cylindrical_pillars_mesh

Generates an array of cylindrical pillars by putting a cylinder at each vertext in a triangular mesh of the domain, so has some randomness while still being quite uniform.

import matplotlib.pyplot as plt
import porespy as ps
import numpy as np
from porespy.visualization import set_mpl_style
set_mpl_style()

[19:54:50] ERROR    PARDISO solver not installed, run `pip install pypardiso`. Otherwise,          _workspace.py:56
                    simulations will be slow. Apple M chips not supported.                                         

No module named 'pyedt'

a

Controls the number of pillars to add. This number tells the mesher the area of each triangle, so a smaller value of a results in more pillars.

fig, ax = plt.subplots(1, 2, figsize=(10, 5))
np.random.seed(0)
im1 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601],
    a=500,
)
im2 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601], 
    a=5000,
)

ax[0].imshow(im1, origin='lower', interpolation='none')
ax[0].set_title('a=500')
ax[1].imshow(im2, origin='lower', interpolation='none')
ax[1].set_title('a=5000');

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
File ~/work/porespy/porespy/src/porespy/generators/_micromodels.py:297, in cylindrical_pillars_mesh(shape, f, a, n, truncate)
    296 try:
--> 297     from nanomesh import Mesher2D
    298 except ModuleNotFoundError:

ModuleNotFoundError: No module named 'nanomesh'

During handling of the above exception, another exception occurred:

ModuleNotFoundError                       Traceback (most recent call last)
Cell In[2], line 3
      1 fig, ax = plt.subplots(1, 2, figsize=(10, 5))
      2 np.random.seed(0)
----> 3 im1 = ps.generators.cylindrical_pillars_mesh(
      4     shape=[401, 601],
      5     a=500,
      6 )
      7 im2 = ps.generators.cylindrical_pillars_mesh(
      8     shape=[401, 601], 
      9     a=5000,
     10 )
     12 ax[0].imshow(im1, origin='lower', interpolation='none')

File ~/work/porespy/porespy/src/porespy/generators/_micromodels.py:300, in cylindrical_pillars_mesh(shape, f, a, n, truncate)
    298 except ModuleNotFoundError:
    299     msg = "The nanomesh package can be installed with `pip install nanomesh`"
--> 300     raise ModuleNotFoundError(msg)
    302 shape = parse_shape(shape)
    303 if len(shape) != 2:

ModuleNotFoundError: The nanomesh package can be installed with `pip install nanomesh`

f

A scale factor to control how large the pillars are relative their maximal size (i.e. overlapping neighboring pillars)

fig, ax = plt.subplots(1, 2, figsize=(10, 5))
np.random.seed(0)
im1 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601],
    f=0.5,
)
im2 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601], 
    f=0.9,
)

ax[0].imshow(im1, origin='lower', interpolation='none')
ax[0].set_title('f=0.5')
ax[1].imshow(im2, origin='lower', interpolation='none')
ax[1].set_title('f=0.95');

n

Controls the density of pillars along the edges. The default is \(\sqrt{a}/f\), which does a decent job a keeping the edge pillars the same size as the internal ones, but this can be overwritten if needed:

fig, ax = plt.subplots(1, 2, figsize=(10, 5))
np.random.seed(0)
im1 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601],
    n=20,
)
im2 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601], 
    n=40,
)

ax[0].imshow(im1, origin='lower', interpolation='none')
ax[0].set_title('n=20')
ax[1].imshow(im2, origin='lower', interpolation='none')
ax[1].set_title('n=40');

truncate

If True it returns an image of the specified size by truncated the pillars on the edge of the image. If False it returns an image that is larger than the requested shape but contains the edge pillars in their entirety.

fig, ax = plt.subplots(1, 2, figsize=(10, 5))
np.random.seed(0)
im1 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601],
    truncate=False,
)
im2 = ps.generators.cylindrical_pillars_mesh(
    shape=[401, 601], 
    truncate=True,
)

ax[0].imshow(im1, origin='lower', interpolation='none')
ax[0].set_title('truncate=False')
ax[1].imshow(im2, origin='lower', interpolation='none')
ax[1].set_title('truncate=True');