reduce_peaks
#
Broad or elongated peaks are replaced with single peaks located at the centre of original voxels
Import packages#
import numpy as np
import porespy as ps
import scipy.ndimage as spim
import matplotlib.pyplot as plt
import skimage
from edt import edt
ps.visualization.set_mpl_style()
np.random.seed(0)
[12:33:55] ERROR PARDISO solver not installed, run `pip install pypardiso`. Otherwise, _workspace.py:56 simulations will be slow. Apple M chips not supported.
peaks
#
Find peaks
on the test image
im = ps.generators.blobs(shape=[200, 200])
dt = edt(im)
peaks = ps.filters.find_peaks(dt, r_max=4)
plt.figure(figsize=[6, 6])
plt.axis(False)
plt.imshow(peaks/im);

Apply reduce_peaks
filter#
x = ps.filters.reduce_peaks(peaks=peaks)
plt.figure(figsize=[6, 6])
plt.axis(False)
plt.imshow(x/im);
