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Suppose I have an array A of dtype int32, and I want to cast it into float64. The standard way to do this (that I know) is A.astype('float64'). But this allocates a new array for the result. If I run this command repeatedly (with different arrays of the same shape), each time using the result and discarding it shortly after, then the overhead from these allocations can be non-negligible.
Suppose I pre-allocated an array B, with the same shape of A and of type float64. Is there a way to use the memory of B for the result of the casting, instead of allocating new memory each time? ufuncs and numpy.dot have an 'out' argument for this, but astpye does not.

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    B[...] = A? -- Commented Apr 2, 2018 at 8:33
  • Yes of course! Don't know why I missed this... Commented Apr 2, 2018 at 8:39

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As Paul Panzer commented, this can be done simply by B[...] = A.

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