New api for html file

.binder/requirements.txt

@@ -8,7 +8,7 @@ tensorflow-addons
 plotly
 pot
 networkx
-gudhi!=3.7.0 # cf. https://github.com/GUDHI/TDA-tutorial/issues/65
+gudhi>=3.9.0 # Tuto-GUDHI-cover-complex.ipynb requires sklearn interfaces
 torch
 tqdm
 eagerpy

utils/KeplerMapperVisuFromTxtFile.py

@@ -1,9 +1,7 @@
 #!/usr/bin/env python
 
-import km
-import numpy as np
-from collections import defaultdict
 import argparse
+from gudhi.cover_complex import _save_to_html
 
 """This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
     See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
@@ -30,48 +28,16 @@
 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
-
+    points = [[float(j) for j in f.readline().split(" ")] for i in range(0, nums[0])]
+    edges = [[int(j) for j in f.readline().split(" ")]    for i in range(0, nums[1])]
     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()
+
+_save_to_html(dat, lens, color, param, points, edges, html_output_filename)