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I am using a set operation in python to perform a symmetric difference between two numpy arrays. The result, however, is a set and I need to convert it back to a numpy array to move forward. Is there a way to do this? Here's what I tried:
a = numpy.array([1,2,3,4,5,6]) b = numpy.array([2,3,5]) c = set(a) ^ set(b) The results is a set:
In [27]: c Out[27]: set([1, 4, 6]) If I convert to a numpy array, it places the entire set in the first array element.
In [28]: numpy.array(c) Out[28]: array(set([1, 4, 6]), dtype=object) What I need, however, would be this:
array([1,4,6],dtype=int) I could loop over the elements to convert one by one, but I will have 100,000 elements and hoped for a built-in function to save the loop. Thanks!
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Convert a list to a NumPy array: numpy. You can convert a list to a NumPy array by passing a list to numpy. array() . The data type dtype of generated numpy. ndarray is automatically determined from the original list but can also be specified with the dtype parameter.
NumPy Set OperationsSets are used for operations involving frequent intersection, union and difference operations.
Create a List object. Add elements to it. Create an empty array with size of the created ArrayList. Convert the list to an array using the toArray() method, bypassing the above-created array as an argument to it.
Do:
>>> numpy.array(list(c)) array([1, 4, 6]) And dtype is int (int64 on my side.)
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Don't convert the numpy array to a set to perform exclusive-or. Use setxor1d directly.
>>> import numpy >>> a = numpy.array([1,2,3,4,5,6]) >>> b = numpy.array([2,3,5]) >>> numpy.setxor1d(a, b) array([1, 4, 6]) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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