Added plot_image_grid function to sigmoidal module

sigmoidal/__init__.py

@@ -1 +1 @@
-from sigmoidal.utils.notebook import plot_image
+from sigmoidal.utils.notebook import plot_image, plot_images_grid

sigmoidal/utils/notebook.py

@@ -5,21 +5,99 @@
 import numpy as np
 
 
+def plot_images_grid(
+    images: List[np.ndarray],
+    grid_size: Tuple[int, int],
+    titles: Optional[List[str]] = None,
+    size: Tuple[int, int] = (10, 10),
+    cmap: str = 'gray',
+) -> None:
+    """
+    Display a grid of images with optional titles.
+
+    Parameters
+    ----------
+    images : List[np.ndarray]
+        A list of images to be displayed. Each image should be a NumPy array.
+
+    grid_size : Tuple[int, int]
+        A tuple specifying the number of rows and columns in the grid layout.
+
+    titles : Optional[List[str]], default=None
+        An optional list of titles for each subplot. The list should have the same length as `images`.
+
+    size : Tuple[int, int], default=(10, 10)
+        A tuple specifying the width and height of the entire plot figure.
+
+    cmap : str, default='gray'
+        The colormap used for displaying single-channel images.
+
+    Raises
+    ------
+    ValueError
+        If the number of images exceeds the total spots in the grid.
+
+    Example
+    -------
+    >>> images = [np.random.rand(10, 10) for _ in range(4)]
+    >>> plot_images_grid(images, grid_size=(2, 2), titles=['Img1', 'Img2', 'Img3', 'Img4'])
+
+    Returns
+    -------
+    None
+    """
+    rows, cols = grid_size
+
+    if len(images) > rows * cols:
+        raise ValueError('Number of images exceeds grid size.')
+
+    # Creating a figure with a specified size
+    plt.figure(figsize=size)
+
+    for i, img in enumerate(images):
+        # Creating subplots
+        plt.subplot(rows, cols, i + 1)
+
+        # If the image is single channel (like grayscale), use the specified colormap
+        if len(img.shape) == 2:
+            plt.imshow(img, cmap=cmap)
+        else:
+            # Convert from BGR to RGB since OpenCV loads in BGR format
+            plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
+
+        # Optional titles
+        if titles is not None:
+            plt.title(titles[i])
+
+        # Removing x and y ticks
+        plt.xticks([])
+        plt.yticks([])
+
+    plt.show()
+
+
 def plot_image(
-        image: np.ndarray,
-        size: Tuple[int, int] = (10, 10),
-        cmap: Optional[str] = 'gray'
+    image: np.ndarray,
+    size: Tuple[int, int] = (5, 5),
+    cmap: Optional[str] = 'gray',
 ) -> None:
     """
-    Exibe uma imagem carregada pelo OpenCV em um Jupyter notebook.
+    Display an image loaded with OpenCV in a Jupyter notebook.
+
+    Parameters
+    ----------
+    image : np.ndarray
+        The image to be displayed.
+
+    size : Tuple[int, int], default=(10, 10)
+        The size of the figure in which the image will be displayed (width, height).
 
-    Parâmetros:
-        image (np.ndarray): Imagem a ser exibida.
-        size (tuple): Tamanho da figura na qual a imagem será exibida (largura, altura).
-        cmap (str): Mapa de cores a ser usado se a imagem for em escala de cinza.
+    cmap : Optional[str], default='gray'
+        The colormap to be used if the image is grayscale.
 
-    Retorno:
-        None
+    Returns
+    -------
+    None
     """
     plt.figure(figsize=size)
 
@@ -28,5 +106,5 @@ def plot_image(
     else:
         plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
 
-    plt.axis("off")
+    plt.axis('off')
     plt.show()