This will work as expected if you call "scatter3d" instead. The 3D interface needs a bit of an overhaul... I agree that something like "scatter" on x/y/z should properly produce a 3D scatter. It's on my radar.
On Tue, Mar 8, 2016 at 11:16 AM, <[email protected]> wrote: > Is it possible to do this color plot for a 3D example?. In this case the > color of the markers will depend on another expression: > > using Plots > pyplot(leg = false, size = (400,300)) > x = linspace(0,20,100) > y = sin(x) > z = cos(x) > scatter(x,y,z, zcolor=20*x + y, marker = (:o, stroke(1))) > > > > On Tuesday, March 8, 2016 at 9:49:36 AM UTC-6, Tom Breloff wrote: >> >> It's possible you have an old version... try doing >> Pkg.checkout("Plots"). I'll get around to tagging a new version soon. >> >> On Tue, Mar 8, 2016 at 10:47 AM, <[email protected]> wrote: >> >>> >>> >>> On Tuesday, March 8, 2016 at 9:41:14 AM UTC-6, [email protected] wrote: >>>> >>>> Thank you very much Tom! However, my plot is not showing the colors, >>>> it's just black, do you know what can be happening? >>>> >>>> On Tuesday, March 8, 2016 at 9:33:39 AM UTC-6, Tom Breloff wrote: >>>>> >>>>> You can almost copy that verbatim with PyPlot.jl, or here's the same >>>>> in Plots: >>>>> >>>>> [image: Inline image 1] >>>>> >>>>> >>>>> On Tue, Mar 8, 2016 at 9:51 AM, <[email protected]> wrote: >>>>> >>>>>> Hello Julia Users, >>>>>> >>>>>> PyPlot has some modules related to color plots. However the >>>>>> documentation in Julia don't address the following application (in >>>>>> Python): >>>>>> >>>>>> import numpy as npimport matplotlib.pyplot as plt >>>>>> >>>>>> x = np.linspace(0, 20, 100) >>>>>> y = np.sin(x) >>>>>> z = x + 20 * y >>>>>> >>>>>> scaled_z = (z - z.min()) / z.ptp() >>>>>> colors = plt.cm.coolwarm(scaled_z) >>>>>> >>>>>> plt.scatter(x, y, marker='+', edgecolors=colors, s=150, linewidths=4) >>>>>> plt.show() >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> Does anyone know how can I define the "colors" as above and plot in >>>>>> Julia the same example? >>>>>> >>>>>> Any information is really helpful. >>>>>> >>>>>> Thank you very much. >>>>>> >>>>> >>>>> >>
