numpy.resize¶

numpy.resize(a,new_shape)[source]¶

Return a new array with the specified shape.

If the new array is larger than the original array, then the newarray is filled with repeated copies ofa. Note that this behavioris different from a.resize(new_shape) which fills with zeros insteadof repeated copies ofa.

Parameters:	a : array_like Array to be resized. new_shape : int or tuple of int Shape of resized array.
Returns:	reshaped_array : ndarray The new array is formed from the data in the old array, repeatedif necessary to fill out the required number of elements. Thedata are repeated in the order that they are stored in memory.

See also

ndarray.resize

resize an array in-place.

Examples

>>>a=np.array([[0,1],[2,3]])>>>np.resize(a,(2,3))array([[0, 1, 2],       [3, 0, 1]])>>>np.resize(a,(1,4))array([[0, 1, 2, 3]])>>>np.resize(a,(2,4))array([[0, 1, 2, 3],       [0, 1, 2, 3]])