

'''simple docstring'''





from __future__ import annotations

from collections.abc import MutableSequence





class 		__SCREAMING_SNAKE_CASE							:







				def __init__(       self     :		Optional[Any]		,					UpperCAmelCase__     :		int		,					UpperCAmelCase__     :		MutableSequence[float]   ):
										'''simple docstring'''
										if len(UpperCAmelCase__   ) != degree + 1:
																raise ValueError(
																    '''The number of coefficients should be equal to the degree + 1.'''   )

										lowercase :							list[float]    		=list(UpperCAmelCase__   )
										lowercase :							Union[str, Any]    		=degree







				def __add__(       self     :		Any		,					UpperCAmelCase__     :		Polynomial   ):
										'''simple docstring'''

										if self.degree > polynomial_a.degree:
																lowercase :							Optional[int]    		=self.coefficients[:]
																for i in range(polynomial_a.degree + 1   ):
																						coefficients[i] += polynomial_a.coefficients[i]
																return Polynomial(self.degree		,					UpperCAmelCase__   )
										else:
																lowercase :							Dict    		=polynomial_a.coefficients[:]
																for i in range(self.degree + 1   ):
																						coefficients[i] += self.coefficients[i]
																return Polynomial(polynomial_a.degree		,					UpperCAmelCase__   )







				def __sub__(       self     :		List[str]		,					UpperCAmelCase__     :		Polynomial   ):
										'''simple docstring'''
										return self + polynomial_a * Polynomial(0		,					[-1]   )







				def __neg__(       self     :		Any   ):
										'''simple docstring'''
										return Polynomial(self.degree		,					[-c for c in self.coefficients]   )







				def __mul__(       self     :		Optional[int]		,					UpperCAmelCase__     :		Polynomial   ):
										'''simple docstring'''
										lowercase :							list[float]    		=[0] * (self.degree + polynomial_a.degree + 1)
										for i in range(self.degree + 1   ):
																for j in range(polynomial_a.degree + 1   ):
																						coefficients[i + j] += (
																						    self.coefficients[i] * polynomial_a.coefficients[j]
																						)

										return Polynomial(self.degree + polynomial_a.degree		,					UpperCAmelCase__   )







				def  lowerCamelCase_	(       self     :		int		,					UpperCAmelCase__     :		int | float   ):
										'''simple docstring'''
										lowercase :							int | float    		=0
										for i in range(self.degree + 1   ):
																result += self.coefficients[i] * (substitution**i)
										return result







				def __str__(       self     :		str   ):
										'''simple docstring'''
										lowercase :							Union[str, Any]    		=''''''
										for i in range(self.degree		,					-1		,					-1   ):
																if self.coefficients[i] == 0:
																						continue
																elif self.coefficients[i] > 0:
																						if polynomial:
																												polynomial += " + "
																else:
																						polynomial += " - "

																if i == 0:
																						polynomial += str(abs(self.coefficients[i]   )   )
																elif i == 1:
																						polynomial += str(abs(self.coefficients[i]   )   ) + "x"
																else:
																						polynomial += str(abs(self.coefficients[i]   )   ) + "x^" + str(UpperCAmelCase__   )

										return polynomial







				def __repr__(       self     :		Dict   ):
										'''simple docstring'''
										return self.__str__()







				def  lowerCamelCase_	(       self     :		int   ):
										'''simple docstring'''
										lowercase :							list[float]    		=[0] * self.degree
										for i in range(self.degree   ):
																lowercase :							Tuple    		=self.coefficients[i + 1] * (i + 1)
										return Polynomial(self.degree - 1		,					UpperCAmelCase__   )







				def  lowerCamelCase_	(       self     :		int		,					UpperCAmelCase__     :		int | float = 0   ):
										'''simple docstring'''
										lowercase :							list[float]    		=[0] * (self.degree + 2)
										lowercase :							str    		=constant
										for i in range(self.degree + 1   ):
																lowercase :							Union[str, Any]    		=self.coefficients[i] / (i + 1)
										return Polynomial(self.degree + 1		,					UpperCAmelCase__   )







				def __eq__(       self     :		str		,					UpperCAmelCase__     :		object   ):
										'''simple docstring'''
										if not isinstance(UpperCAmelCase__		,					UpperCAmelCase__   ):
																return False

										if self.degree != polynomial_a.degree:
																return False

										for i in range(self.degree + 1   ):
																if self.coefficients[i] != polynomial_a.coefficients[i]:
																						return False

										return True







				def __ne__(       self     :		Tuple		,					UpperCAmelCase__     :		object   ):
										'''simple docstring'''
										return not self.__eq__(UpperCAmelCase__   )







"""simple docstring"""






import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX



def      lowerCAmelCase__			(		__magic_name__			,   __magic_name__			,   __magic_name__			,   __magic_name__			,   __magic_name__      )						->float:
			__lowercase       =       np.array([[1, item, train_mtch[i]] for i, item in enumerate(__magic_name__      )]      )
			__lowercase       =       np.array(__magic_name__      )
			__lowercase       =       np.dot(np.dot(np.linalg.inv(np.dot(x.transpose()			,   __magic_name__      )      )			,   x.transpose()      )			,   __magic_name__      )
			return abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2]      )



def      lowerCAmelCase__			(		__magic_name__			,   __magic_name__			,   __magic_name__      )						->float:
			__lowercase       =       (1, 2, 1)
			__lowercase       =       (1, 1, 0, 7)
			__lowercase       =       SARIMAX(
			    __magic_name__			,   exog=__magic_name__			,   order=__magic_name__			,   seasonal_order=__magic_name__      )
			__lowercase       =       model.fit(disp=__magic_name__			,   maxiter=6_0_0			,   method="nm"      )
			__lowercase       =       model_fit.predict(1			,   len(__magic_name__      )			,   exog=[test_match]      )
			return result[0]



def      lowerCAmelCase__			(		__magic_name__			,   __magic_name__			,   __magic_name__      )						->float:
			__lowercase       =       SVR(kernel="rbf"			,   C=1			,   gamma=0.1			,   epsilon=0.1      )
			regressor.fit(__magic_name__			,   __magic_name__      )
			__lowercase       =       regressor.predict(__magic_name__      )
			return y_pred[0]



def      lowerCAmelCase__			(		__magic_name__      )						->float:
			train_user.sort()
			__lowercase       =       np.percentile(__magic_name__			,   2_5      )
			__lowercase       =       np.percentile(__magic_name__			,   7_5      )
			__lowercase       =       qa - qa
			__lowercase       =       qa - (iqr * 0.1)
			return low_lim



def      lowerCAmelCase__			(		__magic_name__			,   __magic_name__      )						->bool:
			__lowercase       =       0
			__lowercase       =       0
			for i in list_vote:
						if i > actual_result:
									__lowercase       =       not_safe + 1
						else:
									if abs(abs(__magic_name__      ) - abs(__magic_name__      )      ) <= 0.1:
												safe += 1
									else:
												not_safe += 1
			return safe > not_safe


if __name__ == "__main__":
					# data_input_df = pd.read_csv("ex_data.csv", header=None)
					_lowercase							=				[[18_231, 0.0, 1], [22_621, 1.0, 2], [15_675, 0.0, 3], [23_583, 1.0, 4]]
					_lowercase							=				pd.DataFrame(
					    data_input, columns=['''total_user''', '''total_even''', '''days''']
					)
					_lowercase							=				Normalizer().fit_transform(data_input_df.values)
					# split data
					_lowercase							=				normalize_df[:, 2].tolist()
					_lowercase							=				normalize_df[:, 0].tolist()
					_lowercase							=				normalize_df[:, 1].tolist()

					# for svr (input variable = total date and total match)
					_lowercase							=				normalize_df[:, [1, 2]].tolist()
					_lowercase							=				x[: len(x) - 1]
					_lowercase							=				x[len(x) - 1 :]

					# for linear regression & sarimax
					_lowercase							=				total_date[: len(total_date) - 1]
					_lowercase							=				total_user[: len(total_user) - 1]
					_lowercase							=				total_match[: len(total_match) - 1]

					_lowercase							=				total_date[len(total_date) - 1 :]
					_lowercase							=				total_user[len(total_user) - 1 :]
					_lowercase							=				total_match[len(total_match) - 1 :]

					# voting system with forecasting
					_lowercase							=				[
					    linear_regression_prediction(
					        trn_date, trn_user, trn_match, tst_date, tst_match
					    ),
					    sarimax_predictor(trn_user, trn_match, tst_match),
					    support_vector_regressor(x_train, x_test, trn_user),
					]

					# check the safety of today's data
					_lowercase							=				'''''' if data_safety_checker(res_vote, tst_user) else '''not '''
					print('''Today\'s data is {not_str}safe.''')





