from typing import Sequence, Any

import numpy as np


class Index:


    

    
    def __init__(self, vocab: Sequence[Any], start=0):
        
        self.d_vocab={}
		self.k=start
		self.ele=vocab
		
        for i in vocab:
            if i not in d_vocab.keys():
                self.d_vocab[i]=start
                start+=1
                
                           
    def objects_to_indexes(self, object_seq: Sequence[Any]) -> np.ndarray:
        
        arr=[]
        for i in object_seq:
            if i in self.d_vocab.keys():
                arr.append(self.d_vocab[i])
            
            else:
                self.k=self.k-1
				arr.append(arr)
                
        nparray_indexes = np.array(arr)
        return nparray_indexes        
        

    def objects_to_index_matrix(self, object_seq_seq: Sequence[Sequence[Any]]) -> np.ndarray:
        getmax=max(len(obj_seq_seq[0],len(obj_seq_seq[1])))
               
        arr_index_matrix = np.zeroes(len(object_seq_seq),getmax)
        row=0
        for in object_seq_seq:
            col=0
            t=self.objects_to_indexes(i).tolist()
            for j in t:
            arr_index_matrix[r][c] = j
            r+=1
            c+=1
        print (arr_index_matrix)
        return arr_index_matrix     
      
    
    def objects_to_binary_vector(self, object_seq: Sequence[Any]) -> np.ndarray:
        binary_vector = []
        for in object_seq:
            if i in self.d_vocab.keys():
                binary_vector.append(1)
            else
                binary_vector.append(0)
        
        np_binary_vector = np.array(binary_vector)
        return np_binary_vector      
            

#Done **********************************************************************************************************************************************************8
    def objects_to_binary_matrix(self, object_seq_seq: Sequence[Sequence[Any]]) -> np.ndarray:#see code
        binary_matrix = []
        for i in object_seq_seq:
            binary_matrix.append(self.objects_to_binary_vector(i).tolist())
        
        np_binary_matrix=np.array(binary_matrix)
        return binary_matrix
#Done******************************
        
            
    def indexes_to_objects(self, index_vector: np.ndarray) -> Sequence[Any]:
        object_sequence = []
               
        for i in index_vector:
            if i in self.d_vocab.values():
                for obj,index in self.d_vocab_items():
                    if index==i:
                        return object_sequence.append(obj)
                                        
        return object_sequence
                    
        

    def index_matrix_to_objects(
            self, index_matrix: np.ndarray) -> Sequence[Sequence[Any]]:
        object_matrix = []
        for i in index_matrix:
            object_matrix.append(self.indexes_to_objects(i))
        
        return object_matrix
        
        

    def binary_vector_to_objects(self, vector: np.ndarray) -> Sequence[Any]:
        object_sequence=[]
        index=0
        for i in vector:
            if (i!=0):
                object_sequence.append(self.ele[index])
            count+=1
        
        return object_sequence                                      
        
    def binary_matrix_to_objects(
            self, binary_matrix: np.ndarray) -> Sequence[Sequence[Any]]:
        """
        Returns a sequence of sequences of objects identified by the nonzero
        indices in the input matrix.

        If, for any of the indexes, there is not an associated object, that
        index is skipped in the output.

        :param binary_matrix: A 2-dimensional binary array
        :return: A sequence of sequences of objects, one for each nonzero index.
        """
        
        object_matrix=[]
        for i in binary_matrix:
            object_matrix.append(self.binary_matrix_to_objects(i))
        
         return object_matrix 
        
        
        
        
        
        
        
        
        
