

import matplotlib.pyplot as plt
import numpy as np







def  UpperCAmelCase_   (_lowerCAmelCase :		List[str]     ,			_lowerCAmelCase :		Optional[int]     ,			_lowerCAmelCase :		List[str]		):
			__UpperCamelCase    :    List[str]								=      len(__lowerCamelCase		)  # Number of training samples
			__UpperCamelCase    :    Optional[Any]								=      np.eye(__lowerCamelCase		)  # Initialize weights as identity matrix
			for j in range(__lowerCamelCase		):
						__UpperCamelCase    :    Union[str, Any]								=      point - x_train[j]
						__UpperCamelCase    :    Dict								=      np.exp(diff @ diff.T / (-2.0 * tau**2)		)

			return weights







def  UpperCAmelCase_   (_lowerCAmelCase :		List[Any]     ,			_lowerCAmelCase :		Any     ,			_lowerCAmelCase :		List[str]     ,			_lowerCAmelCase :		Dict		):
			__UpperCamelCase    :    Dict								=      weight_matrix(__lowerCamelCase     ,			__lowerCamelCase     ,			__lowerCamelCase		)
			__UpperCamelCase    :    Tuple								=      np.linalg.inv(x_train.T @ weight_mat @ x_train		) @ (
			    x_train.T @ weight_mat @ y_train.T
			)

			return weight







def  UpperCAmelCase_   (_lowerCAmelCase :		Dict     ,			_lowerCAmelCase :		Tuple     ,			_lowerCAmelCase :		Any		):
			__UpperCamelCase    :    Union[str, Any]								=      np.zeros(len(__lowerCamelCase		)		)  # Initialize array of predictions
			for i, item in enumerate(__lowerCamelCase		):
						__UpperCamelCase    :    List[Any]								=      item @ local_weight(__lowerCamelCase     ,			__lowerCamelCase     ,			__lowerCamelCase     ,			__lowerCamelCase		)

			return y_pred







def  UpperCAmelCase_   (_lowerCAmelCase :		List[str]     ,			_lowerCAmelCase :		Optional[Any]     ,			_lowerCAmelCase :		Dict		):
			import seaborn as sns

			__UpperCamelCase    :    Union[str, Any]								=      sns.load_dataset(__lowerCamelCase		)
			__UpperCamelCase    :    List[str]								=      np.array(data[x_name]		)
			__UpperCamelCase    :    Dict								=      np.array(data[y_name]		)

			__UpperCamelCase    :    str								=      np.ones(len(__lowerCamelCase		)		)

			# pairing elements of one and x_data
			__UpperCamelCase    :    List[str]								=      np.column_stack((one, x_data)		)

			return x_train, x_data, y_data







def  UpperCAmelCase_   (_lowerCAmelCase :		Tuple     ,			_lowerCAmelCase :		List[str]     ,			_lowerCAmelCase :		Optional[Any]     ,			_lowerCAmelCase :		Dict     ,			_lowerCAmelCase :		List[Any]     ,			_lowerCAmelCase :		Tuple     ,			):
			__UpperCamelCase    :    Optional[int]								=      np.sort(__lowerCamelCase     ,			axis=0		)
			plt.scatter(__lowerCamelCase     ,			__lowerCamelCase     ,			color="blue"		)
			plt.plot(
			    x_train_sorted[:, 1]     ,			preds[x_train[:, 1].argsort(0		)]     ,			color="yellow"     ,			linewidth=5     ,			)
			plt.title("Local Weighted Regression"		)
			plt.xlabel(__lowerCamelCase		)
			plt.ylabel(__lowerCamelCase		)
			plt.show()


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					# Demo with a dataset from the seaborn module
					lowercase     :       str        =       load_data("tips", "total_bill", "tip")
					lowercase     :       Union[str, Any]        =       local_weight_regression(training_data_x, tip, 5)
					plot_preds(training_data_x, predictions, total_bill, tip, "total_bill", "tip")


from .balanced_parentheses import balanced_parentheses
from .stack import Stack







def  UpperCAmelCase_   (_lowerCAmelCase :		str		):
			return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(_lowerCAmelCase     ,			-1		)







def  UpperCAmelCase_   (_lowerCAmelCase :		str		):
			if not balanced_parentheses(_lowerCAmelCase		):
						raise ValueError("Mismatched parentheses"		)
			__UpperCamelCase    :    Stack[str]								=      Stack()
			__UpperCamelCase    :    int								=      []
			for char in expression_str:
						if char.isalpha() or char.isdigit():
									postfix.append(_lowerCAmelCase		)
						elif char == "(":
									stack.push(_lowerCAmelCase		)
						elif char == ")":
									while not stack.is_empty() and stack.peek() != "(":
												postfix.append(stack.pop()		)
									stack.pop()
						else:
									while not stack.is_empty() and precedence(_lowerCAmelCase		) <= precedence(stack.peek()		):
												postfix.append(stack.pop()		)
									stack.push(_lowerCAmelCase		)
			while not stack.is_empty():
						postfix.append(stack.pop()		)
			return " ".join(_lowerCAmelCase		)


if __name__ == "__main__":
					from doctest import testmod

					testmod()
					lowercase     :       int        =       "a+b*(c^d-e)^(f+g*h)-i"

					print("Infix to Postfix Notation demonstration:\n")
					print("Infix notation: " + expression)
					print("Postfix notation: " + infix_to_postfix(expression))