#!/usr/bin/env python3 """Platform probe: reproduce verify.py's hash-relevant FFT steps in isolation. Runs the same scipy.fft.fft / scipy.signal calls that verify.py hashes (csi_processor.py:426, :438, :349) on a deterministic synthetic input, without dragging in src.app / pydantic Settings. Used to empirically locate the source of platform divergence in issue #560 — and now also to verify the quantize-before-hash fix shipped in archive/v1/data/proof/verify.py. Usage: python3 scripts/probe-fft-platform.py Output: single JSON object on stdout. Run on each platform and diff. The output now contains TWO hashes: - `sha256_raw` — hash of unrounded little-endian f64 bytes (legacy) - `sha256_quantized` — hash after np.round(.., 9) (matches verify.py behaviour after the issue-#560 fix; should be IDENTICAL across Intel AVX, ARM NEON, and any scipy pocketfft build) If `sha256_raw` differs across machines but `sha256_quantized` matches, the quantize-before-hash fix is doing its job. """ import hashlib import json import platform import struct import sys import numpy as np import scipy.fft import scipy.signal # Deterministic synthetic input -- no IO, no .env, no Settings rng = np.random.RandomState(42) N_FRAMES = 100 N_SUBC = 100 amp = rng.randn(N_FRAMES, N_SUBC).astype(np.float64) # Mirror the three scipy calls verify.py's hash depends on: # archive/v1/src/core/csi_processor.py:349 -> scipy.signal.windows.hamming # archive/v1/src/core/csi_processor.py:426 -> scipy.fft.fft(mean_phase_diff, n=64) # archive/v1/src/core/csi_processor.py:438 -> scipy.fft.fft(amp.flatten(), n=128) mean_phase_diff = amp.mean(axis=1) doppler = np.abs(scipy.fft.fft(mean_phase_diff, n=64)) ** 2 psd = np.abs(scipy.fft.fft(amp.flatten(), n=128)) ** 2 window = scipy.signal.windows.hamming(56) # Quantization decimals — kept in sync with # archive/v1/data/proof/verify.py:HASH_QUANTIZATION_DECIMALS so this probe # verifies the production hash, not just the FFT outputs. HASH_QUANTIZATION_DECIMALS = 6 def pack_floats(arrays, quantize): """Pack arrays as little-endian f64, optionally rounding first.""" parts = [] for arr in arrays: flat = np.asarray(arr, dtype=np.float64).ravel() if quantize: flat = np.round(flat, HASH_QUANTIZATION_DECIMALS) parts.append(struct.pack(f"<{len(flat)}d", *flat)) return b"".join(parts) arrays = (doppler, psd, window) blob_raw = pack_floats(arrays, quantize=False) blob_quantized = pack_floats(arrays, quantize=True) try: blas_info = np.show_config(mode="dicts") except Exception: blas_info = {"error": "show_config(mode=dicts) unavailable"} print(json.dumps({ "uname": platform.uname()._asdict(), "python": sys.version.split()[0], "numpy": np.__version__, "scipy": __import__("scipy").__version__, "blob_len": len(blob_raw), "sha256_raw": hashlib.sha256(blob_raw).hexdigest(), "sha256_quantized": hashlib.sha256(blob_quantized).hexdigest(), "quantization_decimals": HASH_QUANTIZATION_DECIMALS, "first8_doppler_bytes_hex": doppler[:8].tobytes().hex(), "first4_psd_floats": psd[:4].tolist(), "blas_backend": blas_info if isinstance(blas_info, dict) else str(blas_info), }, indent=2, default=str))