| import torch |
| import numpy as np |
| import plotly.graph_objects as go |
| from stl import mesh as stl_mesh |
| from matplotlib import cm |
|
|
|
|
| def _cm2px(cm, dpi): |
| return int(cm / 2.54 * dpi) |
|
|
| def _pt2px(pt, dpi): |
| return int(pt / 72 * dpi) |
|
|
| def _rgb_colorscale(cmap_name): |
| cmap = cm.get_cmap(cmap_name) if isinstance(cmap_name, str) else cmap_name |
| return [[i / 255, "rgb({},{},{})".format(*[int(c * 255) for c in cmap(i / 255)[:3]])] for i in range(256)] |
|
|
| def _alpha_colorscale(cmap_name, a_min, a_max): |
| cmap = cm.get_cmap(cmap_name) if isinstance(cmap_name, str) else cmap_name |
| scale = [] |
| for i in range(256): |
| t = i / 255 |
| r, g, b, _ = cmap(t) |
| a = a_min + (a_max - a_min) * t ** 5 |
| scale.append([t, f"rgba({int(r*255)},{int(g*255)},{int(b*255)},{a:.3f})"]) |
| return scale |
|
|
|
|
| def plot_2d( |
| data, heatmap_width_cm=2., heatmap_height_cm=2., dpi=300, scale=1.0, |
| use_colorbar=True, colorbar_thickness=24, text_font_size=7, |
| ticklabel_font_size=5, show_x_ticks=True, show_x_ticklabels=True, |
| show_y_ticks=True, show_y_ticklabels=True, x_unit=0.004, y_unit=0.004, |
| x_ticks=[0, 250, 500], y_ticks=[0, 250, 500], boundary_linewidth=1, |
| tick_width=1, x_label='x [μm]', y_label='y [μm]', cmap="Jet", |
| ticklen=16, colorbar_min=None, colorbar_max=None, outer_margin_cm=0.2, |
| colorbar_title=None, |
| ): |
| is_grid = data.ndim == 4 and data.shape[:2] == (2, 2) |
| panels = data if is_grid else data[np.newaxis, np.newaxis] |
| rows, cols = (2, 2) if is_grid else (1, 1) |
|
|
| def cm2px(v): return v / 2.54 * dpi |
|
|
| N = panels[0, 0].shape[0] |
| if N > 1000: |
| x_ticks = [0, 500, 1000]; y_ticks = [0, 500, 1000] |
| heatmap_width_cm *= 2; heatmap_height_cm *= 2 |
| colorbar_thickness *= 2 |
|
|
| data_w = cm2px(heatmap_width_cm) |
| data_h = cm2px(heatmap_height_cm) |
| text_px = int(text_font_size / 72 * dpi * scale) |
| tick_px = int(ticklabel_font_size / 72 * dpi * scale) |
| pad = int(5 * scale) |
| gap = pad * 5 |
| outer = cm2px(outer_margin_cm) |
| cb_gap = pad * 4 |
| cb_tick_w = tick_px * 8 |
|
|
| ml = outer + boundary_linewidth + show_y_ticks * ticklen + show_y_ticklabels * tick_px + (1 if y_label else 0) * text_px + pad |
| mr = outer + boundary_linewidth + pad + use_colorbar * (cb_gap + colorbar_thickness + cb_tick_w) |
| mb = outer + boundary_linewidth + show_x_ticks * ticklen + show_x_ticklabels * tick_px + (1 if x_label else 0) * text_px * 3 + pad |
| mt = outer + boundary_linewidth + pad |
|
|
| fig_w = ml + mr + cols * data_w + (cols - 1) * gap |
| fig_h = mt + mb + rows * data_h + (rows - 1) * gap |
| grid_y0 = mb / fig_h |
| grid_y1 = (mb + rows * data_h + (rows - 1) * gap) / fig_h |
|
|
| vmin = float(colorbar_min if colorbar_min is not None else min(panels[r, c].min() for r in range(rows) for c in range(cols))) |
| vmax = float(colorbar_max if colorbar_max is not None else max(panels[r, c].max() for r in range(rows) for c in range(cols))) |
|
|
| border = dict(showline=True, linecolor='lightgray', linewidth=boundary_linewidth, mirror=True, fixedrange=True) |
|
|
| def xname(i): return 'x' if i == 0 else f'x{i+1}' |
| def yname(i): return 'y' if i == 0 else f'y{i+1}' |
|
|
| def make_xaxis(domain, anchor, is_bottom): |
| ax = dict(domain=domain, anchor=anchor, **border) |
| if is_bottom: |
| ax.update( |
| ticks='outside' if show_x_ticks else '', ticklen=ticklen, tickwidth=tick_width, |
| tickcolor='black', tickfont=dict(size=tick_px, color='black'), |
| showticklabels=show_x_ticklabels, |
| title=dict(text=x_label or '', font=dict(size=text_px, color='black'), standoff=tick_px + ticklen), |
| tickmode='array', tickvals=x_ticks, ticktext=[f"{v * x_unit:.1f}" for v in x_ticks], |
| ) |
| else: |
| ax.update(ticks='', ticklen=0, showticklabels=False, title=dict(text=''), showgrid=False) |
| return ax |
|
|
| def make_yaxis(domain, anchor, is_left): |
| ax = dict(domain=domain, anchor=anchor, **border) |
| if is_left: |
| ax.update( |
| ticks='outside' if show_y_ticks else '', ticklen=ticklen, tickwidth=tick_width, |
| tickcolor='black', tickfont=dict(size=tick_px, color='black'), |
| showticklabels=show_y_ticklabels, |
| title=dict(text=y_label or '', font=dict(size=text_px, color='black'), standoff=tick_px + ticklen), |
| tickmode='array', tickvals=y_ticks, ticktext=[f"{v * y_unit:.1f}" for v in y_ticks], |
| ) |
| else: |
| ax.update(ticks='', ticklen=0, showticklabels=False, title=dict(text=''), showgrid=False) |
| return ax |
|
|
| fig = go.Figure() |
|
|
| for r in range(rows): |
| for c in range(cols): |
| idx = r * cols + c |
| x0 = (ml + c * (data_w + gap)) / fig_w |
| x1 = (ml + c * (data_w + gap) + data_w) / fig_w |
| y0 = (mb + (rows - 1 - r) * (data_h + gap)) / fig_h |
| y1 = (mb + (rows - 1 - r) * (data_h + gap) + data_h) / fig_h |
|
|
| fig.add_trace(go.Heatmap( |
| z=panels[r, c], colorscale=cmap, showscale=False, |
| zmin=vmin, zmax=vmax, xaxis=xname(idx), yaxis=yname(idx), |
| )) |
| fig.update_layout(**{ |
| f'xaxis{"" if idx == 0 else idx+1}': make_xaxis([x0, x1], anchor=yname(idx), is_bottom=(r == rows - 1)), |
| f'yaxis{"" if idx == 0 else idx+1}': make_yaxis([y0, y1], anchor=xname(idx), is_left=(c == 0)), |
| }) |
|
|
| if use_colorbar: |
| n_cb = 256 |
| cb_idx = rows * cols |
| cb_data = np.linspace(vmin, vmax, n_cb).reshape(n_cb, 1) |
| cb_x0 = (ml + cols * data_w + (cols - 1) * gap + cb_gap) / fig_w |
| cb_x1 = cb_x0 + colorbar_thickness / fig_w |
| cb_tickvals = np.linspace(0, n_cb - 1, 5) |
| cb_ticktext = [f"{v:.2f}" for v in np.linspace(vmin, vmax, 5)] |
|
|
| fig.add_trace(go.Heatmap( |
| z=cb_data, colorscale=cmap, showscale=False, |
| zmin=vmin, zmax=vmax, xaxis=xname(cb_idx), yaxis=yname(cb_idx), |
| )) |
| fig.update_layout(**{ |
| f'xaxis{"" if cb_idx == 0 else cb_idx+1}': dict( |
| domain=[cb_x0, cb_x1], anchor=yname(cb_idx), visible=False, fixedrange=True, |
| showline=True, linecolor='black', linewidth=boundary_linewidth, mirror=True, |
| ), |
| f'yaxis{"" if cb_idx == 0 else cb_idx+1}': dict( |
| domain=[grid_y0, grid_y1], anchor=xname(cb_idx), side='right', fixedrange=True, |
| tickmode='array', tickvals=cb_tickvals, ticktext=cb_ticktext, |
| tickfont=dict(size=tick_px, color='black'), tickcolor='black', |
| tickwidth=tick_width, ticklen=ticklen // 2, |
| showline=True, linecolor='black', linewidth=boundary_linewidth, |
| showgrid=False, mirror=False, |
| title=dict(text=colorbar_title or '', font=dict(size=text_px, color='black'), standoff=tick_px + ticklen // 2), |
| ), |
| }) |
|
|
| fig.update_layout( |
| autosize=False, width=int(fig_w), height=int(fig_h), |
| margin=dict(l=0, r=0, t=0, b=0), |
| paper_bgcolor='rgba(0,0,0,0)', plot_bgcolor='rgba(0,0,0,0)', |
| font=dict(family="Arial, sans-serif", size=text_px, color='black'), |
| ) |
| return fig |
|
|
|
|
| def vis_mask(data, cmap='gray'): |
| return plot_2d(torch.flip(data, dims=(0,)), cmap=cmap, use_colorbar=False) |
|
|
| def vis_sc(data, cmap='jet'): |
| return plot_2d(torch.flip(data, dims=(2,)), cmap=cmap, use_colorbar=True, colorbar_title='Amplitude [-]') |
|
|
|
|
| def plot_tensor_slices( |
| data, slice_indices=None, opacity=None, colorscale="jet", |
| vmin=None, vmax=None, alpha_at_cmin=0.1, alpha_at_cmax=1, |
| use_colorbar=True, colorbar_thickness=20, colorbar_title=None, |
| colorbar_title_side="right", use_dummy_colorbar=True, colorbar_length=0.6, |
| colorbar_font="Arial, sans-serif", colorbar_fontsize=7, colorbar_tick_fontsize=5, |
| colorbar_nticks=None, show_axes=True, isotropic_view=True, |
| camera_distance=1.5, fig_width_cm=6.0, fig_height_cm=4.0, dpi=300, png_path=None, |
| ): |
| if data.ndim != 3: |
| raise ValueError("`data` must be a 3-D array (Nx, Ny, Nz).") |
|
|
| N = data.shape[0] |
| sf = 2 if N >= 513 else 1 |
| s, e = N // 2 - 128 * sf, N // 2 + 128 * sf |
| data = data[s:e, s:e, :] |
| fig_width_cm *= sf; fig_height_cm *= sf |
| camera_distance /= sf |
| colorbar_thickness = int(colorbar_thickness * sf) |
|
|
| Nx, Ny, Nz = data.shape |
| ix, iy, iz = map(int, slice_indices) if slice_indices else (Nx // 2, Ny // 2, Nz // 2) |
| vmin = float(np.nanmin(data)) if vmin is None else float(vmin) |
| vmax = float(np.nanmax(data)) if vmax is None else float(vmax) |
|
|
| custom_scale = _alpha_colorscale(colorscale, alpha_at_cmin, alpha_at_cmax) |
| dummy_scale = _rgb_colorscale(colorscale) |
|
|
| x, y, z = np.arange(Nx), np.arange(Ny), np.arange(Nz) |
|
|
| def cb_cfg(): |
| cb = dict( |
| lenmode="fraction", len=colorbar_length, thickness=colorbar_thickness, |
| x=0.85, y=0.45, |
| tickfont=dict(family=colorbar_font, size=_pt2px(colorbar_tick_fontsize, dpi), color="black"), |
| tickwidth=1, tickcolor="black", outlinewidth=1, outlinecolor="black", |
| nticks=colorbar_nticks or 5, |
| ) |
| if colorbar_title is not None: |
| cb["title"] = dict( |
| text=colorbar_title, side=colorbar_title_side, |
| font=dict(family=colorbar_font, size=_pt2px(colorbar_fontsize, dpi), color="black"), |
| ) |
| return cb |
|
|
| surf_kw = dict( |
| colorscale=custom_scale, cmin=vmin, cmax=vmax, |
| lighting=dict(ambient=1.0), opacity=1.0 if opacity is None else opacity, |
| ) |
|
|
| surfaces = [] |
| for k_z in range(0, Nz, 4): |
| show_scale = use_colorbar and not use_dummy_colorbar and len(surfaces) == 0 |
| surfaces.append(go.Surface( |
| x=np.tile(x[:, None], (1, Ny)), y=np.tile(y[None, :], (Nx, 1)), |
| z=np.full((Nx, Ny), k_z), surfacecolor=data[:, :, k_z], |
| showscale=show_scale, colorbar=cb_cfg() if show_scale else None, |
| name=f"XY @ z={k_z}", **surf_kw, |
| )) |
|
|
| surfaces.append(go.Surface( |
| x=np.full((Ny, Nz), Nx - 1), y=np.tile(y[:, None], (1, Nz)), |
| z=np.tile(z[None, :], (Ny, 1)), surfacecolor=data[Nx - 1, :, :], |
| showscale=False, name=f"YZ @ x={Nx-1}", **surf_kw, |
| )) |
| surfaces.append(go.Surface( |
| x=np.tile(x[:, None], (1, Nz)), y=np.full((Nx, Nz), Ny - 1), |
| z=np.tile(z[None, :], (Nx, 1)), surfacecolor=data[:, Ny - 1, :], |
| showscale=False, name=f"XZ @ y={Ny-1}", **surf_kw, |
| )) |
|
|
| fig = go.Figure(data=surfaces) |
|
|
| if use_colorbar and use_dummy_colorbar: |
| fig.add_trace(go.Scatter3d( |
| x=[0.0, 0.0], y=[0.0, 0.0], z=[0.0, 0.0], |
| mode="markers", showlegend=False, hoverinfo="skip", |
| marker=dict( |
| size=0.001, opacity=0.0, color=[vmin, vmax], |
| cmin=vmin, cmax=vmax, colorscale=dummy_scale, |
| showscale=True, colorbar=cb_cfg(), |
| ), |
| )) |
|
|
| bbox_x = [0, Nx-1, Nx-1, 0, 0, None, 0, Nx-1, Nx-1, 0, 0, None, 0, 0, None, Nx-1, Nx-1, None, Nx-1, Nx-1, None, 0, 0] |
| bbox_y = [0, 0, Ny-1, Ny-1, 0, None, 0, 0, Ny-1, Ny-1, 0, None, 0, 0, None, 0, 0, None, Ny-1, Ny-1, None, Ny-1, Ny-1] |
| bbox_z = [0, 0, 0, 0, 0, None, Nz-1, Nz-1, Nz-1, Nz-1, Nz-1, None, 0, Nz-1, None, 0, Nz-1, None, 0, Nz-1, None, 0, Nz-1] |
| fig.add_trace(go.Scatter3d( |
| x=bbox_x, y=bbox_y, z=bbox_z, mode="lines", |
| line=dict(color="black", width=1.5), showlegend=False, |
| )) |
|
|
| tick_px = int(2.5 / 72 * dpi) |
| unit = 0.004 |
| sz = 1 if Nx < 257 else 2 |
| axis_style = dict(visible=show_axes, showbackground=False, mirror=True, linecolor="black", linewidth=0, tickwidth=0, tickcolor="black") |
| title_font = dict(family="Arial, sans-serif", size=tick_px * 1.5, color="black") |
| tick_font = dict(family="Arial, sans-serif", size=tick_px, color="black") |
|
|
| centre = np.array([Nx / 2, Ny / 2, Nz / 2]) |
| diag_len = np.linalg.norm([Nx, Ny, Nz]) / 2 |
|
|
| if isotropic_view: |
| eye_dir = np.array([1.0, 1.0, 1.7 * (2.5 if sf == 2 else 1.0)]) |
| eye_pos = centre + camera_distance * diag_len * eye_dir / np.linalg.norm(eye_dir) / 1.1 |
| else: |
| eye_pos = centre + camera_distance * np.array([0.0, 0.0, diag_len]) |
|
|
| fig.update_layout( |
| scene=dict( |
| xaxis=dict(**axis_style, title=dict(text="x", font=title_font), tickfont=tick_font, |
| tickmode="array", tickvals=[0, Nx//2, Nx-1], |
| ticktext=[f"{abs(sz - v * unit):.1f}" for v in [0, Nx//2, Nx-1]]), |
| yaxis=dict(**axis_style, title=dict(text="y", font=title_font), tickfont=tick_font, |
| tickmode="array", tickvals=[0, Ny//2, Ny-1], |
| ticktext=[f"{abs(sz - v * unit):.1f}" for v in [0, Ny//2, Ny-1]]), |
| zaxis=dict(**axis_style, title=dict(text="z", font=title_font), tickfont=tick_font, |
| tickmode="array", tickvals=[Nz-1], ticktext=[f"{abs(Nz * unit):.2f}"]), |
| aspectmode="data", |
| camera=dict(eye=dict(x=float(eye_pos[0]*0.01), y=float(eye_pos[1]*0.01), z=float(eye_pos[2]*0.01))), |
| ), |
| width=_cm2px(fig_width_cm, dpi), height=_cm2px(fig_height_cm, dpi), |
| paper_bgcolor="rgba(0,0,0,0)", |
| legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1), |
| ) |
|
|
| if png_path is not None: |
| fig.write_image(png_path, width=_cm2px(fig_width_cm, dpi), height=_cm2px(fig_height_cm, dpi), scale=1.0) |
|
|
| return fig |
|
|
|
|
| def vis_field(data, cmap="jet", colorbar_title=None): |
| data = data.permute(2, 1, 0).flip(dims=(0, 2)) |
| return plot_tensor_slices(data, colorscale=cmap, colorbar_title=colorbar_title) |
|
|
|
|
| def _make_ground_plane(xmin, xmax, ymin, ymax, z0=0.0, color="#1653D0", grid_color="black", grid_size=10): |
| return go.Surface( |
| x=[[xmin, xmax]] * 2, y=[[ymin, ymin], [ymax, ymax]], z=[[z0, z0]] * 2, |
| showscale=False, colorscale=[[0, color], [1, color]], |
| contours=dict( |
| x=dict(show=True, color=grid_color, start=xmin, end=xmax, size=(xmax - xmin) / grid_size, width=16), |
| y=dict(show=True, color=grid_color, start=ymin, end=ymax, size=(ymax - ymin) / grid_size, width=16), |
| z=dict(show=False), |
| ), |
| ) |
|
|
|
|
| def plot_stl( |
| stl_path, z_th=0.5, scale_mode="auto", isotropic_view=True, |
| camera_distance=0.9, below_color="rgba(0,0,0,0)", above_color="#86CDFF", |
| flat_shading=False, ambient=0.20, diffuse=0.70, specular=0.45, |
| roughness=0.35, fresnel=0.06, light_xyz=None, width=800, height=600, margin=0, |
| ): |
| tri = stl_mesh.Mesh.from_file(str(stl_path)).vectors |
| vertices, reindex = np.unique(tri.reshape(-1, 3), axis=0, return_inverse=True) |
| i, j, k = reindex.reshape(-1, 3).T |
|
|
| if scale_mode == "auto": |
| diag_len = np.linalg.norm(np.ptp(vertices, axis=0)) |
| vertices = vertices / diag_len |
| elif isinstance(scale_mode, (int, float)): |
| vertices = vertices * float(scale_mode) |
|
|
| vmin, vmax = vertices.min(0), vertices.max(0) |
| center, diag_vec = (vmin + vmax) / 2, vmax - vmin |
| diag_len = np.linalg.norm(diag_vec) |
|
|
| z_centroids = tri.mean(axis=1)[:, 2] |
| if scale_mode == "auto": |
| z_centroids = z_centroids / diag_len |
| face_colors = np.where(z_centroids < z_th, below_color, above_color) |
|
|
| light_pos = light_xyz or (center + 2 * diag_vec) |
| mesh3d = go.Mesh3d( |
| x=vertices[:, 0], y=vertices[:, 1], z=vertices[:, 2], |
| i=i, j=j, k=k, facecolor=face_colors, flatshading=flat_shading, |
| lighting=dict(ambient=ambient, diffuse=diffuse, specular=specular, roughness=roughness, fresnel=fresnel), |
| lightposition=dict(x=light_pos[0], y=light_pos[1], z=light_pos[2]), |
| showscale=False, name="", |
| ) |
|
|
| p = 0.05 * vmax[0] |
| ground = _make_ground_plane(p, vmax[0] - p, p, vmax[1] - p, z0=0.003, color="rgba(200,200,255,1)", grid_color="black") |
|
|
| eye_pos = center + camera_distance * diag_len * ( |
| np.array([1.5, -2, 1.7]) / 4 * 5 if isotropic_view else np.array([0, 0, 1]) |
| ) |
|
|
| fig = go.Figure(mesh3d) |
| fig.add_trace(ground) |
| fig.update_layout( |
| width=width, height=height, |
| margin=dict(l=margin, r=margin, t=margin, b=margin), |
| paper_bgcolor="rgba(0,0,0,0)", |
| scene=dict( |
| aspectmode="data", |
| camera=dict(eye=dict(x=eye_pos[0], y=eye_pos[1], z=eye_pos[2])), |
| xaxis=dict(visible=False), yaxis=dict(visible=False), zaxis=dict(visible=False), |
| ), |
| ) |
| return fig |
|
|
|
|
| _default_layout = [ |
| {'row': 1, 'col': 1, 'title': 'Photomask (M)'}, |
| {'row': 1, 'col': 2, 'title': 'Diffracted near field (E)'}, |
| {'row': 2, 'col': 1, 'title': 'Photoacid (h)'}, |
| {'row': 2, 'col': 2, 'title': 'Deprotection image (m)'}, |
| {'row': 3, 'col': 1, 'title': 'Development rate (R)'}, |
| {'row': 3, 'col': 2, 'title': 'Development time (T)'}, |
| ] |
|
|
| def save_html(figures, filepath, title="Dashboard", layout=_default_layout, cols=2): |
| import plotly.io as pio |
|
|
| html_parts = [pio.to_html(fig, full_html=False, include_plotlyjs=(i == 0)) for i, fig in enumerate(figures)] |
|
|
| items_html = "" |
| for i, part in enumerate(html_parts): |
| L = layout[i] if layout and i < len(layout) else {} |
| row, col = L.get("row", "auto"), L.get("col", "auto") |
| rowspan, colspan = L.get("rowspan", 1), L.get("colspan", 1) |
| fig_title = L.get("title", "") |
| style = f"grid-row: {row} / span {rowspan}; grid-column: {col} / span {colspan};" |
| title_html = f'<div class="fig-title">{fig_title}</div>' if fig_title else "" |
| items_html += f'<div class="fig-item" style="{style}">{title_html}<div class="fig-inner">{part}</div></div>\n' |
|
|
| full_html = f"""<!DOCTYPE html> |
| <html> |
| <head> |
| <meta charset="utf-8"> |
| <title>{title}</title> |
| <style> |
| body {{ font-family: Arial, sans-serif; margin: 20px; background: #f5f5f5; }} |
| h1 {{ margin-bottom: 20px; }} |
| .grid-container {{ display: grid; grid-template-columns: repeat({cols}, 1fr); gap: 16px; }} |
| .fig-item {{ background: white; border-radius: 8px; padding: 12px; box-shadow: 0 2px 8px rgba(0,0,0,0.1); }} |
| .fig-title {{ font-size: 1em; font-weight: bold; color: #333; margin-bottom: 8px; padding-bottom: 6px; border-bottom: 2px solid #e0e0e0; }} |
| .fig-inner {{ width: 100%; }} |
| </style> |
| </head> |
| <body> |
| <h1>{title}</h1> |
| <div class="grid-container">{items_html}</div> |
| </body> |
| </html>""" |
|
|
| with open(filepath, "w", encoding="utf-8") as f: |
| f.write(full_html) |
| print(f"Saved → {filepath}") |