diff --git a/tools/generate_optical_report.py b/tools/generate_optical_report.py
index 457433ed..957fbce6 100644
--- a/tools/generate_optical_report.py
+++ b/tools/generate_optical_report.py
@@ -277,6 +277,105 @@ def aberration_magnitudes(coeffs):
}
+def compute_spatial_freq_metrics(coefficients):
+ """Compute spatial frequency band metrics from Zernike coefficients.
+
+ Decomposes the Zernike spectrum into Low Spatial Frequency (form/figure)
+ and Mid Spatial Frequency (ripple) bands based on radial order.
+
+ Args:
+ coefficients: array of Zernike coefficients (50 modes, Noll convention)
+
+ Returns:
+ dict with band RMS values and per-radial-order breakdown
+ """
+ n_modes = min(len(coefficients), 50)
+ coeffs = np.array(coefficients[:n_modes])
+
+ # Build radial order mapping using noll_indices
+ order_map = {} # n -> list of coeff values
+ for j in range(1, n_modes + 1):
+ n, m = noll_indices(j)
+ if n not in order_map:
+ order_map[n] = []
+ order_map[n].append(coeffs[j - 1])
+
+ # Band definitions (by Noll index, 1-based)
+ # LSF: J4-J15 (n=2..4) — Low Spatial Frequency (form/figure)
+ # MSF: J16-J50 (n=5..9) — Mid Spatial Frequency (ripple)
+ lsf_coeffs = coeffs[3:15] # indices 3..14 → J4..J15
+ msf_coeffs = coeffs[15:n_modes] # indices 15..49 → J16..J50
+ total_coeffs = coeffs[3:n_modes] # J4..J50 (excluding piston/tilt)
+
+ lsf_rms = float(np.sqrt(np.sum(lsf_coeffs**2)))
+ msf_rms = float(np.sqrt(np.sum(msf_coeffs**2)))
+ total_filtered_rms = float(np.sqrt(np.sum(total_coeffs**2)))
+ lsf_msf_ratio = lsf_rms / msf_rms if msf_rms > 0 else float('inf')
+
+ # Per-radial-order RMS
+ per_order = {}
+ for n in sorted(order_map.keys()):
+ order_coeffs = np.array(order_map[n])
+ per_order[n] = float(np.sqrt(np.sum(order_coeffs**2)))
+
+ return {
+ 'lsf_rms': lsf_rms,
+ 'msf_rms': msf_rms,
+ 'total_filtered_rms': total_filtered_rms,
+ 'lsf_msf_ratio': lsf_msf_ratio,
+ 'per_order': per_order,
+ }
+
+
+def _spatial_freq_html(metrics):
+ """Generate HTML card for spatial frequency band metrics."""
+ m = metrics
+
+ # Per-order breakdown for n=2..9
+ order_items = ""
+ for n in range(2, 10):
+ val = m['per_order'].get(n, 0.0)
+ order_items += (
+ f''
+ f'n={n}:'
+ f'{val:.2f}'
+ f'
\n'
+ )
+
+ ratio_str = (
+ f"{m['lsf_msf_ratio']:.1f}\u00d7"
+ if m['lsf_msf_ratio'] < 1000
+ else "\u221e"
+ )
+
+ return f"""
+
+
Spatial Frequency Breakdown
+
+
+
LSF (Form)
+
J4\u2013J15 n\u22644
+
{m['lsf_rms']:.2f} nm
+
+
+
MSF (Ripple)
+
J16\u2013J50 n\u22655
+
{m['msf_rms']:.2f} nm
+
+
+
LSF / MSF
+
Ratio
+
{ratio_str}
+
+
+
+
Per-Order RMS (nm)
+
{order_items}
+
+
{sec_zernike}. Zernike Coefficient Details
40\u00b0 vs 20\u00b0 \u2014 Relative Coefficients
- {bar_40}
+ {sfm_40}{bar_40}
60\u00b0 vs 20\u00b0 \u2014 Relative Coefficients
- {bar_60}
+ {sfm_60}{bar_60}
90\u00b0 \u2014 Absolute Coefficients
- {bar_90}
+ {sfm_90}{bar_90}