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What is the difference between Numpy's array() and asarray() functions? When should you use one rather than the other? They seem to generate identical output for all the inputs I can think of.
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asarray() function is used when we want to convert input to an array. Input can be lists, lists of tuples, tuples, tuples of tuples, tuples of lists and arrays. Syntax : numpy.asarray(arr, dtype=None, order=None)
asanyarray() function is used when we want to convert input to an array but it pass ndarray subclasses through. Input can be scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Syntax : numpy.asanyarray(arr, dtype=None, order=None)
subok : [bool, optional] to make subclass of a or not. Return : array with the same shape and type as a given array.
The definition of asarray is:
def asarray(a, dtype=None, order=None): return array(a, dtype, copy=False, order=order) So it is like array, except it has fewer options, and copy=False. array has copy=True by default.
The main difference is that array (by default) will make a copy of the object, while asarray will not unless necessary.
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