Lucas Bertoni - 7 months ago 67

Python Question

Edit: I managed to figure out what was going on. Scatter has a parameter 'line-width' (lw=n) that determines the thickness of the line surrounding the plot point for a scatter plot. Because my plot points were size 1 (s=1), the line width was so thick it was actually covering the colour of the plot point. Setting the line-width to a thickness of 0 (lw=0) should do the trick.

I want to generate a 3d scatterplot of data-points, colouring them based on the value of their y-coordinate, but I can't manage to get the points to actually colour.

If the value of the datapoint is low, the colour should be closer to the blue-end of the colour spectrum. If the value is higher the, the colour should be closer to the red-end of the spectrum.

I've managed to plot what I want in 2D, but am having trouble replicating the process in 3D. The current code only plots the points in black.

Here is my code for the 3D attempt, and a screenshot of the desired results in 2D. What exactly am I doing wrong here?

x_points, y_points, and z_points are lists of float values.

`import matplotlib.pyplot as plt`

from matplotlib import cm

from mpl_toolkits.mplot3d import Axes3D

def three_dimensional_scatterplot(

self, x_points, y_points, z_points, data_file

):

cm1 = cm.get_cmap('gist_rainbow')

fig = plt1.figure()

ax = fig.add_subplot(111, projection='3d')

ax.scatter(

x_points,

y_points,

z_points,

s=1,

c=y_points,

cmap=cm1

)

ax.set_xlabel('X axis')

plt1.show()

Answer

You have to plot like here:

```
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
x = np.random.rand(25)
y = np.random.rand(25)
z = np.random.rand(25)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
p3d = ax.scatter(x, y, z, s=30, c=y, cmap = cm.coolwarm)
plt.show()
```