satn_to_movie
¶
Produces a movie of the invasion sequence from ibip filter
. This method can be applied for visualizing image-based invasion percolation algorithm.
import matplotlib.pyplot as plt
import numpy as np
import porespy as ps
from IPython.display import HTML
ps.visualization.set_mpl_style()
[18:58:54] ERROR PARDISO solver not installed, run `pip install pypardiso`. Otherwise, _workspace.py:56 simulations will be slow. Apple M chips not supported.
im
¶
The input image is a Boolean image True
values indicating the void voxels and False
for solid. Let’s create a test image:
satn
¶
The saturation image can be generated from ibip
data using seq_to_satn
method. The satn
is the image of porous material where each voxel indicates the global saturation at which it was invaded. Voxels with 0 values indicate solid and and -1 indicate uninvaded.
bd = np.zeros_like(im, dtype=bool)
bd[:, 0] = 1
bd *= im
out = ps.simulations.ibip(im=im, inlets=bd)
inv_seq, inv_size = out.im_seq, out.im_size
satn = ps.filters.seq_to_satn(seq=inv_seq)
Now we can create an animation of the invasion sequence using satn_to_movie
: (To save animation as a file and for visualizing use animation.save
)
mov = ps.visualization.satn_to_movie(im=im, satn=satn)
mov_image_based_ip = mov.to_jshtml()
HTML(mov_image_based_ip)