numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0)
vs
numpy.asarray(a, dtype=None, order=None)
it is like array, except it has fewer options, specially copy=False. but array is copy=True
The following arguments are those that may be passed to array
and not asarray
as mentioned in the documentation :
copy : bool, optional If true (default), then the object is copied. Otherwise, a copy will only be made if
__array__
returns a copy, if obj is a nested sequence, or if a copy is needed to satisfy any of the other requirements (dtype, order, etc.).subok : bool, optional If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default).
ndmin : int, optional Specifies the minimum number of dimensions that the resulting arrayshould have. Ones will be pre-pended to the shape as needed to meet this requirement.
===============================================================================================================================================================
Reference
http://stackoverflow.com/questions/14415741/numpy-array-vs-asarray
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