cah
5b6ad4d3f2
Implement spatially-coupled LDPC code construction with: - split_protograph(): split base matrix edges into w components - build_sc_chain(): build full SC-LDPC H matrix with L positions - sc_encode(): GF(2) Gaussian elimination encoder for SC chain Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
64 lines
2.7 KiB
Python
64 lines
2.7 KiB
Python
#!/usr/bin/env python3
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"""Tests for SC-LDPC construction."""
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import numpy as np
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import pytest
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import sys
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import os
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sys.path.insert(0, os.path.dirname(__file__))
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class TestSCLDPCConstruction:
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"""Tests for SC-LDPC chain construction."""
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def test_split_preserves_edges(self):
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"""Split B into components, verify sum(B_i >= 0) == (B >= 0) for each position."""
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from sc_ldpc import split_protograph
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from ldpc_sim import H_BASE
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components = split_protograph(H_BASE, w=2, seed=42)
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assert len(components) == 2
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# Each edge in B should appear in exactly one component
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for r in range(H_BASE.shape[0]):
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for c in range(H_BASE.shape[1]):
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if H_BASE[r, c] >= 0:
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count = sum(1 for comp in components if comp[r, c] >= 0)
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assert count == 1, f"Edge ({r},{c}) in {count} components, expected 1"
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else:
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for comp in components:
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assert comp[r, c] < 0, f"Edge ({r},{c}) should be absent"
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def test_chain_dimensions(self):
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"""Build chain with L=5, w=2, Z=32. Verify H dimensions."""
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from sc_ldpc import build_sc_chain
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from ldpc_sim import H_BASE
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m_base, n_base = H_BASE.shape
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L, w, z = 5, 2, 32
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H_full, components, meta = build_sc_chain(H_BASE, L=L, w=w, z=z, seed=42)
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expected_rows = L * m_base * z # 5*7*32 = 1120
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expected_cols = (L + w - 1) * n_base * z # 6*8*32 = 1536
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assert H_full.shape == (expected_rows, expected_cols), (
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f"Expected ({expected_rows}, {expected_cols}), got {H_full.shape}"
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)
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def test_chain_has_coupled_structure(self):
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"""Verify non-zero blocks only appear at positions t and t+1 for w=2."""
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from sc_ldpc import build_sc_chain
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from ldpc_sim import H_BASE
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m_base, n_base = H_BASE.shape
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L, w, z = 5, 2, 32
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H_full, components, meta = build_sc_chain(H_BASE, L=L, w=w, z=z, seed=42)
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# For each CN position t, check which VN positions have connections
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for t in range(L):
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cn_rows = slice(t * m_base * z, (t + 1) * m_base * z)
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for v in range(L + w - 1):
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vn_cols = slice(v * n_base * z, (v + 1) * n_base * z)
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block = H_full[cn_rows, vn_cols]
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has_connections = np.any(block != 0)
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if t <= v <= t + w - 1:
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# Should have connections (t connects to t..t+w-1)
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assert has_connections, f"CN pos {t} should connect to VN pos {v}"
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else:
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# Should NOT have connections
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assert not has_connections, f"CN pos {t} should NOT connect to VN pos {v}"
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