Re: [Matplotlib-users] color in plot3d

[Mike A. <ma...@ry...>]

First what version of mpl are you using? if it is recent  this colour word already exists,  I asked about this a couple months ago and i should point you first to the example in the svn it does a checkerboard, but i cannot remember the exact name. Although i know it plots a checkerboard effect on one of the example plots. 

 

The way that color keyword is set up,  it is dedsigned to take a color word or  rgba tuple , (Reinier will know this better than me), however if you want to just assign colors based on a colour map you can take you color array  and reshape  the same way the plot surface command does  then  use surf.set_array()

 

here is a snippet of the code I use to do this I am pretty sure it won’t run the way it is right now but the idea is buried in there

 

note that regmap xyz and costmapz are all the same size and are nxm matrices costmapout is a 2x(m.n) if i can do the math correctly 

 

 

    from mpl_toolkits.mplot3d import Axes3D

    from matplotlib import cm

    import numpy as np

#--------------------------------------------------

    ax = Axes3D(fig)

    

    scale= 3   

    surf = ax.plot_surface(regMAPx ,regMAPy,-regMAPz ,  rstride=scale,cstride=scale, cmap=cm.jet, linewidth=.250 )

 

# to reshape the cost map to match grid used in plot surf

    rows, cols = costMAPz.shape

    costmapout = []

    for rs in np.arange(0, rows-1, scale):

        for cs in np.arange(0, cols-1, scale):

            costmapout.append(costMAPz[rs][cs])

 

    costmapout=np.array(costmapout)

    surf.set_array(costmapout)

 

## do your show plot stuff here!!

 

 

 

 

 

Mike Alger

 

From: Pablo Angulo [mailto:pab...@ua...] 
Sent: June-11-10 7:04 AM
To: mat...@li...
Subject: [Matplotlib-users] color in plot3d

 

   Hello!
   I wonder if there is a way to make 3d plots specifying arbitrary colors, instead of having the color be a function of the height. I was able to achieve this making minimal changes to the plot_surface method of Axes3D, adding as an optional keyword argument a function cfun which specifies the color (it specifies a real number that is mapped into a color by the color map cmap). But is there a standard way?
   Regard
Pablo Angulo



from matplotlib.colors import Normalize, colorConverter
def plot_surface(self, X, Y, Z, *args, **kwargs):
    '''
    Create a surface plot.
 
    By default it will be colored in shades of a solid color,
    but it also supports color mapping by supplying the *cmap*
    argument.
 
    ==========  ================================================
    Argument    Description
    ==========  ================================================
    *X*, *Y*,   Data values as numpy.arrays
    *Z*
    *rstride*   Array row stride (step size)
    *cstride*   Array column stride (step size)
    *color*     Color of the surface patches
    *cmap*      A colormap for the surface patches.
    *cfun*      The function giving the color
    ==========  ================================================
    '''
 
    had_data = self.has_data()
 
    rows, cols = Z.shape
    tX, tY, tZ = np.transpose(X), np.transpose(Y), np.transpose(Z)
    rstride = kwargs.pop('rstride', 10)
    cstride = kwargs.pop('cstride', 10)
 
    color = kwargs.pop('color', 'b')
    color = np.array(colorConverter.to_rgba(color))
    cmap = kwargs.get('cmap', None)
    cfun = kwargs.pop('cfun', None)
    polys = []
    normals = []
    avgz = []
    if not cfun:
        cfun = lambda p:p[2]
 
    for rs in np.arange(0, rows-1, rstride):
        for cs in np.arange(0, cols-1, cstride):
            ps = []
            corners = []
            for a, ta in [(X, tX), (Y, tY), (Z, tZ)]:
                ztop = a[rs][cs:min(cols, cs+cstride+1)]
                zleft = ta[min(cols-1, cs+cstride)][rs:min(rows, rs+rstride+1)]
                zbase = a[min(rows-1, rs+rstride)][cs:min(cols, cs+cstride+1):]
                zbase = zbase[::-1]
                zright = ta[cs][rs:min(rows, rs+rstride+1):]
                zright = zright[::-1]
                corners.append([ztop[0], ztop[-1], zbase[0], zbase[-1]])
                z = np.concatenate((ztop, zleft, zbase, zright))
                ps.append(z)
 
            # The construction leaves the array with duplicate points, which
            # are removed here.
            ps = zip(*ps)
            lastp = np.array([])
            ps2 = []
            avgzsum = 0.0
            for p in ps:
                if p != lastp:
                    ps2.append(p)
                    lastp = p
                    avgzsum += cfun(p)
            polys.append(ps2)
            avgz.append(avgzsum / len(ps2))
 
            v1 = np.array(ps2[0]) - np.array(ps2[1])
            v2 = np.array(ps2[2]) - np.array(ps2[0])
            normals.append(np.cross(v1, v2))
 
    polyc = art3d.Poly3DCollection(polys, *args, **kwargs)
    if cmap is not None:
        polyc.set_array(np.array(avgz))
        polyc.set_linewidth(0)
    else:
        colors = self._shade_colors(color, normals)
        polyc.set_facecolors(colors)
 
    self.add_collection(polyc)
    self.auto_scale_xyz(X, Y, Z, had_data)
 
    return polyc

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