Created
February 18, 2026 15:33
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| { | |
| "frag": "#ifdef GL_ES\nprecision highp float;\n#endif\n\nuniform sampler2D u_tex0;\nuniform sampler2D u_doubleBuffer0; // 128x128\nuniform sampler2D u_scene;\n\nuniform vec2 u_resolution;\nuniform float u_time;\nuniform float u_delta;\nuniform int u_frame;\n\nvarying vec4 v_color;\nvarying vec2 v_texcoord;\n\n#include \"lygia/math/const.glsl\"\n#include \"lygia/math/decimate.glsl\"\n#include \"lygia/math/saturate.glsl\"\n#include \"lygia/color/luma.glsl\"\n#include \"lygia/draw/fill.glsl\"\n#include \"lygia/generative/random.glsl\"\n\n\nvec2 buffRes = vec2(128.0);\nfloat maxSpeed = 0.5;\nfloat dotSize = 10.0;\n\nvec2 buffPixel = 1.0/buffRes;\nvec2 pixel = 1.0/u_resolution;\n\nvoid main(void) {\n vec4 color = vec4(vec3(0.0), 1.0);\n \n vec2 st = v_texcoord;\n vec2 data_uv = decimate(st, buffRes) + 0.5 * buffPixel;\n vec4 data = texture2D(u_doubleBuffer0, data_uv);\n\n// PARTICLES PINGPONG\n#if defined(DOUBLE_BUFFER_0)\n\n // Initial parameters\n vec2 pos = data.xy;\n pos = u_frame < 1 ? st * 2.0 - 1.0: pos;\n\n vec2 vel = data.zw;\n vel = u_frame < 1 ? random2(st * 100.0) * 2.0 - 1.0: vel;\n\n float speed = 0.1 + random(st + pos) * maxSpeed;\n\n vec2 uv = fract(pos * 0.5 + 0.5);\n float l = luma( texture2D(u_tex0, uv).rgb );\n\n float a = 0.0;\n float r = 5.0 + l * l * dotSize;\n float steps = 36.0;\n float a_step = TAU/steps;\n\n vel *= 0.9;\n\n float hits = 1.0;\n vec2 acc = vec2(0.0);\n for (float i = 0.0; i < steps; i++) {\n vec2 index_dir = vec2(cos(a), sin(a));\n vec4 index = texture2D(u_scene, uv + index_dir * r * pixel);\n if (index.a == 1.0 && index.x != data_uv.x && index.y != data_uv.y)\n {\n float amount = 1.0;\n // vec2 neightboor_uv = decimate(index.xy, buffRes) + 0.5 * buffPixel;\n // vec4 neightboor_data = texture2D(u_doubleBuffer0, neightboor_uv);\n // vec2 delta = pos - neightboor_data.xy;\n // amount -= saturate(length(delta));\n amount *= 0.1;\n acc -= index_dir * amount;\n hits++;\n }\n a += a_step;\n }\n\n vel += acc/hits;\n\n pos += vel * speed * u_delta;\n\n if ( abs(pos.x) >= 0.95 || abs(pos.y) >= 0.95 ) \n vel = vel * 0.5 + normalize(pos) * -0.5;\n\n color = vec4(clamp(pos, -1.0, 1.0), clamp(vel, -1.0, 1.0));\n\n#elif defined(POSTPROCESSING)\n vec4 d = texture2D(u_scene, st);\n data = texture2D(u_doubleBuffer0, d.xy);\n \n color.rgb += d.b;\n\n#else\n color = v_color;\n\n float sdf = length(gl_PointCoord.xy - 0.5);\n color.a = fill( sdf, 0.5, 0.1 );\n\n#endif\n\n gl_FragColor = color;\n}\n", | |
| "vert": "#ifdef GL_ES\nprecision highp float;\n#endif\n\nuniform sampler2D u_tex0;\nuniform sampler2D u_doubleBuffer0; // 128x128\n\nuniform vec2 u_resolution;\n\nattribute vec4 a_position;\nvarying vec4 v_position;\n\nvarying vec4 v_color;\nvarying vec2 v_texcoord;\n\n#include \"lygia/math/decimate.glsl\"\n#include \"lygia/color/luma.glsl\"\n\nvec2 buffRes = vec2(128.0);\nvec2 buffPixel = 1.0/buffRes;\nfloat dotSize = 10.0;\n\nvoid main(void) {\n v_position = a_position;\n v_texcoord = a_position.xy;\n\n vec2 uv = v_texcoord;\n\n uv = decimate(uv, buffRes) + 0.5 * buffPixel;\n v_texcoord = uv;\n\n vec4 data = texture2D(u_doubleBuffer0, uv);\n v_position.xy = data.xy;\n\n float l = luma( texture2D(u_tex0, data.xy * 0.5 + 0.5).rgb );\n v_color = vec4(v_texcoord, l, 1.0);\n\n gl_PointSize = 3. + l * l * dotSize;\n \n gl_Position = v_position;\n}\n", | |
| "commands": [ | |
| "pcl_plane,128", | |
| "plot,off", | |
| "textures,off", | |
| "buffers,off", | |
| "floor,off", | |
| "cubemap,off", | |
| "axis,on", | |
| "grid,off", | |
| "bboxes,off", | |
| "camera_position,-0.234623,0.0587271,-2.79589", | |
| "camera_look_at,0,0,0", | |
| "camera,default" | |
| ], | |
| "assets": { | |
| "06d9122360608c8fb5b7fa8373c74e86.jpg": 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" 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