
'''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    UpperCAmelCase_						(__a :       list					,      __a :       list					,      __a :       list					,      __a :       list					,      __a :       list					):






   """simple docstring"""

   _a							:      List[Any]     =  np.array([[1, item, train_mtch[i]] for i, item in enumerate(UpperCamelCase__					)]					)
   _a							:      Union[str, Any]     =  np.array(UpperCamelCase__					)
   _a							:      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    UpperCAmelCase_						(__a :       list					,      __a :       list					,      __a :       list					):






   """simple docstring"""

   _a							:      Union[str, Any]     =  (1, 2, 1)
   _a							:      Union[str, Any]     =  (1, 1, 0, 7)
   _a							:      List[str]     =  SARIMAX(
       UpperCamelCase__					,      exog=UpperCamelCase__					,      order=UpperCamelCase__					,      seasonal_order=UpperCamelCase__					)
   _a							:      int     =  model.fit(disp=UpperCamelCase__					,      maxiter=6_0_0					,      method='nm'					)
   _a							:      List[str]     =  model_fit.predict(1					,      len(UpperCamelCase__					)					,      exog=[test_match]					)
   return result[0]





def    UpperCAmelCase_						(__a :       list					,      __a :       list					,      __a :       list					):






   """simple docstring"""

   _a							:      Dict     =  SVR(kernel='rbf'					,      C=1					,      gamma=0.1					,      epsilon=0.1					)
   regressor.fit(UpperCamelCase__					,      UpperCamelCase__					)
   _a							:      List[str]     =  regressor.predict(UpperCamelCase__					)
   return y_pred[0]





def    UpperCAmelCase_						(__a :       list					):






   """simple docstring"""

   train_user.sort()
   _a							:      Optional[int]     =  np.percentile(UpperCamelCase__					,      2_5					)
   _a							:      Optional[Any]     =  np.percentile(UpperCamelCase__					,      7_5					)
   _a							:      str     =  qa - qa
   _a							:      Tuple     =  qa - (iqr * 0.1)
   return low_lim





def    UpperCAmelCase_						(__a :       list					,      __a :       float					):






   """simple docstring"""

   _a							:      Tuple     =  0
   _a							:      Optional[Any]     =  0
   for i in list_vote:
      if i > actual_result:
         _a							:      Dict     =  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   =       [[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.""")




'''simple docstring'''


import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")





def    lowerCAmelCase       (		UpperCamelCase__					: Dict							):


	"""simple docstring"""
	__UpperCAmelCase      					=      test_file.split(os.path.sep							)
	if components[0:2] != ["tests", "models"]:
		raise ValueError(
		    '''`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '''
		    f"""{test_file} instead."""							)
	__UpperCAmelCase      					=      components[-1]
	if not test_fn.endswith('''py'''							):
		raise ValueError(f"""`test_file` should be a python file. Got {test_fn} instead."""							)
	if not test_fn.startswith('''test_modeling_'''							):
		raise ValueError(
		    f"""`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead."""							)

	__UpperCAmelCase      					=      components[:-1] + [test_fn.replace('''.py'''     ,       ''''''							)]
	__UpperCAmelCase      					=      '''.'''.join(UpperCamelCase__							)

	return test_module_path





def    lowerCAmelCase       (		UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_module_path(UpperCamelCase__							)
	__UpperCAmelCase      					=      importlib.import_module(UpperCamelCase__							)

	return test_module





def    lowerCAmelCase       (		UpperCamelCase__					: Tuple							):


	"""simple docstring"""
	__UpperCAmelCase      					=      []
	__UpperCAmelCase      					=      get_test_module(UpperCamelCase__							)
	for attr in dir(UpperCamelCase__							):
		if attr.endswith('''ModelTester'''							):
			tester_classes.append(getattr(UpperCamelCase__     ,       UpperCamelCase__							)							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: List[Any]							):


	"""simple docstring"""
	__UpperCAmelCase      					=      []
	__UpperCAmelCase      					=      get_test_module(UpperCamelCase__							)
	for attr in dir(UpperCamelCase__							):
		__UpperCAmelCase      					=      getattr(UpperCamelCase__     ,       UpperCamelCase__							)
		# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
		# `all_model_classes` is not empty (which also excludes other special classes).
		__UpperCAmelCase      					=      getattr(UpperCamelCase__     ,       '''all_model_classes'''     ,       []							)
		if len(UpperCamelCase__							) > 0:
			test_classes.append(UpperCamelCase__							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: str							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      set()
	for test_class in test_classes:
		model_classes.update(test_class.all_model_classes							)

	# sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: Any							):


	"""simple docstring"""
	__UpperCAmelCase      					=      test_class()
	if hasattr(UpperCamelCase__     ,       '''setUp'''							):
		test.setUp()

	__UpperCAmelCase      					=      None
	if hasattr(UpperCamelCase__     ,       '''model_tester'''							):
		# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
		if test.model_tester is not None:
			__UpperCAmelCase      					=      test.model_tester.__class__

	return model_tester





def    lowerCAmelCase       (		UpperCamelCase__					: Dict     ,       UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes(UpperCamelCase__							)

	__UpperCAmelCase      					=      []
	for test_class in test_classes:
		if model_class in test_class.all_model_classes:
			target_test_classes.append(UpperCamelCase__							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: Tuple     ,       UpperCamelCase__					: Any							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes_for_model(UpperCamelCase__     ,       UpperCamelCase__							)

	__UpperCAmelCase      					=      []
	for test_class in test_classes:
		__UpperCAmelCase      					=      get_model_tester_from_test_class(UpperCamelCase__							)
		if tester_class is not None:
			tester_classes.append(UpperCamelCase__							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      {test_class: get_model_tester_from_test_class(UpperCamelCase__							) for test_class in test_classes}
	return test_tester_mapping





def    lowerCAmelCase       (		UpperCamelCase__					: str							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_model_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      {
	    model_class: get_test_classes_for_model(UpperCamelCase__     ,       UpperCamelCase__							) for model_class in model_classes
	}
	return model_test_mapping





def    lowerCAmelCase       (		UpperCamelCase__					: Optional[int]							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_model_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      {
	    model_class: get_tester_classes_for_model(UpperCamelCase__     ,       UpperCamelCase__							) for model_class in model_classes
	}
	return model_to_tester_mapping





def    lowerCAmelCase       (		UpperCamelCase__					: Tuple							):


	"""simple docstring"""
	if isinstance(UpperCamelCase__     ,       UpperCamelCase__							):
		return o
	elif isinstance(UpperCamelCase__     ,       UpperCamelCase__							):
		return o.__name__
	elif isinstance(UpperCamelCase__     ,       (list, tuple)							):
		return [to_json(UpperCamelCase__							) for x in o]
	elif isinstance(UpperCamelCase__     ,       UpperCamelCase__							):
		return {to_json(UpperCamelCase__							): to_json(UpperCamelCase__							) for k, v in o.items()}
	else:
		return o
