[Tutor] TypeError: unhashable type: 'pygame.math.Vector2'

[Cravan]

Hi Mats,
	Sorry for the late reply. Thanks for your suggestion, I realised that Q was merely giving only some values due to my class settings. However, I have no idea how to set all the coordinates as my state Space. Assuming WIDTH and HEIGHT are the width and height of my env respectively, how should I define my state space within the class itself?
Something like this (although this is wrong) :
 self.stateSpace = [(i for i in range(int(WIDTH)), q for q in range(int(HEIGHT)))]

Essentially my logic is for each number in range(Width), pair it to a number in range(HEIGHT). How should I rectify the code above so as to fit my logic while also conforming to "Pythonic" laws?
Cravan

On 26/6/20, 10:43 PM, "Tutor on behalf of Mats Wichmann" <tutor-bounces+savageapple850=gmail.com at python.org on behalf of mats at wichmann.us> wrote:

    On 6/26/20 8:25 AM, Cravan wrote:
    > Sadly, an error pops up when I change the code.
    > Here's my edited code for the class file:
    
    > However, this error pops up:
    > #######
    > Traceback (most recent call last):
    >   File "maze.py", line 181, in <module>
    >     g.run()
    >   File "maze.py", line 53, in run
    >     self.update()
    >   File "maze.py", line 109, in update
    >     action_ = maxAction(Q, observationnew, possible_actions)
    >   File "maze.py", line 177, in maxAction
    >     values = np.array([Q[state,a] for a in actions])
    >   File "maze.py", line 177, in <listcomp>
    >     values = np.array([Q[state,a] for a in actions])
    > KeyError: ((6, 26), 'U')
    > ######
    > 
    > Apologies for the (late) and long email here, would appreciate if someone could offer some help.
    Well, again the error tells you what is happening: KeyError means you
    tried to look up a key in a dictionary that is actually not present in
    the dictionary.
    
    So Q does not contain the tuple  ((6, 26), 'U')
    
    only you can tell if that's a legitimate result, or an unexpected one.
    
    if it's *expected* that there will be some mismatches, you can do this:
    
    try:
        values = np.array([Q[state,a] for a in actions])
    except KeyError:
        # take appropriate action for missing key
    
    If it's unexpected, then you have some recoding to do.
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