Wrote my own color function not working..I dont know how much I am right

[mlnjsh]

Hi @ dev

I am sure you will solve this issue..
I am sendng you relevant part of code here

graph = mapper.map(projected_data,X,nr_cubes=14,overlap_perc=0.8,clusterer=sklearn.cluster.DBSCAN(eps=15, min_samples=4))


model = ensemble.IsolationForest(random_state=1729)
model.fit(X)
usecolor = model.decision_function(X).reshape((X.shape[0], 1))

node=graph['nodes'].values()
cluster= list(node)
# My own Function..I am trying to color each node by avg anomaly score of the data points in that node
z=[]
for i in range(0,len(cluster)):   
    z.append(np.round(np.mean(usecolor[cluster[i]])*10,decimals=4,out=None))  
print(z)
s=np.asarray(z)
s

I am getting following output

Mapping on data shaped (150, 4) using lens shaped (150, 2)

Creating 196 hypercubes.

Created 57 edges and 24 nodes in 0:00:00.054112.
[0.6021, 0.4893, 0.2385, -0.2715, 0.7183, 0.7395, 0.6809, 0.4972, 0.333, 0.6087, 0.6839, 0.5749, 0.3008, 0.4609, 0.3176, 0.2205, 0.1462, -0.05, 0.4609, 0.4583, 0.0631, 0.559, 0.5166, 0.1199]

array([ 0.6021,  0.4893,  0.2385, -0.2715,  0.7183,  0.7395,  0.6809,
        0.4972,  0.333 ,  0.6087,  0.6839,  0.5749,  0.3008,  0.4609,
        0.3176,  0.2205,  0.1462, -0.05  ,  0.4609,  0.4583,  0.0631,
        0.559 ,  0.5166,  0.1199])

Now I go to next part of code

# Visualize it

mapper.visualize(simplicial_complex, path_html="/home/dhananjay/kepler-mapper/keplermapper-iris.html", custom_meta={"Data:": "Me"}, custom_tooltips=Y,color_function=z)

But I am getting error

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-14-0692ad6431ec> in <module>()
      6         0.4972,  0.333 ,  0.6087,  0.6839,  0.5749,  0.3008,  0.4609,
      7         0.3176,  0.2205,  0.1462, -0.05  ,  0.4609,  0.4583,  0.0631,
----> 8         0.559 ,  0.5166,  0.1199]))

~/kepler-mapper/kmapper/kmapper.py in visualize(self, graph, color_function, custom_tooltips, custom_meta, path_html, title, save_file, X, X_names, lens, lens_names, show_tooltips)
    507         mapper_data = format_mapper_data(graph, color_function, X,
    508                                          X_names, lens,
--> 509                                          lens_names, custom_tooltips, env)
    510 
    511         histogram = graph_data_distribution(graph, color_function)

~/kepler-mapper/kmapper/visuals.py in format_mapper_data(graph, color_function, X, X_names, lens, lens_names, custom_tooltips, env)
     58     for i, (node_id, member_ids) in enumerate(graph["nodes"].items()):
     59         node_id_to_num[node_id] = i
---> 60         c = _color_function(member_ids, color_function)
     61         t = _type_node()
     62         s = _size_node(member_ids)

~/kepler-mapper/kmapper/visuals.py in _color_function(member_ids, color_function)
    219 
    220 def _color_function(member_ids, color_function):
--> 221     return _color_idx(np.mean(color_function[member_ids]))
    222     # return int(np.mean(color_function[member_ids]) * 30)
    223 

IndexError: index 50 is out of bounds for axis 1 with size 24

[sauln]

The color_function is must have the same number of entries as data points. So for you dataset with 150 observations, you would need it length 150, with each entry associated to each observation. The visualize method will then take the average of these values for you.

Try passing the results of usecolor in:

mapper.visualize(simplicial_complex, path_html="...", 
                 custom_meta={"Data:": "Me"}, 
                 custom_tooltips=Y,
                 color_function=usecolor)

[mlnjsh]

Thanku so much...I got it