On 26 October 2010 21:02, Dewald Pieterse <dewald.piete...@gmail.com> wrote: > I see my slicing was the problem, np.vstack((test[:1], test)) works > perfectly.
Yes and no. np.newaxis (or "None" for short) is a very useful tool; you just stick it in an index expression and it adds an axis of length one there. If what you really wanted to do was pull out one plane of the array, then indexing with a number was the right thing to do. If you want to stack that plane back on the array, just add an axis of length one to it. S = A[1,...] A = np.vstack((S[np.newaxis,...],A)) As a side note, np.newaxis is actually just None, but I find the longer name much clearer, so I try to use it in my own code, and I always use it in examples I'm showing other people. I suppose a third option would be "import numpy.newaxis as na". Anne > On Wed, Oct 27, 2010 at 12:55 AM, <josef.p...@gmail.com> wrote: >> >> On Tue, Oct 26, 2010 at 8:15 PM, Dewald Pieterse >> <dewald.piete...@gmail.com> wrote: >> > Starting with: >> > >> >> In [93]: test = >> >> numpy.array([[[1,1,1],[1,1,1]],[[2,2,2],[2,2,2]],[[3,3,3],[3,3,3]]]) >> >> >> >> In [94]: test >> >> Out[94]: >> >> array([[[1, 1, 1], >> >> [1, 1, 1]], >> >> >> >> [[2, 2, 2], >> >> [2, 2, 2]], >> >> >> >> [[3, 3, 3], >> >> [3, 3, 3]]]) >> >> >> >> Slicing the complete first row: >> >> >> >> In [95]: firstrow = test[0,:,:] >> >> >> >> In [96]: firstrow >> >> Out[96]: >> >> array([[1, 1, 1], >> >> [1, 1, 1]]) >> > >> > I want to stack firstrow onto test to end up with: >> > >> >> ([[[1, 1, 1], >> >> [1, 1, 1]], >> >> >> >> [[1, 1, 1], >> >> [1, 1, 1]], >> >> >> >> [[2, 2, 2], >> >> [2, 2, 2]], >> >> >> >> [[3, 3, 3], >> >> [3, 3, 3]]] >> > >> > >> > vstack wants the array dimensions to be the same, is this possible >> > without >> > doing 1 dimensional reshape, the actual data I want to do this on is >> > some >> > what larger. >> > >> >> numpy.vstack((firstrow,test)) >> >> >> >> >> >> --------------------------------------------------------------------------- >> >> ValueError Traceback (most recent call >> >> last) >> >> >> >> /mnt/home/home/bmeagle/M/programme/analiseerverwerkteprent.py in >> >> <module>() >> >> ----> 1 >> >> 2 >> >> 3 >> >> 4 >> >> 5 >> >> >> >> /usr/lib64/python2.6/site-packages/numpy/core/shape_base.py in >> >> vstack(tup) >> >> 212 >> >> 213 """ >> >> --> 214 return _nx.concatenate(map(atleast_2d,tup),0) >> >> 215 >> >> 216 def hstack(tup): >> >> >> >> ValueError: arrays must have same number of dimensions >> > >> > >> > What is the correct python way to do this? >> >> keep the first dimension or add it back in >> >> >>> test = >> >>> np.array([[[1,1,1],[1,1,1]],[[2,2,2],[2,2,2]],[[3,3,3],[3,3,3]]]) >> >>> np.vstack((test[:1], test)) >> array([[[1, 1, 1], >> [1, 1, 1]], >> >> [[1, 1, 1], >> [1, 1, 1]], >> >> [[2, 2, 2], >> [2, 2, 2]], >> >> [[3, 3, 3], >> [3, 3, 3]]]) >> >>> np.vstack((test[0][None,...], test)) >> array([[[1, 1, 1], >> [1, 1, 1]], >> >> [[1, 1, 1], >> [1, 1, 1]], >> >> [[2, 2, 2], >> [2, 2, 2]], >> >> [[3, 3, 3], >> [3, 3, 3]]]) >> >>> np.vstack((test[0][None,:,:], test)) >> array([[[1, 1, 1], >> [1, 1, 1]], >> >> [[1, 1, 1], >> [1, 1, 1]], >> >> [[2, 2, 2], >> [2, 2, 2]], >> >> [[3, 3, 3], >> [3, 3, 3]]]) >> >> I like expand_dims for arbitrary axis, e.g. >> >> >>> ax=1 >> >>> np.concatenate((np.expand_dims(test[:,0,:],ax), test), ax) >> array([[[1, 1, 1], >> [1, 1, 1], >> [1, 1, 1]], >> >> [[2, 2, 2], >> [2, 2, 2], >> [2, 2, 2]], >> >> [[3, 3, 3], >> [3, 3, 3], >> [3, 3, 3]]]) >> >> Josef >> >> >> > >> > >> > -- >> > Dewald Pieterse >> > >> > >> > _______________________________________________ >> > NumPy-Discussion mailing list >> > NumPy-Discussion@scipy.org >> > http://mail.scipy.org/mailman/listinfo/numpy-discussion >> > >> > >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > -- > Dewald Pieterse > > "A democracy is nothing more than mob rule, where fifty-one percent of the > people take away the rights of the other forty-nine." ~ Thomas Jefferson > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
