dask.array.vstack

dask.array.vstack¶

dask.array.vstack(tup, allow_unknown_chunksizes=False)[source]¶

Stack arrays in sequence vertically (row wise).

This docstring was copied from numpy.vstack.

Some inconsistencies with the Dask version may exist.

This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (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.

np.row_stack is an alias for vstack. They are the same function.

Parameters

tupsequence of ndarrays: The arrays must have the same shape along all but the first axis. 1-D arrays must have the same length.
dtypestr or dtype (Not supported in Dask): If provided, the destination array will have this dtype. Cannot be provided together with out.
.. versionadded:: 1.24
casting{‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional (Not supported in Dask): Controls what kind of data casting may occur. Defaults to ‘same_kind’.
.. versionadded:: 1.24

Returns

stackedndarray: The array formed by stacking the given arrays, will be at least 2-D.

See also

concatenate: Join a sequence of arrays along an existing axis.
stack: Join a sequence of arrays along a new axis.
block: Assemble an nd-array from nested lists of blocks.
hstack: Stack arrays in sequence horizontally (column wise).
dstack: Stack arrays in sequence depth wise (along third axis).
column_stack: Stack 1-D arrays as columns into a 2-D array.
vsplit: Split an array into multiple sub-arrays vertically (row-wise).

Examples

>>> 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]])  
>>> b = np.array([[4], [5], [6]])  
>>> np.vstack((a,b))  
array([[1],
       [2],
       [3],
       [4],
       [5],
       [6]])

dask.array.vdot

dask.array.where