Not-pymc

import time
import sys
import numpy as np
import matplotlib.pyplot as plt

class FakePyMCModel:
    def __init__(self, name="FakeModel"):
        self.name = name
        print(f"FakePyMC: Model '{self.name}' initialized.")

    def Normal(self, name, mu, sigma):
        print(f"FakePyMC: Creating Normal distribution '{name}' with mu={mu} and sigma={sigma}.")

    def run(self, draws=100, chains=4):
        print("FakePyMC: Auto-assigning NUTS sampler...")
        time.sleep(1)
        print("FakePyMC: Starting sampling...")
        self._simulate_sampling(draws, chains)
        self._simulate_trace_plot()
        self._print_summary()

    def _simulate_sampling(self, draws, chains):
        for chain in range(chains):
            print(f"Chain {chain+1}:")
            for i in range(draws):
                time.sleep(0.02)
                eta = np.random.uniform(0.1, 0.5)
                sys.stdout.write(f"\rSampling ({i+1}/{draws}) | ETA: {eta:.2f} s ")
                sys.stdout.flush()
            print("\n")
        print("FakePyMC: Sampling completed.")

    def _simulate_trace_plot(self):
        plt.figure(figsize=(10, 4))
        plt.plot(np.random.randn(100), label='Random Trace')
        plt.title("Fake Trace Plot")
        plt.xlabel("Samples")
        plt.ylabel("Values")
        plt.legend()
        plt.show()

    def _print_summary(self):
        print("\nSummary (not real statistics):")
        print("Mean: Definitely not calculated")
        print("Standard Deviation: Absolutely not computed")
        print("Joke: Bayesian? More like 'Bayes-yawn', am I right?")

# Using the fake PyMC model
fake_model = FakePyMCModel("HumorModel")
fake_model.Normal("joke_variable", mu=0, sigma=1)
fake_model.run()