Matplotlib 渲染所有内部体素(带 alpha) [英] Matplotlib render all internal voxels (with alpha)
问题描述
我想在 matplotlib 中渲染一个体积.体积是一个简单的 7x7x7 立方体，我希望能够看到所有内部体素(即使我知道它看起来会一团糟).
我已经能够渲染具有透明度的体素，但是任何不在表面上的体素似乎永远不会被绘制.
体积的每个 7x7 切片应如下所示:
我拼凑了一个 MWE
以下代码创建一个 5x5x5 的体积，其中包含红色、绿色、蓝色、黄色和青色 5x5 层.每层的 alpha 设置为 0.5，所以整个东西应该是透明的.
然后我将所有非表面体素的颜色更改为带有 alpha 1 的黑色，因此如果它们显示出来，我们应该能够在中心看到一个黑框.
单独渲染它会产生左侧的图形，但是如果我们从青色层中删除填充，我们可以看到黑框确实存在，因为它被100％遮挡了，所以即使它被遮挡，它也不会被显示那些遮挡体素的alpha小于1.
将matplotlib.pyplot导入为plt从mpl_toolkits.mplot3d导入Axes3D#NOQA空间轴 = [5, 5, 5]填充 = np.ones(spatial_axes, dtype=np.bool)颜色 = np.empty(spatial_axes + [4], dtype=np.float32)阿尔法 = .5colors [0] = [1、0、0，alpha]colors [1] = [0，1，0，alpha]颜色[2] = [0, 0, 1, alpha]colors [3] = [1，1，0，alpha]colors [4] = [0，1，1，alpha]#将所有内部颜色设置为带有alpha = 1的黑色colors [1:-1，1:-1，1:-1，0:3] = 0颜色 [1:-1, 1:-1, 1:-1, 3] = 1无花果= plt.figure()ax = fig.add_subplot('111'，projection ='3d')ax.voxels(填充，facecolors=colors，edgecolors='k')无花果= plt.figure()ax = fig.add_subplot('111'，projection ='3d')Filled [-1] = Falseax.voxels(填充，facecolors=colors，edgecolors='k')
有什么方法可以渲染所有被遮挡的体素?
要将上面的评论变成答案:
- 你可能总是像这样绘制所有体素
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I want to render a volume in matplotlib. The volume is a simple 7x7x7 cube, and I want to be able to see all internal voxels (even though I know it will look like a mess).
I've been able to render voxels with transparency, but any voxel not on the surface seems to never be drawn.
Each 7x7 slice of the volume should look like this:
I've thrown together a MWE
The following code creates a 5x5x5 volume with a red,green,blue,yellow, and cyan 5x5 layers. The alpha of each layer is set to .5, so the whole thing should be see-through.
Then I chang the colors of all non-surface voxels to black with alpha 1, so if they were showing we should be able to see a black box in the center.
Rendering it by itself produces the figure on the left, but if we remove the fill from the cyan layer, we can see that the black box does indeed exist, it is just not being shown because it is 100% occluded even though those occluding voxels have alpha less than 1.
import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D # NOQA spatial_axes = [5, 5, 5] filled = np.ones(spatial_axes, dtype=np.bool) colors = np.empty(spatial_axes + [4], dtype=np.float32) alpha = .5 colors[0] = [1, 0, 0, alpha] colors[1] = [0, 1, 0, alpha] colors[2] = [0, 0, 1, alpha] colors[3] = [1, 1, 0, alpha] colors[4] = [0, 1, 1, alpha] # set all internal colors to black with alpha=1 colors[1:-1, 1:-1, 1:-1, 0:3] = 0 colors[1:-1, 1:-1, 1:-1, 3] = 1 fig = plt.figure() ax = fig.add_subplot('111', projection='3d') ax.voxels(filled, facecolors=colors, edgecolors='k') fig = plt.figure() ax = fig.add_subplot('111', projection='3d') filled[-1] = False ax.voxels(filled, facecolors=colors, edgecolors='k')Is there any way to render all occluded voxels?
解决方案To turn my comments above into an answer:
- You may always just plot all voxels as in
- The official example solves this problem by offsettingt the faces of the voxels by a bit, such they are all drawn.
- This matplotlib issue discusses the missing faces on internal cubes. There is a pull request which has some issues still and it hence not merged yet.
Despite the small issues, you may monkey patch the current status of the pull request into your code:
import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D, art3d # NOQA from matplotlib.cbook import _backports from collections import defaultdict import types def voxels(self, *args, **kwargs): if len(args) >= 3: # underscores indicate position only def voxels(__x, __y, __z, filled, **kwargs): return (__x, __y, __z), filled, kwargs else: def voxels(filled, **kwargs): return None, filled, kwargs xyz, filled, kwargs = voxels(*args, **kwargs) # check dimensions if filled.ndim != 3: raise ValueError("Argument filled must be 3-dimensional") size = np.array(filled.shape, dtype=np.intp) # check xyz coordinates, which are one larger than the filled shape coord_shape = tuple(size + 1) if xyz is None: x, y, z = np.indices(coord_shape) else: x, y, z = (_backports.broadcast_to(c, coord_shape) for c in xyz) def _broadcast_color_arg(color, name): if np.ndim(color) in (0, 1): # single color, like "red" or [1, 0, 0] return _backports.broadcast_to( color, filled.shape + np.shape(color)) elif np.ndim(color) in (3, 4): # 3D array of strings, or 4D array with last axis rgb if np.shape(color)[:3] != filled.shape: raise ValueError( "When multidimensional, {} must match the shape of " "filled".format(name)) return color else: raise ValueError("Invalid {} argument".format(name)) # intercept the facecolors, handling defaults and broacasting facecolors = kwargs.pop('facecolors', None) if facecolors is None: facecolors = self._get_patches_for_fill.get_next_color() facecolors = _broadcast_color_arg(facecolors, 'facecolors') # broadcast but no default on edgecolors edgecolors = kwargs.pop('edgecolors', None) edgecolors = _broadcast_color_arg(edgecolors, 'edgecolors') # include possibly occluded internal faces or not internal_faces = kwargs.pop('internal_faces', False) # always scale to the full array, even if the data is only in the center self.auto_scale_xyz(x, y, z) # points lying on corners of a square square = np.array([ [0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0] ], dtype=np.intp) voxel_faces = defaultdict(list) def permutation_matrices(n): """ Generator of cyclic permutation matices """ mat = np.eye(n, dtype=np.intp) for i in range(n): yield mat mat = np.roll(mat, 1, axis=0) for permute in permutation_matrices(3): pc, qc, rc = permute.T.dot(size) pinds = np.arange(pc) qinds = np.arange(qc) rinds = np.arange(rc) square_rot = square.dot(permute.T) for p in pinds: for q in qinds: p0 = permute.dot([p, q, 0]) i0 = tuple(p0) if filled[i0]: voxel_faces[i0].append(p0 + square_rot) # draw middle faces for r1, r2 in zip(rinds[:-1], rinds[1:]): p1 = permute.dot([p, q, r1]) p2 = permute.dot([p, q, r2]) i1 = tuple(p1) i2 = tuple(p2) if filled[i1] and (internal_faces or not filled[i2]): voxel_faces[i1].append(p2 + square_rot) elif (internal_faces or not filled[i1]) and filled[i2]: voxel_faces[i2].append(p2 + square_rot) # draw upper faces pk = permute.dot([p, q, rc-1]) pk2 = permute.dot([p, q, rc]) ik = tuple(pk) if filled[ik]: voxel_faces[ik].append(pk2 + square_rot) # iterate over the faces, and generate a Poly3DCollection for each voxel polygons = {} for coord, faces_inds in voxel_faces.items(): # convert indices into 3D positions if xyz is None: faces = faces_inds else: faces = [] for face_inds in faces_inds: ind = face_inds[:, 0], face_inds[:, 1], face_inds[:, 2] face = np.empty(face_inds.shape) face[:, 0] = x[ind] face[:, 1] = y[ind] face[:, 2] = z[ind] faces.append(face) poly = art3d.Poly3DCollection(faces, facecolors=facecolors[coord], edgecolors=edgecolors[coord], **kwargs ) self.add_collection3d(poly) polygons[coord] = poly return polygons spatial_axes = [5, 5, 5] filled = np.ones(spatial_axes, dtype=np.bool) colors = np.empty(spatial_axes + [4], dtype=np.float32) alpha = .5 colors[0] = [1, 0, 0, alpha] colors[1] = [0, 1, 0, alpha] colors[2] = [0, 0, 1, alpha] colors[3] = [1, 1, 0, alpha] colors[4] = [0, 1, 1, alpha] # set all internal colors to black with alpha=1 colors[1:-1, 1:-1, 1:-1, 0:3] = 0 colors[1:-1, 1:-1, 1:-1, 3] = 1 fig = plt.figure() ax = fig.add_subplot('111', projection='3d') ax.voxels = types.MethodType(voxels, ax) ax.voxels(filled, facecolors=colors, edgecolors='k',internal_faces=True) fig = plt.figure() ax = fig.add_subplot('111', projection='3d') ax.voxels = types.MethodType(voxels, ax) filled[-1] = False ax.voxels(filled, facecolors=colors, edgecolors='k',internal_faces=True) plt.show()这篇关于Matplotlib 渲染所有内部体素(带 alpha)的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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