Multicolor/size issues

[slinnarsson]

Setting colors per datapoint doesn't work:

import ipyvolume
x = np.array([1,2,3,4,5])
y = np.array([2,4,3,2,1])
z = np.array([9,8,3,4,1])
#c = np.array(['red','green','blue','yellow','cyan'])
#c = np.array([(1,1,0), (1,1,0), (1,1,0), (1,1,0), (1,1,0)])
#c = [[1,1,0], [1,1,0],[1,1,0],[1,1,0],[1,1,0]]
c = [1,1,0]
ipyvolume.quickscatter(x, y, z, color=c, size=0.1, marker="sphere")

The result is white spheres in every case.

Also, setting the size doesn't work:

import ipyvolume
x = np.array([1,2,3,4,5])
y = np.array([2,4,3,2,1])
z = np.array([9,8,3,4,1])
s = np.array([1, 2, 3, 4, 5])/10
ipyvolume.quickscatter(x, y, z, color='blue', size=s, marker="sphere")

The result is no spheres at all.

Probably I'm misunderstanding the API, but an example would help.

Finally, I think the case where the color is given as a 1D array of floats should be reserved for a colormap, NOT interpreted as an rgb value. By default, the matplotlib default colormap should be used, or a custom colormap given by the parameter cmap=.

Tagging @jeammimi

[jeammimi]

I think both cases were fixed in the last commit
Also try setting the size to 1, because apparently 0.1 is quite small.

[maartenbreddels]

In the first example, replace size by 10. Initially, size (or s argument) was a fraction of the box size, but since humans aren't that good with numbers between 0 and 1, I switched to percentages, so 100 is the size of the box/volume, 10 is 10% of it. It will be in the changelog for the next release, sorry for this, that's the fate of early adopters I'm afraid ;). For the 2nd example it's the same, try removing the /10. Also, i'm not adopting matplotlib's short argument names (s versus size), since we have tab-completion in the notebook, and that leads to more readable code.

I'm working on examples, stay tuned for the next release.
I agree with you on the colormap.
What is planned for color is these options:

• shape is 0 dim, and it's a string, interpret as color
• shape is 1 dim, items are strings, seperate color for each item
• shape is 2 dim, items are strings, sequence of the above
• no color scale / colormap is set
• shape is 1 dim, items are floats, it should be of length 3 -> rgb values (possibly later 4 for opacity)
• shape is 2 dim, items are float, it should be of shape (len(x), 3) -> rgb values
• shape is 3 dim, items are float, it should be (sequence_length, len(x), 3) -> rgb values
• color scale / colormap is set
  • shape is 0 dim, item if float, use the colorscale to map to color
  • shape is 1 dim, it's a seperate color for each item
  • shape is 2 dim, again a sequence

without having a default colormap/colorscale, it will try to interpret it as rgb values, when a colorscale is set, it will use that. For now you have to use matplotlib's colormaps directly (opacity is ignored):

import ipyvolume
import matplotlib.cm
x = np.array([1,2,3,4,5])
y = np.array([2,4,3,2,1])
z = np.array([9,8,3,4,1])
c = matplotlib.cm.afmhot(np.linspace(0, 1, len(x)))
ipyvolume.quickscatter(x, y, z, color=c, size=10, marker="sphere")

I'd like to delay colormap/colorscale in ipyvolume until jupyter-widgets/ipywidgets#1153 takes more shape.

Let me know if this answer your questions.

[slinnarsson]

Thanks - it works!

[maartenbreddels]

👍 for letting me know