Module Expr Str Import alias identifier ImportFrom alias Import alias FunctionDef arguments args NameParam NameParam NameParam NameParam defaults NameLoad ListLoad Num body Expr Str Assign NameStore Call NameLoad NameLoad Assign NameStore BoolOpOr NameLoad Call NameLoad AttributeLoad AttributeLoad NameLoad attr attr Assign NameStore ListComp NameLoad comprehension NameStore NameLoad CompareNotIn NameLoad NameLoad For NameStore NameLoad body Assign NameStore SubscriptLoad AttributeLoad NameLoad attr ExtSlice Slice Index NameLoad Assign NameStore SubscriptLoad AttributeLoad NameLoad attr ExtSlice Slice Index NameLoad Assign NameStore SubscriptLoad NameLoad Index UnaryOpUSub NameLoad Assign NameStore Call AttributeLoad NameLoad attr If Call NameLoad NameLoad body Assign NameStore BinOpFloorDiv Call NameLoad NameLoad NameLoad Assign NameStore SubscriptLoad ListComp SubscriptLoad NameLoad Index SubscriptLoad NameLoad Index BinOpSub BinOpMult NameLoad NameLoad Num comprehension NameStore Call NameLoad NameLoad Slice Num Assign SubscriptStore AttributeLoad NameLoad attr ExtSlice Slice Index NameLoad Call AttributeLoad NameLoad attr NameLoad NameLoad Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index NameLoad Assign NameStore Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad Expr Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad NameLoad attr Assign AttributeStore NameLoad attr NameLoad Assign SubscriptStore AttributeLoad NameLoad attr Index NameLoad NameLoad If CompareEq Call NameLoad NameLoad AttributeLoad AttributeLoad NameLoad attr attr body Assign AttributeStore NameLoad attr Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Return NameLoad decorator_list
N/A N/A  Collection of data discretization algorithms. N/A numpy N util as_list N/A data maximum_entropy_discretize N/A N/A indata includevars excludevars numbins N/A None N/A 3 N/A N/A Performs a maximum-entropy discretization of data in-place.
    
    Requirements for this implementation:

        1. Try to make all bins equal sized (maximize the entropy)
        2. If datum x==y in the original dataset, then disc(x)==disc(y) 
           For example, all datapoints with value 3.245 discretize to 1
           even if it violates requirement 1.
        3. Number of bins reflects only the non-missing data.
     
     Example:

         input:  [3,7,4,4,4,5]
         output: [0,1,0,0,0,1]
        
         Note that all 4s discretize to 0, which makes bin sizes unequal. 

     Example: 

         input:  [1,2,3,4,2,1,2,3,1,x,x,x]
         output: [0,1,2,2,1,0,1,2,0,0,0,0]

         Note that the missing data ('x') gets put in the bin with 0.0.

     N/A includevars N/A as_list includevars N/A includevars N/A includevars N/A range N/A N/A indata variables size N/A includevars N/A v N/A v includevars N/A v excludevars N/A v includevars N/A N/A vdata N/A N/A indata observations N/A N/A N/A v N/A vmiss N/A N/A indata missing N/A N/A N/A v N/A vdata_nm N/A vdata N/A N/A vmiss N/A argsorted N/A N/A vdata_nm argsort N/A N/A len vdata_nm N/A N/A binsize N/A N/A len vdata_nm numbins N/A binedges N/A N/A N/A vdata_nm N/A N/A argsorted N/A N/A N/A binsize b 1 N/A b N/A range numbins N/A 1 N/A N/A N/A indata observations N/A N/A N/A v N/A N/A N searchsorted binedges vdata N/A oldvar N/A N/A indata variables N/A v N/A newvar N/A N/A data DiscreteVariable N/A oldvar name numbins N/A N/A N/A N/A newvar __dict__ update N/A oldvar __dict__ N/A N/A newvar arity numbins N/A N/A N/A indata variables N/A v newvar N/A N/A N/A len includevars N/A N/A indata variables size N/A N/A N/A indata observations N/A N/A N/A indata observations astype int N/A indata N/A