FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated use `arr[tuple(seq)]` instead of `arr[seq]`

I can reproduce the warning with:

In [313]: x = np.zeros((4,2))In [315]: x[:,1]Out[315]: array([0., 0., 0., 0.])

By replacing the : with a slice(None) we can write this indexing as:

In [316]: x[[slice(None),1]]/usr/local/bin/ipython3:1: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.  #!/usr/bin/python3Out[316]: array([0., 0., 0., 0.])

It really should be a tuple, rather than a list:

In [317]: x[(slice(None),1)]Out[317]: array([0., 0., 0., 0.])In [318]: x[tuple([slice(None),1])]Out[318]: array([0., 0., 0., 0.])

The warning tells us that the list format used to be ok, but will in the future produce an error.

I don't see anything your code that does this sort of slice in a list indexing.

data from genfromtxt is a structured array, so indexing by field name is normal: data["column_1"]. So it's likely that the warning is generated within the plot code. But we don't have any clue as to where. The warning doesn't give any sort of error stack trace, do it?

So without a sample array like data, or a csv file like Example.csv, we can't reproduce the warning, and dig further.

For a start I'd put some sort of print between each of your code lines. The goal is to pin down which matplotlib call is producing the warning.

If for example it is produced in

host.set_xlim([data["column_1"][0], data["column_1"][-1]])

I might try changing that call to

host.set_xlim((data["column_1"][0], data["column_1"][-1]))

or

host.set_xlim(data["column_1"][0], data["column_1"][-1])

That's a bit of wild guess...

edit

FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated use `arr[tuple(seq)]`

This latest SO, helps us identify a problem function in the scipy.stats package. It constructs a list of slices, and uses it without further conversion to tuple.

Upadating Scipy fixed this problem in my case. Cause the Scipy.stats class was deprecated.

I would have tested this before posting (well, I did test it for areas where I was having the same problem), but I suspect that this will help you. Using your first line where you call a plot above, use tuple type casting as I've shown and do the same to your other lines calling plot.

p1, = host.plot(tuple(data["column_1"]),                 tuple(data["column_2"]),                 "b-", label="column_2")

When I studied numpy methods of indexing, the warning made a little more sense. However, I don't really understand why things need to go this way.