Hi all, I must say this is best package I have come across in Python for TDA, but after trying my best to visualize stastics like in the TOR TDA code using my own dataset, I am not getting the mean, or statistics or even displaying Below average or Above Average features in the Visualisation of my final output in HTML.
The error below is what I get OR is there something else I need to do. I am a newbie to Python but still managed to get my understanding visualizing my graph, but the problem is ease of intrepretability, which I am finding very hard. Its my humble request if someone can help me. I am currently doing my Phd in TDA in marketing datasets.
that line of code:
_ = mapper.visualize(
G,
custom_tooltips=y,
path_html="Desktop/marketingfile.html",
inverse_X=X,
inverse_X_names=list(df[features].columns),
projected_X=lens,
projected_X_names=["IsolationForest", "KNN-distance 5"],
title="Marketing Dataset"
)
and the error for the above is'
TypeError Traceback (most recent call last)
in
36 projected_X=lens,
37 projected_X_names=["IsolationForest", "KNN-distance 5"],
---> 38 title="Detecting ETF Relationships"
39 )
TypeError: visualize() got an unexpected keyword argument 'inverse_X'
Can someone help me with this.
Thank you all so much.
nathanqfinance
commented
3 years ago
Hi all, I must say this is best package I have come across in Python for TDA, but after trying my best to visualize stastics like in the TOR TDA code using my own dataset, I am not getting the mean, or statistics or even displaying Below average or Above Average features in the Visualisation of my final output in HTML.
The error below is what I get OR is there something else I need to do. I am a newbie to Python but still managed to get my understanding visualizing my graph, but the problem is ease of intrepretability, which I am finding very hard. Its my humble request if someone can help me. I am currently doing my Phd in TDA in marketing datasets.
that line of code: _ = mapper.visualize( G, custom_tooltips=y, path_html="Desktop/marketingfile.html", inverse_X=X, inverse_X_names=list(df[features].columns), projected_X=lens, projected_X_names=["IsolationForest", "KNN-distance 5"], title="Marketing Dataset" )
and the error for the above is'
TypeError Traceback (most recent call last)