Python中的 Matplotlib.axes.Axes.hist2d()

Matplotlib是Python中的一个库，它是 NumPy 库的数值数学扩展。 Axes 类包含大部分图形元素：Axis、Tick、Line2D、Text、Polygon 等，并设置坐标系。 Axes 的实例通过回调属性支持回调。

matplotlib.axes.Axes.hist2d()函数

matplotlib 库的 axes 模块中的Axes.hist2d()函数用于制作二维直方图。

Syntax: Axes.hist2d(self, x, y, bins=10, range=None, density=False, weights=None, cmin=None, cmax=None, *, data=None, **kwargs)

Parameters: This method accept the following parameters that are described below:

x, y : These parameter are the sequence of data.
bins : This parameter is an optional parameter and it contains the integer or sequence or string.
range : This parameter is an optional parameter and it the lower and upper range of the bins.
density : This parameter is an optional parameter and it contains the boolean values.
weights : This parameter is an optional parameter and it is an array of weights, of the same shape as x.
cmin : This parameter has all bins that has count less than cmin will not be displayed.
cmax : This parameter has all bins that has count more than cmax will not be displayed.

Returns: This returns the following:

h :This returns the bi-dimensional histogram of samples x and y.
xedges :This returns the bin edges along the x axis.
yedges :This returns the bin edges along the y axis.
image :This returns the QuadMesh.

编程需要懂一点英语

下面的示例说明了 matplotlib.axes 中的 matplotlib.axes.Axes.hist2d()函数：

示例 1：

# Implementation of matplotlib function
from matplotlib import colors
from matplotlib.ticker import PercentFormatter
import numpy as np
import matplotlib.pyplot as plt
  
N_points = 100000
x = np.random.randn(N_points)
y = .4 * x + np.random.randn(100000) + 5
  
fig, ax = plt.subplots()
ax.hist2d(x, y, bins = 100, 
          norm = colors.LogNorm(),
          cmap ="Greens")
  
ax.set_title('matplotlib.axes.Axes.\
hist2d() Example')
  
plt.show()

输出：

示例 2：

# Implementation of matplotlib function
from matplotlib import colors
import numpy as np
from numpy.random import multivariate_normal
import matplotlib.pyplot as plt
  
result = np.vstack([
    multivariate_normal([10, 10],
            [[3, 2], [2, 3]], size = 100000),
    multivariate_normal([30, 20],
            [[2, 3], [1, 3]], size = 1000)
])
  
fig, [axes, axes1] = plt.subplots(nrows = 2, 
                                  ncols = 1,
                                  sharex = True)
  
axes.hist2d(result[:, 0], result[:, 1],
            bins = 100, cmap ="GnBu",
            norm = colors.LogNorm())
  
axes1.hist2d(result[:, 0], result[:, 1],
             bins = 100, norm = colors.LogNorm())
  
axes.set_title('matplotlib.axes.Axes.\
hist2d() Example')
  
plt.show()

输出：