
iQc           @   s  d  d l  Z  d  d l Z d  d l Z d  d l Z d  d l Z d d% d     YZ d d& d     YZ d d' d     YZ d d( d	     YZ d
 e f d     YZ	 d   Z
 d e f d     YZ d   Z d   Z d   Z d d  Z d   Z d   Z d   Z d   Z d   Z d   Z d   Z e d  Z d   Z d   Z d  d l Z d  d l Z d e f d     YZ  d d) d      YZ! d a" d a# e$ a% d! d* d"     YZ& d#   Z' d$   Z( d S(+   iNt   FixedRandomc           B   s   e  Z d    Z RS(   c      r  C   s2   d dsd  f } t j   |  _ |  j j |  d  S(t  Ni   l        l   &n<l   a+yQl   m%l   T5 l   suW l   \X l   dtl   Ccq l   }l   IKP`l   Y l   j4il   )oq l    l   +X l   TXl   @e l   ;l   kd\l   ?Sl   "C l   01 l   sl   0) l   $M l   Cogl l   f>;l   Gw_ l    s< l   P" l   U l   in?j l   y l   .*, l   Z l   :u l   Zsul   .G l   Xl   %W l   t^b] l   ,}Tl   k< l   = l   A.77 l   i l   2M l   E% l   S l   Rjv l   6D l   v2pNl   0
 l   #J l   jE6 l   AFf l   XD l   zM l   	s l   6l   X3 l   Ce l   pCX l   <=2Z l   %`<% l   'Dl   ?gq< l   H l   G6D l   oAl   V] l   I l   )H: l   $$l   fYo l   O3a> l   @/l   o? l   El   \ l   .& l   {%) l   0_ l   8G? l    +l   l*Z/ l   3}^l   qc l    l   ^vF l   Gp l   _*q3 l   `w l   Nl   O"dl   aV5J l   L[ l   JY l   gPl   =~~l   a9=l   JPz$ l   , l   cs l   9>1 l   H l   7FX l   P^ l   <J l   IV l   HG-~ l   |&G l   > l   ?+xl   5ql   5.w l   zq l   L[S l   ? l   6gOA l   V l   )4l   ~o l   U l   wN` l   1)Hl   O l   ubxv l   ^Rl l   b&5 l   ~Zt l   0g l   < 9F l   (.G!l   =/( l   h l   !L~N l   S] l   %'fl   !' l   C\o l   8 l   F}s l   %C l   Ym1L l   C l   RSl   Z: l   =; l   FJR l   _AaI l   D$< l   bty l   !jN l   X  l   *Q
l   =Zl   C l   a&l   :| l   2'!l   k1`l   1Vl   PQ l   %u l   br l   3l   V6= l   m6 l   Nc[ l   U!`l   U7T l   ~,
 l   O l   UL l   L" l   vx# l   >(" l   kvl   n'fl   PtIl   n l   Sf|9 l   ~ l   'L l   ~d l   WQ1l   `L l   cw&K l   -j l   CIJ	 l   &Z$ l   ! l   `d
 l   )lC l   | l   MyOl   lT3Y l   OEx l   rZ
 l   :i l   jXl   5p l   S\6l   &B l   O? l   jBp l   JBl   bxE l    H l   ; l   { l   s_jl   l   8l~ l   [ l   !Q l   -N> l   C2T l   X$Hl   x:El   p6a l   w
l   > l   +/$ l     l   Ks l   ? l   }To l   5 l   c<{ l   R? l   3Rl     l   #l   	 l   my0 l   u l   2+` l   xk l    ?l   $h l   M7 l   cgl   \ugl   #Q l   =*( l   9 l   2m l   )D l   c l   }!^l   bv l   s l   Fll   Sx l   f[l   |/k l   E)-l   & l    l    P~i l   QDJ l   l$z l   n- l   2?Bl   vq l   S+ l   D$ l   >x l   #Nl   i9l   "~l   !? l   ? l   tDWl   4 l   iq l   !RU l   )s l   8L l   ^ l   X: l   ,8ml   oh* l   Ja l   6-l l   V l    l   .:, l   d l   }H- l   /lO l   tl   %(l    \l   :vbh l   )Dw l   r K l   Pj] l   > l   yc l   m& l   bG9 l   tNc l   NS3 l   r+- l   +^ l   PEX l   R3 l   l;&l   Spl   1r l   AH l   >!	 l   CTp l   jS l   oE l     l   km} l   
 l   $U l   xal   Wc# l   6* l   3FQ l   ^"l   	{ l   ES+ql   K F l   *K:l   ]< l   HCQ l   ol1l   nR l   S|4
l   H~Yl   s l   7# l   byY l   ^R8Ml   	y l   * l   2 l   OOt l   u&l   # l   
b l   1L l   ( l   vfAl   ( l   \l   >7Y l   Xl   7m` l   V; l   ;5N*l   ~Dal   dC- l    pl   Zy^l   W8 l   =cP l   El   n=^ l   , l   q5l   wc l   _{n l   Qul   l   ## l   (^l   -y6 l   4-6l   o8l   Qd l   _c>l   GP l   ]N(`l   R9: l    ] l   ~: l   >mI l   aG l   >f l   6a l   2p< l   '< l   ;Oc l   1m` l   V l   _[x8 l   4H l   !z l   /W l    bPl   5% l   Tl9l   oNb l   Vl   KD$3 l    \Nl   e7D l   f l   A& l   r. l   `L l   uf l   w0 l   Yof l   #vJ l   => l   5pj l   Tk l   ,% l   #ql   m_l   wCQl   Al   :F l   u l   Q l   t[l   Jn l   PDr l   {JP l   [| l   !"j/l   &x l   O5 Vl   5 m& l   EH l   E%Ln l   (~ l   "i, l   HTl   J{ l   ,Rl   	r l   Q)9l   5Dl   ?$@= l   +}  l   Oj l   1 l   ?w  l   fT2g l    l   2" l   /+T l   K?* l   	 l   @ l   ]H l   m l   yz I l   Oz, l   ,| l   }[l   > l   Z;~ l   I- l   =x l   qC l   y<l   M3 l   b{ l   zC l   $. l   +@ l   \6l   8zl   N$ l   vk l   %i l   z&|3l   ~ l   Lu l   [jl   5 l   7^( l   ,Z_ l   5_ l   J*G l   V|l    } l   ~!+ l   -[v l   JD l   SNal   I  l   X l   e@c3 l   o[ l    l   ~uc l   f` l   J:U l   r8l   6
tl   7u=l   aHml   +(6 l   aH l   <9i l   J= l   e~F l   HMl   iw l   "H0rl   <PMl   ZUG l   0Agl   
vel   w l   !rl   'P_l   5ni l   JM_l   j+! l   3'# l   &e l   EW?l   74 l   %  l   @b l   rkl   S9M{ l   dl   m l   PpB l   B1"l   jfXK l   Mql   Tp,[l   <} l   Ub l   &-=l   71 l   bCl   2 l   S\ l   sHVl   %& l   -Pl   8{ l   z[ l   _j	l   0*	 l   r~ l   _XP l   5H/ l   V-HDl   =f l   3f=il   Aom l   7hl   b	 l   D l   u,g l   @ l   N.= l   g\ l   ]?:l   eA l   * l   ) l   $Tcl   [vC l   c^2 l   l   v9S l   QNXI l   V8 l   [y l   h l   b l   U]V l   ;q l   = l   Lo l   <#e l   5GKl   Yu l   l"d} l   92 l   8F l   c# l   ~Q l   ?A l   6 l   =a l   ;w l   I;2l   jN l   3O4 l   rg l   Pr\ l     - l   1uI l   ST l   & l   K2 l   V* l   5s l   Y?l   ;A l   L l   '0l   \p" l   <l   'z l   Y@Nl   i"	 l   E+l   P l   F_ l   ~Zjl   u	l   z$Ul   D l   p(q  l        l   &n<l   a+yQl   m%l   T5 l   suW l   \X l   dtl   Ccq l   }l   IKP`l   Y l   j4il   )oq l    l   +X l   TXl   @e l   ;l   kd\l   ?Sl   "C l   01 l   sl   0) l   $M l   Cogl l   f>;l   Gw_ l    s< l   P" l   U l   in?j l   y l   .*, l   Z l   :u l   Zsul   .G l   Xl   %W l   t^b] l   ,}Tl   k< l   = l   A.77 l   i l   2M l   E% l   S l   Rjv l   6D l   v2pNl   0
 l   #J l   jE6 l   AFf l   XD l   zM l   	s l   6l   X3 l   Ce l   pCX l   <=2Z l   %`<% l   'Dl   ?gq< l   H l   G6D l   oAl   V] l   I l   )H: l   $$l   fYo l   O3a> l   @/l   o? l   El   \ l   .& l   {%) l   0_ l   8G? l    +l   l*Z/ l   3}^l   qc l    l   ^vF l   Gp l   _*q3 l   `w l   Nl   O"dl   aV5J l   L[ l   JY l   gPl   =~~l   a9=l   JPz$ l   , l   cs l   9>1 l   H l   7FX l   P^ l   <J l   IV l   HG-~ l   |&G l   > l   ?+xl   5ql   5.w l   zq l   L[S l   ? l   6gOA l   V l   )4l   ~o l   U l   wN` l   1)Hl   O l   ubxv l   ^Rl l   b&5 l   ~Zt l   0g l   < 9F l   (.G!l   =/( l   h l   !L~N l   S] l   %'fl   !' l   C\o l   8 l   F}s l   %C l   Ym1L l   C l   RSl   Z: l   =; l   FJR l   _AaI l   D$< l   bty l   !jN l   X  l   *Q
l   =Zl   C l   a&l   :| l   2'!l   k1`l   1Vl   PQ l   %u l   br l   3l   V6= l   m6 l   Nc[ l   U!`l   U7T l   ~,
 l   O l   UL l   L" l   vx# l   >(" l   kvl   n'fl   PtIl   n l   Sf|9 l   ~ l   'L l   ~d l   WQ1l   `L l   cw&K l   -j l   CIJ	 l   &Z$ l   ! l   `d
 l   )lC l   | l   MyOl   lT3Y l   OEx l   rZ
 l   :i l   jXl   5p l   S\6l   &B l   O? l   jBp l   JBl   bxE l    H l   ; l   { l   s_jl   l   8l~ l   [ l   !Q l   -N> l   C2T l   X$Hl   x:El   p6a l   w
l   > l   +/$ l     l   Ks l   ? l   }To l   5 l   c<{ l   R? l   3Rl     l   #l   	 l   my0 l   u l   2+` l   xk l    ?l   $h l   M7 l   cgl   \ugl   #Q l   =*( l   9 l   2m l   )D l   c l   }!^l   bv l   s l   Fll   Sx l   f[l   |/k l   E)-l   & l    l    P~i l   QDJ l   l$z l   n- l   2?Bl   vq l   S+ l   D$ l   >x l   #Nl   i9l   "~l   !? l   ? l   tDWl   4 l   iq l   !RU l   )s l   8L l   ^ l   X: l   ,8ml   oh* l   Ja l   6-l l   V l    l   .:, l   d l   }H- l   /lO l   tl   %(l    \l   :vbh l   )Dw l   r K l   Pj] l   > l   yc l   m& l   bG9 l   tNc l   NS3 l   r+- l   +^ l   PEX l   R3 l   l;&l   Spl   1r l   AH l   >!	 l   CTp l   jS l   oE l     l   km} l   
 l   $U l   xal   Wc# l   6* l   3FQ l   ^"l   	{ l   ES+ql   K F l   *K:l   ]< l   HCQ l   ol1l   nR l   S|4
l   H~Yl   s l   7# l   byY l   ^R8Ml   	y l   * l   2 l   OOt l   u&l   # l   
b l   1L l   ( l   vfAl   ( l   \l   >7Y l   Xl   7m` l   V; l   ;5N*l   ~Dal   dC- l    pl   Zy^l   W8 l   =cP l   El   n=^ l   , l   q5l   wc l   _{n l   Qul   l   ## l   (^l   -y6 l   4-6l   o8l   Qd l   _c>l   GP l   ]N(`l   R9: l    ] l   ~: l   >mI l   aG l   >f l   6a l   2p< l   '< l   ;Oc l   1m` l   V l   _[x8 l   4H l   !z l   /W l    bPl   5% l   Tl9l   oNb l   Vl   KD$3 l    \Nl   e7D l   f l   A& l   r. l   `L l   uf l   w0 l   Yof l   #vJ l   => l   5pj l   Tk l   ,% l   #ql   m_l   wCQl   Al   :F l   u l   Q l   t[l   Jn l   PDr l   {JP l   [| l   !"j/l   &x l   O5 Vl   5 m& l   EH l   E%Ln l   (~ l   "i, l   HTl   J{ l   ,Rl   	r l   Q)9l   5Dl   ?$@= l   +}  l   Oj l   1 l   ?w  l   fT2g l    l   2" l   /+T l   K?* l   	 l   @ l   ]H l   m l   yz I l   Oz, l   ,| l   }[l   > l   Z;~ l   I- l   =x l   qC l   y<l   M3 l   b{ l   zC l   $. l   +@ l   \6l   8zl   N$ l   vk l   %i l   z&|3l   ~ l   Lu l   [jl   5 l   7^( l   ,Z_ l   5_ l   J*G l   V|l    } l   ~!+ l   -[v l   JD l   SNal   I  l   X l   e@c3 l   o[ l    l   ~uc l   f` l   J:U l   r8l   6
tl   7u=l   aHml   +(6 l   aH l   <9i l   J= l   e~F l   HMl   iw l   "H0rl   <PMl   ZUG l   0Agl   
vel   w l   !rl   'P_l   5ni l   JM_l   j+! l   3'# l   &e l   EW?l   74 l   %  l   @b l   rkl   S9M{ l   dl   m l   PpB l   B1"l   jfXK l   Mql   Tp,[l   <} l   Ub l   &-=l   71 l   bCl   2 l   S\ l   sHVl   %& l   -Pl   8{ l   z[ l   _j	l   0*	 l   r~ l   _XP l   5H/ l   V-HDl   =f l   3f=il   Aom l   7hl   b	 l   D l   u,g l   @ l   N.= l   g\ l   ]?:l   eA l   * l   ) l   $Tcl   [vC l   c^2 l   l   v9S l   QNXI l   V8 l   [y l   h l   b l   U]V l   ;q l   = l   Lo l   <#e l   5GKl   Yu l   l"d} l   92 l   8F l   c# l   ~Q l   ?A l   6 l   =a l   ;w l   I;2l   jN l   3O4 l   rg l   Pr\ l     - l   1uI l   ST l   & l   K2 l   V* l   5s l   Y?l   ;A l   L l   '0l   \p" l   <l   'z l   Y@Nl   i"	 l   E+l   P l   F_ l   ~Zjl   u	l   z$Ul   D l   p(   t   Nonet   randomt   Randomt   setstate(   t   selft
   fixedState(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   __init__   s                                                                                            (   t   __name__t
   __module__R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR       s   t   Stackc           B   s2   e  Z d  Z d   Z d   Z d   Z d   Z RS(   s;   A container with a last-in-first-out (LIFO) queuing policy.c         C   s   g  |  _  d  S(   N(   t   list(   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR   v   s    c         C   s   |  j  j |  d S(   s   Push 'item' onto the stackN(   R   t   append(   R   t   item(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   pushy   s    c         C   s   |  j  j   S(   s0   Pop the most recently pushed item from the stack(   R   t   pop(   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR   }   s    c         C   s   t  |  j  d k S(   s"   Returns true if the stack is emptyi    (   t   lenR   (   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   isEmpty   s    (   R   R	   t   __doc__R   R   R   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR
   t   s
   			t   Queuec           B   s2   e  Z d  Z d   Z d   Z d   Z d   Z RS(   s<   A container with a first-in-first-out (FIFO) queuing policy.c         C   s   g  |  _  d  S(   N(   R   (   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    c         C   s   |  j  j d |  d S(   s!   Enqueue the 'item' into the queuei    N(   R   t   insert(   R   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    c         C   s   |  j  j   S(   s   
          Dequeue the earliest enqueued item still in the queue. This
          operation removes the item from the queue.
        (   R   R   (   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    c         C   s   t  |  j  d k S(   s"   Returns true if the queue is emptyi    (   R   R   (   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    (   R   R	   R   R   R   R   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s
   			t   PriorityQueuec           B   s2   e  Z d  Z d   Z d   Z d   Z d   Z RS(   s  
      Implements a priority queue data structure. Each inserted item
      has a priority associated with it and the client is usually interested
      in quick retrieval of the lowest-priority item in the queue. This
      data structure allows O(1) access to the lowest-priority item.

      Note that this PriorityQueue does not allow you to change the priority
      of an item.  However, you may insert the same item multiple times with
      different priorities.
    c         C   s   g  |  _  d |  _ d  S(   Ni    (   t   heapt   count(   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    	c         C   s8   | |  j  | f } t j |  j |  |  j  d 7_  d  S(   Ni   (   R   t   heapqt   heappushR   (   R   R   t   priorityt   entry(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    c         C   s   t  j |  j  \ } } } | S(   N(   R   t   heappopR   (   R   t   _R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    c         C   s   t  |  j  d k S(   Ni    (   R   R   (   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    (   R   R	   R   R   R   R   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s
   
			t   PriorityQueueWithFunctionc           B   s    e  Z d  Z d   Z d   Z RS(   s
  
    Implements a priority queue with the same push/pop signature of the
    Queue and the Stack classes. This is designed for drop-in replacement for
    those two classes. The caller has to provide a priority function, which
    extracts each item's priority.
    c         C   s   | |  _  t j |   d S(   s#   priorityFunction (item) -> priorityN(   t   priorityFunctionR   R   (   R   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    	c         C   s    t  j |  | |  j |   d S(   sB   Adds an item to the queue with priority from the priority functionN(   R   R   R   (   R   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s    (   R   R	   R   R   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR      s   	c         C   s,   t  |  d | d  t  |  d | d  S(   s9   Returns the Manhattan distance between points xy1 and xy2i    i   (   t   abs(   t   xy1t   xy2(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   manhattanDistance   s    t   Counterc           B   sz   e  Z d  Z d   Z d   Z d   Z d   Z d   Z d   Z d   Z	 d   Z
 d	   Z d
   Z d   Z d   Z RS(   s  
    A counter keeps track of counts for a set of keys.

    The counter class is an extension of the standard python
    dictionary type.  It is specialized to have number values
    (integers or floats), and includes a handful of additional
    functions to ease the task of counting data.  In particular,
    all keys are defaulted to have value 0.  Using a dictionary:

    a = {}
    print a['test']

    would give an error, while the Counter class analogue:

    >>> a = Counter()
    >>> print a['test']
    0

    returns the default 0 value. Note that to reference a key
    that you know is contained in the counter,
    you can still use the dictionary syntax:

    >>> a = Counter()
    >>> a['test'] = 2
    >>> print a['test']
    2

    This is very useful for counting things without initializing their counts,
    see for example:

    >>> a['blah'] += 1
    >>> print a['blah']
    1

    The counter also includes additional functionality useful in implementing
    the classifiers for this assignment.  Two counters can be added,
    subtracted or multiplied together.  See below for details.  They can
    also be normalized and their total count and arg max can be extracted.
    c         C   s    |  j  | d  t j |  |  S(   Ni    (   t
   setdefaultt   dictt   __getitem__(   R   t   idx(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR'      s    c         C   s%   x | D] } |  | c | 7<q Wd S(   s   
        Increments all elements of keys by the same count.

        >>> a = Counter()
        >>> a.incrementAll(['one','two', 'three'], 1)
        >>> a['one']
        1
        >>> a['two']
        1
        N(    (   R   t   keysR   t   key(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   incrementAll   s    c         C   sf   t  |  j    d k r d S|  j   } g  | D] } | d ^ q/ } | j t |   } | | d S(   s9   
        Returns the key with the highest value.
        i    i   N(   R   R)   R   t   itemst   indext   max(   R   t   allt   xt   valuest   maxIndex(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   argMax  s     c         C   s@   |  j    } d   } | j d |  g  | D] } | d ^ q, S(   s'  
        Returns a list of keys sorted by their values.  Keys
        with the highest values will appear first.

        >>> a = Counter()
        >>> a['first'] = -2
        >>> a['second'] = 4
        >>> a['third'] = 1
        >>> a.sortedKeys()
        ['second', 'third', 'first']
        c         S   s   t  | d |  d  S(   Ni   (   t   sign(   R0   t   y(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   <lambda>$  s    t   cmpi    (   R,   t   sort(   R   t   sortedItemst   compareR0   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt
   sortedKeys  s    	c         C   s   t  |  j    S(   s9   
        Returns the sum of counts for all keys.
        (   t   sumR1   (   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt
   totalCount(  s    c         C   sO   t  |  j    } | d k r" d Sx& |  j   D] } |  | | |  | <q/ Wd S(   s   
        Edits the counter such that the total count of all
        keys sums to 1.  The ratio of counts for all keys
        will remain the same. Note that normalizing an empty
        Counter will result in an error.
        i    N(   t   floatR=   R)   (   R   t   totalR*   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt	   normalize.  s
     c         C   s1   t  |  } x |  D] } |  | c | :<q Wd S(   s/   
        Divides all counts by divisor
        N(   R>   (   R   t   divisorR*   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt	   divideAll:  s    c         C   s   t  t j |    S(   s/   
        Returns a copy of the counter
        (   R$   R&   t   copy(   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyRC   B  s    c         C   sq   d } |  } t  |  t  |  k r4 | | } } n  x6 | D]. } | | k rS q; n  | | | | | 7} q; W| S(   s  
        Multiplying two counters gives the dot product of their vectors where
        each unique label is a vector element.

        >>> a = Counter()
        >>> b = Counter()
        >>> a['first'] = -2
        >>> a['second'] = 4
        >>> b['first'] = 3
        >>> b['second'] = 5
        >>> a['third'] = 1.5
        >>> a['fourth'] = 2.5
        >>> a * b
        14
        i    (   R   (   R   R5   R<   R0   R*   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   __mul__H  s    c         C   s1   x* | j    D] \ } } |  | c | 7<q Wd S(   s_  
        Adding another counter to a counter increments the current counter
        by the values stored in the second counter.

        >>> a = Counter()
        >>> b = Counter()
        >>> a['first'] = -2
        >>> a['second'] = 4
        >>> b['first'] = 3
        >>> b['third'] = 1
        >>> a += b
        >>> a['first']
        1
        N(   R,   (   R   R5   R*   t   value(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   __radd__b  s    c         C   s   t    } xA |  D]9 } | | k r; |  | | | | | <q |  | | | <q Wx. | D]& } | |  k rl qT n  | | | | <qT W| S(   sY  
        Adding two counters gives a counter with the union of all keys and
        counts of the second added to counts of the first.

        >>> a = Counter()
        >>> b = Counter()
        >>> a['first'] = -2
        >>> a['second'] = 4
        >>> b['first'] = 3
        >>> b['third'] = 1
        >>> (a + b)['first']
        1
        (   R$   (   R   R5   t   addendR*   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   __add__t  s    	c         C   s   t    } xA |  D]9 } | | k r; |  | | | | | <q |  | | | <q Wx2 | D]* } | |  k rl qT n  d | | | | <qT W| S(   sp  
        Subtracting a counter from another gives a counter with the union of all keys and
        counts of the second subtracted from counts of the first.

        >>> a = Counter()
        >>> b = Counter()
        >>> a['first'] = -2
        >>> a['second'] = 4
        >>> b['first'] = 3
        >>> b['third'] = 1
        >>> (a - b)['first']
        -5
        i(   R$   (   R   R5   RG   R*   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   __sub__  s    	(   R   R	   R   R'   R+   R3   R;   R=   R@   RB   RC   RD   RF   RH   RI   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR$      s   '			
								c          C   s_   t  j   d d }  t  j   d d } t  j   d d } d | | |  f GHt j d  d  S(   Ni   i   i   s/   *** Method not implemented: %s at line %s of %s(   t   inspectt   stackt   syst   exit(   t   fileNamet   linet   method(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   raiseNotDefined  s
    c   	      C   s   t    } t |   t |  k r| |  } t | j    } | d k rI | Sx, | j   D] } | | } | | | | <qV W| S|  } t t |   } | d k r | Sg  | D] } | | ^ q Sd S(   sW   
    normalize a vector or counter by dividing each value by the sum of all values
    i    N(   R$   t   typeR>   R=   R)   R<   (	   t   vectorOrCountert   normalizedCountert   counterR?   R*   RE   t   vectort   st   el(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR@     s    	 
 c   	      C   s   t  |   d k r! t |   }  n  g  t |  D] } t j   ^ q. } | j   g  } d d |  d } } } xV | | k  r | | | k  r | d 7} | j | |  qq | d 7} | |  | 7} qq W| S(   Ni   i    (   R<   R@   t   rangeR   R8   R   (	   t   distributionR1   t   nt   it   randt   samplest	   samplePost   distPost   cdf(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   nSample  s    %


c         C   s   t  |   t k r[ |  j   } g  | D] } | d ^ q% }  g  | D] } | d ^ qB } n  t |   d k r| t |   }  n  t j   } d |  d } } x( | | k r | d 7} | |  | 7} q W| | S(   Ni   i    (   RR   R$   R,   R<   R@   R   (   RZ   R1   R,   R\   t   choiceR?   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   sample  s     
c         C   sK   |  j    } t g  | D] \ } } | ^ q g  | D] \ } } | ^ q2  S(   N(   R,   Rd   (   t   ctrR,   t   kt   v(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   sampleFromCounter  s    c         C   sC   d } x6 t  | |  D]% \ } } | |  k r | | 7} q q W| S(   st   
      Gives the probability of a value under a discrete distribution
      defined by (distributions, values).
    g        (   t   zip(   RE   RZ   R1   R?   t   probt   val(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   getProbability  s
    c         C   s   t  j    } | |  k  S(   N(   R   (   t   pt   r(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   flipCoin  s    c         C   su   t  |   t k s$ t  |   t k r. t |   St j   } d } x. |  D]& \ } } | | 7} | | k rG | SqG Wd S(   sA   Takes either a counter or a list of (prob, key) pairs and samplesg        N(   RR   R&   R$   Rd   R   (   RZ   Rn   t   baseRj   t   element(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   chooseFromDistribution  s    $

 c         C   s6   |  \ } } t  | d  } t  | d  } | | f S(   sC   
    Finds the nearest grid point to a position (discretizes).
    g      ?(   t   int(   t   post   current_rowt   current_colt   grid_rowt   grid_col(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   nearestPoint  s    c         C   s   |  d k r d Sd Sd S(   s4   
    Returns 1 or -1 depending on the sign of x
    i    i   iN(    (   R0   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR4     s    c         C   s`   g  |  D] } g  ^ q } x@ |  D]8 } x/ t  t |   D] } | | j | |  q9 Wq  W| S(   s5   
    Inverts a matrix stored as a list of lists.
    (   RY   R   R   (   t   arrayR\   t   resultt   outert   inner(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   arrayInvert  s
    c         C   s   t  |   t  |  d  } } g  } xU t |  D]G } x> t |  D]0 } |  | | | k rC | j | | f  qC qC Wq0 W| S(   sP   
    Turns a matrix into a list of coordinates matching the specified value
    i    (   R   RY   R   (   t   matrixRE   t   rowst   colst   cellst   rowt   col(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   matrixAsList  s    c   	      C   sO  |  j  d  } | d k rd d j |  j d  d   |  j d  d } } t |  } t | |  Sg  | j   D]$ } t t |   d k rq | ^ qq } g  | D]' } |  t |  k r t | |   ^ q } | g  | j	   D]  } | d |  k r | d ^ q 7} t
 |  d k r | d St
 |  d k r>t d  n  t d |   d S(	   sr   
    Get a method or class from any imported module from its name.
    Usage: lookup(functionName, globals())
    t   .i    is   <type 'module'>i   s   Name conflict for %ss!   %s not found as a method or classN(   R   t   joint   splitt
   __import__t   getattrR1   t   strRR   t   dirR,   R   t	   Exception(	   t   namet	   namespacet   dotst
   moduleNamet   objNamet   modulet   objt   modulest   options(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   lookup'  s    0747  c           C   s   d GHt    d S(   s:   
    Pauses the output stream awaiting user feedback.
    s    <Press enter/return to continue>N(   t	   raw_input(    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   pause9  s    t   TimeoutFunctionExceptionc           B   s   e  Z d  Z RS(   s   Exception to raise on a timeout(   R   R	   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR   K  s   t   TimeoutFunctionc           B   s#   e  Z d    Z d   Z d   Z RS(   c         C   s   | |  _  | |  _ d  S(   N(   t   timeoutt   function(   R   R   R   (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR   Q  s    	c         C   s   t     d  S(   N(   R   (   R   t   signumt   frame(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   handle_timeoutU  s    c         O   s   t  t d  rt t j t j |  j  } t j |  j  z |  j | |   } Wd  t j t j |  Xt j d  nP t j   } |  j | |   } t j   | } | |  j k r |  j d  d   n  | S(   Nt   SIGALRMi    (	   t   hasattrt   signalR   R   t   alarmR   R   t   timeR   (   R   t   argst   keyArgst   oldR{   t	   startTimet   timeElapsed(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   __call__X  s    (   R   R	   R   R   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR   P  s   		t   WritableNullc           B   s   e  Z d    Z RS(   c         C   s   d  S(   N(    (   R   t   string(    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   writes  s    (   R   R	   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyR   r  s   c           C   s)   t  r
 d  St a  t j a t   t _ d  S(   N(   t   _MUTEDt   TrueRL   t   stdoutt   _ORIGINAL_STDOUTR   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt	   mutePrintv  s
    	c           C   s   t  s
 d  St a  t t _ d  S(   N(   R   t   FalseR   RL   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   unmutePrint  s    (    (    (    (    (    (    ()   RL   RJ   R   R   t	   cStringIOR    R
   R   R   R   R#   R&   R$   RQ   R@   Rb   R   Rd   Rh   Rl   Ro   Rr   Ry   R4   R~   R   R   R   R   R   R   R   R   R   R   t   _ORIGINAL_STDERRR   R   R   R   R   (    (    (    sK   C:\MyDocuments\Studies\Berkeley CS188X\05 Projects\03 Reinforcement\util.pyt   <module>   sD   c	
							
	
			
			