From 3c9418f0c0850fa741020bf4362ec6e947bb8d53 Mon Sep 17 00:00:00 2001 From: smgr Date: Wed, 19 Nov 2025 00:25:19 -0800 Subject: [PATCH] fix tags in v1.3.0 FF themes, outline CLI tool --- .gitignore | 1 + app-config/firefox/alpine-monobiome-dark.xpi | Bin 472 -> 472 bytes app-config/firefox/alpine-monobiome-light.xpi | Bin 471 -> 471 bytes app-config/firefox/alpine-monobiome.xpi | Bin 560 -> 560 bytes .../firefox/badlands-monobiome-dark.xpi | Bin 484 -> 485 bytes .../firefox/badlands-monobiome-light.xpi | Bin 482 -> 482 bytes app-config/firefox/badlands-monobiome.xpi | Bin 577 -> 577 bytes .../firefox/chaparral-monobiome-dark.xpi | Bin 488 -> 488 bytes .../firefox/chaparral-monobiome-light.xpi | Bin 487 -> 487 bytes app-config/firefox/chaparral-monobiome.xpi | Bin 583 -> 583 bytes .../firefox/grassland-monobiome-dark.xpi | Bin 488 -> 488 bytes .../firefox/grassland-monobiome-light.xpi | Bin 487 -> 487 bytes app-config/firefox/grassland-monobiome.xpi | Bin 582 -> 582 bytes app-config/firefox/savanna-monobiome-dark.xpi | Bin 484 -> 484 bytes .../firefox/savanna-monobiome-light.xpi | Bin 484 -> 484 bytes app-config/firefox/savanna-monobiome.xpi | Bin 578 -> 578 bytes app-config/firefox/tundra-monobiome-dark.xpi | Bin 487 -> 488 bytes app-config/firefox/tundra-monobiome-light.xpi | Bin 484 -> 484 bytes app-config/firefox/tundra-monobiome.xpi | Bin 580 -> 580 bytes images/color_stats/chroma-curves-v130.png | Bin 0 -> 48522 bytes monobiome/constants.py | 157 ++++++++++++++++++ monobiome/curves.py | 114 +++++++++++++ monobiome/plotting.py | 131 +++++++++++++++ monobiome/schemes.py | 140 ++++++++++++++++ monobiome/writer.py | 39 +++++ notebooks/figures/mb_contrast_r50.gif | Bin 2334111 -> 2334130 bytes notebooks/figures/mb_sphere.gif | Bin 3481857 -> 3481876 bytes notebooks/figures/mb_trajectories.gif | Bin 5293502 -> 2960044 bytes notebooks/monobiome_qbr-shapenorm-v130.ipynb | 59 ++++--- remove_big_ipynb.py | 10 ++ .../templates/none-dark.auto-manifest.json | 2 +- .../templates/none-dark.dark-manifest.json | 2 +- .../templates/none-dark.light-manifest.json | 2 +- .../theme/default-alpine-monobiome-dark.toml | 1 + .../theme/default-alpine-monobiome-light.toml | 1 + .../default-badlands-monobiome-dark.toml | 1 + .../default-badlands-monobiome-light.toml | 1 + .../default-chaparral-monobiome-dark.toml | 1 + .../default-chaparral-monobiome-light.toml | 1 + .../default-grassland-monobiome-dark.toml | 1 + .../default-grassland-monobiome-light.toml | 1 + .../theme/default-savanna-monobiome-dark.toml | 1 + .../default-savanna-monobiome-light.toml | 1 + .../theme/default-tundra-monobiome-dark.toml | 1 + .../theme/default-tundra-monobiome-light.toml | 1 + .../theme/hard-alpine-monobiome-dark.toml | 1 + .../theme/hard-alpine-monobiome-light.toml | 1 + .../theme/hard-badlands-monobiome-dark.toml | 1 + .../theme/hard-badlands-monobiome-light.toml | 1 + .../theme/hard-chaparral-monobiome-dark.toml | 1 + .../theme/hard-chaparral-monobiome-light.toml | 1 + .../theme/hard-grassland-monobiome-dark.toml | 1 + .../theme/hard-grassland-monobiome-light.toml | 1 + .../theme/hard-savanna-monobiome-dark.toml | 1 + .../theme/hard-savanna-monobiome-light.toml | 1 + .../theme/hard-tundra-monobiome-dark.toml | 1 + .../theme/hard-tundra-monobiome-light.toml | 1 + .../theme/soft-alpine-monobiome-dark.toml | 1 + .../theme/soft-alpine-monobiome-light.toml | 1 + .../theme/soft-badlands-monobiome-dark.toml | 1 + .../theme/soft-badlands-monobiome-light.toml | 1 + .../theme/soft-chaparral-monobiome-dark.toml | 1 + .../theme/soft-chaparral-monobiome-light.toml | 1 + .../theme/soft-grassland-monobiome-dark.toml | 1 + .../theme/soft-grassland-monobiome-light.toml | 1 + .../theme/soft-savanna-monobiome-dark.toml | 1 + .../theme/soft-savanna-monobiome-light.toml | 1 + .../theme/soft-tundra-monobiome-dark.toml | 1 + .../theme/soft-tundra-monobiome-light.toml | 1 + 69 files changed, 659 insertions(+), 34 deletions(-) create mode 100644 images/color_stats/chroma-curves-v130.png create mode 100644 monobiome/constants.py create mode 100644 monobiome/curves.py create mode 100644 monobiome/plotting.py create mode 100644 monobiome/schemes.py create mode 100644 monobiome/writer.py create mode 100644 remove_big_ipynb.py diff --git a/.gitignore b/.gitignore index 191c43e..71958ad 100644 --- a/.gitignore +++ b/.gitignore @@ -22,3 +22,4 @@ archive/ notebooks/color_spaces_manyview.ipynb notebooks/oklch_srgb_spherical.ipynb +notebooks/v1.4.0/ diff --git a/app-config/firefox/alpine-monobiome-dark.xpi b/app-config/firefox/alpine-monobiome-dark.xpi index 28f2857a77cb0a10678ced1aebc308560cc9ff21..9c7565829b5bf7f9ccc66219cf96f9610987ec52 100644 GIT binary patch delta 360 zcmcb?e1n-cz?+#xgn@*35%*UDzXaPOqsc`XV8ZSQNj9)-@{F?&_+u9v4J z0zx(&5IC^xWZM0`GS}W-x^?2{1fH5Re~NdAa7<b&>M7 zAA3vYsft~R=bYdm!BKS}#?X_W`P%c28#CFSJ(79;?SSL#-SY2r7}O(vJ5<#x`R6a^ za;@f53|h7M%jtC)mrX>Y`dj3_`p!Cj>pGXKw{p@Y!8`NSdAnsM9r(KY@b%>2V<$A^ 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= np.arange(0, 100+L_resolution, L_resolution) + +monotone_C_map = { + "alpine": 0, + "badlands": 0.011, + "chaparral": 0.011, + "savanna": 0.011, + "grassland": 0.011, + "tundra": 0.011, +} + +h_weights = { + "red": 3.0, + "orange": 3.8, # 3.6 + "yellow": 3.8, # 4.0 + "green": 3.8, + "blue": 3.4, # 3.8 +} +h_L_offsets = { + "red": 0, # -1, + "orange": -5.5, # -3, + "yellow": -13.5, # -8 + "green": -11, # -8 + "blue": 10, # 14 +} +h_C_offsets = { + "red": 0, # 0 + "orange": -0.01, # -0.02 + "yellow": -0.052, # -0.08 + "green": -0.088, # -0.105 + "blue": 0.0, # 0.01 +} + +monotone_h_map = { + "alpine": 0, + "badlands": 29, + "chaparral": 62.5, + "savanna": 104, + "grassland": 148, + "tundra": 262, +} +accent_h_map = { + "red": 29, + "orange": 62.5, + "yellow": 104, + "green": 148, + "blue": 262, +} +h_map = {**monotone_h_map, **accent_h_map} + + +v111_L_space = list(range(15, 95+1, 5)) +v111_hC_points = { + "red": [ + 0.058, + 0.074, + 0.092, + 0.11, + 0.128, + 0.147, + 0.167, + 0.183, + 0.193, + 0.193, + 0.182, + 0.164, + 0.14, + 0.112, + 0.081, + 0.052, + 0.024, + ], + "orange": [ + 0.030, + 0.038, + 0.046, + 0.058, + 0.07, + 0.084, + 0.1, + 0.114, + 0.125, + 0.134, + 0.138, + 0.136, + 0.128, + 0.112, + 0.092, + 0.064, + 0.032, + ], + "yellow": [ + 0.02, + 0.024, + 0.03, + 0.036, + 0.044, + 0.05, + 0.06, + 0.068, + 0.076, + 0.082, + 0.088, + 0.088, + 0.086, + 0.082, + 0.072, + 0.058, + 0.04, + ], + "green": [ + 0.0401, + 0.048, + 0.056, + 0.064, + 0.072, + 0.08, + 0.09, + 0.098, + 0.104, + 0.108, + 0.11, + 0.108, + 0.102, + 0.094, + 0.084, + 0.072, + 0.05, + ], + "blue": [ + 0.06, + 0.072, + 0.084, + 0.096, + 0.106, + 0.116, + 0.124, + 0.13, + 0.132, + 0.128, + 0.122, + 0.11, + 0.096, + 0.08, + 0.064, + 0.044, + 0.023, + ], +} diff --git a/monobiome/curves.py b/monobiome/curves.py new file mode 100644 index 0000000..4680d08 --- /dev/null +++ b/monobiome/curves.py @@ -0,0 +1,114 @@ +import json +from pathlib import Path +from functools import cache + +import numpy as np + +from pprint import pprint +from coloraide import Color + +from monobiome.constants import ( + L_points, + L_resolution, + L_space, + + monotone_C_map, + h_weights, + h_L_offsets, + h_C_offsets, + + monotone_h_map, + accent_h_map, + h_map, +) + + +@cache +def max_C_Lh(L, h, space='srgb', eps=1e-6, tol=1e-9): + ''' + Binary search for max chroma at fixed lightness and hue + + Parameters: + L: lightness percentage + ''' + def C_in_gamut(C): + return Color('oklch', [L/100, C, h]).convert(space).in_gamut(tolerance=tol) + + lo, hi = 0.0, 0.1 + while C_in_gamut(hi): + hi *= 2 + while hi - lo > eps: + m = (lo + hi) / 2 + lo, hi = (m, hi) if C_in_gamut(m) else (lo, m) + + Cmax = lo + # c_oklch = Color('oklch', [L, Cmax, h]) + # c_srgb = c_oklch.convert('srgb') + + return Cmax + +def quad_bezier_rational(P0, P1, P2, w, t): + t = np.asarray(t)[:, None] + num = (1-t)**2*P0 + 2*w*(1-t)*t*P1 + t**2*P2 + den = (1-t)**2 + 2*w*(1-t)*t + t**2 + + return num/den + +def bezier_y_at_x(P0, P1, P2, w, x_query, n=400): + t = np.linspace(0, 1, n) + B = quad_bezier_rational(P0, P1, P2, w, t) + x_vals, y_vals = B[:, 0], B[:, 1] + + return np.interp(x_query, x_vals, y_vals) + + +# compute C max values over each point in L space +h_Lspace_Cmax = { + h_str: [max_C_Lh(_L, _h) for _L in L_space] + for h_str, _h in h_map.items() +} + +# compute *unbounded* chroma curves for all hues +h_L_points_C = {} +h_ctrl_L_C = {} + +for h_str, _h in monotone_h_map.items(): + h_L_points_C[h_str] = np.array([monotone_C_map[h_str]]*len(L_points)) + +for h_str, _h in accent_h_map.items(): + Lspace_Cmax = h_Lspace_Cmax[h_str] + + # get L value of max chroma; will be a bezier control + L_Cmax_idx = np.argmax(Lspace_Cmax) + L_Cmax = L_space[L_Cmax_idx] + + # offset control point by any preset x-shift + L_Cmax += h_L_offsets[h_str] + + # and get max C at the L offset + Cmax = max_C_Lh(L_Cmax, _h) + + # set 3 control points; shift by any global linear offest + C_offset = h_C_offsets.get(h_str, 0) + + p_0 = np.array([0, 0]) + p_Cmax = np.array([L_Cmax, Cmax + C_offset]) + p_100 = np.array([100, 0]) + + B_L_points = bezier_y_at_x(p_0, p_Cmax, p_100, h_weights.get(h_str, 1), L_points) + h_L_points_C[h_str] = B_L_points + h_ctrl_L_C[h_str] = np.vstack([p_0, p_Cmax, p_100]) + +# compute full set of final chroma curves; limits every point to in-gamut max +h_LC_color_map = {} +h_L_points_Cstar = {} + +for h_str, L_points_C in h_L_points_C.items(): + _h = h_map[h_str] + + h_L_points_Cstar[h_str] = [ + max(0, min(_C, max_C_Lh(_L, _h))) + for _L, _C in zip(L_points, L_points_C) + ] + +# if __name__ == "__main__": diff --git a/monobiome/plotting.py b/monobiome/plotting.py new file mode 100644 index 0000000..c494e9a --- /dev/null +++ b/monobiome/plotting.py @@ -0,0 +1,131 @@ +import matplotlib.pyplot as plt +from scipy.interpolate import interp1d, CubicSpline, BSpline + +from monobiome.constants import ( + L_points, + L_space, + h_weights, + monotone_h_map, + accent_h_map, + h_map, +) +from monobiome.curves import ( + h_L_points_Cstar, + h_Lspace_Cmax, +) + +ax_h_map = {} +fig, axes = plt.subplots( + len(monotone_h_map), + 1, + sharex=True, + sharey=True, + figsize=(4, 8) +) + +for i, h_str in enumerate(h_L_points_Cstar): + _h = h_map[h_str] + L_points_Cstar = h_L_points_Cstar[h_str] + L_space_Cmax = h_Lspace_Cmax[h_str] + + if _h not in ax_h_map: + ax_h_map[_h] = axes[i] + ax = ax_h_map[_h] + + # plot Cmax and Cstar + ax.plot(L_space, L_space_Cmax, c="b", alpha=0.2) + ax.plot(L_points, L_points_Cstar, alpha=0.7) + + ax.title.set_text(f"Hue [${_h}$]") + +axes[-1].set_xlabel("Lightness (%)") +axes[-1].set_xticks([L_points[0], L_points[-1]]) + +fig.tight_layout() +fig.subplots_adjust(top=0.9) + +plt.suptitle("$C^*$ curves for hue groups") +plt.show() + + + +ax_h_map = {} +fig, axes = plt.subplots( + len(monotone_h_map), + 1, + sharex=True, + sharey=True, + figsize=(5, 10) +) + +for i, h_str in enumerate(h_L_points_Cstar): + _h = h_map[h_str] + L_points_Cstar = h_L_points_Cstar[h_str] + L_space_Cmax = h_Lspace_Cmax[h_str] + + if _h not in ax_h_map: + ax_h_map[_h] = axes[i] + ax = ax_h_map[_h] + + # plot Cmax and Cstar + ax.plot(L_space, L_space_Cmax, c="b", alpha=0.2, label='Cmax') + ax.plot(L_points, L_points_Cstar, alpha=0.7, label='C*') + + if h_str in v111_hC_points: + ax.scatter(v111_L_space, v111_hC_points[h_str], s=4, label='Cv111') + + if h_str in h_ctrl_L_C: + cpts = h_ctrl_L_C[h_str] + cpt_x, cpt_y = cpts[:, 0], cpts[:, 1] + h_w = h_weights.get(h_str, 1) + + P0, P1, P2 = cpts[0], cpts[1], cpts[2] + d0 = 2 * h_w * (P1 - P0) + d2 = 2 * h_w * (P2 - P1) + + handle_scale = 0.25 + H0 = P0 + handle_scale * d0 + H2 = P2 - handle_scale * d2 + + # ax.plot([P0[0], H0[0]], [P0[1], H0[1]], color='tab:blue', lw=1) + # ax.plot([P2[0], H2[0]], [P2[1], H2[1]], color='tab:orange', lw=1) + + ax.plot(cpt_x, cpt_y, '--', color='gray', lw=1, label='Bezier polygon') + ax.scatter(cpt_x, cpt_y, color='red', zorder=5, s=2, label='Control points') + + ax.title.set_text(f"Hue [${_h}$]") + +axes[-1].set_ylabel("Chroma (C)") +axes[-1].set_xlabel("Lightness (%)") +axes[-1].set_xticks([L_points[0], 50, 65, L_points[-1]]) + +fig.tight_layout() +fig.subplots_adjust(top=0.9) + +handles, labels = axes[-1].get_legend_handles_labels() +unique = dict(zip(labels, handles)) +fig.legend(unique.values(), unique.keys(), loc='lower center', bbox_to_anchor=(0.5, -0.06), ncol=3) + +plt.suptitle("$C^*$ curves for hue groups + v111 5% lightness") +plt.show() + + + + +from numpy import arctan2, degrees + +fig, ax = plt.subplots(1, 1, figsize=(8, 6)) + +for h_str in h_L_points_Cstar: + if h_str not in accent_h_map: + continue + ax.fill_between(L_points, h_L_points_Cstar[h_str], alpha=0.2, color='grey', label=h_str) + + x, y = L_points, h_L_points_Cstar[h_str] + n = int(0.5*len(x)) + ax.text(x[n], y[n]-0.01, h_str, rotation=10, va='center', ha='left') + +ax.set_xlabel("Lightness (%)") +ax.set_xticks([L_points[0], 45, 50, 55, 60, 65, 70, L_points[-1]]) +plt.suptitle("$C^*$ curves (v1.3.0)") +fig.show() diff --git a/monobiome/schemes.py b/monobiome/schemes.py new file mode 100644 index 0000000..8bd4f5d --- /dev/null +++ b/monobiome/schemes.py @@ -0,0 +1,140 @@ +def compute_dma_map(dT, metric=None): + """ + For threshold `dT`, compute the nearest accent shades + that exceed that threshold for every monotone shade. + + Returns: + + Map like + { "alpine": { + "oklch( ... )": { + "red": *nearest oklch >= dT from M base* + """ + + if metric is None: + metric = lambda mc,ac: mc.distance(ac, space="oklch") + + oklch_color_map = { + c_name: [Color(c_str) for c_str in c_str_dict.values()] + for c_name, c_str_dict in oklch_hL_dict.items() + } + + dT_mL_acol_map = {} + for m_name in monotone_h_map: + mL_acol_map = {} + m_colors = oklch_color_map[m_name] + + for m_color in m_colors: + acol_min_map = {} + + for a_name in accent_h_map: + a_colors = oklch_color_map[a_name] + oklch_dists = filter( + lambda d: (d[1] - dT) > 0, + [ + (ac, metric(m_color, ac)) + for ac in a_colors + ] + ) + oklch_dists = list(oklch_dists) + if oklch_dists: + min_a_color = min(oklch_dists, key=lambda t: t[1])[0] + acol_min_map[a_name] = min_a_color + + # make sure the current monotone level has *all* accents; o/w ignore + if len(acol_min_map) < len(accent_h_map): + continue + + mL = m_color.coords()[0] + mL_acol_map[int(mL*100)] = acol_min_map + dT_mL_acol_map[m_name] = mL_acol_map + return dT_mL_acol_map + + + + + + +mode = "dark" # ["dark", "light"] +biome = "alpine" # [ ... ] +metric = "wcag" # ["wcag", "oklch"] +metric_map = { + "wcag": lambda mc,ac: ac.contrast(mc, method='wcag21'), + "oklch": lambda mc,ac: mc.distance(ac, space="oklch"), +} +metric_func = metric_map[metric] + +term_color_map = { + "red": "red", + "organge": "orange", + "yellow": "yellow", + "green": "green", + "cyan": "green", + "blue": "blue", + "violet": "blue", + "magenta": "red", +} + +L = 20 +d = 4.5 +I = 5 +fg_gap = 50 +grey_gap = 30 + +dT_mL_acol_map = compute_dma_map(d, metric=metric_func) +Lma_map = { + m_name: mL_acol_dict[L] + for m_name, mL_acol_dict in dT_mL_acol_map.items() + if L in mL_acol_dict +} + +# the `mL_acol_dict` only includes lightnesses where all accent +# colors were within threshold. Coverage here will be partial if, +# at the `mL`, there is some monotone base that doesn't have all +# accents within threshold. This can happen at the edge, e.g., alpine@L15 +# has all accents w/in the distance, but the red accent was too far under +# tundra@L15, so there's no entry. This particular case is fairly rare; it's +# more likely that *all* monotones are undefined. Either way, both such +# cases lead to partial scheme coverage. +if len(Lma_map) < len(monotone_h_map): + print(f"Warning: partial scheme coverage for {mL=}@{dT=}") +if biome not in Lma_map: + print(f"Biome {biome} unable to meet {metric} constraints") +accent_colors = Lma_map.get(biome, {}) + +scheme_pairs = [] +for i in range(4): + scheme_pairs.append( + ( + f"bg{i}", + f"f{{{{{biome}.l{L+i*I}}}}}" + ) + ) +for i in range(4): + scheme_pairs.append( + ( + f"fg{3-i}", + f"f{{{{{biome}.l{fg_gap+L+i*I}}}}}" + ) + ) +for term_color, mb_accent in term_color_map.items(): + aL = int(100*accent_colors[mb_accent].coords()[0]) + scheme_pairs.append( + ( + f"{term_color}", + f"f{{{{{mb_accent}.l{aL}}}}}" + ) + ) + +term_fg_gap = 60 +scheme_pairs.extend([ + ("background", f"f{{{{{biome}.l{L}}}}}"), + ("selection_bg", f"f{{{{{biome}.l{L+I}}}}}"), + ("selection_fg", f"f{{{{{biome}.l{L+term_fg_gap}}}}}"), + ("foreground", f"f{{{{{biome}.l{L+term_fg_gap+I}}}}}"), +]) + +scheme_toml = [ + f"{lhs:<12} = {rhs:<16}" + for lhs, rhs in scheme_pairs +] diff --git a/monobiome/writer.py b/monobiome/writer.py new file mode 100644 index 0000000..c444b08 --- /dev/null +++ b/monobiome/writer.py @@ -0,0 +1,39 @@ + +# put together objects for output formats +toml_lines = [] +oklch_hL_dict = {} + +for h_str, L_points_Cstar in h_L_points_Cstar.items(): + _h = h_map[h_str] + toml_lines.append(f"[{h_str}]") + oklch_hL_dict[h_str] = {} + + for _L, _C in zip(L_points, L_points_Cstar): + oklch = Color('oklch', [_L/100, _C, _h]) + srgb = oklch.convert('srgb') + + hex_str = srgb.to_string(hex=True) + + l, c, h = oklch.convert('oklch').coords() + # oklch_str = oklch.to_string(percent=False) + oklch_str = f"oklch({l*100:.1f}% {c:.4f} {h:.1f})" + + toml_lines.append(f'l{_L} = "{hex_str}"') + oklch_hL_dict[h_str][_L] = oklch_str + + toml_lines.append("") + + + +# write files -- QBR = "quadratic bezier rational" +PALETTE_DIR = "palettes" + +toml_content = '\n'.join(toml_lines) +with Path(PALETTE_DIR, 'monobiome-vQBRsn-130.toml').open('w') as f: + f.write(toml_content) +print("[TOML] written") + +with Path(PALETTE_DIR, 'monobiome-vQBRsn-130-oklch.json').open('w') as f: + json.dump(oklch_hL_dict, f) +print("[JSON] written") + diff --git a/notebooks/figures/mb_contrast_r50.gif b/notebooks/figures/mb_contrast_r50.gif index a0064a2c8b6abd06f050ac5eb8a94b9d25fc064e..3b8c2cd0252bd5e6bcff573b4fce42c07c97a97c 100644 GIT binary patch delta 188 zcmWm0yAHun9Khjo`gbYEq3V9G+NJ4KqezKGBn(#1Vz3#E7SF(9@L)!MhA;W%%`|C&v@-!10bG@eGHl~N}wXDb>G{?8zb9P)5cKoJHdSd>wLhbny3 cP)7qzw9rNeUG&h$07HxrV2to(Wpcg!0I?4w+yDRo delta 169 zcmWm0yA6U+7=Y2hFQ8roL=^A=_remo0LBe$nZ<&R#MZ_cu(4n{K8ll^-`HDUsQaV2 z-dZhByBn0q%SdO$f{pnLIB?-%i51pR@UcOF5D~VBu|tAA4oHz9#}Ox-aY2C+8V1$h HNd5jyGc6-H diff --git a/notebooks/figures/mb_sphere.gif b/notebooks/figures/mb_sphere.gif index bafa1af672848066213fa3e32dadf56704fe2d93..ee2a9dace6c0cb38eda9bd2038ee0a6ee3e7730d 100644 GIT binary patch delta 260 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