Python:从Numpy矩阵创建2D直方图 [英] Python: Creating a 2D histogram from a numpy matrix

问题描述

我是python的新手.

I'm new to python.

我有一个numpy矩阵，尺寸为42x42，其值在0-996范围内.我想使用此数据创建2D直方图.我一直在看教程，但是它们似乎都显示了如何根据随机数据而非numpy矩阵创建2D直方图.

I have a numpy matrix, of dimensions 42x42, with values in the range 0-996. I want to create a 2D histogram using this data. I've been looking at tutorials, but they all seem to show how to create 2D histograms from random data and not a numpy matrix.

到目前为止，我已经导入:

So far, I have imported:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors

我不确定这些输入是否正确，我只是想从我所看到的教程中学到什么.

I'm not sure if these are correct imports, I'm just trying to pick up what I can from tutorials I see.

我有一个numpy矩阵M，其中包含所有值(如上所述).最后，我希望它看起来像这样:

I have the numpy matrix M with all of the values in it (as described above). In the end, i want it to look something like this:

很显然，我的数据会有所不同，所以我的情节应该看起来有所不同.有人可以帮我吗?

obviously, my data will be different, so my plot should look different. Can anyone give me a hand?

出于我的目的，下面的 Hooked 正是使用matshow的示例，正​​是我想要的.

For my purposes, Hooked's example below, using matshow, is exactly what I'm looking for.

推荐答案

如果您有来自计数的原始数据，则可以使用plt.hexbin为您创建图(恕我直言，这比正方形格子更好):改编自 hexbin :

If you have the raw data from the counts, you could use plt.hexbin to create the plots for you (IMHO this is better than a square lattice): Adapted from the example of hexbin:

import numpy as np
import matplotlib.pyplot as plt

n = 100000
x = np.random.standard_normal(n)
y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
plt.hexbin(x,y)

plt.show()

如果您已经提到矩阵中已经有Z值，则只需使用plt.imshow或plt.matshow:

If you already have the Z-values in a matrix as you mention, just use plt.imshow or plt.matshow:

XB = np.linspace(-1,1,20)
YB = np.linspace(-1,1,20)
X,Y = np.meshgrid(XB,YB)
Z = np.exp(-(X**2+Y**2))
plt.imshow(Z,interpolation='none')

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