mplot3d

As I present here (in 2D), I'm wondering if how I could "scale" an image input to be plotted to a range in the plot. To be more clear, this is what I need: I have a 400 * 400 image that is generated based on a function which interval is -1..1. So, I do a translate to save this data, like this: x = Utils.translate(pos_x, 0, self.width, -1, 1) y = Utils.translate(pos_y, 0, self.height, -1, 1) data = Utils.map_position_to_function(x, y) I.e, first I map its position to my range and then I calculate de f(x, y) based on this "new position" and save the data. Also, as I save this image, I do a

When making a figure using the mplot3d package, three gray walls are automatically created and the axis ticks and grid lines are placed along these walls, as shown in this mplot3d example which I will be referring to later . These walls are positioned such that they are placed slightly outside the given axis limits. For instance, as you can see in the figure of the referred example, the vertical grid walls stretch from slightly below 0 to slightly above 1. A negative side effect of this is that the bottom wall (the floor of the plot, if you will), is placed at a z coordinate slightly below 0.

I know that matplotlib 3D is not reliable for plotting multiple 3D objects (planes, lines, points) in the right order: please see Matplotlib 3D plot zorder issue and How to draw intersecting planes? . However these questions seem quite old, so the proposed solutions. Thus, I would like to know if there are some new developments, tools, workarounds or hard-coded solutions for the following specific simple scenario: import mpl_toolkits.mplot3d as a3 import matplotlib.pylab as plt import numpy as np fig = plt.figure() ax = a3.Axes3D(fig) # create an orizontal plane corners = [[0,0,0],[0,5,0],[5,5

If I have a 3D matplotlib plot ( Axes3D object), how do I change the color of the tick marks? I figured out how to change the color of the axis line, the tick labels, and the axis label. The obvious solution, use ax.tick_params(axis='x', colors='red') , only changes the tick labels not the tick marks themselves. Here is code that tries to change all the axes to red and gets everything but the tick marks: from mpl_toolkits.mplot3d import Axes3D from matplotlib import pyplot as plt fig = plt.figure() ax = Axes3D(fig) ax.scatter((0, 0, 1), (0, 1, 0), (1, 0, 0)) ax.w_xaxis.line.set_color('red') ax

I'm trying to plot in 3D colouring the surface with predefined colours using facecolors . The problem here is that cm.ScalarMappable normalizes surface V of colours while plt.cm.jet don't normalizes, so there is a mismatch of colours and colorbar. I've manually tried to normalize V (i.e. V_normalized ) but the result is still not quite correct. In fact, the highest value of V should be in a corner of the surface, but this is not reflected in the image in practice. How to plot ensuring to have the corrects colours on the surface? import numpy as np import pandas as pd import matplotlib.pyplot