Visualise detected centre and tracked fibre

To visualise volume accross the slice, detected centres and tracked fibre

fibretracker.viz

fibretracker.viz.orthogonal

orthogonal(vol, cmap='gray', img_height=5, img_width=5)

Interactive widget for visualizing orthogonal slices of a 3D volume.

Parameters:

Name	Type	Description	Default
vol	ndarray or Tensor	The 3D volume to be sliced.	required
cmap	str	Specifies the color map for the image. Defaults to "gray".	'gray'
img_height(int,	optional	Height of the figure.	required
img_width(int,	optional	Width of the figure.	required

Returns:

Name	Type	Description
orthogonal_obj	HBox	The interactive widget for visualizing orthogonal slices of a 3D volume.

Example

import fibretracker as ft

vol = ft.io.load("path/to/volume.txm")
ft.viz.orthogonal(vol, cmap="gray")

Source code in fibretracker/viz/visualize.py

def orthogonal(
    vol: np.ndarray,
    cmap: str = "gray",
    img_height: int = 5,
    img_width: int = 5
)-> widgets.HBox:
    """Interactive widget for visualizing orthogonal slices of a 3D volume.

    Args:
        vol (np.ndarray or torch.Tensor): The 3D volume to be sliced.
        cmap (str, optional): Specifies the color map for the image. Defaults to "gray".
        img_height(int, optional): Height of the figure.
        img_width(int, optional): Width of the figure.

    Returns:
        orthogonal_obj (widgets.HBox): The interactive widget for visualizing orthogonal slices of a 3D volume.

    Example:
        ```python
        import fibretracker as ft

        vol = ft.io.load("path/to/volume.txm")
        ft.viz.orthogonal(vol, cmap="gray")
        ```
        ![viz orthogonal](figures/viz-orthogonal.gif)
    """

    fig, ax = plt.subplots(1, 3, figsize=(3*img_width, img_height))
    ax[0].axis("off")
    ax[1].axis("off")
    ax[2].axis("off")

    def _slice(slice_idx_z, slice_idx_y, slice_idx_x):
        slice_img_z = vol.take(slice_idx_z, axis=0)
        slice_img_y = vol.take(slice_idx_y, axis=1)
        slice_img_x = vol.take(slice_idx_x, axis=2)

        ax[0].imshow(slice_img_z, cmap=cmap)
        ax[0].set_aspect('equal')
        ax[1].imshow(slice_img_y, cmap=cmap)
        ax[1].set_aspect('equal')
        ax[2].imshow(slice_img_x, cmap=cmap)
        ax[2].set_aspect('equal')

    slice_slider_z = widgets.IntSlider(
        value=vol.shape[0] // 2,
        min=0,
        max=vol.shape[0] - 1,
        description="Z",
        continuous_update=True,
    )

    slice_slider_y = widgets.IntSlider(
        value=vol.shape[1] // 2,
        min=0,
        max=vol.shape[1] - 1,
        description="Y",
        continuous_update=True,
    )

    slice_slider_x = widgets.IntSlider(
        value=vol.shape[2] // 2,
        min=0,
        max=vol.shape[2] - 1,
        description="X",
        continuous_update=True,
    )

    slicer_obj = interactive(_slice, slice_idx_z=slice_slider_z, slice_idx_y=slice_slider_y, slice_idx_x=slice_slider_x)

    # Create a horizontal box for the sliders
    hbox = widgets.HBox([slicer_obj.children[0], slicer_obj.children[1], slicer_obj.children[2]], layout=widgets.Layout(align_items="stretch", justify_content="center", align_content="center", justify_items="center", justify_self="center", align_self="center", width="100%"))

    # Replace the sliders in the interactive widget with the horizontal box
    slicer_obj.children = (hbox,) + slicer_obj.children[3:]

    return slicer_obj

fibretracker.viz.slicer

slicer(vol, detect_coords=None, mark_size=None, axis=0, cmap='gray', img_height=5, img_width=5)

Interactive widget for visualizing slices of a 3D volume and fibres centre if provided.

Parameters:

Name	Type	Description	Default
vol	ndarray	The 3D volume to be sliced.	required
detect_coords	list	List of coordinates of detected fibres. Defaults to None.	None
mark_size	int	Size of the marker for detected fibres. Defaults to None.	None
axis	int	Specifies the axis, or dimension, along which to slice. Defaults to 0.	0
cmap	str	Specifies the color map for the image. Defaults to "gray".	'gray'
img_height	int	Height of the figure. Defaults to 5.	5
img_width	int	Width of the figure. Defaults to 5.	5

Returns:

Name	Type	Description
slicer_obj	interactive	The interactive widget for visualizing slices of a 3D volume.

Example

import fibretracker as ft

# Load the volume and visualize the slices
vol = ft.io.load("path/to/volume.txm")
ft.viz.slicer(vol)

import fibretracker as ft

# Load the volume and detected coordinates
vol = ft.io.load("path/to/volume.txm")
vol = ft.io.normalize(vol)
vol = vol[100:350] # 250 slices along the z-axis
detect_coords = ft.models.get_fibre_coords(vol)
ft.viz.slicer(vol, detect_coords=detect_coords, mark_size=4)

Source code in fibretracker/viz/visualize.py

def slicer(
    vol: np.ndarray,
    detect_coords: Optional[List[np.ndarray]] = None,
    mark_size: Optional[int] = None,
    axis: int = 0,
    cmap: str = "gray",
    img_height: int = 5,
    img_width: int = 5, 
) -> widgets.interactive:
    """Interactive widget for visualizing slices of a 3D volume and fibres centre if provided.

    Args:
        vol (np.ndarray): The 3D volume to be sliced.
        detect_coords (list, optional): List of coordinates of detected fibres. Defaults to None.
        mark_size (int, optional): Size of the marker for detected fibres. Defaults to None.
        axis (int, optional): Specifies the axis, or dimension, along which to slice. Defaults to 0.
        cmap (str, optional): Specifies the color map for the image. Defaults to "gray".
        img_height (int, optional): Height of the figure. Defaults to 5.
        img_width (int, optional): Width of the figure. Defaults to 5.

    Returns:
        slicer_obj (widgets.interactive): The interactive widget for visualizing slices of a 3D volume.

    Example:
        ```python
        import fibretracker as ft

        # Load the volume and visualize the slices
        vol = ft.io.load("path/to/volume.txm")
        ft.viz.slicer(vol)
        ```
        ![viz slicer](figures/viz-slicer.gif)

        ```python
        import fibretracker as ft

        # Load the volume and detected coordinates
        vol = ft.io.load("path/to/volume.txm")
        vol = ft.io.normalize(vol)
        vol = vol[100:350] # 250 slices along the z-axis
        detect_coords = ft.models.get_fibre_coords(vol)
        ft.viz.slicer(vol, detect_coords=detect_coords, mark_size=4)
        ```

        ![viz slicer](figures/viz-slicer_detector.gif)

    """

    if detect_coords is None:
        fig, ax = plt.subplots(figsize=(img_width, img_height))
        ax.axis("off")
    else:
        fig, ax = plt.subplots(1, 2, figsize=(2*img_width, img_height), sharex=True, sharey=True, gridspec_kw={'wspace': 0})
        ax[0].axis("off")
        ax[1].axis("off")

    def _slice(slice_idx):
        slice_img = vol.take(slice_idx, axis=axis)
        if detect_coords is not None:
            [l.remove() for l in ax[1].lines]
            ax[0].imshow(slice_img, cmap=cmap)
            ax[1].imshow(slice_img, cmap=cmap)
            if mark_size is not None:
                ax[1].plot(detect_coords[slice_idx][:, 0], detect_coords[slice_idx][:, 1], 'rx', markersize=mark_size)
            else:
                ax[1].plot(detect_coords[slice_idx][:, 0], detect_coords[slice_idx][:, 1], 'rx', markersize=3)
        else:
            ax.imshow(slice_img, cmap=cmap)

    def on_release(event):
        if detect_coords is not None:
            xlim = ax[0].get_xlim()
            ylim = ax[0].get_ylim()
            ax[1].set_xlim(xlim)
            ax[1].set_ylim(ylim)
        else:
            xlim = ax.get_xlim()
            ylim = ax.get_ylim()

    slice_slider = widgets.IntSlider(
        value=vol.shape[axis] // 2,
        min=0,
        max=vol.shape[axis] - 1,
        description="Slice",
        continuous_update=True,
    )

    slice_slider.style.description_width = 'middle'  # Set the width of the description to fit the larger font size
    slice_slider.style.handle_color = 'blue'  # Optional: Change the handle color
    slice_slider.style.font_size = '150px'  

    fig.canvas.mpl_connect('button_release_event', on_release)
    slicer_obj = interactive(_slice, slice_idx = slice_slider)

    return slicer_obj

fibretracker.viz.plot_tracks

plot_tracks(tracks, grid=False)

Plot tracks of fibres detected in the volume

Parameters:

Name	Type	Description	Default
tracks	List[ndarray]	List of arrays of shape (n_points, 3)	required
grid	bool	Whether to show grid in the plot	False

Returns:

Name	Type	Description
fig	Figure	matplotlib figure object

Example

import fibretracker as ft

# Load the volume and detected coordinates
vol = ft.io.load("path/to/volume.txm")
vol = ft.io.normalize(vol)
vol = vol[100:350] # 250 slices along the z-axis
detect_coords = ft.models.get_fibre_coords(vol)
tracks_gauss = ft.models.track_fibres(coords=detect_coords, smoothtrack_gaussian=True)
ft.viz.plot_tracks(tracks_gauss)

Source code in fibretracker/viz/plotting.py

def plot_tracks(
        tracks: List[np.ndarray],
        grid: bool = False,):

    '''Plot tracks of fibres detected in the volume

    Args:
        tracks: List of arrays of shape (n_points, 3)
        grid: Whether to show grid in the plot

    Returns:
        fig (matplotlib.figure.Figure): matplotlib figure object

    Example:
        ```python
        import fibretracker as ft

        # Load the volume and detected coordinates
        vol = ft.io.load("path/to/volume.txm")
        vol = ft.io.normalize(vol)
        vol = vol[100:350] # 250 slices along the z-axis
        detect_coords = ft.models.get_fibre_coords(vol)
        tracks_gauss = ft.models.track_fibres(coords=detect_coords, smoothtrack_gaussian=True)
        ft.viz.plot_tracks(tracks_gauss)
        ```

        ![viz tracks](figures/tracks_gauss.gif)


    '''
    fig, ax = plt.subplots(figsize=(10, 10))
    ax = fig.add_subplot(projection='3d')
    for track in tracks:
        ax.plot(track[:,0], track[:,1], track[:,2])
    ax.grid(grid)
    ax.set_aspect('equal')

    plt.show()
    return fig