`spheres_from_coords`#

In cases where an external package is used to generate a sphere packing, this function can be used to convert the result to an ndimage.

import porespy as ps
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

[17:43:16] ERROR    PARDISO solver not installed, run `pip install pypardiso`. Otherwise,          _workspace.py:56
                    simulations will be slow. Apple M chips not supported.

`df`#

The function is designed to accept the input coordinates and sphere radii as a pandas DataFrame, which is why this argument is called df…although as we’ll see this is somewhat flexible.

Let assume we have 4 spheres whose x, y, and z coordinates plus their respective radii are stored as column an Excel file with each row representing a sphere. This format can be directly read into a DataFrame using df = pd.read_excel or df = pd.read_csv, which is why the DataFrame is the format of choice.

Let’s enter a DataFrame by hand for this demonstration, then print it:

df = pd.DataFrame({'X': [10, 20, 40, 40], 'Y': [10, 30, 50, 10], 'Z': [0, 0, 0, 0], 'R': [5.0, 8.0, 17.5, 4.0]})
print(df)

    X   Y  Z     R
10  10  0   5.0
20  30  0   8.0
40  50  0  17.5
40  10  0   4.0

This array of spheres is only 2D as can be seen by all the ‘Z’ values being 0. The returned image will be in 2D.

im = ps.generators.spheres_from_coords(df)

The function also accepts numpy arrays with the same format as the above DataFrame:

arr = np.array(df)
print(arr)

[[10.  10.   0.   5. ]
 [20.  30.   0.   8. ]
 [40.  50.   0.  17.5]
 [40.  10.   0.   4. ]]

im = ps.generators.spheres_from_coords(arr)
plt.imshow(im);

../../../_images/2d1f7dd0b2d0391ba82039cc87d6bba6c1838c35636f4b1eb6c694b637cee9a7.png

It is also acceptable to pass a python dict:

dct = {'X': [10, 20, 40, 40], 'Y': [10, 30, 50, 10], 'Z': [0, 0, 0, 0], 'R': [5.0, 8.0, 17.5, 4.0]}
im = ps.generators.spheres_from_coords(dct)
plt.imshow(im);

It is also acceptable to leave the ‘X’ or ‘Y’ columns as 0’s. The function will ignore the column with all 0’s and return a 2D image.

dct = {'X': [10, 20, 40, 40], 'Y': [0, 0, 0, 0], 'Z': [10, 30, 50, 10], 'R': [5.0, 8.0, 17.5, 4.0]}
im = ps.generators.spheres_from_coords(dct)
plt.imshow(im);

Of course, it also works with 3D images:

dct = {'X': [10, 20, 40, 40], 'Y': [10, 30, 50, 10], 'Z': [4, 8, 12, 16], 'R': [5.0, 8.0, 17.5, 4.0]}
im = ps.generators.spheres_from_coords(dct)
plt.imshow(ps.visualization.sem(~im, axis=0).T);

../../../_images/79f48cb8c4d32176a61d55c74e5d51dbcdbadb2be4265961df3f293d18ba8399.png

`mode`#

The options are 'extended' which means the spheres are allowed to extend beyond the edge of the image, and contained meaning the sphere lie fully inside the image.

im1 = ps.generators.spheres_from_coords(df, mode='extended')
im2 = ps.generators.spheres_from_coords(df, mode='contained')
fig, ax = plt.subplots(1, 2)
ax[0].imshow(im1)
ax[1].imshow(im2);

../../../_images/48a4c83913f62af815465b41efcfcade0d0cd221204567c291504c919096e47f.png

`smooth`#

This controls the outer shape of the spheres.

im1 = ps.generators.spheres_from_coords(df, smooth=True)
im2 = ps.generators.spheres_from_coords(df, smooth=False)
fig, ax = plt.subplots(1, 2)
ax[0].imshow(im1)
ax[1].imshow(im2);

../../../_images/979af0546b0e93c689a78fbb59456f11387d857006225ebf8162db9530fc1e05.png

spheres_from_coords#

df#

mode#

smooth#

`spheres_from_coords`#

`df`#

`mode`#

`smooth`#