How to add/append customized plot in for loop to Single subplot in Python using Matplotlib?-CodePudding

I do realize this has already been addressed here (e.g.,

I want to add the above-customized plot in for loop to one single plot as subplots.

for i in [somelist]:
    pretty_plot_confusion_matrix(i, annot=True, cmap="Oranges", fmt='.2f', fz=11,
      lw=0.5, cbar=False, figsize=[5,5], show_null_values=0, pred_val_axis='y')

   # Add/append plot to subplots

Example of Desired Output:

CodePudding user response：

Okay so I went through the library's github repository and the issue is that the figure and axes objects are created internally which means that you can't create multiple plots on the same figure. I created a somewhat hacky solution by forking the library. This is the forked library I created to do what you want. And here is a an example piece of code:

matrices = [np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]]),
            np.array( [[13,  0,  1,  0,  2,  0],[ 0, 50,  2,  0, 10,  0],[ 0, 13, 16,  0,  0,  3],[ 0,  0,  0, 13,  1,  0],[ 0, 40,  0,  1, 15,  0],[ 0,  0,  0,  0,  0, 20]])]
fig = plt.figure(tight_layout=True)
ax = fig.add_gridspec(3,3)
ax_list = [] #list containing axes objects
for i in range(9):
    ax_list.append(fig.add_subplot(ax[i%3,i//3])) 
    df_cm = DataFrame(matrices[i], index=range(1,7), columns=range(1,7))
    pretty_plot_confusion_matrix(df_cm, ax_list[i], annot=True, cmap="Oranges", fmt='.2f', fz=7,
    lw=0.5, cbar=False, show_null_values=0, pred_val_axis='y')
plt.show()

Let me know if there are any issues (Oh and be careful with fontsizes).