Hi Ravi,
Here is a script that does what you want but it isn't too pretty.
from mayavi import mlab
import numpy as np
x, y, z = np.random.random((3, 100))
rgba = np.random.randint(0, 256, size=(100, 4), dtype=np.uint8)
rgba[:, -1] = 255
src = mlab.pipeline.scalar_scatter(x, y, z)
src.add_attribute(rgba, 'colors')
src.data.point_data.set_active_scalars('colors')
g = mlab.pipeline.glyph(src)
g.glyph.glyph.scale_factor = 0.1
# To update the colors later, call the dataset's modified method to update the
UI as below.
rgba[:, 1] = 0
src.data.modified()
mlab.show()
I wish this were easier to do but it isn't currently. Also the above requires
Mayavi 4.6.1 (which should be pip installable).
cheers,
Prabhu
On 7/25/18 12:28 AM, mys...@ravijoshi.info wrote:
> Hi,
>
> Thank you very much for the suggestions.
>
> I tried scalar and colormap arguments of points3d function but it didn't work.
> Let me explain you the requirements briefly-
> 1) I have some points in 3-dimensional space
> 2) All of these points have a color value associated with it. The color value
> is packed RGB value using the following formulation- rgb = (r<<16) + (g<<8) +
> b
> 3) My goal is to visualize these color points
>
> In short, I have a numpy array of shape (N,4) where first 3 columns are
> positions and last column is the packed color value. Below is the best what I
> could get so far-
>
> -----------------------------------------------------------
> import numpy as np
> from mayavi import mlab
>
> N = 40000
> scale = 0.1
> ones = np.ones(N)
> scalars = np.arange(N)
> (x, y, z) = np.random.random((3, N))
> # assume packed RGB value is unpacked into (r, g, b) individually
> colors = (np.random.random((N, 4)) * 255).astype(np.uint8) # RGBA
> colors[:,-1] = 255 # no transparency
>
> mlab.figure()
> pts = mlab.quiver3d(x, y, z, ones, ones, ones, scalars=scalars, mode='sphere',
> scale_factor=scale)
> pts.glyph.color_mode = 'color_by_scalar'
> pts.module_manager.scalar_lut_manager.lut.table = colors
> mlab.show()
> -----------------------------------------------------------
>
> The above code snippet takes RGBA color in a numpy array of shape (N,4). I am
> able to unpack RGB into (r, g, b) individually in another code. However, I am
> not able to scale down the radius of all points.
>
> I want to know that how to scale down all the points?
>
> Also, based on my requirements, if you have any better idea in your mind to
> achieve the same, please let me know.
>
> -
> Thanks
> Ravi
>
>
>
> On 2018-07-22 23:06, Shankar Kulumani wrote:
>> The documentation shows a solution by using an additional scalar value
>> and a colormap:
>>
>> The documentation is very thorough and shows a good example as well
>>
>> http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html#points3d
>>
>> import numpy
>> from mayavi.mlab import *
>>
>> def test_points3d():
>> t = numpy.linspace(0, 4 * numpy.pi, 20)
>> cos = numpy.cos
>> sin = numpy.sin
>>
>> x = sin(2 * t)
>> y = cos(t)
>> z = cos(2 * t)
>> s = 2 + sin(t)
>>
>> return points3d(x, y, z, s, colormap="copper", scale_factor=.25)
>>
>> On Sun, Jul 22, 2018 at 4:39 AM <mys...@ravijoshi.info> wrote:
>>
>>> Hi,
>>>
>>> Thank you very much. I almost reached there. points3d is working
>>> however, I am having a hard time in assigning colors to each point.
>>> Please see the code snippet below-
>>>
>>> -------------------------------------
>>> import numpy as np
>>> from mayavi import mlab
>>>
>>> # generate random data (just for checking)
>>> pts = 10 # number of points (just for checking)
>>> x = np.arange(pts)
>>> y = np.arange(pts)
>>> z = np.arange(pts)
>>> c = np.random.rand(pts, 3) #r, g, b values
>>>
>>> mlab.figure()
>>> mlab.points3d(x, y, z, color=c)
>>> mlab.show()
>>> -------------------------------------
>>>
>>> The above code throws following error-
>>> The 'color' trait of a GlyphFactory instance must be a tuple of the
>>> form: (0.0 <= a floating point number <= 1.0, 0.0 <= a floating
>>> point
>>> number <= 1.0, 0.0 <= a floating point number <= 1.0) or None, but a
>>>
>>> value of array([[...]]) <type 'numpy.ndarray'> was specified.
>>>
>>> It seems that the color is a tuple i.e., (r, g, b)in mlab.points3d()
>>>
>>> function and it is globally applied to all points. However, in my
>>> case,
>>> each point has a color value, which is different from others.
>>>
>>> The simplest thing which came to my mind is to assign each point one
>>> by
>>> one as shown below-
>>>
>>> -------------------------------------
>>> mlab.figure()
>>> for i in range(pts):
>>> mlab.points3d(x[i], y[i], z[i], color=tuple(c[i].reshape(-1)))
>>> mlab.show()
>>> -------------------------------------
>>>
>>> This works fine for a few points. However, I have approximately
>>> 40,000
>>> points and the above approach isn't working!
>>>
>>> -
>>> Thanks
>>> Ravi
>>>
>>> On 2018-07-21 22:12, Shankar Kulumani wrote:
>>>> This function will do exactly what you want
>>>>
>>>>
>>>
>> http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html#points3d
>>>>
>>>> Example
>>>>
>>>> points3d(x, y, z...)
>>>> points3d(x, y, z, s, ...)
>>>> points3d(x, y, z, f, ...)
>>>>
>>>> On Sat, Jul 21, 2018, 03:12 <mys...@ravijoshi.info> wrote:
>>>>
>>>>> Hello,
>>>>>
>>>>> I am new to mayavi and I am trying to use mayavi in python to
>>>>> visualize
>>>>> a point cloud. I have a colored point cloud
>>>>> (PointCloud<PointXYZRGB>)
>>>>> stored in a numpy array of shape (40000, 4). The first three
>>> columns
>>>>> of
>>>>> this array are the position in 3D space (x, y, z) and the last
>>>>> column is
>>>>> RGB color packed in one using the following formulation-
>>>>>
>>>>> // pack r/g/b into rgb
>>>>> uint8_t r = 255, g = 0, b = 0; // Example: Red color
>>>>> uint32_t rgb = ((uint32_t)r << 16 | (uint32_t)g << 8 |
>>> (uint32_t)b);
>>>>>
>>>>> Hence, the point cloud contains 40,000 points in which each point
>>>>> has a
>>>>> color assigned to it.
>>>>>
>>>>> I want to know if it is possible to visualize it using mayavi
>>>>> python?
>>>>> Any sample code will be appreciated more.
>>>>>
>>>>> -
>>>>> Thanks
>>>>> Ravi
>>>>>
>>>>>
>>>>
>>>
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