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

4 files changed, 139 insertions, 48 deletions

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<std::vector<int> > 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 <OFF input file> 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 <OFF input file> 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.
+