2d Density Plot With X Y Z Data

I am trying to plot 2d terrain map with x,y and z (elevation). I followed the steps from the following link but I am getting very weird plot. Python : 2d contour plot from 3 lists

Solution 1:

I think the problem is that the data you're giving it is not smooth enough to interpolate with the default parameters. Here's one approach, using mgrid instead of meshgrid:

import numpy as np
import pandas as pd
from scipy.interpolate import Rbf

# fname is your data, but as a CSV file.
data = pd.read_csv(fname).values
x, y = data.T

x_min, x_max = np.amin(x), np.amax(x)
y_min, y_max = np.amin(y), np.amax(y)

# Make a grid with spacing 0.002.
grid_x, grid_y = np.mgrid[x_min:x_max:0.002, y_min:y_max:0.002]

# Make up a Z.
z = np.hamming(x.size)

# Make an n-dimensional interpolator.
rbfi = Rbf(x, y, z, smooth=2)

# Predict on the regular grid.
di = rbfi(grid_x, grid_y)

Then you can look at the result:

import matplotlib.pyplotas plt

plt.imshow(di)

I get:

I wrote a Jupyter Notebook on this topic recently, check it out for a few other interpolation methods, like kriging and spline fitting.