def match_non_removable(index, verbose=True):
if verbose and index % 2**14 == 0:
print('PK12 LUT non-removables: %d / %d' % (index, 2**26))
cube = t3d.cube_from_index(index=index, center=False)
n = cube.sum()
if n < 2:
return True
if n > 3:
return False
x, y, z = np.where(cube)
if n == 2:
if np.any(np.abs([x[1] - x[0], y[1] - y[0], z[1] - z[0]]) == 2):
return True
else:
return False
else:
if np.any(np.abs(
[x[1] - x[0], y[1] - y[0], z[1] - z[0]]) == 2) and np.any(
np.abs([x[2] - x[0], y[2] - y[0], z[2] -
z[0]]) == 2) and np.any(
np.abs([x[1] - x[2], y[1] - y[2], z[1] -
z[2]]) == 2):
return True
else:
return False
def index_to_smoothing(index, verbose = True):
"""Match index of configuration to smoothing action"""
if verbose and index % 2**14 == 0:
print('Smoothing LUT: %d / %d' % (index, 2**27));
cube = t3d.cube_from_index(index=index, center=None);
return cube_to_smoothing(cube);
def match_index(index, verbose=True):
if verbose and index % 2**14 == 0:
print('PK12 LUT: %d / %d' % (index, 2**26))
cube = t3d.cube_from_index(index=index, center=True)
return match(cube)
def _test():
import numpy as np
import ClearMap.ImageProcessing.Topology.Topology3d as top
from importlib import reload
reload(top)
label = top.cube_labeled()
top.print_cube(label)
# Test rotations
c = np.zeros((3, 3, 3), dtype=bool)
c[1, 0, 0] = True
top.print_cube(c)
cs = [top.rotate(c, axis=2, steps=r) for r in range(4)]
[top.print_cube(cc) for cc in cs]
reload(top)
l = top.cube_labeled()
rts = top.rotations6(l)
[top.print_cube(r) for r in rts]
reload(top)
b = top.cube_from_index(6)
i = top.cube_to_index(b)
print(i, 6)
us = np.zeros((3, 3, 3), dtype=int)
us[1, 1, 2] = 1
us[1, 0, 1] = 1
us[1, 2, 0] = 2
r12 = top.rotations12(us)
[top.print_cube(cc) for cc in r12]
#check configuration utlity
reload(top)
index = 11607
source = top.cube_from_index(index)
c = top.index_from_binary(source)
c[1, 1, 1] == index
x = np.random.rand(1500, 500, 500) > 0.6
c = top.index_from_binary(x)
import numpy as np
import ClearMap.ImageProcessing.Topology.Topology3d as top
#check fortran vs c order
x = np.random.rand(5, 5, 5) > 0.35
y = np.asanyarray(x, order='F')
ix = top.index_from_binary(x)
iy = top.index_from_binary(y)
ax = ix.array
ay = iy.array
#%% profile
import io
io.DEFAULT_BUFFER_SIZE = 2**32
import pstats, cProfile
import numpy as np
import ClearMap.ImageProcessing.Topology.Topology3d as top
x = np.ones((3000, 500, 1000), dtype=bool, order='F')
import ClearMap.IO.IO as io
import ClearMap.ParallelProcessing.DataProcessing.ArrayProcessing as ap
ap.write('test.npy', x)
y = io.as_source('test.npy')
z = io.create('resuly.npy', shape=y.shape, order='C', dtype='uint32')
cProfile.runctx(
"c =top.index_from_binary(y, method='!shared', sink=z, verbose=True, processes=None)",
globals(), locals(), "Profile.prof")
s = pstats.Stats("Profile.prof")
s.strip_dirs().sort_stats("time").print_stats()
import mmap
mmap.ACCESS_COPY