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napari_ndev.image_overview #

Function and class to create and manage image overviews with stackview.

It includes a function image_overview to generate an overview of images and a class ImageOverview to generate and save image overviews.

ImageOverview #

A class for generating and saving image overviews.

Use this class to prevent a memory leak otherwise generated by the image_overview() function when show=True. For some reason, preventing the memory leak requires the use of a class instead of a function, and show=False.

Source code in src/napari_ndev/image_overview.py 
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class ImageOverview:
    """
    A class for generating and saving image overviews.

    Use this class to prevent a memory leak otherwise generated by the
    image_overview() function when show=True. For some reason, preventing
    the memory leak requires the use of a class instead of a function, and
    show=False.
    """

    def __init__(
        self,
        image_sets: list[dict],
        xscale: float = 3,
        yscale: float = 3,
        image_title: str = '',
        show: bool = False,
    ):
        """
        Initialize an ImageOverivew object.

        Parameters
        ----------
        image_sets : list of dict
            A list of dictionaries containing image sets. See
            `napari_ndev.image_overview` for more information.
        xscale : float, optional
            The scale factor for the x-axis. Default is 3.
        yscale : float, optional
            The scale factor for the y-axis. Default is 3.
        image_title : str, optional
            The title of the image overview. Default is an empty string.
        show : bool, optional
            Whether to display the generated overview. Default is False.
            Prevents memory leak when False.

        """
        plt.ioff()
        self.fig = image_overview(image_sets, xscale, yscale, image_title)
        if show:
            plt.show()
        plt.close()

    def save(
        self,
        directory: str | None = None,
        filename: str | None = None,
    ):
        """
        Save the generated image overview with matplotlib.savefig.

        Parameters
        ----------
        directory : str, optional
            The directory to save the image overview. If not provided, the
            current directory will be used.
        filename : str, optional
            The filename of the saved image overview. If not provided, a
            default filename will be used.

        """
        import pathlib

        path_dir = pathlib.Path(directory)
        path_dir.mkdir(parents=True, exist_ok=True)
        filepath = path_dir / filename
        self.fig.savefig(filepath)

__init__ #

__init__(image_sets, xscale=3, yscale=3, image_title='', show=False)

Initialize an ImageOverivew object.

Parameters:

  • image_sets #

    (list of dict) –

    A list of dictionaries containing image sets. See napari_ndev.image_overview for more information.

  • xscale #

    (float, default: 3 ) –

    The scale factor for the x-axis. Default is 3.

  • yscale #

    (float, default: 3 ) –

    The scale factor for the y-axis. Default is 3.

  • image_title #

    (str, default: '' ) –

    The title of the image overview. Default is an empty string.

  • show #

    (bool, default: False ) –

    Whether to display the generated overview. Default is False. Prevents memory leak when False.

Source code in src/napari_ndev/image_overview.py 
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def __init__(
    self,
    image_sets: list[dict],
    xscale: float = 3,
    yscale: float = 3,
    image_title: str = '',
    show: bool = False,
):
    """
    Initialize an ImageOverivew object.

    Parameters
    ----------
    image_sets : list of dict
        A list of dictionaries containing image sets. See
        `napari_ndev.image_overview` for more information.
    xscale : float, optional
        The scale factor for the x-axis. Default is 3.
    yscale : float, optional
        The scale factor for the y-axis. Default is 3.
    image_title : str, optional
        The title of the image overview. Default is an empty string.
    show : bool, optional
        Whether to display the generated overview. Default is False.
        Prevents memory leak when False.

    """
    plt.ioff()
    self.fig = image_overview(image_sets, xscale, yscale, image_title)
    if show:
        plt.show()
    plt.close()

save #

save(directory=None, filename=None)

Save the generated image overview with matplotlib.savefig.

Parameters:

  • directory #

    (str, default: None ) –

    The directory to save the image overview. If not provided, the current directory will be used.

  • filename #

    (str, default: None ) –

    The filename of the saved image overview. If not provided, a default filename will be used.

Source code in src/napari_ndev/image_overview.py 
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def save(
    self,
    directory: str | None = None,
    filename: str | None = None,
):
    """
    Save the generated image overview with matplotlib.savefig.

    Parameters
    ----------
    directory : str, optional
        The directory to save the image overview. If not provided, the
        current directory will be used.
    filename : str, optional
        The filename of the saved image overview. If not provided, a
        default filename will be used.

    """
    import pathlib

    path_dir = pathlib.Path(directory)
    path_dir.mkdir(parents=True, exist_ok=True)
    filepath = path_dir / filename
    self.fig.savefig(filepath)

image_overview #

image_overview(image_sets, xscale=3, yscale=3, plot_title='')

Create an overview of images.

Parameters:

  • image_sets #

    (list of dict) –

    A list of dictionaries, each containing an image set. Each image set should be a dictionary containing the following keys: - image (list): A list of images to display. - title (list of str, optional): The title of the image set. - colormap (list of str, optional): The colormap to use. "labels" will display the image as labels. - labels (list of bool, optional): Whether to display labels. - **kwargs: Additional keyword arguments to pass to stackview.imshow.

  • xscale #

    (float, default: 3 ) –

    The x scale of the overview. Defaults to 3.

  • yscale #

    (float, default: 3 ) –

    The y scale of the overview. Defaults to 3.

  • plot_title #

    (str, default: '' ) –

    The title of the plot. Defaults to an empty string.

Returns:

  • fig ( Figure ) –

    The matplotlib figure object containing the image overview.

Source code in src/napari_ndev/image_overview.py 
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def image_overview(
    image_sets: list[dict],
    xscale: float = 3,
    yscale: float = 3,
    plot_title: str = '',
):
    """
    Create an overview of images.

    Parameters
    ----------
    image_sets : list of dict
        A list of dictionaries, each containing an image set. Each image set
        should be a dictionary containing the following keys:
        - image (list): A list of images to display.
        - title (list of str, optional): The title of the image set.
        - colormap (list of str, optional): The colormap to use.
            "labels" will display the image as labels.
        - labels (list of bool, optional): Whether to display labels.
        - **kwargs: Additional keyword arguments to pass to stackview.imshow.
    xscale : float, optional
        The x scale of the overview. Defaults to 3.
    yscale : float, optional
        The y scale of the overview. Defaults to 3.
    plot_title : str, optional
        The title of the plot. Defaults to an empty string.

    Returns
    -------
    fig : matplotlib.figure.Figure
        The matplotlib figure object containing the image overview.

    """
    # create the subplot grid
    num_rows = len(image_sets)
    num_columns = max([len(image_set['image']) for image_set in image_sets])
    fig, axs = plt.subplots(
        num_rows,
        num_columns,
        figsize=(num_columns * xscale, num_rows * yscale),
    )

    if num_rows == 1:
        axs = [axs]
    if num_columns == 1:
        axs = [[ax] for ax in axs]

    # iterate through the image sets
    for row, image_set in enumerate(image_sets):
        for col, _image in enumerate(image_set['image']):
            # create a dictionary from the col-th values of each key
            image_dict = {key: value[col] for key, value in image_set.items()}

            # turn off the subplot and continue if there is no image
            if image_dict.get('image') is None:
                axs[row][col].axis('off')
                continue

            # create a labels key if it doesn't exist, but does in colormap
            cmap = image_dict.get('colormap')
            if cmap is not None and cmap.lower() == 'labels':
                image_dict['labels'] = True

            stackview.imshow(**image_dict, plot=axs[row][col])

    plt.suptitle(plot_title, fontsize=16)
    plt.tight_layout()
    # plt.subplots_adjust(wspace=0.1, hspace=0.1)

    return fig