cfaqpec

import math
import time

class QuantizedPoint:
    def __init__(self, name, energy, space):
        self.name = name
        self.energy = energy
        self.space = space

def calculate_distance(point1, point2):
    return math.sqrt((point1.energy - point2.energy) ** 2 + (point1.space - point2.space) ** 2)

def find_associations(points, distance_threshold):
    associations = []

    for i, point1 in enumerate(points):
        for point2 in points[i + 1:]:
            distance = calculate_distance(point1, point2)
            if distance <= distance_threshold:
                associations.append((point1, point2))

    return associations

def evaluate_energy_equation(equation, m, c, r=1, i=1, l=1):
    if equation == "E=mci²":
        return m * c * i ** 2
    elif equation == "E=(-1)(mci)²":
        return -1 * (m * c * i) ** 2
    elif equation == "E=mc²":
        return m * c ** 2
    else:
        return None

class CrimeDataGatherer:
    def __init__(self):
        self.crime_data = []
        self.frequency = "2.5GHz"  # Initial frequency setting

    def gather_data(self):
        print("Gathering crime-related data...")
        self.generate_frequency_bursts()
        time.sleep(2)  # Simulate data gathering process
        self.crime_data = [
            {"name": "John Doe", "location": "Street A, City X", "description": "Theft"},
            {"name": "Jane Smith", "location": "Street B, City Y", "description": "Assault"},
            {"name": "Alice Johnson", "location": "Street C, City Z", "description": "Vandalism"}
        ]
        print("Data gathering complete.")

    def process_data(self):
        print("Processing gathered crime data...")
        time.sleep(1)  # Simulate data processing
        print("Crime data processing complete.")

    def generate_frequency_bursts(self):
        print("Generating frequency bursts while gathering data...")
        for frequency in range(2500, 4411, 100):
            print(f"Frequency burst: {frequency}MHz")
            self.frequency = f"{frequency / 1000}GHz"
            self.gather_data()
            time.sleep(0.5)

class CrimeDataAnalyzer:
    def __init__(self):
        self.data_gatherer = CrimeDataGatherer()

    def search_crime_data(self):
        self.data_gatherer.process_data()
        print("Crime data search functionality:")
        for crime in self.data_gatherer.crime_data:
            print(f"- Name: {crime['name']}, Location: {crime['location']}, Description: {crime['description']}")

def calculate_nested_exponential_limit(iterations):
    nested_pi = math.pi
    for _ in range(iterations):
        nested_pi = math.pow(nested_pi, nested_pi)
    return math.pow(nested_pi, 1.0 / 3)

def main():
    # Quantized points
    points = [
        QuantizedPoint("Point1", 100.0, 50.0),
        QuantizedPoint("Point2", 150.0, 30.0),
        QuantizedPoint("Point3", 90.0, 60.0),
        QuantizedPoint("Point4", 120.0, 40.0)
    ]

    distance_threshold = 20.0
    associations = find_associations(points, distance_threshold)

    print("Associations within a distance threshold of", distance_threshold, ":")
    for point1, point2 in associations:
        print(point1.name, "-", point2.name)

    # Nested exponential limit calculation
    nested_iterations = 100000
    pi_nested_limit_value = calculate_nested_exponential_limit(nested_iterations)
    print("Nested Exponential Limit Value:", pi_nested_limit_value)

    # Evaluate equations
    m = 2
    c = 3
    r = 4
    i = 5
    l = 6

    equations = [
        "E=mci²",
        "(-)E=mci²",
        "E≠mci²",
        "E=(-1)(mci)²",
        "E≠imc",
        "E=(-1)((λ^i)mc)²",
        "E≠(imc)²",
        "E=(-1)imc²",
        "E≠imc²",
        "E=(-1)((λ^i)(mc))²",
        "E≠((i)(mc))²"
    ]

    for equation in equations:
        result = evaluate_energy_equation(equation, m, c, r, i, l)
        print(f"{equation}: {result}")

if __name__ == "__main__":
    main()