Contour plot in Python importing txt table file

matplotlib, python

Solution

Followup from my comment... first, I would replace all these lines:

data = np.loadtxt(r'dataa.txt')

a = [data[:,0]]
b = [data[:,1]]
n = [data[:,2]]

x = np.asarray(a)
y = np.asarray(b)
z = np.asarray(n)

With:

x, y, z = np.genfromtxt(r'dataa.txt', unpack=True)

Your original code is adding an extra axis at the front, since `[data[:,0]]` is a list of arrays with one element. The result is that `x.shape` will be `(1, N)` instead if `(N,)`. All of this can be done automatically using the last line above, or you could just use the same `data` loading and say:

x = data[:,0]
y = data[:,1]
z = data[:,2]

since those slices will give you an array back.

However, you're not quite done, because `plt.contour` expects you to give it a 2d array for `z`, not a 1d array of values. Right now, you seem to have `z` values at given `x, y` points, but `contour` expects you to give it a 2d array, like an image.

Before I can answer that, I need to know how `x` and `y` are spaced. If regularly, you can just populate an array pretty easily. If not regularly, you basically have to interpolate before you can make a contour plot.

To do the interpolation, use

import numpy as np
import matplotlib.pyplot as plt
import scipy.interpolate

N = 1000 #number of points for plotting/interpolation

x, y, z = np.genfromtxt(r'dataa.txt', unpack=True)

xi = np.linspace(x.min(), x.max(), N)
yi = np.linspace(y.min(), y.max(), N)
zi = scipy.interpolate.griddata((x, y), z, (xi[None,:], yi[:,None]), method='cubic')

fig = plt.figure()
plt.contour(xi, yi, zi)
plt.xlabel("X")
plt.ylabel("Y")
plt.show()

Problem

Original source