plots elements - persistence = sorted(persistence, key=lambda life_time: life_time[1][1]-life_time[1][0], reverse=True)[:max_barcodes] - - persistence = sorted(persistence, key=lambda birth: birth[1][0]) - - (min_birth, max_death) = __min_birth_max_death(persistence) - ind = 0 - delta = ((max_death - min_birth) * inf_delta) - # Replace infinity values with max_death + delta for bar code to be more - # readable - infinity = max_death + delta - axis_start = min_birth - delta - # Draw horizontal bars in loop - for interval in reversed(persistence): - if float(interval[1][1]) != float('inf'): - # Finite death case - plt.barh(ind, (interval[1][1] - interval[1][0]), height=0.8, - left = interval[1][0], alpha=alpha, - color = palette[interval[0]], - linewidth=0) - else: - # Infinite death case for diagram to be nicer - plt.barh(ind, (infinity - interval[1][0]), height=0.8, - left = interval[1][0], alpha=alpha, - color = palette[interval[0]], - linewidth=0) - ind = ind + 1 - - if legend: - dimensions = list(set(item[0] for item in persistence)) - plt.legend(handles=[mpatches.Patch(color=palette[dim], - label=str(dim)) for dim in dimensions], - loc='lower right') - plt.title('Persistence barcode') - # Ends plot on infinity value and starts a little bit before min_birth - plt.axis([axis_start, infinity, 0, ind]) - return plt - -def plot_persistence_diagram(persistence=[], persistence_file='', alpha=0.6, - band=0., max_plots=1000, inf_delta=0.1, legend=False): - """This function plots the persistence diagram from persistence values list - or from a :doc:`persistence file <fileformats>`. - - :param persistence: Persistence values list. - :type persistence: list of tuples(dimension, tuple(birth, death)). - :param persistence_file: A :doc:`persistence file <fileformats>` style name - (reset persistence if both are set). - :type persistence_file: string - :param alpha: plot transparency value (0.0 transparent through 1.0 opaque - default is 0.6). - :type alpha: float. - :param band: band (not displayed if :math:`\leq` 0. - default is 0.) - :type band: float. - :param max_plots: number of maximal plots to be displayed - Set it to 0 to see all, Default value is 1000. - (persistence will be sorted by life time if max_plots is set) - :type max_plots: int. - :param inf_delta: Infinity is placed at ((max_death - min_birth) x inf_delta). - A reasonable value is between 0.05 and 0.5 - default is 0.1. - :type inf_delta: float. - :returns: A matplotlib object containing diagram plot of persistence - (launch `show()` method on it to display it). + Only 13 colors for the palette """ - if persistence_file is not '': - if os.path.isfile(persistence_file): - # Reset persistence - persistence = [] - diag = read_persistence_intervals_grouped_by_dimension(persistence_file=persistence_file) - for key in diag.keys(): - for persistence_interval in diag[key]: - persistence.append((key, persistence_interval)) - else: - print("file " + persistence_file + " not found.") - return None - - if max_plots > 0 and max_plots < len(persistence): - # Sort by life time, then takes only the max_plots elements - persistence = sorted(persistence, key=lambda life_time: life_time[1][1]-life_time[1][0], reverse=True)[:max_plots] - - (min_birth, max_death) = __min_birth_max_death(persistence, band) - ind = 0 - delta = ((max_death - min_birth) * inf_delta) - # Replace infinity values with max_death + delta for diagram to be more - # readable - infinity = max_death + delta - axis_start = min_birth - delta - - # line display of equation : birth = death - x = np.linspace(axis_start, infinity, 1000) - # infinity line and text - plt.plot(x, x, color='k', linewidth=1.0) - plt.plot(x, [infinity] * len(x), linewidth=1.0, color='k', alpha=alpha) - plt.text(axis_start, infinity, r'$\infty$', color='k', alpha=alpha) - # bootstrap band - if band > 0.: - plt.fill_between(x, x, x+band, alpha=alpha, facecolor='red') - - # Draw points in loop - for interval in reversed(persistence): - if float(interval[1][1]) != float('inf'): - # Finite death case - plt.scatter(interval[1][0], interval[1][1], alpha=alpha, - color = palette[interval[0]]) - else: - # Infinite death case for diagram to be nicer - plt.scatter(interval[1][0], infinity, alpha=alpha, - color = palette[interval[0]]) - ind = ind + 1 - - if legend: - dimensions = list(set(item[0] for item in persistence)) - plt.legend(handles=[mpatches.Patch(color=palette[dim], label=str(dim)) for dim in dimensions]) - - plt.title('Persistence diagram') - plt.xlabel('Birth') - plt.ylabel('Death') - # Ends plot on infinity value and starts a little bit before min_birth - plt.axis([axis_start, infinity, axis_start, infinity + delta]) - return plt + palette = ['#ff0000', '#00ff00', '#0000ff', '#00ffff', '#ff00ff', '#ffff00', + '#000000', '#880000', '#008800', '#000088', '#888800', '#880088', + '#008888'] + + def plot_persistence_barcode(persistence=[], persistence_file='', alpha=0.6, + max_barcodes=1000, inf_delta=0.1, legend=False): + """This function plots the persistence bar code from persistence values list + or from a :doc:`persistence file <fileformats>`. + + :param persistence: Persistence values list. + :type persistence: list of tuples(dimension, tuple(birth, death)). + :param persistence_file: A :doc:`persistence file <fileformats>` style name + (reset persistence if both are set). + :type persistence_file: string + :param alpha: barcode transparency value (0.0 transparent through 1.0 opaque - default is 0.6). + :type alpha: float. + :param max_barcodes: number of maximal barcodes to be displayed. + Set it to 0 to see all, Default value is 1000. + (persistence will be sorted by life time if max_barcodes is set) + :type max_barcodes: int. + :param inf_delta: Infinity is placed at ((max_death - min_birth) x inf_delta). + A reasonable value is between 0.05 and 0.5 - default is 0.1. + :type inf_delta: float. + :returns: A matplotlib object containing horizontal bar plot of persistence + (launch `show()` method on it to display it). + """ + if persistence_file is not '': + if os.path.isfile(persistence_file): + # Reset persistence + persistence = [] + diag = read_persistence_intervals_grouped_by_dimension(persistence_file=persistence_file) + for key in diag.keys(): + for persistence_interval in diag[key]: + persistence.append((key, persistence_interval)) + else: + print("file " + persistence_file + " not found.") + return None + + if max_barcodes > 0 and max_barcodes < len(persistence): + # Sort by life time, then takes only the max_plots elements + persistence = sorted(persistence, key=lambda life_time: life_time[1][1]-life_time[1][0], reverse=True)[:max_barcodes] + + persistence = sorted(persistence, key=lambda birth: birth[1][0]) + + (min_birth, max_death) = __min_birth_max_death(persistence) + ind = 0 + delta = ((max_death - min_birth) * inf_delta) + # Replace infinity values with max_death + delta for bar code to be more + # readable + infinity = max_death + delta + axis_start = min_birth - delta + # Draw horizontal bars in loop + for interval in reversed(persistence): + if float(interval[1][1]) != float('inf'): + # Finite death case + plt.barh(ind, (interval[1][1] - interval[1][0]), height=0.8, + left = interval[1][0], alpha=alpha, + color = palette[interval[0]], + linewidth=0) + else: + # Infinite death case for diagram to be nicer + plt.barh(ind, (infinity - interval[1][0]), height=0.8, + left = interval[1][0], alpha=alpha, + color = palette[interval[0]], + linewidth=0) + ind = ind + 1 + + if legend: + dimensions = list(set(item[0] for item in persistence)) + plt.legend(handles=[mpatches.Patch(color=palette[dim], + label=str(dim)) for dim in dimensions], + loc='lower right') + plt.title('Persistence barcode') + # Ends plot on infinity value and starts a little bit before min_birth + plt.axis([axis_start, infinity, 0, ind]) + return plt + + def plot_persistence_diagram(persistence=[], persistence_file='', alpha=0.6, + band=0., max_plots=1000, inf_delta=0.1, legend=False): + """This function plots the persistence diagram from persistence values list + or from a :doc:`persistence file <fileformats>`. + + :param persistence: Persistence values list. + :type persistence: list of tuples(dimension, tuple(birth, death)). + :param persistence_file: A :doc:`persistence file <fileformats>` style name + (reset persistence if both are set). + :type persistence_file: string + :param alpha: plot transparency value (0.0 transparent through 1.0 opaque - default is 0.6). + :type alpha: float. + :param band: band (not displayed if :math:`\leq` 0. - default is 0.) + :type band: float. + :param max_plots: number of maximal plots to be displayed + Set it to 0 to see all, Default value is 1000. + (persistence will be sorted by life time if max_plots is set) + :type max_plots: int. + :param inf_delta: Infinity is placed at ((max_death - min_birth) x inf_delta). + A reasonable value is between 0.05 and 0.5 - default is 0.1. + :type inf_delta: float. + :returns: A matplotlib object containing diagram plot of persistence + (launch `show()` method on it to display it). + """ + if persistence_file is not '': + if os.path.isfile(persistence_file): + # Reset persistence + persistence = [] + diag = read_persistence_intervals_grouped_by_dimension(persistence_file=persistence_file) + for key in diag.keys(): + for persistence_interval in diag[key]: + persistence.append((key, persistence_interval)) + else: + print("file " + persistence_file + " not found.") + return None + + if max_plots > 0 and max_plots < len(persistence): + # Sort by life time, then takes only the max_plots elements + persistence = sorted(persistence, key=lambda life_time: life_time[1][1]-life_time[1][0], reverse=True)[:max_plots] + + (min_birth, max_death) = __min_birth_max_death(persistence, band) + ind = 0 + delta = ((max_death - min_birth) * inf_delta) + # Replace infinity values with max_death + delta for diagram to be more + # readable + infinity = max_death + delta + axis_start = min_birth - delta + + # line display of equation : birth = death + x = np.linspace(axis_start, infinity, 1000) + # infinity line and text + plt.plot(x, x, color='k', linewidth=1.0) + plt.plot(x, [infinity] * len(x), linewidth=1.0, color='k', alpha=alpha) + plt.text(axis_start, infinity, r'$\infty$', color='k', alpha=alpha) + # bootstrap band + if band > 0.: + plt.fill_between(x, x, x+band, alpha=alpha, facecolor='red') + + # Draw points in loop + for interval in reversed(persistence): + if float(interval[1][1]) != float('inf'): + # Finite death case + plt.scatter(interval[1][0], interval[1][1], alpha=alpha, + color = palette[interval[0]]) + else: + # Infinite death case for diagram to be nicer + plt.scatter(interval[1][0], infinity, alpha=alpha, + color = palette[interval[0]]) + ind = ind + 1 + + if legend: + dimensions = list(set(item[0] for item in persistence)) + plt.legend(handles=[mpatches.Patch(color=palette[dim], label=str(dim)) for dim in dimensions]) + + plt.title('Persistence diagram') + plt.xlabel('Birth') + plt.ylabel('Death') + # Ends plot on infinity value and starts a little bit before min_birth + plt.axis([axis_start, infinity, axis_start, infinity + delta]) + return plt + +except ImportError: + # Continue in case of import error, functions won't be available + pass diff --git a/cython/cython/rips_complex.pyx b/cython/cython/rips_complex.pyx index 59c16bff..30ca4443 100644 --- a/cython/cython/rips_complex.pyx +++ b/cython/cython/rips_complex.pyx @@ -51,7 +51,7 @@ cdef class RipsComplex: """RipsComplex constructor. :param max_edge_length: Rips value. - :type max_edge_length: int + :type max_edge_length: float :param points: A list of points in d-Dimension. :type points: list of list of double diff --git a/cython/cython/subsampling.pyx b/cython/cython/subsampling.pyx index ac09b7a3..e9d61a37 100644 --- a/cython/cython/subsampling.pyx +++ b/cython/cython/subsampling.pyx @@ -112,7 +112,8 @@ def pick_n_random_points(points=None, off_file='', nb_points=0): 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. + """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]]. @@ -122,8 +123,9 @@ def sparsify_point_set(points=None, off_file='', min_squared_dist=0.0): :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. + :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]] """ |