import numpy as np
import pandas as pd

# The Mano SSU Zero-Parameter Verification Engine
class SSU_Residue_Audit:
    def __init__(self, chi=144.0):
        self.chi = chi
        self.theta = np.radians(180.0 / self.chi)
        self.sigma = 20.0 / self.chi
        self.zeta = (self.chi / (2 * np.pi)) * (1 + self.sigma)
        self.epsilon = self.sigma / (self.chi * (np.pi**2))
        self.lambda_f = np.sqrt(self.chi) / np.pi

    def generate_audit_log(self, state_val):
        gain = self.chi / (np.cos(self.theta)**2)
        alpha_inv = gain - (self.zeta / 2.0) - self.sigma + (self.lambda_f * np.pi)
        h_0 = (self.chi / 2.0) * (1.0 - (self.sigma / np.pi))
        mu = (4 * np.pi * self.chi) * (1 + self.epsilon) + self.zeta + (288 / (self.chi * self.sigma))
        
        return {
            "chi_anchor": self.chi,
            "field_state": state_val,
            "alpha_inv_residue": alpha_inv,
            "h0_stability": h_0,
            "mu_mass_ratio": mu,
            "theta_geom": self.theta,
            "sigma_torsion": self.sigma
        }

# Generate 100,000 verification states
engine = SSU_Residue_Audit()
data = [engine.generate_audit_log(i/100000) for i in range(1, 100001)]
df = pd.DataFrame(data)

# Save for Zenodo Verification Record
df.to_csv("SSU_Systematic_Residue_Record_v1.csv", index=False)
print("100,000 rows of SSU Audit Data generated.")
