The alphashape3d::ashape3d function computes the 3D $$\alpha$$-shape of a cloud of points. This is an approximation to the visual outline of the cloud. It may include isolated points, line segments, and triangular faces: this function converts the triangular faces to an RGL tmesh3d object.

# S3 method for class 'ashape3d'
as.mesh3d(x,
alpha = x\$alpha[1],
tri_to_keep = 2L,
col = "gray",
smooth = FALSE, normals = NULL,
texcoords = NULL, ...)

## Arguments

x

An object of class "ashape3d".

alpha

Which alpha value stored in x should be converted?

tri_to_keep

Which triangles to keep. Expert use only: see triang entry in Value section of ashape3d for details.

col

The surface colour.

smooth

Whether to attempt to add normals to make the surface look smooth. See the Details below.

normals, texcoords

Normals and texture coordinates at each vertex can be specified.

...

Additional arguments to pass to use as material3d properties on the resulting mesh.

## Details

Edelsbrunner and Mucke's (1994) $$\alpha$$-shape algorithm is intended to compute a surface of a general cloud of points. Unlike the convex hull, the cloud may have voids, isolated points, and other oddities. This function is designed to work in the case where the surface is made up of simple polygons.

If smooth = TRUE, this method attempts to orient all of the triangles in the surface consistently and add normals at each vertex by averaging the triangle normals. However, for some point clouds, the $$\alpha$$-shape will contain sheets of polygons with a few solid polyhedra embedded. This does not allow a consistent definition of "inside" and outside. If this is detected, a warning is issued and the resulting mesh will likely contain boundaries where the assumed orientation of triangles changes, resulting in ugly dark lines through the shape. Larger values of alpha in the call to alphashape3d::ashape3d may help.

Methods for plot3d and persp3d are also defined: they call the as.mesh3d method and then plot the result.

## Value

A "mesh3d" object, suitable for plotting.

## References

Edelsbrunner, H., Mucke, E. P. (1994). Three-Dimensional Alpha Shapes. ACM Transactions on Graphics, 13(1), pp.43-72.

Lafarge, T. and Pateiro-Lopez, B. (2017). alphashape3d: Implementation of the 3D Alpha-Shape for the Reconstruction of 3D Sets from a Point Cloud. R package version 1.3.

Duncan Murdoch

## Examples

if (requireNamespace("alphashape3d", quietly = TRUE)) {
set.seed(123)
n <- 400    # 1000 gives a nicer result, but takes longer
xyz <- rbind(cbind(runif(n), runif(n), runif(n)),
cbind(runif(n/8, 1, 1.5),
runif(n/8, 0.25, 0.75),
runif(n/8, 0.25, 0.75)))
ash <- suppressMessages(alphashape3d::ashape3d(xyz, alpha = 0.2))
m <- as.mesh3d(ash, smooth = TRUE)
open3d()
mfrow3d(1, 2, sharedMouse = TRUE)
plot3d(xyz, size = 1)
plot3d(m, col = "red", alpha = 0.5)
points3d(xyz, size = 1)
}
3D plot

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P/ia4z2CcjQ/78AhP2J3eT6bVFw+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\nYWBPP4eeaz4EEiE+wvhPP//yMD8l/u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2 1\n// File 1 is the vertex shader\n#ifdef GL_ES\n#ifdef GL_FRAGMENT_PRECISION_HIGH\nprecision highp float;\n#else\nprecision mediump float;\n#endif\n#endif\n\nattribute vec3 aPos;\nattribute vec4 aCol;\nuniform mat4 mvMatrix;\nuniform mat4 prMatrix;\nvarying vec4 vCol;\nvarying vec4 vPosition;\n\n#ifdef NEEDS_VNORMAL\nattribute vec3 aNorm;\nuniform mat4 normMatrix;\nvarying vec4 vNormal;\n#endif\n\n#if defined(HAS_TEXTURE) || defined (IS_TEXT)\nattribute vec2 aTexcoord;\nvarying vec2 vTexcoord;\n#endif\n\n#ifdef FIXED_SIZE\nuniform vec3 textScale;\n#endif\n\n#ifdef FIXED_QUADS\nattribute vec3 aOfs;\n#endif\n\n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\nvarying float normz;\nuniform mat4 invPrMatrix;\n#else\nattribute vec3 aPos1;\nattribute vec3 aPos2;\nvarying float normz;\n#endif\n#endif // IS_TWOSIDED\n\n#ifdef FAT_LINES\nattribute vec3 aNext;\nattribute vec2 aPoint;\nvarying vec2 vPoint;\nvarying float vLength;\nuniform float uAspect;\nuniform float uLwd;\n#endif\n\n#ifdef USE_ENVMAP\nvarying vec3 vReflection;\n#endif\n\nvoid main(void) {\n  \n#ifndef IS_BRUSH\n#if defined(NCLIPPLANES) || !defined(FIXED_QUADS) || defined(HAS_FOG) || defined(USE_ENVMAP)\n  vPosition = mvMatrix * vec4(aPos, 1.);\n#endif\n  \n#ifndef FIXED_QUADS\n  gl_Position = prMatrix * vPosition;\n#endif\n#endif // !IS_BRUSH\n  \n#ifdef IS_POINTS\n  gl_PointSize = POINTSIZE;\n#endif\n  \n  vCol = aCol;\n  \n// USE_ENVMAP implies NEEDS_VNORMAL\n\n#ifdef NEEDS_VNORMAL\n  vNormal = normMatrix * vec4(-aNorm, dot(aNorm, aPos));\n#endif\n\n#ifdef USE_ENVMAP\n  vReflection = normalize(reflect(vPosition.xyz/vPosition.w, \n                        normalize(vNormal.xyz/vNormal.w)));\n#endif\n  \n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\n  /* normz should be calculated *after* projection */\n  normz = (invPrMatrix*vNormal).z;\n#else\n  vec4 pos1 = prMatrix*(mvMatrix*vec4(aPos1, 1.));\n  pos1 = pos1/pos1.w - gl_Position/gl_Position.w;\n  vec4 pos2 = prMatrix*(mvMatrix*vec4(aPos2, 1.));\n  pos2 = pos2/pos2.w - gl_Position/gl_Position.w;\n  normz = pos1.x*pos2.y - pos1.y*pos2.x;\n#endif\n#endif // IS_TWOSIDED\n  \n#ifdef NEEDS_VNORMAL\n  vNormal = vec4(normalize(vNormal.xyz), 1);\n#endif\n  \n#if defined(HAS_TEXTURE) || defined(IS_TEXT)\n  vTexcoord = aTexcoord;\n#endif\n  \n#if defined(FIXED_SIZE) && !defined(ROTATING)\n  vec4 pos = prMatrix * mvMatrix * vec4(aPos, 1.);\n  pos = pos/pos.w;\n  gl_Position = pos + vec4(aOfs*textScale, 0.);\n#endif\n  \n#if defined(IS_SPRITES) && !defined(FIXED_SIZE)\n  vec4 pos = mvMatrix * vec4(aPos, 1.);\n  pos = pos/pos.w + vec4(aOfs,  0.);\n  gl_Position = prMatrix*pos;\n#endif\n  \n#ifdef FAT_LINES\n  /* This code was inspired by Matt Deslauriers' code in \n   https://mattdesl.svbtle.com/drawing-lines-is-hard */\n  vec2 aspectVec = vec2(uAspect, 1.0);\n  mat4 projViewModel = prMatrix * mvMatrix;\n  vec4 currentProjected = projViewModel * vec4(aPos, 1.0);\n  currentProjected = currentProjected/currentProjected.w;\n  vec4 nextProjected = projViewModel * vec4(aNext, 1.0);\n  vec2 currentScreen = currentProjected.xy * aspectVec;\n  vec2 nextScreen = (nextProjected.xy / nextProjected.w) * aspectVec;\n  float len = uLwd;\n  vec2 dir = vec2(1.0, 0.0);\n  vPoint = aPoint;\n  vLength = length(nextScreen - currentScreen)/2.0;\n  vLength = vLength/(vLength + len);\n  if (vLength > 0.0) {\n    dir = normalize(nextScreen - currentScreen);\n  }\n  vec2 normal = vec2(-dir.y, dir.x);\n  dir.x /= uAspect;\n  normal.x /= uAspect;\n  vec4 offset = vec4(len*(normal*aPoint.x*aPoint.y - dir), 0.0, 0.0);\n  gl_Position = currentProjected + offset;\n#endif\n  \n#ifdef IS_BRUSH\n  gl_Position = vec4(aPos, 1.);\n#endif\n}","fragmentShader":"#line 2 2\n// File 2 is the fragment shader\n#ifdef GL_ES\n#ifdef GL_FRAGMENT_PRECISION_HIGH\nprecision highp float;\n#else\nprecision mediump float;\n#endif\n#endif\nvarying vec4 vCol; // carries alpha\nvarying vec4 vPosition;\n#if defined(HAS_TEXTURE) || defined (IS_TEXT)\nvarying vec2 vTexcoord;\nuniform sampler2D uSampler;\n#endif\n\n#ifdef HAS_FOG\nuniform int uFogMode;\nuniform vec3 uFogColor;\nuniform vec4 uFogParms;\n#endif\n\n#if defined(IS_LIT) && !defined(FIXED_QUADS)\nvarying vec4 vNormal;\n#endif\n\n#if NCLIPPLANES > 0\nuniform vec4 vClipplane[NCLIPPLANES];\n#endif\n\n#if NLIGHTS > 0\nuniform mat4 mvMatrix;\n#endif\n\n#ifdef IS_LIT\nuniform vec3 emission;\nuniform float shininess;\n#if NLIGHTS > 0\nuniform vec3 ambient[NLIGHTS];\nuniform vec3 specular[NLIGHTS]; // light*material\nuniform vec3 diffuse[NLIGHTS];\nuniform vec3 lightDir[NLIGHTS];\nuniform bool viewpoint[NLIGHTS];\nuniform bool finite[NLIGHTS];\n#endif\n#endif // IS_LIT\n\n#ifdef IS_TWOSIDED\nuniform bool front;\nvarying float normz;\n#endif\n\n#ifdef FAT_LINES\nvarying vec2 vPoint;\nvarying float vLength;\n#endif\n\n#ifdef USE_ENVMAP\nvarying vec3 vReflection;\n#endif\n\nvoid main(void) {\n  vec4 fragColor;\n#ifdef FAT_LINES\n  vec2 point = vPoint;\n  bool neg = point.y < 0.0;\n  point.y = neg ? (point.y + vLength)/(1.0 - vLength) :\n                 -(point.y - vLength)/(1.0 - vLength);\n#if defined(IS_TRANSPARENT) && defined(IS_LINESTRIP)\n  if (neg && length(point) <= 1.0) discard;\n#endif\n  point.y = min(point.y, 0.0);\n  if (length(point) > 1.0) discard;\n#endif // FAT_LINES\n  \n#ifdef ROUND_POINTS\n  vec2 coord = gl_PointCoord - vec2(0.5);\n  if (length(coord) > 0.5) discard;\n#endif\n  \n#if NCLIPPLANES > 0\n  for (int i = 0; i < NCLIPPLANES; i++)\n    if (dot(vPosition, vClipplane[i]) < 0.0) discard;\n#endif\n    \n#ifdef FIXED_QUADS\n    vec3 n = vec3(0., 0., 1.);\n#elif defined(IS_LIT)\n    vec3 n = normalize(vNormal.xyz);\n#endif\n    \n#ifdef IS_TWOSIDED\n    if ((normz <= 0.) != front) discard;\n#endif\n\n#ifdef IS_LIT\n    vec3 eye = normalize(-vPosition.xyz/vPosition.w);\n    vec3 lightdir;\n    vec4 colDiff;\n    vec3 halfVec;\n    vec4 lighteffect = vec4(emission, 0.);\n    vec3 col;\n    float nDotL;\n#ifdef FIXED_QUADS\n    n = -faceforward(n, n, eye);\n#endif\n    \n#if NLIGHTS > 0\n    // Simulate two-sided lighting\n    if (n.z < 0.0)\n      n = -n;\n    for (int i=0;i<NLIGHTS;i++) {\n      colDiff = vec4(vCol.rgb * diffuse[i], vCol.a);\n      lightdir = lightDir[i];\n      if (!viewpoint[i]) {\n        if (finite[i]) {\n          lightdir = (mvMatrix * vec4(lightdir, 1.)).xyz;\n        } else {\n          lightdir = (mvMatrix * vec4(lightdir, 0.)).xyz;\n        }\n      }\n      if (!finite[i]) {\n        halfVec = normalize(lightdir + eye);\n      } else {\n        lightdir = normalize(lightdir - vPosition.xyz/vPosition.w);\n        halfVec = normalize(lightdir + eye);\n      }\n      col = ambient[i];\n      nDotL = dot(n, lightdir);\n      col = col + max(nDotL, 0.) * colDiff.rgb;\n      col = col + pow(max(dot(halfVec, n), 0.), shininess) * specular[i];\n      lighteffect = lighteffect + vec4(col, colDiff.a);\n    }\n#endif\n    \n#else // not IS_LIT\n    vec4 colDiff = vCol;\n    vec4 lighteffect = colDiff;\n#endif\n    \n#ifdef IS_TEXT\n    vec4 textureColor = lighteffect*texture2D(uSampler, vTexcoord);\n#endif\n    \n#ifdef HAS_TEXTURE\n\n// These calculations use the definitions from \n// https://docs.gl/gl3/glTexEnv\n\n#ifdef USE_ENVMAP\n    float m = 2.0 * sqrt(dot(vReflection, vReflection) + 2.0*vReflection.z + 1.0);\n    vec4 textureColor = texture2D(uSampler, vReflection.xy / m + vec2(0.5, 0.5));\n#else\n    vec4 textureColor = texture2D(uSampler, vTexcoord);\n#endif\n\n#ifdef TEXTURE_rgb\n\n#if defined(TEXMODE_replace) || defined(TEXMODE_decal)\n    textureColor = vec4(textureColor.rgb, lighteffect.a);\n#endif \n\n#ifdef TEXMODE_modulate\n    textureColor = lighteffect*vec4(textureColor.rgb, 1.);\n#endif\n\n#ifdef TEXMODE_blend\n    textureColor = vec4((1. - textureColor.rgb) * lighteffect.rgb, lighteffect.a);\n#endif\n\n#ifdef TEXMODE_add\n    textureColor = vec4(lighteffect.rgb + textureColor.rgb, lighteffect.a);\n#endif\n\n#endif //TEXTURE_rgb\n        \n#ifdef TEXTURE_rgba\n\n#ifdef TEXMODE_replace\n// already done\n#endif \n\n#ifdef TEXMODE_modulate\n    textureColor = lighteffect*textureColor;\n#endif\n\n#ifdef TEXMODE_decal\n    textureColor = vec4((1. - textureColor.a)*lighteffect.rgb) +\n                     textureColor.a*textureColor.rgb, \n                     lighteffect.a);\n#endif\n\n#ifdef TEXMODE_blend\n    textureColor = vec4((1. - textureColor.rgb) * lighteffect.rgb,\n                    lighteffect.a*textureColor.a);\n#endif\n\n#ifdef TEXMODE_add\n    textureColor = vec4(lighteffect.rgb + textureColor.rgb,\n                    lighteffect.a*textureColor.a);\n#endif\n    \n#endif //TEXTURE_rgba\n    \n#ifdef TEXTURE_alpha\n    float luminance = dot(vec3(1.,1.,1.),textureColor.rgb)/3.;\n\n#if defined(TEXMODE_replace) || defined(TEXMODE_decal)\n    textureColor = vec4(lighteffect.rgb, luminance);\n#endif \n\n#if defined(TEXMODE_modulate) || defined(TEXMODE_blend) || defined(TEXMODE_add)\n    textureColor = vec4(lighteffect.rgb, lighteffect.a*luminance);\n#endif\n \n#endif // TEXTURE_alpha\n    \n// The TEXTURE_luminance values are not from that reference    \n#ifdef TEXTURE_luminance\n    float luminance = dot(vec3(1.,1.,1.),textureColor.rgb)/3.;\n\n#if defined(TEXMODE_replace) || defined(TEXMODE_decal)\n    textureColor = vec4(luminance, luminance, luminance, lighteffect.a);\n#endif \n\n#ifdef TEXMODE_modulate\n    textureColor = vec4(luminance*lighteffect.rgb, lighteffect.a);\n#endif\n\n#ifdef TEXMODE_blend\n    textureColor = vec4((1. - luminance)*lighteffect.rgb,\n                        lighteffect.a);\n#endif\n\n#ifdef TEXMODE_add\n    textureColor = vec4(luminance + lighteffect.rgb, lighteffect.a);\n#endif\n\n#endif // TEXTURE_luminance\n \n    \n#ifdef TEXTURE_luminance_alpha\n    float luminance = dot(vec3(1.,1.,1.),textureColor.rgb)/3.;\n\n#if defined(TEXMODE_replace) || defined(TEXMODE_decal)\n    textureColor = vec4(luminance, luminance, luminance, textureColor.a);\n#endif \n\n#ifdef TEXMODE_modulate\n    textureColor = vec4(luminance*lighteffect.rgb, \n                        textureColor.a*lighteffect.a);\n#endif\n\n#ifdef TEXMODE_blend\n    textureColor = vec4((1. - luminance)*lighteffect.rgb,\n                        textureColor.a*lighteffect.a);\n#endif\n\n#ifdef TEXMODE_add\n    textureColor = vec4(luminance + lighteffect.rgb, \n                        textureColor.a*lighteffect.a);\n\n#endif\n\n#endif // TEXTURE_luminance_alpha\n    \n    fragColor = textureColor;\n\n#elif defined(IS_TEXT)\n    if (textureColor.a < 0.1)\n      discard;\n    else\n      fragColor = textureColor;\n#else\n    fragColor = lighteffect;\n#endif // HAS_TEXTURE\n    \n#ifdef HAS_FOG\n    // uFogParms elements: x = near, y = far, z = fogscale, w = (1-sin(FOV/2))/(1+sin(FOV/2))\n    // In Exp and Exp2: use density = density/far\n    // fogF will be the proportion of fog\n    // Initialize it to the linear value\n    float fogF;\n    if (uFogMode > 0) {\n      fogF = (uFogParms.y - vPosition.z/vPosition.w)/(uFogParms.y - uFogParms.x);\n      if (uFogMode > 1)\n        fogF = mix(uFogParms.w, 1.0, fogF);\n      fogF = fogF*uFogParms.z;\n      if (uFogMode == 2)\n        fogF = 1.0 - exp(-fogF);\n      // Docs are wrong: use (density*c)^2, not density*c^2\n      // https://gitlab.freedesktop.org/mesa/mesa/-/blob/master/src/mesa/swrast/s_fog.c#L58\n      else if (uFogMode == 3)\n        fogF = 1.0 - exp(-fogF*fogF);\n      fogF = clamp(fogF, 0.0, 1.0);\n      gl_FragColor = vec4(mix(fragColor.rgb, uFogColor, fogF), fragColor.a);\n    } else gl_FragColor = fragColor;\n#else\n    gl_FragColor = fragColor;\n#endif // HAS_FOG\n    \n}","players":[],"webGLoptions":{"preserveDrawingBuffer":true},"fastTransparency":true},"evals":[],"jsHooks":[]}