Source code for porespy.visualization.__views__

import scipy as sp
# import matplotlib.pyplot as plt
# from mpl_toolkits.mplot3d.art3d import Poly3DCollection


def show_planes(im):
    r"""
    Create a quick montage showing a 3D image in all three directions

    Parameters
    ----------
    im : ND-array
        A 3D image of the porous material

    Returns
    -------
    image : ND-array
        A 2D array containing the views.  This single image can be viewed using
        ``matplotlib.pyplot.imshow``.

    """
    if sp.squeeze(im.ndim) < 3:
        raise Exception('This view is only necessary for 3D images')
    x, y, z = (sp.array(im.shape)/2).astype(int)
    im_xy = im[:, :, z]
    im_xz = im[:, y, :]
    im_yz = sp.rot90(im[x, :, :])

    new_x = im_xy.shape[0] + im_yz.shape[0] + 10

    new_y = im_xy.shape[1] + im_xz.shape[1] + 10

    new_im = sp.zeros([new_x + 20, new_y + 20], dtype=im.dtype)

    # Add xy image to upper left corner
    new_im[10:im_xy.shape[0]+10,
           10:im_xy.shape[1]+10] = im_xy
    # Add xz image to lower left coner
    x_off = im_xy.shape[0]+20
    y_off = im_xy.shape[1]+20
    new_im[10:10 + im_xz.shape[0],
           y_off:y_off + im_xz.shape[1]] = im_xz
    new_im[x_off:x_off + im_yz.shape[0],
           10:10 + im_yz.shape[1]] = im_yz

    return new_im


[docs]def sem(im, direction='X'): r""" Simulates an SEM photograph looking into the porous material in the specified direction. Features are colored according to their depth into the image, so darker features are further away. Parameters ---------- im : array_like ND-image of the porous material with the solid phase marked as 1 or True direction : string Specify the axis along which the camera will point. Options are 'X', 'Y', and 'Z'. Returns ------- image : 2D-array A 2D greyscale image suitable for use in matplotlib\'s ```imshow``` function. """ im = sp.array(~im, dtype=int) if direction in ['Y', 'y']: im = sp.transpose(im, axes=[1, 0, 2]) if direction in ['Z', 'z']: im = sp.transpose(im, axes=[2, 1, 0]) t = im.shape[0] depth = sp.reshape(sp.arange(0, t), [t, 1, 1]) im = im*depth im = sp.amax(im, axis=0) return im
[docs]def xray(im, direction='X'): r""" Simulates an X-ray radiograph looking through the porouls material in the specfied direction. The resulting image is colored according to the amount of attenuation an X-ray would experience, so regions with more solid will appear darker. Parameters ---------- im : array_like ND-image of the porous material with the solid phase marked as 1 or True direction : string Specify the axis along which the camera will point. Options are 'X', 'Y', and 'Z'. Returns ------- image : 2D-array A 2D greyscale image suitable for use in matplotlib\'s ```imshow``` function. """ im = sp.array(~im, dtype=int) if direction in ['Y', 'y']: im = sp.transpose(im, axes=[1, 0, 2]) if direction in ['Z', 'z']: im = sp.transpose(im, axes=[2, 1, 0]) im = sp.sum(im, axis=0) return im