numpy.ma.hstack¶

numpy.ma.
hstack
(tup) = <numpy.ma.extras._fromnxfunction_seq object>¶ Stack arrays in sequence horizontally (column wise).
This is equivalent to concatenation along the second axis, except for 1D arrays where it concatenates along the first axis. Rebuilds arrays divided by
hsplit
.This function makes most sense for arrays with up to 3 dimensions. For instance, for pixeldata 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.Parameters: tup : sequence of ndarrays
The arrays must have the same shape along all but the second axis, except 1D arrays which can be any length.
Returns: stacked : ndarray
The array formed by stacking the given arrays.
See also
stack
 Join a sequence of arrays along a new axis.
vstack
 Stack arrays in sequence vertically (row wise).
dstack
 Stack arrays in sequence depth wise (along third axis).
concatenate
 Join a sequence of arrays along an existing axis.
hsplit
 Split array along second axis.
block
 Assemble arrays from blocks.
Notes
The function is applied to both the _data and the _mask, if any.
Examples
>>> a = np.array((1,2,3)) >>> b = np.array((2,3,4)) >>> np.hstack((a,b)) array([1, 2, 3, 2, 3, 4]) >>> a = np.array([[1],[2],[3]]) >>> b = np.array([[2],[3],[4]]) >>> np.hstack((a,b)) array([[1, 2], [2, 3], [3, 4]])