Python中的 Matplotlib.pyplot.hist2d()

Matplotlib是Python中的一个库，它是 NumPy 库的数值数学扩展。 Pyplot是Matplotlib模块的基于状态的接口，它提供了一个类似 MATLAB 的接口。

matplotlib.pyplot.hist2d()函数

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

Syntax:matplotlib.pyplot.hist2d(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.pyplot 中的 matplotlib.pyplot.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) + 50
   
plt.hist2d(x, y,
           bins = 100, 
           norm = colors.LogNorm(), 
           cmap ="gray")
  
plt.title('matplotlib.pyplot.hist2d() function \
Example\n\n', fontweight ="bold")
  
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=1000000),
    multivariate_normal([30, 20],
            [[2, 3], [1, 3]], size=100000)
])
  
plt.hist2d(result[:, 0],
           result[:, 1],
           bins = 100, 
           cmap = "Greens",
           norm = colors.LogNorm())
plt.title('matplotlib.pyplot.hist2d function \
Example')
plt.show()
  
plt.hist2d(result[:, 0], 
           result[:, 1],
           bins = 100, 
           cmap = "RdYlGn_r",
           norm = colors.LogNorm())
plt.show()

输出：