问XY数据的逐点面元编号和面元高度(使用Python)

EN

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

np.random.seed(9)

x = np.round(10*np.random.rand(12), 1)
y = np.round(10*np.random.rand(12), 1)

binrange=([x.min(), x.max()+1], [y.min(), y.max()+1]

h, ex, ey = np.histogram2d(x, y, bins=5, range=binrange), density=False)
nx = np.digitize(x, bins=ex)
ny = np.digitize(y, bins=ey)

print('Why do my points fall into empty bins??')
print('Values:', '\n', x, '\n', y, '\n')
print('Bins', '\n', ex, '\n', ey, '\n')
print('Bin numbers:\n', nx, '\n', ny, '\n')

sns.histplot(x=x, y=y, bins=5, binrange=binrange), cbar=True)
sns.scatterplot(x=x, y=y, s=15, color='k')
plt.suptitle('What I expect to see')

 Values: 
 [0.1 5.  5.  1.3 1.4 2.2 4.2 2.5 0.8 3.5 1.7 8.8] 
 [9.5 0.4 7.  5.7 9.  6.7 5.5 7.  3.9 6.9 8.2 4.7] 

Bins 
 [0.1  2.04 3.98 5.92 7.86 9.8 ] 
 [ 0.4   2.42  4.44  6.46  8.48 10.5 ] 

Bin numbers:
 [1 3 3 1 1 2 3 2 1 2 1 5] 
 [5 1 4 3 5 4 3 4 2 4 4 3] 

plt.imshow(np.rot90(h, 1), 
           extent=[x.min(), x.max()+1, y.min(), y.max()+1], origin='upper', cmap='Blues')
plt.colorbar()
plt.scatter(x=x, y=y, s=10, color='k')

def transform(distrA, limitsA, limitsB):
    '''Transforms distribution of unevenly distributed points in a space A to space B"
    Input:
    distrA - numpy 2D array [[arrdim1 ...], [arrdim2 ...], [arrdim3 ...], [arrdim4 ...]] - 
             Distribution to be transformed.
    limitsA and limitsB - (array of pairs) - 
             Limits of space A and B, correspondingly, in the form (lower, higher)
        
    Output:
    distrB - transformed distribution'''
    
    shape=distrA.shape
    distrB = np.empty(shape=distrA.shape)
    for i in range(shape[0]):
        spanA = limitsA[i][1] - limitsA[i][0]
        spanB = limitsB[i][1] - limitsB[i][0]
        for j in range(shape[1]):  
            distrB[i, j] = spanB * (distrA[i, j]-limitsA[i][0]) / spanA + limitsB[i][0]
        
    return distrB

hm=sns.heatmap(np.rot90(h, 1), cmap='Blues', annot=True)
h_trans=transform(np.asarray([x, y]), 
                  [[x.min(), x.max()+1], [y.min(), y.max()+1]], 
                  ((0,5), (5,0))
                  )

sns.scatterplot(x=h_trans[0], y=h_trans[1], s=20, color='k')
plt.title('Desired seaborn heatmap')