问题
I have a list of [float, (float,float,float..) ] ... Which is basically an n-dimensional point along with a fitness value for each point. For eg.
4.3, (2,3,4)
3.2, (1,3,5)
.
.
48.2, (23,1,32)
I wish to randomly sample one point based upon the fitness values. I decided the best way to do this would be to use numpy.random.choice(range(n), 1, plist[:,:1,:1])
However, i need to convert this into an numpy array, for which i tried
>> pArr = np.array( plist )
ValueError: setting an array element with a sequence
I got the same error for np.asarray(plist) as well.. any suggestions??
回答1:
The following should work:
A = np.array([tuple(i) for i in initial_list],dtype=[('fitness',float),('point',(float,3))])
with initial_list = [[4.3, (2, 3, 4)], [3.2, (1, 3, 5)], ...]
. Note that we need to transform each item of initial_list
into a tuple for that trick to work, else NumPy cannot recognize the structure.
Your fitness entries are now accessible as A['fitness']
, with the corresponding points as A['point']
. If you select a list of actual fitness entries, indices
, the corresponding points are given by A['point'][indices]
, which is a simple (n,3)
array.
回答2:
Your question is difficult to understand. Is this what you're trying to do?
>>> x
[[4.3, (2, 3, 4)], [3.2, (1, 3, 5)], [48.2, (23, 1, 32)]]
>>> np.array([(a, b, c, d) for a, (b, c, d) in x])
array([[ 4.3, 2. , 3. , 4. ],
[ 3.2, 1. , 3. , 5. ],
[ 48.2, 23. , 1. , 32. ]])
来源:https://stackoverflow.com/questions/12253447/converting-a-list-of-ints-tuples-into-an-numpy-array