# MIT License

# Copyright (c) 2025 Leandro Santiago de Araújo

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.

# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# SOFTWARE.

from pandas import read_csv
from torchwnn.datasets.dataset import Dataset

class LetterRecognition(Dataset):
    name = "letter-recognition"
    id = 59
    categorical_features = []
    numeric_features = ['x-box', 'y-box', 'width', 'high', 'onpix', 'x-bar', 'y-bar', 'x2bar', 'y2bar', 'xybar', 'x2ybr', 'xy2br', 'x-ege', 'xegvy', 'y-ege', 'yegvx']

    def __init__(self, path = None):
        if not path:
            # Loading dataset from uci repo
            self.load_uci_repo()           
        else: 
            names = ["class"] + self.numeric_features  
            self.target_col = "class"
            data = read_csv(path, names=names)
            self.features = data[self.numeric_features]
            self.targets = data[[self.target_col]]  
        
        self.gen_class_ids()
            
    
           
            