vstack(*args, **kwargs)
This is equivalent to concatenation along the first axis after 1-D arrays of shape :None:None:`(N,)` have been reshaped to :None:None:`(1,N)`. Rebuilds arrays divided by vsplit
.
This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions concatenate
, stack
and block
provide more general stacking and concatenation operations.
The function is applied to both the _data and the _mask, if any.
The arrays must have the same shape along all but the first axis. 1-D arrays must have the same length.
The array formed by stacking the given arrays, will be at least 2-D.
Stack arrays in sequence vertically (row wise).
block
Assemble an nd-array from nested lists of blocks.
column_stack
Stack 1-D arrays as columns into a 2-D array.
concatenate
Join a sequence of arrays along an existing axis.
dstack
Stack arrays in sequence depth wise (along third axis).
hstack
Stack arrays in sequence horizontally (column wise).
stack
Join a sequence of arrays along a new axis.
vsplit
Split an array into multiple sub-arrays vertically (row-wise).
>>> a = np.array([1, 2, 3])
... b = np.array([4, 5, 6])
... np.vstack((a,b)) array([[1, 2, 3], [4, 5, 6]])
>>> a = np.array([[1], [2], [3]])See :
... b = np.array([[4], [5], [6]])
... np.vstack((a,b)) array([[1], [2], [3], [4], [5], [6]])
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