



"""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						(		__UpperCamelCase      :			list					, __UpperCamelCase      :			list					, __UpperCamelCase      :			list					, __UpperCamelCase      :			list					, __UpperCamelCase      :			list    ):


						'''simple docstring'''






						snake_case_   : Dict						=			np.array([[1, item, train_mtch[i]] for i, item in enumerate(__UpperCamelCase    )]    )
						snake_case_   : Dict						=			np.array(__UpperCamelCase    )
						snake_case_   : Any						=			np.dot(np.dot(np.linalg.inv(np.dot(x.transpose()					, __UpperCamelCase    )    )					, x.transpose()    )					, __UpperCamelCase    )
						return abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			list					, __UpperCamelCase      :			list					, __UpperCamelCase      :			list    ):


						'''simple docstring'''






						snake_case_   : Union[str, Any]						=			(1, 2, 1)
						snake_case_   : Optional[Any]						=			(1, 1, 0, 7)
						snake_case_   : Tuple						=			SARIMAX(
						    __UpperCamelCase					, exog=__UpperCamelCase					, order=__UpperCamelCase					, seasonal_order=__UpperCamelCase    )
						snake_case_   : List[str]						=			model.fit(disp=__UpperCamelCase					, maxiter=6_0_0					, method="""nm"""    )
						snake_case_   : Union[str, Any]						=			model_fit.predict(1					, len(__UpperCamelCase    )					, exog=[test_match]    )
						return result[0]
def 	__lowerCAmelCase						(		__UpperCamelCase      :			list					, __UpperCamelCase      :			list					, __UpperCamelCase      :			list    ):


						'''simple docstring'''






						snake_case_   : str						=			SVR(kernel="""rbf"""					, C=1					, gamma=0.1					, epsilon=0.1    )
						regressor.fit(__UpperCamelCase					, __UpperCamelCase    )
						snake_case_   : Tuple						=			regressor.predict(__UpperCamelCase    )
						return y_pred[0]
def 	__lowerCAmelCase						(		__UpperCamelCase      :			list    ):


						'''simple docstring'''






						train_user.sort()
						snake_case_   : Optional[int]						=			np.percentile(__UpperCamelCase					, 2_5    )
						snake_case_   : List[str]						=			np.percentile(__UpperCamelCase					, 7_5    )
						snake_case_   : List[str]						=			qa - qa
						snake_case_   : Optional[int]						=			qa - (iqr * 0.1)
						return low_lim
def 	__lowerCAmelCase						(		__UpperCamelCase      :			list					, __UpperCamelCase      :			float    ):


						'''simple docstring'''






						snake_case_   : Any						=			0
						snake_case_   : str						=			0
						for i in list_vote:
												if i > actual_result:
																		snake_case_   : Tuple						=			not_safe + 1
												else:
																		if abs(abs(__UpperCamelCase    ) - abs(__UpperCamelCase    )    ) <= 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       :					Optional[int]      					=					[[1_8231, 0.0, 1], [2_2621, 1.0, 2], [1_5675, 0.0, 3], [2_3583, 1.0, 4]]
					__lowerCAmelCase       :					Any      					=					pd.DataFrame(
					    data_input, columns=['''total_user''', '''total_even''', '''days''']
					)
					__lowerCAmelCase       :					Tuple      					=					Normalizer().fit_transform(data_input_df.values)
					# split data
					__lowerCAmelCase       :					str      					=					normalize_df[:, 2].tolist()
					__lowerCAmelCase       :					Union[str, Any]      					=					normalize_df[:, 0].tolist()
					__lowerCAmelCase       :					Tuple      					=					normalize_df[:, 1].tolist()

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

					# for linear regression & sarimax
					__lowerCAmelCase       :					Any      					=					total_date[: len(total_date) - 1]
					__lowerCAmelCase       :					Optional[Any]      					=					total_user[: len(total_user) - 1]
					__lowerCAmelCase       :					int      					=					total_match[: len(total_match) - 1]

					__lowerCAmelCase       :					List[Any]      					=					total_date[len(total_date) - 1 :]
					__lowerCAmelCase       :					str      					=					total_user[len(total_user) - 1 :]
					__lowerCAmelCase       :					List[str]      					=					total_match[len(total_match) - 1 :]

					# voting system with forecasting
					__lowerCAmelCase       :					Optional[Any]      					=					[
					    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       :					Dict      					=					'''''' if data_safety_checker(res_vote, tst_user) else '''not '''
					print('''Today\'s data is {not_str}safe.''')






"""simple docstring"""





import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_rjieba
@require_tokenizers
class    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__  ,				unittest.TestCase		):





		"""simple docstring"""






		_lowerCamelCase			  =       RoFormerTokenizer
		_lowerCamelCase			  =       RoFormerTokenizerFast
		_lowerCamelCase			  =       True
		_lowerCamelCase			  =       True





		def    UpperCAmelCase__							(					self   ) ->						Any:







								'''simple docstring'''

								super().setUp()





		def    UpperCAmelCase__							(					self							,    **_lowercase   ) ->						str:







								'''simple docstring'''

								return self.tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""							,    **_lowercase   )





		def    UpperCAmelCase__							(					self							,    **_lowercase   ) ->						Union[str, Any]:







								'''simple docstring'''

								return self.rust_tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""							,    **_lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Dict:







								'''simple docstring'''

								snake_case_   : Tuple						=			"""永和服装饰品有限公司,今天天气非常好"""
								snake_case_   : int						=			"""永和 服装 饰品 有限公司 , 今 天 天 气 非常 好"""
								return input_text, output_text





		def    UpperCAmelCase__							(					self   ) ->						str:







								'''simple docstring'''

								snake_case_   : List[str]						=			self.get_tokenizer()
								snake_case_			,		snake_case_   : Optional[Any]						=			self.get_chinese_input_output_texts()
								snake_case_   : List[str]						=			tokenizer.tokenize(_lowercase   )

								self.assertListEqual(_lowercase							,    output_text.split()   )

								snake_case_   : str						=			tokens + [tokenizer.unk_token]
								snake_case_   : Tuple						=			[2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase   )							,    _lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Any:







								'''simple docstring'''

								snake_case_   : int						=			self.get_rust_tokenizer()
								snake_case_			,		snake_case_   : List[Any]						=			self.get_chinese_input_output_texts()
								snake_case_   : Union[str, Any]						=			tokenizer.tokenize(_lowercase   )
								self.assertListEqual(_lowercase							,    output_text.split()   )
								snake_case_   : Optional[int]						=			tokens + [tokenizer.unk_token]
								snake_case_   : Union[str, Any]						=			[2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase   )							,    _lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Tuple:







								'''simple docstring'''

								pass





		def    UpperCAmelCase__							(					self   ) ->						Optional[Any]:







								'''simple docstring'''

								pass





		def    UpperCAmelCase__							(					self   ) ->						Optional[int]:







								'''simple docstring'''

								pass

