Why can't I produce a Numpy Array from my list? Indexing Error-CodePudding

Trying to follow the Scipy documentation to apply the linear_sum_assignment function to my code, in which I'm trying to assign 1 robot to each pizza so that the total travel time of the robots is as small as possible.

Robots is a list of 6 robot objects of which I am purposely ignoring the first robot. SwapTargets is a list of 5 Pizza objects

newlist = []
for j in range(1,len(Robots)):
  for i in range(0,len(SwapTargets)):
    ref_x = SwapTargets[i].coordinates[0]
    ref_y = SwapTargets[i].coordinates[1]
    value = ((ref_x - Robots[j].x)**2)   (ref_y - Robots[j].y)**2
    newlist.append(value)
  
myarray = np.array(newlist).reshape(len(Robots[1:]),len(SwapTargets))  

from scipy.optimize import linear_sum_assignment

row_ind, col_ind = linear_sum_assignment(myarray)

PizzaList = np.array([SwapTargets])[row_ind]
RobotList = np.array([Robots[1:]])[col_ind]
result = dict(zip(PizzaList, RobotList))
print(result)

At PizzaList = np.array([SwapTargets])[row_ind] I'm getting an error IndexError: index 1 is out of bounds for axis 0 with size 1

Just as a test, If I replace [SwapTargets] with ["A,"B","C","D","E"] in PizzaList = np.array([SwapTargets])[row_ind] in I pull no error, but dont understand why my list of 5 objects does not work.

Thx from a python noobie

CodePudding user response：

You are almost answering your own question. You state that SwapTargets is a list of 5 Pizza objects. This means that it could have been initialized like this:

SwapTargets = [pizza0, pizza1, pizza2, pizza3, pizza4, pizza5]

Then you say that while executing:

PizzaList = np.array(["A", "B", "C", "D", "E"])[row_ind]

works, executing

PizzaList = np.array([SwapTargets])[row_ind]

does not. To understand what's going on, simply substitute the initialization of SwapTargets for the identifier, the above becomes:

PizzaList = np.array([[pizza0, pizza1, pizza2, pizza3, pizza4, pizza5]])[row_ind]

See the double nested brackets?

What's happening here is that you are calling np.array() on a list of just one item (that item itself is a list of 5 items). In the successful call, you were calling the same function of a list of 5 items, which is probably what you want.

What you wanted to write was actually:

PizzaList = np.array(SwapTargets)[row_ind]

(no brackets around the argument).

CodePudding user response：

Consider the difference between the following:

>>> numpy.array([1,2,3])
array([1, 2, 3])

and

>>> numpy.array([[1,2,3]])
array([[1, 2, 3]])

The first is a vector of length 3, the second is a matrix with dimensions (1, 3). You can see by checking the shape of both:

>>> numpy.array([1,2,3]).shape
(3,)
>>> numpy.array([[1,2,3]]).shape
(1, 3)

np.array([SwapTargets]) is just the same as the second example above. Its first dimension is of length 1, and so indexing ends at 0 in the first dimension. You probably want np.array(SwapTargets) instead.