from __future__ import annotations


class 			lowerCamelCase_  :






    '''simple docstring'''






    def __init__(			self				,				__lowercase) ->			Tuple:
        __UpperCamelCase  :List[Any]    						=	TypeError(
            '''Matrices must be formed from a list of zero or more lists containing at '''
            '''least one and the same number of values, each of which must be of type '''
            '''int or float.''')
        if len(A__) != 0:
            __UpperCamelCase  :Optional[Any]    						=	len(rows[0])
            if cols == 0:
                raise error
            for row in rows:
                if len(A__) != cols:
                    raise error
                for value in row:
                    if not isinstance(A__				,				(int, float)):
                        raise error
            __UpperCamelCase  :List[Any]    						=	rows
        else:
            __UpperCamelCase  :Union[str, Any]    						=	[]







    def     UpperCamelCase__     (			self) ->			List[Any]:
        return [[row[i] for row in self.rows] for i in range(len(self.rows[0]))]







    @property
    def     UpperCamelCase__     (			self) ->			Optional[Any]:
        return len(self.rows)







    @property
    def     UpperCamelCase__     (			self) ->			Optional[int]:
        return len(self.rows[0])







    @property
    def     UpperCamelCase__     (			self) ->			str:
        return (self.num_rows, self.num_columns)







    @property
    def     UpperCamelCase__     (			self) ->			List[Any]:
        return self.order[0] == self.order[1]







    def     UpperCamelCase__     (			self) ->			Tuple:
        __UpperCamelCase  :Any    						=	[
            [0 if column_num != row_num else 1 for column_num in range(self.num_rows)]
            for row_num in range(self.num_rows)
        ]
        return Matrix(A__)







    def     UpperCamelCase__     (			self) ->			Tuple:
        if not self.is_square:
            return 0
        if self.order == (0, 0):
            return 1
        if self.order == (1, 1):
            return int(self.rows[0][0])
        if self.order == (2, 2):
            return int(
                (self.rows[0][0] * self.rows[1][1])
                - (self.rows[0][1] * self.rows[1][0]))
        else:
            return sum(
                self.rows[0][column] * self.cofactors().rows[0][column]
                for column in range(self.num_columns))







    def     UpperCamelCase__     (			self) ->			Any:
        return bool(self.determinant())







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase) ->			Optional[Any]:
        __UpperCamelCase  :str    						=	[
            [
                self.rows[other_row][other_column]
                for other_column in range(self.num_columns)
                if other_column != column
            ]
            for other_row in range(self.num_rows)
            if other_row != row
        ]
        return Matrix(A__).determinant()







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase) ->			List[str]:
        if (row + column) % 2 == 0:
            return self.get_minor(A__				,				A__)
        return -1 * self.get_minor(A__				,				A__)







    def     UpperCamelCase__     (			self) ->			Dict:
        return Matrix(
            [
                [self.get_minor(A__				,				A__) for column in range(self.num_columns)]
                for row in range(self.num_rows)
            ])







    def     UpperCamelCase__     (			self) ->			Union[str, Any]:
        return Matrix(
            [
                [
                    self.minors().rows[row][column]
                    if (row + column) % 2 == 0
                    else self.minors().rows[row][column] * -1
                    for column in range(self.minors().num_columns)
                ]
                for row in range(self.minors().num_rows)
            ])







    def     UpperCamelCase__     (			self) ->			int:
        __UpperCamelCase  :Tuple    						=	[
            [self.cofactors().rows[column][row] for column in range(self.num_columns)]
            for row in range(self.num_rows)
        ]
        return Matrix(A__)







    def     UpperCamelCase__     (			self) ->			Optional[Any]:
        __UpperCamelCase  :Optional[int]    						=	self.determinant()
        if not determinant:
            raise TypeError('''Only matrices with a non-zero determinant have an inverse''')
        return self.adjugate() * (1 / determinant)







    def __repr__(			self) ->			Tuple:
        return str(self.rows)







    def __str__(			self) ->			Optional[int]:
        if self.num_rows == 0:
            return "[]"
        if self.num_rows == 1:
            return "[[" + ". ".join(str(self.rows[0])) + "]]"
        return (
            "["
            + "\n ".join(
                [
                    '''[''' + '''. '''.join([str(A__) for value in row]) + '''.]'''
                    for row in self.rows
                ])
            + "]"
        )







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase = None) ->			Tuple:
        __UpperCamelCase  :List[Any]    						=	TypeError('''Row must be a list containing all ints and/or floats''')
        if not isinstance(A__				,				A__):
            raise type_error
        for value in row:
            if not isinstance(A__				,				(int, float)):
                raise type_error
        if len(A__) != self.num_columns:
            raise ValueError(
                '''Row must be equal in length to the other rows in the matrix''')
        if position is None:
            self.rows.append(A__)
        else:
            __UpperCamelCase  :Optional[int]    						=	self.rows[0:position] + [row] + self.rows[position:]







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase = None) ->			Dict:
        __UpperCamelCase  :Any    						=	TypeError(
            '''Column must be a list containing all ints and/or floats''')
        if not isinstance(A__				,				A__):
            raise type_error
        for value in column:
            if not isinstance(A__				,				(int, float)):
                raise type_error
        if len(A__) != self.num_rows:
            raise ValueError(
                '''Column must be equal in length to the other columns in the matrix''')
        if position is None:
            __UpperCamelCase  :int    						=	[self.rows[i] + [column[i]] for i in range(self.num_rows)]
        else:
            __UpperCamelCase  :Dict    						=	[
                self.rows[i][0:position] + [column[i]] + self.rows[i][position:]
                for i in range(self.num_rows)
            ]







    def __eq__(			self				,				__lowercase) ->			Optional[int]:
        if not isinstance(A__				,				A__):
            return NotImplemented
        return self.rows == other.rows







    def __ne__(			self				,				__lowercase) ->			List[Any]:
        return not self == other







    def __neg__(			self) ->			Dict:
        return self * -1







    def __add__(			self				,				__lowercase) ->			str:
        if self.order != other.order:
            raise ValueError('''Addition requires matrices of the same order''')
        return Matrix(
            [
                [self.rows[i][j] + other.rows[i][j] for j in range(self.num_columns)]
                for i in range(self.num_rows)
            ])







    def __sub__(			self				,				__lowercase) ->			Tuple:
        if self.order != other.order:
            raise ValueError('''Subtraction requires matrices of the same order''')
        return Matrix(
            [
                [self.rows[i][j] - other.rows[i][j] for j in range(self.num_columns)]
                for i in range(self.num_rows)
            ])







    def __mul__(			self				,				__lowercase) ->			str:
        if isinstance(A__				,				(int, float)):
            return Matrix(
                [[int(element * other) for element in row] for row in self.rows])
        elif isinstance(A__				,				A__):
            if self.num_columns != other.num_rows:
                raise ValueError(
                    '''The number of columns in the first matrix must '''
                    '''be equal to the number of rows in the second''')
            return Matrix(
                [
                    [Matrix.dot_product(A__				,				A__) for column in other.columns()]
                    for row in self.rows
                ])
        else:
            raise TypeError(
                '''A Matrix can only be multiplied by an int, float, or another matrix''')







    def __pow__(			self				,				__lowercase) ->			List[str]:
        if not isinstance(A__				,				A__):
            raise TypeError('''A Matrix can only be raised to the power of an int''')
        if not self.is_square:
            raise ValueError('''Only square matrices can be raised to a power''')
        if other == 0:
            return self.identity()
        if other < 0:
            if self.is_invertable():
                return self.inverse() ** (-other)
            raise ValueError(
                '''Only invertable matrices can be raised to a negative power''')
        __UpperCamelCase  :Union[str, Any]    						=	self
        for _ in range(other - 1):
            result *= self
        return result







    @classmethod
    def     UpperCamelCase__     (			cls				,				__lowercase				,				__lowercase) ->			Optional[int]:
        return sum(row[i] * column[i] for i in range(len(A__)))


if __name__ == "__main__":
  import doctest

  doctest.testmod()






from collections import Counter

import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

__lowercase											=      datasets.load_iris()

__lowercase											=      np.array(data['''data'''])
__lowercase											=      np.array(data['''target'''])
__lowercase											=      data['''target_names''']

__lowercase				, __lowercase				, __lowercase				, __lowercase											=      train_test_split(X, y)



def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    return np.linalg.norm(np.array(SCREAMING_SNAKE_CASE			) - np.array(SCREAMING_SNAKE_CASE			)			)



def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE=5			):
    '''simple docstring'''







    __UpperCamelCase  :Optional[int]    						=	zip(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			)
    # List of distances of all points from the point to be classified
    __UpperCamelCase  :List[str]    						=	[]
    for data_point in data:
        __UpperCamelCase  :Optional[int]    						=	euclidean_distance(data_point[0]						,    SCREAMING_SNAKE_CASE			)
        distances.append((distance, data_point[1])			)
    # Choosing 'k' points with the least distances.
    __UpperCamelCase  :Any    						=	[i[1] for i in sorted(SCREAMING_SNAKE_CASE			)[:k]]
    # Most commonly occurring class among them
    # is the class into which the point is classified
    __UpperCamelCase  :Union[str, Any]    						=	Counter(SCREAMING_SNAKE_CASE			).most_common(1			)[0][0]
    return classes[result]


if __name__ == "__main__":
    print(classifier(X_train, y_train, classes, [4.4, 3.1, 1.3, 1.4]))





