Function matshow3d

monai/visualize/utils.py:34–161

Create a 3D volume figure as a grid of images. Args: volume: 3D volume to display. data shape can be `BCHWD`, `CHWD` or `HWD`. Higher dimensional arrays will be reshaped into (-1, H, W, [C]), `C` depends on `channel_dim` arg. A list of channel-first (C, H[,

(
    volume: NdarrayOrTensor,
    fig: Any = None,
    title: str | None = None,
    figsize: tuple[int, int] = (10, 10),
    frames_per_row: int | None = None,
    frame_dim: int = -3,
    channel_dim: int | None = None,
    vmin: float | None = None,
    vmax: float | None = None,
    every_n: int = 1,
    interpolation: str = "none",
    show: bool = False,
    fill_value: Any = np.nan,
    margin: int = 1,
    dtype: DtypeLike = np.float32,
    **kwargs: Any,
)

def matshow3d(
    volume: NdarrayOrTensor,
    fig: Any = None,
    title: str | None = None,
    figsize: tuple[int, int] = (10, 10),
    frames_per_row: int | None = None,
    frame_dim: int = -3,
    channel_dim: int | None = None,
    vmin: float | None = None,
    vmax: float | None = None,
    every_n: int = 1,
    interpolation: str = "none",
    show: bool = False,
    fill_value: Any = np.nan,
    margin: int = 1,
    dtype: DtypeLike = np.float32,
    **kwargs: Any,
) -> tuple[Any, np.ndarray]:
    """
    Create a 3D volume figure as a grid of images.

    Args:
        volume: 3D volume to display. data shape can be `BCHWD`, `CHWD` or `HWD`.
            Higher dimensional arrays will be reshaped into (-1, H, W, [C]), `C` depends on `channel_dim` arg.
            A list of channel-first (C, H[, W, D]) arrays can also be passed in,
            in which case they will be displayed as a padded and stacked volume.
        fig: matplotlib figure or Axes to use. If None, a new figure will be created.
        title: title of the figure.
        figsize: size of the figure.
        frames_per_row: number of frames to display in each row. If None, sqrt(firstdim) will be used.
        frame_dim: for higher dimensional arrays, which dimension from (`-1`, `-2`, `-3`) is moved to
            the `-3` dimension. dim and reshape to (-1, H, W) shape to construct frames, default to `-3`.
        channel_dim: if not None, explicitly specify the channel dimension to be transposed to the
            last dimensionas shape (-1, H, W, C). this can be used to plot RGB color image.
            if None, the channel dimension will be flattened with `frame_dim` and `batch_dim` as shape (-1, H, W).
            note that it can only support 3D input image. default is None.
        vmin: `vmin` for the matplotlib `imshow`.
        vmax: `vmax` for the matplotlib `imshow`.
        every_n: factor to subsample the frames so that only every n-th frame is displayed.
        interpolation: interpolation to use for the matplotlib `matshow`.
        show: if True, show the figure.
        fill_value: value to use for the empty part of the grid.
        margin: margin to use for the grid.
        dtype: data type of the output stacked frames.
        kwargs: additional keyword arguments to matplotlib `matshow` and `imshow`.

    See Also:
        - https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html
        - https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.matshow.html

    Example:

        >>> import numpy as np
        >>> import matplotlib.pyplot as plt
        >>> from monai.visualize import matshow3d
        # create a figure of a 3D volume
        >>> volume = np.random.rand(10, 10, 10)
        >>> fig = plt.figure()