.. _examples:

********
Examples
********

Retina Vessels
==============

Extracting the minimal path through the retina vessels with additional way points.

.. plot::

    from skimage.data import retina
    from skimage.color import rgb2gray
    from skimage.transform import rescale
    from skimage.filters import sato

    from skmpe import mpe

    image = rescale(rgb2gray(retina()), 0.5)
    speed_image = sato(image)

    start_point = (76, 388)
    end_point = (611, 442)
    way_points = [(330, 98), (554, 203)]

    path_info = mpe(speed_image, start_point, end_point, way_points)

    px, py = path_info.path[:, 1], path_info.path[:, 0]

    plt.imshow(image, cmap='gray')
    plt.plot(px, py, '-r')
    plt.plot(*start_point[::-1], 'oy')
    plt.plot(*end_point[::-1], 'og')
    for p in way_points:
        plt.plot(*p[::-1], 'ob')
    plt.axis('off')


Bricks
======

Extracting the shortest paths through "bricks" image.

.. plot::

    from skimage.data import brick
    from skimage.transform import rescale
    from skimage.exposure import rescale_intensity, adjust_sigmoid

    from skmpe import parameters, mpe

    image = rescale(brick(), 0.5)
    speed_image = rescale_intensity(
        adjust_sigmoid(image, cutoff=0.5, gain=10).astype(np.float_), out_range=(0., 1.))

    start_point = (44, 13)
    end_point = (233, 230)
    way_points = [(211, 59), (17, 164)]

    with parameters(integrate_max_step=1.0):
        path_info1 = mpe(speed_image, start_point, end_point)
        path_info2 = mpe(speed_image, start_point, end_point, way_points)

    px1, py1 = path_info1.path[:, 1], path_info1.path[:, 0]
    px2, py2 = path_info2.path[:, 1], path_info2.path[:, 0]

    plt.imshow(image, cmap='gray')
    plt.plot(px1, py1, '-r', linewidth=2)
    plt.plot(px2, py2, '--r', linewidth=2)

    plt.plot(*start_point[::-1], 'oy')
    plt.plot(*end_point[::-1], 'og')
    for p in way_points:
        plt.plot(*p[::-1], 'ob')
    plt.axis('off')


Maze
====

Finding the path in the maze.

.. plot::

    from skimage.io import imread
    from skimage.exposure import rescale_intensity

    from skmpe import parameters, mpe, OdeSolverMethod

    image = imread('_static/maze.png', as_gray=True).astype(np.float_)
    speed_image = rescale_intensity(image, out_range=(0.005, 1.0))

    start_point = (60, 238)
    end_point = (77, 189)

    with parameters(ode_solver_method=OdeSolverMethod.LSODA, integrate_max_step=1.0):
        path_info = mpe(speed_image, start_point, end_point)

    path = path_info.path

    plt.imshow(image, cmap='gray')
    plt.plot(path[:, 1], path[:, 0], '-r', linewidth=2)

    plt.plot(*start_point[::-1], 'oy')
    plt.plot(*end_point[::-1], 'og')

    plt.axis('off')