
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        _a   (		lowerCamelCase,      lowerCamelCase,      lowerCamelCase,      lowerCamelCase,      lowerCamelCase				):
 lowerCamelCase						:      Any							     = np.array([[1, item, train_mtch[i]] for i, item in enumerate(lowerCamelCase__				)]				)
 lowerCamelCase						:      List[Any]							     = np.array(lowerCamelCase__				)
 lowerCamelCase						:      List[Any]							     = np.dot(np.dot(np.linalg.inv(np.dot(x.transpose(),      lowerCamelCase__				)				),      x.transpose()				),      lowerCamelCase__				)
 return abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2]				)





def        _a   (		lowerCamelCase,      lowerCamelCase,      lowerCamelCase				):
 lowerCamelCase						:      Union[str, Any]							     = (1, 2, 1)
 lowerCamelCase						:      Optional[Any]							     = (1, 1, 0, 7)
 lowerCamelCase						:      str							     = SARIMAX(
     lowerCamelCase__,      exog=lowerCamelCase__,      order=lowerCamelCase__,      seasonal_order=lowerCamelCase__				)
 lowerCamelCase						:      str							     = model.fit(disp=lowerCamelCase__,      maxiter=600,      method="""nm"""				)
 lowerCamelCase						:      Union[str, Any]							     = model_fit.predict(1,      len(lowerCamelCase__				),      exog=[test_match]				)
 return result[0]





def        _a   (		lowerCamelCase,      lowerCamelCase,      lowerCamelCase				):
 lowerCamelCase						:      str							     = SVR(kernel="""rbf""",      C=1,      gamma=0.1,      epsilon=0.1				)
 regressor.fit(lowerCamelCase__,      lowerCamelCase__				)
 lowerCamelCase						:      Dict							     = regressor.predict(lowerCamelCase__				)
 return y_pred[0]





def        _a   (		lowerCamelCase				):
 train_user.sort()
 lowerCamelCase						:      Any							     = np.percentile(lowerCamelCase__,      25				)
 lowerCamelCase						:      Any							     = np.percentile(lowerCamelCase__,      75				)
 lowerCamelCase						:      Tuple							     = qa - qa
 lowerCamelCase						:      Dict							     = qa - (iqr * 0.1)
 return low_lim





def        _a   (		lowerCamelCase,      lowerCamelCase				):
 lowerCamelCase						:      List[Any]							     = 0
 lowerCamelCase						:      int							     = 0
 for i in list_vote:
  if i > actual_result:
   lowerCamelCase						:      Tuple							     = not_safe + 1
  else:
   if abs(abs(lowerCamelCase__				) - abs(lowerCamelCase__				)				) <= 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)
      _lowerCamelCase     =[[1_8_2_3_1, 0.0, 1], [2_2_6_2_1, 1.0, 2], [1_5_6_7_5, 0.0, 3], [2_3_5_8_3, 1.0, 4]]
      _lowerCamelCase     =pd.DataFrame(
          data_input, columns=["""total_user""", """total_even""", """days"""]
      )
      _lowerCamelCase     =Normalizer().fit_transform(data_input_df.values)
      # split data
      _lowerCamelCase     =normalize_df[:, 2].tolist()
      _lowerCamelCase     =normalize_df[:, 0].tolist()
      _lowerCamelCase     =normalize_df[:, 1].tolist()

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

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

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

      # voting system with forecasting
      _lowerCamelCase     =[
          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
      _lowerCamelCase     ="" if data_safety_checker(res_vote, tst_user) else "not "
      print("""Today's data is {not_str}safe.""")








UpperCAmelCase   :    Any     =		[0, 2, 4, 6, 8]
UpperCAmelCase   :    Optional[Any]     =		[1, 3, 5, 7, 9]






def 	__lowerCamelCase						(							lowerCamelCase__		:						int  ,							lowerCamelCase__		:						int  ,							lowerCamelCase__		:						list[int]  ,							lowerCamelCase__		:						int      ):





			'''simple docstring'''




			if remaining_length == 0:
						if digits[0] == 0 or digits[-1] == 0:
									return 0

						for i in range(length // 2 - 1  ,							-1  ,							-1      ):
									remainder += digits[i] + digits[length - i - 1]

									if remainder % 2 == 0:
												return 0

									remainder //= 10

						return 1

			if remaining_length == 1:
						if remainder % 2 == 0:
									return 0

						lowerCamelCase    		=  0
						for digit in range(10      ):
									lowerCamelCase    		=  digit
									result += reversible_numbers(
									    0  ,							(remainder + 2 * digit) // 10  ,							lowerCamelCase__  ,							lowerCamelCase__      )
						return result

			lowerCamelCase    		=  0
			for digita in range(10      ):
						lowerCamelCase    		=  digita

						if (remainder + digita) % 2 == 0:
									lowerCamelCase    		=  ODD_DIGITS
						else:
									lowerCamelCase    		=  EVEN_DIGITS

						for digita in other_parity_digits:
									lowerCamelCase    		=  digita
									result += reversible_numbers(
									    remaining_length - 2  ,							(remainder + digita + digita) // 10  ,							lowerCamelCase__  ,							lowerCamelCase__  ,							)
			return result






def 	__lowerCamelCase						(							lowerCamelCase__		:						int = 9      ):





			'''simple docstring'''




			lowerCamelCase    		=  0
			for length in range(1  ,							max_power + 1      ):
						result += reversible_numbers(lowerCamelCase__  ,							0  ,							[0] * length  ,							lowerCamelCase__      )
			return result


if __name__ == "__main__":
		print(f"""{solution() = }""")

