How to use python imshow, for example, with the irregular data points?

Question

Suppose I have a list of data points of the form (xi, yi, zi) and I want to plot a 2D density plot with it. In mathematica, you just call the function ListDensityPlot function. In python, it seems density plot is achieved by using imshow. However, it seems the required data should be in regular form. How to get the similar effect given the data sets?

Here is the mathematica code:

n = 100;
xs = RandomReal[1, n];
ys = RandomReal[1, n];
zs = xs + ys;
data = Table[{xs[[i]], ys[[i]], zs[[i]]}, {i, n}];
ListDensityPlot[data, PlotRange -> All, PlotLegends -> Automatic]

The effect of the above code is (of course, one can set the range to remove the white regions):

In python, I have generated the data, how to throw it into a function list_density_plot to achieve similar effects?

def f(x, y):
    return x+y

N = 100
xs = np.random.random(N)
ys = np.random.random(N)
zs = f(xs, ys)

data = [(xs[i], ys[i], zs[i]) for i in range(N)]
list_density_plot(data)  # ???

philgzl · Accepted Answer · 2024-03-13 10:42:59Z

2

I think you are looking for plt.tricontourf or plt.tripcolor.

Example with plt.tripcolor:

import matplotlib.pyplot as plt
import numpy as np


def f(x, y):
    return x + y


N = 100
xs = np.random.random(N)
ys = np.random.random(N)
zs = f(xs, ys)

plt.tripcolor(xs, ys, zs)
plt.show()

answered Mar 13, 2024 at 10:42

philgzl

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