diff options
Diffstat (limited to 'src/cython/cython')
| -rw-r--r-- | src/cython/cython/nerve_gic.pyx | 30 | ||||
| -rw-r--r--[-rwxr-xr-x] | src/cython/cython/persistence_graphical_tools.py | 310 | ||||
| -rw-r--r-- | src/cython/cython/rips_complex.pyx | 56 | ||||
| -rw-r--r-- | src/cython/cython/simplex_tree.pyx | 14 | ||||
| -rw-r--r-- | src/cython/cython/strong_witness_complex.pyx | 12 | ||||
| -rw-r--r-- | src/cython/cython/tangential_complex.pyx | 26 | ||||
| -rw-r--r-- | src/cython/cython/witness_complex.pyx | 12 |
7 files changed, 327 insertions, 133 deletions
diff --git a/src/cython/cython/nerve_gic.pyx b/src/cython/cython/nerve_gic.pyx index 30a14d3b..5f01b379 100644 --- a/src/cython/cython/nerve_gic.pyx +++ b/src/cython/cython/nerve_gic.pyx @@ -38,14 +38,14 @@ cdef extern from "Nerve_gic_interface.h" namespace "Gudhi": double compute_distance_from_confidence_level(double alpha) void compute_distribution(int N) double compute_p_value() - void compute_PD() + vector[pair[double, double]] 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_color_from_range(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) @@ -67,6 +67,8 @@ cdef extern from "Nerve_gic_interface.h" namespace "Gudhi": void write_info() void plot_DOT() void plot_OFF() + void set_point_cloud_from_range(vector[vector[double]] cloud) + void set_distances_from_range(vector[vector[double]] distance_matrix) # CoverComplex python interface cdef class CoverComplex: @@ -102,6 +104,22 @@ cdef class CoverComplex: """ return self.thisptr != NULL + def set_point_cloud_from_range(self, cloud): + """ Reads and stores the input point cloud from a vector stored in memory. + + :param cloud: Input vector containing the point cloud. + :type cloud: vector[vector[double]] + """ + return self.thisptr.set_point_cloud_from_range(cloud) + + def set_distances_from_range(self, distance_matrix): + """ Reads and stores the input distance matrix from a vector stored in memory. + + :param distance_matrix: Input vector containing the distance matrix. + :type distance_matrix: vector[vector[double]] + """ + return self.thisptr.set_distances_from_range(distance_matrix) + def compute_confidence_level_from_distance(self, distance): """Computes the confidence level of a specific bottleneck distance threshold. @@ -145,7 +163,7 @@ cdef class CoverComplex: def compute_PD(self): """Computes the extended persistence diagram of the complex. """ - self.thisptr.compute_PD() + return self.thisptr.compute_PD() def create_simplex_tree(self): """ @@ -162,7 +180,7 @@ cdef class CoverComplex: self.thisptr.find_simplices() def read_point_cloud(self, off_file): - """Reads and stores the input point cloud. + """Reads and stores the input point cloud from .(n)OFF file. :param off_file: Name of the input .OFF or .nOFF file. :type off_file: string @@ -206,14 +224,14 @@ cdef class CoverComplex: else: print("file " + color_file_name + " not found.") - def set_color_from_vector(self, color): + def set_color_from_range(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) + self.thisptr.set_color_from_range(color) def set_cover_from_file(self, cover_file_name): """Creates the cover C from a file containing the cover elements of diff --git a/src/cython/cython/persistence_graphical_tools.py b/src/cython/cython/persistence_graphical_tools.py index 314bd6db..d7be936f 100755..100644 --- a/src/cython/cython/persistence_graphical_tools.py +++ b/src/cython/cython/persistence_graphical_tools.py @@ -24,65 +24,70 @@ __author__ = "Vincent Rouvreau, Bertrand Michel" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" -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) +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). """ - Only 13 colors for the palette + # 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_intervals=1000, 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 intervals values list grouped by dimension. + :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_intervals: maximal number of intervals to display. + Selected intervals are those with the longest life time. Set it + to 0 to see all. Default value is 1000. + :type max_intervals: int. + :param inf_delta: Infinity is placed at :code:`((max_death - min_birth) x + inf_delta)` above :code:`max_death` value. A reasonable value is + between 0.05 and 0.5 - default is 0.1. + :type inf_delta: float. + :param legend: Display the dimension color legend (default is False). + :type legend: boolean. + :returns: A matplotlib object containing horizontal bar plot of persistence + (launch `show()` method on it to display it). """ - 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). - """ + try: + import matplotlib.pyplot as plt + import matplotlib.patches as mpatches + import numpy as np + import os + if persistence_file is not '': if os.path.isfile(persistence_file): # Reset persistence @@ -95,9 +100,13 @@ try: 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] + if max_barcodes is not 1000: + print('Deprecated parameter. It has been replaced by max_intervals') + max_intervals = max_barcodes + + if max_intervals > 0 and max_intervals < len(persistence): + # Sort by life time, then takes only the max_intervals elements + persistence = sorted(persistence, key=lambda life_time: life_time[1][1]-life_time[1][0], reverse=True)[:max_intervals] persistence = sorted(persistence, key=lambda birth: birth[1][0]) @@ -134,30 +143,43 @@ try: 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). - """ + except ImportError: + print("This function is not available, you may be missing numpy and/or matplotlib.") + +def plot_persistence_diagram(persistence=[], persistence_file='', alpha=0.6, + band=0., max_intervals=1000, 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 intervals values list grouped by dimension. + :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_intervals: maximal number of intervals to display. + Selected intervals are those with the longest life time. Set it + to 0 to see all. Default value is 1000. + :type max_intervals: int. + :param inf_delta: Infinity is placed at :code:`((max_death - min_birth) x + inf_delta)` above :code:`max_death` value. A reasonable value is + between 0.05 and 0.5 - default is 0.1. + :type inf_delta: float. + :param legend: Display the dimension color legend (default is False). + :type legend: boolean. + :returns: A matplotlib object containing diagram plot of persistence + (launch `show()` method on it to display it). + """ + try: + import matplotlib.pyplot as plt + import matplotlib.patches as mpatches + import numpy as np + import os + if persistence_file is not '': if os.path.isfile(persistence_file): # Reset persistence @@ -170,12 +192,15 @@ try: 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] + if max_plots is not 1000: + print('Deprecated parameter. It has been replaced by max_intervals') + max_intervals = max_plots + + if max_intervals > 0 and max_intervals < len(persistence): + # Sort by life time, then takes only the max_intervals elements + persistence = sorted(persistence, key=lambda life_time: life_time[1][1]-life_time[1][0], reverse=True)[:max_intervals] (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 @@ -202,7 +227,6 @@ try: # 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)) @@ -215,6 +239,110 @@ try: 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 + except ImportError: + print("This function is not available, you may be missing numpy and/or matplotlib.") + +def plot_persistence_density(persistence=[], persistence_file='', + nbins=300, bw_method=None, + max_intervals=1000, dimension=None, + cmap=None, legend=False): + """This function plots the persistence density from persistence + values list or from a :doc:`persistence file <fileformats>`. Be + aware that this function does not distinguish the dimension, it is + up to you to select the required one. This function also does not handle + degenerate data set (scipy correlation matrix inversion can fail). + + :param persistence: Persistence intervals values list grouped by dimension. + :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 nbins: Evaluate a gaussian kde on a regular grid of nbins x + nbins over data extents (default is 300) + :type nbins: int. + :param bw_method: The method used to calculate the estimator + bandwidth. This can be 'scott', 'silverman', a scalar constant + or a callable. If a scalar, this will be used directly as + kde.factor. If a callable, it should take a gaussian_kde + instance as only parameter and return a scalar. If None + (default), 'scott' is used. See + `scipy.stats.gaussian_kde documentation + <http://scipy.github.io/devdocs/generated/scipy.stats.gaussian_kde.html>`_ + for more details. + :type bw_method: str, scalar or callable, optional. + :param max_intervals: maximal number of points used in the density + estimation. + Selected intervals are those with the longest life time. Set it + to 0 to see all. Default value is 1000. + :type max_intervals: int. + :param dimension: the dimension to be selected in the intervals + (default is None to mix all dimensions). + :type dimension: int. + :param cmap: A matplotlib colormap (default is + matplotlib.pyplot.cm.hot_r). + :type cmap: cf. matplotlib colormap. + :param legend: Display the color bar values (default is False). + :type legend: boolean. + :returns: A matplotlib object containing diagram plot of persistence + (launch `show()` method on it to display it). + """ + try: + import matplotlib.pyplot as plt + import numpy as np + from scipy.stats import kde + import os + import math + + 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 + + persistence_dim = [] + if dimension is not None: + persistence_dim = [(dim_interval) for dim_interval in persistence if (dim_interval[0] == dimension)] + else: + persistence_dim = persistence + + if max_intervals > 0 and max_intervals < len(persistence_dim): + # Sort by life time, then takes only the max_intervals elements + persistence_dim = sorted(persistence_dim, + key=lambda life_time: life_time[1][1]-life_time[1][0], + reverse=True)[:max_intervals] + + # Set as numpy array birth and death (remove undefined values - inf and NaN) + birth = np.asarray([(interval[1][0]) for interval in persistence_dim if (math.isfinite(interval[1][1]) and math.isfinite(interval[1][0]))]) + death = np.asarray([(interval[1][1]) for interval in persistence_dim if (math.isfinite(interval[1][1]) and math.isfinite(interval[1][0]))]) + + # line display of equation : birth = death + x = np.linspace(death.min(), birth.max(), 1000) + plt.plot(x, x, color='k', linewidth=1.0) + + # Evaluate a gaussian kde on a regular grid of nbins x nbins over data extents + k = kde.gaussian_kde([birth,death], bw_method=bw_method) + xi, yi = np.mgrid[birth.min():birth.max():nbins*1j, death.min():death.max():nbins*1j] + zi = k(np.vstack([xi.flatten(), yi.flatten()])) + + # default cmap value cannot be done at argument definition level as matplotlib is not yet defined. + if cmap is None: + cmap = plt.cm.hot_r + # Make the plot + plt.pcolormesh(xi, yi, zi.reshape(xi.shape), cmap=cmap) + + if legend: + plt.colorbar() + + plt.title('Persistence density') + plt.xlabel('Birth') + plt.ylabel('Death') + return plt + + except ImportError: + print("This function is not available, you may be missing numpy, matplotlib and/or scipy.") diff --git a/src/cython/cython/rips_complex.pyx b/src/cython/cython/rips_complex.pyx index 30ca4443..7c83241c 100644 --- a/src/cython/cython/rips_complex.pyx +++ b/src/cython/cython/rips_complex.pyx @@ -33,7 +33,11 @@ __license__ = "GPL v3" cdef extern from "Rips_complex_interface.h" namespace "Gudhi": cdef cppclass Rips_complex_interface "Gudhi::rips_complex::Rips_complex_interface": - Rips_complex_interface(vector[vector[double]] values, double threshold, bool euclidean) + Rips_complex_interface() + void init_points(vector[vector[double]] values, double threshold) + void init_matrix(vector[vector[double]] values, double threshold) + void init_points_sparse(vector[vector[double]] values, double threshold, double sparse) + void init_matrix_sparse(vector[vector[double]] values, double threshold, double sparse) void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, int dim_max) # RipsComplex python interface @@ -44,10 +48,11 @@ cdef class RipsComplex: function, or a distance matrix. """ - cdef Rips_complex_interface * thisptr + cdef Rips_complex_interface thisref # Fake constructor that does nothing but documenting the constructor - def __init__(self, points=None, distance_matrix=None, max_edge_length=float('inf')): + def __init__(self, points=None, distance_matrix=None, + max_edge_length=float('inf'), sparse=None): """RipsComplex constructor. :param max_edge_length: Rips value. @@ -59,29 +64,38 @@ cdef class RipsComplex: Or :param distance_matrix: A distance matrix (full square or lower - triangular). + triangular). :type points: list of list of double + + And in both cases + + :param sparse: If this is not None, it switches to building a sparse + Rips and represents the approximation parameter epsilon. + :type sparse: float """ # The real cython constructor - def __cinit__(self, points=None, distance_matrix=None, max_edge_length=float('inf')): - if distance_matrix is not None: - self.thisptr = new Rips_complex_interface(distance_matrix, max_edge_length, False) + def __cinit__(self, points=None, distance_matrix=None, + max_edge_length=float('inf'), sparse=None): + if sparse is not None: + if distance_matrix is not None: + self.thisref.init_matrix_sparse(distance_matrix, + max_edge_length, + sparse) + else: + if points is None: + # Empty Rips construction + points=[] + self.thisref.init_points_sparse(points, max_edge_length, sparse) else: - if points is None: - # Empty Rips construction - points=[] - self.thisptr = new Rips_complex_interface(points, max_edge_length, True) - - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr + if distance_matrix is not None: + self.thisref.init_matrix(distance_matrix, max_edge_length) + else: + if points is None: + # Empty Rips construction + points=[] + self.thisref.init_points(points, max_edge_length) - def __is_defined(self): - """Returns true if RipsComplex pointer is not NULL. - """ - return self.thisptr != NULL def create_simplex_tree(self, max_dimension=1): """ @@ -92,5 +106,5 @@ cdef class RipsComplex: :rtype: SimplexTree """ simplex_tree = SimplexTree() - self.thisptr.create_simplex_tree(simplex_tree.thisptr, max_dimension) + self.thisref.create_simplex_tree(simplex_tree.thisptr, max_dimension) return simplex_tree diff --git a/src/cython/cython/simplex_tree.pyx b/src/cython/cython/simplex_tree.pyx index e302486b..0ab97f80 100644 --- a/src/cython/cython/simplex_tree.pyx +++ b/src/cython/cython/simplex_tree.pyx @@ -44,8 +44,8 @@ cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": void set_dimension(int dimension) int dimension() int upper_bound_dimension() - bint find_simplex(vector[int] simplex) - bint insert_simplex_and_subfaces(vector[int] simplex, + bool find_simplex(vector[int] simplex) + bool insert_simplex_and_subfaces(vector[int] simplex, double filtration) vector[pair[vector[int], double]] get_filtration() vector[pair[vector[int], double]] get_skeleton(int dimension) @@ -355,7 +355,7 @@ cdef class SimplexTree: :param filtration: Maximum threshold value. :type filtration: float. :returns: The filtration modification information. - :rtype: bint + :rtype: bool .. note:: @@ -406,7 +406,7 @@ cdef class SimplexTree: value than its faces by increasing the filtration values. :returns: The filtration modification information. - :rtype: bint + :rtype: bool .. note:: @@ -432,6 +432,10 @@ cdef class SimplexTree: 0.0. Sets min_persistence to -1.0 to see all values. :type min_persistence: float. + :param persistence_dim_max: If true, the persistent homology for the + maximal dimension in the complex is computed. If false, it is + ignored. Default is false. + :type persistence_dim_max: bool :returns: The persistence of the simplicial complex. :rtype: list of pairs(dimension, pair(birth, death)) """ @@ -515,7 +519,7 @@ cdef class SimplexTree: :returns: The persistence intervals. :rtype: list of pair of list of int - :note: intervals_in_dim function requires + :note: persistence_pairs function requires :func:`persistence()<gudhi.SimplexTree.persistence>` function to be launched first. """ diff --git a/src/cython/cython/strong_witness_complex.pyx b/src/cython/cython/strong_witness_complex.pyx index 74c5cb05..4b7bff34 100644 --- a/src/cython/cython/strong_witness_complex.pyx +++ b/src/cython/cython/strong_witness_complex.pyx @@ -47,8 +47,10 @@ cdef class StrongWitnessComplex: def __init__(self, nearest_landmark_table=None): """StrongWitnessComplex constructor. - :param nearest_landmark_table: A list of nearest landmark. - :type nearest_landmark_table: list of list of pair of unsigned and double + :param nearest_landmark_table: A list of lists of nearest landmarks and their distances. + `nearest_landmark_table[w][k]==(l,d)` means that l is the k-th nearest landmark to + witness w, and d is the (squared) distance between l and w. + :type nearest_landmark_table: list of list of pair of int and float """ # The real cython constructor @@ -65,10 +67,10 @@ cdef class StrongWitnessComplex: """ return self.thisptr != NULL - def create_simplex_tree(self, max_alpha_square, limit_dimension = -1): + def create_simplex_tree(self, max_alpha_square = float('inf'), limit_dimension = -1): """ - :param max_alpha_square: The maximum alpha square threshold the - simplices shall not exceed. Default is set to infinity. + :param max_alpha_square: The maximum relaxation parameter. + Default is set to infinity. :type max_alpha_square: float :returns: A simplex tree created from the Delaunay Triangulation. :rtype: SimplexTree diff --git a/src/cython/cython/tangential_complex.pyx b/src/cython/cython/tangential_complex.pyx index 4bb07076..293ef8cb 100644 --- a/src/cython/cython/tangential_complex.pyx +++ b/src/cython/cython/tangential_complex.pyx @@ -36,6 +36,7 @@ cdef extern from "Tangential_complex_interface.h" namespace "Gudhi": Tangential_complex_interface(int intrisic_dim, vector[vector[double]] points) # bool from_file is a workaround for cython to find the correct signature Tangential_complex_interface(int intrisic_dim, string off_file, bool from_file) + void compute_tangential_complex() except + vector[double] get_point(unsigned vertex) unsigned number_of_vertices() unsigned number_of_simplices() @@ -43,6 +44,7 @@ cdef extern from "Tangential_complex_interface.h" namespace "Gudhi": unsigned number_of_inconsistent_stars() void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree) void fix_inconsistencies_using_perturbation(double max_perturb, double time_limit) + void set_max_squared_edge_length(double max_squared_edge_length) # TangentialComplex python interface cdef class TangentialComplex: @@ -92,6 +94,17 @@ cdef class TangentialComplex: """ return self.thisptr != NULL + def compute_tangential_complex(self): + """This function computes the tangential complex. + + Raises: + ValueError: In debug mode, if the computed star dimension is too + low. Try to set a bigger maximal edge length value with + :func:`~gudhi.Tangential_complex.set_max_squared_edge_length` + if this happens. + """ + self.thisptr.compute_tangential_complex() + def get_point(self, vertex): """This function returns the point corresponding to a given vertex. @@ -152,3 +165,16 @@ cdef class TangentialComplex: """ self.thisptr.fix_inconsistencies_using_perturbation(max_perturb, time_limit) + + def set_max_squared_edge_length(self, max_squared_edge_length): + """Sets the maximal possible squared edge length for the edges in the + triangulations. + + :param max_squared_edge_length: Maximal possible squared edge length. + :type max_squared_edge_length: double + + If the maximal edge length value is too low + :func:`~gudhi.Tangential_complex.compute_tangential_complex` + will throw an exception in debug mode. + """ + self.thisptr.set_max_squared_edge_length(max_squared_edge_length) diff --git a/src/cython/cython/witness_complex.pyx b/src/cython/cython/witness_complex.pyx index 8591465a..b1cce83f 100644 --- a/src/cython/cython/witness_complex.pyx +++ b/src/cython/cython/witness_complex.pyx @@ -47,8 +47,10 @@ cdef class WitnessComplex: def __init__(self, nearest_landmark_table=None): """WitnessComplex constructor. - :param nearest_landmark_table: A list of nearest landmark. - :type nearest_landmark_table: list of list of pair of unsigned and double + :param nearest_landmark_table: A list of lists of nearest landmarks and their distances. + `nearest_landmark_table[w][k]==(l,d)` means that l is the k-th nearest landmark to + witness w, and d is the (squared) distance between l and w. + :type nearest_landmark_table: list of list of pair of int and float """ # The real cython constructor @@ -65,10 +67,10 @@ cdef class WitnessComplex: """ return self.thisptr != NULL - def create_simplex_tree(self, max_alpha_square, limit_dimension = -1): + def create_simplex_tree(self, max_alpha_square = float('inf'), limit_dimension = -1): """ - :param max_alpha_square: The maximum alpha square threshold the - simplices shall not exceed. Default is set to infinity. + :param max_alpha_square: The maximum relaxation parameter. + Default is set to infinity. :type max_alpha_square: float :returns: A simplex tree created from the Delaunay Triangulation. :rtype: SimplexTree |