From c2d46e0e6cfea1927875219bd5e03962cef7b010 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Mon, 29 Jan 2018 16:31:18 +0000 Subject: Fix doc issue for utilities part on the web site git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/trunk@3176 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 3bafd9e13a5646ca93023144705d3ac7ed7c9b3a --- src/Alpha_complex/utilities/README | 148 ++++++++++----------- src/Bitmap_cubical_complex/utilities/README | 42 ++++-- src/Bottleneck_distance/utilities/README | 32 ++++- src/Nerve_GIC/doc/Intro_graph_induced_complex.h | 6 +- src/Nerve_GIC/include/gudhi/GIC.h | 11 +- .../utilities/KeplerMapperVisuFromTxtFile.py | 97 ++++++++------ src/Nerve_GIC/utilities/covercomplex.md | 73 ++++++++++ src/Rips_complex/utilities/README | 67 ++++------ src/Witness_complex/utilities/README | 70 +++++----- src/common/utilities/README | 46 +++++-- 10 files changed, 365 insertions(+), 227 deletions(-) create mode 100644 src/Nerve_GIC/utilities/covercomplex.md diff --git a/src/Alpha_complex/utilities/README b/src/Alpha_complex/utilities/README index 1cd2ca95..56bce602 100644 --- a/src/Alpha_complex/utilities/README +++ b/src/Alpha_complex/utilities/README @@ -1,16 +1,35 @@ -# Alpha_complex # - -## `alpha_complex_3d_persistence` ## +--- +layout: page +title: "Alpha complex" +meta_title: "alphacomplex" +subheadline: "" +teaser: "" +permalink: "/alphacomplex/" +--- +{::comment} +These flags above are here for web site generation, please let them. +cf. https://gitlab.inria.fr/GUDHI/website +Must be in conformity with _data/navigation.yml +{:/comment} + + + +## alpha_complex_3d_persistence ## This program computes the persistent homology with coefficient field Z/pZ of the 3D alpha complex built from a 3D point cloud. The output diagram contains one bar per line, written with the convention: -`p dim birth death` +``` +p dim birth death +``` where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, and `p` is the characteristic of the field *Z/pZ* used for homology coefficients (`p` must be a prime number). **Usage** -`alpha_complex_3d_persistence [options] ` -where -`` is the path to the input point cloud in [nOFF ASCII format](http://www.geomview.org/docs/html/OFF.html). + +``` + alpha_complex_3d_persistence [options] +``` + +where `` is the path to the input point cloud in [nOFF ASCII format](http://www.geomview.org/docs/html/OFF.html). **Allowed options** @@ -20,43 +39,38 @@ where * `-m [ --min-persistence ]` (default = 0) Minimal lifetime of homology feature to be recorded. Enter a negative value to see zero length intervals. **Example** -`alpha_complex_3d_persistence ../../data/points/tore3D_300.off -p 2 -m 0.45` -outputs: ``` -Simplex_tree dim: 3 -2 0 0 inf -2 1 0.0682162 1.0001 -2 1 0.0934117 1.00003 -2 2 0.56444 1.03938 +alpha_complex_3d_persistence ../../data/points/tore3D_300.off -p 2 -m 0.45 ``` -Here we retrieve expected Betti numbers on a tore 3D: -``` -Betti numbers[0] = 1 -Betti numbers[1] = 2 -Betti numbers[2] = 1 -``` +N.B.: -N.B.: * `alpha_complex_3d_persistence` only accepts OFF files in dimension 3. * Filtration values are alpha square values. +## exact_alpha_complex_3d_persistence ## + +Same as `alpha_complex_3d_persistence`, but using exact computation. +It is slower, but it is necessary when points are on a grid for instance. -## `exact_alpha_complex_3d_persistence` ## -Same as `alpha_complex_3d_persistence`, but using exact computation. It is slower, but it is necessary when points are on a grid for instance. +## weighted_alpha_complex_3d_persistence ## -## `weighted_alpha_complex_3d_persistence` ## Same as `alpha_complex_3d_persistence`, but using weighted points. **Usage** -`weighted_alpha_complex_3d_persistence [options] ` + +``` + weighted_alpha_complex_3d_persistence [options] +``` + where -`` is the path to the input point cloud in [nOFF ASCII format](http://www.geomview.org/docs/html/OFF.html). -`` is the path to the file containing the weights of the points (one value per line). + +* `` is the path to the input point cloud in [nOFF ASCII format](http://www.geomview.org/docs/html/OFF.html). +* `` is the path to the file containing the weights of the points (one value per line). **Allowed options** @@ -66,32 +80,33 @@ where * `-m [ --min-persistence ]` (default = 0) Minimal lifetime of homology feature to be recorded. Enter a negative value to see zero length intervals. **Example** -`weighted_alpha_complex_3d_persistence ../../data/points/tore3D_300.off ../../data/points/tore3D_300.weights -p 2 -m 0.45` -outputs: ``` -Simplex_tree dim: 3 -2 0 -1 inf -2 1 -0.931784 0.000103311 -2 1 -0.906588 2.60165e-05 -2 2 -0.43556 0.0393798 + weighted_alpha_complex_3d_persistence ../../data/points/tore3D_300.off ../../data/points/tore3D_300.weights -p 2 -m 0.45 ``` + N.B.: + * Weights values are explained on CGAL [Alpha shape](https://doc.cgal.org/latest/Alpha_shapes_3/index.html#title0) and [Regular triangulation](https://doc.cgal.org/latest/Triangulation_3/index.html#Triangulation3secclassRegulartriangulation) documentation. * Filtration values are alpha square values. -## `periodic_alpha_complex_3d_persistence` ## +## periodic_alpha_complex_3d_persistence ## Same as `alpha_complex_3d_persistence`, but using periodic alpha shape 3d. Refer to the [CGAL's 3D Periodic Triangulations User Manual](https://doc.cgal.org/latest/Periodic_3_triangulation_3/index.html) for more details. **Usage** -`periodic_alpha_complex_3d_persistence [options] ` + +``` + periodic_alpha_complex_3d_persistence [options] +``` + where -`` is the path to the input point cloud in [nOFF ASCII format](http://www.geomview.org/docs/html/OFF.html). -`` is the path to the file describing the periodic domain. It must be in the format described [here](http://gudhi.gforge.inria.fr/doc/latest/fileformats.html#FileFormatsIsoCuboid). + +* `` is the path to the input point cloud in [nOFF ASCII format](http://www.geomview.org/docs/html/OFF.html). +* `` is the path to the file describing the periodic domain. It must be in the format described [here](http://gudhi.gforge.inria.fr/doc/latest/fileformats.html#FileFormatsIsoCuboid). **Allowed options** @@ -102,46 +117,36 @@ where **Example** -`periodic_alpha_complex_3d_persistence ../../data/points/grid_10_10_10_in_0_1.off ../../data/points/iso_cuboid_3_in_0_1.txt -p 3 -m 1.0` -outputs: ``` -Periodic Delaunay computed. -Simplex_tree dim: 3 -3 0 0 inf -3 1 0.0025 inf -3 1 0.0025 inf -3 1 0.0025 inf -3 2 0.005 inf -3 2 0.005 inf -3 2 0.005 inf -3 3 0.0075 inf +periodic_alpha_complex_3d_persistence ../../data/points/grid_10_10_10_in_0_1.off ../../data/points/iso_cuboid_3_in_0_1.txt -p 3 -m 1.0 ``` -Here we retrieve expected Betti numbers on an 3D iso-oriented cuboids: -``` -Betti numbers[0] = 1 -Betti numbers[1] = 3 -Betti numbers[2] = 3 -Betti numbers[3] = 1 -``` +N.B.: -N.B.: * Cuboid file must be in the format described [here](http://gudhi.gforge.inria.fr/doc/latest/fileformats.html#FileFormatsIsoCuboid). * Filtration values are alpha square values. +## alpha_complex_persistence ## -## `alpha_complex_persistence` ## -This program computes the persistent homology with coefficient field Z/pZ of the dD alpha complex built from a dD point cloud. The output diagram contains one bar per line, written with the convention: +This program computes the persistent homology with coefficient field Z/pZ of the dD alpha complex built from a dD point cloud. +The output diagram contains one bar per line, written with the convention: -`p dim birth death` +``` + p dim birth death +``` -where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, and `p` is the characteristic of the field *Z/pZ* used for homology coefficients (`p` must be a prime number). +where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, +and `p` is the characteristic of the field *Z/pZ* used for homology coefficients (`p` must be a prime number). **Usage** -`alpha_complex_persistence [options] ` + +``` + alpha_complex_persistence [options] +``` + where `` is the path to the input point cloud in [nOFF ASCII format](http://www.geomview.org/docs/html/OFF.html). @@ -154,24 +159,11 @@ where * `-m [ --min-persistence ]` (default = 0) Minimal lifetime of homology feature to be recorded. Enter a negative value to see zero length intervals. **Example** -`alpha_complex_persistence -r 32 -p 2 -m 0.45 ../../data/points/tore3D_300.off` -outputs: ``` -Alpha complex is of dimension 3 - 9273 simplices - 300 vertices. -Simplex_tree dim: 3 -2 0 0 inf -2 1 0.0682162 1.0001 -2 1 0.0934117 1.00003 -2 2 0.56444 1.03938 -``` - -Here we retrieve expected Betti numbers on a tore 3D: -``` -Betti numbers[0] = 1 -Betti numbers[1] = 2 -Betti numbers[2] = 1 + alpha_complex_persistence -r 32 -p 2 -m 0.45 ../../data/points/tore3D_300.off ``` N.B.: + * Filtration values are alpha square values. diff --git a/src/Bitmap_cubical_complex/utilities/README b/src/Bitmap_cubical_complex/utilities/README index ddff7034..393b2654 100644 --- a/src/Bitmap_cubical_complex/utilities/README +++ b/src/Bitmap_cubical_complex/utilities/README @@ -1,18 +1,40 @@ -# Bitmap_cubical_complex # +--- +layout: page +title: "Bitmap cubical complex" +meta_title: "cubicalcomplex" +subheadline: "" +teaser: "" +permalink: "/cubicalcomplex/" +--- +{::comment} +These flags above are here for web site generation, please let them. +cf. https://gitlab.inria.fr/GUDHI/website +Must be in conformity with _data/navigation.yml +{:/comment} -## `cubical_complex_persistence` ## -This program computes persistent homology, by using the Bitmap_cubical_complex class, of cubical complexes provided in text files in Perseus style. See [here](http://gudhi.gforge.inria.fr/doc/latest/fileformats.html#FileFormatsPerseus) for a description of the file format. -Example: +## cubical_complex_persistence ## +This program computes persistent homology, by using the Bitmap_cubical_complex class, of cubical complexes provided in text files in Perseus style. +See [here](http://gudhi.gforge.inria.fr/doc/latest/fileformats.html#FileFormatsPerseus) for a description of the file format. -* Create a Cubical Complex from the Perseus style file `CubicalTwoSphere.txt`, computes Persistence cohomology from it and writes the results in a persistence file `CubicalTwoSphere.txt_persistence`: -`cubical_complex_persistence data/bitmap/CubicalTwoSphere.txt` +**Example** -## `periodic_cubical_complex_persistence` ## +``` + cubical_complex_persistence data/bitmap/CubicalTwoSphere.txt +``` + +* Creates a Cubical Complex from the Perseus style file `CubicalTwoSphere.txt`, +computes Persistence cohomology from it and writes the results in a persistence file `CubicalTwoSphere.txt_persistence`. + +## periodic_cubical_complex_persistence ## Same as above, but with periodic boundary conditions. -Example: +**Example** + +``` + periodic_cubical_complex_persistence data/bitmap/3d_torus.txt +``` -* Create a Periodical Cubical Complex from the Perseus style file `3d_torus.txt`, computes Persistence cohomology from it and writes the results in a persistence file `3d_torus.txt_persistence`: -`periodic_cubical_complex_persistence data/bitmap/3d_torus.txt` +* Creates a Periodical Cubical Complex from the Perseus style file `3d_torus.txt`, +computes Persistence cohomology from it and writes the results in a persistence file `3d_torus.txt_persistence`. diff --git a/src/Bottleneck_distance/utilities/README b/src/Bottleneck_distance/utilities/README index d9fdd252..04e1c4bd 100644 --- a/src/Bottleneck_distance/utilities/README +++ b/src/Bottleneck_distance/utilities/README @@ -1,10 +1,30 @@ -# Bottleneck_distance # +--- +layout: page +title: "Bottleneck distance" +meta_title: "bottleneckdistance" +subheadline: "" +teaser: "" +permalink: "/bottleneckdistance/" +--- +{::comment} +These flags above are here for web site generation, please let them. +cf. https://gitlab.inria.fr/GUDHI/website +Must be in conformity with _data/navigation.yml +{:/comment} + + + +## bottleneck_read_file_example ## -## `bottleneck_read_file_example` ## This program computes the Bottleneck distance between two persistence diagram files. -Usage: -`bottleneck_read_file_example []` +**Usage** + +``` + bottleneck_read_file_example [] +``` + where -`` and `` must be in the format described [here](http://gudhi.gforge.inria.fr/doc/latest/fileformats.html#FileFormatsPers). -`` is an error bound on the bottleneck distance (set by default to the smallest positive double value). + +* `` and `` must be in the format described [here](http://gudhi.gforge.inria.fr/doc/latest/fileformats.html#FileFormatsPers). +* `` is an error bound on the bottleneck distance (set by default to the smallest positive double value). diff --git a/src/Nerve_GIC/doc/Intro_graph_induced_complex.h b/src/Nerve_GIC/doc/Intro_graph_induced_complex.h index f2409087..474f0f0e 100644 --- a/src/Nerve_GIC/doc/Intro_graph_induced_complex.h +++ b/src/Nerve_GIC/doc/Intro_graph_induced_complex.h @@ -77,8 +77,8 @@ namespace cover_complex { * * \include Nerve_GIC/Nerve.txt * - * The program also writes a file SC.txt. The first three lines in this file are the location of the input point cloud - * and the function used to compute the cover. + * The program also writes a file ../../data/points/human_sc.txt. The first three lines in this file are the location + * of the input point cloud and the function used to compute the cover. * The fourth line contains the number of vertices nv and edges ne of the Nerve. * The next nv lines represent the vertices. Each line contains the vertex ID, * the number of data points it contains, and their average color function value. @@ -118,7 +118,7 @@ namespace cover_complex { * * the program outputs SC.off. Using e.g. * - * \code $> geomview SC.off + * \code $> geomview ../../data/points/human_sc.off * \endcode * * one can obtain the following visualization: diff --git a/src/Nerve_GIC/include/gudhi/GIC.h b/src/Nerve_GIC/include/gudhi/GIC.h index 58831bbf..ff95b913 100644 --- a/src/Nerve_GIC/include/gudhi/GIC.h +++ b/src/Nerve_GIC/include/gudhi/GIC.h @@ -934,7 +934,7 @@ class Cover_complex { } graphic << "}"; graphic.close(); - std::cout << ".dot file generated. It can be visualized with e.g. neato." << std::endl; + std::cout << mapp << " file generated. It can be visualized with e.g. neato." << std::endl; } public: // Create a .txt file that can be compiled with KeplerMapper. @@ -944,7 +944,7 @@ class Cover_complex { void write_info() { int num_simplices = simplices.size(); int num_edges = 0; - std::string mapp = point_cloud_name + "_sc.dot"; + std::string mapp = point_cloud_name + "_sc.txt"; std::ofstream graphic(mapp.c_str()); for (int i = 0; i < num_simplices; i++) @@ -970,7 +970,8 @@ class Cover_complex { if (cover_color[simplices[i][0]].first > mask && cover_color[simplices[i][1]].first > mask) graphic << name2id[simplices[i][0]] << " " << name2id[simplices[i][1]] << std::endl; graphic.close(); - std::cout << ".txt generated. It can be visualized with e.g. python KeplerMapperVisuFromTxtFile.py and firefox." + std::cout << mapp + << " generated. It can be visualized with e.g. python KeplerMapperVisuFromTxtFile.py and firefox." << std::endl; } @@ -988,7 +989,7 @@ class Cover_complex { std::vector > edges, faces; int numsimplices = simplices.size(); - std::string mapp = point_cloud_name + "_sc.dot"; + std::string mapp = point_cloud_name + "_sc.off"; std::ofstream graphic(mapp.c_str()); graphic << "OFF" << std::endl; @@ -1016,7 +1017,7 @@ class Cover_complex { for (int i = 0; i < numfaces; i++) graphic << 3 << " " << faces[i][0] << " " << faces[i][1] << " " << faces[i][2] << std::endl; graphic.close(); - std::cout << ".off generated. It can be visualized with e.g. geomview." << std::endl; + std::cout << mapp << " generated. It can be visualized with e.g. geomview." << std::endl; } // ******************************************************************************************************************* diff --git a/src/Nerve_GIC/utilities/KeplerMapperVisuFromTxtFile.py b/src/Nerve_GIC/utilities/KeplerMapperVisuFromTxtFile.py index d2897774..c811f610 100755 --- a/src/Nerve_GIC/utilities/KeplerMapperVisuFromTxtFile.py +++ b/src/Nerve_GIC/utilities/KeplerMapperVisuFromTxtFile.py @@ -3,6 +3,7 @@ import km import numpy as np from collections import defaultdict +import argparse """This file is part of the Gudhi Library. The Gudhi library (Geometric Understanding in Higher Dimensions) is a generic C++ @@ -30,43 +31,59 @@ __author__ = "Mathieu Carriere" __copyright__ = "Copyright (C) 2017 INRIA" __license__ = "GPL v3" -network = {} -mapper = km.KeplerMapper(verbose=0) -data = np.zeros((3,3)) -projected_data = mapper.fit_transform( data, projection="sum", scaler=None ) - -f = open('SC.txt','r') -nodes = defaultdict(list) -links = defaultdict(list) -custom = defaultdict(list) - -dat = f.readline() -lens = f.readline() -color = f.readline(); -param = [float(i) for i in f.readline().split(" ")] - -nums = [int(i) for i in f.readline().split(" ")] -num_nodes = nums[0] -num_edges = nums[1] - -for i in range(0,num_nodes): - point = [float(j) for j in f.readline().split(" ")] - nodes[ str(int(point[0])) ] = [ int(point[0]), point[1], int(point[2]) ] - links[ str(int(point[0])) ] = [] - custom[ int(point[0]) ] = point[1] - -m = min([custom[i] for i in range(0,num_nodes)]) -M = max([custom[i] for i in range(0,num_nodes)]) - -for i in range(0,num_edges): - edge = [int(j) for j in f.readline().split(" ")] - links[ str(edge[0]) ].append( str(edge[1]) ) - links[ str(edge[1]) ].append( str(edge[0]) ) - -network["nodes"] = nodes -network["links"] = links -network["meta"] = lens - -mapper.visualize(network, color_function = color, path_html="SC.html", title=dat, -graph_link_distance=30, graph_gravity=0.1, graph_charge=-120, custom_tooltips=custom, width_html=0, -height_html=0, show_tooltips=True, show_title=True, show_meta=True, res=param[0],gain=param[1], minimum=m,maximum=M) +parser = argparse.ArgumentParser(description='Creates an html Keppler Mapper ' + 'file to visualize a SC.txt file.', + epilog='Example: ' + './KeplerMapperVisuFromTxtFile.py ' + '-f ../../data/points/human.off_sc.txt' + '- Constructs an human.off_sc.html file.') +parser.add_argument("-f", "--file", type=str, required=True) + +args = parser.parse_args() + +with open(args.file, 'r') as f: + network = {} + mapper = km.KeplerMapper(verbose=0) + data = np.zeros((3,3)) + projected_data = mapper.fit_transform( data, projection="sum", scaler=None ) + + nodes = defaultdict(list) + links = defaultdict(list) + custom = defaultdict(list) + + dat = f.readline() + lens = f.readline() + color = f.readline(); + param = [float(i) for i in f.readline().split(" ")] + + nums = [int(i) for i in f.readline().split(" ")] + num_nodes = nums[0] + num_edges = nums[1] + + for i in range(0,num_nodes): + point = [float(j) for j in f.readline().split(" ")] + nodes[ str(int(point[0])) ] = [ int(point[0]), point[1], int(point[2]) ] + links[ str(int(point[0])) ] = [] + custom[ int(point[0]) ] = point[1] + + m = min([custom[i] for i in range(0,num_nodes)]) + M = max([custom[i] for i in range(0,num_nodes)]) + + for i in range(0,num_edges): + edge = [int(j) for j in f.readline().split(" ")] + links[ str(edge[0]) ].append( str(edge[1]) ) + links[ str(edge[1]) ].append( str(edge[0]) ) + + network["nodes"] = nodes + network["links"] = links + network["meta"] = lens + + html_output_filename = args.file.rsplit('.', 1)[0] + '.html' + mapper.visualize(network, color_function = color, path_html=html_output_filename, title=dat, + graph_link_distance=30, graph_gravity=0.1, graph_charge=-120, custom_tooltips=custom, width_html=0, + height_html=0, show_tooltips=True, show_title=True, show_meta=True, res=param[0],gain=param[1], minimum=m,maximum=M) + message = repr(html_output_filename) + " is generated. You can now use your favorite web browser to visualize it." + print(message) + + + f.close() diff --git a/src/Nerve_GIC/utilities/covercomplex.md b/src/Nerve_GIC/utilities/covercomplex.md new file mode 100644 index 00000000..692e44e7 --- /dev/null +++ b/src/Nerve_GIC/utilities/covercomplex.md @@ -0,0 +1,73 @@ +--- +layout: page +title: "Cover complex" +meta_title: "covercomplex" +subheadline: "" +teaser: "" +permalink: "/covercomplex/" +--- +{::comment} +These flags above are here for web site generation, please let them. +cf. https://gitlab.inria.fr/GUDHI/website +Must be in conformity with _data/navigation.yml +{:/comment} + + + +## Nerve ## +This program builds the Nerve of a point cloud sampled on an OFF file. +The cover C comes from the preimages of intervals covering a coordinate function, +which are then refined into their connected components using the triangulation of the .OFF file. + +The program also writes a file SC.txt. +The first three lines in this file are the location of the input point cloud and the function used to compute the cover. +The fourth line contains the number of vertices nv and edges ne of the Nerve. The next nv lines represent the vertices. +Each line contains the vertex ID, the number of data points it contains, and their average color function value. +Finally, the next ne lines represent the edges, characterized by the ID of their vertices. + +**Usage** + +`Nerve coordinate resolution gain [--v]` + +where + +* `coordinate` is the coordinate function to cover +* `resolution` is the number of the intervals +* `gain` is the gain for each interval +* `--v` is optional, it activates verbose mode. + +**Example** + +`Nerve ../../data/points/human.off 2 10 0.3` + +* Builds the Nerve of a point cloud sampled on a 3D human shape (human.off). +The cover C comes from the preimages of intervals (10 intervals with gain 0.3) covering the height function (coordinate 2). + +`python KeplerMapperVisuFromTxtFile.py -f ../../data/points/human.off_sc.txt` + +* Constructs `human.off_sc.html` file. You can now use your favorite web browser to visualize it. + +## VoronoiGIC ## + +This util builds the Graph Induced Complex (GIC) of a point cloud. +It subsamples *N* points in the point cloud, which act as seeds of a geodesic Voronoï diagram. +Each cell of the diagram is then an element of C. + +The program also writes a file `*_sc.off`, that is an OFF file that can be visualized with GeomView. + +**Usage** + +`VoroniGIC samples_number [--v]` + +where + +* `samples_number` is the number of samples to take from the point cloud +* `--v` is optional, it activates verbose mode. + +**Example** + +`VoroniGIC ../../data/points/human.off 700` + +* Builds the Voronoi Graph Induced Complex with 700 subsamples from `human.off` file. +`../../data/points/human_sc.off` can be visualized with GeomView. + diff --git a/src/Rips_complex/utilities/README b/src/Rips_complex/utilities/README index 4d20c806..44a37543 100644 --- a/src/Rips_complex/utilities/README +++ b/src/Rips_complex/utilities/README @@ -1,6 +1,20 @@ -# Rips_complex # - -## `rips_persistence` ## +--- +layout: page +title: "Rips complex" +meta_title: "ripscomplex" +subheadline: "" +teaser: "" +permalink: "/ripscomplex/" +--- +{::comment} +These flags above are here for web site generation, please let them. +cf. https://gitlab.inria.fr/GUDHI/website +Must be in conformity with _data/navigation.yml +{:/comment} + + + +## rips_persistence ## This program computes the persistent homology with coefficient field *Z/pZ* of a Rips complex defined on a set of input points. The output diagram contains one bar per line, written with the convention: `p dim birth death` @@ -8,6 +22,7 @@ This program computes the persistent homology with coefficient field *Z/pZ* of a where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, and `p` is the characteristic of the field *Z/pZ* used for homology coefficients (`p` must be a prime number). **Usage** + `rips_persistence [options] ` **Allowed options** @@ -22,53 +37,25 @@ where `dim` is the dimension of the homological feature, `birth` and `death` are Beware: this program may use a lot of RAM and take a lot of time if `max-edge-length` is set to a large value. **Example 1 with Z/2Z coefficients** -`rips_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 2` -outputs: -``` -2 0 0 inf -2 1 0.0983494 inf -2 1 0.104347 inf -2 2 0.138335 inf -``` +`rips_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 2` **Example 2 with Z/3Z coefficients** -rips_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 3 - -outputs: -``` -3 0 0 inf -3 1 0.0983494 inf -3 1 0.104347 inf -3 2 0.138335 inf -``` +`rips_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 3` +## rips_distance_matrix_persistence ## +Same as `rips_persistence` but taking a distance matrix as input. -## `rips_distance_matrix_persistence` ## -Same as `rips_persistence` but taking a distance matrix as input. - **Usage** -`rips_persistence [options] ` -where + +`rips_persistence [options] ` + +where `` is the path to the file containing a distance matrix. Can be square or lower triangular matrix. Separator is ';'. **Example** -`rips_distance_matrix_persistence data/distance_matrix/full_square_distance_matrix.csv -r 15 -d 3 -p 3 -m 0` -outputs: -``` -The complex contains 46 simplices - and has dimension 3 -3 0 0 inf -3 0 0 8.94427 -3 0 0 7.28011 -3 0 0 6.08276 -3 0 0 5.83095 -3 0 0 5.38516 -3 0 0 5 -3 1 11 12.0416 -3 1 6.32456 6.7082 -``` +`rips_distance_matrix_persistence data/distance_matrix/full_square_distance_matrix.csv -r 15 -d 3 -p 3 -m 0` diff --git a/src/Witness_complex/utilities/README b/src/Witness_complex/utilities/README index 1141033e..5cdb1f88 100644 --- a/src/Witness_complex/utilities/README +++ b/src/Witness_complex/utilities/README @@ -1,18 +1,34 @@ -# Witness_complex # +--- +layout: page +title: "Witness complex" +meta_title: "witnesscomplex" +subheadline: "" +teaser: "" +permalink: "/witnesscomplex/" +--- +{::comment} +These flags above are here for web site generation, please let them. +cf. https://gitlab.inria.fr/GUDHI/website +Must be in conformity with _data/navigation.yml +{:/comment} + For more details about the witness complex, please read the [user manual of the package](http://gudhi.gforge.inria.fr/doc/latest/group__witness__complex.html). -## `weak_witness_persistence` ## -This program computes the persistent homology with coefficient field *Z/pZ* of a Weak witness complex defined on a set of input points. The output diagram contains one bar per line, written with the convention: +## weak_witness_persistence ## +This program computes the persistent homology with coefficient field *Z/pZ* of a Weak witness complex defined on a set of input points. +The output diagram contains one bar per line, written with the convention: `p dim birth death` -where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, and `p` is the characteristic of the field *Z/pZ* used for homology coefficients. +where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, +and `p` is the characteristic of the field *Z/pZ* used for homology coefficients. + +**Usage** -*Usage* `weak_witness_persistence [options] ` -*Allowed options* +**Allowed options** * `-h [ --help ]` Produce help message * `-l [ --landmarks ]` Number of landmarks to choose from the point cloud. @@ -22,33 +38,28 @@ where `dim` is the dimension of the homological feature, `birth` and `death` are * `-m [ --min-persistence ]` (default = 0) Minimal lifetime of homology feature to be recorded. Enter a negative value to see zero length intervals. * `-d [ --cpx-dimension ]` (default = 2147483647) Maximal dimension of the weak witness complex we want to compute. -*Example* -`weak_witness_persistence data/points/tore3D_1307.off -l 20 -a 0.5 -m 0.006` +**Example** -outputs: -``` -Successfully read 1307 points. -Ambient dimension is 3. -The complex contains 732 simplices and has dimension 8 -11 0 0 inf -11 1 0 inf -11 2 0.0275251 0.0534586 -11 1 0 0.0239952 -``` +`weak_witness_persistence data/points/tore3D_1307.off -l 20 -a 0.5 -m 0.006` N.B.: output is random as the 20 landmarks are chosen randomly. -## `strong_witness_persistence` ## -This program computes the persistent homology with coefficient field *Z/pZ* of a Strong witness complex defined on a set of input points. The output diagram contains one bar per line, written with the convention: + +## strong_witness_persistence ## + +This program computes the persistent homology with coefficient field *Z/pZ* of a Strong witness complex defined on a set of input points. +The output diagram contains one bar per line, written with the convention: `p dim birth death` -where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, and `p` is the characteristic of the field *Z/pZ* used for homology coefficients. +where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, +and `p` is the characteristic of the field *Z/pZ* used for homology coefficients. + +**Usage** -*Usage* `strong_witness_persistence [options] ` -*Allowed options* +**Allowed options** * `-h [ --help ]` Produce help message * `-l [ --landmarks ]` Number of landmarks to choose from the point cloud. @@ -58,17 +69,8 @@ where `dim` is the dimension of the homological feature, `birth` and `death` are * `-m [ --min-persistence ]` (default = 0) Minimal lifetime of homology feature to be recorded. Enter a negative value to see zero length intervals. * `-d [ --cpx-dimension ]` (default = 2147483647) Maximal dimension of the weak witness complex we want to compute. -*Example* -`strong_witness_persistence data/points/tore3D_1307.off -l 20 -a 0.5 -m 0.06` +**Example** -outputs: -``` -Successfully read 1307 points. -Ambient dimension is 3. -The complex contains 1836 simplices and has dimension 8 -11 0 0 inf -11 1 0.00674748 inf -11 2 0.0937751 0.235354 -``` +`strong_witness_persistence data/points/tore3D_1307.off -l 20 -a 0.5 -m 0.06` N.B.: output is random as the 20 landmarks are chosen randomly. diff --git a/src/common/utilities/README b/src/common/utilities/README index 18fa8cc4..f39c63b8 100644 --- a/src/common/utilities/README +++ b/src/common/utilities/README @@ -1,19 +1,43 @@ -# Pointset generator # +--- +layout: page +title: "Pointset generator" +meta_title: "pointsetgenerator" +subheadline: "" +teaser: "" +permalink: "/pointsetgenerator/" +--- +{::comment} +These flags above are here for web site generation, please let them. +cf. https://gitlab.inria.fr/GUDHI/website +Must be in conformity with _data/navigation.yml +{:/comment} -## `off_file_from_shape_generator` ## +## off_file_from_shape_generator ## Generates a pointset and save it in an OFF file. Command-line is: -`off_file_from_shape_generator on|in sphere|cube|curve|torus|klein ...` + +``` +off_file_from_shape_generator on|in sphere|cube|curve|torus|klein ... +``` Warning: "on cube" generator is not available! -Examples: +**Examples** + +``` +off_file_from_shape_generator on sphere onSphere.off 1000 3 15.2 +``` + +* Generates an onSphere.off file with 1000 points randomized on a sphere of dimension 3 and radius 15.2. + +``` +off_file_from_shape_generator in sphere inSphere.off 100 2 +``` + +* Generates an inSphere.off file with 100 points randomized in a sphere of dimension 2 (circle) and radius 1.0 (default). -* Generate an onSphere.off file with 1000 points randomized on a sphere of dimension 3 and radius 15.2: -`off_file_from_shape_generator on sphere onSphere.off 1000 3 15.2` - -* Generate an inSphere.off file with 100 points randomized in a sphere of dimension 2 (circle) and radius 1.0 (default): -`off_file_from_shape_generator in sphere inSphere.off 100 2` +``` +off_file_from_shape_generator in cube inCube.off 10000 3 5.8 +``` -* Generates a inCube.off file with 10000 points randomized in a cube of dimension 3 and side 5.8: -`off_file_from_shape_generator in cube inCube.off 10000 3 5.8` +* Generates a inCube.off file with 10000 points randomized in a cube of dimension 3 and side 5.8. -- cgit v1.2.3