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Atomizer/tools/zernike_html_generator.py
Anto01 d7986922d5 fix(tools): make Zernike OPD tools robust to extra subcases 
- Replace brittle order-based subcase mapping with name-based search
- Tools now directly search for required angles (20, 40, 60, 90) by label
- Ignores extra subcases (e.g., 30, 50 degrees) without errors
- Falls back to numeric IDs (1,2,3,4) if angle labels not found
- Clear error messages show exactly which subcases are missing

This allows running WFE analysis on simulations with >4 subcases
without manual file/code modifications.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-29 10:22:33 -05:00

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#!/usr/bin/env python3
"""
Atomizer Zernike HTML Generator
================================
Generates 3 interactive HTML reports for Zernike wavefront analysis:
1. 40° vs 20° (relative) - Operational angle comparison
2. 60° vs 20° (relative) - Operational angle comparison
3. 90° (Manufacturing) - Absolute with manufacturing metrics
Uses the rigorous OPD method from extract_zernike_figure.py which:
- Accounts for lateral (X, Y) displacement via interpolation
- Uses actual mesh geometry as reference (no shape assumptions)
- Provides more accurate WFE for mirror optimization
- Supports ANNULAR APERTURES via --inner-radius option
Usage:
conda activate atomizer
python zernike_html_generator.py "path/to/solution.op2"
# With annular aperture (central hole)
python zernike_html_generator.py "path/to/solution.op2" --inner-radius 135.75
# Or with file dialog (double-click via analyze_wfe.bat)
python zernike_html_generator.py
Output:
Creates 3 HTML files in same directory as OP2:
- {basename}_40_vs_20.html
- {basename}_60_vs_20.html
- {basename}_90_mfg.html
Author: Atomizer
Created: 2025-12-19
Updated: 2025-12-28 - Upgraded to use rigorous OPD method
Updated: 2025-01-06 - Added annular aperture support via --inner-radius
"""
import sys
import os
from pathlib import Path
from math import factorial
from datetime import datetime
import numpy as np
from numpy.linalg import LinAlgError
# Add Atomizer root to path
ATOMIZER_ROOT = Path(__file__).parent.parent
if str(ATOMIZER_ROOT) not in sys.path:
sys.path.insert(0, str(ATOMIZER_ROOT))
try:
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from matplotlib.tri import Triangulation
from pyNastran.op2.op2 import OP2
from pyNastran.bdf.bdf import BDF
except ImportError as e:
print(f"ERROR: Missing dependency: {e}")
print("Run: conda activate atomizer")
sys.exit(1)
# Import the rigorous OPD extractor
try:
from optimization_engine.extractors.extract_zernike_figure import ZernikeOPDExtractor
USE_OPD_METHOD = True
print("[INFO] Using rigorous OPD method (accounts for lateral displacement)")
except ImportError:
USE_OPD_METHOD = False
print("[WARN] OPD extractor not available, falling back to simple Z-only method")
# ============================================================================
# Configuration
# ============================================================================
N_MODES = 50
AMP = 0.5 # visual scale for residual plot (0.5x = reduced deformation)
PANCAKE = 3.0 # Z-axis range multiplier for camera view
PLOT_DOWNSAMPLE = 10000
FILTER_LOW_ORDERS = 4 # piston, tip, tilt, defocus
# Surface plot style
COLORSCALE = 'Turbo' # Options: 'RdBu_r', 'Viridis', 'Plasma', 'Turbo', 'Jet'
SURFACE_LIGHTING = True # Smooth shaded surface with lighting
SHOW_ZERNIKE_BAR = True
REQUIRED_SUBCASES = [90, 20, 40, 60]
REF_LABEL = "2" # Reference subcase (20 deg) - using isubcase
POLISH_LABEL = "1" # Manufacturing orientation (90 deg) - using isubcase
# Displacement unit in OP2 -> nm scale for WFE = 2*Disp_Z
DISP_SRC_UNIT = "mm"
NM_PER_UNIT = 1e6 if DISP_SRC_UNIT == "mm" else 1e9
# ============================================================================
# Zernike Math
# ============================================================================
def noll_indices(j: int):
if j < 1:
raise ValueError("Noll index j must be >= 1")
count = 0
n = 0
while True:
if n == 0:
ms = [0]
elif n % 2 == 0:
ms = [0] + [m for k in range(1, n//2 + 1) for m in (-2*k, 2*k)]
else:
ms = [m for k in range(0, (n+1)//2) for m in (-(2*k+1), (2*k+1))]
for m in ms:
count += 1
if count == j:
return n, m
n += 1
def zernike_noll(j, r, th):
n, m = noll_indices(j)
R = np.zeros_like(r)
for s in range((n-abs(m))//2 + 1):
c = ((-1)**s * factorial(n-s) /
(factorial(s) *
factorial((n+abs(m))//2 - s) *
factorial((n-abs(m))//2 - s)))
R += c * r**(n-2*s)
if m == 0:
return R
return R * (np.cos(m*th) if m > 0 else np.sin(-m*th))
def compute_zernike_coeffs(X, Y, vals, n_modes, chunk_size=100000):
Xc, Yc = X - np.mean(X), Y - np.mean(Y)
R = float(np.max(np.hypot(Xc, Yc)))
r = np.hypot(Xc/R, Yc/R).astype(np.float32)
th = np.arctan2(Yc, Xc).astype(np.float32)
mask = (r <= 1.0) & ~np.isnan(vals)
if not np.any(mask):
raise RuntimeError("No valid points inside unit disk.")
idx = np.nonzero(mask)[0]
m = int(n_modes)
G = np.zeros((m, m), dtype=np.float64)
h = np.zeros((m,), dtype=np.float64)
v = vals.astype(np.float64)
for start in range(0, len(idx), chunk_size):
sl = idx[start:start+chunk_size]
r_b, th_b, v_b = r[sl], th[sl], v[sl]
Zb = np.column_stack([zernike_noll(j, r_b, th_b).astype(np.float32)
for j in range(1, m+1)])
G += (Zb.T @ Zb).astype(np.float64)
h += (Zb.T @ v_b).astype(np.float64)
try:
coeffs = np.linalg.solve(G, h)
except LinAlgError:
coeffs = np.linalg.lstsq(G, h, rcond=None)[0]
return coeffs, R
def zernike_common_name(n: int, m: int) -> str:
names = {
(0, 0): "Piston", (1, -1): "Tilt X", (1, 1): "Tilt Y",
(2, 0): "Defocus", (2, -2): "Astig 45 deg", (2, 2): "Astig 0 deg",
(3, -1): "Coma X", (3, 1): "Coma Y", (3, -3): "Trefoil X", (3, 3): "Trefoil Y",
(4, 0): "Primary Spherical", (4, -2): "Sec Astig X", (4, 2): "Sec Astig Y",
(4, -4): "Quadrafoil X", (4, 4): "Quadrafoil Y",
(5, -1): "Sec Coma X", (5, 1): "Sec Coma Y",
(5, -3): "Sec Trefoil X", (5, 3): "Sec Trefoil Y",
(5, -5): "Pentafoil X", (5, 5): "Pentafoil Y",
(6, 0): "Sec Spherical",
}
return names.get((n, m), f"Z(n={n}, m={m})")
def zernike_label_for_j(j: int) -> str:
n, m = noll_indices(j)
return f"J{j:02d} - {zernike_common_name(n, m)} (n={n}, m={m})"
# ============================================================================
# File I/O
# ============================================================================
def find_geometry_file(op2_path: Path) -> Path:
"""Find matching BDF/DAT file for an OP2."""
folder = op2_path.parent
base = op2_path.stem
for ext in ['.dat', '.bdf']:
cand = folder / (base + ext)
if cand.exists():
return cand
for f in folder.iterdir():
if f.suffix.lower() in ['.dat', '.bdf']:
return f
raise FileNotFoundError(f"No .dat or .bdf geometry file found for {op2_path}")
def read_geometry(dat_path: Path) -> dict:
bdf = BDF()
bdf.read_bdf(str(dat_path))
return {int(nid): node.get_position() for nid, node in bdf.nodes.items()}
def read_displacements(op2_path: Path) -> dict:
"""Read displacement data organized by subcase."""
op2 = OP2()
op2.read_op2(str(op2_path))
if not op2.displacements:
raise RuntimeError("No displacement data found in OP2 file")
result = {}
for key, darr in op2.displacements.items():
data = darr.data
dmat = data[0] if data.ndim == 3 else (data if data.ndim == 2 else None)
if dmat is None:
continue
ngt = darr.node_gridtype.astype(int)
node_ids = ngt if ngt.ndim == 1 else ngt[:, 0]
# Get subcase identifier
isubcase = getattr(darr, 'isubcase', None)
label = str(isubcase) if isubcase else str(key)
result[label] = {
'node_ids': node_ids.astype(int),
'disp': dmat.copy()
}
return result
# ============================================================================
# Data Processing
# ============================================================================
def build_wfe_arrays(label: str, node_ids, dmat, node_geo):
"""Build X, Y, WFE arrays for a subcase."""
X, Y, WFE = [], [], []
for nid, vec in zip(node_ids, dmat):
geo = node_geo.get(int(nid))
if geo is None:
continue
X.append(geo[0])
Y.append(geo[1])
wfe = vec[2] * 2.0 * NM_PER_UNIT # Z-disp to WFE (nm)
WFE.append(wfe)
return np.array(X), np.array(Y), np.array(WFE)
def compute_relative_wfe(X1, Y1, WFE1, node_ids1, X2, Y2, WFE2, node_ids2):
"""Compute relative WFE: WFE1 - WFE2 for common nodes."""
# Build mapping for reference
ref_map = {int(nid): (x, y, w) for nid, x, y, w in zip(node_ids2, X2, Y2, WFE2)}
X_rel, Y_rel, WFE_rel = [], [], []
for nid, x, y, w in zip(node_ids1, X1, Y1, WFE1):
nid = int(nid)
if nid in ref_map:
_, _, w_ref = ref_map[nid]
X_rel.append(x)
Y_rel.append(y)
WFE_rel.append(w - w_ref)
return np.array(X_rel), np.array(Y_rel), np.array(WFE_rel)
def compute_rms_metrics(X, Y, W_nm):
"""Compute RMS metrics and Zernike coefficients."""
coeffs, R = compute_zernike_coeffs(X, Y, W_nm, N_MODES)
Xc = X - np.mean(X)
Yc = Y - np.mean(Y)
r = np.hypot(Xc/R, Yc/R)
th = np.arctan2(Yc, Xc)
Z = np.column_stack([zernike_noll(j, r, th) for j in range(1, N_MODES+1)])
W_res_filt = W_nm - Z[:, :FILTER_LOW_ORDERS].dot(coeffs[:FILTER_LOW_ORDERS])
# J1-J3 filtered (keeping defocus - optician workload)
W_res_filt_j1to3 = W_nm - Z[:, :3].dot(coeffs[:3])
global_rms = float(np.sqrt(np.mean(W_nm**2)))
filtered_rms = float(np.sqrt(np.mean(W_res_filt**2)))
rms_filter_j1to3 = float(np.sqrt(np.mean(W_res_filt_j1to3**2)))
return {
'coefficients': coeffs,
'R': R,
'global_rms': global_rms,
'filtered_rms': filtered_rms,
'rms_filter_j1to3': rms_filter_j1to3,
'W_res_filt': W_res_filt,
}
def compute_mfg_metrics(coeffs):
"""Manufacturing aberration magnitudes from Zernike coefficients.
Noll indexing (1-based): J1=Piston, J2=TiltX, J3=TiltY, J4=Defocus,
J5=Astig45, J6=Astig0, J7=ComaX, J8=ComaY, J9=TrefoilX, J10=TrefoilY, J11=Spherical
Python 0-indexed: coeffs[0]=J1, coeffs[3]=J4, etc.
"""
# Individual mode magnitudes (RSS for paired modes)
defocus = float(abs(coeffs[3])) # J4
astigmatism = float(np.sqrt(coeffs[4]**2 + coeffs[5]**2)) # RSS(J5, J6)
coma = float(np.sqrt(coeffs[6]**2 + coeffs[7]**2)) # RSS(J7, J8)
trefoil = float(np.sqrt(coeffs[8]**2 + coeffs[9]**2)) # RSS(J9, J10)
spherical = float(abs(coeffs[10])) if len(coeffs) > 10 else 0.0 # J11
# RMS of higher-order terms (J4+): sqrt(sum of squares of coefficients)
# This is the proper Zernike-coefficient-based RMS excluding piston/tip/tilt
higher_order_rms = float(np.sqrt(np.sum(coeffs[3:]**2)))
return {
'defocus_nm': defocus,
'astigmatism_rms': astigmatism,
'coma_rms': coma,
'trefoil_rms': trefoil,
'spherical_nm': spherical,
'higher_order_rms': higher_order_rms, # RMS of all J4+ coefficients
}
# ============================================================================
# HTML Generation
# ============================================================================
def generate_html(
title: str,
X: np.ndarray,
Y: np.ndarray,
W_nm: np.ndarray,
rms_data: dict,
is_relative: bool = False,
ref_title: str = "20 deg",
abs_pair: tuple = None,
is_manufacturing: bool = False,
mfg_metrics: dict = None,
correction_metrics: dict = None,
) -> str:
"""Generate complete HTML for Zernike visualization."""
coeffs = rms_data['coefficients']
global_rms = rms_data['global_rms']
filtered_rms = rms_data['filtered_rms']
W_res_filt = rms_data['W_res_filt']
labels = [zernike_label_for_j(j) for j in range(1, N_MODES+1)]
coeff_abs = np.abs(coeffs)
# Downsample for display
n = len(X)
if n > PLOT_DOWNSAMPLE:
rng = np.random.default_rng(42)
sel = rng.choice(n, size=PLOT_DOWNSAMPLE, replace=False)
Xp, Yp, Wp = X[sel], Y[sel], W_res_filt[sel]
else:
Xp, Yp, Wp = X, Y, W_res_filt
res_amp = AMP * Wp
max_amp = float(np.max(np.abs(res_amp))) if res_amp.size else 1.0
# Triangulate for smooth mesh surface
mesh_traces = []
try:
tri = Triangulation(Xp, Yp)
if tri.triangles is not None and len(tri.triangles) > 0:
i, j, k = tri.triangles.T
# Create smooth shaded mesh with lighting
mesh_traces.append(go.Mesh3d(
x=Xp, y=Yp, z=res_amp,
i=i, j=j, k=k,
intensity=res_amp,
colorscale=COLORSCALE,
opacity=1.0,
flatshading=False, # Smooth shading (interpolated normals)
lighting=dict(
ambient=0.4,
diffuse=0.8,
specular=0.3,
roughness=0.5,
fresnel=0.2
),
lightposition=dict(x=100, y=200, z=300),
showscale=True,
colorbar=dict(
title=dict(text="Residual (nm)", side="right"),
thickness=15,
len=0.6,
tickformat=".1f"
),
hovertemplate="X: %{x:.1f}<br>Y: %{y:.1f}<br>Residual: %{z:.2f} nm<extra></extra>"
))
except Exception as e:
print(f"Triangulation warning: {e}")
# Fallback scatter only if mesh failed
if not mesh_traces:
mesh_traces.append(go.Scatter3d(
x=Xp, y=Yp, z=res_amp,
mode='markers',
marker=dict(size=2, color=res_amp, colorscale=COLORSCALE, showscale=True),
showlegend=False
))
title_suffix = f" (relative to {ref_title})" if is_relative else " (absolute)"
# Build figure layout based on content type
if is_manufacturing and mfg_metrics and correction_metrics:
# Manufacturing page: 5 rows
fig = make_subplots(
rows=5, cols=1,
specs=[[{"type":"scene"}],
[{"type":"table"}],
[{"type":"table"}],
[{"type":"table"}],
[{"type":"xy"}]],
row_heights=[0.38, 0.12, 0.12, 0.18, 0.20],
vertical_spacing=0.025,
subplot_titles=[
f"<b>Surface Residual - {title}{title_suffix}</b>",
"<b>RMS Metrics (Absolute 90 deg)</b>",
"<b>Mode Magnitudes at 90 deg</b>",
"<b>Pre-Correction (90 deg - 20 deg)</b>",
"<b>|Zernike Coefficients| (nm)</b>"
]
)
elif SHOW_ZERNIKE_BAR:
# Standard page with bar chart: 4 rows
fig = make_subplots(
rows=4, cols=1,
specs=[[{"type":"scene"}],
[{"type":"table"}],
[{"type":"table"}],
[{"type":"xy"}]],
row_heights=[0.45, 0.12, 0.25, 0.18],
vertical_spacing=0.03,
subplot_titles=[
f"<b>Surface Residual - {title}{title_suffix}</b>",
"<b>RMS Metrics</b>",
f"<b>Zernike Coefficients ({N_MODES} modes)</b>",
"<b>|Zernike Coefficients| (nm)</b>"
]
)
else:
# Standard page without bar: 3 rows
fig = make_subplots(
rows=3, cols=1,
specs=[[{"type":"scene"}],
[{"type":"table"}],
[{"type":"table"}]],
row_heights=[0.55, 0.15, 0.30],
vertical_spacing=0.03,
subplot_titles=[
f"<b>Surface Residual - {title}{title_suffix}</b>",
"<b>RMS Metrics</b>",
f"<b>Zernike Coefficients ({N_MODES} modes)</b>"
]
)
# Add 3D mesh traces
for tr in mesh_traces:
fig.add_trace(tr, row=1, col=1)
# Configure 3D scene with better camera angle and proportional axes
fig.update_scenes(
camera=dict(
eye=dict(x=1.2, y=1.2, z=0.8), # Angled view from above
up=dict(x=0, y=0, z=1)
),
xaxis=dict(
title="X (mm)",
showgrid=True,
gridcolor='rgba(128,128,128,0.3)',
showbackground=True,
backgroundcolor='rgba(240,240,240,0.9)'
),
yaxis=dict(
title="Y (mm)",
showgrid=True,
gridcolor='rgba(128,128,128,0.3)',
showbackground=True,
backgroundcolor='rgba(240,240,240,0.9)'
),
zaxis=dict(
title="Residual (nm)",
range=[-max_amp * PANCAKE, max_amp * PANCAKE],
showgrid=True,
gridcolor='rgba(128,128,128,0.3)',
showbackground=True,
backgroundcolor='rgba(230,230,250,0.9)'
),
aspectmode='manual',
aspectratio=dict(x=1, y=1, z=0.4) # Flatten Z for better visualization
)
# RMS table (row 2)
if is_relative and abs_pair:
abs_global, abs_filtered = abs_pair
fig.add_trace(go.Table(
header=dict(values=["<b>Metric</b>", "<b>Relative (nm)</b>", "<b>Absolute (nm)</b>"],
align="left", fill_color='#1f2937', font=dict(color='white')),
cells=dict(values=[
["Global RMS", "Filtered RMS (J1-J4 removed)"],
[f"{global_rms:.2f}", f"{filtered_rms:.2f}"],
[f"{abs_global:.2f}", f"{abs_filtered:.2f}"],
], align="left", fill_color='#374151', font=dict(color='white'))
), row=2, col=1)
elif is_manufacturing and mfg_metrics and correction_metrics:
# 90 deg absolute RMS
fig.add_trace(go.Table(
header=dict(values=["<b>Metric</b>", "<b>Value (nm)</b>"],
align="left", fill_color='#1f2937', font=dict(color='white')),
cells=dict(values=[
["Global RMS", "Filtered RMS (J1-J4)"],
[f"{global_rms:.2f}", f"{filtered_rms:.2f}"]
], align="left", fill_color='#374151', font=dict(color='white'))
), row=2, col=1)
# Mode magnitudes (row 3) - MFG_90 objective (relative 90-20, J1-J3 filtered)
fig.add_trace(go.Table(
header=dict(values=["<b>Mode</b>", "<b>Value (nm)</b>"],
align="left", fill_color='#1f2937', font=dict(color='white')),
cells=dict(values=[
["MFG_90 Objective (90-20, J1-J3 filtered)",
"Astigmatism (J5+J6)",
"Coma (J7+J8)",
"Trefoil (J9+J10)",
"Spherical (J11)"],
[f"{rms_data['rms_filter_j1to3']:.2f}",
f"{mfg_metrics['astigmatism_rms']:.2f}",
f"{mfg_metrics['coma_rms']:.2f}",
f"{mfg_metrics['trefoil_rms']:.2f}",
f"{mfg_metrics['spherical_nm']:.2f}"]
], align="left", fill_color='#374151', font=dict(color='white'))
), row=3, col=1)
# Pre-correction (row 4) - Aberrations to polish out (90° - 20°)
# Shows what correction is needed when manufacturing at 90° to achieve 20° figure
fig.add_trace(go.Table(
header=dict(values=["<b>Aberration</b>", "<b>Magnitude (nm)</b>"],
align="left", fill_color='#1f2937', font=dict(color='white')),
cells=dict(values=[
["Defocus (J4)",
"Astigmatism (J5+J6)",
"Coma (J7+J8)",
"Trefoil (J9+J10)",
"Spherical (J11)"],
[f"{correction_metrics['defocus_nm']:.2f}",
f"{correction_metrics['astigmatism_rms']:.2f}",
f"{correction_metrics['coma_rms']:.2f}",
f"{correction_metrics['trefoil_rms']:.2f}",
f"{correction_metrics['spherical_nm']:.2f}"]
], align="left", fill_color='#374151', font=dict(color='white'))
), row=4, col=1)
else:
# Standard absolute table
fig.add_trace(go.Table(
header=dict(values=["<b>Metric</b>", "<b>Value (nm)</b>"],
align="left", fill_color='#1f2937', font=dict(color='white')),
cells=dict(values=[
["Global RMS", "Filtered RMS (J1-J4 removed)"],
[f"{global_rms:.2f}", f"{filtered_rms:.2f}"]
], align="left", fill_color='#374151', font=dict(color='white'))
), row=2, col=1)
# Zernike coefficients table (row 3 or skip if manufacturing)
if not (is_manufacturing and mfg_metrics and correction_metrics):
fig.add_trace(go.Table(
header=dict(values=["<b>Noll j</b>", "<b>Label</b>", "<b>|Coeff| (nm)</b>"],
align="left", fill_color='#1f2937', font=dict(color='white')),
cells=dict(values=[
list(range(1, N_MODES+1)),
labels,
[f"{c:.3f}" for c in coeff_abs]
], align="left", fill_color='#374151', font=dict(color='white'))
), row=3, col=1)
# Bar chart (last row)
if SHOW_ZERNIKE_BAR:
bar_row = 5 if (is_manufacturing and mfg_metrics and correction_metrics) else 4
fig.add_trace(
go.Bar(
x=coeff_abs.tolist(),
y=labels,
orientation='h',
marker_color='#6366f1',
hovertemplate="%{y}<br>|Coeff| = %{x:.3f} nm<extra></extra>",
showlegend=False
),
row=bar_row, col=1
)
# Layout
height = 1500 if (is_manufacturing and mfg_metrics and correction_metrics) else 1300
fig.update_layout(
width=1400,
height=height,
margin=dict(t=60, b=20, l=20, r=20),
paper_bgcolor='#111827',
plot_bgcolor='#1f2937',
font=dict(color='white'),
title=dict(
text=f"<b>Atomizer Zernike Analysis - {title}</b>",
x=0.5,
font=dict(size=18)
)
)
return fig.to_html(include_plotlyjs='cdn', full_html=True)
# ============================================================================
# Main
# ============================================================================
def find_op2_file(working_dir=None):
"""Find the most recent OP2 file in the working directory."""
if working_dir is None:
working_dir = Path.cwd()
else:
working_dir = Path(working_dir)
op2_files = list(working_dir.glob("*solution*.op2")) + list(working_dir.glob("*.op2"))
if not op2_files:
op2_files = list(working_dir.glob("**/*solution*.op2"))
if not op2_files:
return None
return max(op2_files, key=lambda p: p.stat().st_mtime)
def main_opd(op2_path: Path):
"""Generate all 3 HTML files using rigorous OPD method."""
print("=" * 70)
print(" ATOMIZER ZERNIKE HTML GENERATOR (OPD METHOD)")
print("=" * 70)
print(f"\nOP2 File: {op2_path.name}")
print(f"Directory: {op2_path.parent}")
print("\n[INFO] Using OPD method: accounts for lateral (X,Y) displacement")
# Initialize extractor
extractor = ZernikeOPDExtractor(
op2_path,
displacement_unit='mm',
n_modes=N_MODES,
filter_orders=FILTER_LOW_ORDERS
)
print(f"\nAvailable subcases: {list(extractor.displacements.keys())}")
# Map subcases - find required angles by name (robust to extra subcases)
displacements = extractor.displacements
required_angles = ['90', '20', '40', '60']
subcase_map = {}
# First, try direct angle matching (e.g., "20", "40", "60", "90")
for angle in required_angles:
if angle in displacements:
subcase_map[angle] = angle
# If we didn't find all angles, try numeric IDs (e.g., "1"=90, "2"=20, "3"=40, "4"=60)
if len(subcase_map) < 4:
if all(str(i) in displacements for i in range(1, 5)):
subcase_map = {'90': '1', '20': '2', '40': '3', '60': '4'}
print(f"[INFO] Using numeric subcases: 1=90°, 2=20°, 3=40°, 4=60°")
# Check if we found all required angles
if len(subcase_map) < 4:
missing = [a for a in required_angles if a not in subcase_map]
print(f"[ERROR] Missing required subcases: {missing}")
print(f"[ERROR] Available subcases: {list(displacements.keys())}")
print(f"[ERROR] Required subcases must be named: {required_angles} (or numeric 1,2,3,4)")
return
print(f"[INFO] Using subcase mapping: {subcase_map}")
output_dir = op2_path.parent
base = op2_path.stem
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
html_files = []
# ========================================================================
# Extract absolute metrics for each subcase
# ========================================================================
print("\nExtracting absolute metrics (OPD method)...")
results_abs = {}
for angle, label in subcase_map.items():
result = extractor.extract_subcase(label, include_coefficients=True)
results_abs[angle] = result
lat_disp = result.get('max_lateral_displacement_um', 0)
print(f" {angle} deg: Filtered RMS = {result['filtered_rms_nm']:.2f} nm, "
f"Lateral disp max = {lat_disp:.3f} um")
# ========================================================================
# Extract relative metrics (40-20, 60-20, 90-20)
# ========================================================================
print("\nExtracting relative metrics (OPD method)...")
# 40 vs 20
result_40_rel = extractor.extract_relative(subcase_map['40'], subcase_map['20'], include_coefficients=True)
print(f" 40-20: Relative Filtered RMS = {result_40_rel['relative_filtered_rms_nm']:.2f} nm")
# 60 vs 20
result_60_rel = extractor.extract_relative(subcase_map['60'], subcase_map['20'], include_coefficients=True)
print(f" 60-20: Relative Filtered RMS = {result_60_rel['relative_filtered_rms_nm']:.2f} nm")
# 90 vs 20 (for correction metrics)
result_90_rel = extractor.extract_relative(subcase_map['90'], subcase_map['20'], include_coefficients=True)
print(f" 90-20: Relative Filtered RMS = {result_90_rel['relative_filtered_rms_nm']:.2f} nm")
# ========================================================================
# Generate HTML files
# ========================================================================
# Helper to convert OPD results to the format expected by generate_html
def opd_to_rms_data(result, is_relative=False):
"""Convert OPD extractor result to rms_data dict for generate_html."""
coeffs = np.array(result.get('coefficients', [0] * N_MODES))
# Recompute filtered residuals for visualization
# For now, use simplified approach - the metrics are correct
filtered_rms = result.get('relative_filtered_rms_nm' if is_relative else 'filtered_rms_nm', 0)
global_rms = result.get('relative_global_rms_nm' if is_relative else 'global_rms_nm', 0)
rms_j1to3 = result.get('relative_rms_filter_j1to3' if is_relative else 'rms_filter_j1to3_nm', 0)
# We need W_res_filt for visualization - extract from diagnostic data
# For now, create a placeholder that will be updated
return {
'coefficients': coeffs,
'R': 1.0, # Will be updated
'global_rms': global_rms,
'filtered_rms': filtered_rms,
'rms_filter_j1to3': rms_j1to3,
'W_res_filt': None, # Will compute separately for visualization
}
# For visualization, we need the actual WFE arrays
# Get diagnostic data from extractor
print("\nGenerating HTML reports...")
# 40 vs 20
print(" Generating 40 deg vs 20 deg...")
opd_40 = extractor._build_figure_opd_data(subcase_map['40'])
opd_20 = extractor._build_figure_opd_data(subcase_map['20'])
# Build relative WFE arrays
ref_wfe_map = {int(nid): wfe for nid, wfe in zip(opd_20['node_ids'], opd_20['wfe_nm'])}
X_40_rel, Y_40_rel, WFE_40_rel = [], [], []
for i, nid in enumerate(opd_40['node_ids']):
nid = int(nid)
if nid in ref_wfe_map:
X_40_rel.append(opd_40['x_deformed'][i])
Y_40_rel.append(opd_40['y_deformed'][i])
WFE_40_rel.append(opd_40['wfe_nm'][i] - ref_wfe_map[nid])
X_40_rel = np.array(X_40_rel)
Y_40_rel = np.array(Y_40_rel)
WFE_40_rel = np.array(WFE_40_rel)
rms_40_rel = compute_rms_metrics(X_40_rel, Y_40_rel, WFE_40_rel)
rms_40_abs = compute_rms_metrics(opd_40['x_deformed'], opd_40['y_deformed'], opd_40['wfe_nm'])
html_40 = generate_html(
title="40 deg (OPD)",
X=X_40_rel, Y=Y_40_rel, W_nm=WFE_40_rel,
rms_data=rms_40_rel,
is_relative=True,
ref_title="20 deg",
abs_pair=(rms_40_abs['global_rms'], rms_40_abs['filtered_rms'])
)
path_40 = output_dir / f"{base}_{timestamp}_40_vs_20.html"
path_40.write_text(html_40, encoding='utf-8')
html_files.append(path_40)
print(f" Created: {path_40.name}")
# 60 vs 20
print(" Generating 60 deg vs 20 deg...")
opd_60 = extractor._build_figure_opd_data(subcase_map['60'])
X_60_rel, Y_60_rel, WFE_60_rel = [], [], []
for i, nid in enumerate(opd_60['node_ids']):
nid = int(nid)
if nid in ref_wfe_map:
X_60_rel.append(opd_60['x_deformed'][i])
Y_60_rel.append(opd_60['y_deformed'][i])
WFE_60_rel.append(opd_60['wfe_nm'][i] - ref_wfe_map[nid])
X_60_rel = np.array(X_60_rel)
Y_60_rel = np.array(Y_60_rel)
WFE_60_rel = np.array(WFE_60_rel)
rms_60_rel = compute_rms_metrics(X_60_rel, Y_60_rel, WFE_60_rel)
rms_60_abs = compute_rms_metrics(opd_60['x_deformed'], opd_60['y_deformed'], opd_60['wfe_nm'])
html_60 = generate_html(
title="60 deg (OPD)",
X=X_60_rel, Y=Y_60_rel, W_nm=WFE_60_rel,
rms_data=rms_60_rel,
is_relative=True,
ref_title="20 deg",
abs_pair=(rms_60_abs['global_rms'], rms_60_abs['filtered_rms'])
)
path_60 = output_dir / f"{base}_{timestamp}_60_vs_20.html"
path_60.write_text(html_60, encoding='utf-8')
html_files.append(path_60)
print(f" Created: {path_60.name}")
# 90 deg Manufacturing
print(" Generating 90 deg Manufacturing...")
opd_90 = extractor._build_figure_opd_data(subcase_map['90'])
rms_90 = compute_rms_metrics(opd_90['x_deformed'], opd_90['y_deformed'], opd_90['wfe_nm'])
mfg_metrics = compute_mfg_metrics(rms_90['coefficients'])
# 90-20 relative for correction metrics
X_90_rel, Y_90_rel, WFE_90_rel = [], [], []
for i, nid in enumerate(opd_90['node_ids']):
nid = int(nid)
if nid in ref_wfe_map:
X_90_rel.append(opd_90['x_deformed'][i])
Y_90_rel.append(opd_90['y_deformed'][i])
WFE_90_rel.append(opd_90['wfe_nm'][i] - ref_wfe_map[nid])
X_90_rel = np.array(X_90_rel)
Y_90_rel = np.array(Y_90_rel)
WFE_90_rel = np.array(WFE_90_rel)
rms_90_rel = compute_rms_metrics(X_90_rel, Y_90_rel, WFE_90_rel)
# Get all correction metrics from Zernike coefficients (90° - 20°)
correction_metrics = compute_mfg_metrics(rms_90_rel['coefficients'])
html_90 = generate_html(
title="90 deg Manufacturing (OPD)",
X=opd_90['x_deformed'], Y=opd_90['y_deformed'], W_nm=opd_90['wfe_nm'],
rms_data=rms_90_rel, # Use RELATIVE (90-20) for mfg_90 objective match
is_relative=False,
is_manufacturing=True,
mfg_metrics=mfg_metrics,
correction_metrics=correction_metrics
)
path_90 = output_dir / f"{base}_{timestamp}_90_mfg.html"
path_90.write_text(html_90, encoding='utf-8')
html_files.append(path_90)
print(f" Created: {path_90.name}")
# ========================================================================
# Summary
# ========================================================================
print("\n" + "=" * 70)
print("SUMMARY (OPD Method)")
print("=" * 70)
print(f"\nGenerated {len(html_files)} HTML files:")
for f in html_files:
print(f" - {f.name}")
print("\n" + "-" * 70)
print("OPTIMIZATION OBJECTIVES (OPD Method)")
print("-" * 70)
print(f" 40-20 Filtered RMS: {rms_40_rel['filtered_rms']:.2f} nm")
print(f" 60-20 Filtered RMS: {rms_60_rel['filtered_rms']:.2f} nm")
print(f" MFG 90 (J1-J3): {rms_90_rel['rms_filter_j1to3']:.2f} nm")
# Weighted sums
ws_v4 = 5*rms_40_rel['filtered_rms'] + 5*rms_60_rel['filtered_rms'] + 2*rms_90_rel['rms_filter_j1to3']
ws_v5 = 5*rms_40_rel['filtered_rms'] + 5*rms_60_rel['filtered_rms'] + 3*rms_90_rel['rms_filter_j1to3']
print(f"\n V4 Weighted Sum (5/5/2): {ws_v4:.2f}")
print(f" V5 Weighted Sum (5/5/3): {ws_v5:.2f}")
# Lateral displacement summary
print("\n" + "-" * 70)
print("LATERAL DISPLACEMENT SUMMARY")
print("-" * 70)
for angle in ['20', '40', '60', '90']:
lat = results_abs[angle].get('max_lateral_displacement_um', 0)
print(f" {angle} deg: max {lat:.3f} um")
print("\n" + "=" * 70)
print("DONE")
print("=" * 70)
return html_files
def main(op2_path: Path):
"""Generate all 3 HTML files (legacy Z-only method)."""
print("=" * 70)
print(" ATOMIZER ZERNIKE HTML GENERATOR")
print("=" * 70)
print(f"\nOP2 File: {op2_path.name}")
print(f"Directory: {op2_path.parent}")
# Find geometry
print("\nFinding geometry file...")
geo_path = find_geometry_file(op2_path)
print(f"Found: {geo_path.name}")
# Read data
print("\nReading geometry...")
node_geo = read_geometry(geo_path)
print(f"Loaded {len(node_geo)} nodes")
print("\nReading displacements...")
displacements = read_displacements(op2_path)
print(f"Found subcases: {list(displacements.keys())}")
# Map subcases - find required angles by name (robust to extra subcases)
required_angles = ['90', '20', '40', '60']
subcase_map = {}
# First, try direct angle matching (e.g., "20", "40", "60", "90")
for angle in required_angles:
if angle in displacements:
subcase_map[angle] = angle
# If we didn't find all angles, try numeric IDs (e.g., "1"=90, "2"=20, "3"=40, "4"=60)
if len(subcase_map) < 4:
if all(str(i) in displacements for i in range(1, 5)):
subcase_map = {'90': '1', '20': '2', '40': '3', '60': '4'}
print(f"[INFO] Using numeric subcases: 1=90°, 2=20°, 3=40°, 4=60°")
# Check if we found all required angles
if len(subcase_map) < 4:
missing = [a for a in required_angles if a not in subcase_map]
print(f"[ERROR] Missing required subcases: {missing}")
print(f"[ERROR] Available subcases: {list(displacements.keys())}")
print(f"[ERROR] Required subcases must be named: {required_angles} (or numeric 1,2,3,4)")
return
print(f"[INFO] Using subcase mapping: {subcase_map}")
# Check all required subcases exist
for angle, label in subcase_map.items():
if label not in displacements:
print(f"[ERROR] Subcase '{label}' (angle {angle}) not found")
return
output_dir = op2_path.parent
base = op2_path.stem
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
html_files = []
# ========================================================================
# Build WFE arrays for reference (20 deg) and manufacturing (90 deg)
# ========================================================================
print("\nProcessing subcases...")
# Reference: 20 deg
ref_label = subcase_map['20']
ref_data = displacements[ref_label]
X_ref, Y_ref, WFE_ref = build_wfe_arrays(
'20', ref_data['node_ids'], ref_data['disp'], node_geo
)
rms_ref = compute_rms_metrics(X_ref, Y_ref, WFE_ref)
print(f" 20 deg: Global RMS = {rms_ref['global_rms']:.2f} nm, Filtered = {rms_ref['filtered_rms']:.2f} nm")
# Manufacturing: 90 deg
mfg_label = subcase_map['90']
mfg_data = displacements[mfg_label]
X_90, Y_90, WFE_90 = build_wfe_arrays(
'90', mfg_data['node_ids'], mfg_data['disp'], node_geo
)
rms_90 = compute_rms_metrics(X_90, Y_90, WFE_90)
mfg_metrics = compute_mfg_metrics(rms_90['coefficients'])
print(f" 90 deg: Global RMS = {rms_90['global_rms']:.2f} nm, Filtered = {rms_90['filtered_rms']:.2f} nm")
# ========================================================================
# 1. Generate 40 deg vs 20 deg (relative)
# ========================================================================
print("\nGenerating 40 deg vs 20 deg...")
sc_40_label = subcase_map['40']
sc_40_data = displacements[sc_40_label]
X_40, Y_40, WFE_40 = build_wfe_arrays(
'40', sc_40_data['node_ids'], sc_40_data['disp'], node_geo
)
X_40_rel, Y_40_rel, WFE_40_rel = compute_relative_wfe(
X_40, Y_40, WFE_40, sc_40_data['node_ids'],
X_ref, Y_ref, WFE_ref, ref_data['node_ids']
)
rms_40_abs = compute_rms_metrics(X_40, Y_40, WFE_40)
rms_40_rel = compute_rms_metrics(X_40_rel, Y_40_rel, WFE_40_rel)
html_40 = generate_html(
title="40 deg",
X=X_40_rel, Y=Y_40_rel, W_nm=WFE_40_rel,
rms_data=rms_40_rel,
is_relative=True,
ref_title="20 deg",
abs_pair=(rms_40_abs['global_rms'], rms_40_abs['filtered_rms'])
)
path_40 = output_dir / f"{base}_{timestamp}_40_vs_20.html"
path_40.write_text(html_40, encoding='utf-8')
html_files.append(path_40)
print(f" Created: {path_40.name}")
print(f" Relative: Global={rms_40_rel['global_rms']:.2f}, Filtered={rms_40_rel['filtered_rms']:.2f}")
# ========================================================================
# 2. Generate 60 deg vs 20 deg (relative)
# ========================================================================
print("\nGenerating 60 deg vs 20 deg...")
sc_60_label = subcase_map['60']
sc_60_data = displacements[sc_60_label]
X_60, Y_60, WFE_60 = build_wfe_arrays(
'60', sc_60_data['node_ids'], sc_60_data['disp'], node_geo
)
X_60_rel, Y_60_rel, WFE_60_rel = compute_relative_wfe(
X_60, Y_60, WFE_60, sc_60_data['node_ids'],
X_ref, Y_ref, WFE_ref, ref_data['node_ids']
)
rms_60_abs = compute_rms_metrics(X_60, Y_60, WFE_60)
rms_60_rel = compute_rms_metrics(X_60_rel, Y_60_rel, WFE_60_rel)
html_60 = generate_html(
title="60 deg",
X=X_60_rel, Y=Y_60_rel, W_nm=WFE_60_rel,
rms_data=rms_60_rel,
is_relative=True,
ref_title="20 deg",
abs_pair=(rms_60_abs['global_rms'], rms_60_abs['filtered_rms'])
)
path_60 = output_dir / f"{base}_{timestamp}_60_vs_20.html"
path_60.write_text(html_60, encoding='utf-8')
html_files.append(path_60)
print(f" Created: {path_60.name}")
print(f" Relative: Global={rms_60_rel['global_rms']:.2f}, Filtered={rms_60_rel['filtered_rms']:.2f}")
# ========================================================================
# 3. Generate 90 deg Manufacturing (absolute with correction metrics)
# ========================================================================
print("\nGenerating 90 deg Manufacturing...")
# Compute 90 deg - 20 deg for correction metrics
X_90_rel, Y_90_rel, WFE_90_rel = compute_relative_wfe(
X_90, Y_90, WFE_90, mfg_data['node_ids'],
X_ref, Y_ref, WFE_ref, ref_data['node_ids']
)
rms_90_rel = compute_rms_metrics(X_90_rel, Y_90_rel, WFE_90_rel)
# Get all correction metrics from Zernike coefficients (90° - 20°)
correction_metrics = compute_mfg_metrics(rms_90_rel['coefficients'])
html_90 = generate_html(
title="90 deg (Manufacturing)",
X=X_90, Y=Y_90, W_nm=WFE_90,
rms_data=rms_90_rel, # Use RELATIVE (90-20) for mfg_90 objective match
is_relative=False,
is_manufacturing=True,
mfg_metrics=mfg_metrics,
correction_metrics=correction_metrics
)
path_90 = output_dir / f"{base}_{timestamp}_90_mfg.html"
path_90.write_text(html_90, encoding='utf-8')
html_files.append(path_90)
print(f" Created: {path_90.name}")
print(f" Absolute: Global={rms_90['global_rms']:.2f}, Filtered={rms_90['filtered_rms']:.2f}")
print(f" Optician Workload (J1-J3): {rms_90['rms_filter_j1to3']:.2f} nm")
# ========================================================================
# Summary
# ========================================================================
print("\n" + "=" * 70)
print("SUMMARY")
print("=" * 70)
print(f"\nGenerated {len(html_files)} HTML files:")
for f in html_files:
print(f" - {f.name}")
print("\n" + "-" * 70)
print("OPTIMIZATION OBJECTIVES")
print("-" * 70)
print(f" 40-20 Filtered RMS: {rms_40_rel['filtered_rms']:.2f} nm")
print(f" 60-20 Filtered RMS: {rms_60_rel['filtered_rms']:.2f} nm")
print(f" MFG 90 (J1-J3): {rms_90_rel['rms_filter_j1to3']:.2f} nm")
# Weighted sums
ws_v4 = 5*rms_40_rel['filtered_rms'] + 5*rms_60_rel['filtered_rms'] + 2*rms_90_rel['rms_filter_j1to3']
ws_v5 = 5*rms_40_rel['filtered_rms'] + 5*rms_60_rel['filtered_rms'] + 3*rms_90_rel['rms_filter_j1to3']
print(f"\n V4 Weighted Sum (5/5/2): {ws_v4:.2f}")
print(f" V5 Weighted Sum (5/5/3): {ws_v5:.2f}")
print("\n" + "=" * 70)
print("DONE")
print("=" * 70)
return html_files
if __name__ == '__main__':
if len(sys.argv) > 1:
op2_path = Path(sys.argv[1])
if not op2_path.exists():
print(f"ERROR: File not found: {op2_path}")
sys.exit(1)
else:
print("No OP2 file specified, searching...")
op2_path = find_op2_file()
if op2_path is None:
print("ERROR: No OP2 file found in current directory.")
print("Usage: python zernike_html_generator.py <path/to/solution.op2>")
sys.exit(1)
print(f"Found: {op2_path}")
# Check for --legacy flag to use old Z-only method
use_legacy = '--legacy' in sys.argv or '--z-only' in sys.argv
try:
if USE_OPD_METHOD and not use_legacy:
main_opd(op2_path)
else:
if use_legacy:
print("[INFO] Using legacy Z-only method (--legacy flag)")
main(op2_path)
except Exception as e:
print(f"\nERROR: {e}")
import traceback
traceback.print_exc()
sys.exit(1)
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