Matplotlib : display array values with imshow

You want to loop over the values in grid, and use ax.text to add the label to the plot.

Fortunately, for 2D arrays, numpy has ndenumerate, which makes this quite simple:

for (j,i),label in np.ndenumerate(grid):    ax1.text(i,j,label,ha='center',va='center')    ax2.text(i,j,label,ha='center',va='center')

If for any reason you have to use a different extent from the one that is provided naturally by imshow the following method (even if more contrived) does the job:

size = 4data = np.arange(size * size).reshape((size, size))# Limits for the extentx_start = 3.0x_end = 9.0y_start = 6.0y_end = 12.0extent = [x_start, x_end, y_start, y_end]# The normal figurefig = plt.figure(figsize=(16, 12))ax = fig.add_subplot(111)im = ax.imshow(data, extent=extent, origin='lower', interpolation='None', cmap='viridis')# Add the textjump_x = (x_end - x_start) / (2.0 * size)jump_y = (y_end - y_start) / (2.0 * size)x_positions = np.linspace(start=x_start, stop=x_end, num=size, endpoint=False)y_positions = np.linspace(start=y_start, stop=y_end, num=size, endpoint=False)for y_index, y in enumerate(y_positions):    for x_index, x in enumerate(x_positions):        label = data[y_index, x_index]        text_x = x + jump_x        text_y = y + jump_y        ax.text(text_x, text_y, label, color='black', ha='center', va='center')fig.colorbar(im)plt.show()

If you want to put other type of data and not necessarily the values that you used for the image you can modify the script above in the following way (added values after data):

size = 4data = np.arange(size * size).reshape((size, size))values = np.random.rand(size, size)# Limits for the extentx_start = 3.0x_end = 9.0y_start = 6.0y_end = 12.0extent = [x_start, x_end, y_start, y_end]# The normal figurefig = plt.figure(figsize=(16, 12))ax = fig.add_subplot(111)im = ax.imshow(data, extent=extent, origin='lower', interpolation='None', cmap='viridis')# Add the textjump_x = (x_end - x_start) / (2.0 * size)jump_y = (y_end - y_start) / (2.0 * size)x_positions = np.linspace(start=x_start, stop=x_end, num=size, endpoint=False)y_positions = np.linspace(start=y_start, stop=y_end, num=size, endpoint=False)for y_index, y in enumerate(y_positions):    for x_index, x in enumerate(x_positions):        label = values[y_index, x_index]        text_x = x + jump_x        text_y = y + jump_y        ax.text(text_x, text_y, label, color='black', ha='center', va='center')fig.colorbar(im)plt.show()