在Python中绘制一个网格，颜色对应于不同的值

Question

我试图绘制一个网格，其中为每个值绘制相应的颜色。例如：

[[1,1,1,1,1,1,1,1,1],  
[1,0,0,0,0,0,0,0,1],  
[1,0,0,0,2,2,0,0,1],  
[1,0,0,0,2,2,0,0,1],  
[1,1,1,1,1,1,1,1,1]] 

将显示为带有蓝色边框一9X5栅格（1），填充有黑色（0），与红色的2×2块在底部（2）。

显然这可以用imshow完成，但我不知道语法是什么。

在此先感谢您的帮助！

Answer 1

一种解决方案与matplotlib和NumPy的：

import numpy as np 
import matplotlib.pyplot as plt 


def show_values(pc, fmt="%.2f", **kw): 
    ''' 
    Heatmap with text in each cell with matplotlib's pyplot 
    Source: http://stackoverflow.com/a/25074150/395857 
    By HYRY 
    ''' 
    from itertools import izip 
    pc.update_scalarmappable() 
    ax = pc.get_axes() 
    for p, color, value in izip(pc.get_paths(), pc.get_facecolors(), pc.get_array()): 
     x, y = p.vertices[:-2, :].mean(0) 
     if np.all(color[:3] > 0.5): 
      color = (0.0, 0.0, 0.0) 
     else: 
      color = (1.0, 1.0, 1.0) 
     ax.text(x, y, fmt % value, ha="center", va="center", color=color, **kw) 

def cm2inch(*tupl): 
    ''' 
    Specify figure size in centimeter in matplotlib 
    Source: http://stackoverflow.com/a/22787457/395857 
    By gns-ank 
    ''' 
    inch = 2.54 
    if type(tupl[0]) == tuple: 
     return tuple(i/inch for i in tupl[0]) 
    else: 
     return tuple(i/inch for i in tupl) 

def heatmap(AUC, title, xlabel, ylabel, xticklabels, yticklabels): 
    ''' 
    Inspired by: 
    - http://stackoverflow.com/a/16124677/395857 
    - http://stackoverflow.com/a/25074150/395857 
    ''' 

    # Plot it out 
    fig, ax = plt.subplots()  
    c = ax.pcolor(AUC, edgecolors='k', linestyle= 'dashed', linewidths=0.2, cmap='YlOrRd', vmin=0.0, vmax=2.0) 

    # put the major ticks at the middle of each cell 
    ax.set_yticks(np.arange(AUC.shape[0]) + 0.5, minor=False) 
    ax.set_xticks(np.arange(AUC.shape[1]) + 0.5, minor=False) 

    # set tick labels 
    #ax.set_xticklabels(np.arange(1,AUC.shape[1]+1), minor=False) 
    ax.set_xticklabels(xticklabels, minor=False) 
    ax.set_yticklabels(yticklabels, minor=False) 

    # set title and x/y labels 
    plt.title(title) 
    plt.xlabel(xlabel) 
    plt.ylabel(ylabel)  

    # Remove last blank column 
    plt.xlim((0, AUC.shape[1])) 

    # Turn off all the ticks 
    ax = plt.gca()  
    for t in ax.xaxis.get_major_ticks(): 
     t.tick1On = False 
     t.tick2On = False 
    for t in ax.yaxis.get_major_ticks(): 
     t.tick1On = False 
     t.tick2On = False 

    # Add color bar 
    plt.colorbar(c) 

    # Add text in each cell 
    show_values(c) 

    # resize 
    fig = plt.gcf() 
    fig.set_size_inches(cm2inch(40, 20)) 



def main(): 
    data = np.array([[1,1,1,1,1,1,1,1,1],  
        [1,0,0,0,0,0,0,0,1],  
        [1,0,0,0,2,2,0,0,1],  
        [1,0,0,0,2,2,0,0,1],  
        [1,1,1,1,1,1,1,1,1]]) 
    x_axis_size = data.shape[1] 
    y_axis_size = data.shape[0] 
    title = "Title" 
    xlabel= "xlabel" 
    ylabel="ylabel" 
    xticklabels = range(1, x_axis_size+1) # could be text 
    yticklabels = range(1, y_axis_size+1) # could be text 
    heatmap(data, title, xlabel, ylabel, xticklabels, yticklabels) 
    plt.savefig('image_output.png', dpi=300, format='png', bbox_inches='tight') # use format='svg' or 'pdf' for vectorial pictures 
    plt.show() 


if __name__ == "__main__": 
    main() 
    #cProfile.run('main()') # if you want to do some profiling