[SciPy-User] Choosing sub array based on values in a column
Mon Mar 22 22:00:04 CDT 2010
I feel kinda stupid as I think this must be easier than I am making it.
Below my question you will see an answer I got to a question that I thought
I would be able to complete the last steps my self I was wrong :)
So if I have an array
Y = np.rec.array([(1.0, 0.0, 3.0, 3.5), (0.0, 0.0, 6.0, 6.5), (1.0, 1.0,
9.0, 9.5)], dtype=[('var1', '<f8'), ('var2', '<f8'), ('var3',
'<f8'), ('var4', '<f8')])
do this works like I would expect
>>>array([(3.0, 3.5), (9.0, 9.5)],
dtype=[('var3', '<f8'), ('var4', '<f8')])
But I would like to do this,
>>> Y[['var3','var4']][Y['var1']==0 and Y['var2']==0]
Traceback (most recent call last):
File "<string>", line 1, in <fragment>
ValueError: The truth value of an array with more than one element is
ambiguous. Use a.any() or a.all()
I tried some any() and all() combination but nothing worked. What s the
right way to go about this?
This answer was received on the mail list from Skipper Seabold
If you have a rec array
Y = np.rec.array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0), (7.0, 8.0, 9.0)],
You can access the rows like,
Note the list within .
If you want a "normal" array, I like this way that Pierre recently
pointed out. 3 is the number of columns, and it fills in the number
note the tuple for the view, if they're all floats. Taking a view
might not work if var# have different types, like ints and floats.
If you want the mean of the rows (mean over the columns axis = 1)
Also, for now, the columns will given back to you in the order they're
in in the array no matter which way you ask for them. A patch has
been submitted for returning the order you ask that I hope gets picked
my blog <http://vincentdavis.net> |
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