Leland McInnes

@ivenzor Yes, that would be the right approach right now. One alternative would be to check out the 0.4dev branch which has a (very!) experimental class called DataframeUMAP that would...

Fortunately that is just a warning: you won't be able to use the ``inverse_transform`` method -- but then you can't use that in the model here anyway, so there is...

The intersection functionality is more mature, so I would definitely suggest that as the right way to go. If you are getting very different results and you prefer the older...

No, that is a definite downside. If you need mixing weights you can take a look at how the ``__mul__`` operator is implemented and potentially code up an equivalent adding...

This is the right thing to do; the difference is that the SGD in the basic UMAP implementation uses sampling to apply edge weights (edges are sampled proportionally to their...

I think we actually need to change the plot API to accept an axis argument to make this work easily in the manner you are trying here. I suspect, since...

Sadly I think that is the recommended approach at this point. You could also look at using joblib for serialization instead of pickle.

I think the simplest thing is to delete the ``_rp_trees`` attribute. You'll only need it if you want to transform new data, and for the use cases you describe that...

The easiest hacky way would be to use ``init="random"``. It won't be great, but it will get you something in the interim. I'll have to think a little harder about...

I'm afraid I can't help too much more without being able to reproduce the problem at this end. One catch might be the disconnection distance. You could explicitly set that...