Dask ( http://dask.pydata.org/en/latest/array-api.html ) is a flexible parallel computing library for analytics. It scales to big data, in constrast to Numpy and has many similar methods. How can I achieve the same effect as numpy.tile
on a dask array?
Using dask.array.concatenate()
could be a possible workaround.
Demo in NumPy:
In [374]: x = numpy.arange(4).reshape((2, 2))
In [375]: x
Out[375]:
array([[0, 1],
[2, 3]])
In [376]: n = 3
In [377]: numpy.tile(x, n)
Out[377]:
array([[0, 1, 0, 1, 0, 1],
[2, 3, 2, 3, 2, 3]])
In [378]: numpy.concatenate([x for i in range(n)], axis=1)
Out[378]:
array([[0, 1, 0, 1, 0, 1],
[2, 3, 2, 3, 2, 3]])
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