"""Theory verification. Offline, ~10 s, NumPy only.

Six checks. Two of them exist to demonstrate that claims from an earlier draft
were tautological or scope-violating, which is why they test against
adversarial inputs rather than confirming ones.
"""
import numpy as np
np.set_printoptions(precision=6, suppress=True)

def rot(t):
    return np.array([[np.cos(t), -np.sin(t)], [np.sin(t), np.cos(t)]])

def d0_cycle(N, theta, c=None):
    """Cellular sheaf coboundary on cycle C_N with R^2 stalks.
    c: optional per-vertex stiffness weight."""
    if c is None: c = np.ones(N)
    D = np.zeros((2*N, 2*N)); I = np.eye(2)
    for i in range(N-1):
        D[2*i:2*i+2, 2*i:2*i+2]         = -np.sqrt(c[i])*I
        D[2*i:2*i+2, 2*(i+1):2*(i+1)+2] =  np.sqrt(c[i+1])*I
    e = N-1
    D[2*e:2*e+2, 2*(N-1):2*(N-1)+2] = -np.sqrt(c[N-1])*I
    D[2*e:2*e+2, 0:2]               =  np.sqrt(c[0])*rot(theta)
    return D

def d0_path(N, theta):
    """Open chain (tree). N-1 edges, no loop-closing bond."""
    D = np.zeros((2*(N-1), 2*N)); I = np.eye(2)
    for i in range(N-1):
        D[2*i:2*i+2, 2*i:2*i+2]         = -I
        D[2*i:2*i+2, 2*(i+1):2*(i+1)+2] =  rot(theta) if i == 0 else I
    return D

print("=" * 72)
print("CHECK 1  closed form  lambda_k^pm = 2 - 2cos((2*pi*k +- theta)/N)")
print("=" * 72)
worst = 0.0
for N in [5, 6, 8, 12]:
    for th in [0.0, 0.3, np.pi/4, np.pi/2, 2.0, np.pi, 4.5]:
        D = d0_cycle(N, th)
        num = np.sort(np.linalg.eigvalsh(D.T @ D))
        ana = np.sort(np.concatenate([
            [2 - 2*np.cos((2*np.pi*k + th)/N) for k in range(N)],
            [2 - 2*np.cos((2*np.pi*k - th)/N) for k in range(N)]]))
        worst = max(worst, np.max(np.abs(num - ana)))
print(f"  max |numeric - closed form|, N in 5..12, 7 angles : {worst:.3e}")
print(f"  VERDICT: {'EXACT' if worst < 1e-9 else 'MISMATCH'}")

print("\n" + "=" * 72)
print("CHECK 2  strain floor  lambda_min = 2 - 2cos(theta/N) -> theta^2/N^2")
print("=" * 72)
print(f"  {'N':>3} {'theta':>7} {'lambda_min':>12} {'2-2cos(th/N)':>14} {'th^2/N^2':>12}")
for N in [5, 10, 20]:
    for th in [0.1, 0.5, np.pi/2]:
        lm = np.sort(np.linalg.eigvalsh(d0_cycle(N, th).T @ d0_cycle(N, th)))[0]
        print(f"  {N:>3} {th:>7.4f} {lm:>12.7f} {2-2*np.cos(th/N):>14.7f} {th**2/N**2:>12.7f}")

print("\n" + "=" * 72)
print("CHECK 3  residue stiffness does NOT change Betti numbers")
print("=" * 72)
for name, c in {"AAAAA": [1,1,1,1,1], "APPPA": [1,4,4,4,1],
                "AGGGA": [1,.15,.15,.15,1], "random": [0.31,2.7,0.08,5.2,1.9]}.items():
    c = np.array(c, float); row = []
    for th in [0.0, 0.4, np.pi/2, np.pi]:
        D = d0_cycle(5, th, c)
        row.append((10 - np.linalg.matrix_rank(D, tol=1e-9),
                    np.sort(np.linalg.eigvalsh(D.T @ D))[0]))
    print(f"  {name:>7}  h0 = {[x[0] for x in row]}   lambda_min = "
          + " ".join(f"{x[1]:.4f}" for x in row))
print("  h0 identical across sequences. Only the energy scale moves.")

print("\n" + "=" * 72)
print("CHECK 4  chi = h0 - h1 = 0 is rank-nullity, not a conservation law")
print("=" * 72)
rng = np.random.default_rng(7); bad = 0
for _ in range(2000):
    N = rng.integers(3, 9)
    D = rng.normal(size=(2*N, 2*N))          # arbitrary, no sheaf, no biology
    if rng.random() < 0.3: D[:, rng.integers(0, 2*N)] = 0
    r = np.linalg.matrix_rank(D, tol=1e-9)
    if (2*N - r) - (2*N - r) != 0: bad += 1
print(f"  chi != 0 in {bad} / 2000 random square coboundaries.")
print("  Holds for ANY square d0. Carries zero information about the peptide.")

print("\n" + "=" * 72)
print("CHECK 5  open backbones cannot frustrate (scope limit)")
print("=" * 72)
for th in [0.0, 0.7, np.pi/2, np.pi, 3.0]:
    D = d0_path(6, th); r = np.linalg.matrix_rank(D, tol=1e-9)
    print(f"  theta={th:6.3f}  rank={r:2d}  h0={12-r}  "
          f"lambda_min={np.sort(np.linalg.eigvalsh(D.T@D))[0]:.2e}")
print("  h0=2 always. The mechanism REQUIRES the ring-closing bond.")

print("\n" + "=" * 72)
print("CHECK 6  sqrt(c) in restriction maps breaks the kernel interpretation")
print("=" * 72)
c = np.array([1, 4, 4, 4, 1], float)
D = d0_cycle(5, 0.0, c)
ns = np.linalg.svd(D)[2][np.linalg.matrix_rank(D, tol=1e-9):].T
s = ns[:, 0].reshape(5, 2)
print("  kernel section at theta=0, APPPA stiffness:")
for i, r in enumerate(s):
    print(f"    v{i}: ({r[0]:+.4f}, {r[1]:+.4f})  "
          f"norm*sqrt(c) = {np.linalg.norm(r)*np.sqrt(c[i]):.4f}")
print("  Residues do not share a dihedral vector. The kernel means 'equal after")
print("  rescaling', which is not a conformation. Use edge weights instead:")
print("  Delta = d0^T W d0 with d0 isometric.")