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method
ndarray.copy(order='C')
Return a copy of the array.
Parameters:order{‘C’, ‘F’, ‘A’, ‘K’}, optionalControls the memory layout of the copy. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible. (Note that this function and
are very similar but have different default values for their order= arguments, and this function always passes sub-classes through.)
Notes
This function is the preferred method for creating an array copy. The function
is similar, but it defaults to using order ‘K’, and will not pass sub-classes through by default.
Examples
>>> importnumpyasnp>>> x=np.array([[1,2,3],[4,5,6]],order='F')>>> y=x.copy()>>> x.fill(0)>>> xarray([[0, 0, 0], [0, 0, 0]])>>> yarray([[1, 2, 3], [4, 5, 6]])>>> y.flags['C_CONTIGUOUS']TrueFor arrays containing Python objects (e.g. dtype=np.object_), the copy is a shallow one. The new array will contain the same object which may lead to surprises if that object can be modified (is mutable):
>>> a=np.array([1,'m',[2,3,4]],dtype=np.object_)>>> b=a.copy()>>> b[2][0]=10>>> aarray([1, 'm', list([10, 3, 4])], dtype=object)To ensure all elements within an object array are copied, use
:
>>> importcopy>>> a=np.array([1,'m',[2,3,4]],dtype=np.object_)>>> c=copy.deepcopy(a)>>> c[2][0]=10>>> carray([1, 'm', list([10, 3, 4])], dtype=object)>>> aarray([1, 'm', list([2, 3, 4])], dtype=object)