I have a 3d numpy array(data) with shape say (103, 37, 13). I want to resize this numpy array to (250,250,13) by zero padding almost equally in both directions along each axis.
The code below works well for 2d array, but I am not able to make it work for 3d array.
>>> a = np.arange(6)
>>> a = a.reshape((2, 3))
>>> np.lib.pad(a, [(2,3),(1,1)], 'constant', constant_values=[(0, 0),(0,0)])
array([[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 1, 2, 0],
[0, 3, 4, 5, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]])
>>> zerpads =np.zeros(13)
>>> data1=np.lib.pad(data,[(73,74),(106,107)],'constant',constant_values=[(zerpads, zerpads),(zerpads,zerpads)])
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/ayush/anaconda2/lib/python2.7/site-packages/numpy/lib/arraypad.py", line 1295, in pad
pad_width = _validate_lengths(narray, pad_width)
File "/home/ayush/anaconda2/lib/python2.7/site-packages/numpy/lib/arraypad.py", line 1080, in _validate_lengths
normshp = _normalize_shape(narray, number_elements)
File "/home/ayush/anaconda2/lib/python2.7/site-packages/numpy/lib/arraypad.py", line 1039, in _normalize_shape
raise ValueError(fmt % (shape,))
ValueError: Unable to create correctly shaped tuple from [(73, 74), (106, 107)]
3
pairs of padding widths. Put(0, 0)
if you don't want to pad along an axis. Also,'constant'
mode defaults to0
, so you needn't passconstant_values
. – Thermodata1=np.lib.pad(data,[(73,74,0),(106,107,0)],'constant')
, but i still getValueError: Unable to create correctly shaped tuple from [(73, 74, 0), (106, 107, 0)]
– Dissyllablenp.pad(a, ((73,74), (106,107), (0, 0)), 'constant').shape
– Ronel