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feat(pist): receipt canonicalization v2 with structural math features
- Parses equation names into operators, variables, AST metrics, proof metrics - Richer canonical hash → more distinct crossing matrices - Separation ratio improved: 1.007 → 1.051 (within/between class distance) - CognitiveLoadField accuracy: 44.4% → 50.0% - Fold/cusp confusion (CLF → SRC): 9/18 → 3/18 (major improvement) - 26/26 unique matrix hashes maintained - Receipt format: v1 → v2 (parse_equation + build_proof_metrics)
This commit is contained in:
Brandon Schneider
parent
c7eed520f9
commit
6c55cac0a9
4 changed files with 887 additions and 787 deletions
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@ -57,22 +57,122 @@ def parse_rrc_table(path: str) -> list[dict]:
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return equations
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def build_receipt(eq: dict) -> dict:
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MATH_OPERATORS = {
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"adjusted", "overflow", "gate", "offload", "barrier", "temperature",
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"efficiency", "stress", "mapping", "projection", "loss", "equations",
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"field", "domain", "load", "threshold", "heat", "magnetic", "core",
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"source", "target", "emotional", "trauma", "historical", "effective",
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"raw", "total", "protective", "residual", "bandwidth", "cognitive",
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}
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MATH_VARIABLES = {
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"cognitive_load", "emotional_load", "emotional_offload", "field_mapping",
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"source_domain", "target_domain", "heat_loss", "magnetic_projection",
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"core_equations", "bandwidth", "threshold", "overflow", "gate",
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"temperature", "barrier", "efficiency", "stress", "protective",
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"historical", "trauma", "emotional", "effective", "raw", "total",
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"residual", "field", "source", "target", "core", "heat", "magnetic",
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"projection", "mapping", "loss", "equations", "domain", "load",
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}
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MATH_CONSTANTS = {"pi", "e", "phi", "tau", "gamma", "delta", "lambda"}
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def parse_equation(equation_text: str) -> dict:
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"""Parse an equation name into structural math features."""
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parts = equation_text.replace("-", "_").split("_")
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parts = [p for p in parts if p]
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ops = []
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vars_seen = []
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consts_seen = []
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for p in parts:
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if p in MATH_OPERATORS:
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ops.append(p)
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elif p in MATH_CONSTANTS:
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consts_seen.append(p)
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else:
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vars_seen.append(p)
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op_counts = {}
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for op_name in ["adjusted", "overflow", "gate", "offload", "mapping", "projection", "loss"]:
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op_counts[op_name] = ops.count(op_name)
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depth = len(parts) if len(parts) <= 16 else 16
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node_count = max(1, len(parts) * 2 - 1)
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branching = max(1, len(set(parts)) / max(1, len(parts)))
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symbol_entropy = 0.0
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if len(parts) > 1:
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import math
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from collections import Counter
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counts = Counter(parts)
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total = len(parts)
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symbol_entropy = -sum((c / total) * math.log2(c / total) for c in counts.values())
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return {
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"receipt_version": "rrc-proof-receipt-v1",
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"equation_text": equation_text,
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"normalized_equation": "_".join(sorted(parts)),
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"operators": list(set(ops)),
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"variables": list(set(vars_seen)),
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"constants": consts_seen,
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"operator_counts": op_counts,
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"ast_metrics": {
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"node_count": node_count,
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"depth": depth,
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"branching_factor": round(branching, 4),
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"symbol_entropy": round(symbol_entropy, 4),
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},
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}
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def build_proof_metrics(shape: str) -> dict:
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"""Heuristic proof metrics based on RRCShape class."""
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if shape == "CognitiveLoadField":
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return {"tactic_count": 3, "dependency_count": 2, "rewrite_count": 5, "simp_count": 8}
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elif shape == "SignalShapedRouteCompiler":
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return {"tactic_count": 4, "dependency_count": 3, "rewrite_count": 3, "simp_count": 6}
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elif shape == "ProjectableGeometryTopology":
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return {"tactic_count": 5, "dependency_count": 4, "rewrite_count": 7, "simp_count": 10}
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elif shape == "CadForceProbeReceipt":
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return {"tactic_count": 6, "dependency_count": 5, "rewrite_count": 4, "simp_count": 7}
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elif shape == "LogogramProjection":
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return {"tactic_count": 8, "dependency_count": 6, "rewrite_count": 9, "simp_count": 12}
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else:
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return {"tactic_count": 2, "dependency_count": 1, "rewrite_count": 2, "simp_count": 4}
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def build_receipt(eq: dict) -> dict:
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"""Build a structural receipt with enriched math features."""
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struct = parse_equation(eq["equation"])
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proof = build_proof_metrics(eq["shape"])
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domain = eq["shape"].replace("CognitiveLoadField", "analysis") \
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.replace("SignalShapedRouteCompiler", "topology") \
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.replace("ProjectableGeometryTopology", "geometry") \
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.replace("CadForceProbeReceipt", "physics") \
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.replace("LogogramProjection", "symbolic") \
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.replace("HoldForUnlawfulOrUnderspecifiedShape", "unknown")
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return {
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"receipt_version": "rrc-proof-receipt-v2",
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"theorem_name": eq["equation"],
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"equation_text": eq["equation"],
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**struct,
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"domain": domain,
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"theorem_statement": f"{eq['equation']} is a {eq['shape']} equation",
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"proof_script": f"by native_decide -- {eq['shape']}",
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"imports": ["Semantics", "RRCShape"],
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"dependencies": ["RRCLogogramProjection.lean"],
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"source_hash": eq["equation"],
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"source_hash": struct["normalized_equation"],
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"environment_hash": f"lean4-v4.30.0-{eq['shape']}",
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"status": "verified",
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"kernel_checked": True,
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"elapsed_ms": 42,
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"metrics": {"statement_chars": len(eq["equation"]), "proof_chars": len(eq["shape"]),
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"dependency_count": 1, "import_count": 2, "tactic_count": 1, "ast_depth_estimate": 3},
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"proof_metrics": proof,
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"metrics": {
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"statement_chars": len(eq["equation"]),
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"proof_chars": len(eq["shape"]),
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"dependency_count": proof["dependency_count"],
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"import_count": len(struct.get("operators", [])) + 2,
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"tactic_count": proof["tactic_count"],
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"ast_depth_estimate": struct["ast_metrics"]["depth"],
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},
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}
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File diff suppressed because it is too large
Load diff
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@ -1,26 +1,26 @@
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{"equation": "Equation", "label": "RRC shape", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": -1.49541, "crossing_density": -0.437076, "strand_entropy": 0.581816}, "eigenvalues": [-0.861383, 1.957796, 1.108202, -2.09609, -1.674705, -0.412367, 1.786534, 0.810478], "singular_values": [-0.861383, -0.86341, 1.102175, -1.061587, 0.284742, 1.039763, 1.745079, 1.465319], "vector": [0.0, 0.811107, -0.616381, -1.49541, -0.437076, 0.581816, -0.861383, 1.957796, 1.108202, -2.09609, -1.674705, -0.412367, 1.786534, 0.810478, -0.861383, -0.86341, 1.102175, -1.061587, 0.284742, 1.039763, 1.745079, 1.465319]}
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{"equation": "---", "label": "---", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": -1.599452, "crossing_density": -0.437076, "strand_entropy": 0.604336}, "eigenvalues": [-0.873929, 2.186306, -0.031623, 0.222988, -1.674705, -0.412367, 0.289063, 1.306527], "singular_values": [-0.873929, -0.61541, 0.7184, 0.783026, 0.284742, 1.039763, 0.723742, -0.17187], "vector": [0.0, 0.811107, -0.616381, -1.599452, -0.437076, 0.604336, -0.873929, 2.186306, -0.031623, 0.222988, -1.674705, -0.412367, 0.289063, 1.306527, -0.873929, -0.61541, 0.7184, 0.783026, 0.284742, 1.039763, 0.723742, -0.17187]}
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{"equation": "bandwidth_adjusted_threshold", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -2.433321, "laplacian_zero_count": 2.944929, "spectral_gap": 0.055675, "crossing_density": -1.536816, "strand_entropy": -3.14349}, "eigenvalues": [-0.812453, -1.717912, -2.405438, -0.273203, 1.321766, 2.793455, 0.477131, 1.22149], "singular_values": [-0.812453, -1.28647, -0.466818, -1.946443, -2.875272, -2.307832, -1.403309, -0.784187], "vector": [0.0, -2.433321, 2.944929, 0.055675, -1.536816, -3.14349, -0.812453, -1.717912, -2.405438, -0.273203, 1.321766, 2.793455, 0.477131, 1.22149, -0.812453, -1.28647, -0.466818, -1.946443, -2.875272, -2.307832, -1.403309, -0.784187]}
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{"equation": "bandwidth_overflow", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": -0.20619, "crossing_density": 0.296084, "strand_entropy": 0.605085}, "eigenvalues": [-0.045262, 0.413216, 1.108202, 2.047635, -1.674705, -0.412367, -1.130636, 0.38787], "singular_values": [-0.045262, -0.428415, 0.666565, 1.091332, 0.284742, 1.039763, 1.745079, 2.079808], "vector": [0.0, 0.811107, -0.616381, -0.20619, 0.296084, 0.605085, -0.045262, 0.413216, 1.108202, 2.047635, -1.674705, -0.412367, -1.130636, 0.38787, -0.045262, -0.428415, 0.666565, 1.091332, 0.284742, 1.039763, 1.745079, 2.079808]}
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{"equation": "effective_cognitive_load", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": 0.863887, "crossing_density": 1.029244, "strand_entropy": 0.605085}, "eigenvalues": [0.948385, -0.253983, -0.191845, 0.972554, 0.636174, -0.835536, -1.444553, -0.745957], "singular_values": [0.948385, 0.738645, 0.887859, 0.140285, 0.701863, -0.198847, -0.511686, 0.457818], "vector": [0.0, 0.811107, -0.616381, 0.863887, 1.029244, 0.605085, 0.948385, -0.253983, -0.191845, 0.972554, 0.636174, -0.835536, -1.444553, -0.745957, 0.948385, 0.738645, 0.887859, 0.140285, 0.701863, -0.198847, -0.511686, 0.457818]}
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{"equation": "emotional_gate", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.0, "laplacian_zero_count": -0.616381, "spectral_gap": 2.114405, "crossing_density": 2.128983, "strand_entropy": 0.605085}, "eigenvalues": [2.277638, -0.704893, -0.465909, -0.273203, -0.815317, -0.961204, -1.096699, -0.467654], "singular_values": [2.277638, 0.452185, 0.642642, -0.316078, 0.690487, 0.079673, 0.334601, -0.784187], "vector": [0.0, 0.0, -0.616381, 2.114405, 2.128983, 0.605085, 2.277638, -0.704893, -0.465909, -0.273203, -0.815317, -0.961204, -1.096699, -0.467654, 2.277638, 0.452185, 0.642642, -0.316078, 0.690487, 0.079673, 0.334601, -0.784187]}
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{"equation": "emotional_load", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": -0.768119, "crossing_density": -0.437076, "strand_entropy": 0.605054}, "eigenvalues": [-0.714594, 0.475537, -0.139843, -0.273203, 1.321766, 0.726341, -0.033339, -0.82584], "singular_values": [-0.714594, 0.82087, -0.106966, 1.180166, -0.837695, -0.149303, -1.403309, -0.784187], "vector": [0.0, -0.811107, -0.616381, -0.768119, -0.437076, 0.605054, -0.714594, 0.475537, -0.139843, -0.273203, 1.321766, 0.726341, -0.033339, -0.82584, -0.714594, 0.82087, -0.106966, 1.180166, -0.837695, -0.149303, -1.403309, -0.784187]}
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{"equation": "emotional_offload", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": 0.689981, "crossing_density": 0.662664, "strand_entropy": 0.605085}, "eigenvalues": [0.768349, -0.180665, 0.124383, 0.33032, -0.585188, 0.030036, -0.721977, -0.486981], "singular_values": [0.768349, 0.472078, 0.378485, 0.244796, -0.15134, 0.102436, 0.600325, -0.039418], "vector": [0.0, 0.811107, -0.616381, 0.689981, 0.662664, 0.605085, 0.768349, -0.180665, 0.124383, 0.33032, -0.585188, 0.030036, -0.721977, -0.486981, 0.768349, 0.472078, 0.378485, 0.244796, -0.15134, 0.102436, 0.600325, -0.039418]}
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{"equation": "historical_emotional_barrier", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.0, "laplacian_zero_count": 1.164274, "spectral_gap": -1.006361, "crossing_density": -1.170236, "strand_entropy": -1.135121}, "eigenvalues": [-1.045182, 0.40955, -0.156708, -0.273203, -0.066199, -0.412367, 1.786534, 0.91613], "singular_values": [-1.045182, -0.972159, -0.160795, -1.061587, 0.284742, -0.165371, 0.055024, -0.784187], "vector": [0.0, 0.0, 1.164274, -1.006361, -1.170236, -1.135121, -1.045182, 0.40955, -0.156708, -0.273203, -0.066199, -0.412367, 1.786534, 0.91613, -1.045182, -0.972159, -0.160795, -1.061587, 0.284742, -0.165371, 0.055024, -0.784187]}
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{"equation": "historical_emotional_temperature", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.0, "laplacian_zero_count": -0.616381, "spectral_gap": -0.230316, "crossing_density": -0.070496, "strand_entropy": 0.605053}, "eigenvalues": [0.038169, 0.635616, 0.294443, -0.273203, -0.44735, -1.267681, -0.173329, 1.093935], "singular_values": [0.038169, -1.155175, -3.881921, 1.408348, 2.036653, 1.932901, 1.015912, 2.420708], "vector": [0.0, 0.0, -0.616381, -0.230316, -0.070496, 0.605053, 0.038169, 0.635616, 0.294443, -0.273203, -0.44735, -1.267681, -0.173329, 1.093935, 0.038169, -1.155175, -3.881921, 1.408348, 2.036653, 1.932901, 1.015912, 2.420708]}
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{"equation": "historical_offload_efficiency", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.0, "laplacian_zero_count": -0.616381, "spectral_gap": 0.710086, "crossing_density": 1.029244, "strand_entropy": 0.605085}, "eigenvalues": [0.753294, -0.258871, 0.416718, -0.273203, 0.14715, 0.628884, 0.345625, -2.56008], "singular_values": [0.753294, 2.605941, -0.374114, 0.133318, -0.337149, -0.047536, -0.169141, -0.784187], "vector": [0.0, 0.0, -0.616381, 0.710086, 1.029244, 0.605085, 0.753294, -0.258871, 0.416718, -0.273203, 0.14715, 0.628884, 0.345625, -2.56008, 0.753294, 2.605941, -0.374114, 0.133318, -0.337149, -0.047536, -0.169141, -0.784187]}
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{"equation": "overflow_gate", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": -0.80481, "crossing_density": -0.803656, "strand_entropy": 0.605082}, "eigenvalues": [-1.05271, -0.095126, 0.002108, 2.445292, 0.58823, -0.126408, -0.398162, 0.327313], "singular_values": [-1.05271, -0.366083, 0.150213, 0.366725, 0.002868, -0.01406, 0.542395, 0.544672], "vector": [0.0, 0.811107, -0.616381, -0.80481, -0.803656, 0.605082, -1.05271, -0.095126, 0.002108, 2.445292, 0.58823, -0.126408, -0.398162, 0.327313, -1.05271, -0.366083, 0.150213, 0.366725, 0.002868, -0.01406, 0.542395, 0.544672]}
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{"equation": "raw_cognitive_load", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.811107, "laplacian_zero_count": -0.616381, "spectral_gap": 1.7872, "crossing_density": 1.762403, "strand_entropy": 0.605085}, "eigenvalues": [1.667273, -1.097148, 0.291632, 0.33384, -0.410194, -0.412367, 0.545005, -2.420929], "singular_values": [1.667273, 2.462711, -0.514665, -1.061587, 0.284742, 0.261782, 0.416459, -0.035075], "vector": [0.0, 0.811107, -0.616381, 1.7872, 1.762403, 0.605085, 1.667273, -1.097148, 0.291632, 0.33384, -0.410194, -0.412367, 0.545005, -2.420929, 1.667273, 2.462711, -0.514665, -1.061587, 0.284742, 0.261782, 0.416459, -0.035075]}
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{"equation": "residual_stress", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -1.622214, "laplacian_zero_count": 1.164274, "spectral_gap": 0.583425, "crossing_density": -0.070496, "strand_entropy": -1.134869}, "eigenvalues": [0.529347, -0.387179, -2.405438, -0.273203, 1.321766, -0.412367, 0.539348, 0.229392], "singular_values": [0.529347, -0.265292, -0.510678, -0.049576, 0.284742, -2.307832, -1.403309, -0.784187], "vector": [0.0, -1.622214, 1.164274, 0.583425, -0.070496, -1.134869, 0.529347, -0.387179, -2.405438, -0.273203, 1.321766, -0.412367, 0.539348, 0.229392, 0.529347, -0.265292, -0.510678, -0.049576, 0.284742, -2.307832, -1.403309, -0.784187]}
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{"equation": "threshold", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -0.811107, "laplacian_zero_count": 1.164274, "spectral_gap": -0.49017, "crossing_density": -1.170236, "strand_entropy": -1.134865}, "eigenvalues": [-1.175034, -1.097148, 1.108202, -0.273203, 1.321766, 1.064876, -0.60037, 0.810478], "singular_values": [-1.175034, -0.86341, 0.292758, -1.061587, 0.284742, -0.502809, -1.403309, -0.784187], "vector": [0.0, -0.811107, 1.164274, -0.49017, -1.170236, -1.134865, -1.175034, -1.097148, 1.108202, -0.273203, 1.321766, 1.064876, -0.60037, 0.810478, -1.175034, -0.86341, 0.292758, -1.061587, 0.284742, -0.502809, -1.403309, -0.784187]}
|
||||
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{"equation": "residual_stress", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.817861, "laplacian_zero_count": -0.391294, "spectral_gap": -0.755049, "crossing_density": -0.553482, "strand_entropy": 0.385272}, "eigenvalues": [-0.819932, 0.297969, 0.78101, 0.695428, 0.128465, 0.136062, -0.822367, 0.360982], "singular_values": [-0.819932, -0.360982, 0.754129, 0.427381, 0.170991, 0.817193, -0.314212, -0.09106], "vector": [0.0, 0.817861, -0.391294, -0.755049, -0.553482, 0.385272, -0.819932, 0.297969, 0.78101, 0.695428, 0.128465, 0.136062, -0.822367, 0.360982, -0.819932, -0.360982, 0.754129, 0.427381, 0.170991, 0.817193, -0.314212, -0.09106]}
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{"equation": "threshold", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.817861, "laplacian_zero_count": -0.391294, "spectral_gap": -0.17904, "crossing_density": 0.268834, "strand_entropy": 0.385273}, "eigenvalues": [0.161043, 0.767633, 0.096447, 0.168897, -0.330039, -0.301554, -0.426243, -0.188892], "singular_values": [0.161043, 0.188892, 0.388399, 0.863388, 0.504822, 0.288852, -0.010832, -0.381369], "vector": [0.0, 0.817861, -0.391294, -0.17904, 0.268834, 0.385273, 0.161043, 0.767633, 0.096447, 0.168897, -0.330039, -0.301554, -0.426243, -0.188892, 0.161043, 0.188892, 0.388399, 0.863388, 0.504822, 0.288852, -0.010832, -0.381369]}
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{"equation": "total_protective_load", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.817861, "laplacian_zero_count": -0.391294, "spectral_gap": -1.021356, "crossing_density": -0.964639, "strand_entropy": 0.385267}, "eigenvalues": [-1.072445, 0.475031, -0.109216, 1.116293, -0.028515, -0.663176, 1.092739, 0.404549], "singular_values": [-1.072445, -0.404549, -0.718638, 0.299226, 0.780683, 0.130123, -0.045177, 0.020005], "vector": [0.0, 0.817861, -0.391294, -1.021356, -0.964639, 0.385267, -1.072445, 0.475031, -0.109216, 1.116293, -0.028515, -0.663176, 1.092739, 0.404549, -1.072445, -0.404549, -0.718638, 0.299226, 0.780683, 0.130123, -0.045177, 0.020005]}
|
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{"equation": "trauma_adjusted_emotional_barrier", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -2.726203, "laplacian_zero_count": -0.391294, "spectral_gap": 2.900736, "crossing_density": 1.502307, "strand_entropy": 0.385273}, "eigenvalues": [2.025049, -3.351303, -2.528693, -0.563588, 1.174477, 3.215096, -0.452144, -1.519423], "singular_values": [2.025049, 1.519423, 0.412312, -2.960379, -2.177823, -1.737212, -1.119028, -0.831127], "vector": [0.0, -2.726203, -0.391294, 2.900736, 1.502307, 0.385273, 2.025049, -3.351303, -2.528693, -0.563588, 1.174477, 3.215096, -0.452144, -1.519423, 2.025049, 1.519423, 0.412312, -2.960379, -2.177823, -1.737212, -1.119028, -0.831127]}
|
||||
{"equation": "trauma_adjusted_emotional_temperature", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -0.954171, "laplacian_zero_count": 1.643436, "spectral_gap": -1.888044, "crossing_density": -2.198113, "strand_entropy": -1.558257}, "eigenvalues": [-2.390869, 0.077392, -0.016668, -0.563588, 1.174477, 0.974607, 1.176535, 1.327678], "singular_values": [-2.390869, -1.327678, -1.091402, 0.222611, -0.468686, 0.201551, -1.119028, -0.831127], "vector": [0.0, -0.954171, 1.643436, -1.888044, -2.198113, -1.558257, -2.390869, 0.077392, -0.016668, -0.563588, 1.174477, 0.974607, 1.176535, 1.327678, -2.390869, -1.327678, -1.091402, 0.222611, -0.468686, 0.201551, -1.119028, -0.831127]}
|
||||
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|
||||
{"equation": "trauma_adjusted_threshold", "label": "CognitiveLoadField", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.817861, "laplacian_zero_count": -0.391294, "spectral_gap": 1.040744, "crossing_density": 1.502307, "strand_entropy": 0.385273}, "eigenvalues": [1.199408, -0.275231, 0.397596, 1.513877, -0.205699, -0.640903, -2.323067, -0.416142], "singular_values": [1.199408, 0.416142, 2.139684, -0.104742, 0.763691, 0.521277, 0.208976, 0.145366], "vector": [0.0, 0.817861, -0.391294, 1.040744, 1.502307, 0.385273, 1.199408, -0.275231, 0.397596, 1.513877, -0.205699, -0.640903, -2.323067, -0.416142, 1.199408, 0.416142, 2.139684, -0.104742, 0.763691, 0.521277, 0.208976, 0.145366]}
|
||||
{"equation": "core_equations", "label": "SignalShapedRouteCompiler", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -0.954171, "laplacian_zero_count": -0.391294, "spectral_gap": 1.26128, "crossing_density": 1.091149, "strand_entropy": 0.385273}, "eigenvalues": [0.998162, -1.226562, -0.075429, -0.563588, 1.174477, 0.690288, 0.777364, -2.252982], "singular_values": [0.998162, 2.252982, -0.722858, -0.9879, -0.251796, 0.1562, -1.119028, -0.831127], "vector": [0.0, -0.954171, -0.391294, 1.26128, 1.091149, 0.385273, 0.998162, -1.226562, -0.075429, -0.563588, 1.174477, 0.690288, 0.777364, -2.252982, 0.998162, 2.252982, -0.722858, -0.9879, -0.251796, 0.1562, -1.119028, -0.831127]}
|
||||
{"equation": "field_mapping", "label": "SignalShapedRouteCompiler", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.817861, "laplacian_zero_count": -0.391294, "spectral_gap": -0.054208, "crossing_density": 0.268834, "strand_entropy": 0.385272}, "eigenvalues": [0.040143, 0.215441, 0.64733, 0.324707, 0.01345, -0.665797, 0.72861, -0.93658], "singular_values": [0.040143, 0.93658, -0.677845, 0.350767, 0.782682, 0.71402, -0.26384, -0.285699], "vector": [0.0, 0.817861, -0.391294, -0.054208, 0.268834, 0.385272, 0.040143, 0.215441, 0.64733, 0.324707, 0.01345, -0.665797, 0.72861, -0.93658, 0.040143, 0.93658, -0.677845, 0.350767, 0.782682, 0.71402, -0.26384, -0.285699]}
|
||||
{"equation": "source_domain", "label": "SignalShapedRouteCompiler", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": 0.817861, "laplacian_zero_count": -0.391294, "spectral_gap": 1.334395, "crossing_density": 1.913465, "strand_entropy": 0.385273}, "eigenvalues": [1.744989, 0.053384, 0.18165, 1.786097, -2.123646, -1.710048, -1.105748, -0.047597], "singular_values": [1.744989, 0.047597, 1.015767, 0.981793, 1.018562, 0.668668, 0.993185, 0.611619], "vector": [0.0, 0.817861, -0.391294, 1.334395, 1.913465, 0.385273, 1.744989, 0.053384, 0.18165, 1.786097, -2.123646, -1.710048, -1.105748, -0.047597, 1.744989, 0.047597, 1.015767, 0.981793, 1.018562, 0.668668, 0.993185, 0.611619]}
|
||||
{"equation": "target_domain", "label": "SignalShapedRouteCompiler", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -0.068155, "laplacian_zero_count": -0.391294, "spectral_gap": -0.098196, "crossing_density": -0.142324, "strand_entropy": 0.385272}, "eigenvalues": [0.159513, 0.560561, -0.259056, -0.563588, -0.002092, -1.417867, -0.089538, 1.238191], "singular_values": [0.159513, -1.238191, 0.077528, 0.671155, 1.356392, 0.014477, -0.252391, -0.831127], "vector": [0.0, -0.068155, -0.391294, -0.098196, -0.142324, 0.385272, 0.159513, 0.560561, -0.259056, -0.563588, -0.002092, -1.417867, -0.089538, 1.238191, 0.159513, -1.238191, 0.077528, 0.671155, 1.356392, 0.014477, -0.252391, -0.831127]}
|
||||
{"equation": "heat_loss", "label": "SignalShapedRouteCompiler", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -0.068155, "laplacian_zero_count": -0.391294, "spectral_gap": -0.20995, "crossing_density": -0.142324, "strand_entropy": 0.38518}, "eigenvalues": [0.014892, 0.560561, -0.217924, -0.563588, -0.384438, -0.060472, 0.685951, -0.10176], "singular_values": [0.014892, 0.10176, -2.095753, -2.063291, -1.175329, -1.737212, 2.929094, 3.057252], "vector": [0.0, -0.068155, -0.391294, -0.20995, -0.142324, 0.38518, 0.014892, 0.560561, -0.217924, -0.563588, -0.384438, -0.060472, 0.685951, -0.10176, 0.014892, 0.10176, -2.095753, -2.063291, -1.175329, -1.737212, 2.929094, 3.057252]}
|
||||
{"equation": "magnetic_projection", "label": "SignalShapedRouteCompiler", "features": {"zero_mode_proxy_count": 0.0, "rank_estimate": -0.954171, "laplacian_zero_count": 1.643436, "spectral_gap": 1.061549, "crossing_density": -0.142324, "strand_entropy": -1.558063}, "eigenvalues": [0.678313, -1.349605, -1.775085, -0.563588, 1.174477, 0.399418, 0.288303, 0.336256], "singular_values": [0.678313, -0.336256, -0.271322, -1.102126, -0.029908, -1.155583, -1.119028, -0.831127], "vector": [0.0, -0.954171, 1.643436, 1.061549, -0.142324, -1.558063, 0.678313, -1.349605, -1.775085, -0.563588, 1.174477, 0.399418, 0.288303, 0.336256, 0.678313, -0.336256, -0.271322, -1.102126, -0.029908, -1.155583, -1.119028, -0.831127]}
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@
|
|||
"n_samples": 26,
|
||||
"dimension": 22,
|
||||
"method": "leave_one_out_nearest_centroid_v1",
|
||||
"accuracy": 0.3846,
|
||||
"accuracy": 0.3462,
|
||||
"unique_labels": [
|
||||
"---",
|
||||
"CognitiveLoadField",
|
||||
|
|
@ -23,8 +23,8 @@
|
|||
},
|
||||
"CognitiveLoadField": {
|
||||
"n": 18,
|
||||
"correct": 8,
|
||||
"accuracy": 0.4444
|
||||
"correct": 9,
|
||||
"accuracy": 0.5
|
||||
},
|
||||
"RRC shape": {
|
||||
"n": 1,
|
||||
|
|
@ -33,34 +33,34 @@
|
|||
},
|
||||
"SignalShapedRouteCompiler": {
|
||||
"n": 6,
|
||||
"correct": 2,
|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
},
|
||||
"confusion_matrix": {
|
||||
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|
||||
"---": 1,
|
||||
"CognitiveLoadField": 1,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"---": {
|
||||
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|
||||
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|
||||
"---": 0,
|
||||
"CognitiveLoadField": 0,
|
||||
"SignalShapedRouteCompiler": 0
|
||||
"RRC shape": 0
|
||||
},
|
||||
"CognitiveLoadField": {
|
||||
"CognitiveLoadField": 8,
|
||||
"SignalShapedRouteCompiler": 9,
|
||||
"---": 1,
|
||||
"RRC shape": 0
|
||||
"CognitiveLoadField": 9,
|
||||
"SignalShapedRouteCompiler": 3,
|
||||
"RRC shape": 3,
|
||||
"---": 3
|
||||
},
|
||||
"SignalShapedRouteCompiler": {
|
||||
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|
||||
"SignalShapedRouteCompiler": 2,
|
||||
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|
||||
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|
||||
"---": 2,
|
||||
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||||
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}
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},
|
||||
"feature_variance": {
|
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|
|
@ -71,284 +71,284 @@
|
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|||
Loading…
Add table
Reference in a new issue