My Smart plotter to reduce some redundance in code (uses matplotlib)

SmartPlot.py

import matplotlib.pyplot as plt
from typing import List, Tuple
import math
import numpy as np

class SmartPlot:
    @staticmethod
    def plot_single_image(image,
                          title,
                          colorbar=False):
        plt.imshow(image)
        plt.title(title)
        if colorbar:
            plt.colorbar()
        plt.show()
    
    @staticmethod
    def get_dimensions(N):
        sqrt = round(math.sqrt(N))
        if sqrt * sqrt == N:
            return (sqrt, sqrt)
        for m in range(5, 0, -1):
            if N % m == 0:
                return (N//m, m)
    
    @classmethod
    def plot_multi_images(cls,
                          images: List,
                          titles: List,
                          figsize: Tuple[int, int],
                          axis: List | str = 'on',
                          cmaps: List | str = 'virdis',
                          suptitle: str | None = None,
                          dimensions: Tuple[int, int] | None = None,
                          colorbar: bool | List[bool] = False,
                          return_fig_axis: bool = False
                          ):
        num_images = len(images)
        if dimensions is None:
            dimensions = cls.get_dimensions(num_images)
        if type(colorbar) is bool:
            colorbar = [colorbar] * num_images
        if type(axis) is str:
            axis = [axis] * num_images
        if type(cmaps) is str:
            cmaps = [cmaps] * num_images

        fig, ax = plt.subplots(*dimensions, figsize=figsize)
        ax = np.array(ax).flatten()

        for i, (img, title, cbar) in enumerate(zip(images, titles, colorbar)):
            t = ax[i].imshow(img, cmap=cmaps[i])
            if title:
                ax[i].set_title(title)
            if cbar:
                plt.colorbar(t)
            ax[i].axis(axis[i])
        
        if suptitle:
            fig.suptitle(suptitle)
        if return_fig_axis:
            return fig, ax
        else:
            plt.show()