hstack(tup, allow_unknown_chunksizes=False)
This docstring was copied from numpy.hstack.
Some inconsistencies with the Dask version may exist.
This is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis. Rebuilds arrays divided by :None:None:`hsplit`.
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 :None:None:`concatenate`, stack
and block
provide more general stacking and concatenation operations.
The arrays must have the same shape along all but the second axis, except 1-D arrays which can be any length.
The array formed by stacking the given arrays.
Stack arrays in sequence horizontally (column 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).
hsplit
Split an array into multiple sub-arrays horizontally (column-wise).
stack
Join a sequence of arrays along a new axis.
vstack
Stack arrays in sequence vertically (row wise).
>>> a = np.array((1,2,3)) # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... b = np.array((4,5,6)) # doctest: +SKIP
... np.hstack((a,b)) # doctest: +SKIP array([1, 2, 3, 4, 5, 6])
>>> a = np.array([[1],[2],[3]]) # doctest: +SKIPSee :
... b = np.array([[4],[5],[6]]) # doctest: +SKIP
... np.hstack((a,b)) # doctest: +SKIP array([[1, 4], [2, 5], [3, 6]])
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.routines.dstack
dask.array.core.block
dask.utils.concatenate
dask.array.routines.vstack
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