


from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter
def     __lowerCamelCase						(			UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		float = 1 / sqrt(2						)						):




      """simple docstring"""





      a						:int										=	tau * frequency / samplerate
      a						:Any										=	sin(UpperCAmelCase_						)
      a						:Dict										=	cos(UpperCAmelCase_						)
      a						:Tuple										=	_sin / (2 * q_factor)

      a						:List[str]										=	(1 - _cos) / 2
      a						:Optional[Any]										=	1 - _cos

      a						:Any										=	1 + alpha
      a						:int										=	-2 * _cos
      a						:int										=	1 - alpha

      a						:int										=	IIRFilter(2						)
      filt.set_coefficients([aa, aa, aa]			,  [ba, ba, ba]						)
      return filt
def     __lowerCamelCase						(			UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		float = 1 / sqrt(2						)						):




      """simple docstring"""





      a						:str										=	tau * frequency / samplerate
      a						:str										=	sin(UpperCAmelCase_						)
      a						:int										=	cos(UpperCAmelCase_						)
      a						:Tuple										=	_sin / (2 * q_factor)

      a						:Optional[Any]										=	(1 + _cos) / 2
      a						:str										=	-1 - _cos

      a						:Tuple										=	1 + alpha
      a						:Any										=	-2 * _cos
      a						:Optional[Any]										=	1 - alpha

      a						:str										=	IIRFilter(2						)
      filt.set_coefficients([aa, aa, aa]			,  [ba, ba, ba]						)
      return filt
def     __lowerCamelCase						(			UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		float = 1 / sqrt(2						)						):




      """simple docstring"""





      a						:int										=	tau * frequency / samplerate
      a						:Dict										=	sin(UpperCAmelCase_						)
      a						:Any										=	cos(UpperCAmelCase_						)
      a						:Dict										=	_sin / (2 * q_factor)

      a						:Optional[int]										=	_sin / 2
      a						:List[str]										=	0
      a						:Dict										=	-ba

      a						:Dict										=	1 + alpha
      a						:Dict										=	-2 * _cos
      a						:str										=	1 - alpha

      a						:Optional[Any]										=	IIRFilter(2						)
      filt.set_coefficients([aa, aa, aa]			,  [ba, ba, ba]						)
      return filt
def     __lowerCamelCase						(			UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		float = 1 / sqrt(2						)						):




      """simple docstring"""





      a						:int										=	tau * frequency / samplerate
      a						:Dict										=	sin(UpperCAmelCase_						)
      a						:Tuple										=	cos(UpperCAmelCase_						)
      a						:List[str]										=	_sin / (2 * q_factor)

      a						:int										=	1 - alpha
      a						:Tuple										=	-2 * _cos
      a						:str										=	1 + alpha

      a						:int										=	IIRFilter(2						)
      filt.set_coefficients([ba, ba, ba]			,  [ba, ba, ba]						)
      return filt
def     __lowerCamelCase						(			UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		float			,  UpperCAmelCase_						:		float = 1 / sqrt(2						)			,  ):




      """simple docstring"""





      a						:Tuple										=	tau * frequency / samplerate
      a						:Optional[int]										=	sin(UpperCAmelCase_						)
      a						:Optional[int]										=	cos(UpperCAmelCase_						)
      a						:str										=	_sin / (2 * q_factor)
      a						:int										=	10 ** (gain_db / 40)

      a						:Optional[Any]										=	1 + alpha * big_a
      a						:Optional[int]										=	-2 * _cos
      a						:Tuple										=	1 - alpha * big_a
      a						:Optional[int]										=	1 + alpha / big_a
      a						:Any										=	-2 * _cos
      a						:Optional[int]										=	1 - alpha / big_a

      a						:Dict										=	IIRFilter(2						)
      filt.set_coefficients([aa, aa, aa]			,  [ba, ba, ba]						)
      return filt
def     __lowerCamelCase						(			UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		float			,  UpperCAmelCase_						:		float = 1 / sqrt(2						)			,  ):




      """simple docstring"""





      a						:str										=	tau * frequency / samplerate
      a						:List[str]										=	sin(UpperCAmelCase_						)
      a						:str										=	cos(UpperCAmelCase_						)
      a						:Union[str, Any]										=	_sin / (2 * q_factor)
      a						:Dict										=	10 ** (gain_db / 40)
      a						:Tuple										=	(big_a + 1) - (big_a - 1) * _cos
      a						:Union[str, Any]										=	(big_a + 1) + (big_a - 1) * _cos
      a						:str										=	(big_a - 1) - (big_a + 1) * _cos
      a						:Dict										=	(big_a - 1) + (big_a + 1) * _cos
      a						:List[str]										=	2 * sqrt(UpperCAmelCase_						) * alpha

      a						:Dict										=	big_a * (pmc + aaa)
      a						:Tuple										=	2 * big_a * mpc
      a						:Tuple										=	big_a * (pmc - aaa)
      a						:List[Any]										=	ppmc + aaa
      a						:Tuple										=	-2 * pmpc
      a						:List[Any]										=	ppmc - aaa

      a						:List[Any]										=	IIRFilter(2						)
      filt.set_coefficients([aa, aa, aa]			,  [ba, ba, ba]						)
      return filt






def     __lowerCamelCase						(			UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		float			,  UpperCAmelCase_						:		float = 1 / sqrt(2						)			,  ):




      """simple docstring"""





      a						:List[str]										=	tau * frequency / samplerate
      a						:Union[str, Any]										=	sin(UpperCAmelCase_						)
      a						:int										=	cos(UpperCAmelCase_						)
      a						:Dict										=	_sin / (2 * q_factor)
      a						:str										=	10 ** (gain_db / 40)
      a						:str										=	(big_a + 1) - (big_a - 1) * _cos
      a						:List[str]										=	(big_a + 1) + (big_a - 1) * _cos
      a						:int										=	(big_a - 1) - (big_a + 1) * _cos
      a						:int										=	(big_a - 1) + (big_a + 1) * _cos
      a						:Optional[Any]										=	2 * sqrt(UpperCAmelCase_						) * alpha

      a						:List[str]										=	big_a * (ppmc + aaa)
      a						:Dict										=	-2 * big_a * pmpc
      a						:int										=	big_a * (ppmc - aaa)
      a						:Optional[int]										=	pmc + aaa
      a						:str										=	2 * mpc
      a						:Optional[int]										=	pmc - aaa

      a						:Tuple										=	IIRFilter(2						)
      filt.set_coefficients([aa, aa, aa]			,  [ba, ba, ba]						)
      return filt









import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def     __lowerCamelCase						(			UpperCAmelCase_						:		dict						):




      """simple docstring"""





      return (data["data"], data["target"])
def     __lowerCamelCase						(			UpperCAmelCase_						:		np.ndarray			,  UpperCAmelCase_						:		np.ndarray						):




      """simple docstring"""





      a						:Optional[Any]										=	XGBClassifier()
      classifier.fit(UpperCAmelCase_			,  UpperCAmelCase_						)
      return classifier
def     __lowerCamelCase						(			):




      """simple docstring"""





      a						:List[Any]										=	load_iris()
      a							,    a						:Any										=	data_handling(UpperCAmelCase_						)
      a							,    a							,    a							,    a						:Tuple										=	train_test_split(
          UpperCAmelCase_			,  UpperCAmelCase_			,  test_size=0.25						)

      a						:List[Any]										=	iris['''target_names''']

      # Create an XGBoost Classifier from the training data
      a						:Optional[int]										=	xgboost(UpperCAmelCase_			,  UpperCAmelCase_						)

      # Display the confusion matrix of the classifier with both training and test sets
      ConfusionMatrixDisplay.from_estimator(
          UpperCAmelCase_			,  UpperCAmelCase_			,  UpperCAmelCase_			,  display_labels=UpperCAmelCase_			,  cmap='''Blues'''			,  normalize='''true'''			,  )
      plt.title('''Normalized Confusion Matrix - IRIS Dataset'''						)
      plt.show()


if __name__ == "__main__":
     import doctest

     doctest.testmod(verbose=True)
     main()





