| """MagNET-Zero vs DFT residuals on the DELTA50 benchmark (50 common organics). No plotting. |
| |
| MagNET-Zero is compared against the DFT level it reproduces, on the same AIMNet2 geometries: protons |
| vs WP04/pcSseg-2, carbons vs wB97X-D/pcSseg-2, gas phase; residual = DFT shielding minus MagNET. |
| This is the comparison behind the paper's DELTA50 outlier observation (nitromethane, nitroethane, and |
| 2-methyl-2-nitropropane are the significant outliers). Read via data/delta50/decode_delta50.py. |
| """ |
| import numpy as np |
|
|
| from stats import summarize_errors |
|
|
| |
| NUCLEI = { |
| "H": {"atomic_number": 1, "dft": "shielding_wp04_pcSseg2", "nn": "nn_magnet_zero"}, |
| "C": {"atomic_number": 6, "dft": "shielding_wb97xd_pcSseg2", "nn": "nn_magnet_zero"}, |
| } |
|
|
|
|
| def load_shieldings(delta50_path): |
| """Flat per-atom arrays from the released reader: atomic_numbers, the MagNET predictions, the |
| DFT reference shieldings, and experimental_shift (all ppm, NaN where absent).""" |
| from decode_delta50 import Delta50 |
| with Delta50(delta50_path) as ds: |
| return ds.all_atoms() |
|
|
|
|
| def residuals(shieldings, nucleus): |
| """DFT-minus-MagNET-Zero shielding residuals (ppm) for one nucleus ("H" or "C"), over that |
| element's atoms where both values are present.""" |
| spec = NUCLEI[nucleus] |
| z = np.asarray(shieldings["atomic_numbers"]) |
| dft = np.asarray(shieldings[spec["dft"]], dtype=float) |
| nn = np.asarray(shieldings[spec["nn"]], dtype=float) |
| keep = (z == spec["atomic_number"]) & np.isfinite(dft) & np.isfinite(nn) |
| return dft[keep] - nn[keep] |
|
|
|
|
| def residual_stats(errors): |
| """count / RMSE / MAE / median AE / max absolute error for a residual array.""" |
| errors = np.asarray(errors, dtype=float) |
| if not errors.size: |
| return {"n": 0, "rmse": float("nan"), "mae": float("nan"), "median_ae": float("nan"), |
| "max_ae": float("nan")} |
| stats = summarize_errors(errors, np.zeros_like(errors)) |
| stats["max_ae"] = float(np.abs(errors).max()) |
| return stats |
|
|
|
|
| def residual_summary(delta50_path): |
| """{nucleus: residual_stats} for both nuclei, from the released file.""" |
| shieldings = load_shieldings(delta50_path) |
| return {nucleus: residual_stats(residuals(shieldings, nucleus)) for nucleus in NUCLEI} |
|
|
|
|
| def per_molecule_max_residual(delta50_path): |
| """{molecule_name: {"H": max|residual|, "C": max|residual|}} - the DFT-vs-MagNET-Zero outlier |
| magnitudes per molecule (nitromethane, nitroethane, 2-methyl-2-nitropropane rank highest for C).""" |
| from decode_delta50 import Delta50 |
| out = {} |
| with Delta50(delta50_path) as ds: |
| for i in range(len(ds)): |
| m = ds.molecule(i) |
| z = m["atomic_numbers"] |
| ref = np.where(z == 1, m["shielding_wp04_pcSseg2"], |
| np.where(z == 6, m["shielding_wb97xd_pcSseg2"], np.nan)) |
| r = ref - m["nn_magnet_zero"] |
| res = {} |
| for nucleus, zz in (("H", 1), ("C", 6)): |
| sel = (z == zz) & np.isfinite(r) |
| res[nucleus] = float(np.abs(r[sel]).max()) if sel.any() else float("nan") |
| out[m["name"]] = res |
| return out |
|
|
